CN110188126B - Method for dynamically determining tunnel safety monitoring and early warning value by utilizing big data - Google Patents
Method for dynamically determining tunnel safety monitoring and early warning value by utilizing big data Download PDFInfo
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- CN110188126B CN110188126B CN201910422018.3A CN201910422018A CN110188126B CN 110188126 B CN110188126 B CN 110188126B CN 201910422018 A CN201910422018 A CN 201910422018A CN 110188126 B CN110188126 B CN 110188126B
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- E—FIXED CONSTRUCTIONS
- E21—EARTH 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention discloses a method for dynamically determining a tunnel safety monitoring early warning value by utilizing big data, which is used for collecting related information of a current construction tunnel; comparing the related information of the current construction tunnel with a database; the deformation of the tunnel detection of the plurality of samples is represented as an abscissa, and the number of monitoring sections, of which the deformation is within 0.5mm of x, of the plurality of samples is represented as an ordinate, and the y is taken as the y; obtaining a distribution form map; calculating delta 1, taking delta 1 as an alarm value, and taking care of safety when deformation reaches the alarm value, wherein the shutdown is not needed; given the risk probability P1, calculating delta 2, taking delta 2 as an alarm value, and automatically sending out a safety alarm when the deformation reaches delta 2, so that the tunnel is stopped. The method and the system can dynamically determine the tunnel construction safety monitoring early warning value and the alarm value according to similar data in the database, avoid delay of construction period and guarantee the tunnel construction safety.
Description
Technical Field
The invention belongs to the technical field of tunnel security, and particularly relates to a method for dynamically determining a tunnel security monitoring and early warning value by utilizing big data.
Background
The mountain tunnel construction by the explosion method is work with very high safety risk, and collapse accidents are very easy to occur. If the tunnel collapses, the economic loss is caused, the construction period is delayed, and the casualties are caused by heavy weight.
In order to prevent tunnel collapse and reduce various losses caused by tunnel collapse, tunnel construction safety monitoring is an important measure for ensuring tunnel construction safety, and is widely (100%) adopted in tunnel construction.
The tunnel construction safety monitoring means that deformation (mainly vault sinking and peripheral convergence) of a tunnel structure is monitored by using instrument equipment (such as a level gauge), and when the deformation (or the deformation rate) of the tunnel structure exceeds a certain value, a safety alarm is sent out by a system.
How to reasonably determine the safety monitoring and early warning value of tunnel construction is a technical problem. At present, a design unit determines a specific numerical value according to specifications and engineering experience of a designer. The construction unit performs as such.
The safety of tunnel construction, influence factor is many, and a fixed monitoring early warning value is difficult to accurately judge the safe state of tunnel. In order to ensure construction safety, a preset early warning value is designed to be smaller. Therefore, the early warning is frequently triggered during tunnel construction, and two adverse effects are generated: (1) taking importance of units for early warning and forecasting, stopping the process when encountering early warning, inviting all parties of design, supervision and owners to diagnose the safety state of the tunnel together, and starting the process after judging the safety, so that the construction period is delayed (and the safety risk is brought to the stopping process of the tunnel engineering); (2) for units which are not emphasized in early warning and forecasting, after early warning frequently occurs and the actual engineering has no safety risk, relaxation can occur in the long term, and early warning is not paid attention any more. When the tunnel is in an unsafe state, the construction unit ignores the tunnel after the monitoring system gives out an early warning alarm, and the tunnel collapse accident is caused by the structure.
The early warning value given under individual conditions is bigger, the tunnel detection system does not early warn, and the collapse accident occurs in the tunnel, so that the tunnel is more dangerous.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides the method for dynamically determining the tunnel safety monitoring and early warning value by utilizing the big data, which can reasonably determine the tunnel construction safety monitoring and early warning value, avoid delaying the construction period and ensure the tunnel construction safety.
