New Methods for Control System Signal Sampling in Neural Networks of Power Facilities

Abstract

The authors of the paper emphasize that when the Nyquist-Shannon sampling theorem is used in practice, there arise several problems, which can be explained only through the use of new methodologies and mathematical models. The review of the researchers' works, as well as the authors' own practical research in the course of processing the statistical sample, which is described by a wave-like sine-cosine function, leads to the conclusion that it is necessary to take into account optimization criteria for high-tech processes and innovative indicators of building functions for the statistical sample, for example, when signals are transmitted and sampled using neural networks at production facilities. In the practice of economic calculations, for example, when making a graphic presentation of trend lines based on the functions built subject to the sampling conditions by the Nyquist theorem, the authors propose to use new methods for approximating piece linear functions, which allow for achieving a smaller error as compared to standard calculation methods. The work resulted in the creation of a neural network regulation algorithm, which will be trained based on the collected data and adapted to a specific type of a boiler unit. Besides, it was established that the task of neural network algorithms in the program is to find the optimal value of the weight coefficient for each argument of the resulting function to obtain the maximum number of predictions of the flare level and the particle burn-up time, which are consistent with reality. The use of these methods for the first time made it possible to significantly reduce the error, which is confirmed not only by calculations, but also by experimental data.

Experimental Study of a Coil Type Steam Boiler Operated on an Oil Field in the Subarctic Continental Climate

“…In addition, in [34], Toropov et al proposed to use the results of [33] for lowand medium-pressure thermal power equipment. It should be noted that the paper by Osintsev et al [35] shows the possibility of using the results of the work [33] in order to organize neural network control of combustion processes, including natural gas combustion. Thus, the methodological basis of the article was laid by the authors earlier in the work [33].…”

Combined Approach to Analysis and Regulation of Thermodynamic Processes in the Energy Technology Complex

“…Considerable attention was paid to the issues of automatic control of the energy technology complex in the publications of Salikhov [26,27]. The simplest control methods using neural networks in relation to rotating furnaces were studied in detail in [28,29]. However, the absence of the concept of combining methods does not provide the necessary characteristics for the depth of analysis and the quality of management according to the criterion of ensuring total efficiency.…”

“…Step 8 when using standard Equations ( 1)-( 6) and new approximation methods as in our previous works [9,29], shown in Equations ( 7)- (30). Figure 12 shows graphs of several approximations when approximating a function, which is typical for estimating oscillations during signal transmission, as well as when converting thermodynamic functions.…”

“…The calculation results are summarized in Table 4 and correspond to Steps 5-7 of the algorithmic scheme in Figure 5. Thus, Table 4 shows the difference between the data obtained using the mathematical dependencies as in our previous works [9,29] with the original weight coefficients and the improved ones.…”

“…Another conclusion from the analysis of Table 4 can be the statement that the use of new weight coefficients for learning neural networks and new approximation methods gives an even smaller error in signal transmission (Figure 9). tained using the mathematical dependencies as in our previous works [9,29] with the original weight coefficients and the improved ones.…”