An Experimental Study on the Defect Detectability of Time- and Frequency-Domain Analyses for Flash Thermography

A defect’s detectability in flash thermography is highly dependent on the applied post-processing methodology. The majority of the existing analysis techniques operate either on the time-temperature data or on the frequency-phase data. In this paper, we compare the efficiency of time- and frequency-domain analysis techniques in flash thermography for obtaining good defect detectability. Both single-bin and integrated-bin evaluation procedures are considered: dynamic thermal tomography and thermal signal area for the time-domain approach, and frequency domain tomography and adaptive spectral band integration for the frequency-domain approach. The techniques are applied on various carbon fiber reinforced polymer samples having a range of defect sizes and defect types. The advantages and drawbacks of the different post-processing techniques are evaluated and discussed. The best defect detectability is achieved using the integrated procedure in frequency domain.

Thermographic Inspection of Internal Defects in Steel Structures: Analysis of Signal Processing Techniques in Pulsed Thermography

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.

CIVA Simulation and Experiment Verification for Thin-Walled Small-Diameter Pipes by Using Phased Array Ultrasonic Testing

Regular inspection is important to verify the integrity of in-service pipeline in the petrochemical industry. Early detection of flaws is therefore essential to ensure the continued safe operation of pipeline. In generally, Conventional ultrasonic for thin-walled small-diameter pipes has limitations due to regulation requirements, efficiencies, lack of permanent results and repeatability. In many cases, the preferred method of inspection is radiographic testing, however there are many obvious shortcomings for radiographic detection. The aim of this work was to propose appropriate phased array ultrasonic scan plans that were able to achieve the following: reduce the inspection times, improve defect detectability and sizing, and reduce human intervention, which will reduce workforce radiation uptake. Ultrasonic simulation using CIVA and experimental verification for thin-walled small-diameter pipe with flaws that were carried out to determine the most appropriate phased array probe and its detection capabilities in this paper.

Principal Component Thermography for Defect Detection in Concrete

The goal of the condition assessment of concrete structures is to gain an insight into current condition of concrete and the existence of defects, which decrease durability and usability of the structure. Defects are quite difficult to detect using infrared thermography when concrete elements cannot be thermally excited with the Sun, together with unfavorable thermophysical properties of concrete structures. In this paper, principal component thermography (PCT) is applied as a post-processing method to a sequence of thermograms in order to enhance defect detectability in concrete structures. Defects are detected by analyzing a set of empirical orthogonal functions (EOFs), which were acquired by applying principal component analysis to a sequence of thermograms. The research was performed using concrete samples containing known defects, which were tested using a step heating thermography setup. The results of presented research show that PCT is an effective post-processing method to improve defect detection in concrete structures. By effectively improving the defect detection, PCT has a potential to improve the non-destructive testing (NDT) accuracy of using infrared thermography (IRT) on concrete structures, especially in shaded areas of such structures. The research also shows the defect detectability depending on concrete type thermal excitation setup and defect geometry.