In allusion to the limitations of the traditional attitude measurement system consisting of a three-axis magnetic sensor and two accelerometers on high-spinning projectile, a new scheme comprised of two magnetic senso...In allusion to the limitations of the traditional attitude measurement system consisting of a three-axis magnetic sensor and two accelerometers on high-spinning projectile, a new scheme comprised of two magnetic sensors and two accelerometers installed in a particular way is given. The configuration of the sensors is described. The calculation method and the mathematical model of the projectile attitude based on the sensor configuration are discussed. The basic calculation method including the Magsonde Window, the proof of the ratios of maximums and minimums and the calculation of the attitude angles are analyzed in theory. Finally, the system is simulated under the given conditions. The simulation result indicates that the estimated attitude angles are in agreement with the true attitude angles.展开更多
To address the deficiency of existing technologies in long-term,large-scale in-situ seafloor geohazard monitoring,a dynamic monitoring device based on an inertial navigation system was designed.It features a three-lev...To address the deficiency of existing technologies in long-term,large-scale in-situ seafloor geohazard monitoring,a dynamic monitoring device based on an inertial navigation system was designed.It features a three-level architecture with MPU9250 nine-axis sensors,RS485 multi-node communication and independent power supply.An algorithm system combining Euler angle-rotation matrix transformation,Mahony attitude solution and multi-filtering methods was built to realize sensor data denoising,attitude calculation and trajectory reconstruction.Laboratory static and dynamic free-release impact experiments under different inclined angles were conducted for verification.The results show that the device achieves drift-free static data acquisition,accurate and stable dynamic data collection and transmission,and can precisely reconstruct the 3D motion trajectory of monitoring terminals,with the impact acceleration within the measuring range.It meets the basic requirements for seafloor geohazard monitoring and provides a new technical solution for relevant in-situ monitoring.展开更多
Marine seismic exploration is an important part of offshore oil and gasexploration, which requires accurate attitude information of submarine towingequipment. Conventional attitude solution algorithm or Kalman filter ...Marine seismic exploration is an important part of offshore oil and gasexploration, which requires accurate attitude information of submarine towingequipment. Conventional attitude solution algorithm or Kalman filter algorithmcannot satisfy the current requirements of high accuracy, high reliability, strongenvironmental adaptability and low cost. In view of the low accuracy and poorenvironmental adaptability of the traditional Kalman filter algorithm, this paperproposes a CNN-EKF fusion attitude calculation algorithm based on the studyof the extended Kalman filter (EKF) model and the convolutional neural network(CNN) model. The system noise variance matrix (Q) and the observationnoise variance matrix(R)of EKF were optimized by CNN, and the final solutionresults were obtained. Compared the traditional Kalman filtering model with theCNN-EKF fusion filtering model, experimental results shows that the algorithmimproves the accuracy of attitude calculation and enhances the adaptive ability tothe environment.展开更多
文摘In allusion to the limitations of the traditional attitude measurement system consisting of a three-axis magnetic sensor and two accelerometers on high-spinning projectile, a new scheme comprised of two magnetic sensors and two accelerometers installed in a particular way is given. The configuration of the sensors is described. The calculation method and the mathematical model of the projectile attitude based on the sensor configuration are discussed. The basic calculation method including the Magsonde Window, the proof of the ratios of maximums and minimums and the calculation of the attitude angles are analyzed in theory. Finally, the system is simulated under the given conditions. The simulation result indicates that the estimated attitude angles are in agreement with the true attitude angles.
文摘To address the deficiency of existing technologies in long-term,large-scale in-situ seafloor geohazard monitoring,a dynamic monitoring device based on an inertial navigation system was designed.It features a three-level architecture with MPU9250 nine-axis sensors,RS485 multi-node communication and independent power supply.An algorithm system combining Euler angle-rotation matrix transformation,Mahony attitude solution and multi-filtering methods was built to realize sensor data denoising,attitude calculation and trajectory reconstruction.Laboratory static and dynamic free-release impact experiments under different inclined angles were conducted for verification.The results show that the device achieves drift-free static data acquisition,accurate and stable dynamic data collection and transmission,and can precisely reconstruct the 3D motion trajectory of monitoring terminals,with the impact acceleration within the measuring range.It meets the basic requirements for seafloor geohazard monitoring and provides a new technical solution for relevant in-situ monitoring.
基金The research was supported by the National Key Research and Development Program of China(GrantNo.2016YFC0303901)Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(ZJW-2019-04).
文摘Marine seismic exploration is an important part of offshore oil and gasexploration, which requires accurate attitude information of submarine towingequipment. Conventional attitude solution algorithm or Kalman filter algorithmcannot satisfy the current requirements of high accuracy, high reliability, strongenvironmental adaptability and low cost. In view of the low accuracy and poorenvironmental adaptability of the traditional Kalman filter algorithm, this paperproposes a CNN-EKF fusion attitude calculation algorithm based on the studyof the extended Kalman filter (EKF) model and the convolutional neural network(CNN) model. The system noise variance matrix (Q) and the observationnoise variance matrix(R)of EKF were optimized by CNN, and the final solutionresults were obtained. Compared the traditional Kalman filtering model with theCNN-EKF fusion filtering model, experimental results shows that the algorithmimproves the accuracy of attitude calculation and enhances the adaptive ability tothe environment.
