Abstract
In large-scale and complex industrial systems, unplanned outages and hazardous accidents cause huge economic losses, environmental contamination, and human injuries, due to component degradation, exogenous changes, and operational mistakes. In order to ensure safety and increase operational performance and reliability of complex system, this study proposes an integrated method for safety pre-warning to analyze the current safety state of each component and the whole system indicating hidden hazards and potential consequence, and furthermore predict future degradation trends in the long term. The work presented here describes the rationale and implementation of the integrated method incorporating HAZOP study, degradation process modeling, dynamic Bayesian network construction, condition monitoring, safety assessment and prognosis steps, taking advantage of the priori knowledge of the interactions and dependencies among components and the environment, the relationships between hazard causes and effects, and the use of historical failure data and online real-time data from condition monitoring. The application of the integrated safety pre-warning approach described here to the specific example of the gas turbine compressor system demonstrates how each phase of the presented method contributes to completion of the safety pre-warning system development in a systematic way.
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