Airport pavement freezing point temperature real-time monitoring method, device and system

Abstract

The invention provides an airport pavement freezing point temperature real-time monitoring method, device and system, and relates to the technical field of airport pavement monitoring. The method comprises the following steps: identifying a ponding area included in each acquisition area in an airport pavement image, and determining a ponding distribution main axis of the ponding area, each acquisition area including a water film sensor; determining the ponding position influence degree based on the ponding total area change trend of the collection area and the distance between each ponding area and the ponding distribution main axis, and determining the ponding area sensitivity by combining the area ratio of each ponding area to the collection area; determining the water film thickness sensitivity of the water film sensor based on the ponding area sensitivity, the pavement water film thickness, the average value and the change rate, and determining the water film thickness sensitivity consistency by combining the average water film thickness sensitivity; and determining the parameter sensitivity of the water film sensor, determining the data accuracy by combining the average parameter sensitivity, correcting the pavement water film thickness, and determining the freezing point temperature. The freezing point temperature monitoring accuracy can be improved.

Description

TECHNICAL FIELD

[0001] The application relates to the field of airport pavement monitoring technology, in particular to an airport pavement freezing point temperature real-time monitoring method, device and system. BACKGROUND

[0002] Airport pavement icing is a core risk factor threatening winter aviation safety. Iced pavement can significantly reduce the friction between the aircraft tires and the pavement, causing safety risks such as loss of control in turning and extended braking distance during takeoff, landing and taxiing. Therefore, timely and accurate pavement icing warning and efficient deicing and anti-icing operations through airport pavement monitoring technology are crucial to ensuring normal winter airport operations and flight safety.

[0003] The related technology mainly monitors the airport pavement freezing point temperature through water film sensors arranged at fixed positions. Specifically, the water film sensors arranged at fixed positions are used to collect pavement temperature, water film thickness, conductivity, pavement physical state and pollution concentration and other multi-dimensional parameters. Then, the pavement freezing point temperature is calculated by combining the built-in algorithm and all influencing factors to realize pavement icing warning.

[0004] In the above method, the accuracy of the freezing point temperature calculation directly depends on the accuracy of the water film sensor parameter collection. However, since the water film sensor is deployed at a fixed position, the degree of parameter response to different pavement physical states is different, resulting in uneven accuracy of measurement results under different pavement states, which cannot uniformly reflect the real situation of the pavement. The measurement object of the water film sensor is the total of all soluble substances in the water film, and the presence of pollutants will cause the parameters collected by the water film sensor to deviate from the true water film characteristics, thereby causing deviations between the calculated freezing point temperature and the actual freezing point. The pavement freezing point temperature calculation needs to rely on the cooperative analysis of multiple parameters, and the above method does not fully consider the response degree of each monitoring parameter to the change of the pavement state. The difference in parameter response will further amplify the measurement error and reduce the data reliability. SUMMARY

[0005] In order to solve the problems of insufficient accuracy of airport pavement freezing point temperature monitoring data caused by the measurement deviation of the water film sensor due to the fixed position, the interference of pavement water film pollutants and the influence of not considering the parameter response on accuracy, and the inability to provide accurate support for icing warning and deicing and anti-icing operations, the application provides an airport pavement freezing point temperature real-time monitoring method, device and system, and the technical solutions adopted are as follows: A plurality of water film sensors arranged on the airport pavement are used to collect monitoring data. The monitoring data includes pavement water film thickness. Collecting airport pavement images and dividing into multiple collection areas, identifying the water accumulation area in the collection area, determining the water accumulation distribution main axis based on the centroid coordinates of all the water accumulation areas; each of the collection areas contains one water film sensor; Based on the change trend of the total area of the water accumulation area in the collection area in multiple consecutive collections and the distance of each water accumulation area from the water accumulation distribution main axis, the water accumulation position influence degree is determined, and based on the water accumulation position influence degree of each water accumulation area and the area ratio of the water accumulation area to the collection area, the water accumulation area sensitivity of the collection area is determined. Based on the water accumulation area sensitivity and the water film thickness, water film thickness average value and water film thickness change rate collected by the water film sensor, the water film thickness sensitivity is determined, based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all the water film sensors, the water film thickness sensitivity consistency is determined, and based on the water film thickness sensitivity and the water film thickness sensitivity consistency of the water film sensor, the parameter sensitivity is determined. Based on the deviation of the parameter sensitivity of the water film sensor from the average parameter sensitivity of all the water film sensors, the data accuracy is determined, based on the average data accuracy probability of all the water film sensors, the pavement water film thickness is corrected, and based on the corrected pavement water film thickness, the freezing point temperature of the airport pavement is determined.

[0006] Illustratively, the water accumulation distribution main axis is determined based on the centroid coordinates of all the water accumulation areas, including: constructing a two-dimensional space point set based on the centroid coordinates of all the water accumulation areas; extracting the principal component direction of the two-dimensional space point set by principal component analysis algorithm, denoted as the water accumulation distribution main axis, the water accumulation distribution main axis is used to represent the linear distribution characteristics of the water accumulation on the airport pavement along the running direction of the aircraft, and the extension direction is consistent with the direction of the aircraft sliding track of the airport runway.

[0007] Illustratively, the water accumulation position influence degree is determined based on the change trend of the total area of the water accumulation area in the collection area in multiple consecutive collections and the distance of each water accumulation area from the water accumulation distribution main axis, including: calculating the sum of the areas of all the water accumulation areas contained in the collection area at each data collection time, denoted as the total area of the water accumulation area corresponding to the collection time; calculating the area difference value of the total area of the water accumulation area of each adjacent collection time and summing up, based on the sum of the area difference value, the area stability degree of the collection area is determined; for each of the water accumulation areas in the collection area, the Euclidean distance between the water accumulation area and the water accumulation distribution main axis is determined, denoted as the distance influence factor; based on the area stability degree and the distance influence factor corresponding to the water accumulation area, the water accumulation position influence degree of the water accumulation area is determined.

