CN110702423A - Dynamic stability analysis method and device for metro vehicle door system - Google Patents

Dynamic stability analysis method and device for metro vehicle door system Download PDF

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CN110702423A
CN110702423A CN201910903329.1A CN201910903329A CN110702423A CN 110702423 A CN110702423 A CN 110702423A CN 201910903329 A CN201910903329 A CN 201910903329A CN 110702423 A CN110702423 A CN 110702423A
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路绳方
陈烨
高阳
张嘉超
孟琳
焦良葆
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Nanjing Institute of Technology
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Abstract

The invention discloses a method and a device for analyzing the dynamic stability of a subway vehicle door system, which are characterized in that a binocular vision measurement system is used for solving the three-dimensional pose information of a dynamic target point generated by laser projection, the target point is formed by intersecting a laser light strip projected by a linear array laser and a vertical adhesive tape on a subway train door, the coordinate of the target point in an image is extracted by using an image processing algorithm, the three-dimensional reconstruction of the target point is realized according to the image coordinate, the dynamic running condition analysis of the vehicle door system is realized by adjusting and analyzing processing results at different moments, and the dynamic detection of the vehicle door system is completed. The invention has high measurement precision, strong portability and high reliability, effectively solves the online dynamic analysis of the stable running state of the metro vehicle door system, and has important significance for guaranteeing the safe operation of the metro and the life and property safety of passengers.

Description

Dynamic stability analysis method and device for metro vehicle door system
Technical Field
The invention relates to the technical field of computer vision measurement, in particular to a method and a device for analyzing dynamic stability of a metro vehicle door system.
Background
The subway train door system is an important component of a subway train. The subway train door system is frequently opened and closed in the operation of a subway train and is a high-frequency device contacted with passengers. The running stability of the vehicle door system reflects the health state of the vehicle door system, and the early warning and monitoring of the health state of the vehicle door system can be realized through the analysis of the dynamic stability of the vehicle door system, so that the system has important significance for ensuring the running safety of trains and the safety of lives and properties of passengers. The visual measurement has the characteristics of wide range, high precision, portability and the like, and is suitable for analyzing and monitoring the dynamic stability of the metro door system.
The subway vehicle door system relates to the technologies of mechanical power technology, control technology, information and the like, is a complex mechanical and electrical device integrating multiple technologies, and is easy to break down due to frequent opening and closing of subway doors, thereby causing driving failures and endangering the life and property safety of passengers under severe conditions. The monitoring of the door motion stability of the metro door system is a research content with great significance. At present, the analysis on the dynamic stability of the subway door system is not enough, so that a method and a device for analyzing the dynamic stability of the subway door system are urgently needed to realize the safety monitoring of the subway door system.
Disclosure of Invention
The purpose of the invention is as follows: the invention discloses a method and a device for analyzing the dynamic stability of a metro vehicle door system, and provides a method based on active visual analysis and a high-precision, low-cost and movable measuring device, aiming at the defects of the prior art in analyzing the dynamic stability of the metro vehicle door system and the requirements of the system dynamic measuring device.
The technical scheme is as follows: the invention discloses a dynamic stability analysis method of a metro vehicle door system, which comprises the following steps of:
step A, image acquisition: the method comprises the following steps that a laser light strip emitted by a laser device, the center line of the light strip and the edge of a vertical black adhesive tape at the door edge of a subway door form two intersection points, the intersection points are marked as target points, a camera in a binocular stereo vision measuring system is triggered and started to work at any time t in the opening or closing process of the door, and the images of the door with the laser light strip are respectively obtained;
b, sub-pixel extraction and fitting of a line equation: accurately extracting sub-pixels of the car door image with the laser light bars by using a Steger algorithm, wherein the sub-pixels comprise sub-pixel positions and edge directions of the light bar central lines, and fitting and solving linear equations of the light bar central lines in the two images respectively according to the extracted sub-pixel positions of the light bar central lines;
step C, solving the coordinates of the two target points in the image: b, solving a linear equation of the edges of the vertical black adhesive tapes on the two door edges of the train door in the two images by using Hough transformation, and solving coordinates of the two target points in the two images respectively by combining the linear equation of the light strip center line solved in the step B;
step D, initializing a binocular stereo vision measuring system: calibrating the binocular stereo vision measuring system according to the two images in the step A, and solving internal parameters and external structure parameters of the two cameras;
step E, finding two target points at time tDistance in three-dimensional space: in the binocular stereo vision measuring system, the result of camera calibration in the step D is combined, the three-dimensional reconstruction of two target points at the moment t can be respectively realized by the image coordinates of each target point in the step C in the binocular camera, and the three-dimensional distance D between the two target points at the moment t is obtainedt；
Step F, solving the distance between two target points at the time t + delta t in the actual three-dimensional space: at the time t + delta t of the opening or closing process of the vehicle door, according to the method in the step E, the three-dimensional distance d at the time t + delta t is obtainedt+Δt；
G, data processing and analysis: d obtained from step E and step FtAnd dt+ΔtCalculating the average speed of the vehicle door system in the delta t time
Figure BDA0002211252910000021
And average acceleration
Figure BDA0002211252910000022
Wherein the average velocity
Figure BDA0002211252910000023
Average acceleration
Figure BDA0002211252910000024
In the process time of opening and closing the train door, the instantaneous running speed and acceleration of the train door are reduced by adjusting the acquisition interval delta t of the camera image, and therefore the stability analysis of the dynamic running state of the subway train door and the online monitoring of the health state are achieved.
Preferably, the step B further includes:
step B1: for any pixel (x) on the laser stripe in the image obtained in step A0，y0) Solving the Hessian matrix of the point;
step B2: the eigenvector corresponding to the maximum eigenvalue of the Hessian matrix in step B1 corresponds to the normal direction of the light bars, pixel (x)0，y0) Can be represented as a quadratic taylor polynomialEquation, find the pixel (x)0，y0) Sub-pixel coordinates in the center of the light bar;
step B3: and according to the extracted sub-pixel positions of the central line of the light strip, fitting and solving linear equations of the central line of the light strip in the two images respectively.
Preferably, the step E further comprises:
step E1: establishing a coordinate system O of the two cameras according to the binocular stereo vision measuring system in the step D1-xlylzlAnd O2-xryrzrAnd the image coordinate systems o of the two cameras1-u1v1And o2-u2v2；
Step E2: the homogeneous coordinates of the projection points of any one eye point P on the two images are selected as
Figure BDA0002211252910000031
Andobtaining homogeneous coordinates of the point P in a three-dimensional world coordinate system according to a perspective projection model of the camera
Figure BDA0002211252910000033
The system of equations of (1):
Figure BDA0002211252910000035
wherein M is1And M2Respectively point P to image point P1And p2Determined by the intrinsic and extrinsic structural parameters of the corresponding camera, lambdauAnd λ'uRespectively are projection coefficients of the space points on the corresponding image planes;
step E3: and E, expanding and simplifying the equation set obtained in the step E2, and obtaining a general formula of the pixel coordinates on the imaging planes of the two images corresponding to the three-dimensional coordinates in the world coordinate system:
Figure BDA0002211252910000036
wherein the content of the first and second substances,
Figure BDA0002211252910000037
step E4: substituting the coordinates of the first target point (8) and the second target point (9) in the two images obtained in the step C according to the step E3, obtaining the three-dimensional coordinates of the two target points in the world coordinate system at the time point t, and then obtaining the distance d between the two pointst。
The invention also discloses a device for analyzing the dynamic stability of the metro vehicle door system, which comprises a group of binocular stereo vision measuring systems for three-dimensional reconstruction of target points, wherein the binocular stereo vision measuring systems mainly comprise a first camera and a second camera; the laser is used for projecting laser light stripes towards the direction of the subway door; the bracket is used for supporting the binocular stereoscopic vision measuring system and the laser; a computer for receiving and processing images shot by the high-speed camera is arranged at one side of the binocular stereo vision measuring system; a hand cart for carrying a computer and a stand.
Preferably, the laser is a fan laser type linear array projector, which presents a horizontally elongated light strip projected onto the train door, the horizontal angle and the pitch angle of the projector being adjustable according to the measurement position.
Preferably, when calibrating the binocular stereo vision measuring system, the camera and the camera in the binocular stereo vision measuring system are fixed so that the camera and the camera do not move relatively.
