Sequential Harmonic Component Tracking For Underdetermined Blind Source Separation in a Multi-Target Tracking Framework - HAL UNIV-PARIS8 - open access Access content directly
Book Sections Year : 2024

Sequential Harmonic Component Tracking For Underdetermined Blind Source Separation in a Multi-Target Tracking Framework

Abstract

Smart factories are composed of heterogeneous cyber-physical systems. In light of their complexity and the lack of transparency in their design, monitoring the health of these machines in real-time is made possible by the use of non-intrusive sensors. Such sensors produce mixed signals capturing component-specific signatures. Retrieving the activation statuses of the components (over the different operating modes of a machine) is essential for estimating their associated performance indicators. This is a special case of Underdetermined Blind Source Separation (UBSS), yet a sensor fusion perspective is adopted in this paper. A harmonic component detector produces observations in the Time-Frequency (TF) domain, inherently entailing noise-induced false alarms. The main contribution of this paper consists in a clutter-resilient multi-harmonic component tracking algorithm, based on the Sequential Monte-Carlo Probability Hypothesis Density (SMC-PHD) filter. Additionally, this paper presents a track association algorithm adapting the results obtained in the multi-target tracking framework for unsupervised multi-label classification. The combination of the two algorithms mitigates typical difficulties encountered in traditional UBSS problems, such as non-stationary and partially-coupled mode decomposition. The performance of the proposed technique is assessed upon synthetic data.
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Dates and versions

hal-03912257 , version 1 (09-02-2023)
hal-03912257 , version 2 (01-03-2023)

Identifiers

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Romain Delabeye, Martin Ghienne, Jean-Luc Dion. Sequential Harmonic Component Tracking For Underdetermined Blind Source Separation in a Multi-Target Tracking Framework. Model Validation and Uncertainty Quantification, Volume 3, Springer Nature Switzerland, pp.93-100, 2024, Conference Proceedings of the Society for Experimental Mechanics Series, ⟨10.1007/978-3-031-37003-8_15⟩. ⟨hal-03912257v2⟩
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