3-D measurement of solder paste using two-step phase shift profilometry

A two-step phase shift profilometry method (2-step PSP) with prefiltering and postfiltering stages is proposed to reconstruct the 3-D profile of solder paste. Two sinusoidal patterns which are π-out-of-phase are used in the 3-D reconstruction. The new method uses only two fringe patterns rather than four as the four-step phase shift profilometry (4-step PSP). In Fourier transform profilometry (FTP), a bandpass filter is required to extract the fundamental spectrum from the background and higher order harmonics due to camera noise and imperfectness of the pattern projector. By using two π-out-of-phase sinusoidal fringe patterns, the background term can be eliminated directly by taking the average of the two fringe patterns. The fringe pattern which is close to its ideal form can also be recovered from the averaging process. Prefiltering is utilized in filtering raw images to remove noise causing higher order harmonics. Hilbert transform is then used to obtain the in-quadrate component of the processed fringe pattern. Postfiltering is applied for reconstructing an appropriate 3-D profile. © 2008 IEEE.published_or_final_versio

Accidental Light Probes

Recovering lighting in a scene from a single image is a fundamental problem in computer vision. While a mirror ball light probe can capture omnidirectional lighting, light probes are generally unavailable in everyday images. In this work, we study recovering lighting from accidental light probes (ALPs) -- common, shiny objects like Coke cans, which often accidentally appear in daily scenes. We propose a physically-based approach to model ALPs and estimate lighting from their appearances in single images. The main idea is to model the appearance of ALPs by photogrammetrically principled shading and to invert this process via differentiable rendering to recover incidental illumination. We demonstrate that we can put an ALP into a scene to allow high-fidelity lighting estimation. Our model can also recover lighting for existing images that happen to contain an ALP.Comment: CVPR2023. Project website: https://kovenyu.com/ALP

Analysis of the inspection of mechanical parts using dense range data

More than ever, efficiency and quality are key words in modern industry. This situation enhances the importance of quality control and creates a great demand for cheap and reliable automatic inspection systems. Taking into account these facts and the demand for systems able to inspect the final shape of machined parts, we decided to investigate the viability of automatic model-based inspection of mechanical parts using the dense range data produced by laser stripers. Given a part to be inspected and a corresponding model of the part stored in the model data base, the first step of inspecting the part is the acquisition of data corresponding to the part, in our case this means the acquisition of a range image of it. In order to be able to compare the part image and its stored model, it is necessary to align the model with the range image of the part. This process, called registration, corresponds to finding the rigid transformation that superposes model and image. After the image and model are registered, the actual inspection uses the range image to verify if all the features predicted in the model are present and have the right pose and dimensions. Therefore, besides the acquisition of range images, the inspection of machined parts involves three main issues: modelling, registration and inspection diagnosis. The application, for inspection purposes, of the main representational schemes for modelling solid objects is discussed and it is suggested the use of EDT models (see [Zeid 91]). A particular implementation of EDT models is presented. A novel approach for the verification of tolerances during the inspection is proposed. The approach allows not only the inspection of the most common tolerances described in the tolerancing standards, but also the inspection of tolerances defined according to Requicha's theory of tolerancing (see [Requicha 83]). A model of the sensitivity and reliability of the inspection process based on the modelling of the errors during the inspection process is also proposed. The importance of the accuracy of the registration in different inspections tasks is discussed. A modified version of the ICP algorithm (see [Besl &; McKay 92]) for the registration of sculptured surfaces is proposed. The maximum accuracy of the ICP algorithm, as a function of the sensor errors and the number of matched points, is determined. A novel method for the measurement and reconstruction of waviness errors on sculp¬ tured surfaces is proposed. The method makes use of the 2D Discrete Fourier Transform for the detection and reconstruction of the waviness error. A model of the sensitivity and reliability of the method is proposed. The application of the methods proposed is illustrated using synthetic and real range image

3D reconstruction, classification and mechanical characterization of microstructures

