Abstract
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.
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Hua, C., Zhang, Q., Xu, G., Xie, J. (2010). Real-Time Performance Reliability Assessment Method Based on Dynamic Probability Model. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_12
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DOI: https://doi.org/10.1007/978-3-642-16530-6_12
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