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Concurrent Fault Diagnosis for Rotating Machinery Based on Vibration Sensors

Qing-Hua Zhang, Qin Hu, Guoxi Sun, Xiaosheng Si, Aisong Qin
2013 International Journal of Distributed Sensor Networks  
In this paper, to achieve concurrent fault diagnosis for rotating machinery, which cannot be accurately diagnosed by existing methods, we develop an integrated method using artificial immune algorithm  ...  Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment.  ...  In [21] , the author proposed a new method based on support vector machine with genetic algorithm to fault diagnosis of a power transformer.  ... 
doi:10.1155/2013/472675 fatcat:kju5n5kty5grlm5bf4h7eft43e


2018 International Journal of Mechatronics and Applied Mechanics  
(fuzzy kernel clustering based on density function) and vector -UGAFCM (uniform genetic fuzzy clustering) intelligent fault diagnosis method.  ...  To improve the accuracy of mechanical fault diagnosis, based on the full vector spectrum analysis and fuzzy clustering algorithm, two kinds of improved FCM algorithms were proposed, namely vector -DKFCM  ...  and the DKFCM algorithm were combined and applied in fault diagnosis of rotating machinery.  ... 
doi:10.17683/ijomam/issue3.10 fatcat:butxlwrrtbf4zki7rlhs5lenca

Semi-Supervised Fuzzy C-Means Clustering Optimized by Simulated Annealing and Genetic Algorithm for Fault Diagnosis of Bearings

Jianbin Xiong, Xi Liu, Xingtong Zhu, Hongbin Zhu, Haiying Li, Qinghua Zhang
2020 IEEE Access  
Zhang et al. gave a FCM algorithm based on a genetic algorithm (GA).  ...  Significant research for rotating machinery fault diagnosis has been previously conducted, to solve the problem of com-plex rotating machinery failure.  ... 
doi:10.1109/access.2020.3021720 fatcat:3h5y46noszgffma56zw7hmyvru

A Review on Variational Mode Decomposition for Rotating Machinery Diagnosis

M. Firdaus Isham, M. Salman Leong, M. H. Lim, M. K. Zakaria, Lim Meng Hee
2019 MATEC Web of Conferences  
Signal processing method is very important in most diagnosis approach for rotating machinery due to non-linearity, non-stationary and noise signals.  ...  Lastly, the future research suggestion has been pointed out in order to enhance the performance of the VMD method on rotating machinery diagnosis. , 0 (2019) MATEC Web of Conferences  ...  Ren et al. also proposed a selection method based on improve adaptive genetic algorithm (IAGA) [44] . Table 3 summarize the current solution for selecting and values.  ... 
doi:10.1051/matecconf/201925502017 fatcat:2prbneythrejrgow5vtyukb6xm

Signal Denoising Method Based on Adaptive Redundant Second-Generation Wavelet for Rotating Machinery Fault Diagnosis

Na Lu, Guangtao Zhang, Yuanchu Cheng, Diyi Chen
2016 Mathematical Problems in Engineering  
Vibration signal of rotating machinery is often submerged in a large amount of noise, leading to the decrease of fault diagnosis accuracy.  ...  Then, the maximum value of IDRE and the genetic algorithm are taken as the optimization objective and the optimization algorithm, respectively, to search for the optimal parameters of the ARSGW.  ...  Acknowledgments The authors acknowledge the financial support from the National Natural Science Foundation of China under Grant no. 51609203 and from the Fundamental Research Funds for the Central Universities  ... 
doi:10.1155/2016/2727684 fatcat:omyvxs7l6zacjfezj2glalw3lu

Combining the Multi-Genetic Algorithm and Support Vector Machine for Fault Diagnosis of Bearings

Jianbin Xiong, Qinghua Zhang, Qiong Liang, Hongbin Zhu, Haiying Li
2018 Shock and Vibration  
The experimental results demonstrate that by combining the genetic algorithm and SVM algorithm, fault diagnosis can be effectively realized for bearings of rotating machinery.  ...  In this paper, a parameter optimization algorithm for the SVM is proposed based on multi-genetic algorithm.  ...  To test the practicality and feasibility of the algorithm for bearing fault diagnosis in engineering applications, the traditional cross-validation algorithm and SVM algorithm based on the genetic algorithm  ... 
doi:10.1155/2018/3091618 fatcat:473ktmqybbgg3cdgr56zfvrvfm

Smart Fault Diagnostics using Convolutional Neural Network and Adam Stochastic Optimization

Subarna Shakya
2021 Journal of Soft Computing Paradigm  
In rotating machinery, the fault diagnosis schemes using CNN are analyzed and summarized. Various CNN schemes, the potential mechanisms and performance diagnosis are analyzed.  ...  Navigation, aviation and several other fields of engineering extensively make use of rotating machinery.  ...  Fault diagnosis is performed by employing sparse representation based on SVM [10] . The rotary machinery fault may also be diagnosed by combining SVM along with optimized quantum genetic algorithm.  ... 
doi:10.36548/jscp.2021.1.005 fatcat:5ow7r3wsn5bivjdsajpwlnfio4

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

Wei, Li, Xu, Huang
2019 Entropy  
Rotating machinery is widely applied in various types of industrial applications.  ...  After a brief introduction of early fault diagnosis techniques, the applications of EFD of rotating machine are reviewed in two aspects: fault frequency-based methods and artificial intelligence-based  ...  Acknowledgments: Authors are grateful to all the reviewers and the editor for their valuable comments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e21040409 pmid:33267123 pmcid:PMC7514898 fatcat:drfigyw7gzemfirsswsjuzfrii