[0008] Exemplarily, the water area sensitivity of the collection area is determined based on the water position influence degree of each water area and the area ratio of the water area to the collection area, comprising: calculating the ratio of the first area of each water area to the second area of the collection area, denoted as the area contribution factor of the water area; determining the sensitivity contribution factor of each water area based on the area contribution factor and the water position influence degree, and determining the water area sensitivity of the collection area based on the sensitivity contribution factor of each water area.

[0009] Exemplarily, the water film thickness sensitivity of the water film sensor is determined based on the water area sensitivity, the pavement water film thickness collected by the water film sensor, the average pavement water film thickness, and the pavement water film thickness change rate, comprising: obtaining the pavement water film thickness collected by the water film sensor for multiple times in succession; calculating the average of the pavement water film thickness collected for multiple times in succession, denoted as the average pavement water film thickness; calculating the thickness difference between the pavement water film thickness collected by the water film sensor currently and the pavement water film thickness collected last time, and the collection time interval, and taking the absolute value of the ratio of the thickness difference to the collection time interval as the water film thickness change rate; determining the dynamic stability of the water film sensor based on the pavement water film thickness collected by the water film sensor currently, the average pavement water film thickness, and the water film thickness change rate; determining the water film thickness sensitivity of the water film sensor based on the water area sensitivity and the dynamic stability.

[0010] Exemplarily, the water film thickness sensitivity consistency of the water film sensor is determined based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all the water film sensors, comprising: calculating the average of the water film thickness sensitivity of the water film sensor corresponding to each collection area, denoted as the average water film thickness sensitivity; calculating the absolute value of the difference between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity, denoted as the water film thickness sensitivity deviation factor, for each water film sensor; determining the water film thickness sensitivity consistency of the water film sensor based on the water film thickness sensitivity deviation factor.

[0011] Illustratively, the deviation of the parameter sensitivity of the water film sensor from the average parameter sensitivity of all the water film sensors determines the data accuracy thereof, including: calculating the average value of the parameter sensitivity of the water film sensor corresponding to each of the collection areas, denoted as the average parameter sensitivity; for each of the water film sensors, calculating the absolute value of the difference between the parameter sensitivity of the water film sensor and the average parameter sensitivity, denoted as the parameter sensitivity deviation factor; determining the data accuracy of the water film sensor based on the parameter sensitivity of the water film sensor and the parameter sensitivity deviation factor.

[0012] Illustratively, the average data accuracy probability of all the water film sensors is calculated, denoted as the average data accuracy probability; a correction coefficient is determined based on the average data accuracy probability, the pavement water film thickness is corrected based on the correction coefficient, and the corrected pavement water film thickness is substituted into the freezing point reduction formula to calculate the freezing point temperature of the airport pavement.

[0013] Correspondingly, the application also provides an airport pavement freezing point temperature real-time monitoring device, including: A data acquisition module is configured to collect monitoring data through a plurality of water film sensors arranged on the airport pavement; the monitoring data includes pavement water film thickness; An image processing module is configured to collect airport pavement images and divide them into a plurality of collection areas, identify water accumulation areas in the collection areas, and determine a water accumulation distribution main axis based on the centroid coordinates of all the water accumulation areas; each of the collection areas contains one water film sensor; A freezing point monitoring module is configured to determine the water accumulation position influence degree based on the change trend of the total area of water accumulation areas in the collection areas in a plurality of consecutive collections and the distance between each of the water accumulation areas and the water accumulation distribution main axis, and determine the water accumulation area sensitivity of each of the collection areas based on the water accumulation position influence degree of each of the water accumulation areas and the area ratio thereof to the collection area; The freezing point monitoring module is further configured to determine the water film thickness sensitivity of the water film sensor based on the water accumulation area sensitivity and the pavement water film thickness, the average pavement water film thickness, and the pavement water film thickness change rate collected by the water film sensor, determine the water film thickness sensitivity consistency of the water film sensor based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all the water film sensors, and determine the parameter sensitivity of the water film sensor based on the water film thickness sensitivity of the water film sensor and the water film thickness sensitivity consistency. The freezing point monitoring module is further configured to determine data accuracy of the water film sensor based on deviation of the parameter sensitivity of the water film sensor from average parameter sensitivity of all the water film sensors, correct the pavement water film thickness based on average data accuracy probability of all the water film sensors, and determine the freezing point temperature of the airport pavement based on the corrected pavement water film thickness.

[0014] In addition, the application further provides an airport pavement freezing point temperature real-time monitoring system, which determines the freezing point temperature of the airport pavement by executing any one of the above airport pavement freezing point temperature real-time monitoring methods.

[0015] The application can have the following partial or all beneficial effects: In the airport pavement freezing point temperature real-time monitoring method provided by the application, the airport pavement image is collected and divided into a plurality of collection areas (each collection area corresponds to a water film sensor), the corresponding relationship between the water film sensor monitoring range and the actual water distribution of the pavement can be accurately established, and the problem that the fixed water film sensor monitoring range is out of touch with the pavement state is solved; the linear distribution law of the water along the aircraft sliding track is determined by determining the water distribution main axis, the stability degree of the collection area is determined by the water total area change trend of the collection area, and the water position influence degree can be calculated in combination with the distance between each water area and the water distribution main axis, so that the interference of the aircraft main landing gear track belt and other pollutant high-risk areas on the water film sensor measurement can be identified, further, the water area sensitivity can be determined in combination with the area ratio of the water area and the collection area, the parameter abnormality caused by the pollutant can be effectively excluded, and the accuracy of the water film related parameter collection is improved; the water film thickness sensitivity is determined in combination with the real-time value, the historical average value and the change rate of the pavement water film thickness collected by the water film sensor, the parameter reliability can be evaluated by comprehensively considering the spatial distribution characteristics and the dynamic change characteristics of the water area, the spatial consistency of the parameter is further verified by calculating the sensitivity consistency degree through the deviation of the water film thickness sensitivity of the single water film sensor from the average level of all the water film sensors, the parameter sensitivity evaluation is multi-dimensionally optimized, and the reliability of the parameter monitoring is improved; the data accuracy is determined through the deviation of the parameter sensitivity of each water film sensor from the average parameter sensitivity, the pavement water film thickness is corrected based on the average data accuracy probability of all the water film sensors, and the freezing point temperature of the airport pavement is determined based on the corrected pavement water film thickness, the accuracy of the freezing point temperature calculation is improved, the calculation result of the pavement freezing point temperature is matched with the real ice risk of the pavement, and the accuracy of the airport pavement freezing point temperature monitoring is improved.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the application. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on these drawings.

