CN111288910A - Tramcar trapezoidal turnout deformation monitoring system and method - Google Patents
Tramcar trapezoidal turnout deformation monitoring system and method Download PDFInfo
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- CN111288910A CN111288910A CN201911396628.7A CN201911396628A CN111288910A CN 111288910 A CN111288910 A CN 111288910A CN 201911396628 A CN201911396628 A CN 201911396628A CN 111288910 A CN111288910 A CN 111288910A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
- G01B11/165—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge by means of a grating deformed by the object
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61K—AUXILIARY EQUIPMENT SPECIALLY ADAPTED FOR RAILWAYS, NOT OTHERWISE PROVIDED FOR
- B61K9/00—Railway vehicle profile gauges; Detecting or indicating overheating of components; Apparatus on locomotives or cars to indicate bad track sections; General design of track recording vehicles
- B61K9/08—Measuring installations for surveying permanent way
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Abstract
The invention discloses a tramcar trapezoidal turnout deformation monitoring system, which comprises a deformation data measuring unit, a data acquisition unit and a management analysis early warning unit, wherein the deformation data measuring unit is used for measuring the deformation of a tramcar trapezoidal turnout; the deformation data measuring unit comprises fiber bragg grating sensors (4) and a camera device (5), the fiber bragg grating sensors (4) are arranged at the front ends and the roots of the stock rails (3) and the switch rails (3), the frog of the point rail (2) is in deformation coupling with each rail, and the camera devices (5) are arranged at the point rail (1) and the switch rail (1) respectively; the data acquisition unit comprises an optical fiber data transmission module (8), a bandwidth light source (6) and an optical fiber grating regulator (7), and the management analysis early warning unit comprises an image processing module (10) and a data processing module (11). The invention also discloses a deformation monitoring method for the tramcar trapezoidal turnout. The deformation monitoring system for the tramcar trapezoidal turnout provided by the invention fills the blank of tramcar trapezoidal turnout deformation monitoring and is comprehensive and accurate in monitoring.
Description
Technical Field
The invention belongs to the technical field of monitoring of a trapezoidal turnout, and particularly relates to a deformation monitoring system and method for the trapezoidal turnout of a tramcar.
Background
The tramcar has the advantages of low construction cost, low construction difficulty, energy conservation, environmental protection, road right sharing and the like, and is successfully applied to a plurality of cities and generally popularized. The trapezoidal turnout is a turnout combining a straight-strand steel rail and a plurality of curved-strand steel rails, can realize the function of multi-strand wire changing in a limited space, can guide a vehicle to each track in a short distance, and has the advantages of small occupied area and the like, thereby being widely applied in a tramcar base.
The state monitoring prior art of railway rail has had research, but does not have the monitoring system who specially aims at trapezoidal switch deformation at present yet, again because the complicated particularity of trapezoidal switch structure, less deformation will produce very big influence, consequently need design the deformation monitoring system who specially aims at trapezoidal switch to guarantee the security of vehicle operation.
Monitoring the state of the railway steel rail, wherein the common monitoring modes comprise a resistance strain gauge, a video image processing technology, infrared thermal imaging, vibration wire type testing, eddy current and the like, and stress monitoring, displacement monitoring and temperature monitoring are carried out; as shown in fig. 1, the trapezoidal turnout comprises a base rail, a switch rail, a curved rail and three split-center points, the structure is more delicate and complex, and the conventional monitoring mode cannot be adapted to the omnidirectional monitoring of the trapezoidal turnout.
Disclosure of Invention
Aiming at the defects or the improvement requirements in the prior art, the invention provides a deformation monitoring system and a method for a tramcar trapezoidal turnout, wherein a deformation data monitoring system is arranged, fiber bragg grating sensors are arranged on a stock rail, the front end of a switch rail, the root of the switch rail and a point rail frog of the trapezoidal turnout and are coupled with all rails, camera devices are arranged in the areas of the point rail and the switch rail, and the rails are segmented according to shapes and are respectively monitored so as to meet the complexity of the trapezoidal turnout; the data acquisition unit is arranged to transmit the data monitored by the deformation data monitoring system, the management and analysis unit is arranged to process the image shot by the camera device and the information acquired by the fiber bragg grating sensor to obtain the deformation corresponding to each track, so that the deformation of the stock rail, the point rail and the switch rail of the trapezoidal turnout can be comprehensively and accurately monitored.
