| Abstrakt: |
When drilling oil and gas wells, the problem of reliable detection of time of rock cutting tool replacement because of its wear remains unsolved. To solve it, the automated control system of the rock cutting tool condition with the functions of identifying, recognizing, predicting and selecting the strategy of monitoring the exhaustion of the tool was developed. To increase the system performance, the analysis of its subsystems in terms of their impact on the overall control reliability index was carried out. It was found that recognition and prediction subsystems are the most responsible. To implement the algorithms of these subsystems, it is proposed to use neuro and fazzi-artificial intelligence technologies that have proven their efficiency in such tasks. The results obtained are important since they indicate the effective ways to solve the problem, moreover they can be also applied to other problems of this type. [ABSTRACT FROM AUTHOR] |
