CN113689685B - Highway tunnel deformation condition monitoring and early warning system and method - Google Patents
Highway tunnel deformation condition monitoring and early warning system and method Download PDFInfo
- Publication number
- CN113689685B CN113689685B CN202110804483.0A CN202110804483A CN113689685B CN 113689685 B CN113689685 B CN 113689685B CN 202110804483 A CN202110804483 A CN 202110804483A CN 113689685 B CN113689685 B CN 113689685B
- Authority
- CN
- China
- Prior art keywords
- crack
- lining
- tunnel
- section
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 114
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000004062 sedimentation Methods 0.000 claims abstract description 35
- 238000010191 image analysis Methods 0.000 claims abstract description 14
- 238000011835 investigation Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 3
- 230000009471 action Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Images
Classifications
-
- 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
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Business, Economics & Management (AREA)
- Computing Systems (AREA)
- Emergency Management (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses a monitoring and early warning system and a method for deformation condition of a highway tunnel, wherein the monitoring and early warning system comprises a lining dividing module, an image acquisition module, an image analysis module, a monitoring point setting module and a deformation judgment module, the lining dividing module is used for dividing a lining of the tunnel into m sections of lining with equal width along the axial direction of the tunnel in advance, m is a natural number, the image acquisition module is used for acquiring a surface image of each section of lining as a first image, the image analysis module is used for analyzing the first image and selecting the lining as a monitoring section, the monitoring point setting module is used for setting sedimentation monitoring points on the monitoring section, the sedimentation monitoring points are set on the monitoring section, sedimentation values of the sedimentation monitoring points are acquired at intervals of preset time periods, the deformation judgment module is used for judging the relation between the sedimentation values and sedimentation threshold values, and when the settlement value is greater than or equal to the settlement threshold value, transmitting information to overhaul the monitoring section.
Description
Technical Field
The invention relates to the technical field of tunnels, in particular to a highway tunnel deformation condition monitoring and early warning system and a highway tunnel deformation condition monitoring and early warning method.
Background
The road tunnel is a passage specially used for automobile transportation. With the development of social economy and production, a great number of expressways appear, higher standards are provided for road construction technology, and the requirements for straight lines, gentle slopes, spacious road surfaces and the like are met. Therefore, when a road passes through a mountain area, the scheme of winding around the mountain is changed into a tunnel scheme in the past. The construction of the tunnel plays an important role in the aspects of improving the technical state of the road, shortening the running distance, improving the transport capacity, reducing accidents and the like.
The deformation condition of the highway tunnel can occur due to factors such as temperature, humidity and tunnel structure, the operation condition of the highway tunnel can be influenced if the tunnel is not deformed in time to be overhauled, and safety accidents can occur due to the arrangement of the device.
Disclosure of Invention
The invention aims to provide a highway tunnel deformation condition monitoring and early warning system and a highway tunnel deformation condition monitoring and early warning method, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a highway tunnel deformation condition monitoring and early warning system comprises a lining dividing module, an image acquisition module, an image analysis module, a monitoring point setting module and a deformation judgment module, wherein the lining dividing module is used for dividing a lining of a tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, m is a natural number, the image acquisition module is used for acquiring surface images of the sections of lining as first images, the image analysis module is used for analyzing the first images and selecting the sections of lining as monitoring sections, the monitoring point setting module is used for setting sedimentation monitoring points on the monitoring sections, sedimentation monitoring points are arranged on the monitoring sections, sedimentation values of the sedimentation monitoring points are acquired at intervals of preset time periods, the deformation judgment module is used for judging the relation between the sedimentation values and the sedimentation threshold values, and when the sedimentation values are more than or equal to the sedimentation threshold values, and the monitoring section is overhauled by the transmission information.
Furthermore, the image analysis module comprises a crack information extraction module, a crack index calculation module, a crack index comparison module and a monitoring section selection module, wherein the crack information extraction module is used for extracting each piece of crack information from the first image corresponding to each section of lining, and the crack index calculation module is used for calculating the crack index of a certain section of lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the method comprises the steps that the width of the ith crack in the direction along the axis of a tunnel is determined, wherein the direction of the axis of the tunnel is vertical to the direction of the section of the tunnel, the crack index comparison module compares the crack index of a certain section of lining with a crack threshold value, when the crack index is larger than the crack threshold value, the monitoring section selection module is made to judge whether the crack indexes of the adjacent lining on the two sides of the section of lining are larger than the crack threshold value, and if the crack indexes are larger than the crack threshold value, the section of lining is selected as the monitoring section.
