Intellectual Property India Publishes Patent Application for System And Method For Real-Time Tool Wear Monitoring In Cnc Milling Using Deep Learning With Vibration And Acoustic Data

MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641083711 A) filed by Vindhya Ponna; Dr. Gunji. Venkata Punna Rao; Dr. P. Ratna Raju; Praveena. S; Dr S M Jameel Basha; and Dr. J. Venkatesu Naik on July 07, 2026, for System And Method For Real-Time Tool Wear Monitoring In Cnc Milling Using Deep Learning With Vibration And Acoustic Data.

Inventors include Vindhya Ponna; Dr. Gunji. Venkata Punna Rao; Dr. P. Ratna Raju; Praveena. S; Dr S M Jameel Basha; and Dr. J. Venkatesu Naik.

The application for the patent was published on July 10, 2026, under issue no. 28/2026.

Abstract: ABSTRACT SYSTEM AND METHOD FOR REAL-TIME TOOL WEAR MONITORING IN CNC MILLING USING DEEP LEARNING WITH VIBRATION AND ACOUSTIC DATA The present invention discloses a system and method for real-time monitoring of tool wear in CNC milling operations using deep learning techniques applied to multimodal sensor data. The system integrates vibration sensors and acoustic emission microphones to capture dynamic signals generated during machining. A preprocessing unit filters, normalizes, and transforms these signals into structured feature representations suitable for machine learning. A deep learning engine, comprising convolutional neural networks for spatial feature extraction and recurrent neural networks for temporal sequence modeling, is trained to classify tool wear states and predict remaining useful life. The invention provides non-invasive monitoring without requiring modifications to the CNC machine, ensuring adaptability across diverse machining conditions, tool geometries, and workpiece materials. A decision support module generates real-time alerts and visualizations, enabling operators to make informed decisions and schedule predictive maintenance. By combining multimodal sensing with advanced neural architectures, the invention enhances machining efficiency, reduces downtime, and extends tool life, thereby supporting smart manufacturing and Industry 4.0 initiatives.

Disclaimer: Curated by HT Syndication.