Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer

Jing-Min Gao; Ke-Bei Zhang; Fu-Bin Chen; Hong-Bo Yang

doi:10.1007/s11633-015-0899-5

October 2015

Article Contents

Jing-Min Gao, Ke-Bei Zhang, Fu-Bin Chen and Hong-Bo Yang. Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer. International Journal of Automation and Computing, vol. 12, no. 5, pp. 540-550, 2015. doi: 10.1007/s11633-015-0899-5

Cite as: Jing-Min Gao, Ke-Bei Zhang, Fu-Bin Chen and Hong-Bo Yang. Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer. International Journal of Automation and Computing, vol. 12, no. 5, pp. 540-550, 2015. doi: 10.1007/s11633-015-0899-5

Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer

Electronic Information and Control Center, Beijing Information Science & Technology University, Beijing 100085, China;
Beijing Institute of Control Engineering, Beijing 100080, China;
School of Automation, Beijing Information Science & Technology University, Beijing 100085, China

Received: 2013-09-12

Fund Project:

This work was supported by the Importation and Development of High-caliber Talents Project of Beijing Municipal Institutions (No. IT&TCD201304115).

Abstract

Reduction of error due to the influence of temperature on the quartz flexible accelerometer without any heating device is a difficult task, and is also a tendency for research and application. In this paper, static and dynamic temperature compensation models are established in order to reduce the temperature influence on accelerometer measurement accuracy. Combined with the experiment data, the relationship between the accelerometer output accuracy, temperature and the magnitude of acceleration is analyzed. The data collected from the temperature experiment show that output value of the accelerometer varies with temperature. The method of uniaxial quadrature experiment is adopted and the accelerometer output value is gauged at temperature ranging from -20℃ to 50℃. Having used the static and the dynamic temperature compensation models, the accelerometer temperature error compensation experiment is conducted and the compensated errors by the two models are analyzed. The result shows that the compensated value meets the technical requirements. Two technical indicators, the zero bias K₀ and the scaling factor K₁, which are used to measure the degree of accelerometers, are both improved and their fluctuation ranges are reduced.
- Acceleration,
- error compensation,
- temperature characteristics,
- quadrature experiment,
- differential mode