Modeling and classifying 3D microstructures are important steps in precise micro-manipulation. This thesis explores some of the visual reconstruction and classification algorithms for 3D microstructures used in micromanipulation. Mechanical characterization of microstructures has also been considered. In particular, visual reconstruction algorithm (shape from focus - SFF) uses 2D image sequence of a microscopic object captured at different focusing levels to create a 3D range image. Then, the visual classification algorithm takes the range image as an input and applies a curvature-based segmentation method, HK segmentation, which is based on differential geometry. The object is segmented into surface patches according to the curvature of its surface. It is shown that the visual reconstruction algorithm works successfully for synthetic and real image data. The range images are used to classify the surfaces of the micro objects according to their curvatures in the HK segmentation algorithm. Also, a mechanical property characterization technique for cell and embryo is presented. A zebrafish embryo chorion is mechanically characterized using cell boundary deformation. Elastic modulus and developmental stage of the embryo are obtained successfully using visual information. In addition to these, calibrated image based visual servoing algorithm is experimentally evaluated for various tasks in micro domain. Experimental results on optical system calibration and image-based visual servoing in micropositioning and trajectory following tasks are presented

MESOSCALE MICROSTRUCTURE EVOLUTION, RELIABILITY AND FAILURE ANALYSIS OF HIGH TEMPERATURE TRANSIENT LIQUID PHASE SINTERING JOINTS

The continuous increase in application temperature of power electronic devices, due to the growing power density, miniaturization, and functionality in military and commercial applications, requires new packaging technologies with high temperature and reliability capabilities. Currently, the traditional maximum allowable temperature of power electronics (125°C) is a limiting factor for high temperature applications, such as space exploration, drilling, avionics, and electronic vehicles. Substitution of Silicon devices with wide bandgap (e.g., SiC) devices has extended the maximum allowable temperatures to 475 ̊C. However, this created the need for robust high temperature packaging materials, especially interconnects and attachments. High temperature solders are often too expensive, too brittle, or environmentally toxic to be used, leading to increased study of low temperature joining techniques, such as solid phase sintering and Transient Liquid Phase Sintering (TLPS), for producing high temperature stable attachments. TLPS is an emerging electronic interconnect technology enabling the formation of high temperature robust joints between metallic surfaces at low temperatures by the consumption of a transient, low temperature, liquid phase to form high temperature stable intermetallic compounds (IMCs). The performance and durability of these materials strongly depend on their microstructure, which is determined by their processing. The complicated process of IMC formation through eutectic solidification and the extensive number of parameters affecting the final microstructure make it impractical to experimentally study the effect of each factor. In this work, phase field modeling of the microstructure of TLPS materials fabricated by different processing methods will be conducted. Phase-field modeling (PFM) is a powerful thermodynamic consistent method in mesoscale modeling that simulates the evolution of intermetallic compounds during the solidification process, providing insight into the final microstructure. Application of this method facilitates the optimization of influential processing factors. Efforts will also be conducted to identify failure modes and mechanisms experimentally under dynamic, power and thermal cycling loads as a function of critical microstructural features, facilitating the optimization of joining parameters to obtain higher durability TLPS interconnections. The objective of this dissertation is to provide an insight into the processing of a reliable high temperature TLPS and facilitate their application in power electronic industries

Robust density modelling using the student's t-distribution for human action recognition

The extraction of human features from videos is often inaccurate and prone to outliers. Such outliers can severely affect density modelling when the Gaussian distribution is used as the model since it is highly sensitive to outliers. The Gaussian distribution is also often used as base component of graphical models for recognising human actions in the videos (hidden Markov model and others) and the presence of outliers can significantly affect the recognition accuracy. In contrast, the Student's t-distribution is more robust to outliers and can be exploited to improve the recognition rate in the presence of abnormal data. In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement in classification accuracy. © 2011 IEEE

From Field to Failure: Detecting and Understanding Reliability Defects in Crystalline Silicon Photovoltaics

