CN114708698B - Intelligent sensing and early warning system for foreign matters in tunnel - Google Patents
Intelligent sensing and early warning system for foreign matters in tunnel Download PDFInfo
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- CN114708698B CN114708698B CN202210292803.3A CN202210292803A CN114708698B CN 114708698 B CN114708698 B CN 114708698B CN 202210292803 A CN202210292803 A CN 202210292803A CN 114708698 B CN114708698 B CN 114708698B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B19/00—Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
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Abstract
The invention provides an intelligent sensing and early warning system for foreign matters in a tunnel, which comprises a sensing and early warning platform and a mobile patrol platform, wherein the sensing and early warning platform and the mobile patrol platform form a cloud edge end structure; the mobile patrol platform comprises a foreign matter detection subsystem, wherein the foreign matter detection subsystem comprises a 3D laser radar, at least one CMOS camera and an infrared camera, the 3D laser radar is used for accurately positioning foreign matters on a tunnel road surface so as to obtain position information of the foreign matters, the at least one CMOS camera is used for taking an original picture of the road surface, and the infrared camera is used for taking an infrared picture of the road surface; the foreign matter detection subsystem is used for transmitting the foreign matter position information, the road surface original picture and the road surface infrared picture data to the perception and early warning platform for data fusion processing; the CMOS camera at least adopts a shearing lens mode to shoot the road surface. The invention can realize rapid response and early warning of the foreign matter condition of the tunnel pavement.
Description
Technical Field
The invention relates to the field of tunnel detection, in particular to an intelligent sensing and early warning system for foreign matters in a tunnel.
Background
Because of the specificity of the tunnel, accidents are easier to occur relative to other driving road sections, for example, due to poor light rays, drivers often cannot easily find timely avoidance under the conditions that driving loads fall off and equipment parts in the tunnel are scattered, traffic accidents are caused, and life and property losses of masses are caused.
The prior art is mainly applied to the aspects of tunnel foreign matter perception and early warning by manually screening through a video sensor (camera) arranged in a tunnel, so that not only can the manual work be liberated, but also all-weather normalized perception and early warning can not be carried out on the foreign matters in the tunnel, and meanwhile, the problems of high cost, monitoring dead angles and the like exist in the foreign matter perception and early warning modes of arranging the camera in the tunnel under the environments of long tunnels and extra-long tunnels.
Disclosure of Invention
Aiming at the problems, the invention aims to provide an intelligent sensing and early warning system for foreign matters in a tunnel, which comprises a sensing and early warning platform and a mobile patrol platform, wherein the mobile patrol platform is in communication connection with the sensing and early warning platform in a wireless mode, and the sensing and early warning platform and the mobile patrol platform form a cloud edge end structure; the mobile patrol platform comprises a foreign matter detection subsystem, wherein the foreign matter detection subsystem comprises a 3D laser radar, at least one CMOS camera and an infrared camera, the 3D laser radar is used for accurately positioning foreign matters on a tunnel road surface so as to obtain position information of the foreign matters, the at least one CMOS camera is used for taking an original picture of the road surface, and the infrared camera is used for taking an infrared picture of the road surface; the foreign matter detection subsystem is used for transmitting the foreign matter position information, the road surface original picture and the road surface infrared picture data to the perception and early warning platform for data fusion processing; the CMOS camera shoots the pavement at least by adopting a shearing lens mode, and the interval time between the shot original picture of the pavement of the previous frame and the shot original picture of the pavement of the next frame is determined according to the following mathematical formula:
wherein T represents the distance time between the original image of the road surface of the previous frame and the original image of the road surface of the next frame, s represents the driving speed limited by the tunnel, M, N represents the frame width and the frame height of the original image of the road surface, and C n+1 、C n The space sizes of the road surface original picture of the next frame and the road surface original picture of the previous frame are respectively represented, n represents the serial number of the road surface original picture, and L represents the gray level of the road surface original picture.
Further, the mobile patrol platform further comprises an environment detection subsystem, wherein the environment detection subsystem comprises a temperature sensor, a humidity sensor, a toxic and harmful gas sensor and/or a wind speed sensor, and is used for detecting the temperature, the humidity, the toxic and harmful gas and the wind speed in the tunnel in real time and transmitting the temperature, the humidity, the toxic and harmful gas and the wind speed in the tunnel to the sensing and early warning platform in real time.