Preferably, the manual cart is a lifting type manual cart
Has the advantages that: the invention discloses a device and a method for analyzing the dynamic stability of a metro vehicle door system, which are combined with an active vision measurement technology and utilize the intersection point of a laser light bar and a target edge line to realize the accurate positioning of a target point; the calculation of the three-dimensional distance of the target point at any time of opening and closing of the vehicle door system is realized by combining a binocular vision measurement system; by adjusting the acquisition interval of camera images, the state parameters of the train door, such as the running speed, the acceleration and the like at each moment, are approximated and restored, and the dynamic stability analysis of the train door system is realized. The method provided by the invention is simple, easy to operate and high in measurement precision; the provided measuring device greatly reduces the monitoring cost of the train door state, and effectively solves the problems of analysis of the dynamic stability of the train door system and monitoring of the running health state.
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FIG. 1 is a flow chart of a device and method for analyzing the dynamic stability of a door system of a subway vehicle according to the present invention;
FIG. 2 is a structural diagram of a dynamic stability analysis device of a subway vehicle door system according to the present invention;
fig. 3 is a schematic diagram of the active binocular vision measurement based on laser light bars of the present invention.
Detailed Description
The invention discloses a dynamic stability analysis device of a metro vehicle door system, which is based on an active vision measurement method and is characterized by being divided into an image processing stage and a measurement stage. The mobile visual measuring device comprises a manual trolley of a lifting type, which is used for moving the measuring device; a group of binocular stereo vision measuring systems (consisting of cameras 1 and 2) arranged on a manual cart bracket and used for three-dimensional reconstruction of target points; the linear array laser for projecting laser light stripes to the train door direction is used for extracting the characteristics of target points 8 and 9; a computer for receiving and processing images captured by the high speed camera.
In this embodiment, the line laser 3 is a fan laser type projector, and projects a horizontally elongated light strip 5 onto the train door, and the horizontal angle and the pitch angle of the projector can be adjusted according to the measurement position. Preferably, the laser 3 and the binocular stereo vision measuring system are mutually independent, the position of a group of systems is independently adjusted or randomly moved, the integral use of the system is not influenced, and the vision measuring system does not need to be calibrated again.
A device and a method for analyzing the dynamic stability of a metro vehicle door system are characterized in that: the method comprises the following steps:
1.1 image processing phase
Step A: acquiring an image; fixing the measuring device at a proper position, triggering and starting cameras 1 and 2 in the measuring device to work at any time t in the opening or closing process of the vehicle door, and respectively acquiring vehicle door images with laser light bars 5;
and B: extracting sub-pixels and fitting a line equation; accurately extracting sub-pixels of the car door image with the laser light bars 5 by using a Steger algorithm, wherein the sub-pixels comprise sub-pixel positions and edge directions of the light bar central lines, and fitting and solving linear equations of the light bar central lines in the two images respectively according to the extracted sub-pixel positions of the light bar central lines; the Steger algorithm is based on a Hessian matrix, and can realize the sub-pixel precision positioning of the light bar center.
Wherein the step B also comprises the following steps,
step R1: for any pixel (x) on the laser stripe in the image obtained in step A0，y0) Solving the Hessian matrix of the point; for any point (x, y) on the laser stripe in the image, the Hessian matrix can be expressed as:
Figure BDA0002211252910000051
wherein, gxxRepresenting the second partial derivative of the image along x, gxyRepresenting the second partial derivative, g, of the image along x and yyyRepresenting the second partial derivative of the image along y.
Step B2: the eigenvector corresponding to the maximum eigenvalue of the Hessian matrix in step B1 corresponds to the normal direction of the light bars, pixel (x)0，y0) Can be expressed in a quadratic taylor polynomial form, find the pixel (x)0，y0) Sub-pixel coordinates in the center of the light bar; two-dimensional graphic arbitrary pixel (x)0，y0) May be represented in the form of a quadratic taylor polynomial:
Figure BDA0002211252910000052
the eigenvector corresponding to the maximum eigenvalue of the Hessian matrix corresponds to the normal direction of the light bars, as point (x)0，y0) For reference point, in the direction of the edge (n)x，ny) Is shown as
Figure BDA0002211252910000061
For line edge, let
Figure BDA0002211252910000062
The sub-pixel coordinates of the light bar center are:
(px，py)＝(tnx+x0，tny+y0) (4)
wherein the content of the first and second substances,
Figure BDA0002211252910000063
if (tn)x，tny)∈[-0.5，0.5]×[-0.5，0.5]I.e. the point where the first derivative is zero is located within the current pixel, and (n)x，ny) The second derivative of the direction is greater than a specified threshold, then the point (x)0，y0) Is the central point of the light bar, (p)x，py) The sub-pixel coordinates.
