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Fault diagnosis via structural support vector machines

Yi Peng, Qixiang Ye, Jianbin Jiao, Xiaogang Chen, Lijun Wu
2012 2012 IEEE International Conference on Mechatronics and Automation  
Tennessee Eastman Process (TEP), a benchmark chemical engineering problem, is used to generate datasets to evaluate the performance of the propose method.  ...  In this paper, we introduce the structural Support Vector Machines (structural SVMs) to fault diagnosis, which can indentify multiple kinds of faults with only one uniform discriminative model.  ...  In section IV, conclusions are drawn. II. FAULTY DIAGNOSIS A. Tennessee Eastman Process and Data Generalization Tennessee Eastman Process (TEP) is a benchmark problem in process engineering.  ... 
doi:10.1109/icma.2012.6284371 fatcat:s3zmer4v6ndtrdaxfpy54wqszu

Dynamic kernel scatter-difference-based discriminant analysis for diagnosis of Tennessee Eastman process

Sumana C., Venkateswarlu Ch., Ravindra D. Gudi, Mani Bhushan
2009 2009 American Control Conference  
The performance of the proposed method is evaluated by applying it for the isolation of complex faults in the Tennessee Eastman process.  ...  for fault diagnosis of nonlinear chemical processes.  ...  TENNESSEE EASTMAN PROCESS The Tennessee Eastman Process (TEP) was formulated as a challenge problem, representative of an industrial nonlinear chemical process.  ... 
doi:10.1109/acc.2009.5160741 dblp:conf/amcc/CCGB09 fatcat:qna4wdajgzb3bfresluntf2v6a

Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis

Xiaoming Xu, Chenglin Wen
2017 Journal of Control Science and Engineering  
Furthermore, the simulation experiments based on Tennessee Eastman process and Wine datasets demonstrate the feasibility and effectiveness of the new method.  ...  In order to solve it, this paper proposes a kind of fault diagnosis method based on information entropy and Relative Principle Component Analysis.  ...  Acknowledgments This work is supported by National Natural Science Foundation (NNSF) of China under Grant nos. U1509203, 61333005, U1664264, and 61490701.  ... 
doi:10.1155/2017/2697297 fatcat:duwcbffn7bgetekks74u4f5bou

On the use of multi-agent systems for the monitoring of industrial systems

Nafissa Rezki, Okba Kazar, Leila Hayet Mouss, Laid Kahloul, Djamil Rezki
2015 Journal of Industrial Engineering International  
The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.  ...  This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s40092-015-0133-7 fatcat:ben4wlyejne5fatwoxcwqwbb6i

FAULT DIAGNOSIS BASED ON MULTI-SCALE CLASSIFICATION USING KERNEL FISHER DISCRIMINANT ANALYSIS AND GAUSSIAN MIXTURE MODEL AND K-NEAREST NEIGHBOR METHOD

Norazwan Md Nor, Mohd Azlan Hussain, Che Rosmani Che Hassan
2017 Jurnal Teknologi  
When linear discriminant analysis is used for fault diagnosis in the system, a lot of incorrect diagnosis will occur.  ...  These two classifiers are evaluated and compared based on their performance on the Tennessee Eastman process database.  ...  Acknowledgement The authors are thankful to Ministry of Higher Education Malaysia for their ASTS (SLAB) scholarship and financial support toward the project.  ... 
doi:10.11113/jt.v79.11332 fatcat:o5oltln37fa6rnq2jxj77cfjea

Preface for special issue on "Data Analysis: Techniques and Applications"

Raghunathan Rengaswamy, Lakshminarayanan Samavedham
2012 International Journal of Advances in Engineering Sciences and Applied Mathematics  
These are the Kernel PCA and nonlinear transformation of data followed by a correspondence analysis. The Tennessee-Eastman benchmark problem is used to compare the two approaches.  ...  In this work, the data that is being processed is assumed to have been generated by multiple models operating in non-intersecting partitions of the input space.  ...  These are the Kernel PCA and nonlinear transformation of data followed by a correspondence analysis. The Tennessee-Eastman benchmark problem is used to compare the two approaches.  ... 
doi:10.1007/s12572-012-0070-2 fatcat:tysqyl4bi5gyfjsddc7prjq26m

Application of Morphological Filtering and Dynamic Time Warping in Fault Diagnosis of Complex System

Han Li, Chengli Xie
2014 International Journal of Control and Automation  
The proposed methods are applied to deterministic fault classification problem in Tennessee Eastman (TE) process to demonstrate the their validity and advantages.  ...  Pattern classification / recognition is considered as one of the frequently adopted methodology in complex system fault diagnosis.  ...  We also use deterministic fault diagnosis problem in Tennessee Eastman process as a case study to demonstrate the effectness of the proposed approaches.  ... 
doi:10.14257/ijca.2014.7.11.25 fatcat:epjjks3jkfejhonq6gzehjjsli

A Novel Fault Detection and Diagnosis Scheme Based on Independent Component Analysis-Statistical Characteristics: Application on the Tennessee Eastman Benchmark Process

Cheng Zhang, Xiaofang Zheng, Yuan Li
2021 Journal of Chemical Engineering of Japan  
The simulation results of a numerical case and Tennessee Eastman benchmark process illustrate that ICA-SC can reduce the computational complexity and improve the fault detection rate of a dynamic process  ...  Finally, a new statistic index based on these calculated statistical characteristics is developed to monitor the status of the current process, and a fault diagnosis strategy based on the contribution  ...  Tennessee Eastman benchmark process e Tennessee Eastman benchmark process designed by Downs and Vogel in 1993 has been widely used for process monitoring till now (Rato and Reis, 2013) . is process consists  ... 
doi:10.1252/jcej.20we045 fatcat:abkdwvzndzer7c7fxqp4zdk2fe

