An aviation 5G communication system integrating edge computing and multiple communication access methods

Abstract

This invention discloses an aviation 5G communication system integrating edge computing and multiple communication access methods, belonging to the field of aviation communication technology. It includes an airborne sensor network module for acquiring aircraft operating parameters; a link resource acquisition module for acquiring related parameters related to link switching during flight; an edge processing and analysis platform including a data processing module, a storage module, a fault detection module, and a link analysis module; and a response module including a fault response unit and a switching execution unit. This invention first selects a relatively stable link for communication based on the corresponding link switching interval of the aircraft. Then, it sets multiple detection and judgment points within the link switching interval and comprehensively analyzes the link quality, network performance, and flight environment conditions between each detection and judgment point to promptly and accurately determine the link communication status, thereby ensuring communication quality and meeting the personalized needs of passengers.

Description

Technical Field

[0001] This invention belongs to the field of aviation communication technology, specifically relating to an aviation 5G communication system that integrates edge computing and multiple communication access methods. Background Technology

[0002] Aviation communications play a vital role in the field of aircraft flight, and can be used in air traffic management, flight operations, emergency response, and in-flight services to ensure the stable operation of aircraft.

[0003] However, with the rapid development of the aviation industry and the increasing diversification of aviation services, higher demands are being placed on communication systems. For example, current technologies generally rely on installing corresponding detection devices at key locations on the aircraft to monitor its operational status. Firstly, this approach can only detect malfunctions that have already occurred and cannot assess potential malfunction risks. Secondly, the parameters acquired through these devices are mostly analyzed based on single parameters. As aircraft become increasingly intelligent, a malfunction can cause changes in multiple data types, making analysis based on a single parameter insufficiently accurate. On the other hand, passengers have increasingly higher demands for in-flight services, hoping to enjoy high-speed and stable internet access for activities such as watching high-definition videos, playing online games, and video conferencing. This requires aviation communication systems to have higher bandwidth and lower latency to meet passengers' personalized needs. Summary of the Invention

[0004] The purpose of this invention is to provide an aviation 5G communication system that integrates edge computing and multiple communication access methods to solve the problems faced in the background art.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] An aviation 5G communication system integrating edge computing and multiple communication access methods, the system comprising:

[0007] An airborne sensor network module, which is used to acquire the aircraft's operating parameter information;

[0008] A link resource acquisition module, which is used to acquire related parameter information of the aircraft during flight related to link switching;

[0009] The edge processing analysis platform includes a data processing module, a storage module, a fault detection module, and a link analysis module. The data processing module is used to preprocess the acquired parameter information, the storage module is used to store the parameter information, the fault detection module determines whether there is a risk of failure in aircraft operation based on the acquired operating parameter information, and the link analysis module analyzes the acquired related parameter information to determine whether the link needs to be switched.

[0010] The response module includes a fault response unit and a switching execution unit. The fault response unit generates a corresponding alarm response when it determines that there is a fault risk, and the switching execution unit performs a corresponding link switching operation when a link needs to be switched.

[0011] Furthermore, the fault detection module operates by acquiring, in real time, various operating parameters corresponding to the monitored fault type. At the same time, the optimal operating values ​​of various operating parameters for the corresponding fault type are obtained based on historical data. In conjunction with historical data on the impact of various operating parameters on the occurrence of corresponding fault types, weight values ​​are assigned to each operating parameter. Through formula Calculate the deviation coefficient for this fault type. ;

[0012] Simultaneously obtain the deviation coefficients of other fault types associated with this fault type. , ... Thus, through the formula Calculate the correlation deviation coefficient M is the number of other associated fault types, and , This represents the influence ratio coefficient of the i-th associated fault type.

[0013] Through formula Calculate the fault judgment value ;

[0014] when If so, it is determined that the aircraft has a fault of that type. The set fault judgment threshold, This represents the number of operational parameter items that need to be obtained for the corresponding fault type, and .

