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1. Introduction
1.1. Background
The underground excavation monitoring system is an effective monitoring device used to monitor crimes such as theft, jailbreak, and smuggling through shallow underground excavation. The system locates the excavation location mainly through the microseismic information sensed by multiple-seismic detectors.
1.2. Research Status
Based on the sensor’s monitoring of seismic signals, the spatial coordinates and seismic moments of the source are determined. It is one of the main contents of seismic positioning research. Regarding the seismic source positioning method, the predecessor has done a lot of research and put forward a lot of positioning methods, such as Geiger and various improvement methods, joint correction method for the source location and station, relative positioning method, station-pair time difference method, EHB method, and double residual method. The development of seismic source location research has been greatly promoted. These methods can be divided into two categories depending on the parameters involved in solving: one is the method for solving the timing of shocks and the location of microseismic sources after knowing the velocity models, referred to as the classic method [1–6], and the other is the method for solving the seismic source location, the shock time, and the velocity model together, referred to as the joint method. The former is the most widely used in the seismic field and mining engineering, and the uncertainty of the velocity model is the biggest deficiency of the method. Although many studies have been done on the velocity model before it, it is still the biggest factor affecting the stability and accuracy of the positioning algorithm. The latter solves the problem of the uncertain velocity model and greatly improves the accuracy of microseismic source positioning. But the parameters of microseismic source location, shock time, and media velocity are not independent of each other; the solution is not unique, which brings difficulties to the selection of parameters [7–18].
However, the underground excavation monitoring is a new engineering application, and the relevant research cannot be used for reference. It is also different from the traditional location of an underground seismic source and ground sensor network.
The instrument used in traditional underground source location has high price and good performance. It can distinguish
Because the monitoring distance of underground excavation monitoring is close and the monitoring depth is shallow, the monitored signal
Due to the lack of relevant research, it is not clear whether the traditional source location method is applicable or not and the influence of the layout method of a ground motion detector on the positioning accuracy.
In view of the above problems, this paper combines with the engineering practice of underground excavation application to carry out research.
1.3. Contribution
(1) Based on the principle of TDOA, this paper puts forward three layout methods applied to an underground excavation monitoring system and deduces the relevant mathematical model
(2) In this paper, the experiments of common ground motion detectors show that the
2. The Locating Methods
Locating methods are mainly divided into active locating and passive locating. Active locating is a method that uses radar, laser, and other active devices to locate the target. Passive locating is based on receiving and processing the radiation source’s signals generated by the target and extracting information such as the distance, azimuth, and tracking of the target. Passive locating overcomes the disadvantages of large power consumption and the large volume of active locating. In this paper, multiseismic detectors are used to locate underground excavation, which is a passive location method.
At present, the methods of the passive locating algorithms are mainly based on Time of Arrival (TOA), based on TDOA, based on the Direction of Arrival (DOA), and based on Received Signal Strength Indication (RSSI). Table 1 is the compared results of common passive locating methods. The TDOA is a widely used method because of its simple algorithm and no precise synchronization between the target and the node [18–24].
Table 1
Comparison of several common locating methods.
Locating method | Advantage | Disadvantage | Accuracy | Time-consuming |
TOA | Simple technique and algorithm | Moving targets and nodes always are precisely synchronized. But it is susceptible to multipath propagation and noise | Relatively high | Long |
TDOA | Relatively simple technique and algorithm | Accuracy is greatly affected by the environment, and it requires accurate synchronization of node clocks | Relatively high | Relatively long |
DOA | Relatively simple technique and algorithm | Easily affected by the environment and low accuracy | Relatively low | Short |
RSSI | Relatively simple technology, low cost, high precision for short range | It is easily affected by the environment, the accuracy is poor for outdoor long-range locating, and it is easily susceptible to multipath propagation | High (for short range), low (for long range) | / |
3. Math Modeling of Layout Methods
3.1. The Mathematical Modeling of Locating
The key point of the TDOA locating method is the estimation of the arrival time difference. Different from the traditional planar TDOA locating algorithm, locating needs to calculate coordinate positions of
The coordinates of the measured excavation location
When the number of seismic detectors increases, the equation obtained by the distance calculation equation increases correspondingly. In this case, we use the maximum likelihood method to calculate the position coordinates of the measured target. The position coordinates of
The distance between the measured target’s location and each seismic is unknown, and it can be converted into the product of velocity and time according to the distance equation.
