Drift Compensation, Standards, and Calibration Methods

In Webster’s Seventh New Collegiate Dictionary, drift is defined as “a gradual change in any quantitative characteristic that is supposed to remain constant”. Thus, a drifting chemical sensor does not give exactly the same response even if it is exposed to exactly the same environment for a long time. Drift is a common problem for all chemical sensors, and thus needs to be considered as soon asmeasurements aremade for a long period of time. First in this chapter, possible reasons for drift will be discussed. A distinction is made between drift in the sensors, and drift in the measurement system. After this, typical features of drift as seen in the measurements will be shown. These features include gradual increase or decrease, and jumps in the responses. At the end, many different methods for reducing the effects of drift will be described. These drift reduction methods try to compensate for the changes in sensor performance using mathematical models and thus maintaining the gas identification capability of the electronic nose. Many different methods have been applied for different situations. It is impossible to compare all the methods since each one of them makes some assumptions of how themeasurements aremade and/or how the drift is manifested. Not all examples discussed are for measurements with electronic noses, but the concepts may easily be transferred also to such applications. The purpose of describing all the methods is to show some possible ways of reasoning when dealing with a data-set from drifting sensors.