Signal Processing for Ultrasonic Testing Materials with Coarse Structure

T. Stepinski and L. Ericsson

15th World Conference on NDT, Rome, Italy, 15-21 October, 2000

Abstract:

In pulse-echo inspection the backscattering from the grain boundaries appears in the received ultrasonic images as clutter, often referred to as grain noise. The subject of signal processing for material noise reduction has been addressed in a large number of papers during the last decade. Several processing algorithms have been proposed, of which the Split Spectrum Processing (SSP) probably is the most renowned. The SSP technique applies a filter bank to some frequency band that has to be precisely known in advance, to obtain a set of signals with decorrelated noise components. Two novel algorithms are presented and verified in the paper. The first algorithm, is based on the concept of SSP but it does not require a priori knowledge of the frequency range for locating the SSPīs filter bank. The algorithm, referred to as Consecutive Polarity Coincidence (CPC), makes explicit use of the pulse characteristics of the target echo in order to implement local bandwidth estimation. If desired, a gating signal can be constructed by comparing the calculated bandwidth with a user defined threshold. Setting the threshold equal to the frequency range utilised for processing will generate a gating signal identical to the one obtained when using conventional Polarity Thresholding. The second algorithm is based on completely different approach that assumes using a transducer with as wide as possible frequency range and then applying advanced digital signal processing to adapt the effective frequency range to the properties of inspected material. The resulting algorithm is a modified version of noncoherent detection (NCD) which is known from communications. To adapt the algorithm for the use in ultrasonic NDT a two parameter model of ultrasonic wavelets is used. The construction of an NCD filter includes estimation of the autocorrelation of the noise, specification of the two parameters, lower and upper frequency of the signal prototype, and computation of the digital NCD filter. Two different ways, based respectively on signal entropy and signal-to-noise-ratio enhancement, have been developed to determine the frequencies of the prototype in an automated procedure. The performance of the algorithms is illustrated using ultrasonic images acquired from specimens made of cast stainless steel and copper with large grains. The material structures are similar to those found in nuclear power plants and in canisters intended for long term storage of nuclear waste.