Cracks and weld detection approach in solar receiver tubes employing EMATS

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