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Cracks and welds detection approach in solar receiver tubes employing electromagnetic acoustic transducers

机译：使用电磁声换能器的太阳能接收管中的裂纹和焊缝检测方法

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There is a significant rising in development of new concentrated solar plants due to global energy demands. Concentrated solar plant requires to improve the operational and maintainability in this industry. This article presents a new approach to identify defects in the solar receiver tubes and welds employing a simple electromagnetic acoustic transducer. The absorber tubes in normal working conditions must withstand high temperatures, which can cause the tubes to deteriorate in areas such as welding, or it can cause hot spots due to defects or corrosion. A proper predictive maintenance program for the absorber pipes is required to detect defects in the tubes at an early stage, reducing corrective maintenance costs and increasing the reliability, availability, and safety of the concentrated solar plant. This article presents a novel approach based on signal processing and pattern recognition for predictive maintenance employing electromagnetic acoustic transducers. Hilbert transform is used to obtain the envelope of the signal that is smoothed by wavelet transform. It reduces the probability of detecting false-positive alarms. The algorithm uses the distance of the sensors from the edges to perform a self-identification of signal events. The events are located using two possible ways of ultrasound propagation, forward and reverse, and the time of flight of each echo. The algorithm correlates the theoretical events with events found experimentally. These echoes could come from different paths due to the electromagnetic acoustic transducer that generates forward and reverse shear waves. The main novelty in this approach is that the detection and location of the defect is determined considering two echoes that come from the same defect, but they arrive at the sensor flowing by different paths. The results are obtained with a double validation by matching the echoes that meet certain conditions. It increases the accuracy of the inspection and reduces false alarms. The approach has been tested and validated in an experimental platform that simulates the concentrated solar plants.
机译：由于全球能源需求，新型集中式太阳能发电厂的发展显着增加。集中式太阳能发电厂需要改善该行业的运营和可维护性。本文提出了一种使用简单的电磁声换能器来识别太阳能接收管和焊缝中缺陷的新方法。在正常工作条件下的吸收器管必须承受高温，这可能会导致吸收器管在焊接等区域变质，或者由于缺陷或腐蚀而引起热点。需要对吸收器管道进行适当的预测性维护程序，以在早期阶段检测出管道中的缺陷，从而减少纠正性维护成本并提高集中式太阳能发电厂的可靠性，可用性和安全性。本文提出了一种基于信号处理和模式识别的新颖方法，用于采用电磁声换能器的预测性维护。希尔伯特变换用于获得通过小波变换平滑后的信号的包络。它降低了检测到误报警报的可能性。该算法使用传感器到边缘的距离来执行信号事件的自识别。使用两种可能的超声传播方式（向前和向后）以及每个回波的传播时间来确定事件的位置。该算法将理论事件与实验发现的事件相关联。由于产生正向和反向剪切波的电磁声换能器，这些回声可能来自不同的路径。这种方法的主要新颖之处在于，考虑到来自同一缺陷的两个回波来确定缺陷的检测和位置，但是它们会到达流经不同路径的传感器。通过匹配满足某些条件的回波，可以通过双重验证获得结果。它提高了检查的准确性，并减少了误报警。该方法已在模拟集中式太阳能发电厂的实验平台中进行了测试和验证。

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