A controllable helicopter turbine cooling air circulation system
By acquiring real-time data and predicting icing patterns, the problem of icing in turbo cooler pipes was solved, improving system reliability and fuel economy, and extending component life.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHAANXI CHANG LING SPECIAL EQUIP
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-14
Smart Images
Figure CN122106698B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of data processing, and specifically relates to a controllable helicopter turbine cooling air circulation system. Background Technology
[0002] As helicopter applications expand across all sectors and power system performance demands continue to rise, the traditional, rudimentary, and basic turbine cooling air regulation method has become a key bottleneck restricting overall performance improvement. The core background of this approach lies in the fact that, while ensuring safety under extreme operating conditions, the traditional excessive bleed air mode leads to poor engine fuel economy, limited power output, and an inability to adapt to complex mission requirements such as high altitude and high maneuverability, while also exacerbating component thermal fatigue. Therefore, an intelligent and controllable cooling regulation method has emerged. By deeply integrating model predictive control with a health management system, it achieves a paradigm shift from "passive supply" to "precise on-demand regulation" of cooling air. This significantly improves fuel efficiency and available power, extends the lifespan of hot-end components, and enhances adaptability and safety across the entire mission envelope, ultimately providing crucial technical support for improving helicopter range, maneuverability, and life-cycle economics.
[0003] However, during helicopter operation, liquid water will be released from the air after the turbine cooler expands and cools. As the cooling air conditioning system operates, the water accumulated in the pipes may cause icing and blockage, leading to system failure. Summary of the Invention
[0004] To address the problem that water in the pipes of a helicopter turbine cooler may freeze during operation, leading to reduced turbine cooler power and system failure, this invention proposes a controllable helicopter turbine cooling air circulation system.
[0005] To achieve the above objectives, the present invention provides the following technical solution:
[0006] Data acquisition module: acquires the airflow temperature data sequence, total gas pressure data sequence, relative humidity data sequence, and saturated water vapor pressure corresponding to the airflow temperature in the system's flow channel at each acquisition time.
[0007] Moisture content calculation module in the flow channel: Based on the airflow temperature, relative humidity, total pressure, and saturated water vapor pressure corresponding to the airflow temperature in the flow channel at each sampling time, the moisture content in the flow channel of the system at each sampling time is obtained.
[0008] Temperature prediction module: Divides the flow channel in the system into multiple parts to obtain multiple hot melt nodes; obtains the surface heat transfer coefficient, the surface heat transfer area of each hot melt node in the system, the specific heat capacity of the material that makes up each hot melt node in the system, the actual temperature and weight of each hot melt node in the system at each acquisition time; and combines the difference between the temperature of the gas in the flow channel in the system and the actual temperature of each hot melt node in the system at each acquisition time to obtain the predicted temperature of each hot melt node in the system at each acquisition time.
[0009] Ice-forming prediction and processing module: Sets the water droplet freezing temperature, and combines it with the system's first freezing point at each data collection time. The predicted temperature of the first hot melt node, the first Moisture content in the flow channel of the system at each sampling time, the first sampling time... By measuring the saturation temperature corresponding to the vapor partial pressure at each sampling time, the probability of icing at each hot melt node in the system at each sampling time can be obtained, thereby identifying the hot melt nodes that are likely to ic, and taking preventative measures against them.
[0010] Furthermore, the specific calculation formula for obtaining the moisture content in the flow channel of the system at each sampling time is as follows:
[0011]
[0012] In the formula, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The relative humidity of the gas in the flow channel of the system at each sampling time. Indicates the first The saturated water vapor pressure corresponding to the temperature inside the flow channel of the system at each sampling time. Indicates the first Total gas pressure in the flow channel of the system at each acquisition time.
