Low-altitude flight safety guarantee intelligent sensor

Abstract

The invention discloses an intelligent sensor for low-altitude flight safety guarantee. The intelligent sensor comprises a data acquisition unit, a data processing and analysis unit, a safety risk assessment module, an early warning and obstacle avoidance strategy generation unit and a communication interface, the data acquisition unit is used for collecting multi-source data in a low-altitude flight environment; the data processing and analyzing unit performs preprocessing, feature extraction and fusion analysis on the data acquired by the data acquisition unit; the security risk assessment module is based on the output of the data processing and analysis unit; the early warning and obstacle avoidance strategy generation unit automatically triggers an early warning signal when the safety risk value exceeds a preset threshold value; the method has remarkable beneficial effects in the aspects of improving safety risk assessment accuracy, realizing balance between path cost and safety risk, enhancing the autonomous obstacle avoidance capability of the aircraft, improving flight efficiency and fuel economy, promoting aviation technology innovation and development and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent sensors, and in particular to an intelligent sensor for ensuring low-altitude flight safety. Background Art

[0002] In the field of aviation, safe flight and path optimization of aircraft have always been the focus of research. With the advancement of technology and the improvement of aircraft performance, the demand for safety risk assessment and obstacle avoidance path optimization during aircraft flight has become increasingly urgent.

[0003] Traditional aircraft safety risk assessment methods mainly rely on the pilot's personal experience and the mechanical performance parameters of the aircraft. This method is not only highly subjective, but also difficult to comprehensively and accurately assess various safety risks during flight. At the same time, in terms of obstacle avoidance path optimization, traditional algorithms often only consider path costs (such as flight time, fuel consumption, etc.), while ignoring the impact of safety risks on path selection, which may cause the aircraft to face greater safety hazards during flight.

[0004] In order to solve the above problems, in recent years, researchers have begun to explore safety risk assessment methods based on multi-source data fusion and obstacle avoidance path optimization algorithms that comprehensively consider path costs and safety risks. However, these existing methods still have some shortcomings. For example, in the process of multi-source data fusion, how to effectively deal with data differences and conflicts between different data sources to improve data accuracy and reliability is an urgent problem to be solved. In addition, in the obstacle avoidance path optimization algorithm, how to dynamically adjust the weights of path cost and safety risk according to the current state of the aircraft and the remaining flight time to achieve a balance between the two is also a challenging topic.

[0005] Therefore, this study proposes a new method for determining the trade-off coefficient, as well as a safety risk assessment and obstacle avoidance path optimization system based on this method. The system can comprehensively consider the current speed of the aircraft, the remaining flight time, and various safety threat factors, and achieve a balance between path cost and safety risk by dynamically adjusting the trade-off coefficient. At the same time, the system also uses multi-source data fusion analysis technology to improve the accuracy and reliability of the data, providing strong data support for subsequent safety risk assessment and obstacle avoidance strategy generation. Summary of the invention

[0006] The purpose of the present invention is to provide a low-altitude flight safety assurance intelligent sensor to solve the problems raised in the above-mentioned background technology and to improve the safe flight performance and path optimization capability of the aircraft.

[0007] To achieve the above object, the present invention provides the following technical solution: a low-altitude flight safety intelligent sensor, characterized in that it includes: The data acquisition unit is used to collect multi-source data in the low-altitude flight environment, including the position, speed, altitude, attitude parameters of the aircraft, as well as the location of obstacles, meteorological conditions, and electromagnetic interference information in the environment; A data processing and analysis unit, which performs preprocessing, feature extraction and fusion analysis on the data acquired by the data acquisition unit to identify potential security threats; A safety risk assessment module, which calculates a flight safety risk value through a predefined safety risk assessment algorithm based on the output of the data processing and analysis unit; The warning and obstacle avoidance strategy generation unit automatically triggers a warning signal when the safety risk value exceeds the preset threshold, and generates obstacle avoidance or safe flight suggestions based on preset rules or algorithms; Communication interface, used to transmit warning signals, obstacle avoidance strategies or safe flight suggestions to low-altitude aircraft control systems or ground monitoring stations in real time.

[0008] Preferably, the security risk assessment algorithm uses the following formula to calculate the security risk value: ;in, represents the security risk value, Indicates the number of security threat factors considered, Indicates The weight of the threat factor , indicating the The risk function of each threat factor is evaluated according to its quantitative value, and it satisfies foot.

[0009] Preferably, the risk function The specific form is :;in, , and It is a coefficient determined according to specific threat factors.

