CN113959347A - Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle - Google Patents
Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle Download PDFInfo
- Publication number
- CN113959347A CN113959347A CN202110912045.6A CN202110912045A CN113959347A CN 113959347 A CN113959347 A CN 113959347A CN 202110912045 A CN202110912045 A CN 202110912045A CN 113959347 A CN113959347 A CN 113959347A
- Authority
- CN
- China
- Prior art keywords
- grid
- floor
- grid line
- vehicle
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000005259 measurement Methods 0.000 claims abstract description 16
- 238000002360 preparation method Methods 0.000 claims abstract description 12
- 239000004065 semiconductor Substances 0.000 claims description 18
- 238000001514 detection method Methods 0.000 claims description 16
- 238000004458 analytical method Methods 0.000 claims description 12
- 238000009434 installation Methods 0.000 claims description 9
- 238000003556 assay Methods 0.000 claims 1
- 239000000463 material Substances 0.000 abstract description 5
- 229910052782 aluminium Inorganic materials 0.000 description 11
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 11
- 239000004411 aluminium Substances 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 210000001503 joint Anatomy 0.000 description 2
- 238000003754 machining Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003292 glue Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000003466 welding Methods 0.000 description 1
Images
Classifications
-
- 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
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30252—Vehicle exterior; Vicinity of vehicle
Abstract
The invention discloses a method and a system for analyzing the thickness of a floor rubber pad suitable for a metro vehicle, wherein the method comprises the following steps: projecting grid lines to a standard plane, movably acquiring grid line images of all areas on the standard plane, and calibrating initial phase data of each grid line intersection; projecting grid lines with the same parameters to the surface of a vehicle floor to be measured, movably collecting the grid line image, and calculating the actual phase data of each grid intersection point; calculating the height value of each grid intersection point according to the actual phase data and the initial phase data, and performing surface fitting based on the height value to obtain surface type data of the surface of the vehicle floor to be measured; and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved. According to the invention, height data of the rubber gasket to be padded on the surface of the vehicle underframe can be obtained through mobile measurement, so that the thickness of the rubber gasket to be padded can be calculated, and a rubber gasket material preparation table can be conveniently and automatically generated.
Description
Technical Field
The invention relates to the technical field of rail vehicle part detection, in particular to a method and a system for analyzing the thickness of a floor rubber pad suitable for a metro vehicle.
Background
The subway vehicle body is formed by welding a plurality of metal, and in order to resist the deformation generated by the gravity when the vehicle runs in full load, a certain upward bending deformation needs to be reserved on the underframe of the vehicle body to form prestress. When the vehicle is assembled, a rubber pad is paved on the upper surface of the underframe of the vehicle body and is used as a carrier for paving the aluminum honeycomb floor. The aluminum honeycomb floor is generally 2 meters long and is supported by a rubber pad. Because the chassis is the flexion curved surface, the height of each rubber cushion block on the chassis is different, consequently must confirm the height of rubber pad according to chassis curved surface face type, and the butt joint is neat when guaranteeing the aluminium honeycomb panel bedding, guarantees the smooth-going nature of floor glue of laying afterwards, and the aluminium honeycomb panel mutually noninterfere is crowded mutually when guaranteeing simultaneously to be full-loaded. Therefore, before laying the aluminum honeycomb floor, the thickness of the aluminum honeycomb floor at the supporting cushion block needs to be measured so as to pad rubber cushion blocks with different compensation thickness values.
The existing measuring technology for the flatness of the vehicle underframe has the defect of low precision.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention aims to provide a method and a system for analyzing the thickness of a floor rubber pad suitable for a subway vehicle, which can obtain height data of a rubber pad to be padded on the surface of a vehicle underframe through mobile measurement, further calculate the thickness of the rubber pad to be padded and conveniently and automatically generate a rubber pad material preparation table.
