Journal articles: 'Vibration filtering'

1

Feltane, S., S. Yahyaoui, A. Hafsaoui, and A. Boussaid. "Signal processing application for vibration generated by blasting in tunnels." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 5 (2020): 54–60. http://dx.doi.org/10.33271/nvngu/2021-5/054.

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Purpose. To study the vibrations waves generated by blasting in a tunnel using the signal processing tools. Methodology. Field tests are carried out to measure vibration wave during blasting operations at different locations in the tunnel and its immediate environment. Results of the measurements are processed by the autocorrelation method, which consists of filtering based on signal shape recognition. A comparison is accomplished between the peak particle velocities (PPV) measured and those obtained after filtering. Findings. The results obtained after filtering gave a significant reduction in PPV of the measured vibration amplitudes in comparison to those obtained after treatment for the three components: longitudinal, transversal and vertical ones. Good knowledge of vibration source is important for amplitude attenuation regarding the observed difference between the recorded seismogram during explosion of a single unit charge and other standard explosions. Originality. The work introduces signal processing methods for filtering vibration signals related to blasting, which is insufficiently studied. Practical value. This study shows that the treatment of blasting vibrations by a filtering method should reduce the peak velocity of the particles by separating the signals and eliminating the interference in the initial signal.

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Mortimer, B. "A Spider’s Vibration Landscape: Adaptations to Promote Vibrational Information Transfer in Orb Webs." Integrative and Comparative Biology 59, no. 6 (May 20, 2019): 1636–45. http://dx.doi.org/10.1093/icb/icz043.

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Abstract Spider orb webs are used not only for catching prey, but also for transmitting vibrational information to the spider. Vibrational information propagates from biological sources, such as potential prey or mates, but also abiotic sources, such as wind. Like other animals, the spider must cope with physical constraints acting on the propagation of vibrational information along surfaces and through materials—including loss of energy, distortion, and filtering. The spider mitigates these physical constraints by making its orb web from up to five different types of silks, closely controlling silk use and properties during web building. In particular, control of web geometry, silk tension, and silk stiffness allows spiders to adjust how vibrations spread throughout the web, as well as their amplitude and speed of propagation, which directly influences energy loss, distortion, and filtering. Turning to how spiders use this information, spiders use lyriform organs distributed across their eight legs as vibration sensors. Spiders can adjust coupling to the silk fibers and use posture to modify vibrational information as it moves from the web to the sensors. Spiders do not sense all vibrations equally—they are least sensitive to low frequencies (<30 Hz) and most sensitive to high frequencies (ca. 1 kHz). This sensitivity pattern cannot be explained purely by the frequency range of biological inputs. The role of physical and evolutionary constraints is discussed to explain spider vibration sensitivity and a role of vibration sensors to detect objects on the web as a form of echolocation is also discussed.

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Wu, Junjie, Yufei Sun, Peng Guo, Lihui Feng, Yongbin Zhang, and Youqi Zhang. "Effect of Resonance Interference on MEMS Gyroscopes and Filtering Algorithm Elimination." Journal of Physics: Conference Series 2224, no. 1 (April 1, 2022): 012128. http://dx.doi.org/10.1088/1742-6596/2224/1/012128.

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Abstract The mechanical structure of MEMS gyroscope is a spring-mass-damper system, which is susceptible to interference near the resonant frequency. This work compared the interference effects of mechanical vibrations and high frequency sound waves on MEMS gyroscopes. Three MEMS gyroscopes ADXRS620 were interfered by vibrations and sound waves near the resonant frequency. The error outputs increased linearly with the increase of interference intensity. The maximum error output could reach 88.95 °/s, which seriously affect the normal operation of the gyroscope. The waveforms of gyroscope outputs under acoustic and vibration interference were almost coincident, which showed the similarity of acoustic and vibration interference. However, to produce the same effect on gyroscopes, the power required of vibration interference was much less than that of acoustic interference. Taking one of the gyroscopes for example, when the SPL of acoustic interference was up to 90 dB, the maximum error was only 3.37 °/s. But when the acceleration amplitude of vibration interference reached 0.050 g, the maximum error was 3.42 °/s. In addition, the effectiveness against vibration interference of the filtering algorithm based on orthogonal demodulation was verified by testing the self-developed gyroscope. Vibration interference could be reduced by 98.88% at most.

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Lin, Yun, Linghan Zhang, Hongwei Han, Yang Li, Wenjie Shen, and Yanping Wang. "Periodic-Filtering Method for Low-SNR Vibration Radar Signal." Remote Sensing 15, no. 14 (July 8, 2023): 3461. http://dx.doi.org/10.3390/rs15143461.

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Radar is a non-contact, high-precision vibration measurement device and an important tool for bridge vibration monitoring. Vibration information needs to be extracted from the radar phase, but the radar phase information is sensitive to noise. Under low signal-to-noise ratio (SNR) data acquisition conditions, such as low radar transmission power or a long observation distance, differential phase jump errors occur and clutter estimation becomes difficult, which leads to inaccurate inversion of vibration deformation. Traditional low-pass filtering methods can filter out noise to improve SNR, but they require oversampling. The sampling rate needs to be several times higher than the Doppler bandwidth, which is several times higher than the vibration frequency. This puts high data acquisition requirements on radar systems and causes large data volumes. Therefore, this paper proposes a novel vibration signal filtering method called the periodic filtering method. The method uses the periodicity feature of vibration signals for filtering without oversampling. This paper derives the time-domain and frequency-domain expressions for the periodic filter and presents a deformation inversion process based on them. The process involves extracting the vibration frequency in the Doppler domain, suppressing noise through periodic filtering, estimating clutter using circle fitting on the data complex plane, and inverting final deformation with differential phase. The method is verified through simulation experiments, calibration experiments, and bridge vibration experiments. The results show that the new periodic filtering method can improve the SNR by five times, resolve differential phase jumps, and accurately estimate clutter, thus getting submillimeter-level vibration deformation at low SNR.

