Road Surface Sensor Calibration via Iterative Point Cloud Adjustment
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Solution Overview
Problem
Existing road surface inspection systems face challenges in accurately calibrating measuring elements over time due to temperature changes and varying measurement values across multiple sensors, leading to difficulties in accurately measuring road surface properties, especially on complex surfaces, which increases computing time and cost.
Innovation Solution
A method for calibrating measuring elements by setting a reference area, acquiring measurement values, producing point cloud data, and iteratively adjusting calibration values until the separation quantities from the reference plane are within a predetermined threshold, ensuring accurate and rapid calibration of all measuring elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration is preliminarily performed at manufacturing time, then initial measurement accuracy is achieved, but measurement values drift over time due to temperature changes and other factors
Solution Approach 1:
The patent performs calibration preliminarily by acquiring measurement values from all measuring elements on a reference road surface, determining calibration values before actual road surface measurement. This preliminary calibration action establishes a baseline that compensates for future drift caused by temperature changes and time elapsed, maintaining measurement accuracy without requiring frequent recalibration.
2Measurement precision
If smoothing process is performed on point cloud data to handle measurement variations, then measurement accuracy improves on flat surfaces, but computing time and cost increase significantly
Solution Approach 1:
The patent extracts only the necessary calibration information from point cloud data by determining calibration values for each measuring element based on measurement values acquired on a reference road surface. Instead of performing comprehensive smoothing on all point cloud data, the system extracts calibration parameters that can be applied to correct measurements, significantly reducing computing time while maintaining accuracy.
Solution Approach 2:
The calibration values are determined preliminarily before actual road surface measurement. By performing the calibration computation in advance on a reference surface and storing the calibration values, the system avoids the need to perform time-consuming smoothing processes during actual measurement operations, reducing computing time and cost.
3Measurement precision
If calibration values are determined for all measuring elements to compensate for variations, then measurement consistency across sensors improves, but calibration process complexity increases
Solution Approach 1:
The patent segments the calibration process by determining calibration values for each measuring element independently based on its measurement values on the reference road surface. Instead of performing a complex global calibration of the entire measuring apparatus, the system divides the calibration into individual element calibrations, simplifying the overall process while maintaining measurement consistency across all sensors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for rapid and simple calibration of measuring elements, enabling more accurate evaluation of road surface properties by reducing measurement variations and improving data processing efficiency, even on complex road surfaces.
Implementation Method 1
a plurality of measuring elements for emitting measuring light and receiving reflected light
Data Source
AI summary
A method for calibrating unevenness of a plurality of measuring elements in an apparatus for evaluating road surface property having a plurality of measuring elements repeats steps of computing separation quantities from a calibration reference plane on a reference area regarding all measuring elements; determining a measuring element where the separation quantity is maximum from among all the measuring element to calibrate the measuring element such that a difference between point cloud data produced from a measurement value of the measuring element where the separation quantity is maximum and the calibration reference plane becomes equal or less than a predetermined value, producing a new calibration reference plane from the measurement values of the measuring elements including the calibrated measuring element, until RMS of point cloud data does not change.