Relevant bibliographies by topics / Vibration filtering

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Vibration filtering'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Vibration filtering"

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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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Dissertations / Theses on the topic "Vibration filtering"

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Walter, Patrick L. "FILTERING CONSIDERATIONS WHEN TELEMETERING SHOCK AND VIBRATION DATA." International Foundation for Telemetering, 2001. http://hdl.handle.net/10150/607681.

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International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada
The accurate measurement of shock and vibration data via flight telemetry is necessary to validate structural models, indicate off-nominal system performance, and/or generate environmental qualification criteria for airborne systems. Digital telemetry systems require anti-aliasing filters designed into them. If not properly selected and located, these filters can distort recorded time histories and modify their spectral content. This paper provides filter design guidance to optimize the quality of recorded flight structural dynamics data. It is based on the anticipated end use of the data. Examples of filtered shock data are included.
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Xue, Kai. "Modal filtering for active control of floor vibration under impact loading." Kyoto University, 2018. http://hdl.handle.net/2433/232024.

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Magee, David Patrick. "Optimal arbitrary time-delay filtering to minimize vibration in elastic manipulator systems." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/15891.

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Faghidi, Hamid. "Non-parametric and Non-filtering Methods for Rolling Element Bearing Condition Monitoring." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30689.

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Rolling element bearings are one of the most significant elements and frequently-used components in mechanical systems. Bearing fault detection and diagnosis is important for preventing productivity loss and averting catastrophic failures of mechanical systems. In industrial applications, bearing life is often difficult to predict due to different application conditions, load and speed variations, as well as maintenance practices. Therefore, reliable fault detection is necessary to ensure productive and safe operations. Vibration analysis is the most widely used method for detection and diagnosis of bearing malfunctions. A measured vibration signal from a sensor is often contaminated by noise and vibration interference components. Over the years, many methods have been developed to reveal fault signatures, and remove noise and vibration interference components. Though many vibration based methods have been proposed in the literature, the high frequency resonance (HFR) technique is one of a very few methods have received certain industrial acceptance. However, the effectiveness of the HFR methods depends, to a great extent, on some parameters such as bandwidth and centre frequency of the fault excited resonance, and window length. Proper selection these parameters is often a knowledge-demanding and time-consuming process. In particular, the filter designed based on the improperly selected bandwidth and center frequency of the fault excited resonance can filter out the true fault information and mislead the detection/diagnosis decisions. In addition, even if these parameters can be selected properly at beginning of each process, they may become invalid in a time-varying environment after a certain period of time. Hence, they may have to be re-calculated and updated, which is again a time-consuming and error-prone process. This undermines the practical significance of the above methods for online monitoring of bearing conditions. To overcome the shortcomings of existing methods, the following four non-parametric and non-filtering methods are proposed: 1. An amplitude demodulation differentiation (ADD) method, 2. A calculus enhanced energy operator (CEEO) method, 3. A higher order analytic energy operator (HO_AEO) approach, and 4. A higher order energy operator fusion (HOEO_F) technique. The proposed methods have been evaluated using both simulated and experimental data.
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Bjerke, Benjamin A. "Noise and Degradation Reduction for Signal and Image Processing via Non-adaptive Convolution Filtering." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23700.

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Noise and degradation reduction is of significant importance in virtually all systems where these phenomena are present, specifically in the fields of signal and image processing.  The effect of image processing on target detection is of significant interest because noise and degradations can greatly reduce the effectiveness of detection algorithms, due to the presence of high intensity noise which is often mistaken as a target.  In signal processing, noise in vibration data, or any time-series data, can reduce the accuracy of measurement and can prevent the passing of useful information.    
Many filters that have been developed are designed to reduce a single class of noise, such as Wiener and Frost filters.  When these filters are applied to types of noise that they were not designed for, the effect of the noise reduction can be greatly reduced.  The proposed Two-Stage Non-Adaptive Convolution (TSNAC) filter significantly reduces both additive and multiplicative noise in these two unique systems.
The performance of these filters is compared through several Image Quality (IQ) metrics.
It will be shown that the proposed TSNAC filter reduces noise and degradations more effectively in both SAR images and synthetic vibration data than the competing filters.  It will show higher IQ scores, greater computational efficiency in target detection, and significant improvement in signal restoration of simulated vibration data.