[0018] Figure 1 A flow chart of the airport pavement freezing point temperature real-time monitoring method according to an exemplary embodiment of the present application is shown. Figure 2 A schematic block diagram of the airport pavement freezing point temperature real-time monitoring device according to an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0019] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purposes, the specific embodiments, structures, features and effects of the airport pavement freezing point temperature real-time monitoring method, device and system according to the present application are described in detail below in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0021] The specific solutions of the airport pavement freezing point temperature real-time monitoring method, device and system provided by the present application are described in detail below in combination with the accompanying drawings.

[0022] Please refer to Figure 1 , which shows a flow chart of the airport pavement freezing point temperature real-time monitoring method provided by one embodiment of the present application, as shown in Figure 1 , the airport pavement freezing point temperature real-time monitoring method specifically includes the following steps: S110: collecting monitoring data through a plurality of water film sensors arranged on the airport pavement; the monitoring data includes pavement water film thickness; S120: collecting airport pavement images and dividing them into a plurality of collection areas, identifying water accumulation areas in the collection areas, and determining a water accumulation distribution main axis based on the centroid coordinates of all water accumulation areas; each collection area contains one water film sensor; S130: determining the water accumulation position influence degree based on the change trend of the total area of the water accumulation regions in the plurality of continuous acquisitions and the distance between each water accumulation region and the water accumulation distribution main axis, and determining the water accumulation area sensitivity of the acquisition region based on the water accumulation position influence degree of each water accumulation region and the area ratio of the acquisition region; S140: determining the water film thickness sensitivity based on the water accumulation area sensitivity and the pavement water film thickness, the average value of the pavement water film thickness, and the change rate of the pavement water film thickness collected by the water film sensor, determining the water film thickness consistency based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all water film sensors, and determining the parameter sensitivity of the water film sensor based on the water film thickness sensitivity and the water film thickness consistency of the water film sensor; S150: determining the data accuracy rate of the water film sensor based on the deviation of the parameter sensitivity of the water film sensor from the average parameter sensitivity of all water film sensors, correcting the pavement water film thickness based on the average data accuracy probability of all water film sensors, and determining the freezing point temperature of the airport pavement based on the corrected pavement water film thickness.

[0023] Next, each step of the above-mentioned real-time monitoring method for the freezing point temperature of the airport pavement will be described in detail: In step S110, the monitoring data is collected by the plurality of water film sensors arranged on the airport pavement; the monitoring data includes the pavement water film thickness.

[0024] In the embodiments of the present application, the water film sensor described above is a monitoring device for collecting airport pavement water film related parameters; by way of example, the water film sensor can be a buried water film sensor arranged in the specified position of the airport pavement by the core drilling method to obtain the multi-source monitoring data related to the pavement water film required for calculating the freezing point temperature of the airport pavement.

[0025] In the embodiments of the present application, the monitoring data described above includes the multi-source basic data collected by the water film sensor for calculating the freezing point temperature of the airport pavement; by way of example, the monitoring data can include the pavement water film thickness and the pavement physical state. Among them, the pavement water film thickness is the thickness of the liquid water layer formed on the surface of the airport pavement due to precipitation, ice melting, etc.; the pavement physical state includes five typical states of dry, wet, water accumulation, snow accumulation, and ice formation, which are used to assist in judging the water film existence form and the pavement icing risk basic scene.

[0026] In a specific implementation manner of the embodiment of the present application, the above monitoring data collected by the plurality of water film sensors arranged on the airport pavement can be implemented as follows: the above-mentioned embedded water film sensors are arranged on the side shoulder of the airport road by using the core drilling construction method, the total number of arrangement is K, and it is ensured that each water film sensor is attached to the pavement surface to accurately collect the pavement water film thickness and the pavement physical state and other parameters of the region; the K embedded water film sensors are arranged to perform continuous collection operation, and the total collection number is A. When collecting each time, each water film sensor synchronously outputs two types of data: the pavement water film thickness of the region where the water film sensor is located, denoted as (a is in the range of 1-A, and k is in the range of 1-K), and the pavement physical state of the region where the water film sensor is located, which is matched and recorded from the actual state of “dry, wet, water accumulation, snow accumulation, and icing”; the pavement water film thickness and the pavement physical state of the K water film sensors collected each time are classified and temporarily stored according to the collection number and the water film sensor number, which lays a foundation for the alignment and fusion of the water film sensor monitoring data and the image information of the specific pavement region, and ensures that the water film sensor monitoring data can be associated with the image information of the specific pavement region.

[0027] In step S120, the airport pavement image is collected and divided into a plurality of collection regions, the water accumulation region in the collection region is identified, and the water accumulation distribution main axis is determined based on the centroid coordinates of all water accumulation regions; each collection region contains one water film sensor.

[0028] In the embodiment of the present application, the above-mentioned airport pavement image is image data covering the airport pavement monitoring range, which is shot by a high-definition camera matched with a drone.

[0029] In the embodiment of the present application, the above-mentioned collection region is a pavement image sub-region obtained by dividing the airport pavement image according to the principle of matching the number of water film sensors; the number of the collection region and the number of water film sensors are the same, and each collection region uniquely contains one water film sensor, so as to solve the problem that the monitoring range of the fixed water film sensor is disconnected with the pavement state by establishing the corresponding relationship between the monitoring range of the water film sensor and the actual water accumulation distribution of the pavement.

[0030] In the embodiment of the present application, the above-mentioned water accumulation region is a local region where the pavement exists liquid water accumulation, which is identified from the collection region by using an image processing algorithm, and each collection region can contain one or more water accumulation regions.

