Airport runway project non-stop construction regulation and control method and system based on dynamic monitoring

Abstract

The invention, which relates to the technical field of airport construction scheduling, discloses a dynamic-monitoring-based non-stop construction regulation and control method and system for an airport runway project, comprising the following steps: collecting real-time dynamic data and fusing multi-source information; performing airport runway construction scheduling based on intelligent prediction and adaptive optimization; construction conflict prediction and optimization scheduling are simulated through simulation; and comparing the construction progress with flight scheduling data in real time, and dynamically scheduling an adjustment mechanism. According to the dynamic scheduling optimization algorithm based on artificial intelligence, by inputting and analyzing real-time data, it is ensured that construction is arranged in the time period with the low flight flow, and therefore interference on flight take-off and landing is reduced. The construction conflict prediction and analogue simulation mechanism ensures smooth proceeding of construction and flights through accurate analogue simulation, and construction schedule monitoring and adjustment based on multi-dimensional feedback dynamically adjusts construction arrangement by monitoring comparison between the construction schedule and flight scheduling in real time to ensure that the construction schedule is not lagged.

Description

Technical Field

[0001] The present invention relates to the technical field of airport construction scheduling, and particularly to a method and system for regulating non-stop construction of airport runway engineering based on dynamic monitoring. Background Art

[0002] With the rapid development of the air transportation industry, airport operation management faces more complex challenges. In particular, how to avoid conflicts with flight scheduling during the construction process has become a key issue affecting airport operation efficiency and safety. In recent years, methods for regulating non-stop construction of airport runway engineering have been gradually introduced, using modern information technology, sensor technology, and data processing technology to dynamically monitor construction progress and flight scheduling. Scheduling optimization methods based on big data analysis and artificial intelligence technology have also gradually become the mainstream trend for improving construction regulation efficiency. Through the real-time collection and fusion of multi-source information, combined with simulation and artificial intelligence prediction technology, the accuracy and flexibility of construction scheduling have been significantly improved. Especially during peak flight hours, real-time dynamic scheduling can effectively avoid conflicts between construction and flight scheduling, providing guarantee for the safe and efficient operation of the airport.

[0003] However, the existing technologies still face some important deficiencies when dealing with the multi-dimensional interaction of complex construction scenarios, flight traffic, and weather factors. First of all, most traditional construction scheduling methods are based on static pre-designed plans and lack an intelligent response mechanism to real-time data, unable to dynamically adjust construction progress and time periods. Most existing technologies can only arrange construction tasks through simple schedules, unable to fully consider the real-time changes in flight traffic and the influence of external factors, resulting in frequent conflicts between construction and flights. Secondly, although there are already data collection schemes based on sensors and monitoring devices, the data fusion and processing capabilities are weak, and a comprehensive and accurate decision support system has not been formed. Most existing simulations focus on the single-dimensional analysis of construction tasks and cannot systematically evaluate the overall impact of construction on flight traffic. In addition, the existing technologies lack a flexible adjustment mechanism when dealing with uncontrollable factors such as construction progress lag, weather changes, and equipment failures, unable to optimize the construction plan in real time, making it difficult to balance construction progress and flight scheduling. Therefore, the existing technologies fail to achieve the effects of high intelligence, dynamic adjustment, and real-time response, and cannot meet the growing complex needs of airport operation management. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the existing airport runway construction scheduling method has problems such as the inability to dynamically compare the construction progress and flight scheduling in real time, the lack of flexibility in adjusting the construction plan, insufficient data fusion and processing, and how to use real-time data and intelligent algorithms to optimize the construction scheduling to avoid conflicts between construction and flight scheduling.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: A method for regulating non-stop construction of airport runway engineering based on dynamic monitoring, including collecting real-time dynamic data to fuse multi-source information; performing airport runway construction scheduling based on intelligent prediction and adaptive optimization; predicting and optimizing scheduling of construction conflicts through simulation; and dynamically comparing the construction progress and flight scheduling data in real time, with a dynamic scheduling adjustment mechanism.

[0007] As a preferred solution of the method for regulating non-stop construction of airport runway engineering based on dynamic monitoring according to the present invention, wherein: the collecting real-time dynamic data to fuse multi-source information includes installing sensors on each runway of the airport to monitor the usage status of the runway in real time;

[0008] The sensors monitor whether the runway is occupied and the degree of occupancy;

[0009] By connecting to the existing flight scheduling system of the airport in real time, the takeoff and landing times, taxiing paths, and flight volumes of flights are retrieved;

[0010] The flight volume of the airport is monitored in real time, and the flight density is predicted;

[0011] A weather station is set up to monitor wind speed, wind direction, temperature, humidity, and precipitation in real time;

[0012] All the collected meteorological data is transmitted to the central scheduling platform through a wireless network, and the central scheduling platform integrates and analyzes the meteorological data with flight information and construction information;

[0013] The central scheduling platform collects the data of the monitoring system, including runway status, flight scheduling, and environmental meteorological data.

