CN114118797A - Real-time monitoring system and method based on tunnel risks and disasters - Google Patents
Real-time monitoring system and method based on tunnel risks and disasters Download PDFInfo
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Abstract
The invention discloses a real-time monitoring system based on tunnel risks and disasters, which comprises monitoring terminals, wherein the monitoring terminals adopt different measurement types and are used for acquiring seepage, crack change, water level, tunnel structure deformation, foreign matters in a tunnel and abnormal tunnel vibration disaster risks in a tunnel in real time; the remote big data platform is used for receiving monitoring information sent by the monitoring terminal, and storing, intelligently analyzing and displaying the monitoring information; the wireless network transmission terminal is arranged between the monitoring terminal and the remote big data platform and used for transmitting the monitoring information of the monitoring terminal to the remote big data platform; the remote big data platform comprises a real-time monitoring unit, a data analysis unit and an alarm unit; the invention comprehensively collects the tunnel risks and various types of possibility data of disaster occurrence, and timely monitors, analyzes and evaluates the evaluation value with high disaster risk occurrence rate to give an alarm.
Description
Technical Field
The invention belongs to the field of risk and disaster monitoring, and particularly relates to a system and a method for monitoring risks and disasters in real time based on a tunnel.
Background
Because China has a large population and a small land and is in the rapid development stage of urbanization, the existing urban traffic infrastructure faces huge challenges, and China is developing rail transit vigorously to relieve traffic travel pressure. In recent years, tunnel engineering is becoming more and more popular with the increasing demand for environmental protection, western development and ground traffic congestion in large cities. According to incomplete statistics, the business mileage of the China railway reaches 13.9 km by 2019. Wherein, the total length of the operating railway tunnel 16084 seats is 18041 km. 967 operating line railway tunnels are newly added in 2019, and the total length is 1710 km. Wherein, the length of the extra-long tunnel 27 is more than 10km, and the total length is 369 km. 2950 seats of railway tunnel under construction, the total length is 6419 km. And (5) planning 6395 railway tunnels with the total length of 16326 km. China has become the super kingdom for tunnels.
However, the railway engineering construction is in the spotlight in China, and the tunnel engineering construction and operation under complex geological conditions face more and more challenges. The typical engineering disasters during the tunnel construction period mainly include 7 kinds of water inrush and mud outburst, collapse, large deformation, rock burst, harmful gas, high ground temperature, freezing damage and the like. During the operation of the tunnel, the risks of tunnel block falling, water seepage, crack change, box door state, water level, tunnel structure deformation, foreign matters in a rail running area, abnormal tunnel vibration and the like are mainly existed.
For the disaster risks, various tunnel disaster monitoring systems and methods are currently available, for example: patent publication No. CN210899299U discloses a tunnel monitoring system, which includes a collecting device, a processing device connected with the collecting device, and a transmission module connected with the processing device. The acquisition device comprises a temperature monitoring module, a gas monitoring module and a radar foreign matter monitoring module. The processing device comprises a switch connected with the acquisition device and a comprehensive data analysis management server connected with the switch. The monitoring system can monitor the temperature, the gas and the foreign matters in the tunnel in real time.
The above patents have disadvantages: the existing monitoring system cannot realize comprehensive coverage monitoring of the whole tunnel.
