Multi-source information fusion airport runway intelligent monitoring method and system

Abstract

The application relates to a multi-source information fusion airport runway intelligent monitoring method and system, and relates to the field of airport runway monitoring technology, which comprises the following steps: collecting radar monitoring microwaves of a runway for analysis to determine the positions of interference wave sources in the runway; performing microwave signal analysis on the positions of the interference wave sources to determine microwave interference types and interference existing time; matching an adjustment wave band corresponding to a weakening microwave interference type in a preset wave band database; based on the adjustment wave band, indicating a preset radar monitoring device to perform monitoring wave band adjustment, and marking the positions of the interference wave sources to generate a to-be-checked path; performing image collection on the to-be-checked path and performing foreign matter image feature analysis to determine dangerous foreign matters and issue cleaning instructions. The application has the effect of improving the accuracy of runway abnormal monitoring results.

Description

Technical Field

[0001] This application relates to the field of airport runway monitoring technology, and in particular to a multi-source information fusion intelligent monitoring method and system for airport runways. Background Technology

[0002] Airport runways are auxiliary roads for aircraft to take off and land stably. During their long service life, they are subject to the influence of the natural environment and climate, which causes varying degrees of changes in the ground and foundation, thus affecting aviation safety and requiring close monitoring of anomalies.

[0003] In related technologies, when monitoring anomalies on airport runways, radar systems are used to automatically monitor the airport surface. By transmitting microwave signals to the runway and receiving and analyzing the reflected signals, the changes in the runway's ground and foundation parameters can be determined, thereby promptly determining whether the runway needs maintenance.

[0004] Regarding the aforementioned technologies, during the automatic monitoring of the runway, the presence of transportation vehicles or instruments that generate microwave signals within the runway can easily affect the emitted microwave signals, causing deviations in the monitoring results. Summary of the Invention

[0005] To improve the accuracy of runway anomaly monitoring results, this application provides a multi-source information fusion intelligent monitoring method and system for airport runways.

[0006] Firstly, this application provides a multi-source information fusion method for intelligent monitoring of airport runways, employing the following technical solution:

[0007] A multi-source information fusion method for intelligent monitoring of airport runways includes:

[0008] Step S1: Collect and analyze the radar monitoring microwaves of the runway to determine the location of interference wave sources in the runway;

[0009] Step S2: Perform microwave signal analysis on the location of the interference source to determine the type of microwave interference and the duration of its presence;

[0010] Step S3: Match the adjustment band corresponding to the type of microwave interference reduction in the preset band database;

[0011] Step S4: Adjust the monitoring band based on the preset radar monitoring device according to the adjustment band indication, and mark the location of the interference source to generate the path to be checked;

[0012] Step S5: Acquire images of the path to be checked and perform foreign object image feature analysis to identify dangerous foreign objects and issue a cleanup command.

[0013] Optionally, when analyzing the radar monitoring microwaves of the runway in step S1, the following may be included:

[0014] Analyze the takeoff and landing missions of the airport runways to determine which runways are not currently used for takeoff and landing missions.

[0015] Retrieve historical maintenance data for runways not used for takeoff and landing missions to determine the maintenance area and time in the historical maintenance data and collect the current monitoring time;

[0016] The service life of the runway after maintenance is determined based on the current monitoring time and maintenance time.

[0017] If the runway's service life exceeds the preset effective service life, the runway will be marked as a runway to be inspected, and a radar monitoring command will be issued to conduct microwave inspection on the runway to be inspected.

[0018] Optionally, when marking a runway as a runway to be inspected, the method may also include:

[0019] Analyze the runway to be inspected to determine the runway type and corresponding aircraft service type information, and the aircraft taxiing trajectory.

[0020] Runway areas are divided based on aircraft taxiing trajectories to determine landing and taxiing areas, and the runway detection cycles corresponding to the landing and taxiing areas in the preset monitoring trajectory database are matched.

[0021] Based on the runway inspection cycle, runway surface deformation is detected in the landing area to determine the runway surface deformation parameters.

[0022] The analysis is based on the runway surface deformation parameters to determine the runway pavement deformation ratio. When the pavement deformation ratio is within the preset range of the deformation ratio to be inspected, the deformation area is marked and a pavement maintenance prompt is issued.

[0023] Optionally, when performing foreign object image feature analysis in step S5, the method may also include:

[0024] Microwave reflection signals from the area where the hazardous foreign object is located are collected and analyzed. When the microwave reflection signal is the same as the preset metal reflection signal, the metal foreign object model is analyzed based on the reflection signal.