Further, the mobile patrol platform further comprises an important equipment and structure detection subsystem for monitoring the state of the important equipment and structure, wherein the important equipment and structure comprises one or more of a tunnel wall decorative plate, a tunnel top fireproof plate, an electric cabinet door and a fire hydrant door.
Further, the foreign matter detection subsystem is arranged on the mobile patrol robot, and the mobile patrol robot can move along the track erected on the inner wall of the tunnel so as to shoot the road in the whole tunnel in real time.
Further, the power supply of the mobile patrol robot adopts a rechargeable mobile power supply or a wireless charging mode.
Further, after receiving the original road surface pictures, the sensing and early warning platform extracts feature points of at least the original road surface pictures of the previous frame and the original road surface pictures of the next frame, and converts the color space of the original road surface pictures of the previous frame and the next frame from RGB to HSV, sets a value range H E [0,180], S E [0,255], V E [0,255] of H, S, V components, respectively performs four equal-division segmentation on H, S, V components, quantizes the split components, calculates acceleration robust distances between the feature points, and performs feature point matching on the original road surface pictures of the previous frame and the next frame of the HSV color space under a set self-adaptive threshold, wherein the mathematical relationship between the self-adaptive threshold and the acceleration robust distances between the feature points is as follows:
r represents an adaptive threshold, alpha represents an adaptive coefficient, delta and mu are respectively weight coefficients, delta+mu=1, and Y max 、Y min Respectively representing the original pictures of the road surface of the front frame and the rear frameMaximum and minimum acceleration robust distances for a feature, Y' represents the acceleration robust distance, h, for a color feature n+1 、h n H component values s respectively representing original pictures of front and rear frames of pavement n+1 、s n S component values, v of original pictures of front and rear frames of road surfaces are respectively represented n+1 、v n And V component values of original pictures of the front and rear frames of road surfaces are respectively represented.
Furthermore, after extracting the feature points of the original image of the road surface of the previous frame and the original image of the road surface of the next frame, the perception and early warning platform reassigns H, S, V components of feature points, which meet requirements, of the original image of the road surface of the next frame, and converts the reassigned original image of the road surface of the next frame from an HSV color space to an RGB color space and outputs the color space.
The beneficial effects of the invention are as follows: the movable patrol system can monitor the road surface in the tunnel in real time, avoids the screening mode by manpower in the prior art, further realizes the emergency intelligent command of the tunnel, reduces the frequency of accidents in the tunnel, rapidly reacts after the accidents happen, evacuates people, and evacuates emergently, and reduces the loss of lives and properties of people.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a block diagram of a preferred embodiment of an intelligent sensing and early warning system for foreign objects in a tunnel according to the present invention;
FIG. 2 is a frame construction diagram of the foreign object detection subsystem of FIG. 1;
FIG. 3 is a schematic diagram of the working principle of the 3D lidar of FIG. 2;
FIG. 4 is a schematic diagram illustrating the operation of the foreign object detection subsystem of FIG. 1;
fig. 5 is a block diagram of the environment detection subsystem of fig. 1.
Reference numerals:
the system comprises a mobile patrol system 1, a foreign matter detection subsystem 10, an environment detection subsystem 12, an important equipment and structure detection subsystem 13, a perception and early warning platform 2, a 3D laser radar 101, a CMOS camera 102, an infrared camera 103, a temperature sensor 120, a humidity sensor 122, a toxic and harmful gas sensor 123 and a wind speed sensor 126.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Referring to fig. 1, a preferred embodiment of an intelligent sensing and early warning system for foreign matters in a tunnel according to the present invention includes a mobile patrol platform 1 and a sensing and early warning platform 2, where the mobile patrol platform 1 and the sensing and early warning platform 2 are in communication connection in a wireless manner, and form a cloud edge structure. The mobile patrol system 1 includes a foreign matter detection subsystem 10, an environment detection subsystem 12, an important equipment and structure detection subsystem 13. In this embodiment, the foreign matter detection subsystem 10 is disposed on a mobile patrol robot (not shown), and the mobile patrol robot can move along a track erected on the inner wall of the tunnel, so as to shoot the road in the whole tunnel in real time. The power supply of the mobile patrol robot adopts a rechargeable mobile power supply or a wireless charging mode.
