Construction of cloud space fault tree and its application of fault data uncertainty analysis
Shasha Li, Tie Jun Cui, Xingsen Li, Laigui Wang, Jiang Fu-chuan · 2017
The space fault tree (SFT) is a theoretical and technical framework. The SFT measures the reliability with fault probability, and analyzes the relationship between system reliability and influencing factors. The system fault data is different from the general monitoring data, which has the uncertainty. The existing characteristic function is difficult to express the uncertainty of fault data. To this end, using cloud model to transform the characteristic function, so that it has the ability to express the uncertainty of data, called the cloud characteristic function. The cloud SFT(CLSFT) is constructed by using the cloud characteristic function, which enables the relevant theories and methods of SFT to express the data uncertainty. Use the CLSFT to analyze the fault data of a simple electrical component. The relationship is studied between the component fault probability and the using time and using temperature. The results reflect the discreteness, randomness and fuzziness of the fault data to a large extent. In summary, the paper provides the reference for controlling the uncertainty of the reliability in practical application.