A hot air balloon flight altitude intelligent control method and system

Abstract

This application relates to the technical field of hot air balloon control and discloses a method and system for intelligently controlling the flight altitude of a hot air balloon. The method comprises: a sensor unit in the hot air balloon collects internal parameters and environmental data; during takeoff, a control unit simultaneously activates a flame heater and a resistance heater, and removes the flame heater when takeoff conditions are met; after each flight, the internal parameters and environmental data, as well as the movement postures of the resistance heater and the action unit, are stored as historical flight data; the historical flight data is analyzed to generate a control strategy, which includes temperature adjustment strategies for multiple resistance heaters and movement adjustment strategies for the action units; the control strategy is stored in the control unit, and during the flight of the hot air balloon, the control unit uses the corresponding control strategy to adjust the flight altitude based on a set target altitude, current internal parameters, and environmental data. This invention enables precise and intelligent control of the flight altitude of a hot air balloon.

Description

Technical Field

[0001] The present application relates to the field of hot air balloon control technology, and in particular to a method and system for intelligently controlling the flight altitude of a hot air balloon. Background Art

[0002] The altitude control capability of a hot air balloon directly affects flight safety, mission effectiveness, and energy economy. For unmanned hot air balloons, automatic feedback control is currently the main method. For example, Chinese patent document No. CN114115010A discloses a flight altitude control system for an unmanned hot air balloon. The system obtains the current longitude, latitude, altitude, and speed data of the hot air balloon and sends the data to a ground control station. The ground control station compares the altitude command sent with the current altitude of the unmanned hot air balloon and controls the burner combustion time based on the comparison result, thereby controlling the flight altitude of the unmanned hot air balloon. For another example, Chinese patent document No. CN106516068A discloses an intelligent balloon. The application controls the valves and ballast device of the balloon according to the flight mode, environmental parameters, and flight status information, thereby realizing intelligent lifting and lowering control of the balloon.

[0003] The current technical solution is to adjust the temperature of the hot air balloon by controlling the size of the flame, thereby indirectly controlling the height of the hot air balloon. Therefore, the temperature control accuracy is low, resulting in poor height control effect of the hot air balloon. Summary of the Invention

[0004] In order to solve the problems raised in the above background technology, the present application provides a hot air balloon flight altitude intelligent control method and system.

[0005] In order to achieve the above-mentioned object of the invention, the present invention proposes a hot air balloon flight altitude intelligent control method and system, comprising:

[0006] The sensor unit in the hot air balloon collects internal parameters and environmental data, wherein the internal parameters include the internal temperature and internal pressure of the hot air balloon itself;

[0007] When the hot air balloon takes off, the control unit starts the flame heater and the resistance wire heater at the same time, and removes the flame heater when the take-off conditions are met;

[0008] After each flight is completed, the server unit stores the internal parameters and the environmental data, as well as the action postures of the resistance wire heater and the action unit as historical flight data;

[0009] When the historical flight data reaches a first amount, the server unit analyzes the historical flight data to generate a control strategy, the control strategy including a plurality of temperature adjustment strategies for the resistance wire heater and a motion adjustment strategy for the motion unit, the temperature adjustment strategy being used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy being used to adjust the motion posture of the motion unit;

[0010] The server unit uploads the control strategy to the control unit. During the hot air balloon flight, the control unit adjusts the flight altitude using the corresponding control strategy based on the set target altitude, the current internal parameters and the environmental data.

[0011] Furthermore, the environmental data includes wind speed data, altitude data, geographic location data and external temperature data, the action unit includes a fan and a rotor structure, and the action posture includes a rotor rotation speed and a rotor rotation angle.