[0025] Feature identification based on the metal foreign object model is used to determine the source of the metal foreign object and to analyze whether the metal foreign object has cracking characteristics;

[0026] If present, the metal foreign object is marked with its location, and the location of the metal foreign object is detected using a preset homologous metal detection strategy.

[0027] Based on the cleaning command, metal foreign objects at the same metal location and the metal foreign object location are cleaned and recycled.

[0028] Optional, preset homologous metal detection strategies include:

[0029] Based on the cracking characteristics and the metal foreign object model, the number and area of ​​surface notches with cracking characteristics are determined.

[0030] The number and area of ​​surface notches are analyzed to determine the amount of missing metal and the volume of the missing metal.

[0031] The actual number of missing metals causing interference is determined by comparing the metal volume with the preset effective interference volume.

[0032] Based on the actual number of missing metals, the radar detection range in the preset detection parameter database is matched, and a detection command for the same source metal is issued.

[0033] Optionally, when cleaning and recycling metal foreign objects at both the same metal location and the metal foreign object location, the process may also include:

[0034] Pre-collected airport weather information and runway visible light intensity are analyzed to determine the airport weather type and runway illumination.

[0035] When the airport weather type is the same as the preset extreme weather type, compare and analyze whether the runway illumination is less than the preset basic visible brightness range;

[0036] If the value is less than the preset value, the preset marking laser will mark the location of the original metal and the location of the foreign metal object.

[0037] Optionally, when determining the airport weather type, the following may also be included:

[0038] Comparative analysis of airport weather types was conducted. When the airport weather type was snowfall, radar reflection signal parameters were collected and analyzed to determine the reduction ratio of reflected waves.

[0039] The intensity of the reflected wave is determined by calculation based on the percentage decrease in the reflected wave intensity.

[0040] When the intensity of the reflected wave is less than the preset reference reflected wave intensity, the location of the dangerous object is tracked to determine its real-time position.

[0041] Optionally, when tracking hazardous foreign objects, the following may also be included:

[0042] To determine the rate of change of position of hazardous foreign objects, a distance analysis of their positional changes is performed.

[0043] The foreign objects are sorted according to the magnitude of their position change rate to determine the priority order for removal.

[0044] Cleaning instructions are generated based on the priority order of foreign object removal.

[0045] Secondly, this application provides a multi-source information fusion intelligent monitoring system for airport runways, which adopts the following technical solution:

[0046] A multi-source information fusion intelligent monitoring system for airport runways includes:

[0047] The interference source monitoring module collects and analyzes radar-monitored microwave data from the runway to determine the location of interference sources within the runway.

[0048] The interference source analysis module performs microwave signal analysis on the location of the interference source to determine the type of microwave interference and the duration of the interference.

[0049] Match the adjustment band corresponding to the type of microwave interference reduction in the preset band database;

[0050] The interference source adjustment module adjusts the monitoring band based on the preset radar monitoring device indicated by the adjustment band, and marks the location of the interference source to generate a path to be checked.

[0051] The foreign object removal module acquires images of the path to be checked and performs foreign object image feature analysis to identify dangerous foreign objects and issue removal commands.

[0052] In summary, this application includes at least one of the following beneficial technical effects:

[0053] 1. Microwave detection using radar is used to identify vehicles and instruments that generate interference on the runway. The corresponding detection microwaves are adjusted to different monitoring frequencies to effectively identify foreign objects on the runway that may interfere with normal aircraft takeoff and landing. Image recognition is then used for analysis to further improve the accuracy of foreign object detection and help maintain the safety of aircraft on the runway.

[0054] 2. Divide the runway into landing and taxiing areas, and match corresponding detection parameters to different areas to perform runway surface monitoring with different detection cycles for different runway areas. This allows runway areas with different stresses to be effectively monitored, facilitating timely maintenance when runway surface deformation occurs and reducing the impact on aircraft taxiing and landing.

[0055] 3. Locate and mark the positions of metallic foreign objects on the runway and those from the same source to make the search for metallic foreign objects more comprehensive and less likely to miss any. This will help further reduce the probability that metallic foreign objects on the runway surface will affect the safety of aircraft take-off and landing. At the same time, prioritize the recovery of foreign objects according to different extreme weather conditions so that foreign objects that are easily moved by the weather can be cleared first, which will improve the cleanup effect and reduce interference with aircraft. Attached Figure Description

[0056] Figure 1 This is a flowchart of steps S1 to S5 in this application.

