Abstract: Technical effects of the invention include use of a data-driven multivariate statistical method for the detection and isolation of sensor faults applied in a virtual flow metering context. In one implementation, the data-driven multivariate statistical method employs principal components analysis, weighted squared prediction error, and partial decomposition contribution plots.

Abstract: The present approach relates to establishing metrics for the computation of uncertainty boundaries for mean values for pressure and temperature drop error and mean values for mass flow error. Using such metric, sensor inaccuracies may be accounted for in the calibration and/or estimation processes of a virtual flow meter. For example, these values may be employed in the assessment of improvement in a calibration process of virtual flow meters, which will facilitate maintaining the accuracy of such virtual flow meters.

Abstract: A hybrid motor includes a motor shaft, a stator comprising a stator core, a plurality of stator windings wound around the stator core, and a plurality of stator bearings for supporting the motor shaft against the stator core. The hybrid motor further includes a rotor disposed within the stator. The rotor includes a plurality of rotor core segments disposed along an axial direction and coupled to the motor shaft. The plurality of rotor core segments includes a damping rotor core segment and a synchronous rotor core segment. The rotor also includes a plurality of rotor bearings for supporting the motor shaft against plurality of rotor core segments.

Abstract: Technical effects of the invention include use of a data-driven multivariate statistical method for the detection and isolation of sensor faults applied in a virtual flow metering context. In one implementation, the data-driven multivariate statistical method employs principal components analysis, weighted squared prediction error, and partial decomposition contribution plots.

Abstract: The present approach relates to establishing metrics for the computation of uncertainty boundaries for mean values for pressure and temperature drop error and mean values for mass flow error. Using such metric, sensor inaccuracies may be accounted for in the calibration and/or estimation processes of a virtual flow meter.