CN114043879A - Medium-low speed maglev train track-passing seam control system based on image processing - Google Patents
Medium-low speed maglev train track-passing seam control system based on image processing Download PDFInfo
- Publication number
- CN114043879A CN114043879A CN202210034568.XA CN202210034568A CN114043879A CN 114043879 A CN114043879 A CN 114043879A CN 202210034568 A CN202210034568 A CN 202210034568A CN 114043879 A CN114043879 A CN 114043879A
- Authority
- CN
- China
- Prior art keywords
- image
- suspension
- gap
- value
- track
- 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.)
- Granted
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L13/00—Electric propulsion for monorail vehicles, suspension vehicles or rack railways; Magnetic suspension or levitation for vehicles
- B60L13/04—Magnetic suspension or levitation for vehicles
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
Abstract
The utility model provides a well low-speed maglev train crosses track seam control system based on image processing, the image acquisition module gathers suspension clearance image and track image through binocular camera, image processing module and clearance calculation module are to above-mentioned image processing and calculate suspension clearance value d and the electromagnet crosses track seam distance L, suspension control module receives d value and target suspension clearance value comparison, current value when there is no track seam is obtained through PID regulation, and cross the seam correction is carried out to current value when there is no track seam through L and d, finally compare with the present current value of electromagnet and obtain the current deviation, change suspension chopper duty ratio through this deviation with this change suspension electromagnet current, keep stable suspension. The invention increases the dynamic rigidity of the system and has the characteristics of strong anti-interference capability, high suspension stability and the like.
Description
Technical Field
The invention relates to the technical field of magnetic suspension trains, in particular to a system for realizing the stable control of the gap between the tracks of a magnetic suspension train through the detection of the gap distance between the suspension gap and the track passing gap of a medium-low speed magnetic suspension train based on machine vision.
Background
Magnetic levitation trains can fly at a certain height off the ground, but there is still a need for a reliable support and guidance system, i.e. a track, on the ground. The rail gap is inevitable between the rails in consideration of expansion and contraction and construction errors.
At present, most of gap sensors of medium and low speed (the speed per hour is less than 200 kilometers) magnetic suspension trains adopt eddy current type gap sensors, the eddy current effect is utilized to realize non-contact measurement of air gaps, and the suspension gap is controlled within the working range of 8-12 mm. When alternating current passes through the detection coil, the sensor can generate an alternating magnetic field, so that annular current is induced in a metal measured body, the current can generate the alternating magnetic field and influence the magnetic field in the detection coil, and the equivalent inductance of the sensor coil is changed along with the change of the gap. The value of the levitation gap can be obtained by measuring the inductance value of the detection circuit.
Although the eddy current sensor is widely applied, certain defects and shortcomings exist, the measuring result is influenced by the surface processing condition of a measured object and the material of the measured object, the working environment of the sensor has the problem of electromagnetic interference, the sensor needs to be calibrated aiming at the measuring environment in practical application, and the sensor cannot normally work if the sensor is not subjected to nonlinear calibration in use. In addition, the temperature of the working environment of the suspension clearance sensor is changed greatly, the measurement accuracy of the eddy current sensor is greatly influenced by the temperature, and the temperature drift influences the output characteristic of the sensor, so that the nonlinearity of the sensor is increased, and even the sensor cannot work normally. And when passing through the rail gap, the metal object to be detected is equivalent to be at infinity, and the suspension gap measured by the eddy current sensor is the maximum suspension gap, so that the suspension gap can cause poor stability of a suspension system and even cause instability of the suspension system.
The traditional magnetic suspension train system mainly comprises an electromagnet, a suspension train, a gap sensor, a suspension control circuit, a chopper and the like. The magnetic suspension train system is a closed-loop control system, generally, a gap sensor detects the distance change between a steel rail and an electromagnet, when a suspension gap is increased, the distance between the steel rail and the electromagnet is increased, the output voltage of the gap sensor is changed, then a gap voltage signal is sent to a suspension controller to be processed, and the current of the electromagnet is adjusted through a chopper, so that the current of the electromagnet is increased, the electromagnetic attraction force is increased, and a suspension train is attracted back to a balance position. However, when a vehicle passes through a rail joint, an accurate suspension gap cannot be obtained only by the eddy current sensor, so that disturbance occurs when the vehicle passes through the rail joint.
Disclosure of Invention
Aiming at the defects of the existing suspension gap measurement technology, the invention aims to provide a control system for the gap between the middle and low speed maglev trains passing through the track based on image processing, which aims to solve the problems that the existing gap sensor of the maglev trains cannot detect the suspension gap when the vehicles pass through the track gap, has weak anti-interference capability, complex installation process, overhigh cost, needs to carry out nonlinear correction and the like, and simultaneously realizes the function of simultaneously detecting the suspension gap, the track gap and the gap distance between the electromagnets passing through the track by a single detection device. The suspension performance of the suspension system is obviously improved through the detection of the parameters, the dynamic rigidity of the system is increased, and the anti-interference capability and the suspension stability of the system are improved.
