Detection Method for Contact Morphology Based on Acoustic Features

Considering that the electrical contact performance of high-voltage direct current (HVDC) contactors is directly influenced by contact morphology, detecting the extent of morphological erosion is crucial. Hence, a detection method of the contact morphology of direct current (DC) contactors based on acoustic signal features was proposed in this paper. Firstly, the contact model following the typical morphology was constructed based on the morphology evolution law of the contact under the action of electrical erosion. The effects of different morphologies on the acoustic signal in the time domain and frequency domain were analyzed by investigating the generation mechanism of the vibrational and acoustic signal during its closure process, providing theoretical guidance for subsequent feature extraction. Secondly, the symplectic geometry mode decomposition (SGMD) method was employed to separate the acoustic signal of its different mechanism components. Given the nonlinear impact characteristics of the contact collision acoustic signal, the kurtosis and the bhattacharyya distance were selected as the determination indices, and the entropy weighted technique for order preference by similarity to ideal solution (EW-TOPSIS) was adopted to extract the sensitive modes of the contact morphology. Finally, the dynamic time warping (DTW) distance between acoustic signals in the time domain and the skewness of the envelope spectrum in the frequency domain were reflected by the maximum peak height and the peak material volume of the contact morphology, respectively, in accordance with the theoretical basis of the influence of contact morphology on acoustic signals. The results reveal that this method extracted the features that characterized the morphology of the contact more effectively compared to other methods, and these parameters demonstrated a highly significant correlation with the morphology of the contact. The proposed method provides a new idea for the contact morphology detection of HVDC contactors while laying a foundation for their online lifetime prediction and residual value analysis.