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Huang, Xili, Cheng Zhang, Hongchen Pang, Zhiqiang Zhao, Qianxi Zhang, Xiaoning Li, Xianzhang Wang, Fang Lin, Bo Li, and Xinxiang Pan. "Ultra−Wide Range Vibration Frequency Detection Sensors Based on Elastic Steel Triboelectric Nanogenerators for Intelligent Machinery Monitoring." Nanomaterials 12, no. 16 (August 14, 2022): 2790. http://dx.doi.org/10.3390/nano12162790.

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Vibration measurement and analysis play an important role in diagnosing mechanical faults, but existing vibration sensors are limited by issues such as dependence on external power sources and high costs. To overcome these challenges, the use of triboelectric nanogenerator (TENG)−based vibration sensors has recently attracted attention. These vibration sensors measure a small range of vibration frequencies and are not suitable for measuring high-frequency vibrations. Herein, a self-powered vibration sensor based on an elastic steel triboelectric nanogenerator (ES−TENG) is proposed. By optimizing the elastic steel sheet structure and combining time-frequency transformation and filtering processing methods, the measurement of medium- and high-frequency vibrations is achieved. These results demonstrate that the ES−TENG can perform vibration measurements in the range of 2–10,000 Hz, with a small average error (~0.42%) between the measured frequency and external vibration frequency values. Therefore, the ES−TENG can be used as a self-powered, highly-accurate vibration sensor for intelligent machinery monitoring.

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HISATANI, Masujiro. "Adaptive Filtering for Unbalance Vibration Suppression." Transactions of the Japan Society of Mechanical Engineers Series C 62, no. 597 (1996): 1706–11. http://dx.doi.org/10.1299/kikaic.62.1706.

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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (January 10, 2021): 144. http://dx.doi.org/10.3390/w13020144.

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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.

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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (January 10, 2021): 144. http://dx.doi.org/10.3390/w13020144.

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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.

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Liu, Ning, and Thomas Schumacher. "Improved Denoising of Structural Vibration Data Employing Bilateral Filtering." Sensors 20, no. 5 (March 5, 2020): 1423. http://dx.doi.org/10.3390/s20051423.

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With the continuous advancement of data acquisition and signal processing, sensors, and wireless communication, copious research work has been done using vibration response signals for structural damage detection. However, in actual projects, vibration signals are often subject to noise interference during acquisition and transmission, thereby reducing the accuracy of damage identification. In order to effectively remove the noise interference, bilateral filtering, a filtering method commonly used in the field of image processing for improving data signal-to-noise ratio was introduced. Based on the Gaussian filter, the method constructs a bilateral filtering kernel function by multiplying the spatial proximity Gaussian kernel function and the numerical similarity Gaussian kernel function and replaces the current data with the data obtained by weighting the neighborhood data, thereby implementing filtering. By processing the simulated data and experimental data, introducing a time-frequency analysis method and a method for calculating the time-frequency spectrum energy, the denoising abilities of median filtering, wavelet denoising and bilateral filtering were compared. The results show that the bilateral filtering method can better preserve the details of the effective signal while suppressing the noise interference and effectively improve the data quality for structural damage detection. The effectiveness and feasibility of the bilateral filtering method applied to the noise suppression of vibration signals is verified.

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Hornik, Beata, Jan Duława, Czesław Marcisz, Wojciech Korchut, and Jacek Durmała. "The Effect of Mechanically-Generated Vibrations on the Efficacy of Hemodialysis; Assessment of Patients’ Safety: Preliminary Reports." International Journal of Environmental Research and Public Health 16, no. 4 (February 18, 2019): 594. http://dx.doi.org/10.3390/ijerph16040594.

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Muscle activity during a hemodialysis procedure improves its efficacy. We have formulated a hypothesis that vibrations generated by a specially-designed dialysis chair can, the same as physical exercise, affect the filtering of various fluids between fluid spaces during the hemodialysis procedure. This prospective and interventional study included 21 dialyzed patients. During a single dialysis session, each patient used a prototype device with the working name “vibrating chair”. The chair’s drive used a low-power cage induction motor, which, along with the worm gear motor, was a part of the low-frequency (3.14 Hz) vibration-generating assembly with an amplitude of 4 mm. Tests and measurements were performed before and after the vibration dialysis. After a single hemodialysis session including five 3-min cycles of vibrations, an increase in K t / V in relation to non-vibration K t / V ( 1.53 ± 0.26 vs. 1.62 ± 0.23 ) was seen. Urea reduction ratio increased significantly ( 0.73 ± 0.03 vs. 0.75 ± 0.03 ). A significant increase in systolic blood pressure was observed between the first and the third measurement ( 146 ± 18 vs. 156 ± 24 ). The use of a chair generating low-frequency vibrations increased dialysis adequacy; furthermore, it seems an acceptable and safe alternative to intradialytic exercise.

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Li, Juan, Yuan Hong Yang, and Shao Hua Jiao. "A Novel Real-Time Algorithm for Torsional Vibration Mode of Generator Sets Based on Rotation IIR Filter." Applied Mechanics and Materials 215-216 (November 2012): 1253–58. http://dx.doi.org/10.4028/www.scientific.net/amm.215-216.1253.

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The shafting torsional vibration mode of generator sets reflects dynamic process of the power grid. This paper proposes a novel real-time algorithm for shafting torsional vibration mode decomposition of generator sets, which has excellent time-frequency resolution. The algorithm realizes the signal frequency resolution filtering based on classic infinite impulse response (IIR) filtering. At the same time, the inertia of the narrow-band filtering algorithm is eliminated through multi-period rotation IIR filtering and the time-frequency dynamic resolution of the modal decomposition is realized. PSCAD-based simulation verifies that the algorithm has the frequency anti-aliasing performance, and can fully reserve the time-frequency variation characteristics and can realize the multi-mode real-time decomposition of the torsional vibration perfectly. The algorithm can also be used for the time-frequency analysis in other fields.

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Qin, Chiyue, Rana Gill, Ravi Tomar, and Kayhan Zrar Ghafoor. "Vibration signal collection and analysis of mechanical equipment failure based on computer simulation detection." Nonlinear Engineering 11, no. 1 (January 1, 2022): 387–94. http://dx.doi.org/10.1515/nleng-2022-0040.

