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1
Feng, Jiacheng, Jun Ma, ZaiYan Gong, Di Kang, and Chao Wang. "Design of Multi-threshold Acceleration Switch Based on Matlab." MATEC Web of Conferences 232 (2018): 04026. http://dx.doi.org/10.1051/matecconf/201823204026.
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Acceleration switch can trigger switches according to the variation of external acceleration without complex control system and circuit. With the excellent characteristics of integration of sensor and actuator, zero power consumption and high reliability, multi-threshold acceleration switch has great application value in the fields of vehicle safety, aerospace and industrial equipment. In order to reduce the complexity of the measurement system and improve the reliability, we realized the design of a multi-threshold and anti-overloading acceleration switch which can distinguish specific pulse width. Additionally, the magnetic elastic contact is designed to prevent the rebound phenomenon when switch is overloaded. Considering the coupling force of spring, magnetic elastic contact and magnetic, we built the dynamic model and analysed the influence of the acceleration threshold and the pulse width on the switch actuation. The numerical simulation shows that the proposed switch has accurate sensitivity of acceleration excitation with specific threshold and certain pulse width, and it also has the ability of anti-overload. Consequently, the proposed method provides a new method for designing acceleration switch.
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Liu, Min, Xinyang Wu, Yanxu Niu, Haotian Yang, Yingmin Zhu, and Weidong Wang. "Research Progress of MEMS Inertial Switches." Micromachines 13, no. 3 (February 24, 2022): 359. http://dx.doi.org/10.3390/mi13030359.
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As a typical type of MEMS acceleration sensor, the inertial switch can alter its on-off state while the environmental accelerations satisfy threshold value. An exhaustive summary of the design concept, performance aspects, and fabrication methods of the micro electromechanical system (MEMS) inertial switch is provided. Different MEMS inertial switch studies were reviewed that emphasized acceleration directional and threshold sensitivity, contact characteristics, and their superiorities and disadvantages. Furthermore, the specific fabrication methods offer an applicability reference for the preparation process for the designed inertial switch, including non-silicon surface micromachining technology, standard silicon micromachining technology, and the special fabrication method for the liquid inertial switch. At the end, the main conclusions of the current challenges and prospects about MEMS inertial switches are drawn to assist with the development of research in the field of future engineering applications.
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Yu, Yudan, Wei Lin, and Zhaoyang Yu. "Research on motion track error detection and compensation algorithm based on MEMS sensor." ITM Web of Conferences 47 (2022): 02010. http://dx.doi.org/10.1051/itmconf/20224702010.
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Due to various errors in actual use, MEMS inertial sensors have large errors in the detection of motion trajectories. Therefore, it is necessary to analyse and model the errors to decrease the impact of error sources on the detection system. This errors mainly include systematic random errors and accumulated errors generated during double integral operation, and different filtering methods are used for different types of errors. For random errors, the wavelet fuzzy threshold method is used to filter the sensor output signal. For the accumulated error, the zero-state adaptive compensation algorithm is used to correct the acceleration and integral velocity. Experiments show that the wavelet threshold denoising algorithm combined with the zero-state adaptive compensation algorithm can enhance the preciseness of the MEMS inertial sensor in object trajectory detection.
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Tian, Wen Chao, Ya Feng Hao, and Hong Fang Ruan. "Simulation and Test of Bistable Inductive Micro-Switch." Advanced Materials Research 230-232 (May 2011): 779–83. http://dx.doi.org/10.4028/www.scientific.net/amr.230-232.779.
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Inductive micro-switch is an integrative device of a sensor and actuator. It can not only induce an external acceleration, but can also be controlled by the external acceleration to realize the trigger action. However, its malfunctions related to “fail-to-closure” and “transient-closure” result in low reliability and weak anti-jamming capability. A new bistable inductive micro-switch is presented based on micro size adhesive effect. The dynamic simulation is obtained by Comsol software. The simulation shows the threshold acceleration is 23.6g, and the response time is 0.38ms. The micro-switch is tested by a centrifuge. The test result shows that the threshold acceleration is 24g.The relative error between the theoretical analysis and the test result is only 1.6%.
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Norhabibah, Siti, Wahyu Andhyka, and Diah Risqiwati. "Rancang Bangun Sistem Monitoring Deteksi Jatuh untuk Manula dengan Menggunakan Accelerometer." JOINCS (Journal of Informatics, Network, and Computer Science) 1, no. 1 (July 21, 2017): 43. http://dx.doi.org/10.21070/joincs.v1i1.803.
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Elderly is a last transitional period of human life. Decrease or disappearance of organ function such as loss of balance, reduced vision and hearing cause the elderly often fall. The limited physical ability of them requires supervision. Supervision is necessary to avoid undesirable thing occurs. Here, a tool called accelerometer can be used to supervise and monitor whether the fall incident occurs or not to the elderly. In this study, the magnitude of the acceleration in x, y, and z axes of the accelerometer sensor is processed into a total value of acceleration. Then the value will be compared with the lower threshold value and the higher threshold value. After that the total value of the acceleration is compared again with the threshold value of the total value orientations. The total value of acceleration is used to distinguish between regular activity and falling. The results of this study indicate that the system developed has the sensitivity values of 89% and specificity of 98%.
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Norhabibah, Siti, Wahyu Andhyka, and Diah Risqiwati. "Design and Build a Fall Detection Monitoring System for the Elderly Using an Accelerometer." JOINCS (Journal of Informatics, Network, and Computer Science) 1, no. 1 (January 25, 2018): 43–52. http://dx.doi.org/10.21070/10.21070/joincs.v1i1.803.
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Elderly is a last transitional period of human life. Decrease or disappearance of organ function such as loss of balance, reduced vision and hearing cause the elderly often fall. The limited physical ability of them requires supervision. Supervision is necessary to avoid undesirable thing occurs. Here, a tool called accelerometer can be used to supervise and monitor whether the fall incident occurs or not to the elderly. In this study, the magnitude of the acceleration in x, y, and z axes of the accelerometer sensor is processed into a total value of acceleration. Then the value will be compared with the lower threshold value and the higher threshold value. After that the total value of the acceleration is compared again with the threshold value of the total value orientations. The total value of acceleration is used to distinguish between regular activity and falling. The results of this study indicate that the system developed has the sensitivity values of 89% and specificity of 98%.
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Lukyanov, Dmitry P., Alexander M. Boronakhin, Sergey Yu Shevchenko, Mariya A. Khivrich, and Temurmalik A. Amirov. "Microaccelerometer on Surface Acoustic Waves with a Ring Resonator on Anisotropic Material." Journal of the Russian Universities. Radioelectronics 22, no. 5 (December 4, 2019): 116–29. http://dx.doi.org/10.32603/1993-8985-2019-22-5-116-129.
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Introduction. Diagnostic systems are designed to monitor the condition of operational components (for example, on the railway). It is imperative that micro-electromechanical systems (MEMS) equipped with acceleration sensors (accelerometers) be used as part of measuring diagnostic systems. It is known that accelerometers are operated under increased vibration and repeated shock loads. This imposes a limitation both on the accelerometer design and the properties of materials from which these devices are produced.Aim. To develop a micromechanical accelerometer (MMA) for surface acoustic waves (SAW), capable of measuring shock effects.Materials and methods. The theoretical part of the study was carried out using the mathematical theory of differential equations, theoretical mechanics, finite element analysis and elements of SAW theory. In the course of the work, the following methods of mathematical processing were applied: MATLAB, Mathcad, Maple, COMSOL Multiphysics, OOFELIE: Multiphysics, Bluehill3 software, CorelDRAW. Experimental studies were also conducted using the INSTRON 5985 floor automated test system.Results. An original design of MMA on a SAW capable of measuring shock effects in hundreds of g was proposed. A sensing element (SE) of the sensor was developed. An analysis of the plate materials for their use as part of the SAW-based MMA design showed that SE from the quartz ST-cut material has a wider range of measured accelerations and a higher sensitivity threshold than SE from the YX-128˚ cut-off lithium niobate material. Requirements were developed to increase the SE sensitivity threshold. Design requirements were developed, and an interdigital transducer (IDT) topology in the form of a ring resonator was proposed. The following output characteristics were assessed: sensitivity threshold, dynamic range and scale factor. In addition, a procedure was developed for calculating MMA on a SAW with a ring resonator on an anisotropic material. It was found that the developed SE is characterized by a high sensitivity threshold, a wide dynamic range and a low transverse sensitivity.Conclusion. The technique proposed for designing a sensing element for use in solid-state linear acceleration sensors facilitates, depending on technical requirements, selection of construction materials and sensor design. Due to the originality of the design and engineering solutions, the proposed accelerometer allows measurements to be carried out across a wide range of impact loads.