In order to achieve the purpose, the invention provides a deformation monitoring system for a tramcar trapezoidal turnout, wherein the trapezoidal turnout comprises a switch rail, a point rail and a stock rail, and comprises a deformation data measuring unit, a data acquisition unit and a management analysis early warning unit;
the deformation data measuring unit comprises fiber bragg grating sensors and a plurality of camera devices, the fiber bragg grating sensors are arranged at the front ends and the roots of the stock rails and the switch rails and at the frog positions of the point rails and are in deformation coupling with the rails, and the camera devices are respectively arranged at the point rails and the switch rails;
the data acquisition unit comprises an optical fiber data transmission module, a bandwidth light source in bidirectional connection with the optical fiber grating sensor and an optical fiber grating regulator connected with the bandwidth light source, one end of the optical fiber data transmission module is connected with the optical fiber grating regulator and the camera device, and the other end of the optical fiber data transmission module is connected with the management analysis early warning unit;
the management analysis early warning unit comprises an image processing module and a data processing module, the image processing module is used for processing the image shot by the camera device to obtain the deformation, and the data processing module is used for processing the information detected by the fiber grating sensor to obtain the deformation.
Furthermore, the image processing module comprises a pixel point position extraction module, a deformation calculation module and an image mixing weighting module;
the pixel point position extraction module is used for establishing a coordinate system and extracting the position of each pixel point in the picture;
the image mixing and weighting module is used for screening a plurality of continuously shot pictures and weighting and averaging the pictures;
the deformation measuring and calculating module is used for obtaining the deformation by utilizing the position relation of the same pixel point of the two pictures at a time interval.
Further, the image processing module comprises an image screening module, an image cutting and extracting module and an image superposition comparison module;
the image screening module is used for deleting images with poor definition or large angle deviation and classifying photos with the same angle into one type;
the image cutting and extracting module is used for establishing the same coordinate system for the same type of photos, extracting the parameters of each pixel point and drawing a corresponding two-dimensional plane graph;
the image registration comparison module is used for comparing two-dimensional plane images corresponding to two same type of photos at intervals, and completing comparison of a plurality of different two-dimensional planes to obtain corresponding deformation.
Furthermore, the management analysis early warning module also comprises an early warning module which is pre-stored with threshold values corresponding to all deformation quantities, and the early warning module is used for receiving the detected deformation data, comparing the detected deformation data with the pre-stored threshold values and giving out early warning when the threshold values are exceeded.
Furthermore, the camera device is an angle and height adjustable device, and a control module connected with the management analysis early warning unit is arranged on the camera device.
Furthermore, the plurality of optical fiber sensors distributed at the front ends and the roots of the stock rails, the switch rails and the point rail frog are all arranged in parallel.
In another aspect of the invention, there is provided a method for monitoring deformation of a tramcar trapezoidal switch, characterized in that,
inputting a threshold value of deformation corresponding to each position of a trapezoidal turnout in an S1 early warning module;
s2, arranging a fiber bragg grating sensor and a camera device;
s3, acquiring deformation data of the trapezoidal turnout by using the fiber bragg grating sensor and the high-definition camera;
and S4, processing the information shot by the camera and the information detected by the fiber grating sensor by using an image processing module and a data processing module to obtain deformation data of each track.
Further, step S4 specifically includes:
s41, extracting pixel points on the photo, and determining the positions of the pixel points: establishing coordinate pixels (x) centered on the position of a defined point on the target to be markedi，yi，zi) I is 0, 1,2,3,4 … … n, i corresponds to different pixel points;
s42, eliminating pixel point values with larger errors and then calculating weighted average value to obtain coordinate positions (x ') of corresponding pixel points'i，y′i，z′i)；
S43 extracting the position of each pixel point after the interval time T, and determining the position (x) of each pixel point after movementti，yti，zti)；
S44, weighting and averaging the moving positions of the pixels after the interval time T to obtain the coordinate position (x ') after the corresponding pixel time interval T'ti，y′ti，z′ti)；
S45 obtaining the deformation of each pixel including displacement, inclination angle and bending degree
Using formulas
Calculating the displacement of pixel point in three-dimensional space by using formula
The displacement amount in each direction is calculated, and the inclination angle or the degree of curvature can be calculated from the established coordinate system and the displacement amount in each direction.