[0013] Furthermore, the specific steps for obtaining the predicted temperature of each hot melt node in the system at each acquisition time are as follows:
[0014] Based on the surface heat transfer coefficient, the surface heat transfer area of each hot-melt node, and the difference between the temperature of the gas in the flow channel of the system and the actual temperature of each hot-melt node in the system at each sampling time, the influence of the gas in the flow channel of the system on the wall temperature of each hot-melt node in the system at each sampling time is obtained.
[0015] Based on the influence of the gas in the flow channel on the wall temperature of each hot-melt node in the system at each acquisition time, the weight of each hot-melt node in the system, the specific heat capacity of the material that makes up each hot-melt node in the system, and the actual temperature of each hot-melt node in the system at each acquisition time, the predicted temperature of each hot-melt node in the system at each acquisition time is obtained.
[0016] Furthermore, the specific calculation formula for the influence of the gas in the flow channel on the wall temperature of each fusion node in the system at each acquisition time is as follows:
[0017]
[0018] In the formula, Indicates the first At the sampling time, the gas in the flow channel of the system affects the first... The influence of the wall temperature of each hot-melt joint. Indicates the first The system's first acquisition time at the [number]th acquisition time The actual temperature of each hot melt node Indicates the surface heat transfer coefficient. Represents the first in the system The surface heat transfer area of each hot melt node Indicates the first Temperature of the gas in the flow channel of the system at each sampling time.
[0019] Furthermore, the specific calculation formula for obtaining the predicted temperature of each hot-melt node in the system at each acquisition time is as follows:
[0020]
[0021] In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first At the sampling time, the gas in the flow channel of the system affects the first... The influence of the wall temperature of each hot-melt joint. Indicates the first The system's first acquisition time at the [number]th acquisition time The actual temperature of each hot melt node express The ratio of the sum of all acquisition intervals divided by the unit time. Represents the first in the system The weight of each hot-melt joint, Represents the first in the system The specific heat capacity of the material at each hot-melt node.
[0022] Furthermore, the specific steps for obtaining the probability of icing occurring at each thermal fusion node in the system at each acquisition time are as follows:
[0023] Based on the predicted temperature of each hot melt node in the system at each acquisition time, the moisture content in the flow channel of the system at each acquisition time, and the saturation temperature corresponding to the vapor partial pressure at each acquisition time, several initial possibilities for icing to occur at each hot melt node in the system at each acquisition time are obtained.
[0024] Based on all the initial possibilities of icing occurring at each thermal fusion node in the system at each acquisition time, the probability of icing occurring at each thermal fusion node in the system at each acquisition time is obtained.
[0025] Furthermore, the specific calculation formula for obtaining the initial possibilities of icing at each thermal fusion node in the system at each acquisition time is as follows:
[0026]
[0027] In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time The initial probability of icing occurring at each hot melt node. This indicates the freezing temperature of water droplets, which is usually set to 0, but can be set to -2℃ if supercooling is considered. Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The saturation temperature corresponding to the vapor partial pressure at each sampling time. It is an exponential function with the natural constant as its base. This represents the sigmoid function.
[0028] Furthermore, the specific steps for obtaining the probability of icing occurring at each thermal fusion node in the system at each acquisition time are as follows:
[0029] The first The system's first acquisition time at the [number]th acquisition time The maximum value among all initial possibilities of icing occurring at the th molten node is denoted as the i-th _____. The system's first acquisition time at the [number]th acquisition time There is a possibility of icing at the hot melt joint.
[0030] Furthermore, the specific steps for obtaining the hot-melt node that will freeze in advance are as follows:
[0031] Preset icing probability threshold If the first The system's first acquisition time at the [number]th acquisition time The probability of icing occurring at each hot melt node is greater than [missing information]. Then the first The system's first acquisition time at the [number]th acquisition time Ice will form at the hot melt joint.
[0032] Furthermore, the specific steps for pre-treating the hot-melt nodes that are prone to freezing are as follows:
[0033] When the analysis revealed the first [unit / item] in the helicopter turbine cooling air circulation system The system's first acquisition time at the [number]th acquisition time Ice will form at the first fusion node, then at the second... During each data collection period, commands are sent to the controllable water discharge and anti-clogging execution module to actively perform operations such as drainage.