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Han, Yingzhou, Guozhe Xuan, Jiahao Zhao, and Zheng You. "Low-G Triggered Acceleration Switch for Near-Zero Power Wake-Up Application." Micromachines 13, no. 8 (August 17, 2022): 1333. http://dx.doi.org/10.3390/mi13081333.
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A low-g triggered micro-electromechanical system (MEMS) resonant acceleration switch is designed, fabricated and tested in this paper for near-zero power wake-up applications. The switch is actuated by ambient low-g vibration, consuming zero power while waiting for vibration at its resonant frequency. A cantilever beam and proof mass structure is adopted in the switch. The patterns of spiral cantilever beams are designed for low resonant frequency and threshold. Once the vibration with resonant frequency exceeds the acceleration threshold of the switch, the movable electrode becomes sufficiently displaced to contact the fixed electrodes and causes them to trigger. The dynamic responses of the switch are tested on a piezoelectric stack. The experimental results show that the switch closes under vibration at a frequency as low as 39.3 Hz and at an acceleration threshold of 0.074 g. A wake-up sensor node connected to the switch can awaken when the switch is under vibration as an intended characteristics.
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Alhusban, Zaid. "Studying sediment transport dynamics by using the Smart sphere." International Journal of Energetica 5, no. 1 (June 30, 2020): 01. http://dx.doi.org/10.47238/ijeca.v5i1.122.
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A new method is introduced by using high precision accelerometer and gyroscope micro-electromechanical sensors (MEMS), which can record Lagrangian observations of sediments and shed light into the dynamics of sediment transport processes at above threshold conditions. The sensor can be used under a range of well-controlled flow conditions and can record measurements at high frequency (200 Hz), which can be used at the field. The smart sphere performance was evaluated by comparing its rotation and acceleration readings from the sensors to the video recordings of both top and underwater high-speed camera for a range of flow rates and sphere densities. Furthermore, an initial attempt to compare the smart-sphere’s velocity is achieved, by transforming the particle’s velocity from the Lagrangian frame of reference, obtained from the inertial sensor, to its velocity at the Eularian frame, obtained from the top camera.
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Jung, Byung, Young Huh, and Jin-Woo Park. "A Self-Powered, Threshold-Based Wireless Sensor for the Detection of Floor Vibrations." Sensors 18, no. 12 (December 5, 2018): 4276. http://dx.doi.org/10.3390/s18124276.
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Smart buildings will soon be a reality due to innovative Internet of Things (IoT) applications. IoT applications can be employed not only for energy management in a building, but also for solving emerging social issues, such as inter-floor noise-related disputes in apartments and the solitary death of an elderly person. For example, acceleration sensors can be used to detect abnormal floor vibrations, such as large vibrations due to jumping children or unusual vibrations in a house where an elderly person is living alone. However, the installation of a conventional accelerometer can be restricted because of the sense of privacy invasion. In this study, a self-powered wireless sensor using a threshold-based method is studied for the detection of floor vibrations. Vibration levels of a bare slab in a testbed are first measured when a slab is impacted by a bang machine and an impact ball. Second, a piezoelectric energy harvester using slab vibration is manufactured to generate electrical power over a threshold. Next, the correlation among harvested energy, floor vibration, and impact noise is studied to check whether harvested energy can be employed as a condition detection threshold. Finally, a prototype of a self-powered wireless sensor to detect abnormal conditions in floor vibrations is developed and its applicability is demonstrated.
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Avisena, Shandy, Freddy Kurniawan, and Ndaru Atmi Purnami. "Penentuan Koreksi Sudut Attitude pada Quadrotor Menggunakan Algoritma Zero Acceleration Compensation." AVITEC 4, no. 1 (January 24, 2022): 27. http://dx.doi.org/10.28989/avitec.v4i1.1109.
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The orientation angle of a quadrotor UAV can be estimated from gyroscope and accelerometer data. Orientation can be predicted from gyroscope data under static or dynamic conditions, but the predicted value has accumulated errors. Meanwhile, orientation can also be calculated from accelerometer data, but only correct if the sensor is in a static state. To get a more precise orientation angle, the orientation predicted from the gyroscope data and the orientation calculated from the accelerometer data were fused using a Kalman filter. Determination of the condition of the sensor using a threshold value that is applied to the covariance of the acceleration data. in this study, the zero-acceleration compensation algorithm is used so that when the sensor is static, the orientation angle is calculated from the accelerometer. The use of this algorithm can increase the accuracy of the quadrotor orientation for roll angle to 96.84% and pitch angle to 98.91%.
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Du, Ronghua, Gang Qiu, Kai Gao, Lin Hu, and Li Liu. "Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor." Sensors 20, no. 2 (January 13, 2020): 451. http://dx.doi.org/10.3390/s20020451.
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In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed. After comparing the field investigation results with the algorithm recognition results, the accuracy of the proposed algorithm is rigorously evaluated. The test results show that the vehicle vibration acceleration contains the road surface condition information, which can be used to identify the abnormal road conditions. The test result shows that the accuracy of the recognition of the road surface pothole is 96.03%, and the accuracy of the road surface bump is 94.12%. The proposed road surface recognition method can be utilized to replace the special patrol vehicle for timely and low-cost road maintenance.
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Doan, H. G., and N. T. Nguyen. "Fusion Machine Learning Strategies for Multi-modal Sensor-based Hand Gesture Recognition." Engineering, Technology & Applied Science Research 12, no. 3 (June 6, 2022): 8628–33. http://dx.doi.org/10.48084/etasr.4913.
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Hand gesture recognition has attracted the attention of many scientists, because of its high applicability in fields such as sign language expression and human machine interaction. Many approaches have been deployed to detect and recognize hand gestures, like wearable devices, image information, and/or a combination of sensors and computer vision. However, the method of using wearable sensors brings much higher accuracy and is less affected by occlusion, lighting conditions, and complex background. Existing solutions separately utilize sensor information and/or only use sensor information processing and decision-making algorithms over conventional threshold comparison algorithms and do not analyze data or utilize machine learning algorithms. In this paper, a multi-modal solution is proposed that combines information for measuring the curvature of the fingers and sensors for measuring angular velocity and acceleration. The provided information from the sensors is normalized and analyzed and various fusion strategies are used. Then, the most suitable algorithm for these sensor-based multiple modalities is proposed. The proposed system also analyzes the differences between gestures and actions that are almost similar but in fact, they are just normal moving gestures.
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Jachowicz, Marcin, and Grzegorz Owczarek. "Studies of Acceleration of the Human Body during Overturning and Falling from a Height Protected by a Self-Locking Device." International Journal of Environmental Research and Public Health 19, no. 19 (September 24, 2022): 12077. http://dx.doi.org/10.3390/ijerph191912077.
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The use of individual fall protection equipment is one of the most commonly applied methods of protecting workers whose worksites are located above the floor level. The safety of the user in such a situation depends on both the proper selection and correct use of such equipment. Additionally, aspects such as minimizing the free-fall distance before the fall arrest, as well as quick notification of an accident and efficient rescue operation, are important factors influencing safety. This paper presents a new testing method for fall arrest equipment using a test stand consisting of the Hybrid III 50th Pedestrian ATD anthropomorphic manikin and measuring set with three-axis acceleration transducers. The proposed method and test stand were developed for the design and testing of new fall protection devices equipped with electronic detection and alarm systems, for which it is necessary to determine acceleration limits in order to determine the alarm threshold. The proposed method is based on the measurement of accelerations that occur during tipping and falling from the height of an anthropomorphic manikin secured by a self-locking device. Two places of attachment of the measuring set with a three-axis acceleration sensor were analyzed at the waist belt of the manikin (abdomen and back). Moreover, the self-locking device lanyard was attached to the two points of the safety harnesses (the front and back point). The aim of the research was to check whether the acceleration values depend on the places of attachment of the measuring and anchored system, as well as to determine their maximum values. Acceleration values corresponding to fall arrest and tipping were analyzed. Limits of acceleration have been established in order to determine the threshold of alarm triggering. The non-parametric Mann–Whitney U test was used to check whether the location of the three-axis acceleration transducer and the position of the self-locking device lanyard attachment affect the value of the recorded acceleration. For results of acceleration measurements when testing the behavior of the manikin during fall arrest, no statistically significant differences were found. For results of acceleration measurements when testing the tipping behavior of the manikin, statistically significant differences occurred. This means that during fall arrest, the location of the three-axis acceleration transducer and the position of the self-locking device lanyard attachment do not matter. This work is a continuation of previous research on accelerations characterizing human body positions occurring during normal physical activities (ADL—activities of daily living).