[0010] Preferably, the early warning and obstacle avoidance strategy generating unit includes: The warning threshold setting module is used to dynamically adjust the warning threshold according to flight mission requirements, aircraft performance and environmental conditions; The obstacle avoidance strategy optimization module uses the following formula to calculate the optimal obstacle avoidance path: ;in , represents the optimal obstacle avoidance path, Represents the set of all possible obstacle avoidance paths, The path cost function is shown in Figure 2. represents the safety risk value on the path, and is a trade-off coefficient used to adjust the relative importance of path cost and safety risk.

[0011] Preferably, the path cost function The specific form is: ;in, Indicates the path Flight time on Indicates the path Fuel consumption on Indicates the path The degree of wear and tear that may be caused to the aircraft, , and are the trade-off coefficients.

[0012] Preferably, the data processing and analysis unit uses the following formula to perform fusion analysis on multi-source data: ;in, Represents the comprehensive data index after fusion, Indicates the number of data sources. Indicates The weight of the data source, Indicates The actual data value of the data source, and Respectively represent The mean and standard deviation of the data sources.

[0013] Preferably, the trade-off coefficient and The method for determining is as follows: ; ;in, Indicates the maximum safe speed of the aircraft. Indicates the current flight speed. Indicates the remaining flight time. represents the total flight time, and is the adjustment factor.

[0014] The invention proposes a low-altitude flight safety intelligent sensor, which has the following beneficial effects: 1. By comprehensively considering multiple security threat factors and conducting a comprehensive assessment based on the weights and quantified values ​​of each factor, the present invention can more accurately reflect the safety risk status of an aircraft during flight; in addition, the multi-source data fusion analysis technology is used to effectively integrate information from different data sources, thereby improving the accuracy and reliability of the data and further improving the accuracy of the safety risk assessment.

[0015] 2. The present invention proposes a new method for determining the trade-off coefficient, which can dynamically adjust the weights of the path cost and the safety risk according to the current state of the aircraft and the remaining flight time; in the process of obstacle avoidance path optimization, the system can fully consider the path cost while ensuring safety, and achieve an effective balance between the two, thereby improving the overall flight performance of the aircraft.

[0016] 3. By applying the obstacle avoidance path optimization algorithm of the present invention, the aircraft can quickly and accurately find the optimal obstacle avoidance path in a complex environment and effectively avoid collisions with obstacles; this not only improves the aircraft's autonomous obstacle avoidance capability, but also reduces the pilot's workload and improves the level of flight safety.

[0017] 4. Since the present invention fully considers the path cost, including factors such as flight time and fuel consumption, in the process of obstacle avoidance path optimization, it is possible to select a more economical and efficient flight path while ensuring safety; this helps to reduce the fuel consumption of the aircraft, improve flight efficiency, and reduce operating costs.

[0018] In summary, the present invention has shown significant beneficial effects in improving the accuracy of safety risk assessment, achieving a balance between path cost and safety risk, enhancing the autonomous obstacle avoidance capability of aircraft, improving flight efficiency and fuel economy, and promoting innovation and development of aviation technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a principle block diagram of the present invention; Figure 2 Schematic diagram of the early warning and obstacle avoidance strategy generation unit of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] For examples, see Figure 1-2 ,The present invention provides a technical solution: a low-altitude flight safety assurance intelligent sensor, including: a data acquisition unit, a data processing and analysis unit, a safety risk assessment module, a warning and obstacle avoidance strategy generation unit and a communication interface; Data acquisition unit: responsible for collecting multi-source data in the low-altitude flight environment; including the aircraft's location information, speed, altitude, attitude parameters (such as pitch angle, roll angle, yaw angle), as well as the location of obstacles in the environment, meteorological conditions (such as wind speed, rainfall), electromagnetic interference information, etc.; these data are the basis for subsequent analysis and decision-making, ensuring that the system can fully understand the situation of the aircraft and its surrounding environment; Data processing and analysis unit: preprocesses, extracts features and performs fusion analysis on the data acquired by the data acquisition unit; preprocessing includes data cleaning and denoising; feature extraction is to extract key feature parameters from the original data; fusion analysis is to integrate data from different sensors to identify potential security threats; through these processing steps, the system can more accurately understand the flight environment and aircraft status, and provide reliable data support for subsequent risk assessment; Safety risk assessment module: Based on the output of the data processing and analysis unit, the flight safety risk value is calculated through a predefined safety risk assessment algorithm; using a specific algorithm (such as a weighted risk assessment formula), the weights and quantitative values ​​of different threat factors are considered to comprehensively assess the safety of the current flight status; flight risks can be assessed in real time to ensure that the system can detect potential dangerous situations in a timely manner; When the safety risk value exceeds the preset threshold, the warning signal is automatically triggered and obstacle avoidance or safe flight suggestions are generated. According to the preset rules or algorithms, the system will issue an alarm when a high risk is detected and calculate the optimal obstacle avoidance path or safe flight strategy. It can provide early warning before the danger occurs and recommend specific countermeasures, thereby improving flight safety. Communication interface: used to transmit warning signals, obstacle avoidance strategies or safe flight suggestions to the low-altitude aircraft control system or ground monitoring station in real time; transmit important information in real time through radio, satellite communication or other communication means to ensure that the aircraft and ground control personnel can receive safety prompts and operational suggestions in a timely manner; the communication interface ensures the timely transmission of information, allowing the aircraft to respond quickly to security threats and the ground monitoring station to understand the status of the aircraft at any time.

