Design and Implementation of Tunnel Displacement Management System Based on Sensor Networks 1

Transcription

1 Vol. 7, No. 2 February 2016 ISSN CIS Journal. All rights reserved. Design and Implementation of Tunnel Displacement Management System Based on Sensor Networks 1 Seung-Ki Ryu *, 2 Young-Eok Kwon, 3 Gun-Hyoung Park, 4 Yeo-Hwan Yoon 1 Research Fellow, Korea Institute of Civil Engineering and Building Technology, Korea 2 CEO, Heung-in Engineering & Construction, Korea 3 Researcher, Korea Institute of Civil Engineering and Building Technology, Korea 4 Senior Research Fellow, Korea Institute of Civil Engineering and Building Technology, Korea 1 skryu@kict.re.kr, 2 heunginenc@daum.net, 3 godpark@kict.re.kr, 4 kictyyh@kict.re.k ABSTRACT During the construction and maintenance of tunnels, external environment factors affecting structure deformation such as pressure, load, and stress may cause ground collapse, and such hazard may induce a loss of human life. To detect the state of tunnels, most safety inspections generally have been measured the shape transformation during the procedure of construction and maintenance. However, it can fail to respond to unexpected accident owing to the manual measurement by non-regular inspectors. Recently, the measurement systems of tunnel displacement have been studied in tunnel construction fields. However, complete implementation of the system has not been finished. Thus, in this paper, we propose new tunnel displacement measurement system using a real-time measurement of tunnel deformation in sensor networks. We evaluate our system in a modeled tunnel for approving system validity. Keywords: Tunnel, road facilities, displacement, sensor network, simulator 1. INTRODUCTION To detect the abnormal changes of tunnels, general inspections of tunnels have been performed by manual measurement. Thus, the data collection cannot be performed constantly. Moreover, real-time data cannot be transmitted before certain incidents, which can make the inspectors in danger. Due to the problems mentioned earlier, regular monitoring of displacement data cannot be performed, which would lead to diverse problems such as inaccurate measurement of structure deformation, inspection cost increase by frequent inspections, and inspector accidents. It is very difficult to estimate hazardous situations with high accuracy. However, the facility cannot be accessed by manual measurement method to rely on human resources. It might be in risk situations and in deteriorating weather. We should prevent personal injury. Therefore, it is necessary to develop an automatic measurement system. Owing to the advance of information technology (IT), a real-time measurement technique based on the sensor networks for combining the sensor analysis and communication has been introduced. The sensor network stabilization technology, real-time data collection and analysis techniques were highly developed. Thus, facility measurement can be developed regardless of the facility location and weather conditions with new techniques. We applied these techniques to the monitoring system and ground facilities, which can be able to monitor the status of site facilities in detail. In addition, continuous gathering of historical data and time-series analysis of the data can be used for short-term prediction of the facility conditions. Tunnel facility measurement is divided into two steps: construction and maintenance. The construction step should supplement the uncertainty of facility design and investigate the feasibility of the design, which provides the safety and economy of construction. During the maintenance step, continuous data gathering should be satisfied, which provides safety monitoring and optimal maintenance for efficient facility management. Displacement monitoring is performed using displacement measuring sensor systems in various environments such as structure constructions (a tunnel, a cut-slope, a retaining wall, and a dam) and building safety management (a tunnel and a bridge). 2. RELATED WORK 2.1 Criteria for the Inspection of Facilities Detailed safety monitoring guidelines are described in the Guidelines of the Safety Diagnosis [1]. Inspection of safety diagnosis has been divided into regular inspection, precise inspection, and emergency inspection. The status monitoring of tunnel facility is performed for crack detection such as crack absence and crack shapes. Regular inspection includes crack absence, crack direction and crack shapes. Detailed inspection is performed by measuring ultrasonic velocity and impact echo. Regular inspection by a simple visual inspection is performed once in six months [2]. It cannot determine the occurrence of various structural modifications at the time of external environment change such as pressure, force, stress, and aging, because the inspection process may determine a static state of the facility. Thus, the amount of deformation that occurs rapidly should be managed in real-time by an automatic system. 110

