Research On Magnetic Compensation Method Of Superconducting Tensor Aeromagnetic Gradient Measurement System

Magnetic detection is an important technical means for mineral resources exploration in the field of geophysics.With the continuous improvement of the sensitivity of the detection sensor,the magnetic interference caused by the measurement platform and the external magnetic environment to the sensor has become a key factor restricting the accuracy of the magnetic measurement data.Scholars at home and abroad have done a lot of work on magnetic compensation,and the traditional compensation scheme of the total magnetic field has tended to be perfect.But the compensation of the magnetic gradient tensor field is still dominated by simulation,which means there is often a large difference between the simulation results and the real data.At present,there is no aeromagnetic tensor compensation method that can be effectively applied to the real data.Based on the LTS full tensor aeromagnetic gradient measurement system,this paper establishes corresponding compensation methods for different interference sources from a practical point of view.We use the combination of frequency domain smoothing filter and wavelet filter to suppress the power frequency interference and high frequency noise in the magnetic gradient tensor data.On the basis of the traditional magnetic compensation model,a magnetic tensor compensation model is constructed.A magnetic sphere model is established based on the interference of the equipment in the pod to the measuring instrument.In this paper,the generated magnetic disturbance is described by the vector magnetic moment,and the magnetic compensation model is simplified to the form of a system of linear equations.On this basis,two ways to solve the compensation equation are given: least squares method and Huber norm fitting.The difference between the two in data fitting is compared with an example,and a method based on Huber norm fitting is proposed to solve the compensation model.The compensation model is tested with survey line data,and the test results show that the compensation model is effective and can greatly improve the quality of tensor data.Finally,the applicability of the magnetic compensation model is verified using closed box data.The final results show that the compensation method can be effectively applied to the real data,and the average comprehensive compensation improvement ratio is 372.