Feature Transformation Method for Wheel Hub Shape Based on Target Detection and Geometric Analysis

Extracting and transforming shape features has been an important research domain in wheel hub design. The study of design based on semantics, brand planning, structural optimization requires regression analysis by using the corresponding variables to guide through correlation model. practical role feature transformation is determined its effectiveness, accuracy, convenience. This process, however, generally handled manually previous studies, limiting universality comprehensiveness outcomes. With development artificial intelligence, automation this process become possible, ushering era big data for extraction transformation. Hence, proposes a method target detection geometric analysis. implements following steps: (1) point YOLO model; (2) grouping morphological parameters position parameters; (3) grooming relations; (4) parameter construction features. Thus, automatic, bidirectional, mechanism can be developed. proposed model, related transformed quickly, generative conducted data.