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Quwaider, Muhannad, and Subir Biswas. "Physical Context Detection using Wearable Wireless Sensor Networks." Journal of Communications Software and Systems 4, no. 3 (September 22, 2008): 191. http://dx.doi.org/10.24138/jcomss.v4i3.219.
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This paper presents the architecture of a wearable sensor network and a Hidden Markov Model (HMM) processingframework for stochastic identification of body postures andphysical contexts. The key idea is to collect multi-modal sensor data from strategically placed wireless sensors over a human subject’s body segments, and to process that using HMM in order to identify the subject’s instantaneous physical context. The key contribution of the proposed multi-modal approach is a significant extension of traditional uni-modal accelerometry in which only the individual body segment movements, without their relative proximities and orientation modalities, is used for physical context identification. Through real-life experiments with body mounted sensors it is demonstrated that while the unimodal accelerometry can be used for differentiating activityintensive postures such as walking and running, they are not effective for identification and differentiation between lowactivity postures such as sitting, standing, lying down, etc. In the proposed system, three sensor modalities namely acceleration, relative proximity and orientation are used for context identification through Hidden Markov Model (HMM) based stochastic processing. Controlled experiments using human subjects are carried out for evaluating the accuracy of the HMMidentified postures compared to a naïve threshold based mechanism over different human subjects.
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Xu, Fengyu, Zhong Yang, JinLong Hu, Guoping Jiang, and GuoHong Dai. "Fault diagnosis of a selective compliance assembly robot arm manipulator based on the end joint motion analysis: Threshold algorithm and experiments." Transactions of the Institute of Measurement and Control 40, no. 5 (May 3, 2017): 1691–700. http://dx.doi.org/10.1177/0142331217690222.
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This paper presented a method to carry out fault diagnosis via analyzing the motion signals of a SCARA. To analyze the motion signals of the end joint of a selective compliance assembly robot arm (SCARA) and carry out fault diagnosis. A model parameter-based threshold algorithm is proposed in this study to improve the efficiency of the fault diagnosis on the end joint of a SCARA manipulator. The operation state of the robot is determined by comparing the speed curve of the end joint of the robot with the threshold using the proposed algorithm. Firstly, the threshold range of the system output is estimated using the speed observer constructed via parameter separation. Secondly, the acceleration signals of the end joint of the robot are collected at various operational angular speeds by a single acceleration sensor installed at the end joint of the manipulator. The operation state of the robot is evaluated by analyzing the trend and vibration characteristics of its acceleration. Finally, experiments are conducted at three different speeds: 2.4rad/s, 3.12rad/s and 3.6rad/s. Some robot malfunctions are detected by comparing the actual speed with the threshold. Thus, the proposed method can be used to monitor the variation signal in each robot joint through a single accelerometer mounted on the top of the manipulator.
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Kong, Yawen, Dapeng Tian, and Yutang Wang. "An Adaptive Three-Axis Attitude Estimation Method Based on Multi-Sensor Fusion for Optoelectronic Platform." Applied Sciences 12, no. 7 (April 6, 2022): 3693. http://dx.doi.org/10.3390/app12073693.
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Optoelectronic platform is an important payload in the field of aerospace and widely used in geographic mapping, measurement, and positioning. In order to obtain high-precision attitude measurement, gyro and accelerometer are applied in the feedback loop of light of sight (LOS) control system of optoelectronic platform. Aiming at compensating for gyro drift and maneuvering acceleration disturbance, an adaptive 3-axis attitude estimation method is proposed in this paper. An adaptive threshold criterion is designed by applying the accelerometer data in the sliding window. The threshold is determined in real time to judge whether the maneuvering acceleration exists. If it exists, the angular attitude error is compensated for by the gyro drift model. Otherwise, the angular attitude error is compensated by multi-sensor fusion. Furthermore, a phase-lag-free low pass filter (LPF) is applied to compensate for the phase lag error introduced in the above attitude estimation process. Compared with the angular attitude calculated by gyro, the root mean square error (RMSE) of the proposed method in roll, pitch, and yaw attitude decreased 44.23%, 49.91%, and 46.21%, respectively. In addition, the proposed method can estimate the attitude accurately without obvious phase lag when the maneuvering acceleration disturbance exists. The focus of this paper is to improve the performance of LOS motion control system of optoelectronic platform from the perspective of sensor signal processing. This method is suitable for aerospace applications with high-precision measurement and positioning requirements without maneuver interference, drift error and phase lag.
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Bradai, Sonia, Ghada Bouattour, Dhouha El Houssaini, and Olfa Kanoun. "Vibration Converter with Passive Energy Management for Battery-Less Wireless Sensor Nodes in Predictive Maintenance." Energies 15, no. 6 (March 8, 2022): 1982. http://dx.doi.org/10.3390/en15061982.
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Predictive maintenance is becoming increasingly important in industry and requires continuous monitoring to prevent failures and anticipate maintenance processes, resulting in reduced downtime. Vibration is often used for failure detection and equipment conditioning as it is well correlated to the machine’s operation and its variation is an indicator of process changes. In this context, we propose a novel energy-autonomous wireless sensor system that is able to measure without the use of batteries and automatically deliver alerts once the machine has an anomaly by the variation in acceleration. For this, we designed a wideband electromagnetic energy harvester and realized passive energy management to supply a wireless sensor node, which does not need an external energy supply. The advantage of the solution is that the designed circuit is able to detect the failure without the use of additional sensors, but by the Analog Digital Converter (ADC) of the Wireless Sensor Nodes (WSN) themselves, which makes it more compact and have lower energy consumption. The electromagnetic converter can harvest the relevant energy levels from weak vibration, with an acceleration of 0.1 g for a frequency bandwidth of 7 Hz. Further, the energy-management circuit enabled fast recharging of the super capacitor on a maximum of 31 s. The designed energy-management circuit consists of a six-stage voltage multiplier circuit connected to a wide-band DC-DC converter, as well as an under-voltage lock-out (UVLO) circuit to connect to the storage device to the WSN. In the failure condition with a frequency of 13 Hz and an acceleration of 0.3 g, the super capacitor recharging time was estimated to be 24 s. The proposed solution was validated by implementing real failure detection scenarios with random acceleration levels and, alternatively, modus. The results show that the WSN can directly measure the harvester’s response and decide about the occurrence of failure based on its characteristic threshold voltage without the use of an additional sensor.
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Pan, Daohua, and Hongwei Liu. "Human Falling Recognition Based on Movement Energy Expenditure Feature." Discrete Dynamics in Nature and Society 2021 (November 13, 2021): 1–12. http://dx.doi.org/10.1155/2021/1422586.
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Falls in the elderly are a common phenomenon in daily life, which causes serious injuries and even death. Human activity recognition methods with wearable sensor signals as input have been proposed to improve the accuracy and automation of daily falling recognition. In order not to affect the normal life behavior of the elderly, to make full use of the functions provided by the smartphone, to reduce the inconvenience caused by wearing sensor devices, and to reduce the cost of monitoring systems, the accelerometer and gyroscope integrated inside the smartphone are employed to collect the behavioral data of the elderly in their daily lives, and the threshold analysis method is used to study the human falling behavior recognition. Based on this, a three-level threshold detection algorithm for human fall behavior recognition is proposed by introducing human movement energy expenditure as a new feature. The algorithm integrates the changes of human movement energy expenditure, combined acceleration, and body tilt angle in the process of falling, which alleviates the problem of misjudgment caused by using only the threshold information of acceleration or (and) angle change to discriminate falls and improves the recognition accuracy. The recognition accuracy of this algorithm is verified by experiments to reach 95.42%. The APP is also devised to realize the timely detection of fall behavior and send alarms automatically.
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Shevchenko, Sergey, Maria Khivrich, and Oleg Markelov. "Ring-Shaped Sensitive Element Design for Acceleration Measurements: Overcoming the Limitations of Angular-Shaped Sensors." Electronics 8, no. 2 (January 29, 2019): 141. http://dx.doi.org/10.3390/electronics8020141.
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A new modification of an acceleration measurement sensor based on an acoustic waves resonance principle is proposed. Common angular-shaped sensors exhibit stress concentrations at the angular points near the origin points of destruction under external stresses; these points are the “Achilles’ heel” of the entire design. To overcome the above limitation, we suggest an angular-free ring-shaped sensitive element design that is characterized by enhanced robustness against external stress. The analytical treatment is validated by computer simulation results performed using the COMSOL Multiphysics software package. For an appropriate model parameterization, an original experiment has been carried out to estimate the stress-strained robustness of two potential candidates for sensitive console materials. Moreover, characteristics of the proposed sensor design, such as sensitivity threshold and maximum stress, have been obtained from the simulation data. The above results indicate that the proposed concept offers a promising advancement in surface acoustic waves (SAW) based accelerometer devices, and could, therefore, be used for several practical applications in such areas as biomedical and sports wearable devices; vehicular design, including unmanned solutions; and industrial robotics, especially those where high-G forces are expected.
