Water distributor water supply control system for an airport

Abstract

The application discloses a water distributor water supply control system for an airport, and belongs to the technical field of automatic control of airport infrastructure, comprising: a multi-dimensional information acquisition unit for acquiring multi-dimensional information such as weather, pavement state and flight operation in real time; a digital twin and prediction decision unit for constructing a digital twin model based on the multi-dimensional information and predicting future heat load demand; a dual-mode energy supply strategy generation unit for generating reserve or pulse type rapid response instructions according to the prediction results; and a full life cycle health diagnosis unit for diagnosing pipe network leakage, blockage and corrosion state online. Through the combination of predictive control and health self-diagnosis, the beneficial effects of significantly reducing energy consumption, rapid response, high operation reliability and intelligent management are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of airport infrastructure automation control, in particular to a water distributor water supply control system for an airport. BACKGROUND

[0002] The safety of the pavement area of the airport runway, taxiway, etc. is the cornerstone of ensuring the normal operation of air transportation. Under the condition of low temperature in winter, the snow and ice on the pavement are the main hidden dangers that seriously threaten the safety of aircraft take-off and landing. To solve this problem, the existing technology usually adopts two schemes: one is chemical deicing, that is, spraying snow melting agent, but this method will cause corrosion to the pavement structure and the aircraft body, and bring environmental pollution problems; the other is physical heating, that is, embedding pipes or heating cables in the pavement structure to form an indirect contact type heat exchange equipment, and the heat is conducted to the pavement to melt the ice and snow through the heating of the fluid medium in the pipe or the cable itself.

[0003] However, the existing physical heating scheme has significant technical defects in the control level. When water or glycol solution is used as the heat transfer medium, the control system mostly adopts a simple threshold feedback logic based on the pavement temperature sensor. When the temperature is lower than the set value, the system starts global or large-area heating. The one-size-fits-all passive response control mode cannot predict weather changes and combine with the actual operation needs of the airport, so the system often performs invalid or excessive heating, which causes huge energy waste for the vast pavement area of the airport. In addition, the pavement concrete and the circulating water both have large thermal inertia, and it usually takes a long time from starting heating to the pavement reaching the effective snow melting temperature, which is difficult to deal with sudden severe weather such as freezing rain and snowstorm, and there is a safety hazard. At the same time, once the heat exchange pipeline buried underground has faults such as leakage and blockage, the traditional control system cannot sense and locate, and it can only be found after the fault expands or the system fails, which results in high maintenance cost and serious impact on airport operation. Therefore, there is an urgent need in the field for a water distributor water supply control system for an airport. SUMMARY

[0004] The purpose of the present application is to solve the defects in the prior art, and a water distributor water supply control system for an airport is provided.

[0005] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0006] A water distributor water supply control system for an airport, comprising:

[0007] A multi-dimensional information acquisition unit for acquiring multi-dimensional information composed of airport meteorological data, pavement internal temperature and humidity state data, and airport coordinated decision system flight operation data in real time;

[0008] The digital twin and the prediction decision unit are in communication connection with the multi-dimensional information collection unit, and are configured to construct a digital twin model integrating pavement static geometry, dynamic thermodynamics and material properties based on preset pavement physical parameters and the multi-dimensional information, and predict future heat load demand of different pavement partitions served by the water distributor using the digital twin model.

[0009] The dual-mode energy supply strategy generation unit is configured to generate dual-mode water supply control instructions for different pavement partitions according to the future heat load demand output by the digital twin and the prediction decision unit, and the dual-mode water supply control instructions include:

[0010] The reserve mode instruction is configured to control the external main heat source to store energy for the distributed phase change energy storage module integrated with the water distributor pipe network and maintain trickle circulation of the pipe network medium when predicting long-term heat load demand;

[0011] The pulse response mode instruction is configured to control the circulating medium to flow through the phase change energy storage module that has completed energy storage to rapidly heat the circulating medium using the latent heat of phase change when predicting short-term heat load demand;

[0012] The full life cycle health diagnosis unit is configured to receive and process distributed optical fiber acoustic sensing data and electrochemical impedance spectroscopy sensing data arranged in the water distributor pipe network, diagnose and accurately locate the abnormal state of leakage, blockage or corrosion of the water distributor pipe network by comparing the sensing data with a preset system health benchmark model, and generate a warning instruction or a maintenance instruction.

