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Acousto-optical effect signal denoising algorithm based on ICEEMDAN-grey correlation degree

Acousto-optical effect signal denoising algorithm based on I...

引用

2024 Conference on Spectral Technology and Applications, CSTA 2024

作者： Yang, Xueshuai Zhang, Jianyuan Li, Zhiwei School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications Tianjin300384 China

ISBN: (纸本)9781510683082

In the optical-based measurement of the speed of sound in seawater, considering the influence of the measurement system and the media environment, the signal is embodied as a noise signal with acoustic markers in addition to the signal, especially when the SNR of the signal is low, which poses a great challenge to the subsequent time-of-flight analysis of ultrasound, thus seriously affecting the accuracy of the results of the speed of sound measurements, and it is necessary to suppress the noise. In this paper, we propose a noise reduction method based on Improved Complete Ensemble Empirical Mode Decomposition with Adative Noise (ICEEMDAN)-gray correlation. The noise-containing optical signal is decomposed into a series of IMF components and residuals using ICEEMDAN, and then the gray correlation between each IMF component and the original signal is used as the demarcation point for dividing it into noise-dominant and signal-dominant parts, and the IMF components and residuals in the signal-dominant part are reconstructed to get the noise-reduced signal at last. The relative performance of the algorithm is evaluated on experimental data, for low SNR 9dB acousto-optic signal after the algorithm the SNR is improved to 34.6861dB and compared with the existing methods, the combined data results show that the method is superior to the existing methods with higher SNR, NCC and lower MSE. © 2024 SPIE.

关键词： Noise abatement

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ES-MSCNN: An Echo State Multi-Scale Convolutional Neural Network for Multi-Step Prediction of Wastewater Quality Variables 7

ES-MSCNN: An Echo State Multi-Scale Convolutional Neural Net...

引用

7th International Conference on Robotics, control and automation engineering, RCAE 2024

作者： Sun, Yue Liu, Yiqi South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science & Engineering Guangzhou510640 China

ISBN: (纸本)9798350355642

Given the limitations of hardware sensors together with strong nonlinearities and nexus between variables in wastewater treatment processes (WWTPs), the measurement of key quality variables is usually inaccurate or even impossible. Moreover, due to the short data sampling period, the single-output single-step prediction model cannot meet the actual demand. Therefore, this paper proposes a new soft sensor, termed as the Echo State Multi-Scale Convolutional Neural Network (ES-MSCNN), designed for accurate multivariate multi-step prediction. ES-MSCNN first generates an echo state representation (ESR) containing temporal information through an echo state network (ESN). Subsequently, a convolutional neural network (CNN) is employed to avoid the shallowness of ESN and further extract high-dimensional feature information from the data. Besides, a multi-scale learning strategy is used in the convolutional module to capture multi-timescale features and improve the multivariate prediction accuracy. Validation on the benchmark simulation model 2 platform and comparison with several models indicate that the proposed ES-MSCNN has higher accuracy and stronger robustness in multi-step prediction tasks with multi-input and multi-output. © 2024 IEEE.

关键词： Convolutional neural networks

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Autonomous Path Planning and Realization for Dual Robot Cooperation Based on ROS Framework 8

Autonomous Path Planning and Realization for Dual Robot Coop...

引用

8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Shao, Jiawei Gan, Yahui Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China

ISBN: (纸本)9798350300178

To realize dual-robot autonomous path planning and realization, the trajectory planning research of dual-robot is carried out using the open-source robot operating system ROS as the simulation platform. The motion planning-related file configuration is completed by using MoveIt! In trajectory planning, cubic spline interpolation is performed on the trajectory points generated by the RRT-Connect path planning algorithm to complete the planning of the dual-arm assembly task. The communication between ROS nodes and ROS is established in the controller, and the processed trajectory points are communicated with the controller through ROS-Industrial. The experimental results show that the trajectory of the dual robot movement process is smooth and continuous, the stability is strong, and the error is small, which can ensure the completion of basic assembly tasks. © 2023 IEEE.

