Broadband acoustic signal sensing using an adaptive metamaterial

Early-stage issue diagnosis requires non-contact weak signal detection in extreme environments characterized by elevated temperatures and pressures. However, current acoustic sensors have a conflict between sensitivity and bandwidth for weak signal detection. We designed a sensitive, broadband, real-time sensor based on self-tuning and acoustic rainbow trapping. The acoustic pressure at a given frequency was enhanced by optimizing the metamaterial, imparting broadband improvement to the sensor. An adaptive metamaterial acoustic sensor (AMAS) was manufactured to validate the acoustic pressure enhancement phenomena and acoustic sensing performance. The AMAS had high sensitivity (signal-to-noise ratio [SNR] = 35 dB) and a broad bandwidth (up to 10 kHz), facilitating the precise detection of weak acoustic signals. The SNR increased by approximately 15.0 dB, indicating an improvement in the target signal quality. The system’s utility was validated via non-contact, early-stage aeroengine fault diagnosis under harsh conditions, demonstrating potential in mechanical health monitoring and environmental acoustic detection.