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

Abstract

The invention relates to a multi-source information fusion airport runway intelligent monitoring method and system, and relates to the technical field of airport runway monitoring, and the method comprises the steps: collecting radar monitoring microwaves of a runway, and carrying out the analysis, so as to determine the position of an interference wave source in the runway; performing microwave signal analysis on the interference wave source position to determine a microwave interference type and interference existence time; matching an adjusting wave band corresponding to the microwave interference weakening type in a preset wave band database; indicating a preset radar monitoring device to perform monitoring band adjustment based on the adjustment band, and marking the position of the interference wave source to generate a to-be-checked path; and performing image acquisition on the to-be-checked path and performing foreign matter image feature analysis to determine dangerous foreign matters and send a cleaning instruction. The method has the effect of improving the accuracy of the runway abnormity monitoring result.

Description

Technical Field

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

[0002] An airport runway is an auxiliary road for aircraft to take off and land stably. During its long-term service, it needs to withstand the influence of natural environment and climate, resulting in varying degrees of ground and foundation changes on the airport runway, which has a certain impact on aviation safety and requires close abnormal monitoring.

[0003] In related technologies, when monitoring the abnormality of an airport runway, a radar system is used to automatically monitor the airport surface. By transmitting microwave signals to the runway and receiving and analyzing the reflected signals, the ground and foundation change parameters of the runway are determined, so as to timely know whether the runway needs maintenance.

[0004] In view of the above related technologies, during the process of automatically monitoring the runway, when there are transportation tools or instruments generating microwave signals in the runway, it is easy to affect the transmitted microwave signals, resulting in deviation of the monitoring results. Summary of the Invention

[0005] In order to improve the accuracy of the runway abnormality monitoring results, the present application provides a multi-source information fusion intelligent monitoring method and system for airport runways.

[0006] In a first aspect, the present application provides a multi-source information fusion intelligent monitoring method for an airport runway, adopting the following technical solution:

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

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

[0009] Step S2: Analyze the microwave signals at the position of the interference wave source to determine the type of microwave interference and the existence time of the interference;

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

[0011] Step S4: Based on the adjustment band, instruct the preset radar monitoring device to adjust the monitoring band, and mark the position of the interference wave source to generate a path to be verified;

[0012] Step S5: Collect images of the path to be verified and perform foreign object image feature analysis to determine dangerous foreign objects and issue a cleaning instruction.

[0013] Optionally, when analyzing the radar monitoring microwaves of the runway in step S1, it includes:

[0014] Obtain the takeoff and landing tasks of the airport runway for analysis to determine the runway that is not in the takeoff and landing tasks;

[0015] Call the historical maintenance data of the runway that is not in the takeoff and landing tasks to determine the maintenance area and maintenance time in the historical maintenance data and collect the current monitoring time;

[0016] Calculate based on the current monitoring time and the maintenance time to determine the service duration of the runway after maintenance;

[0017] If the service duration of the runway is greater than the preset effective service duration, mark the runway as a runway to be inspected and issue a radar monitoring instruction to perform microwave detection on the runway to be inspected.

[0018] Optionally, when marking the runway as a runway to be inspected, it also includes:

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

[0020] Based on the taxiing trajectory of the aircraft, divide the runway area to determine the landing area and the taxiing area, and match the runway detection periods corresponding to the landing area and the taxiing area in the preset monitoring trajectory database;

[0021] Based on the runway detection period, detect the surface deformation of the landing area of the runway to determine the runway surface deformation parameters;

[0022] Based on the runway surface deformation parameters for analysis to determine the pavement deformation ratio value of the runway. When the pavement deformation ratio value is within the preset range of deformation ratio values to be repaired, mark the deformed area and issue a pavement maintenance prompt.

[0023] Optionally, when performing foreign object image feature analysis in step S5, it also includes:

[0024] Collect and analyze the microwave reflection signals in the area where the dangerous foreign object is located. When the microwave reflection signals are the same as the preset metal reflection signals, analyze the metal foreign object model according to the reflection signals;

[0025] Based on the metal foreign object model, perform feature recognition to determine the source of the metal foreign object and analyze whether the metal foreign object has cracking characteristics;

[0026] If it exists, mark the metal foreign object at the position of the metal foreign object and perform detection of the positions of homologous metals with the preset homologous metal detection strategy;

[0027] Based on the cleaning instruction, clean and recycle the metals at the positions of the homologous metals and the metal foreign object.

