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intelligent equalizing pressure ventilation system for coal mine: A case study of the 104 coal mining face in Shige Tai Mine

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Energy Reports 2025年 13卷 4998-5005页

作者： Geng, Feng Li, Wei Liu, Yanqing Peng, Ran Li, Zongxiang Liu, Hanwu Intelligent Control Technology Co. Ltd. Beijing100013 China Mine Intelligent Ventilation Division China Coal Research Institute Beijing100013 China Beijing Engineering and Research Center of Mine Safe Beijing100013 China National Key Laboratory of Intelligent Coal Mining and Rock Strata Control Beijing100013 China Safety Science and Engineering College Liaoning Technical University Liaoning 123000 China Beijing100083 China

This study investigates the application of an intelligent equalizing pressure ventilation system in the 104 coal mining face of the Shige Tai Mine. The relationship between the balanced pressure window opening area and the face air volume, as well as the equalizing pressure, was analyzed. A formula for calculating the local resistance of the balanced pressure window was derived. The combined regulation of the equalizing pressure local fan and the balanced pressure window was used to develop an intelligent equalizing pressure ventilation system, which can remotely and intelligently regulate the equalizing pressure of the mining face. The results show that the local wind resistance of the balanced pressure window is negatively exponentially related to its ventilation area, and the ventilation resistance of the working face is positively correlated with the air supply volume. After the combined equalizing pressure regulation, the volume fractions of CO2 and CO were significantly reduced, meeting the required air volume of the working face and achieving the expected effect of equalizing pressure ventilation. This study provides theoretical references for the intelligent equalizing pressure ventilation in coal mine mining faces. © 2025 The Authors

关键词： Coal mines

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Sim2Real Learning With Domain Randomization for Autonomous Guidewire Navigation in Robotic-Assisted Endovascular Procedures

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IEEE Transactions on Automation science and engineering 2025年 22卷 13842-13854页

作者： Yao, Tianliang Wang, Haoyu Lu, Bo Ge, Jiajia Pei, Zhiqiang Kowarschik, Markus Sun, Lining Seneviratne, Lakmal Qi, Peng Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology Department of Control Science and Engineering Shanghai200092 China Shanghai University of Engineering Science School of Electronic and Electrical Engineering Shanghai201620 China Soochow University Robotics and Microsystems Center School of Mechanical and Electrical Engineering Jiangsu Suzhou215131 China Advanced Therapies Siemens Healthineers Ltd. Shanghai201318 China University of Shanghai for Science and Technology Oriental Pan-Vascular Devices Innovation College Shanghai200093 China Bavaria Forchheim91301 Germany Khalifa University KUCARS Department of Mechanical and Nuclear Engineering Abu Dhabi United Arab Emirates Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center Shanghai East Hospital Department of Control Science and Engineering School of Medicine Shanghai200092 China

Over the past decade, significant advancements have been made in the research and industrialization of robotic systems for endovascular procedures, yet their clinical application remains relatively limited. Physicians commonly report that these robots lack certain intelligent assistive capabilities during procedures. There has been increasing interest and attempts to apply learning-centered algorithms to the training and enhancement of surgical robot skills. This paper proposes an autonomous navigation algorithm for interventional guidewires that is initially trained solely in a virtual simulation environment and subsequently deployed to a real-world robot. Experimental results demonstrate the feasibility of this approach for real-world applications. The proposed approach can help physicians reduce the learning curve for guidewire manipulation and elevate the robot to a higher level of autonomous operation, thereby breaking through the current bottleneck in the level of intelligence for clinical applications of interventional robots. It also holds promise for bringing intelligent transformation to future interventional procedures. © 2004-2012 IEEE.

关键词： Adversarial machine learning

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Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios With Multiagent Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 317-326页

作者： Liu, Weiwei Hu, Wenxuan Jing, Wei Lei, Lanxin Gao, Lingping Liu, Yong Zhejiang University The Advanced Perception on Robotics and Intelligent Learning Lab College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang 310027 China Alibaba DAMO Academy Autonomous Driving Lab Zhejiang 311121 China Huzhou University College of Information Engineering Zhejiang 313000 China

Autonomous vehicles trained through multiagent reinforcement learning (MARL) have shown impressive results in many driving scenarios. However, the performance of these trained policies can be impacted when faced with diverse driving styles and personalities, particularly in highly interactive situations. This is because conventional MARL algorithms usually operate under the assumption of fully cooperative behavior among all agents and focus on maximizing team rewards during training. To address this issue, we introduce the personality modeling network (PeMN), which includes a cooperation value function and personality parameters to model the varied interactions in high-interactive scenarios. The PeMN also enables the training of a background traffic flow with diverse behaviors, thereby improving the performance and generalization of the ego vehicle. Our extensive experimental studies, which incorporate different personality parameters in high-interactive driving scenarios, demonstrate that the personality parameters effectively model diverse driving styles and that policies trained with PeMN demonstrate better generalization than traditional MARL methods. © 2007-2012 IEEE.

