scholarly journals Transient Modeling and Recovery of Non-Stationary Fault Signature for Condition Monitoring of Induction Motors

2021 ◽  
Vol 11 (6) ◽  
pp. 2806
Author(s):  
Bilal Asad ◽  
Toomas Vaimann ◽  
Anouar Belahcen ◽  
Ants Kallaste ◽  
Anton Rassõlkin ◽  
...  
Keyword(s):  
Function Analysis ◽  
Diagnostic Algorithm ◽  
Efficient Utilization ◽  
Transient Time ◽  
Time Frequency ◽  
Motor Current ◽  
Laboratory Setup ◽  
Rotor Faults ◽  
Power Spectral ◽  
Definition Of

This paper presents the modeling and the broken rotor bar fault diagnostics by time–frequency analysis of the motor current under an extended startup transient time. The transient current-based nonstationary signal is retrieved and investigated for its time–frequency response to segregate the rotor faults and spatial harmonics. For studying the effect of reduced voltage on various parameters and the theoretical definition of the fault patterns, the winding function analysis (WFA)-based model is presented first. Moreover, an algorithm to improve the spectrum legibility is proposed. It is shown that by efficient utilization of the attenuation filter and consideration of the area containing the maximum power spectral density, the diagnostic algorithm gives promising results. The results are based on the machine’s analytical model and the measurements taken from the laboratory setup.

scholarly journals Evolutionary Spectra Estimation of Field Measurement Typhoon Processes Using Wavelets

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-Dong Zhou ◽  
You-Liang Ding ◽  
Ai-Qun Li
Keyword(s):  
Estimation Method ◽  
Engineering Application ◽  
Frequency Component ◽  
Time Frequency ◽  
Whole Process ◽  
Power Spectral ◽  
Frequency Domains ◽  
Definition Of ◽  
Evolutionary Spectra ◽  
Oscillatory Processes

This paper presents a wavelet-based method for estimating evolutionary power spectral density (EPSD) of nonstationary stochastic oscillatory processes and its application to field measured typhoon processes. The EPSD, which is deduced in a closed form based on the definition of the EPSD and the algorithm of the continuous wavelet transform, can be formulated as a sum of squared moduli of the wavelet functions in time domain modulated by frequency-dependent coefficients that relate to the squared values of wavelet coefficients and two wavelet functions with different time shifts. A parametric study is conducted to examine the efficacy of the wavelet-based estimation method and the accuracy of different wavelets. The results indicate that all of the estimated EPSDs have acceptable accuracy in engineering application and the Morlet transform can provide desirable estimations in both time and frequency domains. Finally, the proposed method is adopted to investigate the time-frequency characteristics of the Typhoon Matsa measured in bridge site. The nonstationary energy distribution and stationary frequency component during the whole process are found. The work in this paper may promote an improved understanding of the nonstationary features of typhoon winds.

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

scholarly journals Noise power spectral density scaled SNR response estimation with restricted range search for sound source localisation using unmanned aerial vehicles

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Benjamin Yen ◽  
Yusuke Hioka
Keyword(s):  
Spectral Density ◽  
Noise Reduction ◽  
Power Spectral Density ◽  
Sound Source ◽  
Processing Algorithm ◽  
Post Processing ◽  
Time Frequency ◽  
Distance Error ◽  
Rotor Noise ◽  
Power Spectral

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

scholarly journals Two Current-Based Methods for the Detection of Bearing and Impeller Faults in Variable Speed Pumps

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4514
Author(s):  
Vincent Becker ◽  
Thilo Schwamm ◽  
Sven Urschel ◽  
Jose Alfonso Antonino-Daviu
Keyword(s):  
Condition Monitoring ◽  
False Alarms ◽  
Signature Analysis ◽  
Variable Speed ◽  
Monitoring Methods ◽  
Time Frequency ◽  
Motor Current ◽  
Load Point ◽  
Bearing Defects ◽  
Current Signature

The growing number of variable speed drives (VSDs) in industry has an impact on the future development of condition monitoring methods. In research, more and more attention is being paid to condition monitoring based on motor current evaluation. However, there are currently only a few contributions to current-based pump diagnosis. In this paper, two current-based methods for the detection of bearing defects, impeller clogging, and cracked impellers are presented. The first approach, load point-dependent fault indicator analysis (LoPoFIA), is an approach that was derived from motor current signature analysis (MCSA). Compared to MCSA, the novelty of LoPoFIA is that only amplitudes at typical fault frequencies in the current spectrum are considered as a function of the hydraulic load point. The second approach is advanced transient current signature analysis (ATCSA), which represents a time-frequency analysis of a current signal during start-up. According to the literature, ATCSA is mainly used for motor diagnosis. As a test item, a VSD-driven circulation pump was measured in a pump test bench. Compared to MCSA, both LoPoFIA and ATCSA showed improvements in terms of minimizing false alarms. However, LoPoFIA simplifies the separation of bearing defects and impeller defects, as impeller defects especially influence higher flow ranges. Compared to LoPoFIA, ATCSA represents a more efficient method in terms of minimizing measurement effort. In summary, both LoPoFIA and ATCSA provide important insights into the behavior of faulty pumps and can be advantageous compared to MCSA in terms of false alarms and fault separation.

