MATLAB Program for Time Domain, Frequency Domain, and Time-Frequency Domain Feature Extraction of Tool Fault Signals in Online Monitoring

The MATLAB program for time domain, frequency domain, and time-frequency domain feature extraction of tool fault signals in online monitoring is an essential tool for analyzing tool operating conditions. This program processes tool fault signals through comprehensive feature extraction techniques, including statistical time-domain analysis (such as RMS, kurtosis, and peak values), frequency-domain transformation using FFT algorithms to identify characteristic frequencies, and time-frequency analysis through wavelet transform methods for non-stationary signal examination. The MATLAB implementation enables detection of various tool faults including tool wear, fracture, and runout by employing signal processing algorithms that calculate distinctive feature vectors. The program's architecture typically includes functions for signal preprocessing, feature calculation modules, and classification algorithms for fault identification. This monitoring system is crucial for manufacturing as it facilitates early detection of tool failures, allowing for timely maintenance interventions to prevent unexpected production downtime and associated losses. The MATLAB program incorporates machine learning capabilities where extracted features can be used to train classifiers for automated fault diagnosis. Therefore, this comprehensive feature extraction MATLAB program represents an indispensable tool in modern manufacturing industries, providing reliable condition monitoring through advanced signal processing techniques.