Journal articles: 'Sensor modelling'

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Yu, Qinxiao, Ning Zhu, Geng Li, and Shoufeng Ma. "Simulation-Based Sensor Location Model for Arterial Street." Discrete Dynamics in Nature and Society 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/854089.

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Traffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly dynamic and the movement of vehicles is disturbed by signals and irregular vehicle maneuver. It is challenging to estimate the arterial street travel time with limited sensors. In order to solve the problem, the paper presents travel time estimation models that rely on speed data collected by sensor. The relationship between sensor position and vehicle trajectory in single link is investigated. A sensor location model in signalized arterial is proposed to find the optimal sensor placement with the minimum estimation error of arterial travel time. Numerical experiments are conducted in 3 conditions: synchronized traffic signals, green wave traffic signals, and vehicle-actuated signals. The results indicate that the sensors should not be placed in vehicle queuing area. Intersection stop line is an ideal sensor position. There is not any fixed sensor position that can cope with all traffic conditions.

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Fan, Hua, Huichao Yue, Jiangmin Mao, Ting Peng, Siming Zuo, Quanyuan Feng, Qi Wei, and Hadi Heidari. "Modelling and fabrication of wide temperature range Al_0.24Ga_0.76As/GaAs Hall magnetic sensors." Journal of Semiconductors 43, no. 3 (March 1, 2022): 034101. http://dx.doi.org/10.1088/1674-4926/43/3/034101.

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Abstract Silicon Hall-effect sensors have been widely used in industry and research fields due to their straightforward fabrication process and CMOS compatibility. However, as their material property limitations, technicians usually implement complex CMOS circuits to improve the sensors’ performance including temperature drift and offset compensation for fitting tough situation, but it is no doubt that it increases the design complexity and the sensor area. Gallium arsenide (GaAs) is a superior material of Hall-effect device because of its large mobility and stable temperature characteristics. Concerning there is no specified modelling of GaAs Hall-effect device, this paper investigated its modelling by using finite element method (FEM) software Silvaco TCAD® to help and guide GaAs Hall-effect device fabrication. The modeled sensor has been fabricated and its experimental results are in agreement with the simulation results. Comparing to our previous silicon Hall-effect sensor, the GaAs Hall-effect sensor demonstrates potential and reliable benchmark for the future Hall magnetic sensor developments.

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Skvortsov, Alex, and Branko Ristic. "Modelling and Performance Analysis of a Network of Chemical Sensors with Dynamic Collaboration." International Journal of Distributed Sensor Networks 8, no. 1 (November 24, 2011): 656231. http://dx.doi.org/10.1155/2012/656231.

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The problem of environmental monitoring using a wireless network of chemical sensors with a limited energy supply is considered. Since the conventional chemical sensors in active mode consume vast amounts of energy, an optimisation problem arises in the context of a balance between the energy consumption and the detection capabilities of such a network. A protocol based on “dynamic sensor collaboration” is employed: in the absence of any pollutant, the majority of sensors are in the sleep (passive) mode; a sensor is invoked (activated) by wake-up messages from its neighbors only when more information is required. The paper proposes a mathematical model of a network of chemical sensors using this protocol. The model provides valuable insights into the network behavior and near optimal capacity design (energy consumption against detection). An analytical model of the environment, using turbulent mixing to capture chaotic fluctuations, intermittency, and nonhomogeneity of the pollutant distribution, is employed in the study. A binary model of a chemical sensor is assumed (a device with threshold detection). The outcome of the study is a set of simple analytical tools for sensor network design, optimisation, and performance analysis.

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Vilas, Sheetal, and G. G. "Modelling of Hexagonal Electromagnetic Sensor." International Journal of Computer Applications 151, no. 8 (October 17, 2016): 1–4. http://dx.doi.org/10.5120/ijca2016911843.

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Schmidt, D., M. Krämer, T. Kuhn, and N. Wehn. "Energy modelling in sensor networks." Advances in Radio Science 5 (June 13, 2007): 347–51. http://dx.doi.org/10.5194/ars-5-347-2007.

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Abstract. Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

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Siart, U., S. Tejero, and J. Detlefsen. "Exponential Modelling for Mutual-Cohering of Subband Radar Data." Advances in Radio Science 3 (May 12, 2005): 199–204. http://dx.doi.org/10.5194/ars-3-199-2005.

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Abstract. Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.

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Daniel, M., M. Janicki, W. Wroblewski, A. Dybko, Z. Brzozka, and A. Napieralski. "Ion selective transistor modelling for behavioural simulations." Water Science and Technology 50, no. 11 (December 1, 2004): 115–23. http://dx.doi.org/10.2166/wst.2004.0679.

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Computer aided design and simulation of complex silicon microsystems oriented for environment monitoring requires efficient and accurate models of ion selective sensors, compatible with the existing behavioural simulators. This paper concerns sensors based on the back-side contact Ion Sensitive Field Effect Transistors (ISFETs). The ISFETs with silicon nitride gate are sensitive to hydrogen ion concentration. When the transistor gate is additionally covered with a special ion selective membrane, selectivity to other than hydrogen ions can be achieved. Such sensors are especially suitable for flow analysis of solutions containing various ions. The problem of ion selective sensor modelling is illustrated here on a practical example of an ammonium sensitive membrane. The membrane is investigated in the presence of some interfering ions and appropriate selectivity coefficients are determined. Then, the model of the whole sensor is created and used in subsequent electrical simulations. Providing that appropriate selectivity coefficients are known, the proposed model is applicable for any membrane, and can be straightforwardly implemented for behavioural simulation of water monitoring microsystems. The model has been already applied in a real on-line water pollution monitoring system for detection of various contaminants.