[0031] In a specific implementation manner of the embodiment of the present application, the above-mentioned collecting airport pavement images and dividing into multiple collection areas, and identifying the water accumulation area in the collection area can be implemented as follows: a UAV carrying a high-definition camera is used to shoot the airport pavement covering the layout range of all water film sensors to obtain complete airport pavement images; the shot airport pavement images are preprocessed, and the preprocessed images are uniformly divided into N collection areas (N=K, K is the total number of water film sensors) according to the principle that the collection areas correspond to the water film sensors one by one; for each collection area, an image threshold segmentation algorithm (Otsu method or adaptive threshold method) is used to perform pixel-level segmentation on the water accumulation area and the non-water accumulation area in the collection area by setting a pixel grayscale threshold, and the area of each water accumulation area is calculated and recorded. Specifically, taking the i-th water accumulation area in the n-th collection area in the a-th collection data in the A-th continuous collection as an example, the area of the water accumulation area is recorded as ; the water film sensor data and the image data are aligned and fused to form a multi-source data set.

[0032] During the take-off and landing stages of the aircraft, the main landing gear tires and the specific area of the runway will produce continuous and intense friction, thereby forming a track belt area on the airport pavement. The track belt area is more prone to accumulate water due to its physical characteristics (such as texture changes, rubber deposition), and the water accumulation areas contained therein exhibit a roughly linear distribution characteristic along the running direction of the aircraft, rather than a random distribution. In addition, the friction process produces contaminants such as rubber particles, hydraulic oil residues, and dust, so the probability of contaminants such as rubber particles and dust being mixed into the water film of the above-mentioned track belt area is higher, and the closer the water accumulation area is to the tire track belt, the higher the probability of containing contaminants and the stronger the degree of interference with the measurement results.

[0033] In the embodiment of the present application, the above-mentioned water accumulation distribution main axis, which reflects the roughly linear distribution characteristic of the water accumulation area along the running direction of the aircraft during take-off and landing, is consistent with the track belt formed by the main landing gear tires on the pavement, and is a reference benchmark for determining whether the water accumulation area is close to the high-incidence area of contaminants.

[0034] For example, the above-mentioned determination of the water accumulation distribution main axis based on the centroid coordinates of all water accumulation areas can be implemented as follows: a two-dimensional space point set is constructed based on the centroid coordinates of all water accumulation areas; the principal component direction of the two-dimensional space point set is extracted by a principal component analysis algorithm, and is recorded as the water accumulation distribution main axis.

[0035] In a specific implementation manner of the embodiment of the present application, the above-mentioned determination of the water accumulation distribution main axis can be implemented as follows: for each water accumulation area, the centroid coordinates of the pixel contour thereof are determined through geometric calculation. Taking the i-th water accumulation area in the n-th collection area in the a-th collection data in the A-th continuous collection as an example, the centroid coordinates of the water accumulation area are recorded as ; the centroid coordinates of all water accumulation regions in the a-th acquisition are summarized to construct a two-dimensional spatial point set of the water accumulation region centroid coordinates; a main distribution direction of the two-dimensional spatial point set constructed above is extracted by a principal component analysis algorithm, and is denoted as a water accumulation distribution main axis The extension direction of the main axis is consistent with the sliding track direction of the aircraft during takeoff and landing on the runway, and can represent the main distribution rule of the water accumulation.

[0036] In step S130, the water accumulation position influence degree is determined based on the change trend of the total area of the water accumulation regions in the acquisition region in the plurality of continuous acquisitions and the distance of each water accumulation region from the water accumulation distribution main axis, and the water accumulation area sensitivity of the acquisition region is determined based on the water accumulation position influence degree of each water accumulation region and the area ratio of the water accumulation region to the acquisition region.

[0037] In the embodiments of the present application, the water accumulation position influence degree is an index for quantifying the interference degree of the water accumulation region on the measurement result of the water film sensor; the water accumulation position influence degree can be determined based on the distance of the water accumulation region from the water accumulation distribution main axis and the stability of the acquisition region in which the water accumulation region is located. Specifically, the closer the water accumulation region is to the water accumulation distribution main axis, the more stable the acquisition region in which the water accumulation region is located, and the higher the probability of containing contaminants such as rubber particles and hydraulic oil, and the stronger the interference on the measurement.

[0038] For example, the determination of the water accumulation position influence degree based on the change trend of the total area of the water accumulation regions in the acquisition region in the plurality of continuous acquisitions and the distance of each water accumulation region from the water accumulation distribution main axis can be implemented as follows: the sum of the areas of all water accumulation regions contained in the acquisition region at each data acquisition is calculated, denoted as the total area of the water accumulation regions corresponding to the acquisition number; the area difference of the total area of the water accumulation regions of each adjacent acquisition number is calculated and summed to determine the regional stability degree of the acquisition region; for each water accumulation region in the acquisition region, the Euclidean distance between the water accumulation region and the water accumulation distribution main axis is determined, denoted as the distance influence factor; and the water accumulation position influence degree of the water accumulation region is determined based on the regional stability degree and the distance influence factor corresponding to the water accumulation region.

[0039] In one specific implementation manner of the embodiments of the present application, taking the n-th acquisition region in the a-th acquisition data in the A consecutive acquisitions as an example, the process of determining the water accumulation position influence degree can be implemented as follows: the total area of all water accumulation regions of the n-th acquisition region in the A consecutive acquisitions is obtained (a = 1, 2,..., A); the regional stability degree of the n-th acquisition region is calculated by the following formula: , wherein The stability of the nth collection area is used to characterize the smoothness of water accumulation fluctuations in the nth collection area during A consecutive monitoring sessions. It is an indicator for quantifying the stability of water accumulation in the collection area. This represents the sum of the areas of all waterlogged areas in the nth data collection region during the a-th data collection. It is the sum of the areas of all waterlogged areas in the nth collection region in the (a-1)th data collection; This represents the area difference between the total area of ​​the waterlogged area in the nth sampling region among adjacent sampling times; The formula is a natural exponential function; it accumulates the fluctuation range of water accumulation in adjacent sampling times and maps it to water accumulation stability. , The larger the value, the more likely the water accumulation status of the nth sampling area is to remain stable over a long period.

