In order to improve the stability and reliability of the gas drainage monitoring system, reduce and eliminate the hidden danger of gas overrun safety accidents caused by the monitoring system failure. We designed a gas drainage monitoring system based on redundant control technology. First of all, we designed the overall architecture of the monitoring system. Siemens S7-1500R series programmable logic controller (PLC) was used as the core control unit, redundant design was carried out for CPU and DC24V power supply, and the PLC control cabinet was designed according to the on-site requirements. In the design, smart sensors and digital signal transmission are used to improve the anti-interference ability of the system. Secondly, we designed RS485 communication program and PID control program in portal software to realize data acquisition of smart sensors and constant pressure control of gas drainage system. Finally, we use WinCC configuration software to design the human-machine interface (HMI), which realizes the online monitoring and remote control of the gas drainage system. The application shows that the switching time from the primary CPU to the backup CPU automatically due to failure is about 300 ms. In addition, when any CPU, profinet cable or power supply fails, the system can still work normally, effectively improving the stability and reliability of the gas drainage monitoring system, and achieving the goal of monitoring the gas drainage system efficiently.
Article
Design of gas drainage system based on PLC redundancy control technology
https://doi.org/10.21203/rs.3.rs-2361008/v1
This work is licensed under a CC BY 4.0 License
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redundancy control technology
PLC
WinCC
smart sensor
PID
monitoring system
Methane is a by-product, which is released during the production of coal. It is a potent greenhouse gas with a global warming potential (GWP) 28–36 times that of CO2 [1]. Methane is also a valuable clean energy. Its calorific value per cubic meter is equivalent to the calorific value of 1.13 kilograms of gasoline, which can reduces global greenhouse gas emissions through utilization [2]. In China, high gas mines and gas outburst mines account for 32.7% of productive mines [3]. In recent years, with the rapid development of coal mining technology and equipment, the mining intensity continues to improve, and the mining level continues to extend to the depth. It is deepening at the rate of 10-20 meters every year. The average mining depth in China is close to 700 meters [4-5]. With the continuous increase of mining depth, the stress of coal seams increases, the gas content and gas pressure of coal seams increase, the mining conditions of coal mines deteriorate, serious casualties and property loss accidents occur frequently, which seriously affect the safety of mine production and miners' lives [6]. When the methane content in the environment is 5% - 16%, explosion may occur in case of fire, causing serious accidents. According to statistics, more than 70% of these accidents are gas accidents, so it is necessary to effectively control the coal mine gas to reduce the occurrence of safety accidents [7-8]. Gas drainage is the fundamental method to reduce the pressure and content of methane gas in coal seams. The principle of negative pressure generated by the gas drainage pump is used to pump the gas stored in goaf and pre mining coal seams to the ground for gas power generation and thermal storage and oxidation utilization through drilling, burying pipes, etc., so as to reduce the emission of greenhouse gas and fundamentally solve the gas disaster [9-11].
In recent years, researchers in various fields have combined Programmable Logic Controller (PLC), touch screen and configuration software for monitoring, control and fault diagnosis of various systems[12-14]. Su et al. used S7-1200 PLC as the main controller to control the analog heating furnace, and communicated with SINAMICS V90 PN servo motor in real time to achieve deformation displacement control [15]. Vadi et al. realized the control of induction motor through PLC and Profibus communication, and obtained current, voltage, power and other parameters through the bus, which is more reliable and safe than the method of using cables and electronic cards [16]. Gao et al. designed a carbon dioxide critical command platform based on PLC and HMI to control the compressor, air cooler fan, auxiliary cooler fan, EEV and pressure regulating valve [17]. Kaczmarek et al. used PLC and HMI to control the water in the small-scale recycling analysis device of the swimming pool, and analyzed the reaction kinetics of the water in the small-scale recycling analysis device [18]. Guo et al. designed a PLC based evaporative cooling simulation platform, in order to verify the feasibility of the application of evaporative cooling system to supercomputers[19]. W ł Odarczak et al. designed a fluid velocity measurement device based on PLC controller, and realized the test of flowmeter [20]. Chang et al. designed a single tube heat transfer experimental platform and developed a measurement and control platform based on PLC and HMI, which reduced the difficulty of equipment operation [21]. Pan et al. developed the monitoring platform WinCC for helium refrigerator by using the configuration software Step7 of Siemens PLC and the industrial monitoring software [22]. Wu et al. proposed a remote diagnosis system based on PLC automation system, and analyzed the factors affecting the system performance [23]. Ghosh used automaton and neural network to diagnose the faults of PLC controlled manufacturing system, effectively detecting and isolating the faults and exceptions in the PLC controlled manufacturing system [24]. In order to improve the reliability and fault tolerance of the control system, researchers have adopted redundant control in some systems[25-26]. Cai et al. developed an extremely reliable remote control system for subsea BOP stack using redundancy technology [27]. Ali et al. used hardware redundancy strategy to improve the performance and efficiency in case of actuator and sensor failure in the fault-tolerant scheme of nonlinear robust backstepping control manipulator with friction compensation [28]. In order to improve the stable operation of the pulse gyrotron, Wang et al. proposed a fast recovery auxiliary system with full redundancy, explosion-proof and long-term operation of the pulse gyrotron, which improved the stability of the system [29]. Zhang et al. used actuator redundancy in the specified performance increment adaptive optimal error tolerance control of nonlinear systems with actuator failures, which improved the fault tolerance of the system [30].
