检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Wang, Zihao Wu, Bebei Liao, Jiali Li, Xifeng Wang, Chen Sun, Yanling Jin, Li Feng, Junbo Cao, Changqing School of Optoelectronic Engineering XiDian University Shannxi Xi’an710071 China No.20 Xiyuan South Street Xiyong Microelectronics Industry Park Gaoxin District Chongqing China Science and Technology on Electromechanical Dynamic Control Laboratory Shannxi Xi’an710065 China

We report in this paper the design and testing scheme of 16×16 optical phased arrays (OPAs) based on the silicon-on-insulator (SOI) platform. We improve the conventional stochastic parallel gradient descent algorithm used to calibrate its output beam, and verify the improved algorithm superiority through simulations and experiments. The experimental results are consistent with theoretical values of the OPA design, proving the high quality of the chip and the reliability of the algorithm. We assume that this OPA design approach and the algorithm can provide help for the development and application of LiDAR. © 2022, The Authors. All rights reserved.

关键词： Calibration

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A noncontact method for UAV electrostatic charge measurement incorporating the influence of parasitic capacitance

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Measurement 2025年 254卷

作者： Zhongzheng He Sichao Qin Hanzhou Wu Bing Wang Yu Gong Xi Chen School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Science and Technology on Electromechanical Dynamic Control Laboratory China Beijing Institute of Special Mechanic-Electric Beijing 100012 China

During flight operations, unmanned aerial vehicles (UAVs) accumulate significant electrostatic charges, which may lead to electrostatic discharge events, potentially damaging onboard electronic systems and compromising flight safety. Accurate measurement of these accumulated charges is crucial for optimizing anti-static protection measures. First, a refined physical model for UAV charge measurement is proposed, which incorporates the influence of parasitic capacitance. The model utilizes the electrode’s spatial sensitivity to establish a quantitative relationship between the induced charge on the electrode and the UAV electrostatic charge. Then, a noncontact method for measuring UAV charge is proposed, utilizing the spatial sensitivity at the UAV’s position and the induced charge on the electrode to estimate the UAV charge. Further, experimental validation was conducted using electrometer measurements as the reference values. The results demonstrate strong correlation and consistency between measured and reference values, with measurement error maintained within ± 10 %. Finally, the proposed method was applied to measure the UAV charge, and its experiment result ranges from 9 to 18 nC. The proposed method accurately measures the UAV charge during flight and can be used to evaluate electrostatic discharge risk, providing a foundation for the anti-static design of UAVs and enhancing flight safety.

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An open dataset for intelligent recognition and classification of abnormal condition in longwall mining

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Coal International 2024年第4期272卷 22-35页

作者： Yang, Wenjuan Zhang, Xuhui Ma, Bing Wang, Yanqun Wu, Yujia Yan, Jianxing Liu, Yongwei Zhang, Chao Wan, Jicheng Wang, Yue Huang, Mengyao Li, Yuyang Zhao, Dian School of Mechanical Engineering Xi’an University of Science and Technology No.58 Mid-Yanta Road Xi’an710054 China Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control No.58 Yanta Road Xi’an710054 China MARCO automatic control system development Co. LTD No.20 Fenghui South Road Xi’an710054 China

The underground coal mine production of the fully mechanised mining face exists many problems, such as poor operating environment, high accident rate and so on. Recently, the intelligent autonomous coal mining is gradually replacing the traditional mining process. The artificial intelligence technology is an active research area and is expected to identify and warn the underground abnormal conditions for intelligent longwall mining. It is inseparable from the construction of datasets, but the downhole dataset is still blank at present. This work develops an image dataset of underground longwall mining face (DsLMF+), which consists of 138004 images with annotation 6 categories of mine personnel, hydraulic support guard plate, large coal, towline, miners’ behaviour, and mine safety helmet. All the labels of dataset are publicly available in YOLO format and COCO format. The availability and accuracy of the datasets were reviewed by experts in coal mine field. The dataset is open access and aims to support further research and advancement of the intelligent identification and classification of abnormal conditions for underground mining. © 2024 Tradelink Publications Ltd.. All rights reserved.

关键词： Longwall mining

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Numerical simulation and experimental research on Taylor Couette flow characteristics in air gap of aviation motor

Numerical simulation and experimental research on Taylor Cou...