In order to solve the technical problems, the invention adopts the following technical scheme: a method for dynamically determining a tunnel safety monitoring early warning value by utilizing big data comprises the following steps:
(1) And collecting the related information of the current tunnel construction and storing the related information into a database. The information in the database comprises two major categories of similar information and monitoring information;
(2) Setting one or more screening conditions from the database 'similar information';
(3) Comparing the current tunnel construction related information obtained in the step (1) with a database according to the screening conditions set in the step (2) to obtain n samples with similar conditions;
(4) The deformation of tunnel detection of the n obtained samples represents the abscissa and is taken as x; the unit and the precision of x are integers of millimeter; the number of monitoring sections of which the deformation of the n samples is within 0.5mm of x is represented by an ordinate, and y is taken as y; obtaining a distribution morphology graph, wherein the morphology accords with a normal distribution rule, and the fitting curve function is as follows:
the two key parameter calculation formulas are as follows:
(5) Taking delta 1 = mu to represent the average deformation value of the tunnel section under the same similar condition; taking delta 1 as an early warning value; when the deformation reaches the early warning value, attention is paid to safety, but normal construction can be performed, and shutdown is not needed;
(6) Input risk probability P 1 ＝P i Where i ε (- ≡Δ2);
(7) According to
Obtaining delta 2; delta 2 is taken as an alarm value; when the deformation reaches delta 2, a safety alarm is automatically sent out, and the tunnel is required to stop construction for evaluation.
Preferably, samples approximating the monitored cross-section are screened out based on similar conditions in the database.
Preferably, in step (3), n samples are screened from the database, the coordinates of each sampleDenoted as x i ,y i The method comprises the steps of carrying out a first treatment on the surface of the Wherein x is a deformation value of the sample, and the precision is an integer of millimeter; y is the number of monitoring sections of the sample with deformation of about 0.5mm each.
Preferably, the early warning value Δ1 and the alarm value Δ2 of the tunnel construction safety monitoring can be calculated according to the sample obtained in the step (3) and the risk probability P1 in the step (6).
Preferably, Δ1 and Δ2 obtained according to step (5) and step (7) are dynamically variable as the samples in the database change.
Compared with the prior art, the invention has the following beneficial effects: the method reasonably determines the tunnel construction safety monitoring and early warning value, avoids delay of the construction period and ensures the tunnel construction safety.
Drawings
FIG. 1 is a diagram showing the relationship between the deformation amount and the number of sections according to the present invention;
FIG. 2 is a schematic diagram of the early warning values according to the present invention.
Detailed Description
The present invention will be described in detail below with reference to the drawings and the specific embodiments, so that those skilled in the art can better understand the technical solutions of the present invention.
The embodiment of the invention discloses a method for dynamically determining a tunnel safety monitoring early warning value by utilizing big data, taking a monitoring section of a to-be-repaired tunnel positive line DK558+300 mileage section of a Yukun railway Yunnan section as an example, comprising the following steps:
(1) Recording monitoring information (vault sinking and peripheral convergence) of the section of the tunnel to be repaired DK558+300 monitored on the same day as delta, and recording the delta into a database; see in particular table 1;
(2) "Yukun line", "Yunnan province", "basalt", "three steps", "IV-grade surrounding rock", "broad width 14.2m" are taken as similar conditions.
(3) Taking the risk probability P1=0.75 as an input condition input;
(4) Screening the database in the step (1) according to similar conditions, and selecting data with the same similar conditions as samples to obtain n samples with similar conditions;
(5) The deformation amount of tunnel detection of n samples represents an abscissa, x is taken as x, the unit of x is taken as mm, and the precision is taken as an integer of millimeter; the number of monitoring sections with the sample deformation in x (the range of 0.5mm on the left and right) represents the ordinate, and y is taken as y; obtaining a distribution morphology graph, predicting that the morphology accords with a normal distribution rule, and fitting a curve function as follows:
(6) Taking the expected value mu of the delta 1 = function, and representing the average deformation value of the tunnel section under the same similar condition; taking delta 1 as an early warning value;
(7) According to
Delta 2 was obtained. Delta 2 is taken as an early warning value;
(8) The system automatically compares the section deformation delta measured in the step (1) with delta 1 and delta 2; when delta is less than delta 1, the tunnel is considered to be safe, and normal construction can be performed; Δ1< Δ < Δ2 is still workable, but should be safe to pay attention to; when delta 2 is less than or equal to delta, the system automatically gives a safety alarm. The construction unit should stop immediately, withdraw constructors after taking necessary safe treatment to the tunnel face, and inform owners, proctories and designers to arrive as soon as possible, study whether to take reinforcing measures.
As shown, a vertical line is drawn with an abscissa Δ2, so as to illustrate the meaning of Δ2 in probability, namely: the line is left area/total area = P 1 . Meanwhile, the line is also significant in engineering, and can intuitively reflect the determined alarm probability P 1 Is a safety level of (2). The more right the line, the description P 1 The greater the degree of security, the lower the degree of security. P (P) 1 The value range suggests 0.65-0.85.
