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A sensor array optimization method for electronic noses with sub-arrays
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DOI：10.1016/j.snb.2009.08.015.png)
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Sensor array configuration needs to be optimized in developing an application-specific instrument of electronic noses. Currently, sensor array optimization is commonly done by feature selection techniques. These methods could solve how to optimize a sensor array. However, they could not figure out what are the unique functions that each sensor plays in the optimized sensor array. The method proposed in this paper could solve this problem by sensor clustering and dividing the whole sample classification mission into several small recognition tasks. A measurement with a six Taguchi Gas Sensors (TGS sensor hereinafter) sensors array to classify 11 gas sorts was used in the data validation. The sensor array was optimized to three sensors with the proposed method. Each sensor in the optimized array had unique functions to solve different recognition tasks. TGS2600 had the unique functions to discriminate butanone and acetaldehyde. TGS2602 had the unique functions to discriminate benzene and cyclohexane, methanol and ethanol. TGS813 had the unique functions to discriminate cyclohexane and pentane. The combination of TGS2600 and TGS2602 had the unique functions to discriminate acetone and butanone, acetone and acetaldehyde. The proposed method might be a new generation of sensor array optimization methods. (C) 2009 Elsevier B. V. All rights reserved.
Keyword:
Sensor array optimization
Sub-array
Electronic nose
Selectivity similarity
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7.7
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3.4W
被引数:
12.6W
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Enhancing electronic nose performance by sensor selection using a new integer-based genetic algorithm approach使用新的基于整数的遗传算法方法通过传感器选择来增强电子鼻性能
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