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Sensors 2013, 13(12), 17281-17291; doi:10.3390/s131217281

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

1
Department of Information Management, Transworld University, 1221 Zhennan Rd., Yunlin 64063, Taiwan
2
Graduate School of Electronic and Optoelectronic Engineering, National Yunlin University of Science and Technology, 123 University Rd., Yunlin 64002, Taiwan
*
Author to whom correspondence should be addressed.
Received: 10 October 2013 / Revised: 19 November 2013 / Accepted: 11 December 2013 / Published: 13 December 2013
(This article belongs to the Section Chemical Sensors)
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Abstract

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. View Full-Text
Keywords: fault diagnosis; data fusion; ruthenium dioxide; sensor array; LabVIEW fault diagnosis; data fusion; ruthenium dioxide; sensor array; LabVIEW
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Liao, Y.-H.; Chou, J.-C.; Lin, C.-Y. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW. Sensors 2013, 13, 17281-17291.

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