At present, although PLC is used in some gas drainage systems for control, the redundancy design is not realized. When the CPU, power supply and other components fail, the normal operation of the exhaust system will be seriously affected, with potential safety hazards. Therefore, we designed a gas emission monitoring system based on redundant control technology. We have designed the overall architecture of the monitoring system, using Siemens S7-1500R series PLC as the core control unit, and designed the redundancy of CPU and DC24V power supply, and designed the PLC control cabinet according to the site requirements. Smart sensors are selected in the design, and digital signal transmission is used to improve the anti-interference capability of the system. In the process of PLC program development, RS485 communication program is developed to collect field data, and PID control program is developed to control the negative pressure of gas drainage system. At the same time, we use WinCC configuration software to design human machine interface (HMI).
The operating principle of the gas drainage system is to use the negative pressure characteristics of the gas drainage pump to transport the gas stored in the coal seam to the ground for use, so as to prevent gas outburst accidents in the process of coal mining. The object of this study is the gas drainage system composed of four gas drainage pumps, as shown in Figure 1. The system consists of gas drainage pump, water pump, cooling tower, electric valve, frequency converter, control cabinet, circulating water tank, water seal flame arrester, explosion-proof device, steam water separator, gas discharge pipe network and other equipment. Among them, two 2BEC62 water ring vacuum pumps are used for high negative pressure gas drainage , and are equipped with YB2-400-4 high-voltage explosion-proof three-phase asynchronous motors. The rated voltage is 6 kV, the rated speed is 1482 r/min, the rated power is 400 kW, and the average working negative pressure of the system is 28 Kpa. Two BEC42 water ring vacuum pumps are used for low negative pressure gas drainage . They are equipped with YB2-3551-4 high-voltage explosion-proof three-phase asynchronous motor. The rated voltage is 6 kV, the rated power is 160 kW, the rated speed is 1482 r/min, and the average working negative pressure is 16 Kpa. All gas drainage pumps are controlled by Hekang high-voltage frequency converter. The system is equipped with six IS100-65-230 water pumps, two for gas drainage pump water supply, two for reducer water supply, and two for cooling tower water supply. The water pump has a flow of 30 m3/h, a lift of 17 m and a power of 5.5 kW. The system is also equipped with two 70 m3/h cooling towers to cool the circulating water temperature. Redundant design is adopted for key equipment such as gas extraction pump, water pump and cooling tower in the system.
We have designed the architecture of the gas drainage monitoring system, as shown in Fig. 2. The monitoring system is divided into the perception and execution layer, the network transmission layer and the application layer from the bottom to the top. The perceptual execution layer consists of sensors and controllers. It uses various sensors to convert physical quantities such as temperature, liquid level, vibration and flow into digital signals that can be recognized by PLC. PLC is responsible for the logic control of the gas drainage system, and the automatic control and gas drainage pump, water pump, cooling tower, electric valve and other equipment according to the sensor data collected on site and the pre prepared control program flow. The transmission layer mainly transmits the information in PLC to the application layer in real time and at high speed through network devices such as optical fiber transceivers or switches. The application layer is responsible for the remote monitoring and management of the entire gas drainage system, as well as advanced applications such as data display, analysis and storage, so as to complete the monitoring of the gas drainage system.
4.1. Design of redundant system
We use two S7-1515R-2PN controllers as the primary CPU and backup CPU, and design a redundant control system by adding digital input/output module, analog input/output module, communication module and redundant power supply module to the Profinet network, as shown in Figure 3. S7-1515R-2PN controller integrates two Profinet interfaces, a dual port X1 interface (X1P1R and X1P2R) and a single port X2 interface (X2P1). The X1P1R interface is used to connect two CPU and I/O devices to build a Profinet network. The X1P2R interface is used to connect two redundant CPUs in the Profinet network. In a Profinet network, two identical CPUs synchronize data through redundant connections. If one CPU fails, the other CPU will continue to control the process. X2P1 is used to communicate with HMI. We designed three remote I/O devices. The first remote I/O device consists of a high-performance interface module (ET 200MP IM 155-5 PN HF), four digital input modules (DI 32X24VDC), three digital output modules (DQ 32X24VDC/0.5A), two analog input modules (AI 8XU/I/RTD/TC) and an analog output module ( AQ 8XU/I). The second remote I/O device consists of a high-performance interface module ET 200MP IM 155-5 PN HF, three analog input modules (AI 8XU/I/RTD/TC), three point-to-point communication modules (CM PtP RS422/485 HF), and three digital output modules (DQ 32X24VDC/0.5A).
