A condition-based preventive maintenance arrangement for thermal power plants

Abstract

In the onsite operation phase, failures are the main causes of worsened performance and degraded reliability. Consequently, an effective maintenance is the main approach to failure reduction. According to the maintenance performed before or after a failure, maintenance can be sorted as preventive maintenance (PM) and corrected maintenance (CM). Preventive maintenance is an effective approach to improving reliability. Time-based and condition-based maintenance are two major categories of preventive maintenance. In contrast, condition-based maintenance can be a better and more cost-effective type of maintenance than time-based maintenance. To improve condition-based preventive maintenance, this study uses a hybrid Petri net modeling method coupled with fault-tree analysis and parameter trend to perform early failure detection and isolation. A Petri net arrangement, namely early failure detection and isolation arrangement (EFDIA), is employed that facilitates alarm, early failure detection, fault isolation, event count, system state description, and automatic shutdown or regulation. These functions are very useful for health monitoring and preventive maintenance of a system. Besides, the Petri net with these capabilities is not only done on paper but also actualized on an FPGA as an application-specific integrated circuit (ASIC) so that the proposed scheme is practicable. A thermal power plant is adopted as an example to demonstrate the method.