References

[1]	K. Albert, T. David. High accelerometer, high performance solid state accelerometer development. Electronics Letters, vol.,38, no.,23, pp.,20-25, 1994.
[2]	H. Hamacher. Microgravity characterisation and microgravity improvement for the columbus orbiting facility. In Proceedings of Space Satation Utilisation, ESOC, Darmstadt, Germang, SP-385, pp.,209-219, 1996.
[3]	R. V. Alauev, Y. V. Ivanov, D. M. Malyutin, V. Y. Raspopov, V. A. Dmitriev, S. P. Ermilov, G. A. Ermilova. High-precision algorithmic compensation of temperature instability of accelerometer's scaling factor. Automation and Remote Control, vol.,72, no.,4, pp.,853-860, 2011.
[4]	R. Levy, Q. L. Traon, S. Masson, O. Ducloux, D. Janiaud, J. Guerard, V. Gaudineau, C. Chartier. An integrated resonator-based thermal compensation for vibrating beam accelerometers. In Proceedings of the IEEE Sensors, IEEE, Taipei, Taiwan, China, pp.,1-5, 2012.
[5]	Y. J. Pan, L. L. Li, C. H. Ren, H. L. Luo. Study on the compensation for a quartz accelerometer based on a wavelet neural network. Measurement Science & Technology, vol.,21, no.,10, pp.,102-115, 2010.
[6]	Y. Yu, Y. S. Zhong. High precision two-stage robust temperature control for accelerometer unit. Acta Aeronautica et Astronautica Sinica, vol.,30, no.,6, pp.,1103-1108, 2009. (in Chinese)
[7]	J. Lee, R. Jaewook. Temperature compensation method for the resonant frequency of a differential vibrating accelerometer using electrostatic stiffness control. Journal of Micromechanics and Microengineering, vol.,22, no.,9, pp.,172-184, 2012.
[8]	S. Eichstat, A. Link, T. Bruns. On-line dynamic error compensation of accelerometers by uncertainty-optimal filtering. Measurement, vol.,43, no.,5, pp.,708-713, 2010.
[9]	D. H. Li, X. Y. Gao, Z. X. Zhang, F. Zhou. Research on temperature property of piezoelectric vibration accelerometer based on cymbal transducer. Ferroelectrics, vol.,405, no.,1, pp126-132, 2010.
[10]	S. Shinomiya. Temperature error of two-phase induction generator-type accelerometer and its compensation. Electrical Engineering in Japan, vol.,96, no.,4, pp.,53-59, 1976.
[11]	L. T. Grigorie, R. M. Botez. The bias temperature dependence estimation and compensation for an accelerometer by use of the neuro-fuzzy techniques. Transactions of the Canadian Society for Mechanical Engineering, vol.,32, no.,3-4, pp.,383-340, 2008.
[12]	H. Takao, Y. Matsumoto, M. Ishida, T. Nakamura, H. Tanaka, H. D. Seo. Three-dimensional vector accelerometer using SOI structure for high-temperature use. Electronics and Communications in Japan, vol.,79, no.,3, pp.,61-72, 1996.
[13]	E. Gaura, R. Rider, N. Steele. Neural network based compensation of micromachined accelerometers for static and low frequency applications. In Proceedings of the 13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, New Orleans, USA, pp.,534-542, 2000.
[14]	C. H. Ren, Y. J. Pan, J. F. Li, J. J. Liu. Two-dimensional compensation on time and temperature drift of quartzose flexible accelerometer based on neural network. Journal of Chinese Inertial Technology, vol.,15, no.,3, pp.,366-376, 2007.
[15]	L.T. Grigorie. The bias temperature dependence estimation and compensation for an accelerometer by the use of the neuro-fuzzy techniques. Transactions of the Canadian Society for Mechanical Engineering, vol.,32, no.,3-4, pp.,383-400, 2008.
[16]	Z. Xu, Y. F. Liu, J. X. Dong. Thermal bias drift compensation of MEMS accelerometer based on relevance vector machine. Journal of Beijing University of Aeronautics and Astronautics, vol.,39, no.,11, pp.,1558-1562, 2013.
