Improved Instrument Approach Stability Analysis for Helicopters Using Data Fusion and Analytics

Abstract

Approach and landing are among the most challenging and dangerous tasks required of helicopter pilots. Helicopter accident statistics suggest that the majority of helicopter accidents occur during the approach and landing phases of flight. Unstabilized approaches are a leading cause of these accidents due to the increased potential for loss of control, loss of situational awareness, or controlled flight into terrain. In the present work, routine flight data records obtained as part of a voluntary helicopter flight data monitoring program are used to identify, analyze, and evaluate the stability of instrument approach events. A data fusion process is developed that enables detection of the approach phase, identification of an associated instrument approach procedure, analysis of approach stability, and knowledge discovery through data mining. The process identified 385 instrument approach events in a set of 7063 operational helicopter flight data records. Manual analysis of these events reveals some common errors, including crossing the final approach fix far below the assigned altitude and violating the minimum altitude requirement during initial and intermediate approach legs and course reversal maneuvers. Data mining algorithms are tested and found to be capable of automatically identifying atypical or unstable approach events.