Results 31 to 40 of about 3,123 (260)

An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN

Jixie chuandong, 2016
An approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed.
Han Tao, Yuan Jianhu, Tang Jian, An Lizhou   +3 more
doaj   +2 more sources

Application of the Rational Hermite Interpolation LMD Method in the Compound Fault Diagnosis Research

Jixie chuandong, 2018
In view of the multi-component coupling modulation characteristics of complex fault signals and the envelope error phenomenon of the local average decomposition method,an LMD method based on rational sub-interval Hermite interpolation is proposed ...
Cui Yanping, Lu Zhaojing, Wu Chunyu
doaj   +2 more sources

Compound Fault Diagnosis of Aero-Engine Rolling Element Bearing Based on CCA Blind Extraction

IEEE Access, 2021
Fault diagnosis of aero-engine spindle bearing is a critical technique of engine prognostics and health management. As is known that the diagnosis of compound fault of aero-engine spindle bearing is very difficult and easily affected by other vibration ...
Wei-Tao Zhang, Xiao-Fan Ji, Ju Huang, Shun-Tian Lou   +3 more
doaj   +1 more source

A feature learning method for rotating machinery fault diagnosis via mixed pooling deep belief network and wavelet transform

Results in Physics, 2022
Deep learning has extensive application in fault diagnosis regarding the health monitoring of machinery core components. Although deep networks have better nonlinear representation ability, they inevitably introduce a large number of parameters ...
Jiahui Tang, Jimei Wu, Jiajuan Qing
doaj   +1 more source

Compound Fault Diagnosis of Rolling Bearing Based on ALIF-KELM [PDF]

Mathematical Problems in Engineering, 2021
Aiming at the shortcomings of difficult classification of rolling bearing compound faults and low recognition accuracy, a composite fault diagnosis method of rolling bearing combined with ALIF and KELM is proposed. First, the basic concepts of ALIF and KELM are introduced, and then ALIF is used to decompose the sample data of vibration signals of ...
Jie Ma, Shitong Liang, Zhengyu Du, Ming Chen   +3 more
openaire   +1 more source

Lightweight Convolutional Transformers Enhanced Meta Learning for Compound Fault Diagnosis of Industrial Robot [PDF]

, 2023
Recent advance of deep learning has seen remarkable progress in compound fault diagnosis modeling for industrial robots. Nevertheless, the data scarcity of compound fault samples jeopardizes the modeling performance of deep learning algorithms.
Chen, Chong, Liu, Chao, Liu, Yuxin, Wang, Tao, Cheng, Lianglun   +4 more
core   +1 more source

Compound Fault Feature Extraction of Wind Power Gearbox Based on DRS and Improved Autogram

Zhongguo dianli, 2023
Compound fault feature extraction is the key to analyzing the root cause of wind power gearbox faults. A compound fault feature extraction method based on DRS and improved Autogram is proposed.
Haifei MA, Wei TENG, Dikang PENG, Yibing LIU, Tao JIN   +4 more
doaj   +1 more source

Research on rolling bearing compound fault diagnosis based on AMOMCKD and convolutional neural network. [PDF]

Sci Rep
Due to the uncertainty existing in the actual industrial environment, the rolling bearing compound fault features present coupling and complexity, which brings challenges to the compound fault feature extraction.
Hao R, Bai Y, Yang K, Cheng Y, Chang S.
europepmc   +2 more sources

Fault Diagnosis of Rotating Machinery Using Denoising-Integrated Sparse Autoencoder Based Health State Classification

IEEE Access, 2023
The diagnostic study on single-fault with distinguishing features based on monitoring data analysis is mature and fruitful in recent years. However, the early fault signals collected by practical monitoring systems often possess the following ...
Jing Yang, Guo Xie, Yanxi Yang
doaj   +1 more source

Intelligent diagnosis of rolling bearing compound faults based on device state dictionary set sparse decomposition feature extraction–hidden Markov model

Advances in Mechanical Engineering, 2020
Identification of rolling bearing fault patterns, especially for the compound faults, has attracted notable attention and is still a challenge in fault diagnosis.
HongChao Wang, WenLiao Du
doaj   +1 more source