In order to suppress the influence of temperature changes on the performance of accelerometers,a digital quartz resonant accelerometer with low temperature drift is developed using a quartz resonator cluster as a tran...In order to suppress the influence of temperature changes on the performance of accelerometers,a digital quartz resonant accelerometer with low temperature drift is developed using a quartz resonator cluster as a transducer element.In addition,a digital intellectual property(IP) is designed in FPGA to achieve signal processing and fusion of integrated resonators.A testing system for digital quartz resonant accelerometers is established to characterize the performance under different conditions.The scale factor of the accelerometer prototype reaches 3561.63 Hz/g in the range of -1 g to +1 g,and 3542.5 Hz/g in the range of-10 g to+10 g.In different measurement ranges,the linear correlation coefficient R~2 of the accelerometer achieves greater than 0.998.The temperature drift of the accelerometer prototype is tested using a constant temperature test chamber,with a temperature change from -20℃ to 80℃.After temperature-drift compensation,the zero bias temperature coefficient falls to 0.08 mg/℃,and the scale factor temperature coefficient is 65.43 ppm/℃.The experimental results show that the digital quartz resonant accelerometer exhibits excellent sensitivity and low temperature drift.展开更多
散射中心匹配是当前散射中心用于SAR图像目标识别的一个主要技术途径。散射中心匹配的难点在于散射中心特征存在的误差和缺失。Coherent Point Drift(CPD)方法从概率密度估计的角度解决点模式匹配问题,能够较好地考虑散射中心的误差和...散射中心匹配是当前散射中心用于SAR图像目标识别的一个主要技术途径。散射中心匹配的难点在于散射中心特征存在的误差和缺失。Coherent Point Drift(CPD)方法从概率密度估计的角度解决点模式匹配问题,能够较好地考虑散射中心的误差和缺失。本文将CPD方法用于散射中心匹配,并在此基础上引入车辆目标SAR图像方位角估计先验信息和散射中心属性信息,以提高散射中心匹配的准确性和稳健性。MSTAR数据实验说明了该方法的有效性。展开更多
A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantag...A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective.展开更多
A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG tempe...A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.展开更多
The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer ca...The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.展开更多
Products are often subject to dynamic environmental conditions in field use.When stress transition occurs,products may be exposed to instantaneous shocks that result in shock damages to the products,causing a permanen...Products are often subject to dynamic environmental conditions in field use.When stress transition occurs,products may be exposed to instantaneous shocks that result in shock damages to the products,causing a permanent change of the degradation signals.Meanwhile,under some conditions,instantaneous shocks also lead to stress drift,causing a temporary change of the degradation signals.In this paper,a degradation model is proposed to assess the reliability and predict the residual lifetime of products operating in a dynamic environment considering shock damage and stress drift.The model is established based on a Wiener process which combines a stress-dependent degradation rate function,a shock damage function and a stress drift function in response to the dynamic environment.The shock damage function is established as a linear function of the stress transition start level and the stress level increment.The stress drift function is established as the difference value of a specified function at the stress transition start and end levels.A simulation study is presented to demonstrate the application of the model,and a case study for miniature light bulbs is used to validate the effectiveness of the proposed model.展开更多
In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,trunca...In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,truncation method and the Yamada-Watanabe approximation technique,we derived the strong Feller property of the solution.展开更多
The frequent change in ice drift direction poses a significant challenge for turret moored ship in ice. Variability in ice drift is mainly caused by the winds and currents. To solve this problem, a new method with num...The frequent change in ice drift direction poses a significant challenge for turret moored ship in ice. Variability in ice drift is mainly caused by the winds and currents. To solve this problem, a new method with numerical simulation based on heading control is applied to reduce the risk of operation of The Arctic Tandem Offloading Terminal(ATOT),which includes an offloading icebreaker(OIB) moored to a submerged turret and a shuttle tanker moored at the stern of the OIB in this paper. An icebreaking tanker, MT Uikku, was modeled in a simulation program. Then the level ice load on the tanker was calculated with different ice thicknesses and drift speeds, after which a heading controller assisted with mooring system is used to simulate the horizontal motion of the tanker under the ice action.展开更多
Large temperature drift is an important factor for improving the performance of FOG.A trend term of temperature drift of FOG is obtained using stationary wavelets transform,and an FOG drift algorithm with least square...Large temperature drift is an important factor for improving the performance of FOG.A trend term of temperature drift of FOG is obtained using stationary wavelets transform,and an FOG drift algorithm with least squares wavelet support vector machine(LS-WSVM) is developed.The algorithm used Maxihat wavelet as a kernel function of LS-WSVM to establish an FOG drift model.It has better modeling precise than LS-WSVM model with Gauss kernel.Results indicate the efficiency of this algorithm of LS-WSVM.展开更多
文摘In order to suppress the influence of temperature changes on the performance of accelerometers,a digital quartz resonant accelerometer with low temperature drift is developed using a quartz resonator cluster as a transducer element.In addition,a digital intellectual property(IP) is designed in FPGA to achieve signal processing and fusion of integrated resonators.A testing system for digital quartz resonant accelerometers is established to characterize the performance under different conditions.The scale factor of the accelerometer prototype reaches 3561.63 Hz/g in the range of -1 g to +1 g,and 3542.5 Hz/g in the range of-10 g to+10 g.In different measurement ranges,the linear correlation coefficient R~2 of the accelerometer achieves greater than 0.998.The temperature drift of the accelerometer prototype is tested using a constant temperature test chamber,with a temperature change from -20℃ to 80℃.After temperature-drift compensation,the zero bias temperature coefficient falls to 0.08 mg/℃,and the scale factor temperature coefficient is 65.43 ppm/℃.The experimental results show that the digital quartz resonant accelerometer exhibits excellent sensitivity and low temperature drift.
