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A CNN-ELM Compound Fault Diagnosis Method Based on Joint Distribution Modification

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A CNN-ELM Compound Fault Diagnosis Method Based on Joint Dis...

International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Jiechao Dong Liping Yan Yuanqing Xia Jinhui Zhang Xianghua Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Shandong Key Laboratory of Big-data Driven Safety Control Technology for Complex Systems Shandong China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based on joint distribution modification. Firstly, considering the complementarity and coupling of data from multiple sensors, a data input trick of multi-sensor data connected in parallel is designed. Secondly, due to the discrepancy of distribution between the compound fault data features and the single fault data features, the marginal distribution matrix and the posterior distribution matrix are used to modify the CNN-ELM network, so that the network can extract more reliable data features for fault diagnosis. Finally, referring to the categories and criteria of bearing damage proposed by Paderborn University, the label code is defined. The corresponding data set is used to verify the proposed algorithm. Experimental results show that the algorithm can accurately obtain detailed fault information such as fault location, fault type, and fault severity.

关键词： Fault diagnosis Rolling bearings Materials reliability Feature extraction Sensor systems Sensors Compounds

Privacy-Preserving Brain-Computer Interfaces: A Systematic Review

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arXiv 2024年

作者： Xia, Kun Duch, Wlodzislaw Sun, Yu Xu, Kedi Fang, Weili Luo, Hanbin Zhang, Yi Sang, Dong Xu, Xiaodong Wang, Fei-Yue Wu, Dongrui The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Zhejiang Lab Hangzhou311121 China The Department of Informatics School of Physics Astronomy and Informatics Neurocognitive Laboratory Center for Modern Interdisciplinary Technologies Nicolaus Copernicus University Torun Poland The Ministry of Education Key Laboratory for Biomedical Engineering Zhejiang University Hangzhou China The Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou China Department of Biomedical Engineering Zhejiang University Hangzhou China The School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China The College of Public Administration Huazhong University of Science and Technology Wuhan430074 China The NetsUnion Clearing Corporation Beijing100045 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100049 China

A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most research so far focuses on making BCIs more accurate and reliable, but much less attention has been paid to their privacy. Developing a commercial BCI system usually requires close collaborations among multiple organizations, e.g., hospitals, universities, and/or companies. Input data in BCIs, e.g., electroencephalogram (EEG), contain rich privacy information, and the developed machine learning model is usually proprietary. Data and model transmission among different parties may incur significant privacy threats, and hence privacy protection in BCIs must be considered. Unfortunately, there does not exist any contemporary and comprehensive review on privacy-preserving BCIs. This paper fills this gap, by describing potential privacy threats and protection strategies in BCIs. It also points out several challenges and future research directions in developing privacy-preserving BCIs. © 2024, CC BY.

关键词： Differential privacy

Limit-Cycle-Based Design of Formation control for Mobile Agents

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Limit-Cycle-Based Design of Formation Control for Mobile Age...

作者： Wang, Chen Xia, Weiguo Xie, Guangming National Engineering Research Center for Software Engineering Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

In this article, we study the formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations where the distances between neighboring agents or the distances between each agent and the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors, and the acceleration of the target. In order to solve the formation problem, a limit-cycle-based controller design is delivered. We divide the overall control objective into two subobjectives, where the first is target circling that each agent keeps its own desired distance to the static/moving target as well as rotating around or remaining static relative to the target as expected, and the second is distribution adjustment that each agent maintains the desired distance to its neighbors. Then, we propose a controller comprised of two parts, where a limit cycle oscillator named a converging part is designed to deal with the first subobjective, while a layout part is introduced to address the second subobjective. One key merit of the controller is that it can be implemented by each agent in its local frame so that only local information is utilized without knowing global information. Theoretical analysis of the convergence to the desired formation, of which the agents are required to be evenly distributed on a circle around the target, is provided for the multiagent system under the proposed controller. Numerical simulations are given to validate the effectiveness of the proposed controller for the cases of general formations, and to show that no collision between agents ever takes place throughout the system's evolution. © 1963-2012 IEEE.

关键词： Multi agent systems

Research on Vibration Isolation control of Six wheel-legged Robot Based on Impedance control

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Research on Vibration Isolation Control of Six wheel-legged ...

第三十九届中国控制会议

作者： Binkai Yue Shoukun Wang Zhihua Chen Kang Xu Junzheng Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology

The electric parallel six wheel-legged robot（EPSWLR） is characterized by heavy load and fast moving speed. But the body will shake and vibrate while passing through rough roads, which affects its stability. In order to solve this problem, the single-leg structure based on Stewart structure was equivalent to the impedance system composed of mass block, spring and damping in this paper. Due to changes in environmental forces and environmental impedance parameters caused by environmental changes, the traditional impedance control（IC） still causes force error at the foot end of robot and thus results in poor vibration isolation effect. Therefore, a new adaptive algorithm was proposed in this paper and added to IC algorithm to reduce the force error caused by environmental changes and thus improve the vibration isolation effect. In this paper, the characteristic equation of adaptive impedance control（AIC） algorithm was first obtained and the condition for system stability was calculated based on Routh-Hurwitz stability criterion. Finally, the stability of this system was verified. The simulation experiment combining MATlab and Adams was designed and performed with EPSWLR. The effectiveness of AIC was proved by monitoring the changes in the force of single leg and the attitude of robot body.

