Damage to a huge dam can cause great loss of human life and property, but disasters and their consequences can be minimized by implementing effective dam safety monitoring strategies. However, establishing a permanent monitoring system on a huge dam is costly. Additionally, for reasons of national security, many dams and information about them may not be able to be accessed by researchers. Accordingly, continuously monitoring the structural health of a dam by measurement may be difficult. This study presents a way to continuously monitor the health of a dam using vibration signals that are measured not on the dam but close to it. The Sayano-Shushenskaya Dam in Russia is used to demonstrate the idea. Intensive ambient vibration measurements were firstly made once to determine the natural frequencies of the dam. Then the natural frequencies of the dam under varying environmental effects are obtained from the spectra of the seismic records obtained at Cheryomushki seismic station, which is located 4.4 km northeast of the dam. To account for the effects of varying environmental conditions on the natural frequencies, an autoencoder in the form of an unsupervised learning neural network, was employed. The autoencoder was trained using the natural frequencies without using any environmental factors to learn the intrinsic behavior of the dam under varying environmental conditions. The errors between input data to the trained autoencoder and the regenerated data from the autoencoder can be used to determine whether the dam is under normal conditions. A finite element model of the dam was constructed to simulate changes of natural frequencies due to cracks in the dam structure. The results demonstrate that the proposed method can feasibly monitor the structural health of the dam.
A method is proposed for monitoring the natural frequencies of hydro power plant dams using continuous seismic observation data. The object of the research is the largest in Russia arched Chirkey dam located in the Caucasus. At the initial stage, a detailed study of the natural oscillations of the dam was performed using the method of coherent restoration of the standing wave fields with the definition of both the natural frequencies of the structure and their modes. The features of seasonal changes in the total field of standing waves are studied and factors affecting changes in natural frequencies are established. At the next stage, the values of natural frequencies were determined from the spectra of microseismic oscillations recorded by seismic equipment installed on the object. Observation points located in the antinodes of standing waves were used. The values of the natural frequencies of the Chirkey dam, as a whole, decrease with increasing upstream level. It was determined that there are additional factors leading to the hysteresis effect in the relationship between the values of the upstream level and natural frequencies, presumably associated with relaxation processes in the dam body and/or in the dam-base system after the change of level. A method for monitoring the state of the dam is proposed, based on a comparison of the observed values of natural frequencies with the predicted ones. The latter are determined by linear dependencies on the upstream level, taking into account the time shifts associated with relaxation processes
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.