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Fault diagnosis scheme for open-circuit faults in switched reluctance motor drives using fast fourier transform algorithm with bus current detection

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IET POWER ELECTRONICS 2016年第1期9卷 20-30页

作者： Gan, Chun Wu, Jianhua Yang, Shiyou Hu, Yihua Cao, Wenping Si, Jikai Zhejiang Univ Coll Elect Engn Hangzhou 310027 Zhejiang Peoples R China Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT9 5AH Antrim North Ireland Henan Polytech Univ Sch Elect Engn & Automat Jiaozuo 454003 Peoples R China

Reliability of power converters is of crucial importance in switched reluctance motor drives used for safety-critical applications. Open-circuit faults in power converters will cause the motor to run in unbalanced states, and if left untreated, they will lead to damage to the motor and power modules, and even cause a catastrophic failure of the whole drive system. This study is focused on using a single current sensor to detect open-circuit faults accurately. An asymmetrical half-bridge converter is considered in this study and the faults of single-phase open and two-phase open are analysed. Three different bus positions are defined. On the basis of a fast fourier transform algorithm with Blackman window interpolation, the bus current spectrums before and after open-circuit faults are analysed in details. Their fault characteristics are extracted accurately by the normalisations of the phase fundamental frequency component and double phase fundamental frequency component, and the fault characteristics of the three bus detection schemes are also compared. The open-circuit faults can be located by finding the relationship between the bus current and rotor position. The effectiveness of the proposed diagnosis method is validated by the simulation results and experimental tests.

关键词： fault diagnosis reluctance motor drives fast fourier transforms power convertors electric sensing devices rotors circuit reliability fault diagnosis scheme open-circuit fault detection switched reluctance motor drives fast fourier transform algorithm bus current spectrum detection power converter reliability power modules catastrophic failure single current sensor asymmetrical half-bridge converter single-phase open faults two-phase open faults bus positions blackman window interpolation double phase fundamental frequency component rotor position safety-critical applications unbalanced states

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Improved aggregation levels of ITS data via wavelet decomposition and fast fourier transform algorithm

Improved aggregation levels of ITS data via wavelet decompos...

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6th IEEE International Conference on Intelligent Transportation Systems

作者： Liu, MH Yu, L Yuan, ZZ Jiao Tong Univ Sch Traff & Transportat Beijing 100044 Peoples R China

ISBN: (纸本)0780381254

To make the real-time ITS data more useful to transportation planners, ITS data should be reasonably processed to acquire appropriate aggregation levels and sampling frames. Conventional aggregation techniques concentrated. on the statistical comparison between the original and aggregated data sets, so they cannot eliminate the undesired information (e.g., error or noise). This research improves the wavelet technique which analyzes real-time data within frequency domain. ITS data were decomposed by wavelet transformation and then transformed by FFT. Through unifying the parameter of FFT and creating grading system, the optimal aggregation level can be determined. As a result of this research, the computer software compiled in MATLAB was developed, which can provide the optimal aggregation levels and aggregated data series, which was applied to the archived 2-minute traffic data in Beijing. Optimal Aggregation levels for different days of a week and different time periods of a day were obtained by the proposed approach.

关键词： data aggregation fast fourier transform algorithm wavelet decomposition

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Precision manufacturing technology and measurements in steel rolling industry using multi threshold fast fourier transform and back propagation algorithm for analysis of X-ray diffractometry 1

Precision manufacturing technology and measurements in steel...

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International Conference and Exposition on Mechanical, Material and Manufacturing Technology (ICE3MT)

作者： Sujatha, K. Ponmagal, R. S. Deepalakshmi, B. Jayachitra, N. Dr MGR Educ & Res Inst EEE Dept Chennai Tamil Nadu India SRM Inst Sci & Technol Dept CSE Chennai Tamil Nadu India Ramco Inst Technol Dept ECE Chennai Tamil Nadu India Dr MGR Educ & Res Inst Dept Chem Engn Chennai Tamil Nadu India

X-ray diffractometry is a unique technique and that the X-ray diffraction patterns which depict the structure of the steel sheets during processing with the features extracted, that they serve directly as a signature which is very complicated. X-ray diffraction (XRD) techniques are a type of non-destructive method of investigation to identify the flaws during the fabrication of steel sheets. X-ray diffraction is comparatively simple and can be effectively used for the examination and identification of flaws during the rolling process of steel sheets. XRD technique finds application in various fields like textile industry, forensic, qualitative and quantitative phase analysis of poly crystalline material, to infer overall properties of the fiber and measure the degree of crystalline nature. It is extensively used to explore areas like material science, chemistry and in industry for research and quality control. This effective method gains novelty by combining the signal processing algorithms like multiple threshold based fast fourier transform (FFT) and Artificial neural network (ANN) trained with Back Propagation algorithm (BPA) thereby offering an automated system for online monitoring during fabrication of flawless metal sheets. The hot rolled steel sheets for three categories namely, flawless, moderate flaw and extreme flaw conditions are obtained from the XRD pattern. Then multiple thresholds are incorporated to identify the peak position, peak width and peak intensity. The FFT algorithm computes the power spectrum which is used as features to identify the flaws in the steel sheets during cold rolling process. The extracted features are used as inputs to train the ANN with BPA whose performance is evaluated to be 90% efficient. (C) 2020 The Authors. Published by Elsevier Ltd.

