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Using Micro-Electro-Mechanical Systems MEMS to Develop Diagnostic Tools
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Note: Parallel processing algorithm of temperature and noise error for micro-electro-mechanical system gyroscope

Chong Shen1, Jiangtao Yang1, Jun Tang1

  • 1National Key Laboratory for Electronic Measurement Technology, School of Instrument and Electronics, North University of China, Taiyuan 030051, People's Republic of China.

The Review of Scientific Instruments
|August 3, 2018
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Summary
This summary is machine-generated.

A new parallel processing algorithm for gyroscope temperature error uses variational mode decomposition (VMD) and an augmented nonlinear differentiator (AND) to improve accuracy. This method synchronizes de-noising and drift compensation, reducing errors in micro-electro-mechanical systems.

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Area of Science:

  • Instrumentation and Measurement
  • Signal Processing
  • Mechanical Engineering

Background:

  • Traditional gyroscope temperature error processing is serial, creating dependencies between de-noising and drift compensation.
  • This serial approach can lead to error propagation, where imperfect de-noising negatively impacts compensation accuracy.

Purpose of the Study:

  • To develop a parallel processing algorithm for gyroscope temperature error that reduces dependence on sequential de-noising.
  • To enhance the efficiency and accuracy of temperature error compensation in micro-electro-mechanical system (MEMS) gyroscopes.

Main Methods:

  • Proposed a parallel processing algorithm integrating Variational Mode Decomposition (VMD) and an Augmented Nonlinear Differentiator (AND).
  • Developed an adaptive accelerometer factor determination method for AND, leveraging VMD for improved de-noising effectiveness.
  • Applied the algorithm to a micro-electro-mechanical system (MEMS) gyroscope.

Main Results:

  • The proposed VMD-AND integrated method enhances de-noising effectiveness.
  • Synchronous extraction and processing of temperature drift and noise reduce compensation dependency on de-noising performance.
  • Demonstrated improved effectiveness and applicability of the parallel processing algorithm for gyroscope temperature error.

Conclusions:

  • The parallel processing algorithm offers a more efficient and accurate method for managing gyroscope temperature errors.
  • Synchronous processing significantly mitigates error propagation issues inherent in traditional serial methods.
  • The integration of VMD, extreme learning machines, and AND provides a robust solution for MEMS gyroscope temperature compensation.