Furthermore, the image analysis module further comprises a crack type acquisition module and an oblique crack processing module, wherein the crack type acquisition module is used for acquiring the crack type of each crack, the crack type comprises a longitudinal crack, a circumferential crack and an oblique crack, the oblique crack processing module is used for projecting the crack in the tunnel axis direction to obtain the width of the crack in the tunnel axis direction when the crack type of a certain crack is the oblique crack, and projecting the crack in the tunnel section direction to obtain the length of the crack in the tunnel section direction.
Further, the monitoring and early warning system further comprises a longitudinal crack analysis module, the longitudinal crack analysis module comprises a supervision crack selection module, an observation lining selection module and a crack continuity acquisition and evaluation module, the supervision crack selection module is used for screening out longitudinal cracks from the cracks of each sublevel and acquiring the length of each longitudinal crack on each sublevel, when the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is selected as a supervision crack, the observation lining selection module is used for judging whether continuous sublevels exist in the lining of the tunnel are all first sublevels, when the continuous sublevels exist, the whole of the sublevels which are continuously first sublevels is set as a lining for observation, the continuous number of the first sublevels in the observation lining is set as b, wherein when the supervision crack exists on a certain sublevel, the lining is a first lining, and the crack continuity acquisition module is used for acquiring the distance between cracks on the connected lining in the observation lining and judging whether to overhaul the tunnel according to the distance.
A monitoring and early warning method for deformation conditions of a highway tunnel comprises the following steps:
dividing a lining of a tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, wherein m is a natural number, collecting a surface image of each section of lining as a first image, analyzing the first image, and selecting the lining as a monitoring section;
setting a settlement monitoring point on the monitoring section, acquiring a settlement value of the settlement monitoring point at preset time intervals, and if the settlement value is greater than or equal to a settlement threshold value, transmitting information to overhaul the monitoring section.
Further, the analyzing the first image includes:
extracting each piece of crack information from a first image corresponding to a certain section of lining,
calculating the crack index of a section of lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the width of the ith crack is along the axial direction of the tunnel, wherein the axial direction of the tunnel is perpendicular to the section direction of the tunnel.
If the crack index of a certain section of lining is larger than the crack threshold value, whether the crack indexes of the sub-linings adjacent to the two sides of the section of lining are both larger than the crack threshold value is judged, if so, the section of lining is taken as a monitoring section, or the sub-lining with the crack index larger than the crack threshold value is directly selected as the monitoring section, but the mode has more selected monitoring sections and more monitoring points.
Further, the calculating the fracture index of a certain section of lining further includes:
obtaining the fracture types of each fracture, wherein the fracture types comprise a longitudinal fracture, a circumferential fracture and an oblique fracture,
when the crack type of a certain crack is a longitudinal crack, the length of the crack along the section direction of the tunnel is 0, namely the length of the crack along the surface direction of the tunnel is 0;
when the crack type of a certain crack is a circumferential crack, the width of the crack in the direction along the axis of the tunnel is 0;
when the crack type of a certain crack is an oblique crack, the width of the crack in the direction along the axis of the tunnel is obtained by projecting the crack in the direction along the axis of the tunnel, the length of the crack in the direction along the section of the tunnel is obtained by projecting the crack in the direction along the section of the tunnel, namely the length of the crack in the direction along the surface of the tunnel is obtained by projecting the crack in the direction vertical to the direction along the axis of the tunnel on the surface of the tunnel.
