Acquired Waveform Metadata for Large-File Signal Analysis
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Solution Overview
Problem
Existing test and measurement systems struggle to efficiently extract and abstract waveform data into tangible information for scalable and efficient human understanding and analysis, particularly due to the time-consuming process of performing measurements on large files and the lack of automated metadata generation.
Innovation Solution
A system that attaches measurements as metadata to waveform files using automated processes and machine learning, enabling efficient and scalable data analysis by crawling historical data and utilizing modern cloud resources, with a library of measurements and classifications that can be updated dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If measurements are performed on large waveform files at analysis time, then complete measurement data is available, but the processing time becomes excessively long and scalability is poor
Solution Approach 1:
The system performs measurements on waveform files during the acquisition phase and stores the results as metadata alongside the waveform data. This preliminary action ensures that measurements are completed before the files are stored, making them immediately available for later analysis without requiring re-processing of the original large waveform files.
2Productivity
If engineers extract only the specific information needed to solve current problems, then immediate problem-solving efficiency is improved, but future analysis capabilities are limited when understanding changes
Solution Approach 1:
The system performs a comprehensive set of measurements on each waveform file and stores all results as metadata, making the data universally useful for multiple purposes. The same metadata serves both immediate problem-solving needs and future analysis requirements, eliminating the need to re-acquire data when analysis requirements change.
3Quantity of substance
If waveform data is stored without attached measurements, then storage efficiency is improved, but data accessibility and searchability are reduced
Solution Approach 1:
The system extracts measurements from the waveform data and stores them separately as metadata attached to the waveform files. This separation allows the original waveform data to be stored in its compact form while the measurement results are stored in a lightweight, easily searchable format that improves data accessibility without significantly increasing storage requirements.
Data Source
AI summary
A computing device includes a port to allow the computing device to connect to a network, and one or more processors, the one or more processors configured to execute code to cause the one or more processors to determine that a new waveform has been added to a repository connected to the computing device, perform a set of measurements on the new waveform, attach results from the measurements to the new waveform as metadata, and store the new waveform and attached metadata to the repository. A method of managing waveform data includes determining that a new waveform has been added to a repository, performing a set of measurements on the new waveform, attaching results from the measurements to the new waveform as metadata, and storing the new waveform and attached metadata to the repository.