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.

This article treats the matter of calibration transfer, i.e. how to mathematicallysuppress sensor-to-sensor differences. We propose an approach in which the strategyis to find a model that compactly describes the behavior of a sensor type. Theparameters of the model serve as ‘data sheets’ and can be used to differentiate characteristicsbetween individual sensor devices. We illustrate that by keeping recordof these parameters it does not only becomes possible to characterize individualsensors, but also to calibrate their responses.

As will be discussed, the main virtue of the suggested approach comes by itscompact and device specific description of the sensor response pattern. This opensup for the construction of flexible calibration transfer schemes. The idea is to let asensor manufacturer construct and distribute ‘data sheets’ describing the characteristicsof each sensor component. Customers can then to use these to mathematicallycounteract for sensor-to-sensor differences. The counteraction can be made at sensorlevel, prior to the signals enter any host system. This is important if a customerwishes to avoid extensive adaptations being made to a product as soon as a slightlydifferent sensor component must be used.

The approach is tested on real experimental data made with Metal-Insulator-Silicon-Carbide-Transistors. Data driven modeling techniques were used to approximatethe sensor responses. The results of this paper positively demonstrate thatthe suggested approach can be used to counteract for sensor-to-sensor differences.

SiC based field effect gas sensors have been evaluated for future possible use in combustion control schemes for domestic heating systems. Emphasis has been on the possibility to monitor the state of combustion and follow the development of the combustion process from an emissions point of view and to determine its cause. The sensor signals have been compared to true emissions data – CO and total hydrocarbon concentration – as obtained by an IR spectrometer and a flame ionization detector (FID) as well as flue gas concentration of oxygen as obtained by a paramagnetic cell. The sensor characteristics have been evaluated using multivariate statistics and the results suggest that, by using the signals from one or more SiC-based field effect sensors and a thermocouple, it seems possible to provide a rough picture of the state of combustion applicable to a control scheme in order to reduce emissions and increase the power to fuel economy.

Metal insulator silicon carbide field-effect transistor sensors, metal-oxide sensors, and a linear Lambda sensor in an electronic nose was used to measure on-line in hot flue gases from a boiler. Flue gas from a 100-MW pellets-fuelled boiler has been used to feed the experimental setup. Several reference instruments, which measure the flue gases in parallel to the sensor array, are connected to the electronic nose. Data was collected during six weeks and then evaluated. Using principal component analysis as the data evaluation method, different operating modes for the boiler have been identified in the data set. The different modes could be described in terms of high or low O 2 and CO concentration. Furthermore, we have shown that it seems possible to use a sensor array to determine the operating mode of the boiler and, by partial least-squares models, measure the CO concentration when the boiler operates in its optimum mode.

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.

The possible utility of MISiCFET gas sensors in the application of combustion control in small-scale boilers has been tested and compared to commercially available resistive-type MOS sensors. The results suggest that by using the signals from one or more MISiCFET sensors, together with the measured temperature of the furnace, it seems possible to provide a rough picture of the state of combustion applicable to a control scheme in order to reduce emissions and increase the power to fuel economy.

In this paper, we have examined the behavior of a chaotic circuit where one of the components has been replaced by a chemical sensor. The response of the sensor is manifested as a change in the attractor of the circuit. Furthermore, with a proper operating point, a small response of the sensor causes a change in the attractor of the circuit within a time much shorter than the normally defined response time of the sensor. This technique unites sensors and data processing as one combined unit in a unique fashion. © 2002 IEEE.

Reduction of the number of variables in data from a so-called electronic tongue contributes to simpler model calculations and less storage requirements. In this study, we have developed a model for this purpose. This model describes the response from the electrodes in the electronic tongue with two exponential functions plus a constant term, i(t) = k + kf e-ta + kc e-tß, where t is the time. From the model, five parameters which describe the signal are extracted. These parameters can be used as inputs instead of the original signal to any multivariate algorithm. The results show that the variables obtained are at least as good as the original data to separate between different classes, even though the number of parameters has been reduced between 80 and 199 times. © 2002 Elsevier Science B.V. All rights reserved.

A measurement in a multi-sensor system is characterized by a large array of numbers (a vector or a matrix), sometimes several thousands. In order to increase the interpretability of the measurements, decrease the calculation demand on the computer, and/or to reduce noise, an alternative, more compact, representation of the measurement can be made which describes the important features of the measurement well but with a much smaller vector. The purpose of this paper is to show that for a particular wet-chemical sensor system (pulsed voltammetry, also called an electronic tongue) the data compression can be made using a wavelet transform together with different wavelet selection algorithms for different purposes. The resulting compressed data can also be used for easy interpretation of the measurements and to give hints for improvements or simplifications of the measurement procedure. Two different criteria for selection of wavelet coefficients have been used, variance and discriminance, in two different cases. The variance criterion was used when variations of any kind in the raw data was studied during monitoring of water in drinking water production plant. In this case, the number of variables was reduced with a factor of 18, without loosing relevant information. In the other case, the focus was to separate different microorganisms, therefore, the discriminance selection criterion was successfully used. The number of variables was reduced by a factor of 144, this smaller data set captured the important information for separating the microorganisms, which led to better classification of the test set. © 2002 Published by Elsevier Science B.V.

The interaction of chemical species with molecular films of porphyrins causes variations of the work function of the film itself, as it has been recently demonstrated by using the Kelvin probe technique. This characteristic makes porphyrins films suitable to be used as sensitive layers in ChemFET sensors. In this paper, we present a preliminary report about the fabrication and testing of such gas sensitive devices. The technological solutions towards an optimised device are also illustrated and discussed. © 2001 Elsevier Science B.V.