3,121 research outputs found

    Repair of metallic components using hybrid manufacturing

    Get PDF
    Many high-performance metal parts users extend the service of these damaged parts by employing repair technology. Hybrid manufacturing, which includes additive manufacturing (AM) and subtractive manufacturing, provides greater build capability, better accuracy, and surface finish for component repair. However, most repair processes still rely on manual operations, which are not satisfactory in terms of time, cost, reliability, and accuracy. This dissertation aims to improve the application of hybrid manufacturing for repairing metallic components by addressing the following three research topics. The first research topic is to investigate and develop an efficient best-fit and shape adaption algorithm for automating 3D models\u27 the alignment and defect reconstruction. A multi-feature fitting algorithm and cross-section comparison method are developed. The second research topic is to develop a smooth toolpath generation method for laser metal deposition to improve the deposition quality for metallic component fabrication and repair. Smooth connections or transitions in toolpath planning are achieved to provide a constant feedrate and controllable deposition idle time for each single deposition pass. The third research topic is to develop an automated repair process could efficiently obtain the spatial information of a worn component for defect detection, alignment, and 3D scanning with the integration of stereo vision and laser displacement sensor. This dissertation investigated and developed key technologies to improve the efficiency, repair quality, precision, and automation for the repair of metallic components using hybrid manufacturing. Moreover, the research results of this dissertation can benefit a wide range of industries, such as additive manufacturing, manufacturing and measurement automation, and part inspection --Abstract, page iv

    Heterogeneous Object Modeling for Rapid Prototyping

    Get PDF

    From 3D Models to 3D Prints: an Overview of the Processing Pipeline

    Get PDF
    Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044

    Study of time-lapse processing for dynamic hydrologic conditions

    Get PDF
    The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies

    A Robust Segmentation for Malaria Parasite Detection of Thick Blood Smear Microscopic Images

    Get PDF
    Parasite Detection on thick blood smears is a critical step in Malaria diagnosis. Most of the thick blood smear microscopic images have the following characteristics: high noise, a similar intensity between background and foreground, and the presence of artifacts. This situation makes the detection process becomes complicated. In this paper, we proposed a robust segmentation technique for malaria parasite detection of microscopic images obtained from various endemic places in Indonesia. The proposed method includes pre-processing, blood component segmentation using intensity slicing and morphological operation, blood component classification utilising rule based on properties of parasite candidates, and parasite candidate formation. The performance was evaluated on 30 thick blood smear microscopic images. The experimental results showed that the proposed segmentation method was robust to the different condition of image and histogram. It reduced the misclassification error and relative foreground error by 2.6% and 45.5%, respectively. Properties addition to blood component classification increased the system precision. Average of precision, recall, and F-measure of the proposed method were all 86%. It is proven that the proposed method is appropriate to be used for malaria parasites detection

    Automatic Error Detection in 3D Pritning using Computer Vision

    Get PDF
    During recent years Additive Manufacturing Technology, or 3D Printing, has become extremely popular. 3D printing is being actively used in fields ranging from rapid prototyping and rapid manufacturing to Bio-printing for tissue manufacturing. However, it is a very time consuming process as a single object, depending on its size and complexity, may take from only a couple of hours to several days to print. In many cases, errors occurs in the middle of a printing process due to misalignment of the 3D printed object, slicing errors or blocked filament extrusion, causing a complete failure of the process. During longer printing processes such errors may occur several hours before we are able to detect them, and a lot of time and material are wasted. If we are able to detect these errors automatically as they occur we may be able to interrupt the process and save both time and material. Severe damage may be caused to a 3D printer if layers of material are continuously added to an object that is misaligned or has detached from the build plate. In this thesis we investigate the possibilities of using traditional Computer Vision algorithms and image processing techniques to automatically detect these errors as they occur. We built a prototype using two different camera angles to analyze both the first layer from a top-down view and the subsequent layers by placing the second camera in front of the build plate. In one of the modules developed in our prototype we managed to compare the 3D printed bottom layer with a simulation of the same layer to detect deviations from the CAD model.Masteroppgave i Programutvikling samarbeid med HVLPROG399MAMN-PRO
    • …
    corecore