A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing

A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing

Each pattern recognition method has its advantages and disadvantages to diagnose the state of rotating machinery. There are many fault types of rolling bearings with apparent uncertainty. The optimal fusion level is usually challenging to be selected for a specific fault diagnosis task, and extensiv...

Full description

Bibliographic Details
Main Authors:	Weixiao Xu, Luyang Jing, Jiwen Tan, Lianchen Dou
Format:	Article
Language:	English
Published:	Hindawi Limited 2020-01-01
Series:	Shock and Vibration
Online Access:	http://dx.doi.org/10.1155/2020/8856818

Similar Items

Bearing fault diagnosis based on improved VMD and DCNN
by: Ran Wang, et al.
Published: (2020-08-01)

An Irrigation Decision Support Tool (IDST) for Smallholdings in Tanzania
by: Ngimbwa, Peter Cosmas
Published: (2016)

Fault Diagnosis Method for Rolling Mill Multi Row Bearings Based on AMVMD-MC1DCNN under Unbalanced Dataset
by: Chen Zhao, et al.
Published: (2021-08-01)

Research on Bearing Fault Diagnosis of Wind Turbine Gearbox Based on 1DCNN-PSO-SVM
by: Xiaolin Zhang, et al.
Published: (2020-01-01)

An Antinoise Fault Diagnosis Method Based on Multiscale 1DCNN
by: Jie Cao, et al.
Published: (2020-01-01)

1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling
by: Shuzhan Huang, et al.
Published: (2020-01-01)

A Hierarchical Decision Fusion Diagnosis Method for Rolling Bearings
by: Jingzhou Fei, et al.
Published: (2021-01-01)

DCNN With Explicable Training Guide and its Application to Fault Diagnosis of the Planetary Gearboxes
by: Peng Luo, et al.
Published: (2020-01-01)

Improving Rolling Bearing Fault Diagnosis by DS Evidence Theory Based Fusion Model
by: Xuemei Yao, et al.
Published: (2017-01-01)

Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster–Shafer evidence theory
by: Xianbin Sun, et al.
Published: (2016-01-01)

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC
by: Mingtao Ge, et al.
Published: (2017-12-01)

Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory
by: Jingchao Li, et al.
Published: (2019-02-01)

A Multimodel Fusion Engine for Filtering Webpages
by: Ziyun Deng, et al.
Published: (2018-01-01)

Phase Space Similarity as a Signature for Rolling Bearing Fault Diagnosis and Remaining Useful Life Estimation
by: Fang Liu, et al.
Published: (2016-01-01)

On the Accuracy of Fault Diagnosis for Rolling Element Bearings Using Improved DFA and Multi-Sensor Data Fusion Method
by: Qiang Song, et al.
Published: (2020-11-01)

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

Application of SVM Optimized by IPSO in Rolling Bearing Fault Diagnosis
by: Lv Mingzhu, et al.
Published: (2018-01-01)

Weak fault diagnosis of rolling bearing based on FRFT and DBN
by: Xing He, et al.
Published: (2020-01-01)

An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing
by: Meijiao Li, et al.
Published: (2014-11-01)

Local coordinate weight reconstruction for rolling bearing fault diagnosis
by: Chenxi Wu, et al.
Published: (2020-11-01)

Rolling Bearing Fault Diagnosis Based on an Improved HTT Transform
by: Bin Pang, et al.
Published: (2018-04-01)

A rolling bearing fault diagnosis method based on LSSVM
by: Xuejin Gao, et al.
Published: (2020-01-01)

Application of MCKD and improved LSSVM in fault diagnosis of rolling bearing
by: Liu Bo, et al.
Published: (2018-07-01)

Fault diagnosis of rolling bearing using CVA based detector
by: Baoxiang Wang, et al.
Published: (2016-11-01)

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

Rolling Bearing Fault Diagnosis Based on the Coherent Demodulation Model
by: Yinghua Shao, et al.
Published: (2020-01-01)

Multi-Bandwidth Mode Manifold for Fault Diagnosis of Rolling Bearings
by: Tao Jiang, et al.
Published: (2019-01-01)

Frequency Phase Space Empirical Wavelet Transform for Rolling Bearings Fault Diagnosis
by: Xin Huang, et al.
Published: (2019-01-01)

Simultaneously Low Rank and Group Sparse Decomposition for Rolling Bearing Fault Diagnosis
by: Kai Zheng, et al.
Published: (2020-09-01)

Multiple Feature Vectors Based Fault Classification for WSN Integrated Bearing of Rolling Mill
by: Bo Qin, et al.
Published: (2018-01-01)

Enhanced Lightweight Multiscale Convolutional Neural Network for Rolling Bearing Fault Diagnosis
by: Yaowei Shi, et al.
Published: (2020-01-01)

Diagnosis Approach for Incipient Faults of Rolling Bearings Under Sectional Jumping Speed
by: Ke Lanyan, et al.
Published: (2019-01-01)

Bearing Fault Feature Extraction and Fault Diagnosis Method Based on Feature Fusion
by: Huibin Zhu, et al.
Published: (2021-04-01)

Imbalanced Fault Diagnosis of Rolling Bearing Using Data Synthesis Based on Multi-Resolution Fusion Generative Adversarial Networks
by: Du, J., et al.
Published: (2022)

Transformer Fault Identification with an IF-1DCNN Based on Informative Integration of Heterogeneous Sources
by: Huipeng Du, et al.
Published: (2021-01-01)

A Fast Kurtogram Demodulation Method in Rolling Bearing Fault Diagnosis
by: Li Li, et al.
Published: (2016-01-01)

Fault diagnosis method of rolling bearings Based on SPA-FE-IFSVM
by: Hui Han, et al.
Published: (2020-10-01)

An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis
by: Zhicheng Qiao, et al.
Published: (2020-01-01)

Application of the phase difference correct method in rolling bearing fault diagnosis
by: Xinyi Li, et al.
Published: (2017-12-01)

A Novel Rolling Bearing Fault Diagnosis and Severity Analysis Method
by: Yinsheng Chen, et al.
Published: (2019-06-01)

Cannot write session to /tmp/vufind_sessions/sess_v4kvjcortu7nvs57lantogq5hc