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Research On Controllable Pitch Propeller Hydraulic System Fault Modeling And Diagnosis

Posted on:2014-05-02Degree:MasterType:Thesis
Country:ChinaCandidate:S WangFull Text:PDF
GTID:2252330425966561Subject:Power Machinery and Engineering
Abstract/Summary:PDF Full Text Request
The hydraulic system is an important part of the controllable pitch propeller.Its failuremodes also account for a large part of the failures of the CPP system. Therefore.researchingon CPP hydraulic system’s failure modes and their formation mechanism and fault diagnosishas important practical significance. In this paper, on the basis of research summarizes theswap pitch propeller hydraulic system failure, to carry out the fault modeling and diagnostictechniques researches, work are as follows:1Theory, composition and application of CPP systems are introduced, And more detailedexplanation are to do on the operation principle of the hydraulic system. On this basis, useAMESim software to create a controllable pitch propeller hydraulic system model and verifythe correctness of the model.2Analyze CPP hydraulic system typical failure modes,such as relief valve main spoolorifice clogged、filter clogging、hydraulic pump abrasion,etc. failure mechanism for eachfailure mode is analised. Its AMESim fault modeling based on the component level faultmodel is embedded into the normal model, run the model and get failed state system operatingparameters, find out the failure characteristics of each failure indicators, and they are servedas fault sample data for controllable pitch propeller hydraulic system fault diagnosis。3FMEA method is used to analyze each failure above and a FMEA table is formed;Thefault characteristic indicators for each fault model simulation fault data, each fault diagnosisusing RBF neural network. We can quickly get fault information such as formation of thereasons, the impact and the use of compensatory measures out of the FMEA table.so effectivemeasures can be taken to remove failure.The method has practical value in use.
Keywords/Search Tags:controllable-pitch propeller, fault diagnosis, neural network, AMESim
PDF Full Text Request
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