检测系统中接触式测头的预行程误差预测模型

Pretravel error prediction model of touch trigger probes used in online inspection systems

针对在线检测系统中触发式测头存在预行程误差的问题,建立了测头预行程误差的实验模型。采用基于正则化RBF神经网络算法,在对网络进行训练的基础上,建立了相应的触发式测头预行程的误差模型。对触发式测头在空间不同法矢上的预行程误差进行预测,并将得到的预测结果与实验中得到的实际结果对比验证。实验结果表明,利用正则化RBF神经网络,能较好地解决对触发式测头不同法矢下的预行程误差的预测问题。

Abstract： Due to the problem of the pretravel error of touch trigger probes in online inspection systems, it is important for the systems to predict the pretravel error and verify it through an experimental model. A prediction model has been established through the algorithm of a regularized RBF neural network. By training the proposed network, the pretravel error can be predicted along the normal vector direction of the probe contact space. The prediction model is verified and tested by experiments. The results show that the RBF-based prediction model can properly predict the probe pretravel error which can be further used in online inspection to compensate the errors caused by various probes.