Master of Science
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Erazo, Kalil. "Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring." ScholarWorks @ UVM, 2015. http://scholarworks.uvm.edu/graddis/513.

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During strong earthquakes structural systems exhibit nonlinear behavior due to low-cycle fatigue, cracking, yielding and/or fracture of constituent elements. After a seismic event it is essential to assess the state of damage of structures and determine if they can safely resist aftershocks or future strong motions. The current practice in post-earthquake damage assessment relies mainly on visual inspections and local testing. These approaches are limited to the ability of inspectors to reach all potentially damaged locations, and are typically intended to detect damage near the outer surfaces of the structure leaving the possibility of hidden undetected damage. Some structures in seismic prone-regions are instrumented with an array of sensors that measure their acceleration at different locations. We operate under the premise that acceleration response measurements contain information about the state of damage of structures, and it is of interest to extract this information and use it in post-earthquake damage assessment and decision making strategies. The objective of this dissertation is to show that Bayesian filters can be successfully employed to estimate the nonlinear dynamic response of instrumented structural systems. The estimated response is subsequently used for structural damage diagnosis. Bayesian filters combine dynamic response measurements at limited spatial locations with a nonlinear dynamic model to estimate the response of stochastic dynamical systems at the model degrees-of-freedom. The application of five filters is investigated: the extended, unscented and ensemble Kalman filters, the particle filter and the model-based observer. The main contributions of this dissertation are summarized as follows: i) Development of a filtering-based mechanistic damage assessment framework; ii) Experimental validation of Bayesian filters in small and large-scale structures; iii) Uncertainty quantification and propagation of response and damage estimates computed using Bayesian filters.
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Geiger, Douglas J. "Investigation into the influence of threshold forces and vibrations in diamond roll plunge dressing of grinding wheels." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-042605-154235/.

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Thesis (M.S.) -- Worcester Polytechnic Institute.
Keywords: Threshold Forces; Vibrations; Signal Processing; Force Adaptive Grinding; Diamond Roll Dressing. Includes bibliographical references (p. 29 ).
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Wilson, David. "Prediction of bending wave transmission across coupled plates affected by spatial filtering and non-diffuse vibration fields." Thesis, University of Liverpool, 2014. http://livrepository.liverpool.ac.uk/15433/.

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This thesis concerns models based on Statistical Energy Analysis (SEA) to predict bending wave vibration in heavyweight buildings from structure-borne sound sources such as machinery. These sources tend to inject most power in the low- and mid-frequency ranges where the walls and floors have low mode counts and low modal overlap for which calculated Coupling Loss Factors (CLFs) from semi-infinite plate theory can be in error. For machinery it is necessary to predict vibration on walls/floors that are remote from the source room. In this situation, propagation across successive structural junctions causes spatial filtering of the wave field and the assumption of a diffuse field in each plate subsystem breaks down. The predictive approach described in the European Standard EN12354 uses SEA path analysis which assumes that transmission is dominated by first-order paths. However the feasibility of extending the concept of path analysis to walls and floors of rooms that are distant from the source room(i.e. not adjacent) is unknown. These issues are addressed in the thesis. The feasibility of SEA path analysis was assessed by quantifying the total contribution to receiver subsystem energy from paths containing specified numbers of CLFs. For receiving subsystems which are attached directly to the source subsystem, the EN12354 approach was found to underestimate the energy levels. For rooms remote from the source room, path analysis was found to significantly underestimate the vibration of the walls/floors which form the receiver room. Alternative approaches to improve predictions in large heavyweight buildings were assessed through comparison with Monte-Carlo Finite Element Method (MCFEM) models which were validated on a small heavyweight building. Matrix SEA was used with CLFs calculated for L-, T- and X-junctions using analytical models for rectangular plates to try and incorporate modal features. For isolated junctions, there was good agreement with MCFEM but in large buildings. However, it was unable to predict the peaks and troughs in the vibration response to one-third octave band accuracy although it can estimate the envelope response for plates that are directly connected to the source plate. In general, matrix SEA using finite plate theory CLFs does not improve the prediction in one-third octave bands when the statistical mode count is less than unity. Ray tracing was therefore investigated which showed that the angular distribution of power incident on the plate edges differed significantly from a diffuse field. Computationally efficient ray tracing was then developed for inclusion in Advanced SEA (ASEA) models to account for indirect coupling between plate subsystems. ASEA gave significant improvements over matrix SEA when there were large numbers of structural junctions between the source and receiving plates.
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Nauclér, Peter. "Estimation and Control of Resonant Systems with Stochastic Disturbances." Doctoral thesis, Uppsala University, Department of Information Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8688.

