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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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Adaptive Sliding Mode control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

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IEEE/CAA Journal of Automatica Sinica 2015年第1期2卷 94-101页

作者： Jingmei Zhang Changyin Sun Ruimin Zhang Chengshan Qian the Flight Control Research Center Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University the College of Information and Control Nanjing University of Information Science & Technology

Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances. © 2014 Chinese Association of Automation.

关键词： Airships Angular velocity Attitude control Backstepping control theory Design Functions Hypersonic aerodynamics Hypersonic vehicles Navigation Radial basis function networks Sliding mode control Uncertainty analysis Vehicles

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Continuous finite-time TSM control for electronic throttle system

Continuous finite-time TSM control for electronic throttle s...

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2019 Jiangsu Annual Conference on Automation, JACA 2019

作者： Agbaje, Oluwatoyin Timothy Li, Shihua Sun, Hao Zhang, Lu Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

This article examines the position tracking difficulties of the electronic throttle (ET) system and presents a continuous finite-time terminal sliding mode (TSM) control method. The development of this control method involves two procedures: (i) designing a global finite-time observer to estimate the derivative and higher order derivatives of the ET system output, and the total disturbances;and (ii) construction of a continuous finite-time TSM controller based on observer estimations, to ensure the realisation of fast finite-time convergence of system output with a comparatively smooth control action. Comprehensive stability proof, simulation study, and experimental implementation are provided to affirm the applicability of the proposed method. © 2019 Institution of engineering and Technology. All rights reserved.

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Convergence Analysis of Consensus based Distributed Filtering Algorithm in Sensor Networks 34

Convergence Analysis of Consensus based Distributed Filterin...

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第三十四届中国控制会议

作者： ZHANG Ya TIAN Yu-Ping CAI Jun School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education 73658 Army

ISBN: (纸本)9781467374439

This paper studies the distributed filtering problem of sensor networks, where a set of heterogeneous sensing nodes is required to estimate the state of a linear discrete-time dynamic system in a collaborative manner. Due to limited sensing range and communication constraints, just part of sensors can get observations of the process and a consensus based sub-optimal filtering algorithm is designed. The convergence properties of the estimation error covariance is further studied, and a necessary and sufficient convergence condition is provided based on LMIs. This condition shows that the convergence of the algorithm requires the target node in the extended topology of network is globally reachable and each sensing node is observable to the process. Simulation examples are given to illustrate the results.

关键词： Distributed filter,Sensor networks,Consensus,Convergence analysis,LMIs

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Towards an Esox lucius inspired multimodal robotic fish

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Science China(Information Sciences) 2015年第5期58卷 182-194页

作者： WU ZhengXing YU JunZhi SU ZongShuai TAN Min LI ZhenLong State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Electronic Information and Control Engineering Beijing University of Technology

In this paper, we further explore multimodal locomotion via an updated robotic fish model based on Esox lucius. Besides the improved actuation properties like higher torque servomotors and powerful electronics,the robotic fish has some innovative mechanical design to pursue diverse swimming modes and superior performance. Specifically, we introduced a ±50° yawing head joint that functions as the neck for enhancing turning ability. A pair of pectoral mechanisms with two DOFs per fin is constructed to achieve 3-D swimming and to enrich multiple pectoral motions. At the control level, an improved central pattern generator(CPG) model allowing for free adjustment of the phase relationship among outputs is employed to produce rhythmic signals of multimodal swimming. Extensive experiments were carried out to examine how characteristic parameters in CPGs including amplitude, frequency, and phase lag affect the swimming performance. As a result, the robotic fish successfully performed various locomotion actions such as forward swimming, backward swimming, turning, diving, surfacing, as well as three pectoral motions in the form of pitching, heaving, and *** found that small phase lag between oscillating joints which means large propulsive body wave length and undulation width could lead to a faster swimming in body and/or caudal fin(BCF) locomotion.

关键词： bio-inspired robot robotic fish CPG multimodal swimming motion control

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Coordinated Adaptive Flowfield Estimation for Second-Order Agents Formation Tracking Given Orbits 35

Coordinated Adaptive Flowfield Estimation for Second-Order A...

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第35届中国控制会议

作者： CHEN Yang-Yang TIAN Yu-Ping WANG Zan-Zan School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

ISBN: (纸本)9781509009107

This paper deals with cooperative estimation and control for second-order agents formation tracking a set of given orbit in an external flowfield,where only direction of flow inertial velocity is spatiotemporal and known.A novel coordinated adaptive estimator based on local neighbor-to-neighbor information is proposed to estimate the flow *** is shown that our previous geometric extension design,consensus and adaptive backstepping method can be combined together to construct the robust formation tracking controller under bidirectional *** theoretical result is proved by the numerical simulation.

