Detection Of Surface Defects And Subsurface Defects Of Polished Optics With Multisensor Image Fusion

Surface defects (SDs) and subsurface defects (SSDs) are the key factors decreasing the laser damage threshold of optics. Due to the spatially stacked structure, accurately detecting and distinguishing them has become a major challenge. Herein a detection method for SDs and SSDs with multisensor image fusion is proposed. The optics is illuminated by a laser under dark field condition, and the defects are excited to generate scattering and fluorescence lights, which are received by two image sensors in a wide-field microscope. With the modified algorithms of image registration and feature-level fusion, different types of defects are identified and extracted from the scattering and fluorescence images. Experiments show that two imaging modes can be realized simultaneously by multisensor image fusion, and HF etching verifies that SDs and SSDs of polished optics can be accurately distinguished. This method provides a more targeted reference for the evaluation and control of the defects of optics, and exhibits potential in the application of material surface research.

Non-contact ultrasonic inspection by Gas-Coupled Laser Acoustic Detection (GCLAD)

Gas-Coupled Laser Acoustic Detection (GCLAD) is an ultrasonic, non-contact detection technique that has been recently proven to be applicable to the inspection of mechanical components. GCLAD response raises as the intersection length between the probe laser beam and the acoustic wavefront propagating in the air increases; such feature differentiates the GCLAD device from other optical detection instruments, making it a line detection system rather than a point detector. During the inspection of structures mainly extending in two dimensions, the capability to evidence presence of defects in whichever point over a line would enable moving the emitter and the detector along a single direction: this translates in the possibility to decrease the overall required time for interrogation of components compared to point detectors, as well as generating simpler automated monitoring layouts. Based on this assumption, the present study highlights the possibility of employing the GCLAD device as a line inspection tool. To this end, preliminary concepts are provided allowing maximization of the GCLAD response for the non-destructive testing of components which predominantly extend in two dimensions. Afterwards, the GCLAD device is employed in pulse-echo mode for the detection of artificial defects machined on a 12 mm-thick steel plate: the GCLAD probe laser beam is inclined to be perpendicular to the propagation direction of the airborne ultrasound, generated by surface acoustic waves (SAWs) in the solid which are first reflected by the defect flanks and subsequently refracted in the air. Numerical results are provided highlighting the SAW reflection patterns, originated by 3 mm deep surface and subsurface defects, that the GCLAD should interpret. The subsequent experimental campaign highlights that the GCLAD device can identify echoes associated with surface and subsurface defects, located in eight different positions on the plate. B-scan of the component ultimately demonstrates the GCLAD performance in accomplishing the inspection task.

Subsurface Defect Evaluation of Selective-Laser-Melted Inconel 738LC Alloy Using Eddy Current Testing for Additive/Subtractive Hybrid Manufacturing

New materials and manufacturing technologies require applicable non-destructive techniques for quality assurance so as to achieve better performance. This study comprehensively investigated the effect of influencing factors including excitation frequency, lift-off distance, defect depth and size, residual heat, and surface roughness on the defect EC signals of an Inconel 738LC alloy produced by selective laser melting (SLM). The experimental investigations recorded the impedance amplitude and phase angle of EC signals for each defect to explore the feasibility of detecting subsurface defects by merely analyzing these two key indicators. Overall, this study revealed preliminary qualitative and roughly quantitative relationships between influencing factors and corresponding EC signals, which provided a practical reference on how to quantitively inspect subsurface defects using eddy current testing (ECT) on SLMed parts, and also made solid progress toward on-line ECT in additive/subtractive hybrid manufacturing (ASHM) for fabricating SLMed parts with enhanced quality and better performance.

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.