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Sensor Array Optimization using Variable Selection and a Scanning Light Pulse Technique
Linköping University, Department of Physics, Chemistry and Biology, Applied Physics . Linköping University, The Institute of Technology.
Linköping University, Department of Physics, Chemistry and Biology, Applied Physics . Linköping University, The Institute of Technology.
Linköping University, Department of Physics, Chemistry and Biology. Linköping University, The Institute of Technology.
2009 (English)In: Sensors and actuators. B, Chemical, ISSN 0925-4005, Vol. 142, no 2, 435-445 p.Article in journal (Refereed) Published
Abstract [en]

In the design of a chemical sensor. the constructor has several degrees of freedom setting parameters that influence the final characteristics of the component. For applications where several sensors are required, the number of possible parameter configurations increases dramatically. The work of configuring a sensor array is therefore tedious and many test sensors may need to be processed before a final configuration is found. The Scanning Light Pulse Technique (SLPT) is a technique for investigating insulator-semiconductor interfaces and can be used to scan surfaces with non-uniform properties, Thereby a virtual pool of test components can be evaluated simultaneously eliminating the need for processing individual test sensors. We report here on a method combining SLPT with algorithmic sensor selection techniques. This is a powerful combination providing the user with a candidate array configuration containing combinations of sensors optimal for the current application and data analysis algorithms. The need to process many individual test sensors is eliminated and the only sensor components that must be produced are those included in the final array. The selection techniques evaluated here are based on forward selection and Asymmetric Class Projection (ACP), Canonical Correlation Analysis (CCA), Linear Discriminant Analysis (LDA), and Mutual Information (MI). The Suggested method is successfully evaluated using an experiment in which the purpose was to find means to detect small amounts of hydrogen in a background dominated by an interfering gas, in this case ammonia. In this particular study, the selection techniques based on ACP and CCA showed the most promising result.

Place, publisher, year, edition, pages
2009. Vol. 142, no 2, 435-445 p.
Keyword [en]
SLPT, chemical sensor, MIS, sensor selection, Assymetric Class Projection, CCA, LDA, mutual information, forward selection
National Category
Chemical Engineering
URN: urn:nbn:se:liu:diva-14870DOI: 10.1016/j.snb.2009.04.029OAI: diva2:25409
Available from: 2008-09-29 Created: 2008-09-29 Last updated: 2010-04-20
In thesis
1. Multivariate Exploration and Processing of Sensor Data-applications with multidimensional sensor systems
Open this publication in new window or tab >>Multivariate Exploration and Processing of Sensor Data-applications with multidimensional sensor systems
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A sensor is a device that transforms a physical, chemical, or biological stimulus into a readable signal. The integral part that sensors make in modern technology is considerable and many are those trying to take the development of sensor technology further. Sensor systems are becoming more and more complex and may contain a wide range of different sensors, where each may deliver a multitude of signals.Although the data generated by modern sensor systems contain lots of information, the information may not be clearly visible. Appropriate handling of data becomes crucial to reveal what is sought, but unfortunately, that process is not always straightforward and there are many aspects to consider. Therefore, analysis of multidimensional sensor data has become a science.The topic of this thesis is signal processing of multidimensional sensordata. Surveys are given on methods to explore data and to use the data to quantify or classify samples. It is also discussed how to avoid the rise of artifacts and how to compensate for sensor deficiencies. Special interest is put on methods being practically applicable to chemical gas sensors. The merits and limitations of chemical sensors are discussed and it is argued that multivariate data analysis plays an important role using such sensors.

The contribution made to the public by this thesis is primarily on techniques dealing with difficulties related to the operation of sensors in applications. In the second paper, a method is suggested that aims at suppressing the negative effects caused by unwanted sensor-to-sensor differences. If such differences are not suppressed sufficiently, systems where sensors occasionally must be replaced may degrade and lose performance. The strong-point of the suggested method is its relative ease of use considering large-scale production of sensor components and when integrating sensors into mass-market products. The third paper presents a method that facilitates and speeds up the process of assembling an array of sensors that is optimal for a particular application. The method combines multivariate data analysis with the `Scanning Light Pulse Technique'. In the first and fourth papers, the problem of source separation is studied. In two separate applications, one using gas sensors for combustion control and one using acoustic sensors for ground surveillance, it has been identified that the current sensors outputs mixtures of both interesting- and interfering signals. By different means, the two papers applies and evaluates methods to extract the relevant information under such circumstances.

Abstract [sv]

En sensor är en komponent som överför en fysikalisk, kemisk, eller biologisk storhet eller kvalitet till en utläsbar signal. Sensorer utgör idag en viktig del i flertalet högteknologiska produkter och sensorforskning är ett aktivt område.

Komplexiteten på sensorbaserade system ökar och det blir möjligt att registrera allt er olika typer av mätsignaler. Mätsignalerna är inte alltid direkt tydbara, varvid signalbehandling blir ett väsentligt verktyg för att vaska fram den viktiga information som sökes. Signalbehandling av sensorsignaler är dessvärre inte en okomplicerad procedur och det finns många aspekter att beakta. Av denna anledning har signalbehandling och analys av sensorsignaler utvecklats till ett eget forskningsområde.

Denna avhandling avhandlar metoder för att analysera komplexa multidimensionella sensorsignaler. En introduktion ges till metoder för att, utifrån mätningar, klassificera och kvantifiera egenskaper hos mätobjekt. En överblick ges av de effekter som kan uppstå på grund av imperfektioner hos sensorerna och en diskussion föres kring metoder för att undvika eller lindra de problem som dessa imperfektioner kan ge uppkomst till. Speciell vikt lägges vid sådana metoder som medför en direkt applicerbarhet och nytta för system av kemiska sensorer.

I avhandlingen ingår fyra artiklar, som vart och en belyser hur de metoder som beskrivits kan användas i praktiska situationer.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2008. 66 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1162
Chemical sensor, Pattern recognition, sensor selcection, Combustion monitoring, Vector Classification
National Category
Chemical Engineering
urn:nbn:se:liu:diva-14879 (URN)978-91-7393-841-9 (ISBN)
Public defence
2008-09-12, Planck, Fysikhuset, Campus Valla, Linköpings universitet, Linköping, 10:00 (Swedish)
Available from: 2008-09-29 Created: 2008-09-29 Last updated: 2009-05-12Bibliographically approved

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Petersson, HenrikKlingvall, RogerHolmberg, Martin
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