The purpose of the invention is realized as follows:
a control system for a medium-low speed maglev train to pass through a track joint based on image processing comprises an image acquisition module, an image processing module, a gap calculation module, a suspension control module, a suspension chopper, a current sensor, a maglev train and an electromagnet;
the image acquisition module comprises a binocular camera arranged on the magnetic suspension train and is used for acquiring the suspension gap image and the track image and transmitting the suspension gap image and the track image to the image processing module;
the image processing module is connected with the image acquisition module and is used for receiving the transmitted suspension gap image and the rail image and transmitting the processed images to the gap calculation module;
the gap calculation module is connected with the image processing module and used for calculating a suspension gap value through an imagedDistance from the electromagnet to the joint of the trackLAnd transmits it to the suspension control module;
the suspension control module is connected with the gap calculation module and is used for comparing the received suspension gap with a target suspension gap and obtaining a rail gap-free current value through PID regulation; by means of an electromagnetTrack joint distanceLAnd the suspension gap carries out gap correction on the current value without the rail gap, and finally, the current value is compared with the current value of the electromagnet to obtain current deviation, and the duty ratio of the suspension chopper is changed through the deviation so as to change the current of the suspension electromagnet: when current deviation valueEiWhen the current deviation value becomes large, the duty ratio of the PWM wave is increased to increase the output currentEiWhen the current is reduced, the duty ratio of the PWM wave is reduced, so that the output current is reduced, and the stable suspension control is completed;
the current sensor is connected with the electromagnet and transmits the current value of the electromagnet to the suspension control module;
the suspension chopper is connected with the suspension control module and receives the duty ratio of the suspension control module to adjust the current of the electromagnet;
the magnetic-levitation train is a levitation main body and is controlled by the electromagnet to stably levitate.
The binocular camera of the image acquisition module is composed of two high-speed industrial cameras C arranged on the left side and the right side of the magnetic suspension trainLAnd CRThe suspension gap image and the track image of each suspension point are collected by two high-speed industrial cameras, the two high-speed industrial cameras are arranged on the outer side of the suspension point and can observe the positions of the suspension gap and the track, the optical axis of the high-speed industrial camera is parallel to the horizontal plane and forms a fixed included angle with the side edge of the suspension electromagnet on the suspension frame on the sideθNamely, each high-speed industrial camera can shoot the suspension gap image and the track image of the side at the same time; high-speed industrial camera C calibrated through two eyesLAnd CRAnd simultaneously, a suspension gap image and a track image from the upper edge of the electromagnet to the lower edge of the track are shot, and the images acquired respectively are respectively transmitted to the image processing module.
An image processing module: processing the received suspension gap image and the orbit image, wherein the image processing comprises binocular image correction, key region identification, graying, filtering, binaryzation and edge extraction; the image processing module transmits the processed image to the gap calculation module;
a gap calculation module: calculating a suspension gap value according to the image processed by the image processing moduledAnd electricityMagnet cross track joint distanceL。
The suspension control module comprises a suspension gap variation calculation unit, a rail gap-free current value calculation unit, a feedback gain value adjustment unit and a current deviation calculation unit;
value of suspension clearancedA variation calculating unit: according to the suspension clearance value sent by the clearance calculation module in real timedAnd the target suspension gap value is obtained to obtain the suspension gap valuedAmount of change ΔX(t)；
A rail gap-free time current value calculation unit: calculating the current value without rail gap
WhereinKp、Kv、KaRespectively the feedback gains of a proportional link, a differential link and an integral link, and adjusting the magnitude of the feedback gain value according to the requirement of system stability;
Δv(t) Is a value of a levitation gapdFirst order differential of the changeΔX’(t)，
Δa(t) Is a value of a levitation gapdFirst order integral of variation
,
A current deviation calculation unit: deviation of current
;
Wherein the content of the first and second substances,f(d),f(L) Respectively the value of the suspension gapdDistance from the electromagnet to the joint of the trackLAs a function of (a) or (b),i(t) The current value is the current required by the stable suspension of the train when no rail gap exists,Lthe distance of the electromagnet across the seam of the track,
in order to correct the current value when no rail gap exists,i 0 the current value of the current of the electromagnet,
the feedback gain value adjusting unit:
feedback gain through proportional elementKpTo improve the system response speed and reduce the deviation;
feedback gain of the current cause proportion elementKpIf the amplitude is too large, and excessive overshoot, oscillation or system instability is generated, the amplitude is properly adjusted back to reduce the feedback gain of the proportional linkKp；
Feedback gain through a differential elementKvThe dynamic characteristic of the system is improved, and the overshoot is reduced;
feedback gain due to differential elementKvWhen the system damping is too large and the adjusting speed of the system is too slow or the system is unstable due to too large system damping, the feedback gain of a differential link is properly adjusted back to reduceKv；
When the feedback gain of integral elementKaIf the interference is too large and the system is unstable, the feedback gain of the integral link is properly adjusted backKa。
The image processing module:
6.1 obtaining internal reference focal lengths and relative position information of the two high-speed industrial cameras, namely a rotation and translation matrix between the high-speed industrial cameras through binocular calibration, and finishing image correction by using the internal reference focal lengths and the rotation and translation matrix of the high-speed industrial cameras;
6.2 intercepting a key area containing the suspension gap in the corrected image, and graying the key area by adopting a weighted average method to obtain a grayscale image of the key area; the Gray value of the image is Gray (i,j)，i、jIs the coordinate value of any point, Gray: (i,j)=0.299*R(i,j)+0.578*G(i,j)+0.114*B(i,j)；R(i,j)，G(i,j)，B(i,j) Pixel gray values of red, green and blue channels of the image are respectively;
6.3, converting the image from a space domain to a frequency domain to process the frequency domain components of the original unclear image, and correcting the image by utilizing a histogram to enlarge the gray scale interval, increase the contrast and realize image enhancement; filtering the gray level image by adopting a bilateral filtering algorithm, removing noise in the image, and storing image edge information;
6.4 selecting a proper gray threshold Th by adopting a maximum entropy threshold method, carrying out binarization processing on the image, dividing a track gap and a background area, wherein when the gray value is greater than Th, the gray value is changed into 255, and when the gray value is less than Th, the gray value is changed into 0;
6.5, extracting the edges of the binarized image, and identifying the boundaries in the binarized image by using a canny operator;
6.6 transfer the image to the gap calculation module.
