Results 21 to 30 of about 1,252,389 (155)
Non stationary‐ARMA flicker model for squirrel cage induction generators based wind farms
IET Renewable Power Generation, 2021 Time varying nature of the wind power is studied previously considering different time intervals from seconds to days. However for power quality problems such as flicker, a model which considers the extremely fast variations is essential.
Haidar Samet +2 more
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A deep neural network based method for magnetic anomaly detection
IET Science, Measurement & Technology, 2022 Magnetic anomaly detection (MAD) is a technique to find ferromagnets hiding in strong and complicated magnetic background. In many practical cases, the targets are very far from the detection sensor, which leads to low signal‐to‐noise ratio (SNR) and ...
Yizhen Wang +5 more
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Object recognition for power equipment via human‐level concept learning
IET Generation, Transmission & Distribution, 2021 Inspection robots are popularized in substations due to the lack of personnel for operation and maintenance. However, these inspection robots remain at the level of perceptual intelligence, rather than cognition intelligence.
Siheng Xiong +6 more
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IET Science, Measurement & Technology, 2021 Time difference of arrival‐based localisation method has been extensively used by researchers for the partial discharge (PD) diagnosis despite being time‐inefficient and sensitive to time delay estimation.
Atta Ul Munim Zaki +2 more
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IET Communications, 2022 Device‐to‐device (D2D) communication plays a vital role in communication technologies with resource management and power control, which are the major issues for researchers in the era of 2020.
Krishna Pandey, Rajeev Arya
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Complex multitask compressive sensing using Laplace priors
Electronics Letters, 2021 Most existing Bayesian compressive sensing (BCS) algorithms are developed in real numbers. This results in many difficulties in applying BCS to solve complex‐valued problems.
Qilei Zhang, Zhen Dong, Yongsheng Zhang
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Statistical multivariate monitoring of rolling bearings working under varying operational conditions
IET Science, Measurement & Technology, 2021 In recent years, statistical data‐driven approaches have been developed for health monitoring of rolling bearings working under variable operational conditions.
Baoxiang Wang, Hongxia Pan
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Entropy of the Nordic electricity market: anomalous scaling, spikes, and mean-reversion [PDF]
, 2006 The electricity market is a very peculiar market due to the large variety of phenomena that can affect the spot price. However, this market still shows many typical features of other speculative (commodity) markets like, for instance, data clustering and
Clewlow L +11 more
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Fault diagnosis of an induction motor using data fusion based on neural networks
IET Science, Measurement & Technology, 2021 In this paper, neural network‐based data fusion is used to detect fault and isolate stator winding short circuit, outer bearing race, and broken rotor bar defects in an induction motor.
Saeid Jorkesh, Javad Poshtan
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IET Communications, 2021 Autonomic resource management on cloud is a challenging task because of its huge heterogeneous and distributed environment. There are several service providers in the cloud to provide a different set of cloud services. These services are delivered to the
Bhupesh Kumar Dewangan +3 more
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