Research on Fault Diagnosis Based on Singular Value Decomposition and Fuzzy Neural Network
A method based on singular value decomposition (SVD) and fuzzy neural network (FNN) was proposed to extract and diagnose the fault features of diesel engine crankshaft bearings efficiently and accurately. Firstly, vibration signals of crankshaft bearings in known state under the same working conditi...
Saved in:
Main Authors: | Jingbo Gai, Yifan Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2018/8218657 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fault Diagnosis of Rotating Machinery Based on Convolutional Neural Network and Singular Value Decomposition
by: Dong Liu, et al.
Published: (2020-01-01) -
Bearing Fault Diagnosis based on Singular Value Decomposition Denoising and Local Characteristic-scale Decomposition
by: Cui Weicheng, et al.
Published: (2016-01-01) -
BEARING FAULT DIAGNOSIS METHOD BASED ON WINGER DISTRIBUTION AND SINGULAR VALUE DECOMPOSITION
by: QIN HongMao, et al.
Published: (2015-01-01) -
A Bearing Performance Degradation Modeling Method Based on EMD-SVD and Fuzzy Neural Network
by: Jingbo Gai, et al.
Published: (2019-01-01) -
An Effective Gear Fault Diagnosis Method Based on Singular Value Decomposition and Frequency Slice Wavelet Transform
by: Fu-Cheng Zhou, et al.
Published: (2016-01-01)