希尔伯特-黄变换
支持向量机
粒子群优化
计算机科学
传输(电信)
算法
蚁群优化算法
超参数优化
特征提取
分类器(UML)
传动系统
断层(地质)
人工智能
模式识别(心理学)
工程类
计算机视觉
电信
滤波器(信号处理)
地质学
地震学
摘要
Summary The automobile transmission is the core component of the automobile transmission system. Extracting effective fault feature information from a complex mechanical device like a car transmission is the key to fault diagnosis. In this paper, the vibration signals of the normal transmission and different faulty transmissions are collected through experiments, and the weak fault feature extraction of automobile transmission gears is based on the combination of Teager energy operator demodulation method and empirical mode decomposition method. Finally, the theory of SVM and its application in fault diagnosis are introduced. Based on the cross‐validation method, the grid search method and particle swarm optimization algorithm are used to search and optimize the important parameters in the SVM model to improve the performance of the SVM classifier.
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