A.B. Ivanov, S.S. Kotlyar, A.A. Stratonnikov, A.F. Tashoyan, V.V. Shiryaev

At research of distributed physical and informational media and their running processes problems of both control and diagnostics objects testing occur naturally and are usually solved by means of the same name facilities located in nodes of such media and forming integrated monitoring system in aggregate with data processing elements. Testing can run single-stage, periodically or through defined, but unequal intervals of time in terms of monitoring target problem. For example, transmission line testing may accomplish irregular in time, at accumulation of data for the purpose of subsequent change of line state forecasting - periodically or, if test results don-t match predefined masks, - single staged. Tests thus can be structured so that to receive information on deterioration or violation of corresponding line functioning in shortest times or so that to receive the most authentic prognostic information on possibility of malfunctions occurrence in corresponding line. For this purpose one test can be enclosed in the other test which together with separate measurements of the third test form compound trouble-shooting test. Thus the testing plan should provide certain formation sequence of tasks which include set of problems - tests which define type of executed procedures - measurements of parameters for each object of control and diagnostics. This causes necessity of definition of time parameters for both tests and their placement on time axis taking into account restrictions on used resources - control and diagnostics devices and relations of precedence between task elements. Test placing requirements can come to placing of predefined set of tests on the minimal time interval, on the specified time interval, uniform on the specified time interval or dense as much as possible. Solving optimization problems of such kind can be carried out by various means. Specificity of considered problem testifies in favor of genetic approach implementation in spite of the fact that it doesn-t guarantee obtaining the best possible solution, it does however give the basis to assume that derived solution would be close to optimal and would be obtained in acceptable time.