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Badrinath, Suriya, and Raja Muthalagu. "Modelling Human Activity using Smartphone Data." Open Biomedical Engineering Journal 15, no. 1 (October 18, 2021): 58–70. http://dx.doi.org/10.2174/1874120702115010058.

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Background: Over time, multichannel time series data were utilized for the purpose of modeling human activity. Instruments such as an accelerometer and gyroscope which had sensors embedded in them, recorded sensor data which were then utilized to record 6-axes, single dimensional convolution for the purpose of formulating a deep CNN. The resultant network achieved 94.79% activity recognition accuracy on raw sensor data, and 95.57% accuracy when Fast Fourier Transform (FFT) knowledge was added to the sensor data. Objective: This study helps to achieve an orderly report of daily Human activities for the overall balanced lifestyle of a healthy human being. Methods: Interfacing is done using Arduino Uno, Raspberry-Pi 3, heart rate sensor and accelerometer ADXL345 to generate real time values of day-to-day human activities such as walking, sleeping, climbing upstairs/downstairs and so on. Initially, the heart pulse of our four tested individuals is recorded and tabulated to depict and draw conclusions all the way from “Low BP” to “Heavy Exercise”. The convolution neural network is initially trained with an online human activity dataset and tested using our real time generated values which are sent to the MAC OS using a Bluetooth interface. Results: We obtain graphical representations of the amount of each activity performed by the test set of individuals, and in turn conclusions which suggest increase or decrease in the consistency of certain activities to the users, depicted through our developed iOS application, “Fitnesse”. Conclusion: The result of this works is used to improve the daily health routines and the overall lifestyle of distressed patients.

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Magosi, Zoltan Ferenc, Hexuan Li, Philipp Rosenberger, Li Wan, and Arno Eichberger. "A Survey on Modelling of Automotive Radar Sensors for Virtual Test and Validation of Automated Driving." Sensors 22, no. 15 (July 29, 2022): 5693. http://dx.doi.org/10.3390/s22155693.

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Radar sensors were among the first perceptual sensors used for automated driving. Although several other technologies such as lidar, camera, and ultrasonic sensors are available, radar sensors have maintained and will continue to maintain their importance due to their reliability in adverse weather conditions. Virtual methods are being developed for verification and validation of automated driving functions to reduce the time and cost of testing. Due to the complexity of modelling high-frequency wave propagation and signal processing and perception algorithms, sensor models that seek a high degree of accuracy are challenging to simulate. Therefore, a variety of different modelling approaches have been presented in the last two decades. This paper comprehensively summarises the heterogeneous state of the art in radar sensor modelling. Instead of a technology-oriented classification as introduced in previous review articles, we present a classification of how these models can be used in vehicle development by using the V-model originating from software development. Sensor models are divided into operational, functional, technical, and individual models. The application and usability of these models along the development process are summarised in a comprehensive tabular overview, which is intended to support future research and development at the vehicle level and will be continuously updated.

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Aernouts, Michiel, Ben Bellekens, and Maarten Weyn. "MapFuse: Complete and Realistic 3D Modelling." Journal of Robotics 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/4942034.

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Validating a 3D indoor radio propagation model that simulates the signal strength of a wireless device can be a challenging task due to an incomplete or a faulty environment model. In this paper, we present a novel method to simulate a complete indoor environment that can be used for evaluating a radio propagation model efficiently. In order to obtain a realistic and robust model of the full environment, the OctoMap framework is applied. The system combines the result of a SLAM algorithm and secondly a simple initial model of the same environment in a probabilistic way. Due to this approach, sensor noise and accumulated registration errors are minimised. Furthermore, in this article, we evaluate the merging approach with two SLAM algorithms, three vision sensors, and four datasets, of which one is publicly available. As a result, we have created a complete volumetric model by merging an initial model of the environment with the result of RGB-D SLAM based on real sensor measurements.

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Kazda, Jakub, Richard Matas, and Jan Sedláček. "Modelling fluid flow and heat transfer tasks for testing PIR motion Sensor." MATEC Web of Conferences 345 (2021): 00017. http://dx.doi.org/10.1051/matecconf/202134500017.

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The aim of this paper is to describe the methodology of modelling fluid flow and heat transfer tasks for testing electronic motion sensors, especially PIR (passive infra-red) motion sensors. The motion sensor measures changes in electromagnetic radiation in the infrared range caused by the movement of warmer objects compared to its surroundings. Distortion of the perception of the environment can lead to false alarms or insensitivity of the detector. PIR motion sensors should be designed and located to minimize heating of the lens by ambient air. The sensor may be exposed to conditions not specified in the basic standards. The practical part of this article deals with a non-standard test. A single-phase transient simulation in a specific test cabinet for two specific motion sensor models was performed using the computational fluid dynamics (CFD) method. The aim of these simulations was to evaluate the effect of hot flowing air on the lens and to compare the designs of both models. Comparison and analysis of the results showed that the test configuration does not guarantee a defined flow at the outlet of the pipeline, so a new configuration was designed.

