Train load monitoring method and related device

Abstract

The invention discloses a train load monitoring method and a related device, and relates to the technical field of train monitoring, and the method comprises the steps: judging whether each train monitoring mode is effective or not according to the priority of each train load monitoring mode in a train load monitoring mode set; when the video monitoring system required to be used in the train load monitoring mode of the combined video monitoring system with the highest priority is normal, the train load monitoring mode is adopted for train load monitoring; when the video monitoring system is abnormal but the passenger ticket information system required in the train load monitoring mode of the combined passenger ticket information system with the medium priority is normal, the train load monitoring mode is adopted for train load monitoring; when the video monitoring system and the passenger ticket information system are abnormal, train load monitoring is carried out by adopting a mode based on air spring pressure monitoring, the higher the priority is, the more accurate the monitoring result of the train load monitoring mode is, and the occurrence of misjudgment of the train overweight condition is reduced to a certain extent.

Description

Technical Field

[0001] The present application relates to the technical field of train monitoring, and in particular to a train load monitoring method and related devices. Background Art

[0002] Overweight trains have many hazards: they will significantly increase the friction between the wheels and the tracks, increasing energy consumption while also aggravating the wear of the wheels and tracks; they will reduce the running speed and affect transportation efficiency; during emergency braking, the braking distance will be extended due to the increased inertia, which will greatly increase the risk of accidents in emergency situations; they will cause excessive loads on infrastructure such as bridges and tunnels, increasing the risk of structural damage, and in severe cases may cause structural collapse; and so on.

[0003] In the known technology, in order to prevent the danger of overweight trains, an overcrowding alarm function is set on the train: the air spring pressure value is collected, and the air spring pressure value is converted into the train weight according to an empirical formula. When the train weight exceeds the preset train weight threshold, the overweight alarm is triggered.

[0004] However, during the operation of the train, the air spring needs to automatically adjust the pressure according to the load to maintain the appropriate distance between the train body and the track. This dynamic adjustment makes the pressure value of the air spring not fully and accurately reflect the actual weight of the train. In addition, the pressure value of the air spring is also affected by many factors such as vehicle speed, curve passing, weather conditions, etc., which may lead to the misjudgment of the train being overweight. For example, when the train passes a curve at high speed, the pressure value of the air spring may change due to the centrifugal force, which may lead to the misjudgment of whether the train is overweight.

[0005] It can be seen that the accuracy of the method of monitoring whether a train is overweight based on air spring pressure in the known technology is not high. Summary of the invention

[0006] In view of the above problems, the present application provides a train load monitoring method and related devices to achieve the purpose of accurately monitoring whether the train load is overweight. The specific scheme is as follows:

[0007] A first aspect of the present application provides a train load monitoring method, which is applied to a train control system, comprising:

[0008] According to the priorities of each train load monitoring method in the train load monitoring method set from high to low, it is judged in turn whether each train load monitoring method of the ticket information system is effective; the priorities of each train load monitoring method of the ticket information system from high to low are the train load monitoring method of the joint video monitoring system, the train load monitoring method of the joint ticket information system and the train load monitoring method based on air spring pressure monitoring; the higher the priority of each train load monitoring method of the ticket information system, the more accurate the corresponding train load monitoring result;

[0009] When the video monitoring system is normal, the train load monitoring method of the joint video monitoring system is used to monitor the train load;

[0010] When the video monitoring system is abnormal but the ticket information system is normal, the train load monitoring method of the ticket information system is used to monitor the train load;

[0011] When both the video surveillance system and the ticket information system are abnormal, the train load monitoring method based on air spring pressure monitoring is adopted to monitor the train load.

[0012] In a possible implementation, the train load monitoring process of the train load monitoring mode of the joint video monitoring system includes:

[0013] Acquire real-time video data inside the train from the video surveillance system;

[0014] Determine train occupants through real-time video data;

[0015] The train load is calculated by a preset train load calculation formula;

[0016] Determine whether the train load exceeds a preset train load threshold, and when the train load exceeds the preset train load threshold, generate and send an overcrowding alarm instruction.