[0028] Optionally, the preset homologous metal detection strategy includes:

[0029] Analyze according to the cracking characteristics and the metal foreign object model to determine the number and area of surface notches of the cracking characteristics;

[0030] Analyze based on the number and area of surface notches to determine the quantity of missing metal and the metal volume of the missing metal;

[0031] Compare the metal volume with the preset effective interference volume to determine the actual quantity of missing metal that causes interference;

[0032] Match the actual quantity of missing metal with the radar detection range in the preset detection parameter database and issue a homologous metal detection instruction.

[0033] Optionally, when cleaning and recycling the metal foreign objects at the homologous metal position and the metal foreign object position, it further includes:

[0034] Pre-collect and analyze the weather information of the airport and the visible light brightness of the runway to determine the airport weather type and the runway lighting brightness;

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

[0036] If it is less, instruct the preset marking laser to mark and prompt the homologous metal position and the metal foreign object position.

[0037] Optionally, when determining the airport weather type, it further includes:

[0038] Compare and analyze the airport weather type. When the airport weather type is the snowfall weather type, collect and analyze the radar reflection signal parameters to determine the reflection wave decline ratio;

[0039] Calculate based on the reflection wave decline ratio to determine the reflection wave intensity;

[0040] When the reflection wave intensity is less than the preset reference reflection wave intensity, track the position of the dangerous foreign object to determine the real-time position of the dangerous foreign object.

[0041] Optionally, when tracking the dangerous foreign object, it further includes:

[0042] Analyze the position change distance of the dangerous foreign object with changing position to determine the position change rate of the dangerous foreign object;

[0043] Sort based on the numerical value of the position change rate to determine the priority order of cleaning foreign objects;

[0044] Generate a cleaning instruction based on the priority order of cleaning foreign objects.

[0045] In a second aspect, the present application provides a multi-source information fusion intelligent monitoring system for airport runways, adopting the following technical solutions:

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

[0047] An interference source monitoring module, which collects and analyzes the radar monitoring microwaves of the runway to determine the position of the interference wave source in the runway;

[0048] An interference source analysis module, which analyzes the microwave signals at the position of the interference wave source to determine the type of microwave interference and the existence time of the interference;

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

[0050] An interference source adjustment module, which adjusts the monitoring band of the preset radar monitoring device based on the adjustment band and marks the position of the interference wave source to generate a path to be verified;

[0051] A foreign object cleaning module, which collects images of the path to be verified and analyzes the image features of the foreign objects to determine dangerous foreign objects and issue a cleaning instruction.

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

[0053] 1. By using radar for microwave detection to identify vehicles, instruments, etc. that generate interference sources on the runway, and adjusting the bands of the corresponding detection microwaves at different monitoring frequencies, foreign objects that interfere with the normal takeoff and landing of aircraft on the runway can be effectively identified, and image recognition is integrated for analysis to further improve the accuracy of foreign object detection, which is beneficial to maintaining the driving safety of aircraft on the runway;

[0054] 2. Divide the runway into landing areas and taxiing areas, and match the corresponding detection parameters according to different areas to perform runway surface monitoring with different detection cycles for different runway areas, so that the runway areas with different forces can be effectively monitored, which is convenient for timely maintenance when the runway surface deforms and reduces the impact on the taxiing and landing of aircraft;

[0055] 3. Search for and mark metal foreign objects and homologous metal foreign objects from the same source on the runway, so that the search for metal foreign objects is more comprehensive and less likely to be omitted, which helps to further reduce the probability that the presence of metal foreign objects on the runway surface affects the safety of aircraft takeoff and landing. At the same time, prioritize the recovery of foreign objects in different extreme weather conditions, so that foreign objects that are easily affected by the weather and move can be cleaned first to improve the cleaning effect, thereby reducing the interference to aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is the flowchart of the method of steps S1 to S5 in this application.

[0057] Figure 2 It is the flowchart of the method of steps S101 to S104 in this application.

[0058] Figure 3 It is the flowchart of the method of steps S1041 to S1044 in this application.

[0059] Figure 4 It is the flowchart of the method of steps S501 to S504 in this application.