The technical scheme adopted by the invention is as follows: a floor rubber pad thickness analysis method suitable for metro vehicles comprises the following steps:
selecting a standard plane with the same height according to a reference plane where a vehicle floor to be detected is located;
projecting grid lines to the standard plane, and movably collecting grid line images of all areas on the standard plane;
calibrating initial phase data of each grid line intersection point according to the collected grid line image on the standard plane;
projecting grid lines with the same parameters to the surface of the vehicle floor to be detected, and movably collecting grid line images of all areas on the surface of the vehicle floor to be detected;
calculating actual phase data of each grid intersection point according to the collected grid line image on the surface of the floor of the vehicle to be measured;
calculating the height value of each grid intersection point according to the actual phase data and the initial phase data;
performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured;
and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
Optionally, the method further comprises: generating a stock preparation table for automatically installing the rubber pads according to the positions of the rubber pads to be padded and the thicknesses of the rubber pads to be padded at the corresponding positions, and recording the parameters of the rubber pads at the installation positions in the stock preparation table in sequence according to the installation sequence. And the automatic rubber pad installation can be realized by computer control according to the stock preparation table information.
Optionally, the method of the invention respectively collects the grid line images of all areas on the standard plane and the surface of the vehicle floor to be measured in a moving manner by using the cameras with the same parameters;
the calibration method for the camera parameters comprises the following steps:
projecting a grid line image with the same parameters as the actual detection process to the standard plane;
measuring the longitudinal and transverse intervals of the grid line images on the standard plane;
acquiring a grid line image on a standard plane through a camera;
and calibrating the focal length and the image magnification of the camera lens according to the measured data and the acquired grid line image data.
Optionally, the calibration process of the camera parameter and the calibration process of the initial phase data of the grid line intersection are performed simultaneously.
Optionally, in the method of the present invention, based on the height values of the grid intersections, a moving least square Method (MLS) is used to perform surface fitting, so as to obtain surface profile data of the surface of the vehicle floor to be measured.
In another aspect, the present invention provides an analysis system using the method for analyzing thickness of floor rubber mat, comprising: a controller and a detection mechanism; the detection mechanism comprises a bracket and a measuring unit;
the support comprises a support and a measuring arm, a sliding driving mechanism is mounted on the measuring arm, the measuring unit is mounted on the measuring arm in a sliding mode, the sliding driving mechanism is connected with the measuring unit in a driving mode, and the control end of the sliding driving mechanism is connected with a controller;
the measuring unit comprises a laser grid projector and an image collector; the control end of the laser grid projector and the output end of the image collector are respectively connected with the controller;
the controller controls the measuring unit to move on the measuring arm through the sliding driving mechanism, so that a laser grid projector in the measuring unit projects grid lines to the surface of the floor of the vehicle to be measured, and the image collector collects grid line images;
the controller carries out image splicing on the grid line image data collected by the image collector according to the slippage control parameters of the slippage driving mechanism to obtain a full-area grid line image of the surface of the floor of the vehicle to be detected;
the controller calculates actual phase data of each grid intersection point based on pre-calibrated grid line parameters and camera parameters according to the full-area grid line image; calculating the height value of each grid intersection point according to the actual phase data and the pre-calibrated initial phase data; performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured; and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
Optionally, a sliding groove is formed in the measuring arm, the measuring unit is fixedly arranged on a mounting seat, and a sliding block adapted to the sliding groove is arranged on the mounting seat. The sliding block slides on the sliding groove of the measuring arm, so that the measuring unit can move, the whole vehicle body bottom plate is subjected to moving image acquisition, and images of all floor surfaces are obtained.
Optionally, the measuring arm is a telescopic arm or a foldable structure. The length of the measuring arm is variable, so that the detection mechanism can adapt to different lengths of the vehicle body to be detected.
