Development of POD from in-service NDI data

The economic drive towards using aircraft beyond their initial design life has created a great interest in damage-tolerance (DT) based maintenance. The DT approach relies on routine nondestructive inspections (NDI), and requires that the NDI performance to be quantified in terms probability of detection (POD) to determine the safe inspection intervals. The most common approach for determining NDI POD is to perform inspections on representative components or specimens simulating the actual parts. This approach is practical but can be very expensive. A more economical approach may be to use actual field inspection data to obtain POD. This approach is particularly attractive for airframe inspection techniques, since most airframe structures cannot be easily simulated. There are a number of difficulties with this approach: Firstly, there is usually a very limited amount of field data. This may require special statistical treatment. Secondly, crack growth data must exist to allow the estimation of flaw sizes at the inspection sites at inspection times before the flaws were found. These factors and others affect the confidence in the calculated POD, and must be quantified before POD data of this type can be used. In this work, data from full scale fatigue tests were analyzed, and methods of overcoming the problems of small sample sizes and crack growth data requirements were investigated.Peer reviewed: YesNRC publication: Ye