[0060] Figure 5 It is the flowchart of the method of steps S5031 to S5034 in this application.

[0061] Figure 6 It is the flowchart of the method of steps S5041 to S5043 in this application.

[0062] Figure 7 It is the flowchart of the method of steps S5044 to S5049 in this application. Detailed implementation manners

[0063] In order to make the purpose, technical solutions and advantages of this application clearer and more understandable, the following further elaborates on this application in conjunction with the appended Figures 1-7 drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0064] The following further describes the embodiments of the present invention in detail with reference to the drawings of the specification.

[0065] The embodiment of this application discloses a multi-source information fusion intelligent monitoring method for airport runways, analyzes the radar microwaves of the monitored runway, thereby locates the interference sources that interfere with the radar microwave detection on the runway, and then adjusts the detection band of the radar, so that the radar can maintain the detection reliability of the microwave detection, and further analyzes the images of the interference sources, thereby forming a runway foreign object monitoring integrating multi-source information, which helps to improve the accuracy of the foreign object detection results.

[0066] Referring to 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 positions of the interference wave sources in the runway;

[0068] Multiple monitoring radars are set on the airport runway and arranged at certain intervals along the length of the airport runway to emit monitoring microwaves of corresponding band frequencies. By analyzing the backhaul signals of the monitoring microwaves, it can be known whether there is an interference source. In this application, the interference source refers to vehicles on the runway, instruments capable of transmitting radio waves, etc.

[0069] Step S2: Analyze the microwave signals at the position of the interference wave source to determine the type of microwave interference and the existence time of the interference;

[0070] The type of interference source refers to the interference method that generates interference detection microwaves. For example, a road detector is set on an airport maintenance vehicle or a person carries a wireless device, etc. During use, corresponding microwaves will be generated, thus causing interference to the detection radar in the similar band. By counting the existence time of the interference wave source and defining it as the interference existence time, it is convenient to call it during subsequent further analysis.

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

[0072] The band database is an adjustment band database established in advance by the staff, which stores the adjustment bands that can weaken the corresponding microwaves and stores the interference types corresponding to the adjustment bands. When the interference type is input, it can automatically match and output the adjustment band.

[0073] Step S4: Based on the adjustment band, instruct the preset radar monitoring device to adjust the monitoring band and mark the position of the interference wave source to generate a path to be verified;

[0074] The path to be verified is a path formed by connecting the positions of multiple interference wave sources in sequence. After finding the corresponding adjustment band through matching, the radar monitoring device performs the corresponding band adjustment, so that the radar monitoring device is not easily affected by microwave signals.

[0075] Step S5: Collect images of the path to be verified and perform foreign object image feature analysis to determine dangerous foreign objects and issue a cleaning instruction.

[0076] High-definition cameras capable of collecting images of the runway surface are set in the airport runway. By comparing and analyzing the collected images with the preset foreign object image features, it can be known whether there are foreign objects. When there are foreign objects on the airport runway, a cleaning instruction is issued, and the control center cleans the foreign objects according to the cleaning instruction.

[0077] Refer to Figure 2 , when analyzing the radar monitoring microwaves of the runway in step S1, it includes:

[0078] Step S101: Obtain and analyze the takeoff and landing tasks of the airport runway to determine the runway that is not in the takeoff and landing tasks;

[0079] Before analyzing the microwave monitored by the radar, analyze the takeoff and landing tasks of the airport runway. It can be known which runways do not perform takeoff and landing tasks and are defined as non - takeoff - landing task runways. By screening non - takeoff - landing task runways, the runways in use can be avoided to prevent the detected microwave from affecting the aircraft or other vehicles on the runway.

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

[0081] The historical maintenance data is the data information of the runway's maintenance and repair in the past. By calling the historical maintenance data, the location of the maintenance area during the historical maintenance and repair of the currently determined non - takeoff - landing task runway can be known. The purpose of collecting the current monitoring time is for further analysis.

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

[0083] By calculating the difference between the current monitoring time and the maintenance time, the service time of the runway after maintenance can be known, and this service time is defined as the service duration.

[0084] Step S104: If the service duration of the runway is greater than the preset effective service duration, mark the runway as a runway to be inspected and issue a radar monitoring instruction to perform microwave detection on the runway to be inspected.

