| The steel cord conveyor belt has been widely used in coal mines, ports, power, metallurgy, building materials and other industries because it has a lot of benefits, for example, tensile strength, impact resistance, long life, small elongation, into a good groove, better flex resistance and so on. In the mining steel cord conveyor belt conveyor system, a complete steel cord conveyor belt is often made up of several belt by lap and vulcanizing, so conveyor’s joint is the weak link of the whole transport system, which will directly affect the safe operation and service life of the delivery system. In order to detect accidents, ensure the safe operation of the conveyor belt, the nondestructive testing of joint position will be very important.In this paper, through fieldwork existing steel cord conveyor belt monitoring system, proposed an improved texture encoding algorithm through the analysis uploading images and get the number of rope in each row images, then according to the joint qualification to find a set of optimum parameters of joint detection and accurately find out the conveyor belt joint images, use a way that looking for a specific to sort the detected image, make it corresponds to the actual joints, and use a series of detected corners marks the bonding wire of fitting part by Harris corner detection techniques. Through a large number of experiments and practical application proved that this method has high precision, real-time and other characteristics. Especially for repair less or good condition steel cord conveyor belt, the joint detection accuracy up to 100%. |
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