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Akkaş, Mustafa Alper. "Nano-Sensor Modelling for Intra-Body Nano-Networks." Wireless Personal Communications 118, no. 4 (February 11, 2021): 3129–43. http://dx.doi.org/10.1007/s11277-021-08171-2.

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AbstractIn this work, the author has evaluated the propagation of electromagnetic waves inside the human tissue such as blood, skin and fat for single-path and multi-path layers according to nano sensor transmit power calculations. In particular, the propagation characteristics of the Intra-Body Nano-Network communication channel are calculated using a theoretical approach. The analysis in this paper provides an evaluation related to the path loss, bit error rate, signal to noise ratio and the channel capacity. The model is evaluated for each single-path effect and multi-path effect. The effects of human tissue for each blood, skin and fat for single-path effect and multi-path are included in the analysis. The model frequency range is chosen from 0.01 to 1.5 THz frequencies, which are ideal for designing nano sensors antennae and using THz range for communication. This paper will also guide other researchers who are working on the electromagnetic radiation performance of Intra-Body Nano-Network and Nano sensors designed at the THz range.

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Sanusi, Muhammad Syahmi Bin Ahmad, S. A. A. Shukor, and Jalal Johari. "DEVELOPING AR INTERFACE FOR INTERIOR MODELLING FROM 3D SENSOR." Journal of Physics: Conference Series 2107, no. 1 (November 1, 2021): 012035. http://dx.doi.org/10.1088/1742-6596/2107/1/012035.

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Abstract This paper aims to show the process of Augmented Reality (AR) development representing existing building interior from a 3D sensor. These days, AR is becoming well known and widely used in various type of areas such as in gaming industry, medical training, and education. Due to its advantages, AR development for building interior is also necessity, specifically to assist people in understanding the scene more, in Architectural, Engineering, Construction / Facility Management (AEC/FM) applications as well as businesses like interior designing and household marketing. With respect to current situation of COVID-19 pandemic that has restricted travelling makes the usage of AR very beneficial and it could assist people to visualize the interior that needs to be visited. With the aid of suitable sensors like 3D sensor, the development of AR representing existing building interior which is usually full of clutter and occlusion could be eased.

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Bhardwaj, Renu, Neelesh Kumar, and Vipan Kumar. "Errors in micro-electro-mechanical systems inertial measurement and a review on present practices of error modelling." Transactions of the Institute of Measurement and Control 40, no. 9 (September 20, 2017): 2843–54. http://dx.doi.org/10.1177/0142331217708237.

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Micro-electro-mechanical systems (MEMS) technology-based accelerometers and gyroscopes are small size, mass produced, low cost inertial sensors, which are now being used in aerospace, underwater vehicles, automotive, robotics, mobiles, gaming consoles, prosthetic devices and many other applications. MEMS inertial sensors are available in many grades in market and selecting the appropriate grade sensor is very important. Owing to interaction of different types of energies, different noises are generated in MEMS devices; these noises cause significant change in output and the first section of this paper illustrates that. In application, where MEMS inertial sensors are used, the accuracy, repeatability and reproducibility of inertia measurement is probed primarily by complex testing, using extensive range of physical stimuli. Noises in inertial measurement are generally dealt by designing a unit measurement model. Noises are treated as additive error in linear unit model and are modelled using various techniques so that errors can be compensated to improve the accuracy. This paper reviews the theory, framework and methodology used in the error model of a MEMS inertial sensor and stochastic modelling of measurement. Experimental results from the most commonly used Allan variance techniques are discussed. Error modelling methodology, consisting of testing and calibration methods, designing thermal model, stochastic modelling and parameter estimation techniques, is illustrated. Figures and tables under each section summarize features, merits, limitation and future research scope. This paper should serve as a single reference for researchers and engineers working on application specific system design and instrumentation using MEMS inertial sensors. Conclusion from the study should help in selecting the appropriate grade of sensor as well as the best error modelling as per the trade-off existing between accuracy and development cost of error modelling.

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Miao, Shenghuan, Ling Chen, Rong Hu, and Yingsong Luo. "Towards a Dynamic Inter-Sensor Correlations Learning Framework for Multi-Sensor-Based Wearable Human Activity Recognition." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, no. 3 (September 6, 2022): 1–25. http://dx.doi.org/10.1145/3550331.

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Multi-sensor-based wearable human activity recognition (WHAR) is a research hotspot in the field of ubiquitous computing. Extracting effective features from multi-sensor data is essential to improve the performance of activity recognition. Despite the excellent achievements of previous works, the challenge remains for modelling the dynamic correlations between sensors. In this paper, we propose a lightweight yet efficient GCN-based dynamic inter-sensor correlations learning framework called DynamicWHAR for automatically learning the dynamic correlations between sensors. DynamicWHAR is mainly composed of two modules: Initial Feature Extraction and Dynamic Information Interaction. Firstly, Initial Feature Extraction module performs data-to-feature transformation to extract the initial features of each sensor. Subsequently, Dynamic Information Interaction module explicitly models the specific interaction intensity between any two sensors, and performs dynamic information aggregation between sensors by the learned interaction intensity. Extensive experiments on four diverse WHAR datasets and two different resource-constrained devices validate that DynamicWHAR outperforms the SOTA models in both recognition performance and computational complexity.