[0085] The effective service duration represents the time limit during which the runway can maintain a good road surface condition after maintenance. When the service time is greater than the effective service duration, it means the runway is prone to damage. Then mark the runway as a runway to be inspected and perform microwave detection on the runway to be inspected by receiving the radar monitoring instruction, so that the runways prone to damage can be more targeted.

[0086] Refer to Figure 3 , when marking the 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 the taxiing trajectory of the aircraft corresponding to the service aircraft type information;

[0088] Due to the different sizes of different aircraft types, there are usually regular runways and runways for special aircraft types in the airport. Therefore, by analyzing the runway type of the runway, the corresponding service aircraft type information and the taxiing trajectory of the corresponding aircraft on the runway can be found.

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

[0090] By dividing the aircraft taxiing trajectory, the landing area and the taxiing area during aircraft taxiing can be obtained. The difference between the landing area and the taxiing area lies in the contact and force with the aircraft, which results in a difference in the probability of runway surface damage between the landing area and the taxiing area. The landing area with greater force is more likely to suffer road surface damage. Therefore, different taxiing trajectory areas need to be regularly detected according to different detection periods. Compared with long-term monitoring, it can reduce energy consumption and improve the service life of the radar device. The monitoring trajectory database is established in advance by the staff and stores the runway detection periods corresponding to the landing area and the taxiing area, so as to automatically search and output the corresponding detection periods when different areas are input, for subsequent calling.

[0091] Step S1043: Detect the runway surface deformation of the landing area based on the runway detection period to determine the runway surface deformation parameters;

[0092] Since the runway in the landing area is more likely to be damaged, the landing area is the key area for detection. By performing microwave detection on the runway surface in the landing area according to the runway detection period, it can be known whether the runway surface has deformed. By analyzing the obtained detection microwave parameters, the concave-convex deformation parameters of the runway surface can be obtained, and this parameter is defined as the runway surface deformation parameter.

[0093] Step S1044: Analyze based on the runway surface deformation parameters to determine the road surface deformation ratio value of the runway. When the road surface deformation ratio value is within the preset deformation ratio value range to be repaired, mark the deformed area and issue a road surface maintenance prompt.

[0094] By comparing the difference between the runway road surface in the standard plane after maintenance and the deformed road surface, the change ratio value can be obtained and defined as the road surface deformation ratio value. The deformation ratio value to be repaired represents the corresponding deformation ratio value when the road surface deforms and affects the landing stability of the aircraft. By marking the deformed area and issuing a road surface maintenance prompt, it is convenient for the control center to assign maintenance personnel to perform road surface maintenance.

[0095] Refer to Figure 4 , when performing foreign object image feature analysis in step S5, it further includes:

[0096] Step S501: Collect and analyze the microwave reflection signals in the area where the dangerous foreign object is located. When the microwave reflection signal is the same as the preset metal reflection signal, analyze the metal foreign object model according to the reflection signal;

[0097] By performing microwave detection on the area range of the position of the dangerous foreign object and analyzing whether the reflected signal is the same as the reflected signal of the detected metal, it can be known whether the dangerous foreign object is a metal foreign object. And based on the reflected signal received by the radar, a model of the metal foreign object is constructed, and this model is defined as the metal foreign object model.

[0098] Step S502: Perform feature recognition based on the metal foreign object model to determine the source of the metal foreign object and analyze whether there are cracking features in the metal foreign object;

[0099] By performing feature recognition on the metal foreign object model, the specific information of the metal foreign object can be known, so as to find the source of the metal and define it as the source of the metal foreign object. Further, by searching for cracking features on the edge of the model of the metal foreign object, it can be known whether the metal foreign object has corresponding cracking, so as to facilitate the analysis of whether other residual fragments are generated by the metal foreign object.

[0100] Step S503: If it exists, mark the metal foreign object at the position of the metal foreign object and detect the position of the homologous metal with a preset homologous metal detection strategy;

[0101] When it is analyzed that the metal has cracking features, it means that there may be other small cracked metal foreign objects within the peripheral range of the metal foreign object, which is likely to pose a safety hazard to the takeoff and landing of the aircraft. Then, a corresponding detection is carried out on the small metal foreign objects with a preset homologous metal detection strategy, and the detected small metal foreign objects are marked for their positions and defined as the positions of homologous metals. The specific steps of the homologous metal detection strategy will be further elaborated later.

