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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.
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Polietileno , Termografía , Algoritmos , Calor , TemperaturaRESUMEN
Metal additive manufacturing (AM) allows obtaining functional parts with the possibility of optimizing them topologically without affecting system performance. This is of great interest for sectors such as aerospace, automotive, and medical-surgical. However, from a metrological point of view, the high requirements applied in these sectors constitute a challenge for inspecting these types of parts. Non-contact inspection has gained great relevance due to the rapid verification of AM parts. Optical measurement systems (OMSs) are being increasingly adopted for geometric dimensioning and tolerancing (GD&T) verification within the context of Industry 4.0. In this paper, the suitability (advantages and limitations) of five different OMSs (based on laser triangulation, conoscopic holography, and structured light techniques) for GD&T verification of parts manufactured by selective laser melting (SLM) is analyzed. For this purpose, a specific testing part was designed and SLM-manufactured in 17-4PH stainless steel. Once the part was measured by contact (obtaining the reference GD&T values), it was optically measured. The scanning results allow comparing the OMSs in terms of their inspection speed as well as dimensional and geometrical accuracy. As a result, two portable systems (handheld laser triangulation and structured blue-light scanners) were identified as the most accurate optical techniques for scanning SLM parts.
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This study uses machine vision, feature extraction, and support vector machine (SVM) to compose a vibration monitoring system (VMS) for an in situ evaluation of the performance of industrial motors. The vision-based system respectively offers a spatial and temporal resolution of 1.4 µm and 16.6 ms after the image calibration and the benchmark of a laser displacement sensor (LDS). The embedded program of machine vision has used zero-mean normalized correlation (ZNCC) and peak finding (PF) for tracking the registered characteristics on the object surface. The calibrated VMS provides time-displacement curves related to both horizontal and vertical directions, promising remote inspections of selected points without attaching additional markers or sensors. The experimental setup of the VMS is cost-effective and uncomplicated, supporting universal combinations between the imaging system and computational devices. The procedures of the proposed scheme are (1) setting up a digital camera, (2) calibrating the imaging system, (3) retrieving the data of image streaming, (4) executing the ZNCC criteria, and providing the time-displacement results of selected points. The experiment setup of the proposed VMS is straightforward and can cooperate with surveillances in industrial environments. The embedded program upgrades the functionality of the camera system from the events monitoring to remote measurement without the additional cost of attaching sensors on motors or targets. Edge nodes equipped with the image-tracking program serve as the physical layer and upload the extracted features to a cloud server via the wireless sensor network (WSN). The VMS can provide customized services under the architecture of the cyber-physical system (CPS), and this research offers an early warning alarm of the mechanical system before unexpected downtime. Based on the smart sensing technology, the in situ diagnosis of industrial motors given from the VMS enables preventative maintenance and contributes to the precision measurement of intelligent automation.
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As the rapid progress in the development of optoelectronic components and computational power, 3D optical metrology becomes more and more popular in manufacturing and quality control due to its flexibility and high speed. However, most of the optical metrology methods are limited to external surfaces. This paper proposed a new approach to measure tiny internal 3D surfaces with a scanning fiber endoscope and axial-stereo vision algorithm. A dense, accurate point cloud of internally machined threads was generated to compare with its corresponding X-ray 3D data as ground truth, and the quantification was analyzed by Iterative Closest Points algorithm.
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This work presents an optical non-contact technique to evaluate the fatigue damage state of CFRP structures measuring the irregularity factor of the surface. This factor includes information about surface topology and can be measured easily on field, by techniques such as optical perfilometers. The surface irregularity factor has been correlated with stiffness degradation, which is a well-accepted parameter for the evaluation of the fatigue damage state of composite materials. Constant amplitude fatigue loads (CAL) and realistic variable amplitude loads (VAL), representative of real in- flight conditions, have been applied to "dog bone" shaped tensile specimens. It has been shown that the measurement of the surface irregularity parameters can be applied to evaluate the damage state of a structure, and that it is independent of the type of fatigue load that has caused the damage. As a result, this measurement technique is applicable for a wide range of inspections of composite material structures, from pressurized tanks with constant amplitude loads, to variable amplitude loaded aeronautical structures such as wings and empennages, up to automotive and other industrial applications.