The invention discloses a method for automatically detecting the failure of an insulator. The method comprises the following steps: establishing positive and 
negative sample banks of insulator images, training an insulator classifier by a 
convolutional neural network algorithm, and splitting a collected image by utilizing the image salient area detection 
algorithm to split an equipment area and a background area in the image so as to obtain an insulator searching candidate area; training the insulator classifier by utilizing the 
convolutional neural network algorithm to locate the insulator, and controlling image collection equipment according to the location information of the insulator string in a current image to complete the image collection of the insulator string; and carrying out insulator surface 
stain detection, insulator string 
cracking detection and insulator string breakage or mixed 
foreign substance detection by utilizing an 
image identification technology so as to determine abnormal insulators. According to the method, insulator stains, 
cracking and breakage can be detected by adopting different 
image processing algorithms, insulator states can be comprehensively detected, and potential safety hazards of the insulators in 
transformer substations / converter stations can be reduced.