Step B3: according to the extracted sub-pixel positions of the light strip central lines, linear equations of the light strip central lines in the two images are obtained through fitting; aiming at the extracted sub-pixel coordinates of the central point of the whole light bar, fitting a light bar straight line by using a least square method:
y＝asx+cs(5)
and C: calculating coordinates of the two target points in the image; solving a linear equation of the edges of the vertical black adhesive tapes at the two door edges of the train door in the two images by using Hough transformation, and solving coordinates of the target points 8 and 9 in the two images by combining the linear equation of the light strip center line solved in the step B; in the two-dimensional plane O-xv, let the equation of a straight line be y ═ kx + b (6)
Wherein, (k, b) are the slope and intercept of the straight line respectively, if (k, b) is determined, a straight line on an O-xy plane is uniquely determined; converting the two-dimensional space into an O-kb space, wherein a straight line y ═ kx + b uniquely corresponds to one point (k, b) on an O-kb plane; this line-to-point transformation is the Hough transformation. Without loss of generality, the linear equation is expressed in polar form,
ρ＝x cosθ+y sinθ (7)
by utilizing the transformation and combining the gray information of the image edge, the vertical black adhesive tape edge detection of the left door edge and the right door edge in the train door can be realized, and the linear equation of the two black adhesive tape edges at the time t is respectively solved as
ρ0＝x cosθ0+y sinθ0(8)
ρ1＝x cosθ1+y sinθ1(9)
Simultaneous equations (5) and (8) can be used to determine the coordinates (x) of the target point 8 in the two images8，y8) And (x'8，y’8)，
Figure BDA0002211252910000071
Simultaneous equations (5) and (9) allow the coordinates (x) of the target point 9 in the two images to be determined9，y9) And (x'9，y’9)，
Figure BDA0002211252910000072
1.2 measurement phase
Step D: initializing a binocular stereoscopic vision measurement system; calibrating the binocular stereo vision measuring system, and solving internal parameters and external structure parameters of the two cameras; according to the pinhole imaging model of the camera, the camera calibration method of the plane grid points is utilized, and the accurate calibration of the camera carried by the robot can be realized. Assuming a target planeIs recorded as the homogeneous coordinate of the three-dimensional pointThe two-dimensional point homogeneous coordinate of the image plane is
Figure BDA0002211252910000074
The projective relationship between the two is
Figure BDA0002211252910000075
Where s is an arbitrary non-zero scale factor, [ R t ]]Is a matrix with 3 rows and 4 columns, called an off-camera parameter matrix, R is called a rotation matrix, and t is (t)1，t2，t3)TThe number of the translation matrices, called translation matrices,
Figure BDA0002211252910000076
a is called the internal parameter matrix of the camera. Alpha is alphax、αyIs a scale factor of the u-axis and the v-axis, (u)0，v0) R is a non-perpendicular factor of the u and v axes, as principal point coordinates. The internal parameter matrix A of the camera, namely the internal parameters can be obtained by the Zhang plane calibration method.
The main difference between the calibration of the binocular stereoscopic vision and the calibration of camera internal parameters is that the binocular camera needs to calibrate the relative relationship between the coordinate systems of the left camera and the right camera. Suppose that the external parameters of the left and right cameras in the binocular stereo vision system are R respectivelyl、TlAnd Rr、Tr，Rl、TlRespectively, the relative position of the left camera and the world coordinate system, Rr、TrRespectively, the relative position of the right camera to the world coordinate system. For any point in space, the non-homogeneous coordinate coordinates of the point in the world coordinate system, the working camera coordinate system and the right camera coordinate system are respectively assumed to be xw、xl、xrThen there is
Figure BDA0002211252910000081
Elimination of xwTo obtain
Figure BDA0002211252910000082
Thus, the geometric relationship R, T between the two cameras may be represented by the following relationship:
Figure BDA0002211252910000083
by separately calibrating the left and right cameras, R can be obtainedl、TlAnd Rr、TrFinally, the geometric relationship R, T of the binocular camera, i.e., the external structural parameters are found.
