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A Novel Fault Diagnosis Based Improved WOA-BP for Analog Circuit

A Novel Fault Diagnosis Based Improved WOA-BP for Analog Cir...

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data driven control and learning systems (ddcls)

作者： Zhiqiang Zhang Yang Zhang Aihua Zhang College of Physical Science and Technology Bohai University Jinzhou

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Aiming at the problem that the fault diagnosis signals in the existing analog circuits cannot be effectively classified, a new scheme (BL-WOA-BP) based on the improved whale algorithm(WOA) to optimize the parameters of the back-propagation(BP) neural network is proposed in this paper. the scheme selects the wavelet packet analysis(WPA) with higher precision than the traditional wavelet analysis to extract the fault features of the analog circuit; then, the feedback mechanism is used to improve the global search ability of the WOA, and the transformation of linear and nonlinear factors is used to balance the local and global search ability, so as to better optimize the parameters of the BP neural network. Finally, three analog circuits of different scales are trained and tested by establishing BL-WOA-BP model to realize circuit soft fault diagnosis. After verifying the scheme through simulation experiments, it is shown that the improved WOA optimized BP neural network has higher diagnostic accuracy compared with other methods compared in this paper, and the fault recognition rate reaches 100% at most. through the neural network based on embedded system, the real-time fault diagnosis of analog circuit is carried out to diagnose the circuit fault timely and effectively.

关键词： Fault diagnosis Neural networks Analog circuits Feature extraction Wavelet analysis Wavelet packets Real-time systems

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Application of CPU Parallel Computing in MATLAB Environment for Analysis of Anti-Saturation and Gain Effects in PID controller

Application of CPU Parallel Computing in MATLAB Environment ...

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data driven control and learning systems (ddcls)

作者： Ruirui Huang Zhenhui Wu Yandong Hou Qianshuai Cheng Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China Technology and Media University of Henan Kaifeng Kaifeng China School of Artificial Intelligence Henan University Zhengzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

With the continuous increase in data size and model complexity, the computational workload has grown rapidly, posing a significant challenge to the capabilities of computer data processing and simulation calculations. therefore, parallel programming based on multicore and cluster architectures has become one of the mainstream technologies to enhance program execution efficiency and numerical computation efficiency. the theoretical foundations of parallel program computing have been applied in various aspects of engineering applications and theoretical simulations. In this paper, a new parallel PID anti-integral saturation controller is designed for a second-order closed-loop control system of unmanned aerial vehicles (UAVs). It compares and analyzes the runtime, execution efficiency, and speedup ratio of parallel programs and general serial programs under the same scenario. the experimental results demonstrate that parallel computing significantly improves the simulation program's efficiency for PID controller anti-saturation control systems under identical scenarios, exhibiting a high speedup ratio on the existing computing platform. Additionally, this study consolidates common issues encountered in MATLAB parallel program design, offering valuable insights into overcoming challenges in this domain.

关键词： Runtime Parallel programming Multicore processing Process control Parallel processing control systems Central Processing Unit

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Design and Implementation of Motion Tracking System Based on IMU

Design and Implementation of Motion Tracking System Based on...

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data driven control and learning systems (ddcls)

作者： Yunlong Xing Shaopeng Pang Mingjun Du Fangzhou Xu Peng Ji School of Information and Automation Engineering Qilu University of Technology (Shandong Academy of Sciences) Jinan China International School for Optoelectronic Engineering Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

the inertial measurement unit is widely used in the design and implementation of the motion tracking system. this paper designs a ICM20948-based motion tracking system that supports wireless transmission. Our system consists of 15 motion collection modules, data receiver and PC. the motion collection module is responsible for collecting, calibrating and fusing motion data. the data receiver packs the motion data and transmits it to the PC through the USB transmission module. To reduce the effect of system error on the motion data, we use the 6-sided calibration algorithm to calibrate the accelerometer, use ellipsoidal algorithm to calibrate the magnetometer, and use the deviation value to calibrate the gyroscope. An adaptive extended Kalman filter is used for fusion of motion data to obtain accurate attitude corner information. We use NRF24L01 to build a transmission hardware and innovatively propose a wireless data transmission mechanism to ensure the transmission integrity of data. Our motion tracking system supports wireless transmission and can ensure the real-time, synchronization and stability when collecting and transmitting motion data.

关键词： Wireless communication Tracking Magnetometers Receivers Universal Serial Bus Real-time systems Calibration

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Improved Virtual Sample Generation Method Based on Conditional Regions Denoising Diffusion Probabilistic Model for Soft Sensors with Small data

Improved Virtual Sample Generation Method Based on Condition...

