The design flexibility of aerospace components has been revolutionized with the recent advancements in the manufacturing of composite structures and 3D printed components. Since the manufacturing process is dependent on the control environment, variations from the nominal conditions can result in the degraded surface quality of the manufactured part. It is critical to image these surface features at high-resolutions to enable process feedback, therefore, improving the overall efficiency and process control. In this context, we develop and demonstrate a structured illumination optical fiber probe with embedded speckles for high-resolution surface feature imaging of 3D printed and composite samples. The improved sectioning capabilities by modifying the structured illumination patterns is validated using a plane mirror sample. This method is envisaged for high-resolution surface feature imaging to improve the overall manufacturing process efficiency of critical components.
The surface roughness parameters encoded in a speckle pattern can be effectively extracted through correlation experiments. In the case of spectrally correlated speckle images, the degree of decorrelation arises from wavelength difference in the laser light irradiated on the surface. To obtain accurate results in such methodology, a proper design of experiments is important due to more than one parameter involved in the experiment. Here, experimental investigations and parametric studies of surface roughness measurements using spectral speckle correlation methodology are presented, considering the potential variables in the system. The sources of error and factors affecting the accuracy in measurement are identified and the experimental results obtained from standard calibration plate samples are presented.
In manufacturing engineering the surface finish of a machined component is of fundamental importance in order to ensure its performance. A non-contact and non-destructive device based on optical technique, is a promising alternative to stylus based device for carrying out measurement of surface quality. In addition to this, in situ monitoring of surface roughness on a workpiece is an important requirement in modern machining process, since it would increase on-line machining rate and consequently productivity. Here, measurement approaches and system configuration for surface roughness measurement using laser speckle intensity and contrast are discussed. The technique would allow full-field measurement over sample of interest having both rough and shiny surface properties. Measurement data on standard calibration plates is presented with details on the measurement accuracy and reliability.
A speckle pattern is a direct fingerprint of surface height variation on the sample. In this paper, angular speckle correlation technique is applied to estimate surface roughness Ra of an additive manufactured sample with different surface roughness Ra values varying from 5μm to 20μm. Feasibility study is conducted to evaluate the correct incidence and the change in incidence angle for angular speckle correlation. Speckle correlation is computed from two speckle images that are recorded at two different incidence angles on the rough surface and surface roughness information is gleaned. Test results in terms of surface roughness measurement from standard calibration plate and additive layer manufactured samples are presented.
Surface characterization of the working components has always been a subject of interest among researchers and industry specialists. Especially in the aerospace industry where the aerodynamic capabilities are largely altered by the surface quality of the component of interest, there remains an extensive need for developing systems for effectively characterizing the surface quality. To realize an optical based non-contact and an in-line surface roughness measurement system, it is essential to understand the relationship between the quality of the surface and statistical parameter of the reflected speckles. The range of the measurement system being proportional to the wavelength of light used makes the analysis fundamentally important in order to understand the properties of speckles at a different wavelength. In this context, this paper examines the nature of the formed IR speckles from three different diffusers by analyzing their raw structure. Image processing algorithms that are developed study the different parameters of the 8-bit binary speckles, namely, the fractal property and number of connecting components. The paper also discusses the future work direction on relating the proposed analysis to derive the algorithm required for evaluating the surface finish parameters.
The use of carbon fiber-reinforced polymer (CFRP) composite materials in the aerospace industry have far improved the load carrying properties and the design flexibility of aircraft structures. A high strength to weight ratio, low thermal conductivity, and a low thermal expansion coefficient gives it an edge for applications demanding stringent loading conditions. Specifically, this paper focuses on the behavior of CFRP composites under stringent thermal loads. The properties of composites are largely affected by external thermal loads, especially when the loads are beyond the glass temperature, Tg, of the composite. Beyond this, the composites are subject to prominent changes in mechanical and thermal properties which may further lead to material decomposition. Furthermore, thermal damage formation being chaotic, a strict dimension cannot be associated with the formed damage. In this context, this paper focuses on comparing multiple speckle image analysis algorithms to effectively characterize the formed thermal damages on the CFRP specimen. This would provide us with a fast method for quantifying the extent of heat damage in carbon composites, thus reducing the required time for inspection. The image analysis methods used for the comparison include fractal dimensional analysis of the formed speckle pattern and analysis of number and size of various connecting elements in the binary image.
Gradient-Index (GRIN) lenses are characterized by its small diameter and length, enabling them to be an effective lens for an integrated probe based imaging system. For a speckle-based surface metrology system, the imaging lens plays an important role in deciding the statistical dimensions of the speckles. In such cases, the design and simulation of the lens system would be a key process to better the performance of the lensed imaging fiber probe. In this context, this paper focuses on the design of lensed fiber probes for a speckle-based surface metrological imaging system that can find intra cavity interrogation applications. Different optical properties of GRIN lenses and imaging fibers are considered while designing the final probe distal end to meet the targeted specifications. Singlet GRIN lens configuration is analyzed for a front view configuration and a parameter optimization has been carried out to obtain the specifications including the field-of-view, resolution, working distance and magnification.
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