[0014] As a preferred solution of the method for regulating non-stop construction of airport runway engineering based on dynamic monitoring according to the present invention, wherein: the performing airport runway construction scheduling based on intelligent prediction and adaptive optimization includes inputting all the collected real-time data, and performing intelligent analysis and prediction based on the real-time data in combination with historical data and monitoring data;

[0015] The input content of the data includes: flight scheduling information, runway usage status, construction progress, and meteorological data;

[0016] Based on historical flight traffic data, predict the trend of future flight traffic through a time series model, and identify the periodic and trend characteristics of the change in flight takeoff and landing density;

[0017] Through the LSTM network, while considering seasonal and holiday factors, predict the flight traffic;

[0018] Based on the requirements of construction tasks and the usage of the airfield, the system will automatically select the construction time period and area, including selecting the construction time period and optimizing the construction area;

[0019] Dynamically adjust the construction progress and time period, including a feedback mechanism and adaptive adjustment;

[0020] Adopt a combination of dynamic scheduling optimization and non - linear constraint optimization to construct the objective function, expressed as:

[0021]

[0022] Among them, x i,t ∈{0, 1} is a binary decision variable, indicating whether the i - th construction task is executed at time t, c t is the flight traffic at time t, representing the number of flights at that moment, p i (t) represents the impact degree of the i - th construction task on flight traffic at time t, d i represents the duration of the i - th construction task, f i (t) represents the non - linear impact function of the i - th construction task on flight traffic, α is a weight factor used to balance the impact of construction tasks on flight traffic and construction progress, β i represents the construction impact coefficient related to task i, reflecting the complexity and intensity of the construction task's impact, W t represents the weather impact weight at time t, used to indicate the impact of weather on construction tasks;

[0023] ∑ i ∑ t p i (t)·c t ·x i,t is the impact of construction tasks on flight traffic;

[0024] α·∑ i d i ·∑ t x i,t is the optimization of the construction task duration;

[0025] β·∑ i ∑ t f i (t)·x i,t is the non - linear interaction between construction tasks and flight traffic;

[0026] Minimize the interference of construction tasks on flight flow through the objective function.

[0027] As a preferred solution of the non-stop construction regulation method for airport apron engineering based on dynamic monitoring described in the present invention, wherein: the airport apron construction scheduling based on intelligent prediction and adaptive optimization includes imposing constraints on the objective function, including:

[0028] Each construction task can only be executed within one time period, which is expressed as:

[0029]

[0030] The duration constraint of the construction task is expressed as:

[0031]

[0032] The conflict limit between the construction task and the flight flow is expressed as:

[0033]

[0034] The time window constraint of the construction task is expressed as:

[0035]

[0036] The dynamic adjustment related to weather factors is expressed as:

[0037]

[0038] Among them, W t represents the impact of weather on construction and dynamically adjusts the construction time.

[0039] As a preferred solution of the non-stop construction regulation method for airport apron engineering based on dynamic monitoring described in the present invention, wherein: the prediction and optimization of construction conflicts through simulation includes simulating the conflicts between construction and flights;

[0040] Input the flight takeoff and landing information for each time period, including the number of flights, taxiing routes, takeoff and landing times, etc., obtain the construction progress and apron usage conditions through real-time monitoring, predict the positions affecting flights during the construction process, and introduce weather data;

[0041] Simulate the potential impacts of different construction plans on flight flow in different time periods and different regions, including the occupation time of the airway, flight flow density, and flight takeoff and landing interference;

[0042] According to the results of the simulation analysis, output the conflict points between construction and flights, and propose scheduling optimization according to the severity of the impacts;

[0043] If it is detected that the construction area overlaps with the takeoff and landing time periods of flights, and the occupancy rate of the construction area on the waterway exceeds 70%, the system evaluates the construction as high-risk construction;

[0044] If the occupancy rate of the construction area on the waterway is greater than or equal to 30% and less than or equal to 70%, the system evaluates the construction as medium-risk construction. At this time, the construction continues, but the flight flow and construction progress need to be monitored;

[0045] If the occupancy rate of the construction area on the waterway is less than 30%, the system evaluates the construction as low-risk construction, and the construction continues according to the plan.

[0046] As a preferred solution of the method for regulating non-stop construction of airport apron engineering based on dynamic monitoring according to the present invention, wherein: the prediction and optimization scheduling of construction conflicts through simulation includes optimizing the construction plan based on the results of simulation and conflict analysis;

[0047] According to the predicted flight flow density, postpone the construction tasks during the periods with a flow rate higher than 60%;

[0048] During the periods when the flight flow is less than or equal to 60%, increase the density of construction tasks;

[0049] Dynamically adjust the construction area to avoid construction on the working waterway and taxiway;

[0050] If the system predicts that the construction area will affect the flight flow, the construction tasks will be moved to an area that does not affect the flights;

[0051] If the system discovers new flights in a period or area, and the construction tasks in the area conflict with the new flights, the system automatically adjusts the construction area or construction progress;

[0052] If during the construction process, it is found that the flight flow increases within a time period, the system immediately adjusts the construction progress;

[0053] If a construction task is delayed and the construction task occurs during a period when the flight flow is higher than 60%, the system will postpone the execution period of the task.

[0054] As a preferred solution of the method for regulating non-stop construction of airport apron engineering based on dynamic monitoring according to the present invention, wherein: for each construction task i in the dynamic scheduling adjustment mechanism that compares the construction progress and flight scheduling data in real time, the change amount Δd i (t) is expressed as:

[0055] Δd i (t) = d i -S i (t)

[0056] wherein, d iDenote the scheduled duration of task i, S i (t) represents the remaining workload of task i at time t. If Δd i (t) > 0, it means the progress of the construction task lags behind the expectation; if Δd i (t) < 0, it means the progress of the construction task is ahead of schedule;

[0057] For each time period t, the comparison between the progress change of the construction task and the flight flow is:

[0058]

[0059] Among them, (1 + β(t)) represents the influence coefficient of external factors on the construction progress, reflecting the additional influence of the external environment on the construction progress and flight flow;

[0060] Introduce the scheduling flexibility coefficient λ i (t), which represents the scheduling flexibility of the construction task within time t, reflecting whether the construction task can be dynamically adjusted according to the flight flow. The adjusted construction impact is expressed as:

[0061] I i,t adjusted = I i,t ·(1 - λ i (t))

