Slope deformation partitioning and monitoring points optimization based on cluster analysis

The scientific and fair positioning of monitoring locations for surface displacement on slopes is a prerequisite for early warning and forecasting.However,there is no specific provision on how to effectively determine the number and location of monitoring points according to the actual deformation characteristics of the slope.There are still some defects in the layout of monitoring points.To this end,based on displacement data series and spatial location information of surface displacement monitoring points,by combining displacement series correlation and spatial distance influence factors,a spatial deformation correlation calculation model of slope based on clustering analysis was proposed to calculate the correlation between different monitoring points,based on which the deformation area of the slope was divided.The redundant monitoring points in each partition were eliminated based on the partition's outcome,and the overall optimal arrangement of slope monitoring points was then achieved.This method scientifically addresses the issues of slope deformation zoning and data gathering overlap.It not only eliminates human subjectivity from slope deformation zoning but also increases the efficiency and accuracy of slope monitoring.In order to verify the effectiveness of the method,a sand-mudstone interbedded CounterTilt excavation slope in the Chongqing city of China was used as the research object.Twenty-four monitoring points deployed on this slope were monitored for surface displacement for 13 months.The spatial location of the monitoring points was discussed.The results show that the proposed method of slope deformation zoning and the optimized placement of monitoring points are feasible.

Land deformation monitoring in mining area with PPP-AR

The mining area deformation monitoring theory and method using precise point positioning （PPP） ambi- guity resolution （AR） were studied, and an ambiguity fixing model with satellite and receiver combina- tion phase delay （CPD） was proposed for zero-differenced PPP ambiguity fixing and its corresponding formula derivation was given. The data processing results for I h at six IGS stations in China show that 93% of ambiguities can be fixed within 10 min and all ambiguities can be fixed within 15 min. After ambi- guity fixing, the positioning accuracy is improved by more than 85% in the E and N directions, with abso- lute positioning accuracy reaching millimeter level, and it was improved by 70% in the U direction, reaching centimeter level; the proposed zero-differenced ambiguity fixing model can effectively improve the convergence rate and positioning accuracy in PPP. Data monitoring continuously conducted for half a year at four COPS stations of Shanxi China Coal Pingshuo Group validated the feasibility of using PPP in mining area deformation monitoring.

Distributed fiber optic sensors for tunnel monitoring:A state-of-the-art review

Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.

Grey associated analysis of the underground water quality effected by the leaching water of dumping area or hillock of coal mine

The underground water has been contaminated seriously by the leaching water of dumping area or hillock. To determine the pollution limits of underground water, author took samples in the study area, analyzed samples for water quality, assessed the water quality of each monitoring point by the grey associated analysis method, and gave out the classifications of the underground water quality of the study area. Comparing with fuzzy comprehensive appraisal method, it is demonstrated that grey associated analysis method is applied easily, because of its clear concept, simple and convenient calculation and excellently operation.

Crack status analysis for concrete dams based on measured entropy

The integrity and safety of concrete darns are seriously affected by the existing cracks in dam bodies, and some serious cracks may cause dam failure or disaster. The propagation of cracks in concrete dams is accompanied by changes in energy distribution, which can be represented by changes in the structure＇s system entropy. Therefore, the entropy theory can be used in analyzing the behavior of dam cracks. Due to the randomness and locality of crack propagation, it is difficult to predict the loca- tion of cracks by traditional monitoring methods. To solve this problem, the influence of spatial positions of monitoring points on inspection zones is represented by a weight index, and the weight index is determined by the distance measure method proposed in this paper. Through the weighted linear fusion method, the entropy of multiple monitoring points is obtained for analyzing the behavior of dam cracks in the selected zones. Meanwhile, the catastrophe theory is used as the variation criterion of an entropy sequence in order to predict the instability time of dam cracks. Case studies are put forward on a high arch darn, and the fusion entropy is calculated according to the monitoring data from strain gauges. Results show that the proposed method can effectively predict the occurrence time and location of dam cracks regardless of the layout of monitoring instruments, and it is a new way to analyze the occurrence and propagation of dam cracks.