Abstract
This study performed an experimental investigation on pulsed thermography to detect internal defects, the major degradation phenomena in several structures of the secondary systems in nuclear power plants as well as industrial pipelines. The material losses due to wall thinning were simulated by drilling flat-bottomed holes (FBH) on the steel plate. FBH of different sizes in varying depths were considered to evaluate the detection capability of the proposed technique. A short and high energy light pulse was deposited on a sample surface, and an infrared camera was used to analyze the effect of the applied heat flux. The three most established signal processing techniques of thermography, namely thermal signal reconstruction (TSR), pulsed phase thermography (PPT), and principal component thermography (PCT), have been applied to raw thermal images. Then, the performance of each technique was evaluated concerning enhanced defect detectability and signal to noise ratio (SNR). The results revealed that TSR enhanced the defect detectability, detecting the maximum number of defects, PPT provided the highest SNR, especially for the deeper defects, and PCT provided the highest SNR for the shallower defects.
Highlights
Steel is one of the world’s most versatile materials with excellent qualities of strength, corrosion resistance, weldability, formability, workability, and attractiveness
For the deeper defect B1 ; the raw thermal image provided the signal to noise ratio (SNR) of 19.18 dB; thermal signal reconstruction (TSR) provided the SNR of 31.18 dB, which is an increment of 62.56%; pulsed phase thermography (PPT) provided the SNR of 46.28 dB, which is an increment of 141.29%; principal component thermography (PCT) provided the SNR of 41.6 dB which is an increment of 116.89%; when compared with the raw thermal image
In this work, pulsed thermography was applied to a steel structure with the aim to detect wall thinning defects
Summary
Steel is one of the world’s most versatile materials with excellent qualities of strength, corrosion resistance, weldability, formability, workability, and attractiveness. Used standard thermal contrast method based on PT to estimate the size and depth of FBH defects in austenitic steel. It was demonstrated that PPT can detect the deeper defects with other features such as less influence of optical characteristics and surface infrared, and the possibility to inspect test sample with higher thermal conductivity. S.M. Shepard et al [54] proposed the thermal signal reconstruction (TSR) technique and analyzed the experimental PT data to detect the FBH defects in steel structure. The second purpose to employ the and standard represent real wall thinning as the difference between real wallwas thinning defects signal processing techniques, PPT,ofand evaluate their performance in defects are relatively small.
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