Optical System Peak Acceleration Correction Algorithm
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Solution Overview
Problem
Optical systems, such as FLIR systems, face challenges in accurately capturing peak acceleration due to shock frequencies exceeding the sampling rate of inertial measurement units (IMUs), leading to incomplete acceleration information and potential misalignment.
Innovation Solution
A method that calculates a corrected peak acceleration by averaging the maximum acceleration value with its nearest adjacent value and adjusting for the difference, using constants to optimize accuracy, allowing for realignment determination beyond the IMU's sampling limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the IMU sampling rate is increased to capture peak acceleration accurately, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
A correction algorithm acts as an intermediary between the IMU data and the true peak acceleration value. The algorithm uses adjacent acceleration values and correction factors to estimate the actual peak, bridging the gap between limited sampling capability and accurate measurement requirements without hardware changes
Solution Approach 2:
The system changes the parameter of acceleration measurement from direct sampling to corrected estimation. By applying correction factors derived from adjacent values and system characteristics, the measurement accuracy is improved without changing the fundamental sampling rate parameter of the IMU
2Measurement precision
If the IMU sampling rate is increased to capture shock frequencies, then measurement precision improves, but loss of time increases
Solution Approach 1:
The system uses only the necessary adjacent values (a limited portion of data) rather than processing entire datasets. This partial action approach provides sufficient correction accuracy without the excessive time cost of comprehensive analysis, achieving a balance between precision and processing speed
3Reliability
If acceleration values are smoothed to reduce noise, then reliability improves, but measurement precision of peak acceleration deteriorates
Solution Approach 1:
The correction algorithm is applied preliminarily to identify and compensate for peak attenuation before final measurement decisions are made. By pre-correcting the peak values using adjacent data and correction factors, the system maintains both noise reliability and peak accuracy in the final measurement
Data Source
AI summary
A method includes accessing a plurality of acceleration values generated by an inertial measurement unit of an optical system. The method includes identifying a maximum acceleration value (the accessed acceleration value having the greatest absolute value), identifying one or more adjacent acceleration values (the accessed acceleration value adjacent in time to the maximum acceleration value), and identifying a nearest adjacent acceleration value (the adjacent acceleration value having the value nearest the maximum acceleration value). The method includes determining a corrected peak acceleration. The corrected peak acceleration is the sum of a first value corresponding to an average of the maximum acceleration value and the nearest adjacent acceleration value and a second value corresponding to the product of a correction value and the difference between the maximum acceleration value and the nearest adjacent acceleration value. The method includes determining whether the corrected acceleration value exceeds a predefined threshold acceleration value.