Further, after the analyzing the first image, further analyzing the longitudinal fracture is further included, and the further analyzing the longitudinal fracture includes:
step S1: screening out longitudinal cracks from the cracks of each sub-lining, collecting the length of each longitudinal crack on each sub-lining, if the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is a supervision crack, and turning to the step S2;
step S2: judging whether continuous sub-linings exist in the tunnel lining, namely the first sub-lining, if so,
setting the whole of the sub-linings continuously serving as the first sub-lining as the observation lining, and setting the continuous number of the first sub-linings in the observation lining as b, wherein when a supervision crack is detected to exist on one sub-lining, the sub-lining is the first sub-lining, and turning to the step S3;
step S3: setting the initial value of i to be 1 and the initial value of Di to be 0, and turning to the step S4;
step S4: selecting a supervision crack in the ith sub-lining in the observation lining as an extension crack along the axial direction of the tunnel, setting the initial value of j as 1, and turning to the step S5;
step S5: setting the distance between the end point of a certain monitored crack on the j +1 th sublevel and the end point of an extended crack on the j first sublevel as an investigation distance,
if the corresponding investigation distance of a certain supervised crack on the j +1 th sub-lining is smaller than the correlation distance, selecting the corresponding supervised crack of the j +1 th sub-lining as an extension crack, adding 1 to the value of j, adding 1 to the value of Di, and turning to the step S5;
if the corresponding investigation distances of all the monitored cracks on the j +1 th sub-lining are larger than or equal to the correlation distance, adding 1 to the value of i, if the value of i is larger than or equal to b, turning to step S6, and if the value of i is smaller than b, turning to step S4;
step S6: and respectively acquiring Di corresponding to each observation lining, and if the value of Di existing in a certain observation lining is greater than or equal to the vigilance value, transmitting information to overhaul the tunnel.
Further, setting up settlement monitoring point on the monitoring section still includes:
and the settlement monitoring points are arranged at arch foot positions at two sides of the monitoring section.
Compared with the prior art, the invention has the following beneficial effects: according to the method and the device, the settlement condition of the tunnel is monitored by collecting and analyzing the condition of the cracks of the tunnel lining, selecting the corresponding monitoring position and judging whether the tunnel is deformed or not according to the settlement condition of the monitoring position, so that the monitoring position is not required to be arranged in each place, the monitoring cost is reduced, meanwhile, the related extension condition of the longitudinal cracks in the lining is also analyzed, and the safety of the highway tunnel is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic block diagram of a highway tunnel deformation condition monitoring and early warning system according to the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
Referring to fig. 1, the present invention provides a technical solution: a highway tunnel deformation condition monitoring and early warning system comprises a lining dividing module, an image acquisition module, an image analysis module, a monitoring point setting module and a deformation judgment module, wherein the lining dividing module is used for dividing a lining of a tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, m is a natural number, the image acquisition module is used for acquiring surface images of the sections of lining as first images, the image analysis module is used for analyzing the first images and selecting the sections of lining as monitoring sections, the monitoring point setting module is used for setting sedimentation monitoring points on the monitoring sections, sedimentation monitoring points are arranged on the monitoring sections, sedimentation values of the sedimentation monitoring points are acquired at intervals of preset time periods, the deformation judgment module is used for judging the relation between the sedimentation values and the sedimentation threshold values, and when the sedimentation values are more than or equal to the sedimentation threshold values, and the monitoring section is overhauled by the transmission information.
The image analysis module comprises a crack information extraction module, a crack index calculation module, a crack index comparison module and a monitoring section selection module, wherein the crack information extraction module is used for extracting crack information from a first image corresponding to each section of lining, and the crack index calculation module calculates the crack index of a certain section of lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the method comprises the steps that the width of the ith crack in the direction along the axis of a tunnel is determined, wherein the direction of the axis of the tunnel is vertical to the direction of the section of the tunnel, the crack index comparison module compares the crack index of a certain section of lining with a crack threshold value, when the crack index is larger than the crack threshold value, the monitoring section selection module is made to judge whether the crack indexes of the adjacent lining on the two sides of the section of lining are larger than the crack threshold value, and if the crack indexes are larger than the crack threshold value, the section of lining is selected as the monitoring section.
The image analysis module further comprises a crack type acquisition module and an oblique crack processing module, wherein the crack type acquisition module is used for acquiring the crack type of each crack, the crack type comprises a longitudinal crack, an annular crack and an oblique crack, the oblique crack processing module is used for projecting the crack in the direction of the axis of the tunnel to obtain the width of the crack in the direction along the axis of the tunnel when the crack type of a certain crack is the oblique crack, and projecting the crack in the direction of the cross section of the tunnel to obtain the length of the crack in the direction along the cross section of the tunnel.