4.2. Redundant identity Configuration
In the S7-1500R redundant system, each CPU has a redundant identity, and only when the redundant identities of the two CPUs are different, can redundant operations be implemented. Generally, the redundant identity values are set to 1 and 2. When debugging for the first time, the redundant identity of both CPU is 1 by default, and the identity number can be assigned through the display screen on the CPU. First, connect the two CPUs in the redundant system to each other, and both are in the Stop operation state. Next, start the CPU to which you want to assign redundant Identity. Finally, on the display screen of the CPU, select the menu command (Overview>Redundancy) and set the CPU's assigned redundancy identity to 2. After the redundant identity is assigned, the CPU needs to be restarted. The CPU with redundant identity 1 works in the primary, and the CPU with redundant identity 2 works in the backup.
4.3. Hardware configuration of redundant system
We program in the Siemens configuration and programming software to configure the redundant system, as shown in Figure 4. During configuration, pay attention to that when adding and deleting the primary CPU and the backup CPU, they should be operated in pairs, otherwise communication cannot be achieved. After adding, Portal software will automatically assign an IP address to each Profinet interface of the CPU, or manually assign an IP address to each Profinet interface. However, the IP address of the interface between the two CPUs for the Profinet ring network must be in the same subnet, otherwise communication cannot be carried out. In addition to setting the equipment IP address of each CPU, a system IP address shall also be assigned to the redundant system for data communication with the HMI. The system IP is equivalent to a virtual IP address, which communicates data with the primary CPU of the redundant system. When the primary CPU fails, it automatically communicates data with the backup CPU. After CPU configuration, add three remote profinet interface modules, and each interface module is assigned an IP address. Add various I/O modules required by the system to the remote rack. When connecting the physical network, the connection shall strictly follow the general network topology configuration of the programming software, otherwise the system redundancy cannot be realized.
4.4 Redundant power supply design
In order to improve the reliability of the redundant system, we have designed the redundancy of the DC24V power supply of PLC and sensor, and its working principle is shown in Figure 5. It consists of power network, lightning arrester, circuit breaker, fuse, filter, isolation transformer, switching power module PSU100S and selection module PSE202U. After the first power supply is filtered by the power filter and isolated by the transformer, it enters the switching power supply modules PSU100S-1 and PSU100S-3 to convert AC 220V to DC 24V. Then enter the power selection module PSE202U-1 to output DC 24V power for the PLC module and CPU. Similarly, after passing through the filter and isolation transformer, the second power supply enters the switching power supply modules PSU100S-2 and PSU100S-4 to convert AC 220V to DC 24V. Then enter the power selection module PSE202U-2 to output DC 24V power for the field sensor. During normal operation, the two switching power supplies are in hot backup state. The power selection module continuously monitors two groups of power supplies and provides feedback. When one group of power supply is cut off, the power selection module will automatically switch, and another power supply will take over DC 24V to continue to supply power for PLC and sensors. When any of the two power supplies fails, the output of DC 24V power supply will not be affected, thus improving the reliability of redundant system power supply.
4.5. Smart sensor design
Considering the harsh working environment of the coal mine site, we use smart sensors in sensor design and selection, and exchange data with PLC through RS485 bus. Compared with the traditional current sensor, the smart sensor has the advantage of digital signal transmission, which can reduce the inductive interference of the transducer to the sensor and greatly enhance the anti-interference ability of the sensor. The key sensor configuration of the gas drainage system is shown in Figure 6. In order to monitor the methane concentration, flow, pressure, temperature and carbon monoxide in the gas emission system, a pipeline laser methane sensor, a gas flowmeter and a pipeline carbon monoxide sensor are designed on the intake pipe of the gas emission system. A negative pressure sensor is installed on the pipe at the inlet side of the exhaust pump to monitor the working negative pressure of the exhaust pump. A positive pressure sensor is installed on the pipe on the gas outlet side of the gas discharge pump to monitor whether the gas outlet pipe is blocked. A liquid level sensor is designed and installed on the steam water separator of the exhaust pump to monitor the working liquid level of the exhaust pump. The Pt100 temperature measuring element is designed on the front and rear axles of the exhaust pump and motor to monitor the operating temperature of the pump and motor. The vibration sensor is designed in the horizontal and vertical directions of the pump and motor to monitor the vibration status of the pump and motor. A water flow sensor is designed on the inlet pipe of the exhaust pump to monitor the water supply of the exhaust pump. A low concentration methane sensor is designed in the pump room environment to monitor whether there is gas leakage in the gas discharge pump room. Specific sensor specifications and models are shown in Table 1.
