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A fault state detection method for DC charging pile charging module based on minimum fourth-order moments adaptive filtering algorithm

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JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2024年第2期17卷

作者： Zhang, Yongmin Bao, Jihua Li, Jingjing Cai, Yongmei Yu, Wenjin Guo, Yinshan Xu, Feng State Grid Qinghai Elect Power Co Mkt Serv Ctr Elect Energy Measurement Equipment Verificat & Tes Xining 810000 Qinghai Peoples R China Zhejiang Hanpu Elect Power Technol Co Ltd Jiaxing 314300 Zhejiang Peoples R China

It is necessary to accurately judge the fault state of the charging module of DC charging pile in order to ensure the safe and reliable operation of DC charging pile. However, the fault signal processing of the fault detection method is poor, resulting in low fault detection accuracy. Therefore, a fault state detection method of DC charging pile based on the least fourth moment adaptive filtering algorithm is proposed. This method is based on the electrical structure of DC charging pile. The minimum fourth moment adaptive filtering algorithm is selected to filter the operating signal of the charging module after analyzing the fault signal characteristics of the charging module. The Lagrange algorithm is optimized to obtain the minimum fourth moment adaptive filtering of the operating signal of the charging module in the process. The shape and distribution characteristics of the running signal are analyzed accurately. The filtered operating signal is input into the improved one-dimensional convolutional neural network and bidirectional gated cyclic unit detection model, fault features of the charging module are extracted, and then support vector machine is introduced to further optimize the fault detection method. The fault state detection results of the charging module are output by using support vector machine as a model classifier and combining fault features. The test results show that the proposed method can effectively process different fault signals of charging modules of DC charging pile, determine the characteristic value distribution of each feature, and reliably detect the fault state of 10 charging modules. Its signal amplitude is only between [-0.1,1.0]m & sdot;s-1 after the fault signal is processed by this method, the number of error detection is only 2 times, the detection time is only 0.95s, and the maximum CPU ratio is only 26.7%. Moreover, the number of detected faults is consistent with the actual number under multiple concurrent faults, and the f

关键词： Minimum fourth-order moments adaptive filtering algorithm DC charging pile Charging module Fault state detection Feature extraction

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Speech enhancement using backward adaptive filtering algorithm: Variable step-sizes approaches

Speech enhancement using backward adaptive filtering algorit...

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International Conference on Control, Engineering & Information Technology

作者： Redha Bendoumia Mohamed Djendi University of Blida 1 Signal Processing and Image Laboratory (LATSI)

ISBN: (纸本)9781479982134

This paper addresses the problem of speech quality enhancement and acoustic noise reduction by adaptive blind source separation algorithms. Recently, several two-channel forward-and-backward structures have been proposed for acoustic noise reduction based on normalized least-mean-square (NLMS) algorithm. The backward structure presents the good performance compared with its direct version (forward). But the main drawback of the backward algorithm is its poor performance in steady state regime when the fixed step-size is selected large. In this paper, we propose two new versions of this algorithm by introducing simple variable step-sizes approaches, which allow improving both the steady state values. The proposed modifications are based on efficient estimation of the optimal step-sizes of the cross-coupling filters. To confirm the good performance of the proposed variable step-size algorithms, we have carried out several simulations in very noisy situation.

关键词： Variable step-size Speech quality Output SNR adaptive filtering algorithm Backward structure

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Design of adaptive filtering algorithm and Its Application in Chaotic Echo Cancellation

Design of Adaptive Filtering Algorithm and Its Application i...

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The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Bo Yang Jian Feng School of Electronic and Information Engineering Southwest University Chongqing 400715 China Department of Cardiology First Affiliated Hospital Luzhou Medical College Luzhou 646000 China

An adaptive filtering algorithm is designed in this study, and the convergence of the algorithm is analyzed. The new algorithm is used to cancel echo in the chaotic communication systems experiencing echo channels. The results of computer simulation indicate that the new algorithm has faster convergence speed and higher accuracy of computation than that of the old one. In addition, the new algorithm is more stable in the case of low signal to noise ratio (SNR) .

