Models of optimization of dynamic parameters of an object in passive monitoring
© Mostovoy S.V., Mostovoy V.S.
Structural analysis and identification of dynamic parameters of structures with spectral characteristics within the limits of seismic and bottom part of acoustic ranges are extremely important topics in their monitoring aimed at prediction of substantial changes in dynamic characteristics. By their geometric sizes these are large artificial and natural objects. Method of dynamic identification guarantees a possibility of studying dynamic behavior of the structure by non-destructive tests, and therefore allows estimating "the health" of the structure and probable necessity in more detailed monitoring. The article introduces methodology for identification of the main structural parameters, such as principle intrinsic frequencies and good quality of structure at these frequencies. Methodology of expertise of structure response for dynamic loading is being analyzed, the last one being of any kind of ecological (wind, sea waves, traffic etc.) or produced artificially by testing impulses. Passive monitoring of objects with sources of emission signals, which have parameters to be determined and are characteristics of the structure is of special interest. Emission can have both irregular and regular character. In the last case it can be simulated as a flow with probabilistic characteristics to be determined. Such behavior is typical for geologic faults as a source of emission of seismic signals. Such a flow if it is simulated by binomial one can have unlike the model in active monitoring, a high probability of "not operating" of a source, i.e. the integral of partial density of probability of occurrence of a signal at present moment on a set of the moments can be much less than a unit, while active monitoring can be organized in such a way that the value of this integral will be close to a unit. Dispersion of starting moments of emission of separate signals distribution is essentially more than in the case of active monitoring. Thereupon essential distinctions of two types of monitoring do not come to an end. In active monitoring the researcher can also use a probing signal. It means that the result of the analysis of the data received in passive monitoring of such type of signals is reduced to estimation of parameters of a signal of emission which fluctuates from signal to signal, and distribution of fluctuations of parameters is a priori not known. The important special case of modeling of emission is a case of "short" signals, i. e. well resolved signals.