This is a form of
The estimation of the propagation velocity of seismic wave is calculated based on the distance-time equation, and the specific calculation method is as follows: to simplify the calculation, excavation action is performed at a certain point (within the detection range of the seismic detector) on the extended line of two seismic detectors, and then, the time difference is given by processing the information collected by two seismic detectors. Then, measure the distance between two seismic detectors. The propagation velocity of the seismic wave is estimated by
For popularizing the more general calculation equation of seismic waves’ propagation velocity, the excavation behavior of anywhere within the detection range of a seismic detector can be used as a signal source; then, the equation of the seismic waves’ propagation velocity becomes
For making the measured propagation velocity more comprehensively reflect the seismic wave propagation velocity characteristics of the entire detection area, it is necessary to repeat the calculation in different positions multiple times and get an average value.
3.2. The Mathematical Model of Layout Methods
In general, the more the seismic detectors, the higher the accuracy. However, in actual engineering applications, it is impossible to increase the number of seismic detectors unlimitedly due to the cost. For convenience, we build a submonitoring area using seven seismic detectors, respectively
3.2.1. The 5-1-1 Layout Method
As shown in Figure 1, the 5-1-1 layout method consists of 7 seismic detectors. We set the space Cartesian coordinate system with
[figure omitted; refer to PDF]
The mathematical model is established by using the coordinates of seven seismic detectors.
3.2.2. The 4-3 Layout Method
As shown in Figure 2, the 4-3 layout method consists of 7 seismic detectors. We set the space Cartesian coordinate system with
[figure omitted; refer to PDF]
The mathematical model is established by using the coordinates of seven seismic detectors.
3.2.3. The 7-0-0 Layout Method
As shown in Figure 3, the 7-0-0 layout method consists of 7 seismic detectors. We set the space Cartesian coordinate system with
[figure omitted; refer to PDF]
The mathematical model is established by using the coordinates of seven seismic detectors.
4. Simulation and Experimental Analysis
4.1. Simulation Results
Combined with the actual situation of the underground excavation monitoring system, the main factors that affect the locating accuracy are analyzed as follows: the measurement error of seismic detectors, the spacing of seismic detectors, the propagation velocity of seismic waves, the error of seismic detectors, and the position of mining’s coordinate. Due to the limited detection range of seismic detectors, combined with the actual working conditions, it is assumed that a submonitoring system consists of seven seismic detectors. Due to the difference of the time signals received by each seismic detector, the measurement error and the position error generated by the sensor placement are introduced into each seismic detector to calculate the relative error and the average of the relative errors of each axis during locating. It is assumed that the geological conditions are the same, taking the soil as an example. Because of the shallow excavation, assume that the underground excavation site is outside and that the seismic wave propagation velocity is constant and the velocity is 380 m/s.
4.1.1. The Simulation of the 5-1-1 Layout Method
In order to facilitate the test verification, combined with the performance of the experimental site and experimental equipment, the distance between the seismic detectors assumed in the study was short. Assume that the spacing of the seismic detectors are
[figure omitted; refer to PDF]
As can be seen from Figure 18, the coordinates in Figure 18 indicated the sampling point number and voltage values when the seven seismic sensors received the first wave of the seismic signal. The velocity of the seismic wave is obtained by the distance between the known seven seismic detectors, the interval time, and the difference in sampling points. The measurement results of seismic wave velocity are shown in Table 6. Through experimental tests, the propagation velocity of the seismic wave is about 380 m/s in this geological condition.
