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A switch machine is a core equipment of a signal system with the largest maintenance volume, strongest maintenance difficulty, and a wide range of equipment failures. With the increase in intelligent operation and maintenance research in the urban rail transit industry, research on intelligent operation and maintenance of switch machines has attracted the interest of industry scholars. It is the foundation for achieving intelligent maintenance of urban rail signals and intelligent operation and maintenance production organization modes. This article summarizes the limitations of traditional microcomputer monitoring systems and proposes an intelligent system based on the maintenance difficulties and pain points of switch machines in the industry. The system includes critical state perception, intelligent fault diagnosis, critical state warning, and health assessment, and proposes specific implementation methods. The system was successfully applied to Nanning Metro Lines 4 and 5, and significant benefits were obtained.
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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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