Research And Design Of Intelligent Grab Control System

This paper aims at the situation of overload that frequently happened in gantrycranes in Tianjin port, present the improved scheme to avoid the overload situation.By means of repeated observation at the spot, the cause of the overload was found out.The result reveals that this was caused by the way of operation that the operatorsjudged the timing to close the grab just by their own experience. When the overloadsituation occurred, the operator should lay down the materials and repeat theoperation again. These repeated operations not only waste time and energy, but alsoreduce the efficiency of loading and unloading.To prevent this situation from happening, through the scheme comparison，thisdesign adopt Advantech USB-4711A data acquisition card to read the circuit andtorque signal data of lifting motor and open-close motor during the whole operationprocess, it also designed a signal preprocessing circuit. Moreover, with the uppercomputer program and database technology, it achieves the goal that the real-timedisplay and storage of the signal data. Through the analysis of whole data andobservation of the fetching process, we can divided the whole process into three steps:first of all, open the grab and set it on the materials and close it; then, lift the grabwhen it is half closed so that the materials will leak out; finally, close the grabcompletely. Select maximum current、minimum current、average current of closemotor in first step and peak current of lifting motor in second step as the inputsamples, set the actual lifting weight as the output samples, put them into establishedBP neural network model, through training, we will find out the mapping relationbetween signal data and final lifting weight, and the error between predictive weightand actual weight is satisfactory. On this basis, it is necessary to design an assistantcontrol system which set ATMEGA128as its core control chip. Through the dataaquisition of whole grab process, this system can select input data by program and putthem into the neural network to predict the final lifting weight before the operatorclose the grab. This system can interfere the original control system in case that itforecasts that the gantry crane will be overload. Finally, it can avoid overload totallyby programme rather than operators. The achievement of this modified plan must be based on a large amount of data collection, the required work should include dataacquisition system, data mining model and improved control system.Theoretically, the system designed in this paper, to a great extent, can avoidoverload situation from happening, increase the efficiency and reduce the mechanicalloss. Meanwhile, it can save energy and reduce emission.