2 Inspection methods Regular inspection Detailed Inspection Emergency Inspection Precise inspection Table 1: Criteria for the inspection of facilities Monitoring the exterior and function of a facility Monitoring once in 6 months Description Monitoring current status of a facility in detail Monitoring in 3 years from the approval date Monitoring once in 1~3 years depending on the subsequent facility rating after first detailed inspection Monitoring by the requests of administrative agencies, which checks the damage caused by the disaster accident and the illegal use of restricted facilities Monitoring the facilities by fault severity and necessity Precise visual inspection with equipment and prevention measurement of facilities disasters and ensuring safety Monitoring in 10 years from the approval date Monitoring once every 4~6 years depending on the subsequent facility rating after first precise inspection Table 2: The monitoring items of tunnel inspection Division Monitoring items Monitoring equipment Detailed exterior inspection Simple inspection Major damage (crack, leak, damage, delamination, peeling off, white coated tongue) Intensity investigation by gradient resistance Carbonation test Schmidt hammer Crack meter Hammer, camera, flashlight, writing tool, tape measure Carbonation test tool We have investigated road tunnel usage information and statistics from a tunnel bridge status information of MOLIT in Korea. The 42% of tunnels (1,465) were over 10 years old [3]. 2.2 Existing Technologies Vibrating wire (VW) sensing technology has been developed which comprises a wire and a thin vibrating wire, and is fixed to housing. The end of housing is attached to a facility. Installing a sensor on a facility where cracks are expected, it is possible to measure the changes in crack [4]. Vibrating wire sensors response to more than a certain amount in a small space transformation. Therefore, local measurement range, abrupt changes and displacement out of the measurement range may cause a measurement error [5]. Vibrating wire sensor using a piano wire to measure the stress, pressure, load, displacement. It maintain constant line tension and is output to the change of frequency vibration depending on applied pressure. It is widely used in a variety of sensing applications. It is being used a lot for remote detection, because the attenuation of a signal in long-distance transmission of sensed signals relative to the electrical resistance sensor. Other sensors are strain gauge sensors and optical fiber sensors. Strain gauge sensors have varying resistance properties depending on applied receiving mechanical pressure in the metal semiconductor. Highsensitivity transducer is required. However, owing to a good linearity, it is often used in manual measurement. As the other type of monitoring systems, optical fiber sensors are used for measuring structure deformation. The diameter of an optical fiber is very lightweight and thin. Thus, an optical fiber sensor can be installed on any places without compromising structure functions. The optical fiber sensors and especially Fiber Bragg Grating (FBG) sensors provide multi-points measurement. Thus, several different type of sensors can be made with different centroid wavelength. With the characteristics of the FBG sensors, it can provide high resolution sensing at a single point, as well as wide area monitoring with distributed sensors [6]. 3. PROPOSED DISPLACEMENT SENSING METHOD 3.1 Sensing Algorithm of Displacement This technology is to install the tilt sensor at a predetermined interval in the tunnel, collect data from tilt sensors, and analyze tunnel displacement. First, the sensors installed on series connect to tunnel interior surface. The sensor collects data at a predetermined interval in the three axis directions. By applying a displacement conversion algorithm, we calculate displacement from the tilt angle data. Three-axis data of the sensor is used to periodically measure the axis-specific gradient. We measure the inclination between X-axis and Y-axis direction, and twist degree of surface in Z-axis direction as shown in Figure

