Predictive maintenance for helicopter from usage data: Application to main gear box

Abstract

The Main Gear Box (MGB) is a central mechanical unit of the helicopter and is a very highly monitored system. For years, optimizing the maintenance of a MGB is a challenging problem. In this paper we develop a visual method for predicting the future state and aging of a monitored MGB based on the analysis of in-service usage data history. We have collected such data from several aircrafts since three years. Usage data characterize the real usage of in-service aircrafts for internal process and view of operational data for technical event investigation. To deal with such big data, we have applied an exploratory data analysis process focusing on oil pressure and temperature. The corresponding numerical values have been discretized in classes defined by domain experts, from which co-occurence matrices were built for some predefined time windows. The visualization of successive co-occurence matrices turns out to be quite convenient and have been exploited as a decision support tool in monitoring the state of a MGB. We have applied this approach on three different aircrafts and built several videos. As concrete results, we have been able to recover maintenance operations, such as MGB removals, and one known anomaly � registered in maintenance data � from the proposed visualization.