[0034] The controllable helicopter turbine cooling air circulation system provided by this invention has the following beneficial effects: By integrating intelligent sensing and active control, this invention systematically solves the core problems in helicopter turbine cooling air circulation. The constructed "real-time sensing-state prediction-active execution" closed loop elevates moisture management from a passive response to a predictable and controllable process. By accurately calculating the moisture content and predicting the icing risk at each node, the system can trigger drainage and anti-blocking operations in advance, completely eliminating the risks of decreased heat exchange efficiency, pipe icing, and "water blowing" caused by moisture accumulation. This not only significantly improves the system's reliability and adaptability to all missions, but also optimizes engine fuel economy and the lifespan of hot-end components by avoiding unnecessary bleed air and energy loss, achieving a comprehensive improvement in safety, efficiency, and maintenance costs. Attached Figure Description
[0035] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 This is a flowchart of a controllable helicopter turbine cooling air circulation system according to an embodiment of the present invention. Detailed Implementation
[0037] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.
[0038] Example 1:
[0039] This invention provides a controllable helicopter turbine cooling air circulation system, specifically as follows: Figure 1 As shown, it includes:
[0040] Step S001: Obtain the airflow temperature data sequence, total gas pressure data sequence, relative gas humidity data sequence, and saturated water vapor pressure corresponding to the airflow temperature in the system's flow channel at each acquisition time.
[0041] Specifically, sensors within the helicopter's turbine cooling air circulation system are used to collect data at intervals of [missing information]. Within seconds, the system obtains the airflow temperature data sequence, total gas pressure data sequence, and relative humidity data sequence within the flow channel of the helicopter turbine cooling air circulation system. Furthermore, during each data acquisition, the system obtains the saturated water vapor pressure corresponding to the temperature at that acquisition time, thus generating a saturated water vapor pressure data sequence.
[0042] Thus, the data sequences of airflow temperature, total gas pressure, relative humidity, and saturated water vapor pressure within the flow channel of the helicopter turbine cooling air circulation system were obtained.
[0043] Step S002: Based on the airflow temperature, relative humidity, total pressure, and saturated water vapor pressure corresponding to the airflow temperature in the system at each sampling time, obtain the moisture content in the system's flow channel at each sampling time.
[0044] It should be noted that when the turbocooler expands and cools, liquid water will precipitate from the air. With the operation of the cooling air conditioning system, this moisture reduces subsequent heat exchange efficiency, and water accumulating in the pipes may freeze, causing blockage in the system's flow channels and leading to system failure. Therefore, this invention analyzes data from various sensors in the system to calculate the moisture content in the flow channels at the current temperature. Then, combining this with the relevant parameters of each heat capacity node, it predicts the temperature performance of each heat capacity node in the short time domain, and uses this as a basis to analyze the probability of icing at each heat capacity node. Subsequently, when the probability of icing at the heat fusion node is high, proactive drainage operations are performed to prevent icing blockage in the flow channels, improving the overall reliability, efficiency, and ergonomics of the system.
[0045] It should be further noted that the moisture content in a turbine system can represent the weight concentration of condensable water in an airflow at a given temperature. Furthermore, the higher the moisture content in the turbine system, the greater the likelihood of blockage in the flow channels. Therefore, when calculating the probability of icing at each heat capacity node, the moisture content within the flow channels of the system is calculated first.
[0046] It should be further explained that the moisture content is calculated by using the saturated water vapor pressure and real-time airflow temperature data, real-time total gas pressure, and relative humidity in the flow channel of the turbine system. The formula for obtaining the gas constants of water vapor and dry air is inverted to obtain the moisture content. Since the temperature in the flow channel of the system changes in real time, the saturated water vapor pressure in the flow channel of the system also changes in real time. The saturated water vapor pressure in the flow channel of the system is required when calculating the moisture content. Therefore, the saturated water vapor pressure in the flow channel of the system is obtained in real time when calculating the moisture content.
