Stress and strain measurement of high density polyethylene (HDPE) fuel tanks under dynamic loading is challenging. Motion tracking combined with computer vision was employed to evaluate the strain in an HDPE fuel tank being dynamically loaded with a crash pulse. Traditional testing methods such as strain gages are limited to the small strain elastic region and HDPE testing may exceed the range of the strain gage. In addition, strain gages are limited to a localized area and are not able to measure the deformation and strain across a discontinuity such as a pinch seam. Other methods such as shape tape may not have the response time needed for a dynamic event. Motion tracking data analysis was performed by tracking the motion of specified points on a fuel tank during a dynamic test. An HDPE fuel tank was mounted to a vehicle section and a sled test was performed using a Seattle sled to simulate a high deltaV crash. Multiple target markers were placed on the fuel tank. The motion of these markers was captured using high speed video cameras. The high speed videos were processed using the OpenCV computer vision library. Using OpenCV, the high speed videos were imported, and the position of the central location of each target marker was extracted frame by frame from the high speed videos. Once the position was known, the strain was computed using the change in relative position between two marker positions. Results of the testing showed that the acceleration-induced strain is low, generally less than the material yield strain. It was noted that reliable and accurate results require that the camera be placed normal to, or at a shallow angle to, the points being tracked. In addition, curved surfaces lead to limited fidelity of strain data due to the varying focal length of the points being tracked and measurement increased sensitivity. This method is similar to a “typical” tensile test in which displacement is tracked between two pre-established points on a sample. As such, the methodology was replicated on a tensile specimen to validate the methodology.


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    Titel :

    Fuel Tank Dynamic Strain Measurement Using Computer Vision Analysis


    Weitere Titelangaben:

    Sae Int. J. Adv. and Curr. Prac. in Mobility


    Beteiligte:

    Kongress:

    WCX SAE World Congress Experience ; 2020



    Erscheinungsdatum :

    2020-04-14


    Format / Umfang :

    7 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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