Severe pollution levels and the growing influence of climate change have shown that dirty energy sources need renewable and sustainable replacements. The field of photovoltaics (PV) has grown substantially over the years from a niche space solar market to a commodity in large part due to improvements in reliability. Reliability of all materials in a PV module must be considered. The industry has seen an explosion of innovation in cell interconnection technologies with significant market penetration in the past several years. These emerging, less mature technologies require more reliability information to guide improvements. Degradation studies of long-term outdoor exposure and accelerated stress testing provide the samples, but a comprehensive characterization suite is necessary for impactful results. The state of the art for characterization is highly valuable yet incomplete. This work presents a multiscale, multicomponent process that provides information on device physics, polymer performance, thermal signatures, chemical composition, and degradation mechanisms, as well as advancements in electrical performance and defect localization. A comprehensive characterization suite is proposed which expands upon conventional one-sun current-voltage (I-V) and high injection electroluminescence (EL) imaging to multi-irradiance I-V, suns-Voc, multi-injection EL imaging and analysis, IR thermography, and UV fluorescence imaging. A database of over 1000 I-V curve, high-injection EL image pairs is presented for public use. An analysis and measurement technique is developed using EL images at multiple injection levels to non-destructively extract dark I-V curves for each cell. These curves can be analyzed to extract device properties. A machine learning model is developed using annotated EL images for automated defect detection. The training set of 17,064 cell EL images is publicized for the industry\u27s benefit. While applicable to all module technologies, the focus of this work is on applying this expansion on characterization to studying interconnection and contact degradation. Several interconnection technologies are studied with varying results. Each technology is shown to have distinct advantages and disadvantages with respect to performance and reliability. Modules are studied that have undergone accelerated tests and outdoor exposure. It is shown that full interconnection separation influences degradation differently depending on location of failure, though requires many failures before significant performance losses are evident. In another study, a model is developed for the mechanism behind front contact corrosion in damp heat degraded modules. A coring process is developed to extract cell samples which allows materials characterization. Results demonstrate that the primary mechanism is based on Sn diffusion from interconnection ribbons via acetic acid and moisture. One study examines a system of modules exposed in Florida for 10 years showing rear interconnect corrosion at the Ag/solder interface. Intermetallic compound formation led to reduced carrier transport and contact embrittlement leading to fatigue failure susceptibility. Another study investigates four different interconnection technologies before, during, and after stages of different accelerated stress protocols. Five-busbar ribbon, shingled, soldered wire, and laminated wire technologies underwent mechanical loading, humidity freeze, damp heat, and thermal cycling tests. Laminated wire performed the best overall though showed some features in EL imaging that have not yet been published. In the final study presented, a system of heterojunction modules from a system in Florida after 10 years exposure show resistive degradation. Device and materials characterization shows recombination and resistive losses, with resistive losses due corrosion at the intrinsic a-Si/c-Si interface

A new metallization technology for solar cells application

This Ph.D. thesis is focused on the development and optimization of front and rear side metallization of industrial silicon solar cells. The commonly adopted screen-printed silver metallization has several well-known issues, such as low contact resistance, moderate bulk conductivity and high cost. The approach of this work allows complete silver replacement, both on the front and the rear sides. The development of such a new technology is divided into several parts, each resulting in appropriate feedback in terms of solar cell operation parameters. A detailed investigation of the aluminum-silicon interdiffusion that occurs during the firing process of screen-printed aluminum layer usually deposited onto the rear of solar cells is reported. This process is very important because it affects solar cell operation and performance through back-surface field passivation. In this study different screen-printing aluminum pastes, differing one from each other in aluminum particle dimensions and glass frit composition, are evaluated in terms of their bulk resistivity, contact resistance to silicon, back surface field depth and solar cell performance. Finally, this study allowed to reveal certain dependences between pastes parameters and their effect on solar cells and to develop useful recommendations for better solar cell performance. In this work, a new metallization technology is based on an electroplating technique, which for a real industrial application, however, has some critical issues as throughput, floor space, quantity of liquid to manage and the necessity to use some masking technique, such as photolithography. These issues are strongly influencing the metallization technology cost, making it not economically convenient respect silver screen-printing technology. For this purpose, the proposed metallization technique is based on a novel dynamic liquid drop/meniscus (DLD/DLM) technique able to solve both issues. In this work DLD/DLM technique is studied for possible application in a new rear side metallization technology for solar cells, allowing localized formation of solder pads without any use of photolithography, limiting the cost of the process mainly to the cost of materials, such as nickel and tin, which are significantly cheaper than a silver counterpart that is currently adopted by the industry. The cost reduction is not a single advantage of the proposed technology. An efficiency improvement of up to 0.5 %abs is obtained due to a better back-surface field conditions. The development of a new front side metallization is based on a new approach which introduces a layer of mesoporous silicon helpful for further creation of nickel-copper electrical contacts to the emitter region of a solar cell. Process conditions of mesoporous silicon formation and further electroplating steps are studied and optimized in terms of contact resistance and adhesion of such a contacts, in order to guarantee a beneficial influence for solar cells fabricated with the new metallization approach. As for combination of both front and rear side metallization technologies, together, they result in complete silver removal from a metallization technology of a solar cell with a feasible efficiency enhancement of up to 1 %abs