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The Investigation of Data Voting Algorithm for Train Air-Braking system Based on Multi-Classification SVM and ANFIS

Chinese Journal of Electronics 2024年第1期33卷 274-281页

作者： Juhan WANG Ying GAO Yuan CAO Tao TANG School of Electronics and Information Engineering Beijing Jiaotong University Graduate Department China Academy of Railway Science National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

The pressure data of the train air braking system is of great significance to accurately evaluate its operation state. In order to overcome the influence of sensor fault on the pressure data of train air braking system, it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault, the system can accurately identify and locate the position of the faulty sensor, and estimate the fault data according to other normal data. A fault-tolerant mechanism based on multi-classification support vector machine(SVM) and adaptive network-based fuzzy inference system(ANFIS) is introduced. Multi-classification SVM is used to identify and locate the system fault state, and ANFIS is used to estimate the real data of the fault sensor. After estimation, the system will compare the real data of the fault sensor with the ANFIS estimated data. If it is similar,the system will recognize that there is a false alarm and record it. Then the paper tests the whole mechanism based on the real data. The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.

关键词： Multi-classification support vector machine Adaptive network-based fuzzy inference system Train air braking system Fault-tolerant voting Multi-sensors

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The DRTS-Net Framework: Enhanced Probabilistic Health Perception for Wind Turbine Bearings Under Complex Operating Conditions With Improved Interpretability

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Yang, Tongguang Li, Guanchen Huo, Jinzhao Li, Xiaoyong Zhou, Xianwen Han, Qingkai Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Johns Hopkins University Department of Mechanical Engineering BaltimoreMD21218 United States Foshan University School of Mechatronic Engineering and Automation Foshan528225 China SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety MOE Key Laboratory of Theoretical Chemistry of Environment South China Normal University School of Environment Guangzhou510006 China SCNU Qingyuan Institute of Science and Technology Innovation Company Ltd. Qingyuan511517 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang110819 China

Health perception in mechanical systems is a crucial aspect of prognostics and health management (PHM). Deep learning models have been successfully applied to health perception in wind turbine bearings. However, due to the time-varying, redundant, and noisy characteristics of time-series data representing bearing wear, existing models face significant challenges, particularly in terms of generalization and interpretability. Moreover, although most current models have provided health perceptions, they overlook the strong stochastic nature of bearing degradation data, and thus fail to deliver reliable predictions of uncertainty information. To address these technical challenges, this study introduces a novel Deep residual temporal-spatial framework (DRTS-Net) for probabilistic health perception of wind turbine bearing wear states. This article creatively designs spatiotemporal information fusion module for extracting features from bearing degradation data. Inspired by improvements in residual network structures, the DRTS-Net integrates an attention mechanism and a soft thresholding mechanism from the deep residual shrinkage network to optimize the feature extraction process. This integration aims to mitigate the interference from minor redundant features in the degradation data. The framework incorporates Gaussian process regression in the output layer to yield the probability distribution of single-health perception values for bearing features. A comparative study was conducted using the same bearing health state dataset against current mainstream deep learning methods for bearing health assessment. Results demonstrate that the proposed DRTS-Net achieves superior performance in high-precision health perception, high-reliability probabilistic health perception. © 1963-2012 IEEE.

关键词： Stochastic systems

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Coordinated standoff tracking of moving targets using differential geometry

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Journal of Zhejiang University-Science C(Computers and Electronics) 2014年第4期15卷 284-292页

作者： Zhi-qiang SONG Hua-xiong LI Chun-lin CHEN Xian-zhong ZHOU Feng XU Department of Control and System Engineering School of Management and Engineering Nanjing University Department of Information Suzhou Institute of Trade and Commerce No. 207 Research Institute China North Industries Group Corporation

This research is concerned with coordinated standoff tracking, and a guidance law against a moving target is proposed by using differential geometry. We first present the geometry between the unmanned aircraft(UA) and the target to obtain the convergent solution of standoff tracking when the speed ratio of the UA to the target is larger than one. Then, the convergent solution is used to guide the UA onto the standoff tracking geometry. We propose an improved guidance law by adding a derivative term to the relevant algorithm. To keep the phase angle difference of multiple UAs, we add a second derivative term to the relevant control law. Simulations are done to demonstrate the feasibility and performance of the proposed approach. The proposed algorithm can achieve coordinated control of multiple UAs with its simplicity and stability in terms of the standoff distance and phase angle difference.