[0062] Among them, λ i (t) represents the scheduling flexibility coefficient of the construction task, and its value range is 0 ≤ λ i (t) ≤ 1. When λ i (t) = 0, the time period of the construction task is fixed; when λ i (t) = 1, the construction task fully dynamically adjusts the time period and area;

[0063] According to the real-time comparison of the impact of construction on flight flow, the system evaluates the conflict situation between the construction task and flight scheduling. The evaluation is expressed as:

[0064]

[0065] Among them, Threshold represents the maximum tolerance of construction for flight flow. If I i,t adjusted exceeds the threshold, the system considers that there is a conflict between the construction task and flight scheduling and triggers the adjustment mechanism. The value of C i,t being 1 indicates that a conflict occurs and the construction plan needs to be adjusted; the value being 0 indicates that there is no conflict and the construction can proceed according to the plan;

[0066] When the system detects a conflict between the construction task and flight scheduling, it will automatically adjust the time period or area of the construction task;

[0067] If a conflict occurs during a period when the flight flow is higher than 60%, the adjusted construction period t′ is expressed as:

[0068] t′ = t + Δt

[0069] where Δt represents the adjusted time difference;

[0070] To optimize the coordination between construction scheduling and flight scheduling, the objective functions for construction scheduling and flight scheduling optimization are introduced and expressed as:

[0071]

[0072] where ∑ i ∑ t C i,t ·I i,t ·Δt represents the cost generated by adjusting the construction period or area, and α·∑ i d i ·∑ t x i,t represents the progress optimization of construction tasks, and β·∑ i ∑ t p i (t)·c t ·x i,t represents the impact of construction tasks on flight flow.

[0073] Another object of the present invention is to provide a non-stop construction regulation system for airport runway engineering based on dynamic monitoring, which can solve the problem of conflicts between construction and flight scheduling in the current airport runway construction scheduling through real-time comparison of construction progress and flight scheduling data and a dynamic scheduling adjustment mechanism.

[0074] As a preferred solution of the non-stop construction regulation system for airport runway engineering based on dynamic monitoring according to the present invention, it includes an initialization module, a dynamic scheduling optimization algorithm module, a prediction and simulation module, and a monitoring and adjustment module; the initialization module is used for real-time dynamic data acquisition and multi-source information fusion; the dynamic scheduling optimization algorithm module is used for automatic optimization of construction periods and areas; the prediction and simulation module is used for optimizing construction plans; the monitoring and adjustment module is used for dynamically adjusting construction arrangements.

[0075] A computer device includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps of the non-stop construction regulation method for airport runway engineering based on dynamic monitoring.

[0076] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, it implements the steps of the non-stop construction regulation method for airport runway engineering based on dynamic monitoring.

[0077] Advantages of the present invention: The method for regulating non-stop construction of airport runway engineering based on dynamic monitoring provided by the present invention can, through real-time dynamic data collection and multi-source information fusion, use devices such as intelligent sensors, high-definition cameras, and drones to monitor the usage of the airport runway and the construction progress in real time, and at the same time perform data fusion with the flight scheduling system and the meteorological monitoring system. This link ensures the real-time coordination between construction and flight scheduling and avoids conflicts between construction tasks and flights. Secondly, the dynamic scheduling optimization algorithm based on artificial intelligence inputs and analyzes real-time data, predicts flight flow using machine learning and deep learning, and optimizes the construction time period and area according to the prediction results to ensure that construction is arranged during low flight flow periods, thereby reducing interference with flight takeoffs and landings. Thirdly, the construction conflict prediction and simulation mechanism predicts the potential impact of different construction plans on flight operations through accurate simulation, evaluates conflict periods, generates a conflict assessment report, and then automatically optimizes the construction plan to avoid construction tasks during high flight flow periods and ensure the smooth progress of construction and flights. Finally, the construction progress monitoring and adjustment based on multi-dimensional feedback dynamically adjusts the construction arrangement by comparing the real-time monitoring of the construction progress with the flight scheduling, ensures that the construction progress is not lagging behind, and can cope with the impacts of uncontrollable factors such as weather and equipment failures, and further optimizes the time period and area of construction tasks. Through these steps, the present invention not only improves construction efficiency and scheduling flexibility, but also ensures flight safety and the high efficiency of airport operations, and greatly optimizes the coordination between airport runway construction scheduling and flight scheduling. Description of the Drawings

[0078] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0079] Figure 1 It is the overall flowchart of a method for regulating non-stop construction of airport runway engineering based on dynamic monitoring provided by the first embodiment of the present invention.

[0080] Figure 2 It is the specific flowchart of a method for regulating non-stop construction of airport runway engineering based on dynamic monitoring provided by the first embodiment of the present invention.

[0081] Figure 3 It is the overall flowchart of a system for regulating non-stop construction of airport runway engineering based on dynamic monitoring provided by the third embodiment of the present invention. Detailed Embodiments

[0082] To make the above objects, features, and advantages of the present invention more apparent and understandable, the following provides a detailed description of the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0083] Example 1, referring to Figure 1 - Figure 2 , which is an embodiment of the present invention, provides a method for regulating non-stop construction of airport pavement engineering based on dynamic monitoring, including:

[0084] S1: Collect real-time dynamic data and fuse multi-source information.

[0085] Furthermore, real-time data of airport pavement and flight scheduling are collected through various sensors, monitoring devices, and systems. The specific content is as follows:

[0086] Pavement status monitoring: Use devices such as intelligent sensors, high-definition cameras, and drones to monitor the usage of airport pavement in real time, including the occupancy status of areas such as runways, taxiways, and aprons. In addition, the occupancy of the construction area is also monitored by sensors, and the construction progress is fed back in real time to ensure real-time monitoring of the construction area and the airway area.