关键词： Motion planning

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A Binocular Vision-Based Method for Volume Measurement of Colloids

A Binocular Vision-Based Method for Volume Measurement of Co...

引用

2024 China automation Congress, CAC 2024

作者： Liao, Binrong Li, Yuxuan Zhang, Hao Zhu, Cong Yang, Yongkuan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China

ISBN: (纸本)9798350368604

Traditional binocular vision matching methods struggle to correctly match left and right colloid images due to the high reflectivity and textureless characteristics of colloid material surfaces, making effective volume detection difficult. To address this issue, we propose a binocular vision-based method for detecting the volume of dot-shaped colloids. First, to overcome the challenge of image edge extraction caused by specular reflection on colloid surfaces, we introduce an improved method for detecting and removing specular reflections. This method effectively detects and eliminates specular highlights on the colloid surface while restoring the surface color information, thereby enhancing edge detection accuracy. Next, we acquire the morphological characteristics of colloids from two perspectives (top view and side view) using binocular vision. Finally, we construct a mathematical model of the colloid volume based on its morphological characteristics and use a scale conversion factor to calculate the colloid volume. Experimental results show that the error precision of this volume measurement method is 4.52%, meeting the requirements of industrial production. © 2024 IEEE.

关键词： Binocular vision

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Fall Detection System Based on YOLO Algorithm and MobileNetV2 Model 10

Fall Detection System Based on YOLO Algorithm and MobileNetV...

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10th International Conference on Systems and Informatics, ICSAI 2024

作者： Han, Chunxiao Zhang, Jingyan Wu, Han Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9798331510138

Accidental falls are the major causes of injury among elderly people living alone. However, traditional fall detection algorithms usually have missed or false detections problems. In this paper, we design a fall detection system based on YOLO algorithm and MobileNetV2 model. First, detection frame coordinates and joint coordinates of the human body are fused as feature information, and background information is filtered out. A lightweight deep learning model, MobileNetV2, is then used for classification. Compared with commonly used lightweight classification models such as ShuffleNet and EfficientNet, the MobileNetV2 model performs better in recognizing fall behavior. Our system can effectively distinguish fall behavior from daily activities, meeting the requirements for fall detection. © 2024 IEEE.

关键词： Fall detection

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Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control 5

Inverse Reinforcement Learning Integrated Reinforcement Lear...

引用

5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Gu, Shiyi Zhang, Tingting Zhang, Ya Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China Army Engineering University College of Command and Control Engineering Nanjing210017 China

ISBN: (纸本)9798350325294

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises. © 2023 IEEE.

关键词： Reinforcement learning

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Research and Design of New Energy Dry-Type Transformer Prediction Device 2

Research and Design of New Energy Dry-Type Transformer Predi...

引用

2nd IEEE International Conference on Sensors, Electronics and Computer engineering, ICSECE 2024

作者： Lin, Zhangzheng Sang, Zhongqing Feng, Nairu He, Zewen School of Electrical Engineering and Automation Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China

ISBN: (纸本)9798350373646

The main problem in dry-type transformers for new energy applications is the frequent temperature changes, which can reach temperatures of up to 180°C in actual operation. Due to the different expansion coefficients between epoxy resin and copper rows in dry-type transformers, the sealing of epoxy resin will be destroyed, leading to serious consequences such as dry-type transformer fire and explosion. For this reason, this paper designs a new energy dry-type transformer prediction device for transformer temperature and partial discharge signal monitoring and fault alarm, and studies the application of high-frequency current transformer (HFCT) in partial discharge monitoring to achieve real-time monitoring of transformer operation status. Finite element simulation software was used to analyze a dry-type transformer's simulation model. The simulation data obtained were then verified through real experimental testing. In the real grid system, simulations were conducted to model turn-to-turn short-circuit faults. The aim was to validate the simulation results and determine the required monitoring devices. The effectiveness of different monitoring methods-HFCT (High-Frequency Current Transformer), ultrasonic, ultra-high-frequency (UHF), and ground wave detection-was compared. It was found that HFCT is more effective than the other three methods in monitoring dry-type transformers. © 2024 IEEE.

