To detect if the alloy steel socket sleeve is built in a correct location

an incorporated method for image clustering via the ant colony optimization algorithm and the character differentiation model based on the Support Vector Machine(SVM) was proposed to improve the detection speed and estimation reliability . Firstly

the observation stamps about all of the images were determined according to the differential analysis between each type of the gap images. Then

the first turn of ant colony algorithm for the clustering number unknown was conducted to ascertain the number of basic sorts

and the second turn of ant colony algorithm for the clustering number known was performed to conclude the exceptional sort for the gap images from the another source. Therefore

the every possible states could be covered with the developed differential program. Furthermore

an advanced distributary method based on SVM model was adopted to increase the estimation speed

etc

. The experiment results in production line indicate that the mis-estimated error ratio is less than 0.5% and the irretrievable error is near zero. The instrumentation equipped with above technique can meet the need of industry application well.