Table 6
The measurement values of the seismic detectors.
Number | The estimated propagation velocity for seismic wave (m/s) |
1 | 344 |
2 | 382 |
3 | 396 |
4 | 404 |
5 | 374 |
6 | 356 |
7 | 371 |
8 | 387 |
9 | 397 |
10 | 389 |
Average value | 380 |
Due to the monitoring, the area is smaller and the distance between seismic detectors is relatively close. Limited by the cost control of underground excavation systems, the frequency of the seismic detector is not high. The seismic detector performance is also difficult to distinguish between
On this basis, this paper also carried out the locating experiment of the 5-1-1 layout method, 4-3 layout method, and 7-0-0 layout method. The seismic detector was arranged according to the space coordinates of the previous simulation. Two spacings were used during the experiment: one was 1.5 meters and the other was 2 meters. There are two excavation positions:
[figures omitted; refer to PDF]
[figure omitted; refer to PDF][figure omitted; refer to PDF][figure omitted; refer to PDF][figure omitted; refer to PDF]Table 7
Summary of experimental results of the coordinate of excavation location P1
The locating relative error of the | The locating relative error of the | The locating relative error of the | |
5-1-1 | 0.04 | 0.23 | 0.15 |
0.41 | 1.04 | 1.2 | |
0.09 | 0.56 | 0.35 | |
4-3 | 0.05 | 0.15 | 3.1 |
0.05 | 0.62 | 1.79 | |
0.01 | 0.01 | 3.24 | |
7-0-0 | 0.44 | 0.48 | — |
0.54 | 0.19 | — | |
1.13 | 0.82 | — |
Table 8
Summary of experimental results of the coordinate of excavation location P2
The locating relative error of the | The locating relative error of the | The locating relative error of the | |
5-1-1 | 0.57 | 1.36 | 4.14 |
0.95 | 0.91 | 6.63 | |
1.28 | 0.97 | 8.9 | |
4-3 | 0.04 | 1.03 | 1.07 |
0.21 | 0.62 | 0.02 | |
0.64 | 0.51 | 6.41 | |
7-0-0 | 0.87 | 1.16 | — |
0.54 | 0.56 | — | |
0.68 | 0.91 | — |
Table 9
Summary of experimental results of the coordinate of excavation location P1
The locating relative error of the | The locating relative error of the | The locating relative error of the | |
5-1-1 | 0.52 | 1.4 | 2.5 |
1.32 | 4.05 | 6.8 | |
1.32 | 4.1 | 6.72 | |
4-3 | 0.29 | 1 | 2.4 |
0.11 | 0.95 | 0.64 | |
0.6 | 0.79 | 3.4 | |
7-0-0 | 0.52 | 0.08 | — |
0.75 | 0.54 | — | |
0.67 | 0.87 | — |
Table 10
Summary of experimental results of the coordinate of excavation location P2
The locating relative error of the | The locating relative error of the | The locating relative error of the | |
5-1-1 | 0.6 | 0.6 | 1.6 |
0.9 | 1.1 | 4 | |
0.3 | 0.5 | 0.2 | |
4-3 | 0.92 | 0.95 | 5.7 |
0.5 | 1.1 | 0.5 | |
1 | 0.64 | 7 | |
7-0-0 | 0.08 | 0.88 | — |
0.54 | 1.23 | — | |
0.87 | 1.97 | — |
4.4. Result Analysis
(1) In terms of depth locating, relative errors are relatively large
The 5-1-1 layout method showed a relative error of 8.9 meters on the
(2) Increasing the installation distance between seismic detectors can reduce relative locating errors
The relative locating error is smaller when the installation distance between the seismic detectors is 2 meters rather than the installation distance being 1.5 meters in the same layout method and the same excavation location. This conclusion is by simulation results, which shows that increasing the installation distance between seismic detectors can reduce relative locating errors.
