Test system and method for web platform of ballast track bed section detection system

Abstract

The invention discloses a testing system and method for a web platform of a ballast track bed section detection system, and belongs to the technical field of testing of testing platforms. The invention aims to solve the problems of long test period and incapability of meeting the requirement of complete coverage of a test scene in the manner of carrying out detection system web platform test by matching a train with a ballast track bed section detection system in the prior art. The web platform is tested through the test system, and the test system comprises a RabbitMQ connection and data sending module which is responsible for being connected with a target web platform server and is responsible for sending a test data task at regular time. The equipment operation state maintenance module is used for setting a current task number, monitoring equipment, equipment operation state maintenance information and the like and regularly sending an equipment operation state, the driving process GYK data generation module is used for generating GYK data in the driving process, and the image recognition detection result data module is used for generating ballast track image recognition result parameters.

Description

Technical Field

[0001] The present invention belongs to the technical field of testing platforms, and in particular relates to a testing system and a testing method for a web platform of a track section detection system. Background Art

[0002] The web platform of the ballasted track section detection system is mainly used to display the data of the ballasted track section. These data come from the images of ballast on the railway collected by the equipment status of the ballasted track section detection system during the operation of the train, the passing state data, and the size and proportion results of various indicators of the railway ballast identified by image recognition. The most intuitive test method is to build a ballasted track section detection system test environment at the train operation site and use the real train passing method to perform functional testing of the web platform. However, this method consumes too many resources such as manpower, material resources, time and space, has a long test cycle, and the source of test data (the data source is the ballasted track section detection system, which is also one of the objects to be tested) is unreliable. In addition, the profit and loss state of ballast on a certain section of the railway is relatively simple and is not suitable as a test sample. It is not realistic to test the entire railway section. The test data set is too simple and cannot meet the full coverage of the test scenario.

[0003] Therefore, it is not practical to use the actual train with the ballasted track section detection system to test the detection system web platform. Therefore, it is necessary to come up with a set of testing methods that can save testing resources and achieve the best testing results. Summary of the invention

[0004] The present invention aims to solve the problems of long test cycle and failure to meet the requirement of full coverage of test scenarios in the existing method of testing the detection system web platform by using a train with a ballasted trackbed section detection system.

[0005] A test system for a web platform of a ballasted track section detection system, the test system includes a RabbitMQ connection and data transmission module, an equipment operation status maintenance module, a driving process GYK data generation module, and an image recognition detection result data module; wherein,

[0006] Rabbit MQ connection and data sending module: responsible for connecting with the target web platform server, responsible for sending test data tasks regularly, and providing an interactive interface for setting the frequency of fault data in the sent test data and the total number of test data sent in the current sending task. It is also responsible for counting the total number of test data sent and the total number of fault data sent after the sending task is completed; it is also responsible for testing the test result data statistics function on the web platform; the test data includes GYK data, equipment status data, and image recognition result data; the fault data frequency refers to how many test data have one fault data;

[0007] Equipment operation status maintenance module: provides an interactive interface for setting the current task number, monitoring equipment, and setting the heartbeat interval for maintaining the equipment operation status; is responsible for sending the equipment operation status to the RabbitMQ equipment status queue at regular intervals, and the web platform software can obtain the equipment status information from the equipment status queue;

[0008] GYK data generation module during driving: configure the starting kilometer mark, GYK information sending distance interval, uplink and downlink and train running speed, and calculate the update time interval based on the GYK information sending distance interval and train running speed, and send all GYK information to the corresponding queue at this time interval;

[0009] Image recognition detection result data module: provides an interactive interface for setting the range of changes in the route number and station number that the vehicle passes through, and maintains one route number and station number for a certain period of time, and then randomly changes to another combination to simulate the different line conditions passed by the real-time sports car; it is also used to set special road section types; it is responsible for generating ballasted track image recognition result parameters according to the normal and over-limit range rules of track ballast parameters of different road section types, and the ballasted track image recognition result parameters include the total volume of standard ballast within the specified distance slen, the total volume of real track ballast within the specified distance slen, and the volume value of ballast surplus / deficit.

