Real-time Early Warning Method and System for Abnormal Physiological States Based on Key Flight Events

Abstract

This invention relates to a real-time early warning method and system for abnormal physiological states based on critical events during flight, belonging to the field of aviation medical diagnosis and identification. It addresses the problems of insufficient automated identification of critical events and the lack of real-time early warning of pilot physiological states in existing simulated flight training. The method includes acquiring flight parameter data and physiological parameter data of the pilot during simulated flight; acquiring the pilot's resting baseline physiological parameter data; calculating energy quantification indicators based on the flight parameter data during simulated flight; identifying the types of critical events during simulated flight based on the flight parameter data and energy quantification indicators; and identifying the pilot's physiological state based on the physiological parameter data, resting baseline physiological parameter data, and types of critical events during simulated flight, and issuing real-time early warnings if abnormalities are detected. This achieves real-time early warning of abnormal physiological states of pilots in the air.

Description

Technical Field

[0001] This invention relates to the field of aviation medical diagnosis, identification and electronic data digital processing technology, and in particular to a method and system for real-time early warning of abnormal physiological states based on key events during flight. Background Technology

[0002] In the field of aerospace biomedical engineering, the diagnosis of pilots' physiological states is crucial for flight safety. During flight, pilots face unexpected situations such as severe weather or special flight operations, causing drastic changes in their physical and mental state, often resulting in tension and anxiety. Due to differences in experience and emotional regulation abilities, these emotions can impact flight training and safety to varying degrees. A moderate emotional state can improve focus and stimulate potential; excessive emotional stress, however, can lead to confused thinking, difficulty in decision-making, and an increased risk of flight accidents.

[0003] Current real-time flight anomaly warning systems involve the real-time transmission of physiological data. Existing methods typically focus on recording electronic flight data and post-event digital processing and analysis, lacking real-time processing and analysis capabilities. They cannot dynamically assess changes based on real-time environmental and aircraft energy variations, resulting in insufficient accuracy and reliability of warnings. Existing methods also have limited capabilities in data fusion and multimodal analysis, making it difficult to fully utilize the synergistic effect of flight parameters and physiological parameters acquired through wearable smart devices. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide a method and system for real-time early warning of abnormal physiological states based on critical events during flight, in order to solve the technical problems of insufficient automatic identification of critical events during flight and lack of real-time early warning of pilot physiological states.

[0005] The objective of this invention is mainly achieved through the following technical solutions:

[0006] This invention provides a real-time early warning method for abnormal physiological states based on key events during flight, comprising the following steps:

[0007] Acquire flight parameter data and physiological parameter data of pilots during simulated flight; acquire resting baseline physiological parameter data of pilots;

[0008] Based on the flight parameter data during the simulated flight process, the dynamic energy quantification index during the simulated flight process is calculated;

[0009] Based on flight parameter data and dynamic energy quantification indicators during the simulated flight process, the types of key events during the simulated flight process are identified.

[0010] Based on the physiological parameter data during the simulated flight, the resting baseline physiological parameter data, and the types of key events during the simulated flight, the pilot's physiological state is identified, and real-time warnings are issued if any abnormalities are found.

[0011] Furthermore, the flight parameter data includes flight speed, flight altitude, normal overload, yaw angle, pitch angle, roll angle, flight acceleration, rate of change of yaw angle, rate of change of pitch angle, and rate of change of roll angle; acquiring flight parameter data during pilot simulated flight includes:

[0012] The flight data acquisition device collects flight speed, flight altitude, normal overload, heading angle, pitch angle, roll angle, and flight acceleration.

[0013] Based on the heading angle, pitch angle, and roll angle, the rates of change of heading angle, pitch angle, and roll angle are calculated.

[0014] Furthermore, the dynamic energy quantification indicators during the simulated flight process are calculated, including the kinetic energy, potential energy, total energy, rate of energy change, and dynamic energy index during the flight process; among which,

[0015] Based on the current flight speed and the current mass of the aircraft, the kinetic energy at the current moment is calculated.

[0016] Based on the aircraft's current mass and current flight altitude, the potential energy at the current moment is calculated.

[0017] Based on the kinetic energy and potential energy at the current moment, the total energy at the current moment is calculated, and the rate of change of energy is obtained based on the total energy at the current moment.

[0018] Based on the total energy at the current moment during the simulated flight, the maximum total energy during the flight, and the minimum energy during the taxiing phase, the dynamic energy index at the current moment during the simulated flight is calculated.

[0019] Furthermore, the dynamic energy index EI at the current moment during the simulated flight process t The calculation is as follows:

[0020]

[0021] Among them, E total,t E represents the total energy at the current time t. min The minimum energy required for the gliding phase; m fuel,t m represents the remaining fuel mass at the current moment. payload,t E represents the remaining load mass at the current moment. max (m fuel,t ,m payload,t ) represents the maximum total energy during flight; m tV represents the current mass of the aircraft. t The simulated flight speed at the current moment; g is the acceleration due to gravity; H t The simulated flight altitude at the current moment; V 滑行_min m0 represents the minimum speed during taxiing; m0 represents the inherent mass of the aircraft.