The gap calculation module:
7.1 establishing a plane rectangular coordinate system in the corrected image to obtain a front point B and a rear point A of the lower edge of the track, a front point C and a rear point D of the upper edge of the electromagnet, wherein the front point B and the rear point A of the lower edge of the track in the actual operation of the train respectively correspond to orthographic projection points B 'and A' on the electromagnet, and the orthographic projection points C 'and D' of the front point C and the rear point D of the upper edge of the electromagnet on the track respectively correspond to coordinate points A in an image coordinate system (A)x a ,y a ),B(x b ,y b ),C (x c ,y c ),D (x d ,y d ),A'(x a' ,y a' ),B'(x b' ,y b' ),C'(x c' ,y c' ), D'(x d' ,y d' )；
7.2 converting the coordinates of the image coordinate system into the coordinates of a real world coordinate system by the binocular vision principle, wherein the coordinates are A (X A , Y A ,Z A ),B(X B ,Y B ,Z B ),C(X C ,Y C ,Z C ),D(X D ,Y D ,Z D ),A'(X A' ,Y A' ,Z A' ),B'(X B' ,Y B' ,Z B'),C'(X C' ,Y C' , Z C' ),D'(X D' ,Y D' ,Z D' )；
7.3 calculating the distance between the electromagnet and the joint of the trackLAnd the value of the levitation gapdWidth of electromagnetL M
Compared with the prior art, the invention has the beneficial effects that:
the computer vision measurement technology senses and detects a three-dimensional target object in an objective world by utilizing an image, wherein the three-dimensional target object comprises geometric information such as the position, the posture, the shape and the size of a target to be detected. The computer vision measurement technology can achieve higher detection precision as long as the hardware selection and the algorithm design are reasonably carried out. The binocular stereo vision is based on parallax error, and three-dimensional information is acquired by a trigonometry principle, namely a triangle is formed between image planes of two cameras or image planes of a single camera at different positions and an object to be measured. By knowing the position relationship between the two cameras, the three-dimensional size of the object in the common field of view of the two cameras and the three-dimensional coordinates of the characteristic points of the space object can be obtained.
When the magnetic levitation train passes through the track seam, the magnetic force becomes smaller due to the fact that the magnetic resistance on the seam becomes larger, and the suspension gap detection is inaccurate when the eddy current sensor passes through the seam, so that the suspension stability and the comfort are affected, and the distance between the track seam and the electromagnetic magnet is detected through machine visionLThe current of the electromagnet is increased, and the requirement of stable suspension is met.
The invention adds the gap adjustment link and improves the suspension control method, so that the suspension performance of the suspension system is obviously improved, the dynamic rigidity of the system is increased, the anti-interference capability of the system is improved, the suspension stability of the system is obviously improved, and the stable range of the suspension system is enlarged.
Drawings
Fig. 1 is a schematic view of a binocular camera installation.
FIG. 2 is a levitation gap data transfer block diagram.
FIG. 3 is a graph of levitation gap valuesdAnd the distance of the electromagnet from the joint of the tracksLAnd (5) calculating a schematic diagram.
Fig. 4 is a control system schematic of the present invention.
FIG. 5 is a flow chart of the internal processing of the levitation control module of the present invention.
In the figure: 1 is a high-speed industrial camera, 2 is a track, 3 is a suspension frame (a magnetic suspension train), and 4 is an electromagnet.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
Fig. 4 shows a control system for the middle and low speed maglev train to pass through the track joint based on image processing, which comprises an image acquisition module, an image processing module, a gap calculation module, a levitation control module, a levitation chopper, a current sensor, a maglev train and an electromagnet;
the image acquisition module comprises a binocular camera arranged on the magnetic suspension train and is used for acquiring the suspension gap image and the track image and transmitting the suspension gap image and the track image to the image processing module;
the image processing module is connected with the image acquisition module and is used for receiving the transmitted suspension gap image and the rail image and transmitting the processed images to the gap calculation module;
the gap calculation module is connected with the image processing module and used for calculating a suspension gap value through an imagedDistance from the electromagnet to the joint of the trackLAnd transmits it to the suspension control module;
the suspension control module is connected with the clearance calculation module and is used for receiving the suspension clearance valuedComparing the current value with a target suspension gap, and obtaining a current value without a rail gap through PID regulation; by electromagnet over track joint distanceLAnd the suspension gap carries out gap correction on the current value without the rail gap, and finally, the current value is compared with the current value of the electromagnetAnd comparing the current deviation, and changing the duty ratio of the suspension chopper through the deviation so as to change the current of the suspension electromagnet: when current deviation valueEiWhen the current deviation value becomes large, the duty ratio of the PWM wave is increased to increase the output currentEiWhen the current is reduced, the duty ratio of the PWM wave is reduced, so that the output current is reduced, and the stable suspension control is completed;
the current sensor is connected with the electromagnet and transmits the current value of the electromagnet to the suspension control module;
the suspension chopper is connected with the suspension control module and receives the duty ratio of the suspension control module to adjust the current of the electromagnet;
the magnetic-levitation train is a levitation main body and is controlled by the electromagnet to stably levitate.
