Detection and Diagnosis of Incipient Faults in Heavy-Duty Diesel Engines


获取原文并翻译 | 示例


This paper proposes a new methodology for detecting and diagnosing faults found in heavy-duty diesel engines based upon spectrometric analysis of lubrication samples and is compared against a conventional method, the redline limits, which is utilized in a number of major laboratories in the U.K. and across Europe. The proposed method applies computational power to a well-known maintenance technique and consists of an improved method of preprocessing to form a derivative tuple, which extracts further information from the measured elemental concentrations. To identify incipient faults, the distance in vector space is calculated using a Gaussian contour, generated from prior data, as the zero crossing, which enables novel samples to be classified as normal or abnormal. This information is utilized as the input to a probabilistic directed acyclic graph in the form of a belief network. This network provides a prognosis for the mechanism as well as suggesting possible actions that could be taken to rectify the diagnosed problem, supported with confidence probabilities. The proposed method is evaluated for both accuracy in detecting a fault as well as the duration of time that is provided before the event occurs, with significant improvements in both metrics demonstrated over the conventional method.


  • 论文查重
  • 论文收录引证报告
  • 文档翻译
  • 文档转换

联系方式:18141920177 (微信同号)


京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号