대형회전설비의 효율적인 상태감시를 위한 AHI 가중치 선정 기술 개발 연구

Abstract

Most large rotating facilities are periodically prevented and repaired regardless of the health condition of the facility, and unnecessary maintenance may cause facility operation suspension and economic loss. To overcome this, research is currently underway to develop an Asset Health Index (AHI) for large rotating facilities to implement condition-based maintenance. The AHI can be used to intuitively grasp the status of surveillance targets by calculating scores, and to implement this, it is necessary to set an appropriate weighting factor for each index. This study conducted weight optimization through Genetic Algorithm (GA) to improve the reliability and function of the AHI. Based on the optimized results, AHI score calculation is expected to increase the intuitiveness of state monitoring.