[0015] Furthermore, the fault detection module's operating method also includes: when At this time, a testing cycle should be determined. And within this detection cycle, based on the real-time acquired fault judgment value P, a fault judgment function is formulated. and fault judgment threshold function ;

[0016] Through formula Calculate the failure risk coefficient ,when If so, it is determined that there is a potential risk of failure for that type of aircraft malfunction;

[0017] in, This is the start time of the detection cycle. For function The maximum first derivative during the detection period, The first derivative is the comparison value. The threshold for judging potential failure risks is set.

[0018] Furthermore, the working method of the link analysis module is as follows: based on the flight range of the aircraft's flight route, n link switching intervals are set, and a corresponding communication link for the aircraft is set within each link switching interval. When the aircraft flies into the corresponding link switching interval, the aircraft communication will automatically switch to the corresponding communication link.

[0019] Furthermore, the working method of the link analysis module also includes: when the aircraft flies into the corresponding link switching interval, the aircraft automatically switches to the corresponding communication link and marks the communication link as the initial link. At the same time, n detection and judgment points are set within the link switching interval, and the correlation parameter information between each detection and judgment point is obtained to generate the link quality parameter status value. Network performance parameters status values Flight environment parameter status values A switching decision tree model is constructed by training a neural network model based on a large number of historical state values.

[0020] The obtained link quality parameter status values Network performance parameters status values Flight environment parameter status values The input is fed into the corresponding decision tree model, and the output link is observed to see if it matches the initial link. If they do not match, the link needs to be switched.

[0021] Furthermore, the aforementioned , as well as The acquisition method is as follows: by acquiring the link signal strength, bit error rate, and signal-to-noise ratio during the flight time of two adjacent detection and judgment points, and then performing weighted fusion, the link quality parameter status value is obtained. ;

[0022] By acquiring the network latency, available bandwidth, and packet loss rate during the flight time of two adjacent detection points, and then performing weighted fusion, the network performance parameter state value is obtained. ;

[0023] Meteorological information from the network during the flight time of two adjacent detection points is obtained from the meteorological bureau, including rainfall, snowfall, visibility, atmospheric composition, temperature, humidity, and air pressure. This information is then weighted and fused to derive the flight environment parameter state values. .

[0024] Furthermore, the operation method of the response module is as follows: the fault response unit in When this occurs, a corresponding fault type alarm is generated, and based on... Different alarm levels are set based on the value; When this occurs, a corresponding fault type potential risk alarm is generated, based on... Different alarm levels are set based on the value.

[0025] The switching execution unit switches the corresponding link based on the link results output by the decision tree model.

[0026] The beneficial effects of this invention are:

[0027] This invention can comprehensively analyze multiple parameters corresponding to the aircraft fault type, and combine them with the possible chain failures to accurately determine the corresponding fault of the aircraft, improve the accuracy of fault monitoring, and help ensure stable flight of the aircraft.

[0028] This invention first selects a relatively stable link for communication based on the corresponding link switching interval of the aircraft. Then, it sets multiple detection and judgment points for the link switching interval. Based on a comprehensive analysis of the link quality, network performance, and flight environment conditions between each detection and judgment point, it can promptly and accurately judge the link communication status and perform corresponding switching. By dividing the interval into multiple detection and judgment points, it can judge the subsequent communication status in a timely manner based on the communication status in the previous period, thereby making timely adjustments, reducing the occurrence of delays, ensuring communication quality, and meeting the personalized needs of passengers.

[0029] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, 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.

[0031] Figure 1 This is a block diagram of the communication system of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] In one embodiment, an aviation 5G communication system integrating edge computing and multiple communication access methods is disclosed, such as... Figure 1 As shown, the system includes:

[0034] Airborne sensor network module, used to acquire aircraft operating parameter information;

[0035] The link resource acquisition module is used to acquire related parameter information about link switching during aircraft flight.

[0036] The edge processing analysis platform includes a data processing module, a storage module, a fault detection module, and a link analysis module. The data processing module is used to preprocess the acquired parameter information, the storage module is used to store the parameter information, the fault detection module determines whether there is a risk of failure in the aircraft operation based on the acquired operating parameter information, and the link analysis module analyzes the acquired related parameter information to determine whether the link needs to be switched.

