The Department of Engineering Mathematics and Internetworking, Dalhousie University, Halifax, NS B3H 4R2, Canada.
The Inspection Analysis Department, Ontario Power Generation (OPG), 777 Brock Rd., Pickering, ON L1W 4A7, Canada.
Sensors (Basel). 2023 Apr 12;23(8):3907. doi: 10.3390/s23083907.
The inspection of nuclear power plants is an essential process that occurs during plant outages. During this process, various systems are inspected, including the reactor's fuel channels to ensure that they are safe and reliable for the plant's operation. The inspection of Canada Deuterium Uranium (CANDU) reactor pressure tubes, which are the core component of the fuel channels and house the reactor fuel bundles, is performed using Ultrasonic Testing (UT). Based on the current process that is followed by Canadian nuclear operators, the UT scans are manually examined by analysts to locate, measure, and characterize pressure tube flaws. This paper proposes solutions for the auto-detection and sizing of pressure tube flaws using two deterministic algorithms, the first uses segmented linear regression, while the second uses the average time of flight (ToF) within ±σ of µ. When compared against a manual analysis stream, the linear regression algorithm and the average ToF achieved an average depth difference of 0.0180 mm and 0.0206 mm, respectively. These results are very close to the depth difference of 0.0156 mm when comparing two manual streams. Therefore, the proposed algorithms can be adopted in production, which can lead to significant cost savings in terms of time and labor.
核电站检查是在工厂停机期间进行的重要过程。在此过程中，会检查各种系统，包括反应堆的燃料通道，以确保其在工厂运行中安全可靠。使用超声波检测 (UT) 对加拿大重水铀 (CANDU) 反应堆压力管进行检查，压力管是燃料通道的核心部件，容纳反应堆燃料束。根据加拿大核运营商目前遵循的流程，由分析师手动检查 UT 扫描，以定位、测量和描述压力管缺陷。本文提出了两种确定性算法，用于自动检测和确定压力管缺陷的大小，第一个算法使用分段线性回归，第二个算法使用µ的 ±σ内的平均飞行时间 (ToF)。与手动分析流程相比，线性回归算法和平均 ToF 的平均深度差分别为 0.0180 毫米和 0.0206 毫米。这些结果与两个手动流程之间的深度差 0.0156 毫米非常接近。因此，可以采用所提出的算法进行生产，这可以在时间和劳动力方面节省大量成本。
