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Method Based on Sparse Signal Decomposition for Harmonic and Inter-harmonic Analysis of Power System

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2017年第2期12卷 559-568页

作者： Chen, Lei Zheng, Dezhong Chen, Shuang Han, Baoru Northeast Petr Univ Dept Elect & Informat Engn Qinhuangdao Peoples R China Yanshan Univ Sch Elect Engn Qinhuangdao Peoples R China Hebei Normal Univ Sci & Technol Sch Math & Informat Technol Qinhuangdao Peoples R China Hainan Software Profess Inst Qionghai Hainan Peoples R China

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/interharmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

关键词： matching pursuit algorithm Harmonic Inter-harmonic Sinusoids dictionary Fast Fourier Transform (FFT) Sparse decomposition Optimal computation

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Signal filtering technique to remove Doppler clutter caused by wind turbines

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MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2012年第6期54卷 1455-1460页

作者： Naqvi, Aale Ling, Hao Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA

We construct a physics-based basis to model the radar backscattering from a wind turbine. This basis is used in conjunction with the matching pursuit algorithm to iteratively remove the Doppler clutter due to wind turbines. The algorithm is tested using radar return generated using the high-frequency electromagnetic simulation code Ahilo. It is shown that the presence of multiple turbines overwhelms the return from a weak moving target. However, the target is revealed once the filtering algorithm is applied. (C) 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:14551460, 2012;View this article online at ***. DOI 10.1002/mop.26819

关键词： wind turbine backscattering doppler clutter matching pursuit algorithm signal filtering

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On the methodological unification in electroencephalography

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BIOMEDICAL ENGINEERING ONLINE 2005年第1期4卷 1-9页

作者： Durka, Piotr J. Warsaw Univ Inst Expt Phys Ul Hoza 69 PL-00681 Warsaw Poland

Background: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. Methods: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. Results: Four lemmas and three conjectures support the following conclusion. Conclusion: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications.

关键词： matching pursuit Sleep Spindle Signal Processing Method Gabor Function matching pursuit algorithm

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A Fast and Robust Method for Estimating the Parameters of Ground Penetrating Radar Waves of Concrete Structures

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RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING 2023年第3期59卷 381-391页

作者： Kemache, Nadjib Hacib, Tarik Grimes, Morad Mai, Tien Chin Sbartai, Zoubir Mehdi Univ Mohamed Seddik Benyahia NDT Lab Jijel Algeria Univ Bordeaux Dept I2M GCE Lab Bordeaux France

The received signals in ground penetrating radar (GPR) techniques contain very valuable information on the size and orientation of the reflectors as well as the properties of the propagation path of the electromagnetic wave. Sometimes, these signals contain many overlapping reflected echoes due to the complexity of the studied geometry. Accurate estimation of these echoes is essential for the non-destructive evaluation of reinforced concrete structures. In this study, the matching pursuit (MP) algorithm is used to decompose the GPR signal into multiple echoes. The selection of the appropriate atoms is done by teaching learning based optimization (TLBO) algorithms which, at the same time, change five parameters (bandwidth, arrival time, center frequency, amplitude and phase), until a good representation of the original GPR signal is achieved. The effectiveness of the proposed method is tested using both synthetic signals generated from a gprMax simulation program, and a real data collected on a concrete slab specimen at different offset.

关键词： nondestructive evaluation ground penetrating radar matching pursuit algorithm teaching learning based optimization algorithms gprMax velocity estimation

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Doppler distortion removal based on Dopplerlet transform and re-sampling for wayside fault diagnosis of train bearings

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2021年第17期235卷 3407-3423页

作者： Zhang, Ao Shen, Changqing He, Qingbo Hu, Fei Liu, Fang Kong, Fanrang Sichuan Inst Aerosp Syst Engn Gen Dept Chengdu Peoples R China Univ Sci & Technol China Dept Precis Machinery & Precis Instrumentat Hefei Peoples R China Soochow Univ Sch Rail Transportat 8 Jixue Rd Suzhou Jiangsu Peoples R China