关键词： Electric parallel six wheel-legged robot Impedance control Adaptive algorithm Stewart structure

Dynamics of Small World Effect and Random Fuzzy Graph

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Research Square

Research Square 2021年

作者： Zhang, Yijin Huang, Jie Lin, Zongbing Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing Municipal Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

Small World Effect (or Six Degrees of Separation theory) has generated significant influence in the world. Many researchers and institutes have done lots of work on the study of it. We model Small World Effect by random process and Graph, calculate the probability that any two people i and j in the world can contact each other after n steps (forwarding messages by intermediaries) based on different R (average number of acquaintances everyone has in the world).When R=50 or 80, if, the probability is 0.848 and the search is very likely to happen. When R=150, n=4, this probability is 0.99994, that is, after 4 steps, any two people in the world will establish connection almost surely. In the sense of Dunbar's number (R=150), six degrees of separation becomes four degrees of separation. We propose the concepts of (directed) Random Fuzzy Graph for the very first time which can describe the fact of recognition among people best, because the relation among persons is random and fuzzy. © 2021, CC BY.

关键词： Random processes

Graph Optimization based Visual SLAM fusing keyPoints and Markers

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Graph Optimization based Visual SLAM fusing KeyPoints and Ma...

第三十九届中国控制会议

作者： Zhen Chen Yang Zhou Fengdi Zhang Min Xu Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control

Simultaneous localization and mapping（SLAM） plays an important role in autonomous navigation for mobile *** of the visual SLAM approaches use keypoints for tracking, whose performance however suffers from the unstable landmarks during task due to uncertain light condition and frequently changeable viewpoint. The situation even becomes worse for visual SLAM in low texture environment especially in indoor buildings, where the supplementary artificial markers can be used to improve the robust detection under a wider range of circumstances. Inspired by this thought, this paper developed a visual SLAM system integrated with keypoints and artificial markers. A graph optimization problem is constructed to optimize the trajectory by taking both the reprojection error of keypoints and the influence of markers into consideration. The experimental results on SPM dataset demonstrate the superior accuracy of the proposed graph optimization algorithm compared with the start-of-the-art ORB-SLAM2.

关键词： Visual simultaneous localization and mapping（SLAM） graph optimization keypoints artificial markers

Distributed synchronous and asynchronous algorithms for semi-definite programming with diagonal constraints

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arXiv 2021年

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Ministry of Education Beijing100081 China School of Electronic and Information Engineering Tongji University Shanghai200082 China

This paper develops distributed synchronous and asynchronous algorithms for the large-scale semi-definite programming with diagonal constraints, which has wide applications in combination optimization, image processing and community detection. The information of the semi-definite programming is allocated to multiple interconnected agents such that each agent aims to find a solution by communicating to its neighbors. Based on low-rank property of solutions and the Burer-Monteiro factorization, we transform the original problem into a distributed optimization problem over unit spheres to reduce variable dimensions and ensure positive semi-definiteness without involving semi-definite projections, which are computationally expensive. For the distributed optimization problem, we propose distributed synchronous and asynchronous algorithms, both of which reduce computational burden and storage space compared with existing centralized algorithms. Specifically, the distributed synchronous algorithm almost surely escapes strict saddle points and converges to the set of optimal solutions to the optimization problem. In addition, the proposed distributed asynchronous algorithm allows communication delays and converges to the set of critical points to the optimization problem under mild conditions. By applying proposed algorithms to image segmentation applications, we illustrate the efficiency and convergence performance of the two proposed algorithms. © 2021, CC BY.

关键词： Optimization

Distributed stochastic gradient tracking algorithm with variance reduction for non-convex optimization

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arXiv 2021年

This paper proposes a distributed stochastic algorithm with variance reduction for general smooth non-convex finite-sum optimization, which has wide applications in signal processing and machine learning communities. In distributed setting, large number of samples are allocated to multiple agents in the network. Each agent computes local stochastic gradient and communicates with its neighbors to seek for the global optimum. In this paper, we develop a modified variance reduction technique to deal with the variance introduced by stochastic gradients. Combining gradient tracking and variance reduction techniques, this paper proposes a distributed stochastic algorithm, GT-VR, to solve large-scale non-convex finite-sum optimization over multi-agent networks. A complete and rigorous proof shows that the GT-VR algorithm converges to first-order stationary points with O(k1) convergence rate. In addition, we provide the complexity analysis of the proposed algorithm. Compared with some existing first-order methods, the proposed algorithm has a lower O(PMΕ−1) gradient complexity under some mild condition. By comparing state-of-the-art algorithms and GT-VR in experimental simulations, we verify the efficiency of the proposed algorithm. © 2021, CC BY.

关键词： Stochastic systems

Distributed proximal gradient algorithm for non-smooth non-convex optimization over time-varying networks

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arXiv 2021年

This note studies the distributed non-convex optimization problem with non-smooth regularization, which has wide applications in decentralized learning, estimation and control. The objective function is the sum of different local objective functions, which consist of differentiable (possibly non-convex) cost functions and non-smooth convex functions. This paper presents a distributed proximal gradient algorithm for the non-smooth non-convex optimization problem over time-varying multi-agent networks. Each agent updates local variable estimate by the multi-step consensus operator and the proximal operator. We prove that the generated local variables achieve consensus and converge to the set of critical points with convergence rate O(1/T). Finally, we verify the efficacy of proposed algorithm by numerical simulations. © 2021, CC BY.

关键词： Time varying networks