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SSRN 2023年

作者： Li, Xueyi Yu, Tianyu Wang, Xiangkai Li, Daiyou Xie, Zhijie Kong, Xiangwei College of Mechanical and Electrical Engineering Northeast Forestry University Harbin150040 China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang110819 China School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

Unsupervised rotation mechanical fault diagnosis methods have become popular, but existing unsupervised methods still have some issues. For example, it is challenging to capture vibration signal features at different scales and to address partial class confusion. To improve the diagnostic performance, this study introduces a multi-scale, Efficient Channel Attention (ECA) attention mechanism, Joint Adaptation Network (JAN), and Minimum Class Confusion (MCC) for addressing the aforementioned issues. Firstly, the authors design a multi-scale fault feature extraction module to capture discriminative information at different scales in vibration signals. Secondly, the authors introduce the ECA attention mechanism to weight the extracted features at the channel level, enhancing useful features and suppressing redundant features. Then, the authors employ the JAN method to establish local maximum mean discrepancy, enabling adaptation between corresponding sub-domains of the source and target domains, avoiding the problem of being too close. Finally, the authors use MCC as the loss function to reduce prediction confusion between correct and ambiguous categories in target samples, thus improving transfer performance. Experimental results demonstrate that the proposed method exhibits excellent performance in unsupervised rotation mechanical fault diagnosis tasks. © 2023, The Authors. All rights reserved.

关键词： Fault detection

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Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Double-Layer model predictive control combined with funnel zone control 3

Double-Layer model predictive control combined with funnel z...

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3rd International Conference on Industrial Artificial Intelligence, IAI 2021

作者： Sun, Haojie Liu, Jianbang Wang, Jingyang Yang, Zhijia Zou, Tao University of Chinese Academy of Sciences Beijing China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang China Guangzhou University School of Mechanical and Electrical Engineering Guangzhou China

ISBN: (纸本)9781665435178

In order to solve the problem of the high sensitivity of conventional double-layer model predictive control (DLMPC) algorithm to the process white noise and disturbance, we proposed an improved strategy integrating the tunnel control, which sacrifices a small part of the economic performance for a more smooth and stable control effect. By selecting an appropriate robust factor, an allowable economic performance zone is determined. The tunnel control strategy is implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When the economic performance index (EPI) of output prediction is inside its zone, the corresponding weight is zeroed. When the EPI of prediction lies outside the performance zone, the error weight is made equal to a specified value and the distance between the output prediction and the ideal steady-state set-point is minimized. Finally, the feasibility and effectiveness of the proposed algorithm are verified by simulating based on the Wood-Berry model. © 2021 IEEE.

关键词： Model predictive control

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Scalable No-wait Scheduling with Flow-aware Model Conversion in Time-Sensitive Networking

Scalable No-wait Scheduling with Flow-aware Model Conversion...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Yanzhou Zhang Qimin Xu Shouliang Wang Yingxiu Chen Lei Xu Cailian Chen Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665435413

The development of the Industrial Internet of Things (1IoT) has given rise to massive information from the networked controllers, sensors and actuators, leading to the increasing demands for real-time and reliable transmission. Time-Sensitive Networking (TSN) provides the deterministic mechanism guar-antee for these demands, but with an open scheduling problem. For the low-latency and low-jitter traffic, it is hard to schedule in a scalable way, that is, increasing the scheduling speed under the Quality-of-Service (QoS) requirements. Therefore, this paper constructs a no-wait forwarding (NW-TAS) model with a time-aware shaper to eliminate the queuing delay and jitter, and further converts it into a flow-aware model by divisibility theory for scheduling simplification. With the converted model, an interval transformation-based method is proposed to get the analytical expression of feasible scheduling for each flow. Then, a flow-aware NW- TAS scheduling algorithm (FANS) with cyclic interval searching is designed to compress invalid search spaces. The evaluation results show that our method decreases the transmission latency of 1000 flows by more than 23 % while increasing the scheduling speed by 43x than the existing works.

关键词： Fans Schedules Job shop scheduling Scheduling algorithms Quality of service Jitter Delays

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Variable Frequency Phase-Shift Modulation Technique for Single Stage Dual-Active-Bridge AC-DC Converter

Variable Frequency Phase-Shift Modulation Technique for Sing...

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International Conference on Power Electronics (ICPE)

作者： Dongxin Guo Panbao Wang Chunguang Ren Josep M. Guerrero School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Shanxi Key Lab. of Power System Operation and Control Taiyuan University of Technology Taiyuan China Department of Energy Technology Aalborg University Aalborg Denmark

This article proposes a variable frequency phase-shift modulation technique for single stage dual-active-bridge (DAB) AC-DC converter. This isolated single-stage single-phase converter consists of a DAB and a full bridge (FB) inverter. The proposed strategy applies a composite control strategy combining frequency modulation and extended phase shift (EPS) method to overcome the drawback of the non-linear power control of traditional phase-shift control scheme, which significantly reduces the complexity of the controller algorithm. Moreover, the synchronous inverter control applied to the back-end FB inverter is designed, which can realize the energy conversions in a single-stage, and a high frequency (HF) filter capacitor can replace the electrolytic capacitor at the output side DC-link. Thus, the safety of system operation improves and the power density of the system increases. Finally, simulation results confirm the validity and practical feasibility of the proposed control strategy.

