Abstract
According to the different performance degradation paths, reliability curves and parameters of each product in service phase, the reliability and remaining life of components at current moment can be evaluated in real-time reliability assessment by integrating real-time status, historical information and service time of components. The realtime reliability evaluation is valued because it is more personalized, precise, real-time and lean than traditional methods. Furthermore, the results from real-time reliability assessment can also represent the health status of component at current time. In the current research, real-time reliability assessment mainly relies on regression analysis and time series analysis, but these two methods are mainly used to describe the component degradation process, and cannot reflect the influence of external random environment on the component state change. At the same time, due to these limitations of time, economy and test conditions, it is also worth studying how to obtain more accurate and practical reliability distribution and determine a detection interval under the condition of less data. Therefore, based on the analysis of real-time reliability evaluation principle, a more appropriate real-time reliability evaluation method and the detection interval decision model are proposed by means of random degradation process, parameter sequence test joint distribution estimation and failure risk. The result from this method is a quantized value, which is convenient for the direct application of the follow-up maintenance decision research. Therefore, the research in this paper has extensive reference value and practical application prospect.
Highlights
Real-time reliability assessment[1] refers to the real-time evaluation for reliability index based on real-time detection information from a specific component or system
The primary task of real-time reliability assessment is to obtain the prior distribution in figure 2 by statistical analysis of the historical information of similar products, and to obtain the distribution of performance parameters in figure 1 which integrates real data with the state data measured in the field, so as to obtain the product real-time reliability
Based on studying the principle of real-time reliability assessment, a more suitable method is proposed in this paper for real-time reliability assessment and detection interval prediction of components by integrating real-time status, historical information, environmental factors and service time of components
Summary
Real-time reliability assessment[1] refers to the real-time evaluation for reliability index based on real-time detection information from a specific component or system. The distribution of performance parameters in figure 1 includes both historical experimental data analysis and field measurement data It can better represent the actual situation of the product. The primary task of real-time reliability assessment is to obtain the prior distribution in figure 2 by statistical analysis of the historical information of similar products, and to obtain the distribution of performance parameters in figure 1 which integrates real data with the state data measured in the field, so as to obtain the product real-time reliability. The methods of realtime reliability evaluation and detection interval decision are proposed in this paper based on random process, sequential joint distribution and failure risk theory
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