Non-intrusive Optical Heliostat Error Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Accurately determining the quality of heliostat surface shape at different orientations is challenging in manufacturing and operational settings of concentrating solar power (CSP) and concentrated solar thermal (CST) plants, affecting the efficiency of mirror optics.
Innovation Solution
A method and system using image processing and computer vision to analyze images of a target reflected on a heliostat, creating a model of the target, and determining errors by projecting reflected points onto the model, allowing for non-invasive surface slope mapping without physical contact, utilizing a processor and camera to solve for camera location and calculate surface slope differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional contact-based measurement methods are used to determine heliostat surface shape, then measurement accuracy may be improved, but the complexity of the measurement system and the time required for measurement increase
Solution Approach 1:
The patent replaces traditional mechanical contact-based measurement systems with an optical measurement system. A camera captures images of a target reflected in the heliostat surface, and image processing algorithms analyze the reflected patterns to determine surface shape and errors. This substitution eliminates mechanical contact, reducing system complexity and measurement time while maintaining high precision through computational analysis of optical reflections.
Solution Approach 2:
The patent creates a digital model (copy) of the target object and uses image processing to generate a virtual representation of the heliostat surface. By analyzing the reflected image of the target and comparing it to the known target geometry, the system creates a digital copy of the surface shape, enabling accurate measurement without physical contact or complex mechanical scanning systems.
2Loss of information
If physical contact measurement methods are used on heliostat surfaces, then detailed surface information can be obtained, but the measurement process becomes intrusive and may affect the operational status of the heliostat
Solution Approach 1:
The patent replaces intrusive mechanical measurement methods with non-contact optical imaging. A camera captures reflected images of a target on the heliostat surface without physical contact, allowing measurements to be taken while the heliostat remains in its operational position and orientation. This maintains operational continuity while gathering complete surface quality information through image analysis.
Solution Approach 2:
The heliostat surface itself serves as the measurement tool by reflecting the target image. The natural reflective properties of the heliostat surface are utilized to capture its own geometric information through the reflected target pattern. This self-service approach eliminates the need for external mechanical probes or contact-based measurement devices, enabling non-intrusive measurement during normal operation.
3Measurement precision
If multiple measurement points are taken to accurately map the entire heliostat surface, then measurement precision improves, but the time required for measurement increases
Solution Approach 1:
The patent transitions from one-dimensional point-by-point mechanical scanning to two-dimensional simultaneous optical imaging. By capturing the entire reflected target image in a single photograph, the system measures all surface points across the heliostat aperture simultaneously rather than sequentially. This dimensional change from sequential scanning to parallel imaging dramatically reduces measurement time while maintaining comprehensive surface coverage and precision through image processing algorithms.
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
Enables precise and non-invasive determination of heliostat surface errors, improving quality control in manufacturing and ensuring efficient mirror optics performance in CSP and CST plants.
Implementation Method 1
receiving, using the processor, an image of the target reflected on a heliostat
Data Source
AI summary
Non-invasively detecting or determining heliostat surface opto-mechanical errors (e.g., surface slope, canting, and/or tracking) is described. At least one image captured of a target reflected on a heliostat surface may be used to determine the heliostat error. This may be based on the distortion of the target reflected on the heliostat compared to the expected reflection of the target on the heliostat. Image processing and computer vision may be utilized to generate a surface slope map of the heliostat and determine the error compared to an “ideal” model of the heliostat.