CN210719028U - Contact net geometric parameters detection device based on three-dimensional point cloud - Google Patents
Contact net geometric parameters detection device based on three-dimensional point cloud Download PDFInfo
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Abstract
The utility model discloses a contact net geometric parameters detection device based on three-dimensional point cloud, a serial communication port, including detecting the car, it sets up image acquisition system to detect the car roof, image acquisition system connects gradually data transmission system, image processing system, data analysis system, data storage system and customer end, image acquisition system includes a pair of linear laser instrument, camera and camera COMS component, linear laser instrument symmetrical arrangement installation, the target object is shone in the concentration, the CMOS component that laser passed through the target object reflection to the camera on, catch the degree of depth point cloud data of target, data adopt to convey to image processing system in the form based on GPRS network wireless transmission, image processing system, data analysis system, data storage system and customer end all set up in detecting the car is internal. Compared with the prior art, the device can effectively detect the height of the contact line and the pull-out value of the contact line, can extract the coordinate information contained in the straight line at one time through the straight line fitting of the contact line, and has good detection efficiency.
Description
Technical Field
The utility model relates to a contact net hangs detection area, in particular to based on three-dimensional point cloud contact net geometric parameters detection device.
Background
With the development of the domestic rail transit technology, rail transit becomes one of the most important modes of freight transportation and passenger transportation, and the safe operation of rail transit plays a vital role in the development of national economy. The contact net is composed of a contact suspension device, a positioning device, a supporting device and the like, is used as an important structure of a train power supply system, and the performance of the contact net directly influences the stable operation of a locomotive. The contact net works outdoors for a long time, the operation environment is complex and severe, faults of the contact net frequently occur, the proportion of the contact net in the railway operation faults is large, and the potential safety hazard detection in the operation process of the contact net is particularly important for ensuring the safe and stable operation of a locomotive and reducing the national economic loss. The geometric parameters of the contact network mainly comprise height guide, a pull-out value, the gradient of a positioning tube, contact wire abrasion and the like, and are important indexes for evaluating the power supply performance of the contact network and guiding the maintenance of the contact network. The detection of the geometric parameters has great significance for guaranteeing safe and reliable operation of the electric power.
For the detection of geometric parameters, the current detection technology is mainly divided into a contact detection technology and a non-contact detection technology, the contact detection technology mainly obtains operating state parameters of a bow net by adding a sensor on a line, the non-contact detection technology obtains the operating parameters by devices such as a laser radar, an ultrasonic wave and an infrared imager, and detects the operating state of equipment. However, such detection technologies based on two-dimensional images are greatly influenced by weather and environmental factors, and for some detection methods, the detection accuracy of the detection technologies is greatly influenced by the resolution of the sampling camera, so that the requirements on equipment are high. In addition, in order to ensure the precision of the two-dimensional image acquisition technology, a vibration compensation device is additionally arranged at the bottom of the vehicle, and the device is complex.
SUMMERY OF THE UTILITY MODEL
The utility model aims at providing an improve detection efficiency's contact net geometric parameters detection device.
In order to solve the technical problem, the utility model adopts the following technical scheme
The utility model provides a contact net geometric parameters detection device based on three-dimensional point cloud, including detecting the car, detect the car roof and set up image acquisition system, image acquisition system connects gradually data transmission system, image processing system, data analysis system, data storage system and customer end, image acquisition system includes a pair of linear laser, camera and camera COMS component, linear laser symmetrical arrangement installation, the concentrated target object that shines, laser passes through the CMOS component that target object reflected to the camera on, catch the degree of depth point cloud data of target, data adopt the form based on GPRS network wireless transmission to convey to image processing system in, image processing system, data analysis system, data storage system and customer end all set up in detecting the car internal.
The portable ultrasonic detection device for the parts of the contact net generates high-voltage pulse excitation signals through the ultrasonic excitation circuit; after the excitation signal acts on the contact network parts, the ultrasonic detection device can receive an echo signal with a smaller amplitude; the signal conditioning and acquisition circuit processes the high-voltage pulse excitation signal and the echo signal received by the ultrasonic detection device; the output signal of the portable contact net part ultrasonic detection device is read through a JTAG interface and is displayed on a screen; when a defect echo occurs, the buzzer gives an alarm to prompt a defect detection result.
Compared with the prior art, the utility model has the advantages of it is following:
1. the device obtains the depth point cloud data of the contact net through the linear laser, the camera and the CMOS image sensor, is additionally arranged on a detection vehicle during use, does not need to be in direct contact with the contact net, detects the geometric parameters of the contact net through data preprocessing and recognition through an image processing technology, has good system safety, is less influenced by the environment, and can accurately detect the geometric parameters of the contact net.
2. The utility model discloses a check out test set draws the algorithm through the straight line of three-dimensional point cloud and draws the contact wire, can once only extract the coordinate information that the contact wire contains, and then reachs the geometric parameters of each point, and efficiency is higher.