The monitoring and early warning system further comprises a longitudinal crack analysis module, the longitudinal crack analysis module comprises a supervision crack selection module, an observation lining selection module and a crack continuity acquisition and evaluation module, the supervision crack selection module is used for screening out longitudinal cracks from the cracks of each sublevel and acquiring the length of each longitudinal crack on each sublevel, when the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is selected as a supervision crack, the observation lining selection module is used for judging whether continuous sublevels exist in the lining of the tunnel are all first sublevels, and when the continuous sublevels exist, the whole of the sublevels which are continuously first sublevels is set as an observation lining, the continuous number of the first sublevels in the observation lining is set as b, wherein when the supervision crack exists on a certain sublevel, the sublevel is the first sublevel, the crack continuity acquisition module is used for acquiring and observing the distance between cracks on the connected sub-linings in the lining, and judging whether to overhaul the tunnel according to the distance.
A monitoring and early warning method for deformation conditions of a highway tunnel comprises the following steps:
dividing a lining of a tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, wherein m is a natural number, collecting a surface image of each section of lining as a first image, analyzing the first image, and selecting the lining as a monitoring section;
the analyzing the first image comprises:
extracting each piece of crack information from a first image corresponding to a certain section of lining,
calculating crack index of a section of sub-lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the width of the ith crack in the direction along the axis of the tunnel, wherein the direction of the axis of the tunnel is vertical to the direction of the section of the tunnel; in this embodiment, L is the arc length of the tunnel cross-section,
that is, the arc length of the ith crack along the surface of the tunnel section, the crack index of a section lined in this application is actually determined by
The fracture index of the application not only considers the length condition of the fracture, but also considers the number condition of the fracture, so that the selected monitoring position is more accurate.
If the crack index of a certain section of lining is larger than the crack threshold value, judging whether the crack indexes of the adjacent sub linings on two sides of the section of lining are both larger than the crack threshold value, and if so, taking the section of lining as a monitoring section. The position used for monitoring the sinking deformation of the tunnel in the tunnel is selected according to the condition of the cracks on the lining surface, so that the monitoring position is more targeted, and the monitoring efficiency is improved;
the calculating the fracture index of a certain section of lining further comprises the following steps:
obtaining the fracture types of each fracture, wherein the fracture types comprise a longitudinal fracture, a circumferential fracture and an oblique fracture,
when the crack type of a certain crack is a longitudinal crack, the length of the crack in the direction along the section of the tunnel is 0;
when the crack type of a certain crack is a circumferential crack, the width of the crack in the direction along the axis of the tunnel is 0;
when the crack type of a certain crack is an oblique crack, the width of the crack in the direction along the axis of the tunnel is obtained by projecting the crack in the direction along the axis of the tunnel, and the length of the crack in the direction along the section of the tunnel is obtained by projecting the crack in the direction along the section of the tunnel.
The analyzing the first image further comprises analyzing the longitudinal fracture, wherein the analyzing the longitudinal fracture further comprises:
step S1: screening out longitudinal cracks from the cracks of each sub-lining, collecting the length of each longitudinal crack on each sub-lining, if the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is a supervision crack, and turning to the step S2; the harmfulness of the longitudinal cracks on the tunnel is drunken relative to the harmfulness of the circumferential cracks and the oblique cracks, so that the tunnel is easy to fall off, the side walls are broken and even the tunnel collapses, further detection is carried out on the longitudinal cracks, early warning is carried out in advance through detection of the distance between the longitudinal cracks on each lining, and tunnel accidents are prevented;
step S2: judging whether continuous sub-linings in the tunnel are the first sub-lining or not, if so,
setting the whole of the sub-linings continuously serving as the first sub-lining as an observation lining, and setting the continuous number of the first sub-linings in the observation lining as b, wherein when a supervision crack is detected to exist on a certain sub-lining, the sub-lining is the first sub-lining, and turning to the step S3;
step S3: setting the initial value of i to be 1 and the initial value of Di to be 0, and turning to the step S4;
step S4: selecting the supervised crack in the ith sub-lining in the observation lining as an extended crack along the axial direction of the tunnel, setting the initial value of j as 1, and turning to the step S5;
step S5: setting the distance between the end point of a certain monitored crack on the j +1 th sublevel and the end point of an extended crack on the j first sublevel as an investigation distance,
if the corresponding investigation distance of a certain supervised crack on the j +1 th sub-lining is smaller than the correlation distance, selecting the corresponding supervised crack of the j +1 th sub-lining as an extension crack, adding 1 to the value of j, adding 1 to the value of Di, and turning to the step S5;
if the corresponding investigation distances of all the monitored cracks on the j +1 th sublevel are larger than or equal to the correlation distance, adding 1 to the value of i, if the value of i is larger than or equal to b, turning to step S6, and if the value of i is smaller than b, turning to step S4;
step S6: and respectively acquiring Di corresponding to each observation lining, and if the value of Di existing in a certain observation lining is greater than or equal to the vigilance value, transmitting information to overhaul the tunnel.