Further, step S4 specifically includes:
s41, deleting the photos with larger shooting angle deviation or poorer definition from the photos, classifying the photos with the same angle into one class and marking serial numbers;
s42, establishing the same coordinate system for the same type of photo, extracting the information of each pixel point in the photo, and drawing a plurality of two-dimensional plane graphs corresponding to each structure or pixel point;
s43, the two images of the same two-dimensional plane which belong to the same class at intervals are superposed and compared to obtain the displacement in the direction, the two corresponding images of other two-dimensional planes are compared in the same way, and the deformation conditions such as inclination angle or bending can be obtained through the comparison data of two or more different two-dimensional planes.
Further, a marking target is set in a visual field range of the image pickup device, and the marking target is used as a reference point.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) the deformation monitoring system for the tramcar trapezoidal turnout is provided with a deformation data monitoring system, fiber bragg grating sensors are arranged on a stock rail, the front end of a switch rail, the root of the switch rail and a point rail frog of the trapezoidal turnout and are coupled with various rails, a camera device is arranged in the areas of the point rail and the switch rail, and the rails are segmented according to shapes and are respectively monitored so as to meet the complexity of the trapezoidal turnout; the data acquisition unit is arranged to transmit the data monitored by the deformation data monitoring system, the management and analysis unit is arranged to process the image shot by the camera device and the information acquired by the fiber bragg grating sensor to obtain the deformation corresponding to each track, so that the deformation of the stock rail, the point rail and the switch rail of the trapezoidal turnout can be comprehensively and accurately monitored.
Drawings
FIG. 1 is a schematic structural diagram of a trapezoidal switch;
FIG. 2 is a schematic diagram showing the distribution positions of monitoring components in a deformation data measuring unit according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a trapezoidal turnout deformation monitoring system in an embodiment of the invention;
fig. 4 is a schematic structural diagram of an image processing module in an embodiment of the present invention.
In all the figures, the same reference numerals denote the same features, in particular: the system comprises a point rail 1, a point rail 2, a point rail 3, a stock rail 4, a fiber bragg grating sensor 5, a camera device 6, a bandwidth light source 7, a fiber bragg grating regulator 8, a data transmission module 9, a storage module 9, an image processing module 10, a data processing module 11 and an early warning module 12.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Fig. 2 is a schematic diagram of the distribution positions of monitoring components in a deformation data measuring unit according to an embodiment of the present invention. Fig. 3 is a schematic structural diagram of a trapezoidal turnout deformation monitoring system in the embodiment of the invention. As shown in fig. 2 and 3, the monitoring system of the present invention includes a deformation data measuring unit, a data collecting unit, and a management, analysis and early warning unit, wherein the deformation data measuring unit includes a fiber grating sensor 4, a camera 5, and a marking target.
The fiber bragg grating sensors 4 are arranged at the positions of the stock rail, the front end of the switch rail, the root of the switch rail and the frog of the point rail and are in deformation coupling with the stock rail, the front end of the switch rail, the root of the switch rail and the frog of the point rail, and the fiber bragg grating sensors 4 are used for measuring the internal strain and small displacement deformation of the rail; and the optical fiber sensors 4 distributed at the stock rail, the front end of the switch rail, the root of the switch rail and the frog of the point rail are arranged in parallel, are independent and do not interfere with each other.
The camera device 5 is arranged in the point rail and point rail areas, preferably, the camera device 5 is a high-definition camera, and the high-definition camera measures large deformation of the point rail and the point rail in the turnout area, such as the stretching amount, the bending or inclination angle of the point rail, the displacement of the point rail and the like by utilizing a video sensing technology and an image processing technology. The marking target is matched with the high-definition camera and arranged in the lens range of the high-definition camera, at least one marking target is correspondingly arranged on each high-definition camera, and the marking target is used as a reference point for analyzing the deformation of the switch rail or the point rail. Preferably, the marking target is a structure fixed on the ground or on the rail, or is only a mark, or other reference object which is already present, as long as the reference object can be used for measuring the deformation of the point rail or the point rail.
Preferably, the camera device 5 is an angle and height adjustable device, a control module is arranged on the camera device 5, the control module is connected with the management analysis early warning unit, and the height and the angle of the camera device 5 are controlled and adjusted through the management analysis early warning unit.
The data acquisition unit comprises a broadband light source 6, a fiber bragg grating regulator 7, a data transmission module 8 and a storage module 9. The broadband light source 6 is connected with the fiber grating sensor 4 in a two-way mode, two transmission optical fibers are arranged between the broadband light source 6 and the fiber grating sensor 4, light emitted by the broadband light source 6 is transmitted to the fiber grating sensor 4 through the transmission optical fibers, incident light is reflected after encountering the fiber grating sensor 4 and then transmitted back to the collection center after being reflected, and the light is adjusted by the fiber grating adjusting instrument 7.