关键词： Unmanned aircraft Standoff tracking Differential geometry Coordinated control

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Inhibiting liquid permeation into silicone rubber by superhydrophobic coating for prolonged service life

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High Voltage 2023年第5期8卷 986-996页

作者： Shuming Liu Ying Zhou Zhou Zuo Shuqi Liu Qian Wang Zhong Chen Xidong Liang State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina School of Material Science and Engineering Nanyang Technological UniversitySingaporeSingapore

Liquid permeation into silicone rubber(SR)may lead to the degradation or complete failure of the composite *** to inhibit liquid permeation,two kinds of superhydrophobic coatings are applied to the SR *** liquid permeation properties of SR with different types of liquids are investigated,and the Langmuir diffusion model is applied to analyse the experimental *** results show that the composite superhydrophobic coating can effectively inhibit liquid permeation by reducing the contact area between the surface and liquid,and the stable structure of the composite coating can maintain the performance after the liquid permeation and ***,the nano‐particle coating without the polymer binder experiences severe performance degradation during the immersion test,and it cannot restrain the liquid permeation anymore after it loses the *** a validation of the effective protection,the insulation resistivity change was *** resistivity decreases sharply for the pristine SR after water permeation;however,the decrease is much smaller for the coated *** current study not only provides new insight into the liquid permeation properties of SR with different surface wettability but also suggests an effective measure to prevent liquid permeation into SR.

关键词： coating permeation liquid

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OPTIMAL control WITH QUADRATIC PERFORMANCE INDEX AND FIXED TERMINAL TIME

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IEEE TRANSACTIONS ON AUTOMATIC control 1964年第4期AC 9卷 355-&页

作者： JOHNSON, CD GIBSON, JE Department of Electrical Engineering University of Alabama Huntsville IN USA Control and Information System Laboratory School of Electrical Engineering Purdue University Lafayette AL USA

The conventional solution for the optimal control of a linear-stationary regulator with quadratic performance index and fixed terminal time leads to a linear control law with time-varying gain coefficients [1]. In addition to the usual disadvantages of time-variable controllers, some of the time-varying gain coefficients approach infinity as the specified terminal time is approached. In the present paper, it is shown that the optimal control for the above problem can be expressed in the form of a time-invariant non-linear control law. Certain parameters in the nonlinear control law are functions of the initial time and initial state of the system. The conventional time-varying linear control law can be obtained directly from the time-invariant nonlinear control law. The results of the present paper are applicable to a more general class of optimal control problems involving linear and nonlinear systems. Two examples are given to illustrate the method.

关键词： Optimal control Performance analysis control systems Symmetric matrices Jacobian matrices Equations Strips Regulators Performance gain H infinity control

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Optimization of Nostoc sp. biomass and protein composition in high-density cultivator based on DoE

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Algal Research 2025年 89卷

作者： Lucato, Veronica Ihadjadene, Yob Sut, Stefania Sforza, Eleonora Krujatz, Felix Department of Industrial Engineering DII University of Padova Via Marzolo 9 Padova 35131 Italy Institute of Natural Materials Technology Technische Universität Dresden Dresden 01069 Germany Chair of Automatic Control & System Dynamics Chemnitz University of Technology Chemnitz 09126 Germany Department of Pharmaceutical and Pharmacological Sciences University of Padova Via Marzolo 5 Padova 35131 Italy biotopa gGmbH – Center for Applied Aquaculture & Bioeconomy Radeberg 01454 Germany

High-density (HD) cultivation systems are a valuable alternative to improve the productivity of phototrophic microorganisms. They are designed to address the major challenges such as low cell densities, light attenuation, and inefficient gas exchange, offering innovative solutions. This work investigates the HD cultivation of the nitrogen-fixing cyanobacterium Nostoc sp. PCC 7120 under diazotrophic conditions, employing a hydrophobic membrane system for efficient CO₂ and N₂ transfer. A design of experiment (DoE) approach is applied to evaluate the influence of key operating variables, including light intensity, photoperiod, and phosphorus concentration, on biomass productivity (P_X) and nitrogen fixation (P_N). Mathematical models, describing the interactions between these process variables and growth responses are developed and validated, enabling the optimization of cultivation conditions to maximise productivity. Remarkable biomass productivity of 1.53 g_X L⁻¹ d⁻¹ was obtained in this system, under diazotrophic conditions. P_X was largely affected by light intensity, which should be supplied continuously, aligning with the ability of heterocystous species like Nostoc sp. of simultaneously perform photosynthesis and N-fixation. Additionally, phosphorus concentration was a critical parameter that must be precisely controlled to prevent substrate limitation or inhibition, with an optimal value of 34.1 mg_P L⁻¹. The produced biomass was further characterised with a focus on its nitrogen-rich molecules, particularly proteins, and nutritional value, assessed through essential amino acid content. The results showed that protein content was improved (53.4 %) at 280 μmol m⁻² s⁻¹, 25.5 mg_P L⁻¹_, and 18 h light period, with essential amino acid ranging between 11 % and 15 %. © 2025 The Authors

关键词： Amino acid profile Biomass productivity Nitrogen-fixing cyanobacteria Protein production Response surface methodology

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Phase-based testability analysis of multi-function integrated RF system using generalized stochastic Petri net

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Expert systems with Applications 2025年 284卷

作者： Zhang, Chao Cui, Changkai Zhou, Dingyu Dong, Zhijie He, Shilie Zhou, Zhenwei Department of Integrated Technology and Control Engineering School of Aeronautics Northwestern Polytechnical University Xi'an710072 China National Key Laboratory of Aircraft Design Xi'an710072 China School of Civil Aeronautics Northwestern Polytechnical University Xi'an710072 China Shanghai Civil Aviation Control and Navigation System Co. Ltd Shanghai201100 China The 6th Research Institute of China Electronics Corporation Beijing102209 China China Electronic Product Reliability and Environmental Testing Institute Guangzhou510610 China

