Ultrasonic Power and Data Transfer through Multiple Curved Layers Applied to Pipe Instrumentation

Ultrasonic power and data transfer through multilayered curved walls was investigated using numerical and experimental analysis. The acoustic channel used in this paper was formed by two concentric pipes filled with water, aiming for applications that involve powering and monitoring sensors installed behind the pipe walls. The analysis was carried out in the frequency and time domains using numerical and experimental models. Power and data were effectively simultaneously transferred through the channel. A remote temperature and pressure sensor was powered and interrogated throughout all the layers, and the power insertion loss was 10.72 dB with a data transmission rate of 1200 bps using an amplitude modulated scheme with Manchester coding. The efficiency of the channel was evaluated through an experimental analysis of the bit error rate (BER) with different values of signal-to-noise ratio (SNR), showing a decrease in the number of errors compared with detection without Manchester coding.

Ultrasonic Power and Data Transfer Through Multiple Curved Layers Applied to Pipe Instrumentation

Ultrasonic power and data transfer through multilayered curved walls is investigated using numerical and experimental analysis. The acoustic channel used in this paper is formed by two concentric pipes filled with water, aiming for applications that involve powering and monitoring sensors installed behind the pipe walls. The analysis was carried out in the frequency and time domains using numerical and experimental models. Power and data were effectively simultaneously transferred through the channel. A remote temperature and pressure sensor was powered and interrogated throughout all the layers, and the power insertion loss of 10.72dB with a data transmission rate of 1200 bps using an amplitude modulated scheme with Manchester coding. The efficiency of the channel was evaluated through an experimental analysis of bit error rate (BER) with different values of SNR, showing a decreasing in number of errors comparing with the detection without Manchester coding.