|
Name |
Specification |
Measuring range and error |
|
Electromagnetic water flow sensor |
HDD100 |
Range: 0.00 ～ 100m3/h Error: ± 1.0% (F · S) Output signal: RS485 |
|
Negative pressure sensor |
GF100F(A) |
Range: - 100 ～ 0.00Kpa Error: ± 1.0% (F · S) Output signal: RS485 |
|
Positive pressure sensor |
GF100Z(A) |
Range: 0.00 ～ 100 kPa. Error: ± 1.0% (F · S) Output signal: RS485 |
|
Liquid level sensor of steam water separator |
GPD10 |
Range: 0.00 ～ 1.00 m Error: ± 1% (F · S) Output signal: RS485 |
|
Low concentration methane sensor for mining |
KG9701B |
Range: 0.00 ～ 1.00% CH4 Error: ± 0.10% CH4 Range: 1.00 ～ 4.00% CH4 Error: ± 0.30% CH4 Output signal: RS485 |
|
Multi parameter sensor for mining (including temperature, pressure and flow detection) |
GD3(B) |
Temperature range: - 10.0～60.0 ℃, error: ± 2.50% F.S Absolute pressure: 20.0～150.0 kPa, error: ± 1.0% F.S Velocity range: 0.3~35m/s, accuracy class: 1.5 Output signal: RS485 |
|
Laser methane sensor for mine pipeline |
GJG100J(B) |
Range: (0.00 ～ 100)% CH4 Error: 0.00 ～ 1.00%, ≤± 0.05 CH4 1.00 ～ 100%, ≤± 5% CH4 of the true value Output signal: RS485 |
|
Carbon monoxide sensor for mining pipeline |
GTH1000G |
Range 0~100 (1 × 10-6) Absolute error: ± 4 (1 × 10-6） Range 100~500 (1 × 10-6) Relative error: ± 5% of the true value Range＞500 (1 × 10-6) Relative error: ± 6% of the true value Output signal: RS485 |
|
Vibration analyzer |
YZ15 |
Capacity: 16 channels Signal system: RS485 |
|
Vibration sensor |
GBC34 |
|
|
Temperature patrol detector |
YHW200 |
Capacity: 16 channels Signal system: RS485 |
|
Temperature transmitter |
Pt100 |
|
Table 1. Smart Sensor Specifications
5.1. PLC Program Flow
According to the function of the gas drainage system, we designed the PLC program, which is called circularly in the main program organization block 1 (OB1). The main program flow of PLC is shown in Figure 7. First, the PLC initializes and assigns initial values to control parameters, alarm parameters, fault parameters, etc. Then, detect whether there is a time interrupt response. When there is an interrupt response, the PLC responds to the interrupt subroutine, executes the negative pressure PID control subroutine of the four gas drainage pumps, and automatically returns to the main program after executing the interrupt subroutine. When the program is not interrupted, the main program executes analog data acquisition subroutine, communication subroutine, alarm subroutine, control subroutine and cross control subroutine from top to bottom. The analog quantity acquisition subroutine collects the opening signal of the on-site electric valve. The communication subroutine circularly sends the data fetching command of PLC and intelligent instrument, receives and analyzes the data from the intelligent instrument. The control subroutine controls the gas drainage pump, frequency converter, circulating water pump, electric valve, cooling tower, fan and other equipment. The alarm subroutine analyzes and alerts the field sensor detection data. The cross control subroutine automatically starts the corresponding equipment when the value detected by the sensor exceeds the set value according to the preset control strategy. If the sensor detects that the ambient methane in the pump room exceeds 0.5% CH4, the gas leakage may occur in the gas drainage pump and pipeline, and the roof fan will be automatically started to dilute the accumulated methane. When the water shortage sensor detects that the pump is short of water, it will automatically stop the operation of the pump to prevent the pump from being damaged due to water shortage.
5.2 Modbus communication design
We use the communication module CM RS422/485 to communicate with YZ15 vibration analyzer, PHW200 temperature patrol detector, KJ90-F16 mining monitoring substation and other intelligent instruments to collect vibration, temperature, flow, pressure and other data. The PLC as the master station sends data retrieval commands sequentially, and the intelligent instrument as the slave station responds to the request of the master station. Through MB in Portal software_ COMMLOAD and MB_ MASTER command realizes Modbus communication with intelligent instrument. The procedure is shown in Figure 8. Initialize MB in the first scan cycle_ Communication port, baud rate, communication background block and other parameters of the COMMLOAD command. In MB_ The MASTER command programs the communication address, working mode (0 read command, 1 write command), data length, data pointer and other function pins of the slave station. In the communication subprogram, MB is sent circularly_ MASTER command to realize the read/write operation of the Modbus slave. The PLC shall also analyze the received data according to the format of IEEE-754 binary floating point coding standard.
