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Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

机译:基于LabVIEW的故障诊断和数据融合的pH传感器阵列测量数据的可靠性。

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Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.
机译:LabVIEW程序中实现的故障诊断(FD)和数据融合(DF)技术用于二氧化钌pH传感器阵列。故障诊断和数据融合技术的目的是提高测量数据的可靠性。数据融合是一种非常有用的统计方法,用于许多领域的传感器阵列。故障诊断用于避免传感器故障并测量电化学测量系统中的错误,因此,在本研究中,我们将使用故障诊断来预先清除所有故障传感器,然后在传感器阵列中进行数据融合。本研究采用平均,自适应和方差数据融合方法。使用溅射系统将二氧化钌(RuO 2 )感应膜制成pH电极,并将其沉积在硅基板上,然后制作八个RuO 2 pH电极以形成pH电极这项研究的传感器阵列。

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