For example: the continuous number of the first branch lining in a certain observation lining is 3, the number of the supervision cracks of the 1 st branch lining is 2, the number of the supervision cracks of the 2 nd branch lining is 1, the number of the supervision cracks of the 3 rd branch lining is 1, then from the 1 st branch lining, D1=0, 2 supervision cracks on the 1 st branch lining are extension cracks, the distance between the end point of the 2 extension cracks and the end point of the supervision crack on the 2 nd branch lining is respectively judged as an investigation distance,
if the distances between the end points of 2 extended fractures in the end points of 2 extended fractures on the 1 st subline and the end point of the supervised fracture on the 2 nd subline are both greater than or equal to the correlation distance, D1=0, D1 ends, then starting from the 2 nd subline, D2=0, the supervised fracture on the 2 nd subline is an extended fracture, and whether the distance between the end point of the extended fracture and the end point of the supervised fracture on the 3 rd subline is the investigation distance less than the correlation distance is judged, if less than the correlation distance, D2=1, D2 ends, if greater than or equal to the correlation distance, D2=0, D2 ends;
if the distance between the end point of one extension crack in the end points of the 2 extension cracks on the 1 st segmental lining and the end point of the supervised crack on the 2 nd segmental lining is less than the correlation distance, then the supervised crack on the 2 nd segmental lining is an extension crack, D1=1, continuously judging whether the distance between the end point of the extension crack on the 2 nd segmental lining and the end point of the supervised crack on the 3 rd segmental lining is less than the correlation distance, if so, D1=2, D1 is ended, the same contents are followed after the end of D1 in the above, and then the 2 nd segmental lining is started.
Setting settlement monitoring points on the monitoring section, wherein the settlement monitoring points are arranged at arch foot positions on two sides of the monitoring section, acquiring settlement values of the settlement monitoring points at intervals of a preset time period, and if the settlement values are more than or equal to a settlement threshold value, transmitting information to overhaul the monitoring section. When the settlement monitoring is carried out on the settlement monitoring points, the settlement monitoring can be carried out through a precision level gauge. If the sinking settlement value of one side of the arch leg positions at the two sides is larger than or equal to the settlement threshold value, the tunnel deformation condition is judged to be relatively heavy, and the tunnel is subjected to careful inspection and repair by transmitting information.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A monitoring and early warning system for deformation of a highway tunnel is characterized by comprising a lining dividing module, an image acquisition module, an image analysis module, a monitoring point setting module and a deformation judgment module, wherein the lining dividing module is used for dividing a lining of the tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, m is a natural number, the image acquisition module is used for acquiring a surface image of each section of lining as a first image, the image analysis module is used for analyzing the first image and selecting the lining as a monitoring section, the monitoring point setting module is used for setting sedimentation monitoring points on the monitoring section, sedimentation monitoring points are arranged on the monitoring section, sedimentation values of the sedimentation monitoring points are acquired at intervals of preset time periods, the deformation judgment module is used for judging the relation between the sedimentation values and the sedimentation threshold values, and when the sedimentation values are more than or equal to the sedimentation threshold values, the monitoring section is overhauled by transmitting information;
the image analysis module comprises a crack information extraction module, a crack index calculation module, a crack index comparison module and a monitoring section selection module, wherein the crack information extraction module is used for extracting crack information from a first image corresponding to each section of lining, and the crack index calculation module calculates the crack index of a certain section of lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the method comprises the steps that the width of the ith crack in the direction along the axis of a tunnel is determined, wherein the direction of the axis of the tunnel is vertical to the direction of the section of the tunnel, the crack index comparison module compares the crack index of a certain section of lining with a crack threshold value, when the crack index is larger than the crack threshold value, the monitoring section selection module is made to judge whether the crack indexes of the adjacent lining on the two sides of the section of lining are larger than the crack threshold value, and if the crack indexes are larger than the crack threshold value, the section of lining is selected as the monitoring section.