[0102] Step S504: Clean and recycle the metal foreign objects at the positions of the homologous metals and the metal foreign objects based on the cleaning instruction.

[0103] Recycling the metals at the positions of the homologous metals and the metal foreign objects enables a more comprehensive cleaning of metal foreign objects of different sizes, which helps to improve the safety of aircraft takeoff and landing.

[0104] Refer to Figure 5 , the preset homologous metal detection strategy includes:

[0105] Step S5031: Analyze according to the cracking features and the metal foreign object model to determine the number of surface notches and the surface notch area of the cracking features;

[0106] By performing image analysis on the cracking features on the metal foreign object model, the number of corresponding notches and the area of the notches can be known. 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 based on the number of surface notches and the surface notch area to determine the quantity of missing metal and the metal volume of the missing metal;

[0108] Analyze the quantity of missing metal and the metal volume for further calling when further searching for small metals scattered around the runway later.

[0109] Step S5033: Compare the metal volume with a preset effective interference volume to determine the actual quantity of missing metal causing interference;

[0110] The effective interference volume is the volume size of small metals and the aircraft taxiing on the runway surface that can pose a safety hazard to the taxiing tires, which is obtained from experiments by staff on the contact between metals and foreign objects of corresponding volumes and tires at different taxiing speeds. By screening and counting the quantity of missing metals with a metal volume greater than or equal to the effective interference volume, this quantity is defined as the actual quantity of missing metal.

[0111] Step S5034: Match the actual quantity of missing metal with the radar detection range in a preset detection parameter database and issue a homologous metal detection instruction.

[0112] When the actual quantity of missing metal is larger, it means the detection range required will be relatively larger. By pre - establishing a detection parameter database, different actual quantities of missing metal are stored in the database, and the corresponding radar detection ranges are also stored. When the actual quantity of missing metal is input, the corresponding radar detection range is searched for and output. By issuing a homologous metal detection instruction, it is to instruct the detection radar to detect within the radar detection range to find if there are corresponding small metals, so as to facilitate the subsequent cleaning of small metals.

[0113] Refer to Figure 6 , when cleaning and recycling metal foreign objects at the homologous metal position and the metal foreign object position, it also includes:

[0114] Step S5041: Pre - collect and analyze the weather information of the airport and the visible light brightness of the runway to determine the airport weather type and the runway illumination brightness;

[0115] The weather information includes the real - time weather conditions, humidity, temperature, wind force of the area where the airport is located, and the illumination brightness of the airport runway, etc. The weather type and illumination brightness in the weather information are screened out. The weather type is defined as the airport weather type, and the illumination brightness is defined as the runway illumination brightness.

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

[0117] The airport weather types include regular weather types and extreme weather types. Among them, the regular weather types are the weather conditions suitable for aircraft takeoff and landing, and the extreme weather types are the weather conditions such as heavy rain, strong wind, and heavy snow that are not suitable for aircraft takeoff and landing. When the weather type is an extreme weather type, it means that when metal foreign objects are detected and then cleaned up subsequently, it is easy to be affected by the weather, resulting in difficulties in finding the cleaning location. By comparing and analyzing whether the runway illumination brightness is less than the basic visible brightness range, it can be known whether it is convenient to observe the metal foreign objects when cleaning up the metal foreign objects.

[0118] Step S5043: If it is less, then instruct the preset marking laser to mark and prompt the homologous metal position and the metal foreign object position.

[0119] The marking laser is a laser marking device preset in the airport runway. If the runway illumination brightness is less than the preset basic visible brightness range, it can mark the homologous metal position and the foreign object metal position, so as to facilitate the search when recovering the metal foreign objects, and stop the laser marking when the recovery and cleaning are completed.

[0120] Refer to Figure 7 , when determining the airport weather type, it also includes:

[0121] Step S5044: Compare and analyze the airport weather type. When the airport weather type is the snowfall weather type, collect the radar reflection signal parameters for analysis to determine the reflection wave decline ratio;

[0122] When the airport weather type is snowfall weather, by collecting and analyzing the radar reflection signal parameters, it can be known the decline ratio of the reflection signal intensity, and this ratio value is defined as the reflection wave decline ratio.

