A calibration method for handling the temporal drift of solid state gas-sensors

Haugen, John‐Erik; Tomić, Oliver; Kvaal, Knut

doi:10.1016/s0003-2670(99)00784-9

Cited by 139 publications

(70 citation statements)

References 19 publications

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“…Sejauh ini, tidak ada sensor kimia yang dibuat tanpa adanya drift. Sensor drift harus diberikan perlakuan tertentu agar dapat mencapai data pengukuran yang dapat dipercaya [3][4]. Salah satu metode untuk mengatasi adanya sensor drift adalah dengan menggunakan manipulasi baseline dalam tahapan prapemrosesan.…”

Section: Pendahuluanunclassified

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

Agustika

Triyana

2017

JSD

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AbstrakSistem Sensor gas banyak digunakan untuk pendeteksian aroma. Permasalahan utama dalam sistem ini adalah adanya sensor drift yang membuat buruknya reprodusibilitas sensor. Reprodusibilitas sensor dapat ditingkatkan dengan menerapkan seleksi ciri pada respon luaran sensor dan manipulasi baseline. Penelitian ini difokuskan untuk menenentukan metode yang dapat mengurangi adanya sensor dift dengan tahapan manipulasi baseline dan memilih jenis manipulasi baseline yang optimal saat sistem sensor gas mendeteksi tiga jenis jamu yang berbeda. Data yang telah diseleksi ciri kemudian diterapkan tiga jenis manipulasi baseline yang berbeda (diferensial, relatif dan fraksional) dan dimasukkan ke sistem pengenalan pola Principal Component Analysis (PCA). Dari hasil analisis PCA manipulasi baseline yang meberikan hasil optimal adalah diferensial dengan nilai PC1 82,71%. Hal ini menunjukkan manipulasi baseline diferensial efektif dalam mereduksi terjadinya sensor drift.Kata kunci: electronic nose, sensor gas, manipulasi baseline, seleksi ciri AbstractGas sensor system is widely used for the detection of aroma. The main problem in this system is the sensor drift that makes poor reproducibility of the sensor. The reproducibility of the sensor can be improved by applying the feature selection of the sensor's output response and baseline manipulation. This research focused on determining methods that can reduce the dift sensor of gas sensor by using basaeline manipulation and selecting the optimal type of baseline manipulation when gas sensor system detects three different types of herbal drinks. The data that have been feature selected were then applied to three different types of baseline manipulation (differential, relative and fractional)

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Section: Pendahuluanunclassified

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

Agustika

Triyana

2017

JSD

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“…The first scheme finds the drift signal through comparison with a reference gas immediately. (5) Unfortunately, it is difficult to maintain uniform testing conditions for both reference gas and sample gas in practical applications. Thus, the evaluated drift elements calculated from the reference gas and sample gas may be different.…”

Section: Introductionmentioning

confidence: 99%

A Novel Retraining Method of Multiple Self-Organizing Maps for Gas Sensor Drift Compensation

2013

Sensors and Materials

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The drift effect of gas sensors severely affects the performance of an electronic nose, because the primarily built pattern recognition models degrade over time. A multiple self-organizing map (MSOM) network is an adaptive approach to compensate for gas sensor drift by self-retraining during the test phase. However, the conventional local retraining method of multiple self-organizing maps may lose drift information if the retraining is carried out with successive homogeneous samples for a long time. In this paper, we propose a novel global retraining method to keep each retraining vector (RV) fresh over time. Compared with the local retraining approach, the new method updates all the retraining vectors after one of them has been replaced. Experimental results demonstrate that the global retraining method retains the network recognition ability on drift effect, whereas the local retraining and adaptive resonance theory methods show high error rates. Finally, a discussion on the retraining rate is given to optimize the process speed of the MOSM network with the global retraining strategy.

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“…On the other hand, signal processing methods for drift counteraction are based on different approaches: univariate [13,14] or multivariate [15][16][17], linear [18,19] or non-linear [15][16][17], adaptive [15,16] or not, based in reference samples [14] or based in component removal [18,19]. Univariate corrections include basic baseline corrections [13], or more complex per-sensor correction by means of a calibration sample [14].…”

Section: Introductionmentioning

confidence: 99%

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Padilla

Perera

Montoliu

et al. 2010

Chemometrics and Intelligent Laboratory Systems

209

103

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Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

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A calibration method for handling the temporal drift of solid state gas-sensors

Cited by 139 publications

References 19 publications

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

A Novel Retraining Method of Multiple Self-Organizing Maps for Gas Sensor Drift Compensation

Drift compensation of gas sensor array data by Orthogonal Signal Correction

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