[0047] Specifically, to obtain the first The specific formula for calculating the moisture content in the flow channel of the system at each sampling time is as follows:
[0048]
[0049] In the formula, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The relative humidity of the gas in the flow channel of the system at each sampling time. Indicates the first The saturated water vapor pressure corresponding to the temperature inside the flow channel of the system at each sampling time. Indicates the first The total gas pressure in the system's flow channel at each sampling time, 0.62198 is the ratio of the gas constant of water vapor to that of dry air.
[0050] It should be noted that, Indicates the first Water vapor partial pressure in the airflow within the system's flow channel at each sampling time. It indicates the first By inverting the formulas for obtaining the gas constants of water vapor and dry air at different sampling times, the non-water vapor partial pressure in the airflow within the system's channel can be obtained. .
[0051] Thus, the moisture content in the flow channel of the system at each time point is obtained.
[0052] Step S003: Divide the flow channel in the system into multiple parts to obtain multiple hot melt nodes; obtain the surface heat transfer coefficient, the surface heat transfer area of each hot melt node in the system, the specific heat capacity of the material constituting each hot melt node in the system, and the actual temperature and weight of each hot melt node in the system at each acquisition time; combine the difference between the temperature of the gas in the flow channel in the system and the actual temperature of each hot melt node in the system at each acquisition time to obtain the predicted temperature of each hot melt node in the system at each acquisition time.
[0053] It should be noted that, due to the relatively long length of the flow channel in the system, when determining the likelihood of icing at each location within the flow channel, the flow channel is first divided into multiple sections, resulting in multiple heat-fusion nodes. Each heat-fusion node is a portion of the flow channel.
[0054] It should be further noted that because the wall temperature of the fusion node is lower than the freezing temperature of water droplets, and simultaneously lower than the saturation temperature corresponding to the vapor partial pressure in the flow channel, icing is prone to occur at the heat capacity nodes in the flow channel. That is, before icing occurs at each fusion node, the wall temperature within that fusion node must first meet certain conditions before icing will occur. Therefore, when predicting the future icing situation at each point in the flow channel, it is necessary to first predict the temperature within the fusion node.
[0055] It should be further noted that when predicting temperature changes within the hot-melt joint, the temperature of the gas within the flow channel affects the wall temperature of the hot-melt joint. Therefore, the prediction process first obtains the difference between the gas flow temperature within the system flow channel and the wall temperature of the hot-melt joint. Then, by combining the heat transfer area and surface heat transfer coefficient of the hot-melt joint surface, the influence of the gas temperature within the flow channel on the wall temperature of the hot-melt joint is obtained. Finally, by combining the material weight, specific heat capacity, and initial wall temperature at each hot-melt joint, the temperature prediction is completed.
[0056] Specifically, the flow channel in the system is divided into multiple parts to obtain multiple hot melt nodes. Dividing the flow channel into multiple parts is a well-known technique and will not be elaborated upon in this embodiment.
[0057] Furthermore, using sensors within the system, the actual temperature of each heat-fusion node in the system is acquired at each acquisition time. The surface heat transfer coefficient, the surface heat transfer area of each heat-fusion node in the system, and the composition of the system are also obtained. The specific heat capacity of the material of the first hot-melt node, and the first in the system The weight of each hot melt node.
[0058] Furthermore, obtain the first The system's first acquisition time at the [number]th acquisition time The specific formula for calculating the predicted temperature of each hot melt node is as follows:
[0059]
[0060]
[0061] In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first At the sampling time, the gas in the flow channel of the system affects the first... The influence of the wall temperature of each hot-melt joint. Indicates the first The system's first acquisition time at the [number]th acquisition time The actual temperature of each hot melt node Indicates the surface heat transfer coefficient. Represents the first in the system The surface heat transfer area of each hot melt node Indicates the first Temperature of the gas in the flow channel of the system at each sampling time. express The ratio of the sum of all acquisition intervals divided by the unit time. Represents the first in the system The weight of each hot-melt joint, Represents the first in the system The specific heat capacity of the material at each hot-melt node.