[0040] After determining the regional stability of the collection area, this specific implementation method calculates the influence of the water accumulation location of the i-th water accumulation area in the n-th collection area of ​​the a-th data collection using the following formula: in, The degree of influence of the water accumulation location on the i-th water accumulation area within the n-th data collection area in the a-th data collection; This represents the regional stability of the nth sampling area, reflecting the stability of the water accumulation area within that area. Stable water accumulation area (corresponding to...) Larger values ​​indicate a higher likelihood of being located in areas with high pollutant incidence (such as near the main landing gear track area of ​​an aircraft), resulting in higher confidence levels regarding interference with measurements. Unstable areas (corresponding to...) (If the value is small) Because the water accumulation is temporary, the predictability of pollutant interference is low, and the interference weight needs to be reduced. The i-th waterlogged area within the n-th data collection region in the a-th data collection session and the main axis of waterlogging distribution. The smaller the Euclidean distance between them, the closer the i-th waterlogged area is to the main axis of water distribution, the greater the likelihood that it contains pollutants, and the greater its impact on parameter monitoring. Adding 1 to the denominator is to prevent the denominator from being 0.

[0041] In this embodiment of the application, the above-mentioned water accumulation area sensitivity is an index used to quantify the influence of water accumulation in the collection area on the reliability of water film sensor parameter measurement. The water accumulation area sensitivity can be determined based on the influence of water accumulation location in each water accumulation area and its area contribution weight. Specifically, the larger the value of the water accumulation area sensitivity, the more representative the parameters measured by the water film sensor in the corresponding collection area are of the true water film state, and the higher the data reliability.

[0042] Exemplarily, the above determining the water area sensitivity of the collection area based on the water position influence degree of each water accumulation area and the area ratio of the water accumulation area to the collection area can be implemented as follows: for each water accumulation area in the collection area, a ratio of a first area of the water accumulation area to a second area of the collection area is calculated, denoted as an area contribution factor of the water accumulation area; a sensitivity contribution factor of each water accumulation area is determined based on the area contribution factor and the water position influence degree, and the water area sensitivity of the collection area is determined based on the sensitivity contribution factors of the water accumulation areas.

[0043] In a specific implementation manner of the embodiments of the present application, taking the nth collection area in the a-th collection data in the A consecutive collections as an example, the water area sensitivity of the nth collection area can be calculated by the following formula: wherein, is the water area sensitivity of the nth collection area in the a-th collection data; is the number of water accumulation areas in the nth collection area; is the water position influence degree of the i-th water accumulation area in the nth collection area in the a-th collection data, the greater the value, the stronger the interference of the i-th water accumulation area to the parameter monitoring, and the weight of the i-th water accumulation area should be reduced, the denominator is added by 1 to avoid the denominator being 0; is the area of the i-th water accumulation area in the nth collection area in the a-th collection data (i.e. the above first area); is the area of the nth collection area in the a-th collection data (i.e. the above second area); is the area contribution factor of the i-th water accumulation area, which is used to quantify the representativeness of a single water accumulation area to the overall water film state of the collection area, and the greater the area of the water accumulation area, the more it can reflect the overall water film characteristics (such as thickness, pollutant content) of the collection area, and the higher weight should be given to the water accumulation area; is the reliability contribution of the i-th water accumulation area (i.e. the above sensitivity contribution factor), and the above formula quantifies the overall reliability contribution of the collection area by accumulating the reliability contributions of all water accumulation areas in the nth collection area , the greater the value, the greater the water accumulation area in the nth collection area and the farther away from the main shaft, the less the possibility of containing pollutants, the more the data measured by the water film sensor arranged in the collection area can represent the real water film state of the entire collection area, and the higher the data reliability.

[0044] In step S140, the water film thickness sensitivity of the water film sensor is determined based on the ponding area sensitivity and the pavement water film thickness, the pavement water film thickness average value and the pavement water film thickness change rate collected by the water film sensor, the water film thickness sensitivity consistency of the water film sensor is determined based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all water film sensors, and the parameter sensitivity of the water film sensor is determined based on the water film thickness sensitivity and the water film thickness sensitivity consistency of the water film sensor.

[0045] In the embodiments of the present application, the water film thickness sensitivity is the reliable sensitivity degree of the pavement water film thickness measured by the corresponding water film sensor, which can be used to evaluate the response reliability of the water film sensor to the change of the water film thickness. The greater the value of the water film thickness sensitivity is, the more the water film thickness measured by the corresponding water film sensor can reflect the real dynamic change of the pavement water film (i.e. less interference from ponding and accurate response to thickness fluctuation), and the higher the data reliability is.

[0046] For example, the water film thickness sensitivity of the water film sensor can be determined based on the ponding area sensitivity and the pavement water film thickness, the pavement water film thickness average value and the pavement water film thickness change rate collected by the water film sensor as follows: the pavement water film thickness collected by the water film sensor for multiple times is obtained; the average value of the pavement water film thickness collected for multiple times is calculated and recorded as the pavement water film thickness average value; the thickness difference between the pavement water film thickness currently collected by the water film sensor and the pavement water film thickness collected last time and the collection time interval are calculated, and the absolute value of the ratio of the thickness difference to the collection time interval is recorded as the water film thickness change rate; the dynamic stability of the water film sensor is determined based on the pavement water film thickness currently collected by the water film sensor, the pavement water film thickness average value and the water film thickness change rate; and the water film thickness sensitivity of the water film sensor is determined based on the ponding area sensitivity and the dynamic stability.

[0047] Specifically, taking the kth water film sensor in the ath collection data collected for A times as an example, the water film thickness sensitivity of the kth water film sensor in the ath collection data can be calculated by the following formula: wherein, is the water film thickness sensitivity of the kth water film sensor in the ath collection data; is the ponding area sensitivity of the nth collection area in the ath collection data, and the greater the value is, the less the interference of the ponding of the nth collection area to the measurement of the water film sensor is; is the pavement water film thickness measured by the kth water film sensor in the ath collection data; is the average value of the pavement water film thickness measured by the kth water film sensor in the A times of continuous collection (i.e. the pavement water film thickness average value described above); a deviation of the current collected pavement water film thickness of the water film sensor from the historical average value of the pavement water film thickness, the smaller the value, the higher the reliability of the data collected by the water film sensor; a thickness difference value of the pavement water film thickness collected by the kth water film sensor in the a th and a-1th data collection processes, a time interval between the a th and a-1th data collection processes; a water film thickness change rate, the smaller the value, the more gentle the thickness fluctuation, and the more stable the data; a dynamic stability, used for dynamically adjusting the reliability of the water film thickness data collected by the water film sensor; the formula corrects the reliability of the water film thickness data by comprehensively considering the water accumulation interference constraint and the thickness dynamic characteristic, and the value of the water film thickness sensitivity the greater the value, the more the data measured by the water film sensor represents the water film condition of the entire collection area, and the higher the accuracy of the collected data.

