Intelligent planetary gear fault diagnosis system based on MEMS acoustic emission sensor

基于MEMS声发射传感器的智能行星齿轮故障诊断系统

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Abstract

Early equipment fault diagnosis can identify potential risks, significantly reduce maintenance costs, and minimize property damage. However, vibration, strain, and force sensors operating at low frequencies with narrow bandwidths are insufficiently sensitive to fault information, making early fault prediction challenging. Here, we introduce a high-performance, cost-effective, and tiny-sized micro-electromechanical system (MEMS) acoustic emission sensor. This sensor utilizes a 10 × 11 hexagonal array of piezoelectric micromachined ultrasonic transducers with a chip size of 4 mm × 4 mm × 0.4 mm. The sensor is encapsulated using an epoxy/Al(2)O(3) composite for acoustic impedance matching, and its overall size is Φ 16 mm × H 5.5 mm, with a weight of approximately 3 g. This acoustic emission sensor achieves a peak sensitivity of 88.4 dB (ref. V/(m/s)) at 335 kHz, and its sensitivity remains above 60 dB across the frequency range from 15 kHz to 620 kHz. In addition, combined with the residual neural networks, an intelligent fault diagnosis of the planetary gear is realized. This MEMS acoustic emission sensor can provide a promising approach for in-situ fault monitoring of highly integrated and miniaturized industrial equipment.

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