[17]	X. F. Li, D. H. Li, J. M. Gao, M. Pang. Temperature drift compensation algorithm based on BP and GA in quartz flexible accelerometer. Applied Mechanics and Mechanical Engineering, vol.,249-250, pp.,95-99, 2013.
[18]	M. L. Ding, Q. D. Zhou, K. Song. A new method for accelerometer dynamic compensation based on CMAC. In Proceedings of the 4th International Symposium on Neural Networks:Advances in Neural Networks, Nanjing, China, pp.,667-675, 2007.
[19]	L. Lang, J. G. Chen, M. P. Wu. Study of the temperature error model and the technology for compensating temperature of the quartz flexible accelerometer. Navigation and Control, vol.,8, no.,2,pp.,46-51, 2009. (in Chinese)
[20]	R. V. Alaluev, Y. V. Ivanov, D. M. Malyutin, V. Y. Raspopov, V. A. Dmitriev, S. P. Ermilov, G. A. Ermilova. High-precision algorithmic compensation of temperature instability of accelerometer's scaling factor. Automation and Remote Control, vol.,72, no.,4, pp.,853-860, 2011.
[21]	Test Methods for Single-axis Pendulous Servo Linear Accelerometers, National Science and Technology Commission, GJB 1037-2004, 2004. (in Chinese)
[22]	Verification Equipment of Linear Accelerometer by Earth's Gravitation. State Administration of Quality Supervision and Inspection Quarantine, GJB 1071-2011, 2011. (in Chinese)
[23]	V. M. Gotlib, E. N. Evlanov, B. V. Zhbkov,V. M. Linkin, A. B. Manukin, S. N. Podkolzin, V. I. Rebrov. High-sensitivity quartz accelerometer for measurements of small accelerations of spacecraft. Cosmic Research, vol.,42, no.,1, pp.,54-59, 2004.
[24]	F. Li, L. Y. Wang, J. H. Zhao. Research on error compensation for oil drilling angle based on ANFIS. In Proceedings of the 3th International Conference on Intelligent Computing, Springer, Qingdao, China, pp.,730-737, 2007.
[25]	B. V. Amini, F. Ayazi. Micro-gravity capacitive silicon-on-insulator accelerometers. Journal of Micromechanics and Microengineering, vol.,15, no.,11, pp.,2113-2120, 2005.
[26]	M. A. Barulina, V. E. Dzhashitov, V. M. Pankratov, M. A. Kalinin, A. A. Papko. Mathematical model of a micromechanical accelerometer with temperature influences, dynamic effects, and the thermoelastic stress-strain state taken into account. Gyroscopy and Navigation, vol.,1, no.,1, pp.,52-61, 2010.
[27]	K. I. Lee, H. Takao, K. Sawada, H. D. Seo M. Ishida. Improvement of thermal response in temperature controlled precise three-axis accelerometer with stabilized characteristics over a wide temperature range. In Proceedings of the 13th International Conference on Solid-State Sensors, Actuators, and Microsystems, IEEE, Seoul, South Korea, vol.,1, pp.,800-803, 2005.
[28]	J. Mackley, S. Nahavandi. Active temperature compensation for an accelerometer based angle measuring device. In Proceedings of the Intelligent Automation and Control Trends, IEEE, Seville, Spain, pp.,383-388, 2004.
[29]	A. Stefani, W. Yuan, C. Markos, H. K. Rasmussen, S. Andresen, R. Guastavino, F. K. Nielsen, B. Rose, O. Jespersen, N. Herholdt-Rasmussen, O. Bang. Temperature compensated, humidity insensitive, high-Tg TOPAS FBGs for accelerometers and microphones. In Proceedings of the 22nd International Conference on Optical Fiber Sensors, Beijing, China, vol.,8421, pp.,100-115, 2012.
[30]	X. T. Yu, L. Zhang, L. R. Guo, F. Zhou. Identification for temperature model of accelerometer based on proximal SVR and particle swarm optimization algorithms. Journal of Control Theory and Applications, vol.,10, no.,3, pp.,349-353, 2012.
[31]	J. Lundberg, A. Parida, P. Söoderholm. Running temperature and mechanical stability of grease as maintenance parameters of railway bearings. International Journal of Automation & Computing, vol.,7, no.,2, pp.,160-166, 2010.

