The Facult Diagnosis Decision-marking And Simulation Of Heavy Transporter’s Hydraulic Based On T-S Fauzzy Facult Tree Analysis And Bayesian Network

The fault diagnosis of hydraulic system is a necessary way to improves theeffectiveness of hydraulic equipments, which means the improvement of the reliability ofhydraulic equipments, the high-amplitude climbing production rate of the factory and theeconomic benefit harvesting comes from the market. It has great theoretical and realisticsignificance to researching the Hydraulic malfunction diagnosis of hydraulic system.This article has a mainline which is “theory analysis-analog simulation-field failurediagnosis decision-marking-thoubleshooting and repair”. Firstly, In view of the hydrauliccontrol system of heavy transporter, it emphatically analyses the typical fault mechanismof the hydraulic suspension system and hydraulic steering system, at the same time, itintroduces the method of T-S fuzzy fault tree analysis to calculate the fuzzy possibility andrelated importance degree of the system failure. Furthermore, it lays foundation forstudying on deeply the fault diagnosis of hydraulic system based on T-S fuzzy fault tree,according to T-S criticality importance as hydraulic system fault diagnosis.Secondly, it puts forward a kind of fault diagnosis decision method which fused T-Sfuzzy fault tree and uncertain multi-attribute decision model coming from bayesiannetwork. This kind of method admits the importance degree, the searching cost and thecomprehensive cost of maintenance of T-S fuzzy fault tree as attributes, establish bayesiannetwork analysis model, analysis reasoning and gets the final fault diagnosis searchingorder.Finally, it sets fault parameters using AMESim software to simulate faultphenomenon to verify the consistency of the simulation analysis and T-S fuzzy fault treealgorithms. By the way, collecting the field work failure of the heavy transporter,simulating fault phenomenon and diagnosing with fault diagnosis decision method, whichis prove that this kind of method can make up a right diagnostic to every faults quickly.