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

[0124] Calculate the signal reflection wave intensity corresponding to the reflection wave decline ratio for subsequent call.

[0125] Step S5046: When the reflection wave intensity is less than the preset reference reflection wave intensity, perform position tracking on the dangerous foreign object to determine the real-time position of the dangerous foreign object.

[0126] The reference reflection wave intensity represents a reference value with good reflection wave signal intensity. When the received reflection wave intensity is less than the reference reflection wave intensity, it means that the reflection wave is affected by snowfall at this time, resulting in a weak received reflection wave intensity, which is not conducive to positioning the metal foreign object.

[0127] When tracking the dangerous foreign object, it also includes:

[0128] Step S5047: Analyze the position change distance of the dangerous foreign object with position change to determine the position change rate of the dangerous foreign object;

[0129] By continuously monitoring the position of the dangerous foreign object, when the dangerous foreign object moves due to weather influence, analyze the change numerical rate of the moving distance, and define it as the position change rate, that is, within the set unit time, how fast the distance of the dangerous foreign object changes.

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

[0131] By sorting the position change rates of multiple monitored dangerous foreign objects, it is possible to know each dangerous foreign object that is more affected by the weather, and define this sorting as the order of priority for cleaning foreign objects.

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

[0133] Clean each foreign object in the order of priority for cleaning foreign objects according to the cleaning instruction, so that foreign objects that are easily affected by the weather, such as those moved by wind force, can be processed preferentially to reduce the influence of the movement of foreign objects to different areas on the cleaning efficiency.

[0134] Based on the same inventive concept, an embodiment of the present invention provides a multi-source information fusion airport runway intelligent monitoring system, including:

[0135] An interference source monitoring module, which collects and analyzes the radar monitoring microwaves of the runway to determine the position of the interference wave source in the runway;

[0136] An interference source analysis module, which performs microwave signal analysis on the position of the interference wave source to determine the microwave interference type and the interference existence time;

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

[0138] An interference source adjustment module, which based on the adjustment band, instructs the preset radar monitoring device to adjust the monitoring band, and marks the position of the interference wave source to generate a path to be verified;

[0139] A foreign object cleaning module, which performs image acquisition on the path to be verified and analyzes the foreign object image features to determine dangerous foreign objects and issue cleaning instructions.

[0140] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0141] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded and executed by a processor to perform the multi-source information fusion airport runway intelligent monitoring method.

[0142] Computer storage media include, for example, various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0143] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal including a memory and a processor, and a computer program that can be loaded and executed by the processor to perform the multi-source information fusion airport runway intelligent monitoring method is stored on the memory.

[0144] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0145] The above are all the preferred embodiments of this application. The protection scope of this application is not limited accordingly. Any feature disclosed in this specification (including the abstract and drawings), unless specifically described, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically described, each feature is only an example of a series of equivalent or similar features.

Claims

1. An intelligent monitoring method for airport runways with multi-source information fusion, characterized in that, Including: Step S1: Collect and analyze the radar monitoring microwaves of the runway to determine the position of the interference wave source in the runway; Step S2: Analyze the microwave signal at the interference wave source position to determine the microwave interference type and the interference existence time; Step S3: Match the adjustment band corresponding to the microwave interference type weakened in the preset band database; Step S4: Based on the adjustment band, instruct the preset radar monitoring device to adjust the monitoring band, and mark the position of the interference wave source to generate a path to be verified; Step S5: Collect images of the path to be verified and perform foreign object image feature analysis to determine dangerous foreign objects and issue a cleaning instruction.

2. The multi-source information fusion airport runway intelligent monitoring method according to claim 1, wherein When collecting and analyzing the radar monitoring microwaves of the runway in Step S1, it includes: Obtain the takeoff and landing tasks of the airport runway for analysis to determine the runway that is not in the takeoff and landing tasks; Call the historical maintenance data of the runway that is not in the takeoff and landing tasks to determine the maintenance area and maintenance time in the historical maintenance data and collect the current monitoring time; Calculate based on the current monitoring time and the maintenance time to determine the service life of the runway after maintenance; If the service life of the runway is greater than the preset effective service life, mark the runway as a runway to be inspected, and issue a radar monitoring instruction to perform microwave detection on the runway to be inspected.

