Bearing Fault Classification Based on Conditional Random Field

Bearing Fault Classification Based on Conditional Random Field

Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment. To overcome the drawbacks of the hidden Markov model (HMM) and improve the diagnosis accuracy, conditional random field (CRF) model based classif...

Full description

Saved in:

Bibliographic Details
Main Authors:	Guofeng Wang, Xiaoliang Feng, Chang Liu
Format:	Article
Language:	English
Published:	Wiley 2013-01-01
Series:	Shock and Vibration
Online Access:	http://dx.doi.org/10.3233/SAV-130770
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fractional Dimensionless Indicator with Random Forest for Bearing Fault Diagnosis under Variable Speed Conditions
by: Yujing Huang, et al.
Published: (2022-01-01)

Bearing Fault Classification Using Improved Antlion Optimizer and Extreme Learning Machine
by: Zhuanzhe Zhao, et al.
Published: (2022-01-01)

Imbalanced Fault Classification of Bearing via Wasserstein Generative Adversarial Networks with Gradient Penalty
by: Baokun Han, et al.
Published: (2020-01-01)

Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features
by: Wei Peng, et al.
Published: (2016-01-01)

Fault Diagnosis for Rolling Bearing under Variable Conditions Based on Image Recognition
by: Bo Zhou, et al.
Published: (2016-01-01)

Recent advances in journal bearings: wear fault diagnostics, condition monitoring and fault diagnosis methodologies
by: Nazik Jebur, et al.
Published: (2025-01-01)

Rolling Bearing Fault Diagnostic Method Based on VMD-AR Model and Random Forest Classifier
by: Te Han, et al.
Published: (2016-01-01)

The Hybrid KICA-GDA-LSSVM Method Research on Rolling Bearing Fault Feature Extraction and Classification
by: Jiyong Li, et al.
Published: (2015-01-01)

Adaptive Morphological Feature Extraction and Support Vector Regressive Classification for Bearing Fault Diagnosis
by: Jun Shuai, et al.
Published: (2017-01-01)

Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm
by: Pengcheng Jiang, et al.
Published: (2020-01-01)

Rolling Bearings Fault Diagnosis under Variable Speed Conditions Based on Multitime-Frequency Ridge Extraction
by: Qing Xiong, et al.
Published: (2024-01-01)

Bearing Fault Diagnosis Based on Domain Adaptation Using Transferable Features under Different Working Conditions
by: Zhe Tong, et al.
Published: (2018-01-01)

Fault Diagnosis of Subway Traction Motor Bearing Based on Information Fusion under Variable Working Conditions
by: Yanwei Xu, et al.
Published: (2021-01-01)

Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE
by: Dejun Meng, et al.
Published: (2022-01-01)

Aircraft Bearing Fault Diagnosis Method Based on LSTM-IDRSN
by: Lei Wang, et al.
Published: (2025-01-01)

Bearing Fault Diagnosis Based on Multilayer Domain Adaptation
by: Bingru Yang, et al.
Published: (2020-01-01)

MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning
by: Guangyuan Xu, et al.
Published: (2025-01-01)

Rolling Bearing Fault Diagnosis Based on Domain Adaptation and Preferred Feature Selection under Variable Working Conditions
by: Xiao Yu, et al.
Published: (2021-01-01)

An Improved Dual-Kurtogram-Based T2 Control Chart for Condition Monitoring and Compound Fault Diagnosis of Rolling Bearings
by: Zhiyuan Jiao, et al.
Published: (2021-01-01)

Classification of points in 2-dimensional space based on realizations of Gaussian random fields
by: Jūratė Šaltytė, et al.
Published: (1999-12-01)

The Fault Diagnosis of Rolling Bearing Based on Improved Deep Forest
by: Xiwen Qin, et al.
Published: (2021-01-01)

Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis
by: Jinde Zheng, et al.
Published: (2014-01-01)

Research on bearing fault diagnosis based on a multimodal method
by: Hao Chen, et al.
Published: (2024-12-01)

Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals
by: Hongmei Liu, et al.
Published: (2016-01-01)

Rolling Bearing Fault Diagnosis Based on Sensitive Feature Transfer Learning and Local Maximum Margin Criterion under Variable Working Condition
by: Shiyuan Liu, et al.
Published: (2020-01-01)

A Spectrum Detection Approach for Bearing Fault Signal Based on Spectral Kurtosis
by: Yunfeng Li, et al.
Published: (2017-01-01)

Fault Diagnosis of Train Axle Box Bearing Based on Multifeature Parameters
by: Xiaofeng Li, et al.
Published: (2015-01-01)

Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM
by: Jiang Xingmeng, et al.
Published: (2016-01-01)

Rolling Element Bearing Fault Recognition Approach Based on Fuzzy Clustering Bispectrum Estimation
by: W.Y. Liu, et al.
Published: (2013-01-01)

Fault Identification of Low-Speed Hub Bearing of Crane Based on MBMD and BP Neural Network
by: Li-Hong Guo, et al.
Published: (2022-01-01)

Optimal SES Selection Based on SVD and Its Application to Incipient Bearing Fault Diagnosis
by: Longlong Li, et al.
Published: (2018-01-01)

An Enhancement Deep Feature Extraction Method for Bearing Fault Diagnosis Based on Kernel Function and Autoencoder
by: Fengtao Wang, et al.
Published: (2018-01-01)

The Fault Feature Extraction of Rolling Bearing Based on EMD and Difference Spectrum of Singular Value
by: Te Han, et al.
Published: (2016-01-01)

Bearing Defect Classification Algorithm Based on Autoencoder Neural Network
by: Manhuai Lu, et al.
Published: (2020-01-01)

Bearing Fault Diagnosis of End-to-End Model Design Based on 1DCNN-GRU Network
by: Liu Zhiwei
Published: (2022-01-01)

Improved VMD‐KFCM algorithm for the fault diagnosis of rolling bearing vibration signals
by: Yong Chang, et al.
Published: (2021-06-01)

A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor
by: Omar AlShorman, et al.
Published: (2020-01-01)

Data-Driven Bearing Fault Diagnosis for Induction Motor
by: Aqib Raqeeb, et al.
Published: (2023-01-01)

Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images
by: Mingquan Qiu, et al.
Published: (2018-01-01)

Single Feature Extraction Method of Bearing Fault Signals Based on Slope Entropy
by: Erna Shi
Published: (2022-01-01)