Research On Position And Attitude Monitoring Of Shearer Based On SINS＿WSN Combined Positioning

Coal mine resources are one of the important basic energy sources in my country,and coal mine production is a key basic industry,which strongly supports the country’s industrial development.In order to improve the safety of coal mining,the fully mechanized mining face is developing in the direction of less or even unmanned.The machine position and attitude monitoring technology is also the basis of the "three machines" collaborative technology.Therefore,the position and attitude monitoring of the shearer in the complex and changeable mine environment has become a current research hotspot.This paper takes the shearer as the research object,and studies the shearer positioning technology under the strapdown inertial navigation and the wireless sensor network respectively.Aiming at the positioning defects existing in a single positioning,under the strapdown inertial navigation,the adaptive Kalman based on the fade-out is used.On the basis of the initial alignment of the filtering algorithm and the multi-lateral positioning based on the hybrid filtering and the LSR model under the wireless signal positioning technology,the data fusion of the two positioning technologies is carried out to improve the positioning accuracy.(1)Aiming at the positioning error caused by the initial alignment,which is one of the measurement errors of the inertial navigation system,based on the working principle of inertial navigation,the conversion relationship between coordinate systems and the inertial navigation error model are established,and the standard Kalman filter is improved based on the IGG Ⅲ variable weight innovation covariance.The state equation and the measurement equation are established in the precise alignment process of the initial alignment,and the improved Kalman filter algorithm is used to optimally estimate the measurement noise to improve the positioning accuracy and reduce the influence of accumulated errors.(2)Combined with the complex underground environment of the mine,the wireless sensor network positioning technology is comprehensively analyzed.Based on the analysis of its positioning error,a ranging model is established.Aiming at the measurement positioning error existing in the ranging model,a hybrid filtering and LSR model based method is proposed.Multilateral positioning strategy,and set up a comparison experiment before and after the measurement data processing,to verify the feasibility and accuracy of the WSN positioning method.(3)In view of the inherent cumulative error of pure inertial navigation and cannot be used for long-term positioning and WSN positioning,which is susceptible to signal attenuation,multipath effects,and non-line-of-sight problems,a compact combination positioning model is used,and the improved Kalman filter algorithm is used to detect SINS /WSN positioning data for data fusion,continuous error correction,so as to suppress accumulated errors and improve combined positioning accuracy.