Intelligent technical audit system for boiler equipment based on iot monitoring and digital twin
DOI:
https://doi.org/10.31548/energiya4(86).2026.109Keywords:
boiler plant, IoT monitoring, digital twin, technical audit, energy efficiency, predictive maintenance, PI controller, mathematical modelAbstract
The relevance of the study is determined by the critical condition of boiler equipment in the municipal and industrial sectors of Ukraine, which leads to excessive fuel and energy consumption and an increased risk of failures. The purpose of the work is to develop the concept and architecture of an intelligent technical audit system for boiler equipment, combining real-time IoT monitoring, digital twin-based mathematical modeling, and automated analysis of key energy efficiency indicators (KPIs). The research methods include automatic control theory, mathematical modeling of dynamic systems via Laplace transfer functions, Hurwitz stability criterion, and digital twin methodology (ISO 23247). A three-level architecture was developed comprising: IoT field devices level, mathematical identification and parameter estimation level, and digital twin level for predictive analysis. Eight KPIs were formalized covering energy conversion efficiency, control quality (steady-state error, overshoot, settling time), and Z-score anomaly detection relative to the digital twin reference profile. The feasibility of applying a predictive maintenance algorithm based on the analysis of deviations from the reference model of the digital twin is proposed and justified.
Recieved: 10.05.2025. Recieved: 08.07.2026. Accepted: 20.08.2026
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