CN102435173B - System and method for quickly inspecting tunnel disease based on machine vision - Google Patents
System and method for quickly inspecting tunnel disease based on machine vision Download PDFInfo
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- CN102435173B CN102435173B CN 201110281700 CN201110281700A CN102435173B CN 102435173 B CN102435173 B CN 102435173B CN 201110281700 CN201110281700 CN 201110281700 CN 201110281700 A CN201110281700 A CN 201110281700A CN 102435173 B CN102435173 B CN 102435173B
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Abstract
The invention discloses a system and method for quickly inspecting a tunnel defect based on machine vision. The system is arranged on an investigation bearing vehicle. The system comprises a machine vision sub-system used for acquiring the to-be-investigated object image data by a CCD (Charge Coupled Device) camera, a laser ranging sub-system used for measuring an imaging distance of an image acquired by the machine vision sub-system by a laser ranging method, a photoelectric speed measuring sub-system used for providing a corresponding coordinate of the acquired image in a tunnel, a control sub-system used for controlling the laser ranging sub-system and the photoelectric speed measuring sub-system, transmitting the data acquired by the laser ranging sub-system and the photoelectric speed measuring sub-system to a data processing sub-system and triggering the machine vision sub-system to acquire an image and transmit the image to the data processing sub-system, a data processing sub-system used for processing the image acquired by the machine vision sub-system according to the data from the control sub-system, and a power supply sub-system used for providing voltage for other sub-systems. According to the invention, the general tunnel defect can be regularly and quickly inspected and the inspecting process is safe, quick, full-automatic and real-time without influencing normal work of the tunnel.
Description
Technical field
The present invention relates to the tunnel defect technique for investigation, relate in particular to a kind of tunnel defect system based on machine vision, be applied to the detection of tunnel defect.
Background technology
In recent years, the diseases such as Lining Crack, distortion and percolating water appear in China's built various highways, railway, the bottom and subway tunnel to some extent.The existence of disease can affect traffic quality, threaten traffic safety in the tunnel, cause security incident, need science badly, effectively analyze and research method, the analysis and evaluation disease produces the impact that liner structure safety and usability are caused, for disease management method and countermeasure provide foundation.The prerequisite of control tunnel defect is that kind, distribution and the degree to tunnel defect carried out in detail and comprehensively investigation, can provide foundation for the Gernral Check-up in tunnel by the system investigation to disease.
What at present China mainly adopted the disease survey in tunnel is artificial field investigation method, this method needs investigator's health status to the tunnel in the tunnel to investigate, comprise that position, length, width and area to tunnel slot, distortion and percolating water place carry out survey record, and to the record data add up, sort out and file, according to certain standard tunnel defect is estimated at last.The method of this manual research tends to affect the high consumption of normal operation, investigation method in tunnel and poor efficiency when operation, there are artificial subjective factor in measuring method and reading out data during during the process of the investigation often with very large danger and investigation, and the reliability of the data and completeness are limited.
For the detection and Identification in crack, existing method has laser scanning method and pattern-recognition method.These two kinds of methods are mainly used in the crack identification of highway pavement at present.Laser scanning method is to send the laser scanning road surface by laser scanner, then optical receiver receives the light that fires back from the road surface at a certain angle, when the crack appears in the road surface that is scanned, the crack can make laser light scattering or the refraction of arrival, the catoptrical intensity that optical receiver receives will reduce, therefore can according to the variation of the intensity of reflected light of optical receiver output, determine whether the road surface exists the crack.The shortcoming of this method is that light environment on every side is large to the Accuracy that detects, the reflection of laser can be subject to the impact of sunshine in the time of by day, so generally in night work, make troubles to the testing staff, and in testing process, need the artificially to carry out mark and the evaluation in crack, inefficiency.And the image recognition rule is to obtain the image on road surface and send images to computing machine by the video camera on the inspection vehicle, image by the computing machine road pavement carries out pre-service, the image that is only contained road surface background and crack, and then utilize corresponding recognizer to determine whether the road surface exists the crack, and fracture positions.
