A smart sensor for low-altitude flight safety

Abstract

This invention discloses an intelligent sensor for low-altitude flight safety, comprising: 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 collects multi-source data from the low-altitude flight environment; the data processing and analysis unit preprocesses, extracts features, and performs fusion analysis on the data acquired by the data acquisition unit; the safety risk assessment module generates the data 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; this invention demonstrates 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 in aviation technology.

Description

Technical Field

[0001] This invention relates to the field of intelligent sensor technology, specifically to an intelligent sensor for ensuring low-altitude flight safety. Background Technology

[0002] In the aviation field, safe flight and path optimization for aircraft have always been key research areas. With advancements in technology and improvements in aircraft performance, the need for safety risk assessment and obstacle avoidance path optimization during flight is becoming increasingly urgent.

[0003] Traditional aircraft safety risk assessment methods rely primarily on pilots' personal experience and the aircraft's mechanical performance parameters. This approach is not only highly subjective but also struggles to comprehensively and accurately assess various safety risks during flight. Furthermore, in obstacle avoidance path optimization, traditional algorithms often only consider path costs (such as flight time and fuel consumption) while neglecting the impact of safety risks on path selection. This could potentially lead to significant safety hazards for the aircraft during flight.

[0004] To address these issues, researchers have recently begun exploring safety risk assessment methods based on multi-source data fusion and obstacle avoidance path optimization algorithms that comprehensively consider path cost and safety risk. However, existing methods still have some shortcomings. For example, effectively handling data differences and conflicts between different data sources during multi-source data fusion to improve data accuracy and reliability is a problem that urgently needs to be solved. Furthermore, in obstacle avoidance path optimization algorithms, dynamically adjusting the weights of path cost and safety risk based on the aircraft's current state and remaining flight time to achieve a balance between the two is also a challenging task.

[0005] Therefore, this study proposes a novel method for determining trade-off coefficients, and a safety risk assessment and obstacle avoidance path optimization system based on this method. This system comprehensively considers the aircraft's current speed, remaining flight time, and various safety threat factors, achieving a balance between path cost and safety risk by dynamically adjusting the trade-off coefficients. Simultaneously, the system employs multi-source data fusion analysis technology, improving the accuracy and reliability of the data and providing strong data support for subsequent safety risk assessment and obstacle avoidance strategy generation. Summary of the Invention

[0006] The purpose of this invention is to provide a smart sensor for low-altitude flight safety, in order to solve the problems mentioned in the background art and improve the safe flight performance and path optimization capabilities of aircraft.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a smart sensor for low-altitude flight safety, characterized in that it comprises:

[0008] The data acquisition unit is used to collect multi-source data in the low-altitude flight environment, including the aircraft's position, speed, altitude, attitude parameters, as well as the location of obstacles, weather conditions, and electromagnetic interference information in the environment.

[0009] The data processing and analysis unit preprocesses, extracts features, and performs fusion analysis on the data acquired by the data acquisition unit to identify potential security threats.

[0010] The safety risk assessment module calculates flight safety risk values ​​based on the output of the data processing and analysis unit using a predefined safety risk assessment algorithm.

[0011] The warning and obstacle avoidance strategy generation unit automatically triggers a warning signal when the safety risk value exceeds a preset threshold, and generates obstacle avoidance or safe flight suggestions based on preset rules or algorithms.

[0012] The communication interface is used to transmit warning signals, obstacle avoidance strategies, or safe flight recommendations to the low-altitude aircraft control system or ground monitoring station in real time.

[0013] Preferably, the security risk assessment algorithm calculates the security risk value using the following formula: ;in, Indicates the safety risk value. This indicates the number of security threat factors considered. Indicates the first Weight of each threat factor , indicating the first Each threat factor is assessed using a risk function based on its quantified value, and satisfies foot.

[0014] Preferably, the risk function The specific form is :;in, , and A coefficient determined based on the specific threat factor.

[0015] Preferably, the early warning and obstacle avoidance strategy generation unit includes:

[0016] The warning threshold setting module is used to dynamically adjust the warning threshold according to flight mission requirements, aircraft performance, and environmental conditions;

[0017] The obstacle avoidance strategy optimization module uses the following formula to calculate the optimal obstacle avoidance path: ;in , representing the optimal obstacle avoidance path. Represents the set of all possible obstacle avoidance paths, table Show the path cost function, This indicates the security risk value along the path. and It is a trade-off factor used to adjust the relative importance of path costs and safety risks.

[0018] Preferably, the path cost function The specific form is as follows: ;in, Representing a path Flight time on Representing a path Fuel consumption on Representing a path The extent of wear and tear that may occur on the aircraft , The sum is the weighting factor.

[0019] Preferably, the data processing and analysis unit uses the following formula to perform fusion analysis on multi-source data: ;in, This represents the integrated data indicators after merging. Indicates the number of data sources. Indicates the first The weight of each data source, Indicates the first The actual data values ​​from each data source and They represent the first The mean and standard deviation of each data source.

