Data mining from PLEIADES telecommand logbooks

The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. All the operations carried out on a spacecraft need to be logged somewhere. Such daily activity is essential to get a macroscopic view of the maintenance activities, especially for monthly or yearly reporting. Up to now the list of everyday activities carried out on CNES Earth observation spacecraft of the French Space Agency (CNES) has been filled manually by each Flight Control Team (FCT) in an Excel® file. However the accuracy of the information depends a lot on the proficiency of the FCT members involved in the process. Obviously there is always the risk of human error. For example, forgetting to log an operation or typing errors can and sometimes do lead to inaccurate overall reporting. Hence the need to improve the general process of data gathering. This paper deals with a new foolproof method which has been tested successfully on the Pleiades spacecraft (PHR1A and PHR1B) in order to automatically compile spacecraft activities from telecommand logbooks which are huge XML files (around 10 million lines per year). This kind of issue falls typically within a data mining approach and algorithms have been implemented to filter the various data inside the logbooks and extract the relevant information out of them. Output files are simple ASCII tab separated files which list the main operations performed during the period under consideration. These files may be either edited with Excel® (to benefit from its world renowned filtering capabilities) or plotted as a chronogram with PrestoPlot® which is a COTS already used in CNES for displaying telemetry parameters. Such chronograms are particularly useful for people in charge of spacecraft maintenance because they help them easily establish a potential link between spacecraft operations and telemetry behavior, especially for trend analysis. Activity files are generated every month, but they can be generated for a shorter period. The monthly files are also concatenated to build overall activity files which gather information from the beginning of life of each spacecraft. This process has been tested and tuned during PHR1B in orbit test phase beginning of 2013 and then successfully retrofitted to PHR1A. An activity data base is also a great help for the FCT because any operation performed on a spacecraft can be found again very easily. Finally this innovative system is adaptive and may be applied very easily to any existing spacecraft program.