关键词： Reinforcement learning

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Research on the Characteristics of Multi-Outlet Internal Rotary Nozzle 14th

Research on the Characteristics of Multi-Outlet Internal Rot...

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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Jiang, Wenbo Xu, Weipeng College of Mechanical and Electronic Engineering Shandong University of Science and Technology Qingdao266590 China State Key Laboratory of Intelligent Coal Mining and Strata Control Shanghai China

ISBN: (纸本)9789819626243

This paper proposes a multi-outlet internal rotating nozzle structure to address the issues of soot generation and friction/wear associated with mineral mining. The atomization and jet characteristics of the nozzle are simulated and analysed using CFD software, and the effects of initial pressure and outlet diameter on the jet effect of the internal rotating nozzle are investigated. The findings indicate that the jet velocity in the lateral exit channel and the canter exit of the multi-outlet nozzle increases with an increase in the initial pressure. Conversely, the exit flow velocity of the nozzle at a constant initial pressure shows a gradual decrease with an increase in the exit diameter. At low pressure and outlet diameter, the atomization effect of the nozzle is not significant. However, the atomization angle increases gradually with an increase in the initial pressure and outlet diameter. Under the same pressure, the atomization angle shows a tendency of increasing and then decreasing with the increase of outlet diameter. And the best atomization angle is obtained when the outlet diameter is 1.3 mm and the initial pressure is 0.7 MPa. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nozzles

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Force Analysis and Reliability Improvement Method for the Conical Picks of the Coal Mining Machine Drum 14th

Force Analysis and Reliability Improvement Method for the Co...

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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Wang, Shuxue Xu, Weipeng College of Mechanical and Electronic Engineering Shandong University of Science and Technology Qingdao266590 China State Key Laboratory of Intelligent Coal Mining and Strata Control Shanghai China

ISBN: (纸本)9789819626243

In response to the situation where the first blade pick of a coal mining machine is prone to failure when cutting hard coal, the working process of the drum was simulated using finite element method. The force on the pick at different positions was obtained, and the main reasons for the failure of the first blade pick were analyzed. The effectiveness and practicality of reducing the force on the first blade pick were proposed and simulated. The research results indicate that the force on the first blade tooth can be effectively reduced by increasing the diameter of the end disk. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Coal mines

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Research on Meshing Characteristics and Vibration of Aluminum Miner Based on MASTA 14th

Research on Meshing Characteristics and Vibration of Aluminu...

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14th International Workshop of Advanced Manufacturing and Automation, IWAMA 2024

作者： Dong, Guanzhan Xu, Weipeng Gao, Kuidong College of Mechanical and Electronic Engineering Shandong University of Science and Technology Qingdao266590 China State Key Laboratory of Intelligent Coal Mining and Strata Control Shanghai China

ISBN: (纸本)9789819626243

Aiming at the mechanical continuous operation of bauxite mining process, firstly, an improved scheme of cutting bauxite with an 8-pole motor shearer is proposed, which is practical and feasible, and a 3D model is established in Solid Edge. Secondly, considering the higher meshing frequency of high-speed gear in the cutting part, the meshing characteristics under different loads were investigated by MASTA software, and the laws of contact stress, meshing dislocation and trans-mission error were obtained. Finally, the vibration displacement of one axis is obtained in view of the significant influence of individual order energy on the vibration of the shell under rated working conditions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bauxite deposits

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Complementary Learning Subnetworks Towards Parameter-Efficient Class-Incremental Learning

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IEEE Transactions on Knowledge and Data engineering 2025年第6期37卷 3240-3252页

作者： Li, Depeng Zeng, Zhigang Dai, Wei Suganthan, Ponnuthurai Nagaratnam Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Qatar University Kindi Center for Computing Research College of Engineering Doha2713 Qatar

In the scenario of class-incremental learning (CIL), deep neural networks have to adapt their model parameters to non-stationary data distributions, e.g., the emergence of new classes over time. To mitigate the catastrophic forgetting phenomenon, typical CIL methods either cumulatively store exemplars of old classes for retraining model parameters from scratch or progressively expand model size as new classes arrive, which, however, compromises their practical value due to little attention paid to parameter efficiency. In this paper, we contribute a novel solution, effective control of the parameters of a well-trained model, by the synergy between two complementary learning subnetworks. Specifically, we integrate one plastic feature extractor and one analytical feed-forward classifier into a unified framework amenable to streaming data. In each CIL session, it achieves non-overwritten parameter updates in a cost-effective manner, neither revisiting old task data nor extending previously learned networks;Instead, it accommodates new tasks by attaching a tiny set of declarative parameters to its backbone, in which only one matrix per task or one vector per class is kept for knowledge retention. Experimental results on a variety of task sequences demonstrate that our method achieves competitive results against state-of-the-art CIL approaches, especially in accuracy gain, knowledge transfer, training efficiency, and task-order robustness. Furthermore, a graceful forgetting implementation on previously learned trivial tasks is empirically investigated to make its non-growing backbone (i.e., a model with limited network capacity) suffice to train on more incoming tasks. © 2025 IEEE.

关键词： Contrastive Learning

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Research on Fault Diagnosis Method for Rolling Bearings Based on Improved ConvNext V2

Research on Fault Diagnosis Method for Rolling Bearings Base...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Qin, Feifan Zhang, Chao Wang, Jianguo Wu, Le Wu, Yangbiao Ouyang, Bing Liu, Guiyi College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China

ISBN: (纸本)9783031734069

Aiming to address issues such as insensitivity to fault characteristics, inadequate feature extraction, and susceptibility to external environmental interference in traditional bearing fault diagnosis methods, an improved approach to rolling bearing fault diagnosis based on ConvNext V2 is proposed. Firstly, leveraging the advantages of wavelet time-frequency analysis, one-dimensional vibration signals collected from the experimental setup are transformed into two-dimensional images containing abundant time-frequency information using continuous wavelet transform. Secondly, the next-generation convolutional neural network ConvNext V2 is introduced as the underlying network for rolling bearing fault diagnosis, and the Efficient Channel Attention (ECA) network is incorporated to enhance the feature extraction capability of the Block module in the base network. Subsequently, the wavelet time-frequency images are used as feature map inputs to the improved ConvNext V2 network for training, enabling the diagnosis and recognition of rolling bearing faults. Finally, experimental results demonstrate that the proposed method exhibits good fault recognition accuracy and stability in laboratory data, with high generalization capability, thereby offering a new solution for rolling bearing fault diagnosis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Roller bearings

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Conditional Disturbance Compensation-Based Fault-Tolerant Group Consensus control for MASs: An Event-Based Switching Method

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IEEE Transactions on Automation science and engineering 2025年 22卷 13828-13841页

作者： Liu, Pei-Ming Guo, Xiang-Gui Wang, Jian-Liang Che, Wei-Wei Wu, Zheng-Guang University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering Beijing100083 China University of Science and Technology Beijing Shunde Innovation School Foshan528000 China Beihang University Hangzhou Innovation Institute Autonomous Intelligent Systems Department Hangzhou310051 China Northeastern University College of Information Science and Engineering Shenyang266071 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China

With respect to the group consensus control for multi-agent systems (MASs) with disturbances and actuator nonidentical and unknown direction faults (NUDFs), this paper proposes a novel fault-tolerant control scheme by incorporating an event-based switching function and a saturation function. The event-based switching function is implemented to directly switch to the desired working mode, thereby reducing invalid switching after a reverse fault. Concurrently, the saturation function, acting at the software level, can not only prevent the instantaneous impact of excessive reverse input caused by a reverse fault, but also eliminate input peaking and state chattering after switching the working mode. It is worth mentioning that the proposed switching-based fault-tolerant control method can avoid the control chocks and excessive control gains as in the existing methods by using Nussbaum functions and thus improve the transient performance. Additionally, for disturbances, the designed conditional disturbance compensation mechanism ensures a smaller steady-state error, and less energy consumption by utilizing beneficial disturbances and compensating for harmful ones. Besides, the conditional compensation mechanism also reduces the saturation error. Finally, the effectiveness of the proposed control scheme are verified through a simulation example of uncrewed aerial vehicles (UAVs). © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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