As shown in figure 1, the suspension gap image and the track image of each suspension point are collected by two high-speed industrial cameras 1, the two high-speed industrial cameras are arranged at the outer sides of the suspension points and can observe the positions of the suspension gap and the track 2, the optical axes of the high-speed industrial cameras are parallel to the horizontal plane and form a fixed included angle with the side edge of a suspension electromagnet 4 on a side suspension frame 3θNamely, each high-speed industrial camera can simultaneously shoot the suspension gap image and the track image on the side. The suspension gap data processing process is shown in fig. 2, and the gap detection method of the invention comprises the following steps:
and simultaneously shooting a suspension gap image from the upper edge of the electromagnet to the lower edge of the track and a track image by using a binocular calibrated high-speed industrial camera. Respectively transmitting the acquired images to an image processing module, wherein the image processing module comprises the following steps;
6.1 obtaining internal reference focal length and relative position information of the two high-speed industrial cameras, namely a rotation and translation matrix between the high-speed industrial cameras through binocular calibration, and finishing picture correction by using the internal reference and rotation and translation matrices of the high-speed industrial cameras.
6.2 intercepting a key area containing the suspension gap in the corrected image, and graying the key area by adopting a weighted average method to obtain a grayscale image of the key area; the Gray value of the image is Gray (i,j)，i、jIs the coordinate value of any point, then
Gray(i,j)=0.299*R(i,j)+0.578*G(i,j)+0.114*B(i,j)；R(i,j)，G(i,j)，B(i,j) Pixel gray values of red, green and blue channels of the image are respectively;
6.3, converting the image from a space domain to a frequency domain to process the frequency domain components of the original unclear image, and correcting the image by utilizing a histogram to enlarge the gray scale interval, increase the contrast and realize image enhancement; filtering the gray level image by adopting a bilateral filtering algorithm, removing noise in the image, and storing image edge information;
6.4 selecting a proper gray threshold Th by adopting a maximum entropy threshold method, carrying out binarization processing on the image, dividing a track gap and a background area, wherein when the gray value is greater than Th, the gray value is changed into 255, and when the gray value is less than Th, the gray value is changed into 0;
6.5, extracting the edges of the binarized image, and identifying the boundaries in the binarized image by using a canny operator;
6.6 transfer the image to the gap calculation module.
Calculating the actual gap value and the distance between the electromagnet and the joint of the trackLThe processing procedure is as shown in fig. 3, and includes the following steps:
7.1 establishing a plane rectangular coordinate system in the corrected image to obtain a front point B and a rear point A of the lower edge of the track, a front point C and a rear point D of the upper edge of the electromagnet, wherein the front point B and the rear point A of the lower edge of the track in the actual operation of the train respectively correspond to orthographic projection points B 'and A' on the electromagnet, and the orthographic projection points C 'and D' of the front point C and the rear point D of the upper edge of the electromagnet on the track respectively correspond to coordinate points A in an image coordinate system (A)x a ,y a ),B(x b ,y b ),C (x c ,y c ), D (x d ,y d ),A'(x a' ,y a' ),B'(x b' ,y b' ),C'(x c' ,y c' ),D'(x d' ,y d' )；
7.2 principle of binocular VisionThe coordinates of the image coordinate system are converted into the coordinates of a real world coordinate system, and the coordinates are A (A)X A , Y A ,Z A ),B(X B ,Y B ,Z B ),C(X C ,Y C ,Z C ),D(X D ,Y D ,Z D ),A'(X A' ,Y A' ,Z A' ),B'(X B' ,Y B' ,Z B'),C'(X C' ,Y C' , Z C' ), D'(X D' ,Y D' ,Z D' )；
7.3 calculating the distance between the electromagnet and the joint of the trackLAnd the value of the levitation gapdWidth of electromagnetL M
The invention relates to a control method for a suspension train passing through a rail gap, which comprises the following steps (as shown in figures 4 and 5):
step 1: according to the suspension clearance value sent by the clearance calculation module in real timedObtaining the value of the suspension clearancedAmount of change ΔX(t)
Step 2: calculating the value of the levitation gapdFirst order differential of the changeΔX’(t) Is recorded as Δv(t)
And step 3: calculating the value of the levitation gapdFirst order integral of variation
Is recorded as Δa(t)
And 4, step 4: calculating the current to be output for maintaining the stability of the system without the rail gap
WhereinKp、Kv、KaRespectively obtaining feedback gains, and adjusting the feedback gain values according to the system stability requirement;
and 5: receiving electromagnet currenti 0 ；
Step 6: the adjustment link of the gap is
Deviation of current of
。f (d),f(L)Respectively the value of the suspension gapdDistance from the electromagnet to the joint of the trackLAs a function of (c).
