Geomagnetic micro-pulsation automatic detection via deep leaning approach guided with discrete wavelet transform

Rabie, Esraa Mohamed; Hafez, Ali G.; Saad, Omar M.; El‐Sayed, Abou‐Hashema M.; Abdelrahman, Kamal; Al-Otaibi, Naif

doi:10.1016/j.jksus.2020.101263

Cited by 5 publications

(7 citation statements)

References 23 publications

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“…The geomagnetic data modeling and analysis problems are associated with their complicated irregular structure and the presence of noises of different origin (natural and anthropogenic) [22,[24][25][26]. The geomagnetic data structure and the anomalous feature occurrence times contain essential information on nonstationary processes in NES and characterize magnetic disturbance intensity at the place of data recording.…”

Section: Introductionmentioning

confidence: 99%

“…allow us to investigate long-term variations and regular diurnal changes of the magnetic field [2]. However, they are not effective enough to analyze sudden short-period features occurring during increased solar activity and magnetic storms [5,22,[24][25][26]. At the present time, new methods and approaches are being developed to analyze complex geophysical data.…”

Section: Introductionmentioning

confidence: 99%

“…Application of fuzzy logic elements was further developed in the paper [22], where the authors consider a multi-scale approach and study morphological features of several intensive geomagnetic storms based on it. At the present time, to improve the efficiency of complicated raw data analysis, hybrid approaches, including machine learning methods, are frequently used [8,[26][27][28]. For example, the paper [8] suggests a model of fuzzy wavelet neural network (FWNN), applying fuzzy logic elements and wavelet transform [29,30] to forecast a signal code transmitted from a well to the surface with wastewater.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we propose to use the approach developed by the authors [31][32][33]. It is based on wavelet transform, which allows us to investigate complicated nonstationary changes in geophysical data and is widely used in physics, in particularly, in geophysics [4,7,9,26,[34][35][36][37][38]. Based on the wavelet transform, we proposed an automated method to detect geomagnetic pulsations [34,35], constructed an algorithm for automatic detection of magnetic storms with increased risk of occurrence of geomagneticallyinduced currents [3], and developed a method to calculate the geomagnetic activity index WISA [36,38].…”

Section: Introductionmentioning

confidence: 99%

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Wavelet Model of Geomagnetic Field Variations and Its Application to Detect Short-Period Geomagnetic Anomalies

2022

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Geomagnetic data analysis is an important basis for the investigation of the processes in the near-Earth space, Earth magnetosphere, and ionosphere. The negative impact of geomagnetic anomalies on modern technical objects and human health determine the applied significance of the investigation and requires the creation of effective methods for timely detection of the anomalies. Priory complicated structure of geomagnetic data makes their formalization and analysis difficult. This paper proposes a wavelet model for geomagnetic field variations. It describes characteristic changes and anomalies of different amplitude and duration. Numerical realization of the model provides the possibility to apply it in online analysis. We describe the process of model identification and show its efficiency in the detection of sudden, short-period geomagnetic anomalies occurring before and during magnetic storms. Raw second data of the Paratunka and Magadan observatories and post-processed minute data were used in the paper. The question of noise effect on the proposed model results was under consideration.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wavelet Model of Geomagnetic Field Variations and Its Application to Detect Short-Period Geomagnetic Anomalies

2022

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“…In order to realize large‐scale synchronous trigger, multiple photoelectric detection sensors are used in the experiment. However, this method increases the cost, and also introduces the problem of fusion recognition of multiple photoelectric detection sensors 11,12 . In order to solve the problem of the simultaneous acquisition of the parameters of the burst point of the projectile based on the multi‐acoustic sensor array, also due to the influence of external environment, the flare signal of projectile explosion cannot provide accurate synchronization signal 13,14 .…”

Section: Introductionmentioning

confidence: 99%

Design of optical system of photoelectric detection sensor and flare signal processing with array lens

Zhang

2021

Micro & Optical Tech Letters

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Because the flare signal formed by projectile explosion is affected by the external environment, it is difficult for multi‐acoustic sensor array to obtain accurate synchronization signal. In order to solve this problem, this paper proposes a design method of ultra‐wide‐angle photoelectric detection sensor by using circular curved surface array lens, analyze the detection ability of photoelectric detection sensor with array lens, and establish the output signal function calculation model. According to the output signal of flare detection circuit, the feature points detection algorithm of modulus maxima based on wavelet transform is studied. Based on this algorithm, the signal is processed on the hardware processor to output the actual flare trigger control signal. The processing and recognition algorithm of signal mainly uses the relationship among wavelet modulus maxima, scale, Lipschitz index, and signal singularity to select the appropriate wavelet basis to process the flare signal formed by projectile explosion. Thus, the feature points of the flare signal singularity can be obtained. When the detection conditions of the feature points of the signal singularity are satisfied, the hardware outputs pulse signals to control the acoustic sensor array. The experimental results show that the designed detection algorithm of wavelet filtering and modulus maxima feature points can effectively detect the flare signal.

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Pathological brain classification using multiple kernel-based deep convolutional neural network

Dora,

Agrawal,

Panda

et al. 2023

Neural Comput & Applic

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Geomagnetic micro-pulsation automatic detection via deep leaning approach guided with discrete wavelet transform

Cited by 5 publications

References 23 publications

Wavelet Model of Geomagnetic Field Variations and Its Application to Detect Short-Period Geomagnetic Anomalies

Wavelet Model of Geomagnetic Field Variations and Its Application to Detect Short-Period Geomagnetic Anomalies

Design of optical system of photoelectric detection sensor and flare signal processing with array lens

Pathological brain classification using multiple kernel-based deep convolutional neural network

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