Optionally, the laser grid projector adopts a semiconductor laser grid projector, and is configured with a two-dimensional phase type diffraction grating and a red light semiconductor laser module, wherein the grating constant of the two-dimensional phase type diffraction grating is 500 lines/mm, and the wavelength of the red light semiconductor laser module is 635 nm;
the image collector adopts a gigabit network industrial CMOS camera with 2592 multiplied by 2048 pixels, the pixel size is 4.8 multiplied by 4.8 mu m, a 6mm focal length industrial camera lens is configured, and an interference filter is arranged in front of the camera lens and matched with the wavelength and the bandwidth of the semiconductor laser grid projector. An interference filter matched with the wavelength and the bandwidth of the semiconductor laser is arranged in front of the lens so as to greatly reduce the influence of the ambient background light. Different vehicle types have different requirements on the row-column spacing of the rubber pad, and the grating parameters of the two-dimensional phase type diffraction grating are calculated by a diffraction theory.
Optionally, in the measurement unit, two CMOS cameras are respectively disposed on two sides of the laser grid projector, and the viewing directions of the two CMOS cameras are respectively inclined to one side of the laser grid projector by a set angle;
the measuring range of a single CMOS camera is 2.4m multiplied by 3.1m in length, and a semiconductor laser grid projector projects 0.4m multiplied by 0.4m equidistant laser grid lines.
Advantageous effects
The method and the system can realize mobile measurement to obtain height data of the rubber mat to be padded on the surface of the vehicle underframe, further can calculate the thickness of the rubber mat to be padded, and in the measuring process, the image collector can continuously and stably collect the grid line image on the surface of the floor to be padded under the calibrated height, so that the reliability of the image collecting result can be ensured, the accuracy of the surface type calculating result of the vehicle floor to be padded is ensured, the rubber cushion block with proper thickness is obtained, the butt joint is neat when the aluminum honeycomb floor is laid, and the aluminum honeycomb plates are prevented from being interfered with each other and extruded when the aluminum honeycomb floor is fully loaded.
Meanwhile, after calibration, the detection system can automatically measure the surface type of the underframe of the railway vehicle body, has short detection process time, convenient operation and accurate result, and can further generate a floor rubber pad material preparation table for feeding in the subsequent automatic laying process of the floor rubber pads.
Drawings
FIG. 1 is a top view of an application structure of a rubber mat thickness detection system for a subway vehicle floor according to an embodiment of the present invention;
FIG. 2 is a side view of FIG. 1;
in the figure: 1. a semiconductor laser grid projector; 2. a CMOS camera; 3. a measuring arm; 4. a mounting seat; 5. a supporting seat; 6. a vehicle body to be tested; 7. and (4) a support.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
Example 1
The present embodiment describes an analysis system for a method for analyzing the thickness of a floor rubber mat, and referring to fig. 1 and 2, the system includes a controller and a detection mechanism; the detection mechanism comprises a bracket and a measuring unit; the support comprises a support 7 and a measuring arm 3, a sliding driving mechanism is installed on the measuring arm, the measuring unit is installed on the measuring arm in a sliding mode, the sliding driving mechanism is connected with the measuring unit in a driving mode, and the control end of the sliding driving mechanism is connected with a controller.
The measuring unit comprises a laser grid projector 1 and an image collector 2; the control end of the laser grid projector and the output end of the image collector are respectively connected with the controller;
the controller controls the measuring unit to move on the measuring arm through the sliding driving mechanism, and controls the laser grid projector in the measuring unit to project grid lines to the surface of the floor of the vehicle to be measured in the moving process, and the image collector collects grid line images;
the controller carries out image splicing on the grid line image data collected by the image collector according to the slippage control parameters of the slippage driving mechanism to obtain a full-area grid line image of the surface of the floor of the vehicle to be detected;
the controller calculates actual phase data of each grid intersection point based on pre-calibrated grid line parameters and camera parameters according to the full-area grid line image; calculating the height value of each grid intersection point according to the actual phase data and the pre-calibrated initial phase data; performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured; and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
Furthermore, in this embodiment, a sliding groove is formed on the measuring arm, the measuring unit is fixedly mounted on a mounting seat 4, and a sliding block adapted to the sliding groove is formed on the mounting seat. The sliding of the mounting on the measuring arm can also be achieved by means of other types of guide rails.
For the vehicle that awaits measuring that can adapt to different length, the convenient storage of measuring rack simultaneously, in this embodiment, the measuring arm can set up to telescopic boom or beta structure.