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Bruneo, D., A. Puliafito, and M. Scarpa. "Energy control in dependable wireless sensor networks: a modelling perspective." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 225, no. 4 (July 20, 2011): 424–34. http://dx.doi.org/10.1177/1748006x10397845.

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Wireless sensor networks (WSN) are composed of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, battery-operated sensors undergo cycles of sleeping–active periods that reduce their ability to send/receive data. Starting from the Markov reward model theory, this paper presents a dependability model to analyse the reliability of a sensor node. Also, a new dependability parameter is introduced, referred to as producibility, which is able to capture the capability of a sensor to accomplish its mission. Two different model solution techniques are proposed, one based on the evaluation of the accumulated reward distribution and the other based on an equivalent model based on non-Markovian stochastic Petri nets. The obtained results are used to investigate the dependability of a whole WSN taking into account the presence of redundant nodes. Topological aspects are taken into account, providing a quantitative comparison among three typical network topologies: star, tree, and mesh. Numerical results are provided in order to highlight the advantages of the proposed technique and to demonstrate the equivalence of the proposed approaches.

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Majewski, Jacek. "Low Humidity Characteristics of Polymer-Based Capacitive Humidity Sensors." Metrology and Measurement Systems 24, no. 4 (December 20, 2017): 607–16. http://dx.doi.org/10.1515/mms-2017-0048.

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AbstractPolymer-based capacitive humidity sensors emerged around 40 years ago; nevertheless, they currently constitute large part of sensors’ market within a range of medium (climatic and industrial) humidity 20−80%RH due to their linearity, stability and cost-effectiveness. However, for low humidity values (0−20%RH) that type of sensor exhibits increasingly nonlinear characteristics with decreasing of humidity values. This paper presents the results of some experimental trials of CMOS polymer-based capacitive humidity sensors, as well as of modelling the behaviour of that type of sensor. A logarithmic functional relationship between the relative humidity and the change of sensor output value at low humidity is suggested.

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Ostaszewska-Liżewska, Anna, Roman Szewczyk, Peter Raback, and Mika Malinen. "Modelling the Characteristics of Ring-Shaped Magnetoelastic Force Sensor in Mohri’s Configuration." Sensors 20, no. 1 (January 2, 2020): 266. http://dx.doi.org/10.3390/s20010266.

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Magnetoelastic force sensors exhibit high sensitivity and robustness. One commonly used configuration of force sensor with a ring-shaped core was presented by Mohri at al. In this configuration force is applied in the direction of a diameter of the core. However, due to inhomogeneous distribution of stresses, model of such sensor has not been presented yet. This paper is filling the gap presenting a new method of modelling the magnetoelastic effect, which is especially suitable for the finite element method. The presented implementation of proposed model is in good agreement with experimental data and creates new possibilities of modelling other devices utilizing magnetoelastic effect.

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Setiawan, Ari, Dina Angela, and Billy Irawan. "Modelling of Cutting Tool Condition Monitoring System (CTCMS) to support industry 4.0." MATEC Web of Conferences 204 (2018): 02012. http://dx.doi.org/10.1051/matecconf/201820402012.

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One of the value drivers in Industry 4.0 is asset utilization that has capability to remote monitoring and controlling the assets. Some of the problems on the production floor, especially in modern manufacturing areas such as machining process in the Flexible Manufacturing System (FMS), requires the condition of the cutting tools. This paper will discuss a model of cutting tools online monitoring system that operated in web based application. The model involves three sensors and a human machine interface to show the cutting tools condition. The sensors consist of temperature sensor, accelerometer, and electrical power consumption sensor; while in the experiment, the data of those sensors will be compared with the flank wear and crater wear on the cutting tools. The model shows that the data of temperatures, vibration and power consumption are collected by the sensors and sent by internet to the monitoring systems.

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Markowski, Piotr Marek, Mirosław Gierczak, and Andrzej Dziedzic. "Modelling of the Temperature Difference Sensors to Control the Temperature Distribution in Processor Heat Sink." Micromachines 10, no. 9 (August 23, 2019): 556. http://dx.doi.org/10.3390/mi10090556.

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This paper has three main purposes. The first is to investigate whether it is appropriate to use a planar thick-film thermoelectric sensor to monitor the temperature difference in a processor heat sink. The second is to compare the efficiency of two heat sink models. The third is to compare two kinds of sensors, differing in length. The model of the CPU heat sink sensor system was designed for numerical simulations. The relations between the CPU, heat sink, and the thermoelectric sensor were modelled because they are important for increasing the efficiency of fast processors without interfering with their internal structure. The heat sink was mounted on the top of the thermal model of a CPU (9.6 W). The plate fin and pin fin heat sinks were investigated. Two planar thermoelectric sensors were mounted parallel to the heat sink fins. These sensors monitored changes in the temperature difference between the CPU and the upper surface of the heat sink. The system was equipped with a cooling fan. Switching on the fan changed the thermal conditions (free or forced convection). The simulation results showed the temperature gradient appearing along the sensor for different heat sinks and under different thermal conditions. Comparison of the results obtained in the simulations of the CPU heat sink sensor systems proves that changes in the cooling conditions can cause a strong, step change in the response of the thermoelectric sensor. The results suggest that usage of the pin fin heat sink model is a better solution for free convection conditions. In the case of strong forced convection the heat sink type ceases to be significant.