[0012] Furthermore, analyzing the historical flight data includes the following steps:

[0013] constructing an altitude change sequence based on the altitude data in the historical flight data, locating a time period in the altitude change sequence during which the altitude changes continuously as a first time period, obtaining an operation effective time, defining the operation effective time before and during the first time period as a second time period, constructing the internal parameters and the environmental data within the second time period into a plurality of basic sequences, and constructing the temperature value of the resistance wire heater and the action posture of the action unit within the second time period into an action variable sequence;

[0014] performing discretization processing on the basic sequence and the action variable sequence to obtain a corresponding first discrete sequence and a second discrete sequence, respectively; performing a first clustering on the first discrete sequence based on the lowest height and the highest height within the second time period; and performing a second clustering on the results of the first clustering based on the similarity between the first discrete sequences to obtain a plurality of clusters;

[0015] The second discrete sequence in a cluster is obtained, a frequency ratio of occurrence of the second discrete sequence is calculated, and the control strategy is generated based on the second discrete sequence with the largest frequency ratio.

[0016] Furthermore, using the control strategy to adjust the flight altitude of the hot air balloon includes the following steps:

[0017] The sensor unit obtains the average value of the internal parameters and the environmental data within the detection time period, determines the target altitude to be adjusted, matches the corresponding control strategy based on the average value and the target altitude and uses it as the target strategy, obtains the current temperature of the resistance wire heater, and the target temperature to which the resistance wire heater is to be adjusted in the target strategy, the control unit calculates the difference between the current temperature and the target temperature, performs multi-stage adjustment on the temperature of the resistance wire heater based on the difference, and adjusts the current action of the action unit to the action posture in the target strategy to achieve adjustment of the hot air balloon's flight altitude.

[0018] Furthermore, performing multi-stage adjustment on the temperature of the resistance wire heater includes the following steps:

[0019] The control strategy includes an ideal height change curve, sets a standard value, divides the difference into multiple adjustment stages based on the standard value, obtains the stage curve corresponding to each adjustment stage in the ideal height change curve, obtains the first endpoint temperature of the first adjustment stage, and after the real-time temperature of the resistance wire heater reaches the first endpoint temperature, draws the actual height change curve of the temperature adjustment process. If the deviation between the actual height change curve and the first stage curve is greater than the standard threshold, the control strategy is re-matched based on the current internal parameters and the environmental data. If the deviation is less than or equal to the standard threshold, the adjustment is continued according to the second endpoint temperature of the second adjustment stage until the target height is reached.

[0020] Furthermore, generating the height change curve of the control strategy includes the following steps:

[0021] The height change sequence corresponding to each of the second discrete sequences in the same group is used as an analysis sequence, all the analysis sequences in the same group are comprehensively analyzed to generate a height change function, and the ideal height change curve corresponding to the control strategy is generated based on the height change function.

[0022] Furthermore, generating the ideal height change function includes the following steps:

[0023] The ideal height change function includes a first function and a second function. An average change sequence of flight height is generated based on the analysis sequence, and the average change sequence is divided into a uniform change stage and a non-uniform change stage. The part of each analysis sequence located in the uniform change stage is defined as a first sequence, and the part located in the non-uniform change stage is defined as a second sequence. The first function is obtained by fitting the first sequence based on a linear function, and the second function is obtained by fitting the second sequence based on a nonlinear function. A first curve is drawn based on the first function, and a second curve is drawn based on the second function. The first curve and the second curve are used as the ideal height change curves.

[0024] Furthermore, dividing the average change sequence into the uniform change stage and the non-uniform change stage comprises the following steps:

[0025] A Burg coefficient sequence of the average change sequence is calculated, and the average change sequence is divided into the uniform change stage and the non-uniform change stage based on the Burg coefficient sequence.

[0026] Furthermore, when the control unit adjusts the flight altitude based on the control strategy, if the hot air balloon is not adjusted to the target altitude within a preset time period, a manual adjustment reminder is generated.