[0013] Further, the digital twin and the prediction decision unit are further configured to generate differentiated heat load demand for the runway grounding belt based on the aircraft model and the aircraft weight class in the flight operation data;

[0014] And based on the planned take-off and landing time, identify the flight intensive period to adjust the overall heating power level.

[0015] Further, the digital twin and the prediction decision unit are further configured to generate differentiated heat load demand for the runway grounding belt based on the aircraft model and the aircraft weight class in the flight operation data;

[0016] The execution logic of the model predictive control algorithm in a control cycle includes predicting the pavement state evolution trajectory within a preset time window based on the digital twin model;

[0017] Solving the optimal control variable sequence with the system total energy consumption and the pavement icing risk in the time window as the optimization target;

[0018] Further, the dual-mode energy supply strategy generation unit is configured to generate the impulse response mode instruction when the pavement temperature drop rate, the precipitation type and the precipitation level predicted by the prediction decision unit meet the preset sudden severe weather model threshold.

[0019] Further, the impulse response mode instruction includes a valve group control instruction for switching control of the target pavement partition corresponding pipe network valve group, and a water pump control instruction for regulating the start-stop and rotating speed of the target pavement partition circulating water pump, wherein the instruction contains the identification information of the target pavement partition, the target flow set value, the target temperature set value and the target temperature rise rate parameter.

[0020] Further, the full life cycle health diagnosis unit determines the three-dimensional spatial position of the water distributor pipe network leakage point by analyzing the high-frequency acoustic characteristic signal in the distributed optical fiber acoustic sensing data, and generates a maintenance instruction containing the three-dimensional spatial position coordinates, the leakage abnormal type identification and a leakage quantization level calculated based on the signal intensity.

[0021] Further, the full life cycle health diagnosis unit is also used to determine the corrosion rate of the pipe network inner wall based on the electrochemical impedance spectroscopy sensing data.

[0022] The corrosion rate is compared with the preset corrosion rate threshold value, and when the corrosion rate exceeds the threshold value, the compensation current value or the medicament dosing dose is calculated according to the exceeding value, to generate the corresponding current intensity control signal or the medicament dosing signal.

[0023] Further, the full life cycle health diagnosis unit further includes a data interface module, which is used to send the generated maintenance instruction to the airport automatic operation and maintenance work order system.

[0024] Further, the system further includes a model self-optimization unit, which is used to compare the measured data of pavement temperature and system energy consumption with the predicted values of the prediction decision unit after the heat event ends, and iteratively correct the related parameters of the digital twin model by machine learning algorithm according to the deviation.

[0025] Further, the reserve mode instruction further includes an instruction for controlling the start-stop timing and output power of the external main heat source, which is generated according to the real-time energy storage state of the phase change energy storage module and the predicted long-term total heat load.

[0026] Compared with the prior art, the beneficial effects of the present application are:

[0027] By constructing a digital twin model, combining weather forecasts and real-time flight dynamics, runway preheating can be started in advance before severe weather arrives, and through the pulse-type rapid response capability, key runway areas can always be in a safe and ice-free state, improving safety redundancy and reducing runway closure or flight delay due to weather;

[0028] Through the rolling optimization algorithm based on model predictive control, the system can supply energy on demand according to the future precise heat load demand, eliminating the invalid heating in the traditional scheme, significantly reducing energy consumption, combining with the use of time-of-use electricity price and the peak shaving and valley filling ability of phase change energy storage, further optimizing the energy cost, and the whole life cycle health diagnosis capability realizes the predictive maintenance of potential faults, avoiding the high-cost emergency repair and operation interruption loss;

[0029] Through the integrated distributed optical fiber acoustic sensing and electrochemical impedance spectroscopy, the underground pipe network system can accurately locate small leaks, blockages and corrosion states online, and automatically push structured maintenance instructions to the operation and maintenance system, realizing the upgrade from manual inspection to intelligent self-diagnosis, and ensuring the high availability of heat exchange equipment at critical moments. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, used to explain the present application, and do not constitute a limitation of the present application.

