We discuss data symbolization as a tool for identifying temporal patterns in complex measurement signals. We describe the basic concepts involved and illustrate their application for the analysis of gas-bubble injection data. Specific issues addressed include selection of symbolization parameters, construction of symbol-sequence histograms, and statistical characterization and comparison of these histograms. We demonstrate that symbol-sequence statistics can reveal unique information about deterministic patterns. Such information may be useful for developing flow diagnostics and comparing computational models with experiments.

This content is only available via PDF.
You do not currently have access to this content.