The sliding drive of the sliding drive mechanism can adopt the existing drive forms of a pneumatic system, motor screw rod matching and the like, the controller can adopt an industrial control computer to control the mounting seat to move according to a preset step pitch or continuously move at a set speed, and then the controller can realize the splicing of the collected images according to the control parameters of the sliding drive mechanism, and the image splicing technology can also adopt the prior art.
In this embodiment, in the measurement unit, two sides of the laser grid projector are respectively provided with one image collector, and the viewing directions of the two image collectors are respectively inclined towards one side of the laser grid projector by a set angle. The reliability of the image acquisition and analysis results can be further improved by the arrangement of the multiple cameras.
The laser grid projector adopts a semiconductor laser grid projector, and is provided with a two-dimensional phase type diffraction grating and a red light semiconductor laser module, wherein the grating constant of the two-dimensional phase type diffraction grating is 500 lines/mm, and the wavelength of the red light semiconductor laser module is 635 nm; the image collector adopts a gigabit network industrial CMOS camera with 2592 multiplied by 2048 pixels, the pixel size is 4.8 multiplied by 4.8 mu m, a 6mm focal length industrial camera lens is configured, and an interference filter is arranged in front of the camera lens and matched with the wavelength and the bandwidth of the semiconductor laser grid projector.
The measuring range of a single CMOS camera is 2.4m multiplied by 3.1m in length, and the semiconductor laser grid projector projects 0.4m multiplied by 0.4m equidistant laser grid lines, so that the method can be suitable for most sizes of subway vehicle floors.
The specific method for calculating the thickness of the floor rubber pad by using the analysis system of the embodiment can refer to embodiment 2.
Example 2
The embodiment introduces a method for analyzing the thickness of a floor rubber pad suitable for a metro vehicle, which can be realized by the analysis system of the embodiment 1, and the method comprises the following steps:
selecting a standard plane with the same height according to a reference plane where a vehicle floor to be detected is located;
projecting grid lines to the standard plane, and movably collecting grid line images of all areas on the standard plane;
calibrating initial phase data of each grid line intersection point according to the collected grid line image on the standard plane;
projecting grid lines with the same parameters to the surface of the vehicle floor to be detected, and movably collecting grid line images of all areas on the surface of the vehicle floor to be detected;
calculating actual phase data of each grid intersection point according to the collected grid line image on the surface of the floor of the vehicle to be measured;
calculating the height value of each grid intersection point according to the actual phase data and the initial phase data;
performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured;
and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
In order to accommodate the subsequent automatic rubber mat installation procedure which may be realized by computer control, the method of the embodiment may further include: generating a stock preparation table for automatically installing the rubber pads according to the positions of the rubber pads to be padded and the thicknesses of the rubber pads to be padded at the corresponding positions, and recording the parameters of the rubber pads at the installation positions in the stock preparation table in sequence according to the installation sequence.
In the embodiment, the cameras with the same parameters are used for respectively and movably acquiring grid line images of all areas on a standard plane and the surface of the floor of the vehicle to be detected; the calibration of camera parameters, the calibration of the analysis system support and the calibration of grid line image parameters can be performed simultaneously.
The calibration method for the camera parameters comprises the following steps:
projecting a grid line image with the same parameters as the actual detection process to the standard plane;
measuring the longitudinal and transverse intervals of the grid line images on the standard plane;
acquiring a grid line image on a standard plane through a camera;
and calibrating the focal length and the image magnification of the camera lens according to the measured data and the acquired grid line image data.