[0031] Figure 1 is a system overall architecture schematic diagram of an embodiment of the present application;

[0032] Figure 2 is a control system function module diagram of an embodiment of the present application;

[0033] Figure 3 is a digital twin model composition schematic diagram of an embodiment of the present application;

[0034] Figure 4 is a dual-mode energy supply strategy logic flow chart of an embodiment of the present application;

[0035] Figure 5 is a whole life cycle health diagnosis system principle schematic diagram of an embodiment of the present application. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all.

[0037] EMBODIMENT

[0038] As Figure 1As shown, this embodiment of the invention provides a water distribution control system for airports. In a specific application scenario, the system is deployed on the central control server of the airport data center. Through the airport's high-speed data network, it communicates in real time with various sensors distributed on the pavement and pipeline network, as well as field-programmable logic controllers (PLCs) that control valves and water pumps, and the airport tower information system.

[0039] The physical deployment architecture of this system is a three-level distributed control architecture:

[0040] The central control server located in the data center is responsible for running the core algorithm unit of this invention;

[0041] Regional programmable logic controllers (PLCs) set up in different areas of the airport serve as an intermediate layer, responsible for executing instructions issued by the central server and managing the equipment within their respective areas;

[0042] The smart meters, sensors, and actuators such as electric valves / variable frequency pumps on site form the lowest layer.

[0043] Communication between different levels is achieved via industrial Ethernet. Furthermore, those skilled in the art will understand that in some embodiments, some sensors may be replaced or supplemented by non-contact infrared thermal imaging camera arrays. These variations do not depart from the core idea of ​​the present invention.

[0044] like Figure 2 As shown, a water distribution system for airports includes: a multi-dimensional information acquisition unit, a digital twin and predictive decision-making unit, a dual-mode power supply strategy generation unit, and a full life-cycle health diagnosis unit, wherein:

[0045] The multi-dimensional information acquisition unit, acting as the system's data hub, is responsible for providing comprehensive and real-time input for upper-level decision-making. In this embodiment, the multi-dimensional information acquisition unit operates in the following manner:

[0046] By calling the application programming interface provided by the meteorological service provider, refined meteorological information covering the airport area is obtained on a regular basis. The information includes, but is not limited to, hourly temperature, humidity, wind speed, solar radiation intensity, and key predictive precipitation type codes for the next 24 hours.

[0047] Data is collected via an industrial fieldbus from a sensor array embedded 5 cm deep beneath the pavement concrete structure, arranged in a 50x50 meter grid. This array preferably includes a Pt100 platinum resistance sensor for precise temperature measurement and a capacitive humidity sensor for measuring pavement and soil moisture.

[0048] The dynamic operation data of the flight is obtained in real time by accessing the database view of the airport collaborative decision system or subscribing to its Advanced Message Queuing Protocol message queue. The protocol parsing module built in this unit is responsible for extracting the specific model of the aircraft, the maximum take-off weight and other deep parameters from the structured data stream.

[0049] As shown in Figure 3 , the digital twin and predictive decision unit maps the airport pavement in the physical world into a computable and simulatable digital model, and makes predictions and decisions based on this. The digital twin model constructed is a highly integrated multi-physical field simulation model, and its internal structure specifically includes: a static geometry module loaded with accurate three-dimensional Computer Aided Design (CAD) drawings of the pavement and underground pipe network;

[0050] a dynamic thermodynamics module built-in describing the partial differential equation set of heat conduction, convection and radiation processes in multiple media;

[0051] and a material property database storing key physical property parameters such as specific heat capacity and thermal conductivity of pavement concrete, foundation soil, circulating medium (such as 40% glycol solution) at different temperatures, etc., which provides the basis for the accuracy of thermodynamic simulation.

