CN104749187A - Tunnel lining disease detection device based on infrared temperature field and gray level image - Google Patents
Tunnel lining disease detection device based on infrared temperature field and gray level image Download PDFInfo
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Abstract
The invention relates to a tunnel lining disease detection device based on an infrared temperature field and a gray level image. The tunnel lining disease detection device comprises a vehicle-mounted mobile platform, illumination equipment, a photoelectric encoder, a GPS (Global Position System) receiver, an inertia unit, a synchronous controller, an area-array camera, an infrared thermal imager, an acquisition server, a display control device and a power supply system; tunnel lining two-dimensional image data, infrared temperature field data and fracture surface deformation data are combined with positioning data of the GPS, the inertia unit and the photoelectric encoder to establish a tunnel model with gray level information, temperature information and fracture surface deformation; and tunnel lining cracks are analyzed, and the length, width and lining leakage water information of the cracks are automatically detected. For the tunnel lining disease detection device, the advantages of infrared temperature field detection and two-dimensional gray level image crack detection are combined so that the detection result is relatively reliable, the speed is rapid and the working efficiency is greatly improved.
Description
Technical field
The invention belongs to the crossing domain of Surveying and mapping technique and apparatus science, be a kind ofly relate to infrared thermal imaging technique, image processing techniques, laser scanner technique, the tunnel-liner Defect inspection method of mobile precision positioning technology and multiple-sensor integration and synchronous control technique and device, mapping and the field of traffic such as vcehicular tunnel, railway tunnel detection can be widely used in.
Background technology
The disease such as tunnel-liner disease mainly comprises Lining Crack, lining cutting percolating water, lining cutting are come to nothing.Tunnel Lining Cracks evaluates one of most important parameter of tunnel-liner quality, is the Early manifestation form of most of disease, directly affects tunnel serviceable life and traffic safety.Conventional tunnel Lining Crack detection technique checks based on artificial vision, and efficiency is low, and working strength is large, detection speed is slow, and precision is lower, and the result of inspection has very strong subjectivity, and when carrying out manual detection on a highway, testing staff's personal safety receives impact.
Current detection means carries out observe and decide in the tunnel internal mode of taking pictures according to naked eyes or digital camera that scaffolds erecting, later stage is in order to detect the disease of tunnel internal, there is employing tunnel boring method, although this method is more directly perceived, but detection speed is slow, air pressure gun becomes the more difficult control of hole perpendicularity, and feeler lever is felt, tape measure measurement is affected by human factors larger, destroy tunnel waterproof and water drainage system simultaneously, affect the tunnel life-span, testing result is representative poor, is difficult to react tunnel entirety and each position quality comprehensively.
Its shortcoming of classic method mainly contains: a), be affected by human factors comparatively large, also exist that efficiency is low, poor accuracy, can not carry out the problems such as historical data contrast; Need scaffold erecting when b), detecting and there is the factor of life danger;
At present, producer is had to utilize high-rate laser profile scanning instrument to realize the Fracture System collection of tunnel-liner, but due to high-precision data acquisition will be reached, the travel speed of carrier loader platform is very limited, general at 5Km/h ~ 10Km/h, during the work of this checkout equipment, tunnel must carry out traffic control.
In addition, range sensor is combined with internal clocking by vehicle-mounted multiple-sensor integration synchronisation control means, controls the work of sensor for spatially interval sampling, and provides timestamp for the image data of sensor.Its shortcoming is: be not associated with the data of collection by the linear reference coordinate that vehicle travels, and this kind of application that is benchmark with linear reference coordinate usually for Tunnel testing, Road Detection, space orientation expression is very inconvenient.
Summary of the invention
Technical matters to be solved by this invention proposes a kind of tunnel-liner Defect inspection device, to overcome the technical bottleneck that existing Lining Crack quick and precisely identifies.