[0027] The present application also provides a hot air balloon flight altitude intelligent control system for implementing the hot air balloon flight altitude intelligent control method described above, the system comprising:

[0028] a sensor unit for collecting internal parameters and environmental data, wherein the internal parameters include the internal temperature and internal pressure of the hot air balloon itself;

[0029] a control unit, wherein when the hot air balloon takes off, the control unit simultaneously activates the flame heater and the resistance wire heater, and when the take-off conditions are met, removes the flame heater; during the hot air balloon flight, the control unit adjusts the flight altitude using the corresponding control strategy based on a set target altitude, the current internal parameters, and the environmental data;

[0030] The server unit stores the internal parameters and the environmental data, as well as the motion postures of the resistance wire heater and the motion unit as historical flight data after each flight is completed. When the historical flight data reaches a first quantity, the server unit analyzes the historical flight data to generate a control strategy, wherein the control strategy includes a plurality of temperature adjustment strategies for the resistance wire heater and motion adjustment strategies for the motion unit. The temperature adjustment strategy is used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy is used to adjust the motion posture of the motion unit. The server unit uploads the control strategy to the control unit.

[0031] The present invention collects the internal parameters and environmental data of the hot air balloon and stores them as historical flight data. When a certain number is reached, it analyzes and generates a control strategy including a temperature adjustment strategy for the resistance wire heater and a motion posture of the action unit, and stores the control strategy in a control unit. During the subsequent flight of the hot air balloon, relevant personnel only need to set the target altitude of the flight, and the control unit can automatically adjust the flight altitude according to the corresponding strategy based on the current internal parameters and external environment, thereby greatly improving the convenience of operation.

[0032] During flight, this invention replaces traditional flame heating with a resistance wire heater. This system, combined with multi-source sensors that fuse environmental parameters in real time and coordinate control with motion units, enables high-precision adjustment of the hot air balloon's altitude. Furthermore, dynamic rotor compensation for wind disturbances further enhances altitude control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of a hot air balloon flight altitude intelligent control method for this application;

[0034] Figure 2 This is a schematic diagram of the hot air balloon monitoring interface for this application;

[0035] Figure 3 This is a segmented schematic diagram of the ideal height change curve for this application;

[0036] Figure 4 This is a structural diagram of a hot air balloon flight altitude intelligent control system for this application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] It is understood that the terms "first," "second," etc., used herein may be used to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script without departing from the scope of this application.

[0039] like Figure 1 As shown, a hot air balloon flight altitude intelligent control method includes:

[0040] S1: The sensor unit in the hot air balloon collects internal parameters and environmental data. The internal parameters include the internal temperature and internal pressure of the hot air balloon itself.

[0041] In this embodiment, the environmental data includes wind speed data, altitude data, geographic location data and external temperature data, the action unit includes a fan and a rotor structure, and the action posture includes a rotor rotation speed and a rotor rotation angle.

[0042] S2: When the hot air balloon takes off, the control unit starts the flame heater and the resistance wire heater at the same time, and removes the flame heater when the take-off conditions are met.

[0043] Specifically, the sensor unit includes a temperature sensor, a barometric altimeter, and a pressure sensor, etc. The wind speed data includes the wind speed magnitude and direction, the altitude data includes the flight altitude of the hot air balloon, the geographic location data includes the longitude and latitude, and the external temperature data is the ambient temperature at the altitude of the hot air balloon. The hot air balloon in this embodiment is provided with a flame heater and a resistance wire heater. When the hot air balloon takes off, the flame heater is first used to quickly heat up the hot air balloon, and the resistance wire heater is preheated at the same time. A counterweight is provided inside the hot air balloon. When the hot air balloon is able to drive the counterweight to rise, the take-off conditions are met. At this time, the counterweight and the flame heater are removed, and the resistance wire heater is used to maintain the temperature inside the hot air balloon, so that the hot air balloon rises to a certain altitude and remains in flight. When the hot air balloon needs to land, its altitude is lowered by reducing the temperature of the resistance wire heater.

[0044] The hot air balloon is also equipped with a motion unit, specifically a rotor structure, which is located on both sides of the balloon. By controlling the rotation and orientation of the rotor structure, the balloon can assist in adjusting its forward direction and altitude. The hot air balloon is also equipped with a fan structure, which is used to supply or exhaust air to achieve the balloon's ascent and retrieval after landing.

[0045] S3: After each flight is completed, the server unit stores the internal parameters and environmental data, as well as the action postures of the resistance wire heater and the action unit as historical flight data.

