Surface Measurement Instrument Error Characterization
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Solution Overview
Problem
Surface measurement instruments face accuracy issues due to non-linearity in the relationship between measurement probe movement and signal response, caused by misalignment, transducer non-linearity, and finite probe size, which can result in systematic errors that are difficult to calibrate, especially when the position of reference objects is unknown.
Innovation Solution
The method involves obtaining two sets of calibration measurement data from overlapping paths of different reference objects, fitting a common model to characterize instrument error, which includes expected forms of error such as arcuate error, and using this model to correct measurements by determining a common error function that is independent of the measured surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If calibration is performed using a single reference object with unknown position, then the calibration process can be simplified, but the measurement accuracy deteriorates due to insufficient error characterization
Solution Approach 1:
The patent combines data from multiple reference objects (at least two) into a unified calibration process. By merging the calibration datasets and fitting a common error function to all data simultaneously, the system achieves both operational simplicity (single unified process) and high accuracy (comprehensive error characterization from multiple sources).
Solution Approach 2:
The calibration method uses multiple reference objects with different known forms to create a universal calibration process that can characterize various types of instrument errors (arcuate error, transducer non-linearity, probe size effects) simultaneously, making the calibration system more versatile and accurate without requiring separate calibration procedures for each error type.
2Reliability
If the measurement probe is made larger to improve signal response, then the transducer sensitivity improves, but the measurement accuracy deteriorates due to increased contact angle dependence and finite size effects
Solution Approach 1:
The calibration process using multiple reference objects provides feedback about the actual measurement errors introduced by the finite probe size. This feedback is used to adjust and refine the error function, compensating for the contact angle dependence and finite size effects, thereby maintaining measurement accuracy despite using a larger probe for improved signal response.
3Adaptability or versatility
If the measurement probe is made pivotable to accommodate surface variations, then the adaptability to different surface forms improves, but the measurement accuracy deteriorates due to arcuate error from non-linear movement paths
Solution Approach 1:
The patent applies preliminary calibration using multiple reference objects with known forms before actual measurements. This preliminary action characterizes the arcuate error and other systematic errors in advance, creating an error function that is then used to correct subsequent measurements. This allows the pivotable probe to maintain both its adaptability to surface variations and measurement accuracy through pre-characterized error compensation.
Data Source
AI summary
A method for characterising instrument error in a surface measurement instrument, comprising obtaining first calibration measurement data representing a known surface form of a first reference object and obtaining second calibration measurement data representing a known surface form of a second reference object. At least a portion of the second calibration measurement data represents a measurement range that overlaps with at least a portion of a measurement range of the first calibration measurement data. A common error function is obtained that characterises the instrument error.