5.2 Design of negative pressure PID control program
In the study, we found that the working negative pressure of the gas drainage system is related to the rotation speed and water supply of the gas drainage pump. In order to accurately regulate the working negative pressure of the gas drainage system, we choose to regulate the working speed of the gas drainage pump to regulate the negative pressure of the drainage system under the condition that the water supply is certain. When regulating the speed, we use PID algorithm to regulate the speed. PID control algorithm is shown in Formula 1.
(1)
Where, u (t) is the output of the controller, kp is the proportional coefficient, ki is the integral coefficient, and kd is the differential coefficient. The control algorithm is discretized through programming and written into the PLC controller.
PID control principle of working negative pressure of gas drainage system is shown in Figure 9. The PLC controller compares the given pressure with the data collected by the negative pressure sensor, and then performs proportional, integral and differential calculations in the PID controller. The calculation results are output to the inverter through the analog output module, and the control signal type is 0-10V or 4-20mA. By regulating the working frequency of the inverter, the working negative pressure of the gas drainage system is adjusted.
We developed a PID control program in TIA Portal programming software to control four gas discharge pumps, as shown in Figure 10. First, the proportional gain, integral time, differential time, sampling time and process limit of the PID program are configured in the process object. Second, configure setpoints, inputs, outputs, and other parameters in the PID_Compact command block. Finally, the PID_Compat instruction block is called with a timed interrupt in the organization block 30 (OB30) .
In this study, we developed the HMI using WinCC configuration software.WinCC configuration software provides graphic editing, variable management, alarm management, data archiving and other functional modules, as well as a large number of general controls written in high-level languages, and supports VBS script language and standard C language. The software development interface is shown in Fig. 11. The system is designed with human machine interface such as process flow, data display, real-time alarm, historical alarm, real-time curve, historical curve, operation record and user management. The process flow of the gas drainage system can be displayed in the process flow interface, and the left mouse button can be used to click the equipment for inching operation and one "key" control. In the power parameter monitoring interface, the voltage, current, power, power factor and other power data of the motor can be displayed. On the parameter monitoring interface, you can monitor the concentration, carbon monoxide, pressure, temperature, flow, vibration, liquid level and other parameters of the gas drainage system and equipment status online. Real time alarm and historical alarm can be displayed on the alarm interface. The pumping data of each gas pump can be queried in the data query interface. The real-time curve and historical curve of the gas pump can be queried in the curve interface. Alarm parameters, power off parameters, control parameters and other data can be set in the parameter setting interface. The operation time, controlled equipment and operator information can be recorded in the operation record interface.
7.1. Data acquisition accuracy test
In the research, we tested the data acquisition accuracy of key sensors, and compared the portable instrument with the online sensor. Each sensor samples 8 groups of data, and the comparison results are shown in Table 2. The calculation method of sensor error is full range relative error. During the temperature test, the portable infrared thermometer and the temperature patrol detector are used to compare the online data. The maximum measurement error is 0.7%, which meets the temperature measurement requirements. During the methane test, the portable methane instrument is used to compare with the online laser methane sensor, and the maximum measurement error is 1.2%, meeting the methane measurement requirements. During the flow measurement, the portable flow sensor is used to compare with the online gas multi parameter sensor, and the maximum measurement error of flow is 1.35%, meeting the flow measurement requirements. During the negative pressure test, the mechanical negative pressure physical table is used to compare with the online negative pressure sensor, and the maximum measurement error is 0.79%, meeting the requirements of negative pressure detection. The test shows that the system sensor has small detection error and high detection accuracy, meeting the detection requirements of accurate adjustment of gas drainage system.
