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.

Abstract: A system and method are described for rendering a characteristic for a set of particles passing through a measurement volume of a particle optical measurement system. The method includes acquiring raw particle data for the particles passing through the measurement volume. The raw particle data comprises a set of raw particle records. Each particle record comprises at least: a trajectory of at least one particle, and a second primary mark of the at least one particle whose value influences an effective sampling area corresponding to the measurement volume. The method includes generating and storing an effective sampling area based upon: the trajectory of the at least one particle, and the second primary mark. Thereafter, an ensemble characteristic is rendered for the set of particles by performing an operation on the sampling area-corrected set of particle records.

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.

Abstract: A system and method are described for rendering a characteristic for a set of particles passing through a measurement volume of a particle optical measurement system. The method includes acquiring raw particle data for the particles passing through the measurement volume. The raw particle data comprises a set of raw particle records. Each particle record comprises at least: a trajectory of at least one particle, and a second primary mark of the at least one particle whose value influences an effective sampling area corresponding to the measurement volume. The method includes generating and storing an effective sampling area based upon: the trajectory of the at least one particle, and the second primary mark. Thereafter, an ensemble characteristic is rendered for the set of particles by performing an operation on the sampling area-corrected set of particle records.