[0048] An airport runway is a large open area, and a plurality of water film sensors for collecting pavement water film thickness are arranged on the pavement. Since the pavement physical state (such as dryness, wetness, and icing degree) is relatively uniform in spatial distribution, if the monitoring data collected by all water film sensors under the same environmental conditions are close, it indicates that each water film sensor is working normally, and the entire monitoring system is reliable. On the contrary, if the reading of a water film sensor is significantly different from those of other water film sensors, it indicates that the water film sensor may have a fault or be blocked by local foreign matter, and the data obtained by the water film sensor is low in accuracy. That is, under the same pavement physical state, the better the consistency of the data monitored by multiple water film sensors, the more accurate the data.

[0049] In the embodiments of the present application, the water film thickness sensitivity consistency is used to evaluate the spatial consistency of the data of a single water film sensor and the data of all water film sensors; the greater the value, the closer the water film thickness sensitivity of the water film sensor to the average sensitivity level of all water film sensors, and the more reliable the data.

[0050] Exemplarily, the water film thickness sensitivity consistency of the water film sensor can be determined based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all water film sensors as follows: calculating the average value of the water film thickness sensitivity of the water film sensor corresponding to each collection area, denoted as the average water film thickness sensitivity; calculating the absolute value of the difference between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity for each water film sensor, denoted as the water film thickness sensitivity deviation factor; and determining the water film thickness sensitivity consistency of the water film sensor based on the water film thickness sensitivity deviation factor.

[0051] Specifically, taking the kth water film sensor in the ath acquisition data acquired in A consecutive acquisitions as an example, the water film thickness sensitive consistency of the kth water film sensor in the ath acquisition data is determined by the following formula: wherein, is the water film thickness sensitive consistency of the kth water film sensor in the ath acquisition data; is the film thickness sensitivity of the kth water film sensor in the ath acquisition data; is the average value of the film thickness sensitivity of all water film sensors in the ath acquisition data; the denominator plus 1 avoids the denominator being 0.

[0052] After determining the film thickness sensitivity and the water film thickness sensitive consistency of the kth water film sensor in the ath acquisition data by the above method, the parameter sensitivity thereof can be determined by the following formula: wherein, is the parameter sensitivity of the kth water film sensor in the ath acquisition data, which quantifies the overall reliable sensitivity degree of the pavement water film thickness parameter measured by the kth water film sensor, the greater the value, the higher the possibility of the kth water film sensor reading being disturbed by environmental fluctuations or local abnormalities, and the lower the data accuracy; is the water film thickness sensitive consistency of the kth water film sensor in the ath acquisition data; is the water film thickness sensitivity of the kth water film sensor in the ath acquisition data; e is the natural exponential function.

[0053] In step S150, the data accuracy of the water film sensor is determined based on the deviation of the parameter sensitivity of the water film sensor from the average parameter sensitivity of all water film sensors, the pavement water film thickness is corrected based on the average data accuracy probability of all water film sensors, and the ice point temperature of the airport pavement is determined based on the corrected pavement water film thickness.

[0054] In the embodiments of the present application, the above-mentioned data accuracy is an index for evaluating the reliability of the data measured by the corresponding water film sensor; the data accuracy can be determined based on the parameter sensitivity of the corresponding water film sensor and the average parameter sensitivity of all water film sensors, and the greater the value, the more consistent the data measured by the corresponding water film sensor with the overall monitoring level, and the higher the probability of the measured data approaching the real state of the pavement.

[0055] For example, the above-mentioned determination of data accuracy based on the deviation between the parameter sensitivity of the water film sensor and the average parameter sensitivity of all water film sensors can be achieved as follows: calculate the average value of the parameter sensitivity of the water film sensors corresponding to each collection area, and denot it as the average parameter sensitivity; for each water film sensor, calculate the absolute value of the difference between the parameter sensitivity of the water film sensor and the average parameter sensitivity, and denot it as the parameter sensitivity deviation factor; determine the data accuracy of the water film sensor based on the parameter sensitivity of the water film sensor and the parameter sensitivity deviation factor.

[0056] Specifically, taking the k-th water film sensor in the a-th data acquisition from A consecutive acquisitions as an example, the data accuracy of the k-th water film sensor in the a-th data acquisition is determined by the following formula: in, For the first The first data collection in the second collection Data accuracy of individual water film sensors; For the first The first data collection in the second collection The parameter sensitivity of a water film sensor; Indicates the first All data collected in this batch The average value of the parameter sensitivity of each water film sensor (i.e., the average parameter sensitivity mentioned above). This is the normalization function; adding 1 to the denominator term avoids the denominator being 0; the above formula is based on the first... Parameter sensitivity of a water film sensor and its deviation from the average parameter sensitivity Quantify the data accuracy of the k-th water film sensor; parameter sensitivity The smaller the value, the less the sensitivity of the parameters of the k-th water film sensor has to affect the accuracy of the data, and the higher the accuracy of the collected data. The smaller the value, the more consistent the data status of the k-th water film sensor is with the overall level, and the higher the accuracy of the collected data.

[0057] After determining the data accuracy of each water film sensor using the above method, the data accuracy is used as the data weight to adjust the pavement freezing point calculation formula, and the original collected data is corrected to eliminate measurement errors caused by the fixed position of the water film sensor and the sensitivity of the measurement parameters themselves, so as to obtain more accurate measurement data for subsequent computer-controlled pavement freezing point temperature calculation.

[0058] Exemplarily, the above-mentioned correction of the pavement water film thickness based on the average data accuracy probability of all water film sensors can be implemented as follows: calculating the average value of the data accuracy probability of all water film sensors, denoted as the average data accuracy probability; determining a correction coefficient based on the average data accuracy probability, correcting the pavement water film thickness based on the correction coefficient, and substituting the corrected pavement water film thickness into the ice point reduction formula to calculate the ice point temperature.

