Measuring System

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Measuring System


a set of measuring devices that ensure simultaneous receipt by a human operator or computer of the necessary information on the properties and state of some object.

Objects of measurement frequently have very complex designs, and multifaceted processes and phenomena may take place in them; therefore, individual measuring devices that perceive just one parameter of a complex process are usually unable to ensure receipt of sufficient information about the object, especially when it is necessary to know several of its parameters simultaneously. Such knowledge is necessary, for example, to control an electric power plant, blast furnace, aircraft, or motor vehicle, where dozens, and sometimes hundreds, of variables characterizing the state of these objects must be analyzed simultaneously. To some extent the problem solved by a measuring system is the opposite of the problem of an individual measuring device: not to break up the parameters of the object of measurement so as to isolate them and respond to them separately, but to combine data on all the main parameters of the object and thereby provide a sufficiently complete description of it. Thus, the distinguishing characteristics of a measuring system are the simultaneous measurement of many parameters of the object (that is, multichannel measurement), transmission of measurement information to a single center, and representation of the data obtained (including their unification) in the form most convenient for subsequent processing by the receiver.

Building a measuring system involves solving purely “systems” questions: metrological standardization of measurement equipment (sensors, converters, indicators) regardless of the type of variables being measured; optimization of the distribution of errors among different means of measurement included in the measuring system; and the optimal arrangement of indicators in front of the operator. For example, indicators of the most important, determining parameters are made highly visible and placed in the center of the control panel or board, and less important indicators are placed in the operator’s field of peripheral vision. This arrangement is necessary because the human operator cannot perceive the readings of even two instruments at one time; he must read them sequentially, switching his attention alternately from one indicator to another.

The structural plan of any measuring system contains the same basic elements. The sensors sense various parameters of the object of measurement, and standardizing converters standardize the sensor signals and transmit them along communications channels to the one data-collection point. A programmed device receives the information from the sensors and passes it on to the receiver of the information. Practically all measuring systems are constructed on the basis of this plan, including present-day systems for transmitting information from satellites and automatic interplanetary stations.

The most overloaded element in the measuring system is the human being who receives the information. In practice he is unable to perceive the readings of numerous instruments simultaneously. To make his work easier mnemonic diagrams are used; these are schematic representations of the object of measurement with symbolic signaling devices in place of instruments. The signaling devices usually show not the absolute values of the quantities being measured but rather, for the most part, deviations from preassigned norms. In many control points illuminated signaling devices with standard color codes replace instruments. An example of a very simple measuring system is a two-coordinate automatic recorder that makes it possible to receive, for example, the volt-ampere characteristics of diodes and magnetization curves.

As the number of channels in a measuring system is increased, there will usually be substantial differences among particular channels in precision of measurement and speed, as well as in form of presentation. Thus, in the relatively simple measuring system for the driver of a motor vehicle, information on the distance traveled is given in numerical form with a measurement limit of 99,999.9 km and a discreteness of not more than 0.1 km, the speed is shown with an error of about 5 percent, the fuel indicator scale has just four gradations (¼, ½, ¾, and 1), and information on the functioning of the turn signals and headlights is given by just two gradations (“on” and “off”). In a similar manner, in large measuring systems (controlling an aircraft, a gas pipeline, or an electric power plant) part of the information is transmitted with a very high degree of precision, other information has lower precision, and some channels operate with just two or three gradations (“serviceable” and “unserviceable”; “defect of +,” “serviceable,” and “defect of –”).

In measuring systems it is practically always necessary not only to receive information on various parameters of the object of measurement, but also to subject them to certain preliminary processing, such as the comparison of parameter values obtained against values set as minimums (that is, settings), the determination of the value and sign of differences, and the computation of certain generalized (derivative) parameters.

As with other information systems, measuring systems are developing in the direction of automation. Automating measurement processes involves more complete internal processing of information, where instead of reports on the values of particular parameters for each channel the operator receives a certain generalized characteristic of the functioning of the monitored object, determined on the basis of the values of several parameters. Very simple examples of measuring systems with preliminary, elementary processing of several input parameters and output of one generalized value are the electrical wattmeter and the electrical energy counter. (The current and voltage delivered to the object are fed to their inputs and the readings correspond to the power or energy.)

Preliminary processing of the values of individual parameters is even more essential in complex measuring systems. For example, a measuring system serving a chemical production shop may determine not only the composition of the final product but also the productivity of the processes and their economy or overall efficiency. However, such generalized representation of information deprives the human operator of concrete data on precisely which particular parameter has deviated from the optimal value and caused, for example, a decrease in the efficiency of the process. Therefore, in complex installations it is advisable to use such measuring systems together with technical diagnosis systems. The technical diagnosis measuring system gives a “diagnosis of the disease”; that is, it automatically analyzes all signals received to discover the place and cause of technical trouble in the system. The output of the technical diagnosis measuring system is an indication of the number, code, or name of the assembly or unit whose parameters have deviated from the norm (this can be most conveniently given in the form of signals on the mnemonic diagram of the monitored system) and, if possible, an indication of the type of trouble.


Il’in, V.A. Telekontrol’ i teleupravlenie. Moscow, 1969.
Shenbrot, I. M., and M. Ia. Ginzburg. Raschet tochnosti sistem tsentralizovannogo kontrolia. Moscow, 1970.
Krebs, H. Rechner in industriellen Prozessen. Berlin, 1969.
Woschni, E.G. Messgrössenverarbeitung. Leipzig, 1969


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