[0022] The security risk assessment algorithm uses the following formula to calculate the security risk value: ;in, represents the security risk value, Indicates the number of security threat factors considered, Indicates The weight of each threat factor, Indicates Threat factors are quantified according to their The risk function of the evaluation is satisfied The risk function The specific form is: ;in, , and It is a coefficient determined according to the specific threat factors. This formula is used to calculate the comprehensive security risk value. It takes into account multiple security threat factors and makes a comprehensive assessment based on the weight and quantitative value of each factor. The weight reflects the importance of each threat factor to the security risk, while the risk function is defined according to the characteristics of the specific threat factors. It can be a linear, nonlinear or prediction function based on a machine learning model.

[0023] The warning and obstacle avoidance strategy generation unit includes: a warning threshold setting module and an obstacle avoidance strategy optimization module; the warning threshold setting module is used to dynamically adjust the warning threshold according to flight mission requirements, aircraft performance and environmental conditions; the obstacle avoidance strategy optimization module uses the following formula to calculate the optimal obstacle avoidance path: ;in, represents the optimal obstacle avoidance path, represents the set of all possible obstacle avoidance paths, represents the path cost function, represents the safety risk value on the path, and is a trade-off coefficient used to adjust the relative importance of path cost and safety risk. This formula is used to calculate the optimal obstacle avoidance path, taking into account the trade-off between path cost and safety risk value. The path cost function includes cost considerations such as flight time, fuel consumption, and aircraft wear, while the safety risk value is calculated based on the safety risk assessment algorithm. The trade-off coefficients λ and μ are dynamically adjusted according to the current state of the aircraft and the remaining flight time to achieve a balance between path cost and safety risk.

[0024] The path cost function The specific form is: ;in, Indicates the path Flight time on Indicates the path Fuel consumption on Indicates the path The degree of wear and tear that may be caused to the aircraft, and is the trade-off coefficient.

[0025] The data processing and analysis unit uses the following formula to perform fusion analysis on multi-source data: ;in, Represents the comprehensive data index after fusion, Indicates the number of data sources. Indicates The weight of the data source, Indicates The actual data value of the data source, and Represent the mean and standard deviation of the data source respectively. This formula is used to perform fusion analysis on multi-source data, which improves the accuracy and reliability of the data. The data from different data sources are fused through standardization and weighted fusion to form comprehensive data indicators, which provide data support for subsequent safety risk assessment and obstacle avoidance strategy generation.

[0026] The trade-off coefficient and The method for determining is as follows: ; ;in, Indicates the maximum safe speed of the aircraft. Indicates the current flight speed. Indicates the remaining flight time. represents the total flight time, and To adjust the coefficients, these two formulas are used to determine the trade-off coefficients λ and μ, so that the obstacle avoidance path optimization algorithm can be dynamically adjusted according to the current state of the aircraft and the remaining flight time; by adjusting these two coefficients, a balance between path cost and safety risk can be achieved while ensuring safety.

[0027] In summary,: The present invention utilizes a variety of sensor data for comprehensive analysis, which is not limited to traditional position information, but also includes speed, altitude, attitude parameters, and obstacle locations, meteorological conditions, and electromagnetic interference information in the environment; this fusion analysis of multi-source data improves the system's overall perception of the flight environment; through standardization and weighted fusion, the accuracy and reliability of the data are ensured, providing a solid data foundation for safety risk assessment and obstacle avoidance strategies.