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Dahiya, R., A. K. Arora, and V. R. Singh. "Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks." Journal of The Institution of Engineers (India): Series B 96, no. 3 (August 27, 2014): 305–9. http://dx.doi.org/10.1007/s40031-014-0149-1.

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Pachkawade, Vinayak. "A System-Level Modelling of Noise in Coupled Resonating MEMS Sensors." Engineering Proceedings 3, no. 1 (October 30, 2020): 5. http://dx.doi.org/10.3390/iec2020-06971.

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This paper presents realistic system-level modeling of effective noise sources in a coupled resonating mode-localized MEMS sensors. A governing set of differential equations are used to build a numerical model of a mechanical noise source in a coupled-resonator sensor and an effective thermo-mechanical noise is quantified through the simulation performed via SIMULINK. On a similar note, an effective noise that stems from the electronic readout used for the coupled resonating MEMS sensors is also quantified. Various noise sources in electronic readout are identified and the contribution of each is quantified. A comparison between an effective mechanical and electronic noise in a sensor system aids in identifying the dominant noise source in a sensor system. A method to optimize the system noise floor for an amplitude-based readout is presented. The proposed models present a variety of operating conditions, such as finite quality factor, varying coupled electrostatic spring strength, and operation with in-phase and out-of-phase mode. The proposed models aim to study the impact of fundamental noise processes that govern the ultimate resolution into a coupled resonating system used for various sensing applications.

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Kryszyn, Jacek, and Waldemar Smolik. "2D MODELLING OF A SENSOR FOR ELECTRICAL CAPACITANCE TOMOGRAPHY IN ECTSIM TOOLBOX." Informatics Control Measurement in Economy and Environment Protection 7, no. 1 (March 30, 2017): 0. http://dx.doi.org/10.5604/01.3001.0010.4604.

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Electrical capacitance tomography is used to visualize a spatial distribution of dielectrical permittivity of materials placed in a tomographic sensor. An image is reconstructed from measurements of mutual capacitances of electrodes placed around the examined volume. This technique is characterized by very high temporal resolution – it is possible to achieve even few thousands of images per second. One of drawbacks of the method is low spatial resolution. Electrical capacitance tomography is mainly used in industry, e.g. for multiphase flow visualization. One of important elements of a tomographic system is a sensor which parameters influence quality of measurements and therefore affects quality of reconstructed images. In the Division of Nuclear and Medical Electronics a Matlab toolbox called ECTsim was developed. It is used for modelling of sensors, simulations of electrical field and image reconstruction. In this article we present the latest improvement which is modelling of a sensor using algebra of sets. Using primitive elements like rectangle and sector of a ring it is possible to perform operations like union, intersection and difference of two elements with a designed language. With such tools it is easy to prepare complex models of tomographic sensors which have different geometries. In this paper we show two models of sensors with different geometry in order to show how ECTsim solves forward problem.

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Coillot, C., J. Moutoussamy, M. Boda, and P. Leroy. "New ferromagnetic core shapes for induction sensors." Journal of Sensors and Sensor Systems 3, no. 1 (January 15, 2014): 1–8. http://dx.doi.org/10.5194/jsss-3-1-2014.

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Abstract. Induction sensors are used in a wide range of scientific and industrial applications. One way to improve these is rigorous modelling of the sensor combined with a low voltage and current input noise preamplifier aiming to optimize the whole induction magnetometer. In this paper, we explore another way, which consists in the use of original ferromagnetic core shapes of induction sensors, which bring substantial improvements. These new configurations are the cubic, orthogonal and coiled-core induction sensors. For each of them we give modelling elements and discuss their benefits and drawbacks with respect to a given noise-equivalent magnetic induction goal. Our discussion is supported by experimental results for the cubic and orthogonal configurations, while the coiled-core configuration remains open to experimental validation. The transposition of these induction sensor configurations to other magnetic sensors (fluxgate and giant magneto-impedance) is an exciting prospect of this work.

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Vakhromov, Alexander, Alexander Vederniko, and Mikhail Skripachev. "Electromagnetic Sensor with Compensation Winding Modelling." Известия высших учебных заведений. Электромеханика, no. 6 (2016): 72–76. http://dx.doi.org/10.17213/0136-3360-2016-6-72-76.

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Tsiantos, Vasilios, Vasilios Karagiannis, Aphrodite Ktena, Christos Manasis, Onoufrios Ladoukakis, Charalambos Elias, Evangelos Hristoforou, and Polyxeni Vourna. "Modelling of a Magnetostrictive Torque Sensor." MATEC Web of Conferences 41 (2016): 01003. http://dx.doi.org/10.1051/matecconf/20164101003.

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Granstedt, F., M. Folke, M. Ekström, B. Hök, and Y. Bäcklund. "Modelling of an electroacoustic gas sensor." Sensors and Actuators B: Chemical 104, no. 2 (January 2005): 308–11. http://dx.doi.org/10.1016/j.snb.2004.05.026.

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Rombach, Pirmin, and Werner Langheinrich. "Modelling of a micromachined torque sensor." Sensors and Actuators A: Physical 46, no. 1-3 (January 1995): 294–97. http://dx.doi.org/10.1016/0924-4247(94)00908-z.

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Pham, D. T., and K. Hafeez. "Dynamic modelling of a robot sensor." Mathematical and Computer Modelling 14 (1990): 456–62. http://dx.doi.org/10.1016/0895-7177(90)90226-d.