3. The utility model discloses when examining on line the contact net geometric parameters, because the continuity of three-dimensional point cloud data obtains, can avoid the detection error that arouses by external disturbances such as locomotive vibration, need not to install vibrations compensation arrangement additional, simple structure.
Drawings
Fig. 1-1 show a front view of a system architecture according to an embodiment of the present invention.
Fig. 1-2 are side views of system configurations according to embodiments of the present invention
Fig. 2 is a diagram illustrating a hardware structure of a system according to an embodiment of the present invention.
Fig. 3 shows that according to the utility model discloses an embodiment camera depth image gathers the schematic diagram.
Fig. 4 is a schematic diagram illustrating a double-triangle distance measurement according to an embodiment of the present invention.
Fig. 5 shows the effect diagram before and after extracting point cloud data according to the RANSAC straight line extraction algorithm of the present invention.
Fig. 6 is a schematic diagram illustrating parameter detection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
The utility model provides a contact net geometric parameters detection device based on three-dimensional point cloud, including detecting the car, detect the car roof and set up image acquisition system, image acquisition system connects gradually data transmission system, image processing system, data analysis system, data storage system and customer end, image acquisition system includes a pair of linear laser, camera and camera COMS component, linear laser symmetrical arrangement installation, the concentrated target object that shines, laser passes through the CMOS component that target object reflected to the camera on, catch the degree of depth point cloud data of target, data adopt the form based on GPRS network wireless transmission to convey to image processing system in, image processing system, data analysis system, data storage system and customer end all set up in detecting the car internal. The acquired data is transmitted to the image combing system through the data transmission system for processing and calculation, the acquired data is packaged into a data packet and stored in the storage system, meanwhile, the data can be displayed in a client side in an image or table mode, the abnormal data is marked in a striking mode, and the fault position is known concisely and clearly. The system installation structure is shown in the front view of fig. 1-1, the side view of fig. 1-2, and the hardware structure diagram of fig. 2.
The line laser parameters are shown in table 1:
as shown in fig. 3, a pair of symmetrically installed linear lasers emits two beams of linear laser to a target, the camera receives the laser reflected from the target, and the position of the laser spot received by the CMOS device changes correspondingly with the change of the distance from the surface of the target. Obtaining point cloud data by a double-triangle distance measurement principle, wherein the distance measurement principle is as shown in the figure4, respectively. In the figure, O is the optical center of the camera; A. g is a laser spot projected on a target object; B. h is a line laser;
the plane of the camera and the laser, α and β are two included angles between the line laser emitted by the line laser and the plane, f represents the focal length of the camera, d and d1The vertical distance between the center of the laser and the optical center plane of the camera is represented; l, L1The vertical distance between the target object and the optical center plane of the camera is taken as the distance; a. a is1The distances x, x from the imaging point to the edge of the CMOS photosensitive element are reflected to the target object irradiated by the laser1From FIG. 4, △ BOA- △ CDO, &lTtT translation = delta "&gTt Δ &lTt/T &gTt OGH- △ IOJ, then from the geometric relationship of similar triangles:
then
And then the vertical distance from the target object to the optical center of the camera can be calculated, namely
And then the linear distance between the target and the laser is obtained through the sine relation
The laser is symmetrically installed, so d is d1，α＝β，
After the linear distance is obtained, the system can obtain the three-dimensional coordinate of the target in the camera coordinate system through the installation angle of the system camera
Finally, the color information obtained by the CMOS element is combined, namely the coordinate information can be integratedAnd obtaining a point cloud image of the target object by using the color information and the laser intensity.
Fig. 5 is a comparison graph of data sets before and after extraction by the RANSAC straight line extraction algorithm. In order to meet the requirements of speed precision and the like of subsequent identification, point cloud data obtained by an image acquisition system needs to be preprocessed. Wirelessly transmitting the depth point cloud data obtained by the image acquisition system to an image processing system, removing abnormal values in the data, denoising by adopting a median filtering algorithm, and then identifying and extracting contact lines in the obtained point cloud data by using a RANSAC linear detection algorithm. The RANSAC algorithm can be used for obtaining parameters of a mathematical model from a group of data including an outlier in an iterative manner. The process comprises the following steps:
(1) two points in the preprocessed data are randomly selected, and a linear equation of the two points is set.
(2) Setting an iteration threshold epsilon, an iteration number k and a fraction upper limit, wherein the iteration number is
Wherein p is the probability of obtaining the optimal model after iteration, n is the number of points required by the estimation model, and omega is the ratio of the target number of points to the total number of points.
(3) Calculating the distance d from the point to the straight line in the dataiIf d isiIf < epsilon, the point is the target point. And the point is counted into the number of the target points, and the number obtained finally is the fraction of the straight line.
(4) And (4) repeating the steps (1) to (3) and searching for the straight line with the highest score. And after the calculation is finished, extracting point cloud data of a straight line with the highest score.