[0087] Flight scheduling monitoring: By connecting to the airport flight scheduling system, key data such as the takeoff and landing information, taxiing path, and time arrangement of flights are obtained in real time. Through the real-time interface connection with the flight scheduling system, the system can accurately obtain the takeoff and landing times of each flight and the changes in flight flow, avoiding conflicts between construction and flights.

[0088] Environment and meteorological monitoring: Weather information, including factors such as wind speed, temperature, and precipitation, is collected by meteorological station equipment, which may affect the takeoff and landing safety of flights or the construction progress. All data is transmitted to the central dispatching platform through wireless networks to achieve unified management and real-time update of the data.

[0089] Data fusion and processing: All collected data is processed through data fusion to generate comprehensive information including flight scheduling, construction progress, pavement usage status, environmental factors, etc. The central dispatching platform analyzes these data in real time, judges potential conflicts, and provides decision-making support for subsequent scheduling.

[0090] S2: Conduct airport pavement construction scheduling based on intelligent prediction and adaptive optimization.

[0091] Furthermore, all the collected real-time data (including flight scheduling information, airfield road usage status, construction progress, meteorological data, etc.) are input into the artificial intelligence algorithm model. The system will conduct intelligent analysis and prediction based on these real-time data, combined with historical data and monitoring data. The input content of the data includes:

[0092] Flight scheduling information: including the takeoff and landing times of flights, taxiing routes, flight volumes, etc.;

[0093] Airfield road usage status: monitoring the occupancy of airfield roads, including runways, taxiways, aprons, etc.;

[0094] Construction progress: providing real-time feedback on the completion of construction tasks;

[0095] Meteorological data: including weather conditions, wind speed, temperature, precipitation, etc., and their impacts on construction tasks.

[0096] These data are fed back to the system in real time through the artificial intelligence algorithm model for intelligent prediction and decision support.

[0097] For flight volume prediction, the system predicts the flight volume through machine learning algorithms such as time series analysis and neural networks. The specific implementation methods are as follows:

[0098] Time series analysis: Based on historical flight volume data, predict the future trend of flight volume through a time series model, and identify the periodic and trend characteristics of the change in flight takeoff and landing density;

[0099] Neural network: Through deep learning algorithms (such as LSTM networks), accurately predict the flight volume while considering factors such as seasonality and holidays. The system can analyze the peak and trough periods based on the predicted results of flight density in different time periods.

[0100] These prediction results help the system judge the flight volume density in the future period of time, and then provide a basis for the arrangement of construction periods, avoiding arranging construction during the peak flight volume period to ensure that the construction tasks do not interfere with the normal takeoff and landing of flights.

[0101] Automatic optimization of construction periods and areas: Based on the requirements of construction tasks and the usage situation of airfield roads, the system will automatically select the construction periods and areas. This optimization scheme not only depends on static arrangements, but dynamically adjusts the construction schedule through the feedback of real-time data. The specific steps are as follows:

[0102] Selection of construction periods: Combining the real-time flight volume prediction and the requirements of construction tasks, the system preferentially selects the periods with lower flight volumes for construction. For example, the system will select a large-scale construction period during the time period with less flight volume according to the flight volume prediction to ensure that it does not affect the takeoff and landing of flights.

[0103] Construction area optimization: If a construction task needs to occupy a specific apron or area, the system will automatically select an idle area to avoid conflicts between construction tasks and flight schedules. If additional flights are temporarily assigned to a certain airway, the system can adjust the construction area or time period in real time to avoid affecting the newly added flights.

[0104] The core of this system is to dynamically adjust the construction plan to ensure the flexibility of construction tasks and make adaptive adjustments in line with changes in flight flow.

[0105] Through continuous learning and adaptation, the system can dynamically adjust the construction progress and time period to ensure the optimization of construction progress. The specific implementation methods are as follows:

[0106] Feedback mechanism: The system continuously monitors changes in construction progress and flight flow and feeds back real-time data on construction tasks and flight schedules. If the flight flow in a certain time period is higher than expected, the system will re-evaluate the progress and time period of the construction task and automatically adjust the construction arrangement.

[0107] Adaptive adjustment: Combining real-time data feedback, the system can adjust the duration, area, and sequence of construction tasks. For example, in case of weather changes, increased flights, or flight delays, the system will adjust the construction progress and time to ensure that construction tasks do not affect flight operations.

[0108] It should be noted that by combining dynamic scheduling optimization and non-linear constraint optimization, the objective function is constructed and expressed as:

[0109]

[0110] Among them, \(x\) i,t \(\in \{0, 1\}\) is a binary decision variable indicating whether the \(i\)-th construction task is executed at time \(t\), \(c\) t is the flight flow at time \(t\), representing the number of flights at that moment, \(p\) i (t) represents the impact degree of the \(i\)-th construction task on the flight flow at time \(t\), \(d\) i represents the duration of the \(i\)-th construction task, \(f\) i (t) represents the non-linear impact function of the \(i\)-th construction task on the flight flow, \(\alpha\) represents the weight factor used to balance the impact of construction tasks on flight flow and construction progress, \(\beta\) i represents the construction impact coefficient related to task \(i\), reflecting the complexity and intensity of the impact of the construction task, \(W\) t represents the weather impact weight at time \(t\), used to indicate the impact of weather on construction tasks;

[0111] \(\sum\) i \(\sum\) t p i (t)·c t ·x i,tThe impact of construction tasks on flight flow;

[0112] α·∑ i d i ·∑ t x i,t The optimization of construction task duration;

[0113] β·∑ i ∑ t f i (t)·x i,t The non - linear interaction between construction tasks and flight flow;

[0114] Minimize the interference of construction tasks on flight flow through the objective function.

