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2022 International Symposium on Intelligent Robotics and Systems, ISoIRS 2022

作者： Wang, Yunlong Xiong, Lei Wang, Fengsui Xu, Yue School of Electrical Engineering Anhui Polytechnic University Anhui Wuhu241000 China Key Laboratory of Testing Technology and Energy Saving Devices Anhui Province Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Anhui Wuhu241000 China

ISBN: (纸本)9781665455213

At present, there is a problem of complexity and calculation of the image super-resolution algorithm network. To improve this problem, we propose a lightweight super-resolution network that blends global and local features. First, shallow image features are extracted using a convolutional block, and secondly, deep features are extracted by multiple cascading residual feature distillation blocks GLRB, where in order to achieve a good trade-off between model performance and network parameter quantity, local features are learned by enhancing the feature selection module ESA and the balanced dual-attention module to improve model performance. Then, the extracted residual features are fused, and the reconstructed image is obtained by sub-pixel convolution sampling. The experimental results under multiple standard test data sets show that the reconstructed image performance PSNR is improved by 0.25 dB to 32.23, and the number of model parameters is 470.21 K. Compared with DRCN, CARN, IMDN, RFDN and other algorithms, the proposed algorithm has better model lightweight and image reconstruction quality. © 2022 IEEE.

关键词： Distillation

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Regionally Differentiated Real-Time Energy Consumption Prediction of Electric Vehicles Oriented to Travel Characteristics 12th

Regionally Differentiated Real-Time Energy Consumption Predi...

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12th International Conference on Green Intelligent Transportation Systems and Safety, 2021

作者： Wang, Cheng Wang, Ya-nan Tan, Ji-yuan Liu, Fu-yu Jiang, Yuan-yuan Wang, Zhen-po National Engineering Laboratory for Electric Vehicles School of Machinery and Vehicles Beijing Institute of Technology Beijing100144 China Beijing Catarc Technology Center Co. Ltd. Beijing100070 China Beijing Key Lab of Urban Intelligent Traffic Control Technology North China University of Technology Beijing100144 China Beijing Catarc Automotive Testing Technology Center Co. Ltd. Beijing100176 China

ISBN: (纸本)9789811956140

Real-time prediction of electric vehicle energy consumption is of great significance to users’ travel planning and charging decisions. This paper analyzed the influence of travel characteristics and regional differences on the power consumption of electric vehicles, and built a regional electric vehicle energy consumption model based on travel characteristics prediction: In this paper, a large number of travel samples are obtained by preprocessing the real-time operation data of electric vehicles, and the influencing factors of power consumption in the travel samples are analyzed to determine that the most relevant characteristic parameters are travel mileage and time, which are used as the main characteristic indicators of energy consumption prediction. On this basis, a single-region BP neural network energy consumption prediction model was built, and the optimal network model structure was adjusted and determined through error feedback, which achieved a prediction accuracy of 93.2%;then, the travel samples of different cities are modeled and cross predicted, and established a multi-regional energy consumption prediction model;finally, the prediction results of different models are compared. The results show that this model has the highest accuracy in the energy consumption prediction of the actual operation of urban electric vehicles, which can reach 92% and above. Combining the existing electricity with the predicted energy consumption results can provide effective support for users to make reasonable charging decisions before travel. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Insulators Defect Detection for Power Grid Based on Improved Yolov7 Algorithm

Insulators Defect Detection for Power Grid Based on Improved...

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International Conference on Intelligent control and Information Processing (ICICIP)

作者： Zhiwei Zhang Yan Zhuang Zhida Liang Shuai Kong Shengyi Zhu School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province Zhejiang Academy of Special Equipment Science Hangzhou China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

High-current out-of-phase closed bus is an essential link in the transmission of electric energy and is widely used in thermal power stations, hydropower stations and nuclear power plants. Although these busbars have the advantages of excellent dustproof effect and strong magnetic shielding, they are susceptible to insulator aging and damage in long-term operation, posing a potential safety risk to the power grid. Due to the enclosed space inside the bus and the complexity of external maintenance tasks, manual inspection has problems such as inefficiency and low safety. In order to solve these problems, this paper proposes an improved detection algorithm based on Yolov7 for insulator defect detection in hydropower station scenarios. Because of the particularity of Yolov7 network structure and application scenarios, this paper proposes a Channel Feature Enhancement module to enhance the channel representation ability of the network. In addition, an Edge Feature Enhancement module is introduced to improve the boundary detection of insulators by enhancing the contrast between the target and the background. Considering the limitations of existing studies in specific scenarios and the scarcity of dataset, this paper constructs and accurately annotates an insulator defect detection dataset applied to hydropower station scenarios. Experimental results show that the improved-Yolov7-tiny algorithm in this paper achieves a balance between accuracy and inference speed.

