Diesel Engine Fault Information Acquisition Based on Delay Vector Variance Method

被引:4
|
作者
Hu, Hongying [1 ]
Yin, Fuliang [1 ]
机构
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian, Peoples R China
来源
2009 SECOND INTERNATIONAL SYMPOSIUM ON KNOWLEDGE ACQUISITION AND MODELING: KAM 2009, VOL 1 | 2009年
关键词
delay vector variance(DVV); surrogate data; fault diagnose; TIME-SERIES; NONLINEARITY;
D O I
10.1109/KAM.2009.124
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, Delay Vector Variance (DVV) method based on surrogate data is introduced as an efficacious and intuitionistic tool for acquiring the information of determinism and nonlinearity in diesel vibration signals in different conditions. It provides consistent and easy-to interpret diagrams - DVV plot and DVV scatter diagrams, which convey information about the nature of the signals. The experiment shows that vibration signals from diesel engine have strong nonlinearity, and nonlinearity gets stronger as fault becomes worse. Furthermore, the Root Mean Square (RMS) deviation of the DVV scatter diagram from the bisector line is used as a quantitative analysis of the fault state. Therefore this method can be opted to detect faults in diesel engine as well as other equipment faults.
引用
收藏
页码:199 / 202
页数:4
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