(3) The relative locating error does not depend on how many the seismic detector is arranged
The 5-1-1 layout method deploys five seismic detectors in the plane consisting of the
(4) Due to geological differences, relative locating errors are also different for the same layout method when the excavation position is different
In the theoretical simulation, the hypothesis is based on the same geological conditions, but in the actual experiment, the geological conditions are unlikely to be consistent. Therefore, the relative errors in locating are different when two different excavation locations P1 and P2 are excavated. Therefore, locating methods of underground excavation need to expand research.
5. Conclusion
The paper focuses on the locating of underground excavation monitoring systems. Through mathematical modeling, simulation, and experiments, the following conclusions are obtained. (1) When the number of seismic detectors is limited, the depth positioning error is relatively large. (2) To increase the installation distance between the vibration detectors around the place, the relative error of plane positioning can be reduced. (3) The main reasons for the positioning error are the time measurement error, the difference in transmission velocity caused by the terrain, and the detection performance of the seismic detector hardware itself. At close range, the influence of the seismic detector’s layout method on the positioning error is limited. The above research results can help the application of an underground excavation system.
Acknowledgments
This work was supported by the Focus on Research and Development Program (general) in Shanxi under grant 201603D121038.
[1] T. Yue, C. Xiaofei, "Review of seismic location study," Progress in Geophysics, vol. 17 no. 1, pp. 147-155, 2002.
[2] L. Geiger, "Probability method for the determination of earthquake epicenters from arrival time only," Bull. St. Louis. Univ, vol. 8 no. 60, 1912.
[3] B. R. Lienert, E. Berg, L. N. Frazer, "Hypocenter: an earthquake location method using centered, scaled, and adaptively damped least squares," Bulletin of the Seismological Society of America, vol. 76 no. 3, pp. 771-783, 1986.
[4] G. D. Nelson, J. E. Vidale, "Earthquake locations by 3D finite difference travel times," Bulletin of the Seismological Society of America, vol. 80 no. 2, pp. 395-410, 1990.
[5] Z. Zhonghe, "An earthquake location program with multiple velocity model and its application to the Beijing seismic network," Acta Seismologica Sinica, vol. 5 no. 2, pp. 242-254, 1983.
[6] A. F. Prugger, D. J. Gendzwill, "Microearthquake location: a nonlinear approach that makes use of a simplex stepping procedure," Bulletin of the Seismological Society of America, vol. 78 no. 2, pp. 799-815, 1988.
[7] R. S. Crosson, "Crustal structure modeling of earthquake data: 1. Simultaneous least squares estimation of hypocenter and velocity parameters," Journal of Geophysical Research, vol. 81 no. 17, pp. 3036-3046, DOI: 10.1029/JB081i017p03036, 1976.
[8] K. Aki, W. H. K. Lee, "Determination of three-dimensional velocity anomalies under a seismic array using first P arrival times from local earthquakes: 1. A homogeneous initial model," Journal of Geophysical Research, vol. 81 no. 23, pp. 4381-4399, DOI: 10.1029/JB081i023p04381, 1976.
[9] G. Pavlis, J. R. Booker, "The mixed discrete-continuous inverse problem: application to the simultaneous determination of earthquake hypocenters and velocity structure," Journal of Geophysical Research, vol. 85 no. B9, pp. 4801-4810, DOI: 10.1029/JB085iB09p04801, 1980.
[10] Z. Zhonghe, "The joint determination of hypocenter parameters and velocity structure in the Beijing area of China," Chinese Journal of Geophysics, vol. 26 no. 2, pp. 131-139, 1983.
[11] L. Futian, "Simultaneous inversion of earthquake hypocenters and velocity structure (I): theory and method," Chinese Journal of Geophysics, vol. 27 no. 2, pp. 167-175, 1984.
[12] G. Fuan, F. Rui, "The joint inversion of 3D velocity structure and source parameters in Xinfengjiang reservoir," Chinese Journal of Geophysics, vol. 35 no. 3, pp. 331-341, 1992.
