Results 221 to 230 of about 8,705 (267)

Fault detection and diagnosis of a motor bearing shield

Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011
Recent years have seen increased attention to the Preventive Maintenance (PM) where corrective actions are promptly taken before small faults manifest themselves to be serious failures. Also, these undetected incipient faults present in an unhealthy machine can result in unnecessary waste of energy.
Jittiwut Suwatthikul, Sunisa Sornmuang
openaire   +1 more source

Federated Learning Architecture for Bearing Fault Diagnosis

2021 International Conference on System Science and Engineering (ICSSE), 2021
Federated learning (FL) is a distributed machine learning and it can obtain the participants, such as many companies or personal mobiles. The key point of federated learning is that it does not require the participants to send their data to the others, and FL only upload the gradients or weights of model trained by local data of each participant ...
Guan-Ying Huang, Ching-Hung Lee
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Bearing fault diagnosis with morphological gradient wavelet

Journal of the Franklin Institute, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mohammad H. Khakipour, Ali Akbar Safavi, Peyman Setoodeh   +2 more
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A novel rolling bearing fault diagnosis method

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016
In order to solve the problem of traditional methods having low accuracy in recognizing rolling bearings' faults and to reduce time in building a training model, this paper puts forward a method of recognizing faults based on wavelet packet transformation and PCA-PSO-MSVM.
Fan Zhang, Tao Zhang, Hang Yu 0006
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A classifier fusion system for bearing fault diagnosis

Expert Systems with Applications, 2013
In this paper, a new strategy based on the fusion of different Support Vector Machines (SVM) is proposed in order to reduce noise effect in bearing fault diagnosis systems. Each SVM classifier is designed to deal with a specific noise configuration and, when combined together - by means of the Iterative Boolean Combination (IBC) technique - they ...
Luana Batista, Bechir Badri, Robert Sabourin, Marc Thomas 0002   +3 more
openaire   +1 more source

LLM-based framework for bearing fault diagnosis

Mechanical Systems and Signal Processing
25 pages, 11 ...
Laïfa Tao
exaly   +3 more sources

Nonlinear methods for rolling bearing fault diagnosis

2013 Ninth International Conference on Natural Computation (ICNC), 2013
On the basis of the non-stationary and non-linear characteristics of rolling bearing vibration signals, two nonlinear methods, the correlation dimension and the symbolic entropy, are respectively used to extract characteristics factors of rolling bearing vibration signals.
Weixing He, Chunfang Yin, Xiaoping Chen
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Rolling Bearing Fault Diagnosis Research

Applied Mechanics and Materials, 2012
According to the characteristics of the rolling bearing fault, we make the research on fault diagnosis. Time domain signal can not perform the fault feature information well. The power spectrum changes the time domain signals into the frequency signals. It sets up the new data model. It uses the principal component analysis on fault diagnosis.
Zhong Hu Yuan, Yang Su, Xiao Xuan Qi
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Feature optimization for bearing fault diagnosis

2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013
This paper presents methods of feature optimization for bearing fault diagnosis. These methods optimize statistical features in time domain and frequency domain. These optimization methods mainly consist of dimensionless processing and evaluation.
Mao Wang, Niao-Qing Hu, Lei Hu, Ming Gao
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Fault diagnosis for magnetic bearing systems

Mechanical Systems and Signal Processing, 2009
A full fault diagnosis for active magnetic bearing (AMB) and rotor systems to monitor the closed-loop operation and analyze fault patterns on-line in case any malfunction occurs is proposed in this paper. Most traditional approaches for fault diagnosis are based on actuator or sensor diagnosis individually and can solely detect a single fault at a time.
Nan-Chyuan Tsai, Yueh-Hsun King, Rong-Mao Lee   +2 more
openaire   +1 more source