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Fatigue Life Assessment Of General Bridge Crane Based On Equivalent Load Spectrum

Posted on:2019-05-04Degree:MasterType:Thesis
Country:ChinaCandidate:W W ZhangFull Text:PDF
GTID:2382330566976337Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Cranes,called giant arm,are widely used in ports & docks,construction sites,factory workshops,logistics warehouses and so on,providing labor and technical support for the development of many industries,and gradually becoming backbone.Due to the influence of working environment,load performance,welding technology and carrying capacity of materials,safety accidents such as rollover,break,wire rope falling and weights dropping are easily occurred on the construction sites,causing casualties and equipment losses.The metal structure of cranes are mostly formed by welding structure,and most of the cracks originate from the welding joint,which can easily cause fatigue failure.Welding structure largely determines the performance of whole machine,reliability and safety life.Mastering the fatigue failure mechanism of welding structure and accurately evaluating fatigue life can effectively reduce the occurrence of accidents,and have great engineering significance.Aiming at the fatigue failure of crane welding structure,using QD100/40t-28.5m general bridge crane as the research object.The methods based on theoretical analysis and computer simulation are proposed,which are used to conduct fatigue analysis and life assessment of main girder structure of crane.The main contents are as follows:1)Aiming at the varied working environment,complex experimental condition and strong randomness of loading,which lead to large scale spectrum of crane being difficult to obtained.Combined with the related parameters which affect load spectrum.Introducing the basic principle of machine learning algorithm,based on the method of BP neural network and support vector machine to construct the equivalent load spectrum models of cranes.2)Aiming at the defects of BP neural network and support vector machine,which are under learning,over learning and local optimum.Based on the relevance vector machine theory,the relevance vector machine optimized by particle swarm optimization prediction model is established with constructing new kernel function and selection of kernel parameters.Meanwhile,two indexes,error and fitting degree,are introduced to evaluate the performance of model,and to validate the effectiveness and practicability of the proposed model.3)Specified load under typical working conditions can be calculated by the theory of metal structure designed for mechanical equipment and the principle of load combination.The method of allowable stress is proposed to calculate static strength and fatigue strength of the metal structure of crane,and then the fatigue position of the main beam structure is given.4)Aiming at the fatigue failure of crane welding structure,started with the characteristics of welded structure,fatigue failure mechanism and fatigue assessment standard,hot stress method is put into the assessment of fatigue life of welding structure.According to the characteristics of random load,the measured load spectrum based on the mathematical statistics technology and the equivalent load spectrum based on the relevance vector machine are transformed into the fatigue stress spectrum based on the rain flow counting method.Based on the hot stress S-N curve,using cumulative damage method to predict the fatigue life of crane welding structure.
Keywords/Search Tags:Welding structure, Load spectrum, Relevance vector machine optimized by particle swarm optimization, Hot spot stress method, Fatigue life
PDF Full Text Request
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