|
Test content |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
|---|---|---|---|---|---|---|---|---|
|
PHW200 temperature patrol detector (℃) |
10.2 |
16.6 |
21.5 |
26.7 |
30.8 |
38.2 |
46.5 |
51.6 |
|
Portable infrared thermometer (℃) |
9.8 |
16.0 |
21.2 |
26.1 |
30.1 |
37.5 |
46.0 |
51.0 |
|
Percentage error(%) |
0.4 |
0.6 |
0.3 |
0.6 |
0.7 |
0.7 |
0.5 |
0.6 |
|
GJG100J (B) laser methane sensor (% CH4) |
0.52 |
3.47 |
10.5 |
18.2 |
26.9 |
30.3 |
35.5 |
40.7 |
|
Portable gas parameter tester (% CH4) |
0.49 |
3.40 |
10.0 |
17.9 |
26.0 |
29.2 |
34.6 |
39.5 |
|
Percentage error(%) |
0.03 |
0.07 |
0.5 |
0.3 |
0.9 |
1.1 |
0.9 |
1.2 |
|
GD3 (B) gas flow sensor (m3/min) |
18.6 |
50.5 |
70.9 |
104.2 |
125.6 |
137.8 |
150.5 |
160.7 |
|
Portable flow parameter tester (m3/min) |
18.0 |
49.7 |
70.1 |
102.5 |
123.4 |
135.3 |
148.4 |
158.0 |
|
Percentage error(%) |
0.03 |
0.04 |
0.04 |
0.85 |
1.1 |
1.25 |
1.05 |
1.35 |
|
GF100F negative pressure sensor (Kpa) |
2.56 |
10.27 |
15.35 |
18.19 |
25.26 |
29.13 |
32.28 |
40.29 |
|
Portable negative pressure meter (Kpa) |
2.5 |
10 |
15 |
17.5 |
24.5 |
28.5 |
31.5 |
39.5 |
|
Percentage error(%) |
0.06 |
0.27 |
0.35 |
0.69 |
0.76 |
0.63 |
0.78 |
0.79 |
7.2. Negative pressure stability test
We tested the adaptability of the working negative pressure of the gas drainage system, and the performance curve is shown in Fig. 12. During the test, we operated the electric exhaust valve on the intake pipe under the condition of ensuring the constant water supply of the gas extraction pump. With the increase of the opening of the electric valve, the leakage of the exhaust pipe was simulated, and the working negative pressure of the exhaust pump decreased. It can be seen from the figure that the negative pressure curve with and without PID algorithm deviates downward from the negative pressure setting value. When using PID algorithm to adjust, the system can automatically adjust the working frequency of the pump, so as to improve the working speed of the pump, overcome the interference, and adjust the negative pressure of the pump to the given value. However, without PID algorithm adjustment, the system cannot overcome the interference and adjust the negative pressure of the pump to the given value. The experiment shows that the constant pressure control of gas drainage system can be realized by using PID algorithm.
7.3.Redundancy performance test
In order to test the switching time and reliability of the primary and backup CPUs of the redundant system, we simulate three failures, one of which is CPU failure, one of which is profinet network cable failure, and the other is DC24V power failure. First, we shut down the main CPU by manually creating a CPU fault. At this time, the backup CPU switches from the backup mode to the main mode, and the backup CPU is converted to the main CPU to continue working. The switching time is about 300ms. Secondly, we tested the failure points of Profinet. By removing any Profinet cable from the ring network, the working mode of the system's primary CPU and backup CPU remains unchanged, and the system works normally. Finally, we turned off any power supply to the PLC and the sensor, and the power supply to the PLC module and the sensor was normal. The test shows that when any CPU, profinet cable or power supply in the redundant system fails, the normal operation of the redundant system will not be affected, and the reliability of the system is effectively improved.
(1)A gas drainage monitoring system based on redundant control technology is proposed. Through the design of system architecture, PLC hardware, PLC software and human-computer interface, the overall perception of the gas drainage system and the one button control of gas drainage pump, water pump, electric valve and other equipment are realized, which has been successfully applied in coal mines.
(2)In the design of the system, intelligent sensors are used. Through digital signal transmission, the anti-interference ability of the system is effectively improved.The switching time of the primary and backup CPUs of the system is about 300 ms, and the switching efficiency is high. When the primary CPU fails, the operation of the gas drainage system will not be affected.
(3)The field application shows that the system can still work normally when any CPU, profinet cable or power supply fails after the redundancy technology is adopted in the system, which effectively improves the stability and reliability of the gas drainage monitoring system and achieves the goal of monitoring the gas drainage system efficiently.
Data availability
The raw/processed data required to reproduce these findings cannot be shared at this time due to technical or time limitations. However, these data will be shared upon request to the corresponding author.
Author Contributions: Conceptualization, Z.X.W. and T.L.; engineering design, Z.X.W. and T.L.;methodology, Z.X.W. and T.L.; software, Z.X.W.; validation, Z.X.W.; formal analysis, Z.X.W.; investigation, Z.X.W. and T.L.; resources, Z.X.W. and T.L.; data curation, Z.X.W.; writing—original draft preparation, Z.X.W. and T.L.; writing—review and editing, Z.X.W. and T.L.; visualization, Z.X.W. and T.L.; project administration, Z.X.W; funding acquisition,Z.X.W. and T.L. All authors have read and agreed to the published version of the manuscript.
Funding: The work is supported by Science and Technology Innovation Venture Capital Special Project of Tiandi Co., Ltd [Project No. 2021-TD-ZD009] and [Project No. 2022-TD-ZD001]
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
- Kholod N, Evans M, Pilcher RC, Roshchanka V, Ruiz F, Coté M, Collings R. Global methane emissions from coal mining to continue growing even with declining coal production. J Clean Prod. 2020;256:120489. doi: 10.1016/j.jclepro.2020.120489. PMID: 34334967; PMCID: PMC8320667.
