Three-axis magnetometer error and measurement noise influence the accuracy of magnetic measurements. Genetic algorithm (GA) is proposed to calibrate the magnetometer error, and wavelet is proposed for noise cancellation. The noise of a Mag3300 magnetometer and a DM magnetometer were tested within a horizontal barrel shield equipment. Five kinds of wavelet analysis and two kinds of wavelet package were used for noise cancellation, and the performance of different wavelets was compared. Noise of the Mag3300 magnetometer and DM magnetometer were suppressed from 29.6 and 2.3466 to 3.7 and 1.0789 nT, respectively. The scalar error of the Mag3300 magnetometer was tested using a two-dimensional nonmagnetic rotation equipment and a GSM-19T proton magnetometer. Scalar calibration performances of the unscented Kalman filter (UKF), the two-step algorithm, and GA were compared. Experimental results show that GA provides less error intensity (about 370 and 70 nT) than UKF and the two-step algorithm. In addition, the influence of wavelet on scalar calibration using UKF, the two-step algorithm, and GA was analyzed. Results show that wavelet improved the scalar calibration performance. Mean error of the Mag3300 magnetometer scalar was 795.5 nT. When combined with the wavelet package, the error was suppressed to −22.3, 3.3, and −0.4 nT using UKF, the two-step algorithm, and GA, respectively. The results suggest an effective way for magnetometer calibration using GA and wavelet.

Abstract. Magnetometer, misalignment error and distortion field can reduce the accuracy of gradiometers. So, it is important to calibrate and compensate gradiometers error. Scale factor, bias, nonorthogonality, misalignment and distortion field should be considered. A gradiometer is connected by an aluminium frame, which contains two fluxgate magnetometers. A nonmagnetic rotation equipment is used to change gradiometer attitude, and the compensation parameters are estimated. Experiment results show that, after calibration and compensation, error of each axis is reduced from 888.4 nT, 1292.6 nT and 168.9 nT to 15.3 nT, 22.1 nT and 9.9 nT, respectively. It shows that the proposed method can calibrate gradiometer and compensate distortion field. After calibration and compensation, the object remote sensing performance is improved.

According to previous monitoring data, the high humidity environment of certain is 30%RH~40%RH when well ventilated. After the project is plugged, the temperature is generally about 18°C, and the humidity rises quickly to about 80%RH within 2 days and gradually increases to 90%RH in next 7 to 10 days, then remaining unchanged. In order to reduce the environmental humidity after backfilling and plugging the tunnel, and control the ambient humidity below 45%RH. This paper describes a humidity control system which could achieve the isolation of the built-in dehumidification system with outside and the dehumidification with a cycle of dry and wet air in the cavern through the remote controlling. The system could accurately measure the volume of condensate water that collected automatically, and discharged the water into the multiple isolation protection deeper hole. The system accumulated dehumidified water is about 3236 kg in 24 days, and the humidity of the cavern can be effectively controlled at around 30%RH.