Verfahren und System zur Akustikbasierten Anomaliedetektion in Industriellen Maschinen

Details

Veröffentlichungs-Nr.

EP4365898

Aktenzeichen

EP23199581

Anmeldetag

26. September 2023

Veröffentlichung

25. Dezember 2024

Erteilung

25. Dezember 2024

Rechtsraum

EP

IPC

G10L21/0272G10L25/51G01N29/14G01N29/26G01N29/44G05B23/02// G10L25/30G10L21/0216

Abstract

In industrial inspection scenarios, early detection of machine malfunction is extremely essential as it helps in preventing any significant damage and the associated economic losses. Embodiments herein provide a method and system for an acoustic based anomaly detection in industrial machines using a beamforming and a sequential transform learning. Herein, the system employs two-stage multichannel source separation technique that uses the well-known delay and sum beamforming followed by a recent data-driven sequential transform learning (STL) approach to obtain clean sources. The STL is a solution to linear state-space model where operators/matrices are learnt from data and is used here to model the dynamics of time-varying source signals for source separation. Subsequently, a reference template matching is employed on each separated source to detect an anomaly. The numerical results obtained with the Malfunctioning Industrial Machine Investigation and Inspection (MIMII) dataset demonstrate superior performance for source separation and anomaly detection.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete