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Stability mechanism and control of the pumpable supports in longwall recovery room

International Journal of Mining Science and technology 2024年第7期34卷 957-974页

作者： Dong Zhang Jianbiao Bai Zhijun Tian Zizheng Zhang Yonghong Guo Rui Wang Ying Xu Hao Fu Shuai Yan Min Deng Shuaigang Liu State Key Laboratory of Coal Resources and Safe Mining China University of Mining and TechnologyXuzhou 221116China Key Laboratory of Xinjiang Coal Resources Green Mining Xinjiang Key Laboratory of Coal-bearing Resources Exploration and ExploitationXinjiang Engineering Research Center of Green Intelligent Coal MiningXinjiang Institute of EngineeringUrumqi 830023China Work Safety Key Laboratory on Prevention and Control of Gas and Roof Disasters for Southern Goal Mines Hunan Provincial Key Laboratory of Safe Mining Techniques of Coal MinesHunan University of Science and TechnologyXiangtan 411201China School of Mines China University of Mining and TechnologyXuzhou 221116China

The load-bearing performance(LBP)of pumpable supports(PPS)is crucial for the stability of longwall pre-driven recovery room(PRR)surrounding ***,the unbalanced bearing coefficient(UBC)of the PPS(undertaking unequal load along the mining direction)has not been investigated.A mechanical model of the PRR was established,considering the main roof cantilever beam structure,to derive an assessment formula for the load,the failure criteria,and the UBC of the ***,the generation mechanisms,and influencing factors of the UBC were *** sensitivity analysis shows that the main roof hanging length(l_(2))and the spacing between the PPS(r)significantly impact the UBC.A novel design of the PPS and the coupling control technology were proposed and applied to reduce the UBC of the PPS in the adjacent longwall *** results showed no failure of the PPS at the test site,with the UBC(ζ)reduced to 1.1 consistent with the design value(1.15)basically,fully utilizing the collaborative LBP of the ***,the maximum roof-to-floor convergence of the PRR was 234 mm,effectively controlling the stability of the surrounding rock of the PRR and ensuring the mining equipment recovery.

关键词： Pre-driven recovery room Pumpable supports Unbalanced bearing coefficient Hydraulic fracture Stability analysis Surrounding rock control

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Measurement and Analysis of Multiple Parameters of Enhanced Accelerator 18th

Measurement and Analysis of Multiple Parameters of Enhanced ...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Tian, Zihao Zhu, Lihua Hao, Jianying Liu, Ping Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin300382 China

ISBN: (纸本)9789819710713

The armature velocity, electromagnetic field, and spatiotemporal distribution of rail stress are important parameters of enhanced accelerators. It is extremely difficult to obtain dynamic parameters under extreme conditions. In order to obtain them, a multi-parameter measurement platform of enhanced accelerator is designed in this paper. The velocity of the armature and the magnetic field curve at a specific point are obtained by using a B probe, the spatiotemporal distribution characteristics of rail vibration displacement are obtained by using a laser micro displacement measurement device. Finally, the armature velocity, magnetic induction intensity B at a certain point in space, and the vibration changes of the rail at different times during the launch process are obtained through experiments. This work provides experimental basis for numerical calculation of multi field coupling and improving the service life of accelerators. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Probes

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Causality-inspired Comparative Learning Supervised Model for Domain Generalization 15

Causality-inspired Comparative Learning Supervised Model for...

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15th International Conference on Graphics and Image Processing, ICGIP 2023

作者： Zhu, Xiaosong Yang, Bin Guo, Jingfeng Yang, Genghuang Tianjin University of Technology and Education China Tianjin Key Laboratory Information Sensing and Intelligent Control China Yanshan University China

ISBN: (纸本)9781510675018

Machine learning is good at learning general knowledge and predictive knowledge from known and limited environments, and perform well in similar environments. However, their performance in unknown environments is not satisfactory. Machine learning focus on correlation learning, but correlation is not causality. The non-causal part of the correlation forms spurious correlation that affect the model's generalization ability. Therefore, it is necessary to examine machine learning from a causal perspective. By constructing structural causal models, it is found that the targets of different domains are instrumental variables of each other and can be mutually represented. They have same essential features and different domain features, which lead to causal correlation and spurious correlation with labels respectively. In this paper, a causal-inspired contrastive learning supervised model is designed to strengthen essential features and weaken domain features. With the target of improving the ability of model to capture causal correlations and reducing the interference of spurious correlations, we join transfer and autoencoder with image classification model as a cross-domain contrastive learning model. Experiments show that the proposed framework has a simple and easy-to-implement structure, it performs well on public datasets. By adopting visualization technology, the effects of this method are intuitively demonstrated. © 2024 SPIE. All rights reserved.

