In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous drivi...In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.展开更多
Quantitative damage identification of surrounding rock is important to assess the current condition and residual strength of underground tunnels.In this work,an underground tunnel model with marble-like cementitious m...Quantitative damage identification of surrounding rock is important to assess the current condition and residual strength of underground tunnels.In this work,an underground tunnel model with marble-like cementitious materials was first fabricated using the three-dimensional(3D)printing technique and then loaded to simulate its failure mode in the laboratory.Lead zirconate titanate piezoelectric(PZT)transducers were embedded in the surrounding rock around the tunnel in the process of 3D printing.A 3D monitoring network was formed to locate damage areas and evaluate damage extent during loading.Results show that as the load increased,main cracks firstly appeared above the tunnel roof and below the floor,and then they coalesced into the tunnel boundary.Finally,the tunnel model was broken into several parts.The resonant frequency and the peak of the conductance signature firstly shifted rightwards with loading due to the sealing of microcracks,and then shifted backwards after new cracks appeared.An overall increase in the root-mean-square deviation(RMSD)calculated from conductance signatures of all the PZT transducers was observed as the load(damage)increased.Damage-dependent equivalent stiffness parameters(ESPs)were calculated from the real and imaginary signatures of each PZT at different damage states.Satisfactory agreement between equivalent and experimental ESP values was achieved.Also,the relationship between the change of the ESP and the residual strength was obtained.The method paves the way for damage identification and residual strength estimation of other 3D printed structures in civil engineering.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A2C1011216)。
文摘In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.
基金The study is financially supported by the National Major Research Instrument Development Project of the National Natural Science Foundation of China(Grant No.51627812)the National Natural Science Foundation of China(Grant No.52078181)the Natural Science Foundation of Hebei Province,China(Grant No.E2019202484)。
文摘Quantitative damage identification of surrounding rock is important to assess the current condition and residual strength of underground tunnels.In this work,an underground tunnel model with marble-like cementitious materials was first fabricated using the three-dimensional(3D)printing technique and then loaded to simulate its failure mode in the laboratory.Lead zirconate titanate piezoelectric(PZT)transducers were embedded in the surrounding rock around the tunnel in the process of 3D printing.A 3D monitoring network was formed to locate damage areas and evaluate damage extent during loading.Results show that as the load increased,main cracks firstly appeared above the tunnel roof and below the floor,and then they coalesced into the tunnel boundary.Finally,the tunnel model was broken into several parts.The resonant frequency and the peak of the conductance signature firstly shifted rightwards with loading due to the sealing of microcracks,and then shifted backwards after new cracks appeared.An overall increase in the root-mean-square deviation(RMSD)calculated from conductance signatures of all the PZT transducers was observed as the load(damage)increased.Damage-dependent equivalent stiffness parameters(ESPs)were calculated from the real and imaginary signatures of each PZT at different damage states.Satisfactory agreement between equivalent and experimental ESP values was achieved.Also,the relationship between the change of the ESP and the residual strength was obtained.The method paves the way for damage identification and residual strength estimation of other 3D printed structures in civil engineering.
