Method for STEP-NC manufacturing feature recognition based on STEP and improved neural network

Feature recognition is an important step to implement STEP-NC theory and a key to realize the open, intelligent and networked STEP-NC CNC system. A feature recognition method based on STEP and improved neural network for STEP-NC manufacturing features is presented in this paper. This method first extracts the geometric and topological information from the STEP AP203 file of a part, and builds the minimum subgraph of the part based on the judgment of the convexity of edges. Then, an improved BP neural network is proposed by combining the chaos algorithm, the genetic algorithm, and the BP neural network algorithm. Finally, by inputting the information data from the minimum subgraph of the part to the improved BP neural network, efficient and accurate feature recognition for STEP-NC manufacturing features in the part is achieved. The validity and feasibility of the proposed method are verified by two case studies. © 2019, Press of Chinese Journal of Aeronautics. All right reserved.