The shortcoming of this method is that the result who detects depends on the image quality of image and the reliability of recognizer, the imaging of video camera needs the illumination condition of high brightness, imaging is subject to the vibrations of inspection vehicle and the impact of speed easily, and need manually each width of cloth image to be marked with statistic of classification to process, process in real time so can't realize the full-automatic of fracture.
Summary of the invention
The present invention provides a kind of tunnel defect system and investigation method based on machine vision for the defective that overcomes above-mentioned prior art existence, can realize the regular fast investigation to the tunnel Common Diseases, make fact-finding process safely and fast, automatically process and not affect in real time the normal operation in tunnel.
The present invention is achieved in that a kind of tunnel defect system based on machine vision technique, it is characterized in that, is installed on the investigation carrying vehicle, comprising:
Machine vision subsystem is used for utilizing ccd video camera to treat respondent-tunnel surface and adopts picture, obtain after respondent's view data and transfer to data process subsystem;
The laser ranging subsystem is used for the image-forming range by the image of laser distance measurement method monitoring vision subsystem collection;
The photoelectric velocity measurement subsystem is used for using the photoelectric velocity measurement method that the travel speed of investigation carrying vehicle is carried out non-contact measurement, provides to gather the respective coordinates of image in the tunnel;
Control subsystem, be used for control laser ranging subsystem, photoelectric velocity measurement subsystem, the data transfer that receives and laser ranging subsystem, photoelectric velocity measurement subsystem are obtained triggers simultaneously machine vision subsystem and gathers image transmitting to data process subsystem to data process subsystem;
Data process subsystem is used for calling the image that measurement data that control subsystem transmits obtains machine vision subsystem and processes, and carries out disaster and identifies fast statistics;
Power subsystem, being used for unification provides work required burning voltage for above-mentioned subsystems.
Described machine vision subsystem comprises optical lens, CCD area array camera and for the imaging of described CCD area array camera provides the illuminating lamp of light source, also comprises:
Image capture module is used for picture signal with the collection of described CCD area array camera and is converted to digital signal and is input to computing machine and processes;
View data storage and transport module are used for storing the image of Computer Processing, and image data transmission is arrived data process subsystem.
Described investigation carrying vehicle comprises wheel and circular arc car body, circular arc car body outside surface is distributed with machine vision subsystem, laser ranging subsystem and photoelectric velocity measurement subsystem, comprise the illuminating lamp that brightness is fixing in the machine vision subsystem, the circular arc car body is built-in with control subsystem, data process subsystem and power subsystem.
Described photoelectric velocity measurement subsystem is installed in the circular arc car body below of investigation carrying vehicle, the position relative with ground; Per three of described illuminating lamp, machine vision subsystem, laser ranging subsystem form one group, evenly distribute in all directions of the circular arc car body surface of investigation carrying vehicle.
A kind of investigation method of using described tunnel defect system based on machine vision technique is characterized in that being that steps flow chart is as follows:
(1), determines pickup area: after pickup area is determined, the investigation carrying vehicle is positioned over the tunnel inner road central authorities at pickup area place, and it is at the uniform velocity advanced along road axis;
(2), information acquisition: issue distance measuring instruction and receive ranging data to the laser ranging subsystem by control subsystem and be uploaded to data process subsystem, and control the photoelectric velocity measurement subsystem and test the speed, packing was uploaded to data process subsystem after the coordinate setting data of the image that will obtain to gather by testing the speed were carried out format conversion; Produce simultaneously trigger pip, the CCD area array camera that triggers machine vision subsystem gathers image uploading to data process subsystem;
(3), data storing: above-mentioned ranging data, locator data and the view data of the collection that data process subsystem will transmit store;
(4), data analysis: data process subsystem is called range finding, the locator data of the described collection of storage and by pre-set programs the image that gathers is processed, and carries out disaster and identifies fast, judges and add up;
(5), manual analysis: namely by analyst's intervention analysis, reject the error result in the statistics, and net result is added up, sorted out and files.