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Nonlinear vibration response characteristics of a dual-rotor-bearing system with squeeze film damper

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Chinese Journal of Aeronautics 2021年第10期34卷 128-147页

作者： Xinxing MA Hui MA Haiqin QIN Xumin GUO Chenguang ZHAO Mingyue YU School of Mechanical Engineering and Automation Northeastern UniversityShenyang J10819China Institute of Vibration Shock and NoiseShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern UniversityShenyang 110819China Department of Aeronautical Mechanics Naval Aeronautical and Astronautical University Qingdao CampusQingdao 266041China

Rolling bearing and Squeeze Film Damper(SFD)are used in rotor support structures,and most researches on the nonlinear rotor-bearing system are focused on the simple rotor-bearing *** work emphasizes the comparative analysis of the influence of SFD on the nonlinear dynamic behavior of the dual-rotor system supported by rolling ***,a reduced dynamic model is established by combining the Finite Element(FE)method and the freeinterface method of component mode *** proposed model is verified by comparing the natural characteristics obtained from an FE model with those from the ***,the steady-state vibration responses of the system with or without SFD are solved by the numerical integration *** influences of the ball bearing clearance,unbalance,centralizing spring stiffness and oil film clearance of SFD on the nonlinear steady-state vibration responses of the dual-rotor system are *** show that SFD can effectively suppress the amplitude jump of the dual rotor system sustaining two rotors unbalance *** the ball bearing clearance or unbalance increases,the amplitude jump phenomenon becomes more obvious,the resonance hysteresis phenomenon strengthens or weakens,the resonant peaks shift to the left or the right,*** with unreasonable parameters will aggravate the system vibration,the smaller the oil film clearance,the better the damping performance of the SFD,the larger the centralizing spring stiffness is,the larger resonance amplitudes are.

关键词： dual-rotor rolling bearing squeeze film damper finite element method vibration response

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A Review of Parameter Estimation Methods of the Three-Parameter Weibull Distribution

A Review of Parameter Estimation Methods of the Three-Parame...

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International Symposium on system and Software Reliability (ISSSR)

作者： Xiaoyu Yang Liyang Xie Yaoyao Liu Bingfeng Zhao School of Mechanical Engineering and Automation Northeastern University Shenyang P. R. China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang P. R. China

The Weibull distribution, widely employed in reliability engineering, life testing, and failure analysis, stands as a prominent probability distribution. Notably, the three-parameter Weibull distribution proves invaluable in capturing wear-out failure mechanisms within system modeling. This comprehensive review delves into distinct methodologies and techniques on parameter estimation for the three-parameter Weibull distribution, offering detailed comparisons.

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Research on Risk Situation Awareness and Prediction Method of Industrial control systems

Research on Risk Situation Awareness and Prediction Method o...

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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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AGV Detection in Industrial Environments through Computer Vision

AGV Detection in Industrial Environments through Computer Vi...

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IEEE Latin American Robotics Symposium, LARS

作者： Wilson Eduardo Barioni Igor Pardal Latini André Lazzaretti Marco Teixeira Flavio Neves Lucia Valeria Ramos De Arruda Automation and Advanced Control System Laboratory (LASCA) Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnologica Federal do Parana (UTFPR) Curitiba Parana Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Automated Guided Vehicles (AGVs) are usual in industrial settings, with an increasing economic impact on processes. They move through numerous environments inside factories, commonly navigating long distances, while performing several activities. The constant detection of such vehicles, especially in cases of maintenance and safety, is a main issue in an industry setting. Usually, this information could be provided by a supervisory system, but many applications are not so large as to make such a system viable. Thus, a solution via machine learning and computer vision is developed in this work, by using simple cameras, such as the factories' security cameras. As the industrial environment is a scenario with a lot of variation and noise, the Transfer Learning technique is used to improve the training step of the developed AGV detection system. Finally, a database with 1067 images is used to build and validate the model, achieving a result greater than 80% of F1-score for various confidence values.

关键词： Training Computer vision Remotely guided vehicles Computational modeling Transfer learning Cameras Production facilities

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Scene Classification Using Deep Networks Combined with Visual Attention

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Journal of Sensors 2022年第0期2022卷

作者： Shi, Jing Zhu, Hong Li, Yuxing Li, Yanghui Du, Sen School of Automation and Information Engineering Xi'An University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an710048 China

In view of the scene's complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability. © 2022 Jing Shi et al.

关键词： Convolution

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