Title : 
Crackle-Image of Swing Bolster Detection Algorithm Based on Visual Perception
         
        
            Author : 
Peng Lu ; Yongqiang Li ; Zhizhong Wang ; Yuhe Tang ; Eryang Chen ; Kun Jiao
         
        
            Author_Institution : 
Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
         
        
        
        
        
        
            Abstract : 
A novel method based on the visual perception mechanism was proposed for solving the problem of fault-image detection of the running train. The detection of swing bolster crack could be achieved in high efficiency with small samples. Firstly, the receptive field of simple cells in the primary visual cortex was obtained from the image sequence by using the ICA model. Secondly, the neuron response of normal and fault image was calculated, then the neuron responding stronger to the stimulus could be found out, and its corresponding content for fault detecting could be output as well. Experimental results demonstrated that this novel method had a high fault-detecting rate.
         
        
            Keywords : 
fault diagnosis; image sequences; independent component analysis; railway industry; ICA model; crackle image; fault image detection; image sequence; running train; swing bolster detection algorithm; visual perception; Algorithm design and analysis; Fault detection; Information processing; Neurons; Transforms; Visual perception; Visualization;
         
        
        
        
            Conference_Titel : 
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
         
        
            Conference_Location : 
Wuhan
         
        
        
            Print_ISBN : 
978-1-4244-7939-9
         
        
            Electronic_ISBN : 
2156-7379
         
        
        
            DOI : 
10.1109/ICIECS.2010.5678147