电器与能效管理技术 ›› 2026, Vol. 0 ›› Issue (5): 78-87.doi: 10.16628/j.cnki.2095-8188.2026.05.011

• 电器设计与探讨 • 上一篇    下一篇

基于声信号检测的高压直流接触器异常状态识别技术

刘勤能   

  1. 宁德时代新能源科技股份有限公司, 福建 宁德 352100
  • 收稿日期:2026-01-27 出版日期:2026-05-30 发布日期:2026-06-09
  • 作者简介:刘勤能(1990—),男,工程师,研究方向为新能源动力电池可靠性提升技术。

Abnormal State Recognition Technology for High-Voltage Direct Current Contactors Based on Acoustic Signal Detection

LIU Qinneng   

  1. Contemporary Amperex Technology Co., Ltd., Ningde 352100, China
  • Received:2026-01-27 Online:2026-05-30 Published:2026-06-09

摘要:

针对高压直流接触器异常状态识别准确率低、状态识别方法泛化能力不足的问题,提出基于自适应敏感模态筛选与混合架构模型的状态识别方法。首先,对采集的振动和声音信号进行自适应噪声完备集合经验模态分解(CEEMDAN),并通过方差加权策略筛选敏感模态分量。其次,利用对称点模式(SDP)将重构信号融合并可视化。最后,结合EfficientNetV2的高效局部特征提取能力与视觉Transformer的全局建模优势,通过引入MobileViT模块构建了EfficientNetV2-ViT模型,解决SDP图像特征分散性问题。与其他模型相比,所提模型具有更优的计算效率和识别准确率。

关键词: 高压直流接触器, 状态识别, 声信号, 对称点模式, 轻量化模型

Abstract:

To address the issue of low accuracy in identifying abnormal states of high-voltage direct current contactors and to enhance the generalization ability of the state identification method,a state identification method based on adaptive sensitive mode screening and a hybrid architecture model is proposed.Firstly,the collected vibration and acoustic signals are subjected to adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN),and the sensitive mode components are screened through the variance weighted strategy.Secondly,the reconstructed signals are fused and visualized using the symmetrized dot pattern (SDP) method.Finally,by integrating the efficient local feature extraction ability of EfficientNetV2 and the global modeling advantage of visual Transformer,an EfficientNetV2-ViT model is constructed by introducing the MobileViT module to solve the problem of image feature dispersion of SDP.Compared with other models,the proposed model has better computational efficiency and recognition accuracy.

Key words: high voltage DC contactor, state recognition, acoustic signal, symmetrized dot pattern, lightweight model

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