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A Novel Rolling Bearing Vibration Impulsive Signals Detection Approach Based on Dictionary Learning

IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1188-1198页

作者： Chuan Sun Hongpeng Yin Yanxia Li Yi Chai School of Big Data&Software Engineering Chongqing UniversityChongqing 401331China Key Laboratory of Complex System Safety and Control Ministry of EducationChongqing UniversityChongqing 400044China

The localized faults of rolling bearings can be diagnosed by its vibration impulsive ***,it is always a challenge to extract the impulsive feature under background noise and non-stationary *** paper investigates impulsive signals detection of a single-point defect rolling bearing and presents a novel data-driven detection approach based on dictionary *** overcome the effects harmonic and noise components,we propose an autoregressive-minimum entropy deconvolution model to separate harmonic and deconvolve the effect of the transmission *** address the shortcomings of conventional sparse representation under the changeable operation environment,we propose an approach that combines K-clustering with singular value decomposition(K-SVD)and split-Bregman to extract impulsive components *** experiments on synthetic signals and real run-to-failure signals,the excellent performance for different impulsive signals detection verifies the effectiveness and robustness of the proposed ***,a comparison with the state-of-the-art methods is illustrated,which shows that the proposed approach can provide more accurate detected impulsive signals.

关键词： Dictionary learning impulsive signals detection Kclustering with singular value decomposition(K-SVD) minimum entropy deconvolution rolling bearing signal processing

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Biologically inspired information integration pooling module of spiking neural networks for rolling bearing fault diagnosis

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Expert systems with Applications 2025年 286卷

作者： Shi, Mingfei Jiang, Feng Li, Yongbo Du, Lin MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China Unmanned System Research Institute Northwestern Polytechnical University Xi'an710072 China School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'an710072 China School of Aeronautics Northwestern Polytechnical University Xi'an710072 China School of Mathematics and Statics Northwestern Polytechnical University Xi'an710072 China MOE Key Laboratory for Complexity Science in Aerospace Northwestern Polytechnical University Xi'an710072 China

Rolling bearings constitute critical components in mechanical systems, and their effective fault diagnosis plays a vital role in ensuring operational safety and reliability. Despite substantial advancements in diagnostic methodologies, achieving high-precision, low-latency fault detection in large-scale rolling bearing datasets remains a persistent challenge. Artificial neural networks to spiking neural networks (ANN-to-SNN) conversion algorithms offer promising solutions for reducing computational costs and hardware adaptation barriers compared to conventional approaches. However, inherent information degradation during conversion processes has been demonstrated to significantly undermine model performance in terms of accuracy, stability, and interpretability. To overcome these limitations, we propose IIPooling, a novel Information-Integration biological neural mechanism-inspired Pooling module designed to enhance global structural feature extraction. The proposed framework incorporates three core neurobiological information processing principles: (1) promotion, (2) lateral inhibition, and (3) longitudinal inhibition, effectively simulating biological neuronal spiking patterns while optimally utilizing ANN activation characteristics. Additionally, we develop two adaptive learning mechanisms — Surrogate Gradient Adaptive Learning and Spiking Spatiotemporal Adaptive Learning — to implement negative feedback mechanism and adaptive parameter adjustment, thereby improving cross-conditional generalization capabilities. Comprehensive evaluations conducted on five bearing datasets (CWRU: DE/FE, PU, and Lab-collected: 6025/N205EW) demonstrate superior performance across four metrics (ACC, AUC, AUPRC, Mean-ACC). Our method achieves state-of-the-art results, notably attaining ACC values of 0.959 (CWRU-DE) and 0.861 (Lab-N205EW) in IIPooling-ST configurations, confirming its effectiveness for real-time, high-accuracy fault detection in complex operational environments. © 2025

关键词： Failure rate

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The DRTS-Net Framework: Enhanced Probabilistic Health Perception for Wind Turbine Bearings Under complex Operating Conditions With Improved Interpretability

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Yang, Tongguang Li, Guanchen Huo, Jinzhao Li, Xiaoyong Zhou, Xianwen Han, Qingkai Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Johns Hopkins University Department of Mechanical Engineering BaltimoreMD21218 United States Foshan University School of Mechatronic Engineering and Automation Foshan528225 China SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety MOE Key Laboratory of Theoretical Chemistry of Environment South China Normal University School of Environment Guangzhou510006 China SCNU Qingyuan Institute of Science and Technology Innovation Company Ltd. Qingyuan511517 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang110819 China