[0017] In a possible implementation, determining train passengers through real-time video data includes:

[0018] The video surveillance algorithm is used to process the real-time video data to obtain the train passengers.

[0019] In a possible implementation, a video surveillance algorithm is used to process real-time video data to obtain train passengers, including:

[0020] The real-time video data is processed through target detection, target tracking, behavior recognition and face recognition to obtain the train passengers.

[0021] In a possible implementation, the train load monitoring process of the train load monitoring mode of the joint ticket information system includes:

[0022] Obtain ticket information from the ticket information system;

[0023] The train capacity is determined by the ticket information and the fixed number of drivers and passengers;

[0024] The train load is calculated by a preset train load calculation formula;

[0025] Determine whether the train load exceeds a preset train load threshold, and when the train load exceeds the preset train load threshold, generate and send an overcrowding alarm instruction.

[0026] In a possible implementation, the train load is calculated using a preset train load calculation formula, including:

[0027] The train load is obtained by multiplying the train passengers by the preset average weight per person and adding the passenger weight to the pre-obtained empty train mass.

[0028] A second aspect of the present application provides a train load monitoring device, comprising:

[0029] A judgment unit, a first train load monitoring processing unit, a second train load monitoring processing unit and a third train load monitoring processing unit; wherein:

[0030] A judgment unit is used to judge whether each train load monitoring mode is effective in order of priority from high to low according to the train load monitoring mode set; the priorities of each train load monitoring mode are, from high to low, the train load monitoring mode of the joint video monitoring system, the train load monitoring mode of the joint ticket information system, and the train load monitoring mode based on air spring pressure monitoring; the higher the priority of each train load monitoring mode, the more accurate the corresponding train load monitoring result;

[0031] A first train load monitoring processing unit is used to monitor the train load by adopting a train load monitoring method of a joint video monitoring system when the video monitoring system is normal;

[0032] The second train load monitoring processing unit performs train load monitoring by adopting a train load monitoring method of the combined ticket information system when the video monitoring system is abnormal but the ticket information system is normal;

[0033] The third train load monitoring processing unit is used to monitor the train load by adopting a train load monitoring method based on air spring pressure monitoring when both the video monitoring system and the passenger ticket information system are abnormal.

[0034] A third aspect of the present application provides a train load monitoring device, comprising at least one processor and a memory connected to the processor, wherein:

[0035] The memory is used to store computer programs;

[0036] The processor is used to execute a computer program so that the train load monitoring device can implement the train load monitoring method as described in any one of the above.

[0037] A fourth aspect of the present application provides a computer program product comprising computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements a train load monitoring method as described in any one of the above.

[0038] A fifth aspect of the present application provides a computer-readable storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement a train load monitoring method as described in any one of the above.

[0039] By means of the above technical scheme, the train load monitoring method and related devices provided by the present application are applied to the train control system, and the effectiveness of each train load monitoring method is judged in the order of priority of each train load monitoring method in the train load monitoring method concentration. When the video monitoring system required in the train load monitoring method of the joint video monitoring system with the highest priority is normal, the train load monitoring method of the joint video monitoring system is used to monitor the train load; when the video monitoring system is abnormal but the ticket information system required in the train load monitoring method of the joint ticket information system with the medium priority is normal, the train load monitoring method of the joint ticket information system is used to monitor the train load; when both the above video monitoring system and the ticket information system are abnormal, the train load monitoring is performed based on air spring pressure monitoring. The present application also provides two train load monitoring results with higher accuracy than the train load monitoring methods in the known technology, and the train load monitoring method with the highest accuracy is used first, thereby reducing the situation of misjudging the train overweight to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0041] Figure 1 An example flow chart of a train load monitoring method based on air spring pressure monitoring provided in this application;

