智能控制下机械式自动变速器故障检测方法

考虑到当前机械式自动变速器故障检测方法由于故障种类划分能力较差,导致复合故障检测结果正确率较低的情况,设计智能控制下机械式自动变速器故障检测方法。设定信号采样频率,对采集后的信号进行离散处理,提取自动变速器振动信号。使用LSSVM模型构建支持向量机,完成振动信号训练处理。根据机械控制理论结合证据分类检测方法,完成自动变速器故障诊断。至此,智能控制下机械式自动变速器故障检测方法设计完成。构建实验环节,经实验结果证实,新型检测方法的复合故障检测结果正确率得到明显提升,在日后的研究中可应用此方法完成故障检测过程。

Fault Detection Method of Mechanical Automatic Transmission Under Intelligent Control

Considering that the current fault detection method of mechanical automatic transmission has low accuracy of composite fault detection results due to poor fault classification ability,a fault detection method of mechanical automatic transmission under intelligent control is designed. Set the signal sampling frequency,discrete process the collected signal and extract the vibration signal of automatic transmission. LSSVM model is used to construct support vector machine to complete vibration signal training and processing. According to the mechanical control theory and evidence classification detection method,the fault diagnosis of automatic transmission is completed. So far,the design of fault detection method of mechanical automatic transmission under intelligent control has been completed. The experimental results show that the accuracy of the composite fault detection results of the new detection method has been significantly improved. This method can be used to complete the fault detection process in future research.