Data process subsystem is called the described collection of storage in described (4) range finding, locator data are processed the image that gathers, carry out disaster identify fast, analyze judge and the method for statistics as follows:
At first, data process subsystem is called ranging data, locator data and the view data of storage and is analyzed, and image is launched, splices processing;
Secondly, the tunnel is served as a contrast thorough structural images analyze identification, judge and statistics, obtain tunnel slot, distortion and position, percolating water place, length, width, area and lining cutting and invade limit information;
Again, by analyst's intervention the above-mentioned statistical information of obtaining is carried out manual analysis, reject the error result in institute's obtaining information, to strengthen reliability;
The analysis result that will finally be obtained by data process subsystem at last, is added up, is sorted out and files.
Describedly the tunnel is served as a contrast thorough structural images carry out analysis recognition method and comprise and use gray level correction, binary conversion treatment, binary Images Processing and image measuring method.
The present invention compared with prior art, has following advantage: 1, realized the full-automatic real-time investigation to the tunnel Common Diseases, fact-finding process does not need artificial participation, overcome that artificial cognition method labour intensity is large, inefficiency and the large shortcoming of investigation result subjective factor, improved the accuracy of investigation work efficient, security and investigation.
2, the Method and Process of investigation is simple and be easy to realize, once investigation only needs to detect carrying vehicle and travels in tunnel to be investigated and can finish investigation to this section tunnel defect, therefore can realize the regular fast investigation of tunnel defect, greatly reduces research cost and consumption.
3, fact-finding process does not affect the tunnel and normally runs, and has improved the investigation operational security, can carry out the long term monitoring investigation to the tunnel, in time finds the disease that the tunnel exists, and to disease classify automatically, degree of disease evaluation and corresponding processing prediction scheme is provided.
Machine vision is to replace human eye to do various measurements and judgement with machine, Vision Builder for Automated Inspection refers to that will be ingested target by image-pickup device converts picture signal to, send the special image disposal system to, according to information such as pixel distribution and brightness, colors, be transformed into digitized signal; Image processing system carries out the feature that various computings come extracting objects to these signals, and then controls on-the-spot device action according to the result who differentiates.Machine vision technique relates to a plurality of fields such as computing machine, image processing, pattern-recognition, artificial intelligence, signal processing, optics, machinery, it is a kind of noncontact measurement, can not produce any damage to observation with the person of being observed, the reliability of Vision Builder for Automated Inspection is high, has wider spectral response range, for example use Infrared survey invisible to the human eye, expanded the visual range of human eye; Machine Vision Inspecting System can be done for a long time to measure, analyze and identification, and can work under rugged surroundings.
Description of drawings
Fig. 1 is the structural representation based on the tunnel defect system of machine vision technique that the embodiment of the invention provides.
Fig. 2 is the structural representation of the machine vision subsystem that provides of the embodiment of the invention.
Fig. 3 is the process flow diagram based on the application method of the tunnel defect system of machine vision technique that the embodiment of the invention provides.
Fig. 4 is that data process subsystem that the embodiment of the invention provides is carried out disaster identification, judged and the process flow diagram of the method for statistics.
Fig. 5 is the equipment layout synoptic diagram based on the tunnel defect system of machine vision technique that the embodiment of the invention provides.
Embodiment
In order to make purpose of the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing, the present invention is further elaborated.
Referring to Fig. 1, the structure based on the tunnel defect system of machine vision technique that Fig. 1 shows that the embodiment of the invention provides.For convenience of explanation, only show the part relevant with the present invention, existing in conjunction with this accompanying drawing, the present invention is described in detail below.
Described tunnel defect system based on machine vision technique comprises an investigation carrying vehicle, is installed on machine vision subsystem, laser ranging subsystem, photoelectric velocity measurement subsystem, control subsystem, data process subsystem and power subsystem on the investigation carrying vehicle.
Machine vision subsystem based on machine vision technique, is utilized ccd video camera to treat respondent-tunnel surface and is adopted picture, obtains after respondent's view data and transfers to data process subsystem.
Machine vision technique is to replace human eye to do various measurements and judgement with machine, finger will be ingested target by image-pickup device and convert picture signal to, send the special image disposal system to according to image pixel distribution and the information such as brightness, color, be transformed into and these signals carried out various computings after the digitized signal and come the feature of extracting objects to process.
