PAPI lamp monitoring method, system, medium, device and program product

Abstract

The invention provides a PAPI lamp monitoring method and system, a medium, a device and a program product. The method comprises the following steps: acquiring real-time video data of a PAPI lamp from an acquired video picture through a real-time video stream transmission protocol; analyzing the real-time video data by using a pre-trained machine learning model to obtain the state of the PAPI lamp; and when the obtained state of the PAPI lamp indicates that the PAPI lamp has a fault, carrying out corresponding fault early warning. By utilizing the technical scheme, the fault condition of the PAPI lamp can be monitored and early warned in real time, so that the safety risk of an airport runway and air transportation is reduced, and the working efficiency of daily operation and maintenance of an airport is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of precision approach channel indicators, and in particular to a PAPI light monitoring method, system, medium, device and program product. Background Art

[0002] In aviation, the Precision Approach Path Indicator (PAPI) is a key navigational aid used to provide pilots with visual information about the aircraft's position relative to the ideal glide path.

[0003] PAPI lights are usually installed near the touchdown area of ​​the runway, projecting down the glide path at an angle of +3 degrees to guide the aircraft to glide at the correct angle. PAPI lights are composed of four high-brightness bulbs, each of which consists of a light source, a red filter, and two lenses. Through these structures, the white light beam emitted by the light source passes through the red filter, and the upper part of the light beam turns red, while the lower part remains white, thereby helping the pilot to determine whether the aircraft's glide path is correct. Therefore, if the failure of the PAPI light is not discovered and handled in time, it will affect the pilot's runway landing and cause great aviation hazards.

[0004] Currently, traditional airport runway PAPI lights are at risk of long-term operation and the system can generally only monitor and warn of a primary cable loop fault and send out a warning signal, without the ability to alarm for secondary cable faults and PAPI light failures. This means that if the main cable fails, the monitoring system can trigger an alarm and prompt maintenance personnel to inspect, but once the main cable is repaired or replaced, if a new cable fault occurs again, the system may not be able to immediately identify and report these subsequent faults. This may cause the PAPI light monitoring system to lose function in the period between maintenance inspections without being noticed, increasing flight safety risks. Even more problematic is that the monitoring system of traditional PAPI lights lacks an immediate alarm function for light failures, meaning that even if a lamp fails, such as the light source goes out, the optical system is damaged, or there is a power supply problem, the monitoring system cannot actively identify and report it in a timely manner until the pilot feedback or routine inspection. This lag greatly increases flight risks. Summary of the invention

[0005] The embodiments of the present invention provide a PAPI lamp monitoring method, system, medium, device and program product, which are intended to use a pre-trained machine learning model to perform real-time monitoring and early warning of PAPI lamp fault conditions, thereby reducing the safety risks of airport runways and air transportation, and significantly improving the work efficiency of daily airport operations and maintenance.

[0006] In order to achieve the above object, on the one hand, a PAPI lamp monitoring method is provided, the method comprising the following steps:

[0007] Acquire real-time video data of a PAPI lamp from a captured video screen through a real-time video stream transmission protocol, wherein the PAPI lamp includes a plurality of bulbs;

[0008] The real-time video data is analyzed using a pre-trained machine learning model to obtain the state of the PAPI lamp, wherein the analysis includes: extracting bulb information of all bulbs of the PAPI lamp in the real-time video data, and analyzing the on-off mode of all bulbs and the synchronization of all bulbs according to the extracted bulb information of all bulbs; wherein the bulb information includes the brightness of the bulb, the color of the bulb and the on-off time of the bulb; the state of the PAPI lamp includes: the brightness consistency of all bulbs, the color accuracy of all bulbs, the on-off synchronization of all bulbs and the stability of the brightness and color of all bulbs;

[0009] When the obtained status of the PAPI lamp indicates that the PAPI lamp is faulty, a corresponding fault warning is performed, and the fault warning includes: bulb synchronization warning, bulb failure warning, cable connection warning, environmental adaptability warning, power supply failure warning and / or power supply abnormality warning.

[0010] Preferably, the PAPI lamp monitoring method, after acquiring the real-time video data and before using a pre-trained machine learning model to analyze the real-time video data, further includes: preprocessing the real-time video data to obtain preprocessed video data, wherein the preprocessing includes: denoising, contrast enhancement and / or color correction.