For solving the problems of the technologies described above, the present invention proposes a kind of tunnel-liner Defect inspection device utilizing image processing techniques, mobile precision positioning technology and multiple-sensor integration and synchronous control technique, this pick-up unit comprises vehicle-mounted mobile platform, light fixture, photoelectric encoder, GPS, inertance element, isochronous controller, area array cameras, infrared thermography, acquisition server, display control device and electric power system
Described vehicle-mounted mobile platform, for providing the carrying platform of movement for each described equipment;
Described photoelectric encoder, is arranged on the wheel center axle of vehicle-mounted mobile platform, in order to measure travelling speed and the distance of vehicle-mounted mobile platform;
Described GPS, installs on described vehicle-mounted mobile platform, for hi-Fix and the time service of described vehicle-mounted mobile platform;
Described inertance element, is arranged on described vehicle-mounted mobile platform, when not receiving gps signal for GPS described in tunnel, measures the position of described vehicle-mounted mobile platform, attitude data, realizes at the high-precision dead reckoning of tunnel internal;
Described isochronous controller, is arranged on described vehicle-mounted mobile platform, for synchronous, triggering area array cameras, infrared thermography, ensures that all data have unified time and space benchmark;
Described area array cameras, is arranged on described vehicle-mounted mobile platform, connects described isochronous controller, for gathering the two-dimensional image information of tunnel-liner;
Described light fixture, is arranged on described vehicle-mounted mobile platform, for providing lighting source for described area array cameras;
Described infrared thermography, is arranged on described vehicle-mounted mobile platform, connects described isochronous controller, for gathering the infrared temperature field of tunnel-liner;
Described acquisition server, for receiving the data of described GPS, inertance element, photoelectric encoder, isochronous controller, area array cameras, infrared thermography, carries out data Storage and Processing;
Described display control device, connects described acquisition server, and for the man-machine interaction of described acquisition server, comprise the optimum configurations gathering control inerface, data interface shows, the state of detection and the display of result;
Described electric power system, is arranged on described vehicle-mounted mobile platform, for system provides the various power supplys needed for each equipment.
The quantity of described area array cameras is multiple, and an area array cameras gathers the gray level image of a part of tunnel inner wall block, and the gray level image of multiple described block is spliced into the gray level image of a tunnel inner wall section.
The quantity of described infrared thermography is multiple, and an infrared thermography gathers the temperature pattern of a part of tunnel inner wall block, and the temperature pattern of multiple described block is spliced into the temperature pattern of a tunnel inner wall section.
Described based on infrared temperature field and gray level image tunnel-liner Defect inspection device, also comprise laser scanner, described laser scanner is arranged on described vehicle-mounted mobile platform, connect described isochronous controller, for the thermomechanical processing of scanning collection tunnel-liner section, described thermomechanical processing outputs to described acquisition server.
The data processing of described acquisition server comprises, by the tunnel-liner two-dimensional image data, infrared temperature field data and the section deformation data that receive, in conjunction with the locator data of GPS, inertance element and photoelectric encoder, set up the tunnel model of band half-tone information, temperature information and section deformation information; Adopt the two dimensional gray information processing technology to analyze Tunnel Lining Cracks, the length of automatic fracture detection, width and lining cutting percolating water information, and result is preserved, as the reference frame of Tunnel Repair and maintenance.
Based on the tunnel-liner Defect inspection device of infrared temperature field and gray level image, utilize infrared thermography, area array cameras, photoelectric encoder, the multiple-sensor integration such as GPS and inertance element and data fusion principle and method, in vehicular platform moves with the normal city running speed of 1-60 kilometer/hour, the infrared chart of tunnel internal is obtained by the infrared thermography be arranged on platform, the greyscale image data of tunnel-liner is obtained by area array cameras and high-power LED light fixture, range finding and the angle-data of tunnel cross-section is obtained by laser scanner, operating range and the travelling speed of vehicular platform is obtained by the photoelectric encoder be arranged on wheel, the position of platform is obtained by the GPS and inertance element that are arranged on platform, attitude data, fusion treatment is carried out in all sensing datas and synchronous data transmission to computing machine, comprehensive infrared temperature field and gray level image information extract the defect information of lining cutting.