[0115] Furthermore, impose constraints on the objective function, including:

[0116] Each construction task can only be executed within one time period, expressed as:

[0117]

[0118] The duration constraint of construction tasks is expressed as:

[0119]

[0120] The conflict limit between construction tasks and flight flow is expressed as:

[0121]

[0122] The time - window constraint of construction tasks is expressed as:

[0123]

[0124] The dynamic adjustment related to weather factors is expressed as:

[0125]

[0126] Where, W t represents the impact of weather on construction and dynamically adjusts the construction time.

[0127] S3: Predict and optimize the construction conflict through simulation.

[0128] Furthermore, comprehensively consider the flight schedule data, construction progress, area occupancy data and environmental factors (such as weather) to predict construction conflicts.

[0129] For flight scheduling data, the system first inputs flight takeoff and landing information for each time period, including the number of flights, taxi paths, takeoff and landing times, etc.; for construction progress and area occupancy data, the system obtains construction progress and apron usage through real-time monitoring, especially the occupancy time and location of the construction area, and predicts the specific locations that may affect flights during construction; for weather data, weather data (such as wind speed, temperature, precipitation, etc.) is introduced to ensure that construction scheduling can adapt to environmental changes and avoid arranging high-density construction under adverse weather conditions.

[0130] The system simulates the potential impact of different construction plans on flight flow in different time periods and different areas:

[0131] Channel occupancy time, simulate and analyze the occupancy time of different construction areas on the channel. According to the construction progress and area usage, calculate the occupancy of the runway, taxiway and apron by construction. Flight flow density, identify peak and trough periods by predicting flight flow density. The system predicts the impact of construction on flight takeoff and landing based on flight density, and focuses on evaluating the interference caused to flights by construction during high-flow periods. Flight takeoff and landing interference, the system combines construction occupancy data, analyzes the overlap between different construction areas and flight takeoff and landing paths, and predicts possible flight interference situations.

[0132] According to the results of the simulation analysis, the system will generate a detailed conflict assessment report, point out potential construction and flight conflict points, and put forward corresponding scheduling optimization suggestions according to the severity of the impact. The following are the specific rules for conflict analysis:

[0133] High-risk conflict points: If the system detects that a certain construction area overlaps with the critical takeoff and landing time periods of flights, and the occupancy rate of the construction area on the channel exceeds the set threshold (such as 70%), the system will evaluate this construction as "high-risk" construction. High-risk construction will lead to a significant reduction in flight flow or flight delays.

[0134] Medium-risk conflict points: For those time periods with less construction occupancy of the channel or less flight flow, the system marks them as "medium-risk" construction. At this time, construction can continue, but flight flow and construction progress need to be closely monitored.

[0135] Low-risk conflict points: If the construction time is arranged in a time period with low flight density and the construction area has less occupancy of the channel, it is regarded as "low-risk" construction, and construction can proceed smoothly according to the plan.

[0136] Based on the results of simulation and conflict analysis, the system will automatically optimize the construction plan to ensure that the impact on flights is minimized during construction. The following are the logical rules for optimizing the construction plan:

[0137] Construction during high - traffic periods is postponed. The system will postpone construction tasks during high - traffic periods according to the predicted flight traffic density. For example, if the system predicts that the flight traffic is too heavy during the morning rush hour and the construction during this period may cause flight delays, the system will automatically postpone the high - density construction tasks to the low - traffic periods of flights (such as noon or evening).

[0138] Construction during low - traffic periods is increased. During the periods when the flight traffic is low, the system will increase the density of construction tasks. By flexibly adjusting the construction progress and increasing the construction volume during low - traffic periods, the construction progress can be accelerated without disturbing flights.

[0139] Dynamically adjust the construction area: The system will dynamically adjust the construction area to avoid construction on key flight paths and taxiways. If the system predicts that a certain construction area has a greater impact on flight traffic (such as overlapping flight paths), the construction tasks will be moved to other areas that do not affect flights.

[0140] Automatic adjustment for increased flights. If the system detects new flights in a certain period or area and the construction tasks in this area may conflict with the new flights, the system will automatically adjust the construction area or construction progress. For example, if a temporarily added flight needs to use a certain flight path, the system will adjust the construction tasks on this flight path to other non - key flight path areas.

[0141] Real - time scheduling progress adjustment. If, during the construction process, it is found that the flight traffic increases abnormally within a certain period, the system can immediately adjust the construction progress. By real - time monitoring the flight traffic and construction progress, the system can reduce the occupation time of the construction area on the flight path.

[0142] Flexible postponement of construction tasks. If a certain construction task is delayed and this construction task occurs during the flight peak period, the system will postpone the execution period of this task. By flexibly adjusting the construction time period, it is ensured that there are no conflicts between construction tasks during the flight traffic peak period.

[0143] S4: Real - time comparison of construction progress and flight scheduling data, dynamic scheduling adjustment mechanism.

[0144] Furthermore, during the construction process, the system compares the construction progress with the flight scheduling data through a real - time feedback mechanism, evaluates the potential impact between construction tasks and flight traffic in real - time, and dynamically adjusts the construction plan according to the comparison results to ensure that the construction progress is coordinated with the flight scheduling.

[0145] Comparison of construction progress with the expected progress. The difference between the progress of construction tasks and the expected progress can be quantified by the following mathematical formula.

