Abstract
Under the influence of various internal and external factors, the monitoring points are often damaged and abnormal data may occur in the slope deformation monitoring of open-pit mines, which may lead to the deviation of slope stability analysis and errors in slope construction scheme and the prevention and control decision. In order to improve the reliability of slope stability analysis and ensure the safe production and management of mines, it is necessary to correct the abnormal data of deformation monitoring. Taking the slope of Yuebao open-pit mine as the research object, based on the anomaly detection of slope deformation monitoring data, this paper puts forward a spatio-temporal interpolation method of slope deformation monitoring abnormal data considering the change of monitoring point position to correct and interpolate of abnormal data. The experimental results showed that the more uniform the distribution of sample points was, the higher the fitting accuracy of the coordinates of the points to be inserted was, and the Root Mean Square Error (RMSE) of distance increased from 2.56 to 2.17 mm. The uniform distribution of sample points and the change of the spatial distance between the points to be inserted and the sample points had little influence on the degree of fitting the coordinates of the points to be inserted, and the distance RMSE was basically maintained at about 2.2 mm. With the increase of the distance, the interpolation coordinates were closer to the actual values. Compared with Lagrange interpolation and inverse distance weighted interpolation method, the results were more consistent with the real values by the proposed method, and the accuracy is 4–5 times that of the other two methods, proving the feasibility and reliability of the proposed method.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmed SO, Mazloum R, Abou-Ali H (2018) Spatiotemporal interpolation of air pollutants in the Greater Cairo and the Delta Egypt. Environ Res 160(jan.):27–34. https://doi.org/10.1016/j.envres.2017.09.005
Bogaert P (1996) Comparison of kriging techniques in a space-time context. Math Geol 28(1):73–86. https://doi.org/10.1007/BF02273524
Dixon N, Spriggs M (2007) Quantification of slope displacement rates using acoustic emission monitoring. Revue Canadienne De Ge’otechnique 44(8):966–976. https://doi.org/10.1139/T07-046
Duan X (2019) Research on abnormal data detection method of web browser in cloud computing environment. Cluster Comput 22:1229–1238. https://doi.org/10.1007/s10586-017-1221-9
Feng Y, Sun H, Jiang Y (2015) Data fitting and modeling of regional geomagnetic field. Appl Geophys 12(3):303–316. https://doi.org/10.1007/s11770-015-0500-6
Gerber F, Jong RD, Schaepman ME et al (2018) Predicting missing values in spatio-temporal remote sensing data. IEEE Transactions on Geoscience and Remote Sensing 2841-2853. https://doi.org/10.1109/TGRS.2017.2785240
Himeur Y, Alsalemi A, Bensaali F et al (2020) A novel approach for detecting anomalous energy consumption based on micro-moments and deep neural networks. Cognitive Computation 12(1):12,1381–1401. https://doi.org/10.1007/s12559-020-09764-y
Huang R, Jiang L, Shen X et al (2019) An efficient method of monitoring slow-moving landslides with long-range terrestrial laser scanning: a case study of the Dashu landslide in the Three Gorges Reservoir Region, China. Landslides 16:839–855. https://doi.org/10.1007/s10346-018-1118-6
Ishii Y, Ota K, Kuraoka S et al (2012) Evaluation of slope stability by finite element method using observed displacement of landslide. Landslides 9(3):335–348. https://doi.org/10.1007/s10346-011-0303-7
Komac M, Holley R, Mahapatra P et al (2015) Coupling of GPS/GNSS and radar interferometric data for a 3D surface displacement monitoring of landslides. Landslides 12:241–257. https://doi.org/10.1007/s10346-014-0482-0
Lenda G, Ligas M, Lewinska P et al (2016) The use of surface interpolation methods for landslides monitoring. KSCE J Civ Eng 20(1):188–196. https://doi.org/10.1007/s12205-015-0038-4
Li SH, Wu LZ, Chen JJ et al (2020) Multiple data-driven approach for predictinglandslide deformation. Landslides 17:709–718. https://doi.org/10.1007/s10346-019-01320-6