2. The highway tunnel deformation condition monitoring and early warning system according to claim 1, wherein: the image analysis module further comprises a crack type acquisition module and an oblique crack processing module, wherein the crack type acquisition module is used for acquiring the crack type of each crack, the crack type comprises a longitudinal crack, an annular crack and an oblique crack, the oblique crack processing module is used for projecting the crack in the direction of the axis of the tunnel to obtain the width of the crack in the direction along the axis of the tunnel when the crack type of a certain crack is the oblique crack, and projecting the crack in the direction of the cross section of the tunnel to obtain the length of the crack in the direction along the cross section of the tunnel.
3. The highway tunnel deformation condition monitoring and early warning system according to claim 2, wherein: the monitoring and early warning system further comprises a longitudinal crack analysis module, the longitudinal crack analysis module comprises a supervision crack selection module, an observation lining selection module and a crack continuity acquisition and evaluation module, the supervision crack selection module is used for screening out longitudinal cracks from the cracks of each sublevel and acquiring the length of each longitudinal crack on each sublevel, when the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is selected as a supervision crack, the observation lining selection module is used for judging whether continuous sublevels exist in the lining of the tunnel are all first sublevels, and when the continuous sublevels exist, the whole of the sublevels which are continuously first sublevels is set as an observation lining, the continuous number of the first sublevels in the observation lining is set as b, wherein when the supervision crack exists on a certain sublevel, the sublevel is the first sublevel, the crack continuity acquisition module is used for acquiring and observing the distance between cracks on the connected sub-linings in the lining, and judging whether to overhaul the tunnel according to the distance.
4. A highway tunnel deformation condition monitoring and early warning method is characterized by comprising the following steps: the monitoring and early warning method comprises the following steps:
dividing a lining of a tunnel into m sections of lining with equal width in advance along the axis direction of the tunnel, wherein m is a natural number, collecting a surface image of each section of lining as a first image, analyzing the first image, and selecting the lining as a monitoring section;
setting sedimentation monitoring points on the monitoring section, acquiring sedimentation values of the sedimentation monitoring points at intervals of a preset time period, and transmitting information to overhaul the monitoring section if the sedimentation values are greater than or equal to a sedimentation threshold value;
the analyzing the first image comprises:
extracting each piece of crack information from a first image corresponding to a certain section of lining,
calculating crack index of a section of sub-lining
Wherein N is the number of the sub-lined cracks of the section, N is the sum of the number of all the sub-lined cracks, L is the length of the sub-lining along the section direction of the tunnel, K is the width of the sub-lining along the axial direction of the tunnel,
the length of the ith slit in the direction along the section of the tunnel,
the width of the ith crack in the direction along the axis of the tunnel, wherein the direction of the axis of the tunnel is vertical to the direction of the section of the tunnel;
if the crack index of a certain section of lining is larger than the crack threshold value, judging whether the crack indexes of the adjacent lining on two sides of the section of lining are both larger than the crack threshold value, and if so, taking the section of lining as a monitoring section.
5. The highway tunnel deformation condition monitoring and early warning method according to claim 4, wherein the highway tunnel deformation condition monitoring and early warning method comprises the following steps: the calculating the crack index of a certain section of lining further comprises the following steps:
obtaining the fracture types of each fracture, wherein the fracture types comprise a longitudinal fracture, a circumferential fracture and an oblique fracture,
when the crack type of a certain crack is a longitudinal crack, the length of the crack in the direction along the section of the tunnel is 0;
when the crack type of a certain crack is a circumferential crack, the width of the crack in the direction along the axis of the tunnel is 0;
when the crack type of a certain crack is an oblique crack, the width of the crack in the direction along the axis of the tunnel is obtained by projecting the crack in the direction along the axis of the tunnel, and the length of the crack in the direction along the section of the tunnel is obtained by projecting the crack in the direction along the section of the tunnel.
