Research on application of HHT and SVM in safety assessment and prediction for mechanical equipment

doi:10.16265/j.cnki.issn1003-3033.2017.02.011

Abstract

Abstract: In this paper, the vibration condition monitoring technique is adopted for mechanical equipment, based on which the HHT method is utilized to processvibration signals; the vibration frequency-domain energy value obtained is taken as the characteristic quantity to represent the performance degradation of mechanical equipment. Then the Grid Search(GS) and Cross Validation(CV) methods are used to optimize the parameters of SVM, so as to improve the prediction accuracy of degradation characteristic quantity. Therefore, a state space division method is developed to assess and predict the safety status of mechanical equipment. Finally, the method developed by the authors was used for assessing and predicting the vibration state and the corresponding safety status of brushless direct current motors.The results show that the prediction error is only 1.17%.

Key words: mechanical equipment, vibration monitoring, Hilbert-Huang transform(HHT), support vector machine(SVM), safety assessment and prediction

CLC Number:

XUAN Jinquan, WANG Xiaohong, LU Dawei, WANG Lizhi. Research on application of HHT and SVM in safety assessment and prediction for mechanical equipment[J]. China Safety Science Journal, 2017, 27(2): 58-63.

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