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data driven control and learning systems (ddcls)

作者： Wei-Tao Mo Qun-Xiong Zhu Xiao-Lu Song Yan-Lin He Yuan Xu College of Information Science and Technology Beijing University of Chemical Technology (BUCT) Beijing China Engineering Research Center of Intelligent PSE Ministry of Education of China Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Soft sensors have excellent adaptability to complex environments and are widely used in complex industrial processes. However, its construction relies on high-quality samples, which poses a challenge to construct reliable soft sensors. To solve this challenge, this paper proposes a conditional regions denoising diffusion probabilistic model-based virtual sample generation (CRDDPM-VSG) method. It aims to make the generated samples better to fill the low-density regions. In CRDDPM-VSG, density-based spatial clustering with noise application (DBSCAN) is used to find low-density samples. then, the improved CRDDPM is used to generate samples in the specified low-density sample regions. Finally, the generated samples are added to the original samples to enrich the sample information, thus improving the performance of the soft sensor. We used two sets of data to validate the performance of CRDDPM-VSG. Results show that CRDDPM-VSG not only generates samples that match the original distribution, but also better boosts the prediction ability of the soft sensor.

关键词： learning systems Adaptation models Soft sensors Noise reduction Noise Probabilistic logic Diffusion models

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Improving the ALNS Algorithm for PDPTW Problem using a DDQN Agent

Improving the ALNS Algorithm for PDPTW Problem using a DDQN ...

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data driven control and learning systems (ddcls)

作者： Qianlong Wang Peng Wu Lili Guo Ping Chen Yu Ling School of Economics and Management University of Chinese Academy of Sciences Beijing P. R. China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing P. R. China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing P. R. China Business School Nankai University Tianjin P. R. China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In response to practical challenges in food delivery logistics, we introduce a novel algorithm to address the Pickup and Delivery Problem with Time Windows (PDPTW). Our method employs a Double Deep Q-Network (DDQN)-based Large Neighborhood Search (LNS) strategy, which builds on the Adaptive Large Neighborhood Search (ALNS) framework, tailored specifically for the PDPTW. To mitigate the issues of slow convergence and instability observed in the ALNS algorithm, we have refined the state representation of the DDQN agent by integrating information on the current solution, historical data, and the time usage patterns of operators. We evaluated our algorithm using publicly available benchmark instances. the empirical results indicate that our approach not only surpasses the ALNS algorithm in terms of macro-level solution quality and stability but also demonstrates superior performance at the micro-level by achieving faster convergence and enhanced efficiency in operator usage strategy.

关键词： learning systems Reinforcement learning Benchmark testing control systems Convergence Logistics

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Slow Feature thermography for Non-Destructive Evaluation of Defects in Composite Materials

Slow Feature Thermography for Non-Destructive Evaluation of ...

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data driven control and learning systems (ddcls)

作者： Kaixin Liu Xin Zhong Ping Chen Yun Dai Yi Liu The State Key Lab for Electronic Testing Technology North University of China China Department of Information and Communication Engineering North University of China Taiyuan China College of Mechanical Engineering Nantong Vocational University Nantong China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In recent years, various methods for processing and analyzing thermographic data have been applied in non-destructive testing to improve the visibility of defects. Representatively, traditional linear dimensionality reduction methods (e.g. principal component analysis) have achieved good results in thermographic data analysis. In this work, a slow feature thermography (SFT) method for non-destructive evaluation of defects in composite materials. thermographic data can be regarded as a continuous time series generated by an infrared imager at different moments. Slow feature analysis algorithm is subsequently used to extract slow features of the thermal image sequence. Slow features refer to features that are unchanged or slowly changing in time-series data, such as the background of a thermal image. By extracting the slow features of data, the inhomogeneous background, noise and defect features contained in thermal images can be effectively distinguished. Test results on carbon fiber reinforced polymer specimens demonstrate the feasibility and effectiveness of the SFT method.

关键词： Image recognition Composite materials Time series analysis Infrared imaging Feature extraction thermal noise thermal analysis

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Diffusion Ranking Scores Based Improved Hypergraph Generation Method for Visual Classification Tasks

Diffusion Ranking Scores Based Improved Hypergraph Generatio...

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data driven control and learning systems (ddcls)

作者： Shuai Wang Kang Wang Xiaoli Li Faculty of Information Technology Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Visual classification has attracted considerable research attention in the last few decades. this paper presents an approach to improve the hypergraph structure using a diffusion ranking method and employs hypergraph neural networks for such tasks. Hyperedges are formed by connecting a set of vertices, and the generation of the hypergraph structure is typically task-dependent, making hypergraph generation methods less generalizable. Previous approaches have employed implicit hypergraphs for visual tasks, especially in visual classification, using attribute-based or neighborhood-based methods. However, these approaches cannot fully explore the global manifold structure of the feature space. To address this problem, this paper proposes a novel two-stage hypergraph construction method, which fully utilizes the ability of diffusion process to capture the manifold structure of feature data. Initially, the hypergraph structure is constructed using a neighbor-based approach, and subsequently, the final hypergraph structure is obtained by ranking scores of diffusion processes that reflect the degree of vertex similarity. Comparing with state-of-the-art hypergraph neural network algorithms on classical 3D visual image datasets, experimental results demonstrate the effectiveness of the proposed algorithm.

