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system Reliability and Safety engineering (SRSE), International Conference on

作者： Chao Zhang Sijuan Chen Ming Yang Ruoyu Zhu Jiajun Sun Department of Science and Technology Innovation State Nuclear Power Automation System Engineering Company Shanghai China Institute for Advanced Study in Nuclear Energy & Safety College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen City Guangdong Province China Power Plant Control Center State Nuclear Power Automation System Engineering Company Shanghai China

In the operation process of the power plant, in addition to the operating state information of the power plant process systems and components is monitored by Industrial control systems (ICSs), a large number of the operating state information of ICSs and its components themselves can be obtained. These information helps operators to understand the operation safety state of ICSs themselves, and whether ICSs operate reliably, which plays an important role in maintaining the normal operation of the power plant, controlling abnormal events and mitigating the development of accidents. This paper proposes an integrated methodological framework for real-time risk awareness and prediction of ICS based on the particle filtering model whose features are updating monitoring data and predicting the state transition process, and focus on the measurement of risk states, identification of critical risk states and key components, modeling of the state transition process, prediction of risk levels and estimation of remaining arrival time of high-risk residual. The assumption that the transition probability matrix of system states does not change over time in traditional Markov predictions is discarded in this proposed method. Compared with the traditional ICS safety analysis method, this method can provide global and systemic risk insights for ICS risk situation, with a better real-time performance, and it is a kind of more scientific and objective measurement for ICS risk situation.

关键词： Process control Predictive models Particle measurements Real-time systems Data models Time measurement Safety

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Learning Pre-Grasp Manipulation of Flat Objects in Cluttered Environments using Sliding Primitives

Learning Pre-Grasp Manipulation of Flat Objects in Cluttered...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jiaxi Wu Haoran Wu Shanlin Zhong Quqin Sun Yinlin Li State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China Department of Automation University of Science and Technology of China Heifei China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing China Science and Technology on Thermal Energy and Power Laboratory Wuhan China

Flat objects with negligible thicknesses like books and disks are challenging to be grasped by the robot because of the width limit of the robot's gripper, especially when they are in cluttered environments. Pre-grasp manipulation is conducive to rearranging objects on the table and moving the flat objects to the table edge, making them graspable. In this paper, we formulate this task as Parameterized Action Markov Decision Process, and a novel method based on deep reinforcement learning is proposed to address this problem by introducing sliding primitives as actions. A weight-sharing policy network is utilized to predict the sliding primitive's parameters for each object, and a Q-network is adopted to select the acted object among all the candidates on the table. Meanwhile, via integrating a curriculum learning scheme, our method can be scaled to cluttered environments with more objects. In both simulation and real-world experiments, our method surpasses the existing methods and achieves pre-grasp manipulation with higher task success rates and fewer action steps. Without fine-tuning, it can be generalized to novel shapes and household objects with more than 85% success rates in the real world. Videos and supplementary materials are available at https://***/view/pre-grasp-sliding.

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Shakedown Analysis of a Reusable Space Capsule

SSRN

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SSRN 2022年

作者： Chen, Geng Wang, Xin Liu, Feng Zhou, Zhiyong Zhang, Lele School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China National International Science and Technology Cooperation Base Beijing Jiaotong University Beijing100044 China Beijing Institute of Spacecraft System Engineering Beijing100094 China

As the main component of the crewed spacecraft, the space capsule used for future space missions, especially for the deep-space explorations, must be safe, lightweight, and reusable at the same time. Conventional elastic limit-based design approach fails to meet with these requirements simultaneously. To investigate if elastic limit can be replaced by shakedown limit as a new criterion, in this paper, the shakedown limit of a space capsule of reduced size subjected to a time-varied inner pressure was numerically determined. The results are confronted to comparable studies and to own experimental results. This way, the study not only shows that the shakedown behavior of the space capsule exists and can be captured by the elaborated numerical and experimental procedure, but also reveals that the shakedown theory and methods can become viable means for designing similar lightweight structures used in the future reusable spacecraft. © 2022, The Authors. All rights reserved.