3 shape of the tunnel. The values of x'(s), y'(s), and φ are applied to the metrics of Equation 1, and the amount of displacement can be calculated. We calculate displacement from the angle of inclination corrected by allocating accumulated error. s x,3 s x,2 [ s x,1 s x,0 s y,3 s y,2 2 s ] = [ y,1 1 s y, ] x (0) y (0) x (1) y (1) x(0) y(0) [ x(1) y(1) ] (1) Figure 1: Three-axis measurement During the tunnel construction, we consider the relationship between the intensity of the stress generated from the ground by digging the ground. Load carrying capacity with the ground itself is to be utilized for gem ability actively. However, the tunnel information from pre-site investigation is used because of limited specificity of this line structure. Since stress occurs and soil strength is changed by the construction method of excavation methods, it is very difficult to definitely predict the behavior of the tunnel and ground beforehand. Therefore, during the tunnel construction, we perform a variety of measurement, and the result of comprehensive analysis must be applied to construction design. For measuring positioning in tunnels, we investigate weakness and soil characteristics in advance. After consideration of measurement purpose we select measuring position. Figure 2 shows measurement sensors installed on an actual tunnel. 3.2 Displacement Data Collection The sensor module consists of various sensors such as strain gauges, inclinometers, vibration, thermometers and etc. Moreover, each sensor module can be connected to each other. Collected data is transmitted to the remote terminals by RS-485 interface. A remote terminal is designed to connect up to 150 of sensor modules. Typically, 20 sensor modules are used. RS485 serial communication interface was used to transmit the collected data to external monitoring system. In our experiment, we measured displacement value from 17 tiltmeter sensors. The displacement data collected from the tilt-meter sensors is gathered at the same time. The sensor system with serial interfaces transmits the data to Remote Terminal Unit (RTU). In constant intervals, the data transmission from RTU to gateway is performed with 900MHz band RF communication module. Owing to the harsh external environment such as moisture and dust in the tunnel, the sensor housing is designed as a water-proof structure. The sensor housing has been made of water-proof structure of the class IP65 that uses an epoxy to protect the sensors against moisture and dust. Figure 3: Tilt-meter sensor system Figure 2: Installation of measuring sensors on a tunnel Our tilt-meter sensors are mounted on the tunnel and connected to a serial communication port. External stress will be applied to center positioned tilt-meter sensors, and the collected angle data will be converted to displacement data. Since the state twist of plane strain is zero, the curvature can be calculated from the actual amount of displacement measured by a strain gauge, and of tilt angle using a tilt sensor. The displacement calculated by tilt angle is applied to displacement conversion algorithm. This is a problem to reconstruct the 4. DATA ACQUISITION SYSTEM IN SENSOR NETWORKS 4.1 Overview of the Proposed System Sensor data acquisition system consists of data acquisition unit, data transmission unit, database unit, and operating terminal unit. The data acquisition unit consists of strain gauge sensor and inclinometer sensor. The data transmission unit consists of RTU, gateway with 2.4GHz Zigbee RF and CDMA communication. The database module uses MS SQL database for data persistence and storage. The operating terminal unit consists of windows 112

4 operating terminal and android smartphone terminal. Figure 4 shows an overview of our proposed system for integrated management structure capable of synthetically managing various portions of the facility. The data collected from the sensors are transmitted to RTU unit. The sensor data is transmitted to the database server through the gateway from RTU. We collect measured data with acquisition program that uses the three-axis tilt data collected in the tunnel. Ground displacement algorithm can analyze the final status of the tunnel. Figure 5: Tunnel displacement simulator Figure 4: Overview of the proposed system 4.2 Experiment To evaluate our system, we conducted tunnel simulator and tested our conversion algorithm. In the experimental environment, tunnel deformation was made by outside pressure. For the accurate evaluation, any deformation from inside pressure is prevented. Our modeled tunnel has 5.6 m diameter, and the end of each bar is fixed to ground. The center positioned bar of our modeled tunnel provides vertical movement. We installed 17 tilt-meter sensors on the center positioned bar with 35cm interval. As mentioned earlier, all tilt-meter sensors are connected to a RS485 serial port. The tilt-meter sensor 1 is connected to RTU for external data transmission. We installed a cable to create external stress that makes random tunnel deformation. Our tilt-meter sensors measure a tilt angle variation when the cable is pulled. A theodolite target label to measure accurate tunnel displacement value produced by theodolite. We equipped labels to all tilt-meter sensors. The reference equipment has 30 times zoom magnification for each 1 degree accuracy and 1mm distance precision. Figure 6: Test results Simulator data was compared by measuring the coordinate value and the reference data with respect to 17 points on the basis of the base point. In the experiment, the base point of 10mm, 20mm, 30mm and 50mm were sequentially varied and measured on the 17 points. In the experimental results, maximum deviation was 2.6 mm with 10mm deformation at sensor 2. The data of sensor 9 shows stress variation of 1.7 mm, and sensor 10 shows 2.0 mm. The results of sensor 2 and sensor 3 show noise data. Thus, if we remove the two data, the sensors from sensor 1 to sensor 7 and from sensor 12 to sensor 17 show 1mm accuracy. Large deformation stress of the center has been transferred to small variations on both ends, and show a good measurement accuracy at all points. In particular, given the variation of 50 mm, it exhibited a better result. If we remove the data of sensor 2 as a noise, overall measurement error of 17 sensors is less 113