The fiber grating regulator 7 is connected with the data transmission module 8, and the fiber grating regulator 7 transmits the information transmitted back by the fiber grating sensor 4 to the data transmission module 8; the image pickup device 5 is connected to the data transmission module 8, and the image picked up by the image pickup device 5 is transmitted to the data transmission module 8. The storage unit 9 is used for being connected with the data transmission module, storing data monitored by the fiber grating sensor 4 and the high-definition camera 5, and backing up the data.
The management analysis early warning unit comprises an image processing module 10, a data processing module 11 and an early warning module 12, and the data transmission module 8 is connected with the image processing module 10 and the data processing module 11. The data transmission module 8 directly transmits the information monitored by the fiber grating regulator 7 to the data processing module 11, and transmits the image shot by the high-definition camera 5 to the image processing module 10 for processing. Deformation data of stock rails, switch rails or point rails, which are obtained after the image processing module 10 is processed, are transmitted to the early warning module 12, threshold values corresponding to all deformation quantities are prestored in the early warning module 12, and when the actually monitored deformation data received by the early warning module 12 is larger than or equal to the corresponding threshold values, the early warning module 12 gives out early warning.
Example 1:
the image processing module 10 comprises a pixel point position extraction module 101, a deformation amount calculation module 102 and an image mixing weighting module 103, the camera device 5 shoots a video or continuously shoots more than 10 pictures, the continuous shooting frequency is more than 100 times/second, if the shot video is, the image processing module 10 firstly captures the video and intercepts a plurality of pictures with the time interval within 0.1 second;
the pixel point position extraction module 101 is configured to find a plurality of pixel points on the photo, and determine a position corresponding to each pixel point on the photo: establishing coordinate pixel (x) by using the position of the determined point on the marked target as a central point (0,0)i，yi，zi) Wherein, i is 0, 1,2,3,4 … … n, i corresponds to different pixel points. And determining the positions of corresponding pixel points of a plurality of continuous photos or a plurality of photos intercepted within 0.1 second by adopting the mode, wherein the determined points of the marking targets of the plurality of photos are the same, and the corresponding serial numbers i of the same pixel point on each photo are the same, so that the coordinate position of each pixel point on each photo is obtained.
Image mixingThe co-weighting module 103 weights and averages the coordinate position of each pixel point in the plurality of photos, preferably, eliminates the pixel point value with a larger error and then averages the pixel point values to obtain the coordinate position (x ') of the corresponding pixel point'i，y′i，z′i) The method and the device avoid measuring errors caused by the influence of a camera or other factors in the shooting process of the camera device, and improve the detection precision.
The pixel point position extraction module 101 extracts the position of each pixel point corresponding to the interval time T, and determines the position (x) of each pixel point after movement by using the position of the same mark target determination point as a central pointti，yti，zti) The image blending weighting module 103 performs weighting averaging on the moving positions of the pixels after the interval time T to obtain a coordinate position (x ') after the corresponding pixel time interval T'ti，y′ti，z′ti)。
The deformation measurement and calculation module 102 processes the position information of each pixel point processed by the pixel point position extraction module 101 and the image mixing and weighting module 103: using formulas
Calculating the displacement of pixel point in three-dimensional space by using formula
The displacement in each direction is calculated, and the deformation such as the inclination angle or the degree of bending can be calculated from the established coordinate system and the displacement in each direction.
Example 2:
the image processing module 10 comprises an image screening module 104, an image cutting and extracting module 105 and an image superposition comparison module 106, the high-definition camera 5 continuously takes pictures or continuous videos at a frequency of more than 100 times/second, the image screening module 104 comprises an image screen capturing element and an image screening element, the image screen capturing element captures the videos, the image screening element is used for deleting images with large shooting angle deviation or poor definition in the pictures, and meanwhile, the image screening element classifies the pictures with the same angle into one class and marks serial numbers.
The image cutting and extracting module 105 extracts information of the photos screened by the image screening element, the image cutting and extracting module 105 establishes the same coordinate system for the photos of the same type, and extracts parameters of each pixel point in the coordinate system, so that a plurality of two-dimensional plane graphs corresponding to each structure are drawn, and the process is similar to the process of cutting a section of a three-dimensional graph.