Therefore, the present invention at least possesses following beneficial effect:
1) have employed high-precision space-time synchronous control program, set up high-precision space-time datum, improve the synchronization accuracy of each sensor, reduce the difficulty of data fusion, make testing result more reliable;
2) speed obtaining accurate infrared temperature field data and two dimensional gray data is fast, significantly improves operating efficiency;
3) carry out splicing to multiple 2-D gray image data to merge, achieve the identification and extraction to trickle Lining Crack;
4) combine infrared temperature field and detect the advantage with 2-D gray image Crack Detection, solve the technical bottleneck that single detection mode runs into, improve efficiency and the accuracy of tunnel-liner Defect inspection.
Accompanying drawing explanation
Below in conjunction with the drawings and specific embodiments, technical scheme of the present invention is further described in detail.
Fig. 1 is general technical structural representation.
Fig. 2 is greyscale image data acquisition principle figure.
Fig. 3 is temperature pattern data acquisition schematic diagram.
Fig. 4 is high precision timing positioning principle figure.
Fig. 5 is the coordinate acquisition position view of area array cameras in tunnel.
Fig. 6 is greyscale image data splicing schematic diagram.
Fig. 7 is the tunnel-liner Defect inspection schematic diagram based on gray level image and infrared temperature field information.
Embodiment
Based on the tunnel-liner Defect inspection device of infrared temperature field and gray level image, utilize infrared thermography, area array cameras, photoelectric encoder, the multiple-sensor integration such as GPS and inertance element and data fusion principle and method, in vehicular platform moves with the normal city running speed of 1-60 kilometer/hour, the infrared chart of tunnel internal is obtained by the infrared thermography be arranged on platform, the greyscale image data of tunnel-liner is obtained by area array cameras and high-power LED light fixture, range finding and the angle-data of tunnel cross-section is obtained by laser scanner, operating range and the travelling speed of vehicular platform is obtained by the photoelectric encoder be arranged on wheel, the position of platform is obtained by the GPS and inertance element that are arranged on platform, attitude data, fusion treatment is carried out in all sensing datas and synchronous data transmission to computing machine, comprehensive infrared temperature field and gray level image information extract the defect information of lining cutting.
Tunnel-liner Defect inspection system hardware based on infrared temperature field and gray level image comprises:
(1) vehicle-mounted mobile platform; Reequiped by chassis vehicle and shelter and form, for each sensor of tunnel-liner Defect inspection and power supply provide mechanical carrying platform.
(2) photoelectric encoder; Photoelectric encoder is arranged on the central shaft of chassis vehicle trailing wheel of carrier platform, to measure travelling speed and the distance of carrier platform.Present invention employs a high precision photoelectric scrambler, its mileage pulse precision reaches mm level, may be used for precisely controlling the collection of tunnel-liner profile data, adopt the mode of GPS and inertance element collaborative work to obtain the absolute coordinates of carrier platform, can more effectively merge with high density run-length data and precise 2-D image profile data.
(3) inertance element; Inertance element is arranged on the support of roof, measures the attitude parameter of carrier platform, realizes high-precision dead reckoning at tunnel internal.When tunnel is without gps signal, by the navigation residing for inertial measurement component output system, pitching and roll attitude and positional information, the data of high-precision encoder are revised in real time to inertial navigation, realize the hi-Fix of tunnel internal disease.
(4) GPS; GPS is arranged on the support of roof; Hi-Fix and the time service of system is realized under the signal having GPS.
(5) isochronous controller; Be arranged on cabinet equipment in shelter, for synchronously, trigger each sensor and acquisition server, ensure that all data have unified time and space benchmark.Isochronous controller can initiatively trigger sensor collection record the spacetime coordinates of trigger instants, and the synchronizing signal of passive receiving sensor sampling instant on the other hand, to obtain the spacetime coordinates in sensor sample moment, for space-time synchronous and the fusion of image data.
(6) multiple area array cameras; Be arranged on sensor stand, gather the lining cutting gray level image of tunnel inner wall different blocks simultaneously.
(7) multiple LED illumination light source; Different from being arranged on sensor stand, for multiple area array cameras provides lighting source.
(8) infrared thermography; Be arranged on sensor stand, gather the infrared temperature field of tunnel-liner.Because the change that can be reflected in temperature of coming to nothing of tunnel internal can be very little, select highly sensitive infrared camera can realize the identification of coming to nothing of tunnel-liner.