A Time–Frequency Representation Model for Seismic Ground Motions

2020 ◽  
Author(s):  
Xi Zhong Cui ◽  
Han Ping Hong
Keyword(s):  
Ground Motions ◽  
Seismic Source ◽  
Model Parameters ◽  
Time Frequency ◽  
Motion Models ◽  
Power Spectral ◽  
Frequency Representation ◽  
Site Characteristics ◽  
S Transform ◽  
Proposed Model

ABSTRACT A probabilistic model of the time–frequency power spectral density (TFPSD) is presented. The model is developed, based on the time–frequency representation of records from strike-slip earthquakes, in which the time–frequency representation is obtained by applying the S-transform (ST). The model for the TFPSD implicitly considers the amplitude modulation and frequency modulation for the nonstationary ground motions; this differs from the commonly used evolutionary PSD model. Predicting models for the model parameters, based on seismic source and site characteristics, are developed. The use of the model to simulate ground motions for scenario seismic events is illustrated, in which the simulation is carried out using a recently developed model that is based on the discrete orthonormal ST and ST. The illustrative example highlights the simplicity of using the proposed model and the physical meaning of some of the model parameters. A model validation analysis is carried out by comparing the statistics of the pseudospectral acceleration obtained from the simulated records to those obtained using a few ground-motion models available in the literature and considered actual records. The comparison indicates the adequacy of the proposed model.

scholarly journals LINEAR ASSESSMENT OF CEREBRAL AUTOREGULATION IN IDIOPATHIC PARKINSON'S DISEASE

2016 ◽  
Vol 8 (2) ◽  
pp. 14
Author(s):  
Chuang-chien Chiu ◽  
Ken Ying-kai Liao ◽  
Shoou-jeng Yeh
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cerebral Autoregulation ◽  
System Analysis ◽  
Cerebral Blood Flow Velocity ◽  
Function Analysis ◽  
Control Group ◽  
Power Spectral ◽  
Significant Difference ◽  
Density Analysis

<p class="lead">Parkinson’s disease cases have been on the rise in the recent years, which promoted several different researches into the disorder. However, there hasn’t much research been done in the non-motor aspects of the disease. This study aims to improve the understanding of one of the non-motor symptoms of Parkinson’s disease. Specifically, this research aims to further understand cerebral autoregulation in patients with Parkinson’s disease. In order to achieve this aim, 25 subjects were recruited, with 11 healthy controls and 14 patients with Parkinson’s disease. The continuous blood pressure and continuous cerebral blood flow velocity of all subjects were recorded and processed while the subjects were at rest, tilt-up, and during hyperventilation. Linear signal and system analysis techniques were applied such as the power spectral density analysis and cross-correlation function analysis. Results showed that patients with Parkinson’s disease did not show a significant difference from the control group while at rest and after tilt-up. However, there was a significant difference between the groups during hyperventilation. The results obtained in this study suggested that the metabolic regulatory pathway for cerebral autoregulation is impaired in patients with Parkinson’s disease.</p>

Function Analysis of Injection Molding

2011 ◽  
Vol 189-193 ◽  
pp. 2699-2703
Author(s):  
Ji Quan Li ◽  
Yan Hu ◽  
Ying Kong ◽  
Shao Fei Jiang ◽  
Chuan Chen
Keyword(s):  
Injection Molding ◽  
Detailed Analysis ◽  
Function Analysis ◽  
Injection Molding Process ◽  
Molding Process ◽  
Quality Function ◽  
Analysis And Evaluation ◽  
Definition Of

The function of injection molding process is described in the quality, function and costs of injection products from the definition of function. Detailed analysis and evaluation are taken to investigate these three aspects, and the aspect of injection products quality is principally discussed. The analysis and evaluation of injection molding process function will be kept as the judgment of quality of the process.

Use of RVT for Computation of In-Structure Response Spectra and Peak Responses and Comparison to Time History and Response Spectrum Analysis

2018 ◽  
Vol 34 (4) ◽  
pp. 1913-1930 ◽  
Author(s):  
Irmela Zentner
Keyword(s):  
Response Spectrum ◽  
Structural Response ◽  
Time History ◽  
Strong Motion ◽  
Response Spectra ◽  
Combination Rules ◽  
Floor Response Spectra ◽  
Power Spectral ◽  
Time Histories ◽  
Definition Of

The random vibration theory offers a framework for the conversion of response spectra into power spectral densities (PSDs) and vice versa. The PSD is a mathematically more suitable quantity for structural dynamics analysis and can be straightforwardly used to compute structural response in the frequency domain. This allows for the computation of in-structure floor response spectra and peak responses by conducting only one structural analysis. In particular, there is no need to select or generate spectrum-compatible time histories to conduct the analysis. Peak response quantities and confidence intervals can be computed without any further simplifications such as currently used in the response spectrum method, where modal combination rules have to be derived. In contrast to many former studies, the Arias intensity-based definition of strong-motion duration is adopted here. This paper shows that, if the same definitions of strong-motion duration and modeling assumptions are used for time history and RVT computations, then the same result can be expected. This is illustrated by application to a simplified model of a reactor building.

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