Structural airframe maintenance is a subset of aircraft maintenance, which is often performed at scheduled intervals to detect and repair cracks that would otherwise affect the safety of the aircraft. With the progress of structural health monitoring (SHM) techniques, which uses on-board sensors and actuators to assess damage status, condition-based maintenance (CBM) is considered as an alternative to traditional scheduled maintenance. By applying SHM techniques, CBM can access damages status as frequently as needed and unscheduled maintenance can be asked once the damage exceeds a particular threshold. Due to the harsh working environment and sensor limitation, the measurement data acquired from SHM is often quite noisy. In this paper, Extended Kalman filter is used to filer the noise to provide an accurate estimation of crack size and crack growth parameters together with their associated uncertainty. This knowledge is used to obtain a probabilistic estimate of the remaining useful service life of the structure. Based on these estimates, two maintenance philosophies are developed and further compared in terms of maintenance stop number or replaced panel number. The results indicate that both these two strategies reduce considerably the maintenance stop number compared to scheduled maintenance
