Full
Outline
To address the problem that the planetary gears in the gearbox of mine hoists operate under long-term low-speed, heavy-load, and alternating-load conditions, and that single acoustic or vibration signals are easily affected by propagation path, measuring point position and background noise, leading to insufficient feature extraction of fault signals, a fault diagnosis method based on point-symmetric acoustic-vibration fusion and ARFM-Net is proposed. Firstly, an acoustic-vibration synchronous acquisition test system for the planetary gearbox was established, and the differences and complementarities of acoustic and vibration signals in expressing fault information were analyzed. Then, Variational Mode Decomposition (VMD) and Feature Mode Decomposition (FMD) were adopted to process the two types of signals according to their respective characteristics. The effective modal components containing major fault information were selected and mapped into a polar coordinate feature map by using the point-symmetric graph method to realize the image-level fusion of multi-scale acoustic-vibration information. Finally, an ARFM-Net diagnostic network composed of Adaptive RepLK and Frequency-aware Moga was constructed. An adaptive large-kernel convolution was used to enhance the extraction capability of local fault details and long-range texture correlations, and a frequency-aware multi-level gated feature aggregation was used to highlight fault-related information and suppress background redundant textures. The experimental results of five types of planetary gear fault states show that the average recognition accuracy of the proposed method reaches 98.72%, and it shows favorable diagnostic performance in both comparative and ablation tests. This method can effectively improve the fault-recognition accuracy of planetary gears in the gearbox of hoists under complex working conditions, and provide technical support for intelligent monitoring of operation status of hoist transmission systems in mines.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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