Non-Contact Bearing Fault Diagnostics: Experimental Investigation of Microphones Position and Distance

Monitoring the condition of rolling bearings is critical for industrial reliability, yet tradi-tional contact-based accelerometers can be impractical in confined or hazardous envi-ronments. This study investigates the use of microphones as a non-invasive diagnostic alternative, focusing on the impact of sensor distance and spatial placement on fault de-tection sensitivity across various rotational speeds and load conditions. Using an accel-erometer mounted directly on the bearing as a benchmark, acoustic data were acquired on a test bench under different speed and load conditions. The experimental setup evaluated three distinct microphones positions and five distances relative to the source to assess spatial influence. Analysis was conducted comparing scalar indicators, such as Root Mean Square (RMS), Kurtosis and Crest-Factor values, with advanced diagnostic tech-niques, specifically the High-Frequency Resonance Technique (HFRT) for envelope spec-trum extraction. Results indicate that while the signal-to-noise ratio (SNR) predictably decreases with distance, diagnostic performance is significantly compromised by acoustic shielding effects caused by bearing housing. Moreover, while simple statistical factors (RMS, Kurtosis, Crest Factor) show limited reliability across varying distances and noise floors, HFRT-based envelope analysis yields robust fault identification even at the max-imum sensor distance. The study concludes that optimal microphone placement is essen-tial for reliable remote monitoring. Particularly, these findings suggest that a preliminary spatial characterization of the acoustic field can significantly enhance the effectiveness of non-contact diagnostic systems in industrial applications.