An improved chaotic recognition method for weak signal frequency and its application to fault diagnosis of planetary gearboxes

Abstract

Planetary gearboxes are very prone to failure when they are used in low-speed and heavy-load conditions for a long time. Due to strong background noise in the industrial field and the signal decay in the process of fault signal transmission, the weak fault characteristics of planetary gearboxes are submerged by noise and difficult to extract and identify. Aiming at this problem, an improved chaos detection method for weak signal frequency recognition is proposed. In this paper, the maximum weighted kurtosis is selected as the fitness function, and the Aquila optimizer algorithm is used to find the optimal modal number K and penalty factor α of variational modal decomposition. According to the grey relational degree, an inherent modal function (IMF) containing rich fault features is selected to reduce the noise of the original signal. Further, a double-coupled Duffing oscillator equation is constructed, and a quantitative criterion for chaotic oscillator phase transition based on the standard deviation weighted-average Euclidean distance is proposed. Based on the reverse detection method, the sideband growth of the most sensitive IMF after standardization is detected to determine the health state of the planetary gearbox. Detecting the fault characteristic frequency in the most sensitive IMF after normalization and Hilbert transform processing is based on the forward detection method in order to determine the fault type of the planetary gearbox. The effectiveness of the proposed method is verified by simulation and experiment. The results show that the proposed method successfully identifies the weak fault characteristics of the planetary gearbox, which fully shows that this method has an excellent diagnostic effect for planetary gearbox faults with rich frequency fault characteristics, and provides a new method for the diagnosis and identification of weak faults in planetary gearboxes in engineering practice.