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An improved compressed sensing method for dynamic impact signals based on cubic spline interpolation.

Fujing Xu1, Yuting Wang1, Tingwei Jia1

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This study introduces an improved compressed sensing (CS) method using cubic spline interpolation (CSI) for impact signal measurement. The new approach enhances reconstruction accuracy, achieving approximately 5.0% error.

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Area of Science:

  • Signal Processing
  • Measurement Science

Background:

  • High sampling frequencies in impact signal acquisition challenge test systems.
  • Existing compressed sensing (CS) methods require numerous observation points.

Purpose of the Study:

  • To propose an improved compressed sensing (CS) method for dynamic impact signal measurement.
  • To enhance the efficiency and accuracy of impact signal acquisition.

Main Methods:

  • Developed a random non-uniform sampling strategy combining CS and cubic spline interpolation (CSI).
  • Introduced an improved orthogonal matching pursuit (IOMP) algorithm for signal reconstruction.
  • Utilized an impact signals test platform with a Machete hammer for validation.

Main Results:

  • Cubic spline interpolation (CSI) significantly reduced the number of required observation points.
  • The improved orthogonal matching pursuit (IOMP) algorithm enhanced reconstruction success rates.
  • The proposed CS method achieved a data reconstruction error of approximately 5.0%.

Conclusions:

  • The improved CS method effectively measures impact signals with high accuracy.
  • The combination of CS and CSI offers a more efficient approach to dynamic signal acquisition.
  • The IOMP algorithm provides a more robust solution for signal reconstruction compared to traditional OMP.