大连海事大学学报 >
2017 , Vol. 43 >Issue 1: 61 - 66
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2017.01.010
基于融合距离法的柴油机故障诊断方法
收稿日期: 2016-06-21
修回日期: 2016-07-22
网络出版日期: 2016-07-26
基金资助
内蒙古自治区高等学校科学研究项目（NJZZ16178）．
Diesel engine fault diagnosis method based on fusion distance measurement
Received date: 2016-06-21
Revised date: 2016-07-22
Online published: 2016-07-26
刘罡 , 王兴成 , 杨昺崧 . 基于融合距离法的柴油机故障诊断方法[J]. 大连海事大学学报, 2017 , 43(1) : 61 -66 . DOI: 10.16411/j.cnki.issn1006-7736.2017.01.010
In the case of unclear correlation of faults characteristic variable by a complex of monitoring information of diesel engine, the effective features of faults cannot be calculated by neither through Mahalanobis distance nor though Euclidean distance. However, a distance measurement method named fusion distance was put forward. The weight coefficients were determined by using characteristic variable correlation coefficient, and the dynamic weighting of Euclidean distance and Mahalanobis distance was carried out under consideration of both the correlation and independence of characteristic variables, which can effectively improve the accuracy of fault diagnosis. The validity of the fusion distance method was verified by the diagnostic accuracy and clustering effects respectively.
Key words： diesel engine; fault diagnosis; fusion distance; clustering analysis
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