[0020] Preferably, the tradeoff 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. Indicates the total flight time. and This is for adjusting the coefficient.

[0021] The intelligent sensor for low-altitude flight safety proposed in this invention has the following advantages:

[0022] 1. By comprehensively considering multiple safety threat factors and combining the weights and quantification values ​​of each factor for comprehensive evaluation, this invention can more accurately reflect the safety risk status of an aircraft during flight. In addition, by adopting multi-source data fusion analysis technology, information from different data sources is effectively integrated, improving the accuracy and reliability of the data, thereby further enhancing the accuracy of safety risk assessment.

[0023] 2. This invention proposes a new method for determining the trade-off coefficients. This method can dynamically adjust the weights of path cost and safety risk based on the current state and remaining flight time of the aircraft. During the obstacle avoidance path optimization process, the system can fully consider path cost while ensuring safety, and achieve an effective balance between the two, thereby improving the overall flight performance of the aircraft.

[0024] 3. By applying the obstacle avoidance path optimization algorithm of this invention, the aircraft can quickly and accurately find the optimal obstacle avoidance path in complex environments, effectively avoiding collisions with obstacles; this not only improves the aircraft's autonomous obstacle avoidance capability, but also reduces the workload of pilots and enhances flight safety.

[0025] 4. Because this invention fully considers path costs, including flight time and fuel consumption, during obstacle avoidance path optimization, it can select more economical and efficient flight paths while ensuring safety. This helps reduce aircraft fuel consumption, improve flight efficiency, and reduce operating costs.

[0026] In summary, this invention demonstrates 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 in aviation technology. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the principle of the present invention;

[0028] Figure 2 This is a schematic diagram of the early warning and obstacle avoidance strategy generation unit of the present invention. Detailed Implementation

[0029] 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.

[0030] For examples, please refer to Figure 1-2 The present invention provides a technical solution: a smart sensor for low-altitude flight safety, comprising: 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;

[0031] Data acquisition unit: responsible for collecting multi-source data in the low-altitude flight environment; including the aircraft's position 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.; this data is the basis for subsequent analysis and decision-making, ensuring that the system can have a comprehensive understanding of the aircraft and its surrounding environment;

[0032] Data processing and analysis unit: performs preprocessing, feature extraction, and fusion analysis on the data acquired by the data acquisition unit; preprocessing includes data cleaning and noise reduction; feature extraction extracts key feature parameters from the raw data; fusion analysis integrates 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, providing reliable data support for subsequent risk assessment.

[0033] Safety Risk Assessment Module: Based on the output of the data processing and analysis unit, it calculates flight safety risk values ​​using predefined safety risk assessment algorithms; using specific algorithms (such as weighted risk assessment formulas), it considers the weights and quantification values ​​of different threat factors to comprehensively assess the safety of the current flight status; it can assess flight risks in real time, ensuring that the system can detect potential dangers in a timely manner;

[0034] When the safety risk value exceeds a preset threshold, the early warning and obstacle avoidance strategy generation unit automatically triggers an early warning signal and generates obstacle avoidance or safe flight suggestions. According to 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 warnings before danger occurs and suggest specific countermeasures, thereby improving flight safety.

[0035] Communication interface: Used to transmit early warning signals, obstacle avoidance strategies, or safe flight advice 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 advice in a timely manner; the communication interface ensures timely information transmission, enabling the aircraft to respond quickly to safety threats, and the ground monitoring station can also keep track of the aircraft's status at any time.

[0036] The security risk assessment algorithm uses the following formula to calculate the security risk value: ;in, Indicates the safety risk value. This indicates the number of security threat factors considered. Indicates the first The weight of each threat factor Indicates the first Each threat factor is determined by its quantification value. The risk function is evaluated and satisfies... The risk function The specific form is as follows: ;in, , and The coefficients are determined based on specific threat factors. This formula is used to calculate the comprehensive security risk value, taking into account multiple security threat factors and conducting a comprehensive assessment based on the weights and quantification values ​​of each factor. The weights reflect the importance of each threat factor to the security risk, while the risk function is defined according to the characteristics of the specific threat factor and can be a linear, nonlinear, or prediction function based on a machine learning model.

[0037] The early warning and obstacle avoidance strategy generation unit includes: an early warning threshold setting module and an obstacle avoidance strategy optimization module; the early warning threshold setting module is used to dynamically adjust the early warning threshold according to flight mission requirements, aircraft performance, and environmental conditions; the obstacle avoidance strategy optimization module calculates the optimal obstacle avoidance path using the following formula: ;in, This represents the optimal obstacle avoidance path. Represents the set of all possible obstacle avoidance paths. Represents the path cost function. This indicates the security risk value along the path. and The trade-off coefficients are used to adjust the relative importance of path cost and safety risk. This formula is used to calculate the optimal obstacle avoidance path, which comprehensively considers the trade-off between path cost and safety risk value. The path cost function includes cost considerations from multiple aspects 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.