关键词： Machine learning

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Improved target detection algorithm based on YOLOv5s 24

Improved target detection algorithm based on YOLOv5s

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6th International Conference on control and Computer Vision, ICCCV 2024

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

ISBN: (纸本)9798400718045

Target detection is a research hotspot in the field of computer vision and machine learning, and the deep learning model greatly improves the efficiency of target detection and classification by obtaining feature information and classification through multi-layer neural networks, which is the mainstream algorithm for target detection at present. In this paper, YOLOv5s target detection algorithm is improved, and the SIoU loss function is chosen to replace the CIoU loss function used in the original model, while the SimAM attention mechanism is added to the Neck module of the YOLOv5s model, and it is proved through experiments that the improved model improves the average precision (mAP@0.5) by 0.2% over the original model, and the recall rate (Recall) is improved by 0.8%. The faster convergence and improved precision of the model further improves the performance of the model. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Adversarial machine learning

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Study of Double Degree of Freedom Solar Arrays control for Inclined-orbit Spacecraft

Study of Double Degree of Freedom Solar Arrays Control for I...

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2024 China Automation Congress, CAC 2024

作者： Peng, Rui Bai, Jiaxiang Zhu, Bin Cheng, Zhaoyang Zhang, Zhouburan Shanghai Aerospace Control Technology Institute Shanghai China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai China Shanghai Xinyuelianhui Electronic Technology Co LTD Shanghai China

ISBN: (纸本)9798350368604

The spacecraft is powered by solar arrays. Solar arrays control problem for Inclined-orbit spacecraft, which has double degree freedom, is investigated in this paper. By analyzing the variation law of solar height angle, a double degree of freedom solar arrays control algorithm is designed, and the earth-oriented mode and attitude bias mode are studied respectively. Finally, by analyzing the data from the simulation test on the ground and the in-orbit test, it can be concluded that the proposed method is simple and feasible, and can ensure that the accuracy of solar panels orientation towards the sun remains within the allowable range for an extended period. In addition, the approach presented in this work can serve as a guide for the overall design of inclined orbit spacecraft aimed for an extended lifetime. © 2024 IEEE.

关键词： Orbits

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Competitive Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1902-1904页

作者： Boxi Weng Jian Sun Gao Huang Fang Deng Gang Wang Jie Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081 Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China School of Automation Tsinghua UniversityBeijing 100084China Department of Control Science and Engineering Tongji UniversityShanghai 201804 National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China IEEE

Dear Editor,This letter is concerned with developing meta-learning models for fast,stable,and effective few-shot learning across tasks over a few training ***,deep and reinforcement learning(RL)is widely used in auton... 详细信息

关键词： robot autonomous concerned

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A 7DOF redundant manipulator inverse kinematic solution algorithm based on bald eagle search optimization algorithm

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Soft Computing 2024年第23期28卷 13681-13699页

作者： Zhao, Guojun Sun, Ying Jiang, Du Liu, Xin Tao, Bo Jiang, Guozhang Kong, Jianyi Yun, Juntong Liu, Ying Li, Gongfa Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China

Solving inverse kinematics (IK) is an excellent challenge for redundant manipulators due to their highly non-linear and complex coupling, which is not amenable to analytical solutions by conventional methods. In this paper, the conventional solution was replaced by the optimization process of a fitness function. The fitness function aims to obtain a set of solutions for the desired position of the end effector (EE). The function is based on forward kinematics;hence, this method can avoid singularities and be suitable for solving redundant manipulators. For solving this optimization problem, the bald eagle search (BES) optimization algorithm was chosen due to its easy principle and excellent performance. BES integrates the advantages of evolutionary and swarm techniques. On the one hand, BES maximizes the advantages offered by swarm intelligence (SI) in terms of searching within the best position in the swarm. On the other hand, BES capitalizes on the capability of evolutionary techniques to explore the search space frequently and avoid the local optimum. In this study, two 7-degree of freedom (DOF) manipulators were used to test the performance of BES. Meanwhile, several evolutionary and SI optimization algorithms were selected to compare with BES. The experimental results demonstrate that the BES optimization algorithm can efficiently and accurately solve the IK problem of 7DOF redundant manipulators. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Inverse kinematics

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Effect of Free-End Torsion on the Corrosion and Mechanical Properties for Mg-3Zn-0.2Ca Alloy

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Acta Metallurgica Sinica(English Letters) 2025年第1期38卷 59-70页

作者： Li-Lan Gao Jiang Ma Yan-Song Tan Xiao-Hao Sun Qi-Jun Gao De-Bao Liu Chun-Qiu Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin300384China School of Materials Science and Engineering Tianjin University of TechnologyTianjin300384China

