Traditionally, one of the major limitations for magnetic resonance sounding (MRS) measurement is that the weak signal generated by subsurface water molecules is prone to be disturbed by high‐level electromagnetic noise. In China, the power grid coverage is 94.6% and spiky noise and powerline harmonic noise are always present when utilizing MRS measurement in suburban areas or towns. In order to improve the performance of the MRS method, two new techniques, statistical stacking and adaptive notch filter, are introduced to remove spiky noise and power‐line harmonic noise. Firstly, four stacking procedures are analysed to suppress the natural noise and spiky noise. It could be found that statistical stacking can be utilized in the areas with serious spiky noise and can improve the signal‐to‐noise ratio by a factor of 4 to 7. Moreover, the stacking number is less than other stacking procedures and the measurement time may decrease by nearly 50% in some suburban areas or towns. Secondly, there are a variety of filtering procedures available to suppress power‐line harmonic noise, which are all based on analogue or digital notch filtering. But nearly all of them may cause distortion. An adaptive notch filter is applied here to remove power‐line harmonic noise because harmonic frequencies are away from and (or) close to the Larmor frequency, even when the frequency offset between them is zero. From simulation results, it could be noted that the signal can be recovered after adaptive notch filtering because it is not irretrievably distorted but proportionally attenuated. Thus, the amplitude attenuation can accurately be compensated. The effectiveness of the two techniques applied to MRS measurements is demonstrated by field testing with the prototype of the MRS system developed by Jilin University, China. The results show that the statistical stacking and adaptive notch filter are effective methods to remove high‐level electromagnetic noise from MRS measurements.

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The goaf formed by underground mining poses a great safety hazard to the production of the mining area. The accurate calculation of goaf volume is the data basis for the filling and blasting of the goaf, and it also has certain reference significance for the monitoring of collapse accidents. In this paper, the data detected by the 3D ranging scanner is used to build a network model on the Self - developed 3D modeling platform, and the network model is divided into the smallest triangular grid. The algorithm uses the scanner’s laser probe as the common point, accumulates all the minimum tetrahedral volumes constructed by the common point and the smallest triangular grid, and completes the accurate solution of the total volume of the scanned goaf. Experiments and practical applications show that the volumetric algorithm has high accuracy, and has universal applicability to the volume calculation of similar types of space scanning equipment.

Groundwater dynamic monitoring of assessment points and evaluation areas has a significant predictive effect for controlling the occurrence of disasters. Obtaining water level and water temperature change data can provide important theoretical significance and reference values. However, in some remote areas of China, the measurement data concerning water level change are mostly obtained by manual measurement. This measurement method not only wastes manpower, but also cannot ensure the accuracy and real-time nature of the data. Therefore, this paper carried out research and design on a fluviograph, based on the relationship between hydraulic pressure and water depth. In the paper, the fluviograph used ultra-small pressure sensors to complete the data acquisition of the water level, a STM32L011 single-chip microcomputer (STMicroelectronics, Geneva, Switzerland) to process the data, and LabVIEW software to display the final data. Additionally, the water level data record and water temperature information record can be fed back to the user and the manager. After laboratory testing, the water level variation error range of this fluviograph was 1–2 cm, and the water temperature error range was less than 1 °C, which indicates the accuracy of the metrical data. The results show that the fluviograph realizes the function of automatically recording the water level and water temperature of the monitoring point, and it improves the social production efficiency greatly.