Dynamic thresholding for automated analysis of bobbin probe eddy current data

Abstract

An automated algorithm is presented for the analysis and classification of eddy current bobbin probe data obtained from nuclear power plant steam generator tubes (SGT). This algorithm attempts to find a balance between the two seemingly conflicting requirements of SGT eddy current data analysis, namely, detecting and identifying as many of the actual defects as possible, whilst limiting the number of false alarms to a minimum. Initial results presented in this paper look very promising. Steam generator tubes (SGT) in nuclear power plants are routinely inspected using eddy current techniques. Although a variety of probes are employed for inspecting steam generator tubes, the most commonly employed method involves the use of multifrequency differential bobbin type probes. Such probes are very simple and rugged. The structural integrity of the tube is assessed by analyzing the impedance changes of the probe as it travels within the tube. The inspection is usually carried out using four different frequencies to extract additional information concerning the state of the tube. Unfortunately the probe is sensitive to the presence of a number of other structures within the steam generator such as tube support plates, conductive deposits, tube sheets, etc. in addition to flaws present in the tube. The multifrequency measurements allow selective suppression of signal artifacts introduced by such benign structures as well as garner additional information concerning the flaws (1). The inspection of steam generators involves the testing of several hundreds of kilometers of tubing. The data generated by the inspection procedure is very large. Since manual interpretation of the data is extremely cumbersome and time consuming, the industry has considerable interest in automating the analysis procedure. Although a number of automatic analysis systems have been proposed over the years, their performance have fallen short of levels obtained using manual procedures. Typical problems associated with automatic procedures include high false alarm rates and or poor detection/characterization performance. This paper describes anautomatic procedure for analyzing multifrequency eddy current probe data derived from the inspection of nuclear steam generator tubes. The procedure uses a multi-step method to accomplish the task. The first step involves a filtering process to minimize the noise contained in the signal. The second step involves a two-stage process for identifying segments of the signal stream that represent defects. The third stage involves the classification of signals. Initial results obtained using this approach indicate that it is possible to build an automated system capable of meeting the seemingly conflicting the need for high detection and low false alarm rate.