[0059] In a specific implementation manner of the embodiment of the present application, taking the a-th data collection as an example, the above-mentioned process of determining the ice point temperature can be implemented as follows: calculating the average value of the data accuracy probability of all water film sensors in the a-th data collection, denoted as the average data accuracy probability ; calculating the correction coefficient through the following formula: wherein, is the correction coefficient of the pavement water film thickness collected by the k-th water film sensor in the a-th data collection; is the average data accuracy probability; and ln is the natural logarithm function. The above-mentioned formula determines the correction coefficient based on the average data accuracy probability, eliminates the deviation of the original data caused by the sensor fixed position interference and the parameter sensitivity difference through the correction coefficient, makes the corrected thickness value closer to the real water film state of the pavement, and provides accurate input for the ice point temperature calculation.

[0060] After the correction coefficient is determined through the above-mentioned method, the collected pavement water film thickness is corrected through the correction coefficient, and the corrected water film thickness parameter is substituted into the ice point reduction formula to calculate the pavement ice point temperature; wherein the above-mentioned ice point reduction formula is the same as the prior art, and will not be described here.

[0061] The above-mentioned scheme provided by the embodiment of the present application is mainly introduced from the perspective of method. In order to realize the above-mentioned functions, it contains the hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of the examples described in the embodiments disclosed in the present application, the present application can be realized in the form of hardware or the combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0062] Correspondingly, the embodiment of the present application also provides an airport pavement ice point temperature real-time monitoring device, which is described with reference to Figure 2As shown, the airport pavement freezing point temperature real-time monitoring device 200 can include a data acquisition module 210, an image processing module 220, and a freezing point monitoring module 230, wherein: The data acquisition module is configured to acquire monitoring data through the plurality of water film sensors arranged on the airport pavement; the monitoring data includes the water film thickness of the pavement; The image processing module is configured to acquire images of the airport pavement and divide the images into a plurality of acquisition regions, identify water accumulation regions in the acquisition regions, and determine a water accumulation distribution main axis based on the centroid coordinates of all the water accumulation regions; each acquisition region includes one water film sensor. The freezing point monitoring module is configured to determine the water accumulation position influence degree of each water accumulation region based on the change trend of the total area of the water accumulation regions in the acquisition regions in a plurality of consecutive acquisitions and the distance between each water accumulation region and the water accumulation distribution main axis, determine the water accumulation area sensitivity of each water accumulation region based on the water accumulation position influence degree of each water accumulation region and the area ratio of the water accumulation region, and determine the water film thickness sensitivity of each water film sensor based on the water accumulation area sensitivity and the water film thickness, the average water film thickness, and the water film thickness change rate of the pavement water film thickness collected by the water film sensor. The freezing point monitoring module is further configured to determine the water film thickness sensitivity consistency of each water film sensor based on the deviation of the water film thickness sensitivity of the water film sensor from the average water film thickness sensitivity of all the water film sensors, and determine the parameter sensitivity of each water film sensor based on the water film thickness sensitivity and the water film thickness sensitivity consistency of the water film sensor. The freezing point monitoring module is further configured to determine the data accuracy of each water film sensor based on the deviation of the parameter sensitivity of the water film sensor from the average parameter sensitivity of all the water film sensors, correct the water film thickness of the pavement based on the average data accuracy probability of all the water film sensors, and determine the freezing point temperature of the airport pavement based on the corrected water film thickness of the pavement.

[0063] The specific implementation details of the above-mentioned airport pavement freezing point temperature real-time monitoring device have been described in detail in the corresponding positions of the airport pavement freezing point temperature real-time monitoring method, and therefore will not be described here.

[0064] In addition, the embodiments of the present application also provide an airport pavement freezing point temperature real-time monitoring system, which determines the freezing point temperature of the airport pavement by executing any one of the above-mentioned airport pavement freezing point temperature real-time monitoring methods.

[0065] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0066] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

1. A method for real-time monitoring of the freezing point temperature of airport pavement, characterized in that, The method includes: Monitoring data is collected by multiple water film sensors deployed on the airport pavement; the monitoring data includes the thickness of the water film on the pavement. Airport pavement images are acquired and divided into multiple acquisition areas. Water accumulation areas are identified within the acquisition areas, and the main axis of water accumulation distribution is determined based on the centroid coordinates of all the water accumulation areas. Each acquisition area contains one water film sensor. The influence of water location is determined based on the changing trend of the total area of ​​water accumulation in the collection area during multiple consecutive collections and the distance between each water accumulation area and the main axis of water accumulation distribution. The water area sensitivity of the collection area is determined based on the influence of water location in each water accumulation area and its ratio to the area of ​​the collection area. The water film thickness sensitivity is determined based on the water accumulation area sensitivity and the pavement water film thickness, average pavement water film thickness, and pavement water film thickness change rate collected by the water film sensor. The water film thickness sensitivity consistency is determined based on the deviation between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity of all water film sensors. The parameter sensitivity is determined based on the water film thickness sensitivity of the water film sensor and the water film thickness sensitivity consistency. The data accuracy is determined based on the deviation between the parameter sensitivity of the water film sensor and the average parameter sensitivity of all water film sensors. The pavement water film thickness is corrected based on the average data accuracy probability of all water film sensors. The freezing point temperature of the airport pavement is determined based on the corrected pavement water film thickness.

2. The method for real-time monitoring of airport pavement freezing point temperature according to claim 1, characterized in that, The determination of the main axis of water accumulation distribution based on the centroid coordinates of all the water accumulation areas includes: A two-dimensional spatial point set is constructed based on the centroid coordinates of all the water accumulation areas; The principal component directions of the two-dimensional spatial point set are extracted by principal component analysis algorithm and denoted as the main axis of water accumulation distribution. The main axis of water accumulation distribution is used to characterize the linear distribution characteristics of water accumulation on the airport runway along the direction of aircraft take-off and landing. Its extension direction is consistent with the direction of aircraft taxiing trajectory on the airport runway.