[0011] Preferably, in the PAPI lamp monitoring method, the bulb synchronization warning includes: a warning issued when the lighting of the four bulbs of the PAPI lamp is not synchronized;

[0012] The bulb failure warning includes: a warning issued when at least one bulb in the PAPI lamp meets a predetermined abnormal lighting condition; and a warning issued when the color of at least one bulb in the PAPI lamp meets a predetermined color abnormality condition;

[0013] The power supply failure warning includes: a warning issued when the brightness of all bulbs of the PAPI lamp meets a predetermined uniformity abnormality condition;

[0014] The power supply abnormality warning includes: a warning issued when all the bulbs of the PAPI lamp are delayed or flickering in a predetermined time period; and a warning issued when the brightness and color of all the bulbs of the PAPI lamp flicker or the output of light is unstable;

[0015] The cable connection warning includes: a warning issued when the on-off pattern of at least one bulb in the PAPI lamp meets a predetermined abnormal condition;

[0016] The environmental adaptability warning includes: an abnormality issued when at least one bulb in the PAPI lamp has a predetermined abnormal situation under different environmental conditions; the environmental conditions include: time and weather.

[0017] Preferably, in the PAPI lamp monitoring method, the predetermined color abnormality condition includes: an early warning issued when the colors of the upper half and the lower half of the bulb do not meet predetermined clear and distinct conditions.

[0018] Preferably, in the PAPI lamp monitoring method, the PAPI lamp comprises 4 bulbs.

[0019] Preferably, the PAPI lamp monitoring method further comprises: converting the extracted bulb information of all the bulbs, the status of the PAPI lamp and / or the fault warning information into XML format for storage.

[0020] In another aspect, a PAPI lamp monitoring system includes:

[0021] Camera, used to collect video images of PAPI lights in real time;

[0022] A real-time video analysis module uses a pre-trained machine learning model to analyze the real-time video data to obtain the state of the PAPI lamp, wherein the analysis includes: extracting the bulb information of all the bulbs of the PAPI lamp in the real-time video data, and analyzing the on and off modes of all the bulbs and the synchronization of all the bulbs according to the extracted bulb information of all the bulbs; wherein the bulb information includes the brightness of the bulb, the color of the bulb and the on and off time of the bulb; the state of the PAPI lamp includes: the brightness consistency of all the bulbs, the color accuracy of all the bulbs and the on and off synchronization of all the bulbs and the stability of the brightness and color of all the bulbs;

[0023] The early warning module performs corresponding fault early warning when the obtained status of the PAPI lamp indicates that the PAPI lamp is faulty. The fault early warning includes: bulb synchronization early warning, bulb failure early warning, cable connection early warning, environmental adaptability early warning, power supply failure early warning and / or power supply abnormality early warning.

[0024] On the other hand, a PAPI lamp monitoring device is provided, which includes a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of any of the PAPI lamp monitoring methods described above.

[0025] On the other hand, a computer-readable storage medium is provided, wherein at least one program is stored in the storage medium, and the at least one program is executed by a processor to implement the steps of any of the PAPI lamp monitoring methods described above.

[0026] On the other hand, a computer program product comprises a computer program, wherein when the computer program is executed by a processor, the steps of any of the above-mentioned PAPI lamp monitoring methods are implemented.

[0027] The above technical solution has the following technical effects:

[0028] The technical solution of the embodiment of the present invention uses a pre-trained machine learning model to achieve real-time monitoring and early warning of PAPI lamp faults; it monitors and records the brightness consistency, color accuracy, on-off synchronization, and brightness and color stability of the four bulbs of the PAPI lamp in real time, and classifies and warns of these status information, thereby achieving accurate early warning of PAPI lamp fault anomalies, improving the efficiency and accuracy of PAPI lamp monitoring and management, reducing the on-site inspection time and cost of airport employees, and greatly improving work efficiency.

[0029] In a further embodiment, real-time video is captured by a high-definition camera and transmitted using a real-time video stream transmission protocol, the real-time video is pre-processed, and the video content is analyzed using a pre-trained model to accurately extract the working status information of the four high-brightness bulbs of the PAPI lamp. By real-time monitoring and early warning of the working status information of the four high-brightness bulbs of the PAPI lamp, and storing the working status information of the four high-brightness bulbs, automatic and accurate identification and recording of the status of the PAPI lights on the runway of a civil aviation airport is achieved, thereby reducing the risks of airport runways and air transportation, and providing strong support for airport runway management and civil aviation safety transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of a method for monitoring a PAPI lamp according to an embodiment of the present invention;

[0031] Figure 2 FIG. 4 is a device diagram of a PAPI lamp monitoring method according to another embodiment of the present invention. DETAILED DESCRIPTION

[0032] To further illustrate the various embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention, which are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, a person of ordinary skill in the art should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0033] The present invention will now be further described with reference to the accompanying drawings and specific implementation methods.