In wayside fault diagnosis of train bearings, the phenomenon of Doppler distortion in the acoustic signal of moving acoustic source acquired with a microphone leads to the difficulty for signal analysis. In this paper, a new method based on Dopplerlet transform and re-sampling is proposed to remove the Doppler distortion, and applied in the fault diagnosis of train bearings. Firstly, search the parameters space to find the primary functions-Dopplerlet atoms. According to the Morse acoustic theory and Doppler effect, the instantaneous frequency of the Dopplerlet atom which we choose to remove Doppler distortion of the corresponding acoustic source can be acquired. Then, the re-sampling sequence can be established as the re-sampling vector in time domain. Through the resample, the Doppler distortion effect can be removed. Finally, simulations and experiments with practical acoustic signals of train bearings with a defect on the outer race and the inner race are carried out, and the results verified the effectiveness of this method. Comparing with the other methods of Doppler distortion removal, this method works without measuring the motion parameters in advance, and is quite robust to noise. Meanwhile, this method has the potential to eliminate the Doppler distortion of original signal with multiple sources.

关键词： Doppler distortion Dopplerlet transform matching pursuit algorithm re-sampling train bearing fault diagnosis

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Grouping and Selecting Singular Spectrum Analysis Components for Denoising Via Empirical Mode Decomposition Approach

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2019年第1期38卷 356-370页

作者： Lin, Peiru Kuang, Weichao Liu, Yuwei Ling, Bingo Wing-Kuen Guangdong Univ Technol Sch Informat Engn Guangzhou 510006 Guangdong Peoples R China

This paper proposes a threshold-free method for grouping and selecting the singular spectrum analysis (SSA) components for performing the signal denoising via the empirical mode decomposition (EMD) approach. First, the total number of the groups of the SSA components is selected to be the same as the total number of the intrinsic mode functions (IMFs) of the signal. The SSA components are assigned to the group where the absolute correlation coefficient between the IMF and the SSA component is the highest. This grouping method is implemented using the matching pursuit algorithm. Then, the groups of the SSA components are selected based on the selection criterion used in an existing EMD denoising method. As the EMD denoising approach is a time-domain approach and the SSA components are represented in the transformed domain, our proposed method exploits both the time-domain and the transformed-domain information for performing the denoising. Computer numerical simulation results show that the signal-to-noise ratios of common practical signals denoised by our proposed method are higher than those denoised by the existing methods.

关键词： Singular spectrum analysis Empirical mode decomposition Grouping Denoising matching pursuit algorithm

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Application of matching pursuit Based Method to Identify Sources of Time-Vary Magnetic Field

Application of Matching Pursuit Based Method to Identify Sou...

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IEEE International Conference on Environment and Electrical Engineering

作者： Beata Palczynska Department of Marine Telecommunications Gdynia Maritime University Gdynia Poland

ISBN: (纸本)9781509023219

The way of identification of time-vary signals representing non-stationary magnetic field induction was proposed. It is constructed on the adaptive signal decomposition, using the matching pursuit algorithm (MP). The problem of the selection of the optimal number of elementary functions in the MP algorithm was considered. The proposed method for source identification consists of several steps. Its basic principle is to decompose measuring time-waveform into the linear expansion of chirplet atoms. Next, analysis of the obtained matrix containing the parameters of each detected Gaussian chirp is carried out. The distinction of the dominant components in the examined signal is performed on the basis of the previous analysis. Then the Wigner-Ville distribution (WVD) of each chosen atom is calculated to estimate the joint quadratic time-frequency transform of the analyzed signal. The extraction of the time -frequency structures on the plane of the spectrogram allows for the identification of the sources of the time-vary magnetic field occurring in a measurement environment. The method has been tested using real measurements of time-vary magnetic field emissions onboard of the ship.

关键词： sources of a magnetic field matching pursuit algorithm

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Building surrogates with overcomplete bases in computer experiments with applications to bistable laser diodes

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IIE TRANSACTIONS 2011年第1期43卷 39-53页

作者： Chen, Ray-Bing Wang, Weichung Wu, C. F. Jeff Natl Taiwan Univ Dept Math Taipei 10617 Taiwan Natl Univ Kaohsiung Inst Stat Kaohsiung Taiwan Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

It is known that regular kriging models do not perform well in fitting and predicting computer experiments with complicated response surfaces. One such experiment arises in the dynamical system of bistable laser diodes for secure optical communications. The problem is challenging because the response surface is complicated, there are multiple solutions, and function evaluations are computationally expensive. Motivated by this problem, this article iteratively constructs surrogates for the complicated surface by using an overcomplete basis set. Application to the laser diodes problem shows that the proposed algorithms can solve the target problem by quickly capturing the trend of the response surface and efficiently guiding the search of desired solutions quickly. Performances and comparisons of the proposed algorithms and Gaussian process-based surrogate algorithms are presented to demonstrate the advantages of these methods.