[0037] The response module includes a fault response unit and a switching execution unit. The fault response unit generates a corresponding alarm response when it determines that there is a fault risk, and the switching execution unit performs the corresponding link switching operation when it is necessary to switch the link.

[0038] Through the above technical solution, this application first deploys corresponding airborne sensors in key parts of the aircraft to obtain the aircraft's operating parameter information. This operating parameter information is then used to determine aircraft operational faults. Next, a link resource acquisition module acquires related parameter information concerning link switching during flight, including link signal quality parameters, network performance parameters, and flight environment parameters, for link switching determination. The edge processing and analysis platform then performs the specific judgments. Internally, it includes a data processing module, a storage module, a fault detection module, and a link analysis module. The storage module stores the acquired parameter information. The data processing module performs preprocessing operations on the acquired parameter information, including data cleaning and anomaly handling, time series alignment and fusion, and data normalization. The fault detection module analyzes the acquired operating parameters to determine if the aircraft has corresponding faults or fault risks. The link analysis module analyzes the acquired related parameter information to determine if the aircraft's communication link needs to be switched. Finally, a response module issues alarms for corresponding faults and executes link switching operations to ensure the stable and normal operation of the aircraft.

[0039] The fault detection module works by acquiring various operating parameters corresponding to the monitored fault type in real time. At the same time, the optimal operating values ​​of various operating parameters for the corresponding fault type are obtained based on historical data. In conjunction with historical data on the impact of various operating parameters on the occurrence of corresponding fault types, weight values ​​are assigned to each operating parameter. Through formula Calculate the deviation coefficient for this fault type. ;

[0040] Simultaneously obtain the deviation coefficients of other fault types associated with this fault type. , ... Thus, through the formula Calculate the correlation deviation coefficient M is the number of other associated fault types, and , This represents the influence ratio coefficient of the i-th associated fault type.

[0041] Through formula Calculate the fault judgment value ;

[0042] when If so, it is determined that the aircraft has a fault of that type. The set fault judgment threshold, This represents the number of operational parameter items that need to be obtained for the corresponding fault type, and .

[0043] The above scheme provides a specific method for real-time judgment of aircraft malfunctions. First, based on common aircraft malfunctions, they are categorized into multiple monitored malfunction types. Then, various operational parameters related to the occurrence of each malfunction type are acquired through corresponding airborne sensors. Simultaneously, the optimal operating values ​​for each operational parameter for each malfunction type are obtained based on historical data. Furthermore, by combining the impact of each operational parameter on the occurrence of the malfunction when the corresponding malfunction type occurs in historical data, weight values ​​are assigned to each operational parameter. Finally, a formula is used to... Calculate the deviation coefficient for this fault type. It can be seen that the larger the deviation coefficient, the greater the difference between the acquired parameters and the optimal operating values, and thus the greater the possibility of a fault. For example, when dealing with fatigue cracks and abnormal wear faults in aero-engine blades, multiple parameters such as vibration frequency, blade surface strain, concentration of metal abrasive particles in lubricating oil, blade surface temperature, and torsion angle can be acquired by deploying vibration acceleration sensors, strain gauge sensors, oil abrasive particle sensors, infrared thermal imaging sensors, and fiber optic sensors. These parameters are then compared with their respective optimal operating parameters to generate a deviation coefficient for that fault type. Furthermore, since faults in aerospace systems are often interconnected, the occurrence of one fault can trigger a chain reaction. Therefore, it is also necessary to obtain the deviation coefficients of other fault types that are related to this fault type. , ... Thus, through the formula Calculate the correlation deviation coefficient Then through the formula Calculate the fault judgment value Finally, fault judgment thresholds were set based on experience and historical data. ,when If the fault type is detected, the aircraft is deemed to have a fault. This method allows for comprehensive analysis of multiple parameters corresponding to the aircraft's fault type, along with a comprehensive analysis of potential cascading faults, to accurately diagnose the fault, improve the accuracy of fault monitoring, and help ensure stable aircraft flight.

