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Related Concept Videos

Frequency of Spring-Mass System01:17

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One interesting characteristic of the simple harmonic motion (SHM) of an object attached to a spring is that the angular frequency, and the period and frequency of the motion, depend only on the mass and the force constant of the spring, and not on other factors such as the amplitude of the motion or initial conditions. We can use the equations of motion and Newton's second law to find the angular frequency, frequency, and period.
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The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
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Related Experiment Video

Updated: Mar 15, 2026

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S-shape spring sensor: Sensing specific low-frequency vibration by energy harvesting.

Lan Zhang1, Jian Lu1, Ryohei Takei1

  • 1Research Center for Ubiquitous MEMS and Micro Engineering (UMEMSME), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8564, Japan.

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|September 3, 2016
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We created a sensitive silicon microelectromechanical systems sensor for low-frequency vibration detection and energy harvesting. This device uses lead zirconate titanate (PZT) springs and achieves a low resonant frequency (<11 Hz) and good voltage output.

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Electrical Engineering

Background:

  • Microelectromechanical systems (MEMS) sensors are crucial for vibration analysis.
  • Low-frequency vibration sensing and energy harvesting present unique design challenges.
  • Lead zirconate titanate (PZT) is a piezoelectric material suitable for energy conversion.

Purpose of the Study:

  • To develop a highly sensitive Si-based MEMS sensor for low-frequency vibration detection.
  • To optimize the sensor design for improved performance and cost-effectiveness.
  • To explore the potential for energy harvesting from low-frequency vibrations.

Main Methods:

  • Finite-element method (FEM) analysis was employed for sensor structure design and optimization.
  • Geometrical dimensions of the S-shape spring flexures and proof mass were systematically analyzed.
  • Experimental measurements were conducted to validate the sensor's mechanical and electrical performance.

Main Results:

  • A resonant frequency below 11 Hz was achieved, indicating suitability for low-frequency applications.
  • A voltage output of 7.5 mV was measured at an acceleration threshold of 0.2g.
  • The study demonstrated the impact of geometrical parameters on sensor performance.

Conclusions:

  • The developed Si-based MEMS sensor shows high sensitivity for low-frequency vibration sensing.
  • The sensor design is optimized for faster, less expensive prototyping.
  • Potential for advanced civilian and industrial applications in vibration monitoring and energy harvesting exists.