[0057] Figure 2 This is a flowchart of steps S101 to S104 in this application.

[0058] Figure 3 This is a flowchart of steps S1041 to S1044 in this application.

[0059] Figure 4 This is a flowchart of steps S501 to S504 in this application.

[0060] Figure 5 This is a flowchart of steps S5031 to S5034 in this application.

[0061] Figure 6 This is a flowchart of steps S5041 to S5043 in this application.

[0062] Figure 7 This is a flowchart of steps S5044 to S5049 in this application. Detailed Implementation

[0063] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figure 1-7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0064] The embodiments of the present invention will now be described in further detail with reference to the accompanying drawings.

[0065] This application discloses a multi-source information fusion intelligent monitoring method for airport runways. It analyzes radar microwaves from the monitored runway to locate the source of interference that causes the radar microwaves to detect the interference. The method then adjusts the radar's detection band to maintain the reliability of microwave detection. Furthermore, it performs foreign object image analysis on the location of the interference source, thus forming a multi-source information integrated runway foreign object monitoring system, which helps improve the accuracy of foreign object detection results.

[0066] Reference Figure 1 The method flow of the multi-source information fusion intelligent monitoring method for airport runways includes the following steps:

[0067] Step S1: Collect and analyze the radar monitoring microwaves of the runway to determine the location of interference wave sources in the runway;

[0068] Multiple monitoring radars are installed along the length of the airport runway at certain intervals to emit monitoring microwaves of corresponding frequency bands. By analyzing the return signals of the monitoring microwaves, it can be determined whether there is an interference source. In this application, the interference source refers to vehicles on the runway, instruments that can transmit radio waves, etc.

[0069] Step S2: Perform microwave signal analysis on the location of the interference source to determine the type of microwave interference and the duration of the interference.

[0070] The type of interference source indicates the method of interference that generates the microwaves used for detection. For example, road surface detectors installed on airport maintenance vehicles or personnel carrying wireless devices will generate microwaves during operation, thus interfering with detection radars operating in similar frequency bands. The duration of the interfering wave source is statistically analyzed and defined as the interference duration for later analysis.

[0071] Step S3: Match the adjustment band corresponding to the type of microwave interference reduction in the preset band database;

[0072] The band database is a pre-established database of tuning bands by staff. It stores tuning bands that can attenuate corresponding microwaves and the corresponding interference types. When an interference type is input, it can automatically match and output the tuning band.

[0073] Step S4: Adjust the monitoring band based on the preset radar monitoring device according to the adjustment band indication, and mark the location of the interference source to generate the path to be checked;

[0074] The path to be verified is formed by connecting the locations of multiple interference sources in sequence. After matching and finding the corresponding adjustment band, the radar monitoring device performs the corresponding band adjustment, thereby making the radar monitoring device less susceptible to the influence of microwave signals.

[0075] Step S5: Acquire images of the path to be checked and perform foreign object image feature analysis to identify dangerous foreign objects and issue a cleanup command.

[0076] High-definition cameras capable of capturing images of the runway surface are installed inside the airport runway. By comparing and analyzing the captured images with pre-defined foreign object image features, it can be determined whether a foreign object exists. When a foreign object is found on the airport runway, a cleanup command is issued, and the control center then cleans up the foreign object accordingly based on the cleanup command.

[0077] Reference Figure 2 When analyzing the radar monitoring microwaves of the runway in step S1, it includes:

[0078] Step S101: Analyze the takeoff and landing missions of the airport runway to determine which runway is not for takeoff and landing missions;

[0079] Before collecting and analyzing radar-monitored microwaves, analyzing the take-off and landing tasks of airport runways can identify runways that are not used for take-off and landing and define them as non-take-off and landing runways. By filtering non-take-off and landing runways, the system can avoid using runways and prevent the detected microwaves from affecting aircraft or other vehicles on the runways.

[0080] Step S102: Retrieve historical maintenance data of non-takeoff and landing runways to determine the maintenance area and maintenance time in the historical maintenance data and collect the current monitoring time;

[0081] Historical maintenance data contains information about past runway inspections and maintenance. By accessing this data, the maintenance areas of the currently identified non-takeoff and landing runway during past maintenance can be determined. Data collected at the current monitoring time is for further analysis.

