Full
Outline
To enhance the diagnostic accuracy of circuit breaker faults, an improved particle swarm optimization (IPSO) algorithm is used to optimize the relevant parameters of support vector machine (SVM). Then, a novel IPSO-SVM circuit breaker fault diagnosis model is established, in which the IPSO algorithm enhances the traditional particle swarm optimization (PSO) algorithm by incorporating chaotic mapping, dynamically adjusting the inertia coefficient and updating the optimal particle strategy. Therefore, the convergence speed and accuracy of the algorithm are improved. Furthermore, the IPSO-SVM fault diagnosis model is constructed based on several typical high-voltage circuit breaker fault types and the actual operation data of one specific circuit breaker. Finally, a comparison with other circuit breaker fault diagnosis models using the same training dataset is performed. Experimental results show that the IPSO-SVM model outperformed other models in terms of diagnostic accuracy and reduced the need for manual intervention, achieving effective fault identification of fault types and ensuring the reliable operation of the circuit breaker’s opening and closing coils.
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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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