Intelligent chatbot based on the T5 transformer for predictive diagnosis of induction motor faults
DOI:
https://doi.org/10.37135/ns.01.17.01Keywords:
Chatbot, Predictive diagnosis, T5 model, induction motors, TelegramAbstract
The predictive diagnosis of induction motors is essential to improve efficiency and reduce costs. This study introduces a Telegram chatbot based on the NLP model T5, adapted to interpret technical descriptions and generate automatic diagnostics with 96.2% accuracy, a 95.1% F1‑score, and 94.8% sensitivity. The main novelty lies in applying T5—a text‑only approach—rather than previous methods focused on physical signals like vibration or current, integrating it into an accessible mobile interface. The implications are significant: it enables rapid diagnostics from any device, supporting predictive maintenance in real-world environments. However, its limitation stems from being trained on synthetic data, which may affect its performance in real situations with noise and unforeseen conditions. Overall, the approach proves viable, efficient, and scalable, although it requires real-world validation and adaptive capabilities.
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