[0028] The present invention adopts a flexible safety risk assessment algorithm, which dynamically calculates the comprehensive safety risk value by considering multiple threat factors and their weights. This method can reflect changes in the flight environment in real time, improving the real-time and accuracy of safety assessment. The diversity of risk functions (linear, nonlinear or machine learning-based models) enables the system to adapt to different application scenarios and threat characteristics.

[0029] The present invention introduces a dynamic adjustment mechanism for the warning threshold, which dynamically sets the warning threshold according to the specific flight mission, aircraft performance and environmental conditions, thereby improving the applicability and flexibility of the system; the obstacle avoidance strategy optimization formula combines the two aspects of path cost and safety risk, and through the dynamic adjustment of the trade-off coefficient, it achieves the optimization of path selection while ensuring safety.

[0030] The present invention proposes a method for adjusting the trade-off coefficient based on the current state of the aircraft and the remaining flight time, so that the obstacle avoidance path optimization can adapt to the real-time changing flight conditions; this dynamic adjustment mechanism ensures that the system can maintain optimal performance in different flight phases, taking into account both safety and economy.

[0031] In path optimization, the present invention not only considers safety risks, but also multiple factors such as flight time, fuel consumption and aircraft wear; through the comprehensive path cost function, the system can provide the aircraft with a more economical and efficient obstacle avoidance path selection.

[0032] In summary, this technical solution has greatly improved the safety assurance capability of low-altitude aircraft through deep fusion analysis of multi-source data, flexible risk assessment algorithms, intelligent early warning mechanisms and comprehensive path optimization strategies.

[0033] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A low-altitude flight safety intelligent sensor, characterized in that: include: The data acquisition unit is used to collect multi-source data in the low-altitude flight environment, including the position, speed, altitude, attitude parameters of the aircraft, as well as the location of obstacles, meteorological conditions, and electromagnetic interference information in the environment; A data processing and analysis unit, which performs preprocessing, feature extraction and fusion analysis on the data acquired by the data acquisition unit to identify potential security threats; A safety risk assessment module, which calculates a flight safety risk value through a predefined safety risk assessment algorithm based on the output of the data processing and analysis unit; The warning and obstacle avoidance strategy generation unit automatically triggers a warning signal when the safety risk value exceeds the preset threshold, and generates obstacle avoidance or safe flight suggestions based on preset rules or algorithms; Communication interface, used to transmit warning signals, obstacle avoidance strategies or safe flight suggestions to low-altitude aircraft control systems or ground monitoring stations in real time.

2. The low-altitude flight safety intelligent sensor according to claim 1, characterized in that: The security risk assessment algorithm uses the following formula to calculate the security risk value: ;in, represents the security risk value, Indicates the number of security threat factors considered, Indicates The weight of each threat factor, Indicates Threat factors are quantified according to their The risk function of the evaluation is satisfied .

3. A low-altitude flight safety intelligent sensor according to claim 2, characterized in that: The risk function The specific form is: ;in, , and It is a coefficient determined according to specific threat factors.

4. A low-altitude flight safety intelligent sensor according to claim 3, characterized in that: The early warning and obstacle avoidance strategy generation unit comprises: The warning threshold setting module is used to dynamically adjust the warning threshold according to flight mission requirements, aircraft performance and environmental conditions; The obstacle avoidance strategy optimization module uses the following formula to calculate the optimal obstacle avoidance path: ;in, represents the optimal obstacle avoidance path, represents the set of all possible obstacle avoidance paths, represents the path cost function, represents the safety risk value on the path, and is a trade-off coefficient used to adjust the relative importance of path cost and safety risk.

5. A low-altitude flight safety intelligent sensor according to claim 4, characterized in that: The path cost function The specific form is: ;in, Indicates the path Flight time on Indicates the path Fuel consumption on Indicates the path The degree of wear and tear that may be caused to the aircraft, and is the trade-off coefficient.

6. A low-altitude flight safety intelligent sensor according to claim 5, characterized in that: The data processing and analysis unit uses the following formula to perform fusion analysis on multi-source data: ;in, Represents the comprehensive data index after fusion, Indicates the number of data sources. Indicates The weight of the data source, Indicates The actual data value of the data source, and Respectively represent The mean and standard deviation of the data sources.

7. A low-altitude flight safety intelligent sensor according to claim 6, characterized in that: The trade-off coefficient and The method for determining is as follows: ; ;in, Indicates the maximum safe speed of the aircraft. Indicates the current flight speed. Indicates the remaining flight time. represents the total flight time, and is the adjustment factor.

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