[0046] S4: When the historical flight data reaches a first quantity, the server unit analyzes the historical flight data to generate a control strategy, which includes a temperature adjustment strategy for multiple resistance wire heaters and a motion adjustment strategy for the motion unit. The temperature adjustment strategy is used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy is used to adjust the motion posture of the motion unit.

[0047] When a hot air balloon is flying, historical flight data is first collected through simulation or actual flight. When the hot air balloon is flying, the flight data is transmitted to the central server in real time through satellite communication or other communication methods, so that ground personnel can see the current flight status of the hot air balloon in real time. The specific monitoring interface is as follows: Figure 2 As shown in the figure. When there are 2000 historical flight data items, the historical flight data is analyzed to generate a control strategy. Subsequently, each time 2000 historical flight data items are added, data analysis is performed to continuously optimize the control strategy. The current flight altitude is 1000m, the target flight altitude is 1050m, the wind speed is 8m / s (southwest), the external temperature is 5°C, the airbag temperature is 90°C, and the pressure is 110kPa. For example, the control strategy used is as follows: the current resistance wire temperature is increased to 95°C, the rotation speed is increased from 150rpm to 220rpm, and the rotor angle is deflected 25° to the northeast for 8 minutes.

[0048] S5: The server unit uploads the control strategy to the control unit. During the hot air balloon flight, the control unit uses the corresponding control strategy to adjust the flight altitude based on the set target altitude, current internal parameters and environmental data.

[0049] The generated control strategies are stored in the control unit. During subsequent hot air balloon flights, when the balloon's altitude needs to be adjusted, the target altitude is first set. Then, based on previously collected internal parameters and environmental data, the control unit automatically uses the corresponding control strategy to control the balloon's altitude, improving operational convenience for personnel. In the event of an emergency, such as a sudden change in altitude due to unusually strong winds, personnel can still manually adjust the altitude.

[0050] The present invention collects the internal parameters and environmental data of the hot air balloon and stores them as historical flight data. When a certain number is reached, it analyzes and generates a control strategy including a temperature adjustment strategy for the resistance wire heater and a motion posture of the action unit, and stores the control strategy in a control unit. During the subsequent flight of the hot air balloon, relevant personnel only need to set the target altitude of the flight, and the control unit can automatically adjust the flight altitude according to the corresponding strategy based on the current internal parameters and external environment, thereby greatly improving the convenience of operation.

[0051] During flight, this invention replaces traditional flame heating with a resistance wire heater. This system, combined with multi-source sensors that fuse environmental parameters in real time and coordinate control with motion units, enables high-precision adjustment of the hot air balloon's altitude. Furthermore, dynamic rotor compensation for wind disturbances further enhances altitude control accuracy.

[0052] It is particularly noteworthy that the present invention can accurately and intelligently control the flight altitude of a hot air balloon.

[0053] In this embodiment, analyzing historical flight data includes the following steps:

[0054] An altitude change sequence is constructed based on the altitude data in historical flight data. The time period in which the altitude changes continuously in the altitude change sequence is located as the first time period. The operation effective time is obtained, and the operation effective time before and after the first time period is defined as the second time period. The internal parameters and environmental data in the second time period are respectively constructed into multiple basic sequences. The temperature value of the resistance wire heater and the action posture of the action unit in the second time period are constructed as an action variable sequence.

[0055] The basic sequence and the action variable sequence are discretized to obtain the corresponding first discrete sequence and second discrete sequence respectively. The first discrete sequence is clustered for the first time based on the lowest height and the highest height in the second time period. The results of the first clustering are clustered for the second time based on the similarity between the first discrete sequences to obtain multiple clusters.

[0056] First, altitude data is extracted from each historical flight record and sorted chronologically to obtain multiple altitude change sequences. Each altitude change sequence is then analyzed to determine the time periods during which altitude changes occurred continuously. For example, if, during time period A, the altitude data rose from 1000m to 1050m and remained at 1050m without significant fluctuations, time period A is considered the first time period. In other words, the first time period is the time period during which altitude changes occurred. Because the temperature of the resistance heater does not change instantaneously, an operation validity period is also required.