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Abstract This article addresses the challenge of large error rate and low accuracy of the vibration signal collection of mechanical equipment failure, and proposes a mechanical equipment failure vibration signal collection and analysis based on computer simulation detection. Then, it uses the Kalman filter algorithm for data filtering, according to the mathematical model established by the system, thus choosing a suitable noise covariance calculation method. In the integration process after filtering, using a piecewise integration method between acceleration peaks, the integration calculation is optimized to obtain the vibration displacement. The simulation results of this article show the vibration data collected by the main controller, after Kalman filtering and piecewise trapezoidal integration method optimization. The error of the proposed method is 0.5% when the frequency is 80 Hz, relative to the displacement measurement method of the three-axis acceleration sensor at 8.3%, and the error of data calculation results is greatly reduced. The greater the amplitude of vibration, the smaller the error. This method significantly improves the accuracy of vibration signal collection of mechanical equipment.

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Wang, Yonggang, Vishal Jagota, Mamookho Elizabeth Makhatha, and Pawan Kumar. "Vibration signal acquisition and computer simulation detection of mechanical equipment failure." Nonlinear Engineering 11, no. 1 (January 1, 2022): 207–14. http://dx.doi.org/10.1515/nleng-2022-0026.

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Abstract The author in order to solve the problem of optimizing the accuracy of mechanical equipment failure detection proposes a vibration signal collection and computer simulation detection for mechanical equipment failure. Using wavelet domain Wiener filtering-based mechanical equipment fault detection method, the author first combined Wiener filtering and wavelet threshold filtering, established a vibration signal collection model for mechanical equipment, obtained the true signal and the filtered signal error and fusion of the principle of wavelet threshold filtering to perform orthogonal wavelet transform on noisy signals, and through the principle of fast independent component analysis to separate the vibration signals of mechanical equipment, build the initial separation matrix of the signal with unit variance, and found the estimated value of the source signal; the collection of vibration signals of mechanical equipment is completed according to the estimated value, realizing the optimization of the detection of mechanical faults and equipment failures. The simulation results prove that the signal-to-noise ratio of the vibration signal of mechanical equipment collected by this method is higher than 15.7% of the signal-to-noise ratio based on the FastICA method; this is mainly because when this method is used for anti-interference collection of vibration signals of mechanical equipment, combining the principle of fast independent component analysis to separate the vibration signals of mechanical equipment, construct the initial separation matrix of the signal with unit variance. Using the proposed method for signal acquisition can greatly reduce the error, and it can provide effective support for fault detection of mechanical equipment.

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А. Передерко. "THE USE OF A WAVELET TRANSFORMATION FOR REMOVAL OF THE NOISE COMPONENT FROM THE VIBRO SIGNAL." Перспективні технології та прилади, no. 18 (July 7, 2021): 106–11. http://dx.doi.org/10.36910/6775-2313-5352-2021-18-16.

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The article investigates the use of wavelets to remove noise from the measuring vibration signal. It is determined that wavelets are well adapted for signal analysis, for which the principle of causality is important: wavelets preserve the direction of time and do not create parasitic interference between the past and the future. Criteria for selecting an analytical wavelet have been developed, depending on what information should be extracted from the signal and the need to more fully identify and emphasize certain properties of the analyzed signal. It is proposed to use Daubechies wavelets to process the vibration signal data. The simulation of vibration signal filtering from noise with the normal distribution law is performed in the MATCAD package. It is proved that the method of wavelet transform allows to solve the problem of filtering the vibration signal from noise when processing vibration signals obtained by autonomous recording devices in conditions of increased interference from the environment. The obtained results evidence to the prospects of the developed method and its advantages in comparison with the hardware solution of the filtering problem.

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Niu, Dapeng, and Jiaqi Wang. "Elevator Car Vibration Signal Denoising Method Based on CEEMD and Bilateral Filtering." Sensors 22, no. 17 (September 1, 2022): 6602. http://dx.doi.org/10.3390/s22176602.

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Elevator car vibration signals are important information to monitor and diagnose the operating status of elevators, but during the process of vibration signals acquisition, vibration signals are always inevitably disturbed by noise, which affects further research. Therefore, aiming at the vibration signal with noise, we propose a new vibration signal denoising method on the basis of complementary ensemble empirical mode decomposition (CEEMD) and bilateral filtering. Firstly, the collected original vibration signals are decomposed by the CEEMD into several inherent mode functions. Then, the false components are removed by determining the correlation coefficients of mode components, and then the noise-dominate components are denoised by bilateral filtering. Finally, the processed inherent mode functions are reconstructed to require the denoised signal. We test the method through simulation and practical application. The results indicate that the proposed method can efficaciously reduce the noise in the vibration signal of an elevator car.

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Ford, DG, A. Myers, F. Haase, S. Lockwood, and A. Longstaff. "Active vibration control for a CNC milling machine." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 2 (April 4, 2013): 230–45. http://dx.doi.org/10.1177/0954406213484224.

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There is a requirement for improved three-dimensional surface characterisation and reduced tool wear when modern computer numerical control (CNC) machine tools are operating at high cutting velocities, spindle speeds and feed rates. For large depths of cut and large material removal rates, there is a tendency for machines to chatter caused by self-excited vibration in the machine tools leading to precision errors, poor surface finish quality, tool wear and possible machine damage. This study illustrates a method for improving machine tool performance by understanding and adaptively controlling the machine structural vibration. The first step taken is to measure and interpret machine tool vibration and produce a structural model. As a consequence, appropriate sensors need to be selected and/or designed and then integrated to measure all self-excited vibrations. The vibrations of the machine under investigation need to be clearly understood by analysis of sensor signals and surface finish measurement. The active vibration control system has been implemented on a CNC machine tool and validated under controlled conditions by compensating for machine tool vibrations on time-varying multi-point cutting operations for a vertical milling machine. The design of the adaptive control system using modelling, filtering, active vibration platform and sensor feedback techniques has been demonstrated to be successful.

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Liska, J., J. Jakl, and S. Kunkel. "Advanced turbine generator torsional vibration evaluation method using Kalman filtering." Insight - Non-Destructive Testing and Condition Monitoring 64, no. 8 (August 1, 2022): 437–41. http://dx.doi.org/10.1784/insi.2022.64.8.437.