Metrics

[1]	Guo-Han Lin, Jing Zhang, Liu Zhao-Hua. Hybrid Particle Swarm Optimization with Differential Evolution for Numerical and Engineering Optimization . International Journal of Automation and Computing, 2018, 15(1): 103-114. doi: 10.1007/s11633-016-0990-6
[2]	Hui-Bo Zhou, Jun-Hong Song, Shen-Min Song. Sliding Mode Guidance Law Considering Missile Dynamic Characteristics and Impact Angle Constraints . International Journal of Automation and Computing, 2018, 15(2): 218-227. doi: 10.1007/s11633-016-0953-y
[3]	Deqing Huang, Jian-Xin Xu, Xin Deng, Venkatakrishnan Venkataramanan, The Cat Tuong Huynh. Differential Evolution Based High-order Peak Filter Design with Application to Compensation of Contact-induced Vibration in HDD Servo Systems . International Journal of Automation and Computing, 2017, 14(1): 45-56. doi: 10.1007/s11633-016-1034-y
[4]	Yuan Ge, Yaoyiran Li. SCHMM-based Compensation for the Random Delays in Networked Control Systems . International Journal of Automation and Computing, 2016, 13(6): 643-652. doi: 10.1007/s11633-016-1001-7
[5]	Dong-Feng Fang Zhou Su Qi-Chao Xu Ze-Jun Xu. Multi-characteristics Based Data Scheduling Over the Smart Grid . International Journal of Automation and Computing, 2016, 13(2): 151-158. doi: 10.1007/s11633-016-0959-5
[6]	Shotaro Kawahata, Ming-Cong Deng. Operator-based Nonlinear Temperature Control Experiment for Microreactor Group Actuated by Peltier Devices . International Journal of Automation and Computing, 2016, 13(4): 401-408. doi: 10.1007/s11633-016-0994-2
[7]	Mohamadreza Homayounzade, Mehdi Keshmiri, Mostafa Ghobadi. A Robust Tracking Controller for Electrically Driven Robot Manipulators: Stability Analysis and Experiment . International Journal of Automation and Computing, 2015, 12(1): 83-92. doi: 10.1007/s11633-014-0850-1
[8]	Yi-Heng Wei, Zhen-Yuan Sun, Yang-Sheng Hu, Yong Wang. On Fractional Order Adaptive Observer . International Journal of Automation and Computing, 2015, 12(6): 664-670. doi: 10.1007/s11633-015-0929-3
[9]	Jie Chen, Cun-Bao Ma, Dong Song. Kinetic Characteristics Analysis of Aircraft During Heavy Cargo Airdrop . International Journal of Automation and Computing, 2014, 11(3): 313-319. doi: 10.1007/s11633-014-0794-5
[10]	Fang-Fang Zhang, Shu-Tang Liu, Ke-Xin Liu. Adaptive Control of Accumulative Error for Nonlinear Chaotic Systems . International Journal of Automation and Computing, 2014, 11(5): 527-535. doi: 10.1007/s11633-014-0821-6
[11]	Lei-Po Liu, Zhu-Mu Fu, Xiao-Na Song. Tracking Control of a Class of Differential Inclusion Systems via Sliding Mode Technique . International Journal of Automation and Computing, 2014, 11(3): 308-312. doi: 10.1007/s11633-014-0793-6
[12]	Hossein Beikzadeh, Hamid D. Taghirad. Exponential Nonlinear Observer Based on the Differential State-dependent Riccati Equation . International Journal of Automation and Computing, 2012, 9(4): 358-368. doi: 10.1007/s11633-012-0656-y
[13]	. Error Bound for the Generalized Complementarity Problem with Analytic Functions . International Journal of Automation and Computing, 2012, 9(3): 288-291. doi: 10.1007/s11633-012-0646-0
[14]	Xiao-Yong Mei, Yi-Yan Fan, Chang-Qin Huang, Ai-Jun Jiang, Shi-Xian Li. An Aggregation Composition Compensation Method Based on Paired Net . International Journal of Automation and Computing, 2012, 9(5): 530-538. doi: 10.1007/s11633-012-0676-7
[15]	Sheng Chen, Wang Yao, Lajos Hanzo. Semi-blind Adaptive Beamforming for High-throughput Quadrature Amplitude Modulation Systems . International Journal of Automation and Computing, 2010, 7(4): 565-570. doi: 10.1007/s11633-010-0541-5
[16]	Jan Lundberg, Aditya Parida, Peter Söderholm. Running Temperature and Mechanical Stability of Grease as Maintenance Parameters of Railway Bearings . International Journal of Automation and Computing, 2010, 7(2): 160-166. doi: 10.1007/s11633-010-0160-1
[17]	Bidyadhar Subudhi, Debashisha Jena. An Improved Differential Evolution Trained Neural Network Scheme for Nonlinear System Identification . International Journal of Automation and Computing, 2009, 6(2): 137-144. doi: 10.1007/s11633-009-0137-0
[18]	Suchin Arunsawatwong, Van Quang Nguyen. Design of Retarded Fractional Delay Differential Systems Using the Method of Inequalities . International Journal of Automation and Computing, 2009, 6(1): 22-28. doi: 10.1007/s11633-009-0022-x
[19]	Ilona Pabst, Peter C. Müler. General Conditions for Online Estimation and Optimization of Reliability Characteristics . International Journal of Automation and Computing, 2006, 3(2): 177-183. doi: 10.1007/s11633-006-0177-7
[20]	Jie Chen, Feng Pan, Tao Cai. Acceleration Factor Harmonious Particle Swarm Optimizer . International Journal of Automation and Computing, 2006, 3(1): 41-46. doi: 10.1007/s11633-006-0041-9

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Cite This Article

PDF

XML

Entire Issue PDF

用微信扫码二维码

分享至好友和朋友圈

Metrics

Abstract Views (4785) PDF downloads (1960) Citations (0)

Related Articles

Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer

Electronic Information and Control Center, Beijing Information Science & Technology University, Beijing 100085, China;

Beijing Institute of Control Engineering, Beijing 100080, China;

School of Automation, Beijing Information Science & Technology University, Beijing 100085, China

Received: 2013-09-12

Fund Project:

This work was supported by the Importation and Development of High-caliber Talents Project of Beijing Municipal Institutions (No. IT&TCD201304115).

Key words:

Abstract: Reduction of error due to the influence of temperature on the quartz flexible accelerometer without any heating device is a difficult task, and is also a tendency for research and application. In this paper, static and dynamic temperature compensation models are established in order to reduce the temperature influence on accelerometer measurement accuracy. Combined with the experiment data, the relationship between the accelerometer output accuracy, temperature and the magnitude of acceleration is analyzed. The data collected from the temperature experiment show that output value of the accelerometer varies with temperature. The method of uniaxial quadrature experiment is adopted and the accelerometer output value is gauged at temperature ranging from -20℃ to 50℃. Having used the static and the dynamic temperature compensation models, the accelerometer temperature error compensation experiment is conducted and the compensated errors by the two models are analyzed. The result shows that the compensated value meets the technical requirements. Two technical indicators, the zero bias K₀ and the scaling factor K₁, which are used to measure the degree of accelerometers, are both improved and their fluctuation ranges are reduced.

