Rapid Reflective Facet Characterization Using Fringe Reflection Techniques

Abstract

Mirror facets for Concentrating Solar Power (CSP) systems have stringent requirements on slope accuracy in order to provide adequate system performance. This paper presents a newly developed tool that can characterize facets quickly enough for 100% inspection on a production line. A facet for a CSP system, specifically a dish concentrator, has a parabolic design shape. This shape will concentrate near-parallel rays from the sun to a point (or a line for trough systems). Deviations of surface slope from the design shape impact the performance of the system, either losing power that misses the target, or increasing peak fluxes to undesirable levels. Three types of facet slope errors can impact performance. The first is a focal length error, typically caused by springback in the facet forming process. In this case, the wavelength of the error exceeds the size of the facet, resulting in a parabola, but with the wrong focal length. The results in a slope error that is largely systematic across the facet when the measured slope is compared to the design slope. A second shape error, in which the period of the error is on the order of the length of the facet, manifests also as a systematic slope error. In this case, the facet deviates from a parabolic shape, but can be modeled with a higher order curve. Finally, the residual errors after a model is proposed are usually lumped through a Root Mean Square (RMS) process and characterized as the 1-sigma variation of a normal distribution. This usually characterizes the small-scale imperfections in the facet, and is usually called “slope error”. However, all of these deviations from design are in facet errors in the slope of the manufactured facet. The reported characterization system, named SOFAST (Sandia Optical Fringe Analysis Slope Tool) has a computer-connected camera that images the reflective surface, which is positioned so that it views the reflection of an active target, such as an LCD screen. A series of fringe patterns are displayed on the screen while images are captured. Using the captured information, the reflected target location of each pixel of mirror viewed can be determined, and thus through a mathematical transformation, the surface normal map can be developed. This is then fitted to the selected model equation, and the errors from design are characterized. The reported system currently characterizes point focus mirrors (for dish systems), but extensions to line focus facets are planned. While similar approaches have been explored, several key developments are presented here. The combination of the display, capture, and data reduction in one system allows rapid capture and data reduction. An “electronic boresight” approach is developed accommodating physical equipment positioning errors, making the system insensitive to setup errors. A very large number of points are determined on each facet, providing significant detail as to the location and character of the errors. The system is developed in MatLab, providing intimate interactions with the data as techniques and applications are developed. Finally, while commercial systems typically resolve the data to shape determination, this system concentrates on slope characterization and reporting, which is tailored to the solar applications. This system can be used for facet analysis during development. However, the real payoff is in production, where complete analysis is performed in about 10 seconds. With optimized coding, this could be further reduced.

Accurate calibration of geometrical error in reflective surface testing based on reverse Hartmann test

“…1(b), the point light source is replaced by a CCD camera with a finite size of aperture to detect the light reflected from test surface and the detector is replaced by an illumination screen. To obtain the one-to-one correspondence between the illumination screen pixel and the reflection region on test surface, the sinusoidal fringes illumination and phase shifting method can be applied in reverse Hartmann test [15]. In the reflective surface testing based on reverse Hartmann test, the surface error can be measured according to the virtual "null" testing, in which ray tracing of the test system model obtained from the measured system geometry is performed.…”

IEA SHC Task 49/IV - Deliverable A3.1 - Guideline on testing procedures for collectors used in solar process heat

“…The method consists of measuring the reflection of static or dynamic sinusoidal pattern on the reflector, computing the normal vectors from these reflections and calculate the local slope deviations values (Burke et al 2013;Heimsath et al 2011;Heimsath et al 2008). As with photogrammetry, the intercept factor can be calculated with ray tracing using the output normal vectors from the deflectometry method (Andraka et al 2009;Meiser et al 2015). A Guideline for measurement of the solar mirror shape accuracy was drafted by the Solar Paces Task III (SolarPaces Guideline 2013a).…”

Improving Optical Qualification of Solar Concentrator by FOCuS Tool

“…Particularly, Ulmer et al [3][4] have developed the technique for heliostat evaluation and mirror modules qualification. Andraka et al [5][6], through its SOFAST tool, has also made progresses in the implementation of this technique. Their approach is reported for point-focus concentrators.…”