CN111622806A - Intelligent early warning method for high-temperature instability of subway tunnel concrete lining - Google Patents
Intelligent early warning method for high-temperature instability of subway tunnel concrete lining Download PDFInfo
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- CN111622806A CN111622806A CN202010472129.8A CN202010472129A CN111622806A CN 111622806 A CN111622806 A CN 111622806A CN 202010472129 A CN202010472129 A CN 202010472129A CN 111622806 A CN111622806 A CN 111622806A
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- 239000004567 concrete Substances 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000011897 real-time detection Methods 0.000 claims abstract description 24
- 238000006073 displacement reaction Methods 0.000 claims abstract description 16
- 230000001133 acceleration Effects 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 abstract description 8
- 230000008859 change Effects 0.000 abstract description 5
- 230000002159 abnormal effect Effects 0.000 abstract description 2
- 238000013461 design Methods 0.000 abstract description 2
- 238000012423 maintenance Methods 0.000 abstract description 2
- 230000001932 seasonal effect Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 239000011150 reinforced concrete Substances 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 230000003746 surface roughness Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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- Engineering & Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Geology (AREA)
- Lining And Supports For Tunnels (AREA)
Abstract
The invention discloses an intelligent early warning method for high-temperature instability of a subway tunnel concrete lining, which carries out real-time early warning through a deformation real-time detection system and a settlement real-time detection system. Through the mode, according to the intelligent early warning method for the high-temperature instability of the subway tunnel concrete lining, the two sets of systems are controlled to monitor the deformation and the top collapse of the subway tunnel concrete lining respectively, early warning is conducted, the seasonal change rule of the deformation of the tunnel lining is analyzed by the deformation real-time detection system, different early warning threshold values are set according to different temperatures, the method is more reasonable and safer, the settlement real-time detection system automatically achieves real-time monitoring and early warning of the accumulated displacement and the deformation rate of the vault, a reverse cursor does not need to be arranged at a monitoring point, the displacement value of the rough surface of concrete is automatically calculated, abnormal data are accurately removed, real-time performance is achieved, early warning signals can be sent out in time, safety is greatly improved, and certain guiding significance is achieved for design and maintenance of regional tunnels.
Description
Technical Field
The invention relates to the technical field of detection of subway tunnels, in particular to an intelligent early warning method for high-temperature instability of a subway tunnel concrete lining.
Background
The social economy of China is rapidly increased at present, the traffic development is rapid, various railways, highways, tunnels and subways are also greatly constructed, the lining refers to a permanent supporting structure constructed by reinforced concrete and other materials along the periphery of a tunnel body for preventing surrounding rocks from deforming or collapsing, the permanent supporting structure is usually applied to tunnel engineering and water conservancy channels, but in the tunnel engineering construction, concrete lining cracks are very easy to occur due to the internal and external temperature difference of concrete, the internal and external humidity changes of concrete are inconsistent, the curing time is shortened after the concrete is poured, the concrete is poured in sections, and the like, so that the tunnel is damaged, and the economic loss is caused.
Disclosure of Invention
The invention mainly solves the technical problem of providing an intelligent early warning method for high-temperature instability of a subway tunnel concrete lining.
