Statistical threshold determination method through noise map generation for two dimensional amplitude and time-of-flight mapping of guided waves

摘要

Conventional threshold crossing technique generally encounters the difficulty in setting a common threshold level in the extraction of the respective time-of-flights (ToFs) and amplitudes from the guided waves obtained at many different points by spatial scanning. Therefore, we propose a statistical threshold determination method through noise map generation to automatically process numerous guided waves having different propagation distances. First, a two-dimensional (2-D) noise map is generated using one-dimensional (1-D) WT magnitudes at time zero of the acquired waves. Then, the probability density functions (PDFs) of Gamma distribution, Weibull distribution and exponential distribution are used to model the measured 2-D noise map. Graphical goodness-of-fit measurements are used to find the best fit among the three theoretical distributions. Then, the threshold level is automatically determined by selecting the desired confidence level of the noise rejection in the cumulative distribution function of the best fit PDF. Based on this threshold level, the amplitudes and ToFs are extracted and mapped into a 2-D matrix array form. The threshold level determined by the noise statistics may cross the noise signal after time zero. These crossings are represented as salt-and-pepper noise in the ToF and amplitude maps but finally removed by the 1-D median filter. This proposed method was verified in a thick stainless steel hollow cylinder where guided waves were acquired in an area of 180 mm×126 mm of the cylinder by using a laser ultrasonic scanning system and an ultrasonic sensor. The Gamma distribution was estimated as the best fit to the verification experimental data by the proposed algorithm. The statistical parameters of the Gamma distribution were used to determine the threshold level appropriate for most of the guided waves. The ToFs and amplitudes of the first arrival mode were mapped into a 2-D matrix array form. Each map included 447 noisy points out of 90,720 points (0.49%). The salt-and-pepper noisy points were perfectly removed by sliding a 1-D median filter onto the ToF and amplitude maps.