Fault Diagnosis Method in Complex System Using Bayesian Networks’ Sensitivity Analysis

2014 ◽  
Vol 14 (1) ◽  
pp. 24-30 ◽  
Author(s):  
Runmei Zhang ◽  
Xuegang Hu ◽  
Hao Wang ◽  
Hongliang Yao
Keyword(s):  
Complex System ◽  
Sensitivity Analysis ◽  
Fault Diagnosis ◽  
Bayesian Networks ◽  
Diagnosis Method

Application on State Evaluation of the Grounding Conductor Based on Fault Diagnosis Method

2014 ◽  
Vol 635-637 ◽  
pp. 815-818
Author(s):  
Da Xing Wang ◽  
Shou Bao Liu ◽  
De Gang Gan ◽  
Bin He
Keyword(s):  
Sensitivity Analysis ◽  
Fault Diagnosis ◽  
Network Theory ◽  
Electrical Network ◽  
Large Area ◽  
Power Failure ◽  
Grounding Grid ◽  
State Evaluation ◽  
Diagnosis Method ◽  
Diagnosis Model

In this paper, fault diagnosis model of grounding grid is established combining electrical network theory with sensitivity analysis. A new method which is used to select the node pairs to calculate the corrosion situation of grounding grid is presented. Based on this method, the fault branch of grounding grid can be efficiently judged through topology diagram and port resistance without power failure and the excavation of large area. Field test was carried out at 220 kV electrical substations using the diagnosis method. The conductors diagnosed as severely corroded was excavated. The result was identical to the diagnosis results, indicating that this diagnosis method has engineering practicality.

Helicopter main reduction planetary gear fault diagnosis method based on SVDD

2020 ◽  
Vol 64 (1-4) ◽  
pp. 137-145
Author(s):  
Yubin Xia ◽  
Dakai Liang ◽  
Guo Zheng ◽  
Jingling Wang ◽  
Jie Zeng
Keyword(s):  
Fault Diagnosis ◽  
Planetary Gear ◽  
Gaussian Kernel ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Vector Data ◽  
Energy Characteristics ◽  
Gear Fault ◽  
Channel Information ◽  
Diagnosis Method

Aiming at the irregularity of the fault characteristics of the helicopter main reducer planetary gear, a fault diagnosis method based on support vector data description (SVDD) is proposed. The working condition of the helicopter is complex and changeable, and the fault characteristics of the planetary gear also show irregularity with the change of working conditions. It is impossible to diagnose the fault by the regularity of a single fault feature; so a method of SVDD based on Gaussian kernel function is used. By connecting the energy characteristics and fault characteristics of the helicopter main reducer running state signal and performing vector quantization, the planetary gear of the helicopter main reducer is characterized, and simultaneously couple the multi-channel information, which can accurately characterize the operational state of the planetary gear’s state.

Sign in / Sign up

Export Citation Format

Share Document