On-line monitoring of mine tunnel deformation using laser radar

3.1. RPLIDAR laser radar

The design uses a new generation of low-cost two-dimensional laser radar RPLIDAR A2 developed by SLAMTEC Company [9, 10]. RPLIDAR mainly includes the laser ranging core and the power and mechanical parts that rotate the laser ranging core at high speed, RPLIDAR system performance parameters are shown in Table 1.

When the RPLIDAR is working normally, the ranging core will begin rotating clockwise scanning. The user can obtain the RPLIDAR scanning and ranging data through the RPLIDAR communication interface, and control the start, stop and rotation speed of the rotary motor through PWM.

Laser triangulation ranging technology is adopted by RPLIDAR, coupled with SLAMTEC developed high-speed visual acquisition and processing institutions, it can carry out up to 16,000 ranging actions per second [11]. Every time range in the process, RPLIDAR will launch through the infrared laser modulation signal, the laser signal generated after exposure to the target object reflective will be RPLIDAR visual acquisition system receiving, then through embedded within the RPLIDAR real-time DSP processor, the exposure to the target object and RPLIDAR distance and angle of the current information from the output of the communication interface. The schematic diagram of RPLIDAR system is shown in Fig. 3.

Fig. 3Schematic diagram of the RPLIDAR system

3.2. STM32F103C8T6 microcontroller

STM32F103C8T6 Microcontroller is adopted in the system [12, 13], as shown in Fig. 4. The model single-chip crystal frequency multiplier up to 72 MHZ, running fast, low cost, strong anti-interference, applicable to the research system. The design mainly related to the following features STM32F103C8T6. 1) Timer PWM output function; 2) Serial communication; 3) Analog voltage input ADC.

LabVIEW, a graphical programming language, is adopted by this system for program design. The program is divided into two parts: 1) Main program of laser tunnel detection slave computer; 2) Host computer program for laser tunnel detection. The upper and lower computer communication adopts cc2530 ZigBee wireless communication for data transmission. The main program of the lower machine for laser tunnel detection is shown in Fig. 5, and the program of the upper machine for laser tunnel detection is shown in Fig. 6.

Fig. 4STM32F103C8T6 microcontroller

Fig. 5Main program of laser tunnel detection slave computer

Fig. 6Host computer program for laser tunnel detection

3.3. Cc2530 ZigBee wireless communication

The system uses the cc2530 ZigBee wireless communication transceiver module for data mutual transmission, as shown in Fig. 7. ZigBee is a short distance wireless communication technology with low cost, low power consumption and ad-hoc network, which is widely used in environmental monitoring, smart home and other occasions. The ZigBee module needs to be configured before use. There are five steps in configuration, including 1) Connect the device and select serial port number; 2) Set the node type (coordinator or router); 3) Set the radio channel and PAN ID; 4) Set the node number and baud rate; 5) Set the data transmission mode.

Fig. 7Cc2530 ZigBee wireless communication transceiver module

Cc2530 ZigBee wireless communication module is divided into cc2530 ZigBee sending module and cc2530 ZigBee receiving module. The cc2530 ZigBee sending module is connected to the STM32F103C8T6 single chip microcomputer to transmit the data collected by the lidar to the upper computer. The cc 2530 ZigBee receiving module is connected to the upper computer via USB for receiving data. Some ZigBee modules on the market do not have USB interfaces, so they cannot be connected to computers. For this type of module, a USB-to-TTL module (model: CH340C) is required for transfer, the connecting line of module is shown in Fig. 8.

Fig. 8Module transition wiring diagram

3.4. Power supply module

The machine hardware to be mounted on the four-rotor unmanned aerial vehicles, so the power supply using 3S lithium battery as a system power supply [14]. As the 3S lithium battery, the voltage range of 11.1-12.6V DC, and the system supply voltage should be 5V DC power supply, it is necessary to design a DC to DC power supply buck circuit [15]. In this paper, high-power DC-DC adjustable step-down module based on XL4015E buck chip is adopted.

3.5. Tunnel side wall data collection

Tunnel wall data acquisition is based on the next bit machine software program to achieve. The scan request is sent to the RPLIDAR mounted on the UAV, then the RPLIDAR will return the response data. The STM32 will then read the response data in real time. After the preprocessing, the data will be sent to the host computer via the ZigBee module. Driven by the UAV, RPLIDAR will scan the entire mine tunnel, so the host computer can obtain the data of the entire mine tunnel sidewall.

The specific program flow chart and the LabVIEW For STM32 program are shown in Fig. 9.

Fig. 9Slave computer program flow chart

3.6. Tunnel side wall data collection

The data processing and image construction of this paper is based on Processing3.3 software. This paper mainly uses the size (width, height, renderer) function to make the processing work in 3D mode, and then declare the core class, using the Scene (parent) function to build the 3D environment [16], so that we can get a zoom in and out of the 3D scene The In this paper, the use of ControlP5 library cp5.addButton (string). Set Position (X-Position, Y-Position) is respectively, to create a Start button and Stop button, respectively, with the next machine to send and stop the command. The results of its creation are shown in Fig. 10.

PC master software program flow chart is shown in Fig. 11.

Fig. 103D interactive scene

4.1. Tunnel simulation experiment

The system simulates the tunnel in the corridor for 3D image reconstruction. In the night corridor lights and lights off the two environments to simulate, as shown in Fig. 12.

First download the next bit machine program, connect the hardware device, as shown in Fig. 13.

Fig. 11Schematic diagram of the RPLIDAR system

Experiments show that in the corridor lights and lights under the two environments scanning the same image (as shown in Fig. 14), indicating that the system is not limited by the light inside the tunnel.

Fig. 12Two simulated environments in the corridor

Fig. 13Experimental equipment

Fig. 14Two simulated environments in the corridor

4.2. Error analysis

According to the experimental survey corridor contour data, respectively, take 0° and 180°, 90 ° and 270 ° corresponding to the four points (that is, laser radar up and down and left and right four points) distance values, respectively, in Fig. 15 A, C and B, D points, the size of which were${\mathrm{}H}_A$, $H_C$, $L_B$, $L_D$ said.

This can be calculated by measuring the upper and lower corners of the corridor height value $H_0$, with the left and right width value $L_0$. Respectively:

Fig. 15Error analysis point distribution

While the actual height of the corridor is $H=$ 2400 mm, the left and right width is $L=$ 2000 mm. The system measured the corridor height and width of the relative error can be calculated as below:

The numerical analysis of the specific error is shown in Table 2. Respectively.

The system error can be calculated about 0.3 %. As the side walls of the tunnel are the surrounding rock, once the deformation, the change will generally reach more than 50 mm, and the height of the tunnel is generally not less than 1800 mm, deformation caused by the height change rate of more than 5 %, much higher than the system error. The system measurement error meets the actual tunnel deformation measurement needs.