基于形状分布式模型检索的农机装备快速设计方法

为促进农机装备设计重用,提出一种基于形状分布式模型检索的农机装备快速设计方法。首先,对三维模型进行归一化处理,并依次计算模型表面各三角网格面积,根据网格面积将每个模型的三角网格分为Max、Mid、Min 3类,采用Sobol准随机序列对分类后网格交叉组合取点,以采样点数3为基本采样单位对三维模型进行组合式特征点采样;然后,对提取的距离D2、面积D3、曲率C1、角度A3形状特征进行融合,分别计算4种特征值变异系数,以变异系数所占比例作为各形状特征权重,将加权后的不同特征变量值拼接成具有多特征的形状分布直方图,采用χ^2距离度量直方图间的相似性;最后,以VS2010与Matlab 2016b为开发环境,以Open Cascade为几何造型平台,使用自行构建的农机装备关键零部件模型库进行实验。结果表明,在农机三维模型库中,特征查准率由大到小依次为距离D2、曲率C1、角度A3、面积D3特征,本文提出的自适应加权融合特征(AWSD)算法在查全率0~0.5区间内显著优于D2检索算法,在0.5~1.0区间内检索效果与D2特征近似;AWSD算法检索效率符合基本要求,综合检索精度较D2形状分布算法提高了8.5%;拖拉机轮毂与收获机摘穗板检索实例表明,AWSD算法在检索主观满意度方面优于距离D2与曲率C1算法。

Rapid Design Method for Agricultural Machinery Based on Shape-distribution Model Retrieval

A new rapid design method for agricultural machinery was proposed to promote agricultural design reuse technology.The method was implemented based on shape distribution model retrieval.Firstly,the CAD models in agricultural database were normalized.According to mesh area,all the triangular meshes that belong to each model were divided into Max,Mid and Min groups.The Sobol quasi-random sequence was used to sample feature point from each group.Then three points were defined as the basic sample unit,which was used to fuse the D2,D3,C1 and A3 features together.The variation coefficient of each feature was calculated and the proportion was regarded as sub-feature weight of fusion feature.Thereafter,the multi-feature histogram of shape distribution was formed by connecting different weighted features.Theχ^2 distance was selected to measure the similarity between feature histograms.Finally,the effectiveness of the proposed method was proved with self-built agricultural model database using VS2010,Matlab 2016b and Open Cascade.The results showed that the retrieval precision of distance D2 feature was higher than that of curvature C1,angle A3 and area D3 features in agricultural model database.The proposed method of adaptive weighted shape distribution(AWSD)performed better than D2 when retrieval recall was ranged from 0 to 0.5,and as effective as D2 in the range of 0.5~1.0.Compared with D2 retrieval method,the comprehensive retrieval precision of AWSD method was increased by 8.5%.The retrieval cases of tractor wheel hub and harvester picking board demonstrated AWSD outperformance in the aspect of objective retrieval satisfaction.The new model retrieval method that could fuse multi-shape distribution features injected fresh energy to agricultural machinery rapid design.