文摘散射中心匹配是当前散射中心用于SAR图像目标识别的一个主要技术途径。散射中心匹配的难点在于散射中心特征存在的误差和缺失。Coherent Point Drift(CPD)方法从概率密度估计的角度解决点模式匹配问题,能够较好地考虑散射中心的误差和缺失。本文将CPD方法用于散射中心匹配,并在此基础上引入车辆目标SAR图像方位角估计先验信息和散射中心属性信息,以提高散射中心匹配的准确性和稳健性。MSTAR数据实验说明了该方法的有效性。
文摘A novel grey Markov chain predictive model is discussed to reduce drift influence on the output of fiber optical gyroscopes (FOGs) and to improve FOGs' measurement precision. The proposed method possesses advantages of grey model and Markov chain. It makes good use of dynamic modeling idea of the grey model to predict general trend of original data. Then according to the trend, states are divided so that it can overcome the disadvantage of high computational cost of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of the grey model and makes it be fit for prediction of random data with bigger fluctuation. The numerical results of real drift data from a certain type FOG verify the effectiveness of the proposed grey Markov chain model powerfully. The Markov chain is also investigated to provide a comparison with the grey Markov chain model. It is shown that the hybrid grey Markov chain prediction model has higher modeling precision than Markov chain itself, which prove this proposed method is very applicable and effective.
基金supported by the National Natural Science Foundation of China(6110418440904018)+3 种基金the National Key Scientific Instrument and Equipment Development Project(2011YQ12004502)the Research Foundation of General Armament Department(201300000008)the Doctor Innovation Fund of Naval University of Engineering(HGBSCXJJ2011008)the Youth Natural Science Foundation of Naval University of Engineering(HGDQNJJ12028)
文摘A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.
基金supported by the National Natural Science Foundation of China(61503399).
文摘The dual-axis rotational inertial navigation system(INS)with dithered ring laser gyro(DRLG)is widely used in high precision navigation.The major inertial sensor errors such as drift errors of gyro and accelerometer can be averaged out,but the G-sensitive drifts of laser gyro cannot be averaged out by indexing.A 16-position rotational simulation experiment proves the G-sensitive drift will affect the long-term navigation error for the rotational INS quantitatively.The vibration coupling and asymmetric structure of the DRLG are the main errors.A new dithered mechanism and optimized DRLG is designed.The validity and efficiency of the optimized design are conformed by 1 g sinusoidal vibration experiments.An optimized inertial measurement unit(IMU)is formulated and measured experimentally.Laboratory and vehicle experimental results show that the divergence speed of longitude errors can be effectively slowed down in the optimized IMU.In long term independent navigation,the position accuracy of dual-axis rotational INS is improved close to 50%,and the G-sensitive drifts of laser gyro in the optimized IMU are less than 0.0002°/h.These results have important theoretical significance and practical value for improving the structural dynamic characteristics of DRLG INS,especially the highprecision inertial system.
基金supported by the National Natural Science Foundation of China(NSFC71601009)the Technical Foundation Program from the Ministry of Industry and Information Technology of China(JSZL2015601B010)
文摘Products are often subject to dynamic environmental conditions in field use.When stress transition occurs,products may be exposed to instantaneous shocks that result in shock damages to the products,causing a permanent change of the degradation signals.Meanwhile,under some conditions,instantaneous shocks also lead to stress drift,causing a temporary change of the degradation signals.In this paper,a degradation model is proposed to assess the reliability and predict the residual lifetime of products operating in a dynamic environment considering shock damage and stress drift.The model is established based on a Wiener process which combines a stress-dependent degradation rate function,a shock damage function and a stress drift function in response to the dynamic environment.The shock damage function is established as a linear function of the stress transition start level and the stress level increment.The stress drift function is established as the difference value of a specified function at the stress transition start and end levels.A simulation study is presented to demonstrate the application of the model,and a case study for miniature light bulbs is used to validate the effectiveness of the proposed model.
基金Supported by the National Natural Science Foundation of China(11926322)the Fundamental Research Funds for the Central Universities of South-Central MinZu University(CZY22013,3212023sycxjj001)。
文摘In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,truncation method and the Yamada-Watanabe approximation technique,we derived the strong Feller property of the solution.
文摘The frequent change in ice drift direction poses a significant challenge for turret moored ship in ice. Variability in ice drift is mainly caused by the winds and currents. To solve this problem, a new method with numerical simulation based on heading control is applied to reduce the risk of operation of The Arctic Tandem Offloading Terminal(ATOT),which includes an offloading icebreaker(OIB) moored to a submerged turret and a shuttle tanker moored at the stern of the OIB in this paper. An icebreaking tanker, MT Uikku, was modeled in a simulation program. Then the level ice load on the tanker was calculated with different ice thicknesses and drift speeds, after which a heading controller assisted with mooring system is used to simulate the horizontal motion of the tanker under the ice action.
文摘Large temperature drift is an important factor for improving the performance of FOG.A trend term of temperature drift of FOG is obtained using stationary wavelets transform,and an FOG drift algorithm with least squares wavelet support vector machine(LS-WSVM) is developed.The algorithm used Maxihat wavelet as a kernel function of LS-WSVM to establish an FOG drift model.It has better modeling precise than LS-WSVM model with Gauss kernel.Results indicate the efficiency of this algorithm of LS-WSVM.
