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Noesis Data Statistics

Noesis provides the user, and especially the acoustic emission data analyst, with a new way of looking at the data: Statistics. Typical AE practices relay on 'statistics' to discriminate noise, genuine AE and other types of emission. These 'statistics' relied on the capability of the analyst to view graphs and decide how data relate to each other and to known limits and general rules. Noesis provides a full statistical review of the data so that some observations are made easier by looking at straightforward numbers. Especially in the case of data clustering the user has powerful statistics to compare groups with each other and make decisions as to the effectiveness and/or correctness of the classification algorithm or manual data separation into groups (clusters). Statistics can provide information about the separability of data, the correlation between features, clustering efficiency etc.

  • Channel Statistics  including Min, Max, Average etc.
  • Amplitude Distribution tables (per channel and class).
  • Min, Max, Mean, Skewness, Curtosis etc. for all data sets.
  • Feature correlation matrices and dendrograms for tabular and graphical correlation views.
  • Various criteria for vector or feature statistics (Wilk's, Rij etc.). These criteria can be used for evaluating clustering effectiveness.
  • Feature and Class discriminant Statistics.
  • Class Statistics for unsupervised, manual, and supervised acoustic emission data classification (cluster centers, cluster distances etc.) for an overview of data clustering.

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