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CSAA/IET International Conference on Aircraft Utility Systems (AUS 2024)

作者： Hui Ma Shuyue Liang Hongbo Zhan Lin Qi Weijian Chen Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration No.33 Shuige Road Nanjing People's Republic of China Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Areonautics and Astronautics No.29 Yudao Street Nanjing People's Republic of China

ISBN: (数字)9781837242108

A test bench with PIV technology was built and visualization research on Taylor vortex between concentric rotating cylinders was carried out to explore the flow morphology within the annular gap by changing the rotational speed of the inner cylinder. The numerical method and accuracy were verified by experiments. The selected turbulence model was then applied for numerical simulation of the Taylor Couette flow in a simplified air gap model of an aviation motor with smooth inner and outer walls. The Taylor Couette flow characteristics in the air gap under varying rotational speed were studied, and simulation results were given for flow with axial flow and without axial flow.

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Research on the Characteristics of Wireless Power Transfer in Ferromagnetic Metal Pipe

Research on the Characteristics of Wireless Power Transfer i...

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作者： Li Changsheng Sun Wei Hu Defu Liu Yong Science and Technology on Electromechanical Dynamic Control Laboratory Ministerial Key Laboratory of ZNDY Nanjing University of Science and Technology

With the development of society, radio energy transmission technology has been paid more and more attention. However, in the actual application environment, the surrounding metal environment has a significant impact on the radio energy transmission performance. Based on the technology of MRR radio energy transmission, this paper establishes a two coil radio energy transmission model, and analyzes the influence of metal environment on the coil self inductance L, mutual inductance m and coil resistance R of the radio energy transmission system by finite element simulation. On this basis, aiming at the ferromagnetic metal environment, the steel pipe is selected as the research object to study the relationship between coil diameter and mutual inductance in the metal pipe, and the relationship between coil diameter and metal pipe diameter when the maximum mutual inductance is obtained through fitting analysis. At the same time,through the experiment, the mutual inductance between the coils of the wireless energy system in the steel tube is verified, and the experimental results are very consistent with the theory.

关键词： WPT Research on the Characteristics of Wireless Power Transfer in Ferromagnetic Metal Pipe

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Pedestrian Dead Reckoning Assisted by Motion Pattern Recognition

SSRN

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SSRN 2022年

作者： Yang, Wanpeng Li, Qing Beijing Information Science & Technology University Beijing100192 China Beijing Key Laboratory of High Dynamic Navigation Technology Beijing100192 China Ministry of Education Key Laboratory of Modern Measurement & Control Technology Beijing100192 China

The pedestrian dead reckoning (PDR) system based on inertial measurement units (IMU) has become the preferred indoor positioning device because it adapts to the environment without beacons. Aiming at the problem of PDR positioning error accumulation and heading divergence over time in complex motion mode, this paper proposes a dead reckoning algorithm assisted by adaptive human motion pattern recognition. Firstly, a feature-level LSTM-CNN network is designed to recognize human motion. Secondly, the step frequency detection threshold and step length parameters are adaptively determined according to the recognized motion mode. The UKF fusion filter combined with IMU and magnetometer is used to solve the problem of heading divergence. In addition, the barometer is introduced to calculate the 3D position information. The experimental results show that the average accuracy of motion recognition can reach 96.83%. In multi-storey buildings, the horizontal positioning error is 0.8925m, and the elevation positioning error is 0.9010m © 2022, The Authors. All rights reserved.

关键词： Pattern recognition

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A Reinforcement Learning-Based Energy Management Strategy for Fuel Cell Electric Vehicle Considering Coupled-Energy Sources Degradations

SSRN

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SSRN 2023年

作者： Huo, Weiwei Liu, Teng Li, Fajia Institute of Electromechanical Engineering Beijing Information Science & Technology University Beijing100192 China Collaborative Innovation Center of Electric Vehicles in Beijing Beijing Information Science & Technology University Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China University of Jinan Jinan250024 China

The energy management strategy (EMS) is crucial for fuel cell electric vehicles (FCEV) by decreasing the equivalent fuel consumption and postponing fuel cell (FC) deterioration. An improved EMS based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) deep reinforcement learning considering energy sources degradation and economic factor is proposed in this paper. The working condition identification (WCI) implemented by ensemble bagged trees (EBT) is used to expand the diversity of EMS application scenarios. The drastic loading change of FC is avoided for minimizing the instantaneous cost (MIC), which reduces FC degradation greatly. TD3 is applied to optimize the total cost combined with WCI and MIC. The training results based on 13 classic working conditions show that the degradation of the FC system is effectively suppressed, decreasing the overall cost and accelerating the algorithm's convergence time significantly. © 2023, The Authors. All rights reserved.

