测量装置与学习传感器

J. Pieniążek, Piotr Cieciński
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引用次数: 5

摘要

本文的主要课题是利用模糊系统的学习方法对传感器进行标定。采用模糊系统对非线性和温度敏感性进行同步补偿。压力传感器的补偿是为了应用于空气数据计算机。实验结果表明,模糊系统不需要计算高次多项式,优于多项式回归。补偿后,测量装置可以定期验证,必要时可以进行校正。给出了两点校正的一般性质。在被测传感器的情况下,由于单向非线性,假定两点重标定是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measurement device with learned sensor
The main subject of the paper is calibration of the sensor by learning method of the fuzzy system. Fuzzy system is used for simultaneous compensation of the nonlinearity and temperature sensitivity. The compensation of pressure sensors is intended for application in the Air Data Computer. The results obtained experimentally show that fuzzy system is superior to the polynomial regressions because it is not necessary to compute high degree polynomials. After the compensation it is supposed measurement device can be periodically verified and if necessary corrected. General property of two-point correction is presented. In the case of tested sensor two-point re-calibration is assumed as being effective because of one-side nonlinearity.
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