【6h】

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

机译:重型柴油机早期故障的检测与诊断

获取原文
获取原文并翻译 | 示例

摘要

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.
机译:本文基于润滑样品的光谱分析,提出了一种用于检测和诊断重型柴油机故障的新方法,并将其与传统方法红线限值进行了比较,该方法已在英国和美国的许多主要实验室中使用。在整个欧洲。所提出的方法将计算能力应用于一种众所周知的维护技术,并且包括一种改进的预处理方法,以形成一个派生元组,该元组从测量的元素浓度中提取更多信息。为了识别早期故障,矢量空间中的距离是使用从先验数据生成的高斯轮廓作为零交叉来计算的,这使得能够将新样本分类为正常还是异常。该信息被用作信念网络形式的概率有向无环图的输入。该网络为该机制提供了预后,并提出了可以采取的纠正已知问题的可能措施,并带有置信度。对提出的方法进行了评估,以提高检测故障的准确性以及事件发生之前提供的持续时间,与传统方法相比,这两个指标均得到了显着改进。

著录项

站内服务
  • 论文查重
  • 论文收录引证报告
  • 文档翻译
  • 文档转换
获取原文

联系方式:18141920177 (微信同号)

客服邮箱:kefu@zhangqiaokeyan.com

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