缝纫机缝纫性能测量评价系统的设计

针对缝纫机缝纫性能评价难的问题，设计了一种基于BP神经网络的缝纫机缝纫性能客观测量评价系统.在缝纫机机械力学性能与缝纫性能之间构建了一个3层神经网络模型，该神经网络模型由4个子网络模型构成分别负责四个缝纫性能指标的评价,同时研究了面料可缝性、缝纫性能、面料缝纫质量三者之间的量化关系。提出了样本采集方案，设计了一套基于VB与Matlab的应用软件和基于USB数据采集卡的测量系统，在此基础上进行了实验研究。实验结果表明BP神经网络在给定的样本下学习过程收敛效果较好，对被测缝纫机缝纫性能的评价与实际结果一致。

Design of testing-and-evaluating system for sewing performance of sewing machines

A testing-and-evaluating system based on BP-neural network is designed to deal with the difficulty of evaluating sewing performance of sewing machine. A neural network with three levels composed of four sub-networks which are used to evaluate the four sewing performance indexes respectively is modeled between mechanical properties and sewing performance, and the Quantization relationship among sewing performance, sewability performance and sewing quality is researched. The sample collecting method for BP-learn is presented and a set of application software base on VB and Matlab and testing system based on USB-DAQ card are designed, then experiments are performed on the designed system. Testing results show that BP-neural network achieves satisfactory convergence performance, and the evaluating results correspond with the actual fact.