[0146] For each construction task i, the change in construction progress Δd i (t) is expressed as:

[0147] Δd i (t) = d i -S i (t)

[0148] where d i represents the scheduled duration of task i, and S i (t) represents the remaining workload of task i at time t. If Δd i (t) > 0, it means the construction task progress lags behind the expectation; if Δd i (t) < 0, it means the construction task progress is ahead;

[0149] For each time period t, the comparison of the progress change of the construction task with the flight flow is:

[0150]

[0151] where (1 + β(t)) represents the influence coefficient of external factors on the construction progress, reflecting the additional influence of the external environment on the construction progress and flight flow;

[0152] Introduce the scheduling flexibility coefficient λ i (t), which represents the scheduling flexibility of the construction task within time t, reflecting whether the construction task can be dynamically adjusted according to the flight flow. The adjusted construction influence is expressed as:

[0153] I i,t adjusted = I i,t ·(1 - λ i (t))

[0154] where λ i (t) represents the scheduling flexibility coefficient of the construction task, and its value range is 0 ≤ λ i (t) ≤ 1. When λ i (t) = 0, the time period of the construction task is fixed; when λ i (t) = 1, the construction task fully dynamically adjusts the time period and area;

[0155] According to the real-time comparison of the influence of construction on flight flow, the system evaluates the conflict situation between the construction task and flight scheduling. The evaluation is expressed as:

[0156]

[0157] where Threshold represents the maximum tolerance of construction for flight flow. If I i,t adjusted exceeds the threshold, the system considers that there is a conflict between the construction task and flight scheduling and triggers the adjustment mechanism, C i,tA value of 1 indicates that a conflict has occurred and the construction plan needs to be adjusted; a value of 0 indicates that there is no conflict and the construction can proceed as planned.

[0158] When the system detects a conflict between a construction task and flight scheduling, it will automatically adjust the time period or area of the construction task.

[0159] If the conflict occurs during a period when the flight flow is higher than 60%, the adjusted construction time period t′ is expressed as:

[0160] t′ = t + Δt

[0161] Where, Δt represents the adjusted time difference.

[0162] For the adjustment of the construction area, if the area where the construction task is located overlaps with the flight takeoff and landing path, the system will adjust the area of the construction task to avoid interference with key waterways and taxiways.

[0163] For the postponement or advancement of the construction task, based on the change in flight flow and the feedback of the construction progress, the system will balance the conflict between construction and flight scheduling by adjusting the start time or end time of the construction task, ensuring that the construction task is completed on time and minimizing the impact on flights.

[0164] To optimize the coordination between construction scheduling and flight scheduling, an objective function for optimizing construction scheduling and flight scheduling is introduced and expressed as:

[0165]

[0166] Where, ∑ i ∑ t C i,t ·I i,t ·Δt represents the cost generated by adjusting the construction time period or area, and α·∑ i d i ·∑ t x i,t represents the optimization of the construction task progress, and β·∑ i ∑ t p i (t)·c t ·x i,t represents the impact of the construction task on flight flow.

[0167] Example 2, an embodiment of the present invention, provides a method for regulating non-stop construction of airport runway engineering based on dynamic monitoring. To verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0168] First, intelligent sensors, high-definition cameras, and drones were installed at multiple key locations in an experimental airport (such as runways, taxiways, and aprons) to monitor the runway conditions and construction progress in real time. A real-time interface was established with the airport flight scheduling system to obtain information such as flight takeoff and landing times, taxi paths, and flight volumes. A weather station was set up at the airport to monitor environmental factors such as wind speed, temperature, and precipitation in real time, which can affect flight safety and construction progress. All the collected data was transmitted to the central scheduling platform via wireless network for data fusion and real-time analysis to support dynamic scheduling decisions.

[0169] During the implementation process, the system first collected the usage of the airport runway in real time through intelligent sensors, high-definition cameras, and drones, including the occupancy status of areas such as runways, taxiways, and aprons, as well as the real-time occupancy of the construction area. By establishing a connection with the flight scheduling system, the system was able to obtain real-time flight takeoff and landing information, taxi paths, schedules, and other data, and integrate these data with construction progress and meteorological data. After all the data was processed, it was uniformly transmitted to the central scheduling platform for comprehensive analysis to monitor the dynamic changes of construction tasks and flight scheduling in real time.

[0170] The system input the collected real-time data into an artificial intelligence model based on machine learning and deep learning, and combined with historical data to predict flight volumes. The system used time series analysis and neural network algorithms to predict flight volumes to identify peak and trough periods. Based on the prediction of flight volumes, the system would automatically optimize the construction periods and areas to ensure that no construction was scheduled during high-volume periods to avoid interfering with flight takeoffs and landings.

[0171] During the construction process, the system collected the construction status and remaining workload through real-time progress monitoring devices and compared them with flight volume data in real time. If the construction progress lagged behind, the system would make up for the progress gap by dynamically adjusting the construction period or area. For example, construction could be carried out during low-volume periods to avoid construction conflicts during high-flight-volume periods.

[0172] The system used simulation tools to simulate the impact of different construction plans on flight scheduling by combining flight schedule data, construction progress, and area occupancy data. The simulation results could predict the interference of construction at different times and areas on flight takeoffs and landings. After analyzing the simulation results, the system would generate a conflict assessment report, point out potential conflict points, and automatically optimize the construction plan to ensure that construction tasks were carried out outside high-volume periods to reduce interference to flights.

[0173] During the construction process, if there are abnormal changes in flight traffic (such as a sudden increase in flights), the system will adjust the time period or area of the construction tasks through intelligent algorithms to ensure that the construction does not affect the takeoff and landing of flights. Through adaptive adjustment, the system can real-time adjust the construction plan to cope with the impact of weather changes, equipment failures or other uncontrollable factors.

[0174] As mentioned above, Table 1 records the key data during the experiment, including parameters such as flight traffic prediction, construction progress lag time, construction impact degree, weather impact coefficient, etc. The data shows the comparison between different construction tasks and flight traffic, as well as whether there are conflicts.

