Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them requ...Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them require altering the magnetic vector in the vehicle coordinate system.Exploring the use of geomagnetic variation to change the geomagnetic vector in the vehicle coordinate system,this paper proposes a novel vector magnetic measurement calibration method.In this method,a vector magnetometer mounted on a vehicle and an accurate vector magnetometer separately measure the geomagnetic field at diff erent locations within the same area.Based on the physical principle that the geomagnetic variation at two nearby locations is equal,the calibration parameters of the magnetometer on the vehicle can be determined through a set of equations containing the measurements from the two magnetometers.The theoretical derivation and simulation experiment results demonstrate the feasibility of this method.Therefore,it can serve as a new alternative calibration method,especially in scenarios where a high degree of accuracy in the estimation of calibration parameters is not required.展开更多
In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced...In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced, and a fundamental of multi-cameracalibration based on the large scale calibration target is provided.To avoid the shortcomings of the method, the vector differencesof reprojection error with the presence of the constraint conditionof the constant rigid body transformation is modelled, and mini-mized by the Levenberg-Marquardt （LM） method. Results of thesimulation and observation data calibration experiment show thatthe accuracy of the system calibrated by the proposed methodreaches 2 mm when measuring distance section of 20 000 mmand scale section of 7 000 mm × 7 000 mm. Consequently, theproposed method of multi-camera calibration performs better thanthe fundamental in stability. This technique offers a more uniformerror distribution for measuring large scale space.展开更多
To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the ste...To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.展开更多
In this paper, responses of a new dual-induction resistivity logging-while-drilling （LWD） tool in 3D inhomogeneous formation models are simulated by the vectorfinite element method （VFEM）, the influences of the bo...In this paper, responses of a new dual-induction resistivity logging-while-drilling （LWD） tool in 3D inhomogeneous formation models are simulated by the vectorfinite element method （VFEM）, the influences of the borehole, invaded zone, surroundingstrata, and tool eccentricity are analyzed, and calibration loop parameters and calibrationcoefficients of the LWD tool are discussed. The results show that the tool has a greater depthof investigation than that of the existing electromagnetic propagation LWD tools and is moresensitive to azimuthal conductivity. Both deep and medium induction responses have linearrelationships with the formation conductivity, considering optimal calibration loop parametersand calibration coefficients. Due to the different depths of investigation and resolution, deepinduction and medium induction are affected differently by the formation model parameters,thereby having different correction factors. The simulation results can provide theoreticalreferences for the research and interpretation of the dual-induction resistivity LWD tools.展开更多
Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by...Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by environmental interference and sensor drift,highlighting the need for effective calibration methods to improve data reliability.This study proposes a data correction method based on Bayesian Optimization Support Vector Regression(BO-SVR),which combines the nonlinear modeling capability of Support Vector Regression(SVR)with the efficient global hyperparameter search of Bayesian Optimization.By introducing cross-validation loss as the optimization objective and using Gaussian process modeling with an Expected Improvement acquisition strategy,the approach automatically determines optimal hyperparameters for accurate pollutant concentration prediction.Experiments on real-world micro-sensor datasets demonstrate that BO-SVR outperforms traditional SVR,grid search SVR,and random forest(RF)models across multiple pollutants,including PM_(2.5),PM_(10),CO,NO_(2),SO_(2),and O_(3).The proposed method achieves lower prediction residuals,higher fitting accuracy,and better generalization,offering an efficient and practical solution for enhancing the quality of micro-sensor air monitoring data.展开更多
随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先...随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先,构建预测业务偏差校核流程框架,确定代理购电预测业务校核流程。然后分别选取分位数映射法、增量变化法以及支持向量回归(support vector regression,SVR)对预测结果进行校核,得到同一纬度下的不同方法校核结果。最后,建立遗传算法-优劣解距离法(genetic algorithm-technique for order preference by similarity to ideal solution,GA-TOPSIS)模型针对校核结果进行准确性与稳定性双目标优化,选取不同校核方法的最优权重组合。测试结果表明在校核方法权重组合校正后,相较于初始预测值和单一校核方法校核后的结果,预测精度和准确度得到明显提升。展开更多
基金General Project of Basic Research Plan for Natural Sciences in Shaanxi Province,grant number 2023-JC-YB-244Youth Project of Basic Research Plan for Natural Sciences in Shaanxi Province,grant number 2024JC-YBQN-0253.