- Zhai C, Qin L, Liu S, Xu J, Tang Z, Wu S (2016) Pore structure in coal:pore evolution after cryogenic freezing with cyclic liquid nitrogen injection and its implication on coalbed methane extraction. Energy Fuel 30:6009–6020.
- Teng F, Su X, Wang X. Can China Peak Its Non-CO2 GHG Emissions before 2030 by Implementing Its Nationally Determined Contribution? Environ Sci Technol. 2019 Nov 5;53(21):12168–12176. doi: 10.1021/acs.est.9b04162. Epub 2019 Oct 23. PMID: 31600434.
- He X, Song L (2012) Status and future tasks of coal mining safety in China. Safety Sci 50(4):894–898.
- Qianting H, Yunpei L, Han W, Quanle Z, Haitao S. Intelligent and integrated techniques for coalbed methane (CBM) recovery and reduction of greenhouse gas emission. Environ Sci Pollut Res Int. 2017 Jul;24(21):17651–17668. doi: 10.1007/s11356-017-9335-4. Epub 2017 Jun 9. PMID: 28600793.
- Wu H, Li X, Gao X, Chen D, Li Z. Development and Application of Water Sealing Technology for Gas Drainage Boreholes. ACS Omega. 2021 Dec 30;7(1):733–743. doi: 10.1021/acsomega.1c05385. PMID: 35036739; PMCID: PMC8757332.
- Borchardt, J.; Gerilowski, K.; Krautwurst, S.; Bovensmann, H.; Burrows, J.P. Detection and quantification of CH4 plumes using the WFM-DOAS retrieval on A VIRIS-NG hyperspectral data. Atmos. Meas. T ech. 2021, 14, 1267–1291. [CrossRef]
- Linghu J, Chen H, Wang L, An F. New Technology of Mechanical Cavitation in a Coal Seam to Promote Gas Extraction. ACS Omega. 2022 Jun 7;7(24):21163–21171. doi: 10.1021/acsomega.2c01962. PMID: 35935294; PMCID: PMC9348011.
- Liu, Yin; Wen, Hu; Guo, Jun; Jin, Yongfei; Wei, Gaoming; Yang, Zhengwei (2020). Coal spontaneous combustion and N2 suppression in triple goafs: A numerical simulation and experimental study. Fuel, 271(), 117625–. doi:10.1016/j.fuel.2020.117625.
- Qi Q, Jia X, Zhou X, Zhao Y. Instability-negative pressure loss model of gas drainage borehole and prevention technique: A case study. PLoS One. 2020 Nov 23;15(11):e0242719. doi: 10.1371/journal.pone.0242719. PMID: 33227010; PMCID: PMC7682895.
- Cai C, Si J, Li L, Liu H, Zhao S. Optimal Parameters of Gas Drainage and Carbon Dioxide Inerting Technology and Its Application in a High Gassy and Spontaneous Combustion Mine. ACS Omega. 2022 Aug 31;7(36):32512–32524. doi: 10.1021/acsomega.2c04007. PMID: 36120029; PMCID: PMC9476503.
- Valencia-Palomo G, Rossiter JA. Programmable logic controller implementation of an auto-tuned predictive control based on minimal plant information. ISA Trans. 2011 Jan;50(1):92–100. doi: 10.1016/j.isatra.2010.10.002. Epub 2010 Nov 5. PMID: 21056412.
- Bayindir R, Cetinceviz Y. A water pumping control system with a programmable logic controller (PLC) and industrial wireless modules for industrial plants–an experimental setup. ISA Trans. 2011 Apr;50(2):321–8. doi: 10.1016/j.isatra.2010.10.006. Epub 2010 Dec 3. PMID: 21126739.
- A. Honda; F. Okano; K. Ooshima; N. Akino; K. Kikuchi; Y. Tanai; T. Takenouchi; S. Numazawa; Y. Ikeda (2008). Application of PLC to dynamic control system for liquid He cryogenic pumping facility on JT-60U NBI system., 83(2–3), 276–279. doi:10.1016/j.fusengdes.2008.01.005
- Su, Hailong; Luo, Zong-an; Feng, Ying-ying; Liu, Zhao-song (2019). Application of Siemens PLC in Thermal Simulator Control System. Procedia Manufacturing, 37(), 38–45. doi:10.1016/j.promfg.2019.12.009.
- Vadi S, Bayindir R, Toplar Y, Colak I. Induction motor control system with a Programmable Logic Controller (PLC) and Profibus communication for industrial plants - An experimental setup. ISA Trans. 2022 Mar;122:459–471. doi: 10.1016/j.isatra.2021.04.019. Epub 2021 Apr 20. PMID: 33906732.
