灰色马尔科夫的工件尺寸非接触测量补偿预测

The Prediction and Compensation of Workpiece Size Non-Contact Measurement by Gray Markov

摘要:

为了解决非接触式的工件尺寸测量误差预测问题,提出了基于灰色马尔科夫理论体系的预测模型,对三维重构法测量后的测量误差进行预测。通过测试样本获得测量误差的变化关系,从而得到经过灰色和马尔科夫预测后的预测样本,最后对预测样本和检验样本作比较分析。实验结果表明,随着测量次数的增多,测量误差有稍微增大的趋势,而且波动情况与检验样本相似,相似度约为3.3%。通过灰色马尔科夫的非接触工件尺寸测量误差的补偿预测,能有效提高三维重构法的测量精度,为后续的偏移补偿控制器提供准确的输入参量。

Abstract:

To solve the prediction problem of non-contact workpiece size measurement, this paper established a prediction model based on gray Markov theoretical system to predict the measurement error after 3D reconstruction measurement. The change relationships of the error measurement are expressed from the testing sample, so the predicting samples can be obtained through gray and Markov, and a comparative analysis will be done between prediction samples and testing samples. The experimental results indicated that with the increasing of measurement number, the trend of the measurement error is slightly increased and the volatility situation is similar to the testing samples with the similarity 3.3%. Gray Markov positioning error prediction and compensation can effectively improve the accuracy of non-contact workpiece size measurement, and to provide accurate input parameters for subsequent offset compensation controller.