5 than 2mm, which means that our system provides high accuracy. 4.3 Data Analysis Terminal Our data analysis system displays a threedimensional graphic image. We integrated the transformed data, and configured to visualize the terminal system. In general, the deformation data of tunnels should be recorded continuously. However, most cases only hold rough data. In addition, it does not have initial value. Thus, it is difficult to know the variation. In this paper, we record the data trend from an initial value through terminal system, and propose possible prediction system. For the purpose, measured value is transmitted to the operating terminal in real-time, and is stored continuously. As a result, we can produce accurate estimated data of tunnel variations. By measuring the displacement of tunnels in real-time and transmitting the data to the operation terminal, we developed a method of expressing a modified visible data on the threedimensional graphics as shown in Figure 7. In this paper, tunnel experiments were performed to predict the behavior changes based on the displacement data. We predict the amount of movement with initial position of the sensor. The experiment was performed randomly by the displacement given by our tunnel model, and it was compared with the predicted results. The proposed sensing system showed less than 2mm of measurement error in tunnel simulation results. Thus, it presented that our system has real-world applicability. Moreover, the measured data in the field is transmitted to the center database and operating terminal, which provides easy monitoring environment for operators. Our proposed sensing system is to prevent the collapse of the ground; it will help economically and socially. We installed a ground displacement sensors on structures such as tunnels, and collected displacement information in real-time through the sensor node. It is expected to contribute to the efficiency of the facility management. In our future works, we plan to study the reliable communication systems, wireless transmission systems, forecasting efforts and field measurement data to improve the accuracy of remote sensing systems in the collection system. ACKNOWLEDGEMENT This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(msip) ( , Development of High-reliable USN Sensor Node and Data Analysis System for Ground Collapsing Prevention, 2015) REFERENCES [1] MOLIT, Guidelines for the Safety Diagnosis and refine safety inspection of facilities, [2] MOLIT, Safety inspection and precise guidelines detailed guidelines on the Safety Evaluation (tunnel), Korea Infrastructure Safety Corporation, Figure 7:Tunnel displacement visualization [3] MOLIT, Tunnel bridge a status information system, [4] A. Hermanis and K. Nesenbergs, Grid shaped accelerometer network for surface shape recognition, in proceedings of the Electronics Conference (BEC), Oct [5] M. Park and H. Han, Model Experiments and Behavior Analyses of The Tunnel Support Using TDR Sensor, Journal of Korean Geo- Environmental Society, Vol.12, No.9, Figure 8: Experiment result of tunnel displacement 5. CONCLUSION In this study, we introduced sensing system for real-time measurement of the tunnel displacement data, and verified accuracy of the system through experiments. [6] Woo, Jong-Tae, Theory and practice of the tunnel instrumentation, goomiseokwan, 2006 AUTHOR PROFILES Seung-Ki Ryu received the degree in electrical engineering at the ChungBuk National University in Korea. Currently, he is a research fellow at Korea Institute of Civil Engineering and Building Technology. His 114

6 research interest covers intelligent transportation systems, IT technology, smart city, construction IT convergence. Young-Eok Kwon is CEO of Heung-in Engineering & Construction Company in Korea. His research interest covers road facilities monitoring systems, IT technology. Gun-Hyoung Park is the expected graduation PH.D of Kookmin University in Korea. He is a research in KICT and his research interest covers intelligent transportation systems, IT technology, smart city, construction IT convergence and logistics. Yeo-Hwan Yoon received the degree in civil engineering at the Seoul National University in Korea. He is a research fellow at KICT and his research interest covers intelligent transportation systems, IT technology, civil technology, construction IT convergence. 115