Tire Uniformity Analysis via Regression Without Phase Angle
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Solution Overview
Problem
Conventional tire uniformity analysis methods struggle to accurately estimate process harmonic contributions without phase angle information, leading to poorer compensation and adjustments in tire manufacturing.
Innovation Solution
A method and system that determine estimated process harmonic magnitudes for tire uniformity improvement by identifying candidate process effects and their magnitude patterns, using observed magnitudes from test tires, without requiring phase angle information, and modifying tire manufacturing processes accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tire uniformity analysis methods are used, then tire uniformity can be analyzed, but the estimation of process harmonic contributions is inaccurate without phase angle information
Solution Approach 1:
The patent extracts only the magnitude information from the uniformity waveform while discarding the phase angle information. By using regression analysis to estimate process harmonic magnitudes solely from magnitude data, the system achieves accurate process harmonic estimation without requiring phase angle measurements, thus resolving the contradiction between measurement precision and information loss.
Solution Approach 2:
The patent changes the parameter being analyzed from both magnitude and phase angle to only magnitude. By formulating the problem in terms of magnitude-only regression analysis, the system maintains estimation accuracy while eliminating the need for phase angle information, effectively resolving the technical contradiction.
2Measurement precision
If phase angle measurement is implemented, then process harmonic magnitude estimation accuracy improves, but device complexity and manufacturing requirements increase
Solution Approach 1:
The patent extracts only the necessary magnitude information from the uniformity waveform, eliminating the need for complex phase angle measurement systems. This simplifies the measurement apparatus while maintaining the ability to estimate process harmonic magnitudes accurately through regression analysis.
Solution Approach 2:
The patent uses a simpler, less expensive measurement approach that relies on magnitude data alone, avoiding the need for sophisticated phase angle measurement equipment. This reduces device complexity and manufacturing requirements while achieving the desired measurement precision through computational methods.
3Manufacturing precision
If comprehensive uniformity waveform analysis is performed, then tire effects can be identified, but process effect contributions cannot be distinguished without phase angle data
Solution Approach 1:
The patent reformulates the analysis to work with magnitude-only parameters. By using regression analysis that operates exclusively on magnitude data, the system can distinguish between tire effects and process effects without requiring phase angle information, thus maintaining manufacturing precision while accepting information loss.
Solution Approach 2:
The patent introduces regression analysis as an intermediary computational method that bridges the gap between magnitude-only measurements and process harmonic identification. This intermediary technique enables the distinction between tire and process effects without direct access to phase angle data.
Data Source
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Figure 2
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AI summary
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.