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Rodríguez, Dilia E. "On Modelling Sensor Networks in Maude." Electronic Notes in Theoretical Computer Science 176, no. 4 (July 2007): 199–213. http://dx.doi.org/10.1016/j.entcs.2007.06.016.

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Mu, He-Qing, Han-Teng Liu, and Ji-Hui Shen. "Copula-Based Uncertainty Quantification (Copula-UQ) for Multi-Sensor Data in Structural Health Monitoring." Sensors 20, no. 19 (October 6, 2020): 5692. http://dx.doi.org/10.3390/s20195692.

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The problem of uncertainty quantification (UQ) for multi-sensor data is one of the main concerns in structural health monitoring (SHM). One important task is multivariate joint probability density function (PDF) modelling. Copula-based statistical inference has attracted significant attention due to the fact that it decouples inferences on the univariate marginal PDF of each random variable and the statistical dependence structure (called copula) among the random variables. This paper proposes the Copula-UQ, composing multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, for multi-sensor data measured from a SHM system. Multivariate joint PDF is modeled based on the univariate marginal PDFs and the copula. Inference is made by combing the idea of the inference functions for margins and the maximum likelihood estimate. Prediction on the PDF of the target variable, using the complete (from normal sensors) or incomplete information (due to missing data caused by sensor fault issue) of the predictor variable, are made based on the multivariate joint PDF. One example using simulated data and one example using temperature data of a multi-sensor of a monitored bridge are presented to illustrate the capability of the Copula-UQ in joint PDF modelling and target variable prediction.

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S., Jayasri B., and G. Raghavendra Rao. "Analytical Modelling of Power Efficient Reliable Operation of Data Fusion in Wireless Sensor Network." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4637. http://dx.doi.org/10.11591/ijece.v8i6.pp4637-4645.

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Irrespective of inclusion of Wireless Sensor Network (WSN) in majority of the research proposition for smart city planning, it is still shrouded with some significant issues. A closer look into problems in WSN shows that energy parameter is the origination point of majority of the other problems in resource-constrained sensors as well as it significant minimizes the reliability in standard sensory operation in adverse environment. Therefore, this manuscript presents a novel analytical model that is meant for establishing a well balance between energy efficiency over multi-path data forwarding and reliable operation with improved network performance. The complete process is emphasized during data fusion stage to ensure data quality too. A simulation study has been carried out using benchmarked test-bed of MEMSIC nodes to find that proposed system offers good energy conservation process during data fusion operation as well as it also ensure good reliable operation in comparison to existing system.

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Ripka, Pavel, Vaclav Grim, Mehran Mirzaei, Diana Hrakova, Janis Uhrig, Florian Emmerich, Christiane Thielemann, Jiri Hejtmanek, Ondrej Kaman, and Roman Tesar. "Modelling and Measurement of Magnetically Soft Nanowire Arrays for Sensor Applications." Sensors 21, no. 1 (December 22, 2020): 3. http://dx.doi.org/10.3390/s21010003.

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Soft magnetic wires and microwires are currently used for the cores of magnetic sensors. Due to their low demagnetization, they contribute to the high sensitivity and the high spatial resolution of fluxgates, Giant Magnetoimpedance (GMI), and inductive sensors. The arrays of nanowires can be prepared by electrodeposition into predefined pores of a nanoporous polycarbonate membrane. While high coercivity arrays with square loops are convenient for information storage and for bistable sensors such as proximity switches, low coercivity cores are needed for linear sensors. We show that coercivity can be controlled by the geometry of the array: increasing the diameter of nanowires (20 µm in length) from 30 nm to 200 nm reduced the coercivity by a factor of 10, while the corresponding decrease in the apparent permeability was only 5-fold. Finite element simulation of nanowire arrays is important for sensor development, but it is computationally demanding. While an array of 2000 wires can be still modelled in 3D, this is impossible for real arrays containing millions of wires. We have developed an equivalent 2D model, which allows us to solve these large arrays with acceptable accuracy. Using this tool, we have shown that as a core of magnetic sensors, nanowires are efficiently employed only together with microcoils with diameter comparable to the nanowire length.

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Meister, Sebastian, Lars Grundhöfer, Jan Stüve, and Roger M. Groves. "Imaging sensor data modelling and evaluation based on optical composite characteristics." International Journal of Advanced Manufacturing Technology 116, no. 11-12 (July 25, 2021): 3965–90. http://dx.doi.org/10.1007/s00170-021-07591-5.

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AbstractAutomated Fibre Placement is a common manufacturing technique for composite parts in the aero-space industry. Therefore, a visual part inspection is required which often covers up to 50% of the actual production time. Moreover, the inspection quality of this manual step fluctuates significantly. A camera-based automated inline inspection is capable of increasing the inspection efficiency and accuracy. However, the interpretability of the acquired data strongly depends on the sensor configuration and the inspected material. Thus, this paper introduces methods for modelling and assessing an imaging sensor on the example of a composite material reflecting a spot laser to a camera sensor. In this context, the reflection properties of the material are incorporated into a simulation and validated in comparison to real camera images from the experimental setup. The EMVA 1288 sensor model in combination with the Cramér–Rao lower bound indicates a feasible estimability of the beam propagation, but shows limitations in the predictability of the number of incident photons. The laser spot analysis indicated that the laser spot can deviate from an exact oval shape but its peak value is suitable for robust spot identification in an image. The outlined methodology is also adaptable to other imaging sensors, illumination sources and materials. Thus, the findings can be useful for other fields and manufacturing processes.