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Turbine generator torsional vibration is becoming a major concern in modern power grids with a high level of changeability due to the operation of renewable energy sources. The traditional absence of standard torsional vibration monitoring and a lack of experience with the operation of torsional vibration monitoring systems opens up a wide range of opportunities for the design of torsional vibration monitoring systems and the possibility of their installation in power plants. As the measured signals are adversely affected by noise, proper filtering is essential for capturing the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility of tackling two different types of noise: the state noise and the measurement noise. The feasibility of the proposed method is demonstrated by case studies based on practical signals measured on steam turbine generators.

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An, Xueli, Weiwei Yang, and Xuemin An. "Vibration signal analysis of a hydropower unit based on adaptive local iterative filtering." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 7 (August 9, 2016): 1339–53. http://dx.doi.org/10.1177/0954406216656020.

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The vibration signals coming from a hydropower unit have strong nonstationary characteristics when strong vortex develops in the hydraulic turbine draft tube. Related to this problem, a new vibration analysis method for a hydropower unit based on adaptive local iterative filtering is proposed. Firstly, adaptive local iterative filtering was used to decompose the complex vibration signal into several intrinsic mode functions. Then, frequency spectrum analysis of these components was performed to obtain the vortex characteristic frequency from the vibration signal. Simulated and real-world signals were used to verify the proposed method. The obtained results show that this method can overcome the problem of mode mixing in the existing empirical mode decomposition method, since it improves the efficiency and accuracy of feature extraction for nonstationary vibration signals from a hydropower unit.

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Chen, Zhi Gang, Xiao Jiao Lian, and Ming Zhou. "Research on Fault Diagnosis for Petrochemical Running Equipments Based on ICA." Applied Mechanics and Materials 48-49 (February 2011): 950–53. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.950.

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For solving the difficulty of feature signal extraction from vibration signals, a new method based on Independent Component Analysis (ICA) is proposed to realize separation and filtering for multi-source vibration signals. Firstly, the principal and algorithm of ICA used to separate mixed signals is introduced. Secondly, application in signal separation and filtering with ICA is studied in diagnosis. In addition, imitation and field examples are given. The experiments show it is feasible to separate and extract feature signal from multi-source vibration signals and it is an effective method in signal preprocessing in fault diagnosis.

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Zhang, Xiaoguang, Zhenyue Song, Jianpu Da, and Jianbao Fu. "A Novel Acoustic Filtering Sensor for Real-Time Tension Monitoring of Hoist Wire Ropes." Sensors 18, no. 9 (August 30, 2018): 2864. http://dx.doi.org/10.3390/s18092864.

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The real-time tension monitoring of wire ropes is a universal way to judge whether the hoist is overloaded in the special working environment of the coal mine. However, due to the strong drafts, unevenness of guide and flexible vibration of wire ropes, it is a challenge to monitor the tension with high accuracy. For this purpose, a new type of acoustic filtering sensor is designed in this study. To adapt to the violent vibration during the monitoring process, a structure with a cylindrical cavity and a narrow gap is designed in the sensor. The coupling between the internal fluid and sensor structure can greatly absorb the vibration energy. With the view of optimizing the filtering performance of the sensor, the influences on the filtering characteristics are presented and analyzed through employing different structural and acoustic parameters in simulations. Finally, acoustic filtering sensor prototypes based on optimized parameters are calibrated and tested in a real coal mine. The results have revealed that our acoustic filtering sensor can not only address the deficiencies of current pressure sensors in coal mining and achieve tension monitoring in real-time, but is also able to diagnose and forecast the occurrence of tension imbalance accidents.

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Auersch, Lutz. "Different Types of Continuous Track Irregularities as Sources of Train-Induced Ground Vibration and the Importance of the Random Variation of the Track Support." Applied Sciences 12, no. 3 (January 29, 2022): 1463. http://dx.doi.org/10.3390/app12031463.

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Irregularities of the track are a main cause of train-induced ground vibration, and track maintenance is of great importance. Although geometric irregularities at the wheel-rail contact are widely used, other types of irregularities, such as stiffness irregularities, irregularities from different track positions and irregularities in the wave propagation, were analysed in the present study. The track behaviour was investigated by a multi-beam-on-soil model. This track model is coupled with a vehicle model to calculate the vehicle–track interaction. The track model was also used for the track filtering, which transfers a track support error to the equivalent rail irregularity or, conversely, the sharp axle pulse on the rail to a smoother pulse on the soil. In the case in which this filtering varies randomly along the track, the pulses of the moving static load induce a certain ground vibration component (“the scatter of axle pulses”). This effect was calculated by the superposition of axle pulses in the frequency domain and by a stochastic simulation. Simultaneous vehicle, track and soil measurements at a certain site were used to evaluate the different excitation and ground vibration components. The agreement between calculations and axle-box and soil measurements is good. The ground vibrations calculated from rail irregularities and corresponding dynamic loads, however, clearly underestimate the measured ground vibration amplitudes. Only the static load that is moving over a varying track support stiffness can produce the important mid-frequency ground vibration component by the scatter of axle pulses.

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Gu, Song-Nian, Jian-Lin Zhang, Jie-Sheng Jiang, and Cheng-An He. "A Vibration Diagnosis Approach to Structural Fault." Journal of Vibration and Acoustics 111, no. 1 (January 1, 1989): 88–93. http://dx.doi.org/10.1115/1.3269829.

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In this paper the sensitivity of structural vibration parameters to fault is analyzed. The frequency response function, which is sensitive to structural fault and able to reflect structural dynamical properties, is chosen as a parameter for fault diagnosis. The least square identification method, Kalman filtering method, and the adaptive filtering method are adopted to diagnose structural fault. The results of simulation tests show the diagnosis approaches presented in the paper are feasible and accurate. The model testing results indicate that the structural fault can be detected even when the model stiffness is reduced to a rate of 5 percent.

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Zhang, Li Yong, and Yue Long Ran. "Fast Steady Horizon Sensor Based on Filtering Vibration." Advanced Materials Research 139-141 (October 2010): 2482–85. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.2482.