[0057] By extracting and analyzing the altitude change sequence from historical flight data A, we determined that the first time period is from 3:02 PM to 3:05 PM, and the operation takes effect for 1 minute. The corresponding second time period is from 3:01 PM to 3:05 PM. We then continue to obtain internal parameters and environmental data for this time period from historical flight data A and construct a corresponding base sequence. This base sequence includes internal temperature, internal pressure, and wind speed sequences. We also generate an action variable sequence, which includes the temperature values of the resistance wire heater, the rotor speed, and the rotor angle values during this time period.

[0058] To reduce computational complexity, this embodiment discretizes the basic sequence and action variable sequence. For example, the original temperature value sequence [111 112 115 125] is discretized to obtain [(110-120) (110-120) (110-120) (120-130)]. Through the first clustering, time periods with similar altitude changes are found from multiple historical flight data. The similarity between the first discrete sequences of each is then calculated, and the first discrete sequences are clustered again based on the similarity. The similarity is, for example, the Euclidean distance between the two sequences. The first discrete sequences represent internal parameters and environmental data. Therefore, after clustering, first discrete sequences in the same cluster have similar internal parameters and environmental data.

[0059] A second discrete sequence under a class group is obtained, a frequency ratio of the second discrete sequence is calculated, and a control strategy is generated based on the second discrete sequence with the largest frequency ratio.

[0060] Through two clustering operations, we locate the time period with similar height changes, internal parameters and environmental data, and then count the frequency ratios of various second discrete sequences in this time period. For example, if a cluster includes 100 first discrete sequences, there are 100 corresponding second discrete sequences, among which the second discrete sequence A appears 80 times, then the frequency ratio is 80 / 100=0.8, which is the maximum frequency ratio.

[0061] When generating a control strategy, the maximum and final temperatures of the second discrete sequence are obtained. For example, in second discrete sequence A, the maximum temperature of the resistance wire heater is between (130-140°C) and the final temperature range is between (120-130°C). The lower limit of the temperature range is used as the final temperature. The resistance wire heater is maintained at the maximum temperature for 3 minutes, then drops from the maximum temperature to the final temperature, and the final temperature is maintained for 1 minute. A control plan for the temperature of the resistance wire heater can be obtained: first increase its temperature to 130°C and maintain it for 3 minutes, then drop it to 120°C and maintain it for 1 minute. Similarly, a control plan for the rotor angle and speed can be obtained. In other embodiments, the middle value of the range, or the upper limit of the temperature, can also be used as the final temperature.

[0062] In this embodiment, using the control strategy to adjust the flight altitude of the hot air balloon includes the following steps:

[0063] The sensor unit obtains the average value of internal parameters and environmental data within the detection time period, determines the target altitude to be adjusted, matches the corresponding control strategy based on the average value and the target altitude and uses it as the target strategy, obtains the current temperature of the resistance wire heater, and the target temperature to which the resistance wire heater is to be adjusted in the target strategy, the control unit calculates the difference between the current temperature and the target temperature, performs multi-stage adjustment on the temperature of the resistance wire heater based on the difference, and adjusts the current action of the action unit to the action posture in the target strategy to achieve adjustment of the hot air balloon's flight altitude.

[0064] Before matching, the average values of two internal parameters and the average values of various environmental parameters are generated during the test period. For example, during the test period, the average internal temperature was 90°C and the average wind speed was 3 m / s. During matching, the difference between the corresponding parameters is calculated. If the difference in all parameter types is less than the pre-set allowable range, the match is successful. If control strategy A applies to an average internal temperature of 90°C and a wind speed of 3 m / s, with an allowable range of ±2°C, and the internal temperature difference is within the allowable range, control strategy A is selected as the target strategy.

[0065] The rotor angle and speed can be adjusted instantaneously, allowing for quick adaptation to current environmental requirements. However, temperature adjustment requires time, so this embodiment adjusts the temperature of the resistance wire heater in stages. Specifically, this multi-stage adjustment is performed based on the following method.