[0062] It should be noted that, Indicates the first At the first sampling time, the gas in the flow channel of the system and the first The difference in wall temperature at each hot-melt node represents the influence of the gas temperature within the flow channel on the wall temperature; through The effect of the gas temperature inside the flow channel on the wall temperature per unit time was obtained. The larger the value, the more significant the first... The weight of the first hot-melt joint is relatively large, i.e., the first... At each hot melt joint, more heat is required to raise the temperature by one degree. This indicates the final effect of the gas within the flow channel on the wall temperature in the system, through... To complete the temperature prediction.
[0063] Thus, the system's first acquisition time at each acquisition time is obtained. Predicted temperature of each hot melt node.
[0064] Step S004: Set the water droplet freezing temperature, combined with the system's [number]th [item] at each collection time. The predicted temperature of the first hot melt node, the first Moisture content in the flow channel of the system at each sampling time, the first sampling time... By measuring the saturation temperature corresponding to the vapor partial pressure at each sampling time, the probability of icing at each hot melt node in the system at each sampling time can be obtained, thereby identifying the hot melt nodes that are likely to ic, and taking preventative measures against them.
[0065] It should be noted that, after obtaining the system's first data acquisition time, When predicting icing conditions inside the pipe by considering the predicted temperatures of each heat-capacity node and the moisture content of the gas in the system flow channel, it is important to note that icing is more likely to occur at heat-capacity nodes when the wall temperature is below the freezing temperature of water droplets and also below the saturation temperature corresponding to the vapor partial pressure in the flow channel. Therefore, by combining the wall temperature at each heat-capacity node in the system flow channel with the calculated saturation temperature corresponding to the vapor partial pressure, the probability of icing occurring at the x-th heat-capacity node after a time interval ∆t is predicted.
[0066] Specifically, to obtain the first The system's first acquisition time at the [number]th acquisition time The specific formula for calculating the initial probability of icing at each hot melt node is as follows:
[0067]
[0068] In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time The initial probability of icing occurring at each hot melt node. This indicates the freezing temperature of water droplets, which is usually set to 0, but can be set to -2℃ if supercooling is considered. Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The saturation temperature corresponding to the vapor partial pressure at each sampling time. As an exponential function with the natural constant as its base, this embodiment uses it to represent an inverse proportional relationship; This represents the sigmoid function, which is used in this embodiment for normalization.
[0069] It should be noted that, This represents the difference between the wall temperature and the freezing temperature of the water droplet. The greater the difference and the lower the wall temperature is compared to the freezing temperature, the greater the likelihood that the water droplet will condense into ice at that point. Simultaneously, the relationship between the wall temperature and the saturation temperature corresponding to the vapor partial pressure is considered. A higher temperature indicates that the water vapor in the airflow has reached saturation. If the wall temperature of the synchronous heat capacity node is lower than the critical temperature for water vapor to condense into liquid water, it means that the water vapor will condense and freeze rapidly on the cooler wall surface, meaning the probability of freezing is greater. Furthermore, in calculations... At that time, because there was no first The predicted moisture content in the flow channel of the system at each sampling time, therefore, in the calculation At that time, with To be the first The predicted moisture content in the flow channel of the system at a given sampling time. Since there are likely to be multiple possibilities for icing at a single fusion node in the system at a given sampling time, the maximum value among all the initial possibilities for icing at a single fusion node in the system at a given sampling time is denoted as the probability of icing at that fusion node in the system at that sampling time.
[0070] Thus, the probability of icing occurring at each thermal fusion node in the system at each acquisition time is obtained.