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L, Padmasree, Preethi Eluri, Sai Subrahmanya Akhil Badampudi, and Sreedhar Reddy Mukkamalla. "Real Time Vision System for Autonomous Vehicles." Review of Computer Engineering Studies 7, no. 4 (December 31, 2020): 87–90. http://dx.doi.org/10.18280/rces.070402.
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With the increase in vehicle accidents regularly, there is a need to control these accidents and save precious lives. The main reason for accidents on roads are mainly observed by driver misconception, recklessness and over speeding. So, there is a need to develop a Vision system which has a ability to explore its surroundings and move accordingly. The Vision system is divided into 3 subsystems as Visual perception subsystem, Brake and Acceleration subsystem and Steering control subsystem. The Visual perception means the ability to interpret surrounding environment using light in the visual spectrum reflected by the objects in the environment. This subsystem uses distance measuring sensors such as Light Detection and Ranging (LiDAR) and Ultrasonic sensors for detecting objects and sends the data to brake and acceleration subsystem using Arduino IDE software. According to the data received either the brake or acceleration is initiated, it means that when the distance measuring sensor values reach the threshold values then the brakes are applied or else acceleration is implemented. In order to have a smooth ride the acceleration should be uniform without any jerks though speed changes. This is resolved by using Proportional-Integral- Derivative (PID) controller which reduces the gradual difference between the desired and input speed. The Steering control subsystem involves lane detection and path tracking. The lane detection is done using Python and OpenCv which uses various image processing steps, gives the steering angle by calculating the curvature radius of lanes. Therefore path tracking system is initialized taking the steering angle and direction as input for controlling the position of the vehicle.
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Ding, Song Lin, R. Izamshah R.A., John Mo, and Yong Wei Zhu. "Chatter Detection in High Speed Machining of Titanium Alloys." Key Engineering Materials 458 (December 2010): 289–94. http://dx.doi.org/10.4028/www.scientific.net/kem.458.289.
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Chatter is a complex phenomenon characterized by unstable, chaotic motions of the tool and by strong anomalous fluctuations of cutting forces. The situation becomes more serious in the milling of titanium alloys because of their low Young modulus and extended elastic behaviour. This paper presents an online chatter detection system based on the analysis of cutting forces, which is one of the integrated modules of a multi-sensor chatter detection system consisting acoustic and acceleration sensors. The cutting force is transformed into frequency domain by applying Fast Fourier Transform (FFT). Chatter frequency is identified in the frequency domain by comparing its power spectrum with predefined threshold. Experiments were carried out to validate the mythology.
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Mei, Chang, Farong Gao, and Ying Li. "A Determination Method for Gait Event Based on Acceleration Sensors." Sensors 19, no. 24 (December 12, 2019): 5499. http://dx.doi.org/10.3390/s19245499.
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A gait event is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. However, for the data acquisition of a three-dimensional motion capture (3D Mo-Cap) system, the high cost of setups, such as the high standard laboratory environment, limits widespread clinical application. Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. Inertial sensors are now sufficiently small in size and light in weight to be part of a body sensor network for the collection of human gait data. The acceleration signal has found important applications in human gait recognition. In this paper, using the experimental data from the heel and toe, first the wavelet method was used to remove noise from the acceleration signal, then, based on the threshold of comprehensive change rate of the acceleration signal, the signal was primarily segmented. Subsequently, the vertical acceleration signals, from heel and toe, were integrated twice, to compute their respective vertical displacement. Four gait events were determined in the segmented signal, based on the characteristics of the vertical displacement of heel and toe. The results indicated that the gait events were consistent with the synchronous record of the motion capture system. The method has achieved gait event subdivision, while it has also ensured the accuracy of the defined gait events. The work acts as a valuable reference, to further study gait recognition.
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Yong, Han, Huang Shiyong, Han MengXuan, Zhao Tao, Wen Guang, Gu Mingfei, and Zhang Qi. "The Experimental Validation of a Digital Filter Mathematical Modelling for Nuclear Fuel Vibration Monitoring System." Journal of Function Spaces 2022 (June 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/9741419.
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Aiming at vehicles will produce shocks and vibrations for various reasons in the process of transportation and handling, any shock and vibration that exceeds the regulations would cause damage to the nuclear fuel being transported. In order to monitor and analyze the shock and vibration data scientifically, a monitoring system based on MEMS acceleration sensor technology is developed to measure shocks and vibrations. The measured result involves some noise caused by the sensitivity of the sensor and the electrical noise, and a digital filter mathematical modelling is introduced to reduce noise and improve the measured result accuracy. In order to verify the effectiveness of the device designed in this paper, the device and the high-precision seismic acceleration sensor AC73 are, respectively, used for field tests; the results show that the test precision of the designed device can meet the requirements, and also, the designed shock and vibration monitoring system can record and store the three-axis acceleration, temperature, humidity, pressure, time, and other parameters that exceed the set threshold during nuclear fuel transportation in real time and complete the fuel assembly transportation status assessment and promptly remind the transportation personnel to take safety precautions and treatment measures. Therefore, it can be widely used in the monitoring, recording, and postevent data analysis of the transportation process of important products such as nuclear fuel.
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Kapilesh Kathiresh, Balaji Ramachandran, C. Edwin Samuel,. "MATLAB ALGORITHM FOR DRIVING PATTERN DETECTION AND ANALYSIS USING SMARTPHONE SENSORS." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (March 21, 2021): 1457–70. http://dx.doi.org/10.17762/itii.v9i1.299.
Full textAbstract:
In countries like India and China where the population density is very high and the number of vehicles on road keep on increasing every year it presents us with a problem that is monitoring this entire situation and preventing rash driving and accidents and even if they take place there should be immediate action taken to prevent it from happening again and making the roads a safer environment for everyone. To solve this problem, utilized sensors present in the Smartphone specifically the accelerometer sensor to detect the changes in parameters, for this an app was created. The app will read the sensor data that are embedded in the Smartphone and stores the sensors data in the database, The main reason of using the Smartphone is that implementation will be very easy and cost effective as the hardware is already available with everyone and the cost of implementation will be lower when compared to producing an exclusive hardware for this purpose only. The theoretical threshold values for accelerometer sensor data to calculate sudden breaking, sudden acceleration, harsh cornering with the respective axis is used to determine the initial situation. Feeding this data in MATLAB was we use an algorithm developed for this very purpose of analyzing this data.
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Aldawood, Ghufran, and Hamzeh Bardaweel. "Self-Powered Self-Contained Wireless Vibration Synchronous Sensor for Fault Detection." Sensors 22, no. 6 (March 18, 2022): 2352. http://dx.doi.org/10.3390/s22062352.
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Failure in dynamic structures poses a pressing need for fault detection systems. Interconnected sensor nodes of wireless sensor networks (WSN) offer a solution by communicating information about their surroundings. Nonetheless, these battery-powered sensors have an immense labor cost and require periodical battery maintenance and replacement. Batteries pose a significant environmental threat that is expected to cause irreversible damage to the ecosystem. We introduce a fully integrated vibration-powered energy harvester sensor system that is interfaced with a custom-developed fault detection app. Vibrations are used to power a radio frequency (RF) transmitter that is integrated with the vibration sensor subunit. The harvester-sensor unit is comprised of dual moving magnets that are bordered by coil windings for power and signal generation. The power generated from the harvester is used to operate the transmitter while the signal generated from the sensor is transmitted as a vibration signal. Transmitted values are streamed into a high precision fault detection app capable of detecting the frequency of vibrations with an error of 1%. The app employs an FFT algorithm on the transmitted data and notifies the user when a threshold vibration level is reached. The total energy consumed by the transmitter is 0.894 µJ at a 3 V operation. The operable acceleration of the system is 0.7 g [m/s2] at 5–10.6 Hz.
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Droogendijk, H., M. J. de Boer, R. G. P. Sanders, and G. J. M. Krijnen. "A biomimetic accelerometer inspired by the cricket's clavate hair." Journal of The Royal Society Interface 11, no. 97 (August 6, 2014): 20140438. http://dx.doi.org/10.1098/rsif.2014.0438.
