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4樓2015-10-10 10:35:22
fatewu
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2樓2015-10-10 10:16:15
fatewu
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Title: Monotonicity evaluation method of monitoring feature series based on ranking mutual information Authors: Zhao, Chun-yu1 Email author malun018@163.com; Liu, Jing-jiang1; Ma, Lun2; Zhang, Wei-jun3 Author affiliation: 1 Baicheng Ordnance Test Center of China, Baicheng, Jilin, China 2 Academy of Equipment, Beijing, China 3 Divisions 73, Unit 66362, Beijing, China Corresponding author: Zhao, Chun-yu Source title: Journal of Shanghai Jiaotong University (Science) Abbreviated source title: J. Shanghai Jiaotong Univ. Sci. Volume: 20 Issue: 3 Issue date: June 10, 2015 Publication year: 2015 Pages: 380-384 Language: English ISSN: 10071172 E-ISSN: 19958188 Document type: Journal article (JA) Publisher: Shanghai Jiao Tong University, 2200 Xietu Rd no.25,, Shanghai, 200032, China Abstract: As a prerequisite for effective prognostics, the goodness of the features affects the complexity of the prognostic methods. Comparing to features quality evaluation in diagnostics, features evaluation for prognostics is a new problem. Normally, the monotonic tendency of feature series can be used as the visual representation of equipment damage cumulation so that forecasting its future health states is easy to implement. Through introducing the concept of ranking mutual information in ordinal case, a monotonicity evaluation method of monitoring feature series is proposed. Finally, this method is verified by the simulating feature series and the results verify its effectivity. For the specific application in industry, the evaluation results can be used as the standard for selecting prognostic feature. © 2015, Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg. Number of references: 8 Main heading: Quality control Controlled terms: Systems engineering Uncontrolled terms: Equipment damage - Evaluation results - Health state - Monotonicity - Mutual informations - prognostics - Quality evaluation - Visual representations Classification code: 912 Industrial Engineering and Management - 913.3 Quality Assurance and Control - 961 Systems Science DOI: 10.1007/s12204-015-1641-8 Database: Compendex Compilation and indexing terms, © 2015 Elsevier Inc. |
3樓2015-10-10 10:16:43
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