[0052] In addition, on top of this digital twin and predictive decision unit, the model predictive control algorithm is also running on the digital twin and predictive decision unit, which performs rolling optimization every minute and the execution logic within a control period is designed as follows:

[0053] A prediction time window of 2 hours in the future is set, and then the latest weather forecast data is input as a boundary condition into the digital twin model to simulate the evolution trajectory of the temperature and icing risk of each partition of the pavement within the time window if no control is applied;

[0054] A cost function is established, which is the weighted sum of the predicted total energy consumption of the system within the prediction time window and a penalty term related to the length of time during which the pavement temperature is below a safety threshold (e.g. 1°C). Specifically, the value of the penalty term is directly proportional to the product of the area and length of time of all areas of the pavement predicted to be below the safety threshold, and the model predictive control algorithm aims to minimize this cost function to solve an optimal control sequence consisting of a series of pump speeds, valve openings, etc.

[0055] The system only sends the first instruction in the optimal control sequence to the lower-level unit for execution, and at the start of the next period, it obtains the latest pavement state and repeats the prediction and optimization steps described above.

[0056] In particular, the MPC algorithm will convert the flight operation data into dynamic constraints on the model when performing optimization. In a preferred embodiment, the MPC algorithm will match a thermal impact factor according to the acquired aircraft weight class, and dynamically correct the surface heat transfer coefficient of the runway contact strip area in the thermal model with the thermal impact factor, so that the algorithm automatically allocates higher thermal load requirements for this specific area when optimizing.

[0057] In addition, the digital twin and predictive decision unit will also calculate the flight flow density in the next few hours according to the planned take-off and landing time data. When an upcoming "flight intensive period" is identified, the system will automatically increase the overall base heating power level of the corresponding runway or taxiway to ensure the continuous and stable pavement temperature under high frequency use; conversely, in the "flight sparse period", it will be reduced to the minimum economic operation mode, realizing the macro adjustment of energy.

[0058] As shown in Figure 4 The dual-mode energy supply strategy generation unit is responsible for converting the abstract thermal load demand output by the upper unit into specific and executable device control instruction sequences.

[0059] When receiving the reserve mode instruction, the dual-mode energy supply strategy generation unit will calculate the optimal start-stop sequence and output power curve of the main heat source (such as ground source heat pump, gas boiler or city heat exchange station) according to the long-term total thermal load demand predicted by the digital twin unit, combined with the current energy storage state feedback by the real-time temperature sensor of the phase change energy storage module, and superimposed with the time-of-use electricity price table of the airport power system, and finally generate control instructions for the distributed phase change energy storage module (PCM) integrated with the water distributor pipe network and internally filled with inorganic salt hydrate phase change material (phase change temperature preferably 50-60°C) to store energy. At the same time, the instruction will drive the circulating water pump at 5% of the rated power to maintain the trickle circulation of the pipe network medium;

[0060] When receiving the pulse response mode instruction, it is not triggered based on a single threshold, but through a multi-factor weight decision model. The dual-mode energy supply strategy generation unit will analyze the runway temperature drop rate, predicted precipitation type and predicted water level, and other key meteorological indicators in the future time window output by the predictive decision unit in real time. Only when the weighted combination score of these indicators exceeds the preset dangerous weather response threshold, will the system automatically generate a pulse response mode instruction.

[0061] After generating the impulse response pattern instruction, the dual-mode energy supply strategy generation unit immediately generates a structured digital signal package (for example, a Controller Area Network (CAN) bus message) that encapsulates the identification ID of the target partition, the target flow set value accurate to 0.1 m 3 / h, the target temperature set value accurate to 0.5 °C, and a target temperature rise rate parameter. The signal is sent to the PLC controller corresponding to the target partition, and the PLC controls the three-way valve group to switch first, so that the circulating medium is switched from the conventional main heat source circuit to the PCM circuit;

[0062] Then, the variable frequency water pump is started smoothly according to the slope curve defined by the temperature rise rate parameter in the instruction and quickly reaches the target flow, so that a pulse of high-temperature medium carrying latent heat of phase change is delivered to the target pavement.

