Dramatically reduce development time for Acoustic Emission algorithms

Acoustic Emission python code generation

Recent amazing advancements in artificial intelligence have significantly reduced the development time for technological algorithms, including those for Acoustic Emission. As an example, using ChatGPT, we can generate code in seconds for assessing the locations of AE events. For instance, we can prompt ChatGPT with: “Write Python triangulation algorithm for location of an impact event on a 2D plate using several accelerometers. Optimize the location error and provide a measure of location accuracy” and get a nice code that can be further improved by additional prompts. The wise use of AI tools cuts hours, days, and months of coding and debugging, while propelling the technology to new heights.

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