[0034] Embodiment 1:

[0035] In order to improve the efficiency of daily airport operation and maintenance and further reduce the safety risks of airport runways and air transportation, this embodiment provides a PAPI light monitoring method. Figure 1 FIG. 1 is a flow chart of a method for monitoring a PAPI lamp according to an embodiment of the present invention. Figure 1 As shown, the method of this embodiment includes:

[0036] Acquire real-time video data of a PAPI lamp from a captured video screen through a real-time video stream transmission protocol, wherein the PAPI lamp includes a plurality of bulbs;

[0037] The real-time video data is analyzed using a pre-trained machine learning model to obtain the state of the PAPI lamp, wherein the analysis includes: extracting the bulb information of all bulbs of the PAPI lamp in the real-time video data, and analyzing the on and off modes of all bulbs and the synchronization of all bulbs according to the extracted bulb information of all bulbs; wherein the bulb information includes the brightness of the bulb, the color of the bulb and the on and off time of the bulb; the state of the PAPI lamp includes: the brightness consistency of all bulbs, the color accuracy of all bulbs, the on and off synchronization of all bulbs and the stability of the brightness and color of all bulbs; in a specific implementation, the predetermined machine learning model is trained using the bulb information of the historical PAPI lamp, the corresponding PAPI lamp state information and the fault warning information;

[0038] When the obtained PAPI lamp status indicates that the PAPI lamp is faulty, a corresponding fault warning is performed, and the fault warning includes: bulb synchronization warning, bulb failure warning, cable connection warning, environmental adaptability warning, power supply failure warning and / or power supply abnormality warning. Those skilled in the art know that other existing fault types can also be added.

[0039] Preferably, the PAPI lamp monitoring method of the embodiment of the present invention further includes, after acquiring real-time video data and before analyzing the real-time video data using a pre-trained machine learning model:

[0040] The real-time video data is preprocessed to obtain preprocessed video data, wherein the preprocessing includes: denoising, contrast enhancement and / or color correction.

[0041] Preferably, the PAPI lamp monitoring method of the embodiment of the present invention comprises:

[0042] Bulb synchronization warning includes: warning issued when the four bulbs of the PAPI lamp are not on and off synchronously;

[0043] The bulb failure warning includes: a warning issued when at least one bulb in the PAPI lamp meets a predetermined abnormal lighting condition; and a warning issued when the color of at least one bulb in the PAPI lamp meets a predetermined abnormal color condition;

[0044] Power supply failure warnings include: Warnings issued when the brightness of all bulbs of the PAPI lamp meets the predetermined uniformity abnormality condition;

[0045] Power supply abnormality warnings include: warnings issued when all bulbs of the PAPI lamp are delayed or flickering in the predetermined time period; and warnings issued when the brightness and color of all bulbs of the PAPI lamp flicker or the output of light is unstable;

[0046] The cable connection warning includes: a warning issued when the on-off pattern of at least one bulb in the PAPI lamp meets a predetermined abnormal condition;

[0047] Environmental adaptability warnings include: an abnormality issued when at least one bulb in the PAPI lamp exhibits a predetermined abnormal condition under different environmental conditions; environmental conditions include: time and weather. In specific implementations, time includes, for example, day or night; weather includes, for example, rainy days, sunny days, windy days, heavy rains, etc.

[0048] Preferably, in the PAPI lamp monitoring method of the embodiment of the present invention, the predetermined color abnormality condition includes: an early warning issued when the colors of the upper half and the lower half of the bulb do not meet the predetermined clear and distinct conditions.

[0049] Preferably, the PAPI lamp monitoring method according to the embodiment of the present invention is characterized in that the PAPI lamp includes 4 bulbs.

[0050] Preferably, the PAPI lamp monitoring method of the embodiment of the present invention further includes:

[0051] The extracted bulb information of all bulbs, the status of the PAPI lamps and / or the fault warning information are converted into XML format for storage.