And 7: the controller controls the electromagnet current by changing the duty ratio of the output PWM wave according to the current deviation, and the current difference is obtainedEiWhen the output current is increased, the duty ratio of the PWM wave is increased, and the difference value is increasedEiAnd when the current is reduced, the duty ratio of the PWM wave is reduced, so that the output current is reduced, and the stable suspension control is completed.
When the electromagnet crosses the track seam distanceLWhen the size of the material is increased,f(L) Increase to compensate for the suspension force lost due to the track loss, when the suspension gap value isdWhen the magnetic force line becomes larger, the loss of the magnetic force line at the rail gap is relatively reduced, so that the suspension force of the loss is described in a piecewise function form.
The feedback gain value adjusting unit:
feedback gain through proportional elementKpTo improve the system response speed and reduce the deviation;
feedback gain of the current cause proportion elementKpIf the amplitude is too large, and excessive overshoot, oscillation or system instability is generated, the amplitude is properly adjusted back to reduce the feedback gain of the proportional linkKp；
Feedback gain through a differential elementKvThe dynamic characteristic of the system is improved, and the overshoot is reduced;
when due to differential elementFeedback gainKvWhen the system damping is too large and the adjusting speed of the system is too slow or the system is unstable due to too large system damping, the feedback gain of a differential link is properly adjusted back to reduceKv；
When the feedback gain of integral elementKaIf the interference is too large and the system is unstable, the feedback gain of the integral link is properly adjusted backKa。
Claims (7)
1. A control system for the middle-low speed maglev train to pass through a track joint based on image processing is characterized by comprising an image acquisition module, an image processing module, a gap calculation module, a suspension control module, a suspension chopper, a current sensor, a maglev train and an electromagnet;
the image acquisition module comprises a binocular camera arranged on the magnetic suspension train and is used for acquiring the suspension gap image and the track image and transmitting the suspension gap image and the track image to the image processing module;
the image processing module is connected with the image acquisition module and is used for receiving the transmitted suspension gap image and the rail image and transmitting the processed images to the gap calculation module;
the gap calculation module is connected with the image processing module and used for calculating a suspension gap value through an imagedDistance from the electromagnet to the joint of the trackLAnd transmits it to the suspension control module;
the suspension control module is connected with the clearance calculation module and is used for receiving the suspension clearance valuedComparing the current value with a target suspension gap value, and obtaining a current value without a rail gap through PID regulation; by electromagnet over track joint distanceLAnd value of levitation gapdAnd (3) performing gap correction on the current value without the rail gap, finally comparing the current value with the current value of the electromagnet to obtain a current deviation, and changing the duty ratio of the suspension chopper through the deviation so as to change the current of the suspension electromagnet: when current deviation valueEiWhen the current deviation value becomes large, the duty ratio of the PWM wave is increased to increase the output currentEiWhen the current is reduced, the duty ratio of the PWM wave is reduced, so that the output current is reduced, and the stable suspension control is completed;
the current sensor is connected with the electromagnet and transmits the current value of the electromagnet to the suspension control module;
the suspension chopper is connected with the suspension control module and receives the duty ratio of the suspension control module to adjust the current of the electromagnet;
the magnetic-levitation train is a levitation main body and is controlled by the electromagnet to stably levitate.
2. The image processing-based medium and low speed maglev train track-passing joint control system according to claim 1, wherein: the binocular camera of image acquisition module comprises two high-speed industrial cameras of installing on maglev train left side and right side, and the suspension clearance image and the track image of every suspension point are gathered by two high-speed industrial cameras, and two high-speed industrial cameras are installed and can be observed suspension clearance and orbital position in the suspension point outside, and the optical axis of high-speed industrial camera is parallel with the horizontal plane, is fixed contained angle with the side border of the suspension electro-magnet on this side suspension frameθNamely, each high-speed industrial camera can shoot the suspension gap image and the track image of the side at the same time; two high-speed industrial cameras calibrated through a binocular shooting device simultaneously shoot suspension gap images and track images from the upper edge of the electromagnet to the lower edge of the track, and the images collected respectively are transmitted to the image processing module.