Referring to fig. 2, the foreign object detection subsystem 10 includes a 3D lidar 101, at least one CMOS camera 102, and an infrared camera 103. The 3D lidar 101 is configured to accurately locate a foreign object on a tunnel pavement, so as to obtain position information of the foreign object. The at least one CMOS camera 102 is used for taking an original image of the road surface, and the infrared camera 103 is used for taking an infrared image of the road surface. In the present invention, the foreign matter detection subsystem 10 is configured to transmit the foreign matter position information, the road surface original picture and the road surface infrared picture to the sensing and early warning platform 2 through the 3D laser radar 101, the CMOS camera 102 and the infrared camera 103.
The 3D lidar 101 is configured to provide main three-dimensional point cloud data, so as to calculate a position of a foreign object. In this embodiment, the 3D lidar 101 is mounted on a mobile patrol robot that can move along the inner wall of the tunnel, and the 3D lidar 101 is detected obliquely downward, so as to detect the road surface in the tunnel in all directions. Specifically, referring to fig. 3, the 3D lidar 101 may position the foreign object according to the following working principle: firstly, removing some suspended isolated points or invalid points in the original laser radar point cloud through radius filtration; secondly, extracting a moving target from the background image by a segmentation method; thirdly, after the difference is obtained, the point cloud is divided into different target point clouds, for example: distinguishing foreign matter on the ground from normal objects (ground normal object example: tunnel gravel road ground); fourth, identifying and circumscribing the foreign matter, and extracting coordinate information of the abnormal object.
Specifically, in this embodiment, the CMOS camera 102 photographs the road surface at least by using a shearing lens, and the infrared camera 103 is used for photographing an infrared image of the road surface. The distance time between the original image of the road surface of the previous frame and the original image of the road surface of the next frame shot by the CMOS camera 102 can be determined according to the following mathematical formula:
wherein T represents the distance time between the original picture of the road surface of the previous frame and the original picture of the road surface of the next frame, s represents the driving speed limited by the tunnel, and C n+1 、C n The space sizes of the road surface original picture of the next frame and the road surface original picture of the previous frame are respectively represented, n represents the serial number of the road surface original picture, M, N represents the frame width and the frame height of the road surface original picture respectively, and L represents the gray level of the road surface original picture. The above formula can determine when the CMOS camera 102 shoots the road surface by shearing the lensThe spacing time between the original picture of the road surface of the previous frame and the original picture of the road surface of the next frame.
The road surface is shot in the shearing lens mode, so that the characteristic of the gradual lens is not changed greatly is avoided, and the recognition of the change between different images is not facilitated. And different shooting time intervals are determined according to different speed limiting settings of different tunnels, different sizes of pictures shot by the cameras and different gray levels of the pictures, so that the method is suitable for effective shooting of road images in different tunnel environments.
After receiving the road surface original picture and the road surface infrared picture, the perception and early warning platform 2 at least extracts characteristic points of the road surface original picture of the previous frame and the road surface original picture of the next frame, and converts the color space of the road surface original pictures of the previous frame and the road surface original pictures of the next frame from RGB to HSV. HSV refers to the hue H: hue, saturation S: saturation, brightness V: value.
In this embodiment, the range of values of the H, S, V component is set to be H e [0,180], S e [0,255], V e [0,255], and the H, S, V component is further divided into four equal parts and quantized, then, the acceleration robust distance between the feature points is calculated, and under the set adaptive threshold, feature point matching is performed on the two frames of road surface original pictures before and after the HSV color space, where the mathematical relationship between the adaptive threshold and the acceleration robust distance between the feature points is:
r represents an adaptive threshold, alpha represents an adaptive coefficient, delta and mu are respectively weight coefficients, delta+mu=1, and Y max 、Y min The maximum acceleration robust distance and the minimum acceleration robust distance of original picture features of the front frame pavement and the rear frame pavement are respectively represented, Y' represents the acceleration robust distance of color features, and h n+1 、h n H component values s respectively representing original pictures of front and rear frames of pavement n+1 、s n S component values, v of original pictures of front and rear frames of road surfaces are respectively represented n+1 、v n Respectively representing the road surface source of the front and the rear framesV component value of starting picture. In this embodiment, α is 0.3967, δ is 0.6, and μ is 0.4. Of course, in other embodiments, the values of the parameters may be changed according to actual needs.
In the preferred embodiment, feature point extraction is performed on the original image of the road surface of the previous frame and the original image of the road surface of the next frame, and feature points with little change are excluded from the extraction range, so that the position of the foreign matter in the image is identified. And the extraction and screening are carried out by adopting a custom mathematical formula, so that the erroneous judgment condition is avoided.