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Crickets use so-called clavate hairs to sense (gravitational) acceleration to obtain information on their orientation. Inspired by this clavate hair system, a one-axis biomimetic accelerometer has been developed and fabricated using surface micromachining and SU-8 lithography. An analytical model is presented for the design of the accelerometer, and guidelines are derived to reduce responsivity due to flow-induced contributions to the accelerometer's output. Measurements show that this microelectromechanical systems (MEMS) hair-based accelerometer has a resonance frequency of 320 Hz, a detection threshold of 0.10 ms −2 and a dynamic range of more than 35 dB. The accelerometer exhibits a clear directional response to external accelerations and a low responsivity to airflow. Further, the accelerometer's physical limits with respect to noise levels are addressed and the possibility for short-term adaptation of the sensor to the environment is discussed.
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Zhou, Shuwen, and Siqi Zhang. "Study on Tractor Semi-Trailer Roll Stability Control." Open Mechanical Engineering Journal 8, no. 1 (September 16, 2014): 238–42. http://dx.doi.org/10.2174/1874155x01408010238.
Full textAbstract:
The rollover accidents in the tractor semi-trailer are often fatal and many factors could cause the tractor semi-trailer rollover. In this paper, a rollover prevention control method was proposed based on real-time calculation of rollover index. The vehicle Center of Gravity (CG) height from the ground is an important parameter in the rollover index and it is estimated through lateral acceleration sensor and suspension deflection sensors. Comparing the rollover index with the preset threshold, the differential braking will be applied to corresponding wheels once the trigger conditions are met. A roll stability control simulation was performed on the dynamic model based on virtual prototyping. The results show that the rollover prevention control proposed in this paper can stabilize the tractor semi-trailer and prevent from rollover on high speed curve driving.
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Jalalifar, Salman, Afsaneh Kashizadeh, Ishmam Mahmood, Andrew Belford, Nicolle Drake, Amir Razmjou, and Mohsen Asadnia. "A Smart Multi-Sensor Device to Detect Distress in Swimmers." Sensors 22, no. 3 (January 29, 2022): 1059. http://dx.doi.org/10.3390/s22031059.
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Drowning is considered amongst the top 10 causes of unintentional death, according to the World Health Organization (WHO). Therefore, anti-drowning systems that can save lives by preventing and detecting drowning are much needed. This paper proposes a robust and waterproof sensor-based device to detect distress in swimmers at varying depths and different types of water environments. The proposed device comprises four main components, including heart rate, blood oxygen level, movement, and depth sensors. Although these sensors were designed to work together to boost the system’s capability as an anti-drowning device, each could operate independently. The sensors were able to determine the heart rate to an accuracy of 1 beat per minute (BPM), 1% SpO2, the acceleration with adjustable sensitivities of ±2 g, ±4 g, ±8 g, and ±16 g, and the depth up to 12.8 m. The data obtained from the sensors were sent to a microcontroller that compared the input data to adjustable threshold values to detect dangerous situations. Being in hazardous situations for more than a specific time activated the alarming system. Based on the comparison made in the program and measuring the time of submersion, a message indicating drowning or safe was sent to a lifeguard to continuously monitor the swimmer’ condition via Wi-Fi to an IP address reachable by a mobile phone or laptop. It is also possible to continuously monitor the sensor outputs on the device’s display or the connected mobile phone or laptop. The threshold values could be adjusted based on biometric parameters such as swimming conditions (swimming pool, beach, depth, etc.) and swimmers health and conditions. The functionality of the proposed device was thoroughly tested over a wide range of parameters and under different conditions, both in air and underwater. It was demonstrated that the device could detect a range of potentially hazardous aquatic situations. This work will pave the way for developing an effective drowning sensing system that could save tens of thousands of lives across the globe every year.
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Zhao, Long, Jianwei You, and Nianmin Yao. "Smart Mobile Phone Groups - Based Design and Implementation of Vehicle Accident Self-rescue System." Electronics Science Technology and Application 3, no. 1 (August 16, 2016): 1. http://dx.doi.org/10.18686/esta.v3i1.1.
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<p class="p1"><span class="s1">Considering the deficiency that the existing automobile accident self-rescue system requires to assemble the specific sensor, GPS and communication module, the author designed a vehicle collision or crash detection and accident self-rescue system based on the smart mobile phone groups. Taking the acceleration signals of physical moments from the smart mobile phones in the accidents car as the input samples and the assembly of acceleration data as the calculating thresholds, the system can not only improve the accuracy rating of the judgments about the accidents, but can also reduce the unusable distress signals due to the damages to individual vehicle-borne device or mobile phone in severe accidents. When the signals exceed the threshold value, the system can draw support from the functions of video, GPS positioning and 3G networking in the mobile phones automatically to call for help from the rescue center. Meanwhile, a prototype system has been implemented on Android platform. The results of the experiments indicate that the system possesses the advantages of high accuracy of collision or crash recognition, low energy consumption and low cost.</span></p>
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Widodo, Romy Budhi, and Chikamune Wada. "Attitude Estimation Using Kalman Filtering: External Acceleration Compensation Considerations." Journal of Sensors 2016 (2016): 1–24. http://dx.doi.org/10.1155/2016/6943040.
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Attitude estimation is often inaccurate during highly dynamic motion due to the external acceleration. This paper proposes extended Kalman filter-based attitude estimation using a new algorithm to overcome the external acceleration. This algorithm is based on an external acceleration compensation model to be used as a modifying parameter in adjusting the measurement noise covariance matrix of the extended Kalman filter. The experiment was conducted to verify the estimation accuracy, that is, one-axis and multiple axes sensor movement. Five approaches were used to test the estimation of the attitude: (1) the KF-based model without compensating for external acceleration, (2) the proposed KF-based model which employs the external acceleration compensation model, (3) the two-step KF using weighted-based switching approach, (4) the KF-based model which uses thethreshold-basedapproach, and (5) the KF-based model which uses the threshold-based approach combined with a softened part approach. The proposed algorithm showed high effectiveness during the one-axis test. When the testing conditions employed multiple axes, the estimation accuracy increased using the proposed approach and exhibited external acceleration rejection at the right timing. The proposed algorithm has fewer parameters that need to be set at the expense of the sharpness of signal edge transition.
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Segalini, A., A. Valletta, A. Carri, and R. Savi. "Impact identification on flexible rockfall barriers: on site test of a wireless monitoring system." IOP Conference Series: Earth and Environmental Science 1124, no. 1 (January 1, 2023): 012125. http://dx.doi.org/10.1088/1755-1315/1124/1/012125.
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Abstract Flexible rockfall barriers represent an effective measure to mitigate hazard related to falling boulders. The monitoring activity of these protection structures is essential to guarantee their functionality, and usually aims to verify the barrier conditions and to identify any impact on the net. The system here presented, called D-Fence, was specifically developed for the realtime monitoring of flexible rockfall barriers. It consists of a series of separate battery-powered devices installed on the uprights of the monitored structure and transmit data to the elaboration center through a wireless local network. Each module includes a 3D tilt sensor, allowing the near real-time monitoring of the rotation of the uprights, while the integration of a shock sensor makes it possible to measure in real-time the accelerations experienced by the barrier. The onsite test of the D-Fence system involved the installation of four modules on a prototype barrier located in a pilot site in Northern Italy. Each device was placed on a different upright and was connected to a local Wi-Fi network. In this configuration, two different concrete boulders were dropped on the barrier in order to test the D-Fence ability to measure the tilt variation of the uprights and identify the overcoming of a predefined acceleration threshold.
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Xu, Mengjie, Jianhan Wang, Jiahui Mo, Xingfei Li, Lei Yang, and Feng Ji. "Single-Channel Blind Signal Separation of the MHD Linear Vibration Sensor Based on Singular Spectrum Analysis and Fast Independent Component Analysis." Sensors 22, no. 24 (December 9, 2022): 9657. http://dx.doi.org/10.3390/s22249657.
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An MHD vibration sensor, as a new type of sensor used for vibration measurements, meets the technical requirements for the low-noisy measurement of acceleration, velocity, and micro-vibration in spacecraft during their development, launch, and orbit operations. A linear vibration sensor with a runway type based on MHD was independently developed by a laboratory. In a practical test, its output signal was mixed with a large amount of noise, in which the continuous narrowband interference was particularly prominent, resulting in the inability to efficiently carry out the real-time detection of micro-vibration. Considering the high interference of narrowband noise in linear vibration signals, a single-channel blind signal separation method based on SSA and FastICA is proposed in this study, which provides a new strategy for linear vibration signals. Firstly, the singular spectrum of the linear vibration signal with noise was analyzed to suppress the narrowband interference in the collected signal. Then, a FastICA algorithm was used to separate the independent signal source. The experimental results show that the proposed method can effectively separate the useful linear vibration signals from the collected signals with low SNR, which is suitable for the separation of the MHD linear vibration sensor and other vibration measurement sensors. Compared with EEMD, VMD, and wavelet threshold denoising, the SNR of the separated signal is increased by 10 times on average. Through the verification of the actual acquisition of the linear vibration signal, this method has a good denoising effect.