Fault diagnosis of Tennessee Eastman process using signal geometry matching technique

Han Li, De-yun Xiao
2011 EURASIP Journal on Advances in Signal Processing  
This article employs adaptive rank-order morphological filter to develop a pattern classification algorithm for fault diagnosis in benchmark chemical process: Tennessee Eastman process.  ...  Different fault types in Tennessee Eastman process are studied to manifest the effectiveness and advantages of the proposed method.  ...  Acknowledgements This work was supported by National Natural Science Foundation of China No. 60736026 and No. 60904044 grants and the authors would like to thank the control scheme code for TEP fault diagnosis  ... 
doi:10.1186/1687-6180-2011-83 fatcat:4fxaqpscyjakbbfmfobmnexmdm

Process Fault Diagnosis for Continuous Dynamic Systems Over Multivariate Time Series [chapter]

Chris Aldrich
2019 Time Series Analysis [Working Title]  
When considering the well-known simulated Tennessee Eastman process in chemical engineering, it is shown that time series features obtained with this approach can be an effective means of discriminating  ...  Fault diagnosis in continuous dynamic systems can be challenging, since the variables in these systems are typically characterized by autocorrelation, as well as time variant parameters, such as mean vectors  ...  Table 3 . 3 Description of variables in Tennessee Eastman process.  ... 
doi:10.5772/intechopen.85456 fatcat:ltwq2yg2jzfx3fktvgydykagtq

Fault diagnosis of Tennessee Eastman process with multi-scale PCA and ANFIS

C.K. Lau, Kaushik Ghosh, M.A. Hussain, C.R. Che Hassan
2013 Chemometrics and Intelligent Laboratory Systems  
Fault diagnosis in industrial processes are challenging tasks that demand effective and timely decision making procedures under the extreme conditions of noisy measurements, highly interrelated data, large  ...  The proposed MSPCA-ANFIS based framework is tested on the Tennessee Eastman (TE) process and results for the selected fault cases, particularly those which exhibit highly non-linear characteristics, show  ...  and diagnosis of the Tennessee Eastman (TE) process.  ... 
doi:10.1016/j.chemolab.2012.10.005 fatcat:2rjlerzxg5dotc445wdbewhvna

New informative features for fault diagnosis of industrial systems by supervised classification

Sylvain Verron, Teodor Tiplica, Abdessamad Kobi
2010 18th Mediterranean Conference on Control and Automation, MED'10  
The performances of this method are evaluated on the data of a benchmark example: the Tennessee Eastman Process. Three kinds of fault are taken into account on this complex process.  ...  The purpose of this article is to present a method for industrial process diagnosis. We are interested in fault diagnosis considered as a supervised classification task.  ...  Presentation of the TEP The Tennessee Eastman Process (TEP) is a chemical process.  ... 
doi:10.1109/med.2010.5547710 fatcat:mhnhu5enyfdhjfmr3gqw6apmiy

Fault Detection of the Tennessee Eastman Process Using Improved PCA and Neural Classifier [chapter]

Mostafa Noruzi Nashalji, Mahdi Aliyari Shoorehdeli, Mohammad Teshnehlab
2010 Advances in Intelligent and Soft Computing  
This technique is applied to simulated data collected from the Tennessee Eastman chemical plant simulator which was designed to simulate a wide variety of faults occurring in a chemical plant based on  ...  Index Term-Artificial neural network, Fault detection, Genetic algorithm, Multi layer perceptron, Principal component analysis, Tennessee eastman process.  ...  TENNESSEE EASTMAN PROCESS The TEP is a well-known benchmark chemical process, which was firstly introduced by CITATION Dow93 \l 1033 [21] .  ... 
doi:10.1007/978-3-642-11282-9_5 dblp:conf/softco/NashaljiST09 fatcat:fllfgwo3fjcmhkfyi25i2jmwtu

Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes [article]

Mingxuan Li, Yuanxun Shao
2021 arXiv   pre-print
Artificial neural network has achieved the state-of-art performance in fault detection on the Tennessee Eastman process, but it often requires enormous memory to fund its massive parameters.  ...  We have extensively studied 7 different combinations of compression techniques, all methods achieve high model compression rates over 64% while maintain high fault detection accuracy.  ...  CONCLUSION This paper studies deep compression techniques for fault diagnosis on the Tennessee Eastman process.  ... 
arXiv:2101.06993v1 fatcat:zpgqz52cjbg25plggv35yyrjoq

Metric Learning Method Aided Data-Driven Design of Fault Detection Systems

Guoyang Yan, Jiangyuan Mei, Shen Yin, Hamid Reza Karimi
2014 Mathematical Problems in Engineering  
Experiments on Tennessee Eastman (TE) chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis  ...  In this paper, we firstly propose a metric learning-based fault detection framework in fault detection.  ...  Acknowledgments The authors acknowledge the support of China Postdoctoral Science Foundation Grant no. 2012M520738 and Heilongjiang Postdoctoral Fund no. LBH-Z12092.  ... 
doi:10.1155/2014/974758 fatcat:f3qtvfslzvb25k3jpgkrxiaabu
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