After extracting the features of the original image of the road surface of the previous frame and the original image of the road surface of the next frame, the perception and early warning platform 2 reassigns H, S, V components of feature points, which meet requirements, of the original image of the road surface of the next frame, and converts the reassigned original image of the road surface of the next frame from an HSV color space to an RGB color space and outputs the color space. Preferably, in this embodiment, the H component is increased by 2%, the S component is increased by 1%, and the V component is increased by 3%. Of course, in other embodiments, the improvement value of the above component may be changed according to actual needs.
Specifically, the operation principle of the above-described foreign matter detection subsystem will be briefly described below:
referring to fig. 4, the interior of the tunnel is photographed by the CMOS camera 102 and the infrared camera 103, so that a real-time image of the tunnel can be obtained. And transmitting the real-time image to the sensing and early warning platform 2 so as to perform image processing on the real-time image. And judging whether the foreign matters exist in the tunnel or not by judging the foreign matters in the processed image. And then carrying out subsequent treatment according to the specific conditions (namely whether foreign matters exist or not) in the tunnel.
In this embodiment, the method for detecting a foreign object in a tunnel includes: step S1: shooting the internal pavement of the tunnel in real time through a CMOS camera 102 and an infrared camera 103 which are arranged on the mobile patrol robot; step S2: carrying out image processing on the shot image; step S3: identifying the image after the image processing to judge whether foreign matters exist on the road surface in the tunnel; step S4: the identified tunnel pavement foreign matter is precisely positioned by the 3D laser radar 101 arranged in the tunnel so as to obtain the position information of the foreign matter.
Referring to fig. 5, the environment detection subsystem 12 includes a temperature sensor 120, a humidity sensor 122, a toxic and harmful gas sensor 123, and a wind speed sensor 126. The temperature sensor 120 is configured to detect a real-time value of the temperature inside the tunnel, and transmit the real-time value of the temperature inside the tunnel to the sensing and early warning platform 2. And the sensing and early warning platform 2 automatically alarms when the real-time temperature value reaches a preset threshold value. Similarly, the humidity sensor 122 is configured to detect a real-time value of the humidity inside the tunnel, and transmit the real-time value of the humidity inside the tunnel to the sensing and early-warning platform 2, where the sensing and early-warning platform 2 automatically alarms when the real-time value of the humidity reaches a preset threshold. The toxic and harmful gas sensor 123 is configured to detect a real-time value of a toxic and harmful gas, and transmit the real-time value of the toxic and harmful gas in the tunnel to the sensing and early-warning platform 2, where the sensing and early-warning platform 2 automatically alarms when the real-time value of the toxic and harmful gas reaches a preset threshold. The wind speed sensor 126 is configured to detect a real-time value of a wind speed in the tunnel, and transmit the real-time value of the wind speed in the tunnel to the sensing and early-warning platform 2, where the sensing and early-warning platform 2 automatically alarms when the real-time value of the wind speed reaches a preset threshold value.
The important equipment and structure detection subsystem 13 is used for monitoring the status of the important equipment and structure. In this embodiment, the important and structure in the tunnel includes one or more of a tunnel wall decorative board, a tunnel top fireproof board, an electrical cabinet door and a fire hydrant door, and the sensing and early warning platform 2 automatically alarms when one or more of the tunnel wall decorative board, the tunnel top fireproof board, the electrical cabinet door and the fire hydrant door is abnormal.
In the preferred embodiment, through the linkage of the internet of things in the tunnel, the quick intelligent sensing and early warning of the foreign matters in the tunnel are realized, traffic accidents caused by the foreign matters in the tunnel are prevented, the frequency of accidents in the tunnel is reduced, and the loss of lives and properties of people is reduced. Meanwhile, the environment and important equipment in the tunnel can be subjected to daily inspection in the daily inspection process, and an alarm is given when one or more of the environment parameters or the important equipment are abnormal.