[0063] As shown in Figure 5 , the full life cycle health diagnosis unit is used for online and non-destructive monitoring and diagnosis of the pipe network, specifically:

[0064] For leakage and blockage diagnosis, the full life cycle health diagnosis unit periodically emits laser pulses into the communication optical cable laid along the pipe network through a DAS (Distributed Acoustic Sensing) analyzer and receives and analyzes Rayleigh scattering echo signals. The internal signal processing module performs Fast Fourier Transform (FFT) on the echo signals;

[0065] When the pipe network leaks, the high-frequency sound waves (usually in the range of 1-10 kHz) generated by the fluid spouting are perceived by the optical fiber, forming abnormal energy peaks on the FFT spectrum. The unit detects these peaks and combines the flight time of the optical pulse to accurately locate the three-dimensional spatial coordinates of the leakage point. In the final output maintenance instruction, it will explicitly include the coordinates, the abnormal type identification of "leakage", and a leakage quantization level of 1-5 levels evaluated according to the signal amplitude;

[0066] For corrosion and scaling diagnosis, the unit periodically performs Electrochemical Impedance Spectroscopy (EIS) scanning through a three-electrode system (including a working electrode, a reference electrode, and an auxiliary electrode) connected to the pipe, and its analysis logic is:

[0067] Firstly, by fitting the measured Nyquist plot, the key electrochemical parameters such as charge transfer resistance (Rct) are extracted, and then the Rct value is converted into a specific corrosion rate (unit: mm / year) by an empirical model based on the Stern-Geary equation pre-installed in the system;

[0068] Next, the system will compare this calculated rate with the preset safety threshold in real time. Once the threshold is exceeded, the system will automatically calculate a direct current compensation or an inhibitor dosage accurate to the milliliter according to the difference exceeding the threshold, and generate the corresponding current intensity control signal or reagent dosing signal.

[0069] It needs to be particularly emphasized that the various functional units in the embodiment of the present application are not running in isolation, but constitute an intelligent closed-loop system with dynamic cooperation and bidirectional information flow. For example, when the full-life-cycle health diagnosis unit detects that the internal fouling of a certain pipeline partition causes a 5% decrease in heat transfer efficiency, the status information will be fed back to the digital twin and predictive decision unit in real time. The digital twin model will immediately update the thermal resistance parameters of the partition, and automatically allocate higher heat supply to the partition in the next round of MPC optimization calculation to compensate for the performance degradation caused by fouling, which reflects the high robustness and intelligence of the system.

[0070] In addition, the system also includes a model self-optimization unit and a data interface module, wherein:

[0071] The model self-optimization unit will use historical data to iteratively correct the key parameters of the dynamic thermodynamic module in the digital twin model after each snowmelt event, using a machine learning algorithm based on gradient boosting decision trees or long short-term memory networks, making it increasingly accurate;

[0072] The data interface module is responsible for automatically pushing the structured maintenance instructions generated by the health diagnosis unit, encapsulated in JavaScript Object Notation (JSON) or Extensible Markup Language (XML) format, to the airport's computerized maintenance management system through HyperText Transfer Protocol (HTTP) POST requests or message queues. This automated workflow minimizes the delay caused by human intervention, ensuring quick response and closed-loop tracking of maintenance tasks.