[0071] Furthermore, a preset icing probability threshold is defined. If the first The system's first acquisition time at the [number]th acquisition time The probability of icing occurring at each hot melt node is greater than [missing information]. This indicates that the first The system's first acquisition time at the [number]th acquisition time Ice formation can occur at each hot-melt node. The preset probability threshold in this embodiment... This example is used to illustrate the concept; other values can be set in other implementations.
[0072] Furthermore, when the analysis revealed the first... The system's first acquisition time at the [number]th acquisition time Ice will form at the first fusion node, then at the second... During the data acquisition period, commands are sent to the controllable water discharge and anti-clogging execution module to actively perform drainage and other operations. This improves the system's reliability and adaptability to all tasks, and optimizes engine fuel economy and the lifespan of hot-end components by avoiding unnecessary bleed air and energy loss, achieving a comprehensive improvement in safety, efficiency, and maintenance costs.
[0073] This concludes the embodiment.
Claims
1. A controllable helicopter turbine cooling air circulation system, characterized in that, include: Data acquisition module: acquires the airflow temperature data sequence, total gas pressure data sequence, relative humidity data sequence, and saturated water vapor pressure corresponding to the airflow temperature in the system's flow channel at each acquisition time. Moisture content calculation module in the flow channel: Based on the airflow temperature, relative humidity, total pressure, and saturated water vapor pressure corresponding to the airflow temperature in the flow channel at each sampling time, the moisture content in the flow channel of the system at each sampling time is obtained. Temperature prediction module: Divides the flow channel in the system into multiple parts to obtain multiple hot melt nodes; obtains the surface heat transfer coefficient, the surface heat transfer area of each hot melt node in the system, the specific heat capacity of the material that makes up each hot melt node in the system, the actual temperature and weight of each hot melt node in the system at each acquisition time; and combines the difference between the temperature of the gas in the flow channel in the system and the actual temperature of each hot melt node in the system at each acquisition time to obtain the predicted temperature of each hot melt node in the system at each acquisition time. Ice-forming prediction and processing module: Sets the water droplet freezing temperature, and combines it with the system's first freezing point at each data collection time. The predicted temperature of the first hot melt node, the first Moisture content in the flow channel of the system at each sampling time, the first sampling time... By measuring the saturation temperature corresponding to the vapor partial pressure at each sampling time, the probability of icing at each hot melt node in the system at each sampling time can be obtained, thereby identifying the hot melt nodes that are likely to ic, and taking preventative measures against them.
2. The controllable helicopter turbine cooling air circulation system according to claim 1, characterized in that, The specific calculation formula for obtaining the moisture content in the flow channel of the system at each sampling time is as follows: In the formula, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The relative humidity of the gas in the flow channel of the system at each sampling time. Indicates the first The saturated water vapor pressure corresponding to the temperature inside the flow channel of the system at each sampling time. Indicates the first Total gas pressure in the flow channel of the system at each acquisition time.
3. The controllable helicopter turbine cooling air circulation system according to claim 1, characterized in that, The specific steps for obtaining the predicted temperature of each hot melt node in the system at each acquisition time are as follows: Based on the surface heat transfer coefficient, the surface heat transfer area of each hot-melt node, and the difference between the temperature of the gas in the flow channel of the system and the actual temperature of each hot-melt node in the system at each sampling time, the influence of the gas in the flow channel of the system on the wall temperature of each hot-melt node in the system at each sampling time is obtained. Based on the influence of the gas in the flow channel on the wall temperature of each hot-melt node in the system at each acquisition time, the weight of each hot-melt node in the system, the specific heat capacity of the material that makes up each hot-melt node in the system, and the actual temperature of each hot-melt node in the system at each acquisition time, the predicted temperature of each hot-melt node in the system at each acquisition time is obtained.