关键词： Numerical methods

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MAPPG: Multi-Agent Phasic Policy Gradient

MAPPG: Multi-Agent Phasic Policy Gradient

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IEEE Conference on Decision and control

作者： Qi Zhang Xuetao Zhang Yisha Liu Xuebo Zhang Yan Zhuang Intelligent Robotic Laboratory School of Artificial Intelligence School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China Tianjin Key Laboratory of Intelligent Robotics College of Artificial Intelligence Institute of Robotics and Automatic Information System (IRAIS) Nankai University Tianjin China

We propose a Multi-Agent Phasic Policy Gradient (MAPPG) algorithm, which can assist agents to further alleviate the non-stationarity of the environment. Different from the existing methods, the auxiliary phase is introduced to train the local policy directly by using the environment state, which can be naturally integrated into other algorithms. Specifically, the hidden layer feature sharing is proposed, which ensures feature sharing between the global value network and the local policy network for the first time. Meanwhile, mirror descent is utilized to iteratively update the policy in the auxiliary stage, which makes the policy update more robust. Through a series of evaluations on multi-agent Particle and multi-agent Mujoco benchmark environments, the experimental results show that our method achieves higher rewards than state-of-the-art benchmarks.

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The effectiveness of bisulfite-activated permanganate technology to enhance the coagulation efficiency of Microcystis aeruginosa

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Chinese Chemical Letters 2020年第6期31卷 1545-1549页

作者： Yating Zhu Jinfeng Ling Lei Li Xiaohong Guan State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and EngineeringTongji UniversityShanghai 200092China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China International Joint Research Center for Sustainable Urban Water System Tongji UniversityShanghai 200092China

The effects of bisulfite-activated permanganate technology(PM/BS)as a pre-oxidation process on enhancing Microcystis aeruginosa(***)removal by post coagulation were *** results demonstrated that pretreatment with PM/BS process effectively promoted the algae removal by coagulation with Al2(SO4)3 as the coagulant and this phenomenon was more obvious with the increase of water *** to the sole coagulation,PM/BS pre-oxidation combing with coagulation could neutralize the zeta potential of algal cells effectively,decrease the algal cell size,and lead to the formation of more compact flocs due to the in-situ generated *** effect of oxidant dosages on algal organic matter(AOM)was also studied and no obvious release of macromolecular substances was observed with the dosage of KMn04 increasing from 3.0 mg/L to 7.0 mg/L,suggesting the integrity of algal cells at a high KMn04 ***,PM/BS pre-oxidation could lead to the decrease of most analyzed disinfection by-products(DBPs)at a Al2(SO4)3 dosage of 40.0 mg/*** algae removal efficiency was also significantly enhanced by PM/BS pre-oxidation in the test using real algae-laden *** study indicated that PM/BS process might be a potential assistant technology for algae removal by subsequent coagulation.

关键词： Microcystis aeruginosa Permanganate Bisulfite Pre-oxidation Coagulation

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The Investigation of Removal and Mechanism by Different Permeable Paving systems on Runoff Pollutants

SSRN

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SSRN 2024年

作者： Zhang, Ziyang Yang, Ying Li, Zhifei Chen, Hongrui Zhang, Xiaoran Gong, Yongwei Tan, Chaohong Li, Haiyan Key Laboratory of Urban Stormwater System and Water Environment Ministry of Education Beijing University of Civil Engineering and Architecture Beijing102616 China Beijing Energy Conservation & Sustainable Urban and Rural Development Provincial Ministry Co-construction Collaboration Innovation Center Beijing100044 China Beijing General Municipal Engineering Design ＆ Research Institute Co. Ltd Beijing100082 China CRRC Environmental Science & Technology Cooperation Beijing100067 China Beijing Engineering Research Center of Sustainable Urban Sewage System Construction and Risk Control Beijing University of Civil Engineering and Architecture Beijing100044 China

