摘要
运用小波变换的多分辨和时频局部化特性,建立故障征兆的初始征兆参数集合。利用遗传算法理论,对初始征兆参数集合进行空间搜索而得到能够反映故障状态模式的最佳征兆参数。在实践中应用在对东风81-A型手扶拖拉机齿轮箱的故障信号进行特征提取,取得了较好的效果。
By using the characters and advantages of wavelet transform with MRA and loeal time - frequency domain, the feature parameter group which reflecting gear fault features is built. Then, on the basis of the feature group, the best feature parameters can be extracted by using the genetic algorithm which is an optimal method and could search the total space of the feature. This method of feature extraction was used to collect over the fault signals with the gearbox of type Dongfeng 81-A walking tractor,and some satisfactory results were obtained.
出处
《拖拉机与农用运输车》
北大核心
2005年第5期79-81,共3页
Tractor & Farm Transporter
基金
江苏省教育厅自然科学基金资助项目(00KJ46003)