The laser ranging subsystem is used for the image-forming range by the image of laser distance measurement method monitoring vision subsystem collection; This laser ranging subsystem mainly comprises laser emitting module, laser pick-off module and signal processing module, and its distance-finding method adopts pulsed laser ranging method, has distance accuracy height, ranging is far away, antijamming capability by force, does not need cooperative target characteristics; This laser distance measurement method is state of the art, and those of ordinary skills can be achieved laser ranging according to prior art and above-mentioned explanation, no longer describe in detail herein.
The photoelectric velocity measurement subsystem is used for using the photoelectric velocity measurement method that the travel speed of investigation carrying vehicle is carried out non-contact measurement, provides to gather the respective coordinates of image in the tunnel.
The photoelectric velocity measurement subsystem measure the investigation carrying vehicle real time running speed after, according to degree of the testing the speed information operating range that obtains carrying vehicle be mileage, thereby provide each width of cloth image corresponding coordinate in the tunnel, image to this collection positions, and its measuring accuracy is not investigated the impact that carrying vehicle pitches.
Above-described photoelectric velocity measurement subsystem mainly comprises non-contact type photoelectricity tachogenerator, illuminating lamp, tracking filter and the corresponding fixedly stationary installation of aforementioned means that is used for; This photoelectric velocity measurement method is the prior art in this photoelectric velocity measurement field, and this field those of ordinary skill can be achieved the photoelectric velocity measurement purpose according to prior art and above-mentioned explanation, no longer describes in detail herein.
Control subsystem, be used for control laser ranging subsystem, photoelectric velocity measurement subsystem, the data transfer that receives and laser ranging subsystem, photoelectric velocity measurement subsystem are obtained triggers simultaneously machine vision subsystem and gathers image transmitting to data process subsystem to data process subsystem; Be included as laser ranging subsystem, photoelectric velocity measurement subsystem and machine vision subsystem various control signals are provided, such as synchronous trigger unit device vision subsystem, assign distance measuring instruction control signal etc. to the laser ranging subsystem.
Data process subsystem is used for calling the image that measurement data that control subsystem transmits obtains machine vision subsystem and processes, and carries out disaster and identifies fast statistics; This subsystem is the processing enter that above-mentioned corresponding subsystem obtains view data, ranging data and measurement data, and the aforementioned data of obtaining are unified in the work such as the classification of pattern-recognition, disease of the access of carrying out image in this data process subsystem and pre-service, image and evaluation.
Power subsystem, being used for unification provides work required burning voltage for above-mentioned subsystems.
Described investigation carrying vehicle be used for bearing system other all subsystems and stable movement velocity is provided, can exercise reposefully in the tunnel, therefore, the investigation carrying vehicle must use the good carrying vehicle of anti-seismic performance, so that stable running velocity to be provided, the shake of minimizing system can provide power generating source for power subsystem simultaneously to obtain the higher tunnel surface image of quality.
Referring to shown in Figure 2, this Fig. 2 shows the structure of machine vision subsystem provided by the invention, for convenience of explanation, only shows the part relevant with the present invention.Below in conjunction with this accompanying drawing, this machine vision subsystem is described as follows.
This machine vision subsystem comprises optical lens, CCD area array camera, stores and transport module for the imaging of CCD area array camera provides lighting module, image capture module and the view data of light source.
Optical lens is for consisting of imaging on the photosurface that imageable target is focused on ccd image sensor, the CCD area array camera is used for providing quick, high pixel and high-resolution imaging, described lighting module provides needed light source for the imaging of CCD area array camera, by illuminating ray is incident upon on the imageable target, make the imaging of CCD area array camera more clear; Image capture module then is converted to the image light signals of CCD area array camera imaging data image signal and is input to computing machine and processes; The view data storage is then stored the view data after the Computer Processing with transport module, and image data transmission is processed to data process subsystem, carries out disaster and identifies fast, adds up.
The above machine vision subsystem gathers the technology of image and is prior art, no longer describes in detail.
