基于数智化的FPGA检测技术研究

Research on FPGA Testing Technology Based on Digital Intelligence

摘要: 传统元器件检测方法依赖人工目检和单点功能测试，存在误差率大、覆盖率不足、效率低下等局限性，尤其在高密度FPGA、SOC芯片中，测试周期和成本已成为制约装备交付的关键瓶颈。在此技术困境下，数智化技术凭借数据驱动决策、智能协同处理的核心优势，正逐步重塑元器件检测领域的技术范式，推动该领域从传统人工主导模式向智能化、数字化方向加速转型，当前已进入技术迭代的关键窗口期。本文系统探讨了元器件检测技术面临的挑战与创新路径，结合机器学习、边缘计算等前沿检测技术，重点研究了FPGA测试的智能化解决方案。同时，基于元器件检测技术的发展，对当前FPGA测试流程做了优化，旨在外观检测、配置程序、测试向量方面进行速度和精度方面的提升。

Abstract: Traditional component testing methods rely on manual visual inspection and single-point functional testing, which have limitations such as high error rates, insufficient coverage, and low efficiency. Especially in the testing of high-density FPGA and SOC chips, the testing cycle and cost have become key bottlenecks restricting equipment delivery. Against this technical predicament, digital and intelligent technologies, relying on the core advantages of data-driven decision-making and intelligent collaborative processing, are gradually reshaping the technological paradigm in the field of component testing. They are driving the accelerated transformation of this field from the traditional manual-driven model toward the direction of intelligence and digitalization, and the field has currently entered a critical window period for technological iteration. This paper systematically explores the challenges and innovative paths faced by component testing technologies, integrates cutting-edge testing technologies such as machine learning and edge computing, and focuses on studying the intelligent solutions for FPGA testing. Meanwhile, based on the development of component testing technologies, this paper optimizes the current FPGA testing process, aiming to achieve improvements in speed and accuracy in aspects of visual inspection, configuration programs, and test vectors.