P 1 Has the engineering meaning of P 1 The probability (75% here) of the deformation of the sample being less than Δ2 also means that there is still 1-P 1 The deformation value of the sample of = (25%) is greater than Δ2, where the tunnel section is also safe, butHas been closer to the limits of the sample.
And a plurality of different combinations of similar conditions can be selected, and a plurality of different warning values can be calculated so as to comprehensively understand the safety range of tunnel deformation.
The following table is a summary table of database collection information in this application, table 1
The present invention has been described in detail by way of examples, but the description is merely exemplary of the invention and should not be construed as limiting the scope of the invention. The scope of the invention is defined by the claims. In the technical scheme of the invention, or under the inspired by the technical scheme of the invention, similar technical schemes are designed to achieve the technical effects, or equivalent changes and improvements to the application scope are still included in the protection scope of the patent coverage of the invention. It should be noted that for clarity of presentation, descriptions of parts and processes known to those skilled in the art that are not directly apparent to the scope of the present invention have been omitted from the description of the present invention.
Claims (4)
1. The method for dynamically determining the tunnel safety monitoring early warning value by utilizing the big data is characterized by comprising the following steps of:
(1) Collecting related information of a current construction tunnel and storing the related information into a database; the information in the database comprises two major categories of similar information and monitoring information;
(2) Setting one or more screening conditions from the database 'similar information';
(3) Comparing the current tunnel construction related information obtained in the step (1) with a database according to the screening conditions set in the step (2) to obtain n samples with similar conditions;
(4) The deformation of tunnel detection of the n obtained samples represents the abscissa and is taken as x; the unit and the precision of x are integers of millimeter; the number of monitoring sections of which the deformation of the n samples is within 0.5mm of x is represented by an ordinate, and y is taken as y; obtaining a distribution morphology graph, wherein the morphology accords with a normal distribution rule, and the fitting curve function is as follows:
the two key parameter calculation formulas are as follows:
(5) Taking delta 1 = mu to represent the average deformation value of the tunnel section under the same similar condition; taking delta 1 as an early warning value; when the deformation reaches the early warning value, the safety is paid attention to, but the construction is still normal, and the shutdown is not needed;
(6) Input risk probability P 1 ＝P i Where i ε (- ≡Δ2);
(7) According to
Obtaining delta 2; delta 2 is taken as an alarm value; when the deformation reaches delta 2, automatically sending out a safety alarm, and stopping construction of the tunnel to evaluate;
Δ1 and Δ2 obtained according to step (5) and step (7) are dynamically changed with the change of the sample in the database.
2. The method for dynamically determining tunnel safety monitoring and early warning values by utilizing big data according to claim 1, wherein samples similar to monitoring sections are screened out according to similar conditions in a database.
3. The method for dynamically determining tunnel security monitoring and early warning value by utilizing big data according to claim 1, wherein the method comprises the following steps ofIn step (3), n samples are screened from the database, the seat of each sample being denoted as x i ,y i The method comprises the steps of carrying out a first treatment on the surface of the Wherein x is a deformation value of the sample, and the precision is an integer of millimeter; y is the number of monitoring sections of the sample with deformation of about 0.5mm each.
4. The method for dynamically determining the early warning value of tunnel safety monitoring by utilizing big data according to claim 1, wherein the early warning value delta 1 and the alarm value delta 2 of tunnel construction safety monitoring are calculated according to the sample obtained in the step (3) and the risk probability P1 of the step (6).
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| CN111580098B (en) * | 2020-04-29 | 2021-07-06 | 深圳大学 | Bridge deformation monitoring method, terminal and storage medium |
| CN112307089B (en) * | 2020-11-03 | 2024-02-09 | 中铁隆工程集团有限公司 | Detection method and system applied to construction data |
| CN113958369B (en) * | 2021-11-10 | 2023-10-20 | 重庆科技学院 | Tunnel lining structure health monitoring method and system based on digital twinning |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102587986A (en) * | 2012-03-12 | 2012-07-18 | 西安建筑科技大学 | Tunnel construction informatization dynamic monitoring system and monitoring method thereof |
| CN105095679A (en) * | 2015-09-10 | 2015-11-25 | 北京安捷工程咨询有限公司 | Security risk early warning measurement and judgment method of foundation pit tunnel engineering |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102587986A (en) * | 2012-03-12 | 2012-07-18 | 西安建筑科技大学 | Tunnel construction informatization dynamic monitoring system and monitoring method thereof |
| CN105095679A (en) * | 2015-09-10 | 2015-11-25 | 北京安捷工程咨询有限公司 | Security risk early warning measurement and judgment method of foundation pit tunnel engineering |
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