[0038] The path cost function The specific form is as follows: ;in, Representing a path Flight time on Representing a path Fuel consumption on Representing a path The extent of wear and tear that may occur on the aircraft and This is a weighting factor.

[0039] The data processing and analysis unit uses the following formula to fuse and analyze multi-source data: ;in, This represents the integrated data indicators after merging. Indicates the number of data sources. Indicates the first The weight of each data source, Indicates the first The actual data values ​​from each data source and Let represent the mean and standard deviation of the i-th data source, respectively. This formula is used to perform fusion analysis on multi-source data, improving the accuracy and reliability of the data. Data from different data sources are fused through standardization and weighted fusion to form comprehensive data indicators, providing data support for subsequent security risk assessment and obstacle avoidance strategy generation.

[0040] The tradeoff 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. Indicates the total flight time. and To adjust the coefficients, these two formulas are used to determine the tradeoff coefficients λ and μ, enabling the obstacle avoidance path optimization algorithm to dynamically adjust based on the aircraft's current state and remaining flight time. By adjusting these two coefficients, a balance between path cost and safety risk can be achieved while ensuring safety.

[0041] In summary,:

[0042] This invention utilizes comprehensive analysis of data from multiple sensors, not limited to traditional position information, but also including speed, altitude, attitude parameters, as well as information on obstacle locations, weather conditions, and electromagnetic interference in the environment. This multi-source data fusion analysis 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.

[0043] This invention employs a flexible safety risk assessment algorithm that dynamically calculates a 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 performance and accuracy of safety assessments. The diversity of risk functions (linear, nonlinear, or machine learning-based models) enables the system to adapt to different application scenarios and threat characteristics.

[0044] This invention introduces a dynamic adjustment mechanism for the warning threshold, which dynamically sets the warning threshold based on 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 path cost and safety risk, and through the dynamic adjustment of the trade-off coefficient, it achieves optimized path selection while ensuring safety.

[0045] This invention proposes a trade-off adjustment method based on the current state of the aircraft and the remaining flight time, which enables obstacle avoidance path optimization to adapt to 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.

[0046] In path optimization, this invention considers not only safety risks, but also multiple factors such as flight time, fuel consumption, and aircraft wear; by integrating the path cost function, the system can provide the aircraft with a more economical and efficient obstacle avoidance path selection.

[0047] In summary, this technical solution greatly enhances the safety assurance capabilities of low-altitude aircraft through in-depth fusion analysis of multi-source data, flexible risk assessment algorithms, intelligent early warning mechanisms, and comprehensive path optimization strategies.

[0048] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart sensor for low-altitude flight safety, characterized in that, include: The data acquisition unit is used to collect multi-source data in the low-altitude flight environment, including the aircraft's position, speed, altitude, attitude parameters, as well as the location of obstacles, weather conditions, and electromagnetic interference information in the environment. The data processing and analysis unit preprocesses, extracts features, and performs fusion analysis on the data acquired by the data acquisition unit to identify potential security threats. The safety risk assessment module calculates flight safety risk values ​​based on the output of the data processing and analysis unit using a predefined safety risk assessment algorithm. The warning and obstacle avoidance strategy generation unit automatically triggers a warning signal when the safety risk value exceeds a preset threshold, and generates obstacle avoidance or safe flight suggestions based on preset rules or algorithms. The communication interface is used to transmit warning signals, obstacle avoidance strategies, or safe flight recommendations to the low-altitude aircraft control system or ground monitoring station in real time. The security risk assessment algorithm uses the following formula to calculate the security risk value: ;in, Indicates the safety risk value. This indicates the number of security threat factors considered. Indicates the first The weight of each threat factor Indicates the first Each threat factor is determined by its quantification value. The risk function being evaluated, and satisfying... ; The risk function The specific form is as follows: ;in, , and A coefficient determined based on the specific threat factor.

2. The intelligent sensor for low-altitude flight safety as described in claim 1, characterized in that, The early warning and obstacle avoidance strategy generation 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, This represents the optimal obstacle avoidance path. Represents the set of all possible obstacle avoidance paths. Represents the path cost function. This indicates the security risk value along the path. and It is a trade-off factor used to adjust the relative importance of path costs and safety risks.

3. The intelligent sensor for low-altitude flight safety as described in claim 2, characterized in that, The path cost function The specific form is as follows: ;in, Representing a path Flight time on Representing a path Fuel consumption on Representing a path The extent of wear and tear that may occur on the aircraft and This is a weighting factor.

4. The intelligent sensor for low-altitude flight safety as described in claim 3, characterized in that, The data processing and analysis unit uses the following formula to fuse and analyze multi-source data: ;in, This represents the integrated data indicators after merging. Indicates the number of data sources. Indicates the first The weight of each data source, Indicates the first The actual data values ​​from each data source and They represent the first The mean and standard deviation of each data source.

5. The intelligent sensor for low-altitude flight safety as described in claim 4, characterized in that, The tradeoff 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. Indicates the total flight time. and This is for adjusting the coefficient.

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