[0042] Figure 2 A flow chart of a train load monitoring method provided in this application;

[0043] Figure 3An example flow chart of the train load monitoring method provided in this application;

[0044] Figure 4 A structural schematic diagram of a train load monitoring device provided in this application;

[0045] Figure 5 A schematic diagram of the structure of the train load monitoring device provided in this application. DETAILED DESCRIPTION

[0046] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0047] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0048] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0049] In the known technology, in order to prevent the danger of overweight trains, an overcrowding alarm function is set. The overcrowding alarm function is mainly triggered by an air spring pressure sensor. An air spring is a device that compresses and stores air and adjusts the height of the car body and reduces shock by releasing air.

[0050] Optional, see Figure 1 , the present application provides a flow chart showing an example of a train load monitoring method based on air spring pressure monitoring.

[0051] First, the air spring pressure sensor installed on the air spring inlet collects the air spring pressure value, and the air spring pressure sensor sends the collected air spring pressure value to the train control system; the train control system converts the air spring pressure value into the train weight according to the empirical formula, and then determines whether the train weight determined by the air spring exceeds the preset train load threshold. When it is determined that the train weight exceeds the preset train load threshold, the train control system will trigger an overcrowding alarm.

[0052] However, the method of converting the air spring pressure value into the train weight in the known technology has a relatively large error, which may lead to the misjudgment of train overweight. It should also be noted that the misjudgment of train overweight will affect the normal operation order, causing a series of problems such as train delays or passenger complaints.

[0053] With respect to the above-mentioned train load monitoring method based on air spring pressure monitoring, it can be found that there are two methods that can improve the accuracy of train load monitoring in this method.

[0054] The first is to start with air spring pressure monitoring, and improve the detection accuracy of the air spring pressure sensor so that the train weight converted from the air spring pressure value is closer to the actual weight; the second is to optimize the empirical formula mentioned above for converting the air spring pressure value into the train weight.

[0055] It should be noted that the first method of improving the monitoring accuracy of the air spring pressure sensor cannot be realized in the short term with current technology; the second method of optimizing the empirical formula requires a lot of scientific experiments. The above two methods of improving the train load monitoring method based on air spring pressure monitoring are both unrealistic to be completed in the short term.

[0056] In order to solve the problem of low accuracy in train load monitoring in the known technology, the present application provides a train load monitoring method with relatively high accuracy.

[0057] Optional, see Figure 2 , a flow chart of a train load monitoring method provided in the present application.

[0058] It should be noted that the train load monitoring method provided in the present application is specifically applied to a train control system, which monitors the train load in real time.

[0059] like Figure 2 As shown, the train load monitoring method includes the following steps:

[0060] Step 101, according to the priority of each train load monitoring mode in the train load monitoring mode set from high to low, determine whether each train load monitoring mode is effective in turn; the priority of each train load monitoring mode from high to low is the train load monitoring mode of the joint video monitoring system, the train load monitoring mode of the joint ticket information system and the train load monitoring mode based on air spring pressure monitoring; the higher the priority of each train load monitoring mode, the more accurate the corresponding train load monitoring result.

[0061] It should be noted that, the present application provides two train load monitoring methods based on the existing train load monitoring method based on air spring pressure monitoring: a train load monitoring method of a joint video monitoring system and a train load monitoring method of a joint ticket information system.

[0062] The two new train load monitoring methods provide a new train load calculation method: by obtaining the number of train passengers, the weight of the train passengers is estimated, and the train load is obtained by adding the weight of the train passengers to the weight of the empty train. In addition, the two train load monitoring methods are combined with the video monitoring system and the passenger ticket information system respectively, without the need to add any additional hardware equipment.

[0063] Specifically, the train load monitoring process of the train load monitoring method of the joint video monitoring system is as follows:

[0064] The train control system obtains real-time video data in the train from the video monitoring system. Specifically, the train control system obtains real-time video data in each carriage from the video monitoring system.

