改进拉伊达准则在LabVIEW温度采集系统中的应用

Application of Pauta Criterion in Temperature acquisition system based on LabVIEW

摘要:

对温度进行采集是温控系统的前提之一，好的采集系统可以真实有效地反映温度的变化，可靠的采集数据可以为后续的系统性能分析提供有力的保障。在采集的数据当中，粗大误差总是存在的，有效的剔除这些粗大误差可以帮助实验者更好地分析采集系统的性能。对于温度采集系统来说，粗大误差也总是存在的，为了剔除在温度采集系统中出现的粗大误差，文章首先介绍了三种常见的粗大误差剔除方法，包括格拉布斯准则、迪克逊准则和拉伊达准则。比较了拉伊达准则和改进拉伊达准则的优劣，选取了改进拉伊达准则，将其应用于基于Labview设计的温度采集系统当中。整个系统不仅实现了对温度的自动化采集和处理，而且也实现了对非正态分布的数据进行粗大误差剔除，并且剔除的效果满足预期。

Abstract:

The collection of Temperature is one of the prerequisites for temperature control systems, a suitable acquisition system will reflect the real changes of the temperature, and reliable data can provide a strong guarantee for subsequent data analysis. Gross error is modal value in acquisition system, effective removal of these gross error can help the experimenter to better analyze the performance of the acquisition system.In this paper, we first introduces three common gross error elimination methods, including Grabs criteria、Dixon guidelines and Pauta Criterion. Comparing the merits of Pauta Criterion and improved Pauta Criterion, and apply the improved Pauta criterion to LabVIEW temperature acquisition system, and this system not only realized the automatic collection and compute, but also got rid of the coarse error of the non-normal distribution data successfully, and reached expected goal.