关键词： Accuracy Image edge detection Space power stations Hydroelectric power generation Inspection Insulators Feature extraction Power grids Inference algorithms Defect detection

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Fault Detection For Dynamic System Based on Generative Adversarial Networks

Fault Detection For Dynamic System Based on Generative Adver...

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第34届中国控制与决策会议

作者： Junpei Yang Wenyou Du Jianguo Cui Zhonghai Li Shenyang Aerospace University School of Automation Key Laboratory of aircraft testing and control technology in Liao Ning

To solve the problem of multivariable time series fault detection,a Long Short Term Memory Generative Adversarial network(LSTM-GAN) model was proposed in this *** contributions are as follows:*** and discriminators were constructed from LSTM Network to capture the dynamic times series related characteristics;*** Generative Adversarial Network was introduced to generate pseudo-samples from a latent space to capture the real data distribution;*** inverter was proposed to map the time series data back to latent space and the status indicator based on reconstruction error was developed for fault detection.A big normal training dataset was obtained using a Simulink version Tennessee Eastman process simulation and experimental results show that the proposed method can capture dynamic characteristics from big data set and reduces the false alarm rate compared with the traditional method,which verifies the feasibility of the proposed method.

关键词： Fault detection Dynamic System Generative Adversarial Networks Long Short Term Memory Network

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Research on Multi-objective Active Power Optimization Simulation of Novel Improved Water Cycle Algorithm

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IAENG International Journal of Applied Mathematics 2021年第1期51卷 1页

作者： Chen, Gonggui Han, Ying Zhang, Zhizhong Zeng, Xianjun Li, Shuaiyong Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China

Water cycle algorithm (WCA) is a heuristic algorithm proposed in recent years. To overcome the insufficiency of standard WCA algorithm in solving the non-convex optimal power flow (OPF) problems, the multi-objective novel improved water cycle algorithm (MONIWCA) is proposed in this paper. The evaporation process is improved in WCA by introducing evaporation rate and the normal distribution optimization mechanism is used to mutate the individual position. The modified WCA also adopts a constraint-based strategy to ensure zero constraint violations. In order to obtain a high-quality Pareto optimal solution set (POS) and select the best compromise solution (BCs), a global ranking strategy is proposed. The global ranking strategy includes the novel constraint handling method, the rank index calculation and the BCs on fuzzy satisfaction theory to deal with the complex constraints of the optimization problem. The MONIWCA has been simulated under the constraints of zero violations on IEEE 30, IEEE 57 and IEEE 118 standard test systems, including six dual-objective cases and one tri- objective case. The simulation results are compared with the multi-objective particle swarm optimization (MOPSO). The results show that the improved method can effectively solve the MOOPF problem, not only to obtain a uniform continuous Pareto solution set but also to achieve a better compromise solution. In addition, the two performance indicators of the generational distance (GD) and the spacing (SP) also show that the MONIWCA algorithm has uniform distribution, high convergence and strong stability. © 2021, IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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High-voltage planar supercapacitors enabled by Mn-MOF and ionic liquid synergy for high energy-density storage

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Electrochimica Acta 2025年 532卷

作者： Chen, Yi Xie, Xuedan Jing, Jiangtao Wang, Yonghua Cui, Danfeng Liu, Dan Xue, Chenyang State Key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument North University of China Taiyuan030051 China Department of Electrical and Control Engineering Shanxi Institute of Energy Jinzhong030600 China

The combination of pseudocapacitive electrodes with ionic liquid (IL) electrolytes demonstrates a significant synergistic effect in expanding the potential window of supercapacitors, thereby enhancing the energy density of the device. Mn3(HHTP)2, a metal-organic framework (MOF) with high-density redox-active sites and hierarchical porosity, serves as the electrode material paired with [EMIM][BF4] and [EMIM][TFSI] IL electrolytes. The ion size in [EMIM][TFSI] can be precisely aligned with the electrode pore size, thereby reducing interfacial resistance and enhancing ion accessibility. Optimizing the [EMIM][TFSI]/acetonitrile mass ratio to 4:6 achieves superior electrolyte properties, including an ionic conductivity of 50.4 mS cm−1 and viscosity of 5.24 mPa·s. This design extends operating potential from 8 V to 13 V, increasing energy density to 108.0 Wh kg−1, representing a 68.8 % improvement over baseline systems. The device retains 94.34 % capacitance after 2000 cycles at 8 V, with specific capacitances of 7.2 F g−1 at 8 V and 4.6 F g−1 at 13 V. These findings establish a new paradigm for interface engineering in high-voltage supercapacitors. © 2025

关键词： Liquid membrane electrodes

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Sensitivity-Enhanced Tilt Sensor Based on Femtosecond Fiber Bragg Grating

Sensitivity-Enhanced Tilt Sensor Based on Femtosecond Fiber ...