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The presence of vibration is an important problem in many engineering applications. Various passive techniques have traditionally been used in order to reduce waves and vibrations, and their harmful effects. Passive techniques are, however, difficult to apply in the low frequency region. In addition, the use of passive techniques often involve adding mass to the system, which is undesirable in many applications.

As an alternative, active techniques can be used to manipulate system dynamics and to control the propagation of waves and vibrations. This thesis deals with modeling, estimation and active control of systems that have resonant dynamics. The systems are exposed to stochastic disturbances. Some of them excite the system and generate vibrational responses and other corrupt measured signals.

Feedback control of a beam with attached piezoelectrical elements is studied. A detailed modeling approach is described and system identification techniques are employed for model order reduction. Disturbance attenuation of a non-measured variable shows to be difficult. This issue is further analyzed and the problems are shown to depend on fundamental design limitations.

Feedforward control of traveling waves is also considered. A device with properties analogous to those of an electrical diode is introduced. An `ideal´ feedforward controller based on the mechanical properties of the system is derived. It has, however, poor noise rejection properties and it therefore needs to be modified. A number of feedforward controllers that treat the measurement noise in a statistically sound way are derived.

Separation of overlapping traveling waves is another topic under investigation. This operation also is sensitive to measurement noise. The problem is thoroughly analyzed and Kalman filtering techniques are employed to derive wave estimators with high statistical performance.

Finally, a nonlinear regression problem with close connections to unbalance estimation of rotating machinery is treated. Different estimation techniques are derived and analyzed with respect to their statistical accuracy. The estimators are evaluated using the example of separator balancing.

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Olsson, Claes. "Active Vibration Control of Multibody Systems : Application to Automotive Design." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5818.

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Books on the topic "Vibration filtering"

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Patrizio, Colaneri, and SpringerLink (Online service), eds. Periodic Systems: Filtering and Control. London: Springer London, 2009.

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Elliott, S. J. The application of adaptive filtering to the active control of sound and vibration. Southampton, England: University of Southampton, Institute of Sound and Vibration Research, 1985.

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Andrzej, Kozakiewicz, ed. Kalman filter method in the analysis of vibrations due to water waves. Singapore: World Scientific, 1993.

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Hubbard, James E. Spatial filtering for the control of smart structures: An Introduction. Heidelberg: Springer, 2010.

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Bittanti, Sergio, and Patrizio Colaneri. Periodic Systems: Filtering and Control. Springer London, Limited, 2010.

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Book chapters on the topic "Vibration filtering"

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Hubbard, James E. "Active Vibration Control with Spatially Shaded Distributed Transducers." In Spatial Filtering for the Control of Smart Structures, 69–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03804-4_3.

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Castellini, P., P. Chiariotti, and M. Martarelli. "Mode Filtering of Continuous Scanning Laser Doppler Vibration Data." In Topics in Modal Analysis, Volume 7, 655–60. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6585-0_63.

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Magnevall, Martin, and Tomas Beno. "Improved Cutting Force Measurements in Milling Using Inverse Filtering." In Shock & Vibration, Aircraft/Aerospace, Energy Harvesting, Acoustics & Optics, Volume 9, 1–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30087-0_1.

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Meng, Xiangzhong, and Jianghong Wang. "Research on Method of Wavelet Function Selection to Vibration Signal Filtering." In Lecture Notes in Electrical Engineering, 87–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-28807-4_13.

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Pokale, Bharat, R. Rangaraj, and Sayan Gupta. "Parameter Identification in a Beam from Experimental Vibration Measurements Using Particle Filtering." In Proceedings of the International Symposium on Engineering under Uncertainty: Safety Assessment and Management (ISEUSAM - 2012), 683–95. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0757-3_44.

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Iqbal, Mohd, and Anil Kumar. "Flexural Vibration Analysis and Improvement of Wave Filtering Capability of Periodic Pipes." In Mechanisms and Machine Science, 1049–58. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15758-5_108.

