Research On Key Technologies For Attitude Monitoring Of Ocean Towing System

In recent years,deep-sea exploration technology has developed rapidly in the world,which has greatly improved the understanding and exploitation level of deep-sea stratum resources,and made it possible to exploit new deep-sea resources.With the improvement of China's economic strength,the demand for exploiting the stratum resources in the sea area is increasing.The main principle of marine seismic prospecting is to transmit seismic waves by the seismograph installed on the ship and receive them by the hydrophone installed on the digital cable after reflection on the sea floor.Through collecting and analyzing the reflected seismic waves,the underground geological structure and other data can be obtained,so as to analyze the reserves and exploitability of resources.Among them,the high precision attitude and heading reference system(AHRS)is the most basic component to support underwater activities such as deep-sea towing.In this paper,the key technology of attitude monitoring of ocean towing system is studied to ensure that the ocean seismic exploration system can work normally and record the position of submarine towing cable nodes in real time.In order to acquire the attitude information of submarine towing equipment accurately,attitude sensitive elements(such as gyroscope,accelerometer,magnetometer,etc.)are used to measure the attitude information of towing body and digital cable.Then the attitude data acquired by towing body and digital cable are retrieved.The collected data are transformed from the independent carrier coordinate system of each hydrophone to the unified geographic coordinate system,so as to facilitate the post-processing of the data collected by the hydrophone and improve the inversion accuracy of seismic data.Data attitude inversion will use quaternion method to solve four unknown linear differential equations and realize coordinate transformation of the whole attitude.The most difficult problem is the multi-sensor data fusion problem caused by different data acquisition characteristics of different sensors.The traditional data fusion method is based on Kalman filter to fuse the multi-sensor data of the non-linear system in order to improve the measurement accuracy.However,due to the inherent limitation of Kalman filter to non-linearity,the measurement accuracy is not satisfied in the experimental measurement.Therefore,based on the existing mathematical methods,we propose a neural network model for data fusion to improve the measurement accuracy.Finally,in order to display the attitude monitoring in real time in the actual application scenario,a software for displaying the attitude information of the towed body and the nodes on the towline is developed.It can be used to monitor the trajectory and working state of the towed body and to calculate the three-dimensional attitude of the digital cable.At the same time,through inversion calculation of the data,the velocity of the towed body,the direction of traveling and the attitude angle of each node of the towed cable are tracked and displayed in the software.