Tire Uniformity via Re-indexed Harmonic Waveform Analysis
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Solution Overview
Problem
Conventional tire building methods often result in non-uniformities due to manufacturing variations, leading to periodic force variations that cause vibrations and discomfort in vehicles, with existing harmonic component estimation methods lacking accuracy and comprehensiveness.
Innovation Solution
A system and method to estimate candidate process harmonics in tire uniformity, involving measurement of multiple uniformity waveforms, re-indexing, and regression-based analysis to separate process harmonics from tire harmonics, allowing for adjustments to improve tire uniformity by opposing or modifying process harmonics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional tire building methods are used, then manufacturing simplicity is maintained, but tire uniformity deteriorates due to process harmonics and manufacturing variations
Solution Approach 1:
The uniformity waveform is segmented into multiple harmonic components through Fourier analysis, allowing individual identification and estimation of process harmonics. This segmentation enables targeted analysis of specific harmonic orders (e.g., 1st, 2nd, 3rd harmonics) that contribute to tire non-uniformity, resolving the contradiction by breaking down the complex uniformity problem into manageable spectral components.
Solution Approach 2:
A computer-based analysis system acts as an intermediary between manufacturing processes and quality outcomes. The system uses measurement waveforms from test tires as intermediaries to estimate process harmonic characteristics, which then inform adjustments to building processes. This intermediary analysis layer enables precision improvement without requiring direct complex intervention in each manufacturing step.
2Measurement precision
If multiple uniformity waveforms are measured and analyzed, then estimation accuracy of process harmonics is improved, but measurement and processing time increase
Solution Approach 1:
Multiple uniformity waveforms are measured and stored in advance before the estimation process. The system prepares a database of waveforms from multiple test tires measured under different conditions (loaded/unloaded, clockwise/counterclockwise rotation). This preliminary data collection enables comprehensive harmonic estimation without time pressure during the actual analysis phase, resolving the contradiction between thorough measurement and time efficiency.
Solution Approach 2:
Manual measurement and analysis methods are replaced with automated computer-based processing. The computer system automatically performs Fourier analysis, harmonic estimation, and waveform processing algorithms, substituting mechanical/manual operations with electronic computation. This substitution dramatically reduces processing time while maintaining or improving measurement precision through consistent algorithmic application.
3Manufacturing precision
If process harmonics are not separated from tire harmonics, then analysis simplicity is maintained, but uniformity improvement effectiveness deteriorates
Solution Approach 1:
The analysis system dynamically adapts to different harmonic scenarios by processing multiple waveforms with varying characteristics. The computer algorithm adjusts its analysis based on the specific harmonic content present in each waveform set, identifying process harmonics that may vary in magnitude and phase across different measurement conditions. This dynamic approach enables effective separation of process and tire harmonics without requiring fixed, overly complex predetermined analysis structures.
Solution Approach 2:
The system exploits parameter changes in harmonic characteristics under different measurement conditions to separate process harmonics from tire harmonics. By measuring waveforms in different states (loaded/unloaded, different rotation directions) and observing how harmonic parameters (magnitude, phase, frequency) change differently for process versus tire harmonics, the system can distinguish and isolate process harmonic contributions. This parameter-based differentiation resolves the contradiction by using natural variations in measurement parameters to simplify the separation problem.
Data Source
AI summary
Systems and methods for improving tire uniformity include identifying at least one candidate process harmonic and corresponding period. A set of uniformity waveforms is then collected for each test tire in a set of one or more test tires. To provide better data for analysis, the collection of waveforms may include multiple waveforms including measurements obtained before and/or after cure, in clockwise and/or counterclockwise rotational directions, and while the tire is loaded and/or unloaded. The uniformity waveforms may be re-indexed to the physical order of the at least one candidate process harmonic, and selected data points within the waveforms may optionally be deleted around a joint effect or other non-sinusoidal effect. The re-indexed, optionally partial, waveforms may then be analyzed to determine magnitude and azimuth estimates for the candidate process harmonics. Aspects of tire manufacture may then be modified in a variety of different ways to account for the estimated process harmonics.