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Deep Learning-based Intelligent Fault Diagnosis Methods towards Rotating Machinery

Shengnan Tang, Shouqi Yuan, Yong Zhu
2019 IEEE Access  
Fault diagnosis of rotating machinery plays a significant role in the industrial production and engineering field.  ...  INDEX TERMS Deep learning, deep neural network, intelligent fault diagnosis, rotating machinery. VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License.  ...  INTRODUCTION As an essential part and one of the most representative of mechanical equipment, the rotating machinery relies on rotation for purpose of a specific function.  ... 
doi:10.1109/access.2019.2963092 fatcat:h6zkva2ucff7zhcyjlwtckugwm

A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor

Omar AlShorman, Muhammad Irfan, Nordin Saad, D. Zhen, Noman Haider, Adam Glowacz, Ahmad AlShorman, Yongfang Zhang
2020 Shock and Vibration  
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating machinery (RM) have critical importance for early diagnosis to prevent severe damage of infrastructure in industrial  ...  Rolling bearings are considered to be the main component of IM. Undoubtedly, any failure of this basic component can lead to a serious breakdown of IM and for whole industrial system.  ...  In [218] , a new deep residual learningbased fault diagnosis method for the rolling bearing in rotating machinery using vibration signals is proposed. e main contribution of this research study is to  ... 
doi:10.1155/2020/8843759 fatcat:h4zyvhct6nb7lpsj7j5f3yror4

Effect of Pre-processing on Using ANN and ANFIS

Mohamed A. Moustafa Hassan
2020 Zenodo  
The accomplished outcomes are encouraging and promising in the field of diagnosis of machinery faults.  ...  This research work describes a comprehensive methods to some extent for detecting and classification of rotating machines faults using two methods of artificial intelligence which are ANN and ANFIS.  ...  ACKNOWLEDGEMENTS The Authors would like to acknowledge the Sponsor and financial support of Heliopolis University (Cairo -Egypt) for this Research work and presenting it in the international Conferences  ... 
doi:10.5281/zenodo.4007433 fatcat:we3q6lzv4nc77ml23c7icjemmm

Machine Fault Diagnosis and Prognosis: The State of The Art

Tran Van Tung, Bo-Suk Yang
2009 International Journal of Fluid Machinery and Systems  
prognosis of rotating machinery.  ...  With the aim of synthesizing and providing the information of these researches for researcher's community, this paper attempts to summarize and classify the recent published techniques in diagnosis and  ...  Diagnosis and prognosis are the two important aspects in a CBM system.  ... 
doi:10.5293/ijfms.2009.2.1.061 fatcat:btjf42m6mbd33aszky7i4tukrq

Integrated Wireless Technologies with Computer for Industrial Machinery Fault Diagnosis: Challenges Comparison and Characteristics: A Review

Moneer Ali Lilo
2018 Muthanna Journal of Pure Science  
In order to extract the significant features for fault diagnosis and monitoring, different neural, fuzzy, and signal processing based systems were adopted.  ...  A wide range of fault diagnosis approaches have been proposed to improve machinery operations in industries.  ...  The proposed system adopted a digital encoder for recognized the shaft rotation speed. The digital encoder is based on correlation spectrum to automatically recognize the shaft speed.  ... 
doi:10.18081/2226-3284/018-6/61-75 fatcat:7bc435gq4bfrjep5vyd7egfbhy

Cross-Domain Intelligent Fault Diagnosis Method of Rotating Machinery Using Multi-Scale Transfer Fuzzy Entropy

Zheng Dangdang, Bing Han, Geng Liu, Yongbo Li, Huangchao Yu
2021 IEEE Access  
Cross-domain fault diagnosis; Rotating machinery; Transfer learning; Fuzzy entropy NOMENCLATURE ApEn approximate entropy CWRU Case Western Reserve University FE fuzzy entropy KNN k-nearest neighbour  ...  By machine learning theories, the diagnosis models are able to automatically recognize the health conditions of machines.  ... 
doi:10.1109/access.2021.3063743 fatcat:rhllvltlibg4baegwxczzhcg2e

"Integrated Wireless Technologies with Computer for Industrial Machinery Fault Diagnosis: Challenges Comparison and Characteristics: A Review "

Moneer Ali Lilo, Auda Raheemah Odhaib, Abdelkrim K. Ilijanb
2018 Muthanna Journal of Pure Science  
In order to extract the significant features for fault diagnosis and monitoring, different neural, fuzzy, and signal processing based systems were adopted.  ...  A wide range of fault diagnosis approaches have been proposed to improve machinery operations in industries.  ...  The proposed system adopted a digital encoder for recognized the shaft rotation speed. The digital encoder is based on correlation spectrum to automatically recognize the shaft speed.  ... 
doi:10.52113/2/05.01.2018/61-75 fatcat:dgku7lqwj5awna2pm3h5b3udx4

Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng Chen, Shibin Wang, Baijie Qiao, Qiang Chen
2017 Frontiers of Mechanical Engineering  
On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in  ...  This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition  ...  , and reproduction in any medium, provided the appropriate credit is given to the original author(s) and the source, and a link is provided to the Creative Commons license, indicating if changes were made  ... 
doi:10.1007/s11465-018-0472-3 fatcat:xngm4jcct5berhuf33rqoxfc6i