Disclosure of Invention
The invention provides a real-time monitoring system and method based on tunnel risks and disasters, aiming at the problem that the existing monitoring system in the prior art cannot realize comprehensive coverage monitoring of the whole tunnel.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
the system comprises monitoring terminals, wherein the monitoring terminals adopt different measurement types and are used for acquiring seepage, crack change, water level, tunnel structure deformation, foreign matters in the tunnel and abnormal tunnel vibration disaster risks in the tunnel in real time;
the remote big data platform is used for receiving monitoring information sent by the monitoring terminal, and storing, intelligently analyzing and displaying the monitoring information;
the wireless network transmission terminal is arranged between the monitoring terminal and the remote big data platform and used for transmitting the monitoring information of the monitoring terminal to the remote big data platform;
the remote big data platform comprises a real-time monitoring unit, a data analysis unit and an alarm unit; the real-time monitoring unit is preset with a water seepage amount, a water level value, a temperature and humidity value and an early warning value for judging whether foreign matters exist in the tunnel or not, is used for monitoring the water seepage, the water level, the temperature and the humidity in the tunnel and the generation of the foreign matters in the tunnel in real time, and timely reflects real information in the tunnel according to an acquired monitoring terminal; the data analysis unit is used for evaluating the current tunnel disaster risk occurrence rate by combining the tunnel basic data and the historical data change curve; the alarm unit is used for monitoring the water seepage amount, the water level value, the temperature and humidity value and the existence of foreign matters in the tunnel which are preset by the real-time monitoring unit; and meanwhile, alarming is carried out on the evaluation value with high disaster risk occurrence rate of the data analysis unit.
Further, monitor terminal includes camera device, measuring device, temperature and humidity sensor, water sensor, level sensor, crack monitor, vibrations measuring transducer and biosensor.
Furthermore, the remote big data platform also comprises a terrain acquisition unit, a simulation unit and a tunnel basic data entry unit; the simulation unit is used for combining survey data with the tunnel base model to obtain a tunnel simulation model; the tunnel basic data entry unit is used for entering survey data of the tunnel, and the survey data comprises geological survey data, geophysical prospecting data, drilling data and mapping data.
Furthermore, a repeater is arranged between the wireless network transmission terminal and the monitoring terminal, and a local area network is formed inside the wireless network transmission terminal to transmit the data collected by the monitoring terminal before the data is transmitted by the wireless network transmission terminal through the repeater.
A real-time monitoring method based on tunnel risks and disasters comprises the following steps:
s1, collecting topographic data inside and outside the tunnel, and creating a tunnel basic model;
s2, recording survey data of the tunnel on the tunnel basic model to obtain a tunnel simulation model;
s3, acquiring data of disaster risks in the tunnel in real time through a monitoring terminal;
s4, binding and transmitting the data and the position information collected by each monitoring terminal to the repeater;
s5, the repeater transmits the acquired data to a remote big data platform through a wireless network transmission terminal;
s6, displaying the information of the super-preset monitoring device and the position information of the monitoring point in real time through the tunnel simulation model integrated on the remote big data platform;
s7, analyzing whether the super-preset monitoring device information and the monitoring point position information have the probability of generating disaster risks, if so, entering the step S8, and if not, returning to the step S3 to continue collecting the tunnel monitoring terminal data;
and S8, triggering alarm information if the probability of disaster risk is generated, and displaying the position information of the alarm monitoring point on the tunnel simulation model integrated on the remote big data platform.
Further, in the step S7, the method further evaluates the current tunnel disaster risk occurrence rate, and includes the specific steps of:
s701, collecting a change value in the tunnel, and drawing a historical data change curve;
s702, crawling the lowest value of the change of the historical tunnel disaster risk, judging whether the current data change value is higher than the lowest value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, and if the current data change value is higher than the minimum value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, returning to the step S3;
and S703, displaying the position information of the alarm monitoring point on the tunnel simulation model, and simultaneously displaying and drawing a historical data change curve and a data change table.
Compared with the prior art, the invention has the following beneficial effects:
the method comprehensively collects the tunnel risks and various types of possibility data of disaster occurrence, and timely monitors, analyzes and evaluates the evaluation value with high disaster risk occurrence rate to give an alarm.
Drawings
FIG. 1 is a block diagram of a real-time monitoring system for risk and disaster based on tunnels according to the present invention;
FIG. 2 is a flow chart of a real-time monitoring method based on tunnel risk and disaster according to the present invention;
fig. 3 is a flowchart illustrating a detailed evaluation of the risk occurrence rate of the tunnel disaster based on the real-time monitoring method of the tunnel risk and the disaster according to the present invention.
