In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data

Abstract

The in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate results. To solve this problem, we propose one kind of quantitative analysis of its on-wing sensing data to implement remaining useful life prediction of auxiliary power unit. Except the most important performance parameter exhaust gas temperature, the other potential parameters are utilized based on mutual information, which can be used as the quantitative metric. In this way, the quantitative threshold of mutual information for enhancing remaining useful life prediction result can be determined. The implemented cross-validation experiments verify the effectiveness of the proposed method. The real on-wing sensing data of auxiliary power unit for experiment are from China Southern Airlines Company Limited Shenyang Maintenance Base, which spends over $6.5 million on auxiliary power unit maintenance and repair each year for the fleet of over 500 aircrafts. Although the relative improvement is not too large, it is helpful to reduce the maintenance and repair cost.

A fault detection method for Auxiliary Power Unit based on monitoring parameters selection

“…In terms of remaining useful life prediction, Liu et al 5 proposed a hybrid method of remaining useful life prediction for APU, which is evaluated by the real data. Besides, Liu et al 6 proposed an in-situ remaining useful life prediction method based on quantitative analysis of on-wing sensing data. Moreover, Liu et al 2 proposed a performance degradation prediction method for APU based on the improved Support Vector Regression (SVR).…”