[0082] Step S103: Calculate and determine the service life of the runway after maintenance based on the current monitoring time and maintenance time;

[0083] By calculating the difference between the current monitoring time and the maintenance time, we can determine the runway's service life after maintenance, and define this service life as the service duration.

[0084] Step S104: If the runway service life is longer than the preset effective service life, the runway is marked as a runway to be inspected, and a radar monitoring command is issued to conduct microwave detection on the runway to be inspected.

[0085] Effective service life indicates the duration for which a runway can maintain a good surface condition after maintenance. When the service life exceeds the effective service life, it indicates that the runway is prone to damage. The runway is then marked as a runway to be inspected. Microwave testing is performed on the runway to be inspected by receiving radar monitoring instructions, which allows for more targeted selection of runways that are prone to damage.

[0086] Reference Figure 3 When marking a runway as a runway to be inspected, it also includes:

[0087] Step S1041: Analyze the runway to be inspected to determine the runway type and corresponding service aircraft type information of the aircraft taxiing trajectory;

[0088] Since different aircraft types have different sizes, airports usually have regular runways and dedicated runways for specific aircraft types. Therefore, by analyzing the runway types, we can find the corresponding service aircraft information and the taxiing trajectory of the corresponding aircraft on the runway.

[0089] Step S1042: Divide the runway area based on the aircraft taxi trajectory to determine the landing area and taxiway area, and match the runway detection cycle corresponding to the landing area and taxiway area in the preset monitoring trajectory database;

[0090] By dividing the aircraft's taxiway trajectory, we can identify the landing area and the taxiing area. The difference between these two areas lies in the contact and stress experienced by the aircraft, resulting in a difference in the probability of runway surface damage. The landing area, experiencing greater stress, is more prone to surface damage. Therefore, different taxiway trajectory areas require periodic inspections at different intervals. Compared to long-term monitoring, this reduces energy consumption and extends the lifespan of the radar equipment. The monitoring trajectory database is pre-established by staff and stores the runway inspection cycles corresponding to the landing and taxiing areas. This allows for automatic lookup and output of the appropriate inspection cycle when different areas are input, facilitating subsequent retrieval.

[0091] Step S1043: Based on the runway inspection cycle, perform runway surface deformation detection on the landing area to determine the runway surface deformation parameters;

[0092] Because the landing area is more prone to damage, it is a key area for inspection. Microwave testing of the runway surface in the landing area according to the runway inspection cycle can determine whether the runway surface has deformed. Analyzing the obtained microwave parameters can reveal the unevenness deformation parameters of the runway surface, which are defined as runway surface deformation parameters.

[0093] Step S1044: Analyze the runway surface deformation parameters to determine the runway pavement deformation ratio. When the pavement deformation ratio is within the preset range of the deformation ratio to be inspected, mark the deformation area and issue a pavement maintenance prompt.

[0094] By comparing the difference in changes between the runway surface after maintenance and the surface after deformation, the change ratio can be determined and defined as the surface deformation ratio. The deformation ratio to be inspected represents the corresponding deformation ratio that affects aircraft landing stability. Deformed areas are marked and surface maintenance prompts are issued to facilitate the control center in assigning maintenance personnel to perform surface maintenance.

[0095] Reference Figure 4 When performing foreign object image feature analysis in step S5, the following is also included:

[0096] Step S501: Collect and analyze the microwave reflection signal of the area where the hazardous foreign object is located. When the microwave reflection signal is the same as the preset metal reflection signal, analyze the metal foreign object model based on the reflection signal.

[0097] By performing microwave detection on the location of dangerous foreign objects within a certain area and analyzing whether the reflected signal is the same as the reflected signal of detected metal, it can be determined whether the dangerous foreign object is a metal foreign object. Based on the reflected signal received by the radar, a model of the metal foreign object is constructed and defined as the metal foreign object model.

[0098] Step S502: Based on the metal foreign object model, perform feature identification to determine the source of the metal foreign object, and analyze whether the metal foreign object has cracking characteristics;

[0099] By performing feature identification on the metal foreign object model, specific information about the metal foreign object can be obtained, thus identifying the source of the metal and defining it as the source of the metal foreign object. Further analysis of the crack features along the edges of the metal foreign object model reveals whether the metal foreign object has developed corresponding cracks, facilitating the analysis of whether the metal foreign object has produced other residual fragments.