[0073] The above merely describes preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art, according to the technical solution and inventive concept of the present application, makes equivalent replacement or change within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A water distributor water supply control system for an airport, characterized by, The method comprises the following steps: A multi-dimensional information acquisition unit is used to acquire multi-dimensional information in real time, which is composed of airport meteorological data, internal temperature and humidity state data of the runway, and flight operation data of the airport collaborative decision system; A digital twin and prediction decision unit is communicatively connected with the multi-dimensional information acquisition unit, and is used to construct a digital twin model integrating the static geometry, dynamic thermodynamics and material properties of the runway based on the preset runway physical parameters and the multi-dimensional information, and to predict the future heat load demand of different runway partitions served by the water distributor using the digital twin model; A dual-mode energy supply strategy generation unit is used to generate dual-mode water supply control instructions for different runway partitions according to the future heat load demand output by the digital twin and prediction decision unit, which includes: A reserve mode instruction is used to control the external main heat source to store energy for the distributed phase change energy storage module integrated with the water distributor pipe network and maintain the trickle circulation of the pipe network medium when the long-term heat load demand is predicted; A pulse response mode instruction is used to control the circulating medium to flow through the phase change energy storage module that has completed energy storage to quickly warm up the circulating medium using the latent heat of phase change when the short-term heat load demand is predicted; A full life cycle health diagnosis unit is used to receive and process distributed optical fiber acoustic sensing data and electrochemical impedance spectrum sensing data arranged in the water distributor pipe network, diagnose and accurately locate the leakage or blockage abnormal state of the water distributor pipe network based on the distributed optical fiber acoustic sensing data, and diagnose the corrosion abnormal state of the water distributor pipe network based on the electrochemical impedance spectrum sensing data, and generate corresponding warning instructions or maintenance instructions.

2. The water distributor water supply control system for an airport according to claim 1, characterized by, The digital twin and prediction decision unit is further used to generate differentiated heat load demand for the runway grounding zone based on the aircraft type and aircraft weight class in the flight operation data; And identify the flight intensive period based on the planned take-off and landing time to adjust the overall heating power level.

3. The water distributor water supply control system for an airport according to claim 1, characterized by, The model predictive control algorithm built in the digital twin and prediction decision unit includes the following execution logic in a control cycle: Predict the runway state evolution trajectory in a future preset time window based on the digital twin model; Solve the optimal control variable sequence with the system total energy consumption and the runway icing risk in the time window as the optimization objectives; 4. The water distributor water supply control system for an airport according to claim 1, characterized by, And output the first control instruction of the optimal control variable sequence to the dual-mode energy supply strategy generation unit to realize rolling optimization.

5. The water distributor water supply control system for an airport according to claim 1 or 4, characterized by, The dual-mode energy supply strategy generation unit is configured to generate the pulse response mode instruction when the runway temperature drop rate, precipitation type and precipitation level predicted by the digital twin and prediction decision unit meet the preset sudden severe weather model threshold. The pulse response mode instruction includes a valve group control instruction for switching control of the pipe network valve group corresponding to the target runway partition, and a water pump control instruction for adjusting the start-stop and speed of the circulating water pump of the target runway partition, wherein the instruction contains the identification information, target flow set value, target temperature set value and target temperature rise rate parameter of the target runway partition.

6. The water distributor water supply control system for an airport of claim 1, wherein, The full life cycle health diagnosis unit determines the three-dimensional spatial position of the water distributor pipe network leakage point by analyzing the high-frequency acoustic characteristic signal in the distributed optical fiber acoustic sensing data, and generates a maintenance instruction containing the three-dimensional spatial position coordinates, a leakage anomaly type identification, and a leakage quantification level calculated based on the signal strength.

7. The water distributor water supply control system for an airport of claim 1, wherein, The full life cycle health diagnosis unit is also used to determine the corrosion rate of the pipe network inner wall based on the electrochemical impedance spectroscopy sensing data. The corrosion rate is compared with a preset corrosion rate threshold value, and when the corrosion rate exceeds the threshold value, a compensation current value or a medicament dosing dose is calculated according to the exceeding value, to generate a corresponding current intensity control signal or a medicament dosing signal.

8. The water distributor water supply control system for an airport according to claim 6, characterized by, The full life cycle health diagnosis unit also includes a data interface module for sending the generated maintenance instruction to the airport automatic operation and maintenance work order system.

9. The water distributor water supply control system for an airport of claim 1, wherein, The system also includes a model self-optimization unit for comparing the measured data of the runway temperature and system energy consumption with the predicted values of the prediction decision unit after the heat supply event ends, and iteratively correcting the related parameters of the digital twin model by machine learning algorithm according to the deviation.

10. The water distributor water supply control system for an airport of claim 1, wherein, The reserve mode instruction also includes an instruction for controlling the start-stop timing and output power of the external main heat source, which is optimized and generated according to the real-time energy storage state of the phase change energy storage module and the predicted long-term total heat load.

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