关键词： Manifolds learning systems Visualization three-dimensional displays Neural networks Diffusion processes Process control

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Force control Method for the Variable Robot Payload in Metal Slag Removal Operation

Force Control Method for the Variable Robot Payload in Metal...

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data driven control and learning systems (ddcls)

作者： Junhan Liu Degang Xu Yuqian Guo School of Automation Central South University Changsha China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

To achieve accurate force control during slag removal operations in the metallurgical industry, the impedance control strategy is commonly employed. A robot designed for slag removal operation has been developed to handle oxidized slag suspended on the surface of molten metal. However, the oxidized slag typically adheres to the end-effector over time, altering the end-effector's weight and impacting the force control's precision. this paper proposes a novel force control strategy to realize the re-identification of variable parameters of the end-effector without stopping the operation of the robot. First, a six-dimensional force sensor is installed between the robot flange and the end-effector. the paper calibrates and calculates the end-effector's parameters, reducing the influence of the end-effector's gravity on force perception. Secondly, a real-time parameter updating algorithm, termed MRLS (Modified Recursive Least Squares Method), is designed specifically for parameter re-identification of variable robot payload. Finally, experimental results demonstrate that the error of the measured weight of the tool to the true value is 1.64%. When the robot is in the slag removal movement process, the error of the contact force estimated is within 0.13N.

关键词： Accuracy Metals Slag Robot sensing systems End effectors Force control Robots

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Semi-Supervised Domain Adaptation with Feature Separation for Wind Turbine Anomaly Detection

Semi-Supervised Domain Adaptation with Feature Separation fo...

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data driven control and learning systems (ddcls)

作者： Guangqiang Ming Shihao Ma Junyang Xu Jiaye Wang Zhenwei Jia Chunhui Zhao Powerchina Huadong Engineering Corporation Ltd. Electromechanical Engineering Institute (Huachen Electric Power) Hangzhou P. R. China College of Control Science and Engineering Zhejiang University Hangzhou P. R. China Institute of Intelligence Science and Engineering Shenzhen Polytechnic University Shenzhen P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Anomaly detection for the wind power generation process is important for the maintenance and early warning of wind turbines. Deep learning-based methods are widely used in wind turbine anomaly detection. However, the data distribution changes frequently due to the changing working conditions of wind turbines, and deep learning methods are difficult to directly apply to new working conditions with scarce labeled data. therefore, this paper proposes a semi-supervised domain adaptation method with feature separation (SSDA-FS) for wind turbine anomaly detection. First, a feature separation domain adaptation strategy is designed to eliminate inter-domain differences. the feature space is decomposed into domain-related space and anomaly-related space through the devised adversarial training. then a semi-supervised timing augment strategy is proposed, which can augment the unlabeled samples and a few labeled samples in the target domain. the proposed method is implemented and validated in a wind turbine anomaly detection dataset, and the performance is significantly improved compared with the comparison methods.

关键词： Employee welfare Training learning systems Wind power generation Wind farms Feature extraction Wind turbines

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Observer-Based Fault Tolerant Formation control of Multi-Agent systems via Adaptive Dynamic Programming

Observer-Based Fault Tolerant Formation Control of Multi-Age...

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data driven control and learning systems (ddcls)

作者： Yongwei Zhang Bo Zhao Derong Liu College of Mathematics and Informatics South China Agricultural University Guangzhou China School of Systems Science Beijing Normal University Beijing China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper develops a fault tolerant formation control scheme for multi-agent systems (MASs) by using adaptive dynamic programming. In MASs, there exist one leader and multiple followers, where the leader is a generated ideal trajectory and the followers catch up with the leader using appropriate designed control inputs based on their own and neighbors' information. To obtain accurate fault information, a fault observer is established for each follower. Subsequently, a discounted cost function, which includes the estimated fault, the formation error, and the control laws, is developed for each following agent. In order to solve the coupled Hamilton-Jacobi-Bellman equation of each follower, a critic-only structure is built to obtain the approximate fault tolerant formation control law. Furthermore, it is proved that the uniform ultimate boundedness of the formation error of each following agent is guaranteed under the developed observer-based fault tolerant formation control law. It means that all following agents are able to maintain a specified formation and catch up with the leader. Finally, a simulation example is employed to validate the effectiveness of the present control approach.

关键词： Fault tolerance Simulation Fault tolerant systems Observers control systems Formation control Mathematical models

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