Design and application of intelligent operation and maintenance platform for power plant compressed air station based on industrial internet

Abstract

To address the problems of low efficiency, passive fault response, extensive management, and insufficient intelligence in the operation and maintenance (O&M) of conventional power plant compressed air stations, this paper proposes an intelligent O&M platform architecture based on industrial internet. The platform adopts a four-layer cloud-edge collaborative framework, with artificial intelligence-based prognostics and health management (PHM) as its core technology. It realizes multi-source data collection, unified data governance, intelligent fault prediction, health assessment, and full-life cycle equipment management. The system integrates long short-term memory (LSTM) prediction models, health index evaluation, and multi-level early warning mechanisms to support predictive maintenance instead of postrepair. The proposed design provides a systematic and scalable solution for intelligence and digital transformation of auxiliary equipment in thermal power plants.