Study on real-time construction quality monitoring of storehouse surfaces for RCC dams

• A method of real-time construction quality monitoring of storehouse surfaces for RCC dams are proposed.
• Automatic identification of compacted layers is realized.
• A real-time construction quality monitoring system is developed and the application results show its effectiveness.
• Predictive models of compactness and the loss of VC value are built, good results are acquired.

Construction quality control of storehouse surfaces is a major concern in the construction management of roller-compacted concrete (RCC) dams. The construction quality of the special dam-filling material RCC is affected by many factors, including the rolling compaction, concrete temperature and construction climate of storehouse surfaces. Timely collection and comprehensive analysis of construction data from the entire construction process of storehouse surfaces and subsequent feedback to construction operations on site are key issues in the control of construction quality and thus obtain greater attention. Traditional methods of construction quality monitoring, including manual inspections or sampling tests, are labor-intensive and easily lead to indiscoverable and irreparable quality defects. In the present study, a real-time construction quality monitoring method for storehouse surfaces of RCC dams is proposed. The auto-identification of compacted layers is realized. Based on the integration of global positioning system (GPS) and global navigation satellite system (GLONASS) techniques, sensor technology and network transmission technology, a real-time construction quality monitoring system is developed and applied to the LDL dam as a case study. The application results realize the whole process, all-weather and timely monitoring of rolling compaction quality, concrete temperature and construction climate in each compacted layer of storehouse surfaces and guarantees satisfactory construction quality and high efficiency, which demonstrates the effectiveness of this system. Moreover, construction data are used to establish predictive models for compactness and the loss of vibrating-compacted (VC) value by applying a multiple regression analysis method.