[0066] The control strategy includes an ideal height change curve, setting a standard value, splitting the difference into multiple adjustment stages based on the standard value, obtaining the corresponding stage curve of each adjustment stage in the ideal height change curve, obtaining the first endpoint temperature of the first adjustment stage, and after the real-time temperature of the resistance wire heater reaches the first endpoint temperature, drawing the actual height change curve of the temperature adjustment process. If the deviation between the actual height change curve and the first stage curve is greater than the standard threshold, the control strategy is re-matched based on the current internal parameters and environmental data. If the deviation is less than or equal to the standard threshold, the adjustment is continued according to the second endpoint temperature of the second adjustment stage until the target height is reached.

[0067] Each control strategy has an ideal height change curve. By comparing the actual height change curve with the ideal height change curve, it can be determined whether the hot air balloon changes according to the established ideal situation. If not, the environment may have changed, such as a sudden and continuous strong wind. At this time, it is necessary to readjust the control strategy according to the environmental data. The following example illustrates the above steps. The standard value is set to 2°C, the current temperature of the resistance wire heater is 90°C, and the target temperature is 100°C, which is divided into 5 adjustment stages. Similarly, the ideal height change curve is divided into 5 stages, and the first end temperature of the first adjustment stage is 92°C. As Figure 3 As shown, there is an ideal height change curve L in the control strategy A, which is divided into 5 adjustment stages.

[0068] When calculating the deviation between the ideal height change curve and the actual change curve, select N coordinate points with the same horizontal coordinates on the two curves and use the first formula to calculate the deviation , the first formula is: ,in, is the number of selected coordinate points, The ideal height change curve The vertical coordinate value of the coordinate point, The ideal height change curve The ordinate value of each coordinate point. According to the first formula, the greater the deviation, the less similar the two curves are. The standard threshold is set manually; the smaller the standard threshold, the more accurate the hot air balloon adjustment process. When the deviation exceeds the standard threshold, the control strategy is re-adjusted. If it is less than or equal to the standard threshold, the next stage of heating is carried out until the hot air balloon is raised or lowered to the target altitude.

[0069] In this embodiment, generating a height change curve of the control strategy includes the following steps:

[0070] The height change sequence corresponding to each second discrete sequence under the same group is used as the analysis sequence. All analysis sequences under the same group are comprehensively analyzed to generate a height change function. Based on the height change function, an ideal height change curve corresponding to the control strategy is generated.

[0071] The ideal height change function includes a first function and a second function. An average change sequence of flight height is generated based on an analysis sequence, and the average change sequence is divided into a uniform change stage and a non-uniform change stage. The part of each analysis sequence located in the uniform change stage is defined as a first sequence, and the part located in the non-uniform change stage is defined as a second sequence. The first function is obtained by fitting the first sequence based on a linear function, and the second function is obtained by fitting the second sequence based on a nonlinear function. A first curve is drawn based on the first function, and a second curve is drawn based on the second function. The first curve and the second curve are used as ideal height change curves.

[0072] When the average change sequence is divided into the uniform change stage and the non-uniform change stage, the Burg coefficient sequence of the average change sequence is calculated, and the average change sequence is divided into the uniform change stage and the non-uniform change stage based on the Burg coefficient sequence.

[0073] Based on the previous records, a control strategy is generated based on a group, and a corresponding height change curve is generated based on the height change sequence under a group. During the specific analysis, the height change sequence corresponding to the second discrete sequence is first obtained and used as the analysis sequence. The length of the analysis sequence may be different. For example, analysis sequence A includes 20 height data, and analysis sequence B includes 21 height data. To this end, each analysis sequence is first aligned. This embodiment aligns each analysis sequence based on the DTW algorithm. After alignment, the average value of the elements in the same position of the analysis sequence is calculated, and finally an average change sequence is obtained by combining the various average values.

[0074] The Burg coefficient sequence of the average change sequence is then calculated. Based on the numerical mutations in the Burg coefficient sequence, it is possible to determine which parts of the average change sequence are uniformly changing and which parts are non-uniformly changing. For example, through analysis, it is determined that when adjusting the altitude, the altitude of the hot air balloon increases monotonically linearly in the first 3 minutes and monotonically non-linearly in the last 1 minute. A first function is obtained by fitting the sequence portion of the first 3 minutes of each analysis sequence, and a second function is obtained by fitting the sequence portion of the last 1 minute of each analysis sequence. The first and second curves drawn by the first and second functions are used as ideal altitude change curves. In particular, an average change sequence may include multiple uniform change stages and non-uniform change stages.

