Blind source separation methods applied to evaluate harmonic contribution

The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information. However, the separation performance depends largely on the construction of reference signals. To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed, the reference-based cubic blind deconvolution algorithm is proposed in this paper. The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration. The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved. By deriving the optimal step size of gradient iteration under the new contrast function, we propose an efficient adaptive step optimization method. Furthermore, the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation. Numerical simulation analysis is carried out to validate the availability and superiority of this method. Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness. The signals of control moment gyroscope and flywheel were extracted, respectively, and the contribution evaluation of vibration sources to the sensitive load area was realized. This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.

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An Approach for Determining Voltage Imbalance Contributions Based on Complex Independent Component Analysis

Moraes

Brito

Oliveira

2022

Energies

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In the context of power quality problems, the voltage imbalance index is relevant, given its harmful impacts on the networks and loads. Thus, reliable and viable methodologies for practical use are necessary to determine agents’ contributions. This article presents a noninvasive method for sharing responsibility for imbalances based on the principle of superposing the individual voltage imbalance produced by the parties. A procedure based on the Complex Independent Component Analysis (CICA) technique is proposed to meet the parameters required by the superposition method. Based on the measurements of voltages and currents carried out on the point of common coupling (PCC), the negative sequence impedances are determined using the CICA method under the terms needed by the superposition principle. The methodology’s effectiveness is evaluated through performance comparisons carried out over the process, in light of the response from the methods for sharing responsibilities currently published in the literature of this domain. The results obtained through the proposed approach show good adherence to the procedures presented with solid conceptual bases. However, unlike these, this article’s methodology offers practical perspectives for application in the field.

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Blind source separation methods applied to evaluate harmonic contribution

Cited by 3 publications

References 36 publications

Independent Component Analysis for Distortion Estimation at Different Points of a Network with Multiple Harmonic Sources

Independent Component Analysis for Distortion Estimation at Different Points of a Network with Multiple Harmonic Sources

Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

An Approach for Determining Voltage Imbalance Contributions Based on Complex Independent Component Analysis

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