[13] H. S. Ma, G. M. Zhang, L. Q. Zhou, J. Liu, H. Xia, "Simultaneous inversion of small earthquake relocation and velocity structure in Sichuan-Yunnan area," Earth, vol. 28 no. 2, 2008.
[14] Z. Ren, L. Wang, L. Bi, "Robust GICP-based 3D LIDAR SLAM for underground mining environment," Sensors, vol. 19 no. 13,DOI: 10.3390/s19132915, 2019.
[15] W. Feng, S. Lei, F. Weiguo, W. Cong, "Application of computational geometry in coal mine roadway 3D localization," The International Arab Journal of Information Technology, vol. 15 no. 4, 2018.
[16] H. Chen, W. Guan, S. Li, Y. Wu, "Indoor high precision three-dimensional positioning system based on visible light communication using modified genetic algorithm," Optics Communications, vol. 413 no. 15, pp. 103-120, DOI: 10.1016/j.optcom.2017.12.045, 2018.
[17] H. Huang, B. Lin, L. Feng, H. Lv, "Hybrid indoor localization scheme with image sensor-based visible light positioning and pedestrian dead reckoning," Applied Optics, vol. 58 no. 12, pp. 3214-3221, DOI: 10.1364/AO.58.003214, 2019.
[18] L. Zhe, The Key Technology of Underground Seismic Signal Detection and Recognition in the Area of Public Security, 2015.
[19] W. Tao, W. Dongying, P. Yu, F. Wei, "Gas leak localization and detection method based on a multi-point ultrasonic sensor array with TDOA algorithm," Measurement Science and Technology, vol. 26 no. 9, article 095002,DOI: 10.1088/0957-0233/26/9/095002, 2015.
[20] S.-Y. Jung, S. Hann, C.-S. Park, "TDOA-based optical wireless indoor localization using LED ceiling lamps," IEEE Transactions on Consumer Electronics, vol. 57 no. 4, pp. 1592-1597, DOI: 10.1109/tce.2011.6131130, 2011.
[21] J. Shen, A. F. Molisch, J. Salmi, "Accurate passive location estimation using TOA measurements," IEEE Transactions on Wireless Communications, vol. 11 no. 6, pp. 2182-2192, DOI: 10.1109/TWC.2012.040412.110697, 2012.
[22] K. C. Ho, "Bias reduction for an explicit solution of source localization using TDOA," IEEE Transactions on Signal Processing, vol. 60 no. 5, pp. 2101-2114, DOI: 10.1109/TSP.2012.2187283, 2012.
[23] J. L. Wang, D. Z. Qin, S. Y. Pei, T. L. Zhao, "Design of seismic signal detection and identification system based on STM32," Foreign Electronic Measurement Technology, vol. 36 no. 7, pp. 48-51, 2017.
[24] D. Qin, J. Zhang, "A new identification method of underground excavation based on velocity estimation using double point synchronous measurements," IEEE Access, vol. 8, pp. 39104-39112, DOI: 10.1109/access.2020.2975608, 2020.
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Abstract
In this study, we propose effective monitoring equipment intended for monitoring the underground tunnel of illegal excavation (such as theft, jailbreak, and smuggling). It mainly detects the microseismic information produced by underground excavation in a short distance to detect the status of underground excavation. Based on the arrival time difference principle, the positioning mathematical models of the 5-1-1 layout method, 4-3 layout method, and 7-0-0 layout method are established, respectively. In the research process, the measurement and the placement error caused by the installation of a seismic detector are joined into the detectors. Simulation results show that the relative error and its average value are obtained when mining outside the monitoring area. The experiment results demonstrate that, first, the depth positioning error is positively affected by the number of seismic detectors. Then, the relative error of plane positioning can be reduced when the installation distance among detectors is increased. Finally, the main causes of location error include time measurement error, propagation velocity difference caused by terrain, and the performance of detector hardware. The array of a ground motion detector has a weak influence on it. These emerging trends will have profound impacts on application of an underground excavation system.
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