[0100] Step S503: If it exists, mark the metal foreign object with the location of the metal foreign object, and perform the same metal location detection using the preset same metal detection strategy.

[0101] When analysis reveals cracking characteristics in the metal, it indicates that there may be other small, cracked metal foreign objects around the metal foreign object, which could pose a safety hazard to aircraft takeoff and landing. Therefore, a pre-set homologous metal detection strategy is used to detect the small metal foreign objects. The detected small metal foreign objects are marked and defined as homologous metal locations. The specific steps of the homologous metal detection strategy will be further explained later.

[0102] Step S504: Clean and recycle the metal foreign objects at the same metal location and the metal foreign object location based on the cleaning command.

[0103] Recovering metal from both original metal locations and foreign metal locations allows for a more comprehensive removal of foreign metal objects of varying sizes, which helps improve the safety of aircraft takeoff and landing.

[0104] Reference Figure 5 The preset homologous metal detection strategies include:

[0105] Step S5031: Analyze the cracking characteristics and the metal foreign object model to determine the number and area of ​​surface notches in the cracking characteristics;

[0106] By performing image analysis on the crack features on the metal foreign object model, we can determine the number and area of ​​the notches corresponding to the crack features. The number of notches is defined as the number of surface notches, and the area is defined as the surface notch area.

[0107] Step S5032: Analyze the number and area of ​​surface notches to determine the number of missing metals and the volume of the missing metals;

[0108] The analysis of the quantity and volume of missing metal is intended to be used in subsequent searches for smaller metal fragments scattered around the runway.

[0109] Step S5033: Based on the comparison between the metal volume and the preset effective interference volume, determine the actual number of missing metals that cause interference;

[0110] The effective interference volume is the size of a small metal object or aircraft that could pose a safety hazard to the runway tires when it taxis on the runway surface. It is determined by personnel conducting contact experiments on the tires with corresponding volumes of metal and foreign objects at different taxiing speeds. The actual number of missing metal objects is defined as the number of missing metal objects by screening for those with a volume greater than or equal to the effective interference volume and counting them.

[0111] Step S5034: Based on the actual number of missing metals, match the radar detection range in the preset detection parameter database and issue a detection command for the same source metal.

[0112] The greater the actual amount of missing metal, the larger the detection range needs to be. By pre-establishing a detection parameter database, different actual missing metal quantities are stored in the database, along with their corresponding radar detection ranges. When the actual missing metal quantity is input, the corresponding radar detection range is searched and output. By issuing a homologous metal detection command, the detection radar is instructed to search for the presence of corresponding small metal particles within its detection range, facilitating subsequent removal of these small metal particles.

[0113] Reference Figure 6 When cleaning and recycling metal foreign objects at both the same metal location and the metal foreign object location, it also includes:

[0114] Step S5041: Collect and analyze the airport's weather information and runway visible light intensity in advance to determine the airport's weather type and runway illumination.

[0115] The weather information includes real-time weather conditions, humidity, temperature, wind speed, and runway illumination in the area where the airport is located. The weather type and illumination are then filtered out from the weather information. The weather type is defined as the airport weather type, and the illumination is defined as the runway illumination.

[0116] Step S5042: When the airport weather type is the same as the preset extreme weather type, compare and analyze whether the runway illumination is less than the preset basic visible brightness range;

[0117] Airport weather types include normal weather types and extreme weather types. Normal weather types are those suitable for aircraft takeoff and landing, while extreme weather types are those unsuitable for aircraft takeoff and landing, such as heavy rain, strong winds, and heavy snow. When the weather type is extreme, it means that after a metallic foreign object is detected, subsequent removal will be difficult due to weather conditions. Comparing and analyzing whether the runway illumination is less than the baseline visible brightness range can determine whether the metallic foreign object can be easily observed during removal.

[0118] Step S5043: If it is less than, then instruct the preset marking laser to mark the positions of the same metal source and the metal foreign object.

[0119] Marking lasers are laser marking devices pre-installed on airport runways. They can mark the locations of metal objects and foreign objects if the runway illumination is less than a preset basic visible brightness range. This makes it easier to locate the metal objects during recovery. The laser marking stops after recovery and cleaning are completed.

[0120] Reference Figure 7 When determining the airport weather type, the following also applies:

[0121] Step S5044: Compare and analyze the airport weather types. When the airport weather type is snowfall, collect radar reflection signal parameters for analysis to determine the reduction ratio of reflected waves.