[0065] Furthermore, the train control system determines the train occupants through the video data in each carriage. Specifically, the train control system processes the video data in each carriage through a video monitoring algorithm, and the processing steps of the video monitoring algorithm include: target monitoring, target tracking, behavior recognition and face recognition processing.

[0066] Specifically, the video surveillance algorithm defines the detection area of ​​each camera, learns the key features of passengers through the pre-established target detection model, counts the train passengers in each monitoring area, and uses the collected video surveillance data in the train compartment to establish a model training sample library of about 200,000 pictures. Through the training and optimization of the target detection model and verification in combination with experimental tests, the detection accuracy of the target detection model can reach or even exceed 95%. That is, the train control system inputs the video data into the target detection model, and the target detection model processes the video data to obtain the train passengers.

[0067] Then, the train passengers are substituted into the preset train load calculation formula to calculate the train load. Specifically, the preset load calculation formula is to multiply the train passengers by the preset per capita weight to obtain the train passenger weight, and then add the passenger weight to the pre-obtained train empty car mass to obtain the train load. Exemplarily, the preset load calculation formula can be: train passengers × per capita 80kg + measured empty car mass.

[0068] After obtaining the actual train load, it is determined whether the calculated train load exceeds a preset train load threshold. When the train load exceeds the preset load threshold, the train control system generates and sends an overcrowding alarm instruction.

[0069] The train load monitoring process based on the train load monitoring method of the joint video monitoring system is introduced. Next, the train load monitoring process based on the train load monitoring method of the joint ticket information system is introduced:

[0070] The train control system obtains the ticket information from the ticket information system. Specifically, it obtains the ticket information data from the ticket information system, determines the number of passengers through the ticket information data, and adds the number of passengers to the number of drivers and crew members scheduled to board the train to obtain the train capacity.

[0071] Then, as is the case with the processing procedure in the train load monitoring method of the above-mentioned joint ticket information system, the train passengers are substituted into the preset train load calculation formula to calculate the train load, and it is determined whether the calculated train load exceeds the preset train load threshold. When the train load exceeds the preset load threshold, the train control system generates and sends an overcrowding alarm instruction.

[0072] It should be noted that, in theory, the number of train passengers calculated by the train load monitoring method of the joint ticket information system is consistent with that of the joint video surveillance system. However, there are cases where passengers get on the train without buying tickets or buy tickets but do not get on the train, which may lead to the inconsistency between the number of train passengers calculated by the train load monitoring method of the joint ticket information system and that of the joint video surveillance system.

[0073] It is easy to understand that the train load monitoring method of the joint video surveillance system has smaller errors than the train load monitoring method of the joint ticket information system, and the train load monitoring results of the train load monitoring method of the joint video surveillance system are more accurate.

[0074] Therefore, the priority of the train load monitoring method of the joint video monitoring system is set to the highest, followed by the train load monitoring method of the joint ticket information system, and the lowest priority is the train load monitoring method based on air spring pressure monitoring. It can be understood that the higher the priority of each train load monitoring method, the more accurate the corresponding train load monitoring result.

[0075] Optionally, the train control system determines whether each train load monitoring mode is valid according to the priority order of each train load monitoring mode from high to low.

[0076] Step 102: When the video monitoring system is normal, train load monitoring is performed using a train load monitoring method of a joint video monitoring system.

[0077] The train control system first determines whether the video surveillance system is normal. If the video surveillance system is normal, the train load monitoring method of the joint video surveillance system is used to monitor the train load.

[0078] The train load monitoring method of the joint video monitoring system has been described above and will not be repeated here.

[0079] Step 103: When the video monitoring system is abnormal but the ticket information system is normal, train load monitoring is performed using the train load monitoring method of the joint ticket information system.

[0080] When the video monitoring system is abnormal, the train control system will determine whether the passenger ticket information system is normal. If the passenger ticket information system is normal, the train load monitoring method of the joint passenger ticket information system will be used to monitor the train load.