Health perception in mechanical systems is a crucial aspect of prognostics and health management (PHM). Deep learning models have been successfully applied to health perception in wind turbine bearings. However, due to the time-varying, redundant, and noisy characteristics of time-series data representing bearing wear, existing models face significant challenges, particularly in terms of generalization and interpretability. Moreover, although most current models have provided health perceptions, they overlook the strong stochastic nature of bearing degradation data, and thus fail to deliver reliable predictions of uncertainty information. To address these technical challenges, this study introduces a novel Deep residual temporal-spatial framework (DRTS-Net) for probabilistic health perception of wind turbine bearing wear states. This article creatively designs spatiotemporal information fusion module for extracting features from bearing degradation data. Inspired by improvements in residual network structures, the DRTS-Net integrates an attention mechanism and a soft thresholding mechanism from the deep residual shrinkage network to optimize the feature extraction process. This integration aims to mitigate the interference from minor redundant features in the degradation data. The framework incorporates Gaussian process regression in the output layer to yield the probability distribution of single-health perception values for bearing features. A comparative study was conducted using the same bearing health state dataset against current mainstream deep learning methods for bearing health assessment. Results demonstrate that the proposed DRTS-Net achieves superior performance in high-precision health perception, high-reliability probabilistic health perception. © 1963-2012 IEEE.

关键词： Stochastic systems

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control method on serial type pump-valve coordinated electro-hydraulic servo system

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Journal of Beijing Institute of Technology 2016年第1期25卷 100-107页

作者：谢文汪首坤王军政吴建 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to compromise the conflicts between control accuracy and system efficiency of conventional electro-hydraulic servo systems,a novel pump-valve coordinated electro-hydraulic servo system was designed and a corresponding control strategy was *** system was constituted of a pumpcontrolled part and a valve-controlled part,the pump controlled part is used to adjust the flow rate of oil source and the valve controlled part is used to complete the position tracking control of the hydraulic *** on the system characteristics,a load flow grey prediction method was adopted in the pump controlled part to reduce the system overflow losses,and an adaptive robust control method was adopted in the valve controlled part to eliminate the effect of system nonlinearity and parametric uncertainties due to variable hydraulic parameters and system loads on the control *** experimental results validated that the adopted control strategy increased the system efficiency obviously with guaranteed high control accuracy.

关键词： pump-valve coordinated grey prediction adaptive robust control efficiency

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Adaptive robust control for electrical cylinder with friction compensation usingmodified LuGre model

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Journal of Beijing Institute of Technology 2014年第3期23卷 358-367页

作者：郝仁剑王军政赵江波汪首坤 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

The position tracking control problem of an electrical cylinder in the presence of dynamic friction nonlinearities in its transmission process is addressed in this paper. First, a torque decou- piing approach is proposed to formulate the dynamic model. Secondly, to compensate the friction in the case of servo motion, a modified LuGre model is designed to make a continuous transition be- tween a static model at a high speed and a LuGre model at a low speed to avoid instability due to dis- cretization with a finite sampling rate. To accelerate the speed of estimating time-varying parame- ters, a fast adaption law is proposed by designing an attraction domain around a rough value related to the load force. Finally, a discontinuous projection based adaptive robust controller is synthesized to effectively handle parametric uncertainties for ensuring a guaranteed robust performance. A Lya- punov stability analysis demonstrates that all signals including tracking errors have the guaranteed convergent and bounded performance. Extensive comparative simulations with sinusoidal and point- point tracks are obtained respectively in low and high speeds. The results show the effectiveness and the achievable control performance of the proposed control strategy.

