Polar Plot Imbalance Analysis for Rotating Components
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Solution Overview
Problem
Current manufacturing systems face challenges in accurately and efficiently analyzing balance measurements and identifying sources of imbalance during the manufacturing process, particularly in rotating components, where both magnitude and angular direction are critical.
Innovation Solution
A measurement system utilizing a two-dimensional polar plot to assess balance measurements, determining measurement error and product variation, and calculating a discrimination ratio to identify unknown causes of imbalance, while also applying pattern recognition and correlation analysis across multiple processing operations to pinpoint imbalance sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional balance measurement analysis is used, then basic imbalance detection is possible, but the ability to identify unknown causes of imbalance and validate measurement system capability is insufficient
Solution Approach 1:
The system performs repeated balance measurements on the same part multiple times and uses the variation between these repeated measurements to calculate measurement error and validate measurement system capability. This feedback mechanism allows the system to distinguish between true product variation and measurement system variation, thereby validating measurement precision while identifying unknown imbalance causes.
Solution Approach 2:
The patent replaces traditional mechanical balance analysis with a computational approach using polar plots and statistical analysis. By transforming balance measurements into polar coordinates and analyzing the distribution of measurements through correlation coefficients and discrimination ratios, the system achieves more sophisticated measurement validation and cause identification without additional physical measurement equipment.
2Reliability
If balance measurements are taken at multiple processing operations, then more comprehensive imbalance analysis is possible, but the complexity of analyzing and correlating measurements increases
Solution Approach 1:
The system segments the manufacturing process into distinct processing operations (e.g., casting, machining, welding) and collects balance measurements at each stage. By organizing measurements temporally and process-wise, the system can analyze the effect of each specific operation on imbalance without requiring complex analysis of all measurements simultaneously, thus managing complexity while improving reliability.
Solution Approach 2:
The patent introduces a temporal dimension to balance measurement analysis by taking measurements at multiple processing operations and correlating them. This transforms the analysis from a single-point measurement to a multi-dimensional approach that tracks imbalance evolution through the manufacturing process, improving source identification without proportionally increasing complexity through structured data organization.
3Measurement precision
If repeated measurements are taken to validate measurement system, then measurement precision improves, but measurement time and productivity decrease
Solution Approach 1:
The system performs a limited number of repeated measurements (e.g., three measurements) rather than exhaustive repeated measurements. This partial action approach provides sufficient statistical data to calculate meaningful measurement error and validate capability while minimizing the time required. The analysis uses the variation among these partial repeated measurements to achieve precision validation without excessive measurement time.
Data Source
AI summary
In some embodiments, a system uses a two-dimensional polar plot to analyze imbalance of components. On the two-dimensional polar plot imbalance magnitude and orientation are depicted relative to a reference. Some embodiments use the two-dimensional polar plot to assess measurement error for measurement devices and components. Some embodiments use the two-dimensional polar plot to determine patterns associated with processing operations to identify sources of imbalance from the manufacturing process. Some embodiments use the two-dimensional polar plot to determine correlations between processing operations to identify sources of imbalance.