[0010] Furthermore, the Rabbit MQ connection and data sending module is also responsible for providing an interactive interface for setting the duration of a single route number and station number.

[0011] Furthermore, the equipment operation status maintenance module also provides an interactive interface for setting the working status and current temperature value of the camera in the ballast bed section detection system, as well as the connection status of the identification server and the control industrial computer in the ballast bed section detection system.

[0012] Furthermore, the process of generating the total volume of the standard ballast within the specified distance slen in the ballast track image recognition result parameters is as follows:

[0013] First, the total volume of ballast on both sides of the track within the specified distance slen when there is no profit or loss is calculated. The slope volume, ballast shoulder volume, and ballast shoulder lower volume are calculated by the left and right ballast shoulder widths, pile height, slope height, and slope ratio parameters when there is no profit or loss. Then the ballast volume on one side is calculated, and then the ballast volumes on the left and right sides are added together to obtain the total volume within the specified distance slen, which is recorded as the total volume of standard ballast within the specified distance slen.

[0014] Furthermore, the process of calculating the single-side ballast volume includes:

[0015] Slope volume = 1 / 2 * slope length * slope height * slen, where slope length = slope height * slope ratio;

[0016] Ballast shoulder volume = 1 / 2 * ballast shoulder width * pile height * slen;

[0017] The volume of the lower part of the ballast shoulder = slope height * slen * ballast shoulder width;

[0018] The volume of ballast on one side = the volume of slope + the volume of ballast shoulder + the volume below the ballast shoulder.

[0019] Furthermore, the process of generating the total volume of the actual track ballast within the specified distance slen in the ballast track image recognition result parameter is as follows:

[0020] First, the mean values ​​corresponding to the real track ballast parameters within the specified distance slen are calculated. The real track ballast parameter data include left and right ballast shoulder widths, pile height, slope height, and slope ratio. The calculated mean value is used as the real track ballast parameter data;

[0021] The total volume of ballast on both sides of the track within the specified distance slen is calculated using the actual track ballast parameter data, that is, the actual track ballast total volume.

[0022] Furthermore, the volume value of the surplus / deficient ballast in the ballasted track image recognition result parameter is obtained by calculating the difference between the total volume of the actual track ballast and the total volume of the standard ballast within the specified distance slen.

[0023] Furthermore, according to the normal and over-limit range rules of track ballast parameters of different road section types, the over-limit range rules described in the process of generating the parameters of the ballasted track image recognition result are as follows:

[0024] Different levels of over-limit situations are set through the normal range of real track ballast parameters; when fault data needs to be sent, values ​​are randomly selected within the different levels of over-limit range.

[0025] Furthermore, the fault data needs to add a specified fault image path, and place a picture with the same format as the fault image under the specified path to test the fault image display function of the web platform.

[0026] A testing method for a web platform of a ballasted track bed section detection system is based on the testing system of the web platform of the ballasted track bed section detection system. The testing system of the web platform of the ballasted track bed section detection system simulates the GYK information of the passing vehicle given to the platform by the acquisition system during driving, the heartbeat information containing the equipment status of the acquisition system, and the detection result data information of the image recognition software, and gives them to different queues. The web platform reads the information of each queue for display.

[0027] Beneficial effects:

[0028] (1) The present invention can test the web platform under test without using a real train or a ballasted track section detection system. The test environment is simple and low-cost, making the test more convenient, saving a lot of materials, manpower, space, and time consumption, and the test efficiency is higher. In addition, the present invention is easy to use and can perform unattended long-term sports car running tests, saving manpower and shortening the test cycle.

[0029] (2) The present invention adopts a method of sending simulated data directly to RabbitMQ, which is more reliable than using the data source provided by the acquisition system under test, has strong data flexibility, and can cover any test scenario; and the present invention can simulate the operating status and heartbeat of each module equipment of the ballasted track section detection system, and simulate the running status of the train; it can simulate the data of normal and faulty complex scenarios of various parameters of the track ballast that are difficult to manufacture in real scenarios, so as to make the test scenario coverage more comprehensive; therefore, the present invention can fully meet the requirements of complete coverage of the test scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The following is a test flow chart.