Step E: solving the distance between the two target points at the moment t in the actual three-dimensional space; in a binocular stereo vision measuring system, three-dimensional reconstruction of two target points 8 and 9 at the time t is respectively realized, and the three-dimensional distance d between the two target points 8 and 9 at the time t is obtainedt；
Wherein step E further comprises
Step E1: establishing a coordinate system O of the two cameras according to the binocular stereo vision measuring system in the step D1-xlylzlAnd O2-xryrzrAnd the image coordinate systems o of the two cameras1-u1v1And o2-u2v2；
Step E2: suppose that the homogeneous coordinates of the projected points of a target point P on two images are respectively
Figure BDA0002211252910000084
And
Figure BDA0002211252910000085
obtaining homogeneous coordinates of the point P in a three-dimensional world coordinate system according to a perspective projection model of the camera
Figure BDA0002211252910000086
The system of equations of (1):
Figure BDA0002211252910000088
wherein M is1And M2Respectively point P to image point P1And p2Determined by the intrinsic and extrinsic structural parameters of the corresponding camera, lambdauAnd λ'uRespectively are projection coefficients of the space points on the corresponding image planes;
step E3: and E, expanding and simplifying the equation set obtained in the step E2, and obtaining a general formula of the pixel coordinates on the imaging planes of the two images corresponding to the three-dimensional coordinates in the world coordinate system:
Figure BDA0002211252910000091
wherein the content of the first and second substances,
Figure BDA0002211252910000092
step E4: substituting the coordinates of the target points 8 and 9 in the two images obtained in step C into step E3, obtaining three-dimensional coordinates of the two target points in the world coordinate system at time t, and obtaining the distance d between the two pointst. The three-dimensional coordinates of two target points in the world coordinate system are assumed to be
Figure BDA0002211252910000093
And
Figure BDA0002211252910000094
the three-dimensional distance between two target points at time t is
Figure BDA0002211252910000095
Step F: two at time t + Δ t are foundThe distance of the target point in the actual three-dimensional space; at the time t + delta t of the opening or closing process of the vehicle door, according to the method in the step E, the three-dimensional distance d at the time t + delta t is obtainedt+Δt，
Figure BDA0002211252910000096
1.3 data processing phase
Step G: and (3) data processing and analysis: calculating the average speed of the vehicle door system in the delta t time according to the information obtained in the step E and the step F
Figure BDA0002211252910000097
And average accelerationWherein the average velocity
Figure BDA0002211252910000099
Average acceleration
Figure BDA00022112529100000910
In the process time of opening and closing the train door, the running speed and the acceleration of the train door at each moment are approximated and restored by adjusting the acquisition interval delta t of the camera image, and further the stability analysis of the dynamic running state of the train door of the subway and the online monitoring of the health state are realized.
In the invention, the camera 1 and the camera 2 in the binocular stereo vision measuring system are fixed when the binocular stereo vision measuring system is calibrated in the step D, so that the camera 1 and the camera 2 do not move relatively.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (7)

1. A dynamic stability analysis method of a metro vehicle door system is characterized in that: the method comprises the following steps:
step A, image acquisition: the method comprises the following steps that a laser light strip emitted by a laser device, the center line of the light strip and the edge of a vertical black adhesive tape at the door edge of a subway door form two intersection points, the intersection points are marked as target points, a camera in a binocular stereo vision measuring system is triggered and started to work at any time t in the opening or closing process of the door, and the images of the door with the laser light strip are respectively obtained;
b, sub-pixel extraction and fitting of a line equation: accurately extracting sub-pixels of the car door image with the laser light bars by using a Steger algorithm, wherein the sub-pixels comprise sub-pixel positions and edge directions of the light bar central lines, and fitting and solving linear equations of the light bar central lines in the two images respectively according to the extracted sub-pixel positions of the light bar central lines;
step C, solving the coordinates of the two target points in the image: b, solving a linear equation of the edges of the vertical black adhesive tapes on the two door edges of the train door in the two images by using Hough transformation, and solving coordinates of the two target points in the two images respectively by combining the linear equation of the light strip center line solved in the step B;
step D, initializing a binocular stereo vision measuring system: calibrating the binocular stereo vision measuring system according to the two images in the step A, and solving internal parameters and external structure parameters of the two cameras;
step E, solving the distance between the two target points at the moment t in the actual three-dimensional space: in the binocular stereo vision measuring system, the result of camera calibration in the step D is combined, the three-dimensional reconstruction of two target points at the moment t can be respectively realized by the image coordinates of each target point in the step C in the binocular camera, and the three-dimensional distance D between the two target points at the moment t is obtainedt；
Step F, solving the distance between two target points at the time t + delta t in the actual three-dimensional space: at the time t + delta t of the opening or closing process of the vehicle door, according to the method in the step E, the three-dimensional distance d at the time t + delta t is obtainedt+Δt；
G, data processing and analysis: d obtained from step E and step FtAnd dt+ΔtCalculating the average speed of the vehicle door system in the delta t timeAnd average acceleration
Figure FDA0002211252900000012
Wherein the average velocity
Figure FDA0002211252900000013
Average acceleration
Figure FDA0002211252900000014
In the process time of opening and closing the train door, the instantaneous running speed and acceleration of the train door are reduced by adjusting the acquisition interval delta t of the camera image, and therefore the stability analysis of the dynamic running state of the subway train door and the online monitoring of the health state are achieved.
