Affiliation:
1. Institute of Control Systems, Azerbaijan National Academy of Sciences;
Azerbaijan University of Architecture and Construction
2. Azerbaijan University of Architecture and Construction
3. Institute of Control Systems, Azerbaijan National Academy of Sciences
Abstract
The paper deals with the development of algorithms for calculating the high-order moments of the noise of noisy signals and their use in the analysis of the technical condition of industrial facilities. It is shown that for monitoring and controlling the onset of an emergency at oil production facilities, random vibration signals are used, which, in addition to the noise caused by external factors at the time of the initiation of the malfunction, also contain additional noise. The characteristics of this noise contain certain information about the technical condition of the drilling rig. Earlier, algorithms were developed for calculating the variance, standard deviation, and density distribution function of the noise that cannot be separated from the noisy signal. In this paper, it is shown that high-order moments of the noise can be used as a diagnostic indicator for determining the presence and degree of damage development in drilling rigs during the latent period of damage initiation. Possible options for calculating the high-order moments of the noise are analyzed. Recursive algorithms are developed for expressing high-order moments of a normally distributed noise through its variance. The possibility of calculating the high-order moments of the noise through the distribution density functions is also shown. A matrix consisting of estimates of the high-order moments of the noise calculated at different instants of time is built. It is shown that at the first stage, it is possible to determine the presence and degree of the damage based on the values of the matrix elements. At the second stage, the intensity of damage development is determined by comparing the values of the noise characteristics at different instants of time. Calculations are performed for all signals coming from the sensors. Training is carried out and, the correspondence is established between the values of the high-order moments and degrees and intensity of damage development. The possibility of using the proposed algorithms and technologies in the system of noise control of the beginning and development dynamics of accidents at drilling rigs is shown. It is noted that even if the estimates of the high-order moments of the sum noisy vibration signals change within a wide range during drilling, their high-order noise moments do not exceed a predetermined value in the absence of a malfunction. In the event of a malfunction, the estimates of the highorder moments of the noise exceed the predetermined threshold level and, as the defect develops, their values also change. If adverse processes are stabilized, the variation of these estimates stops as well. Moreover, depending on the degree and intensity of stabilization of the technical condition of the drilling rig, the change in the estimates of the moments, starting from the highest to the lowest or vice versa, stops one by one. This specific feature of estimates of high-order noise moments of vibration signals allows us to identify the beginning and to control the development dynamics of the latent period of an emergency state of the drilling process.
Publisher
New Technologies Publishing House
Subject
Electrical and Electronic Engineering,Artificial Intelligence,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software
Cited by
2 articles.
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