A high-power RF transmission line status monitoring method based on sound recognition

To ensure the safe operation of a superconducting accelerator system, real-time monitoring of the RF power source, transmission lines, and superconducting cavities is essential. Currently, the main method for monitoring the status of transmission lines in superconducting accelerator systems is through monitoring the standing wave ratio. However, it is difficult to effectively monitor faults during high reflection or full reflection operations, which can pose significant safety risks. To address this issue, this paper proposes an online monitoring and positioning technique for RF transmission line faults based on acoustic fingerprinting. By studying the spectral characteristics and transmission mechanism of high-power RF transmission line faults, the sound recognition and classification experiment achieved a recognition accuracy of 98.0%, demonstrating the feasibility of this method in identifying faults in RF transmission lines.