The image registration comparison module 106 performs registration comparison on two images of the same two-dimensional plane belonging to the same class at the interval time T, compares two corresponding images of other two-dimensional planes in the same way, can read out displacement in the corresponding direction intuitively through comparison, and can obtain deformation conditions such as an inclination angle or bending through comparison data of two or more different two-dimensional planes.
The invention also provides a method for monitoring the deformation of the trapezoidal turnout of the tramcar, which comprises the following specific steps of:
the method comprises the steps that threshold values of deformation amounts corresponding to all positions of a trapezoidal turnout are input in an S1 early warning module, wherein the threshold values correspond to extension amounts, bending or inclination angles of a stock rail, a front end of a switch rail, a rear end of the switch rail and a point rail;
s2 arranging the fiber grating sensor 4 and the image pickup device 5
Arranging a plurality of fiber bragg grating sensors 4 at the stock rail, the front end of the switch rail, the root of the switch rail and the frog of the point rail, coupling the fiber bragg gratings with deformation of each part, and measuring internal strain and small displacement deformation of the rail through the fiber bragg grating sensors 4; preferably, the fiber grating sensors 4 at all positions are arranged in parallel, and are independent from each other and do not interfere with each other;
arranging the camera device 5 in the area of the point rail and the point rail, adjusting the angle and the height of the camera device 5, and preferably arranging a marking target in the visual field range of the camera device 5, wherein the marking target is used as a reference point;
s3 fiber bragg grating sensor 4 and high-definition camera 5 collect deformation data of trapezoidal turnout
The broadband light source is turned on, light emitted by the broadband light source 6 is transmitted to the fiber bragg grating sensor 4 through the transmission optical fiber, incident light is reflected after encountering the fiber bragg grating sensor 4 and then transmitted back to the acquisition center, and the detected deformation data is transmitted to the data processing module through the data transmission module 8 after being adjusted by the fiber bragg grating adjusting instrument 7;
s4 processes the information captured by the imaging device (5) and the information detected by the fiber grating sensor 4 using the image processing module 10 and the data processing module 11, and obtains deformation data of each track.
The high-definition camera 5 transmits the shot video or picture to the image processing module 10 through the data transmission module 8, the image processing module 10 captures the video to obtain a plurality of captured pictures, and the image processing module 10 processes the pictures, and the specific steps are as follows:
example 1
S41, extracting pixel points on the photo, and determining the positions of the pixel points: establishing coordinate pixel (x) by using the position of the determined point on the marked target as a central point (0,0)i，yi，zi) And the determined points of the labeled targets of the plurality of photos are the same;
wherein, i is 0, 1,2,3,4 … … n, i corresponds to different pixel points, and the serial number i corresponding to the same pixel point on each photo is the same;
s42, eliminating pixel point values with larger errors and then calculating weighted average value to obtain coordinate positions (x ') of corresponding pixel points'i，y′i，z′i) The measuring error caused by the influence of a camera or other factors in the shooting process of the camera device is avoided, and the detection precision is improved;
s43 extracting the position of each pixel point after the interval time T, and determining the position (x) of each pixel point after movementti，yti，zti) Using the position of the same mark target determination point as a central point;
s44, weighting and averaging the moving positions of the pixels after the interval time T to obtain the coordinate position (x ') after the corresponding pixel time interval T'ti，y′ti，z′ti)；
S45 obtaining the deformation of each pixel including displacement, inclination angle and bending degree
Using formulas
Calculating the displacement of pixel point in three-dimensional space by using formula
The displacement amount in each direction is calculated, and the inclination angle or the degree of curvature can be calculated from the established coordinate system and the displacement amount in each direction.
