一种人工智能算法在矿用电源评价中的应用研究

Research on the Application of an Artificial Intelligence Algorithm in Mining Power Supply Evaluation

煤矿井下爆炸性气体环境下的电气设备,在应用前必须要经过防爆认证。目前常用的认证方法是爆炸性火花实验,但是爆炸性火花实验周期长、成本高。若本质安全电路设计人员在设计阶段就能对电路是否本质安全进行基本的判定,那么将大大提高设计效率,并且节省成本。文章建立了基于ANFIS的本质安全电路非爆炸性评价模型,对已建立的基于ANFIS的本质安全电路非爆炸性评价模型进行了实际电路验证,证明了基于ANFIS的本质安全电路非爆炸性评价模型的可行性。

Electrical equipments in an explosive atmosphere environment underground the coal mine must be passed through the explosion-proof certification before the application.At present,the common authentication method is explosive spark experiment,but the explosive spark experimental cycle is long and high cost.At the design stage,if the intrinsically safe circuit designer is able to determine basically whether the circuit is intrinsically safe,it will greatly improve the design efficiency,and save the cost.This paper establishes the non-explosive evaluation model based on ANFIS for intrinsically safe circuits,actually verifies the circuit for the established non-explosive evaluation model based on ANFIS for intrinsically safe circuits,and proves the feasibility of the non-explosive evaluation model based on ANFIS intrinsically safe circuits.