特定车速下轻型卡车驾驶室异常抖动故障诊断方法

Fault Diagnosis Method of Light Truck Cab Abnormal Jitter at Specific SpeedWang Juncheng

摘要:

常规驾驶室异常抖动故障诊断方法多采用神经网络算法,忽略了故障数据之间的关联性,使得诊断准确率较低。为此,提出特定车速下轻型卡车驾驶室异常抖动故障诊断方法。利用数据采集器采集驾驶室在线信息数据,并采用周期性的方式对数据分类,分析故障数据之间的内部关系,解析收集的信息数据,判断车辆驾驶室运行状态,并采用故障树方法计算底事件的概率重要度,进而实现驾驶室抖动故障诊断。利用对比实验对所提方法的诊断性能进行测试,结果显示,所提方法对于驾驶室异常抖动故障具有较高的诊断准确率。

Abstract:

The conventional fault diagnosis method of cab abnormal jitter mostly uses neural network algorithm, which ignores the correlation between fault data, making the diagnosis accuracy low. For this reason, a diagnosis method of light truck cab abnormal jitter under specific speed is proposed. The data collector is used to collect the online information data of the cab, classify the data periodically, analyze the internal relationship between the fault data, analyze the collected information data, judge the operation state of the vehicle cab, and use the fault tree method to calculate the probability importance of the bottom event, thus realizing the cab shake fault diagnosis. The case test results show that the proposed method can diagnose cab jitter fault with high diagnostic accuracy.