Two-stage turnout fault diagnosis based on similarity function and fuzzy c-means
Fault diagnosis for turnouts is crucial to the safety of railways. Existing studies on fault diagnosis depend on human experiences to select reference curves and require fault type information beforehand. Therefore, we proposed a turnout fault diagnosis method, named similarity function and fuzzy c-...
Main Authors: | Shize Huang, Xiaolu Yang, Ling Wang, Wei Chen, Fan Zhang, Decun Dong |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2018-12-01
|
Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814018811402 |
Similar Items
-
Turnout Fault Diagnosis through Dynamic Time Warping and Signal Normalization
by: Shize Huang, et al.
Published: (2017-01-01) -
An intelligent diagnosis for railway turnout fault
by: Ke Ting, et al.
Published: (2020-04-01) -
An Online Classification Method for Fault Diagnosis of Railway Turnouts
by: Dongxiu Ou, et al.
Published: (2020-08-01) -
Photovoltaic Array Fault Diagnosis Based on Gaussian Kernel Fuzzy C-Means Clustering Algorithm
by: Shengyang Liu, et al.
Published: (2019-03-01) -
Turnout twist : higher voter turnout in lower-level elections
by: Horiuchi, Yusaku, 1968-
Published: (2005)