Vibration based fault detection and identification in an aircraft skeleton structure via a stochastic functional model based method

The problem of vibration based fault detection, identification (localization) and estimation in a scale aircraft skeleton structure is considered via a stochastic functional model based method (FMBM). The method is based on the novel class of stochastic Functionally Pooled models, which are capable of accurately representing the structure in a faulty state for the state's continuum of fault magnitudes, as well as interval estimation and formal statistical hypothesis testing procedures. The faults considered consist of small masses attached to the structure. The method is capable of operating even on single-excitation single-response signals, and is shown to achieve effective fault detection and identification, as well as remarkable accuracy in estimating the exact fault magnitude. This is so even for “unmodelled” faults, or faults monitored by remote sensors.