Research On Quantity Transfer Technology Of Outdoor Baseline Based On μ-base Rangefinder

Outdoor baseline is the special length standard,it can provide the length reference for measuring instruments such as total station,which is an important standard device to realize the quantity transfer of large size measurement.In order to reduce the influence of crustal movement,foundation settlement and groundwater level change on the standard length of baseline,outdoor baseline should be calibrated regularly.At present,there are three outdoor baseline calibration methods,optical interferometry by Vaisala interference comparator,direct measurement by 24m invar tape and high precision electro-optical measurement,optical interferometry is the most accurate method to calibrate the outdoor baseline.Currently,there is not a baseline calibrated by optical interferometry in China,the calibration of field baselines is mainly realized by using 24m invar tape or high-precision photoelectric rangefinder,the accuracy of these two methods is lower than that of optical interferometry.Due to the low operating efficiency of the 24m invar tape method,μ-base rangefinder has good performance,and its indoor repeatability measurement accuracy is±10 microns,which is better than the ME5000 rangefinder that has been discontinued,and can meet the requirements of high-precision baseline calibration.Therefore,it is necessary to research the quantity transfer technology of outdoor baseline based onμ-base rangefinder,which has important engineering application value and scientific research value.To perfect outdoor baseline calibration specification of China,this thesis on the basis of related research at home and abroad for reference,quantity transfer technology of outdoor baseline based onμ-base rangefinder is emphatically studied.Based on the error analysis ofμ-base rangefinder calibration baseline,it is found that the measurement error of meteorological parameters has the most serious influence on the ranging accuracy.Through the establishment of an automatic collection system of environmental parameters,temperature-induced error suppression technology of outdoor baseline was further studied,and a series of baseline value transfer experiments are carried out.The main work and innovations are as follows:1.An automatic collection system of environmental parameters was designed and built along a baseline in Zhengzhou.Through deducing the formula of meteorological correction,it is found that temperature parameters have more significant influence than air pressure and humidity,therefore,the key research on temperature parameters is carried out.The influence of ventilation and illumination on the measurement accuracy was analyzed,and the field measurement accuracy of the temperature sensor was significantly improved through the improvement of forced ventilation and sunshade of the umbrella.Through system test,the statistical distribution of temperature along the baseline was explored,and the Sunday variation rule of meteorological elements was analyzed and summarized,which provided an optimal choice for the selection of baseline measurement time.Through the experimental study of meteorological parameter gradient of measuring line,the optimal layout method of meteorological sensor is explored.A simple,intuitive and interactive baseline data processing software is designed,it meets the actual measurement needs of surveyors.2.To solve the problem of poor smoothness of broken lines in the equivalent area model,a radial basis neural network model is proposed,which is more consistent with the distribution law of surface temperature.The meteorological correction model ofμ-base is derived,and the effects of two-point method,equivalent area model,piecewise linear interpolation model and radial basis neural network model are evaluated.Experimental results show that piecewise linear interpolation model and radial basis neural network model have the best correction effect.3.Aiming at the problem that the temperature sensors along the baseline are exposed to the outside for a long time,such as data loss and abnormal data,an improved particle filter algorithm is proposed,which combines with sample entropy to correlate the spatiotemporal characteristics of the temperature sensor network.Experimental results show that the improved algorithm is effective.4.In order to perfect the outdoor baseline calibration standard in China,a series of outdoor baseline value transfer experiments were carried out.Based on the automatic collection system of environmental parameters,the measurement and comparison experiments of"multi-point method"and"two-point method"were conducted.The experimental results show that the standard deviation of"multi-point method"was 34.7%less than that of"two-point method".The uncertainty ofμ-base method is evaluated again,under cloudy conditions,the relative extended uncertainty of baseline measurement can reach 0.62?10^6-.Based on theμ-base rangefinder,the precision of the high precision photoelectric ranging baseline was discussed with that of the 24m invar tape,the experimental results showed that the accuracy of the two methods was equal.The combination measurement ofμ-base rangefinder and high-precision GNSS receiver was studied,which can meet the baseline verification requirements for ultra-long distance.When the baseline length is greater than 600m,the relative error between the measurement ofμ-base rangefinder,24m invar tape and high-precision GNSS receiver is less than 1?10^6-D.