Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information

doi:10.1007/s12204-015-1641-8

Journal of shanghai Jiaotong University (Science) ›› 2015, Vol. 20 ›› Issue (3): 380-384.doi: 10.1007/s12204-015-1641-8

Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information

ZHAO Chun-yu1* (赵春宇), LIU Jing-jiang1 (刘景江), MA Lun2 (马伦), ZHANG Wei-jun3 (张伟君)

(1. Baicheng Ordnance Test Center of China, Baicheng 137001, Jilin, China; 2. Academy of Equipment, Beijing 101416, China; 3. Divisions 73, Unit 66362, Beijing 101200, China)
(1. Baicheng Ordnance Test Center of China, Baicheng 137001, Jilin, China; 2. Academy of Equipment, Beijing 101416, China; 3. Divisions 73, Unit 66362, Beijing 101200, China)

Published:2015-06-11
Contact: ZHAO Chun-yu (赵春宇) E-mail:malun018@163.com

Abstract

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.

Key words: monotonicity evaluation| monitoring feature| ranking mutual information| prognostics

摘要： 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.

关键词: monotonicity evaluation| monitoring feature| ranking mutual information| prognostics

CLC Number:

TP 206

ZHAO Chun-yu1* (赵春宇), LIU Jing-jiang1 (刘景江), MA Lun2 (马伦), ZHANG Wei-jun3 (张伟君). Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 380-384.

References 8

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Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information

Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information

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