2,725 research outputs found

    Non-contact method to assess the surface roughness of metal castings by 3D laser scanning

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    This paper defines a methodology to estimate the surface roughness of metal castings by 3D laser scanning. The proposed method applies Principal Component Analysis (PCA) which transforms the point cloud of the casting surface into an orthogonal coordinate system. Using this coordinate system, the Root Mean Square (RMS) deviation of the surface peaks and valleys is estimated. This method is used to analyze the factors affecting point cloud generation and evaluate the technique used to obtain a consistent roughness parameter. A correlation curve was then established by plotting the roughness parameters obtained by PCA method against the corresponding root-mean square (RMS) readings on the cast micro finish comparator. Surface roughness measurements is performed on SCRATA ‘A’ plates and independent casting surfaces; whose roughness is previously unknown; is measured and the results are found to be consistent with the roughness values of the known cast micro finish comparator. The results from the surface comparators and areas of the scanned castings are also validated using a laser interferometer. The proposed method provides a fast, accurate and automated way of calculating surface roughness from the point cloud data. Its repeatability and versatility compares favorably with existing methods and would aid process control and standard interpretation

    Optical Coherence Tomography guided Laser-Cochleostomy

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    Despite the high precision of laser, it remains challenging to control the laser-bone ablation without injuring the underlying critical structures. Providing an axial resolution on micrometre scale, OCT is a promising candidate for imaging microstructures beneath the bone surface and monitoring the ablation process. In this work, a bridge connecting these two technologies is established. A closed-loop control of laser-bone ablation under the monitoring with OCT has been successfully realised

    Fixtureless automated incremental sheet metal forming

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    Die-based forming is a technology used by many industries to form metal panels. However, this method of forming lacks flexibility and cost effectiveness. In such cases, manual panel beating is typically undertaken for incremental forming of metal panels. Manual panel forming is a highly skilled operation with very little documentation and is disappearing due to non-observance and a lack of interest. Confederation of British Metal forming (CBM) and Institution of Sheet Metal Engineering (ISME) have realised the need for capturing and understanding manual skills used by panel beaters to preserve the knowledge. At the same time, industries seek for alternative panel forming solutions to produce high quality and cost-effective parts at low volume and reduce the repetitive, yet adaptive parts of the panel forming process to free up skilled workers to concentrate on the forming activities that are more difficult to automate. Incremental forming technologies, currently in practice, lack adaptability as they require substantial fixtures and dedicated tools. In this research a new proof-of-concept fixtureless automated sheet metal forming approach was developed on the basis of human skills captured from panel beaters. The proposed novel approach, named Mechatroforming®, consists of integrated mechanisms to form simple sheet metal parts by manipulating the workpiece using a robotic arm under a repetitive hammering tool. Predictive motion planning based on FEA was analysed and the manual forming skills were captured using a motion capture system. This facilitated the coordinated hammering and motion of the part to produce the intended shape accurately. A 3D measurement system with a vertical resolution of 50μm was also deployed to monitor the formation of the parts and make corrections to the forming path if needed. Therefore, the developed mechatronic system is highly adjustable by robotic motion and was closed loop via the 3D measurement system. The developed automated system has been tested rigorously, initially for bowl shape parts to prove the principle. The developed system which is 98% repeatable for depth and diameter, is able to produce targeted bowl shape parts with ±1% dimensional accuracy, high surface quality, and uniform material thickness of 0.95mm when tested with aluminium. It is envisaged that by further research, the proposed approach can be extended to form irregular and more complicated shapes that are highly in demand in various industries

    Impact of new instrumentation on advanced turbine research

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    A description is presented of an orderly test program that progresses from the simplest stationary geometry to the more complex, three dimensional, rotating turbine stage. The instrumentation requirements for this evolution of testing are described. The heat transfer instrumentation is emphasized. Recent progress made in devising new measurement techniques has greatly improved the development and confirmation of more accurate analytical methods for the prediction of turbine performance and heat transfer. However, there remain challenging requirements for novel measurement techniques that could advance the future research to be done in rotating blade rows of turbomachines

    Retinal identification

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