[0031] Figure 2 Schematic diagram of the cross section of ballast stone. DETAILED DESCRIPTION

[0032] Specific implementation method 1: Combination Figure 1 To explain this embodiment,

[0033] This embodiment is a test system and test method for a web platform of a ballasted track section detection system, the test system includes a RabbitMQ connection and data transmission module, a device operation status maintenance module, a driving process GYK (railway vehicle operation control equipment) data generation module, and an image recognition detection result data module, wherein the image recognition detection result data module is the main technical innovation content. The specific test method is implemented through the test system (i.e., the test tool software).

[0034] 1. Rabbit MQ connection and data sending module:

[0035] Responsible for the configuration and connection of the IP, port, username, and password of the target web platform server. Also responsible for the timed sending of GYK data, equipment status data, and image recognition result data tasks, and triggering the start and stop of cyclic sending tasks through the buttons on the software UI interface. You can set how many pieces of data have a fault data, the total number of data sent in this cyclic sending task, and the duration of a single route number and station number (timed switching of route numbers and station numbers). After the sending task is completed, count the total number of data sent and the total number of fault data sent; it is also used to test the test result data statistics function on the web platform.

[0036] One function of the web platform is to count and display the normal and abnormal data of the ballast parameters of the ballasted track detected by the ballasted track bed section detection system. The function of counting the total number of data sent and the total number of fault data sent in the "RabbitMQ connection and data sending module" of the present invention can be used to test this function of the web platform.

[0037] 2. Equipment operation status maintenance module:

[0038] You can set the working status (normal, faulty) of the four cameras in the ballast bed section detection system, and the current temperature value (normal range, abnormal range). You can set the connection status (normal, disconnected) of the identification server and the control industrial computer in the ballast bed section detection system. You can set the current task number and the monitoring device (identification server, control industrial computer) check. You can set the heartbeat interval time (unit: minutes) for the monitoring device operation status. The device operation status is sent to the RabbitMQ monitoring device status queue regularly, and the web platform software goes to the device status queue to obtain these device status information to ensure that users can create tasks normally.

[0039] 3. GYK data generation module during driving process:

[0040] Configure the starting kilometer mark, the GYK information sending distance interval (how many meters a GYK message is sent), the uplink and downlink and train running speeds, and calculate the update time interval based on the GYK information sending distance interval and the train running speed, and send all GYK information to the corresponding queue at this time interval.

[0041] 4. Image recognition detection result data module:

[0042] You can set the range of route numbers and station numbers that the train passes through, and maintain one route number and station number for a certain period of time, and then randomly change to another combination to simulate the different line conditions that the train passes through in real time. You can set special road section types (single track, bridge, tunnel, double track). According to the normal and over-limit range rules of track ballast parameters of different road section types, the corresponding ballasted track image recognition result parameters are generated. For the profit and loss data of the track bed ballast,

[0043] First, calculate the total volume of ballast on both sides of the track within a specified distance slen (e.g. 5 meters) when there is no profit or loss. Calculate the slope volume, ballast shoulder volume, and ballast shoulder lower volume using parameters such as the left and right ballast shoulder widths, pile height, slope height, and slope ratio when there is no profit or loss (standard ballasted trackbed). Then calculate the single-side ballast volume. Then add the ballast volumes on the left and right sides to get the total volume within the specified distance slen, which is recorded as the total volume of standard ballast within the specified distance slen.

[0044] Taking the calculation of the volume of ballast on one side as an example, the cross section of the ballast is as follows: Figure 2 As shown, the calculation process is as follows:

[0045] Slope volume = 1 / 2 * slope length * slope height * slen, where slope length = slope height * slope ratio;

[0046] Ballast shoulder volume = 1 / 2 * ballast shoulder width * pile height * slen;

[0047] The volume of the lower part of the ballast shoulder = slope height * slen * ballast shoulder width;

[0048] The volume of ballast on one side = the volume of the slope + the volume of the ballast shoulder + the volume below the ballast shoulder. Then add the volumes of the ballast on the left and right sides.

