EngineQV: Investigating External Cause of Engine Failures Based on Geo-Temporal Association
Yanchao Wang, Qian Zhang, Feng Lin, Hock Soon Seah · 2019
The heart of every vehicle is its engine. Many factors, either internal or external, contribute to the aircraft engine's durability and lifespan. In this paper, we aim to assist the analyst with a qualitative analysis of the possible external cause of engine failures. We work closely with domain experts to study the domain knowledge, analyze challenging tasks, and abstract user requirements. We present EngineQV, a visualization system that integrates multiple geo-temporal engine-associated records. It provides intuitive exploration and understanding of the data from various aspects. The system features a dynamic query on the datasets and incorporates several customized interactive visualizations. A user may query a certain group of engines or compare multiple engine groups, identify an issue, and find its potential causes. The functionality and usability of EngineQV are evaluated by two case studies, through knowledge discovery from records of a single engine and visual comparison of multiple engines. The validity of the system is confirmed by expert feedback.