[0044] The fault detection module's working method also includes: when At this time, a testing cycle should be determined. And within this detection cycle, based on the real-time acquired fault judgment value P, a fault judgment function is formulated. and fault judgment threshold function ;

[0045] Through formula Calculate the failure risk coefficient ,when If so, it is determined that there is a potential risk of failure for that type of aircraft malfunction;

[0046] in, This is the start time of the detection cycle. For function The maximum first derivative during the detection period, The first derivative is the comparison value. The threshold for judging potential failure risks is set.

[0047] The above scheme provides a method for assessing potential aircraft failure risks. First, it establishes a testing cycle when there is no failure risk. And within this detection cycle, based on the real-time acquired fault judgment value P, a fault judgment function is formulated. and fault judgment threshold function Through formula Calculate the failure risk coefficient Because the set threshold is determined manually based on historical data and experience, the threshold is not accurate enough. While it may be determined that there is no fault if the threshold is not exceeded, if the obtained fault assessment value consistently stays near the threshold, then the possibility of a fault is relatively high. (Formula) This indicates the difference between the change in the fault judgment value obtained within the detection period and the threshold. The smaller the value, the closer it is to the threshold, and therefore the greater the risk. Similarly, the formula... Representation function The greater the variation in the value of the first derivative during the detection period, the more pronounced the increasing trend of the fault judgment value, and thus the greater the risk of fault existence. Therefore, a comprehensive analysis combining these two factors is necessary, using the formula... Calculate the failure risk coefficient ,when If so, it is determined that there is a potential risk of failure for that type of aircraft malfunction. The threshold for judging potential failure risks is set. The first derivative comparison value is determined based on experience and historical data. This method allows for the analysis of potential fault risks by combining the changes in fault assessment values ​​within a period when a fault has not yet occurred. This enables timely early warning and handling, reducing the occurrence of faults and ensuring flight stability.

[0048] The link analysis module works as follows: based on the flight range of the aircraft's flight route, n link switching intervals are set. Within each link switching interval, a corresponding communication link for the aircraft is set. When the aircraft flies into the corresponding link switching interval, the aircraft communication will automatically switch to the corresponding communication link.

[0049] When the aircraft flies into the corresponding link switching interval, it automatically switches to the corresponding communication link and marks this link as the initial link. At the same time, n detection and judgment points are set within the link switching interval, and the correlation parameter information between each detection and judgment point is obtained to generate the link quality parameter status value. Network performance parameters status values Flight environment parameter status values A switching decision tree model is constructed by training a neural network model based on a large number of historical state values.

[0050] The obtained link quality parameter status values Network performance parameters status values Flight environment parameter status values The input is fed into the corresponding decision tree model, and the output link is observed to see if it matches the initial link. If they do not match, the link needs to be switched. , as well as The method for obtaining it is as follows:

[0051] By acquiring the link signal strength, bit error rate, and signal-to-noise ratio during the flight time of two adjacent detection points, and then performing weighted fusion, the link quality parameter status value is obtained. ;

[0052] By acquiring the network latency, available bandwidth, and packet loss rate during the flight time of two adjacent detection points, and then performing weighted fusion, the network performance parameter state value is obtained. ;

[0053] Meteorological information from the network during the flight time of two adjacent detection points is obtained from the meteorological bureau, including rainfall, snowfall, visibility, atmospheric composition, temperature, humidity, and air pressure. After weighted fusion, the flight environment parameter state values ​​are obtained. .