[0081] The train load monitoring method of the joint ticket information system has been described above and will not be repeated here.

[0082] Step 104: When both the video monitoring system and the ticket information system are abnormal, train load monitoring is performed using a train load monitoring method based on air spring pressure monitoring.

[0083] When both the video monitoring system and the ticket information system are abnormal, the train control system will use the train load monitoring method based on air spring pressure monitoring to monitor the train load, which has been described above and will not be repeated here.

[0084] It should be noted that the present application further provides two train load monitoring results that are better than the train load monitoring method based on air spring pressure monitoring. When either the video monitoring system or the passenger ticket information system is operating normally, the purpose of real-time monitoring of the train load can be achieved. Compared with the known technology that only uses the train load monitoring method based on air spring pressure monitoring to monitor the train load, the present application has higher reliability.

[0085] In summary, the train load monitoring method provided by the present application is applied to the train control system, and the effectiveness of each train load monitoring method is judged in the order of priority of each train load monitoring method in the train load monitoring method set. When the video monitoring system required in the train load monitoring method of the joint video monitoring system with the highest priority is normal, the train load monitoring method of the joint video monitoring system is used to monitor the train load; when the video monitoring system is abnormal but the ticket information system required in the train load monitoring method of the joint ticket information system with the medium priority is normal, the train load monitoring method of the joint ticket information system is used to monitor the train load; when the above-mentioned video monitoring system and the ticket information system are both abnormal, the train load monitoring is performed based on air spring pressure monitoring. The present application also provides two train load monitoring results with higher accuracy than the train load monitoring methods in the known technology, and the train load monitoring method with the highest accuracy is used first, thereby reducing the situation of misjudging the train overweight to a certain extent and improving the operating efficiency of the train.

[0086] For example, see Figure 3 , an example flow chart of the train load monitoring method provided in this application.

[0087] like Figure 3 As shown, when the video surveillance system and the ticket information system are both normal, the train load is calculated based on the video information in the carriage provided by the video surveillance system.

[0088] If the video monitoring system fails and the ticket information system is normal, the train load is calculated by taking the number of passengers who received the ticket information system and compensated the driver and crew. When both the video monitoring system and the ticket information system are abnormal, the train load monitoring method based on air spring pressure monitoring is adopted.

[0089] Depend on Figure 3 It can be seen that the train monitoring method of the joint video surveillance system is: after the video surveillance system collects the video information in the car, the train control system calculates the train passengers based on the video information in the car, and inputs the train passengers into the calculation formula of the train weight: number of train passengers × per person's load (including luggage, 80kg / person) + empty car mass (actual weighing mass before leaving the factory). After obtaining the train weight, it is determined whether the train weight exceeds the threshold. When it is determined that the train weight exceeds the threshold, the train control system triggers an overcrowding alarm.

[0090] Depend on Figure 3It can be seen that the train load monitoring method of the joint ticket information system is: the ticket information system counts the train ticket information, the train control system receives the train ticket information, and compensates the number of drivers and crew members to calculate the train capacity, and inputs the train capacity into the train weight calculation formula: number of train passengers × per person load (including luggage, 80kg / person) + empty car mass (actual weighing mass before leaving the factory). After obtaining the train weight, it is determined whether the train weight exceeds the threshold. When it is determined that the train weight exceeds the threshold, the train control system triggers an overcrowding alarm.

[0091] Depend on Figure 3 It can be seen that in the train load monitoring method based on air spring pressure monitoring, the train control system collects the air spring pressure value from the air spring pressure sensor, converts the air spring pressure value into the train weight according to the formula, and determines whether the train weight exceeds the threshold. When it is determined that the train weight exceeds the threshold, the train control system triggers the overcrowding alarm.

[0092] A train load monitoring method provided in an embodiment of the present application is introduced above, and a device for executing the above train load monitoring method will be introduced below.

