Feature extraction for sound detection of industrial parts

In the modern industrial field, the quality of industrial parts is directly related to the smooth progress of the entire production process and the performance of the final product, so its quality control is of great significance. However, the quality inspection of parts in the traditional industrial production process often faces many problems such as time-consuming and large manpower investment. Fortunately, in recent years, the sound detection technology of parts has made rapid development, providing new ways and methods for quality inspection. In this context, feature extraction of sound signals has become a key link. First, the high-frequency component of the sound signal is enhanced with the help of pre-emphasis, which helps to capture the details of the signal more accurately. Subsequently, the signal is divided into frames, and the signal can maintain relatively stable characteristics in each frame by reasonably dividing the frame length and frame shift, which lays the foundation for subsequent analysis. Then, the windowing operation is used to effectively suppress the spectrum leakage, so that the analysis results are smoother and more reliable, and the errors and deviations caused by the spectrum leakage are reduced. Finally, the fast Fourier transform is used to convert the signal to the frequency domain, so that the characteristic information contained in the signal can be deeply mined from the perspective of the frequency domain. It can be said that the effective extraction of signal features is an important prerequisite to ensure the accuracy and validity of sound detection results, and only accurate extraction of features can provide a solid basis for the accurate judgment of part quality and promote the quality detection technology of industrial parts to a new level.