Study On Evaluation Of Excavator Of XCMG Form Design Based On BP Neural Network

With the development of science and technology, relying on technologyies to occupy the construction machinery industry market has become increasingly difficult.At this point, the method of implementing brand strategy--creating a perfert brand image among the social public is an effective means to improve competitiveness. It is a hot issue of concern by researchers both domestic and abroad that how to effectively evaluate the consistency of the modelling of products and the corporate brand gene.In this paper, XCMG group, excavator products as an example to explore the XCMG`s excavator modelling brand evaluation. Artificial neural network has an ability to mimic the functionality of the human brain, building the complex network of wide connections with a large number of simple processing units, which has a great advantages for the modelling of knowledge map processing and approximates any function infinite. Artificial neural network has the ability to the fuzzy reasoning.Intelligence features of artificial neural network can be used to a bigger limit to reduce the influence of the expert subjective evaluation in this paper, which provides a scientific method for accurately and objectively evaluating the consistency of XCMG`s excavator products modelling and brand gene.First of all, from the perspective of brand gene, this article probes into the brand gene in construction machinery industry, and then constructs the design evaluation indexes of XCMG brand construction machinery through the analysis of the XCMG brand gene. In the following, the types of neural network is described and summarizes the basic structure, learning algorithm and calculation steps of BP neural network.Then analyzes the engineering machinery brand modelling characteristics as the characteristics as a starting point and discusses the engineering machinery brand model and the method of feature extraction.Then, focus on the extraction process of the excavator characteristics and analyzes the national famous brand construction machinery excavator model characteristics first. Summarizing 16 elements of the XCMG brand excavator design characteristics according to the engineering machinery XCMG brand model and the method of feature extraction studied excavator shape feature extraction method.Preliminary constructing the output layer neurons and output neurons of the excavator design evaluation system of XCMG based on the BP network model. According to the calculation the method of BP network to determine the structure of the neural networkmodel and according to the model structure, input layer and output layer datas to construct the XCMG`s excavator model evaluation model based on BP network.Through training, testing proves the value that the network model to evaluate the practical.The last, the insufficient on modelling of the original XE75 G type excavator is found through the questionnaire survey and the evaluation of the neural network model. To redesign the excavator based on the brand modeling of XCMG`s excavator characteristics analysis and general design method of product and illustrates the main design points of the design. Eventually, the excavator product modeling that after redesign is evaluated by the system that the XCMG`s excavator model evaluation model based on BP neural network which has built. The results of analysis and optimization design show it can be more accurate to evaluate related to the branded of XCMG`s excavator modelling based on the evaluation system, and can provide a target guidance to modify design schemes according to the evaluation results.Hoping this research can provide some theory references and guidance consistent evaluation and design optimization method between the products modelling and brand genes in engineering machinery and other industry.