A vibro-haptic human–machine interface for structural health monitoring

The goal of the structural health monitoring community has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically, the structural health monitoring community has attempted to do this by instrumenting structures with a variety of sensors and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systems found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases, expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human–machine cooperation. The results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human–machine interface for structural health monitoring. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. The preprocessed data are then encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.