3. The image processing-based medium and low speed maglev train track-passing seam control system according to claim 1,
an image processing module: processing the received suspension gap image and the orbit image, wherein the image processing comprises binocular image correction, key region identification, graying, filtering, binaryzation and edge extraction; the image processing module transmits the processed image to the gap calculation module;
a gap calculation module: calculating a suspension gap value according to the image processed by the image processing moduledAnd the distance of the electromagnet across the track jointL。
4. According to claim 1The image processing-based middle-low speed maglev train track-passing joint control system is characterized in that the suspension control module comprises a suspension gap valuedThe device comprises a variable quantity calculating unit, a rail seam-free current value calculating unit, a feedback gain value adjusting unit and a current deviation calculating unit;
value of suspension clearancedA variation calculating unit: according to the suspension clearance value sent by the clearance calculation module in real timedAnd the target suspension gap value is obtained to obtain the suspension gap valuedAmount of change ΔX(t)；
A rail gap-free time current value calculation unit: calculating the current value without rail gap
WhereinKp、Kv、KaRespectively the feedback gains of a proportional link, a differential link and an integral link, and adjusting the magnitude of the feedback gain value according to the requirement of system stability;
Δv(t) Is a value of a levitation gapdFirst order differential of the changeΔX’(t)，
Δa(t) Is a value of a levitation gapdFirst order integral of variation
,
A current deviation calculation unit: deviation of current
;
Wherein the content of the first and second substances,f(d),f(L) Respectively the value of the suspension gapdDistance from the electromagnet to the joint of the trackLAs a function of (a) or (b),i(t) The current value is the current required by the stable suspension of the train when no rail gap exists,Lthe distance of the electromagnet across the seam of the track,
for the current value after the gap correction,i 0 the current value of the current of the electromagnet,
5. the image-processing-based medium-low speed maglev train track-passing joint control system according to claim 4, wherein the feedback gain value adjusting unit:
feedback gain through proportional elementKpTo improve the system response speed and reduce the deviation;
feedback gain of the current cause proportion elementKpIf the amplitude is too large, and excessive overshoot, oscillation or system instability is generated, the amplitude is properly adjusted back to reduce the feedback gain of the proportional linkKp；
Feedback gain through a differential elementKvThe dynamic characteristic of the system is improved, and the overshoot is reduced;
feedback gain due to differential elementKvWhen the system damping is too large and the adjusting speed of the system is too slow or the system is unstable due to too large system damping, the feedback gain of a differential link is properly adjusted back to reduceKv；
When the feedback gain of integral elementKaIf the interference is too large and the system is unstable, the feedback gain of the integral link is properly adjusted backKa。
6. The image-processing-based medium and low speed maglev train over-track joint control system according to claim 5, wherein the image processing module:
6.1 obtaining internal reference focal lengths and relative position information of the two high-speed industrial cameras, namely a rotation and translation matrix between the high-speed industrial cameras through binocular calibration, and finishing image correction by using the internal reference focal lengths and the rotation and translation matrix of the high-speed industrial cameras;
6.2 intercepting the key area containing the suspension gap in the corrected image, and graying the key area by adopting a weighted average method to obtain the relationA grayscale image of the key region; the Gray value of the image is Gray (i,j)，i、jIs the coordinate value of any point, Gray: (i,j)=0.299*R(i,j)+0.578*G(i,j)+0.114*B(i,j)；R(i,j)，G(i,j)，B(i,j) Pixel gray values of red, green and blue channels of the image are respectively;
6.3, converting the image from a space domain to a frequency domain to process the frequency domain components of the original unclear image, and correcting the image by utilizing a histogram to enlarge the gray scale interval, increase the contrast and realize image enhancement; filtering the gray level image by adopting a bilateral filtering algorithm, removing noise in the image, and storing image edge information;
6.4 selecting a proper gray threshold Th by adopting a maximum entropy threshold method, carrying out binarization processing on the image, dividing a track gap and a background area, wherein when the gray value is greater than Th, the gray value is changed into 255, and when the gray value is less than Th, the gray value is changed into 0;
6.5, extracting the edges of the binarized image, and identifying the boundaries in the binarized image by using a canny operator;
6.6 transfer the image to the gap calculation module.
7. The image-processing-based medium-low speed maglev train over-track joint control system according to claim 6, wherein the gap calculation module:
7.1 establishing a plane rectangular coordinate system in the corrected image to obtain a front point B and a rear point A of the lower edge of the track, a front point C and a rear point D of the upper edge of the electromagnet, wherein the front point B and the rear point A of the lower edge of the track in the actual operation of the train respectively correspond to orthographic projection points B 'and A' on the electromagnet, and the orthographic projection points C 'and D' of the front point C and the rear point D of the upper edge of the electromagnet on the track respectively correspond to coordinate points A in an image coordinate system (A)x a ,y a ),B(x b ,y b ),C(x c ,y c ),D(x d ,y d ),A'(x a' ,y a' ),B'(x b' ,y b' ),C'(x c' , y c' ),D'(x d' ,y d' )；
7.2 converting the coordinates of the image coordinate system into the coordinates of a real world coordinate system by the binocular vision principle, wherein the coordinates are A (X A ,Y A , Z A ),B(X B ,Y B ,Z B ),C(X C ,Y C ,Z C ),D(X D ,Y D ,Z D ),A'(X A' ,Y A' ,Z A' ),B'(X B' ,Y B' ,Z B'),C'(X C' ,Y C' , Z C' ),D'(X D' ,Y D' ,Z D' )；
7.3 calculating the distance between the electromagnet and the joint of the trackLAnd the value of the levitation gapdWidth of electromagnetL M
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210034568.XA CN114043879B (en) | 2022-01-13 | 2022-01-13 | Medium-low speed maglev train track-passing seam control system based on image processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210034568.XA CN114043879B (en) | 2022-01-13 | 2022-01-13 | Medium-low speed maglev train track-passing seam control system based on image processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114043879A true CN114043879A (en) | 2022-02-15 |
| CN114043879B CN114043879B (en) | 2022-03-29 |
Family
ID=80196438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210034568.XA Active CN114043879B (en) | 2022-01-13 | 2022-01-13 | Medium-low speed maglev train track-passing seam control system based on image processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114043879B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114922795A (en) * | 2022-06-09 | 2022-08-19 | 中山劲牛科技有限公司 | Noise reduction method and control circuit for fuel heater plunger pump |
| CN115085591A (en) * | 2022-07-11 | 2022-09-20 | 西南交通大学 | Gap self-sensing electromagnetic suspension system based on composite coil and control method thereof |
Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH05199614A (en) * | 1992-09-28 | 1993-08-06 | Toshiba Corp | Levitation conveyor |
| JPH0654413A (en) * | 1991-02-15 | 1994-02-25 | Hitachi Kiden Kogyo Ltd | Method for controlling gap sensor of magnetic levitation type vehicle |
| CN1915704A (en) * | 2006-08-28 | 2007-02-21 | 中国人民解放军国防科学技术大学 | Suspension method for controling module of electromagnetism type magnetic suspension train in normal conduction and low temperature |
| US20090320713A1 (en) * | 2008-06-25 | 2009-12-31 | Ahmad Amiri | People & Cargo Transit Systems & Vehicles |
| CN101680910A (en) * | 2007-06-15 | 2010-03-24 | 诺思罗普·格鲁曼·利特夫有限责任公司 | Method of work and circuit structure with capacitance type micro mechanical sensor of analog reset |
| CN101872198A (en) * | 2010-05-10 | 2010-10-27 | 北京航天控制仪器研究所 | Vehicle-mounted pick-up stable platform |
| US20150097948A1 (en) * | 2013-10-04 | 2015-04-09 | Kapsch Trafficcom Ab | Method for calibration of a road surveillance system |
| CN104527451A (en) * | 2014-12-04 | 2015-04-22 | 中国人民解放军国防科学技术大学 | Suspension controller detection device for medium and low speed maglev train |
| CN106828185A (en) * | 2017-01-19 | 2017-06-13 | 西南交通大学 | A kind of electromagnetic suspension train suspension control method |
| CN109064448A (en) * | 2018-07-04 | 2018-12-21 | 西南交通大学 | Medium-and low-speed maglev F rail rail gap detection method |
| CN109269544A (en) * | 2018-09-27 | 2019-01-25 | 中国人民解放军国防科技大学 | Inspection system for suspension sensor of medium-low speed magnetic suspension vehicle |
| CN109559314A (en) * | 2019-01-18 | 2019-04-02 | 西南交通大学 | A kind of electromagnetic suspension ball system and its image processing method based on machine vision |
| CN109981980A (en) * | 2019-03-12 | 2019-07-05 | 唐山百川智能机器股份有限公司 | Over the horizon real-time display method, system, storage medium and computer equipment |
| CN110320385A (en) * | 2019-08-13 | 2019-10-11 | 西南交通大学 | A kind of electromagnetic suspension ball system and its control method with acceleration detection function |
| US20190348898A1 (en) * | 2016-12-14 | 2019-11-14 | Robert Bosch Gmbh | Transporting Device with a Stator for the Controlled Transport of a Transport Element Relative to the Stator |
| CN110930407A (en) * | 2020-02-07 | 2020-03-27 | 西南交通大学 | Suspension gap visual detection method based on image processing |
| CN110954005A (en) * | 2020-02-21 | 2020-04-03 | 西南交通大学 | Medium-low speed maglev train gap detection method based on image processing |
| US20200290463A1 (en) * | 2017-09-26 | 2020-09-17 | Crrc Qingdao Sifang Co., Ltd. | Maglev train and moving part thereof |
| CN111932636A (en) * | 2020-08-19 | 2020-11-13 | 展讯通信（上海）有限公司 | Calibration and image correction method and device for binocular camera, storage medium, terminal and intelligent equipment |
| CN113063362A (en) * | 2021-04-07 | 2021-07-02 | 湖南凌翔磁浮科技有限责任公司 | Non-contact type maglev train bogie spacing detection method |
-
2022
- 2022-01-13 CN CN202210034568.XA patent/CN114043879B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0654413A (en) * | 1991-02-15 | 1994-02-25 | Hitachi Kiden Kogyo Ltd | Method for controlling gap sensor of magnetic levitation type vehicle |
| JPH05199614A (en) * | 1992-09-28 | 1993-08-06 | Toshiba Corp | Levitation conveyor |
| CN1915704A (en) * | 2006-08-28 | 2007-02-21 | 中国人民解放军国防科学技术大学 | Suspension method for controling module of electromagnetism type magnetic suspension train in normal conduction and low temperature |
| CN101680910A (en) * | 2007-06-15 | 2010-03-24 | 诺思罗普·格鲁曼·利特夫有限责任公司 | Method of work and circuit structure with capacitance type micro mechanical sensor of analog reset |