[0175] Table 1 Experimental data table

[0176]

[0177] It can be seen from Table 1 that in construction tasks 1, 3 and 5, the construction progress lag time is relatively long and the construction impact degree is relatively high (>70%), which indicates that these tasks may cause greater interference to flight traffic. Comparing construction tasks 2, 4 and 6, the construction progress lag time is shorter and the construction impact degree is lower (<70%). Therefore, these three tasks have less interference to flight scheduling and the construction arrangement is more reasonable. The weather impact coefficients of construction tasks 3 and 6 are relatively high (>15%), which means that their construction arrangements are more vulnerable to weather factors. Therefore, the system will give priority to arranging these construction tasks during low flight traffic periods during scheduling to avoid double interference from weather and flight traffic. In tasks 1, 3 and 5, the system evaluates that there are conflicts (value is 1). These tasks have potential conflicts when in high traffic periods or with a large lag in construction progress. It shows that the scheduling optimization of the system can effectively identify the conflicts between construction and flight traffic and make timely adjustments. Comparing tasks 2, 4 and 6, the system evaluates that there are no conflicts (value is 0). The arrangements of these tasks are more reasonable and will not affect flight traffic.

[0178] By comparing the data in Table 1, it can be seen that the intelligent scheduling optimization method of the present invention has obvious advantages. The system can effectively avoid the interference of construction on flights by real-time monitoring and predicting flight traffic and combining with the dynamic changes of construction tasks. During high traffic periods, the system will automatically adjust the construction tasks and postpone high-density construction tasks to low traffic periods to ensure the normal takeoff and landing of flights. The introduction of simulation and feedback mechanisms further enhances the adaptability and flexibility of the scheduling system, effectively avoiding conflicts between construction tasks and flight scheduling, and improving the accuracy and flexibility of construction scheduling. Through data analysis, the system can not only accurately predict flight traffic, but also optimize the construction plan through factors such as construction progress and weather impact, so as to ensure a high degree of coordination between construction tasks and flight scheduling.

[0179] Example 3, referring to Figure 3 , an embodiment of the present invention provides a non-stop construction regulation system for airport pavement engineering based on dynamic monitoring, including an initialization module, a dynamic scheduling optimization algorithm module, a prediction and simulation module, and a monitoring and adjustment module.

[0180] Among them, the initialization module is used for real-time dynamic data acquisition and multi-source information fusion. The dynamic scheduling optimization algorithm module is used for automatic optimization of construction time periods and regions. The prediction and simulation module is used for optimizing construction plans. The monitoring and adjustment module is used for dynamically adjusting construction arrangements.

[0181] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0182] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0183] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which a program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0184] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

[0185] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring, characterized in that: include: Collect real-time dynamic data and fuse multi-source information; Airport runway construction scheduling based on intelligent prediction and adaptive optimization; Predict construction conflicts and optimize scheduling through simulation; Real-time comparison of construction progress and flight scheduling data, and dynamic scheduling adjustment mechanism.

2. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring according to claim 1, characterized in that: The acquisition of real-time dynamic data and fusion of multi-source information includes installing sensors on each runway of the airport to monitor the use status of the runway in real time; Sensors monitor whether the lanes are occupied and to what extent; Through real-time connection with the airport's existing flight dispatch system, the take-off and landing times, taxi paths and flight traffic of flights can be retrieved; Monitor airport flight traffic in real time and predict flight density; Set up a weather station to monitor wind speed, wind direction, temperature, humidity, and precipitation in real time; All collected meteorological data is transmitted to the central dispatching platform via wireless network, and the central dispatching platform integrates and analyzes meteorological data with flight information and construction information; The central dispatch platform collects data from the monitoring system, including runway status, flight dispatch, and environmental meteorological data.

3. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in claim 2, characterized in that: The airport runway construction scheduling based on intelligent prediction and adaptive optimization includes inputting all collected real-time data, and performing intelligent analysis and prediction based on the real-time data, combined with historical data and monitoring data; The data input includes: flight scheduling information, runway usage status, construction progress, and meteorological data; Based on historical flight traffic data, the trend of future flight traffic is predicted through time series models, and the periodicity and trend characteristics of changes in flight take-off and landing density are identified; Through the LSTM network, flight traffic is predicted while taking into account seasonality and holiday factors; Based on the needs of the construction tasks and the use of the field roads, the system will automatically select the construction period and area, including selecting the construction period and optimizing the construction area; Dynamic adjustment of construction schedule and time period including feedback mechanism and adaptive adjustment; The objective function is constructed by combining dynamic scheduling optimization and nonlinear constraint optimization, which is expressed as: Among them, x i,t ∈{0,1} is a binary decision variable, indicating whether the i-th construction task is executed at time t, c t is the flight flow at time t, indicating the number of flights at that time, p i (t) represents the impact of construction task i on flight flow at time t, d i represents the duration of construction task i, f i (t) represents the nonlinear impact function of construction task i on flight flow, α represents the weight factor, which is used to balance the impact of construction tasks on flight flow and construction progress, β i represents the construction impact coefficient related to task i, reflecting the complexity of the construction task and the intensity of the impact, W t The table shows the weather impact weight at time t, which is used to indicate the impact of weather on construction tasks; ∑ i ∑ t p i (t)·c t ·x i,t The impact of construction tasks on flight traffic; α·∑ i d i ·∑ t x i,t To optimize the duration of construction tasks; β·∑ i ∑ t f i (t)·x i,t The nonlinear interaction between construction tasks and flight flow; The interference of construction tasks on flight flow is minimized through the objective function.

4. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in claim 3 is characterized by: The airport runway construction scheduling based on intelligent prediction and adaptive optimization includes imposing constraints on the objective function, including: Each construction task can only be executed within a time period, which is represented as: The duration constraint of the construction task is expressed as: The conflict constraints between construction tasks and flight flow are expressed as: The time window constraint of the construction task is expressed as: Dynamic adjustment and weather factors are expressed as: Among them, W t Indicates the impact of weather on construction and dynamically adjusts the construction time.

5. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in claim 4, characterized in that: The construction conflict prediction and optimization scheduling by simulation includes simulating the conflict between construction and flight; Input flight takeoff and landing information for each time period, including the number of flights, taxiing paths, takeoff and landing times, etc., obtain construction progress and runway usage through real-time monitoring, and predict the locations that affect flights during the construction process and introduce weather data; Simulate the potential impact of different construction plans on flight traffic in different time periods and in different areas, including channel occupancy time, flight traffic density, and flight takeoff and landing interference; Based on the results of simulation analysis, output the conflict points between construction and flights, and propose scheduling optimization based on the severity of the impact; If it is detected that the construction area overlaps with the take-off and landing time period of the flight, and the occupancy rate of the construction area to the waterway exceeds 70%, the system will assess the construction as high-risk construction; If the occupancy rate of the construction area to the waterway is greater than or equal to 30% and less than or equal to 70%, the system assesses the construction as medium-risk construction. At this time, construction continues, but flight flow and construction progress need to be monitored; If the construction area's occupancy rate of the waterway is less than 30%, the system assesses the construction as low-risk and construction continues as planned.

6. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in claim 5, characterized in that: The construction conflict prediction and optimization scheduling by simulation includes optimizing the construction plan based on the simulation and conflict analysis results; Based on the predicted flight traffic density, postpone construction tasks during periods when traffic is higher than 60%; Increase the density of construction tasks during periods when flight traffic is less than or equal to 60%; Dynamically adjust the construction area to avoid construction on working channels and taxiways; If the system predicts that the construction area will affect flight traffic, the construction task will be moved to an area that does not affect flights; If the system finds that there are new flights in a time period or area, and the construction tasks in the area conflict with the new flights, the system will automatically adjust the construction area or construction progress; If during the construction process, it is found that the flight traffic increases within a time period, the system will immediately adjust the construction progress; If there is a delay in the construction task and the construction task occurs during a period when the flight traffic is higher than 60%, the system will postpone the execution period of the task.

7. The method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in claim 6, characterized in that: The real-time comparison of construction progress and flight scheduling data, the dynamic scheduling adjustment mechanism includes for each construction task i, defining the change in construction progress Δd i (t) is expressed as: Δd i (t)=d i -S i (t) Among them, d i represents the scheduled duration of task i, S i (t) represents the remaining workload of task i at time t, if Δd i (t)>0, indicating that the construction task progress lags behind expectations; if Δd i (t)<0, it means that the construction task progress is ahead of schedule; For each time period t, the comparison between the progress change of the construction task and the flight flow is: Among them, (1+β(t)) represents the influence coefficient of external factors on construction progress, reflecting the additional impact of the external environment on construction progress and flight flow; Introducing the scheduling flexibility coefficient λ i (t), represents the scheduling flexibility of the construction task within time t, reflecting whether the construction task can be dynamically adjusted according to the flight flow. The adjusted construction impact is expressed as: I i,t adjusted=I i,t ·(1-λ i (t)) Among them, λ i (t) represents the scheduling flexibility coefficient of the construction task, and its value range is 0≤λ i (t)≤1, when λ i When (t) = 0, the construction task period is fixed; when λ i When (t) = 1, the construction task fully dynamically adjusts the time period and area; Based on the real-time comparison of the impact of construction on flight flow, the system evaluates the conflict between construction tasks and flight scheduling. The evaluation is expressed as: Among them, Threshold represents the maximum tolerance of construction to flight flow. If I i,t When the threshold is exceeded, the system considers that the construction task conflicts with the flight scheduling and triggers the adjustment mechanism. i,t A value of 1 indicates that a conflict has occurred and the construction plan needs to be adjusted; a value of 0 indicates that there is no conflict and the construction can proceed as planned; When the system detects that a construction task conflicts with flight scheduling, it will automatically adjust the time period or area of ​​the construction task; If the conflict occurs during a period when the flight flow is higher than 60%, the adjusted construction period t′ is expressed as: t′=t+Δt Among them, Δt represents the adjusted time difference; Optimize the coordination between construction scheduling and flight scheduling, introduce the construction scheduling and flight scheduling optimization objective function expressed as: Among them, ∑ i ∑ t C i,t I i,t ·Δt represents the cost of adjusting the construction period or area, α·∑ i d i ·∑ t x i,t represents the progress optimization of the construction task, β·∑ i ∑ t p i (t)·c t ·x i,t Represents the impact of construction tasks on flight flow.

8. A system using the method for controlling the construction of airport runway engineering without stopping flights based on dynamic monitoring as claimed in any one of claims 1 to 7, characterized in that: Including initialization module, dynamic scheduling optimization algorithm module, prediction and simulation module, monitoring and adjustment module; The initialization module is used for real-time dynamic data acquisition and multi-source information fusion; The dynamic scheduling optimization algorithm module is used for automatic optimization of construction periods and areas; The prediction and simulation module is used to optimize the construction plan; The monitoring and adjustment module is used to dynamically adjust the construction schedule.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for controlling the construction of an airport runway project without stopping flights based on dynamic monitoring described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for controlling the construction of an airport runway project without stopping flights based on dynamic monitoring as described in any one of claims 1 to 7 are implemented.

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