3. The multi-source information fusion airport runway intelligent monitoring method according to claim 2, wherein When marking the runway as a runway to be inspected, it also includes: Analyze the runway to be inspected to determine the runway type and the taxiing trajectory of the aircraft corresponding to the service aircraft type information; Based on the aircraft taxiing trajectory, divide the runway area to determine the landing area and the taxiing area, and match the runway detection period corresponding to the landing area and the taxiing area in the preset monitoring trajectory database; Based on the runway detection period, detect the surface deformation of the landing area to determine the surface deformation parameters of the runway; Analyze based on the runway surface deformation parameters to determine the pavement deformation ratio value of the runway. When the pavement deformation ratio value is within the preset range of deformation ratio values to be repaired, mark the deformed area and issue a pavement maintenance prompt.

4. The multi-source information fusion airport runway intelligent monitoring method according to claim 1, characterized in that When performing foreign object image feature analysis in Step S5, it also includes: Collect and analyze the microwave reflection signal in the area where the dangerous foreign object is located. When the microwave reflection signal is the same as the preset metal reflection signal, analyze the metal foreign object model according to the reflection signal; Based on the metal foreign object model, perform feature recognition to determine the source of the metal foreign object, and analyze whether the metal foreign object has a cracking feature; If it exists, mark the metal foreign object at the metal foreign object position, and perform detection of the homologous metal position with a preset homologous metal detection strategy; Based on the cleaning instruction, clean and recycle the metal foreign objects at the homologous metal position and the metal foreign object position.

5. The multi-source information fusion airport runway intelligent monitoring method according to claim 4, characterized in that, The preset homologous metal detection strategy includes: Analyze according to the cracking feature and the metal foreign object model to determine the number of surface notches and the surface notch area of the cracking feature; Analyze based on the number of surface notches and the surface notch area to determine the missing metal quantity and the metal volume of the missing metal; Compare the metal volume with the preset effective interference volume to determine the actual missing metal quantity that generates interference; Based on the actual missing metal quantity, match the radar detection range in the preset detection parameter database, and issue a homologous metal detection instruction.

6. The multi-source information fusion airport runway intelligent monitoring method according to claim 4, wherein, When cleaning and recycling metal foreign objects at the homologous metal positions and the positions of metal foreign objects, it also includes: Pre-collecting and analyzing the weather information of the airport and the visible light brightness of the runway to determine the airport weather type and the runway illumination brightness; When the airport weather type is the same as the preset extreme weather type, comparing and analyzing whether the runway illumination brightness is less than the preset basic visible brightness range; If it is less, indicating the preset marking laser to mark and prompt the homologous metal positions and the positions of metal foreign objects.

7. The multi-source information fusion airport runway intelligent monitoring method according to claim 6, characterized in that When determining the airport weather type, it also includes: Comparing and analyzing the airport weather type. When the airport weather type is the snowfall weather type, collecting and analyzing the radar reflection signal parameters to determine the reflection wave decline ratio; Calculating based on the reflection wave decline ratio to determine the reflection wave intensity; When the reflection wave intensity is less than the preset reference reflection wave intensity, tracking the position of the dangerous foreign object to determine the real-time position of the dangerous foreign object.

8. The multi-source information fusion airport runway intelligent monitoring method according to claim 7, wherein When tracking the dangerous foreign object, it also includes: Analyzing the position change distance of the dangerous foreign object with a changing position to determine the position change rate of the dangerous foreign object; Sorting based on the numerical size of the position change rate to determine the order of priority for cleaning foreign objects; Generating a cleaning instruction based on the order of priority for cleaning foreign objects.

9. A multi-source information fusion intelligent monitoring system for airport runways, characterized in that, It includes: An interference source monitoring module that collects and analyzes the radar monitoring microwaves of the runway to determine the position of the interference wave source in the runway; An interference source analysis module that analyzes the microwave signals at the position of the interference wave source to determine the microwave interference type and the interference existence time; Matching the adjustment band corresponding to the microwave interference type reduced in the preset band database; An interference source adjustment module that instructs the preset radar monitoring device to adjust the monitoring band based on the adjustment band and marks the position of the interference wave source to generate a path to be verified; A foreign object cleaning module that collects images of the path to be verified and analyzes the foreign object image features to determine the dangerous foreign object and issue a cleaning instruction.

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