基于多征兆信息融合理论的柴油机故障诊断

Diesel Engine Fault Diagnosis Based on Multi-symptom Information Fusion

信息融合理论在故障诊断领域中得到广泛应用 ,为复杂机械故障诊断提供了一种新的方法。在研究了多传感器决策层融合理论—— Dem pster- Shafer证据理论及其算法的基础上 ,提出了一种基于多征兆信息融合理论的故障诊断方法。以柴油机活塞和缸套之间的磨损为例 ,论述了该方法的实施过程。结果表明 ,多征兆信息的信息融合诊断方法具有良好的稳定性和容错性 。

Nowadays, the information fusion theory has been widely used in the fault diagnosis domain. It puts forward a new method for the complex machine fault diagnosis. The conception incorporated multi sensor data fusion with Dempster Shafer evidential theory was discussed in brief. The fusion algorithm was stressed that uses the Dempster Shafer evidential theory to fuse different information at the decision level. A method of fault diagnosis based on multi symptom information fusion of fault characteristic was described. Taking the diesel engine piston liner wear as an example, this paper presents the implementing process of this diagnosis method in detail. The diagnosis result indicates that the multi symptom information fusion has the stability and the ability of fault tolerance, and can improve the accuracy and reliability of fault diagnosis of diesel engine effectively.