Referring to Fig. 3, the figure shows the flow process based on the using method of the tunnel defect system of machine vision technique of using that the embodiment of the invention provides; Below in conjunction with this accompanying drawing, it is as follows to this using method process description: as one, to determine pickup area: after pickup area is determined, the investigation carrying vehicle is positioned over the tunnel inner road central authorities at pickup area place, and it is at the uniform velocity advanced along road axis.
Two, information acquisition: issue distance measuring instruction and receive ranging data to the laser ranging subsystem by control subsystem and be uploaded to data process subsystem, and control the photoelectric velocity measurement subsystem and test the speed, packing was uploaded to data process subsystem after the coordinate setting data of the image that will obtain to gather by testing the speed were carried out format conversion; Produce simultaneously trigger pip, the CCD area array camera that triggers machine vision subsystem gathers image uploading to data process subsystem.
Three, data storing: above-mentioned ranging data, locator data and the view data of the collection that data process subsystem will transmit store.
Four, data analysis: data process subsystem is called range finding, the locator data of the described collection of storage and by pre-set programs the image that gathers is processed, and carries out disaster and identifies fast, judges and add up.
Five, manual analysis: namely by analyst's intervention analysis, reject the error result in the statistics, and net result is added up, sorted out and files.
Referring to Fig. 4, the figure shows the flow process that data process subsystem of the present invention is carried out the method that disaster identifies fast, judges and add up.Below in conjunction with this accompanying drawing, the method for the disaster of data process subsystem of the present invention being identified fast statistics is described in detail below.
At first, data process subsystem is called ranging data, locator data and the view data of storage and is analyzed, and image is launched, splices processing.
Secondly, the tunnel is served as a contrast thorough structural images analyze identification, judge and statistics, obtain tunnel slot, distortion and position, percolating water place, length, width, area and lining cutting and invade limit information.
Analysis recognition method comprises methods such as using gray level correction, binary conversion treatment, binary Images Processing and image measurement; The described gray level correction of the embodiment of the invention, binary conversion treatment, binary Images Processing and image measuring method are prior art, those of ordinary skills all can utilize state of the art to realize according to foregoing description, and limit information is invaded in acquisition tunnel slot, distortion and position, percolating water place, length, width, area and lining cutting.
Again, by analyst's intervention the above-mentioned statistical information of obtaining is carried out manual analysis, reject the error result in institute's obtaining information, to strengthen reliability.
The analysis result that will finally be obtained by data process subsystem at last, is added up, is sorted out and files.
5, [user of Microsoft 1] the figure shows the equipment layout method based on the tunnel defect system of machine vision technique.Below in conjunction with accompanying drawing, method for arranging is made a brief description.
As shown in Figure 5, described investigation carrying vehicle 5 comprises wheel and circular arc car body, circular arc car body outside surface is distributed with machine vision subsystem 2, laser ranging subsystem 3 and photoelectric velocity measurement subsystem 4, comprise the illuminating lamp 1 that brightness is fixing in the machine vision subsystem, the circular arc car body is built-in with control subsystem, data process subsystem and power subsystem.
Described photoelectric velocity measurement subsystem 4 is installed in the circular arc car body below of investigation carrying vehicle 5, the position relative with ground; Described illuminating lamp 1, machine vision subsystem 2, laser ranging subsystem 3 per three form one group, evenly distribute in all directions of the circular arc car body surface of investigation carrying vehicle 5.For the comprehensive and accuracy that guarantees to investigate, many group illuminating lamp 1, machine vision subsystem 2 and laser ranging subsystems 3 should be installed evenly on the circular arc surface of this investigation carrying vehicle 5.