The foregoing examples only represent preferred embodiments of the present invention, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (6)
1. An intelligent sensing and early warning system for foreign matters in a tunnel is characterized in that: the intelligent patrol system comprises a sensing and early warning platform and a mobile patrol platform, wherein the mobile patrol platform is in communication connection with the sensing and early warning platform in a wireless mode, and the sensing and early warning platform and the mobile patrol platform form a cloud edge end structure; the mobile patrol platform comprises a foreign matter detection subsystem, wherein the foreign matter detection subsystem comprises a 3D laser radar, at least one CMOS camera and an infrared camera, the 3D laser radar is used for accurately positioning foreign matters on a tunnel road surface so as to obtain position information of the foreign matters, the at least one CMOS camera is used for taking an original picture of the road surface, and the infrared camera is used for taking an infrared picture of the road surface; the foreign matter detection subsystem is used for transmitting the foreign matter position information, the road surface original picture and the road surface infrared picture data to the perception and early warning platform for data fusion processing; the CMOS camera shoots the pavement at least by adopting a shearing lens mode, and the interval time between the shot original picture of the pavement of the previous frame and the shot original picture of the pavement of the next frame is determined according to the following mathematical formula:
wherein T represents the distance time between the original picture of the road surface of the previous frame and the original picture of the road surface of the next frame, and s represents the driving defined by the tunnelSpeed M, N respectively represents frame width and frame height of original pavement picture, C n+1 、C n The method comprises the steps of respectively representing the space sizes of a road surface original picture of a next frame and a road surface original picture of a previous frame, wherein n represents the sequence number of the road surface original picture, and L represents the gray level of the road surface original picture;
after receiving the original road surface pictures, the sensing and early warning platform extracts feature points of at least the original road surface pictures of the previous frame and the original road surface pictures of the next frame, converts the color space of the original road surface pictures of the previous frame and the next frame from RGB to HSV, sets the value range H E [0,180], S E [0,255] and V E [0,255] of H, S, V components, respectively divides H, S, V components into four equal parts, carries out quantization, calculates acceleration robust distances between the feature points, and carries out feature point matching on the original road surface pictures of the previous frame and the next frame of HSV color space under the set self-adaptive threshold, wherein the mathematical relationship between the self-adaptive threshold and the acceleration robust distances between the feature points is as follows:
r represents an adaptive threshold, alpha represents an adaptive coefficient, delta and mu are respectively weight coefficients, delta+mu=1, and Y max 、Y min The maximum acceleration robust distance and the minimum acceleration robust distance of original picture features of the front frame pavement and the rear frame pavement are respectively represented, Y' represents the acceleration robust distance of color features, and h n+1 、h n H component values s respectively representing original pictures of front and rear frames of pavement n+1 、s n S component values, v of original pictures of front and rear frames of road surfaces are respectively represented n+1 、v n And V component values of original pictures of the front and rear frames of road surfaces are respectively represented.
2. The intelligent sensing and early warning system for foreign objects in a tunnel according to claim 1, wherein: the movable patrol platform further comprises an environment detection subsystem, wherein the environment detection subsystem comprises a temperature sensor, a humidity sensor, a toxic and harmful gas sensor and/or a wind speed sensor, is used for detecting the temperature, the humidity, the toxic and harmful gas and the wind speed in the tunnel in real time, and transmits the temperature, the humidity, the toxic and harmful gas and the wind speed in the tunnel to the sensing and early warning platform in real time.
3. The intelligent sensing and early warning system for foreign objects in a tunnel according to claim 1, wherein: the movable patrol platform further comprises an important equipment and structure detection subsystem for monitoring the states of the important equipment and structure, wherein the important equipment and structure comprises one or more of a tunnel wall decorative plate, a tunnel top fireproof plate, an electrical cabinet door and a fire hydrant door.
4. The intelligent sensing and early warning system for foreign objects in a tunnel according to claim 1, wherein: the foreign matter detection subsystem is arranged on the mobile patrol robot, and the mobile patrol robot can move along a track erected on the inner wall of the tunnel so as to shoot a road in the whole tunnel in real time.
5. The intelligent sensing and early warning system for foreign objects in a tunnel according to claim 4, wherein: the power supply of the mobile patrol robot adopts a rechargeable mobile power supply or a wireless charging mode.
6. The intelligent sensing and early warning system for foreign objects in a tunnel according to claim 5, wherein: after feature point extraction is carried out on the original image of the road surface of the previous frame and the original image of the road surface of the next frame, the sensing and early warning platform reassigns H, S, V components of feature points, which meet requirements, of the original image of the road surface of the next frame, converts the reassigned original image of the road surface of the next frame from an HSV color space to an RGB color space and outputs the color space.
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