MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202621056463 A) filed by Rajarambapu Institute Of Technology on May 04, 2026, for Intelligent Hybrid Vibro-Acoustic Gearbox Predictive Maintenance System With Deep Learning.
Inventors include Sakshi Dilip Patil; Harshvardhan Dhanajirao Nayakal; Neha Parashuram Manugade; and Sanika Shyam Hajare.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: ABSTRACT: Intelligent Hybrid Vibro-Acoustic Gearbox Predictive Maintenance System with Deep Learning This invention describes an intelligent predictive maintenance system for monitoring the operational health of industrial gearboxes using hybrid vibro-acoustic sensing, advanced signal processing, and deep learning-based analytics. The system acquires multi-modal data including vibration signals, acoustic emissions, and lubrication condition parameters, which are processed using noise filtering, Fast Fourier Transform (FFT), and wavelet packet decomposition to extract fault-relevant features. A hybrid deep learning model comprising convolutional neural networks (CNN) and Long Short-Term Memory (LSTM) networks analyzes the extracted features to classify gearbox conditions, predict fault progression, and estimate remaining useful life. The system further incorporates a digital twin model for real-time comparison between simulated and actual operating conditions to enhance anomaly detection accuracy. Processed outputs are transmitted via an IoT-enabled framework to a cloud-connected monitoring dashboard, providing real-time visualization and predictive insights, thereby enabling proactive maintenance, reducing downtime, and improving operational reliability.
Disclaimer: Curated by HT Syndication.
