Development of ai techniques for the condition monitoring of ground anchorages

The GRANIT system is a non-destructive method for the condition monitoring of ground anchorages. Ground anchorage systems in the format of ground anchorages or stratabolts are used extensively throughout the world as supporting devices for civil engineering structures such as bridges and tunnels. A need for the condition monitoring of ground anchorages has been identified [1], with only between 1-5% of anchorages currently being monitored in service [2]. The GRANIT system operates by applying an axial load to the anchorage by way of a specially designed impulse device that connects to its protruding length. The acceleration signals are recorded by a laptop computer or equivalent, and the signals are analysed by signal processing techniques for the detection of relevant characteristics in the signal that relate to specific features of the anchorage (for example, its load or the size of its free length). This paper describes recent work undertaken at AMEC's specially designed all weather anchorage test site at Swynnerton, England, for the investigation of the applicability of the GRANIT technique to ground anchorages or stratabolts that are used throughout the UK Coal Mining industry. Results from these trials will be shown, showing the high accuracy in load detection that can be obtained. The Artificial Intelligence schema employed by the GRANIT technique will be described fully and the novel introduction and implementation of a mathematical model of the anchorage system into this schema will also be explained. The development of the AI schema from its original to the present form will be described, showing how various AI schemes have improved and added to the knowledge base of the condition monitoring system.