2. The method for analyzing dynamic stationarity of a railcar door system according to claim 1, characterized in that: the step B also comprises the step of,
step B1: for any pixel (x) on the laser stripe in the image obtained in step A0，y0) Solving the Hessian matrix of the point;
step B2: the eigenvector corresponding to the maximum eigenvalue of the Hessian matrix in step B1 corresponds to the normal direction of the light bars, pixel (x)0，y0) Can be expressed in a quadratic taylor polynomial form, find the pixel (x)0，y0) Sub-pixel coordinates in the center of the light bar;
step B3: and according to the extracted sub-pixel positions of the central line of the light strip, fitting and solving linear equations of the central line of the light strip in the two images respectively.
3. The method for analyzing dynamic stationarity of a railcar door system according to claim 1, characterized in that: step E also comprises
Step E1: establishing a coordinate system O of the two cameras according to the binocular stereo vision measuring system in the step D1-xlylzlAnd O2-xryrzrAnd the image coordinate systems o of the two cameras1-u1v1And o2-u2v2；
Step E2: the homogeneous coordinates of the projection points of any one eye point P on the two images are selected as
Figure FDA0002211252900000021
And
Figure FDA0002211252900000022
obtaining homogeneous coordinates of the point P in a three-dimensional world coordinate system according to a perspective projection model of the camera
Figure FDA0002211252900000023
The system of equations of (1):
Figure FDA0002211252900000024
Figure FDA0002211252900000025
wherein M is1And M2Respectively point P to image point P1And p2Determined by the intrinsic and extrinsic structural parameters of the corresponding camera, lambdauAnd λ'uRespectively are projection coefficients of the space points on the corresponding image planes;
step E3: and E, expanding and simplifying the equation set obtained in the step E2, and obtaining a general formula of the pixel coordinates on the imaging planes of the two images corresponding to the three-dimensional coordinates in the world coordinate system:
Figure FDA0002211252900000026
wherein the content of the first and second substances,
Figure FDA0002211252900000031
step E4: substituting the coordinates of the first target point (8) and the second target point (9) in the two images obtained in the step C according to the step E3, obtaining the three-dimensional coordinates of the two target points in the world coordinate system at the time point t, and then obtaining the distance d between the two pointst。
4. A device for analyzing dynamic stability of a metro vehicle door system is characterized in that: the binocular stereo vision measuring system is mainly composed of a first camera (1) and a second camera (2); the laser device (3) is used for projecting the laser light bar (5) towards the subway door (10); a bracket (4) for supporting the binocular stereo vision measuring system and the laser (3); a computer (11) for receiving and processing images shot by the high-speed camera is arranged at one side of the binocular stereo vision measuring system; a hand cart (12) for carrying the computer (11) and the stand (4).
5. The apparatus for analyzing dynamic stability of a subway vehicle door system according to claim 4, wherein said door system further comprises: the laser (3) adopts a sector laser type linear array projector, a horizontal slender light strip (5) is projected on a train door, and the horizontal angle and the pitching angle of the projector can be adjusted according to the measuring position.
6. The apparatus for analyzing dynamic stability of a subway vehicle door system according to claim 4, wherein said door system further comprises: when the binocular stereo vision measuring system is calibrated, a camera (1) and a camera (2) in the binocular stereo vision measuring system are fixed, so that the camera (1) and the camera (2) do not move relatively.
7. The apparatus for analyzing dynamic stability of a subway vehicle door system according to claim 4, wherein said door system further comprises: the manual cart (12) is a lifting type manual cart.
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