[0122] When the airport weather type is snowfall, by collecting and analyzing radar reflection signal parameters, the intensity of the reflected signal can be reduced by a certain percentage, which is defined as the reflected wave reduction percentage.

[0123] Step S5045: Calculate based on the reflected wave drop ratio to determine the reflected wave intensity;

[0124] The signal reflection wave intensity corresponding to the percentage decrease in reflected wave intensity is calculated for subsequent use.

[0125] Step S5046: When the intensity of the reflected wave is less than the preset reference reflected wave intensity, the location of the dangerous foreign object is tracked to determine the real-time location of the dangerous foreign object.

[0126] The reference reflected wave intensity represents a benchmark value for the strength of the reflected wave signal. When the received reflected wave intensity is less than the reference reflected wave intensity, it indicates that the reflected wave is affected by snowfall, resulting in a weaker received reflected wave intensity, which is not conducive to locating metallic foreign objects.

[0127] Tracking dangerous foreign objects also includes:

[0128] Step S5047: Perform a position change distance analysis on the hazardous foreign object whose position has changed to determine the rate of position change of the hazardous foreign object;

[0129] By continuously monitoring the location of hazardous foreign objects, when the hazardous foreign objects are moved due to weather conditions, the rate of change of the moving distance is analyzed and defined as the rate of change of location, that is, how fast the distance of the hazardous foreign object changes within a set unit of time.

[0130] Step S5048: Sort the objects based on the numerical value of their position change rate to determine the priority order for cleaning them.

[0131] By ranking the rate of change of the positions of multiple monitored hazardous foreign objects, we can identify the hazardous foreign objects that are most affected by the weather. This ranking is defined as the priority order for clearing foreign objects.

[0132] Step S5049: Generate cleaning instructions based on the priority order of cleaning foreign objects.

[0133] According to the cleaning instructions, each foreign object in the priority order for cleaning is cleaned up so that foreign objects that are easily affected by weather, such as wind, can be dealt with first, thereby reducing the impact of foreign objects moving to different areas on cleaning efficiency.

[0134] Based on the same inventive concept, embodiments of the present invention provide a multi-source information fusion intelligent monitoring system for airport runways, comprising:

[0135] The interference source monitoring module collects and analyzes radar-monitored microwave data from the runway to determine the location of interference sources within the runway.

[0136] The interference source analysis module performs microwave signal analysis on the location of the interference source to determine the type of microwave interference and the duration of the interference.

[0137] Match the adjustment band corresponding to the type of microwave interference reduction in the preset band database;

[0138] The interference source adjustment module adjusts the monitoring band based on the preset radar monitoring device indicated by the adjustment band, and marks the location of the interference source to generate a path to be checked.

[0139] The foreign object removal module acquires images of the path to be checked and performs foreign object image feature analysis to identify dangerous foreign objects and issue removal commands.

[0140] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0141] This invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a multi-source information fusion intelligent monitoring method for airport runways.

[0142] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0143] Based on the same inventive concept, embodiments of the present invention provide a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as a multi-source information fusion intelligent monitoring method for airport runways.

[0144] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0145] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A multi-source information fusion airport runway intelligent monitoring method, characterized in that, The method comprises the following steps: Step S1: Collecting radar monitoring microwaves of the runway for analysis to determine the position of the interference wave source in the runway; Step S2: Analyzing the position of the interference wave source to determine the type of microwave interference and the time of interference; Step S3: Matching the adjustment wave band corresponding to the type of microwave interference in the preset wave band database; Step S4: Adjusting the monitoring wave band based on the adjustment wave band and indicating the preset radar monitoring device to adjust the monitoring wave band, and marking the position of the interference wave source to generate a path to be checked; Step S5: Collecting images of the path to be checked and analyzing the image features of foreign objects to determine dangerous foreign objects and issue a cleaning instruction; in step S5, the analysis of the image features of foreign objects further comprises: Collecting microwave reflection signals of the area where the dangerous foreign object is located for analysis, and when the microwave reflection signals are the same as the preset metal reflection signals, analyzing the metal foreign object model according to the reflection signals; Based on the metal foreign object model, the characteristics are identified to determine the source of the metal foreign object, and whether the metal foreign object has a cracking feature is analyzed; If so, mark the metal foreign object at the metal foreign object position, and detect the position of the metal object with the preset homologous metal detection strategy; Based on the cleaning instruction, the metal foreign object at the position of the homologous metal and the metal foreign object is cleaned and recycled; The preset homologous metal detection strategy comprises: According to the cracking feature and the metal foreign object model, the number of surface notches and the surface notch area of the cracking feature are determined; Based on the number of surface notches and the surface notch area, the number of missing metals and the metal volume of the missing metals are determined; Based on the metal volume and the preset effective interference volume, the actual number of missing metals that cause interference is determined; Based on the actual number of missing metals, the radar detection range in the preset detection parameter database is matched, and a homologous metal detection instruction is issued.

