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Temperature Compensation for MEMS Accelerometer Based on a Fusion Algorithm
Yangyanhao Guo1, Zihan Zhang2, Longkang Chang3
1Key Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China.
Micromachines
|July 27, 2024
Summary
This study introduces a novel algorithm combining variational modal decomposition (VMD), FE algorithm, forward linear prediction (FLP), and particle swarm optimization-back propagation (PSO-BP) to effectively reduce temperature drift in accelerometer signals.
Area of Science:
- Sensor technology
- Signal processing
- Data fusion
Background:
- Accelerometer performance is often compromised by temperature drift, affecting measurement accuracy.
- Existing methods for temperature compensation may be insufficient or overly complex.
- Accurate temperature compensation is crucial for reliable sensor data in various applications.
Purpose of the Study:
- To propose and validate a novel fusion algorithm for compensating temperature drift in accelerometer signals.
- To enhance the accuracy and reliability of accelerometer measurements under varying temperatures.
- To improve key performance metrics such as acceleration random walk, zero deviation, and temperature coefficient.
Main Methods:
- Decomposition of accelerometer signals into intrinsic mode functions (IMFs) using variational modal decomposition (VMD).
- Separation of IMFs into mixed components, temperature drift, and pure noise using the FE algorithm.
- Denoising of mixed noise via forward linear prediction (FLP).
- Development of a temperature adjustment model using particle swarm optimization-back propagation (PSO-BP).
- Reconstruction of processed components to obtain an enhanced output signal.
Main Results:
- The VMD-FE-FLP-PSO-BP algorithm significantly improved accelerometer performance.
- Acceleration random walk was enhanced by 23%.
- Zero deviation was improved by 24%.
- Temperature coefficient showed a remarkable enhancement of 92% compared to the original signal.
Conclusions:
- The proposed VMD-FE-FLP-PSO-BP fusion algorithm effectively compensates for temperature drift in accelerometer signals.
- The method demonstrates substantial improvements in key performance metrics, validating its efficacy.
- This approach offers a promising solution for enhancing the precision and stability of accelerometers in temperature-sensitive environments.
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