(9) laser scanner; Be arranged on sensor stand, gather tunnel-liner section deformation data.
(10) electric power system; Be arranged on shelter inside, for system provides the various power supplys needed for each equipment.
(11) acquisition server; Be arranged on shelter inside, gather each sensing data and store.
(12) display control device; Be arranged on shelter inside, for the optimum configurations of acquisition interface, data interface shows, the man-machine interactions such as the state of detection and the display of result.
As shown in Figure 1, GPS, photoelectric encoder are input to isochronous controller, by the process of isochronous controller settling signal, obtain correct time information, spatial information and attitude information.The isochronous controller collection that output pulse signal controls multiple area array cameras, infrared thermography carries out image on the one hand, is sent to acquisition server by GPS absolute positioning data, mileage information and velocity information and synchronous recording data on the other hand and stores.GPS and inertance element obtain the absolute location coordinates of carrier platform jointly, photoelectric encoder obtains speed and the run-length data of carrier platform, area array cameras obtains tunnel-liner surface two dimensional gray information, and infrared thermography obtains the infrared temperature field information on lining cutting surface.Realize mobile precision positioning in conjunction with the position coordinates of photoelectric encoder run-length data, GPS and the attitude data of inertance element, by analyzing tunnel-liner two dimensional gray data and infrared temperature field data, identifying and extracting tunnel-liner defect information.
The present invention is an embody rule of traverse measurement technology, and this invention have employed the new and high technology such as multiple-sensor integration and synchronous control technique, image processing techniques, infrared thermal imaging technique, laser point cloud data treatment technology, high precision movement location technology, Data fusion technique.
Carry out principles illustrated below by the function of subsystems, and then set forth principle of the present invention and scheme.
1) greyscale image data acquisition principle
As shown in Figure 2, isochronous controller receives the mileage pulse signal of photoelectric encoder, according to parameter (the area array cameras data acquisition intervals arranged, can be modified by acquisition server), produce the control signal of area array cameras, control one group of area array cameras and gather tunnel-liner gradation data, record the mileage of photoelectric encoder as the Y-coordinate of platform under linear reference frame simultaneously; An area array cameras once gathers the gradation data that can obtain a tunnel inner wall block, the gradation data of one group of tunnel inner wall block that multiple area array cameras obtains becomes a complete tunnel cross-section gradation data by splicing, and stores in the mode of one-dimension array respectively; Inertance element is according to the attitude data (R, P, H) of certain frequency output stage, and the acquisition parameter setting that acquisition server is used for isochronous controller and area array cameras stores with data.By the movement of carrier loader platform, the multiple profile data of area array cameras continuous acquisition tunnel-liner, thus form tunnel-liner surface two dimensional gray data.
2) infrared temperature field picture data acquisition principle
As shown in Figure 3, isochronous controller receives the mileage pulse signal of photoelectric encoder, according to parameter (the infrared thermography data acquisition intervals arranged, can be modified by acquisition server), produce the control signal of infrared thermography, control one group of infrared thermography and gather tunnel-liner temperature field data, record the mileage of photoelectric encoder as the Y-coordinate of platform under linear reference frame simultaneously; An infrared thermography once gathers the temperature field data that can obtain a tunnel inner wall block, the temperature field data of one group of tunnel inner wall block that multiple infrared thermography obtains can be spliced becomes a complete tunnel inner wall section temperature number of fields, and stores in the mode of one-dimension array respectively; Inertance element is according to the attitude data (R, P, H) of certain frequency output stage, and the acquisition parameter setting that acquisition server is used for isochronous controller and infrared thermography stores with data.By the movement of carrier loader platform, the multiple profile data of infrared thermography continuous acquisition tunnel-liner, thus form tunnel-liner surface red outer temperature field data.
