Department of Informatics, Modeling, Electronics and Systems Engineering, University of Calabria, 87036 Rende, Italy.
Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy.
Sensors (Basel). 2022 Apr 7;22(8):2839. doi: 10.3390/s22082839.
This paper addresses the problem of automatic quality inspection in assembly processes by discussing the design of a computer vision system realized by means of a heterogeneous multiprocessor system-on-chip. Such an approach was applied to a real catalytic converter assembly process, to detect planar, translational, and rotational shifts of the flanges welded on the central body. The manufacturing line imposed tight time and room constraints. The image processing method and the features extraction algorithm, based on a specific geometrical model, are described and validated. The algorithm was developed to be highly modular, thus suitable to be implemented by adopting a hardware-software co-design strategy. The most timing consuming computational steps were identified and then implemented by dedicated hardware accelerators. The entire system was implemented on a Xilinx Zynq heterogeneous system-on-chip by using a hardware-software (HW-SW) co-design approach. The system is able to detect planar and rotational shifts of welded flanges, with respect to the ideal positions, with a maximum error lower than one millimeter and one sexagesimal degree, respectively. Remarkably, the proposed HW-SW approach achieves a 23× speed-up compared to the pure software solution running on the Zynq embedded processing system. Therefore, it allows an in-line automatic quality inspection to be performed without affecting the production time of the existing manufacturing process.
本文通过讨论一种使用异构多核片上系统实现的计算机视觉系统的设计，解决了装配过程中的自动质量检测问题。这种方法应用于实际的催化转化器装配过程中，用于检测焊接在中心体上的法兰的平面、平移和旋转偏移。生产线施加了严格的时间和空间限制。本文描述并验证了基于特定几何模型的图像处理方法和特征提取算法。该算法被设计成高度模块化的，因此适合采用软硬件协同设计策略来实现。确定了最耗时的计算步骤，然后通过专用硬件加速器来实现。整个系统是在 Xilinx Zynq 异构片上系统上实现的，采用软硬件（HW-SW）协同设计方法。该系统能够检测焊接法兰相对于理想位置的平面和旋转偏移，最大误差分别低于一毫米和一度。值得注意的是，与在 Zynq 嵌入式处理系统上运行的纯软件解决方案相比，所提出的 HW-SW 方法实现了 23 倍的速度提升。因此，它允许在不影响现有制造过程生产时间的情况下进行在线自动质量检查。