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Antunes, Alex. "Cheap Deployable Networked Sensors for Environmental Use." Journal of Telecommunications and the Digital Economy 2, no. 4 (May 26, 2020): 15. http://dx.doi.org/10.18080/jtde.v2n4.271.

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We profile the utility and limits in deployment of inexpensive disposable sensor networks by amateurs to achieve environmental monitoring goals. Four current technology movements — PC-on-a-chip processors such as Arduino, prebuilt sensors, 3-D printing, and Wi-Fi and mesh networking — enable rapid sensor platform creation and make it easy for non-specialists to create general sensor-bearing platforms. Deployment of a cluster of multiple sensor-bearing platforms is, however, communications-limited in terms of both range and number of devices supported, and generally requires a base station with internet access. We examine how inexpensive technology supports scenarios for short-term environmental modelling by average citizens.

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Medina-Bailon, Cristina, Naveen Kumar, Rakshita Pritam Singh Dhar, Ilina Todorova, Damien Lenoble, Vihar P. Georgiev, and César Pascual García. "Comprehensive Analytical Modelling of an Absolute pH Sensor." Sensors 21, no. 15 (July 30, 2021): 5190. http://dx.doi.org/10.3390/s21155190.

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In this work, we present a comprehensive analytical model and results for an absolute pH sensor. Our work aims to address critical scientific issues such as: (1) the impact of the oxide degradation (sensing interface deterioration) on the sensor’s performance and (2) how to achieve a measurement of the absolute ion activity. The methods described here are based on analytical equations which we have derived and implemented in MATLAB code to execute the numerical experiments. The main results of our work show that the depletion width of the sensors is strongly influenced by the pH and the variations of the same depletion width as a function of the pH is significantly smaller for hafnium dioxide in comparison to silicon dioxide. We propose a method to determine the absolute pH using a dual capacitance system, which can be mapped to unequivocally determine the acidity. We compare the impact of degradation in two materials: SiO2 and HfO2, and we illustrate the acidity determination with the functioning of a dual device with SiO2.

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Kowalska, Aleksandra, Robert Banasiak, Andrzej Romanowski, and Dominik Sankowski. "A study of the possibility of using 3D modelling and 3D printing for electrical capacitance tomography sensor." Acta Innovations, no. 31 (April 1, 2019): 23–32. http://dx.doi.org/10.32933/actainnovations.31.3.

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Nowadays, the optimization of energy consumption and resources is one of the most urgent topics in worldwide industry. The energy consumption monitoring and control in various multiphase flow industrial applications, where a proper flow characteristic and an optimal phase mixture control is crucial, is hard to perform due to the physical and chemical complexity of the processes. The Electrical Capacitance Tomography (ECT) is one of the relatively cheap non-invasive measurement methods that can help in the monitoring and control of optimal energy and resources dozing in industrial processes. ECT diagnostics systems use unique sensors that can non-intrusively detect spatial capacitance changes caused by spatial changes in the electrical permittivity of industrial process components. One of the latest ECT extensions is a three-dimensional measurement strategy that uses a multilayer structure of the capacitance sensor. In this paper, the authors propose a novel approach to the 3D ECT sensors fabrication process that uses 3D computer modelling and 3D printing to easily get any sensor shape, electrode layout, scale and shielding strategy. This study compares the measurement abilities of a 3D ECT sensor fabricated using a traditional hand-made technique with the 3D printed device. The results have proven the potential of the new 3D print-based sensor regarding its significant fabrication time reduction as well as the improvement of the overall 3D ECT sensor measurement accuracy and stability.

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Kubba, Ali E., Ahmed Hasson, Ammar I. Kubba, and Gregory Hall. "A micro-capacitive pressure sensor design and modelling." Journal of Sensors and Sensor Systems 5, no. 1 (March 30, 2016): 95–112. http://dx.doi.org/10.5194/jsss-5-95-2016.

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Abstract. Measuring air pressure using a capacitive pressure sensor is a robust and precise technique. In addition, a system that employs such transducers lies within the low power consumption applications such as wireless sensor nodes. In this article a high sensitivity with an elliptical diaphragm capacitive pressure sensor is proposed. This design was compared with a circular diaphragm in terms of thermal stresses and pressure and temperature sensitivity. The proposed sensor is targeted for tyre pressure monitoring system application. Altering the overlapping area between the capacitor plates by decreasing the effective capacitance area to improve the overall sensitivity of the sensor (ΔC ∕ C), temperature sensitivity, and built-up stresses is also examined in this article. Theoretical analysis and finite element analysis (FEA) were employed to study pressure and temperature effects on the behaviour of the proposed capacitive pressure sensor. A MEMS (micro electro-mechanical systems) manufacturing processing plan for the proposed capacitive sensor is presented. An extra-low power short-range wireless read-out circuit suited for energy harvesting purposes is presented in this article. The developed read-out circuitry was tested in terms of sensitivity and transmission range.

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Yu, Haiqing, Jun Ji, Ping Li, Fengjing Shao, Shunyao Wu, Yi Sui, Shujing Li, Fengjiao He, and Jinming Liu. "Semi-Supervised Hybrid Local Kernel Regression for Soft Sensor Modelling of Rubber-Mixing Process." Advances in Polymer Technology 2020 (January 31, 2020): 1–8. http://dx.doi.org/10.1155/2020/6981302.