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Saadatzadeh, E., A. Chehreghan, and R. Ali Abbaspour. "PEDESTRIAN DEAD RECKONING USING SMARTPHONES SENSORS: AN EFFICIENT INDOOR POSITIONING SYSTEM IN COMPLEX BUILDINGS OF SMART CITIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 19, 2019): 905–12. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-905-2019.
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Abstract. This paper proposes an indoor positioning method using Pedestrian Dead Reckoning (PDR) based on the detection of the mode of the user’s smartphone. In the first step, to determine the mode of carrying the smartphone (Holding, Calling, Swinging) by suitably formed feature vectors based on sensor data, three classification algorithms (Decision Tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN)) are evaluated. From the classification algorithm perspective, the decision tree algorithm had the best performance in terms of processing time and classification. Secondly, to determine the user position, the step detection is performed by defining the upper threshold and time threshold for Acceleration norm values. The orientation component is obtained by combining accelerometer, magnetometer, and gyroscope data using Complementary Filtering and Principal Component Analysis based on Global Acceleration (PCA-GA) methods. The mean standard deviation along the direct path for the three modes of carrying (Holding, Calling, and Swinging) were obtained 6.22, 6.82, and 14.68 degrees, respectively. Localization experiments were performed on 3 modes of carrying a smartphone in a rectangular geometry path. The mean final error of positioning from ordinary walking for the three modes of holding (Calling, Holding, Swinging) were obtained 2.11, 2.34, and 4.5 m, respectively.
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Wang, Feng, Wen Zhong Lou, Ming Ru Guo, and Yu Fei Lu. "Intelligent Logistics Monitoring Microsystem Based on STM32." Key Engineering Materials 645-646 (May 2015): 896–99. http://dx.doi.org/10.4028/www.scientific.net/kem.645-646.896.
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A intelligent logistics monitoring microsystem has been designed based on STM32F103T8, which is high ability, low power consumption and low cost. The radio frequency (RF) chip CC1101, the acceleration sensor BMA280 and the temperature and humidity sensor HTU21D are selected to acquire the corresponding data for the intelligent logistics microsystem, which are ultra-low power consumption and ultra-small size. Moreover, in order to further reduce power consumption, the interrupt mode is adopted in the data acquisition module and the sleep mode is used in the MCU module in the software control. On the other hand, in order to further optimize the performance of miniaturization, the SWD (Serial Wire Debug) protocol is used. Meanwhile, the system will alarm the transportation officer once the acquired data met or exceed the threshold, which will help him to take corresponding measures timely, thus reducing the risk of occurrence effectively.
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Scheurer, Simon, Janina Koch, Martin Kucera, Hȧkon Bryn, Marcel Bärtschi, Tobias Meerstetter, Tobias Nef, and Prabitha Urwyler. "Optimization and Technical Validation of the AIDE-MOI Fall Detection Algorithm in a Real-Life Setting with Older Adults." Sensors 19, no. 6 (March 18, 2019): 1357. http://dx.doi.org/10.3390/s19061357.
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Falls are the primary contributors of accidents in elderly people. An important factor of fall severity is the amount of time that people lie on the ground. To minimize consequences through a short reaction time, the motion sensor “AIDE-MOI” was developed. “AIDE-MOI” senses acceleration data and analyzes if an event is a fall. The threshold-based fall detection algorithm was developed using motion data of young subjects collected in a lab setup. The aim of this study was to improve and validate the existing fall detection algorithm. In the two-phase study, twenty subjects (age 86.25 ± 6.66 years) with a high risk of fall (Morse > 65 points) were recruited to record motion data in real-time using the AIDE-MOI sensor. The data collected in the first phase (59 days) was used to optimize the existing algorithm. The optimized second-generation algorithm was evaluated in a second phase (66 days). The data collected in the two phases, which recorded 31 real falls, was split-up into one-minute chunks for labelling as “fall” or “non-fall”. The sensitivity and specificity of the threshold-based algorithm improved significantly from 27.3% to 80.0% and 99.9957% (0.43) to 99.9978% (0.17 false alarms per week and subject), respectively.
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Gao, Yang, Jing Min Gao, and Jiu He Wang. "Research of Humen Fall Detection Algorithm Based on Tri-Axis Accelerometer." Key Engineering Materials 500 (January 2012): 623–28. http://dx.doi.org/10.4028/www.scientific.net/kem.500.623.
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The real-time monitoring of human movement can provide valuable information regarding an individual’s degree of functional ability and general level of activity. This paper presents a fall-detection technology based on tri-axial accelerometer sensor was introduced. The acceleration data of the activities with the characteristic quantity SVM and SMA was analyzed. A method based on SVM and SMA, that takes the human body activity (erectness/lies down) as the auxiliary criterion to distinguish fall and ADL is proposed, and concrete threshold value and related parameters are summarized in this article. The experiment results proved that this scheme can obtain highly rate of accuracy and this algorithm has very good timeliness.
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Jakovlev, Sergej, Tomas Eglynas, Miroslav Voznak, Mindaugas Jusis, Pavol Partila, Jaromir Tovarek, and Valdas Jankunas. "Detection of Physical Impacts of Shipping Containers during Handling Operations Using the Impact Detection Methodology." Journal of Marine Science and Engineering 10, no. 9 (September 5, 2022): 1250. http://dx.doi.org/10.3390/jmse10091250.
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The transportation of cargo inside shipping containers is a risky operation that requires constant monitoring activities and real-time operational actions. Yet, the detection of the real dynamics of the container and the surrounding infrastructure and extraction of true subsequent critical events is still an unresolved issue among engineers. In this paper, we analyze the new physical impact detection method, namely the Impact Detection Methodology (IDM), to detect the most obvious and force-dependent impacts from acceleration data, using the IoT sensor in an experimental environment using the heavy machinery of a seaport. By variating the threshold level, we have observed the changes in the number of impacts detected within three separate case studies. Results suggest that the optimal parameters tend to provide an adequate number of events, yet even the slightest change in the threshold level can increase or decrease the number of detected impacts in a non-linear fashion, making the detection harder, due to unforeseen external impacts on the dataset, the filtering of which is still the main priority of our future research.
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Yang, Meng, Xiaoxu Sun, Xiaoting Deng, Zhixiong Lu, and Tao Wang. "Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm." Agriculture 13, no. 6 (May 28, 2023): 1133. http://dx.doi.org/10.3390/agriculture13061133.
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To obtain the load spectrum of the traction resistance of the three-point suspension device under tractor-plowing conditions, a load spectrum extrapolation method based on a genetic algorithm optimal threshold selection is proposed. This article first uses a pin force sensor to measure the plowing resistance of the tractor’s three-point suspension device under plowing conditions and preprocesses the collected load signal. Next, a genetic algorithm is introduced to select the threshold based on the Peak Over Threshold (POT) extremum extrapolation model. The Generalized Pareto Distribution (GPD) fits the extreme load distribution that exceeds the threshold range, generating new extreme points that follow the GPD distribution to replace the extreme points in the original data, achieving the extrapolation of the load spectrum. Finally, the loading spectrum that can be achieved on the test bench is obtained based on the miner fatigue theory and accelerated life theory. The results show that the upper threshold of the time-domain load data obtained by the genetic algorithm is 10.975 kN, and the grey correlation degree is 0.7249. The optimal lower threshold is 8.5455 kN, the grey correlation degree is 0.7722, and the fitting effect of the GPD distribution is good. The plowing operation was divided into five stages: plowing tool insertion, acceleration operation, constant speed operation, deceleration operation, and plowing tool extraction. A traction resistance loading spectrum that can be achieved on the test bench was developed. The load spectrum extrapolation method based on the genetic algorithm optimal threshold selection can improve the accuracy of threshold selection and achieve the extrapolation and reconstruction of the load spectrum. After processing the extrapolated load spectrum, it can be transformed into a load spectrum that can be recognized by the test bench.
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Aoki, Takahiro, Makoto Shibata, Guilherme Violin, Shogo Higaki, and Koji Yoshioka. "Detection of foaling using a tail-attached device with a thermistor and tri-axial accelerometer in pregnant mares." PLOS ONE 18, no. 6 (June 2, 2023): e0286807. http://dx.doi.org/10.1371/journal.pone.0286807.
