Detection of Defects in Geomembranes Using Quasi-Active Infrared Thermography

High-density polyethylene geomembranes are employed as covers for the sewage treatment lagoons at Melbourne Water Corporation’s Western Treatment Plant, to harvest the biogas produced during anaerobic degradation, which is then used to generate electricity. Due to its size, inspecting the cover for defects, particularly subsurface defects, can be challenging, as well as the potential for the underside of the membrane to come into contact with different substrates, viz. liquid sewage, scum (consolidated solid matter), and biogas. This paper presents the application of a novel quasi-active thermography inspection method for subsurface defect detection in the geomembrane. The proposed approach utilises ambient sunlight as the input thermal energy and cloud shading as the trigger for thermal transients. Outdoor laboratory-scale experiments were conducted to study the proposed inspection technique. A pyranometer was used to measure the intensity of solar radiation, and an infrared thermal camera was used to measure the surface temperature of the geomembrane. The measured temperature profile was analysed using three different algorithms for thermal transient analysis, based on (i) the cooling constant from Newton’s law of cooling, (ii) the peak value of the logarithmic second derivative, and (iii) a frame subtraction method. The outcomes from each algorithm were examined and compared. The results show that, while each algorithm has some limitations, when used in combination the three algorithms could be used to distinguish between different substrates and to determine the presence of subsurface defects.

Scanning induction thermography for subsurface defect orientation detection and depth quantification

Pulsed eddy current thermography (PECT) and eddy current lock-in thermography (ECLIT) are non-destructive testing (NDT) techniques of high promising and interest in subsurface defect detection. In the previous researches, the induction coil was set above the defect region and it always parallel to the defect orientation. However, the location and orientation of subsurface defects cannot be determined before detection. Therefore, the scanning induction thermography (SIT) based on dynamic thermography is proposed by some researchers to localize and distinguish the subsurface defects. Still, the main challenges of SIT are how to detect the subsurface defect orientation and quantify the depth. So that, the quantitative analysis in SIT with the new feature extraction methods was investigated and improved to detect the subsurface defect orientation and quantify the defect depth within 5 mm by using experimental studies.