4. A controllable helicopter turbine cooling air circulation system according to claim 3, characterized in that, The specific calculation formula for the influence of the gas in the flow channel on the wall temperature of each hot-melt node in the system at each acquisition time is as follows: In the formula, Indicates the first At the sampling time, the gas in the flow channel of the system affects the first... The influence of the wall temperature of each hot-melt joint. Indicates the first The system's first acquisition time at the [number]th acquisition time The actual temperature of each hot melt node Indicates the surface heat transfer coefficient. Represents the first in the system The surface heat transfer area of each hot melt node Indicates the first Temperature of the gas in the flow channel of the system at each sampling time.
5. A controllable helicopter turbine cooling air circulation system according to claim 3, characterized in that, The specific calculation formula for obtaining the predicted temperature of each hot melt node in the system at each acquisition time is as follows: In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first At the sampling time, the gas in the flow channel of the system affects the first... The influence of the wall temperature of each hot-melt joint. Indicates the first The system's first acquisition time at the [number]th acquisition time The actual temperature of each hot melt node express The ratio of the sum of all acquisition intervals divided by the unit time. Represents the first in the system The weight of each hot-melt joint, Represents the first in the system The specific heat capacity of the material at each hot-melt node.
6. A controllable helicopter turbine cooling air circulation system according to claim 1, characterized in that, The specific steps for obtaining the probability of icing at each hot-melt node in the system at each acquisition time are as follows: Based on the predicted temperature of each hot melt node in the system at each acquisition time, the moisture content in the flow channel of the system at each acquisition time, and the saturation temperature corresponding to the vapor partial pressure at each acquisition time, several initial possibilities for icing to occur at each hot melt node in the system at each acquisition time are obtained. Based on all the initial possibilities of icing occurring at each thermal fusion node in the system at each acquisition time, the probability of icing occurring at each thermal fusion node in the system at each acquisition time is obtained.
7. A controllable helicopter turbine cooling air circulation system according to claim 6, characterized in that, The specific calculation formula for obtaining the initial possibilities of icing at each thermal melting node in the system at each acquisition time is as follows: In the formula, Indicates the first The system's first acquisition time at the [number]th acquisition time The initial probability of icing occurring at each hot melt node. This indicates the freezing temperature of water droplets, which is usually set to 0, but can be set to -2℃ if supercooling is considered. Indicates the first The system's first acquisition time at the [number]th acquisition time Predicted temperature of each hot melt node, Indicates the first Moisture content in the flow channel of the system at each sampling time. Indicates the first The saturation temperature corresponding to the vapor partial pressure at each sampling time. It is an exponential function with the natural constant as its base. This represents the sigmoid function.
8. A controllable helicopter turbine cooling air circulation system according to claim 6, characterized in that, The specific steps for obtaining the probability of icing at each hot-melt node in the system at each acquisition time are as follows: The first The system's first acquisition time at the [number]th acquisition time The maximum value among all initial possibilities of icing occurring at the th molten node is denoted as the i-th _____. The system's first acquisition time at the [number]th acquisition time There is a possibility of icing at the hot melt joint.
9. A controllable helicopter turbine cooling air circulation system according to claim 1, characterized in that, The specific steps for obtaining the hot-melt node that will freeze in advance are as follows: Preset icing probability threshold If the first The system's first acquisition time at the [number]th acquisition time The probability of icing occurring at each hot melt node is greater than [missing information]. Then the first The system's first acquisition time at the [number]th acquisition time Ice will form at the hot melt joint.
10. A controllable helicopter turbine cooling air circulation system according to claim 1, characterized in that, The specific steps for pre-treating the hot-melt nodes that are prone to freezing are as follows: When the analysis revealed the first [unit / item] in the helicopter turbine cooling air circulation system The system's first acquisition time at the [number]th acquisition time Ice will form at the first fusion node, then at the second... During each data collection period, commands are sent to the controllable water discharge and anti-clogging execution module to actively perform operations such as drainage.