Transducer design and neural signature analysis for diagnosis of energized transmission lines

A new sensor technology based on electromagnetic acoustic transducers (EMAT) for nondestructive testing is developed and used for real-time fault recognition of energized overhead transmission lines. The fault detection is achieved by analysis of the reflected signatures from broken strands on the transmission line. Reflected waves received by the EMAT are analyzed using an artificial neural network (ANN) technique for failure detection and signature identification. From the field tests done at two towers of live transmission lines, this EMAT system shows prospective potential for fault detection in electric transmission lines.