Time-domain modeling of electromagnetic diffusion with a frequency-domain code
نویسندگان
چکیده
منابع مشابه
seismic texture recognition in time-frequency domain
in seismic exploration studies different types of techniques are used to recognize seismic features in terms of their temporal and spatial spectra. variations in frequency content are sensitive to subtle changes in reflection information (castro de matos et al., 2003). in this study the joint time-frequency analysis is used for seismic texture recognition. discrete wavelet transform (dwt) witho...
متن کاملTime-domain modeling of high-frequency electromagnetic wave propagation, overhead wires, and earth
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
متن کاملA new technique for bearing fault detection in the time-frequency domain
This paper presents a new Fast Kurtogram Method in the time-frequency domain using novel types of statistical features instead of the kurtosis. For this study, the problem of four classes for Bearing Fault Detection is investigated using various statistical features. This research is conducted in four stages. At first, the stability of each feature for each fault mode is investigated. Then, res...
متن کاملA Time-Domain Method for Shape Reconstruction of a Target with Known Electrical Properties (RESEARCH NOTE)
This paper uses a method for shape reconstruction of a 2-D homogeneous object with arbitrary geometry and known electrical properties. In this method, the object is illuminated by a Gaussian pulse, modulated with sinusoidal carrier plane wave and the time domains’ footprint signal due to object presence is used for the shape reconstruction. A nonlinear feedback loop is used to minimize the diff...
متن کاملA Novel Intelligent Fault Diagnosis Approach for Critical Rotating Machinery in the Time-frequency Domain
The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: GEOPHYSICS
سال: 2008
ISSN: 0016-8033,1942-2156
DOI: 10.1190/1.2799093