Example 2
S41, deleting the photos with larger shooting angle deviation or poorer definition from the photos, classifying the photos with the same angle into one class and marking serial numbers;
s42, establishing the same coordinate system for the same type of photo, extracting the information of each pixel point in the photo, drawing a plurality of two-dimensional plane graphs corresponding to each structure or pixel point, wherein the process is similar to the process of cutting the section of a three-dimensional graph;
s43, the two graphs of the same two-dimensional plane belonging to the same class at the interval time T are superposed and compared to obtain the displacement in the direction, the two corresponding graphs of other two-dimensional planes are compared in the same way, and the deformation conditions such as inclination angle or bending can be obtained through the comparison data of two or more different two-dimensional planes.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A deformation monitoring system for a trapezoidal turnout of a tramcar comprises a switch rail (1), a point rail (2) and a stock rail (3), and is characterized by comprising a deformation data measuring unit, a data acquisition unit and a management analysis early warning unit;
the deformation data measuring unit comprises fiber bragg grating sensors (4) and a camera device (5), the fiber bragg grating sensors (4) are arranged at the front ends and the roots of the stock rails (3) and the switch rails (3), the frog of the point rail (2) and are in deformation coupling with the rails at each position, and the camera devices (5) are arranged at the point rail (1) and the switch rail (1) respectively;
the data acquisition unit comprises an optical fiber data transmission module (8), a bandwidth light source (6) in bidirectional connection with the optical fiber grating sensor (4), and an optical fiber grating regulator (7) connected with the bandwidth light source (6), one end of the optical fiber data transmission module (8) is connected with the optical fiber grating regulator (7) and the camera device (5), and the other end of the optical fiber data transmission module is connected with the management analysis early warning unit;
the management analysis early warning unit comprises an image processing module (10) and a data processing module (11), wherein the image processing module (10) is used for processing the image shot by the camera device (5) to obtain a deformation amount, and the data processing module (11) is used for processing the information detected by the fiber grating sensor (4) to obtain the deformation amount.
2. The tram trapezoidal turnout deformation monitoring system according to claim 1, wherein the image processing module (10) comprises a pixel point position extraction module (101), a deformation measurement and calculation module (102) and an image mixing and weighting module (103);
the pixel point position extraction module (101) is used for establishing a coordinate system and extracting the position of each pixel point in the picture;
the image mixing and weighting module (103) is used for screening a plurality of continuously shot photos and weighting and averaging the photos;
the deformation amount calculation module (102) is used for acquiring deformation amount by using the position relation of the same pixel point of the two photos at a certain time interval.
3. The tram trapezoidal switch deformation monitoring system according to claim 1, wherein the image processing module (10) comprises an image screening module (104), an image cutting and extracting module (105) and an image coincidence comparison module (106);
the image screening module (104) is used for deleting images with poor definition or large angle deviation and classifying the photos with the same angle into one class;
the image cutting and extracting module (105) is used for establishing the same coordinate system for the same type of photos, extracting the parameters of each pixel point and drawing a corresponding two-dimensional plane graph;
the image registration comparison module (106) is used for comparing two-dimensional plane images corresponding to two same type of photos at intervals, and completing comparison of a plurality of different two-dimensional planes to obtain corresponding deformation.
4. The deformation monitoring system for the tram trapezoid turnout according to any one of claims 1-3, wherein the management analysis early warning module further comprises an early warning module (12) pre-storing threshold values corresponding to all deformation quantities, and the early warning module (12) is used for receiving detected deformation data, comparing the detected deformation data with the pre-stored threshold values and giving out early warning when the threshold values are exceeded.
5. The tram trapezoidal turnout deformation monitoring system according to claim 4, wherein the camera device (5) is an angle and height adjustable device, and a control module connected with the management analysis early warning unit is arranged on the camera device (5).
6. A tram keystone switch deformation monitoring system according to claim 1 wherein several of said fiber optic sensors (4) distributed at the front and root of the stock rail (3), point rail (1) and point rail (2) frog are all arranged in parallel.
7. A method for monitoring the deformation of a tram trapezoidal turnout according to any one of claims 1 to 6,
inputting a threshold value of deformation corresponding to each position of a trapezoidal turnout in an S1 early warning module;
s2, arranging a fiber bragg grating sensor (4) and a camera device (5);
s3, acquiring deformation data of the trapezoidal turnout by using the fiber bragg grating sensor (4) and the high-definition camera (5);
s4, the information shot by the camera device (5) and the information detected by the fiber grating sensor (4) are processed by an image processing module (10) and a data processing module (11) to obtain deformation data of each track.
