Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM
This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition param...
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MDPI AG
2025-04-01
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| author | Hongqiao Huang Wen Ye Li Liu Wenjing Wang Yan Wang Huiliang Cao |
| author_facet | Hongqiao Huang Wen Ye Li Liu Wenjing Wang Yan Wang Huiliang Cao |
| author_sort | Hongqiao Huang |
| collection | DOAJ |
| description | This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. Then, TVFEMD decomposes the gyroscope output signal into a series of product function (PF) signals and a residual signal. Next, sample entropy (SE) is employed to classify the decomposed signals into three categories: noise segment, mixed segment, and feature segment. According to the parallel model structure, the noise segment is directly discarded. Meanwhile, time–frequency peak filtering (TFPF) is applied to denoise the mixed segment, while the feature segment undergoes compensation. For compensation, the football team training algorithm (FTTA) is used to optimize the parameters of the long short-term memory (LSTM) neural network, forming a novel FTTA-LSTM architecture. Both simulations and experimental results validate the effectiveness of the proposed algorithm. After processing the MEMS gyroscope output signal using the PSO-TVFEMD-SE-TFPF denoising algorithm and the FTTA-LSTM temperature drift compensation model, the angular random walk (ARW) of the MEMS gyroscope is reduced to 0.02°/√h, while the bias instability (BI) decreases to 2.23°/h. Compared to the original signal, ARW and BI are reduced by 99.43% and 97.69%, respectively. The proposed fusion-based temperature compensation method significantly enhances the temperature stability and noise performance of the gyroscope. |
| format | Article |
| id | doaj-art-b9eea4cd7ee24c5081e85702c7218866 |
| institution | Kabale University |
| issn | 2072-666X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Micromachines |
| spelling | doaj-art-b9eea4cd7ee24c5081e85702c72188662025-08-20T03:47:54ZengMDPI AGMicromachines2072-666X2025-04-0116550710.3390/mi16050507Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTMHongqiao Huang0Wen Ye1Li Liu2Wenjing Wang3Yan Wang4Huiliang Cao5Key Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, ChinaNational Institute of Metrology, China, 18 North Third Ring East Road, Chaoyang District, Beijing 100029, ChinaMechanized Infantry Reconnaissance Department, The Army Infantry Academy of PLA, Shijiazhuang 050083, ChinaSchool of Microelectronics, University of Science and Technology of China, Hefei 230022, ChinaAutomobile NCO School, Army Military Transportation University, No. 1155 Yanshan Road, Yuhui District, Bengbu 233010, ChinaKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, ChinaThis study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. Then, TVFEMD decomposes the gyroscope output signal into a series of product function (PF) signals and a residual signal. Next, sample entropy (SE) is employed to classify the decomposed signals into three categories: noise segment, mixed segment, and feature segment. According to the parallel model structure, the noise segment is directly discarded. Meanwhile, time–frequency peak filtering (TFPF) is applied to denoise the mixed segment, while the feature segment undergoes compensation. For compensation, the football team training algorithm (FTTA) is used to optimize the parameters of the long short-term memory (LSTM) neural network, forming a novel FTTA-LSTM architecture. Both simulations and experimental results validate the effectiveness of the proposed algorithm. After processing the MEMS gyroscope output signal using the PSO-TVFEMD-SE-TFPF denoising algorithm and the FTTA-LSTM temperature drift compensation model, the angular random walk (ARW) of the MEMS gyroscope is reduced to 0.02°/√h, while the bias instability (BI) decreases to 2.23°/h. Compared to the original signal, ARW and BI are reduced by 99.43% and 97.69%, respectively. The proposed fusion-based temperature compensation method significantly enhances the temperature stability and noise performance of the gyroscope.https://www.mdpi.com/2072-666X/16/5/507MEMS ring gyroscopetemperature compensationnoise |
| spellingShingle | Hongqiao Huang Wen Ye Li Liu Wenjing Wang Yan Wang Huiliang Cao Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM Micromachines MEMS ring gyroscope temperature compensation noise |
| title | Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM |
| title_full | Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM |
| title_fullStr | Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM |
| title_full_unstemmed | Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM |
| title_short | Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM |
| title_sort | temperature compensation method for mems ring gyroscope based on pso tvfemd se tfpf and ftta lstm |
| topic | MEMS ring gyroscope temperature compensation noise |
| url | https://www.mdpi.com/2072-666X/16/5/507 |
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