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It is desirable to attend to the mare at the time of foaling in order to assist fetal delivery and prevent complications. The early detection of the onset of labor is an important issue for the equine industry. The purpose of this study was to examine the applicability of a sensor for foaling detection using the data of surface temperature (ST), roll angle (rotation about the y-axis) and y-axis (long axis of the tail) acceleration which were collected from a multimodal device attached to the ventral tail base of the mare. The data were collected every 3 minutes in 17 pregnant mares. Roll angle differences from the reference values and the mare’s posture (standing or recumbent) confirmed by video were compared and associated. Cohen’s kappa coefficient was 0.99 when the threshold was set as ± 0.3 radian in roll angle differences. This result clearly showed that the sensor data can accurately distinguish between standing and recumbent postures. The hourly sensor data with a lower ST (LST < 35.5°C), a recumbent posture determined by the roll angle, and tail-raising (TR, decline of 200 mg or more from the reference value in y-axis acceleration) was significantly higher during the last hour prepartum than 2−120 hours before parturition (P < 0.01). The accuracy of foaling detection within one hour was verified using the following three indicators: LST; lying down (LD, change from standing to recumbent posture); and TR. When LST, LD and TR were individually examined, even though all indicators showed that sensitivity was 100%, the precision was 13.1%, 8.1% and 2.8%, respectively. When the data were combined as LST+LD, LST+TR, LD+TR and LST+LD+TR, detection of foaling improved, with precisions of 100%, 32.1%, 56.7% and 100%, respectively. In conclusion, the tail-attached multimodal device examined in this present study is useful for detecting foaling.
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Maniatis, Georgios, Trevor Hoey, Rebecca Hodge, Dieter Rickenmann, and Alexandre Badoux. "Inertial drag and lift forces for coarse grains on rough alluvial beds measured using in-grain accelerometers." Earth Surface Dynamics 8, no. 4 (December 21, 2020): 1067–99. http://dx.doi.org/10.5194/esurf-8-1067-2020.
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Abstract. Quantifying the force regime that controls the movement of a single grain during fluvial transport has historically proven to be difficult. Inertial micro-electromechanical system (MEMS) sensors (sensor assemblies that mainly comprise micro-accelerometers and gyroscopes) can used to address this problem using a “smart pebble”: a mobile inertial measurement unit (IMU) enclosed in a stone-like assembly that can measure directly the forces on a particle during sediment transport. Previous research has demonstrated that measurements using MEMS sensors can be used to calculate the dynamics of single grains over short time periods, despite limitations in the accuracy of the MEMS sensors that have been used to date. This paper develops a theoretical framework for calculating drag and lift forces on grains based on IMU measurements. IMUs were embedded a spherical and an ellipsoidal grain and used in flume experiments in which flow was increased until the grain moved. Acceleration measurements along three orthogonal directions were then processed to calculate the threshold force for entrainment, resulting in a statistical approximation of inertial impulse thresholds for both the lift and drag components of grain inertial dynamics. The ellipsoid IMU was also deployed in a series of experiments in a steep stream (Erlenbach, Switzerland). The inertial dynamics from both sets of experiments provide direct measurement of the resultant forces on sediment particles during transport, which quantifies (a) the effect of grain shape and (b) the effect of varied-intensity hydraulic forcing on the motion of coarse sediment grains during bedload transport. Lift impulses exert a significant control on the motion of the ellipsoid across hydraulic regimes, despite the occurrence of higher-magnitude and longer-duration drag impulses. The first-order statistical generalisation of the results suggests that the kinetics of the ellipsoid are characterised by low- or no-mobility states and that the majority of mobility states are controlled by lift impulses.
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He, Ren, and Daxing Huang. "Automatic testing method for static pressure drive performance of electronic hydraulic brake system." Thermal Science 24, no. 3 Part A (2020): 1529–36. http://dx.doi.org/10.2298/tsci190511018h.
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To solve the problem of static pressure transmission performance of electronic hydraulic brake system, the mathematical models of main cylinder, solenoid valve, accumulator, and motor hydraulic pump of electronic hydraulic brake system are established. Based on the mathematical model, the static pressure transmission performance of electronic hydraulic brake system is analyzed. Then the standard normal state model of static pressure transmission performance of electronic hydraulic brake system is established by statistical method. The threshold correlation degree between the vibration signal of the static pressure drive and the normal state mode obtained by the vibration acceleration sensor are calculated. If the threshold correlation degree is greater than or equal to 0.5, the precision pressure transmission state of the electronic hydraulic brake system to be tested belongs to the standard normal state, and the threshold correlation degree is less than 0.5, indicating that the precision pressure transmission state of the electronic hydraulic brake system to be tested does not belong to the standard normal state. The test results show that the proposed method can effectively detect the boost response of the static pressure transmission of the electronic hydraulic brake system under high and low strength conditions under normal conditions and accumulator failure conditions. The method can effectively detect the static pressure transmission state of the electronic hydraulic brake system belongs to the fault state according to the threshold correlation degree, which is consistent with the simulation results.
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De Luca, Carlo J., and Emily C. Hostage. "Relationship Between Firing Rate and Recruitment Threshold of Motoneurons in Voluntary Isometric Contractions." Journal of Neurophysiology 104, no. 2 (August 2010): 1034–46. http://dx.doi.org/10.1152/jn.01018.2009.
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We used surface EMG signal decomposition technology to study the control properties of numerous simultaneously active motor units. Six healthy human subjects of comparable age (21 ± 0.63 yr) and physical fitness were recruited to perform isometric contractions of the vastus lateralis (VL), first dorsal interosseous (FDI), and tibialis anterior (TA) muscles at the 20, 50, 80, and 100% maximum voluntary contraction force levels. EMG signals were collected with a five-pin surface array sensor that provided four channels of data. They were decomposed into the constituent action potentials with a new decomposition algorithm. The firings of a total of 1,273 motor unit action potential trains, 20–30 per contraction, were obtained. The recruitment thresholds and mean firing rates of the motor units were calculated, and mathematical equations were derived. The results describe a hierarchical inverse relationship between the recruitment thresholds and the firing rates, including the first and second derivatives, i.e., the velocity and the acceleration of the firing rates. This relationship describes an “operating point” for the motoneuron pool that remains consistent at all force levels and is modulated by the excitation. This relationship differs only slightly between subjects and more distinctly across muscles. These results support the “onion skin” property that suggests a basic control scheme encoded in the physical properties of motoneurons that responds consistently to a “common drive” to the motoneuron pool.
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Yi, Yongdan, and Tingting Yu. "Intelligent Detection and Analysis of Wearable Devices in Wushu Training." Security and Communication Networks 2022 (August 30, 2022): 1–6. http://dx.doi.org/10.1155/2022/1413905.
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With the integration and development of artificial intelligence and medical technology, wearable intelligent technology has become an important health testing equipment in people’s lives, constantly testing physical function and health. However, according to the movement standards, body indicators, and constantly changing detection indexes of athletes in the exercise process, it can effectively guide athletes to use them correctly and efficiently, which has become an important task of wearable intelligent technology. In the design mode of wearable smart devices, wearable bracelets are designed with acceleration sensors, martial arts training data are measured, and machine learning technology is used to analyze and evaluate the data. When a user uses the method, a sensor is used for collecting the data, the data are transmitted to a processing platform through low-power Bluetooth, the data are analyzed through a program, the accuracy of each action is output, and finally, a standard measurement result of a section of the boxing method is combined. This paper collects and analyzes the data of body characteristics and movement characteristics of wearable intelligent devices in Wushu training. Sensor technology and filtering technology are used to collect and filter the collected information, and better analysis data are obtained. Finally, the filtered data of Wushu are analyzed, and then, the efficiency and performance of different algorithms in Wushu training are compared. Wearable intelligent equipment collects Wushu action training data and then uses fixed threshold classification to recognize Wushu action. The results show that the method used has high accuracy.
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Qu, Zhaole, Jianze Liu, Yang Li, Fazhan Yang, and Jiang Liu. "Study on Multi-Mode Switching Control of Intelligent Suspension under Full Road Section." Processes 11, no. 6 (June 11, 2023): 1776. http://dx.doi.org/10.3390/pr11061776.