The notation in the figure is: 10-a monitoring terminal, 20-a remote big data platform, 30-a wireless network transmission terminal, 201-a real-time monitoring unit, 202-a data analysis unit, 203-an alarm unit, 204-a terrain acquisition unit, 205-a simulation unit, 206-a tunnel basic data entry unit, 40-a repeater, 101-a camera device, 102-a measurement device, 103-a temperature and humidity sensor, 104-a water sensor, 105-a water level sensor, 106-a crack monitor, 107-a vibration measurement sensor and 108-a biosensor.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention.
As shown in fig. 1, the real-time monitoring system based on the tunnel risk and disaster includes a monitoring terminal 10, wherein the monitoring terminal 10 adopts monitoring terminals 10 of different measurement types for acquiring water seepage, crack change, water level, tunnel structure deformation, foreign matter in the tunnel, and abnormal tunnel vibration disaster risk in the tunnel in real time; the remote big data platform 20 is used for receiving the monitoring information sent by the monitoring terminal 10, and storing, intelligently analyzing and displaying the monitoring information; the wireless network transmission terminal 30 is arranged between the monitoring terminal 10 and the remote big data platform 20 and is used for forwarding the monitoring information of the monitoring terminal 10 to the remote big data platform 20; the remote big data platform 20 comprises a real-time monitoring unit 201, a data analysis unit 202 and an alarm unit 203; the real-time monitoring unit 201 is preset with a water seepage amount, a water level value, a temperature and humidity value and an early warning value for whether foreign matters exist in the tunnel or not, is used for monitoring the water seepage, the water level, the temperature and the humidity in the tunnel and the generation of the foreign matters in the tunnel in real time, and timely reflects real information in the tunnel according to the collected monitoring terminal 10; the data analysis unit 202 is used for evaluating the current tunnel disaster risk occurrence rate by combining the tunnel basic data and the historical data change curve; the alarm unit 203 is used for monitoring the water seepage amount, the water level value, the temperature and humidity value and the foreign matters in the tunnel preset by the real-time monitoring unit 201; and simultaneously, alarming the evaluation value with high disaster risk occurrence rate of the data analysis unit 202.
The monitoring terminal 10 includes a camera 101, a measuring device 102, a temperature and humidity sensor 103, a water sensor 104, a water level sensor 105, a crack monitor 106, a vibration measuring sensor 107, and a biosensor 108. Gather the tunnel structure through camera device 101, measure each partial structure numerical value in tunnel through measuring device 102 simultaneously, convenient follow-up and reduce to tunnel simulation model on according to the proportion, gather the inside and outside humiture change in tunnel through temperature and humidity sensor 103, whether have the possibility of infiltration around the sensor through water sensor 104, whether change through water level sensor 105 further measurement tunnel internal water seepage department's water level value or measurement tunnel around the water level of natural pond, prevent that the too high tunnel ponding that produces of infiltration department's water level value even collapses the risk, whether the water level of measuring tunnel around the natural pond change prevents tunnel around the geological change unstability, bring the risk of collapsing for the tunnel. The crack monitor 106 monitors the change of the cracks in the tunnel, and the tunnel disaster caused by overlarge or too fast change of the cracks is prevented. The vibration measuring sensor 107 is used for measuring whether the vibration of the tunnel is normal or not, so that the tunnel risk caused by large vibration change is prevented. Whether living organisms enter the tunnel or not is monitored through the biosensor 108, and therefore traffic accidents are prevented from occurring, and normal use of the tunnel is prevented from being influenced.
The remote big data platform 20 further comprises a terrain acquisition unit 204, a simulation unit 205 and a tunnel basic data entry unit 206; the terrain acquisition unit 204 is used for acquiring terrain data inside and outside the tunnel, the simulation unit 205 is used for modeling a CIM system according to the terrain data to obtain a tunnel basic model, and the simulation unit 205 is also used for combining survey data with the tunnel basic model to obtain a tunnel simulation model; the tunnel base data entry unit 206 is used to enter survey data for the tunnel, including geophysical survey data, drilling data, and mapping data. A tunnel simulation model is established through the terrain acquisition unit 204, the simulation unit 205 and the tunnel basic data entry unit 206, so that real tunnel environment information can be conveniently displayed in a virtual environment on a platform, and a monitoring device is provided with a position and an alarm signal. Therefore, the monitoring personnel can more intuitively observe the data change of the monitoring terminals 10 with different measurement types.