HTML

Reference (31)

[1]	K. Albert, T. David. High accelerometer, high performance solid state accelerometer development. Electronics Letters, vol.,38, no.,23, pp.,20-25, 1994.
[2]	H. Hamacher. Microgravity characterisation and microgravity improvement for the columbus orbiting facility. In Proceedings of Space Satation Utilisation, ESOC, Darmstadt, Germang, SP-385, pp.,209-219, 1996.
[3]	R. V. Alauev, Y. V. Ivanov, D. M. Malyutin, V. Y. Raspopov, V. A. Dmitriev, S. P. Ermilov, G. A. Ermilova. High-precision algorithmic compensation of temperature instability of accelerometer's scaling factor. Automation and Remote Control, vol.,72, no.,4, pp.,853-860, 2011.
[4]	R. Levy, Q. L. Traon, S. Masson, O. Ducloux, D. Janiaud, J. Guerard, V. Gaudineau, C. Chartier. An integrated resonator-based thermal compensation for vibrating beam accelerometers. In Proceedings of the IEEE Sensors, IEEE, Taipei, Taiwan, China, pp.,1-5, 2012.
[5]	Y. J. Pan, L. L. Li, C. H. Ren, H. L. Luo. Study on the compensation for a quartz accelerometer based on a wavelet neural network. Measurement Science & Technology, vol.,21, no.,10, pp.,102-115, 2010.
[6]	Y. Yu, Y. S. Zhong. High precision two-stage robust temperature control for accelerometer unit. Acta Aeronautica et Astronautica Sinica, vol.,30, no.,6, pp.,1103-1108, 2009. (in Chinese)
[7]	J. Lee, R. Jaewook. Temperature compensation method for the resonant frequency of a differential vibrating accelerometer using electrostatic stiffness control. Journal of Micromechanics and Microengineering, vol.,22, no.,9, pp.,172-184, 2012.
[8]	S. Eichstat, A. Link, T. Bruns. On-line dynamic error compensation of accelerometers by uncertainty-optimal filtering. Measurement, vol.,43, no.,5, pp.,708-713, 2010.
[9]	D. H. Li, X. Y. Gao, Z. X. Zhang, F. Zhou. Research on temperature property of piezoelectric vibration accelerometer based on cymbal transducer. Ferroelectrics, vol.,405, no.,1, pp126-132, 2010.
[10]	S. Shinomiya. Temperature error of two-phase induction generator-type accelerometer and its compensation. Electrical Engineering in Japan, vol.,96, no.,4, pp.,53-59, 1976.
[11]	L. T. Grigorie, R. M. Botez. The bias temperature dependence estimation and compensation for an accelerometer by use of the neuro-fuzzy techniques. Transactions of the Canadian Society for Mechanical Engineering, vol.,32, no.,3-4, pp.,383-340, 2008.
[12]	H. Takao, Y. Matsumoto, M. Ishida, T. Nakamura, H. Tanaka, H. D. Seo. Three-dimensional vector accelerometer using SOI structure for high-temperature use. Electronics and Communications in Japan, vol.,79, no.,3, pp.,61-72, 1996.
[13]	E. Gaura, R. Rider, N. Steele. Neural network based compensation of micromachined accelerometers for static and low frequency applications. In Proceedings of the 13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, New Orleans, USA, pp.,534-542, 2000.
[14]	C. H. Ren, Y. J. Pan, J. F. Li, J. J. Liu. Two-dimensional compensation on time and temperature drift of quartzose flexible accelerometer based on neural network. Journal of Chinese Inertial Technology, vol.,15, no.,3, pp.,366-376, 2007.
[15]	L.T. Grigorie. The bias temperature dependence estimation and compensation for an accelerometer by the use of the neuro-fuzzy techniques. Transactions of the Canadian Society for Mechanical Engineering, vol.,32, no.,3-4, pp.,383-400, 2008.
[16]	Z. Xu, Y. F. Liu, J. X. Dong. Thermal bias drift compensation of MEMS accelerometer based on relevance vector machine. Journal of Beijing University of Aeronautics and Astronautics, vol.,39, no.,11, pp.,1558-1562, 2013.
[17]	X. F. Li, D. H. Li, J. M. Gao, M. Pang. Temperature drift compensation algorithm based on BP and GA in quartz flexible accelerometer. Applied Mechanics and Mechanical Engineering, vol.,249-250, pp.,95-99, 2013.