[0054] The above scheme provides a method for link switching judgment. First, based on a large amount of historical data and the flight range of the aircraft's flight path, n link switching intervals are set. Within each link switching interval, a corresponding aircraft communication link is set. When the aircraft flies into the corresponding link switching interval, its communication automatically switches to the corresponding communication link. This can reliably determine the aircraft's communication link in advance, ensuring it is under optimal communication conditions. However, this method is easily affected by various factors, such as environmental factors including rainfall, snowfall, visibility, atmospheric composition, temperature, humidity, and air pressure, all of which can affect communication quality. Therefore, when the aircraft flies into the corresponding link switching interval, it automatically switches to the corresponding communication link and marks this link as the initial link. Simultaneously, n detection and judgment points are set within the link switching interval, and the correlation parameter information between each detection and judgment point is obtained. This includes obtaining the link signal strength, bit error rate, and signal-to-noise ratio during the flight time of two adjacent detection and judgment points, performing weighted fusion, and then deriving the link quality parameter status value. By acquiring the network latency, available bandwidth, and packet loss rate during the flight time of two adjacent detection points, and then performing weighted fusion, the network performance parameter state value is obtained. Meteorological information from the network during the flight time of two adjacent detection points is obtained from the meteorological bureau, including but not limited to rainfall, snowfall, visibility, atmospheric composition, temperature, humidity, air pressure, etc. After weighted fusion, the flight environment parameter state values ​​are obtained. The weighted fusion method can input the current parameter values ​​into a pre-built quantization judgment matrix model library. This library can be derived through machine training based on a large amount of historical data. For example, during takeoff and landing, the weights of link quality parameters (signal strength 0.6, bit error rate 0.3), network performance parameters (latency 0.5, packet loss rate 0.4), and environmental parameters (visibility 0.4, rainfall 0.3) can be set. During high-altitude cruise, the weights of link quality parameters (signal-to-noise ratio 0.5, bit error rate 0.3), network performance parameters (available bandwidth 0.6, latency 0.2), and environmental parameters (temperature 0.3, air pressure 0.2) can be set, and so on, ultimately yielding the link quality parameter status values. Network performance parameters status values Flight environment parameter status values Then, based on a large number of historical state values, a neural network model is trained to construct a switching decision tree model. In the model, the type of link being switched includes, but is not limited to, 5G communication links, satellite communication links, ATG links, etc., and each type of link corresponds to specific parameter state values. The acquired link quality parameter state values ​​are then used to... Network performance parameters status values Flight environment parameter status values The input is fed into the corresponding decision tree model, and the output link is observed to ensure it matches the initial link. If they do not match, the link needs to be switched. This method first selects a relatively stable link for communication based on the corresponding link switching interval. Then, multiple detection and judgment points are set within the link switching interval. A comprehensive analysis is performed based on the link quality, network performance, and flight environment conditions between each detection and judgment point to accurately and promptly determine the link communication status and perform corresponding switching. Dividing the interval into multiple detection and judgment points allows for timely assessment of subsequent communication based on the communication status of the previous period, enabling timely adjustments, reducing latency, ensuring communication quality, and meeting the personalized needs of passengers.

[0055] The response module works as follows: the fault response unit in When this occurs, a corresponding fault type alarm is generated, and based on... Different alarm levels are set based on the value; When this occurs, a corresponding fault type potential risk alarm is generated, based on... Different alarm levels are set based on the value.

[0056] The switching execution unit switches the corresponding link based on the link results output by the decision tree model.

[0057] The above technical solution provides a method for the operation of the response module. First, the fault response unit... When this occurs, a corresponding fault type alarm is generated, and based on... Different alarm levels are set based on the value, for example... At that time, a level one alarm is generated. A level 2 alarm is generated in time. At that time, a level three alarm is generated. as well as The alarm level is used as a threshold for fault diagnosis; the higher the alarm level, the more serious the problem and the more urgent the need for action. Similarly, in... When this occurs, a corresponding fault type potential risk alarm is generated, based on... Different alarm levels are set according to the value, and the switching execution unit switches the corresponding link according to the link results output by the decision tree model, so as to ensure communication quality.

[0058] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in the specification, they should all fall within the protection scope of the present invention.