The above only is preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (4)
1. the tunnel defect system based on machine vision technique is characterized in that, is installed on the investigation carrying vehicle (5), comprising:
Machine vision subsystem is used for utilizing ccd video camera to treat respondent-tunnel surface and adopts picture, obtain after respondent's view data and transfer to data process subsystem;
The laser ranging subsystem is used for the image-forming range by the image of laser distance measurement method monitoring vision subsystem collection;
The photoelectric velocity measurement subsystem is used for using the photoelectric velocity measurement method that the travel speed of investigation carrying vehicle is carried out non-contact measurement, provides to gather the respective coordinates of image in the tunnel;
Control subsystem, be used for control laser ranging subsystem, photoelectric velocity measurement subsystem, the data transfer that receives and laser ranging subsystem, photoelectric velocity measurement subsystem are obtained triggers simultaneously machine vision subsystem and gathers image transmitting to data process subsystem to data process subsystem;
Data process subsystem is used for calling the image that measurement data that control subsystem transmits obtains machine vision subsystem and processes, and carries out disaster and identifies fast statistics;
Power subsystem, being used for unification provides work required burning voltage for above-mentioned subsystems;
Described machine vision subsystem comprises optical lens, CCD area array camera and for the imaging of described CCD area array camera provides the illuminating lamp of light source, also comprises:
Image capture module is used for picture signal with the collection of described CCD area array camera and is converted to digital signal and is input to computing machine and processes;
View data storage and transport module are used for storing the image of Computer Processing, and image data transmission is arrived data process subsystem;
Described investigation carrying vehicle (5) comprises wheel and circular arc car body, circular arc car body outside surface is distributed with machine vision subsystem (2), laser ranging subsystem (3) and photoelectric velocity measurement subsystem (4), comprise the illuminating lamp (1) that brightness is fixing in the machine vision subsystem, the circular arc car body is built-in with control subsystem, data process subsystem and power subsystem;
Described photoelectric velocity measurement subsystem (4) is installed in the circular arc car body below of investigation carrying vehicle (5), the position relative with ground; Per three of described illuminating lamp (1), machine vision subsystem (2), laser ranging subsystem (3) form one group, evenly distribute in all directions of the circular arc car body surface of investigation carrying vehicle (5).
2. an application rights requires the investigation method of 1 described tunnel defect system based on machine vision technique, it is characterized in that being that steps flow chart is as follows:
(1), determines pickup area: after pickup area is determined, the investigation carrying vehicle is positioned over the tunnel inner road central authorities at pickup area place, and it is at the uniform velocity advanced along road axis;
(2), information acquisition: issue distance measuring instruction and receive ranging data to the laser ranging subsystem by control subsystem and be uploaded to data process subsystem, and control the photoelectric velocity measurement subsystem and test the speed, packing was uploaded to data process subsystem after the coordinate setting data of the image that will obtain to gather by testing the speed were carried out format conversion; Produce simultaneously trigger pip, the CCD area array camera that triggers machine vision subsystem gathers image uploading to data process subsystem;
(3), data storing: above-mentioned ranging data, locator data and the view data of the collection that data process subsystem will transmit store;
(4), data analysis: data process subsystem is called range finding, the locator data of the described collection of storage and by pre-set programs the image that gathers is processed, and carries out disaster and identifies fast, judges and add up;
(5), manual analysis: namely by analyst's intervention analysis, reject the error result in the statistics, and net result is added up, sorted out and files.
3. investigation method according to claim 2, it is characterized in that being that data process subsystem in the described step (4) calls range finding, the locator data of the described collection of storage the image that gathers is processed, carry out disaster identify fast, analyze judge and the method for statistics as follows:
At first, data process subsystem is called ranging data, locator data and the view data of storage and is analyzed, and image is launched, splices processing;
Secondly, the tunnel is served as a contrast thorough structural images analyze identification, judge and statistics, obtain tunnel slot, distortion and position, percolating water place, length, width, area and lining cutting and invade limit information;
Again, by analyst's intervention the above-mentioned statistical information of obtaining is carried out manual analysis, reject the error result in institute's obtaining information, to strengthen reliability;
The analysis result that will finally be obtained by data process subsystem at last, is added up, is sorted out and files.
4. investigation method according to claim 3 is characterized in that being: describedly the tunnel is served as a contrast thorough structural images carry out analysis recognition method and comprise and use gray level correction, binary conversion treatment, binary Images Processing and image measuring method.
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| CN102435173A (en) | 2012-05-02 |
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