To overcome these limitations, in this work, the Frequency Domain Decomposition (FDD) of the Operational Modal Analysis (OMA) is applied to the spectral characterization of the neutron noise.

In the study of the neutron noise in KWU pre-Konvoi PWRs, the Hilbert Huang Transform and the widely-used Fourier analysis are employed to extract spectral characteristics. However, both techniques are limited in decomposing the signal in the same frequency range to distinguish the contributions from different phenomena, such as the thermal–hydraulic and the mechanical perturbations. In addition, it is difficult for these two techniques to gather and present all the results in a single plot that shows the response of the core as a whole. To overcome these limitations, in this work, the Frequency Domain Decomposition (FDD) of the Operational Modal Analysis (OMA) is applied to the spectral characterization of the neutron noise. The OMA is widely used in the study of the dynamic properties of systems and structures. The FDD was performed on a series of neutron noise signals from simulated scenarios based on the transient nodal code SIMULATE-3 K. The simulations considered different single-source fluctuations and their combinations. The methodology separates in the two first singular values and singular vectors the responses due to mechanical vibrations and thermal–hydraulic fluctuation in all the frequency range, which allows distinguishing the effects of different phenomena on the spectral characteristics at the same frequency range of the neutron noise. The good performance of OMA in the present study provides promising possibilities to infer characteristics of the input excitation from the neutron noise data in PWR. Finally, the methodology shows remarkable advantages in the compilation of the results which can be utilized for monitoring purposes.

为了克服这些限制，在这项工作中，将操作模态分析（OMA）的频域分解（FDD）应用于中子噪声的频谱表征。

在研究KWU-Konvoi前压水堆中的中子噪声时，采用希尔伯特·黄变换和广泛使用的傅里叶分析来提取光谱特征。但是，这两种技术在分解同一频率范围内的信号方面存在局限性，以区分来自不同现象的贡献，例如热工液压和机械扰动。此外，这两种技术很难在一个图上收集并显示所有结果，而图只能显示整个核心的响应。为了克服这些限制，在这项工作中，将操作模态分析（OMA）的频域分解（FDD）应用于中子噪声的频谱表征。OMA被广泛用于研究系统和结构的动态特性。FDD是根据瞬态节点代码SIMULATE-3 K对来自模拟场景的一系列中子噪声信号执行的。模拟考虑了不同的单源波动及其组合。该方法将两个第一奇异值和奇异矢量分离在所有频率范围内由于机械振动和热工波动引起的响应，从而可以区分在中子噪声相同频率范围内不同现象对频谱特性的影响。OMA在本研究中的良好性能为从PWR中的中子噪声数据推断输入激励的特性提供了有希望的可能性。最后，该方法在汇编结果中显示出显着的优势，可用于监测目的。