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The safety, comfort, and energy feedback of active suspension in a single control mode is mutually restricted. To meet the needs of drivers and passengers for vehicle driving performance under different road conditions, this paper proposes a multi-mode switching control strategy of an intelligent suspension system, aiming at improving the stability and comfort of vehicles under different road conditions. In this paper, the adaptive Kalman filter algorithm with a forgetting factor is used to estimate the road input. The accuracy of the algorithm in estimating the road input is verified by simulation and experiment. The single-double threshold logic judgment method is used to formulate the switching rules between each working mode. In the controller, the PID control of the BP neural network and the LQR control optimized by GA are used to optimize and adjust the vehicle driving performance indexes in different modes, which effectively solves the problem of limited adaptability of suspension control optimization objectives under different road driving conditions. Based on the data from the vehicle acceleration sensor and road condition sensor, the modeling and simulation of the switching control system are carried out. The simulation results show that the designed control system can effectively improve the comprehensive performance of the vehicle under different road driving conditions. Compared with the traditional active suspension, the body acceleration is increased by 26% on the B-grade road surface, which effectively improves the user’s ride comfort. Compared with the traditional active suspension, the tire dynamic displacement is increased by 24% on the D-grade road, which can significantly improve the overall performance of the vehicle and meet the design requirements of the system.
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Kumari, shubhangi. "A Thing Speak IoT Based Vibration Measurement and Monitoring System Using an Accelerometer sensor." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 1249–58. http://dx.doi.org/10.22214/ijraset.2021.37599.
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Abstract: This paper presents the development of a Thing Speak IoT on a Real-Time Vibration measurement System using the accelerometer Sensor. Many systems have been designed previously but some lack systems are identified where it does not provide adaptively connections and alert to web pages on logging data collections. Thus, understanding the previous system model is important to compare the importance of new build parameters in designing the new system. An evaluation of the current model, hardware, and software is important before a new architecture is developed. This research has developed a prototype system to monitor and measure the vibration of a system remotely and setting up threshold and alert accordingly. The designed system assisted with an internet as vibration monitoring system for the machines. Research methods consist of two parts involved hardware and software development. The hardware development covers the connections of the accelerometer sensor and the software involved in constructed coding using the C language program. The program then is compiled and uploaded into the Node MCU to display the acceleration of the system. An open-source Internet of Things called Thing Speak is used as a platform to retrieve and display the collected data. Real-time monitoring can be accessed through Smartphone and web applications. This study has been considered successfully implemented and it is a significant study that performs on new IoT platforms and adaptively ready to monitor a vibration remotely. Keyword: Accelerometer Sensor, Internet of Things, Thing Speak, Real-Time.
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Sun, Xu, Kai Zhao, Wei Jiang, and Xinlong Jin. "Method of Analyzing and Managing Volleyball Action by Using Action Sensor of Mobile Device." Journal of Sensors 2021 (September 20, 2021): 1–11. http://dx.doi.org/10.1155/2021/6232968.
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With the development of electronic technology and sensor technology, more and more intelligent electronic devices integrate micro inertial sensors, which makes the research of human action recognition based on action sensing data have great application value. Data-based action recognition is a new research direction in the field of pattern recognition, which is essentially a process of action data acquisition, feature extraction, feature extraction, and recognition, the process of classification and recognition. Inertial motion information includes acceleration and angular velocity information, which is ubiquitous in daily life. Compared with motion recognition based on visual information, it can more directly reflect the meaning of action. This study mainly discusses the method of analyzing and managing volleyball action by using the action sensor of mobile device. Based on the motion recognition algorithm of support vector machine, the motion recognition process of support vector machine is constructed. When the data terminal and gateway of volleyball players are not in the same LAN, the classification algorithm classifies the samples to be tested through the characteristic data, which directly affects the recognition results. In this paper, the support vector machine algorithm is selected as the data classification algorithm, and the calculation of the classification process is reduced by designing an appropriate kernel function. For multiclass problems, the hierarchical structure of directed acyclic graph is optimized to improve the recognition rate. We need to bind motion sensors to human joints. In order to realize real-time recognition of human motion, mobile devices need to add windows to the motion capture data, that is, divide the data into a small sequence of specified length, and provide more application scenarios for the device. This method of embedding motion sensors into devices to read motion information is widely used, which provides a convenient data acquisition method for human motion pattern recognition based on motion information. The multiclassification support vector machine algorithm is used to train the classification algorithm model with action data. When the signal strength of the sensor is 90 t and the speed is 2.0 m/s and 0.5 m/s, the detection accuracy of the adaptive threshold is 93% and 95%, respectively. The results show that the SVM method based on hybrid kernel function can greatly improve the recognition accuracy of volleyball stroke, and the recognition time is short.
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Zhang, Huaibo, and Jianghua Zhu. "Practicability of Sports Goods in the Sports Field Based on Artificial Intelligence Technology." Mobile Information Systems 2022 (June 21, 2022): 1–9. http://dx.doi.org/10.1155/2022/4964894.
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People are in the intellectual age. The use of technologies such as smart search engines, machine translation, fingerprint analysis, facial scanning, and self-driving makes people’s social and work lives happier. The intersection of artificial intelligence and other projects has also become the focus of research in the new era. This article uses comparative experimental methods and sampling methods, puts forward the evaluation method of association rules in the recommendation of sports goods, and compares the selection of sensors used by the five types of sports companies in the sports experiments. In the experiment part, according to the minimum confidence level, the two rules are met. Minimum confidence is a threshold defined by users or experts to measure confidence, which represents the lowest reliability of association rules. The conclusion is that 30% of users have bought running shoes and hiking shoes at the same time and 66.6% of users have also purchased sports suits; there are also sports suits purchased at the same time. All mountain bike users have bought sports gloves. The weight of Freescale is 0.2530, the weight of Bosch is 0.4457, the weight of ST is 0.0946, the weight of VTI is 0.0953, and the weight of Konix is 0.1114. The experimental results show that the selection result of the three-axis acceleration sensor is the SMB380 model of Bosch.
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Borzì, Luigi, Luis Sigcha, and Gabriella Olmo. "Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson’s Disease." Sensors 23, no. 9 (April 30, 2023): 4426. http://dx.doi.org/10.3390/s23094426.
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Freezing of gait (FoG) is a disabling clinical phenomenon of Parkinson’s disease (PD) characterized by the inability to move the feet forward despite the intention to walk. It is one of the most troublesome symptoms of PD, leading to an increased risk of falls and reduced quality of life. The combination of wearable inertial sensors and machine learning (ML) algorithms represents a feasible solution to monitor FoG in real-world scenarios. However, traditional FoG detection algorithms process all data indiscriminately without considering the context of the activity during which FoG occurs. This study aimed to develop a lightweight, context-aware algorithm that can activate FoG detection systems only under certain circumstances, thus reducing the computational burden. Several approaches were implemented, including ML and deep learning (DL) gait recognition methods, as well as a single-threshold method based on acceleration magnitude. To train and evaluate the context algorithms, data from a single inertial sensor were extracted using three different datasets encompassing a total of eighty-one PD patients. Sensitivity and specificity for gait recognition ranged from 0.95 to 0.96 and 0.80 to 0.93, respectively, with the one-dimensional convolutional neural network providing the best results. The threshold approach performed better than ML- and DL-based methods when evaluating the effect of context awareness on FoG detection performance. Overall, context algorithms allow for discarding more than 55% of non-FoG data and less than 4% of FoG episodes. The results indicate that a context classifier can reduce the computational burden of FoG detection algorithms without significantly affecting the FoG detection rate. Thus, implementation of context awareness can present an energy-efficient solution for long-term FoG monitoring in ambulatory and free-living settings.
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Yang, Yongle, Zhifei Zhang, Liangfeng Peng, Jie Jin, and Qinghua Wang. "Accelerated Editing Method for Vehicle Durability Fatigue Load Spectrum Based on Wigner-Ville Transform." Sensors 23, no. 14 (July 16, 2023): 6435. http://dx.doi.org/10.3390/s23146435.
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A Wigner-Ville transform-based (WVT-based) load spectrum fast editing method for vehicle parts is proposed to improve the efficiency of durability tests. In this method, the instantaneous energy spectrum (IES) of the original time-domain signal is obtained via the Wigner-Ville transform, which is used as a criterion to identify time-domain points of ineffective damage contribution. A genetic algorithm (GA) based threshold optimization model is also proposed to automatically set the threshold of the IES under consideration of the relative damage requirements and statistical parameters of the signal. The effectiveness of the above proposed editing method is demonstrated by compiling an SUV’s suspension coil spring signal obtained from physical sensor-based measurements. Meanwhile, the same spectrum is also processed using time-domain editing, Short-time Fourier-transform, and S-transform methods for comparison. The results show that the WVT-based edited spectrum has a time-duration retention ratio of about 76.30%, which is significantly superior to other methods, with the same pseudo-damage retention and statistical parameter error constraints. Moreover, in combination with the fatigue simulation analysis, it verifies that the load effect of the edited spectrum matches well with that of the original. Thus, the proposed method is considered more effective for compiling component load signals in vehicle acceleration durability tests.