A mobile vibratory roller impactor system is proposed, using AI-based pattern recognition for identification of voids through analyzing the tapping force on the AM-2 mat exerted by the roller impactor. The Phase I project will conduct feasibility demonstration of the proposed technology. The basic concepts of the proposed technology will be implemented and demonstrated on a test pad or subgrade covered by AM-2 mat for detection of various voids embedded in the subgrade at different depths. AI-based pattern recognition techniques will be applied to locate the voids by identification of the features on the records of dynamic tapping force over them. The work will address some key issues in the technology development such as selection of magnitude of tapping impact, frequency, noise reduction, transducer selection and detection criteria development. The Phase I work will be divided in two sections: base effort for experimental feasibility demonstration and optional work for numerical simulation to provide guidance for further prototype development. Successful accomplishment of the Phase I and Phase I optional work will provide us with a solid background to proceed into the full scale prototype development.
Benefit: Besides finalizing the proposed vibratory impact system for the NAVY and becoming a technology and service supplier innovation for the government, AAC International may also use the low frequency nondestructive testing technique to explore commercial potential in many other areas. For example, many airports have sinkholes developing under runways; void detection technique under AM-2 mat may also be used to detect sinkholes with little modification. In the construction industry and municipal public works, a device of this nature would provide the ability to detect soil erosion underneath buildings, roads, or runways for infrastructure maintenance. The threat of infrastructure collapse due to defects, voids or sinkholes is evident. Safety concerns about these military and civil structures create great demand for nondestructive inspection technology, especially for technology capable of detecting voids/defects under hard surfaces. The AI-based low frequency inspection system for infrastructure void/defect detection as described in this proposal will meet this particular demand in both military and civilian sectors. Its business potential is well founded.
Keywords: pattern recognition, pattern recognition, FEM Simulation, Airport Runway, Poroelastic Material, Artificial Intelligence, Impactor, AM-2 Matting, Mechanical Impedance