[0049] Then, based on the actual track ballast parameter data, the total volume of the actual track ballast within the specified distance slen is calculated:

[0050] First, calculate the mean values ​​of the real track ballast parameters within the specified distance slen. The real track ballast parameter data include left and right ballast shoulder width, pile height, slope height, and slope ratio; use the calculated mean value as the real track ballast parameter data; calculate the total volume of ballast on both sides of the track within the specified distance slen, that is, the real track ballast total volume, through the real track ballast parameter data. The specified distance slen is set with different over-limit range values ​​according to test needs.

[0051] Finally, the total volume of the actual track ballast obtained from the actual track ballast parameter data is calculated as a difference with the total volume of the standard ballast within the specified distance slen to obtain the excess (deficit) volume value of the ballast. The excess (deficit) volume value can also be adjusted by adjusting the over-limit data of the parameters according to the test needs.

[0052] The advantage of this method is that it can well restore the normal or over-limit data of the actual track ballast profit and loss, and will not produce data that does not conform to the actual situation. Using this data to test the web platform of the system under test can better restore the test scenarios used and meet the diversity of scenarios in actual testing.

[0053] Through the normal range of real track ballast parameters, special scenarios of one to four levels of overrun are set. Track ballast parameters include manufacturing left and right ballast shoulder widths, pile height, slope height, slope ratio and other data; when fault data needs to be sent, values ​​can be randomly selected within the one to four levels of overrun range, and different types of data can be sent to the specified recognition result queue in conjunction with the Rabbit MQ connection and data sending module, thereby simulating the image recognition result data of ballast during actual train operation. Use this data to test the normal and abnormal data display function of the web platform and the display function of the data overrun level.

[0054] Add a specified fault image path to each fault data, place a picture with the same format as the fault image in the specified path, and test the fault image display function of the web platform. At the same time, you can add a simulated sending recognition completion message to the last data to complete the task.

[0055] In the process of implementing the specific test method through the test system, based on the cooperation of the four modules, the GYK information of the passing vehicle, the heartbeat information containing the equipment status of the acquisition system, and the detection result data information of the image recognition software given to the platform during the driving process are simulated, and given to different queues. The web platform reads the information of each queue for display. In this way, the platform is tested for the function of displaying the data collection and recognition results of different driving scenarios and the load test of the long-term running car. On the premise of saving manpower and material resources, the test of flexible and complex scenarios can be completed.

[0056] The above calculation examples of the present invention are only used to explain the calculation model and calculation process of the present invention in detail, and are not intended to limit the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A test system for a ballasted track section detection system web platform, characterized in that: The test system includes a RabbitMQ connection and data transmission module, a device operation status maintenance module, a driving process GYK data generation module, and an image recognition detection result data module; wherein, Rabbit MQ connection and data sending module: responsible for connecting with the target web platform server, responsible for sending test data tasks regularly, and providing an interactive interface for setting the frequency of fault data in the sent test data and the total number of test data sent in the current sending task. It is also responsible for counting the total number of test data sent and the total number of fault data sent after the sending task is completed; it is also responsible for testing the test result data statistics function on the web platform; the test data includes GYK data, equipment status data, and image recognition result data; the fault data frequency refers to how many test data have one fault data; Equipment operation status maintenance module: provides an interactive interface for setting the current task number, monitoring equipment, and setting the heartbeat interval for maintaining the equipment operation status; is responsible for sending the equipment operation status to the RabbitMQ equipment status queue at regular intervals, and the web platform software can obtain the equipment status information from the equipment status queue; GYK data generation module during driving: configure the starting kilometer mark, GYK information sending distance interval, up and down and train running speed, and calculate the update time interval based on the GYK information sending distance interval and train running speed, and send all GYK information to the corresponding queue at this time interval; Image recognition detection result data module: provides an interactive interface for setting the range of changes in the route number and station number that the vehicle passes through, and maintains one route number and station number for a certain period of time, and then randomly changes to another combination to simulate the different line conditions passed by the real-time sports car; it is also used to set special road section types; it is responsible for generating ballasted track image recognition result parameters according to the normal and over-limit range rules of track ballast parameters of different road section types, and the ballasted track image recognition result parameters include the total volume of standard ballast within the specified distance slen, the total volume of real track ballast within the specified distance slen, and the volume value of ballast surplus / deficit.

