A Method for Blind Source Separation of Multichannel Electromagnetic Radiation in the Field

Liu, Sheng; Wang, Bangmin; Zhang, Lanyong

doi:10.1109/access.2020.3032203

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…The brush-rail device provides a new idea for electromagnetic propulsion, which can replace the cable power supply to the electrical equipment and thus achieve higher velocity [14]. However, the electrical contact issues may affect the stability and reliability of the device.…”

Section: Introductionmentioning

confidence: 99%

Research on Electrical Contact Characteristics of Brush-Rail Device With Transient Large Current

Jin

Zhu

et al. 2023

IEEE Access

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An excellent electrical contact state is necessary to ensure safe and stable operation of the system. Therein, contact resistance and arc ablation are essential indexes for estimating the contact state. In view of the characteristics of brush-rail device with transient large current for AC electromagnetic propulsion, a contact resistance model and the concept of arc ablative trigger boundary are proposed in this paper. Firstly, an equivalent circuit model is developed based on structural properties of brush-rail device. Then, the corresponding contact resistance model is established considering the contact pressure, amplitude and frequency of current, sliding velocity and consecutive run times. In addition, the main affecting factors of arc ablation are analyzed and the p-v parameters of arc ablation boundary are determined. Finally, the contact resistance and arc ablative trigger boundary of the brush-rail device are tested on a rotating transient large current experimental platform, which proves the correctness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Research on Electrical Contact Characteristics of Brush-Rail Device With Transient Large Current

Jin

Zhu

et al. 2023

IEEE Access

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“…Then it used an improved Least Mean Square (LMS) algorithm for interference cancellation to achieve better filtering performance. Liu et al proposed a novel multi-channel electromagnetic radiation synchronous blind-source separation method that combines Multiple Empirical Mode Decomposition (MEMD) with Independent Component Analysis (ICA) [15]. The approach employed noise-assisted MEMD for the decomposition of multi-channel data and the creation of virtual channels.…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Interference Cancellation in the Frequency Domain Based on the ASEI-VMD Method

Chen,

Jin,

Liu

et al. 2023

Electronics

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In electromagnetic compatibility (EMC) testing, accurately extracting the radiation emission characteristics from the Equipment Under Test (EUT) in complex electromagnetic environments remains a daunting task. This paper presents a solution by introducing of a frequency-domain electromagnetic interference cancellation method based on the Adaptive Singular Envelope Iterative Variational Mode Decomposition (ASEI-VMD). The process begins with the application of the Adjacent Singular Envelope Entropy Ratio (ASEER) as an evaluation metric to adaptively discern the number of decomposition layers and the penalty factor, allowing the effective decomposition of signals from various channels into modal signals sharing the same center frequency and bandwidth. The singular envelope entropy of each VMD mode is computed as the basis for assessing the efficacy of components in the VMD. This step distinguishes the signals encapsulating the EUT frequency information, which are then isolated for cancellation to retrieve the actual EUT-radiated emission signal. Simulation and experimental data validate the efficacy of this approach. Uniquely, it neither places demands on the testing site nor requires prior conditions for the EUT. The retrieved signal exhibits a correlation of over 96% with the source signal, maintaining a signal-power error below 3 dB. It is suitable for conducting electromagnetic radiation emission testing in complex environments.

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“…Owing to these characteristics, electromagnetic compatibility on site tests are susceptible to interference from the external environment, and these test results are often mixed with electromagnetic radiation from different devices. Regarding the testing of the electromagnetic radiation of devices in a system-level complex electromagnetic environment, one major problem to solve is obtaining the electromagnetic radiation signal of each device from the complex environment without a priori knowledge of such signals [ 1 ]. Blind source separation (BSS) is an important method for solving this problem.…”

Section: Introductionmentioning

confidence: 99%

Blind Source Separation Method Based on Neural Network with Bias Term and Maximum Likelihood Estimation Criterion

Liu

Wang

Zhang

2021

Sensors

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Convergence speed and steady-state source separation performance are crucial for enable engineering applications of blind source separation methods. The modification of the loss function of the blind source separation algorithm and optimization of the algorithm to improve its performance from the perspective of neural networks (NNs) is a novel concept. In this paper, a blind source separation method, combining the maximum likelihood estimation criterion and an NN with a bias term, is proposed. The method adds L2 regularization terms for weights and biases to the loss function to improve the steady-state performance and designs a novel optimization algorithm with a dual acceleration strategy to improve the convergence speed of the algorithm. The dual acceleration strategy of the proposed optimization algorithm smooths and speeds up the originally steep, slow gradient descent in the parameter space. Compared with competing algorithms, this strategy improves the convergence speed of the algorithm by four times and the steady-state performance index by 96%. In addition, to verify the source separation performance of the algorithm more comprehensively, the simulation data with prior knowledge and the measured data without prior knowledge are used to verify the separation performance. Both simulation results and validation results based on measured data indicate that the new algorithm not only has better convergence and steady-state performance than conventional algorithms, but it is also more suitable for engineering applications.

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A Method for Blind Source Separation of Multichannel Electromagnetic Radiation in the Field

Cited by 4 publications

References 24 publications

Research on Electrical Contact Characteristics of Brush-Rail Device With Transient Large Current

Research on Electrical Contact Characteristics of Brush-Rail Device With Transient Large Current

Electromagnetic Interference Cancellation in the Frequency Domain Based on the ASEI-VMD Method

Blind Source Separation Method Based on Neural Network with Bias Term and Maximum Likelihood Estimation Criterion

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