关键词： Echo Cancellation adaptive filtering algorithm Chaos Signal to Noise Ratio

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Blind 2-microphone acoustic noise reduction algorithms using efficient variable step-size adapted by minimizing the intercorrelation function

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ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING 2025年第2期123卷 1-18页

作者： Bendoumia, Redha Blida 1 Univ Dept Elect DIC Lab Blida Algeria

Recent advancements in adaptive noise signal reduction have utilized 2-microphones adaptive algorithms. Specifically, the normalized form of least-mean-square algorithm (NLMS) with fixed-step-size parameters (FS) has been combined with direct-and-recursive structures of source separation. Compared to conventional one-microphone methods, these combinations provide superior speech quality. However, the main limitation of these 2-microphones adapting algorithms (Direct combination: Forward NLMS and Recursive combination: Backward NLMS) lies in their poor steady state regime with large FS value, while small step-sizes values result a slow speed of convergence. To address these issues, we propose a new variable step-size (VS) approach in this study, based on minimizing the intercorrelation function in the time domain for the basic FNLMS and BNLMS algorithms. Our approach is proposed exactly to determine an optimal value of VS parameters by minimizing the intercorrelation between the enhanced signal and the noisy microphone signals. These methods improve steady state values and convergence speed at the same time. The proposed 2-microphones adapting algorithms were evaluated through simulations conducted in high-noise environments, using the system of mismatch criterion and estimation of output segmental signal-to-noise ratio ones. The comparative simulations results confirmed that our algorithms outperform FS algorithms in terms of steady state values and convergence speed.

关键词： Variable step-size Intercorrelation function Output SegSNR adaptive filtering algorithm Speech quality

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A Rayleigh weighted variable step-size sign algorithm for robust adaptive filtering in impulsive noises

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DIGITAL SIGNAL PROCESSING 2017年 68卷 102-111页

作者： Wang, Weihua Zhao, Jihong Qu, Hua Xu, Xiguang Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China

The sign algorithm with a fixed step-size is incapable of addressing the conflicting requirements between fast convergence speed and low steady-state misadjustments. In order to deal with this problem, a Rayleigh weighted gradient vector based variable step-size sign algorithm is proposed in this paper. In the new algorithm, the variable step-size is updated by the squared norm of a Rayleigh weighted sign gradient vector. The proposed algorithm can improve the convergence speed and tracking capability while maintaining the similar steady-state misadjustments in the presence of impulsive noises. A complex valued energy conservation relation based convergence analysis is carried out to evaluate the convergence performance of the new algorithm. Simulation results are presented to verify the theoretical analysis and to demonstrate the desirable performance of the proposed algorithm. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Gradient vector Variable step-size Sign algorithm adaptive filtering algorithm

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Variable Step-Size LMS algorithm Based on Variational Versoria Function and Variational Gaussian Function

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INTERNATIONAL JOURNAL OF adaptive CONTROL AND SIGNAL PROCESSING 2025年第4期39卷 709-723页

作者： Zhao, Baoshui Xiao, Yancai Shen, Haikuo Zhi, Shaodan Beijing Jiaotong Univ Sch Mech Elect & Control Engn Beijing Peoples R China

Aiming at the noise interference problem in wing fatigue tests, this paper improves the traditional LMS algorithm using the variational Versoria function and the variational Gaussian function. Additionally, this paper proposes a variable step-size LMS (VSS-LMS) filtering algorithm based on the composite function (CVSS-LMS). The composite function combines the variational Versoria function and the variational Gaussian function to describe the nonlinear relationship between the iteration step size and the error. To adapt to environments with different signal-to-noise ratios, the algorithm replaces the fixed parameters with a combination of current and previous errors, thus enabling adaptive adjustment of the parameters. Moreover, a step-size dynamic constraint rule is proposed to further improve the stability of the algorithm. The algorithm is normalized using a combination of the cumulative sum of error squares, the mean square error (MSE), and the power of the input signal, which reduces the sensitivity to the input signal amplitude. The above parts finally constitute the adaptive CVSS-LMS (ACVSS-LMS) filtering algorithm. The convergence of the ACVSS-LMS algorithm is verified through theoretical derivation. The ACVSS-LMS algorithm is experimentally analyzed by using the simulation data generated by MATLAB and the actual data collected from the wing fatigue test, and the results show that the ACVSS-LMS algorithm proposed in this paper has a faster convergence speed and lower steady-state error compared to other algorithms.

