基于贝叶斯估计的放入式电子测压器准静态校准数据处理方法

Quasi-Static Calibration Data Processing Method for the Internal Electronic Piezo Gauge Based on Bayesian Estimation

为解决贝叶斯估计法无法用于直接处理准静态校准数据的问题,提出了一种先对数据进行预处理,随后进行正态性分析获得正态性参数,最后依据正态性参数进行贝叶斯估计的多传感器动态测试数据融合的处理方法。经过计算分析,放入式电子测压器准静态校准数据具有较好的正态性,使用贝叶斯估计法处理充分考虑了测试数据的统计规律特性,减轻了多传感器测试系统中单传感器对测量整体结果的影响;经实验验证,其同时明显提高了数据相关性,能进一步提高测试可靠性。对于火炮膛压的精确测量有显著意义。

In order to solve the problem that Bayesian estimation method can not be used to process quasi-static calibration data directly,an improved method for multi-sensor dynamic test data fusion is proposed.In the method,a pre-processing of data is firstly carried out,followed by normality analysis to obtain normal parameters,and finally use Bayesian estimation method based on normal parameters.It has been verified by experiments that the quasi-static calibration data of the internal electronic pressure gauge has good normality.The Bayesian estimation method is used to process the test data fully considering the statistical regularity,which reduces the single sensor pair measurement in the multi-sensor test system and the impact of the overall results,and significantly improve the data correlation as well as the test reliability at the same time.It has indispensably significant for accurate measurement of gun pressure.