ORIGINAL PAPER
Optimized Variational Mode Decomposition combined with Wavelet Thresholding for noise reduction in magnetic induction sorting system
1
School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
2
School of Intelligent Manufacturing and Materials Engineering, Gannan University of Science and Technology, Ganzhou 341000, China
3
School of Mechanical and Electrical Engineering, Heyuan Technician Institute
Submission date: 2025-05-07
Final revision date: 2025-08-16
Acceptance date: 2025-09-07
Publication date: 2026-03-31
Corresponding author
Chunrong Pan
School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
School of Mechanical and Electrical Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2026;42(1):141-161
KEYWORDS
TOPICS
ABSTRACT
The magnetic induction sorting system is an automated intelligent system designed specifically for magnetite ore, which can effectively separate low-grade ores. However, the magnetic induction signals detected by this system are vulnerable to noise interference, posing a significant challenge for accurate signal acquisition, thus affecting both the sorting range and accuracy. To address this issue, this study proposes a denoising method integrating the Sparrow Search Algorithm (SSA)-optimized Variational Mode Decomposition (VMD) with Wavelet Thresholding (WT). Firstly, SSA is employed to optimize the parameter configuration of VMD to achieve optimal signal decomposition. Subsequently, intrinsic mode functions (IMFs) are selectively filtered based on sample entropy analysis, and the retained IMFs undergo WT denoising. Finally, the IMFs are reconstructed to yield the denoised signal. The effectiveness of the proposed method is verified comprehensively through experiments performed with a laboratory-developed magnetic induction sorting system. Experimental results demonstrate substantial performance improvements when compared to four alternative algorithms, achieving an average improvement of 3.3% in Noise Mode (NM) and a reduction of 14.9% in Root of Variance Ratio (RVR). Moreover, the denoising algorithm led to a 38.8% increase in detectable magnetite ores and a 12.5% improvement in sorting accuracy. These results demonstrate that the proposed method effectively suppresses noise interference during the Hall sensor’s collection of magnetic signals, significantly enhancing the grade sorting range and accuracy of magnetite ore.
FUNDING
This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. (72161019), Science and Technology Research Project GJJ2203618.
CONFLICT OF INTEREST
The Authors have no conflict of interest to declare.
METADATA IN OTHER LANGUAGES:
Polish
Zoptymalizowana dekompozycja modów wariacyjnych w połączeniu z progowaniem falkowym w celu redukcji szumów w systemie sortowania z indukcją magnetyczną
system sortowania z indukcją magnetyczną, zakłócenia szumowe, VMD, WT, czujnik Halla
System sortowania z indukcją magnetyczną to zautomatyzowany, inteligentny system zaprojek- towany specjalnie do analizy rud magnetytowych, umożliwiający skuteczną separację rud niskiej jakości. Sygnały indukcji magnetycznej wykrywane przez ten system są jednak podatne na zakłócenia, co stanowi poważne wyzwanie dla dokładnej akwizycji sygnału, wpływając tym samym zarówno na zakres, jak i dokładność sortowania. Aby rozwiązać ten problem, w niniejszym badaniu zaproponowano metodę odszumiania, integrującą zoptymalizowaną algorytmem wyszukiwania Sparrow (SSA) dekompozycję modów wariacyjnych (VMD) z progowaniem falkowym (WT). Najpierw SSA jest wykorzystywany do optymalizacji konfiguracji parametrów VMD w celu uzyskania optymalnej dekompozycji sygnału. Następnie funkcje modów wewnętrznych (IMF) są selektywnie filtrowane na podstawie analizy entropii próbki, a zachowane funkcje IMF są poddawane odszumianiu metodą WT. Na koniec funkcje IMF są rekonstruowane w celu uzyskania odszumionego sygnału. Skuteczność proponowanej metody została kompleksowo zweryfikowana eksperymentami przeprowadzonymi z wykorzystaniem opracowanego w laboratorium systemu sortowania z indukcją magnetyczną. Wyniki eksperymentalne wskazują na znaczną poprawę wydajności w porównaniu z czterema alternatywnymi algorytmami, osiągając średnią poprawę o 3,3% w trybie szumu (NM) i redukcję o 14,9% współczynnika pierwiastka z wariancji (RVR). Ponadto algorytm odszumiania doprowadził do 38,8-procentowego wzrostu wykrywalności rud magnetytu i 12,5-procentowej poprawy dokładności sortowania. Wyniki te dowodzą, że proponowana metoda skutecznie tłumi zakłócenia szumowe podczas zbierania sygnałów magnetycznych przez czujnik Halla, znacząco zwiększając zakres sortowania i dokładność rudy magnetytu.
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