关键词： Energy management

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Identification of abnormal conditions in high-dimensional chemical process based on feature selection and deep learning

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Chinese Journal of Chemical Engineering 2020年第7期28卷 1875-1883页

作者： Wende Tian Zijian Liu Lening Li Shifa Zhang Chuankun Li College of Chemical Engineering Qingdao University of Science&TechnologyQingdao 266042China Qingdao NOVAN Electromechanical Technology Qingdao 266100China State Key Laboratory of Safety and Control for Chemicals SINOPEC Qingdao Research Institute of Safety EngineeringQingdao 266071China

Identification of abnormal conditions is essential in the chemical *** the rapid development of artificial intelligence technology,deep learning has attracted a lot of attention as a promising fault identification method in chemical process *** the high-dimensional data identification using deep neural networks,problems such as insufficient data and missing data,measurement noise,redundant variables,and high coupling of data are often *** tackle these problems,a feature based deep belief networks(DBN)method is proposed in this ***,a generative adversarial network(GAN)is used to reconstruct the random and non-random missing data of chemical ***,the feature variables are selected by Spearman’s rank correlation coefficient(SRCC)from high-dimensional data to eliminate the noise and redundant variables and,as a consequence,compress data dimension of chemical ***,the feature filtered data is deeply abstracted,learned and tuned by DBN for multi-case fault *** application in the Tennessee Eastman(TE)process demonstrates the fast convergence and high accuracy of this proposal in identifying abnormal conditions for chemical process,compared with the traditional fault identification algorithms.

关键词： Chemical process Deep Belief Networks Fault identification Generative Adversarial Networks Spearman Rank Correlation

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Water absorptivity and frost resistance performance of self-ignition coal gangue autoclaved aerated concrete

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Journal of Infrastructure Preservation and Resilience 2021年第1期2卷 1-10页

作者： Cong, Xinyu Tan, Yiqiu Lu, Shuang Wang, Zhaojia Huang, Tianyong School of Transportation Science and Engineering Harbin Institute of Technology Huanghe Road 73 Harbin150090 China School of Civil Engineering Harbin Institute of technology Harbin150090 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education 9 Harbin Institute of Technology Harbin150090 China State Key Laboratory of Solid Waste Reuse for Building Materials Beijing Building 11 Materials Academy of Science Research Beijing100041 China

Self-ignition coal gangue (SCG) used as one of precursors to fabricate autoclaved aerated concrete (AAC). Aiming at studying water absorptivity and frost resistance performance of SCG-based AAC (SCGAAC), three-period water absorption tests and freeze-thaw tests were carried out and the corresponding results were recorded and analyzed. In order to modify the water absorptivity of SCGAAC, foam stabilizer was applied to adjust pore structure while calcium stearate was expected to change hydrophilic feature of SCG. It was demonstrated that the compressive strength of SCGAAC containing foam stabilizer or calcium stearate declined at different levels. For water absorption, foam stabilizer failed to decrease the water content and even increased water absorption rates. Calcium stearate controlled water absorption rate successfully although the ultimate water content hardly reduced. All of the SCGAAC samples exhibited intact appearance after 50 freeze-thaw cycles and showed excellent frost resistance performance. Three models were proposed to predict water absorptivity and frost resistance performance of SCGAAC and the corresponding prediction results matched test resulted well. © The Author(s) 2021.

关键词： Coal

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Mapping-based drift fault repair method for array inertial devices

Mapping-based drift fault repair method for array inertial d...

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9th International Symposium on Test Automation & Instrumentation (ISTAI 2022)

作者： H. Chen Z. Su Z. Xu Q. Li Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science & Technology University Beijing People's Republic of China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing People's Republic of China

The array inertial device can significantly improve the positioning accuracy of the wearable autonomous positioning system, but it is difficult to avoid faults in the working process of the array inertial device, even if the fault is detected, the positioning system will fail. Aiming at the fault that the acceleration drift of array inertial device increases in the process of motion in the wearable autonomous positioning system of emergency rescue personnel, a fault repair method of acceleration array based on BP neural network was proposed. Through data fusion of accelerometer and gyroscope, a fault repair method based on mapping contrast elimination is implemented. The experimental results of twelve IMU array data fusion and fault repair show that the proposed method can be used to repair the typical faults with the increase of accelerometer drift in the array inertial device.

关键词： accelerometers backpropagation fault diagnosis gyroscopes inertial systems sensor fusion

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