6. The highway tunnel deformation condition monitoring and early warning method according to claim 5, wherein the highway tunnel deformation condition monitoring and early warning method comprises the following steps: the analyzing the first image further comprises analyzing the longitudinal fracture, wherein the analyzing the longitudinal fracture further comprises:
step S1: screening out longitudinal cracks from the cracks of each sub-lining, collecting the length of each longitudinal crack on each sub-lining, if the length of a certain longitudinal crack is greater than or equal to a length threshold value, the longitudinal crack is a supervision crack, and turning to the step S2;
step S2: judging whether continuous sub-linings in the tunnel are the first sub-lining or not, if so,
setting the whole of the sub-linings continuously serving as the first sub-lining as an observation lining, and setting the continuous number of the first sub-linings in the observation lining as b, wherein when a supervision crack is detected to exist on a certain sub-lining, the sub-lining is the first sub-lining, and turning to the step S3;
step S3: setting the initial value of i to be 1 and the initial value of Di to be 0, and turning to the step S4;
step S4: selecting a supervision crack in the ith sub-lining in the observation lining as an extension crack along the axial direction of the tunnel, setting the initial value of j as 1, and turning to the step S5;
step S5: setting the distance between the end point of a certain monitored crack on the j +1 th subline and the end point of the extension crack on the j first subline as an investigation distance,
if the corresponding investigation distance of a certain supervised crack on the j +1 th sub-lining is smaller than the correlation distance, selecting the corresponding supervised crack of the j +1 th sub-lining as an extension crack, adding 1 to the value of j, adding 1 to the value of Di, and turning to the step S5;
if the corresponding investigation distances of all the monitored cracks on the j +1 th sublevel are larger than or equal to the correlation distance, adding 1 to the value of i, if the value of i is larger than or equal to b, turning to step S6, and if the value of i is smaller than b, turning to step S4;
step S6: and respectively acquiring Di corresponding to each observation lining, and if the value of Di existing in a certain observation lining is greater than or equal to the vigilance value, transmitting information to overhaul the tunnel.
7. The highway tunnel deformation condition monitoring and early warning method according to claim 6, wherein the highway tunnel deformation condition monitoring and early warning method comprises the following steps: set up the settlement monitoring point on monitoring section still includes:
and the settlement monitoring points are arranged at arch foot positions at two sides of the monitoring section.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110804483.0A CN113689685B (en) | 2021-07-16 | 2021-07-16 | Highway tunnel deformation condition monitoring and early warning system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110804483.0A CN113689685B (en) | 2021-07-16 | 2021-07-16 | Highway tunnel deformation condition monitoring and early warning system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113689685A CN113689685A (en) | 2021-11-23 |
| CN113689685B true CN113689685B (en) | 2022-09-27 |
Family
ID=78577351
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110804483.0A Active CN113689685B (en) | 2021-07-16 | 2021-07-16 | Highway tunnel deformation condition monitoring and early warning system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113689685B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114279394B (en) * | 2021-12-24 | 2024-04-02 | 广西北投交通养护科技集团有限公司 | Real-time online continuous monitoring method for tunnel deformation |
| CN115574776B (en) * | 2022-11-21 | 2023-04-28 | 山东省滨州公路工程有限公司 | Sedimentation control monitoring method and system in roadbed construction |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001032679A (en) * | 1999-07-16 | 2001-02-06 | Ohbayashi Corp | Facing front crack distribution predicting method |
| CN101435208A (en) * | 2008-10-16 | 2009-05-20 | 西安理工大学 | Device and method for monitoring uneven settlement of earth slit formation tunnel |
| CN107154040A (en) * | 2017-05-08 | 2017-09-12 | 重庆邮电大学 | A kind of tunnel-liner surface image crack detection method |
| CN111524323A (en) * | 2020-04-29 | 2020-08-11 | 中国水利水电科学研究院 | Slope fission early warning method and system |
| WO2021003690A1 (en) * | 2019-07-10 | 2021-01-14 | 中国科学院地质与地球物理研究所 | Tailings pond dam burst disaster simulation system and method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA3023641C (en) * | 2016-01-15 | 2020-12-22 | Wuhan Wuda Zoyon Science And Technology Co., Ltd | Object surface deformation feature extraction method based on line scanning three-dimensional point cloud |
-
2021
