MUMBAI, India, Feb. 27 -- Intellectual Property India has published a patent application (202641018522 A) filed by Sr University, Warangal, Telangana, on Feb. 18, for 'automating fault detection in industrial machinery with deep learning techniques.'
Inventor(s) include Dr. Shaik Bazani; and Dr. Balajee Maram.
The application for the patent was published on Feb. 27, under issue no. 09/2026.
According to the abstract released by the Intellectual Property India: "This invention introduces an innovative system for automating fault detection in industrial machinery through advanced deep learning techniques, focusing on real-time monitoring and predictive maintenance to minimize downtime. By integrating convolutional neural networks (CNNs) with sensor fusion data from vibration, temperature, and acoustic signals, the system identifies anomalies with 95% accuracy, surpassing traditional rule-based methods. The deep learning model is trained on augmented datasets simulating various fault scenarios, enabling it to generalize across different machinery types like turbines and conveyor systems. Key features include edge computing for on-site processing, reducing latency to under 100 milliseconds, and an adaptive learning mechanism that refines predictions based on ongoing operational data. This approach not only detects faults early but also classifies them by severity, providing actionable insights via a user-friendly dashboard. With applications in manufacturing, energy, and transportation sectors, the invention promises cost savings of up to 30% by preventing unexpected breakdowns and extending equipment lifespan."
Disclaimer: Curated by HT Syndication.
