基于SVM的多传感器信息融合技术在农用柴油机故障诊断中的应用研究

SVM-based multi-sensor information fusion technology in the agricultural diesel engine fault diagnosis

通过运用基于子模块决策输出融合的多传感器信息融合模型,专门针对农用柴油机运行机理和易发故障的特点,探讨了基于SVM的多传感器信息融合技术在农用柴油机故障诊断中的具体运用。通过对故障农用车实车数据比较试验表明,此方法在识别农用柴油机的故障类型上相比于传统诊断方法更加有效。

Using integration based on the sub-module decision-making output multi-sensor information fusion model,specifically for agricultural diesel engine’ s characteristics of running mechanism and prone to failure,discusses the use of SVM-based multi-sensor information fusion technology in the agricultural diesel engine fault diagnosis.Experiments using real data of the fault agricultural vehicles show that,compared to traditional diagnostic methods,this method is more effective to identify the type of failure of the agricultural diesel.