3) carrier loader platform high precision timing positioning principle
As shown in Figure 4, the absolute location coordinates (X being obtained carrier platform between tunnel by GPS is entered
wGS84, Y
wGS84, Z
wGS84) as the starting point of engineering, at tunnel internal due to without gps signal, then need the continuous attitude (R obtained by high-precision inertance element in carrier platform motion process, P, H) and calculate positional information, photoelectric encoder obtains linear reference coordinate y in conjunction with the reference position of carrier platform, add the calibrating parameters at camera image space center and inertance element center, the calibrating parameters at gps antenna center and inertance element center carries out registration to above locator data, eventually pass through integrated positioning and export carrier platform high precision, highdensity absolute coordinates (X
p, Y
p, Z
p), linear coordinate y and high-precision attitude information (R, P, H).
Timing system is realized by GPS and inner high stability crystal oscillator, under the prerequisite having gps signal, realizes high-precise synchronization by PPS pulse per second (PPS), is realized in tunnel internal is without GPS situation by high stability crystal oscillator and FPGA high-speed, high precision timekeeping system.
4) the splicing principle of greyscale image data
As shown in Figure 5, because tunnel-liner section is general larger, in order to reach higher Crack Detection precision, the covering on tunnel-liner surface must be realized by multiple area array cameras.Certain overlapping region can be there is between every two cameras.In order to show the disease on tunnel-liner surface intuitively, need the image data of multiple area array cameras to splice.Namely several have the image of lap, technology that different visual angles is combined into a large-scale seamless high-definition picture.Image registration and image co-registration are two gordian techniquies of image mosaic.Image registration is the basis of image co-registration, and the calculated amount of image registration algorithm is general very large, and therefore the innovation of image registration techniques is depended in the development of image mosaic technology to a great extent.
As shown in Figure 6, image mosaic mainly comprises the following steps:
First pre-service is carried out to the multiple gray level images gathered, basic operation is carried out to image, comprises histogram treatment and smothing filtering, set up the matching template of image, image is carried out to the operations such as the characteristic set of Fourier transform and extraction image.Image registration is the corresponding in a reference image position of the unique point found out in image to be spliced according to the position of camera and angle.According to the corresponding relation between characteristics of image, each parameter value of mathematical model can be calculated, thus set up the mathematical transformation model of two width images.According to this model, image to be spliced is transformed in the coordinate system of reference picture, is formed complete tunnel-liner image with this.
5) based on the tunnel-liner Defect inspection principle of half-tone information and infrared temperature field information
As shown in Figure 7, the area array cameras original gradation obtained obtains complete Tunnel Lining Cracks image after merging algorithm for images, image information comprises complete half-tone information (X, Y, Z, G), in half-tone information, adopt gradient operator to extract edge of crack, adopt 2D Ostu method to extract crack area, as the alternative area AOCG of tunnel-liner disease;
In the infrared temperature data of having spliced, first adopt gradient orientation histogram to extract lining cutting percolating water marginal information, on this basis, adopt watershed algorithm to extract lining cutting percolating water region, as the alternative area AOCD that tunnel-liner disease is extracted;
Finally comprehensive two kinds of modes extract final disease region AOC, export shape, length, the width of Tunnel Lining Cracks, the index such as position, area of lining cutting percolating water.
The present invention can realize tunnel Dynamic Non-Destruction Measurement, directly obtains the image of tunnel-liner, infrared temperature field, laser point cloud data, utilizes great power LED to throw light on; Under the control of photoelectric encoder and inertial navigation, the interval of tunnel cross section can control within 1mm, greatly improves identification and the Detection results of minute crack.The mode that the present invention takes large area array cameras CCD at a high speed to take pictures, detection speed can reach 60Km/h, just can carry out quick Dynamic Non-Destruction Measurement to tunnel without the need to traffic control;
It should be noted last that, above embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although with reference to preferred embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that, can modify to technical scheme of the present invention or equivalent replacement, and not departing from the spirit and scope of technical solution of the present invention, it all should be encompassed in the middle of right of the present invention.