3. The method for real-time monitoring of airport pavement freezing point temperature according to claim 2, characterized in that, The determination of the influence of water accumulation location based on the changing trend of the total area of ​​water accumulation in the collection area during multiple consecutive collections and the distance of each water accumulation area from the main axis of water accumulation distribution includes: Calculate the sum of the areas of all the waterlogged areas included in the collection area during each data collection, and record it as the total area of ​​the waterlogged areas for the corresponding number of collections; Calculate and sum the area differences of the total area of ​​the waterlogged area for each adjacent sampling number, and determine the regional stability of the sampling area based on the sum of the area differences; For each water accumulation area in the collection area, the Euclidean distance between the water accumulation area and the main axis of water accumulation distribution is determined and denoted as the distance influence factor; The degree of influence of the water accumulation location in the water accumulation area is determined based on the stability of the region and the distance influence factor corresponding to the water accumulation area.

4. The method for real-time monitoring of airport pavement freezing point temperature according to claim 3, characterized in that, The determination of the water area sensitivity of the collection area based on the influence of the water location in each water accumulation area and its ratio to the area of ​​the collection area includes: For each waterlogged area in the collection area, the ratio of the area of ​​the first region of each waterlogged area to the area of ​​the second region of the collection area is calculated and recorded as the area contribution factor of the waterlogged area. The sensitivity contribution factor is determined based on the area contribution factor of each water accumulation area and the degree of influence of the water accumulation location. The water accumulation area sensitivity of the collection area is determined based on the sensitivity contribution factor of each water accumulation area.

5. The method for real-time monitoring of airport pavement freezing point temperature according to claim 4, characterized in that, The determination of water film thickness sensitivity based on the water accumulation area sensitivity and the pavement water film thickness, average pavement water film thickness, and pavement water film thickness change rate collected by the water film sensor includes: The thickness of the water film on the pavement is obtained by the water film sensor through multiple consecutive data acquisitions. Calculate the average value of the pavement water film thickness collected multiple times consecutively, and record it as the average pavement water film thickness; Calculate the thickness difference between the current thickness of the pavement water film collected by the water film sensor and the thickness of the pavement water film collected previously, as well as the collection time interval. The absolute value of the ratio of the thickness difference to the collection time interval is recorded as the water film thickness change rate. The dynamic stability of the water film sensor is determined based on the current water film thickness on the pavement, the average water film thickness on the pavement, and the rate of change of the water film thickness. The water film thickness sensitivity of the water film sensor is determined based on the water accumulation area sensitivity and the dynamic stability.

6. The method for real-time monitoring of airport pavement freezing point temperature according to claim 5, characterized in that, The determination of water film thickness sensitivity consistency based on the deviation between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity of all water film sensors includes: Calculate the average value of the water film thickness sensitivity of the water film sensor corresponding to each of the acquisition areas, and record it as the average water film thickness sensitivity; For each of the aforementioned water film sensors, the absolute value of the difference between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity is calculated and denoted as the water film thickness sensitivity deviation factor. The water film thickness sensitivity consistency of the water film sensor is determined based on the water film thickness sensitivity deviation factor.

7. The method for real-time monitoring of airport pavement freezing point temperature according to claim 6, characterized in that, The determination of data accuracy based on the deviation between the parameter sensitivity of the water film sensor and the average parameter sensitivity of all water film sensors includes: Calculate the average value of the parameter sensitivity of the water film sensor corresponding to each of the acquisition areas, and denot it as the average parameter sensitivity; For each of the aforementioned water film sensors, the absolute value of the difference between the parameter sensitivity of the water film sensor and the average parameter sensitivity is calculated and denoted as the parameter sensitivity deviation factor. The data accuracy of the water film sensor is determined based on the parameter sensitivity and the parameter sensitivity deviation factor of the water film sensor.

8. The method for real-time monitoring of airport pavement freezing point temperature according to claim 7, characterized in that, The process of accurately correcting the pavement water film thickness based on the average data from all the water film sensors, and determining the freezing point temperature of the airport pavement based on the corrected pavement water film thickness, includes: Calculate the average of the data accuracy rates of all the water film sensors, and denote it as the average data accuracy probability; Based on the accuracy probability of the average data, a correction coefficient is determined, and the pavement water film thickness is corrected based on the correction coefficient. The corrected pavement water film thickness is then substituted into the freezing point reduction formula to calculate the freezing point temperature.

9. A real-time monitoring device for the freezing point temperature of airport pavement, characterized in that, The device includes: The data acquisition module is used to collect monitoring data through multiple water film sensors deployed on the airport pavement; the monitoring data includes the thickness of the water film on the pavement. The image processing module is used to acquire airport pavement images and divide them into multiple acquisition areas, identify water accumulation areas in the acquisition areas, and determine the main axis of water accumulation distribution based on the centroid coordinates of all the water accumulation areas; each acquisition area includes one water film sensor; The freezing point monitoring module is used to determine the degree of influence of water accumulation location based on the changing trend of the total area of ​​water accumulation area in the collection area during multiple consecutive collections and the distance between each water accumulation area and the main axis of water accumulation distribution; and to determine the water accumulation area sensitivity of the collection area based on the degree of influence of water accumulation location of each water accumulation area and its area ratio with that of the collection area. The freezing point monitoring module is further configured to determine its water film thickness sensitivity based on the water accumulation area sensitivity and the pavement water film thickness, average pavement water film thickness, and pavement water film thickness change rate collected by the water film sensor; determine its water film thickness sensitivity consistency based on the deviation between the water film thickness sensitivity of the water film sensor and the average water film thickness sensitivity of all the water film sensors; and determine its parameter sensitivity based on the water film thickness sensitivity of the water film sensor and the water film thickness sensitivity consistency. The freezing point monitoring module is further configured to determine the data accuracy based on the deviation between the parameter sensitivity of the water film sensor and the average parameter sensitivity of all the water film sensors, correct the pavement water film thickness based on the average data accuracy probability of all the water film sensors, and determine the freezing point temperature of the airport pavement based on the corrected pavement water film thickness.

10. A real-time monitoring system for the freezing point temperature of airport pavement, characterized in that, The system determines the freezing point temperature of the airport pavement by executing the real-time monitoring method for airport pavement freezing point temperature as described in any one of claims 1-8.

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