Small Sample Reliability Analysis of Automatic Ultrasonic Testing of Austenitic Steel Defect

Abstract

Reliability analysis of the procedure of ultrasonic technique before inspection has been proved to be essential to ensure the equipment operation safety. The conventional evaluation methods are based on statistical models and a remarkable sample size is needed to get a accurate result. In this work, the Bootstrap model for small sample data is established based on the re-sampling technique. The probability of detection (POD) curves in different conditions are calculated based on the Bootstrap model, and used for quantitative analysis the influence of inspection parameter on stainless steel auto ultrasonic testing result. The calculated result based on bootstrap model is compared with which based on model assisted POD method. The results indicate that Bootstrap model is an efficient tool for the reliability analysis of inspection with small sample data, and insure the inspection result.