神经网络与信息融合技术在内燃机车故障诊断中的应用

Application of Neural Network and Information Fusion Technology for Diesel Locomotive′s Fault Diagnosis

内燃机车是我国铁路运输中主要的牵引动力,其质量的优劣直接关系着铁路运输组织状况的好坏和人们的生命财产安全。将现场资深专家的机车故障诊断经验与信息融合技术和人工神经网络技术两种新型的智能化技术作为故障诊断理论基础,以东风系列内燃机车水阻试验系统对机车各个关键部位的状态检测参数作为数据来源,提供了一条内燃机车故障诊断的新途径。

At present,diesel locomotive is the main traction powers in our country＇s railway transportation. The quality of diesel locomotive directly concerns the organization quality of the railway transportation and people＇s safety and property＇s safety. Combining experience on - the - spot with two new style intelligentized fault diagnose theories of the information fusion technology and neural netwgrk as theoretical foundation. Taking the state test parameters about each key position of the locomotive as the data source. They are can be got from the water resistance test system of DF series diesel locomotive. In the end, putting forward a new way of fault diagnose for the diesel locomotive.