[0093] See also Figure 4 , Figure 4 This is a schematic diagram of the structure of a train load monitoring device provided in this application. Figure 4 As shown, the train load monitoring device comprises:

[0094] The judging unit 10, the first train load monitoring processing unit 20, the second train load monitoring processing unit 30 and the third train load monitoring processing unit 40; wherein:

[0095] The judging unit 10 is used to judge whether each train load monitoring mode is effective in order from high to low according to the priority of each train load monitoring mode in the train load monitoring mode set; the priorities of each train load monitoring mode are, from high to low, the train load monitoring mode of the joint video monitoring system, the train load monitoring mode of the joint ticket information system, and the train load monitoring mode based on air spring pressure monitoring; the higher the priority of each train load monitoring mode, the more accurate the corresponding train load monitoring result;

[0096] A first train load monitoring processing unit 20 is used to monitor the train load by adopting a train load monitoring method of a combined video monitoring system when the video monitoring system is normal;

[0097] The second train load monitoring processing unit 30 performs train load monitoring by adopting the train load monitoring method of the ticket information system when the video monitoring system is abnormal but the ticket information system is normal;

[0098] The third train load monitoring processing unit 40 is used to monitor the train load by adopting a train load monitoring method based on air spring pressure monitoring when both the video monitoring system and the ticket information system are abnormal.

[0099] In one embodiment, the train load monitoring process in the first train load monitoring processing unit 20 includes:

[0100] Acquire real-time video data inside the train from the video surveillance system;

[0101] Determine train occupants through video data;

[0102] Substituting the train passengers into the preset train load calculation formula to calculate the train load;

[0103] Determine whether the train load exceeds a preset train load threshold, and when the train load exceeds the preset train load threshold, generate and send an overcrowding alarm instruction.

[0104] In one embodiment, the first train load monitoring processing unit 20 is specifically used to:

[0105] The video surveillance algorithm is used to process the video data to obtain the train passengers' ticket information system.

[0106] In one embodiment, the first train load monitoring processing unit 20 is specifically used to:

[0107] The video data is processed through target detection, target tracking, behavior recognition and face recognition to obtain the train passengers.

[0108] In one embodiment, the train load monitoring process in the second train load monitoring processing unit 30 includes:

[0109] Obtain ticket information from the ticket information system;

[0110] The train capacity of the ticket information system is determined by the ticket information of the ticket information system and the fixed number of drivers and passengers;

[0111] The train load is calculated by a preset train load calculation formula;

[0112] Determine whether the train load exceeds the preset train load threshold of the ticket information system. When the train load exceeds the preset train load threshold, generate and send an overcrowding alarm instruction of the ticket information system.

[0113] In one embodiment, the first train load monitoring processing unit 20 or the second train load monitoring processing unit 30 calculates the train load by a preset train load calculation formula, including:

[0114] The train load is obtained by multiplying the train passengers by the preset average weight per person and adding the passenger weight to the pre-obtained empty train mass.

[0115] The present application also provides a train load monitoring device. Figure 5 As shown, it shows a schematic diagram of the structure of the train load monitoring device provided by the present application. The train load monitoring device in the embodiment of the present application may include but is not limited to fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 5 The train load monitoring device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0116] like Figure 5 As shown, the train load monitoring device may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 to a random access memory (RAM) 603. When the train load monitoring device is powered on, various programs and data required for the operation of the electronic device are also stored in the RAM 603. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0117] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a memory card, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The train load monitoring device with various devices is shown, but it should be understood that it is not required to implement or have all the devices shown. More or fewer devices may be implemented or have instead.

[0118] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any train load monitoring method provided in the embodiment of the present application.

[0119] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any train load monitoring method provided in the embodiment of the present application.

[0120] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0121] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0122] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0123] The computer program product includes one or more computer-readable instructions. When loading and executing computer-readable instructions on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer-readable instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer-readable instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. Available media may be magnetic media, (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid-state drive (SSD)), etc.