关键词： adaptive filtering algorithm fatigue testing of wings Gaussian function Versoria function VSS-LMS algorithm

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Bias-Compensated PNLMS algorithm With Multi-Segment Function for Noisy Input

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IEEE ACCESS 2025年 13卷 43741-43748页

作者： Jin, Zhan Yang, Zhonghao Li, Qianjin Ma, Linfeng Qiqihar Univ Coll Commun & Elect Engn Qiqihar 161006 Peoples R China

To address the estimation bias caused by ignoring input noise in existing adaptive filtering algorithms, a new proportionate-type algorithm is proposed in this paper. First, a bias-compensation term is derived based on an unbiased criterion when constructing the cost function of the algorithm to achieve unbiased estimation. Next, this bias-compensation term is integrated into the mu-law PNLMS (MPNLMS) algorithm to design the bias-compensated PNLMS combined with the multi-segment function (BC-MS-PNLMS) algorithm. Simulation results for echo paths and underwater channels demonstrate that the BC-MS-PNLMS algorithm outperforms other sparse-type algorithms in sparse experimental environments.

关键词： adaptive filtering algorithm proportional NLMS algorithm MPNLMS algorithm unbiased estimation multi-segment function adaptive filtering algorithm proportional NLMS algorithm MPNLMS algorithm unbiased estimation multi-segment function

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An Improved Proportional Normalization Least Mean p-Power algorithm for adaptive filtering

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第11期42卷 6951-6965页

作者： Cai, Banggui Wang, Biao Zhu, Boyu Zhu, Yunan Jiangsu Univ Sci & Technol Ocean Coll Changshan Rd Zhenjiang 212100 Jiangsu Peoples R China Sichuan Vocat Coll Hlth & Rehabil Deming Rd Zigong 643000 Sichuan Peoples R China

Under a stable distribution impulse noise environment, the least mean p-power algorithm (LMP) cannot handle the instability of the algorithm well, due to the large amplitude of the input signal and the large number of useless small weight coefficients in the sparse channel, which delay the convergence speed of the algorithm. In this paper, we develop a new adaptive filtering algorithm, named the proportional normalization least mean p-power (PNLMP) adaptive filtering algorithm. We first introduce a step size control matrix to improve the overall convergence speed and convergence accuracy of the algorithm. Next, to reduce the influence of a large impulse response on the LMP algorithm, a high-order tongue-line function about error is introduced in the normalization processing. Finally, we extend the tongue-line function to ensure that the cost function can also switch freely between V-shaped and M-shaped. This new algorithm overcomes the problem that the traditional LMP algorithm is only applicable to a specific environment and solves the problem of slow convergence speed and low convergence accuracy. Under a stable distribution impulse noise environment, the simulations show that the PNLMP algorithm can improve the convergence speed and stronger system tracking capability compared with existing algorithms, overcoming the problems of slow overall convergence and low convergence accuracy in the traditional algorithm.

关键词： & alpha stable distribution Proportional normalization adaptive filtering algorithm Sigmoid function Least mean p-power (LMP)

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Accelerated Euclidean Direction Search algorithm and related relaxation schemes for solving adaptive filtering problem

Accelerated Euclidean Direction Search algorithm and related...

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6th International Conference on Information, Communications and Signal Processing

作者： Ahmad, Noor Atinah Univ Sains Malaysia Sch Math Sci George Town 11800 Malaysia

ISBN: (纸本)9781424409822

The Euclidean Direction Search (EDS) method is a fairly recent algorithm for solving adaptive filtering problem. The method is a direction set based algorithm, where line searches are perform along euclidean directions in a cyclicmanner in order to search for the minimum of the cost function of the problem. In this paper, the EDS algorithm is described in terms of its relationship with relaxation schemes for solving linear system of equations such as the Gauss-Seidel and Jacobi iterative methods. An acceleration parameter, which is commonly used for such methods, are introduced here and its optimum value derived for uncorrelated input signals with mean 0. Verification of optimum acceleration parameter is demonsrated in the framework of an adaptive system modeling problem.

关键词： adaptive filtering algorithm adaptive least squares problem

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New adaptive filtering algorithms based on an orthogonal projection of gradient vectors

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IEEE SIGNAL PROCESSING LETTERS 2000年第11期7卷 314-316页

作者： Lim, JS Ajou Univ Grad Sch Informat & Commun Suwon 442749 South Korea

In this letter, we propose tno algorithms for adaptive finite impulse response (FIR) filters as variants of the filtered gradient adaptive (FGA) algorithm. The proposed algorithms are formulated from the FGA by introducing an orthogonal constraint between the direction vectors, The algorithms employ the forgetting factor optimized on a sample-by-sample basis so that the direction vector is orthogonal to the previous direction vector, while the FGA algorithm uses a fixed one. It is shown through the computer simulations that the proposed algorithms are superior in terms of convergence and tracking capability to the FGA algorithm.

关键词： adaptive filtering algorithm gradient vectors orthogonal projection

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