Application of the White Noise Generator to Evaluate the System for Modeling the Impact of Soil on the Working Body of the Bulldozer

Improvement of quality, decrease of terms and cost of construction are inseparably linked with problems of effective use of bulldozer equipment. The most important problem of control tractions modes of the bulldozer is the fullest use of traction opportunities of the machine at the expense of management of work tool. Automatic maintenance of the maximum traction power or resistance preset value on work tool is complicated by a large number of the random factors operating on the bulldozer. In this regard the system of automatic control has to possess possibility of self-adjustment. In this paper with applying of analytical simulation method and neural network technologies, been decomposed model bulldozers workflow as mechatronic system realized. Models of the sub-processes are included into the general structure of bulldozer’s workflow simulation model. They are intended to be used to study bulldozer’s separate units applying analytic dependences of between their workflow parameters and to simulate bulldozer’s workflow in general. Technique of identification and modeling of bulldozer’s workflow based on neural networking technologies is described.