Abstract

Vibration analysis using vibration sensors is an effective method of monitoring mechanical faults. However, most current vibration sensors have a narrow working frequency range and a low-frequency vibration response. Therefore, broadening the frequency band to detect high-frequency vibration signals is imperative. This paper proposes a self-powered vibration sensor based on a broadband hybrid generator (VS-BHG) that incorporates a piecewise nonlinear and up-frequency coupling strategy through collisions between the suspension and fixed part, thereby effectively expanding the operational frequency range. By implementing this strategic approach, the VS-BHG can effectively capture the vibration energy across a broad frequency spectrum ranging from 5 to 38Hz and exhibit a robust linear response to acceleration within the frequency range of 20 to 1600Hz. A machine running state monitoring system based on the VS-BHG is established, enabling the recognition of 16 different running states and fault types in industrial fans with an accuracy rate of 98.38% using a deep-learning model. This paper presents an efficient and viable method for monitoring broadband mechanical fault.

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