When calculating the curved surface type data of the floor surface of the vehicle to be measured based on the height values of the grid intersections, the present embodiment performs surface fitting by using a Moving Least Squares (MLS), and specifically relates to the following contents:
the Moving Least Squares (MLS) method, whose (one-dimensional) fitting equation is: f (x) p (x)T·a(x)
Wherein, p (x)i) For the selected basis function, a (x) is the coefficient to be selected, and has: a (x) ═ A-1(x)B(x)z
In the formula:
A(x,y)＝∑w(x-xi)p(xi)pT(xi)(i＝0,1,2,...,m-1)
B(x,y)＝[w(x-x1)p(x1),w(x-x2)p(x2),...,w(x-xn)p(xn)]
z＝[z1,z2,...,zn]T
wherein m is the number of measuring points; w (x-x)i) As a weight at the measurement point, z (x)i) The measured elevation at the measurement point.
p(xi) Take the quadratic basis function as follows:
p(x)＝[1,x,y,x2,xy,y2]T
wherein, yi＝y(xi) I.e. yiIs x ═ xiA node value of (d);
weight function w (x-x)i) Taking cubic spline function, and recording s as x-xi，s0＝s/smaxAnd then:
the prior art can be referred to for specific algorithm implementation of the surface fitting process by using a Moving Least Squares (MLS) method.
Example 3
Combining example 1 and example 2, the application of the present invention in the analysis of the thickness of a rubber mat on a vehicle floor involves the following steps.
And S1, selecting a precision machining standard plane, and hanging the precision machining standard plane on the four supporting seats 5 to be adjusted to be horizontal. And arranging the supports of the detection mechanism at two ends of a standard plane, erecting a measuring arm, and installing the installation seat of the measuring unit and the measuring unit.
S2, starting the semiconductor laser grid projector, projecting grid lines to the standard plane, and measuring the longitudinal and transverse intervals of the grid lines by using a steel tape; and starting the CMOS camera to acquire the grid line image, and determining parameters of the CMOS camera and other related parameters including the focal length and the magnification of a lens of the CMOS camera, the coordinates of the laser grid image and the like according to the measurement data and the image data acquired by the camera.
S3, initial phase calibration: controlling the measuring unit to move from one end of the standard plane to obtain a grid line image until the other end of the standard plane;
the movement process can have pause or continuous movement, the grid line images can be acquired during pause, or the grid line images are periodically acquired according to the movement speed during the movement process, then the images are spliced, and the initial phase of the grid intersection point is determined according to the spliced images.
In order to ensure the accuracy of the acquired images, there is an overlap of image areas between two adjacent acquired images.
S4, measurement sampling: and erecting the bottom plate of the vehicle body to be measured on the supporting seat in the S1, projecting grid lines to the surface of the floor of the vehicle body to be measured, and controlling the measuring unit to move along the measuring arm with the calibrated height from one end of the vehicle body to the other end of the vehicle body. Gridline images of the entire area of the floor surface are acquired during the movement.
S5, grid point height calculation: and calculating the positions of the grid line intersections in the grid line images acquired in the measurement sampling process according to the calibrated camera parameters, and comparing the positions with the calibrated initial phase data to obtain the phase change of the grid lines and the height values at the grid intersections.
A laser grid projector with a two-dimensional diffraction grating in a measuring unit projects two-dimensional orthogonal straight lines to a vehicle underframe to form a laser line grid, and 2 gigabit network industrial CMOS cameras image the vehicle underframe which projects the laser grid lines at a certain inclination angle. After the laser grid lines are imaged by the CMOS, the transverse spacing changes along with the surface fluctuation of the vehicle body underframe. And extracting and calculating the image coordinates of the grid intersections through image processing, and calculating the three-dimensional coordinates of the intersections according to the triangulation principle to obtain the heights of the intersections.
After the measurement is finished, the height data of each intersection point on the surface of the vehicle chassis can be obtained, and the discrete data of the surface type of the chassis can be obtained.
S6, calculating the surface fitting: and (4) performing Moving Least Square (MLS) fitting on the surface of the whole vehicle body underframe according to the discrete height data obtained in the step S5 to obtain surface type data of the upper surface of the vehicle body underframe, and calculating the thickness value of each rubber cushion block according to the vehicle type data and the length information of the aluminum honeycomb panel to form a stock preparation table.