In order to investigate the runoff pollutant control effects by different types of permeable paving systems (PPS), Porous asphalt (PA), Porous concrete (PC), Cement brick (CTB), Ceramic brick (CCB), Sand base brick (SBB) and Shale brick (SB) were selected. The removal effects and mechanisms of six PPS and individual filler layer on chemical oxygen demand (COD), ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3-N), total nitrogen (TN) and total phosphorus (TP)were investigated. Studies have shown that the removal of runoff pollutants varies widely among different PPS. PA had the best removal effect for nearly all runoff pollutants, which the maximum removal rate was 100% for both COD and NH4+-N. Permeable bricks could effectively control on NO3-N and TN pollutants, which the best removal efficiency were more than 94% for SB. Compared with other runoff pollutants, PC was more effective in removing TP with a removal rate of 95.8%. Furthermore, compared with surface material, base layer, subbase layer and soil layer were the most effective in controlling pollution in runoff, which the removal rate were more than 80%. Due to the deeper length, pollutants in runoff could contact with filler longer time and increased the removal efficiency. At the same time, graded gravel and medium sand have a stronger adsorption capacity for pollutants in runoff, resulting in a better purification. This study provides theoretical and practical significance not only for runoff pollution control, but also for the design and use of PPS in runoff. © 2024, The Authors. All rights reserved.

关键词： Fillers

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Topology-Guided Perception-Aware Receding Horizon Trajectory Generation for UAVs

Topology-Guided Perception-Aware Receding Horizon Trajectory...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Gang Sun Xuetao Zhang Yisha Liu Hanzhang Wang Xuebo Zhang Yan Zhuang Intelligent Robotic Laboratory School of Artificial Intelligence also School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China Tianjin Key Laboratory of Intelligent Robotics College of Artificial Intelligence the Institute of Robotics and Automatic Information System (lRAIS) Nankai University Tianjin China

The perception-aware motion planning method based on the localization uncertainty has the potential to improve the localization accuracy for robot navigation. How-ever, most of the existing perception-aware methods pre-build a global feature map and can not generate the perception- aware trajectory in real time. This paper proposes a topology- guided perception-aware receding horizon trajectory generation method, which contains a topology-guided position trajectory generation and a perception-aware yaw angle trajectory generation. Specifically, a memorable active map is built by selectively storing the visual landmarks. After that, a library of candidate topological trajectories are generated, which are then evaluated in terms of the perception quality based on the active map, smoothness, collision possibility and feasibility. In addition, the yaw angle trajectory is obtained through a front-end multiple refined path search and a back-end path- guided trajectory optimization. Comparative simulation and real-world experiments are carried out to confirm that the proposed method can keep more visual features in view and reduce the localization error.

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MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery

arXiv

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arXiv 2025年

作者： Li, Yansheng Wu, Yuning Cheng, Gong Tao, Chao Dang, Bo Wang, Yu Zhang, Jiahao Zhang, Chuge Liu, Yiting Tang, Xu Ma, Jiayi Zhang, Yongjun Information and computing science from Shandong University Weihai China Pattern recognition and intelligent system from the Huazhong University of Science and Technology Wuhan China Computer science and technology from Wuhan University Wuhan China Xidian University Xi’an China Pattern recognition and intelligent systems from Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong China University of Science and Technology Remote sensing science and technology from Wuhan University Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Electronic circuit and system from Xidian University Xi’an China University of Colorado at Boulder BoulderCO United States Control science and engineering from the Huazhong University of Science and Technology Wuhan China Geodesy and photography from Wuhan University Wuhan China

Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples. This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios. To address this limitation, we introduce the Million-scale finE-grained geospatial scEne classification dataseT (MEET), which contains over 1.03 million zoom-free remote sensing scene samples, manually annotated into 80 fine-grained categories. In MEET, each scene sample follows a scene-in-scene layout, where the central scene serves as the reference, and auxiliary scenes provide crucial spatial context for fine-grained classification. Moreover, to tackle the emerging challenge of scene-in-scene classification, we present the Context-Aware Transformer (CAT), a model specifically designed for this task, which adaptively fuses spatial context to accurately classify the scene samples. CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes. Based on MEET, we establish a comprehensive benchmark for fine-grained geospatial scene classification, evaluating CAT against 11 competitive baselines. The results demonstrate that CAT significantly outperforms these baselines, achieving a 1.88% higher balanced accuracy (BA) with the Swin-Large backbone, and a notable 7.87% improvement with the Swin-Huge backbone. Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping. The source code and dataset will be publicly available at https://***/project/***. Copyright © 2025, The Authors. All rights reserved.

关键词： Image classification

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A Computationally Efficient Target Localization Algorithm in Underwater Wireless Sensor Networks

A Computationally Efficient Target Localization Algorithm in...

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International Conference on Computers, Communications, and systems (ICCCS)

作者： Xiaojun Mei Huafeng Wu Dezhi Han Xinqiang Chen Jiangfeng Xian Bing Han College of Information Engineering Shanghai Maritime University National Engineering Research Center of Ship & Shipping Control System Shanghai Ship and Shipping Research Institute Co. Ltd Shanghai China Merchant Marine College Shanghai Maritime University Shanghai China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai China Hubei Key Laboratory of Inland Shipping Technology Wuhan University of Technology Wuhan China

Localization is of paramount importance for underwater wireless sensor networks (UWSNs). However, achieving accurate location is infeasible, especially in the highly dynamic underwater environment. The acoustic signal may suffer hybrid loss, including path and absorption loss, which dramatically degrades the localization accuracy. Even though some localization methods have been proposed, the trade-off between accuracy and computational complexity cannot be well balanced. In this context, the paper proposes a computationally efficient method that investigates the localization problem in the alternating nonnegative constrained least squares (ANCLS) framework after linearization operation. The potential solutions are divided into two groups, wherein the optimal one is filtered under the constraint by exchanging the variables from one to another. A block principal pivoting-based localization (BPPL) method is then presented to estimate the target's location. Simulations reveal that the computational complexity and the localization accuracy of BPPL are competitive compared with the state-of-the-art methods in different scenarios.

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Optimization of Sound Absorption and Insulation Performances of a Dual-Cavity Resonant Micro-Perforated Plate

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Fluid Dynamics & Materials Processing 2022年第2期18卷 481-496页

作者： Wei Chen Zhaofeng Guo Hongda Feng Sheng Hu Ling Lu Chuanmin Chen Xiaowen Wu Hao Cao State Grid Hunan Electric Power Co. Ltd.Electric Power Research InstituteChangsha410000China State Grid Corporation of China Power Facilities Noise and Vibration Laboratory Changsha410000China North China Electric Power University Department of Environmental Science and EngineeringHebei Provincial Key Laboratory of Coal-Fired Power Station Flue Gas Multi-Pollution Cooperative ControlBaoding071003China North China Electric Power University Key Laboratory of Regional Energy System Optimization Ministry of EducationBeijing102206China

This study investigates a dual-cavity resonant composite sound-absorbing structure based on a micro-perforated *** the COMSOL impedance tube model,the effects of various structural parameters on sound absorption and sound insulation performances are *** show that the aperture of the micro-perforated plate has the greatest influence on the sound absorption coefficient;the smaller the aperture,the greater is this *** thickness of the resonance plate has the most significant influence on the sound insulation and resonance frequency;the greater the thickness,the wider the frequency domain in which sound insulation is *** addition,the effect of filling the structural cavity with porous foam ceramics has been studied,and it has been found that the porosity and thickness of the porous material have a significant effect on the sound absorption coefficient and sound insulation,while the pore size exhibits a limited influence.

关键词： Micro perforated plate double cavity compound resonance structure sound absorption coefficient sound insulation

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