关键词： X-ray diffractometry Steel rolling Industry Multi-level threshold fast fourier transform algorithm Back propagation algorithm

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Precision manufacturing technology and measurements in steel rolling industry using multi threshold fast fourier transform and back propagation algorithm for analysis of X-ray diffractometry

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Materials Today: Proceedings 2021年 38卷 2624-2628页

作者： K. Sujatha R.S. Ponmagal B. Deepalakshmi N. Jayachitra EEE Dept. Dr. MGR Educational and Research Institute Maduravoyal Chennai India Department of CSE SRM Institute of Science and Technology India Department of ECE Ramco Institute of Technology India Department of Chemical Engineering Dr. MGR Educational and Research Institute Maduravoyal Chennai India

关键词： X-ray diffractometry Steel rolling Industry Multi-level threshold fast fourier transform algorithm Back propagation algorithm

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Online fuzzy time series analysis based on entropy discretization and a fast fourier transform

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APPLIED SOFT COMPUTING 2014年第partb期14卷 156-166页

作者： Chen, Mu-Yen Chen, Bo-Tsuen Natl Taichung Univ Sci & Technol Dept Informat Management Taichung 404 Taiwan

Fuzzy time series analysis has been used successfully for forecasting in various domains including stock performance, academic enrollment, temperature, and traffic patterns. Research in this field has concentrated primarily on two issues: the reasonable partition of discourse, and defuzzification methods for discrete datasets. Both issues have a huge impact on the prediction performance of forecasting models. This paper integrates the entropy discretization technique with a fast fourier transform (FFT) algorithm to develop a novel fuzzy time series forecasting model to resolve these issues. The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Dow-Jones Industrial Average (DJIA) financial datasets were used to evaluate the model's performance. The results demonstrate that the presented model is a major improvement over previous fuzzy time series models produced by Chen (1996), Yu (2005), Chang et al. (2011), and Hsieh et al. (2011), and five other conventional time series models. The proposed model is implemented using the bootstrapping method, after which it incrementally updates its prediction capability. Results show that the proposed model's incremental learning mechanism allows it to effectively handle large online financial datasets. (C) 2013 Elsevier B. V. All rights reserved.

关键词： Fuzzy time series Entropy-based discretization fast fourier transform algorithm

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Thinned linear array using joint optimization of IWDO/FFT algorithm

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JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS 2021年第18期35卷 2480-2491页

作者： Li, Cheng-Zhang Li, Hai-Ming Nanjing Univ Posts & Telecommun Coll Telecommun & Informat Engn Nanjing 210003 Peoples R China

A sparse array synthesis method based on improved wind-driven optimization algorithm (IWDO) and fast fourier transform (FFT) for the purpose of sidelobe suppression was introduced. First, the uniform linear array was sparse by the FFT algorithm. Then the amplitude excitation weighting of array elements was optimized by IWDO algorithm based on probability factor chaotic map. During the optimization process, the minimum peak sidelobe level was used as the fitness function. By comparing with the simulation results of classic Chebyshev weighting method, the method proposed in this paper has better performance.

关键词： Wind-driven optimization algorithm fast fourier transform algorithm antenna sparse sidelobe suppression

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Online frequency estimation of periodic disturbance based on FFT algorithm with application in repetitive control

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JOURNAL OF VIBRATION AND CONTROL 2024年第7-8期30卷 1479-1486页

作者： Moghadam, Hassan Farrokhi Vasegh, Nastaran Mousavi, Sayed Mohsen Seyed Islamic Azad Univ Dept Elect Engn Ahvaz Branch Ahvaz Iran Shahid Rajaee Teacher Training Univ Fac Elect Engn Tehran 16788 Iran

In this paper, a new adaptive method is proposed for online frequency estimation of a periodic disturbance by the output measurement based on the fast fourier transform algorithm. The performance of the proposed algorithm is evaluated in the face of time varying frequency, time varying amplitude, non-sinusoidal periodic disturbance, and different plants. Also, the convergence rate of the method is compared by other estimation methods. Then, the online estimation is used in the repetitive controller structure for eliminating periodic disturbances with unknown frequencies. A new analysis is performed on RC and the stability conditions are determined in a theorem. These are illustrated in simulation results. The effectiveness of this method is shown on the application of phi-shaped PZT active suspension and it is compared by existing results.