After the detection mechanism is calibrated, the height of the support is kept fixed, the support is quickly erected at two ends of a vehicle body to be measured during measurement, the measurement unit is driven to move in sequence along the direction of the measurement arm by controlling the movement of the mounting seat, the whole vehicle measurement can be completed by moving one end of the vehicle body to the other end, and the thickness value and the material preparation table of the rubber pad at the rubber seat of the aluminum honeycomb panel can be directly given by a controller (an industrial control computer). Constructors prepare materials according to the table and directly install the rubber seat and the rubber pad. The measuring process is quick, and the operation is simple and convenient.
The above is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. The utility model provides a floor rubber pad thickness analysis method suitable for railcar, characterized by includes:
selecting a standard plane with the same height according to a reference plane where a vehicle floor to be detected is located;
projecting grid lines to the standard plane, and movably collecting grid line images of all areas on the standard plane;
calibrating initial phase data of each grid line intersection point according to the collected grid line image on the standard plane;
projecting grid lines with the same parameters to the surface of the vehicle floor to be detected, and movably collecting grid line images of all areas on the surface of the vehicle floor to be detected;
calculating actual phase data of each grid intersection point according to the collected grid line image on the surface of the floor of the vehicle to be measured;
calculating the height value of each grid intersection point according to the actual phase data and the initial phase data;
performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured;
and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
2. The method for analyzing the thickness of floor rubber mats according to claim 1, further comprising: generating a stock preparation table for automatically installing the rubber pads according to the positions of the rubber pads to be padded and the thicknesses of the rubber pads to be padded at the corresponding positions, and recording the parameters of the rubber pads at the installation positions in the stock preparation table in sequence according to the installation sequence.
3. The method for analyzing the thickness of the floor rubber pad as claimed in claim 1, wherein the cameras with the same parameters are used for respectively and movably acquiring grid line images of all areas on a standard plane and the surface of the floor of the vehicle to be measured;
the calibration method for the camera parameters comprises the following steps:
projecting a grid line image with the same parameters as the actual detection process to the standard plane;
measuring the longitudinal and transverse intervals of the grid line images on the standard plane;
acquiring a grid line image on a standard plane through a camera;
and calibrating the focal length and the image magnification of the camera lens according to the measured data and the acquired grid line image data.
4. The method of claim 3 wherein the calibration of the camera parameters and the calibration of the initial phase data at the intersection of the grid lines are performed simultaneously.
5. The method for analyzing the thickness of the floor rubber pad as claimed in claim 1, wherein the curved surface profile data of the floor surface of the vehicle to be measured is obtained by performing curved surface fitting using a Moving Least Squares (MLS) method based on the height values of the grid intersections.
6. An analysis system using the method for analyzing the thickness of floor rubber mats according to any one of claims 1 to 5, comprising: a controller and a detection mechanism; the detection mechanism comprises a bracket and a measuring unit;
the support comprises a support and a measuring arm, a sliding driving mechanism is mounted on the measuring arm, the measuring unit is mounted on the measuring arm in a sliding mode, the sliding driving mechanism is connected with the measuring unit in a driving mode, and the control end of the sliding driving mechanism is connected with a controller;
the measuring unit comprises a laser grid projector and an image collector; the control end of the laser grid projector and the output end of the image collector are respectively connected with the controller;
the controller controls the measuring unit to move on the measuring arm through the sliding driving mechanism, so that a laser grid projector in the measuring unit projects grid lines to the surface of the floor of the vehicle to be measured, and the image collector collects grid line images;
the controller carries out image splicing on the grid line image data collected by the image collector according to the slippage control parameters of the slippage driving mechanism to obtain a full-area grid line image of the surface of the floor of the vehicle to be detected;
the controller calculates actual phase data of each grid intersection point based on pre-calibrated grid line parameters and camera parameters according to the full-area grid line image; calculating the height value of each grid intersection point according to the actual phase data and the pre-calibrated initial phase data; performing surface fitting based on the height values of the grid intersections to obtain surface type data of the surface of the vehicle floor to be measured; and determining the position of each rubber gasket to be cushioned and the thickness of the rubber gasket to be cushioned at the corresponding position according to the curved surface type data and the size of the floor to be paved.
