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The Parameter-Optimized Recursive Sliding Variational Mode Decomposition Algorithm and Its Application in Sensor

Yunyi Liu1,2, Wenjun He2, Tao Pan2

  • 1The Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China.

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|April 28, 2025
PubMed
Summary
This summary is machine-generated.

A new Parameter-Optimized Recursive Sliding Variational Mode Decomposition (PO-RSVMD) algorithm improves real-time signal extraction for industrial polishing sensors. PO-RSVMD significantly reduces iteration time and errors, even in noisy environments.

Keywords:
IMU signaldenoisingparameter optimizationrecursive slidingvariational mode decomposition

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Area of Science:

  • Signal processing
  • Mechanical engineering
  • Data analysis

Background:

  • Real-time signal extraction is crucial for industrial polishing sensors.
  • Variational Mode Decomposition (VMD) lacks sufficient real-time performance.
  • Recursive Sliding Variational Mode Decomposition (RSVMD) shows instability in high-interference scenarios.

Purpose of the Study:

  • To propose a Parameter-Optimized Recursive Sliding Variational Mode Decomposition (PO-RSVMD) algorithm.
  • To enhance the stability and real-time performance of RSVMD in strong interference.
  • To improve signal extraction accuracy for industrial polishing motors.

Main Methods:

  • Introduced an iterative termination condition based on modal component error mutation to prevent over-decomposition.
  • Incorporated a rate learning factor to automatically adjust the initial center frequency, reducing errors.
  • Validated the algorithm through simulations with varying signal-to-noise ratios (SNR) and practical application on Inertial Measurement Unit (IMU) data.

Main Results:

  • PO-RSVMD accelerated iteration time by at least 53% and decreased iterations by at least 57% compared to VMD and RSVMD across SNRs from 0 dB to 17 dB.
  • Root Mean Square Error (RMSE) was reduced by 35% using PO-RSVMD compared to VMD and RSVMD.
  • In practical IMU tests under strong interference, PO-RSVMD demonstrated significantly lower average iteration time and iteration counts than RSVMD, with comparable RMSE.

Conclusions:

  • PO-RSVMD offers superior real-time signal extraction capabilities compared to VMD and RSVMD.
  • The algorithm exhibits high stability and accuracy, particularly in challenging industrial environments with strong interference.
  • PO-RSVMD is a promising solution for accurate and rapid signal extraction in applications like industrial polishing.