Lian C, Zeng Z, Yao W, Tang H (2014) Ensemble of extreme learning machine for landslide displacement prediction based on time series analysis. Neural Comput Appl 24(1):99–107. https://doi.org/10.1007/s00521-013-1446-3
Liu YL, Duan YB, Guan LX (2017) Cubic spline interpolation method and its application in deformation data preprocessing. Site Investig Sci Technol 06:51–54 (in Chinese)
Liu Y, Chen Z, Hu BD et al (2018) A non-uniform spatiotemporal kriging interpolation algorithm for landslide displacement data. Bull Eng Geol Environ 78(665). https://doi.org/10.1007/s10064-018-1388-1
Ma Z, Song J, Zhang J (2017) A real-time detection method of abnormal building energy consumption data coupled POD-LSE and FCD. Procedia Engineering 205:1657–1664. https://doi.org/10.1016/j.proeng.2017.10.334
Manouchehrian A, Gholamnejad J, Sharifzadeh M (2014) Development of a model for analysis of slope stability for circular mode failure using genetic algorithm. Environ Earth Sci 71:1267–1277. https://doi.org/10.1007/s12665-013-2531-8
Michlmayr G, Chalari A, Clarke A et al (2016) Fiber-optic high-resolution acoustic emission (ae) monitoring of slope failure. Landslides 14(3):1139–1146. https://doi.org/10.1007/s10346-016-0776-5
Michoud C, Baumann V, Lauknes T, R, et al (2016) Large slope deformations detection and monitoring along shores of the Potrerillos Dam reservoir, Argentina, based on a small-baseline InSar approach. Landslides 13(3):451–465. https://doi.org/10.1007/s10346-015-0583-4
Notti D, Cina A, Manzino A et al (2020) Low-cost GNSS solution for continuous monitoring of slope instabilities applied to Madonna del Sasso sanctuary (NW Italy). Sensors (Basel, Switzerland) 20(1). https://doi.org/10.3390/s20010289
Rodriguez J, Deane E, Hendry MT et al (2021) Practical evaluation of single-frequency dGNSS for monitoringslow-moving landslides. Landslides 18:3671–3684. https://doi.org/10.1007/s10346-021-01737-y
Rublev AN, Vlasova YV, Gorbarenko EV (2013) Specifying the atmospheric pollutant distribution forecast using the mathematical modeling and measurement data. Russ Meteorol Hydrol 38(5):20–328. https://doi.org/10.3103/S106837391305004X
Seok JH, Kim JJ, Lee JY et al (2014) Abnormal data refinement and error percentage correction methods for effective short-term hourly water demand forecasting. Int J Control Autom Syst 12(6):1245–1256. https://doi.org/10.1007/s12555-014-0001-z
Sertabipolu Z, Zer M, Tundemir H (2020) Assessment of slope instability with effects of critical displacement by using InSar and fem. Arab J Geosci 13(4):1–15. https://doi.org/10.1007/s12517-020-5164-8
Song D, Liu X, Huang J et al (2021a) Energy-based analysis of seismic failure mechanism of a rock slope with discontinuities using Hilbert-Huang Transform and Marginal Spectrum in the time-frequency domain. Landslides 18:105–123. https://doi.org/10.1007/s10346-020-01491-7
Song D, Liu X, Huang J et al (2021) Seismic cumulative failure effects on a reservoir bank slope with a complex geological structure considering plastic deformation characteristics using shaking table tests. Engineering Geology 286(3):106085. https://doi.org/10.1016/j.enggeo.2021b.106085
Su Y, Weng K, Lin C et al (2021) An improved random forest model for the prediction of dam displacement. IEEE Access 9:9142–9153. https://doi.org/10.1109/ACCESS.2021.3049578
Wang J, Su QM, Du SW (2013) The application of kriging apatial interpolation method in monitoring surface deformation. China Land Sciences 27(12):87–91 (in Chinese)
Wang JM, Zhang J, Deng ZB et al (2014) Slope deformation analyses with space-time kriging interpolation method. J China Coal Soc 39(05):874–879 (in Chinese)
Wang S, Zhang Z, Ren Y et al (2019) UAV photogrammetry and AFSA-Elman neural network in slopes displacement monitoring and forecasting. KSCE J Civ Eng 24(1):19–29. https://doi.org/10.1007/s12205-020-1697-3
Wang JM (2016) Intelligent analysis and prediction of mine slope deformation monitoring data based on Gauss process. Ph.D. dissertation, Taiyuan University of Technology, Taiyuan, China. (in Chinese)
