Tire Uniformity via Singlet Regression Analysis
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Solution Overview
Problem
Conventional tire building methods often result in non-uniformities due to various factors, leading to periodic forces during rotation that cause vibrations and noise, which affect ride comfort, and existing technologies struggle to accurately separate tire harmonics from process harmonics in uniformity analysis.
Innovation Solution
A method and system to estimate the magnitude of process harmonics in a measured uniformity waveform, allowing for the separation of tire and process harmonic contributions, enabling improved tire characterization and manufacturing processes by adjusting angular locations of material components and filtering out process effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard Fourier analysis techniques are used to analyze tire harmonics, then the analysis process is simple and familiar, but the ability to identify and separate process harmonics from tire harmonics is insufficient, leading to poor uniformity compensation
Solution Approach 1:
The patent segments the composite uniformity waveform into distinct tire harmonics and process harmonics components. By decomposing the measured waveform into separate frequency components and analyzing each independently, the method enables precise identification of process effects while maintaining a systematic analysis approach that balances precision with manageable complexity.
Solution Approach 2:
The patent introduces an intermediary analysis framework that acts as a mediator between raw uniformity measurements and final uniformity compensation decisions. This framework includes intermediate steps for identifying process harmonics, estimating their magnitudes, and separating them from tire harmonics, thereby improving measurement precision without overwhelming complexity.
2Manufacturing precision
If the angular locations of material components are adjusted to compensate for tire harmonics, then tire uniformity improves, but the effectiveness is reduced by unaccounted process harmonics, leading to suboptimal compensation
Solution Approach 1:
The patent applies preliminary action by identifying and characterizing process harmonics before performing uniformity compensation. By estimating the magnitudes and phases of process harmonics in advance and subtracting their contributions from the measured uniformity waveform, the method ensures that subsequent compensation adjustments for tire harmonics are not contaminated by process effects, thereby improving manufacturing precision.
Solution Approach 2:
The patent implements feedback by using the identified process harmonic information to refine the uniformity compensation process. The estimated process harmonic magnitudes and phases feed back into the compensation algorithm, allowing for more accurate determination of optimal material component angular locations that account for both tire and process effects.
3Measurement precision
If uniformity measurements are taken without separating process effects, then the measurement process is straightforward, but the resulting uniformity characteristics are inaccurate due to contamination from process harmonics
Solution Approach 1:
The patent segments the uniformity measurement analysis into distinct stages: initial measurement, process harmonic identification, process harmonic magnitude estimation, and final tire harmonic analysis. This segmentation allows for accurate separation of process effects while maintaining efficiency by using automated spectral analysis techniques and regression methods that can process the segmented data systematically.
Solution Approach 2:
The patent employs parameter changes by transforming the uniformity measurement data from the time domain to the frequency domain through spectral analysis. By changing the representation parameters of the data and analyzing harmonics at different frequency components, the method achieves precise separation of process and tire effects while maintaining measurement efficiency through mathematical transformations.
Data Source
AI summary
A system and related method for improving tire uniformity includes identifying at least one candidate process effect and a corresponding process harmonic number for each process effect. A given uniformity parameter, such as radial or lateral run-out, balance, mass variation, radial lateral or tangential force variation, is measured for each tire in a test set, such that the measurements contain tire harmonics as well as a process harmonics corresponding to each candidate process effect. Rectangular coordinate coefficients are electronically constructed for each said process harmonic, after which point the rectangular coordinates corresponding to each process harmonic are solved for (e.g., by using regression-based analysis). The magnitude of each said process harmonic is estimated, and a final magnitude estimate for each process harmonic can be determined by summarizing (e.g., by taking the average or median value) the respectively estimated magnitudes for each process harmonic across all test tires.