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Initial studies on the possibility to use chemical sensors to monitor and control boilers
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.
2005 (English)In: Sensors and actuators. B, Chemical, ISSN 0925-4005, Vol. 111-112, 487-493 p.Article in journal (Refereed) Published
Abstract [en]

Small-scale boilers are quite often installed in facilities like schools, households and at local heat distributors. Because of economical considerations such boilers often lack appropriate control-systems, which results in inefficient and pollutant combustions with high levels of carbon monoxides, hydrocarbons, and in ashes with unburned charcoal. Monitoring of oxygen, carbon monoxide, and hydrocarbons, which is essential to be able to control a boiler, requires expensive instruments like flame-ionization detectors, IR- and mass-spectrometers.

We demonstrate the possibility to use a low-cost chemical sensor array to monitor a small-scaled boiler. By using metal oxide sensors, metal insulator silicon carbide field effect transistors, and by applying multivariate data modeling, promising results have been obtained. The data modeling was made using a joint approach based on blind source separations and multiple linear regressions. This approach showed similar result compared to results from the well-known PLSR algorithm.

Place, publisher, year, edition, pages
2005. Vol. 111-112, 487-493 p.
Keyword [en]
Chemical sensor array, Pattern recognition, Combustion monitoring, Blind source separation, Canonical correlation analysis
National Category
Chemical Engineering
URN: urn:nbn:se:liu:diva-14866DOI: 10.1016/j.snb.2005.03.045OAI: diva2:25399
Available from: 2008-09-29 Created: 2008-09-29 Last updated: 2013-11-12
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
2. Chemical Sensors and Multivariate Data Analysis
Open this publication in new window or tab >>Chemical Sensors and Multivariate Data Analysis
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Today, sensors can be found in many different applications, such as in home appliances, vehicles, medical equipments, mobile technology etc. Nearly all products with a reasonable technological height have a sensor integrated.

Chemical Sensors are devices able to sense the chemical environment and are today an active area of research. A great potential has been predicted for these kinds of sensors, meeting future demands of e.g. environmental monitoring, health-care issues and safety. The potential lies in the fact that chemical sensors are unspecific in general, responding to several different species in the ambient. By using several different sensors simultaneously a great portion of the chemical environment can be sensed at one instant.

The data generated when making measurements with multiple chemical sensors contain a lot of information, but t he information is not clearly visible and it is not easy to interpret the data as it is.

Along with the development of complex sensor systems comes the need for advanced data analysis procedures, able to interpret and visualize the information provided by the sensors. In this work, various aspects of data analysis procedures are discussed. Techniques for exploring large dataset are treated and a general overview is given on algorithms able to learn characteristic patterns within data. Difficult ies caused by unwanted sensor phen6mena such as drift and noise are identified and it is discussed how to counteract for these.

The thesis touches upon applications where chemical sensors are useful, and which requirements these applications put on the sensors and the data analysis procedures.

Work will be presented in which attempts have been made to learn the composition of flue gases produced by boilers used for heat and power production. It will be shown that it is possible roughly estimate the concentration of carbon monoxides, oxygen, and hydrocarbons by using a set of relatively in-expensive chemical sensors and by applying data analysis procedures. Work will also be presented in which it is discussed how to counteract for unintentional differences between sensor elements, a problem causing trouble prior to commercialization and mass-market production of chemical sensor systems.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2006. 48 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1238
National Category
Natural Sciences
urn:nbn:se:liu:diva-33743 (URN)19785 (Local ID)91-85497-37-1 (ISBN)19785 (Archive number)19785 (OAI)
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-11-12

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