Wei L, Xiong H, Sun H et al (2015) De-noise of online monitoring basic data collected by surveying robots. International Journal of Online Engineering (iJOE), 11(2). https://doi.org/10.3991/ijoe.v11i2.4476
Wen HH, Yang P (2015) Application of GM(1,1) model based on Hermite interpolation method in prediction of soft foundation surface subsidence. Port&waterway Engineering 3:47–50 (in Chinese)
Wu X, Guo Q, Zhang J (2020) Application of double GPS multi-rotor UAV in the investigation of high slope perilous rock-mass in an open pit iron mine. Geotech Geol Eng 38:71–78. https://doi.org/10.1007/s10706-019-00999-7
Xia H, Chen Y, Gong A, Li K et al (2021) Modeling daily temperatures via a phenology-based annual temperature cycle model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14:6219–6229. https://doi.org/10.1109/JSTARS.2021.3085342
Xiao HP, Zhang ZC, Chen LL et al (2020) An improved spatio-temporal kriging interpolation algorithm and its application in slope. IEEE Access 2020:1–1. https://doi.org/10.1109/ACCESS.2020.2994050
Xiao HP (2019) Dynamic evaluation method and application of slope stability in small and medium open-pit mines. Ph.D. dissertation, CUMT, Xuzhou, China. (in Chinese)
Xu DS, Dong LJ, Borana L et al (2017) Early-warning system with quasi-distributed fiber optic sensor networks and cloud computing for soil slopes. IEEE Access 5:25437–25444. https://doi.org/10.1109/ACCESS.2017.2771494
Yan JF, Shi B, Ansari F et al (2017) Analysis of the strain process of soil slope model during infiltration using BOTDA. Bull Eng Geol Env 76:947–959. https://doi.org/10.1007/s10064-016-0916-0
Yang HX, Li T, Zhang ZJ et al (2017) Application of metabolic model in slope displacement monitoring by Lagrange interpolation method. Saf Environ Eng 2:33–38 (in Chinese)
Yang A, Wu M, Hu J et al (2021) Discrimination and correction of abnormal data for condition monitoring of drilling process. Neurocomputing 433:275–286. https://doi.org/10.1016/j.neucom.2020.11.064
Yu G, Wang T, Zhang L et al (2017) A multiple method of discriminating and correcting abnormal operation data of power grid based on point-to-point ratio. 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference. https://doi.org/10.2991/jimec-17.2017.84
Zahraie B, Nasseri M, Nematizadeh F (2017) Exploring spatiotemporal meteorological correlations for basin scale meteorological drought forecasting using data mining methods. Arab J Geosci 10(19):419. https://doi.org/10.1007/s12517-017-3211-x
Zang Y, Shen X, Niu S (2021) A method for detecting abnormal data of network nodes based on convolutional neural network
Zeybek M, Sanlioglu I (2015) Accurate determination of the Takent (Konya, Turkey) landslide using a long-range terrestrial laser scanner. Bull Eng Geol Env 74(1):61–76. https://doi.org/10.1007/s10064-014-0592-x
Zhang YA, Ren JR, Sun LX (2018) Selection and precision analysis for interpolation method of observing settlement observation data. Geomatics&spatial Information Technology 6:214–217 (in Chinese)
Zhang F, Yang T, Li L et al (2021) Assessment of the rock slope stability of Fushun West open-pit mine [J]. Arab J Geosci 14(15):1–20. https://doi.org/10.1007/s12517-021-07815-8
Zhu HH, Shi B, Zhang J et al (2014) Distributed fiber optic monitoring and stability analysis of a model slope under surcharge loading. J Mt Sci 11:979–989. https://doi.org/10.1007/s11629-013-2816-0
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 42171437), Jiangxi Provincial Natural Science Foundation (No. 20212BAB204030), and the high level talents research start-up project of Jiangxi University of Science and Technology (No. jxxjbs19032). The authors would also like to thank the anonymous reviewers for their comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Additional information
Responsible Editor: Zeynal Abiddin Erguler
Rights and permissions
About this article
Cite this article
Chen, L., Xiao, H., Xia, Y. et al. A method of spatio-temporal interpolation on abnormal deformation monitoring data considering point change in mine slope. Arab J Geosci 15, 1294 (2022). https://doi.org/10.1007/s12517-022-10518-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-022-10518-3