关键词： adaptive robust electrical cylinder friction compensation LuGre model

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Line-element based nonlinear adaptive piecewise compensating correction for LVDT sensors

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Journal of Beijing Institute of Technology 2013年第4期22卷 497-503页

作者：王立鹏王军政赵江波吴江丰 Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology

In order to solve the linear variable differential transformer （LVDT） displacement sensor nonlinearity of overall range and extend its working range, a novel line-element based adaptively seg- menting method for piecewise compensating correction was proposed. According to the mechanical structure of LVDT, the output equation was calculated, and then the theoretic nonlinear source of output was analyzed. By the proposed line-element adaptive segmentation method, the nonlinear output of LVDT was divided into linear and nonlinear regions with a given threshold. Then the com- pensating correction function was designed for nonlinear parts employing polynomial regression tech- nique. The simulation of LVDT validates the feasibility of proposed scheme, and the results of cali- bration and testing experiments fully prove that the proposed method has higher accuracy than the state-of-art correction algorithms.

关键词： line element adaptively segment linear variable differential transformer （LVDT） non-linear compensation correction

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Optimal Tuning of Plant-Friendly PID controllers

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Journal of Beijing Institute of Technology 2010年第3期19卷 331-336页

作者：史大威王军政马立玲 Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

A plant-friendly proportional-integral-derivative （PID） controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as the weighted sum of the integral of squared time-weighted error and the integral of squared timeweighted derivative of the control variable with respect to set-point response,while the robustness of the system is guaranteed by constraints on gain and phase *** to the complex structure of the constraints,the problem is solved by genetic *** analysis show the proposed method could efficiently reduce the controller output variations while maintaining a short settling *** on the simulation results,iterative tuning rules for the weighting factor in the objective function are obtained,which allows efficient simple proportional-integral（PI） tuning formulae to be derived.

关键词： PID control plant-friendliness genetic algorithm constrained optimization

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Localization and mapping in urban area based on 3D point cloud of autonomous vehicles

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Journal of Beijing Institute of Technology 2016年第4期25卷 473-482页

作者：王美玲李玉杨毅朱昊刘彤 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping （SLAM） algorithm, which uses a VoxelGrid filter to down sample the point cloud data, with the combination of iterative closest points （ICP） algorithm and Gaussian model for particles updating, the matching between the local map and the global map to quantify particles＇ importance weight. The crude estimation by using ICP algorithm can find the high probability area of autonomous vehicles＇ poses, which would decrease particle numbers, increase algorithm speed and restrain particles＇ impoverishment. The calculation of particles＇ importance weight based on matching of attribute between grid maps is simple and practicable. Experiments carried out with the autonomous vehicle platform validate the effectiveness of our approaches.

关键词： simultaneous localization and mapping （SLAM） Rao-Blackwellized particle filter （ RB-PF） VoxelGrid filter ICP algorithm Gaussian model urban area

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Novel algorithm of gait planning of hydraulic quadruped robot to avoid foot slidingand reduce impingement

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Journal of Beijing Institute of Technology 2016年第1期25卷 91-99页

作者：马立玲杨超峰王立鹏王军政 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed in this ***,the foot trajectory is designated as the improved composite cycloid foot ***,the landing angle of each leg of the robot is controlled to satisfy friction cone to improve the stability performance of the *** with the controllable landing angle of quadruped robot and a geometry method,the kinematic equation is derived in this ***,agait planning method of quadruped robot is proposed,a dynamic co-simulation is done with ADAMS and MATLAB,and practical experiments are *** validity of the proposed algorithm is confirmed through the co-simulation and *** results show that the robot can avoid sliding,reduce impingement,and trot stably in trot gait.

关键词： landing angle gait planning foot trajectory friction cone sliding impingement

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Force-feedback based active compliant position control strategy for a hydraulic quadruped robot

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Journal of Beijing Institute of Technology 2015年第4期24卷 546-552页

作者：王立鹏王军政马立玲陈光荣杨超峰 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots＇ ability of walking on rough terrain is of great importance but is seldom achieved. Being compliant to external unperceived impacts is cru- cial since it is unavoidable that the slip, modeling errors and imprecise information of terrain will make planned trajectories to be followed with errors and unpredictable contacts. The impedance control gives an inspiration to realize an active compliance which allows the legged robots to follow reference trajectories and overcome external disturbances. In this paper, a novel impedance force/ position control scheme is presented, which is based on Cartesian force measurement of leg＇ s end effector for our hydraulic quadruped robot The simulation verifies the efficiency of the impedance model, and the experimental results at the end demonstrate the feasibility of the proposed control scheme.

关键词： active compliance impedance control force feedback contact force constrains space

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