Gas sensor array concentration detection method based on fuzzy division and model integration

A gas sensor, fuzzy division technology, applied in the direction of material resistance, etc., can solve the problems of not considering the difference in importance, the prediction accuracy needs to be improved, and the degree of drift change is not considered.

Inactive Publication Date: 2016-09-14
JILIN UNIV
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Problems solved by technology

However, there are still problems in the current method. First, the time period division of the data set adopts the division method of uniform distribution of data volume, which does not consider the degree of drift change; second, the current classifier integration method is only used for qualitat

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  • Gas sensor array concentration detection method based on fuzzy division and model integration
  • Gas sensor array concentration detection method based on fuzzy division and model integration
  • Gas sensor array concentration detection method based on fuzzy division and model integration

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Embodiment 1

[0064] The data set used in this embodiment is a data set measured and published by A Vergara, S Vembu, T Ayhan, M Ryan, M Homer, R Huerta et al. For literature, see "Chemical gas sensor drift compensation using classifier ensembles." Sensors and Actuators B: Chemical 166(2012):320-329. The sensor array is composed of TGS2600, TGS2602, TGS2610 and TGS26204 from Figaro Company, each with 4 gas sensors and a total of 16 gas sensors. Test gases include ammonia, acetaldehyde, acetone, ethylene, ethanol, and toluene. Each sensor extracts 8 signal features for each sample, including two steady-state features and 6 transient features. Therefore, a 128-dimensional feature vector can be obtained from the sensor array for each test. The test lasted for three years (36 months), with a total of 13,910 measurements. That is, the data set is a matrix of 13910×128.

[0065] Such as figure 1 As shown, the drift compensation method of metal oxide gas sensor array concentration detection ...

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Abstract

A gas sensor array concentration detection method based on fuzzy division and model integration belongs to the field of a gas sensor array signal processing technology. According to the method, time division of baseline drift data is carried out by a fuzzy clustering method, and a source dataset is divided into multiple sub-datasets with different drift degrees; then, regression models of different training datasets are established to obtain several sub-regression models; an optimal weight set of each sub-regression model is obtained within the training dataset, and center of clustering and optimal weight undergo fitting to obtain an optimal weight fitting function; and during the test phase, fitting weight is calculated on the basis of the optimal weight fitting function and clustering center time, and the sub-regression models integrate forecasted results of data to be tested so as to obtain the final gas concentration value. By the method, a pattern recognition model can be changed adaptively, changes of drifting can be traced, the influence of drifting on concentration detection performance is effectively reduced, and long-term accuracy of concentration measurement is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of gas sensor array signal processing, and in particular relates to a metal oxide gas sensor array concentration detection method based on long-term drift compensation based on fuzzy division and fuzzy weighted multi-output support vector regression model integration. Background technique [0002] The use of gas sensor devices to replace traditional analytical instruments is a new method for mixed gas detection. Metal oxide semiconductor (Metal Oxide Semiconductor, MOS) gas sensors and other types of gas sensors (such as electrochemical sensors, surface acoustic wave sensors, conductive polymer sensors, etc.) etc.) have the advantages of small size, low cost, fast response and recovery, and long service life. With the advancement of MEMS processing technology, arrays can be realized on Si substrates. Microstructure gas sensors using this process have low power consumption, good compatibility with semiconduct...

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Application Information

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IPC IPC(8): G01N27/12
Inventor 王庆凤卢革宇孙鹏
Owner JILIN UNIV
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