[0075] When the control unit adjusts the flight altitude based on the control strategy, if the hot air balloon is not adjusted to the target altitude within a preset time period, a manual adjustment reminder is generated.

[0076] like Figure 4 As shown, the present application also provides a hot air balloon flight altitude intelligent control system for implementing the above-mentioned hot air balloon flight altitude intelligent control method, the system comprising:

[0077] The sensor unit is used to collect internal parameters and environmental data. The internal parameters include the internal temperature and internal pressure of the hot air balloon itself.

[0078] Control unit, when the hot air balloon takes off, the control unit starts the flame heater and the resistance wire heater at the same time. When the take-off conditions are met, the flame heater is removed. During the flight of the hot air balloon, the control unit uses the corresponding control strategy to adjust the flight altitude based on the set target altitude, current internal parameters and environmental data.

[0079] The server unit stores the internal parameters and environmental data, as well as the motion postures of the resistance wire heater and the action unit as historical flight data after each flight is completed. When the historical flight data reaches a first quantity, the server unit analyzes the historical flight data to generate a control strategy. The control strategy includes temperature adjustment strategies for multiple resistance wire heaters and motion adjustment strategies for the action unit. The temperature adjustment strategy is used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy is used to adjust the motion posture of the action unit. The server unit uploads the control strategy to the control unit.

[0080] It should be understood that the various technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included outside the scope of protection of the present invention.

Claims

1. A hot air balloon flight altitude intelligent control method, characterized in that: The sensor unit in the hot air balloon collects internal parameters and environmental data, wherein the internal parameters include the internal temperature and internal pressure of the hot air balloon itself; When the hot air balloon takes off, the control unit starts the flame heater and the resistance wire heater at the same time, and removes the flame heater when the take-off conditions are met; After each flight is completed, the server unit stores the internal parameters and the environmental data, as well as the action postures of the resistance wire heater and the action unit as historical flight data; When the historical flight data reaches a first amount, the server unit analyzes the historical flight data to generate a control strategy, the control strategy including a plurality of temperature adjustment strategies for the resistance wire heater and a motion adjustment strategy for the motion unit, the temperature adjustment strategy being used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy being used to adjust the motion posture of the motion unit; The server unit uploads the control strategy to the control unit. During the hot air balloon flight, the control unit adjusts the flight altitude using the corresponding control strategy based on the set target altitude, the current internal parameters and the environmental data.

2. The method according to claim 1, characterized in that The environmental data includes wind speed data, altitude data, geographic location data and external temperature data; the action unit includes a fan and a rotor structure; and the action posture includes a rotor rotation speed and a rotor rotation angle.

3. The method according to claim 2, characterized in that Analyzing the historical flight data includes the following steps: constructing an altitude change sequence based on the altitude data in the historical flight data, locating a time period in the altitude change sequence during which the altitude changes continuously as a first time period, obtaining an operation effective time, defining the operation effective time before and during the first time period as a second time period, constructing the internal parameters and the environmental data within the second time period into a plurality of basic sequences, and constructing the temperature value of the resistance wire heater and the action posture of the action unit within the second time period into an action variable sequence; performing discretization processing on the basic sequence and the action variable sequence to obtain a corresponding first discrete sequence and a second discrete sequence, respectively; performing a first clustering on the first discrete sequence based on the lowest height and the highest height within the second time period; and performing a second clustering on the results of the first clustering based on the similarity between the first discrete sequences to obtain a plurality of clusters; The second discrete sequence in a cluster is obtained, a frequency ratio of occurrence of the second discrete sequence is calculated, and the control strategy is generated based on the second discrete sequence with the largest frequency ratio.