7. The analytical system of claim 6, wherein the measuring arm has a sliding slot, the measuring unit is fixed to a mounting base, and the mounting base has a sliding block adapted to the sliding slot.
8. An assay system as claimed in claim 6 or 7, wherein the measurement arm is a telescopic arm or a collapsible structure.
9. The analysis system of claim 6, wherein the laser grid projector is a semiconductor laser grid projector, and is configured with a two-dimensional phase type diffraction grating and a red semiconductor laser module, the grating constant of the two-dimensional phase type diffraction grating is 500 lines/mm, and the wavelength of the red semiconductor laser module is 635 nm;
the image collector adopts a gigabit network industrial CMOS camera with 2592 multiplied by 2048 pixels, the pixel size is 4.8 multiplied by 4.8 mu m, a 6mm focal length industrial camera lens is configured, and an interference filter is arranged in front of the camera lens and matched with the wavelength and the bandwidth of the semiconductor laser grid projector.
10. The analysis system of claim 9, wherein in the measuring unit, two CMOS cameras are respectively disposed at two sides of the laser grid projector, and the viewing directions of the two CMOS cameras are respectively inclined to one side of the laser grid projector by a set angle;
the measuring range of a single CMOS camera is 2.4m multiplied by 3.1m in length, and a semiconductor laser grid projector projects 0.4m multiplied by 0.4m equidistant laser grid lines.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110912045.6A CN113959347A (en) | 2021-08-10 | 2021-08-10 | Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110912045.6A CN113959347A (en) | 2021-08-10 | 2021-08-10 | Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113959347A true CN113959347A (en) | 2022-01-21 |
Family
ID=79460479
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110912045.6A Pending CN113959347A (en) | 2021-08-10 | 2021-08-10 | Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113959347A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117516395A (en) * | 2024-01-05 | 2024-02-06 | 常州新区盛晖针纺织品有限公司 | Detection device and detection method for blanket production |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1758020A (en) * | 2005-11-18 | 2006-04-12 | 北京航空航天大学 | Stereo vision detection system based on adaptive sine streak projection |
| CN101750017A (en) * | 2010-01-18 | 2010-06-23 | 战强 | Visual detection method of multi-movement target positions in large view field |
| CN102535316A (en) * | 2011-12-23 | 2012-07-04 | 同济大学 | Novel asphalt pavement damage comprehensive intelligent detecting vehicle |
| CN102798349A (en) * | 2011-05-24 | 2012-11-28 | 上海瑞伯德智能系统科技有限公司 | Three-dimensional surface extraction method based on equal-gray line search |
| CN103971353A (en) * | 2014-05-14 | 2014-08-06 | 大连理工大学 | Splicing method for measuring image data with large forgings assisted by lasers |
| CN206954227U (en) * | 2017-05-18 | 2018-02-02 | 武汉汉宁轨道交通技术有限公司 | Track plates detect car and system |
| US20180094918A1 (en) * | 2016-04-06 | 2018-04-05 | 4D Sensor Inc. | Measurement method, measurement apparatus, measurement program and computer readable recording medium in which measurement program has been recorded |
| CN110425998A (en) * | 2019-06-05 | 2019-11-08 | 中北大学 | The components three-dimensional measurement method of gray level image coupling feature point height |
| CN111981991A (en) * | 2020-08-20 | 2020-11-24 | 南京中车浦镇城轨车辆有限责任公司 | Method and system for obtaining compensation height of rail vehicle floor mounting seat |
| CN112669379A (en) * | 2020-12-22 | 2021-04-16 | 大连工业大学 | Image feature rapid extraction method based on auxiliary mark points |
-
2021
- 2021-08-10 CN CN202110912045.6A patent/CN113959347A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1758020A (en) * | 2005-11-18 | 2006-04-12 | 北京航空航天大学 | Stereo vision detection system based on adaptive sine streak projection |
| CN101750017A (en) * | 2010-01-18 | 2010-06-23 | 战强 | Visual detection method of multi-movement target positions in large view field |