Magnesium alloys with excellent degradability and biocompatibility are promising materials for biomedical implants,saving patients the burden of second ***,their mechanical properties and corrosion resistance are significantly below the requirements for implant *** study aims to improve the mechanical and corrosion resistance properties of Mg-3Zn-0.2Ca alloy by pre-torsion treatment,and find out the optimal shear *** rod-shaped Mg-3Zn-0.2Ca alloy specimens were pre-torsion treated at different torsion *** effect of free-end torsion on Mg-3Zn-0.2Ca alloy was characterized through microstructure analysis,mechanical testing,and corrosion ***-torsion treatment can refine grain and induce twins and dislocations in Mg-3Zn-0.2Ca *** surface hardness increases with the increase in torsion *** yield strength and ultimate strength initially increase and then decrease with increasing torsion angle,while ductility decreases with increasing torsion *** with a shear strain of 30%exhibit the highest tensile strength,reaching 284.78±10.62 MPa,with an elongation of 19.37±1.66%.Furthermore,they show a significant improvement in fatigue lives both before and after *** the stress amplitude is 120 MPa,the fatigue lives for specimens without pre-torsion treatment are 54,275 cycles and 4324 cycles before and after pre-corrosion,while they increased significantly to 92,015 cycles and 5050 cycles with the 30%shear strain,***,the 30%shear strain specimens show a significant reduction in corrosion *** conclusion,pre-torsion treatment can effectively modify the microstructure of Mg-3Zn-0.2Ca alloy,enhancing both mechanical properties and corrosion *** optimal shear strain for this improvement is 30%.This study provides a practical method to enhance the mechanical properties and corrosion resistance of Mg-3Zn-0.2Ca alloy,making it more suitable for biomedical implan

关键词： Magnesium alloy Pre-torsion Microstructure Mechanical property Corrosion resistance

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Fiber Bragg gratings inscription with a single UV laser pulse by high-temperature arc pretreatment

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Optics Express 2025年第10期33卷 21692-21706页

作者： Xin, Jingtao Liao, Jingjing Yu, Chenbo Li, Qihui Zhu, Lianqing Beijing Information Science and Technology University Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing100101 China Guangzhou Nansha Intelligent Photonic Sensing Research Institute Guangzhou100094 China Beijing Information Science and Technology University Beijing Laboratory of Optical Fiber Sensing and System Beijing130033 China

This study proposes a high-temperature arc discharge pretreatment method to enhance the photosensitivity of hydrogen-loaded germanium-doped fibers for single-pulse FBG inscription. By coupling hydrogen diffusion dynamics with hydroxyl reaction kinetics, a numerical model based on Fick’s law and Arrhenius equations was established. Finite difference analysis revealed that 400°C with 50 ms heating maximizes hydroxyl concentration while suppressing hydrogen escape. In the experiments study, the pretreatment temperature and duration are controlled by adjusting the electrode discharge power and discharge time. The effectiveness of fiber sensitization is verified through single-pulse grating writing using a phase mask and a 248 nm ultraviolet laser. After optimizing the heat treatment parameters, fiber Bragg gratings (FBGs) with a reflectivity exceeding 83.7% were successfully written using a single pulse laser of 160mJ, representing a 130-fold improvement compared to the results obtained without heat treatment. This method not only enhances the efficiency of FBG writing but also fundamentally mitigates the issue of grating erasure, significantly reducing the stability requirements for the writing system. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Fiber Bragg gratings

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Research on Automotive Parts Recognition Based on Improved YOLOv5 Algorithm

Research on Automotive Parts Recognition Based on Improved Y...

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2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024

作者： Xu, Yu Hu, Shan Ming, Rui Zhang, Tianzhi School of Automation and Electrical Engineering Tianjin University of Technology and Education Key Laboratory of Information Sensing & Intelligent Control Tianjin China

ISBN: (纸本)9781510680012

With the continuous development of the automotive industry, the target detection and recognition of automotive parts have become crucial factors for automakers to enhance automation levels. In this paper, to ensure improved detection accuracy while meeting real-time detection requirements, we propose an enhanced YOLOv5 model for automotive parts recognition. This method optimizes candidate box parameters using the K-Means algorithm, addresses feature mismatch issues through variational convolution, and optimizes the loss function using GIOU instead of IOU. Experimental results show that the improved YOLOv5 algorithm achieves an average precision of 99.1%, representing a relative improvement of 1.72% over Fast R-CNN and 3.91% over the standard YOLOv5 algorithm. Furthermore, it demonstrates excellent real-time detection performance, meeting the demands of practical application scenarios. © 2024 SPIE.

关键词： Object recognition

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