Over the last years, standard network protocols and technologies have become very popular basis for distributed measurement system design. This paper describes a set of distributed measurement experiments designed with the use of selected network technologies. The performed test results give us an opportunity to compare these technologies and consider how particular technology affects the distributed experiment performance. We also discuss some important factors that influence performance. Finally, we give some advice for developers that we hope will help them to choose the best design methodology.

An extension of the formal PSIQ-model of measurement procedure is proposed in order to have possibility to describe algorithms of measurement result correction in the ratio scale. An example of application of the model proposed to synthesis of a speedy correction method is given.

The paper presents a systematic design of fault-tolerant measurement systems for linear time-invariant processes. The discussed methods utilize analytic redundancy of the underlying process. Two multivariable linear model types (PCA for static and ARX for dynamic modeling) are considered. Both model types can be directly identified from the measured process data. Analysis of the primary and structured residuals enables very sensitive detection, isolation, and identification of single and multiple sensor and actuator faults. The fault diagnosis is conducted via analysis of the identified faults and can be followed by appropriate fault accommodation actions. A faulty sensor variable can be reconstructed using faultfree process variables and appropriate models. Faults which degrade sensor performance in a recoverable way (c.f. bias and gain errors) can be compensated using model-based sensor recalibration. Best data source in groups of doubled sensors can be selected through application of the voting scheme (where the third sensor is the soft sensor), thus enabling optimal sensor reconfiguration.

Classical Taxonomy is the reservoir of methods and techniques used in the life sciences to bring scientific order to the grouping of living things. Although the orders or problems of Taxonomy were not clearly described until the late 19th century the methods used can be traced back to the time of Plato and Aristotle. This paper commences by introducing the main ideas associated with classical taxonomy. A brief overview of the classification of the sciences is given. Subsequently, classification principles are used to show that Instrumentation and Measurement Technology is a sub-science of what may be called Machine Science. Taxonomy is then adapted and developed for general application in machine systems but more specifically in measuring systems. It is clearly shown that machines, and hence measuring systems should be grouped on the basis of ”what they do”, or function, ”why they do”, or purpose, ”when they do”, or signal form, ”way they do”, or energy domain, ”where they do”, or location, ”how they do”, or structure and ”while they do”, or sensors.

In this paper the concept of virtual system, using graphical environment, designed for approving parameters of microprocessor measurement instruments was presented. The exemplary structure of virtual examining station used for research of metrological features of multifunction instrument for measurement of ship power engineering system parameters was discussed. The selected research results were shown. The automated algorithm of instrument metrological accuracy assessment was presented. The example illustrating the way of formulating of newly-designed measurement instruments research program was proposed.