No abstract

The probability of detection (POD) is the minimum detectable size of defects that helps in selecting an appropriate method for nondestructive testing (NDT) for a particular application and it is usually expressed as a function of defect size or aspect ratio (dimension/depth). It is a measure of the efficiency of an inspection process which is used to quantify the capability of the NDT method. For characterizing and quantifying the inspection capability and reliability of the method, POD curves are analyzed. The objective of this study is to measure the efficiency of an image processing algorithm that can locate defected areas that may be present in the analyzed sample in a completely automated way. In this article, for Frequency Modulated Thermal Wave Imaging (FMTWI), different data processing algorithms are compared by POD curves. POD curves of different segmentation algorithms for different processing algorithms are also carried out and compared with the proposed segmentation algorithm. The POD curves of the hit/miss data processing are used for estimating the detection capability and FMTWI image of glass fiber–reinforced composites, and the effects of the defect aspect ratio with 90 % POD (r90) and the defect aspect ratio for which a 90 % POD is reached at the 95 % confidence level (r90/95) on POD curves are compared.

No abstract

Abstract:The Infrared non-destructive evaluation (IRNDE) is an emerging approach for non-contact inspection of various solid materials such as metals, composites and semiconductors for industrial and research interest. Data processing is an essential step in IRNDE in order to visualize the subsurface defects in the sample and determine the shapes and sizes of the same. The data processing intends to analyse temporal variations in the contrast of each pixel, relative to defect-free reference point on the sample. For that, several post processing algorithms are applied to the recorded thermograms. In this work, it is proposed to an advanced graphical user interface (GUI) for processing the recorded thermograms by IR camera using MATLAB, that supports preprocessing, processing and quantification is presented. Investigations arecarried out using the thermal image sequence recorded with different active thermographic methods: frequency modulated thermal wave imaging (FMTWI) Pulse thermography (PT), lock in thermography (LT). A comparative analysis of the results from different themographic techniques for defect visualization is presented.