2018In that year, our company began to implement the "Intelligent Fault Early Warning and Diagnosis System for Power Plant Equipment" project of Huaiyin Power Plant.

This project integrates the management resources of equipment such as boilers, turbines and electrical systems, extending the management process from condition monitoring, root cause analysis and reliability improvement to design defect analysis and service life extension, thereby achieving the goal of "controllable equipment condition, controllable management process and controllable economic cost".

The construction of this system includes the leakage early warning and life management system module for the "four tubes" of the boiler. Online vibration monitoring module for steam turbine generator sets Online vibration monitoring module for important auxiliary equipment Temperature and temperature rise monitoring modules for important auxiliary equipment; Infrared imaging monitoring module Lubricating oil monitoring module Turning machine rolling bearing life management module Fan automatic regulation system status monitoring module, etc. Centered on the analysis of equipment operation status, and using status assessment and risk assessment as means, it integrates core technologies such as intelligent expert diagnosis libraries and big data mining,Build an integrated equipment management platform.

After the project is completed, it will cover the equipment management of main equipment such as boilers, steam turbines and generators, as well as important auxiliary equipment. A cross-professional, multi-disciplinary, multi-technology and multi-functional big data information platform will be established. The vertical sorting and horizontal integration of application systems in various specialties and the application of expert diagnosis systems will be carried out to achieve real-time monitoring, intelligent diagnosis and comprehensive assessment of equipment. It will surely enhance the reliability of equipment, reduce maintenance costs, alleviate the labor intensity of workers, and innovate the equipment management model.