Thermal Imaging for Enhancing Inspection Reliability: Detection and Characterization

Abstract

Reliable performance of an equipment or structure depends on pre-service quality and in-service degradation of the equipment or structure under operating conditions. The role of non-destructive testing (NDT) is to ensure integrity, and in turn, reliability of equipment or structure. Besides, NDT can also monitor in-service degradation and to avoid premature failure of the equipments/structures and prevent accidents as well as save human life. Up to now, NDT has been used in various fields of applications such as the inspection of electrical power plant, substation, storage tanks, bridges, aircraft, pressure vessel, rail, pipeline and so on. Efficient and reliable NDT evaluation techniques are necessary to ensure the safe operation of complex parts and construction in an industrial environment for assessing service life, acceptability, and risk, as well as for reducing or even eliminating human error. Hence, making the inspection process to be fully automated could produce a more reliable, reproducible, faster evaluation and also sustainability. Previously, due to the lack of effective computational and analytical tools, the data interpretation depends strongly on the experienced and expert of NDT personnel. Nonetheless, since the advancements in computer engineering, modern electronic systems, material science and other related fields made a major impact on all or many of the NDT methods. Data acquisition, analysis and interpretation were automated to increase the reliability and thus reduce the effect of human errors and wrong diagnosis. As NDT is not a direct measurement method, the nature and size of defects must be obtained through analysis of the signals obtained from inspection. Signal and image processing have provided powerful techniques to extract information on material characterization, size, defect detection, and so on. For instance, in the case of images, the major processing and analysis methods include image restoration and enhancement, morphological operators, wavelet transforms, image segmentation, as well as object and pattern recognition, facilitating extraction of special information from the original images, which would not, otherwise, be available. Therefore this chapter will emphasize the application of thermal image processing in assessing the reliability of concrete structure and diagnosing the condition of electrical equipments.