基于多元回归模型的某型轨道交通车辆制动系统故障预测模型

Failure Prediction Model for One Type of Rail Transit Vehicle Braking System Based on Multivariate Regression Model

为了提高轨道交通车辆制动系统基本事件故障率的判断准确率,进而提高制动系统重要部件在动态条件下的可靠性,基于多元回归模型分析,以某型车辆制动系统实际故障数据为依据,结合制动缸压力、列车运行速度随时间变化的规律,发现制动缸压力与时间的关系较符合BidoseResp函数,进而建立制动系统故障预测模型。以实际故障数据训练后,利用故障预测模型对关键部件的故障发生情况进行预测。预测结果显示,该故障预测模型的准确率较高,具有适用性。

To further elevate the reliability of braking system important components under dynamic conditions,it is necessary to improve the judgement accuracy rate of elementary event failure rate for rail transit vehicle braking system.Based on the multivariate regression model analysis,taking the actual failure data of a vehicle′s braking system,and considering the braking cylinder pressure and the law of train running speed changing with time,it is discovered that the relationship between braking cylinder pressure and time is generally in accordance with BidoseResp function,a braking system failure prediction model is thus established.After training with the actual failure data,the failure occurrence situation of key components is predicted using the failure prediction model.Prediction results show that the failure prediction model has high accuracy rate and applicability.