关键词： fast fourier transform algorithm frequency estimation repetitive control disturbance rejection

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Method for estimating the central frequency of phase-coded radar signals

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IET SIGNAL PROCESSING 2016年第9期10卷 1073-1081页

作者： Yildirim, Alper TUBITAK BILGEM ILTAREN Ankara Turkey

The authors analyse radar carrier frequency estimation errors in digital electronic support measures receivers. They assume that the received signal is phase-coded, real-valued and embedded in white Gaussian noise. The corresponding Cramer-Rao lower bound (CRLB) for the frequency estimation is derived and formulated. The performance degradation can be significant when just a single traditional fast fourier transform (FFT) algorithm used to estimate the central frequency of a phase-coded signal, where the spectrum is wide and distributes across many frequency bins. In this study, they assume that the FFT magnitude response of the received signal can be approximated by a raised Gaussian-shaped function. The corresponding Gaussian function fitting (GFF) estimator is proposed as a peak frequency estimation technique. Typical FFT-based frequency estimation process is simulated and the performance of the GFF estimator is compared with that of the most commonly used peak estimators: namely, with the maximum point (MAX) and the spline interpolation (INT). GFF estimator performance is also compared with a K-means-based peak estimator. With extensive set of simulations for different code lengths, they demonstrate that the proposed technique significantly reduces carrier (central) frequency estimation errors while illustrating CRLB within the figure.

关键词： frequency estimation radar signal processing phase coding Gaussian noise white noise fast fourier transforms Gaussian processes interpolation central frequency estimation method phase-coded radar signals radar carrier frequency estimation error analysis digital electronic receivers white Gaussian noise Cramer-Rao lower bound CRLB performance degradation fast fourier transform algorithm frequency bins raised Gaussian-shaped function peak frequency estimation technique FFT-based frequency estimation process GFF estimator spline interpolation maximum point K-means-based peak estimator Gaussian function fitting estimator

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Frequency-domain weighted non-linear least-squares estimation of continuous-time, time-varying systems

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IET CONTROL THEORY AND APPLICATIONS 2011年第7期5卷 923-933页

作者： Lataire, J. Pintelon, R. Vrije Univ Brussel Dept ELEC Fundamental Elect & Instrumentat B-1050 Brussels Belgium

A frequency-domain least-squares estimator is presented for identifying linear, continuous-time, time-varying dynamical systems. The model considered is a linear, ordinary differential equation whose coefficients vary as polynomials in time. A frequency-domain approach is used, thus allowing the user to determine easily the frequency band(s) of interest. It is shown that the bias errors because of windowing and sampling the continuous-time signals can be modelled by a polynomial function of the frequency. The regression matrices of the estimators are shown to be very efficiently computed using the fast fourier transform algorithm and its inverse. The total least-squares, generalised total least-squares and weighted, non-linear least-squares estimators are constructed. The latter two are shown to be consistent. The estimators are illustrated on simulation and measurement data.

关键词： Signal processing theory Other topics in statistics linear differential equations ordinary differential equation time-varying systems continuous-time signals frequency-domain weighted nonlinear least-squares estimation Time-varying control systems Control system analysis and synthesis methods Integral transforms Nonlinear control systems fast fourier transform algorithm matrix algebra linear systems regression matrices continuous-time systems Algebra polynomial function windowing time-varying dynamical systems Mathematical analysis continuous time systems nonlinear dynamical systems regression analysis frequency-domain analysis signal sampling Simulation, modelling and identification nonlinear estimation fast fourier transforms parameter estimation

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Joint ML time-frequency synchronisation and channel estimation algorithm for MIMO-OFDM systems

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IET CIRCUITS DEVICES & SYSTEMS 2008年第1期2卷 103-111页

作者： Saemi, A. Meghdadi, V. Cances, J. -P. Zahabi, M. R. Univ Limoges ENSIL F-87000 Limoges France

The maximum-likelihood (ML) time-frequency synchronisation algorithm combined with channel estimation for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems in frequency selective fading channels is addressed. In the proposed algorithm, the authors use two steps to maximise an ML metric to obtain first the frequency offset and then timing. A fast fourier transform algorithm is used to estimate the frequency offset. Using these two estimates, the channel is identified. A simple iterative algorithm is proposed to improve the frequency offset estimation. The performance of the proposed synchronisation approach, in terms of timing failure probability and mean square error of the estimated frequency offset and bit error rate, is compared with others in the literature. Comparison of simulation results with the Cramer-Rao lower bound clearly illustrates the accuracy of the proposed algorithm, which outperforms the state-of-the-art synchroniser devices in the open literature.

关键词： iterative methods OFDM modulation mean square error method fading channels frequency selective fading channel synchronisation channel estimation algorithm MIMO systems maximum likelihood estimation fast fourier transforms time-frequency analysis channel estimation mean square error methods timing failure probability Cramer-Rao lower bound joint maximum likelihood time-frequency synchronisation multiple input multiple output-orthogonal frequency division multiplexing MIMO-OFDM system probability fast fourier transform algorithm iterative algorithm frequency offset estimation

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