Intelligent fault diagnosis of rotating machine elements using machine learning through optimal features extraction and selection

Syed Muhammad Tayyab, Eram Asghar, Paolo Pennacchi, Steven Chatterton
2020 Procedia Manufacturing  
Results show the ability of KNN classifier in combination with GA for correct and confident fault diagnosis of rotating machine elements in case of proper selection of parameters for features extraction  ...  Importance of feature selection for optimal performance of KNN in defect classification is studied by selecting most important and useful features using Genetic Algorithm (GA).  ...  Genetic operators are based on the idea of heredity of genetic characters over the generations.  ... 
doi:10.1016/j.promfg.2020.10.038 fatcat:cxrrvckslfbytjxplwdttjtywi

A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography

Yongbo Li, Xianzhi Wang, Shubin Si, Xiaoqiang Du
2019 Complexity  
A novel systematic framework, infrared thermography- (IRT-) based method, for rotating machinery fault diagnosis under nonstationary running conditions is presented in this paper.  ...  The diagnosis results show that the IRT-based method has certain advantages in classification rotating machinery faults under nonstationary running conditions compared with the traditional vibration-based  ...  Above all, a novel fault diagnosis method of rotating machinery based on IRT, BoVW, and SVM is proposed in this paper.  ... 
doi:10.1155/2019/2619252 fatcat:flyj274f5nhihlyikz3y3zyxoi

A Novel Method for Fault Diagnosis of Rotating Machinery

Meng Tang, Yaxuan Liao, Fan Luo, Xiangshun Li
2022 Entropy  
Then, a PARCMFDE is proposed for fault feature extraction, where its embedding dimension and class number are determined by Genetic Algorithm (GA).  ...  To extract effective fault features from the collected vibration signals and improve the diagnostic accuracy of weak faults, a novel method for fault diagnosis of rotating machinery is proposed.  ...  machinery, a new fault diagnosis method of the rotating machinery based on FIF-PARCMFDE and Fuzzy C-means (FCM) is proposed.  ... 
doi:10.3390/e24050681 fatcat:vx2z6qyq6rblrpj3a4mttgie3m

Application of Rotating Machinery Fault Diagnosis Based on Deep Learning

Wei Cui, Guoying Meng, Aiming Wang, Xinge Zhang, Jun Ding, M.Z. Naser
2021 Shock and Vibration  
The fault diagnosis technology of rotating machinery is one of the key means to ensure the normal operation of equipment and safe production, which has very important significance.  ...  of rotating machinery.  ...  Acknowledgments is research work was supported by the Fundamental Research Funds for the Central Universities (Grant no. 00/ 800015A353) and Langfang Science and Technology Support  ... 
doi:10.1155/2021/3083190 fatcat:4no2xr3f75hszivh7uhq3r2t6y

A Novel End-To-End Feature Selection and Diagnosis Method for Rotating Machinery

Gang Wang, Yang Zhao, Jiasi Zhang, Yongjie Ning
2021 Sensors  
According to the results of classification accuracy testing after dimensionality reduction on rotating machinery status, the MIVs-WBDA method has a 3% classification accuracy improvement under the low-dimensional  ...  Compared with the modified network variable selection algorithm (MIVs), the principal component analysis dimensionality reduction algorithm (PCA), variable selection based on compensative distance evaluation  ...  This paper studies the rotating machinery fault diagnosis method based on noise signals.  ... 
doi:10.3390/s21062056 pmid:33804053 pmcid:PMC7999413 fatcat:es75qwbbkvgdlnflv7t4fr4rii

Novel Rotating Machinery Structural Faults Signal Adaptive Multiband Filtering and Automatic Diagnosis

Song Xuewei, Liao Zhiqiang, Wang Hongfeng, Song Weiwei, Chen Peng, John S. Sakellariou
2021 Mathematical Problems in Engineering  
To realize an automatic diagnosis of rotating machinery structure faults, this paper presents a novel fault diagnosis model based on adaptive multiband filter and stacked autoencoders (SAEs).  ...  Results show that the proposed automatic diagnosis model can extract the characteristic components abundantly and accurately recognize rotating machinery structural faults.  ...  Rotating Machinery Structural Faults Automatic Diagnosis Method is paper proposes a method for automatically diagnosing rotating machinery structural faults based on an adaptive multiband filter and the  ... 
doi:10.1155/2021/1497964 fatcat:lnbseecafff6znaftaz2igh64a

Self-adaptive fault diagnosis of roller bearings using infrared thermal images

Zhiqiang Huo, Yu Zhang, Richard Sath, Lei Shu
2017 IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society  
The results have demonstrated that the proposed scheme can be employed effectively as an intelligent system for bearing fault diagnosis in rotating machinery.  ...  Fault diagnosis of roller bearings in rotating machinery is of great significance to identify latent abnormalities and failures in industrial plants.  ...  In the past decades, great efforts have been devoted to fault diagnosis of bearings in rotating machinery based on IRT.  ... 
doi:10.1109/iecon.2017.8217062 dblp:conf/iecon/HuoZSS17 fatcat:g7e6n5mjjzg2xdbwnhmnk5ixii
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