Multi-Function Integrated RF system (MIRFS) is a crucial part of an aircraft's airborne systems. Unlike disposable equipment such as missiles and torpedoes, MIRFS has to face two different operating environments, ground and air, during a mission cycle. In these two operating environments, the test equipment and data processing methods are different. These differences bring problems with test information not being fully utilized and testability indexes not being accurately calculated. Traditional testability modelling and analysis method cannot deal with the above problems. In this paper, a phase-based testability modelling and analysis method using generalized stochastic Petri net (GSPN) is proposed to fully use test information and determinate accurate testability indexes. Firstly, depending on the operating environment, two phases which are readiness phase and flight combat phase are designed to build separate testability models. Secondly, since static modelling techniques like UML and SysML lack the ability to dynamically evaluate and analyse system, GSPN is used to model the testability of each phase to better describe the MIRFS state and behavior. Then the testability models for each phase are integrated and optimised into the mission cycle GSPN testability model, which contains fully test information. The integration principle involves linking testability models according to the mission cycle sequence, including time synchronization, fault detection synchronization, and maintenance synchronization. Finally, Markov chain is used to solve the mission cycle GSPN model and obtain the precise testability indexes. The testability indexes obtained effectively enhances the testability of the MIRFS. This method can also be used when there are more phases of the mission. © 2025 Elsevier Ltd

关键词： Data integration

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Nanopowder production by gas-embedded electrical explosion of wire

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Chinese Physics B 2013年第4期22卷 350-353页

作者：邹晓兵毛志国王新新江伟华 State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University Department of Physics and Chemistry College of Science North China University of Technology

A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and a production chamber housing the exploding wire load and ambient gas. With the EEW device, nanosize powders of titanium oxides, titanium nitrides, copper oxides, and zinc oxides are successfully synthesized. The average particle size of synthesized powders under different experimental conditions is in a range of 20nm–80nm. The pressure of ambient gas or wire vapor can strongly affect the average particle size. The lower the pressure, the smaller the particle size is. For wire material with relatively high resistivity, such as titanium, whose deposited energy Wd is often less than sublimation energy W s due to the flashover breakdown along the wire prematurely ending the Joule heating process, the synthesized particle size of titanium oxides or titanium nitrides increases with overheat coefficient k （k = W d /Ws ） increasing.

关键词： electrical explosion of wire nanosized powders particle size

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GENERALIZED MATRIX EUCLIDEAN ALGORITHMS FOR SOLVING DIOPHANTINE EQUATIONS AND ASSOCIATED PROBLEMS

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 1993年第12期25卷 55-72页

作者： TSAI, JSH CHEN, SS SHIEH, LS Control System Laboratory Department of Electrical Engineering National Cheng-Kung University Tainan 70101 Taiwan R.O.C.

Based on the matrix fraction descriptions of multi-variable control systems, this paper presents the generalized matrix Euclidean algorithms for solving Diophantine equations and associated problems. A chain rule is developed for finding the greatest common right(left) divisor of two square(non-square) polynomial matrices and the irreducible right(left) matrix fraction description from the reducible or irreducible left(right) matrix fraction description. Also, the development of multi-variable pole-assignment controllers are discussed for engineering applications.

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Deep learning-based distributionally robust joint chance constrained distribution networks PV hosting capacity assessment

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Applied Energy 2025年 394卷

作者： Wang, Zihui Jia, Yanbing Han, Xiaoqing Wang, Peng Liu, Jiajie Key Laboratory of Cleaner Intelligent Control on Coal & Electricity Ministry of EducationShanxi Key Laboratory of Power System Operation and Control Taiyuan University of Technology Taiyuan China Department of Electrical and Electronic Engineering Nanyang Technology University Singapore

As distributed photovoltaic (PV) penetration in distribution networks (DNs) is increasing, it is essential to assess the PV hosting capacity (PVHC) to ensure the safe operation of DNs. This paper proposes a data-driven distributionally robust joint chance constrained (DRJCC) distribution networks PVHC assessment framework. Firstly, the spatiotemporal attention, projection, supervision, and Transformer architecture-based generative adversarial blocks are introduced to develop an augmented time series generative adversarial network (ATS-GAN), which, by integrating both supervised and unsupervised learning during the joint training process, better captures the spatiotemporal characteristics of PV and load power. Subsequently, leveraging the ATS-GAN, a Wasserstein metrics-based ambiguity set of PV and load power probability distributions is constructed, centered on the distributions induced by the generator neural network. Secondly, the DRJCC PVHC assessment model is proposed. A combination of the Bonferroni inequality and conditional value-at-risk approximation is adopted to transform the multivariate DRJCC model into a tractable conic formulation for efficient computation. Numerical results demonstrate that the proposed method effectively captures the spatiotemporal characteristics and uncertainties of multivariate distributions under multiple constraints, significantly reducing the conservatism typically associated with distributionally robust individual chance constraints. © 2025

关键词： Normal distribution

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