Fault Analysis Of Mine Locomotive Driverless System Based On AFFPN Model

The research on mine locomotive unmanned driving system,as a mining country,can improve the mining efficiency,reduce the occurrence of mine accidents,protect the safety of miners,and have great economic and social benefits.However,the research on mine locomotive unmanned driving system is in a functional realization,and there are few studies on its system stability and fault diagnosis methods.In this thesis,a self-adaptive fuzzy fault Petri net model is created.The improved particle swarm algorithm is introduced into the model to optimize the parameters.The model is applied to the mine locomotive driverless system to realize the adaptive reasoning and diagnosis of the fault.The main work of this thesis includes:1.Research on the improvement of Petri net technology,using basic Petri net as a theoretical basis,using fuzzified semantic expression to define fuzzy regular expression,proposing an adaptive fuzzy fault Petri net model,and using the matrix in the fault propagation concurrency process.The formal expression is used to derive the confidence calculation algorithm for the reasoning process of the fault propagation process and the diagnostic reasoning algorithm for fault diagnosis.2.Adjust the adaptive parameters of the Petri net model,use the appropriate algorithm to optimize the parameters,analyze the parameter initial value setting rules when the algorithm is combined with the model,change the actual application of the fault model,and propose the optimized training adjustment parameters.Steps,faults and knowledge bases are updated and added to realize the self-learning ability of diagnostic methods.3.The failure analysis of the mine locomotive unmanned driving system,the use of system stratified analysis method to logically classify the failure of the system,based on the analysis of its structural principles,combined it with the Petri net model,put forward all parts of the system Fuzzy rule expressions and create a fuzzy fault Petri net model.4.Apply the fault reasoning and diagnostic analysis methods to the mine locomotive unmanned driving system,analyze and judge it,propose common fault propagation paths in each system,and diagnose the most likely cause of a fault.