Abstract

In micro-satellite engineering, telemetry data is the only basis for the ground staffs to judge the condition of spacecraft in-orbit, and is also a critical reference for testing, operation, and Prognostics and Health Management (PHM). In practice, the analysis and processing of raw telemetry data is very complicated and cumbersome. To maintain the micro-satellites' performance and ensure their reliability, it is important to implement on-line interesting pattern discovery in the ground station monitoring system or Electrical Ground Support Equipment (EGSE) system. The goal of this paper is to monitor evolving telemetry sequence of micro-satellite, and to discover subsequences that are similar to the given query sequence, under the Dynamic Time Warping (DTW) distance. However, in the processing of telemetry sequence, massive amounts of data arrive continuously and it is infeasible to directly use DTW distance. Therefore, this paper improves the DTW and proposes a novel method (eDTW) that can perform pattern discovery on telemetry sequence online. First, the sub-sequence time warping matrix is constructed by taking the telemetry sequence as the X-axis and the query sequence as the Y-axis; Second, calculate the DTW distance from each unit, and the initial position of each path; Finally, determine the current local optimal subsequence and determine the next starting point of the next discovery. Experiments with telemetry sequence of Tsinghua University's NS2 satellite show that eDTW can discover interesting pattern quickly, with no buffering of stream values and without comparing pairs of streams. Our experimental case studies show that eDTW can incrementally capture correlations and discover trends, efficiently and effectively.

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