Title : 
Fault diagnosis for hydraulic hoisting system based on the probabilistic SDG model
         
        
            Author : 
Lei, Su ; Hua, Song ; Hong, Wang
         
        
            Author_Institution : 
Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
         
        
        
        
        
        
            Abstract : 
Focusing on the hoisting mechanism of crane hydraulic, this paper gives the fault mechanism analysis and fault probability calculation method based on the probabilistic SDG model. The fault mechanism is described by the probabilistic SDG model while the fault propagation is presented by the conditional probability. And so the connection tree algorithm and figure elimination algorithm can be used in Bayesian inference to calculate the fault probability. In case of the given fault, the fault probabilities of the part components can be given.
         
        
            Keywords : 
Bayes methods; cranes; fault diagnosis; hoists; hydraulic systems; inference mechanisms; trees (mathematics); Bayesian inference; conditional probability; connection tree algorithm; crane hydraulic; fault diagnosis; fault mechanism analysis; fault probability calculation method; figure elimination algorithm; hoisting mechanism; hydraulic hoisting system; part component; probabilistic SDG model; Analytical models; Cranes; Data models; Probabilistic logic; Valves; Winches; Bayesian inference; Fault mechanism analysis; Hydraulic; Probabilistic SDG model;
         
        
        
        
            Conference_Titel : 
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4673-0312-5
         
        
        
            DOI : 
10.1109/INDIN.2012.6301196