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A System for Nuclear Fuel Inspection Based on Ultrasonic Pulse-Echo Technique

机译:基于超声脉冲回波技术的核燃料检查系统

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摘要

Nuclear Pressurized Water Reactor (PWR) technology has been widely used for electric energy generation. The follow-up of the plant operation has pointed out the most important items to optimize the safety and operational conditions. The identification of nuclear fuel failures is in this context. The adoption of this operational policy is due to recognition of the detrimental impact that fuel failures have on operating cost, plant availability, and radiation exposure. In this scenario, the defect detection in rods, before fuel reloading, has become an important issue. This paper describes a prototype of an ultrasonic pulse-echo system designed to inspect failed rods (with water inside) from PWR. This system combines development of hardware (ultrasonic transducer, mechanical scanner and pulser-receiver instrumentation) as well as of software (data acquisition control, signal processing and data classification). The ultrasonic system operates at center frequency of 25 MHz and failed rod detection is based on the envelope amplitude decay of successive echoes reverberating inside the clad wall. The echoes are classified by three different methods. Two of them (Linear Fisher Discriminant and Neural Network) have presented 93% of probability to identify failed rods, which is above the current accepted level of 90%. These results suggest that a combination of a reliable data acquisition system with powerful classification methods can improve the overall performance of the ultrasonic method for failed rod detection.
机译:核压水堆(PWR)技术已被广泛用于发电。工厂运行的后续行动指出了最重要的项目,以优化安全和运行条件。在这种情况下,核燃料故障的识别。该运营政策的采用是由于认识到燃料故障对运营成本,工厂可用性和辐射暴露的有害影响。在这种情况下,燃料重新装填之前,杆中的缺陷检测已成为一个重要问题。本文介绍了一种超声波脉冲回波系统的原型,该系统旨在检查PWR发生故障的棒(内部有水)。该系统结合了硬件(超声波换能器,机械扫描仪和脉冲接收器仪器)的开发以及软件(数据采集控制,信号处理和数据分类)的开发。超声波系统以25 MHz的中心频率运行,而棒检测失败是基于包层壁内部回荡的连续回波的包络振幅衰减。回声通过三种不同的方法进行分类。其中两个(线性Fisher判别式和神经网络)已提供了93%的概率来识别故障杆,该概率高于当前公认的90%的水平。这些结果表明,将可靠的数据采集系统与强大的分类方法结合使用,可以提高超声波方法在检测棒失败中的整体性能。

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