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The liquid switch gyroscope is used as a reference of the original horizontal coordinate system in the inertial navigation system of ballistic rockets. The stability of gyro is significant for finding ground level when a missile enters the destination region. A damping is adapted to increase the tremor convergence rate which may be caused by vibrations of generators, crustal movement and others. This paper proposed several experiments of the liquid electrolyte in the gyro horizon. The damping rate is variational with the bubbles. As a result of that, small tremor can be eliminated and the gyrohorizon can achieve steady mode rapidly.

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Neri, P., A. Paoli, A. V. Razionale, and C. Santus. "Time-Domain Image Filtering for DIC Vibration Measurements." Journal of Physics: Conference Series 2041, no. 1 (October 1, 2021): 012008. http://dx.doi.org/10.1088/1742-6596/2041/1/012008.

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Simin, Kang, Wang Yuelong, Sun Tao, Gao Yi, and He Yan. "LMS Adaptive Filtering of Drilling Tool Vibration Signal." Journal of Physics: Conference Series 1237 (June 2019): 042018. http://dx.doi.org/10.1088/1742-6596/1237/4/042018.

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Silva-Castro, Jhon, and Lifeng Li. "Deconvolution of blast vibration signals by wiener filtering." Inverse Problems in Science and Engineering 26, no. 10 (January 7, 2018): 1522–38. http://dx.doi.org/10.1080/17415977.2017.1422734.

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Singer, N., W. Singhose, and W. Seering. "Comparison of Filtering Methods for Reducing Residual Vibration." European Journal of Control 5, no. 2-4 (January 1999): 208–18. http://dx.doi.org/10.1016/s0947-3580(99)70155-x.

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Winkless, Laurie. "Vibration filtering in nature: how a spider hears." Materials Today 17, no. 9 (November 2014): 420. http://dx.doi.org/10.1016/j.mattod.2014.10.017.

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Singhose, William, and Joshua Vaughan. "Reducing Vibration by Digital Filtering and Input Shaping." IEEE Transactions on Control Systems Technology 19, no. 6 (November 2011): 1410–20. http://dx.doi.org/10.1109/tcst.2010.2093135.

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Wu, Huachun, Mengying Yu, Chunsheng Song, and Nianxian Wang. "Unbalance Vibration Suppression of Maglev High-Speed Motor Based on the Least-Mean-Square." Actuators 11, no. 12 (November 26, 2022): 348. http://dx.doi.org/10.3390/act11120348.

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The harmonic response caused by unbalanced excitation vibration for the high-speed rotating machinery will reduce the control accuracy and stability of the maglev high-speed motor, and limit the increase of its speed. When the active magnetic bearing is used to solve the unbalanced vibration, it will increase additional electromagnetic force and energy consumption, sometimes leading to the saturation of the power amplifier, and will transfer to the bearing foundation, causing the foundation to vibrate. In this paper, we analyzed periodic unbalance excitation force and the principle of rotor unbalanced vibration suppression, and the unbalance vibration model of the maglev rotor is derived. The Least-Mean-Square (LMS) algorithm is introduced into the PID control, an unbalance vibration control strategy based on real-time filtering compensation of rotor displacement signal is proposed, the vibration is eliminated by filtering the synchronous frequency and harmonic signal of the input of the PID control. The experimental results show that the proposed method can improve the maglev rotor’s rotation accuracy, reduce the magnetic bearing’s maximum control current, and decrease the vibration of the supporting foundation.

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Hao, Xiang Yu, Ming Li, Xue Feng Han, and Hong Guang Jia. "Analysis on the Influence of Random Vibration on MEMS Gyro Precision and Error Compensation." Applied Mechanics and Materials 130-134 (October 2011): 4164–68. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.4164.

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In order to improve its precision in dynamic environment, a Kalman filter was designed. Firstly, two sets of random drift data of MEMS gyro were respectively analysed, and it was found that the variance of random drift under random vibration significantly increased and its mean also changed. Then calculation results show that attitude angle error under random vibration is 2.6°, while in the static test it is 0.25°. Analysis on the characteristics of random drift was carried out, and it is found that it can be treated as stable, normally distributed random signal. Finally, a corresponding Kalman filter was designed. The results indicated that after filtering the variance of random drift is reduced to 0.0282, 26.4% of pre-filtering and the attitude angle error is reduced to 1.5°, 57.7% of pre-filtering. The above method can effectively compensate for the attitude angle error of MEMS gyro caused by random vibration. This study can be a reference to the application of low-cost MEMS gyro in aircraft navigation.

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Zhou, J., R. Goodall, L. Ren, and H. Zhang. "Influences of car body vertical flexibility on ride quality of passenger railway vehicles." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 223, no. 5 (June 5, 2009): 461–71. http://dx.doi.org/10.1243/09544097jrrt272.

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To study the influences of carbody vertical stiffness on vehicle ride quality, a vertical model of railway passenger vehicles, which includes the carbody flexible effects and all vertical rigid modes, is built. With the model and the covariance method, the requirements for the carbody bending frequency are researched. The results show that when the stiffness of a carbody decreases to certain frequencies there are significant vibrations in the carbody, although structural damping provided by a fully equipped carbody will help attenuate the vibration to some extent. A simple way to avoid resonant vibration is to increase the bending frequencies of a carbody: the higher the vehicle running speed, the higher carbody stiffness could be required. However, there are practical limitations to such an increase and the method used in this study can readily obtain the lowest bending frequency required by vehicle ride quality. Finally, the geometric filtering phenomenon and its influences on the carbody resonant flexural vibration are analysed. Results show that it is this phenomenon rather than the natural vibrations of bogie bounce that most strongly influences the resonant flexural vibration of a railway carbody.

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Zhang, Huanrui, and Xiaoyue Zhang. "Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment." Sensors 21, no. 8 (April 7, 2021): 2597. http://dx.doi.org/10.3390/s21082597.

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This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration.

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Ma, Ye. "Construction of Biologic Microscopic Image Segmentation Model Based on Smoothing of Fourth-Order Partial Differential Equation." Scanning 2022 (July 25, 2022): 1–8. http://dx.doi.org/10.1155/2022/1908644.

