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A DTC decoupling method for complex coupling faults of vehicles is proposed in this paper. Firstly, by analyzing the complex association of DTCs through the principle of vehicle fault selfdiagnosis and the propagation process of fault signals, the strong association relationship between DTCs is mined combined with the association rule technology and the multidimensional association rules of DTC are defined. Secondly, the FPGrowth algorithm for DTC multidimensional association rule mining is improved by the characteristics of the DTCs dataset. Finally, the DTC association knowledge graph is constructed by multidimensional association rules to realize complex DTCs decoupling by combining graph theory. The results show that this method can effectively reduce the number and complexity of DTCs, and improve the efficiency of troubleshooting faults based on DTCs.
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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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