A repeater 40 is arranged between the wireless network transmission terminal 30 and the monitoring terminal 10, and before the wireless network transmission terminal 30 transmits data, a local area network is formed inside the wireless network transmission terminal 40 to transmit data collected by the monitoring terminal 10. The data information of all the monitoring terminals 10 is transmitted at one time through the repeater 40, so that the problems that a single transmission occupies a network line, data messy codes are easy to occur, and data transmission is incomplete are prevented. And the communication distance is enlarged. The maximum number of nodes is increased. Different communication rates may be used for each network segment. The reliability is improved. When the network fails, only individual network segments are generally affected, and the whole wireless network transmission network is not affected.
As shown in fig. 2, the real-time monitoring method based on the tunnel risk and disaster includes the steps of:
s1, collecting topographic data inside and outside the tunnel, and creating a tunnel basic model;
s2, recording survey data of the tunnel on the tunnel basic model to obtain a tunnel simulation model;
s3, acquiring data of disaster risks generated in the tunnel in real time through the monitoring terminal 10;
s4, binding and transmitting the data and the position information collected by each monitoring terminal 10 to the repeater 40;
s5, the repeater 40 transmits the collected data to the remote big data platform 20 through the wireless network transmission terminal 30;
s6, displaying the super-preset monitoring device information and the monitoring point position information in real time through the tunnel simulation model integrated on the remote big data platform 20;
s7, analyzing whether the super-preset monitoring device information and the monitoring point position information have the probability of generating the disaster risk, if so, entering the step S8, and if not, returning to the step S3 to continuously acquire the data of the tunnel monitoring terminal 10;
and S8, triggering alarm information if the probability of disaster risk is generated, and displaying the position information of the alarm monitoring point on the tunnel simulation model integrated on the remote big data platform 20.
As shown in fig. 3, in step S7, the method further evaluates the risk occurrence rate of the current tunnel disaster, and includes the specific steps of:
s701, collecting a change value in the tunnel, and drawing a historical data change curve;
s702, crawling the lowest value of the change of the historical tunnel disaster risk, judging whether the current data change value is higher than the lowest value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, and if the current data change value is higher than the minimum value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, returning to the step S3;
and S703, displaying the position information of the alarm monitoring point on the tunnel simulation model, and simultaneously displaying and drawing a historical data change curve and a data change table.
Compared with the prior art, the invention has the following beneficial effects:
the method comprehensively collects the tunnel risks and various types of possibility data of disaster occurrence, and timely monitors, analyzes and evaluates the evaluation value with high disaster risk occurrence rate to give an alarm.
The system and the method for monitoring risks and disasters in real time based on the tunnel are described in detail above. The description of the specific embodiments is only intended to facilitate an understanding of the methods of the present application and their core concepts. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
Claims (6)
1. The system is characterized by comprising monitoring terminals (10), wherein the monitoring terminals (10) of different measurement types are adopted by the monitoring terminals (10) and are used for acquiring seepage, crack change, water level, tunnel structure deformation, foreign matters in the tunnel and tunnel abnormal vibration disaster risks in the tunnel in real time;
the remote big data platform (20) is used for receiving monitoring information sent by the monitoring terminal (10), and storing, intelligently analyzing and displaying the monitoring information;
the wireless network transmission terminal (30) is arranged between the monitoring terminal (10) and the remote big data platform (20) and is used for forwarding the monitoring information of the monitoring terminal (10) to the remote big data platform (20);
the remote big data platform (20) comprises a real-time monitoring unit (201), a data analysis unit (202) and an alarm unit (203); the real-time monitoring unit (201) is preset with a water seepage amount, a water level value, a temperature and humidity value and an early warning value for judging whether foreign matters exist in the tunnel or not, is used for monitoring the water seepage, the water level, the temperature and the humidity in the tunnel and the generation of the foreign matters in the tunnel in real time, and timely reflects real information in the tunnel according to the collected monitoring terminal (10); the data analysis unit (202) is used for evaluating the current tunnel disaster risk occurrence rate by combining the tunnel basic data and the historical data change curve; the alarm unit (203) is used for presetting the water seepage amount, the water level value, the temperature and humidity value and the existence of foreign matters in the tunnel for the real-time monitoring unit (201); and simultaneously, alarming the evaluation value with high disaster risk occurrence rate of the data analysis unit (202).
