A temperature and humidity synchronization detection method based on microwave coupled-resonator

Guo, Hao; Zhu, Qiang; Tang, Jun; Nian, Fushun; Liu, Wenyao; Zhao, Rui; Du, Fangfang; Yang, Bin; Li, Jun

doi:10.1016/j.snb.2018.01.142

Cited by 37 publications

(20 citation statements)

References 18 publications

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“…Allan variance [27,28]is used to evaluate the noise reduction e ect and temperature compensation e ect of the four methods (Figure 14). e results for the acceleration random walk (which represents the noise characteristics) and zero-bias stability are shown in Table 2.…”

Section: Results Analysismentioning

confidence: 99%

Fusion Algorithm‐Based Temperature Compensation Method for High‐G MEMS Accelerometer

Shen

Cao

et al. 2019

Shock and Vibration

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In recent years, High-G MEMS accelerometers have been widely used in aviation, medicine, and other fields. So it is extremely important to improve the accuracy and performance of High-G MEMS accelerometers. For this purpose, we propose a fusion algorithm that combines EMD, wavelet thresholding, and temperature compensation to process measurement data from a High-G MEMS accelerometer. In the fusion algorithm, the original accelerometer signal is first decomposed by EMD to obtain the intrinsic mode function (IMF). Then, sample entropy (SE) is used to divide the IMF components into three segments. The noise segment is directly omitted, wavelet thresholding is performed on the mixing segment, and a GA-BP performs temperature compensation on the drift segment. Finally, signal reconstruction is implemented. Later, a comparative analysis is carried out on the results from four models: EMD, wavelet thresholding, EMD + wavelet thresholding, and EMD + wavelet thresholding + temperature compensation. The experimental data show that the acceleration random walk change from 1712.66 g/h/Hz0.5 to 79.15 g/h/Hz0.5 and the zero-deviation stability change from 49275 g/h to 774.7 g/h. This indicates that the fusion algorithm (EMD + wavelet thresholding + temperature compensation) not only effectively suppresses the noise of high-frequency components but also compensates for temperature drift in the accelerometer.

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Section: Results Analysismentioning

confidence: 99%

Fusion Algorithm‐Based Temperature Compensation Method for High‐G MEMS Accelerometer

Shen

Cao

et al. 2019

Shock and Vibration

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“…The MEMS gyroscope based on Coriolis acceleration mainly conveys vibration between the drive mode and the detection mode [1,2], due to its advantages such as robustness, low noise, and low power consumption [3], MEMS technology and gyroscopes have been widely used in aviation, aerospace, measuring and other important fields [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

Cao

Shen

2020

Electronics

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To deal with the influence of temperature drift for a Micro-Electro-Mechanical System (MEMS) gyroscope, this paper proposes a new temperature error parallel processing method based on a novel fusion algorithm. Firstly, immune based particle swarm optimization (IPSO) is employed for optimal parameters search for Variational Modal Decomposition (VMD). Then, we can get the optimal decomposition parameters, wherein permutation entropy (PE) is employed as the fitness function of the particles. Then, the improved VMD is performed on the output signal of the gyro to obtain intrinsic mode functions (IMFs). After judging by sample entropy (SE), the IMFs are divided into three categories: noise term, mixed term and feature term, which are processed differently. Filter the mixed term and compensate the feature term at the same time. Finally, reconstruct them and get the result. Compared with other optimization algorithms, IPSO has a stronger global search ability and faster convergence speed. After Back propagation neural network (BP) is enhanced by Adaptive boosting (Adaboost), it becomes a strong learner and a better model, which can approach the real value with higher precision. The experimental result shows that the novel parallel method proposed in this paper can effectively solve the problem of temperature errors.Electronics 2020, 9, 499 2 of 21 circuit design structure to reduce the damping coefficient, which is convenient and economical [15]. Yang et al. adopted a new concept whereby the on-chip temperature compensation of the MEMS gyroscope is realized by the on-chip sensor. In order to make the on-chip temperature of the micro gyroscope well controlled, the newly integrated serpentine micro heater is used to achieve this function [16]. Cui et al. analyzed the working principle of the gyroscope and adopted the vibration compensation of the drive mode, which has a good effect [17]. However, the hardware compensation cost is high and it is too difficult to implement.The second is through software compensation, it includes the removal of noise and temperature compensation. The software compensation method mainly establishes a model for the drift part and the noise part of the MEMS gyroscope to remove noise and compensate drift. For the establishment of the temperature drift model, the reference temperature and the corresponding temperature drift output obtained in advance are used as a set of training set data. The model is established after the learning and training of the algorithm. When the temperature value is input, the model can predict the output value as compensation. There are two main methods. The first one is serial processing, which first uses a filter to perform noise reduction on the signal and then uses a model to eliminate drift. The other one is parallel processing, which refers to extracting and processing noise components and drift components separately. Dominik uses a combination of experiments and numerical values to provide accurate ceramic acceleration at higher temperature [18]. Yang uses a sim...

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“…Studies have shown that the navigation strategies which integrate one or more navigation means, such as GPS [5][6][7], Spectral Redshift [8], Polarized Light [9] etc., with INS can obtain complementary advantages and achieve better navigation results. The Unmanned Aerial Vehicle (UAV) has played an increasingly important role in various fields in recent years [10], to achieve better navigation results, GPS/INS is the most widely used integrated navigation system especially for UAVs [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Brain-Like Navigation Scheme based on MEMS-INS and Place Recognition

et al. 2019

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Animals have certain cognitive competence about the environment so they can correct their navigation errors. Inspired by the excellent navigational behavior of animals, this paper proposes a brain-like navigation scheme to improve the accuracy and intelligence of Micro-Electro-Mechanical System based Inertial Navigation Systems (MEMS-INS). The proposed scheme employs vision to acquire external perception information as an absolute reference to correct the position errors of INS, which is established by analyzing the navigation and error correction mechanism of rat brains. In addition, to improve the place matching speed and precision of the system for visual scene recognition, this paper presents a novel place recognition algorithm that combines image scanline intensity (SI) and grid-based motion statistics (GMS) together which is named the SI-GMS algorithm. The proposed SI-GMS algorithm can effectively reduce the influence of uncertain environment factors on the recognition results, such as pedestrians and vehicles. It solves the problem that the matching result will occasionally go wrong when simply using the scanline intensity (SI) algorithm, or the slow matching speed when simply using grid-based motion statistics (GMS) algorithm. Finally, an outdoor Unmanned Aerial Vehicle (UAV) flight test is carried out. Based on the reference information from the high-precision GPS device, the results illustrate the effectiveness of the scheme in error correction of INS and the algorithm in place recognition.

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A temperature and humidity synchronization detection method based on microwave coupled-resonator

Cited by 37 publications

References 18 publications

Fusion Algorithm‐Based Temperature Compensation Method for High‐G MEMS Accelerometer

Fusion Algorithm‐Based Temperature Compensation Method for High‐G MEMS Accelerometer

A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

Brain-Like Navigation Scheme based on MEMS-INS and Place Recognition

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