[18]	M. L. Ding, Q. D. Zhou, K. Song. A new method for accelerometer dynamic compensation based on CMAC. In Proceedings of the 4th International Symposium on Neural Networks:Advances in Neural Networks, Nanjing, China, pp.,667-675, 2007.
[19]	L. Lang, J. G. Chen, M. P. Wu. Study of the temperature error model and the technology for compensating temperature of the quartz flexible accelerometer. Navigation and Control, vol.,8, no.,2,pp.,46-51, 2009. (in Chinese)
[20]	R. V. Alaluev, Y. V. Ivanov, D. M. Malyutin, V. Y. Raspopov, V. A. Dmitriev, S. P. Ermilov, G. A. Ermilova. High-precision algorithmic compensation of temperature instability of accelerometer's scaling factor. Automation and Remote Control, vol.,72, no.,4, pp.,853-860, 2011.
[21]	Test Methods for Single-axis Pendulous Servo Linear Accelerometers, National Science and Technology Commission, GJB 1037-2004, 2004. (in Chinese)
[22]	Verification Equipment of Linear Accelerometer by Earth's Gravitation. State Administration of Quality Supervision and Inspection Quarantine, GJB 1071-2011, 2011. (in Chinese)
[23]	V. M. Gotlib, E. N. Evlanov, B. V. Zhbkov,V. M. Linkin, A. B. Manukin, S. N. Podkolzin, V. I. Rebrov. High-sensitivity quartz accelerometer for measurements of small accelerations of spacecraft. Cosmic Research, vol.,42, no.,1, pp.,54-59, 2004.
[24]	F. Li, L. Y. Wang, J. H. Zhao. Research on error compensation for oil drilling angle based on ANFIS. In Proceedings of the 3th International Conference on Intelligent Computing, Springer, Qingdao, China, pp.,730-737, 2007.
[25]	B. V. Amini, F. Ayazi. Micro-gravity capacitive silicon-on-insulator accelerometers. Journal of Micromechanics and Microengineering, vol.,15, no.,11, pp.,2113-2120, 2005.
[26]	M. A. Barulina, V. E. Dzhashitov, V. M. Pankratov, M. A. Kalinin, A. A. Papko. Mathematical model of a micromechanical accelerometer with temperature influences, dynamic effects, and the thermoelastic stress-strain state taken into account. Gyroscopy and Navigation, vol.,1, no.,1, pp.,52-61, 2010.
[27]	K. I. Lee, H. Takao, K. Sawada, H. D. Seo M. Ishida. Improvement of thermal response in temperature controlled precise three-axis accelerometer with stabilized characteristics over a wide temperature range. In Proceedings of the 13th International Conference on Solid-State Sensors, Actuators, and Microsystems, IEEE, Seoul, South Korea, vol.,1, pp.,800-803, 2005.
[28]	J. Mackley, S. Nahavandi. Active temperature compensation for an accelerometer based angle measuring device. In Proceedings of the Intelligent Automation and Control Trends, IEEE, Seville, Spain, pp.,383-388, 2004.
[29]	A. Stefani, W. Yuan, C. Markos, H. K. Rasmussen, S. Andresen, R. Guastavino, F. K. Nielsen, B. Rose, O. Jespersen, N. Herholdt-Rasmussen, O. Bang. Temperature compensated, humidity insensitive, high-Tg TOPAS FBGs for accelerometers and microphones. In Proceedings of the 22nd International Conference on Optical Fiber Sensors, Beijing, China, vol.,8421, pp.,100-115, 2012.
[30]	X. T. Yu, L. Zhang, L. R. Guo, F. Zhou. Identification for temperature model of accelerometer based on proximal SVR and particle swarm optimization algorithms. Journal of Control Theory and Applications, vol.,10, no.,3, pp.,349-353, 2012.
[31]	J. Lundberg, A. Parida, P. Söoderholm. Running temperature and mechanical stability of grease as maintenance parameters of railway bearings. International Journal of Automation & Computing, vol.,7, no.,2, pp.,160-166, 2010.

Temperature Characteristics and Error Compensation for Quartz Flexible Accelerometer

Abstract

References

Metrics

Related Articles

通讯作者: 陈斌, bchen63@163.com

Metrics