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

• Published in: IEEE transactions on nuclear science 2011-10, Vol.58 (5), p.2452-2458
• Main Authors: Thome, Z. D., Pereira, W. C. A., Machado, J. C., Seixas, J. M., Soares-Filho, W.
• Format: Article
• Language: English
• Subjects: Acoustics; Assembly; Classification; Echoes; Electron tubes; Face; Failure; Fuels; Inspection; Neural network; Neural networks; non-destructive testing; nuclear fuel inspection; Power plants; Pressurized water reactors; Probes; Rods; Studies; Ultrasonic testing; Ultrasonic transducers; ultrasound
• ISSN: 0018-9499; 1558-1578
• DOI: 10.1109/TNS.2011.2164557

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.