Machine learning protocol from ultrasound data for monitoring, predicting, and supporting the analysis of dam slopes

Dam monitoring can be used as an important indicator for dam risk management. In this study, a methodology based on machine learning and ultrasound for dam safety monitoring is presented. First, a prototype dam was built to simulate different environmental conditions. Second, ultrasound images were acquired in different areas of a prototype dam. Finally, various machine learning algorithms were applied to distinguish the different regions observed in the prototype dam. The results show that it is possible to distinguish the dam regions, which is of great value for dam safety monitoring and operation.