8. The method for monitoring the deformation of the trapezoidal turnout of the tram according to claim 7, wherein the step S4 specifically comprises the following steps:
s41, extracting pixel points on the photo, and determining the positions of the pixel points: establishing coordinate pixels (x) centered on the position of a defined point on the target to be markedi，yi，zi) I is 0, 1,2,3,4 … … n, i corresponds to different pixel points;
s42, eliminating pixel point values with larger errors and then calculating weighted average value to obtain coordinate positions (x ') of corresponding pixel points'i，y′i，z′i)；
S43 extracting the position of each pixel point after the interval time T, and determining the position (x) of each pixel point after movementti，yti，zti)；
S44, weighting and averaging the moving positions of the pixels after the interval time T to obtain the coordinate position (x ') after the corresponding pixel time interval T'ti，y’ti，z’ti)；
S45 obtaining the deformation of each pixel including displacement, inclination angle and bending degree
Using formulas
Calculating the displacement of pixel point in three-dimensional space by using formula
The displacement amount in each direction is calculated, and the inclination angle or the degree of curvature can be calculated from the established coordinate system and the displacement amount in each direction.
9. The method for monitoring the deformation of the trapezoidal turnout of the tram according to claim 7, wherein the step S4 specifically comprises the following steps:
s41, deleting the photos with larger shooting angle deviation or poorer definition from the photos, classifying the photos with the same angle into one class and marking serial numbers;
s42, establishing the same coordinate system for the same type of photo, extracting the information of each pixel point in the photo, and drawing a plurality of two-dimensional plane graphs corresponding to each structure or pixel point;
s43, the two images of the same two-dimensional plane which belong to the same class at intervals are superposed and compared to obtain the displacement in the direction, the two corresponding images of other two-dimensional planes are compared in the same way, and the deformation conditions such as inclination angle or bending can be obtained through the comparison data of two or more different two-dimensional planes.
10. The method for monitoring the deformation of the trapezoidal turnout of the tram according to claim 7, wherein a marking target is arranged in the visual field range of the camera device (5) and is marked as a reference point.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111532311A (en) * | 2020-06-18 | 2020-08-14 | 北交智汇千路(北京)科技有限公司 | Railway turnout monitoring system device with optical fiber sensor and AI image recognition linkage |
| CN111572590A (en) * | 2020-06-01 | 2020-08-25 | 王正位 | Dynamic monitoring device for high-speed railway track condition |
| CN112411281A (en) * | 2020-11-20 | 2021-02-26 | 中铁宝桥集团有限公司 | Switch service state intelligent detection system and device |
| CN114379606A (en) * | 2022-01-11 | 2022-04-22 | 中铁第四勘察设计院集团有限公司 | High-speed magnetic levitation track comprehensive detection vehicle |
| CN114485787A (en) * | 2022-01-11 | 2022-05-13 | 中铁第四勘察设计院集团有限公司 | Multi-sensor information fusion high-speed magnetic suspension turnout real-time monitoring system |
| CN114518295A (en) * | 2020-11-19 | 2022-05-20 | 中车株洲电力机车研究所有限公司 | Tower load measuring method, device and system |
| CN115447640A (en) * | 2022-08-09 | 2022-12-09 | 中国国家铁路集团有限公司 | Method and device for recognizing geometric tiny changes of track in turnout area |
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2019
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111572590A (en) * | 2020-06-01 | 2020-08-25 | 王正位 | Dynamic monitoring device for high-speed railway track condition |
| CN111572590B (en) * | 2020-06-01 | 2021-11-02 | 郑州铁路职业技术学院 | Dynamic monitoring device for high-speed railway track condition |
| CN111532311A (en) * | 2020-06-18 | 2020-08-14 | 北交智汇千路(北京)科技有限公司 | Railway turnout monitoring system device with optical fiber sensor and AI image recognition linkage |
| CN114518295A (en) * | 2020-11-19 | 2022-05-20 | 中车株洲电力机车研究所有限公司 | Tower load measuring method, device and system |
| CN112411281A (en) * | 2020-11-20 | 2021-02-26 | 中铁宝桥集团有限公司 | Switch service state intelligent detection system and device |
| CN114379606A (en) * | 2022-01-11 | 2022-04-22 | 中铁第四勘察设计院集团有限公司 | High-speed magnetic levitation track comprehensive detection vehicle |
| CN114485787A (en) * | 2022-01-11 | 2022-05-13 | 中铁第四勘察设计院集团有限公司 | Multi-sensor information fusion high-speed magnetic suspension turnout real-time monitoring system |
| CN115447640A (en) * | 2022-08-09 | 2022-12-09 | 中国国家铁路集团有限公司 | Method and device for recognizing geometric tiny changes of track in turnout area |
| CN115447640B (en) * | 2022-08-09 | 2024-03-12 | 中国国家铁路集团有限公司 | Method and device for identifying geometric minor changes of track in turnout area |
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