关键词： Partial discharges

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Multi-Channel Knowledge Distillation via Efficient Feature Fusion Module for Anomaly Segmentation

Multi-Channel Knowledge Distillation via Efficient Feature F...

引用

2023 China automation Congress, CAC 2023

作者： Zhou, You Huang, Zihao Zeng, Deyu Wu, Zongze School of Automation Guangdong University of Technology Guangzhou China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350303759

Unsupervised image anomaly detection and segmentation algorithms hold significant importance in enhancing product quality in real-world industrial manufacturing. Anomaly detection methods based on the knowledge distillation framework perform detection by characterizing differences between anomalous samples. However, knowledge distillation-based anomaly detection methods often employ similar or identical architectures for constructing both teacher and student models. This practice has led to the issue of vanishing anomaly activation values, resulting in detection failures. Hence, the proposed Multi-Channel Knowledge Distillation model (MCKD) consists of a pair of student networks proficient at effectively capturing defect-related information. One branch of the student network enhances its diverse representation of anomalies by restoring the input's multi-scale representations. The other branch enriches the model's capacity to represent detailed defect information by extracting features from different scales. Additionally, our design of the Residual Features Aggregation Module (RFAM) ensures better retention of normal pattern information within the student network while disregarding information from abnormal patterns, resulting in enhanced modeling of positive samples. The proposed framework achieves state-of-the-art (SOTA) on the well-known MVTec AD dataset, with an area under the receiver operating characteristic curve of 97.1% for anomaly detection across all 15 categories and an area under the anomaly segmentation of 98.14%. © 2023 IEEE.

关键词： Distillation

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A Cluster-Based Distributed State Estimation Method Utilizing Cooperative Target Tracking 7th

A Cluster-Based Distributed State Estimation Method Utilizin...

引用

7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhu, Bangzhao Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Beihang University Beijing China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789819733316

Cooperative target tracking in sensor networks involves optimizing tracking performance by leveraging various sensor types. This entails networked communication between sensors to track targets within a designated area. The process also includes harmonizing target estimations and achieving optimal fusion of results. In cluster systems, where nodes monitor each other’s status, the estimation of a specific node’s state evolves into a multi-sensor single-target tracking challenge, extending to multi-sensor multi-target tracking. This paper presents an innovative approach to distributed target tracking, using relative position information for fusion, yielding enhanced results. ... © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： State estimation

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Review of Islanding Detection Methods for New Energy Grid Integration Systems 3rd

Review of Islanding Detection Methods for New Energy Grid In...

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3rd International Joint Conference on Energy, Electrical and Power engineering, CoEEPE 2023

作者： He, Xianqiang Zhao, Weixing Cao, Fei Ma, Qinfeng Liu, Mingshun Qin, Hai Pu, Qingxin Zhang, Wanting Yuan, Jiaxin Guizhou Power Grid Co. Ltd. Electric Dispatching and Control Center Guiyang China Beijing Sifang Protection and Automation Engineering Technology Co. Ltd. Beijing China School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (纸本)9789819739394

With the continuous development and growth of new energy grid integration, the phenomenon of islanding occurs frequently in the new energy grid integration system, which poses a significant threat to the safety and stable operation of the power grid. Islanding detection is an essential means of determining whether an islanding phenomenon has occurred in the new energy grid integration system. This paper first explains the principle and harm of islanding, and introduces the main islanding detection methods currently available, analyzing their advantages and disadvantages. Finally, based on the current status of islanding detection development, this paper proposes the problems that need to be addressed and the future development trends to promote further development in this research field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Distributed power generation

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