In order to solve the technical problems, the invention adopts a technical scheme that:
the intelligent early warning method for the high-temperature instability of the subway tunnel concrete lining comprises the following steps:
(1) the method comprises the steps that a deformation real-time detection system and a settlement real-time detection system are arranged at safe distances from an inlet and an outlet of a tunnel and at a cross section of a lining with cracks, the deformation real-time detection system compares a strain value with a first early warning threshold value through set time to start early warning, the deformation real-time detection system comprises strain sensors, a data acquisition instrument, a GPRS module and a server, the strain sensors are distributed on an arc surface of the cross section of the lining at equal intervals, the settlement real-time detection system compares settlement displacement with a second early warning threshold value to start early warning, the settlement real-time detection system comprises a laser range finder, an automatic filtering device and a memory, and the laser range finder is arranged on the horizontal ground of the cross section of the lining;
(2) the data acquisition instrument comprises a comprehensive acquisition module, a signal lightning protection module and a power supply lightning protection module which are integrated in an acquisition box body, wherein the strain value sigma of the strain sensor acquired by the data acquisition instrument is sent to a main control system, and the deformation acceleration is obtained according to continuous different time points t1, t2 and t3 and time intervals △ t = t3-t2= t2-t1
Taking the average value of the deformation acceleration of the quarter of the last year as a first early warning threshold value of the same quarter of the year
；
(3) The laser range finder data acquisition device sends the memory after filtering through the automatic filter device, and the main control system data of gathering the memory are analyzed, and the laser range finder places in the same position on the horizontal ground of cross section, carries out the range finding of different time points, and laser projection forms the facula at the deformation surface monitoring point, and the laser straight line distance to the facula is measured to the laser range finder, and the distance that initial time point n1 measured is
The distance measured at the time point n2 is
Then, according to the included angle α between the laser and the horizontal direction, the settlement displacement is obtained as
Taking the average value of the settlement displacement of the last year as a second early warning threshold value of the current year
；
(4) When in use
When or when
And starting early warning.
In a preferred embodiment of the invention, the safety distance is 80 meters.
In a preferred embodiment of the present invention, the set time is 1 hour.
In a preferred embodiment of the invention, the quarter is a year comprising four quarters, the first quarter being 1-3 months, the first quarter being 4-6 months, the first quarter being 7-9 months, the first quarter being 9-12 months.
In a preferred embodiment of the present invention, the server transmits the strain value data collected by the data collector to the controller through a TCP/UDP network protocol.
In a preferred embodiment of the present invention, the strain sensor is a vibrating wire strain gauge.
In a preferred embodiment of the invention, the GPRS module comprises RS232 and RS485 interfaces.
In a preferred embodiment of the present invention, the main control system includes a database, a controller, a lower computer and an early warning module.
In a preferred embodiment of the present invention, the early warning module includes an alarm lamp and a buzzer.
In a preferred embodiment of the present invention, the master control system analyzes and stores data of the memory.
The invention has the beneficial effects that: the intelligent early warning method for the high-temperature instability of the subway tunnel concrete lining is characterized in that two sets of systems are controlled to monitor the deformation and the top collapse of the subway tunnel concrete lining respectively, early warning is conducted, a deformation real-time detection system analyzes seasonal change rules of tunnel lining deformation, different early warning threshold values are set according to different temperatures, the method is reasonable and safe, the settlement real-time detection system automatically achieves real-time monitoring and early warning of accumulated displacement and deformation rate of a vault, an anti-cursor does not need to be arranged at a monitoring point, the displacement value of the rough surface of concrete is automatically calculated, abnormal data are accurately removed, real-time performance is achieved, early warning signals can be sent out in time, safety is greatly improved, and certain guiding significance is achieved for design and maintenance of regional tunnels.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention comprises the following steps:
an intelligent early warning method for high-temperature instability of a subway tunnel concrete lining comprises the following steps.
(1) The method comprises the steps that a deformation real-time detection system and a settlement real-time detection system are arranged at safe distances from an inlet and an outlet of a tunnel and at a cross section of a lining with cracks, the deformation real-time detection system judges whether to start early warning through comparison of a strain value of set time and a first early warning threshold value, the deformation real-time detection system comprises strain sensors, a data acquisition instrument, a GPRS module and a server, the strain sensors are distributed on the arc surface of the cross section of the lining at equal intervals, the settlement real-time detection system judges whether to start early warning according to comparison of settlement displacement and a second early warning threshold value, the settlement real-time detection system comprises a laser range finder, an automatic filtering device and a memory, and the laser range finder is arranged on the horizontal ground of the cross section of the lining.
The main control system comprises a database, a controller, a lower computer and an early warning module, and can realize the functions of making graphs and reports, analyzing data, automatically storing, early warning and the like, wherein the early warning module comprises an alarm lamp and a buzzer.
The strain sensor is a vibrating wire strain gauge, the measuring range is 1000 mu, the sensitivity is 1 mu, the temperature range is-10-60 ℃, the temperature sensor is arranged in the strain sensor and can directly measure the temperature of a measuring point for temperature correction of a strain value, the safety distance is 80 meters, 15 strain sensors are arranged on the arc surface of each transverse section, and the set time is 1 hour.
