http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Thermo-optical Analysis and Correction Method for an Optical Window in Low Temperature and Vacuum
Ruoyan Wang,Ruihu Ni,Zhishan Gao,Lingjie Wang,Qun Yuan 한국광학회 2023 Current Optics and Photonics Vol.7 No.2
The optical window, as a part of the collimator system, is the connector between the outside light source and the optical system inside a vacuum tank. The temperature and pressure difference between the two sides of the optical window cause not only thermoelastic deformation, but also refractive-index irregularities. To suppress the influence of these two changes on the performance of the collimator system, thermo-optical analysis is employed. Coefficients that characterize the deformations and refractiveindex distributions are derived through finite-element analysis, and then imported into the collimator system using a user-defined surface in ZEMAX. The temperature and pressure difference imposed on the window seriously degrade the system performance of the collimator. A decentered and tilted lens group is designed to correct both field aberrations and the thermal effects of the window. Through lensinterval adjustment of the lens group, the diffraction-limited performance of the collimator can be maintained with a vacuum level of 10 −5 Pa and inside temperature ranging from −100 ℃ to 20 ℃.
Partial Discharge Detection Method Based on DD-DT CWT and Singular Value Decomposition
Wu Chao,Gao Yiran,Wang Ruoyan,Wang Kai,Liu Siyang,Nie Yongjie,Wang Ping 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.4
Partial discharge (PD) detection is signifi cant for insulation condition evaluation of electrical equipment. However, it often happens that the PD signals are submerged by interferences, which will cause the inaccurate detection results. In this paper, we propose a PD detection method based on double-density dual-tree complex wavelet transform (DD-DT CWT) and singular value decomposition (SVD) to solve this problem. The denoising method based on DD-DT CWT has better performance in both removing interferences and retaining features of PD signals. The inner product of the singular value matrix obtained by applying SVD to denoised high-frequency wavelet coeffi cient matrix can concisely represent the complexity of the tested signal, which can be used as a basis to judge the existence of the PD signal. Besides, Otsu algorithm is introduced to calculate the threshold to locate the appearance time of the PD signal. Experimental results show that the proposed method can detect the PD signal with the accuracy rate of 77.8% when PD signals are submerged by noises, while the traditional method cannot detect the existence of the PD signal. In addition, only the method proposed in this paper can detect the appearance time of the PD signal with the accuracy rate of 97.2%.