<p>Digital image correlation (DIC) systems such as Zeiss-Aramis are widely used for deformation and strain analysis in forming experiments but are associated with high acquisition and operational costs. This study investigates the feasibility of using consumer-grade smartphone cameras as a low-cost alternative for deformation analysis based on image tracking and optical flow techniques. Experiments were conducted on the MUC-Test and a uniaxial tensile test. Feature point tracking and dense optical flow methods were applied to image sequences acquired using an iPhone camera to estimate in-plane displacements and crack loci. The resulting displacement fields were compared to results from images obtained via a commercial Zeiss-Aramis DIC system. While a full three-dimensional reconstruction and strain mapping could not be achieved due to limitations in camera calibration, synchronization, and image resolution, the smartphone-based approach successfully captured global deformation trends, crack initiation and proved to maintain sharp images without blurring during deformation along the camera axis. Although not a replacement for established DIC systems, the proposed approach offers a promising low-cost tool for preliminary analysis and monitoring in production processes, where cost-effective and fast analysis tools are required.</p>

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Smartphone-based Deformation Analysis Applied to the MUC-Test and the Tensile Test

  • Paul Richter,
  • Edgar Marker,
  • Tianyou Liu,
  • Michael Ott,
  • Christoph Hartmann

摘要

Digital image correlation (DIC) systems such as Zeiss-Aramis are widely used for deformation and strain analysis in forming experiments but are associated with high acquisition and operational costs. This study investigates the feasibility of using consumer-grade smartphone cameras as a low-cost alternative for deformation analysis based on image tracking and optical flow techniques. Experiments were conducted on the MUC-Test and a uniaxial tensile test. Feature point tracking and dense optical flow methods were applied to image sequences acquired using an iPhone camera to estimate in-plane displacements and crack loci. The resulting displacement fields were compared to results from images obtained via a commercial Zeiss-Aramis DIC system. While a full three-dimensional reconstruction and strain mapping could not be achieved due to limitations in camera calibration, synchronization, and image resolution, the smartphone-based approach successfully captured global deformation trends, crack initiation and proved to maintain sharp images without blurring during deformation along the camera axis. Although not a replacement for established DIC systems, the proposed approach offers a promising low-cost tool for preliminary analysis and monitoring in production processes, where cost-effective and fast analysis tools are required.