Identification of Yarn Periodical Errors Using Signal Processing Techniques Based on Capacitive and Optical Sensors Measurements

This paper presents a study to identify the type and location of yarn periodical errors applying three different signal processing approaches based on FFT – Fast Fourier Transform, FWHT-Fast Walsh-Hadamard Transform and FDFI – Fast Impulse Frequency Determination. The errors determination is applied for the mass measurement of yarn using a capacitive sensor and for the measurement of yarn diameter/hairiness based on optical sensors. Commercial equipment uses exclusively a FFT approach which is not able to clearly detect other types of common periodical yarn errors, especially impulse errors, as well as an inferior resolution than the 1mm used in this work. The theoretical description of each signal processing technique is presented, as well as their application to several simulated errors, namely, sinusoidal, rectangular, pulse and impulse errors, showing proper results and a more complete analysis of periodical errors. Keywordscapacitive sensors; optical sensors; periodical errors; yarn mass; yarn hairiness; yarn diameter; fast walshhadamard; fast impulse frequency determination; fft.