| US20090320713A1 (en) * | 2008-06-25 | 2009-12-31 | Ahmad Amiri | People & Cargo Transit Systems & Vehicles |
| CN101872198A (en) * | 2010-05-10 | 2010-10-27 | 北京航天控制仪器研究所 | Vehicle-mounted pick-up stable platform |
| US20150097948A1 (en) * | 2013-10-04 | 2015-04-09 | Kapsch Trafficcom Ab | Method for calibration of a road surveillance system |
| CN104527451A (en) * | 2014-12-04 | 2015-04-22 | 中国人民解放军国防科学技术大学 | Suspension controller detection device for medium and low speed maglev train |
| US20190348898A1 (en) * | 2016-12-14 | 2019-11-14 | Robert Bosch Gmbh | Transporting Device with a Stator for the Controlled Transport of a Transport Element Relative to the Stator |
| CN106828185A (en) * | 2017-01-19 | 2017-06-13 | 西南交通大学 | A kind of electromagnetic suspension train suspension control method |
| US20200290463A1 (en) * | 2017-09-26 | 2020-09-17 | Crrc Qingdao Sifang Co., Ltd. | Maglev train and moving part thereof |
| CN109064448A (en) * | 2018-07-04 | 2018-12-21 | 西南交通大学 | Medium-and low-speed maglev F rail rail gap detection method |
| CN109269544A (en) * | 2018-09-27 | 2019-01-25 | 中国人民解放军国防科技大学 | Inspection system for suspension sensor of medium-low speed magnetic suspension vehicle |
| CN109559314A (en) * | 2019-01-18 | 2019-04-02 | 西南交通大学 | A kind of electromagnetic suspension ball system and its image processing method based on machine vision |
| CN109981980A (en) * | 2019-03-12 | 2019-07-05 | 唐山百川智能机器股份有限公司 | Over the horizon real-time display method, system, storage medium and computer equipment |
| CN110320385A (en) * | 2019-08-13 | 2019-10-11 | 西南交通大学 | A kind of electromagnetic suspension ball system and its control method with acceleration detection function |
| CN110930407A (en) * | 2020-02-07 | 2020-03-27 | 西南交通大学 | Suspension gap visual detection method based on image processing |
| CN110954005A (en) * | 2020-02-21 | 2020-04-03 | 西南交通大学 | Medium-low speed maglev train gap detection method based on image processing |
| LU101669B1 (en) * | 2020-02-21 | 2020-07-09 | Univ Southwest Jiaotong | Gap detection method of medium-low speed maglev train based on image processing |
| CN111932636A (en) * | 2020-08-19 | 2020-11-13 | 展讯通信（上海）有限公司 | Calibration and image correction method and device for binocular camera, storage medium, terminal and intelligent equipment |
| CN113063362A (en) * | 2021-04-07 | 2021-07-02 | 湖南凌翔磁浮科技有限责任公司 | Non-contact type maglev train bogie spacing detection method |
Non-Patent Citations (3)
| Title |
|---|
| 陈志贤: "高速常导电磁悬浮车辆系统动力学优化研究", 《中国优秀硕士学位论文全文数据库》 * |
| 靖永志: "高速磁悬浮列车悬浮气隙测量系统的设计", 《传感器技术》 * |
| 黎松奇: "磁悬浮列车静态悬浮轨道参数识别", 《机车电传动》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114922795A (en) * | 2022-06-09 | 2022-08-19 | 中山劲牛科技有限公司 | Noise reduction method and control circuit for fuel heater plunger pump |
| CN115085591A (en) * | 2022-07-11 | 2022-09-20 | 西南交通大学 | Gap self-sensing electromagnetic suspension system based on composite coil and control method thereof |
| CN115085591B (en) * | 2022-07-11 | 2022-11-11 | 西南交通大学 | Gap self-sensing electromagnetic suspension system based on composite coil and control method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114043879B (en) | 2022-03-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114043879B (en) | Medium-low speed maglev train track-passing seam control system based on image processing | |
| US6985619B1 (en) | Distance correcting apparatus of surroundings monitoring system and vanishing point correcting apparatus thereof | |
| US9586455B2 (en) | Road surface condition estimating apparatus | |
| KR100942925B1 (en) | Stereo vision system and control method thereof | |
| CN102159918B (en) | Method and measuring assembly for determining wheel or axle geometry of vehicle | |
| WO2017080108A1 (en) | Flying device, flying control system and method | |
| CN105606127A (en) | Calibration method for relative attitude of binocular stereo camera and inertial measurement unit | |
| CN110264525A (en) | A kind of camera calibration method based on lane line and target vehicle | |
| CN110930407B (en) | Suspension gap visual detection method based on image processing | |
| EP2181417A2 (en) | Method and system for online calibration of a video system | |
| KR20200077426A (en) | Aircraft positioning on a taxiway | |
| CN110174059B (en) | Monocular image-based pantograph height and pull-out value measuring method | |
| CN109559314B (en) | Electromagnetic suspension ball system based on machine vision and image processing method thereof | |
| CN110954005B (en) | Medium-low speed maglev train suspension gap detection method based on image processing | |
| CN108931240B (en) | Path tracking sensor and tracking method based on electromagnetic induction | |
| CN107433391B (en) | Welding calibration method and system based on image recognition | |
| CN112258583B (en) | Distortion calibration method for close-range image based on equal distortion partition | |
| Wang et al. | An improved ArUco marker for monocular vision ranging | |
| CN110458785B (en) | Magnetic levitation ball levitation gap detection method based on image sensing | |
| CN110400333B (en) | Training binocular stereoscopic vision device and high-precision stereoscopic vision image acquisition method | |
| CN110171263B (en) | Bend identification and vehicle height adjustment method for ECAS system | |
| CN111028275A (en) | Tracing robot PID method based on cross-correlation image positioning matching | |
| CN114913231A (en) | Driving target object positioning method based on machine vision | |
| CN114463387A (en) | Contact net tracking detection method and detection device | |
| CN114161939B (en) | Fusion control method and system for high-speed maglev train suspension system |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |