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针对RPV钢磁巴克豪森噪声检测的传感器设计

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辐照损伤是影响RPV使用寿命的重要因素,为了提升MBN信号检测仪器对RPV钢辐照损伤程度的评估性能,设计一种小型化MBN信号检测传感器;该传感器是由H型硅钢片磁轭、激励线圈、感应线圈和工型锰锌铁氧体构成,可以使检测仪器获得更为稳定的MBN信号,从而对RPV钢的辐照损伤进行有效评估;此外,利用电磁仿真软件ANSYS Maxwell对励磁模块进行了仿真与分析,获得试件的有效磁化区域,即长度8 mm(磁轭两脚之间的距离)、宽度8 mm(磁轭的厚度)、深度约为1 mm(试件的厚度)的立方体;为了降低激励信号对MBN信号接收的影响,分析了试件上方的磁感应强度分布,获得了 MBN信号接收器应该位于磁轭两脚的中间位置;最后通过对RPV试样测量数据结果分析,确定了最佳激励信号的幅值为7 V,频率为 6 Hz。
Design of Magnetic Bakhausen Noise Detection Sensor for RPV Steel
Irradiation damage is an important factor affecting the service life of reactor pressure vessel(RPV),in order to improve the performance of magnetic Barkhausen noise(MBN)signal detection instrument to evaluate the degree of irradiation damage of RPV steel,a miniaturized MBN signal detection sensor is designed.The sensor is composed of H-shaped silicon steel yoke,excitation coil,induction coil and work-type manganese zinc ferrite.It can make the detection instrument obtain a more stable MBN signal,which can effectively evaluate the irradiation damage of RPV steel.In addition,the electromagnetic simulation software ANSYS Maxwell was used to simulate and analyze the excitation module,to obtain the effective magnetization area of the specimen,namely a cube with the length of 8 mm(the distance between the two legs of the yoke),width of 8 mm(the thickness of the yoke)and depth of approximate-ly 1 mm(the thickness of the specimen).The magnetic induction intensity distribution above the specimen was analyzed to reduce the influence of the excitation signal on the MBN signal reception,and obtain the MBN signal receiver,which locates in the middle of the two legs of the magnetic yoke.Finally,by analyzing the results of the RPV specimen measurement data,the optimal excitation signal was determined wtih the amplitude of 7 V and frequency of 6 Hz.

Barkhausen noisesensorreactor pressure vesselMaxwell simulationeigenvalue extraction

边闯、王海涛、刘向兵、钱王洁、丁同乐、陈怀东、马官兵、郑凯

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南京航空航天大学 自动化学院,南京 210016

苏州热工研究院,江苏苏州 215004

中广核检测技术有限公司,广东深圳 518031

江苏省特种设备安全监督检测研究院,南京 210036

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巴克豪森噪声 传感器 反应堆压力容器 Maxwell仿真 特征值提取

广东省基础与应用基础研究基金

2019B030302011

2024

计算机测量与控制
中国计算机自动测量与控制技术协会

计算机测量与控制

CSTPCD
影响因子:0.546
ISSN:1671-4598
年,卷(期):2024.32(2)
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