Claims (5)
1. one kind based on infrared temperature field and gray level image tunnel-liner Defect inspection device, it is characterized in that, comprise vehicle-mounted mobile platform, light fixture, photoelectric encoder, GPS, inertance element, isochronous controller, area array cameras, infrared thermography, acquisition server, display control device and electric power system
Described vehicle-mounted mobile platform, for providing the carrying platform of movement for each described equipment;
Described photoelectric encoder, is arranged on the wheel center axle of vehicle-mounted mobile platform, in order to measure travelling speed and the distance of vehicle-mounted mobile platform;
Described GPS, installs on described vehicle-mounted mobile platform, for hi-Fix and the time service of described vehicle-mounted mobile platform;
Described inertance element, is arranged on described vehicle-mounted mobile platform, when not receiving gps signal for GPS described in tunnel, measures the position of described vehicle-mounted mobile platform, attitude data, realizes at the high-precision dead reckoning of tunnel internal;
Described isochronous controller, is arranged on described vehicle-mounted mobile platform, for synchronous, triggering area array cameras, infrared thermography, ensures that all data have unified time and space benchmark;
Described area array cameras, is arranged on described vehicle-mounted mobile platform, connects described isochronous controller, for gathering the two-dimensional image information of tunnel-liner;
Described light fixture, is arranged on described vehicle-mounted mobile platform, for providing lighting source for described area array cameras;
Described infrared thermography, is arranged on described vehicle-mounted mobile platform, connects described isochronous controller, for gathering the infrared temperature field of tunnel-liner;
Described acquisition server, for receiving the data of described GPS, inertance element, photoelectric encoder, isochronous controller, area array cameras, infrared thermography, carries out data processing and storage;
Described display control device, connects described acquisition server, and for the man-machine interaction of described acquisition server, comprise the optimum configurations gathering control inerface, data interface shows, the state of detection and the display of result;
Described electric power system, is arranged on described vehicle-mounted mobile platform, for system provides the various power supplys needed for each equipment.
2. according to claim 1 based on infrared temperature field and gray level image tunnel-liner Defect inspection device, it is characterized in that, the quantity of described area array cameras is multiple, an area array cameras gathers the gray level image of a part of tunnel inner wall block, and the gray level image of multiple described block is spliced into the gray level image of a tunnel inner wall section.
3. according to claim 2 based on infrared temperature field and gray level image tunnel-liner Defect inspection device, it is characterized in that, the quantity of described infrared thermography is multiple, an infrared thermography gathers the temperature pattern of a part of tunnel inner wall block, and the temperature pattern of multiple described block is spliced into the temperature pattern of a tunnel inner wall section.
4. according to one of claims 1 to 3 Suo Shu based on infrared temperature field and gray level image tunnel-liner Defect inspection device, it is characterized in that, also comprise laser scanner, described laser scanner is arranged on described vehicle-mounted mobile platform, connect described isochronous controller, for the thermomechanical processing of scanning collection tunnel-liner section, described thermomechanical processing outputs to described acquisition server.
5. according to claim 4 based on infrared temperature field and gray level image tunnel-liner Defect inspection device, it is characterized in that, the data processing of described acquisition server comprises, by the tunnel-liner two-dimensional image data, infrared temperature field data and the section deformation data that receive, in conjunction with the locator data of GPS, inertance element and photoelectric encoder, set up the tunnel model of band half-tone information, temperature information and section deformation information; Adopt the two dimensional gray information processing technology to analyze Tunnel Lining Cracks, the length of automatic fracture detection, width and lining cutting percolating water information, and result is preserved, as the reference frame of Tunnel Repair and maintenance.