2. The real-time monitoring system based on tunnel risk and disaster as claimed in claim 1, wherein the monitoring terminal (10) comprises a camera device (101), a measuring device (102), a temperature and humidity sensor (103), a water sensor (104), a water level sensor (105), a crack monitor (106), a vibration measuring sensor (107) and a biosensor (108).
3. The real-time tunnel risk and disaster based monitoring system according to claim 1 or 2, wherein the remote big data platform (20) further comprises a terrain acquisition unit (204), a simulation unit (205) and a tunnel base data entry unit (206); the terrain acquisition unit (204) is used for acquiring terrain data inside and outside the tunnel, the simulation unit (205) is used for modeling a CIM system according to the terrain data to obtain a tunnel basic model, and the simulation unit (205) is also used for combining survey data with the tunnel basic model to obtain a tunnel simulation model; a tunnel basis data entry unit (206) is for entering survey data for the tunnel, the survey data including geophysical data, drilling data, and mapping data.
4. The real-time monitoring system based on the tunnel risk and disaster according to claim 3, wherein a relay (40) is arranged between the wireless network transmission terminal (30) and the monitoring terminal (10), and before the wireless network transmission terminal (30) transmits data, the relay (40) internally forms a local area network transmission monitoring terminal (10) to collect data.
5. A real-time monitoring method based on tunnel risks and disasters is characterized by comprising the following steps:
s1, collecting topographic data inside and outside the tunnel, and creating a tunnel basic model;
s2, recording survey data of the tunnel on the tunnel basic model to obtain a tunnel simulation model;
s3, acquiring data of disaster risks generated in the tunnel in real time through the monitoring terminal (10);
s4, binding and transmitting the data collected by each monitoring terminal (10) and the position information to the repeater (40);
s5, the repeater (40) transmits the collected data to the remote big data platform (20) through the wireless network transmission terminal (30);
s6, displaying the information of the super-preset monitoring device and the position information of the monitoring point in real time through a tunnel simulation model integrated on the remote big data platform (20);
s7, analyzing whether the super-preset monitoring device information and the monitoring point position information have the probability of generating disaster risks, if so, entering the step S8, and if not, returning to the step S3 to continuously acquire data of the tunnel monitoring terminal (10);
and S8, if the probability of disaster risk is generated, triggering alarm information, and displaying the position information of the alarm monitoring point on a tunnel simulation model integrated on the remote big data platform (20).
6. The real-time tunnel risk and disaster monitoring method according to claim 5, wherein the step S7 of evaluating the current tunnel disaster risk occurrence rate further comprises the following specific steps:
s701, collecting a change value in the tunnel, and drawing a historical data change curve;
s702, crawling the lowest value of the change of the historical tunnel disaster risk, judging whether the current data change value is higher than the lowest value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, and if the current data change value is higher than the minimum value of the change of the historical tunnel disaster risk or the average value of the change of the historical tunnel disaster risk, returning to the step S3;
and S703, displaying the position information of the alarm monitoring point on the tunnel simulation model, and simultaneously displaying and drawing a historical data change curve and a data change table.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115457742A (en) * | 2022-08-15 | 2022-12-09 | 广东新电电力科技有限公司 | Water logging sensor alarm device based on big data analysis reports to police |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115457742A (en) * | 2022-08-15 | 2022-12-09 | 广东新电电力科技有限公司 | Water logging sensor alarm device based on big data analysis reports to police |
| CN115457742B (en) * | 2022-08-15 | 2024-04-19 | 广东新电电力科技有限公司 | Water logging sensor alarm device based on big data analysis carries out warning |
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