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health status assessment for New Urban Rail Vehicle Traction Systems Based on Cross Entropy and SVM

Chinese Journal of Electrical Engineering 2022年第2期8卷 108-120页

作者： Zhenglong Zhou Yang Cheng Shenggang Lv Kai Chen Weijing Du School of Power Technology Liuzhou Railway Vocational Technical CollegeLiuzhou 545616China

A health status assessment method based on cross entropy and support vector machine(SVM)is proposed for the new urban rail vehicle traction systems.First,an index system for health assessment of the traction system is established,and combined weights of the index layer are obtained via cross entropy.Then,an SVM assessment model considering actual operating data and each status level of the traction system is established.Finally,the model is simulated in Matlab to obtain assessment results.The results indicate that the proposed method can provide the health status information of the traction system intuitively and complete the health status assessment of the traction system of the new urban rail vehicle effectively,by exploiting the traction system’s layered analysis model.The health status can be assessed accurately and reliably by adopting the cross entropy theory and SVM theory.

关键词： New urban rail vehicle traction system cross entropy SVM health status assessment

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health status assessment of axial piston pump under variable speed

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High Technology Letters 2020年第3期26卷 315-322页

作者：郭锐 Li Hucheng Zhao Zhiqian Zhang Rongbing Zhao Jingyi Gao Dianrong Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power'Transmission and Control Yanshan UniversityQinhuangdao 066004P.R.China State key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027P.R.China Key Labratory of Advanced Forging&Stamping Teclnology and Science Yanshan UniversityQinhuangdao O66004P.R.China Hebei Key Laboratory of Special Delivery Equipment Yanshan University Qinhuangdao 066004P.R.China

The axial piston pump usually works under variable speed conditions.It is important to evaluate the health status of the axial piston pump under the variable speed condition.Aiming at the characteristic signals obtained under different wear levels of the port plate,a feature signal extraction method under variable speed conditions is proposed.Firstly,the combination of complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)energy spectrum and fast spectral kurtosis principle is used to accurately extract the intrinsic mode function(IMF)component containing the sensitive information of the degraded feature.Then,the aspect ratio analysis method of the angle domain variational mode decomposition(VMD)is used to process the feature index containing the sensitive information of the degraded feature.In order to evaluate the health status of the axial piston pump under variable speed,the vibration reliability analysis method for axial piston pump based on Weibull proportional failure rate model is proposed.The experimental results show that the proposed method can accurately evaluate the health status of the axial piston pump.

关键词： axial piston pump variable speed condition order ratio variational mode decomposition(VMD)in angle domain health status assessment

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health assessment Method of Reinforcement Processing Equipment Based on Time Series

Health Assessment Method of Reinforcement Processing Equipme...

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作者： Pan YANG China First Metallurgical Group Co.Ltd.

In view of the large quantity and wide area of steel bar processing equipment but lack of scientific evaluation and management, a method of health evaluation of steel bar processing equipment based on time series is proposed. Firstly, the health index is taken as the standard to evaluate the overall health level of the equipment and a comprehensive evaluation model of the equipment health state is constructed. Secondly, the most representative characteristic parameters are determined to reflect the running state of the equipment and a variable health factor is proposed to modify the running state health index of the equipment by referring to the aging formula of the equipment health condition. In order to comprehensively consider the importance of equipment characteristic parameters and construct a more reasonable evaluation system, the method of calculating the weight value of characteristic parameters is improved by combining the ordinal relation method and the entropy weight method. Finally, a non-linear relationship model based on time series is established to fit the trend of the comprehensive health index of the equipment and predict the future health status and maintenance nodes of the equipment. The model is used to analyze the bending hoop machine of a steel bar processing factory and the results show that the model is feasible.

关键词： health index health status assessment health factors Hoop bender

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