FIG. 6 is a schematic view of parameters of a non-contact detection device, point P (X)C,YC,ZC) After the identification and extraction of the contact line are completed for one point on the contact line, the coordinate of the P point is subjected to space coordinate conversion, the coordinate of the target point cloud in the camera coordinate system is converted into a world coordinate system through coordinate conversion, and the contact line lead-up and pull-out value are calculated. In fig. 4, the coordinate system of the camera and the coordinate system of the world have a rotation transformation around the X axis and a translation transformation in the direction of the X, Y axis.
Wherein the rotation transformation matrix is:
theta is the installation angle of the camera, generally the angle between the camera and the plane of the rail, i.e. the horizontal plane, and the installation angle needs to be adjusted during installation to ensure the optimal installation angle.
The translation transformation matrix is:
l is the width between the running rails; h is the height of the camera to the ground; d1The distance from the column side of the point that is the optical center of the camera projected to the ground.
The final transformation matrix is
From this, world coordinate system coordinates (X) can be obtainedW,YW,ZW) With point cloud coordinates (X)C,YC,ZC) The corresponding relation between the two is as follows:
after coordinate transformation, the height Hc and the pull-out value Sv of the point can be calculated.
Hc＝YW＝YCcosθ+ZCsinθ+h
Sv＝XW＝Xc+l/2-d1
The calculation of the relevant geometric parameters can be done based on the above principles.
A friendly man-machine interaction client is developed by adopting Microsoft VC + +6.0 software, the calculated geometric parameters are displayed in the form of images or tables, and the data of each link are stored in a database in the form of data packets. Data that is outside the normal range is highlighted.
Claims (1)
1. The utility model provides a contact net geometric parameters detection device based on three-dimensional point cloud, a serial communication port, including detecting the car, it sets up image acquisition system to detect the car roof, image acquisition system connects gradually data transmission system, image processing system, data analysis system, data storage system and client, image acquisition system includes a pair of linear laser instrument, camera and camera COMS component, linear laser instrument symmetrical arrangement installation, the concentrated target object that shines, laser passes through the CMOS component on target object reflection to the camera, catch the degree of depth point cloud data of target, data adopt the form based on GPRS network wireless transmission to convey to image processing system in, image processing system, data analysis system, data storage system and client all set up in detecting the car internal.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112325781A (en) * | 2020-10-16 | 2021-02-05 | 易思维（杭州）科技有限公司 | Rail transit contact line abrasion detection device and method |
| CN112669391A (en) * | 2020-12-29 | 2021-04-16 | 苏州大晚成智能科技有限公司 | Calibration method and device for four-camera contact line measuring instrument |
| WO2021135392A1 (en) * | 2019-12-30 | 2021-07-08 | 科沃斯机器人股份有限公司 | Structured light module and autonomous moving apparatus |
| CN113504545A (en) * | 2021-09-09 | 2021-10-15 | 成都中轨轨道设备有限公司 | Contact network data detection method based on laser radar |
| CN113534142A (en) * | 2021-07-13 | 2021-10-22 | 中国人民解放军国防科技大学 | Railway contact network measuring method based on radar system and rail car |
| CN115993091A (en) * | 2021-10-18 | 2023-04-21 | 合肥中车轨道交通车辆有限公司 | Contact net pull-out value detection method and device |
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2019
- 2019-09-19 CN CN201921557739.7U patent/CN210719028U/en active Active
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021135392A1 (en) * | 2019-12-30 | 2021-07-08 | 科沃斯机器人股份有限公司 | Structured light module and autonomous moving apparatus |
| CN112325781A (en) * | 2020-10-16 | 2021-02-05 | 易思维（杭州）科技有限公司 | Rail transit contact line abrasion detection device and method |
| CN112325781B (en) * | 2020-10-16 | 2022-05-17 | 易思维（杭州）科技有限公司 | Rail transit contact line abrasion detection device and method |
| CN112669391A (en) * | 2020-12-29 | 2021-04-16 | 苏州大晚成智能科技有限公司 | Calibration method and device for four-camera contact line measuring instrument |
| CN113534142A (en) * | 2021-07-13 | 2021-10-22 | 中国人民解放军国防科技大学 | Railway contact network measuring method based on radar system and rail car |
| CN113534142B (en) * | 2021-07-13 | 2022-05-13 | 中国人民解放军国防科技大学 | Railway contact net measuring method based on radar system and rail car |
| CN113504545A (en) * | 2021-09-09 | 2021-10-15 | 成都中轨轨道设备有限公司 | Contact network data detection method based on laser radar |
| CN115993091A (en) * | 2021-10-18 | 2023-04-21 | 合肥中车轨道交通车辆有限公司 | Contact net pull-out value detection method and device |
| CN115993091B (en) * | 2021-10-18 | 2024-05-14 | 合肥中车轨道交通车辆有限公司 | Contact net pull-out value detection method and device |
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