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In order to solve the problem of microscopic image noise, a biological microscopic image segmentation model based on the smoothing of the fourth-order partial differential equation was proposed. Based on the functional description of image smoothness by directional curvature mode value, a fourth-order PDE image denoising model is derived, which can effectively reduce noise while preserving edges. The result of this method is piecewise linear image, and the gradient at the edge of the target has a step. Using the feature of noise reduction, a new geodesic active contour model is proposed. The experiment result shows that when the variance of Gaussian white noise is 15, the enhancement and denoising effects of the proposed method are 80.35% and 69.84 higher than those of the original vibration filtering method and L. Alvarez method. In terms of time, the proposed method is 1.3075 seconds slower than the original vibration filtering method and 17.5754 seconds faster than the L. Alvarez method. When the variance of Gaussian white noise is 25, the enhancement and denoising effects of the proposed method are 97.79% and 81.16 higher than those of the original vibration filtering method and L. Alvarez method. In terms of time, the proposed method is 1.3246 seconds slower than the original vibration filtering method and 17.5796 seconds faster than the L. Alvarez method. Conclusion. The new model is not only stable but also has strong ability of contour extraction and fast convergence.

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Elvira-Ortiz, David Alejandro, Rene de Jesus Romero-Troncoso, Arturo Yosimar Jaen-Cuellar, Luis Morales-Velazquez, and Roque Alfredo Osornio-Rios. "Vibration Suppression for Improving the Estimation of Kinematic Parameters on Industrial Robots." Shock and Vibration 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/6954012.

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Vibration is a phenomenon that is present on every industrial system such as CNC machines and industrial robots. Moreover, sensors used to estimate angular position of a joint in an industrial robot are severely affected by vibrations and lead to wrong estimations. This paper proposes a methodology for improving the estimation of kinematic parameters on industrial robots through a proper suppression of the vibration components present on signals acquired from two primary sensors: accelerometer and gyroscope. A Kalman filter is responsible for the filtering of spurious vibration. Additionally, a sensor fusion technique is used to merge information from both sensors and improve the results obtained using each sensor separately. The methodology is implemented in a proprietary hardware signal processor and tested in an ABB IRB 140 industrial robot, first by analyzing the motion profile of only one joint and then by estimating the path tracking of two welding tasks: one rectangular and another one circular. Results from this work prove that the sensor fusion technique accompanied by proper suppression of vibrations delivers better estimation than other proposed techniques.

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Naumoski, Nove, Moe S. Cheung, and Simon Foo. "Dynamic characteristics of the Confederation Bridge." Canadian Journal of Civil Engineering 29, no. 3 (June 1, 2002): 448–58. http://dx.doi.org/10.1139/l02-041.

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Dynamic characteristics of the Confederation Bridge were determined from recorded accelerograms of vibrations due to traffic and wind. Natural frequencies of four vertical and five transverse modes of the bridge were identified from the Fourier amplitude spectra of the accelerograms. By appropriate filtering and processing of the accelerograms, displacement time histories of vibrations associated with each of these modes were computed, which were used to determine the mode shapes of the bridge. These characteristics are essential for investigations of the dynamic performance of the bridge. The computed natural frequencies are significantly larger than those of the finite element model used in the design of the bridge. Since the dynamic effects due to traffic, wind, and seismic loads depend on the natural frequencies of the bridge, an evaluation study of these effects is needed using the natural frequencies and mode shapes obtained from measured vibrations.Key words: bridge, acceleration, displacement, record, vibration, filtering, frequency, mode, Fourier spectrum.

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Gibbs, B. M., and J. D. Tattersall. "Vibrational Energy Transmission and Mode Conversion at a Corner-Junction of Square Section Rods." Journal of Vibration and Acoustics 109, no. 4 (October 1, 1987): 348–55. http://dx.doi.org/10.1115/1.3269452.

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The low frequency reflection and transmission of vibrational energy at an L-junction of square section rods is investigated theoretically and experimentally. The theoretical description, in which thin rod theory is employed, is complete in that all modes of vibration are considered including compression, torsion, and bending both for the incident and generated waves. It is seen that bending vibration in the plane of the system is coupled to compressional waves and bending vibration normal to the plane of the system is coupled to torsional waves. The theory applies to junctions of semi-infinite rods and this condition was simulated experimentally by means of impulse response techniques in which the reflected waves were removed by truncating the time histories prior to frequency analysis. A novel combination of phase separation, time of flight methods, and filtering has allowed the various modes of vibration to be separated and the agreement between predicted and measured reflection and transmission loss, both for same mode and dissimilar mode coupling, is promising.

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Morgan, Wani J., and Hsiao-Yeh Chu. "An Unsupervised Vibration Noise Reduction Approach and Its Application in Lubrication Condition Monitoring." Lubricants 11, no. 2 (February 19, 2023): 90. http://dx.doi.org/10.3390/lubricants11020090.

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Accelerometers are sensitive devices that capture vibrational fault signatures from industrial machines. However, noise often contaminates these fault signatures and must be eliminated before analysis. A data-driven (DD) denoising algorithm capable of filtering useful vibrational fault signatures from background noises was derived in this study. The algorithm was first validated by comparing its denoised result with a numerically generated ideal signal with a known exact solution. The DD denoising approach reduced the Mean Squared Error (MSE) from 0.459, when no denoising was performed, to 0.068, indicating an 85.2% decrease in noise. This novel approach outperformed the Discrete Wavelet (DW) denoising approach, which had an MSE of 0.115. The proposed DD denoising algorithm was also applied to preprocess vibration data used for the real-time lubrication condition monitoring of the plastic injection molding machine’s toggle clamping system, thereby reducing false positive relubrication alarms. The false positive rates, when analysis was performed on the raw vibration and the DW denoised vibration, were 10.7% and 7.6%, respectively, whereas the DD denoised vibration yielded the lowest false positive rate at 1%. This low false positive rate of the DD denoised vibration indicates that it is a more reliable condition monitoring system, thereby making this technique suitable for the smart manufacturing industry.

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Figlus, Tomasz. "A Method for Diagnosing Gearboxes of Means of Transport Using Multi-Stage Filtering and Entropy." Entropy 21, no. 5 (April 27, 2019): 441. http://dx.doi.org/10.3390/e21050441.

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The paper presents a method of processing vibration signals which was designed to detect damage to wheels of gearboxes for means of transport. This method uses entropy calculation, and multi-stage filtering calculated by means of digital filters and the Walsh–Hadamard transform to process signals. The presented method enables the extraction of vibration symptoms, which are symptoms of gear damage, from a complex vibration signal of a gearbox. The combination of multi-stage filtering and entropy enables the elimination of fast-changing vibration impulses, which interfere with the damage diagnosis process, and make it possible to obtain a synthetic signal that provides information about the state of the gearing. The paper demonstrates the usefulness of the developed method in the diagnosis of a gearbox in which two types of gearing damage were simulated: tooth chipping and damage to the working surface of the teeth. The research shows that the application of the proposed method of vibration of signal processing enables observation of the qualitative and quantitative changes in the entropy signal after denoising, which are unambiguous symptoms of the diagnosed damage.

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Qin, S. R., and Y. Guo. "Order Tracking Filtering for Rotating Machinery Diagnosis Based on Zero Phase Distortion Digital Filtering." Key Engineering Materials 295-296 (October 2005): 747–52. http://dx.doi.org/10.4028/www.scientific.net/kem.295-296.747.

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A new method for order tracking filtering of rotating machinery based on instantaneous frequency estimation and zero-phase distortion digital filtering is proposed. Compared with the traditional methods for order tracking filtering, the new method has a number of attractive features such as tacholess, no hardware-based tracking filter and no frequency shift to the original sampling data. The theorems and algorithms of the method are discussed. Filtering of overlapped data blocks, used to restrain the edge effect, which is caused by digital filtering, is introduced. An actual test example of run-up and coast down vibration of a motor is presented to demonstrate the validity of the method.

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Donn, S. C., K. C. Huang, and Ching-Cherng Sun. "Dynamic Grating Filtering in Photorefractive Crystals by Using Vibration." Japanese Journal of Applied Physics 37, Part 1, No. 7A (July 15, 1998): 3983–85. http://dx.doi.org/10.1143/jjap.37.3983.

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SENBA, Hiromasa, Nobuo TANAKA, Yoshihiro KIKUSHIMA, and Masaharu KURODA. "Vibration-Mode Filtering for Flexible Beams Using Optical Fibers." Transactions of the Japan Society of Mechanical Engineers Series C 62, no. 602 (1996): 3929–37. http://dx.doi.org/10.1299/kikaic.62.3929.

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He, Dawei, Boxin Wang, Xin Gao, and Xia Wang. "An Adaptive Filtering Method for Bridge Vibration Signals Based on Improved CEEMDAN and Multi-Scale Permutation Entropy." Environmental and Earth Sciences Research Journal 8, no. 4 (December 31, 2021): 163–68. http://dx.doi.org/10.18280/eesrj.080404.

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Aiming at the serious noise of bridge vibration signals in complex environment, this paper proposed an adaptive filtering and denoising optimization method for bridge structural health monitoring. The method took CEEMDAN algorithm as the core, during the step-by-step decomposition of original signals, white noise with opposite signs was added in each stage, meanwhile multi-scale permutation entropy (MPE) was introduced to analyze the mean entropy of each intrinsic mode function (IMF) at different scales, and components with serious noise were eliminated to complete the first filtering; then, in order to optimize the remaining IMFs for signal reconstruction and ensuring the smoothness and similarity of filtering, an optimized reconstruction model was established to complete the second filtering. Compared with the CEEMDAN method, the proposed method could solve the problems of mode mixing and endpoint effect with good completeness, orthogonality, and signal-to-noise ratio. At last, the advantages and application value of the proposed method were verified again by the vibration signal analysis of a real long-span bridge structure.

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Shirzad-Ghaleroudkhani, Nima, and Mustafa Gül. "An Enhanced Inverse Filtering Methodology for Drive-By Frequency Identification of Bridges Using Smartphones in Real-Life Conditions." Smart Cities 4, no. 2 (April 15, 2021): 499–513. http://dx.doi.org/10.3390/smartcities4020026.

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This paper develops an enhanced inverse filtering-based methodology for drive-by frequency identification of bridges using smartphones for real-life applications. As the vibration recorded on a vehicle is dominated by vehicle features including suspension system and speed as well as road roughness, inverse filtering aims at suppressing these effects through filtering out vehicle- and road-related features, thus mitigating a few of the significant challenges for the indirect identification of the bridge frequency. In the context of inverse filtering, a novel approach of constructing a database of vehicle vibrations for different speeds is presented to account for the vehicle speed effect on the performance of the method. In addition, an energy-based surface roughness criterion is proposed to consider surface roughness influence on the identification process. The successful performance of the methodology is investigated for different vehicle speeds and surface roughness levels. While most indirect bridge monitoring studies are investigated in numerical and laboratory conditions, this study proves the capability of the proposed methodology for two bridges in a real-life scale. Promising results collected using only a smartphone as the data acquisition device corroborate the fact that the proposed inverse filtering methodology could be employed in a crowdsourced framework for monitoring bridges at a global level in smart cities through a more cost-effective and efficient process.

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Chen, Gong, Shaojie Liu, Zhigong Tang, Jiangtao Xu, and Wenzheng Wang. "A novel method of multiple adaptive notch filtering for flexible missile vibration suppression." Aircraft Engineering and Aerospace Technology 92, no. 8 (July 11, 2020): 1149–57. http://dx.doi.org/10.1108/aeat-03-2020-0047.

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Purpose The modern missile has low uncertain and wide range vibration frequency. The conventional notch filter with the fixed notch frequency is less effective than that of the adaptive notch filter (ANF) in vibration suppression for the time-varying vibration frequency. Design/methodology/approach To overcome the drawback, a novel method is based on frequency estimators made by interpolation of three discrete Fourier transform (DFT) spectral lines. The modified frequency estimators based on the interpolation of three DFT spectral lines are presented to identify and track the vibration frequency. Then the notch frequencies of multiple ANFs are real-timely tuned according to estimators. Findings Finally, taking the second-order flexible missile as an example, the performance of the proposed method is verified. The verified simulation results show that multiple ANFs are effective in vibration suppression. Practical implications Cascading multiple ANFs to achieve multi-order vibration suppression is more efficient and feasible than conventional fixed-parameter notch filtering. Originality/value The frequency estimation method based on three DFT spectral lines proposed in this paper can effectively identify and track signals in the noise environment. Compared with conventional methods, the method pretended in this paper has high identification accuracy and a stronger ability to track signals. It can meet the fast frequency identification requirements of the actual flexible missile.

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Gu, Jun, Yuxing Peng, and Bobo Cao. "Studies of filtering effect on fault diagnosis of spindle device in hoist." Insight - Non-Destructive Testing and Condition Monitoring 63, no. 6 (June 1, 2021): 348–56. http://dx.doi.org/10.1784/insi.2021.63.6.348.

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Spindle devices, which are among the core components of mine hoists, are typical rotor-bearing systems. Vibration-based fault diagnosis techniques are often used to help prevent mechanical failures of such systems. The fault vibration signals generally include pulse information reflecting fault type, independent vibration components caused by other non-faulty mechanical components, noise in the surrounding environment and so on. The reduction of noise in the vibration signal collected by the sensor is of practical significance for the correct diagnosis of subsequent rotating machinery faults. To solve this problem, a fault diagnosis method based on a smooth (SM) filtering algorithm combined with variational mode decomposition (VMD) and a support vector machine (SVM) is proposed. Wavelet transform (WT) and wavelet packet transform (WPT) methods are used to compare the noise reduction. The reliability and effectiveness of the method are verified by experiments on a hoist mechanical fault simulator. Experimental results show that the proposed method has high prediction accuracy and can provide a good practical reference for fault diagnosis of rotating machinery.

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Boz, Utku, and Ipek Basdogan. "A numerical and experimental implementation and integration of Steiglitz–McBride algorithm with the frequency domain IIR filtering technique for active vibration control." Journal of Vibration and Control 24, no. 6 (July 6, 2016): 1086–100. http://dx.doi.org/10.1177/1077546316657502.

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In adaptive control applications for noise and vibration, finite ımpulse response (FIR) or ınfinite ımpulse response (IIR) filter structures are used for online adaptation of the controller parameters. IIR filters offer the advantage of representing dynamics of the controller with smaller number of filter parameters than with FIR filters. However, the possibility of instability and convergence to suboptimal solutions are the main drawbacks of such controllers. An IIR filtering-based Steiglitz–McBride (SM) algorithm offers nearly-optimal solutions. However, real-time implementation of the SM algorithm has never been explored and application of the algorithm is limited to numerical studies for active vibration control. Furthermore, the prefiltering procedure of the SM increases the computational complexity of the algorithm in comparison to other IIR filtering-based algorithms. Based on the lack of studies about the SM in the literature, an SM time-domain algorithm for AVC was implemented both numerically and experimentally in this study. A methodology that integrates frequency domain IIR filtering techniques with the classic SM time-domain algorithm is proposed to decrease the computational complexity. Results of the proposed approach are compared with the classical SM algorithm. Both SM and the proposed approach offer multimodal vibration suppression and it is possible to predict the performance of the controller via simulations. The proposed hybrid approach ensures similar vibration suppression performance compared to the classical SM and offers computational advantage as the number of control filter parameters increases.

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Hu, Si Quan, Chun Dong She, and Hui Yao. "A Vibration Data Acquisition System Based on ICP Sensor and Cortex-M3." Applied Mechanics and Materials 303-306 (February 2013): 1017–20. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1017.

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Vibration data acquisition has comprehensive applications such as machine monitoring, seismic data gathering. This paper presented a design of a vibration monitoring system based on an ICP acceleration sensor and a Cortex-M3 microcontroller. The sensor modulation circuit is illustrated in detail including the constant current source and filtering. An evaluation on the prototype is developed and the results show that our design can successfully monitor the vibration situations of interested objects.

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An, Xueli, and Luoping Pan. "Wind turbine bearing fault diagnosis based on adaptive local iterative filtering and approximate entropy." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 17 (April 4, 2016): 3228–37. http://dx.doi.org/10.1177/0954406216642478.

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For the unsteady characteristics of a fault vibration signal from a wind turbine rolling bearing, a bearing fault diagnosis method based on adaptive local iterative filtering and approximate entropy is proposed. The adaptive local iterative filtering method is used to decompose original vibration signals into a finite number of stationary components. The components which comprise major fault information are selected for further analysis. The approximate entropy of the selected components is calculated as a fault feature value and input to a fault classifier. The classifier is based on the nearest neighbor algorithm. The vibration signals from a spherical roller bearing on a wind turbine in its normal state, with an outer race fault, an inner race fault and a roller fault are analyzed. The results show that the proposed method can accurately and efficiently identify the fault modes present in the rolling bearings of a wind turbine.

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Luo, Yong Shun, Yong Yang, Yu Zhong Li, and Xiao Jun Wang. "Malfunction Signal Analysis of NC Machine Tool Gear Based on Kalman." Applied Mechanics and Materials 33 (October 2010): 28–33. http://dx.doi.org/10.4028/www.scientific.net/amm.33.28.

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Malfunction prediction is a trend of NC machine tool malfunction diagnosis development and the diagnosis accuracy is heavily dependent on the real and online acquisition of malfunction parameters. Gear malfunction is one of main mechanical malfunctions, and it is very meaningful to forecast its malfunction. The shock vibration of gear malfunction is non-stationary, so it should be processed by time frequency algorithms. Kalman filtering and Laplace wavelet are time frequency algorithms. Klaman filtering is self-adapting algorithm, and can filter noise in real-time. Laplace wavelet can obtain malfunction parameters by correlation filtering when correlation parameter k is the maximum. The proposed technique features two appealing advantages, which include self-adapting Kalman filter-based time-frequency algorithm and a Laplace wavelet-based parameters extraction. A set of simulating gear vibration data was used for verification. It provides a quantitative and more efficient means for obtaining the malfunction parameters to malfunction forecasting system.

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Journal articles on the topic 'Vibration filtering'

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