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WO2024065919A1 (en) * | 2022-09-27 | 2024-04-04 | 深圳大学 | Central control system for tunnel diagnosis vehicle, and method |
Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101694084A (en) * | 2009-10-14 | 2010-04-14 | 武汉武大卓越科技有限责任公司 | Ground on-vehicle mobile detecting system |
CN201449649U (en) * | 2009-07-09 | 2010-05-05 | 南京武大卓越科技有限公司 | Spontaneous combustion monitoring and warning system for coal |
CN101988961A (en) * | 2009-08-04 | 2011-03-23 | 武汉武大卓越科技有限责任公司 | Geographic location data collecting system |
CN102279081A (en) * | 2011-04-26 | 2011-12-14 | 同济大学 | Method and device for detecting water seepage of tunnel |
CN102425991A (en) * | 2011-09-15 | 2012-04-25 | 武汉武大卓越科技有限责任公司 | Automation storage yard laser measurement device and application method thereof |
CN102768027A (en) * | 2012-07-20 | 2012-11-07 | 山东理工大学 | Method for monitoring whole-process safe displacement of underground surrounding rock |
CN202735798U (en) * | 2012-06-27 | 2013-02-13 | 山东康威通信技术股份有限公司 | Cable channel intelligent inspection robot monitoring application system |
CN203280940U (en) * | 2013-06-06 | 2013-11-13 | 成都慧拓自动控制技术有限公司 | Suspension type intelligent fire-fighting robot |
CN104005325A (en) * | 2014-06-17 | 2014-08-27 | 武汉武大卓越科技有限责任公司 | Pavement crack detecting device and method based on depth and gray level images |
CN104019742A (en) * | 2014-06-05 | 2014-09-03 | 武汉武大卓越科技有限责任公司 | Method for rapidly detecting cracks of tunnel lining |
CN104048970A (en) * | 2014-06-19 | 2014-09-17 | 樊晓东 | High-speed detection system and method of tunnel defects |
CN104237257A (en) * | 2014-09-25 | 2014-12-24 | 同济大学 | Device for comprehensively and rapidly detecting structure damage of running metro tunnel |
CN104236827A (en) * | 2013-06-09 | 2014-12-24 | 同济大学 | Tunnel water leakage detection method and device based on temperature gradient |
-
2015
- 2015-03-25 CN CN201510131839.3A patent/CN104749187A/en active Pending
Patent Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN201449649U (en) * | 2009-07-09 | 2010-05-05 | 南京武大卓越科技有限公司 | Spontaneous combustion monitoring and warning system for coal |
CN101988961A (en) * | 2009-08-04 | 2011-03-23 | 武汉武大卓越科技有限责任公司 | Geographic location data collecting system |
CN101694084A (en) * | 2009-10-14 | 2010-04-14 | 武汉武大卓越科技有限责任公司 | Ground on-vehicle mobile detecting system |
CN102279081A (en) * | 2011-04-26 | 2011-12-14 | 同济大学 | Method and device for detecting water seepage of tunnel |
CN102425991A (en) * | 2011-09-15 | 2012-04-25 | 武汉武大卓越科技有限责任公司 | Automation storage yard laser measurement device and application method thereof |
CN202735798U (en) * | 2012-06-27 | 2013-02-13 | 山东康威通信技术股份有限公司 | Cable channel intelligent inspection robot monitoring application system |
CN102768027A (en) * | 2012-07-20 | 2012-11-07 | 山东理工大学 | Method for monitoring whole-process safe displacement of underground surrounding rock |
CN203280940U (en) * | 2013-06-06 | 2013-11-13 | 成都慧拓自动控制技术有限公司 | Suspension type intelligent fire-fighting robot |
CN104236827A (en) * | 2013-06-09 | 2014-12-24 | 同济大学 | Tunnel water leakage detection method and device based on temperature gradient |
CN104019742A (en) * | 2014-06-05 | 2014-09-03 | 武汉武大卓越科技有限责任公司 | Method for rapidly detecting cracks of tunnel lining |
CN104005325A (en) * | 2014-06-17 | 2014-08-27 | 武汉武大卓越科技有限责任公司 | Pavement crack detecting device and method based on depth and gray level images |
CN104048970A (en) * | 2014-06-19 | 2014-09-17 | 樊晓东 | High-speed detection system and method of tunnel defects |
CN104237257A (en) * | 2014-09-25 | 2014-12-24 | 同济大学 | Device for comprehensively and rapidly detecting structure damage of running metro tunnel |
Non-Patent Citations (5)
Title |
---|
刘新业等: "红外热成像在电气设备维护中的应用", 《红外与激光工程》 * |
刘普霖: "红外物理与技术发展", 《世界科技研究与发展》 * |
张科强等: "混凝土的无损检测方法及其新发展", 《混凝土》 * |
毛东晖: "三维扫描技术在隧道工程中的应用分析", 《铁道建筑技术》 * |
肖书安等: "高速铁路隧道竣工测量新技术", 《铁道标准设计》 * |
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Application publication date: 20150701 |