Wavelet packet decomposition and grey relational analysis application in fault diagnosis of aero hydraulic pump

Author(s):  
Zehua Liu ◽  
Jing Su ◽  
Cheng Qin ◽  
Zhenshui Li
2014 ◽  
Vol 8 (1) ◽  
pp. 129-131
Author(s):  
Wang Qizhi ◽  
Wang Xiaoxia

Power transformer is one of the most important equipments in the electric system. Dissolved Gases Analysis is an important method in the diagnosis of internal fault of transformers. Because the signs and types of fault have complicated nonlinear relations, the traditional methods cannot exactly meet the requirements of engineer application. This paper proposes synthesis of relational grey incidence to analyze the comparability and the proximity of the sequence which can effectively diagnose the type of transformer faults.


Author(s):  
Bangcheng Zhang ◽  
Jing Chen ◽  
Xiaojing Yin ◽  
Zhi Gao

The gas-path system is an important sub-system in aero-engines. There are various indistinguishable faults in aero-engine gas-path systems. These faults are easily misjudged because the characteristic parameters are similar. Due to the many kinds of faults, current studies have poor accuracy in distinguishing similar faults. To improve fault diagnosis accuracy for gas-path systems, a fault diagnosis method based on grey relational analysis and synergetic pattern recognition is proposed. In the proposed method, grey relational analysis is used to initially distinguish the faults into different types and obtain similar fault types. Synergetic pattern recognition contributes to accurately diagnose faults which are difficult to recognize. A case study is used to verify the effectiveness and accuracy of the proposed model. The results show that faults in common types of gas-path systems can be diagnosed accurately by the proposed method.


2011 ◽  
Vol 65 ◽  
pp. 272-275
Author(s):  
Fan Yang ◽  
Cai Li Zhang

Considering the poor accuracy of grey relational analysis method in fault diagnosis field, a rough set based weighted grey fault diagnosis algorithm is provided. The algorithm extracts the core characteristic parameters described the fault description and calculate their weight with rough sets and its attribute reduction method, the possible fault pattern of the unknown pattern is judged by the relation degree which calculated quantitatively with each typical fault pattern in history diagnosis record based on weighted grey relational analysis method. Experiment result of recognizing a diesel engine working state indicates that rough set based weighted grey fault diagnosis algorithm find effectively the optimization characteristics parameter for fault description, emphasize the importance of the different characteristics parameters, improve the accuracy of grey diagnose algorithm, and can play significant performance in actual application.


2019 ◽  
Vol 1303 ◽  
pp. 012088
Author(s):  
Huayong Lu ◽  
Hongzuo Guo ◽  
Zhe Liu ◽  
Xiao Yang ◽  
Bing Leng

Sign in / Sign up

Export Citation Format

Share Document