| CN102798349A (en) * | 2011-05-24 | 2012-11-28 | 上海瑞伯德智能系统科技有限公司 | Three-dimensional surface extraction method based on equal-gray line search |
| CN102535316A (en) * | 2011-12-23 | 2012-07-04 | 同济大学 | Novel asphalt pavement damage comprehensive intelligent detecting vehicle |
| CN103971353A (en) * | 2014-05-14 | 2014-08-06 | 大连理工大学 | Splicing method for measuring image data with large forgings assisted by lasers |
| US20180094918A1 (en) * | 2016-04-06 | 2018-04-05 | 4D Sensor Inc. | Measurement method, measurement apparatus, measurement program and computer readable recording medium in which measurement program has been recorded |
| CN206954227U (en) * | 2017-05-18 | 2018-02-02 | 武汉汉宁轨道交通技术有限公司 | Track plates detect car and system |
| CN110425998A (en) * | 2019-06-05 | 2019-11-08 | 中北大学 | The components three-dimensional measurement method of gray level image coupling feature point height |
| CN111981991A (en) * | 2020-08-20 | 2020-11-24 | 南京中车浦镇城轨车辆有限责任公司 | Method and system for obtaining compensation height of rail vehicle floor mounting seat |
| CN112669379A (en) * | 2020-12-22 | 2021-04-16 | 大连工业大学 | Image feature rapid extraction method based on auxiliary mark points |
Non-Patent Citations (1)
| Title |
|---|
| 吴剑波, 骆清铭, 谭玉山: "网格投影式立体视觉三维表面重建系统", 光电工程, no. 11, 30 November 2004 (2004-11-30) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117516395A (en) * | 2024-01-05 | 2024-02-06 | 常州新区盛晖针纺织品有限公司 | Detection device and detection method for blanket production |
| CN117516395B (en) * | 2024-01-05 | 2024-03-22 | 常州新区盛晖针纺织品有限公司 | Detection device and detection method for blanket production |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110425977B (en) | Contact rail geometric parameter detection system and detection method | |
| CN203569401U (en) | Device for checking flatness of plate surface of track plate | |
| CN113959347A (en) | Method and system for analyzing thickness of floor rubber pad suitable for subway vehicle | |
| CN106289059B (en) | Bogie detection device | |
| CN110231347A (en) | A kind of bridge bottom surface detection device and method | |
| CN111830546A (en) | Outdoor railcar landmark deployment method | |
| CN103592190A (en) | Apparatus and method for precisely detecting Bauschinger effect of repeated bending of metal plate | |
| CN110986797B (en) | Vehicle compartment size and position measuring device and method of full-automatic bagged vehicle stacking machine | |
| CN115615338A (en) | Airplane complete machine horizontal measurement system and measurement method | |
| CN115307565A (en) | Device and method for monitoring deformation and displacement of bridge track | |
| JP5235458B2 (en) | Guideway side wall installation method, measurement system, adjustment system and installation system | |
| CN109239087B (en) | Image detection platform | |
| CN112977535B (en) | Electrified railway clearance detection method and system based on laser scanning | |
| JP2009221738A5 (en) | ||
| CN204461353U (en) | Based on the vehicle external profile Size Measuring System of three projecting plane principles | |
| CN112109765A (en) | Suspension type magnetic suspension track space structural member data acquisition system and judgment method | |
| CN104748688A (en) | Overall dimension measuring system of vehicle based on three projection plane theory | |
| KR102534613B1 (en) | Measurement device and method of rail acoustic roughness using the laser scanning | |
| CN112504173B (en) | Track irregularity measuring device and method based on laser profile scanning | |
| CN110174061B (en) | Positioning platform and method for silicon steel sheet measurement | |
| CN114001680A (en) | Vehicle side wall unevenness measuring device and measuring method | |
| CN209405534U (en) | Automatically scanning Water ball system positioning performance measuring device | |
| CN110440701A (en) | A kind of intelligent more curved surface detecting systems of rail vehicle and method | |
| CN113686244B (en) | Detection device | |
| CN217179519U (en) | Efficient intelligent detection equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |