IMPROVEMENT OF TIRE UNIFORMITY THROUGH IDENTIFICATION OF PROCESS EFFECTS USING REGRESSION ANALYSIS WITHOUT AZIMUTH DATA
Systems and methods for improving the uniformity of a tire based on estimated process harmonic magnitudes for one or more process effects are provided. Magnitudes of process harmonics associated with one or more candidate process effects can be determined from the observed magnitudes of one or more...
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description | Systems and methods for improving the uniformity of a tire based on estimated process harmonic magnitudes for one or more process effects are provided. Magnitudes of process harmonics associated with one or more candidate process effects can be determined from the observed magnitudes of one or more harmonics of measured uniformity parameters. The estimated process harmonic magnitude(s) can be determined without requiring phase angle or azimuth information associated with the observed magnitudes. The estimated process harmonic magnitude(s) can be determined by identifying a process harmonic magnitude pattern for identified candidate process effects. A model can be constructed correlating the candidate magnitudes specified by the process harmonic magnitude pattern with observed magnitudes of corresponding harmonics of a measured uniformity waveform. Regression or programming techniques can be used to estimate coefficients associated with candidate magnitude terms in the model. |
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Magnitudes of process harmonics associated with one or more candidate process effects can be determined from the observed magnitudes of one or more harmonics of measured uniformity parameters. The estimated process harmonic magnitude(s) can be determined without requiring phase angle or azimuth information associated with the observed magnitudes. The estimated process harmonic magnitude(s) can be determined by identifying a process harmonic magnitude pattern for identified candidate process effects. A model can be constructed correlating the candidate magnitudes specified by the process harmonic magnitude pattern with observed magnitudes of corresponding harmonics of a measured uniformity waveform. 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Magnitudes of process harmonics associated with one or more candidate process effects can be determined from the observed magnitudes of one or more harmonics of measured uniformity parameters. The estimated process harmonic magnitude(s) can be determined without requiring phase angle or azimuth information associated with the observed magnitudes. The estimated process harmonic magnitude(s) can be determined by identifying a process harmonic magnitude pattern for identified candidate process effects. A model can be constructed correlating the candidate magnitudes specified by the process harmonic magnitude pattern with observed magnitudes of corresponding harmonics of a measured uniformity waveform. 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Magnitudes of process harmonics associated with one or more candidate process effects can be determined from the observed magnitudes of one or more harmonics of measured uniformity parameters. The estimated process harmonic magnitude(s) can be determined without requiring phase angle or azimuth information associated with the observed magnitudes. The estimated process harmonic magnitude(s) can be determined by identifying a process harmonic magnitude pattern for identified candidate process effects. A model can be constructed correlating the candidate magnitudes specified by the process harmonic magnitude pattern with observed magnitudes of corresponding harmonics of a measured uniformity waveform. Regression or programming techniques can be used to estimate coefficients associated with candidate magnitude terms in the model.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | MEASURING PHYSICS TESTING TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR |
title | IMPROVEMENT OF TIRE UNIFORMITY THROUGH IDENTIFICATION OF PROCESS EFFECTS USING REGRESSION ANALYSIS WITHOUT AZIMUTH DATA |
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