Fault Detection through Vibration Signal Analysis based on HSM with TRIPPY Classifier

2020 International Journal of Mathematics and Computers in Simulation  
A proficient fault detection model has to be sketched for detecting slight variations of the vibrating signal of rotating machine whereas the diagnosis process prominently stuck with the inefficient extraction  ...  Accurate classification of faulty features can be accomplished by casting inimitable Trippy classifier which is designed based on selective predictive character of trippy fish which provokes a good path  ...  Comparison of Diagnosis Accuracy: The Diagnosis Accuracy is defined as the overall probability that a fault will be correctly classified based on the learning sample data set.  ... 
doi:10.46300/9102.2020.14.21 fatcat:klp4jwxp3jcs5bzqegx2rn6nze

Related Entropy Theories Application in Condition Monitoring of Rotating Machineries

Liu, Zhi, Zhang, Guo, Peng, Liu
2019 Entropy  
This article aims to review the related entropy theories which have been applied for condition monitoring of rotating machinery.  ...  Rotating machinery plays an important role in various kinds of industrial engineering. How to assess their conditions is a key problem for operating safety and condition-based maintenance.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e21111061 fatcat:zz7ii3sd6faxfnc5lll34rs2j4

A Review of Artificial Intelligence Algorithms Used for Smart Machine Tools

Chih-Wen Chang, Hau-Wei Lee, Chein-Hung Liu
2018 Inventions  
feature extraction scheme for the diagnosis of journal bearing rotor systems [85], a CNN method for fault detection in rotating machinery [86], a hierarchical adaptive deep CNN approach to bearing fault  ...  DNN scheme for rolling bearing fault diagnosis [76], a transfer learning-based approach for bearing fault diagnosis [77], the DNN for fault characteristic mining and the intelligent diagnosis of rotating  ...  Diagnosis and Detection of Mechanical Components Bearings Bearings play a significant role in all motors and other rotating systems.  ... 
doi:10.3390/inventions3030041 fatcat:6qrwhmrl2bfwrgmovqvsyx5p3y

Degradation assessment of bearing based on machine learning classification matrix

Satish Kumar, Paras Kumar, Girish Kumar
2021 Eksploatacja i Niezawodnosc  
A classification model which is based on machine learning classification matrix to assess the degradation of bearing is proposed to improve the accuracy of classification model.  ...  Review work demonstrates the comparisons among the available state-of-the-art methods.  ...  Orbit pattern recognition algorithm using the deep learning proposed for rotating machinery diagnostic [24] . They classified the fault modes of rotating machinery through orbit images.  ... 
doi:10.17531/ein.2021.2.20 fatcat:wcrzvh33m5aqroytctuw76xsne

A New Deep Stacked Architecture for Multi-Fault Machinery Identification with Imbalanced Samples

Hanen Karamti, Maha M. A. Lashin, Fadwa Alrowais, Abeer M. Mahmoud
2021 IEEE Access  
Effective intelligent fault diagnosis of rotating machinery using its vibrational signals has a considerable influence on certain analysis factors such as the reliability, performance, and productivity  ...  On the other hand, the Deep Learning (DL) studies have reported capabilities higher than the expectations of the researchers' objectives.  ...  [7] designed a new data-driven based fault diagnosis system based on fuzzy clustering techniques.  ... 
doi:10.1109/access.2021.3071796 fatcat:tyeh5z6r35e3npaxt24jj5uujm

Engineering Applications of Intelligent Monitoring and Control

Qingsong Xu, Pak-Kin Wong, Chengjin Zhang, Shane Xie, Ping-Lang Yen
2013 Mathematical Problems in Engineering  
Results of the optimally controlled model demonstrate superior performance in comparison to uncontrolled model. Bearing failure is one of the main causes of breakdown in rotating machinery. H.  ...  Friction affects the performance of the systems that control a mechanism, producing positioning errors during the execution of a given task.  ...  Acknowledgment We would like to express our heartfelt thanks to all the authors who submitted their papers and all the reviewers who helped improving the papers for this special issue.  ... 
doi:10.1155/2013/564021 fatcat:vlr6bt34hrbo5nfjiax27zrsx4

Author Index

2021 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)  
Bi, Xinjie Visibility Graph based Feature Extraction for Fault Diagnosis of Rolling Bearings [570256] Bin, Jie Optimization Method of Virtual Sand Table Background Server Based on Unity 3D [571175] C  ...  Rotating Machinery Health State Based on TPE-XGBoost [570379] Xiao, Zhuo A Review of Fault Diagnosis Methods Based on Machine Learning Patterns [570472] Xie, Bin Mechanical Fault Diagnosis Based on Self-sensing  ...  Fuzzy enhanced Failure Mode and Effects Analysis Method for Automatic Train Operation System [570315] Song, Liuyang A Novel Model of Bearing Fault Diagnosis Based on Convolutional Auto-encoder and Capsule  ... 
doi:10.1109/phm-nanjing52125.2021.9612757 fatcat:h4xp5wbdvjdpvmsri2dktwupbi
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