Дем’янюк, А. В. та Стефанишин, Д. В. та Demianiuk, A. V. та Stefanyshyn, D. V. (2022) ПРО ДЕЯКІ ВИКЛИКИ ІНТЕРПРЕТАЦІЇ ДАНИХ ІНСТРУМЕНТАЛЬНИХ СПОСТЕРЕЖЕНЬ ЗА СТАНОМ ГРЕБЕЛЬ, ОТРИМАНИХ ЗА ДОПОМОГОЮ АВТОМАТИЗОВАНИХ СИСТЕМ КОНТРОЛЮ. Вісник Національного університету водного господарства та природокористування (2(98)). с. 80-91.

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Анотація

Розглянуто основні проблеми, що виникають при обробці та інтерпретації даних інструментальних спостережень за станом гребель за допомогою сучасних автоматизованих систем контролю. Обладнання гребель такими системами розширює можливості моніторингу стану за рахунок збору даних у великих об’ємах, проте при цьому виникають певні ускладнення і виклики, що потребують врахування при розробці алгоритмів оцінки стану споруди за даними спостережень.

Title in English

SOME CHALLENGES IN THE INTERPRETATION OF THE DATA OF INSTRUMENTED MONITORING OF THE DAM CONDITION OBTAINED WITH AUTOMATED MONITORING SYSTEMS

English abstract

As water retaining structures dams are hazard potential. An effective way of dam failure prevention is providing dam control (monitoring). Proper interpretation of monitoring data is a crucial part of dam control which is as important as measurements and collecting observational data. Development of the algorithms and techniques of data processing and assessment of the dam condition based on monitoring data is a currently important but also a complicated intelligent problem. During the last decades automated monitoring systems (AMS) are widely used for hydraulic works control in the world and in Ukraine as well. Much experience in handling of monitoring data has already been gained. In the paper the generalization of the typical issues of the proper interpretation of instrumented control data obtained with the use of AMS in regards to the consistency of dam condition estimates is done. The complications in data handling can occur as on the step of the preliminary processing and preparing of the data, as on the step of statistical analysis, as well on the step of data interpretation. Monitoring data by their nature, volume and characteristics can be classified as “big data” and the processing and interpreting of data should be considered as an “intelligent data analysis”. Besides, it must be taken into account that AMS can start to pro�duce faulty data at any moment that leads to the need of providing constant control of the reliability of AMS operation. Furthermore, interpretation of the empirical data for the purpose of the assessment of dam condition is a multivariate problem. It requires the development of advanced algorithms with branching on each step of the problem solving. The particularities of the hydraulic works and special aspects of their operation should also be taken into account in the algorithm of data interpretation. In this insight the problem of the dam monitoring data interpretation can become challenging. Neglecting the mentioned issues can result in obtaining faulty estimates of the reliability and safety of the dam in spite of implementation of the most up-to-date AMS equipment. On one hand the wrong estimates of dam condition can result in overrun in cost of repairing, on the other hand it can lead to dam failure.

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