TY - GEN
T1 - Real-time performance reliability assessment method based on dynamic probability model
AU - Hua, Cheng
AU - Zhang, Qing
AU - Xu, Guanghua
AU - Xie, Jun
PY - 2010
Y1 - 2010
N2 - Most previous reliability estimation methods are researched on the assumption of empirical information or prior distribution which is difficult to be acquired in practice. To solve this problem, a real-time reliability assessment method based on Dynamic Probability Model is proposed. The primary step is to establish a Dynamic Probability Model on the basis of nonparametric Parzen window estimating method, and the sliding time-window technique is used to pick statistical samples respectively, then conditional probability density of performance degradation data is estimated. A sequential probability density curve is used to trace the performance degradation process, and probability distribution function on performance degradation data which exceeds the failure threshold is regarded as reliability indicator. Meanwhile, the failure rate is calculated. By analyzing the data from high pressure water descaling pump in the process of failure, it is verified that this method contributes individual equipment to estimate reliability with inadequate empirical information.
AB - Most previous reliability estimation methods are researched on the assumption of empirical information or prior distribution which is difficult to be acquired in practice. To solve this problem, a real-time reliability assessment method based on Dynamic Probability Model is proposed. The primary step is to establish a Dynamic Probability Model on the basis of nonparametric Parzen window estimating method, and the sliding time-window technique is used to pick statistical samples respectively, then conditional probability density of performance degradation data is estimated. A sequential probability density curve is used to trace the performance degradation process, and probability distribution function on performance degradation data which exceeds the failure threshold is regarded as reliability indicator. Meanwhile, the failure rate is calculated. By analyzing the data from high pressure water descaling pump in the process of failure, it is verified that this method contributes individual equipment to estimate reliability with inadequate empirical information.
KW - Dynamic probability model
KW - Performance degradation
KW - Reliability estimation
UR - https://www.scopus.com/pages/publications/78649952525
U2 - 10.1007/978-3-642-16530-6_12
DO - 10.1007/978-3-642-16530-6_12
M3 - 会议稿件
AN - SCOPUS:78649952525
SN - 364216529X
SN - 9783642165290
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 88
EP - 96
BT - Artificial Intelligence and Computational Intelligence - International Conference, AICI 2010, Proceedings
T2 - 2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Y2 - 23 October 2010 through 24 October 2010
ER -