- 2021-07-16 CN CN202110804483.0A patent/CN113689685B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001032679A (en) * | 1999-07-16 | 2001-02-06 | Ohbayashi Corp | Facing front crack distribution predicting method |
| CN101435208A (en) * | 2008-10-16 | 2009-05-20 | 西安理工大学 | Device and method for monitoring uneven settlement of earth slit formation tunnel |
| CN107154040A (en) * | 2017-05-08 | 2017-09-12 | 重庆邮电大学 | A kind of tunnel-liner surface image crack detection method |
| WO2021003690A1 (en) * | 2019-07-10 | 2021-01-14 | 中国科学院地质与地球物理研究所 | Tailings pond dam burst disaster simulation system and method |
| CN111524323A (en) * | 2020-04-29 | 2020-08-11 | 中国水利水电科学研究院 | Slope fission early warning method and system |
Non-Patent Citations (1)
| Title |
|---|
| 隧道渗漏水的原因及预防措施;游延敏等;《山西建筑》;20101120;第36卷(第33期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113689685A (en) | 2021-11-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113689685B (en) | Highway tunnel deformation condition monitoring and early warning system and method | |
| CN108664715B (en) | Three-dimensional evaluation and driving safety analysis method for accumulated water ruts on road surface | |
| CN106441530B (en) | A kind of bridge dynamic weighing method and dynamic weighing system based on long gauge length optical fibre grating sensing technique | |
| CN103886594B (en) | Road surface line laser rut detection and recognition methods and disposal system | |
| CN107091085B (en) | Multi-parameter discrimination method for stratum stability of shallow-buried and underground-excavated tunnel | |
| CN108229803B (en) | Feature road section extraction method and dangerous road section judgment method and system | |
| CN114623776B (en) | Tunnel deformation monitoring-based tunnel damage prediction method | |
| CN117115135B (en) | Concrete crack detection system and method based on machine vision | |
| CN113158469B (en) | Asphalt pavement detection time prediction method based on longitudinal cracks | |
| CN113804242A (en) | Pavement monitoring system, and method and device for determining sensor arrangement position | |
| CN108921319B (en) | Monitoring method for safety early warning of karst tunnel structure | |
| CN110455210A (en) | A kind of high-speed rail tunnel-type position sensing method based on imbedded fiber | |
| WO2017055838A1 (en) | Method and system for predicting railway track quality | |
| Peng et al. | Long-term condition monitoring of cables for in-service cable-stayed bridges using matched vehicle-induced cable tension ratios | |
| CN111189424B (en) | Road data bending degree detection method based on multistage search radius | |
| CN117057600A (en) | Online monitoring and analyzing method for concrete bridge structural cracks | |
| CN115326266A (en) | Multi-source heterogeneous landslide early warning model based on Newton force monitoring | |
| Masoudi et al. | An investigation of rail failure due to wear using statistical pattern recognition techniques | |
| CN106157182B (en) | Method for judging quality defect degree of inverted arch of highway tunnel | |
| CN115062697B (en) | Track irregularity recognition method, system, computer device and readable storage medium | |
| CN102323269B (en) | Method for establishing pavement crack identifying and decision-making model on basis of hypothesis testing | |
| CN116242774A (en) | Light three-dimensional detection method and device suitable for rural highways | |
| CN115793086B (en) | Optical cable laying environment underground cavity judging method and system based on optical fiber sensing | |
| CN114353866B (en) | Multi-element comprehensive quantitative detection method for health state of pipe gallery structure | |
| CN105293001B (en) | Belt longitudinal tear detection method based on image line structure matching |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240425 Address after: Room 301, Unit 1, Building 5, No. 195 Xigong South Second Lane, Heping North Road, Wanbailin District, Taiyuan City, Shanxi Province, 030000 Patentee after: Shanxi Dasheng Andi Survey Technology Co.,Ltd. Country or region after: China Address before: 045000 Shanxi Institute of engineering and technology, No.1 Xueyuan Road, Yangquan economic and Technological Development Zone, Shanxi Province Patentee before: SHANXI INSTITUTE OF TECHNOLOGY Country or region before: China |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240711 Address after: 045000, 4th Floor, Block C, Yungu Science and Technology Innovation Park, Shanxi Zhichuangcheng No.7, Dalian Street, High tech Industrial Development Zone, Yangquan City, Shanxi Province Patentee after: Shanxi Zhongkuang Zhilian Technology Co.,Ltd. Country or region after: China Address before: Room 301, Unit 1, Building 5, No. 195 Xigong South Second Lane, Heping North Road, Wanbailin District, Taiyuan City, Shanxi Province, 030000 Patentee before: Shanxi Dasheng Andi Survey Technology Co.,Ltd. Country or region before: China |
|
| TR01 | Transfer of patent right |