2. The test system of the web platform of the ballasted track section detection system according to claim 1 is characterized in that: The Rabbit MQ connection and data sending module is also responsible for providing an interactive interface for setting the duration of a single route number and station number.

3. The test system of the web platform of the ballasted track section detection system according to claim 1 is characterized in that: The equipment operation status maintenance module also provides an interactive interface for setting the working status and current temperature value of the camera in the ballast bed section detection system, as well as the connection status of the identification server and the control industrial computer in the ballast bed section detection system.

4. The test system of the web platform of the ballasted track section detection system according to claim 1 is characterized in that: The process of generating the total volume of standard ballast within the specified distance slen in the ballast track image recognition result parameters is as follows: First, the total volume of ballast on both sides of the track within the specified distance slen when there is no profit or loss is calculated. The slope volume, ballast shoulder volume, and ballast shoulder lower volume are calculated by the left and right ballast shoulder widths, pile height, slope height, and slope ratio parameters when there is no profit or loss. Then the ballast volume on one side is calculated, and then the ballast volumes on the left and right sides are added together to obtain the total volume within the specified distance slen, which is recorded as the total volume of standard ballast within the specified distance slen.

5. The test system of the web platform of the ballasted track section detection system according to claim 4 is characterized in that: The process of calculating the volume of ballast rock on one side includes: Slope volume = 1 / 2 * slope length * slope height * slen, where slope length = slope height * slope ratio; Ballast shoulder volume = 1 / 2 * ballast shoulder width * pile height * slen; The volume of the lower part of the ballast shoulder = slope height * slen * ballast shoulder width; The volume of ballast on one side = the volume of slope + the volume of ballast shoulder + the volume below the ballast shoulder.

6. The test system of the web platform of the ballasted track section detection system according to claim 4 is characterized in that: The process of generating the total volume of actual track ballast within the specified distance slen in the ballast track image recognition result parameter is as follows: First, the mean values ​​corresponding to the real track ballast parameters within the specified distance slen are calculated. The real track ballast parameter data include left and right ballast shoulder widths, pile height, slope height, and slope ratio. The calculated mean value is used as the real track ballast parameter data; The total volume of ballast on both sides of the track within the specified distance slen is calculated using the actual track ballast parameter data, that is, the actual track ballast total volume.

7. The test system of the web platform of the ballasted track section detection system according to claim 6 is characterized in that: The volume value of the ballast surplus / deficit in the ballasted track image recognition result parameter is obtained by calculating the difference between the total volume of the actual track ballast and the total volume of the standard ballast within the specified distance slen.

8. A test system for a web platform of a ballasted track section detection system according to any one of claims 1 to 7, characterized in that: According to the normal and over-limit range rules of track ballast parameters of different road section types, the over-limit range rules described in the process of generating the parameters of the ballasted track image recognition result are as follows: Different levels of over-limit situations are set through the normal range of real track ballast parameters; when fault data needs to be sent, values ​​are randomly selected within the different levels of over-limit range.

9. The test system of the web platform of the ballasted track section detection system according to claim 8, characterized in that: The fault data needs to add a specified fault image path, and place a picture with the same format as the fault image under the specified path to test the fault image display function of the web platform.

10. A test method for a web platform of a ballasted track bed section detection system, characterized in that: The test is performed on a test system of a web platform for a ballasted track bed section detection system according to any one of claims 1 to 9, wherein the test system of a web platform for a ballasted track bed section detection system simulates the GYK information of passing vehicles, the heartbeat information containing the equipment status of the acquisition system, and the detection result data information of the image recognition software given to the platform by the acquisition system during driving, and gives them to different queues. The web platform reads the information of each queue for display.

Images