The position of software as a component in sensor systems is reviewed. The precision load cell is taken as a typical sensor, and the various methods of software compensation which can be applied to it are discussed. The problems of ‘tailored’ compensation of individual sensors by software techniques are outlined. The advantages of optimization techniques are stated and the particular example of frequency response compensation is discussed.

Software techniques for sensor compensation

The impact of thick-film technology on the development of new, inexpensive, robust and miniaturised sensors is discussed in the light of new designs and results by the authors and others. The three aspects covered are the realisation of electronic systems within sensors, the provision of support structures for sensor materials and the development of new primary sensors in the form of strain gauges.

Sensor applications of thick-film technology

Neural networks models and their training algorithms on a central computer with reference to a previously developed distributed sensor network are considered. The requirements for its intelligent node are formulated. Also the node's structure is offered which realises such intelligent functions, as sensor and other measuring channel components drift prediction using remote reprogramming.

Intelligent nodes for distributed sensor network

In many applications electronic sensors are used to improve performance and reliability of measurement systems. Such sensors should provide a correct transfer from the physical signal to be measured to the electrical output signal. One important step to achieve this, is to calibrate each sensor by applying different reference input signals and adjusting the sensor transfer accordingly. Besides expensive reference equipment the calibration process takes much time and attention per individual sensor, which means a considerable increase in sensor production costs. By including at the sensor or sensor interface chip a programmable calibration facility the calibration of such smart sensors can easily be automated and can be executed for a batch of sensors at a time, thus minimizing the calibration time and costs. This paper presents a calibration method and options for integration in the smart sensor concept, in hardware as well as in software. An advantage of the proposed method is that it does not need a large matrix of calibration data, which needs to be stored in a look-up table or converted into a correction formula, but instead it uses a step-by-step approach to correct the sensor transfer at each calibration measurement until the error is sufficiently small.

Integrated smart sensor calibration

Methods of improving the measurement accuracy by estimation and correction of the maximum error components, are analyzed. The functional structure of the measurement channel in an intelligent sensing instrumentation system is described along with the procedures of component error correction. An experimental setup, implementing such methods in a multi-processing neural network configuration, is presented.

Error compensation in an intelligent sensing instrumentation system

The defects of sensor performance are reviewed in the light of the availability of modern digital methods for dealing with them. Particular emphasis is placed on modern distributed, and potentially large, instrumentation systems. Suggestions are made as to how this will change future industrial practice.

http://iopscience.iop.org/article/10.1088/0022-3735/20/9/005/pdf

Digital compensation of sensors

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Digital compensation of sensors