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| 1 | Land subsidence monitoring by D-InSAR technique显示文摘Nowadays, the researches of using Differential Interferometric Synthetic Aperture Radar (D-InSAR) tech- nique to monitor the land subsidence are mainly on how to qualitatively analyze the subsidence areas and values, but the analysis of subsidence process and mechanism are insufficient. In order to resolve these problems, 6 scenes of ERS1/2 images captured during 1995 and 2000 in a certain place of Jiangsu province were selected to obtain the subsidence and velocities in three time segments by ''two-pass'' D- InSAR method. Then the relationships among distributions of pumping wells, exploitation quantity of groundwater, and confined water levels were studied and the subsidence mechanism was systematically analyzed. The results show that using D-InSAR technique to monitor the deformation of large area can obtain high accuracies, the disadvantages of classical observation methods can be remedied and there is a linear relationship among the velocities of land subsidence, the water level and the exploitation quantity. | Fan Hongdong Deng Kazhong Ju Chengyu Zhu Chuanguang Xue Jiqun China | 2011 | Mining Science and Technology2011，21，6： | 15 |
| 2 | Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration显示文摘Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient,we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection.The proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling.The specifc process can be described as follows:frst,large-scale deformation points in the interferogram are masked out based on interferometric coherence;second,the interferogram with holes is unwrapped to obtain a deformation map with holes,and last,the holes in the deformation map are flled with point cloud data using inverse distance weighting algorithm,which will achieve seamless connection of monitoring region.We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in mining area using the proposed method.The results show that the maximum absolute error is 64 mm,relative error of maximum subsidence value is 4.95%,and they are consistent with leveling data of ground observation stations,which confrms the feasibility of this method.The method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area. | Chen Bingqian Deng Kazhong Fan Hongdong Hao Ming | 2013 | International Journal of Mining Science and Technology2013，23，4： | 12 |
| 3 | Monitoring and analysis of mining 3D deformation by multiplatform SAR images with the probability integral method显示文摘Only one-dimensional (1D)deformation along the radar line of sight (LOS)can be obtained using differential interferometry synthetic aperture radar (D-InSAR),and D-InSAR observation is insensitive to deformation in the north direction.This study inferred three-dimensional (3D)deformation of a mining subsidence basin by combining the north-south deformation predicted by a probability integral method with the LOS deformation obtained by D-InSAR.The 15235 working face in Fengfeng mining area (Hebei Province,China)was used as the object of study.The north-south horizontal movement was predicted by the probability integral method according to the site's geological and mining conditions.Then,the vertical and east-west deformation fields were solved by merging ascend-orbit RadarSAT-2, descend-orbit TerraSAR,and predicted north-south deformation based on a least squares method.Comparing with the leveling data,the results show that the vertical deformation accuracy of the experimental method is better than the inversed vertical deformation neglecting the horizontal deformation.Finally,the impact of the relationship between the azimuth of the working face and the SAR imaging geometry on the monitoring of the mining subsidence basin was analyzed.The results can be utilized in monitoring mining subsidence basins by single SAR image sources. | Meinan ZHENG Kazhong DENG Hongdong FAN Jilei HUANG | 2019 | Frontiers of Earth Science2019，13，1： | 4 |
| 4 | Maintaining partially observed systems with imperfect observation and resource constraint显示文摘 | Chen Maoyin Fan Hongdong Hu Changhua | 2014 | IEEE Trans- actions on Reliability2014，63，4： | 1 |
| 5 | Coop- erative predictive maintenance of repairable systems with de- pendent failure modes and resource constraint 显示文摘 | FAN Hongdong HU Changhua CHEN Maoyin | 2011 | IEEE Transactions on Reliability2011，60，1： | 1 |
| 6 | A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems显示文摘In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,theDensityPeakClustering(DPC)algorithmis used todetermine referential values of indicators forBRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump. | Yu Zhao Zhijie Zhou Hongdong Fan Xiaoxia Han JieWang Manlin Chen | 2024 | Intelligent Automation & Soft Computing2024，39，1： | 0 |
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