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Valente, Nicholas A., Celso T. do Cabo, Zhu Mao, and Christopher Niezrecki. "Template Matching and Particle Filtering for Structural Identification of High- and Low-Frequency Vibration." In Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6, 43–50. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04098-6_5.

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Burdzik, Rafał, and Paweł Słowiński. "Application of Pass-Band Step Filtering Method for Identification the Vibration-Acoustic Signature of a Moving Train." In TRANSBALTICA XII: Transportation Science and Technology, 68–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94774-3_7.

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Smith, J. D. "Signal filtering and improvement." In Vibration Measurement and Analysis, 126–38. Elsevier, 1989. http://dx.doi.org/10.1016/b978-0-408-04101-0.50016-4.

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Du, Chunling, and Lihua Xie. "Adaptive Filtering Algorithms for Active Vibration Control." In Modeling and Control of Vibration in Mechanical Systems, 275–92. CRC Press, 2018. http://dx.doi.org/10.1201/9781315218069-15.

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Conference papers on the topic "Vibration filtering"

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Plisson, Jules, Adrien Pelat, François Gautier, Vicent Romero-Garcia, and Thierry Bourdon. "Design of a Multiwaves Vibration Filtering." In 11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2020. http://dx.doi.org/10.4271/2020-01-1560.

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Long, Guo, Kan Wang, and Teik Lim. "Subband Adaptive Filtering Algorithms for Active Broadband Noise Control in Impulsive Vehicle Noise Environment." In Noise and Vibration Conference & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-01-1528.

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Wu, Houde, Bin Wang, Ming Zhao, and Wenhai Xu. "A self-adaptive anti-vibration pipeline-filtering algorithm." In Sixth International Conference on Graphic and Image Processing (ICGIP 2014), edited by Yulin Wang, Xudong Jiang, and David Zhang. SPIE, 2015. http://dx.doi.org/10.1117/12.2178769.

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Komma, P., C. Weiss, and A. Zell. "Adaptive bayesian filtering for vibration-based terrain classification." In 2009 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2009. http://dx.doi.org/10.1109/robot.2009.5152327.

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Sterian, Andreea-Rodica P., and Cristian I. Toma. "Filtering possibilities for processing optoelectronic current for acceleration measurements." In Fifth International Conference on Vibration Measurements by Laser Techniques, edited by Enrico P. Tomasini. SPIE, 2002. http://dx.doi.org/10.1117/12.468162.

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Marx, L. R. K., and L. Swathi. "Vibration control of piezoactuated cantilever beams using adaptive filtering." In 2013 International Conference on Information Communication and Embedded Systems (ICICES 2013). IEEE, 2013. http://dx.doi.org/10.1109/icices.2013.6508391.

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Qingmei Yang and Jiammin Sun. "Study on vibration control based on adaptive filtering algorithm." In 2009 International Conference on Mechatronics and Automation (ICMA). IEEE, 2009. http://dx.doi.org/10.1109/icma.2009.5246696.

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Qin, Shuren, and Yu Guo. "Order Tracking Filtering Based on Instantaneous Frequency Estimation and Zero-Phase Distortion Digital Filtering." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/vib-48483.

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Abstract:
A new method for run-up or coast down vibration signal order tracking filtering of rotating machinery based on instantaneous frequency estimation and zero-phase distortion digital filtering is proposed in this paper. By contrast with traditional methods of order tracking filtering, the features of tacholess, no hardware-based tracking filter required and no frequency shift to original sampling data, etc, make it more attractive. The theorems and algorithms of the method are detailed discussed in this paper. The filtering of overlapped data blocks is used to restrain the edge effect, which caused by digital filtering, is also introduced. An actual test example of a motor’s run-up and coast down vibration is introduced to demonstrate the validity of the method.
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Magee, David P., and Wayne J. Book. "Implementing Modified Command Filtering to Eliminate Multiple Modes of Vibration." In 1993 American Control Conference. IEEE, 1993. http://dx.doi.org/10.23919/acc.1993.4793386.

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Zhang, Xiao, and Yue Wang. "Research on a filtering method for integrated navigation vibration interference." In 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/iceeecs-16.2016.60.

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Reports on the topic "Vibration filtering"

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Candy, J., K. Fisher, B. Markowicz, and D. Paulsen. Multichannel Deconvolution of Vibrational Shock Signals: An Inverse Filtering Approach. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1727270.

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