[0052] Embodiment two:

[0053] The embodiment of the present invention provides a monitoring system for PAPI lights. On the one hand, it provides a monitoring solution for secondary cable failures and light failures of PAPI lights at civil aviation airports, reducing the risks of airport runways and air transportation. On the other hand, it establishes a mechanism for monitoring, video storage and review, and abnormal fault alarms for PAPI lights at civil aviation airports. The monitoring system significantly reduces the time and cost of on-site inspections by airport employees, and while improving work efficiency, it can also greatly reduce the inspection error rate. And through the monitoring system for PAPI lights, the latest information on PAPI lights can be obtained in the first place, providing strong support for airport runway management and civil aviation safety transportation.

[0054] In a specific implementation, the PAPI light monitoring system includes a camera, a real-time video analysis module, an early warning module, etc. Preferably, the camera collects the video image of the PAPI light in real time and transmits the video data to the real-time video analysis module via the video streaming protocol (RTSP).

[0055] Preferably, the video data is preprocessed, wherein the preprocessing includes steps such as denoising, contrast enhancement, and color correction on the collected video data to improve the accuracy of subsequent analysis.

[0056] Preferably, the real-time video analysis module uses a pre-trained machine learning model to analyze the pre-processed real-time video data to obtain the status of the PAPI lamp. The analysis of the real-time video data includes: extracting the bulb information of all bulbs of the PAPI lamp in the real-time video data, and analyzing the on and off mode of all bulbs and the synchronization of all bulbs according to the extracted bulb information of all bulbs. The bulb information includes the brightness of the bulb, the color of the bulb and the on and off time of the bulb. The status of the PAPI lamp includes: the brightness consistency of all bulbs, the color accuracy of all bulbs, the on and off synchronization of all bulbs, and the stability of the brightness and color of all bulbs.

[0057] Preferably, the early warning module performs a corresponding fault early warning when the status of the PAPI lamp indicates that the PAPI lamp is faulty.

[0058] In a specific implementation, the extracted bulb information of all bulbs, the status of the PAPI lamps and / or the fault warning information are converted into XML format for storage.

[0059] In a specific implementation, the status of the PAPI light includes:

[0060] Lamp synchronization, check whether all lamps light up and go out synchronously to ensure the consistency of indication;

[0061] Lamp fault status, identifying if a lamp is faulty, such as a single lamp going out or flickering;

[0062] Cable connection status: by analyzing the on and off pattern of the light bulb, it can indirectly detect whether the cable connection is stable;

[0063] Environmental adaptability status, monitoring the performance of PAPI lamps under different environmental conditions, such as night, rainy days, etc.

[0064] In one specific implementation, a PAPI lamp monitoring system records status data of the PAPI lamp and performs long-term analysis to optimize monitoring strategies and maintenance plans.

[0065] In a specific implementation, the characteristics of the PAPI lamp when working normally are: consistent brightness, that is, the brightness of each bulb of the PAPI lamp is uniform and consistent, without obvious brightness differences; the upper half of each bulb of the PAPI lamp displays red light, and the lower half displays white light, and the colors are clear and distinct; the lighting and extinguishing of each bulb of the PAPI lamp are synchronized, without delay or flickering; the brightness and color of each bulb of the PAPI lamp remain stable for a certain period of time, without flickering or unstable light output.

[0066] Embodiment three:

[0067] The present invention also provides a monitoring device for a PAPI lamp, such as Figure 2 As shown, the device includes a processor 201, a memory 202, a bus 203, and a computer program stored in the memory 202 and executable on the processor 201. The processor 201 includes one or more processing cores. The memory 202 is connected to the processor 201 via the bus 203. The memory 202 is used to store program instructions. When the processor executes the computer program, the steps in the above method embodiment of the first embodiment of the present invention are implemented.

[0068] Further, as an executable solution, the monitoring device of the PAPI lamp can be a computer unit, and the computer unit can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The computer unit can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the composition structure of the above-mentioned computer unit is only an example of a computer unit and does not constitute a limitation on the computer unit. It can include more or less components than the above, or a combination of certain components, or different components. For example, the computer unit can also include input and output devices, network access devices, buses, etc., which are not limited in the embodiments of the present invention.

[0069] Further, as an executable solution, the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, and various interfaces and lines are used to connect the various parts of the entire computer unit.

[0070] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the computer unit by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0071] Embodiment 4:

[0072] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method in the embodiment of the present invention are implemented.

[0073] If the module / unit integrated in the computer unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory) and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0074] Embodiment five:

[0075] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method described above are implemented.

[0076] Although the present invention has been specifically shown and described in conjunction with the preferred embodiments, it should be understood by those skilled in the art that various changes may be made to the present invention in form and details without departing from the spirit and scope of the present invention as defined by the appended claims, all of which are within the scope of protection of the present invention.