(2) The data acquisition instrument comprises a comprehensive acquisition module, a signal lightning protection module and a power supply lightning protection module which are integrated in an acquisition box body, wherein the strain value sigma of the strain sensor acquired by the data acquisition instrument is sent to a main control system, and the deformation acceleration is obtained according to continuous different time points t1, t2 and t3 and time intervals △ t = t3-t2= t2-t1
Taking the average value of the deformation acceleration of the quarter of the last year as a first early warning threshold value of the same quarter of the year
The set time is 1 hour.
The quarter is a year comprising four quarters, the first quarter being 1-3 months, the first quarter being 4-6 months, the first quarter being 7-9 months, the first quarter being 9-12 months.
The GPRS module is an internet of things wireless data terminal, a public operator network is used for providing a wireless long-distance data transmission function, a high-performance industrial 16/32-bit communication processor and an industrial wireless module are adopted, an embedded real-time operating system is used as a software supporting platform, RS232 and RS485 interfaces are provided at the same time, serial port equipment can be directly connected, a transparent data transmission function is realized, a C/S network architecture network system for transmitting data through a TCP/UDP network protocol can support networking communication modes such as point-to-point and point-to-multipoint, and an extended short message function and application systems issued by various information service platforms are supported, and a server receives data sent by the GPRS module through a mobile communication network and stores the data in a database.
(3) The laser range finder data acquisition device sends the memory after filtering through the automatic filter device, and the main control system data of gathering the memory are analyzed, and the laser range finder places in the same position on the horizontal ground of cross section, carries out the range finding of different time points, and laser projection forms the facula at the deformation surface monitoring point, and the laser straight line distance to the facula is measured to the laser range finder, and the distance that initial time point n1 measured is
The distance measured at the time point n2 is
Then, according to the included angle α between the laser and the horizontal direction, the settlement displacement is obtained as
Taking the average value of the settlement displacement of the last year as a second early warning threshold value of the current year
；
Because the tunnel vault has the settlement displacement of H, the laser spot on the deformation surface moves from the position A to the position B, the distance of the laser is reduced by △ L, obviously △ L = L1-L2, when the surface roughness of the concrete sprayed at the initial stage of the vault is within an acceptable range, the laser spot can be in an oval shape, the laser ranging is the distance from the centroid of the spot to equipment, namely, the distance from the rugged rough deformation surface within the oval spot range to the equipment is averaged, when the deformation surface of the monitoring point of the vault is larger than the deformation surface
Will cause a vertical displacement of
Laser distance △
The change of △ L data change sensitivity is larger than the change of direct settlement displacement H, which is very beneficial to the monitoring of real-time alarm, obviously, the value of △ L is much more convenient than the value of H, no instrument is required to be installed at the section position, and the interference to the construction can be avoided.
(4) When in use
When or when
And starting early warning.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by the present specification, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. The intelligent early warning method for high-temperature instability of the subway tunnel concrete lining is characterized by comprising the following steps of:
(1) the method comprises the steps that a deformation real-time detection system and a settlement real-time detection system are arranged at safe distances from an inlet and an outlet of a tunnel and at a cross section of a lining with cracks, the deformation real-time detection system compares a strain value with a first early warning threshold value through set time to start early warning, the deformation real-time detection system comprises strain sensors, a data acquisition instrument, a GPRS module and a server, the strain sensors are distributed on an arc surface of the cross section of the lining at equal intervals, the settlement real-time detection system compares settlement displacement with a second early warning threshold value to start early warning, the settlement real-time detection system comprises a laser range finder, an automatic filtering device and a memory, and the laser range finder is arranged on the horizontal ground of the cross section of the lining;
(2) the data acquisition instrument comprises a comprehensive acquisition module, a signal lightning protection module and a power supply lightning protection module which are integrated in an acquisition box body, wherein the strain value sigma of the strain sensor acquired by the data acquisition instrument is sent to a main control system, and the deformation acceleration is obtained according to continuous different time points t1, t2 and t3 and time intervals △ t = t3-t2= t2-t1
Taking the average value of the deformation acceleration of the quarter of the last year as a first early warning threshold value of the same quarter of the year
；
(3) The laser range finder collects data, the data are filtered by the automatic filtering device and then sent to the memory, the main control system collects the data of the memory for analysis, the laser range finder is placed at the same position of the horizontal ground of the cross section for ranging at different time points, and the laser projector is used for projecting laserThe laser range finder measures the laser linear distance to the light spot, and the distance measured at the initial time point n1 is
The distance measured at the time point n2 is
Then, according to the included angle α between the laser and the horizontal direction, the settlement displacement is obtained as
Taking the average value of the settlement displacement of the last year as a second early warning threshold value of the current year
；
(4) When in use
When or when
And starting early warning.
2. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said safe distance is 80 meters.
3. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein the set time is 1 hour.
4. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said quarter is a year including four quarters, the first quarter is 1-3 months, the first quarter is 4-6 months, the first quarter is 7-9 months, the first quarter is 9-12 months.
5. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said server transmits the strain value data collected by the data collector to the controller through a TCP/UDP network protocol.
6. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said strain sensor is a vibrating wire strain gauge.
7. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said GPRS module comprises RS232 and RS485 interfaces.
8. The intelligent early warning method for the high-temperature instability of the subway tunnel concrete lining as claimed in claim 1, wherein the main control system comprises a database, a controller, a lower computer and an early warning module.
9. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 8, wherein said early warning module comprises an alarm lamp and a buzzer.
10. The intelligent early warning method for high-temperature instability of a subway tunnel concrete lining as claimed in claim 1, wherein said main control system analyzes and stores the data of the memory.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010472129.8A CN111622806A (en) | 2020-05-29 | 2020-05-29 | Intelligent early warning method for high-temperature instability of subway tunnel concrete lining |
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| CN202010472129.8A CN111622806A (en) | 2020-05-29 | 2020-05-29 | Intelligent early warning method for high-temperature instability of subway tunnel concrete lining |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112576311A (en) * | 2020-12-14 | 2021-03-30 | 中交文山高速公路建设发展有限公司 | Tunnel real-time monitoring and grading early warning method and system thereof |
| CN113281742A (en) * | 2021-06-02 | 2021-08-20 | 西南交通大学 | SAR landslide early warning method based on landslide deformation information and meteorological data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203385385U (en) * | 2013-08-26 | 2014-01-08 | 山东高速股份有限公司 | Tunnel lining surface deformation monitoring system |
| CN109458984A (en) * | 2018-12-12 | 2019-03-12 | 中交第二航务工程局有限公司 | Tunnel deformation real-time monitoring device and method |
| CN110243335A (en) * | 2019-07-16 | 2019-09-17 | 贵州省交通规划勘察设计研究院股份有限公司 | A kind of constructing tunnel wall rock loosening ring deformation auto-monitoring prior-warning device and method |
-
2020
- 2020-05-29 CN CN202010472129.8A patent/CN111622806A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203385385U (en) * | 2013-08-26 | 2014-01-08 | 山东高速股份有限公司 | Tunnel lining surface deformation monitoring system |
| CN109458984A (en) * | 2018-12-12 | 2019-03-12 | 中交第二航务工程局有限公司 | Tunnel deformation real-time monitoring device and method |
| CN110243335A (en) * | 2019-07-16 | 2019-09-17 | 贵州省交通规划勘察设计研究院股份有限公司 | A kind of constructing tunnel wall rock loosening ring deformation auto-monitoring prior-warning device and method |
Non-Patent Citations (1)
| Title |
|---|
| 徐俊国: "运营隧道衬砌变形实时监测预警系统及季节性变形规律研究", 《公路交通科技》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112576311A (en) * | 2020-12-14 | 2021-03-30 | 中交文山高速公路建设发展有限公司 | Tunnel real-time monitoring and grading early warning method and system thereof |
| CN113281742A (en) * | 2021-06-02 | 2021-08-20 | 西南交通大学 | SAR landslide early warning method based on landslide deformation information and meteorological data |
| CN113281742B (en) * | 2021-06-02 | 2023-07-25 | 西南交通大学 | SAR landslide early warning method based on landslide deformation information and meteorological data |
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