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Soft sensor techniques have been widely adopted in chemical industry to estimate important indices that cannot be online measured by hardware sensors. Unfortunately, due to the instinct time-variation, the small-sample condition and the uncertainty caused by the drifting of raw materials, it is exceedingly difficult to model the fed-batch processes, for instance, rubber internal mixing processing. Meanwhile, traditional global learning algorithms suffer from the outdated samples while online learning algorithms lack practicality since too many labelled samples of current batch are required to build the soft sensor. In this paper, semi-supervised hybrid local kernel regression (SHLKR) is presented to leverage both historical and online samples to semi-supervised model the soft sensor using proposed time-windows series. Moreover, the recursive formulas are deduced to improve its adaptability and feasibility. Additionally, the rubber Mooney soft sensor of internal mixing processing is implemented using real onsite data to validate proposed method. Compared with classical algorithms, the performance of SHLKR is evaluated and the contribution of unlabelled samples is discussed.

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Boroujerdi, Ramin, and Richard Paul. "Introducing Graphene–Indium Oxide Electrochemical Sensor for Detecting Ethanol in Aqueous Samples with CCD-RSM Optimization." Chemosensors 10, no. 2 (January 24, 2022): 42. http://dx.doi.org/10.3390/chemosensors10020042.

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There is significant demand for portable sensors that can deliver selective and sensitive measurement of ethanol on-site. Such sensors have application across many industries, including clinical and forensic work as well as agricultural and environmental analysis. Here, we report a new graphene–indium oxide electrochemical sensor for the determination of ethanol in aqueous samples. Graphene layers were functionalised by anchoring In2O3 to its surface and the developed composite was used as a selective electrochemical sensor for sensing ethanol through cyclic voltammetry. The detection limit of the sensor was 0.068 mol/L and it showed a linear response to increasing ethanol in the environment up to 1.2 mol/L. The most significant parameters involved and their interactions in the response of the sensor and optimization procedures were studied using a four-factor central composite design (CCD) combined with response surface modelling (RSM). The sensor was applied in the detection of ethanol in authentic samples.

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Hameed, Ashwaq Q., and Majd N. Abass. "Design and Modelling of Wireless Sensor System." IARJSET 4, no. 2 (February 20, 2017): 76–80. http://dx.doi.org/10.17148/iarjset.2017.4216.

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Ya Lvovich, I., Ya E. Lvovich, A. P. Preobrazhenskiy, Yu P. Preobrazhenskiy, and O. N. Choporov. "Modelling and optimizing sensor wireless network systems." Journal of Physics: Conference Series 1889, no. 2 (April 1, 2021): 022080. http://dx.doi.org/10.1088/1742-6596/1889/2/022080.

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Gerasimov, S. I., and T. V. Sych. "Finite element modelling of acoustic emission sensor." Journal of Physics: Conference Series 881 (August 2017): 012003. http://dx.doi.org/10.1088/1742-6596/881/1/012003.

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Bokov, Vladimir B. "Multivariate hybrid modelling of air-gauge sensor." Measurement Science and Technology 17, no. 6 (May 8, 2006): 1537–46. http://dx.doi.org/10.1088/0957-0233/17/6/035.

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Boukhris, Anass, Stéphane Giuliani, and Gilles Mourot. "Rainfall-Runoff Modelling for Sensor Fault Diagnosis." IFAC Proceedings Volumes 30, no. 18 (August 1997): 1131–36. http://dx.doi.org/10.1016/s1474-6670(17)42548-1.

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Paton, M. D., G. Kargl, A. J. Ball, S. F. Green, A. Hagermann, N. I. Kömle, M. Thiel, and J. C. Zarnecki. "Computer modelling of a penetrator thermal sensor." Advances in Space Research 46, no. 3 (August 2010): 337–45. http://dx.doi.org/10.1016/j.asr.2010.03.007.

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Kutiš, Vladimír, Jaroslav Dzuba, Juraj Paulech, Justín Murín, and Tibor Lalinský. "MEMS Piezoelectric Pressure Sensor-modelling and Simulation." Procedia Engineering 48 (2012): 338–45. http://dx.doi.org/10.1016/j.proeng.2012.09.523.

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Omara, Fatma A., Abdelmageid A. Ali, Noha M. M. AbdElnapi, and Nahla F. Omran. "Modelling a smart non-invasive adrenaline sensor." International Journal of Sensor Networks 32, no. 2 (2020): 96. http://dx.doi.org/10.1504/ijsnet.2020.10026656.

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AbdElnapi, Noha M. M., Nahla F. Omran, Abdelmageid A. Ali, and Fatma A. Omara. "Modelling a smart non-invasive adrenaline sensor." International Journal of Sensor Networks 32, no. 2 (2020): 96. http://dx.doi.org/10.1504/ijsnet.2020.104926.

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Dedecius, K., and V. Sečkárová. "Centralized Bayesian reliability modelling with sensor networks." Mathematical and Computer Modelling of Dynamical Systems 19, no. 5 (October 2013): 471–82. http://dx.doi.org/10.1080/13873954.2013.789064.

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Journal articles on the topic 'Sensor modelling'

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