Smart thermal power
Health Analysis system for four Tubes of TRI Boiler

The TRI boiler four-tube health analysis system is developed based on big data analysis platform, which can realize real-time on-line monitoring and early warning of boiler four tubes. The system has a four-tube life prediction model based on artificial intelligence analysis technology, and the digital twin simulation modeling technology is used to realize the intuitive and three-dimensional display of the internal structure of the boiler. and view the relevant dynamic and static ledger, tube replacement data, explosion data, as well as wall temperature monitoring and other information.

  • "four tubes" real-time monitoring, advance early warning, ultra-high accuracy
    The system supports the combination of artificial intelligence algorithm model and mechanism model, and realizes intelligent analysis and advanced prediction of boiler four-tube defects by establishing thinning model, wear model, creep model and corrosion model, with an accuracy of more than 80%. The system also supports cooperation with the water-cooled wall climbing detection robot, the data can verify each other, and the analysis conclusion is more accurate. It reduces the maintenance time, reduces the direct maintenance cost, and avoids the economic loss caused by non-stop.
  • Maintenance is more scientific, greatly reducing the non-stop rate of "four pipes"
    To provide an accurate plan and plan for maintenance, in general, the non-stop caused by the leakage of the four boiler tubes can be reduced by more than 50%, or even zero non-stop, basically achieve condition-based maintenance, reduce the maintenance time, reduce the direct maintenance cost, and avoid the economic loss caused by non-stop at the same time.
  • Artificial intelligence learning, precipitation of expert experience, improvement of work standards
    The system can refine the expert experience into a self-optimizing artificial intelligence learning model, and establish a medical record database and fault knowledge base based on knowledge graph technology, while strengthening standardization and standardization. Protect and inherit the knowledge assets of business experts.