Coiled sonic black hole based contactless sensor for physical signal processing and its application in mechanical fault diagnosis

Closely related to equipment condition, acoustic based sensing method becomes the one of the most effective tools for state monitoring, but application is still restricted by challenges arise from attenuation in long-distance propagation and environmental noise interference. In response to the shortcomings of traditional acoustic signal sensing methods, a coiled sonic black hole (CSBH) is proposed in this paper. The acoustic rainbow trapping phenomenon in CSBH is observed and theoretically derived, and the correctness of theoretical analysis is proved by numerical simulation and experiment. Differ from common idea in sound absorption, CSBH is designed as a sensor for acoustic signal amplification and filtering in a completely physical way. Based on the characteristics of CSBH, feature extraction and enhancement of weak signals as well as mechanical fault diagnosis are studied comparatively, and experimental results show that the signal quality and intensity from CSBH are improved significantly. Acting as a physical amplifier and filter, the features in acoustic signals are well reserved by CSBH from strong background noise pollution. The methods proposed in this paper provide a brand-new perspective in acoustic signal enhancement, and it has the promising application in remote contactless condition sensing.