4. The method according to claim 3, characterized in that Using the control strategy to adjust the flight altitude of a hot air balloon includes the following steps: The sensor unit obtains the average value of the internal parameters and the environmental data within the detection time period, determines the target altitude to be adjusted, matches the corresponding control strategy based on the average value and the target altitude and uses it as the target strategy, obtains the current temperature of the resistance wire heater, and the target temperature to which the resistance wire heater is to be adjusted in the target strategy, the control unit calculates the difference between the current temperature and the target temperature, performs multi-stage adjustment on the temperature of the resistance wire heater based on the difference, and adjusts the current action of the action unit to the action posture in the target strategy to achieve adjustment of the hot air balloon's flight altitude.

5. The method according to claim 4, characterized in that The multi-stage adjustment of the temperature of the resistance wire heater includes the following steps: The control strategy includes an ideal height change curve, sets a standard value, divides the difference into multiple adjustment stages based on the standard value, obtains the stage curve corresponding to each adjustment stage in the ideal height change curve, obtains the first endpoint temperature of the first adjustment stage, and after the real-time temperature of the resistance wire heater reaches the first endpoint temperature, draws the actual height change curve of the temperature adjustment process. If the deviation between the actual height change curve and the first stage curve is greater than the standard threshold, the control strategy is re-matched based on the current internal parameters and the environmental data. If the deviation is less than or equal to the standard threshold, the adjustment is continued according to the second endpoint temperature of the second adjustment stage until the target height is reached.

6. The method according to claim 5, characterized in that Generating the height change curve of the control strategy comprises the following steps: The height change sequence corresponding to each of the second discrete sequences in the same group is used as an analysis sequence, all the analysis sequences in the same group are comprehensively analyzed to generate a height change function, and the ideal height change curve corresponding to the control strategy is generated based on the height change function.

7. The method according to claim 6, characterized in that Generating the ideal height change function comprises the following steps: The ideal height change function includes a first function and a second function. An average change sequence of flight height is generated based on the analysis sequence, and the average change sequence is divided into a uniform change stage and a non-uniform change stage. The part of each analysis sequence located in the uniform change stage is defined as a first sequence, and the part located in the non-uniform change stage is defined as a second sequence. The first function is obtained by fitting the first sequence based on a linear function, and the second function is obtained by fitting the second sequence based on a nonlinear function. A first curve is drawn based on the first function, and a second curve is drawn based on the second function. The first curve and the second curve are used as the ideal height change curves.

8. The method according to claim 7, characterized in that Dividing the average change sequence into the uniform change stage and the non-uniform change stage comprises the following steps: A Burg coefficient sequence of the average change sequence is calculated, and the average change sequence is divided into the uniform change stage and the non-uniform change stage based on the Burg coefficient sequence.

9. The method according to claim 1, characterized in that When the control unit adjusts the flight altitude based on the control strategy, if the hot air balloon is not adjusted to the target altitude within a preset time period, a manual adjustment reminder is generated.

10. A hot air balloon flight altitude intelligent control system, used to implement a hot air balloon flight altitude intelligent control method according to any one of claims 1 to 9, characterized in that: include: a sensor unit for collecting internal parameters and environmental data, wherein the internal parameters include the internal temperature and internal pressure of the hot air balloon itself; a control unit, wherein when the hot air balloon takes off, the control unit simultaneously activates the flame heater and the resistance wire heater, and when the take-off conditions are met, removes the flame heater; during the hot air balloon flight, the control unit adjusts the flight altitude using the corresponding control strategy based on a set target altitude, the current internal parameters, and the environmental data; The server unit stores the internal parameters and the environmental data, as well as the motion postures of the resistance wire heater and the motion unit as historical flight data after each flight is completed. When the historical flight data reaches a first quantity, the server unit analyzes the historical flight data to generate a control strategy, wherein the control strategy includes a plurality of temperature adjustment strategies for the resistance wire heater and motion adjustment strategies for the motion unit. The temperature adjustment strategy is used to adjust the temperature of the resistance wire heater, and the motion adjustment strategy is used to adjust the motion posture of the motion unit. The server unit uploads the control strategy to the control unit.

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