Aiming at the non-stationary characteristics of early failure vibration signal of gear and the fact that it is seriously affected by environmental noise and the fault feature is weak so it is hard to be extracted, the ensemble local mean decomposition is used to decompose the fault vibration signal of gear to obtain the product function of finite single component, so as to highlight the local characteristics of the signal. However, because of the noise interference, it is difficult to extract the fault feature frequency information from frequency spectrum of each component, and based on that, in the paper, the fault diagnosis method of ensemble local mean decomposition and minimum entropy deconvolution is proposed. Through the analysis of gear fault simulation experiment and project case, fault characteristic information of gear can be extracted accurately and effectively, which provides a new method for practical engineering application.
| 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 |