2. The multi-source information fusion airport runway intelligent monitoring method according to claim 1, characterized in that, In step S1, when collecting radar monitoring microwaves of the runway for analysis, the method comprises the following steps: Obtaining the take-off and landing tasks of the airport runway for analysis to determine the runway in a non-take-off and landing task; Call the historical maintenance data of the non-take-off and landing task runway to determine the maintenance area and maintenance time in the historical maintenance data and collect the current monitoring time; Based on the current monitoring time and the maintenance time, the runway service time after maintenance is calculated; If the runway service time is greater than the preset effective service time, the runway is marked as a runway to be checked, and a radar monitoring instruction is issued to detect the microwave of the runway to be checked.

3. The multi-source information fusion airport runway intelligent monitoring method according to claim 2, characterized in that, When the runway is marked as a runway to be checked, the method further comprises the following steps: Analyzing the runway to be checked to determine the runway type and the aircraft sliding track corresponding to the service aircraft type information; Based on the aircraft sliding track, the runway area is divided to determine the landing area and the sliding area, and the runway detection cycle corresponding to the landing area and the sliding area in the preset monitoring track database is matched; Based on the runway detection cycle, the runway surface deformation of the landing area is detected to determine the runway surface deformation parameter; Based on the runway surface deformation parameter, the runway surface deformation ratio is determined, and when the runway surface deformation ratio is within the preset range of the runway surface deformation ratio to be repaired, the deformation area is marked and a runway surface maintenance prompt is issued.

4. The multi-source information fusion airport runway intelligent monitoring method according to claim 1, characterized in that, The metal foreign matter in the homologous metal position and the metal foreign matter position is cleaned and recycled, and the method further comprises the following steps: Collecting and analyzing the weather information and runway visible light brightness of the airport in advance to determine the weather type of the airport and the runway light brightness; When the weather type of the airport is the same as the preset extreme weather type, the runway light brightness is compared and analyzed to determine whether it is less than the preset basic visible brightness range; If it is less than, the preset marker laser is used to mark and prompt the homologous metal position and the metal foreign matter position.

5. The multi-source information fusion airport runway intelligent monitoring method according to claim 4, characterized in that, When determining the weather type of the airport, the method further comprises the following steps: When the weather type of the airport is compared and analyzed, if the weather type of the airport is snow weather type, the radar reflection signal parameter is collected and analyzed to determine the reflection wave decline ratio; Based on the reflection wave decline ratio, the reflection wave intensity is calculated; When the reflection wave intensity is less than the preset reference reflection wave intensity, the position of the dangerous foreign matter is tracked to determine the real-time position of the dangerous foreign matter.

6. The multi-source information fusion airport runway intelligent monitoring method according to claim 5, characterized in that, When tracking the dangerous foreign matter, the method further comprises the following steps: The position change distance of the position changed dangerous foreign matter is analyzed to determine the position change rate of the dangerous foreign matter; Based on the numerical value of the position change rate, the dangerous foreign matter is sorted in order of priority to determine the priority cleaning order of the foreign matter; Based on the priority cleaning order of the foreign matter, a cleaning instruction is generated.

7. A multi-source information fusion airport runway intelligent monitoring system, applying the method of any one of claims 1-6, characterized in that, The method comprises the following steps: The interference source monitoring module collects and analyzes the radar monitoring microwave of the runway to determine the position of the interference wave source in the runway; The interference source analysis module analyzes the microwave signal of the interference wave source position to determine the microwave interference type and the interference existing time; Matching the adjustment wave band corresponding to the weakening microwave interference type in the preset wave band database; The interference source adjustment module adjusts the monitoring wave band of the preset radar monitoring device based on the adjustment wave band, marks the position of the interference wave source to generate a to-be-checked path, and analyzes the image features of the foreign matter in the to-be-checked path to determine the dangerous foreign matter and issue a cleaning instruction. ​

Images