- Gao J, Wang J, Xie J. Application of PLC and HMI in the CO2 transcritical refrigeration experimental platform. Sci Rep. 2022 Sep 7;12(1):15199. doi: 10.1038/s41598-022-19602-w. PMID: 36071207; PMCID: PMC9452586.
- Kaczmarek W, Panasiuk J, Borys S, Pobudkowska A, Majsterek M. Analysis of the Kinetics of Swimming Pool Water Reaction in Analytical Device Reproducing Its Circulation on a Small Scale. Sensors (Basel). 2020 Aug 26;20(17):4820. doi: 10.3390/s20174820. PMID: 32858989; PMCID: PMC7506937.
- Shu, Q. G., Lin, R., Zhen, G. L. & Fei, H. L. The design of controlling system in the evaporative cooling super computer simulation experiment platform based on PLC. Appl. Mech. Mater. 2773, 734–739. https://doi.org/10.4028/www.scientific.net/ AMM. 437. 734 (2013).
- Włodarczak S, Ochowiak M, Doligalski M, Kwapisz B, Krupińska A, Mrugalski M, Matuszak M. Flow Rate Control by Means of Flow Meter and PLC Controller. Sensors (Basel). 2021 Sep 14;21(18):6153. doi: 10.3390/s21186153. PMID: 34577360; PMCID: PMC8470381.
- Chang, Wanying; Xie, Jing; Wang, Jinfeng; Teng, Wenqiang; Sun, Yuyao; Zheng, Mingtao (2020). Application of PLC and HMI in the measurement and control platform of single-tube heat transfer experiment rig. Advances in Mechanical Engineering, 12(11), 168781402097116–. doi:10.1177/1687814020971162.
- Pan, W., Wu, J. H., Li, Q., Liu, L. Q. & Li, Q. The control system of a 2kW@20K helium refrigerator. IOP Conf. Ser. Mater. Sci. Eng. 278, 1. https://doi.org/10.1088/1757- 899X/278/1/012087 (2017).
- Wu, Zhenhua; Sekar, Ramnath; Hsieh, Sheng-jen (“Tony”) (2014). Study of factors impacting remote diagnosis performance on a PLC based automated system. Journal of Manufacturing Systems, 33(4), 589–603. doi:10.1016/j.jmsy.2014.05.007.
- Ghosh, Arup; Wang, Gi-Nam; Lee, Jooyeoun (2020). A novel automata and neural network based fault diagnosis system for PLC controlled manufacturing systems. Computers & Industrial Engineering, 139(), 106188–. doi:10.1016/j.cie.2019.106188.
- Cheng B, Cheng X, Song S, Deng S, Zhou R, Hu Y, Wu H. Fault-Tolerant Control of Magnetically-Levitated Rotor with Redundant Structures Based on Improved Generalized Linearized EMFs Model. Sensors (Basel). 2021 Aug 10;21(16):5404. doi: 10.3390/s21165404. PMID: 34450844; PMCID: PMC8401880.
- Ye W, Cheng R, Zhang M, Zhu Y, Wang L, Hu J, Li X. Grating Interferometer with Redundant Design for Performing Wide-Range Displacement Measurements. Sensors (Basel). 2022 May 14;22(10):3738. doi: 10.3390/s22103738. PMID: 35632147; PMCID: PMC9144901.
- Cai B, Liu Y, Liu Z, Wang F, Tian X, Zhang Y. Development of an automatic subsea blowout preventer stack control system using PLC based SCADA. ISA Trans. 2012 Jan;51(1):198–207. doi: 10.1016/j.isatra.2011.08.003. Epub 2011 Sep 1. PMID: 21889767.
- Ali K, Mehmood A, Iqbal J. Fault-tolerant scheme for robotic manipulator-Nonlinear robust back-stepping control with friction compensation. PLoS One. 2021 Aug 20;16(8):e0256491. doi: 10.1371/journal.pone.0256491. PMID: 34415970; PMCID: PMC8378759.
- Wang Z, Zhang J, Sun X, Wang P, Xiao H, Ding T, Xie J, Han X. Fully redundant auxiliary system for gyrotron-based terahertz sources in long-term operation. Rev Sci Instrum. 2021 May 1;92(5):054711. doi: 10.1063/5.0050044. PMID: 34243330.
- Zhang S, Huang C, Ji K, Zhang H. Prescribed performance incremental adaptive optimal fault-tolerant control for nonlinear systems with actuator faults. ISA Trans. 2022 Jan;120:99–109. doi: 10.1016/j.isatra.2021.03.011. Epub 2021 Mar 19. PMID: 33814263.
No competing interests reported.