Kenneth J. LaBry, Chief Scientist, Acoustics, Underwater Acoustics International
We are now living in a time where robotics and remote sensing, are utilized to unburden human activity from risk exposure and repetitive effort as well as to provide cataloged and characterized information from remote sensing observation, which is used to make better decisions in all aspects of society from medicine to transportation and civil infrastructure. This paper proposes to implement a combined effort of robotics, remote sensing and digital data management for Predictive Maintenance modeling of dams.
There are 84,000 Dams in the United States, 1,756 of these are also hydroelectric power generating facilities. These Dams are an average of 52 years old. Most of these dams have unknown disposition of underwater components and un-mapped stages of degradation. The examination of any Dam is a singular exercise. Some Dams may be of similar design but no two Dams are quite alike with each Dam requiring a tailored examination plan. This paper presents a system and methodology for the application of high definition Underwater Acoustic Remote Sensing in the inspection of submerged dam structure components and the interfaces of those structures with the surrounding water bottom and shows how the information acquired can be presented in a platform that is of value to the owner-operator.
The paper demonstrates the pitfalls and problems associated with acoustics and sonar utilization in substructure inspection, the challenges inherent in shallow environments, confined spaces and difficult access, the environmental difficulties, cost-effectiveness, and benefits, as well as result capabilities. It outlines the basic acoustic principles involved in the inspection of substructures, the development of remote sensing equipment capable of generating the necessary resolution and definition for shallow environments, as well as the development of the techniques and methodologies necessary for proper execution of substructure inspections and comprehensive shallow water-bottom surface mapping. The discussion also encompasses remarks regarding the economic and safety advantages of remote sensing in substructure inspections.
Case study examples are shown and briefly discussed. The examples depict integrated modeling capabilities for illustrating the inspection results, the utilization of reiterative modeling to track conditional changes and provide a knowledge-based predictive basis for maintenance and rehabilitation scheduling.