关键词： matching pursuit algorithm Garbor functions Gaussian process kriging uniform design

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Faulty feeder detection based on mixed atom dictionary and energy spectrum energy for distribution network

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第3期12卷 596-606页

作者： Wang, Xiaowei Song, Guobing Chang, Zhongxue Luo, Juan Gao, Jie Wei, Xiangxiang Wei, Yanfang Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China Henan Polytech Univ Sch Elect Engn & Automat Jiaozuo 454000 Peoples R China Shanghai Univ Elect Power Coll Automat Engn Shanghai 200090 Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China

The authors proposed a faulty feeder detection method based on the combination of feature extraction and information entropy in the distribution network. Firstly, analysed the characteristics of a transient zero-sequence current (TZSC) waveform, and constructed a mixed atom dictionary by a cosine packet and a wavelet, and then, the authors adopted the matching pursuit algorithm to extract characteristic atoms of each feeder. For energy aspects, used energy spectrum entropy (ESE) to measure;for the waveform similarity, calculated correlation coefficient between characteristic atoms and the original TZSC, then, the authors obtained the ESE of modified atoms and integrated atoms, respectively. In a faulty feeder detection criterion, calculated the difference value between the maximum and the minimum of integrated atoms ESE, and compared the value and the threshold. If the value is smaller than the threshold, the bus is judged as a faulty feeder, otherwise, the maximum corresponding to the feeder is judged as the faulty feeder. Simulation and field tests show that the method can accurately judge the faulty feeder, and its accuracy is immune to transition resistance, iteration numbers, data window length, different compensation degrees, capacitor switching, and unbalanced load.

关键词： power distribution faults feature extraction entropy wavelet transforms faulty feeder detection mixed atom dictionary energy spectrum energy distribution network feature extraction information entropy transient zero-sequence current waveform TZSC waveform cosine packet matching pursuit algorithm characteristic atom extraction used energy spectrum entropy ESE waveform similarity correlation coefficient faulty feeder detection criterion transition resistance iteration numbers data window length capacitor switching unbalanced load compensation degrees

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Ultrasonic Characterization Method of Carbon Nanotubes Orientation Using Sparse Representation

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RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING 2022年第2期58卷 96-107页

作者： Hu, Hongwei Tian, Jia Zeng, Huijie Yu, Xiaofeng Wang, Xianghong Changsha Univ Sci & Technol Coll Automot & Mech Engn Changsha 410114 Hunan Peoples R China Hunan Prov Key Lab Intelligent Mfg Technol High P Changsha 410114 Hunan Peoples R China

Carbon nanotubes orientation has a significant impact on the performance of carbon nanotubes/epoxy resin (CNTs/EP) composite materials. The ultrasonic velocity is sensitive to the degree of carbon nanotubes orientation. However, the time-of-flight (TOF) is difficulty to accurately measured due to ultrasonic echo aliasing and waveform distortion occurred in the thin CNTs/EP composite material. Therefore, the ultrasonic characterization method of carbon nanotubes orientation based on the sparse representation is studied in this paper. Two groups of CNTs/EP specimens are taken as research objects. Firstly, the dictionary is constructed by Gabor function, and the matching degree between dictionary and ultrasonic echo signals is researched. Then, the matching pursuit (MP) algorithm is used to solve the problem of dictionary redundancy and obtain the best matching atom;the signal reconstruction is completed and ultrasonic TOF of carbon nanotubes is extracted more accurately. Finally, a carbon nanotubes orientation prediction model based on the sparse representation is established. The result shows that the Gabor dictionary has good similarity with ultrasonic echo signals and the root mean square relative error is 0.0147. The degree of carbon nanotubes orientation and ultrasonic velocity have positive correlation. The carbon nanotubes orientation prediction model relative error is 5.58%. This paper has provided an effective method to characterize the degree of carbon nanotubes orientation.

关键词： orientation prediction ultrasonic velocity measurement sparse representation matching pursuit algorithm carbon nanotubes

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