MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641109545 A) filed by Sri Venkateswara College Of Engineering on September 11, 2026, for Intelligent Mechanical Fault Detection System.
Inventors include Dr. Jagath Narayana Kamineni; Dr. N Rajesh; Dr. Venkata Kondaiah E; Mr. C P Balaji; Mr. D Anjan Kumar Reddy; Dr. Vamsi Krishna Mamidi; Mr. M Peeraiah; Dr. Balaji Ganesh N; Dr. T Chandrasekhar Rao; Mr. K. Harshavardhan Reddy; and Mr. Eswaraiah Billu.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to an Intelligent Mechanical Fault Detection System configured for continuous monitoring, early detection, and classification of mechanical faults in industrial machinery. The system comprises a plurality of sensor units, a data acquisition unit, a signal preprocessing unit, an intelligent fault detection module, a fault classification module, a machine health assessment module, an alert generation unit, a data storage unit, and a monitoring interface. The sensor units acquire machine-condition parameters including vibration, temperature, acoustic signals, rotational speed, pressure, and other relevant operating characteristics. The acquired signals are transmitted to the data acquisition unit and subjected to filtering, noise reduction, normalization, segmentation, and feature extraction to obtain meaningful condition-related information. The processed data is analysed by the intelligent fault detection module using machine-learning, signal-processing, and pattern-recognition techniques to identify deviations from normal operating behavior. When an abnormal condition is detected, the fault classification module determines the probable fault type, including bearing defects, shaft misalignment, rotor imbalance, gear damage, mechanical looseness, lubrication-related abnormalities, overheating, and other mechanical failures. The machine health assessment module determines the operating condition and severity of the detected abnormality. An alert generation unit provides timely notifications to operators or maintenance personnel, while the storage unit maintains historical operating and diagnostic information for trend analysis and predictive maintenance. The system supports real-time or near-real-time monitoring and may employ local, edge, or remote processing. The invention improves early fault identification, reduces dependence on manual inspection, minimizes unexpected downtime and maintenance costs, and enhances the reliability, safety, and service life of mechanical equipment.
Disclaimer: Curated by HT Syndication.
