Bayesian-based information extraction and aggregation approach for multilevel systems with multi-source data

The ever-increasing complexity of industry facilities has made the reliability analysis and assessment an imperative yet tough work. Motivated by practical engineering requirement, this paper develops a Bayesian-based information extraction and aggregation (BIEA) approach for system level reliability estimation of a complex system. It takes both subjective judgments and objective field outputs into consideration. Novel features of this approach is a unique information content based aggregation process, which allows a flexible application of this framework in separated modules on account for purpose. The coherency of which is guaranteed by the objective information content calculation. This work goes beyond the alternatives that deal with solely attributed data under ideal information circumstance, and investigates a more generic tool for real engineering application. Limitations embedded in traditional statistical modeling methods have been eliminated in a nature manner by information transition and integration. In addition, a double axis driving mechanism (DADM) for erecting the antenna of a satellite is demonstrated as case study for benefit illustration and effectiveness verification.