文摘Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them require altering the magnetic vector in the vehicle coordinate system.Exploring the use of geomagnetic variation to change the geomagnetic vector in the vehicle coordinate system,this paper proposes a novel vector magnetic measurement calibration method.In this method,a vector magnetometer mounted on a vehicle and an accurate vector magnetometer separately measure the geomagnetic field at diff erent locations within the same area.Based on the physical principle that the geomagnetic variation at two nearby locations is equal,the calibration parameters of the magnetometer on the vehicle can be determined through a set of equations containing the measurements from the two magnetometers.The theoretical derivation and simulation experiment results demonstrate the feasibility of this method.Therefore,it can serve as a new alternative calibration method,especially in scenarios where a high degree of accuracy in the estimation of calibration parameters is not required.
基金supported by the National Natural Science Foundation of China(61473100)
文摘In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced, and a fundamental of multi-cameracalibration based on the large scale calibration target is provided.To avoid the shortcomings of the method, the vector differencesof reprojection error with the presence of the constraint conditionof the constant rigid body transformation is modelled, and mini-mized by the Levenberg-Marquardt （LM） method. Results of thesimulation and observation data calibration experiment show thatthe accuracy of the system calibrated by the proposed methodreaches 2 mm when measuring distance section of 20 000 mmand scale section of 7 000 mm × 7 000 mm. Consequently, theproposed method of multi-camera calibration performs better thanthe fundamental in stability. This technique offers a more uniformerror distribution for measuring large scale space.
文摘To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.
基金supported by the National Oil and Gas Major Projects(No.2011ZX05020-002)
文摘In this paper, responses of a new dual-induction resistivity logging-while-drilling （LWD） tool in 3D inhomogeneous formation models are simulated by the vectorfinite element method （VFEM）, the influences of the borehole, invaded zone, surroundingstrata, and tool eccentricity are analyzed, and calibration loop parameters and calibrationcoefficients of the LWD tool are discussed. The results show that the tool has a greater depthof investigation than that of the existing electromagnetic propagation LWD tools and is moresensitive to azimuthal conductivity. Both deep and medium induction responses have linearrelationships with the formation conductivity, considering optimal calibration loop parametersand calibration coefficients. Due to the different depths of investigation and resolution, deepinduction and medium induction are affected differently by the formation model parameters,thereby having different correction factors. The simulation results can provide theoreticalreferences for the research and interpretation of the dual-induction resistivity LWD tools.
文摘Miniature air quality sensors are widely used in urban grid-based monitoring due to their flexibility in deployment and low cost.However,the raw data collected by these devices often suffer from low accuracy caused by environmental interference and sensor drift,highlighting the need for effective calibration methods to improve data reliability.This study proposes a data correction method based on Bayesian Optimization Support Vector Regression(BO-SVR),which combines the nonlinear modeling capability of Support Vector Regression(SVR)with the efficient global hyperparameter search of Bayesian Optimization.By introducing cross-validation loss as the optimization objective and using Gaussian process modeling with an Expected Improvement acquisition strategy,the approach automatically determines optimal hyperparameters for accurate pollutant concentration prediction.Experiments on real-world micro-sensor datasets demonstrate that BO-SVR outperforms traditional SVR,grid search SVR,and random forest(RF)models across multiple pollutants,including PM_(2.5),PM_(10),CO,NO_(2),SO_(2),and O_(3).The proposed method achieves lower prediction residuals,higher fitting accuracy,and better generalization,offering an efficient and practical solution for enhancing the quality of micro-sensor air monitoring data.
文摘随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先,构建预测业务偏差校核流程框架,确定代理购电预测业务校核流程。然后分别选取分位数映射法、增量变化法以及支持向量回归(support vector regression,SVR)对预测结果进行校核,得到同一纬度下的不同方法校核结果。最后,建立遗传算法-优劣解距离法(genetic algorithm-technique for order preference by similarity to ideal solution,GA-TOPSIS)模型针对校核结果进行准确性与稳定性双目标优化,选取不同校核方法的最优权重组合。测试结果表明在校核方法权重组合校正后,相较于初始预测值和单一校核方法校核后的结果,预测精度和准确度得到明显提升。