Claims

1. A method for monitoring a PAPI lamp, characterized in that: include: Acquire real-time video data of a PAPI lamp from a captured video screen through a real-time video stream transmission protocol, wherein the PAPI lamp includes a plurality of bulbs; The real-time video data is analyzed using a pre-trained machine learning model to obtain the state of the PAPI lamp, wherein the analysis includes: extracting bulb information of all bulbs of the PAPI lamp in the real-time video data, and analyzing the on-off mode of all bulbs and the synchronization of all bulbs according to the extracted bulb information of all bulbs; wherein the bulb information includes the brightness of the bulb, the color of the bulb and the on-off time of the bulb; the state of the PAPI lamp includes: the brightness consistency of all bulbs, the color accuracy of all bulbs, the on-off synchronization of all bulbs and the stability of the brightness and color of all bulbs; When the obtained status of the PAPI lamp indicates that the PAPI lamp is faulty, a corresponding fault warning is performed, and the fault warning includes: bulb synchronization warning, bulb failure warning, cable connection warning, environmental adaptability warning, power supply failure warning and / or power supply abnormality warning.

2. The PAPI lamp monitoring method according to claim 1, characterized in that: After acquiring the real-time video data and before using the pre-trained machine learning model to analyze the real-time video data, the method further includes: The real-time video data is preprocessed to obtain preprocessed video data, wherein the preprocessing includes: denoising, contrast enhancement and / or color correction.

3. The PAPI lamp monitoring method according to claim 1, characterized in that: The bulb synchronization warning includes: a warning issued when the lighting and extinguishing of the four bulbs of the PAPI lamp are not synchronized; The bulb failure warning includes: a warning issued when at least one bulb in the PAPI lamp meets a predetermined abnormal lighting condition; and a warning issued when the color of at least one bulb in the PAPI lamp meets a predetermined color abnormality condition; The power supply failure warning includes: a warning issued when the brightness of all bulbs of the PAPI lamp meets a predetermined uniformity abnormality condition; The power supply abnormality warning includes: a warning issued when all the bulbs of the PAPI lamp are delayed or flickering in a predetermined time period; and a warning issued when the brightness and color of all the bulbs of the PAPI lamp flicker or the output of light is unstable; The cable connection warning includes: a warning issued when the on-off pattern of at least one bulb in the PAPI lamp meets a predetermined abnormal condition; The environmental adaptability warning includes: an abnormality issued when at least one bulb in the PAPI lamp has a predetermined abnormal situation under different environmental conditions; the environmental conditions include: time and weather.

4. The PAPI lamp monitoring method according to claim 3, characterized in that: The predetermined color abnormality condition includes: an early warning issued when the colors of the upper half and the lower half of the light bulb do not meet the predetermined clear and distinct conditions.

5. The PAPI lamp monitoring method according to claim 1, characterized in that: The PAPI lamp includes 4 bulbs.

6. The PAPI lamp monitoring method according to claim 1, characterized in that: Also includes: The extracted bulb information of all the bulbs, the status of the PAPI lamp and / or the fault warning information are converted into XML format for storage.

7. A PAPI lamp monitoring system, characterized in that: include: Camera, used to collect video images of PAPI lights in real time; A real-time video analysis module uses a pre-trained machine learning model to analyze the real-time video data to obtain the state of the PAPI lamp, wherein the analysis includes: extracting the bulb information of all the bulbs of the PAPI lamp in the real-time video data, and analyzing the on and off modes of all the bulbs and the synchronization of all the bulbs according to the extracted bulb information of all the bulbs; wherein the bulb information includes the brightness of the bulb, the color of the bulb and the on and off time of the bulb; the state of the PAPI lamp includes: the brightness consistency of all the bulbs, the color accuracy of all the bulbs, the on and off synchronization of all the bulbs and the stability of the brightness and color of all the bulbs; The early warning module performs corresponding fault early warning when the obtained status of the PAPI lamp indicates that the PAPI lamp is faulty. The fault early warning includes: bulb synchronization early warning, bulb failure early warning, cable connection early warning, environmental adaptability early warning, power supply failure early warning and / or power supply abnormality early warning.

8. A PAPI lamp monitoring device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the steps of the PAPI lamp monitoring method as claimed in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The storage medium stores at least one program, and the at least one program is executed by a processor to implement the steps of the PAPI lamp monitoring method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the PAPI lamp monitoring method as described in any one of claims 1 to 6 are implemented.

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