关键词： Coordinated Adaptive Estimation Second-Order Agents Formation Tracking control

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Nonlinear Time-varying systems Identification Based on Multi-dimensional Taylor Network and Variable Forgetting Factor Recursive Least Squares Algorithm

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IFAC-PapersOnLine 2015年第11 11期48卷 1103-1107页

作者： Zhang, Jiao-Jun Yan, Hong-Sen School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

A novel method for nonlinear time-varying systems identification based on multi-dimensional Taylor network and variable forgetting factor recursive least squares algorithm is proposed. In this paper, the connection weight coefficients of multi-dimensional Taylor network are regarded as time-varying parameters, which are trained by the variable forgetting factor recursive least squares algorithm, to reflect the input-output change of nonlinear time-varying systems. Simulation results show that the method proposed in this paper is valid. © 2015

关键词： Time varying networks Identification (control systems) Least squares approximations Time varying systems Connection weights Input output Multi dimensional Nonlinear time varying systems Recursive least squares algorithms Time varying parameter Variable forgetting factors

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Evolutionary Self-Questioning Games with Local Contribution

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中国物理快报（英文版） 2009年第8期26卷 375-378页

作者： LIU Yong-Kui LI Zhi CHEN Xiao-Jie WANG Long Center for Complex Systems Department of Automatic Control EngineeringXidian UniversityXi'an 710071 State Key Laboratory for Turbulence and Complex Systems Center for Systems and ControlCollege of EngineeringPeking UniversityBeijing 100871 Department of Zoology University of British ColumbiaVancouver BC V6T 1Z4Canada Center for Complex Systems Department of Automatic Control EngineeringXidian UniversityXi'an 710071 State Key Laboratory for Turbulence and Complex Systems Center for Systems and ControlCollege of EngineeringPeking UniversityBeijing 100871

We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their strategies by self-questioning. An individual with introspection can determine whether its current strategy is superior by playing a virtual round of the game and its local contribution is defined as the sum of all the payoffs its neighbors collect against it. In our model, the performance of an individual is determined by both its payoff and local contribution through a linear combination. We demonstrate that the present mechanism can produce very robust cooperative behavior in both games. Furthermore, we provide theoretical analysis based on mean-field approximation, and find that the analytical predictions are qualitatively consistent with the simulation results.

关键词： No English keyword

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Prisoner's Dilemma Game on Two Types of Positively Correlated Networks

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中国物理快报（英文版） 2009年第4期26卷 265-268页

作者： LIU Yong-Kui LI Zhi CHEN Xiao-Jie WANG Long Center for Complex Systems Department of Automatic Control EngineeringXidian UniversityXi'an 710071 State Key Laboratory for Turbulence and Complex Systems Center for Systems and ControlCollege of EngineeringPeking UniversityBeijing 100871 Department of Zoology University of British ColumbiaVancouver BC V6T 1Z4Canada State Key Laboratory for Turbulence and Complex Systems Center for Systems and ControlCollege of EngineeringPeking UniversityBeijing 100871 Center for Complex Systems Department of Automatic Control EngineeringXidian UniversityXi'an 710071

We study the effects of degree correlations on the evolution of cooperation in the prisoner's dilemma game with individuals located on two types of positively correlated networks. It is shown that the positive degree correlation can either promote or inhibit the emergence of cooperation depending on network configurations. Furthermore, we investigate the probability to cooperate as a function of connectivity degree, and find that high-degree individuals generally have a higher tendency to cooperate. Finally, it is found that small-degree individuals usually change their strategy more frequently, and such change is shown to be unfavourable to cooperation for both kinds of networks.

关键词： No English keywords

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Data-Based Optimal Tracking of Autonomous Nonlinear Switching systems

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 227-238页

作者： Xiaofeng Li Lu Dong Changyin Sun the School of Automation Southeast UniversityNanjing 210096 the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the College of Electronics and Information Engineering Tongji UniversityShanghai 201804China

In this paper,a data-based scheme is proposed to solve the optimal tracking problem of autonomous nonlinear switching *** system state is forced to track the reference signal by minimizing the performance ***,the problem is transformed to solve the corresponding Bellman optimality equation in terms of the Q-function(also named as action value function).Then,an iterative algorithm based on adaptive dynamic programming(ADP)is developed to find the optimal solution which is totally based on sampled *** linear-in-parameter(LIP)neural network is taken as the value function *** the presence of approximation error at each iteration step,the generated approximated value function sequence is proved to be boundedness around the exact optimal solution under some verifiable ***,the effect that the learning process will be terminated after a finite number of iterations is investigated in this paper.A sufficient condition for asymptotically stability of the tracking error is ***,the effectiveness of the algorithm is demonstrated with three simulation examples.

关键词： Adaptive dynamic programming approximation error data-based control Q-learning switching system

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