Claims

1. An aviation 5G communication system integrating edge computing and multiple communication access methods, characterized in that, The system includes: An airborne sensor network module, which is used to acquire the aircraft's operating parameter information; A link resource acquisition module, which is used to acquire related parameter information of the aircraft during flight related to link switching; The edge processing analysis platform includes a data processing module, a storage module, a fault detection module, and a link analysis module. The data processing module is used to preprocess the acquired parameter information, the storage module is used to store the parameter information, the fault detection module determines whether there is a risk of failure in aircraft operation based on the acquired operating parameter information, and the link analysis module analyzes the acquired related parameter information to determine whether the link needs to be switched. The response module includes a fault response unit and a switching execution unit. The fault response unit generates a corresponding alarm response when it determines that there is a fault risk, and the switching execution unit performs a corresponding link switching operation when it is necessary to switch the link. The fault detection module works by acquiring various operating parameters corresponding to the monitored fault type in real time. At the same time, the optimal operating values ​​of various operating parameters for the corresponding fault type are obtained based on historical data. In conjunction with historical data on the impact of various operating parameters on the occurrence of corresponding fault types, weight values ​​are assigned to each operating parameter. Through formula Calculate the deviation coefficient for this fault type. ; Simultaneously obtain the deviation coefficients of other fault types associated with this fault type. , ... Thus, through the formula Calculate the correlation deviation coefficient M is the number of other associated fault types, and , The coefficient representing the proportion of the i-th associated fault type. Through formula Calculate the fault judgment value ; when If so, it is determined that the aircraft has a fault of that type. The set fault judgment threshold, This represents the number of operational parameter items that need to be obtained for the corresponding fault type, and ; when At this time, a testing cycle should be determined. And within this detection cycle, based on the real-time acquired fault judgment value P, a fault judgment function is formulated. and fault judgment threshold function ; Through formula Calculate the failure risk coefficient ,when If so, it is determined that there is a potential risk of failure for that type of aircraft malfunction; in, This is the start time of the detection cycle. For function The maximum first derivative during the detection period, The first derivative is the comparison value. The threshold for judging potential failure risks is set.

2. The aviation 5G communication system integrating edge computing and multiple communication access methods according to claim 1, characterized in that, The link analysis module works as follows: Based on the flight range of the aircraft's flight path, n link switching intervals are set. Within each link switching interval, a corresponding communication link for the aircraft is set. When the aircraft flies into the corresponding link switching interval, the aircraft communication will automatically switch to the corresponding communication link.

3. The aviation 5G communication system integrating edge computing and multiple communication access methods according to claim 2, characterized in that, The working method of the link analysis module also includes: When the aircraft flies into the corresponding link switching interval, it automatically switches to the corresponding communication link and marks this link as the initial link. At the same time, n detection and judgment points are set within the link switching interval, and the correlation parameter information between each detection and judgment point is obtained to generate the link quality parameter status value. Network performance parameters status values Flight environment parameter status values A switching decision tree model is constructed by training a neural network model based on a large number of historical state values. The obtained link quality parameter status values Network performance parameters status values Flight environment parameter status values The input is fed into the corresponding decision tree model, and the output link is observed to see if it matches the initial link. If they do not match, the link needs to be switched.

4. The aviation 5G communication system integrating edge computing and multiple communication access methods according to claim 3, characterized in that, The , as well as The method for obtaining it is as follows: By acquiring the link signal strength, bit error rate, and signal-to-noise ratio during the flight time of two adjacent detection points, and then performing weighted fusion, the link quality parameter status value is obtained. ; By acquiring the network latency, available bandwidth, and packet loss rate during the flight time of two adjacent detection points, and then performing weighted fusion, the network performance parameter state value is obtained. ; Meteorological information from the network during the flight time of two adjacent detection points is obtained from the meteorological bureau, including rainfall, snowfall, visibility, atmospheric composition, temperature, humidity, and air pressure. This information is then weighted and fused to derive the flight environment parameter state values. .

5. The aviation 5G communication system integrating edge computing and multiple communication access methods according to claim 4, characterized in that, The response module works as follows: Fault response unit in When this occurs, a corresponding fault type alarm is generated, and based on... Different alarm levels are set based on the value; When this occurs, a corresponding fault type potential risk alarm is generated, based on... Different alarm levels are set based on the value. The switching execution unit switches the corresponding link based on the link results output by the decision tree model.

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