Rapid detection and classification of airborne time-domain electromagnetic anomalies using weighted multi-linear regression

2008 ◽  
Vol 39 (3) ◽  
pp. 164-180 ◽  
Author(s):  
Maxime Claprood ◽  
Michel Chouteau ◽  
Li Zhen Cheng
Keyword(s):  
Linear Regression ◽  
Time Domain ◽  
Rapid Detection ◽  
Time Domain Electromagnetic ◽  
Multi Linear Regression

USE OF DECAY PATTERNS FOR THE CLASSIFICATION OF ANOMALIES IN TIME‐DOMAIN AEM MEASUREMENTS

Geophysics ◽  
1976 ◽  
Vol 41 (5) ◽  
pp. 1031-1041 ◽  
Author(s):  
G. J. Palacky
Keyword(s):  
Time Domain ◽  
Field Measurements ◽  
System Response ◽  
Electromagnetic Measurements ◽  
Time Domain Electromagnetic ◽  
Decay Pattern ◽  
Body Parameters ◽  
Flight Computer

Interpretation of time‐domain electromagnetic measurements normally comprises visual anomaly selection and determination of body parameters, such as conductance, depth, and dip. A study is made to examine the possibility of in‐flight computer interpretation on the basis of decay patterns. Analysis of system response over conducting loops, vertical and dipping sheets, horizontal strips, and a half‐space indicates that identification of models and some of their parameters by decay patterns is feasible. By the simultaneous use of vertical and horizontal coil receivers, a reliable recognition of models may be achieved. While the secondary magnetic field over a conducting loop decays exponentially, other models show distinctive nonexponential patterns. Decay patterns are affected by conductance and conductor size, but less by depth and dip variations. Field measurements indicate that decay pattern may be used to distinguish between geologic bodies of various types.

scholarly journals Multivariate Analysis for the Classification of Chocolate According to its Percentage of Cocoa by Using Terahertz Time-Domain Spectroscopy (THz-TDS)

Proceedings ◽  
2020 ◽  
Vol 70 (1) ◽  
pp. 109
Author(s):  
Jimy Oblitas ◽  
Jorge Ruiz
Keyword(s):  
Machine Learning ◽  
Time Domain ◽  
Electromagnetic Pulse ◽  
Machine Learning Algorithms ◽  
Classification Models ◽  
Terahertz Time Domain Spectroscopy ◽  
Time Domain Spectroscopy ◽  
Svm Algorithm ◽  
Classification Of Images

Terahertz time-domain spectroscopy is a useful technique for determining some physical characteristics of materials, and is based on selective frequency absorption of a broad-spectrum electromagnetic pulse. In order to investigate the potential of this technology to classify cocoa percentages in chocolates, the terahertz spectra (0.5–10 THz) of five chocolate samples (50%, 60%, 70%, 80% and 90% of cocoa) were examined. The acquired data matrices were analyzed with the MATLAB 2019b application, from which the dielectric function was obtained along with the absorbance curves, and were classified by using 24 mathematical classification models, achieving differentiations of around 93% obtained by the Gaussian SVM algorithm model with a kernel scale of 0.35 and a one-against-one multiclass method. It was concluded that the combined processing and classification of images obtained from the terahertz time-domain spectroscopy and the use of machine learning algorithms can be used to successfully classify chocolates with different percentages of cocoa.

Modeling and multi-class classification of vibroarthographic signals via time domain curvilinear divergence random forest

2021 ◽  
Author(s):  
Balajee Alphonse ◽  
Venkatesan Rajagopal ◽  
Sudhakar Sengan ◽  
Kousalya Kittusamy ◽  
Amudha Kandasamy ◽  
...  
Keyword(s):  
Random Forest ◽  
Time Domain ◽  
Multi Class Classification

scholarly journals Lightweight Unmanned Aerial System for Time-Domain Electromagnetic Prospecting—The Next Stage in Applied UAV-Geophysics

2021 ◽  
Vol 11 (5) ◽  
pp. 2060 ◽  
Author(s):  
Alexander Parshin ◽  
Ayur Bashkeev ◽  
Yuriy Davidenko ◽  
Marina Persova ◽  
Sergey Iakovlev ◽  
...  
Keyword(s):  
Time Domain ◽  
Gamma Ray ◽  
Pulse Generator ◽  
Measuring System ◽  
Electromagnetic Sounding ◽  
Mountainous Regions ◽  
Time Domain Electromagnetic ◽  
Unmanned System ◽  
Classical Triad ◽  
The Time Domain

Nowadays in solving geological problems, the technologies of UAV-geophysics, primarily magnetic and gamma surveys, are being increasingly used. However, for the formation of the classical triad of airborne geophysics methods in the UAV version, there was not enough technology for UAV-electromagnetic sounding, which would allow studying the geological environment at depths of tens and hundreds of meters with high detail. This article describes apparently the first technology of UAV-electromagnetic sounding in the time domain (TDEM, TEM), implemented as an unmanned system based on a light multi-rotor UAV. A measuring system with an inductive sensor—an analogue of a 20 × 20 or 50 × 50 m receiving loop is towed by a UAV, and a galvanically grounded power transmitter is on the ground and connected to a pulse generator. The survey is carried out along a network of parallel lines at low altitude with a terrain draping at a speed of 7–8 m/s, the maximum distance of the UAV’s departure from the transmitter line can reach several kilometers, thus the created technology is optimal for performing detailed areal electromagnetic soundings in areas of several square kilometers. The results of the use of the unmanned system (UAS) in real conditions of the mountainous regions of Eastern Siberia are presented. Based on the obtained data, the sensitivity of the system was simulated and it was shown that the developed technology allows one to collect informative data and create geophysical sections and maps of electrical resistivity in various geological situations. According to the authors, the emergence of UAV-TEM systems in the near future will significantly affect the practice of geophysical work, as it was earlier with UAV-magnetic prospecting and gamma-ray survey.

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