Claims

1. A train load monitoring method, characterized in that: Applied to train control systems, including: According to the priorities of the train load monitoring methods in the train load monitoring method set from high to low, whether the train load monitoring methods are effective is judged in turn; the priorities of the train load monitoring methods from high to low are the train load monitoring method of the joint video monitoring system, the train load monitoring method of the joint ticket information system and the train load monitoring method based on air spring pressure monitoring; the higher the priority of each train load monitoring method, the more accurate the corresponding train load monitoring result; When the video monitoring system is normal, the train load monitoring method of the combined video monitoring system is used to monitor the train load; When the video monitoring system is abnormal but the ticket information system is normal, train load monitoring is performed using the train load monitoring method of the combined ticket information system; In the case that both the video monitoring system and the passenger ticket information system are abnormal, the train load monitoring method based on air spring pressure monitoring is adopted to perform train load monitoring.

2. The train load monitoring method according to claim 1, characterized in that: The train load monitoring process of the train load monitoring mode of the joint video monitoring system includes: Acquiring real-time video data in the train from the video monitoring system; Determining the train passengers through the real-time video data; The train load is calculated by a preset train load calculation formula; It is determined whether the train load exceeds a preset train load threshold value, and when the train load exceeds the preset train load threshold value, an overcrowding alarm instruction is generated and sent.

3. The train load monitoring method according to claim 2, characterized in that: The determining of the train passengers through the real-time video data comprises: The real-time video data is processed using a video monitoring algorithm to obtain the train passengers.

4. The train load monitoring method according to claim 3, characterized in that: The adopting a video monitoring algorithm to process the real-time video data to obtain the train passengers includes: The real-time video data is processed through target detection, target tracking, behavior recognition and face recognition to obtain the train passengers.

5. The train load monitoring method according to claim 1, characterized in that: The train load monitoring process of the train load monitoring mode of the joint ticket information system includes: Acquiring ticket information from the ticket information system; Determining the train crew based on the ticket information and the fixed number of drivers and passengers; The train load is calculated by a preset train load calculation formula; It is determined whether the train load exceeds the preset train load threshold value, and when the train load exceeds the preset train load threshold value, the overcrowding alarm instruction is generated and sent.

6. The train load monitoring method according to claim 2 or 5, characterized in that: The train load is calculated by a preset train load calculation formula, including: The passenger weight is obtained by multiplying the train passengers by a preset per capita weight, and the passenger weight is added to the pre-acquired empty train mass to obtain the train load.

7. A train load monitoring device, characterized in that: include: A judgment unit, a first train load monitoring processing unit, a second train load monitoring processing unit and a third train load monitoring processing unit; wherein: The judging unit is used to judge whether each train load monitoring mode is effective in order from high to low according to the priority of each train load monitoring mode in the train load monitoring mode set; the priorities of each train load monitoring mode are, from high to low, the train load monitoring mode of the joint video monitoring system, the train load monitoring mode of the joint ticket information system, and the train load monitoring mode based on air spring pressure monitoring; the higher the priority of each train load monitoring mode, the more accurate the corresponding train load monitoring result; The first train load monitoring processing unit is used to monitor the train load using the train load monitoring method of the joint video monitoring system when the video monitoring system is normal; The second train load monitoring processing unit, when the video monitoring system is abnormal but the ticket information system is normal, performs train load monitoring using the train load monitoring method of the joint ticket information system; The third train load monitoring processing unit is used to perform train load monitoring by adopting the train load monitoring method based on air spring pressure monitoring when both the video monitoring system and the passenger ticket information system are abnormal.

8. A train load monitoring device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the train load monitoring device can implement the train load monitoring method as described in any one of claims 1 to 6.

9. A computer program product, characterized in that It comprises computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the train load monitoring method as claimed in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the train load monitoring method as described in any one of claims 1 to 6.

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