Interval extended PCA-based fault diagnosis of spacecraft thrusters

2016 ◽  
Author(s):  
Imen Gueddi ◽  
Othman Nasri ◽  
Kamel Benothman ◽  
Philippe Dague
Keyword(s):  
Fault Diagnosis

Erratum: Single-fault diagnosis of nonlinear resistive networks

1987 ◽  
Vol 134 (2) ◽  
pp. 110
Author(s):  
M.E. Zaghloul ◽  
D. Gobovic
Keyword(s):  
Fault Diagnosis ◽  
Single Fault ◽  
Resistive Networks

Single-fault diagnosis of nonlinear resistive networks

1987 ◽  
Vol 134 (1) ◽  
pp. 16 ◽  
Author(s):  
M.E. Zaghloul ◽  
D. Gobovic
Keyword(s):  
Fault Diagnosis ◽  
Single Fault ◽  
Resistive Networks

Fault Diagnosis Method for Marine Hydraulic System

ICLEM 2012 ◽  
2012 ◽  
Author(s):  
Changwei He ◽  
Dawei Liu
Keyword(s):  
Fault Diagnosis ◽  
Hydraulic System ◽  
Diagnosis Method

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.

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle

Case Study on Fault Diagnosis of the Actual Operating Transformer by FRA

2011 ◽  
Vol 131 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Takahiro Sano ◽  
Yoshiharu Ogawa ◽  
Takaaki Shimonosono ◽  
Tadayuki Wada
Keyword(s):  
Fault Diagnosis ◽  
Actual Operating

Development of Fault Diagnosis Classification Method System using Mahalanobis Distance in Micro Wind Turbine

2015 ◽  
Vol 135 (9) ◽  
pp. 577-578
Author(s):  
Toshio Bouno ◽  
Shinichi Arimori ◽  
Toshifumi Yuji ◽  
Hiroyuki Kinoshita
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Mahalanobis Distance ◽  
Classification Method ◽  
Diagnosis Classification

A Fault Diagnosis Expert System for Building Chillers

2017 ◽  
Vol 11 (4) ◽  
pp. 270
Author(s):  
C. N. Tan ◽  
C. F. Tan ◽  
M. A. Abdullah
Keyword(s):  
Fault Diagnosis ◽  
Expert System
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