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Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Theophilus Nutsuglo Chuanchen Guo Qiang Li Li Xiong Yongxing Guo Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan China Tiezheng Testing Technology Company Limited Jinan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan China

Tilt sensors are crucial in intelligent monitoring, enabling precise measurements and analysis of tilt angles. They have found extensive use in different industries, particularly in robotic systems and structural safety, as they serve as instrumental components within artificial intelligence (AI)based frameworks to facilitate real-time adjustments and operational efficiency. However, conventional tilt sensors may not be as accurate due to performance issues, such as electromagnetic interference (EMI) or temperature changes. This paper proposes a tilt sensor utilizing fiber Bragg grating (FBG) technology to overcome these drawbacks. This paper introduces a fiber Bragg grating tilt sensor with an enhancedsensitivity. When the sensor experiences a tilt angle (θ), the mass block induces a gravitational force and bending moment on the cantilever beam, leading to strain. The two FBGs detect the induced strain, hence causing a wavelength shift. The two FBGs are positioned a distance away from the neutral axis in a cantilever-based design to increase the sensitivity of the sensor. The results of the experiments show the sensor's linearity of 99.94% and sensitivity of 107.46 pm/° over a tilting angle range of -30° to 30°. Additionally, femtosecond FBGs exhibit hightemperature stability and ultrafast response, making them ideal for real-time monitoring applications. The proposed FBG tilt sensor is a femtosecond-inscribed FBG that leverages the capability to withstand high-temperature settings.

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Optimized Power Dispatch for Regional Fatigue Balancing in Offshore Wind Farms

Optimized Power Dispatch for Regional Fatigue Balancing in O...

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2021 China Automation Congress, CAC 2021

作者： Lin, Kunwei Tang, Xiao-Yu Zhao, Wenbo Ling, Zhangwei State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhqiang University Hangzhou310027 China Zhqiang Academy of Special Equipment Science Hangzhou China Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province Hangzhou China

ISBN: (纸本)9781665426473

With the rapid development of offshore wind utilization, how to reduce the high cost of offshore wind farms (WFs) has become a key issue. One way is to reduce the maintenance costs, while the other is to increase the captured wind energy. Herein, a novel strategy of regional fatigue load balance islntroduced, and then an offshore wind fartn (WF) power dispatch method for regional fatigue balancing is proposed. This strategy aims to increase the captured wind energy as well as reduce the maintenance costs, by striving to decrease the number of outlier wind turbines in the fatigue distribution and then cut down the offshore WFs maintenance frequency. After modelling the offshore WF power generation and fatigue distribution, an optimization problem is established according to the proposed regional fatigue load balance strategy. The partfcle swarm optimization (PSO) algorithm is adoptedlo solve the problem of dispatch optimization. A simulation case study with an offshore WF with 49 wind turbines validates the effectiveness of the proposed strategy. In addition, as the comparison of the proposed dispatch strategy, two traditional strategies, the WF maximum power point tracking (MPPT) strategy and the farm-level overall fatigue load balance strategy, are also applied on the simulation case. The results show that the proposed strategy significantly decreases the number of outlier wind turbines in the farm, as well as maintaining the proper power generation. © 2021 IEEE

关键词： Offshore wind farms

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Eigenvector of Gram-Matrix based Open-Fault Diagnosis Method for Two-level Three-Phase Inverter

Eigenvector of Gram-Matrix based Open-Fault Diagnosis Method...

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International Conference on Power Electronics and Motion control (IPEMC)

作者： Yang Zhou Jin Zhao Yang Liu Lijun Sun Ministry of Education School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan China China Electronic Product Reliability and Environmental Testing Research Institute Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology Guangzhou China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

This paper studies the power switch open-circuit(OC) fault in two-level three-phase (2L3P) voltage source inverter (VSI). According to the topological symmetry of the inverter, when it works in healthy conditions, its phase currents are standard sine waves with only 120-degree phase difference, and the similarity between phase currents is high. When OC fault occurs, the current waveforms of both normal and fault phases will be distorted, the similarity will be changed. Therefore, this paper introduces the Gram matrix in image processing to measure the similarity and proposes a fast and computationally efficient diagnostic method based on the eigenvector of Gram-Matrix. Physical experiment shows that both single-switch fault and multiple-switch fault on the same leg can be effectively detected and located.

关键词： Legged locomotion Fault diagnosis Voltage source inverters Switches Computational efficiency Maintenance Velocity measurement

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot

Gait Planning and Motion Control Based on Vrep Simulation fo...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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