Data summarization is a process to reduce and segment data in order to perform subsequent calculations on only relevant segments of data. In aviation, this means identifying the segments of flight, storage, and maintenance data that contain information relevant to calculating remaining useful life (RUL). Examples of this data include sensor data, flight schedules and maintenance logs. This summarization is necessary to reduce data transfer and processing time in subsequent steps. Creating a useful data pipeline that will effectively remove unnecessary segments of data, while leaving in relevant segments, employs a variety of techniques and introduces challenges in deciding when and where summarization is to take place. Once summarized, data are more readily available for downstream processing and inference. In this context, strategic pre-processing for data reduction amounts to data transformation, feature selection and decomposition techniques. Statistical analyses may be used to quantify the efficacy of the data transforms so performed. Data pre-processing for the purpose of summarization becomes even more necessary as fleet size increases, mission tempo increases, and/or the environment becomes more austere. This paper provides an overview of data summarization techniques with examples across several different types of aviation data.
Intelligent Summarization of Aviation Data for Maintenance
2024-03-02
30143723 byte
Conference paper
Electronic Resource
English
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