Structural identification using a low-cost search method

An easily implementable and trainable damage detection method is proposed and implemented for a simple truss structure. The approach uses the iterative search identification method and is compatible with low-cost and low-power microcontroller hardware. This method employs pattern matching for a data set from a strain sensor array and predicts location (truss member) and severity (member cross sectional area) of damage. As a health monitoring approach, the method is not as robust or rigorous as more complex methods. However, it has modest processing requirements and can handle noisy signals. The work presents an algorithm applied to a truss structure, the simulation performance from a finite-element-analysis, and a discussion of capabilities. The simulation demonstrates differing damage locations, damage severity, and signal noise. Its suitability for low-cost and low-power field processors is discussed.