Detecting welding defects in industrial equipment (welded joints and built-up structures) is a key aspect in evaluating the probability of failure in different situations. Acoustic Emission (AE) is an effective non-destructive detecting technique, and can be a promising application for welding defect detection. This work presents a systematic experimental investigation on using AE technique for detecting and classifying different weld defects in carbon steel joint material. Four certified carbon steel samples were used in this study. A defect free control sample was used as the reference and three samples with induced defects, namely slag, porosity and crack. A pencil lead break (PLB) test was used to generate simulated AE sources on one side of the joint whereas the AE sensor was mounted on the other side to capture AE signals. A total of four experimental arrangements were used to investigate the effect of propagating distance (sensor to source distance) on the ability of AE to detect and identify defects in welds. For each of these arrangements, AE features such as peak amplitude, rise time, decay time, duration, and count numbers along with statistical features such as AE energy, root mean square (RMS) were extracted and analysed. Also, frequency analysis using FFT and wavelet transform were investigated for each weld test specimen for all arrangements. The results show that AE energy, peak amplitude and RMS 2 value can be used to automatically detect and identify the presence of a defect in carbon steel welds. It is concluded that AE has a considerable potential in use in welding inspection to assess the overall structural health and identify defects that can significantly reduce the strength and reliability of welded material and consequently reduce the risk of component's failure.
Wave energy has a great potential to solve the unrelenting energy deficiency in Egypt. The present work recommends Wells turbine as a suitable choice for the Egyptian coasts due to its simple and efficient operation under low input air flow. In addition, the possibility of extracting the wave energy from the Egyptian coasts was investigated using the oscillating water system based on real data from the site. To achieve this purpose, two-dimensional numerical models for Wells turbine airfoils, functioning under sinusoidal wave flow conditions, were built. Moreover, the running and starting characteristics under sinusoidal-flow conditions were investigated using a mathematical code. The results were discussed using the first law analysis, in addition to the second law analysis by using the entropy generation minimization method. It was found that the NACA0015 airfoil always gives a global entropy generation rate that is less than other airfoils by approximately -14%, -10.3% and -14.7% for the sinusoidal wave with time periods equal to 4, 6 and 8 seconds respectively. Moreover, the effects of blade profile, time period and solidity on the output power (kW) value were discussed
– Welding defects can create a major threat in industrial equipments and pressure vessels can during operation. Detecting and identifying of existing welding defects has a great role in the assessment of the probability of failure in different situations. Acoustic emission (AE) is only a nondestructive technique that can be used as in-service testing and used on large structures. This paper examines the changes in the properties of AE source generated from Pencil Lead Break (PLB). AE is recorded across different seam welds with pre-identified welding defects. Series of experiments are carried out on three certified standard Carbon Steel plates. Each plate has different pre-identified defect such as lack of fusion, porosity and slag. Different AE parameters such Energy, Amplitude and number of counts have been used to identify quantitatively the type of defects. The results are showing that AE technique is capable to identifying the different defects types which can be upgraded for higher productivity and accuracy for welding inspection.
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