- Patent Title: Machine learning-based particle-laden flow field characterization
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Application No.: US16950011Application Date: 2020-11-17
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Publication No.: US11709121B2Publication Date: 2023-07-25
- Inventor: Chad Sipperley , Rudolf J. Schick
- Applicant: Spraying Systems Co.
- Applicant Address: US IL Wheaton
- Assignee: Spraying Systems Co.
- Current Assignee: Spraying Systems Co.
- Current Assignee Address: US IL Wheaton
- Agency: Leydig, Voit & Mayer, Ltd.
- Main IPC: G01N15/02
- IPC: G01N15/02 ; G06N3/04 ; G06N3/08 ; G06V10/70

Abstract:
A particle measurement system and method of operation thereof are described. The system and method render a characteristic for a set of particles measured while passing through a measurement volume. The system includes a source that generates a particle-laden field containing the set of particles. The system further includes a sensor that generates a raw particle data corresponding to the set particles passing through the measurement volume of the particle measurement system, where the raw particle data comprises a set of raw particle records and each of one of the raw particle records includes a particle data content. A preconditioning stage carries out a preconditioning operation on the particle data content of the set of raw particle records to render a conditioned input data. A machine learning stage processes the conditioned input data to render an output characteristic parameter value for the set of particles.
Public/Granted literature
- US20210148802A1 MACHINE LEARNING-BASED PARTICLE-LADEN FLOW FIELD CHARACTERIZATION Public/Granted day:2021-05-20
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