[0022] Furthermore, based on flight parameter data and energy quantification indicators during the simulated flight process, the types of key events during the simulated flight process are identified, including:

[0023] If the flight speed, pitch angle, roll angle, dynamic energy index, and energy change rate are all within the preset threshold range of taxiing critical event, climb critical event, or cruise critical event, then they are identified as taxiing critical event, climb critical event, or cruise critical event.

[0024] If the flight speed, flight altitude, normal overload, pitch angle, roll angle, flight acceleration, dynamic energy index, and energy change rate are all within the preset threshold range of takeoff critical events, then they are identified as takeoff critical events.

[0025] If the normal overload, flight altitude, rate of change of heading angle, rate of change of pitch angle, rate of change of roll angle, dynamic energy index, and rate of change of energy are all within the preset threshold range of attack critical event or evasion critical event, then it is identified as attack critical event or evasion critical event.

[0026] If the flight speed, flight altitude, pitch angle, roll angle, dynamic energy index, and energy change rate are all within the preset threshold range of a critical descent event, then it is identified as a critical descent event.

[0027] If the flight speed, flight altitude, pitch angle, flight acceleration, dynamic energy index, and energy change rate are all within the preset threshold range of landing critical events, then it is identified as a landing critical event.

[0028] Furthermore, the acquisition of pilot resting baseline physiological parameter data includes:

[0029] Based on the pilot's wearable physiological monitoring device, the pilot's blood oxygen, heart rate and respiratory rate are collected during a preset period in the pilot's resting state;

[0030] Based on the pilot's blood oxygen, heart rate, and respiratory rate during a preset period, the mean blood oxygen, heart rate, and respiratory rate during rest are calculated and used as the pilot's baseline physiological parameter data at rest.

[0031] Furthermore, based on the pilot's wearable physiological monitoring device, physiological parameter data including blood oxygen, heart rate and respiratory rate are acquired in real time during the pilot's simulated flight.

[0032] Based on real-time acquired blood oxygen, heart rate, and respiratory rate, as well as the pilot's resting baseline physiological parameter data, the rate of change of blood oxygen, heart rate, and respiratory rate were calculated.

[0033] The abnormality of a pilot's physiological state during a critical event is identified based on the changes in blood oxygen saturation, heart rate, and respiratory rate.

[0034] Furthermore, based on the type of critical event, if the blood oxygen change rate, heart rate change rate, and respiratory rate change rate are all within the preset threshold ranges for blood oxygen change rate, heart rate change rate, and respiratory rate change rate corresponding to the type of critical event, then the pilot's physiological state is normal; otherwise, it is abnormal.

[0035] Furthermore, if the pilot's physiological state is abnormal, voice and visual alarms are triggered, and automatic flight takeover is initiated.

[0036] This invention provides a real-time early warning system for abnormal physiological states based on critical events during flight, comprising:

[0037] The multimodal data acquisition module is used to acquire flight parameter data and physiological parameter data of the pilot during simulated flight; and to acquire the pilot's resting baseline physiological parameter data.

[0038] The dynamic energy analysis module is used to calculate the energy quantification index during the simulated flight process based on the flight parameter data during the simulated flight process;

[0039] The critical flight event identification module is used to identify the types of critical events during the simulated flight process based on flight parameter data and energy quantification indicators.

[0040] The physiological state recognition module is used to identify the pilot's physiological state based on the physiological parameter data during the simulated flight, the resting baseline physiological parameter data, and the types of key events during the simulated flight, and to issue a real-time warning if there is an abnormality.

[0041] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0042] 1. This invention's dynamic energy index achieves precise state quantification. By calculating kinetic energy, potential energy, total energy, energy change rate, and dynamic energy index in real time during simulated flight, combined with dynamic fuel consumption compensation, it overcomes the limitations of traditional static thresholds and accurately quantifies the aircraft's energy change trends (such as energy storage before an attack or violent fluctuations during evasion). The dynamic energy index reflects the changes in the aircraft's energy state during simulated flight. This invention can dynamically assess the pilot's physiological load state based on real-time environmental changes and aircraft performance, thereby providing more accurate early warnings of abnormal physiological states.

[0043] 2. By processing and analyzing flight parameters and physiological parameters in real time, this invention can more accurately and automatically identify key events in flight and assess the pilot's physiological state accordingly, thereby improving the accuracy and reliability of the early warning system.

[0044] 3. This invention utilizes the synergistic effect of flight parameters and physiological parameters during flight to perform multimodal data processing, comprehensively analyze the pilot's physiological state, and provide real-time monitoring and early warning of the pilot's physiological state throughout the flight process;

[0045] 4. When the present invention detects an abnormal physiological state of the pilot, it triggers a voice or visual alarm in real time and performs automatic flight takeover when necessary, which can minimize safety risks and has important value for assisting flight training and ensuring flight safety.

[0046] 5. This invention can adapt to different flight conditions, including severe weather and special flight missions, thereby improving the effectiveness of flight training and ensuring flight safety.

[0047] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0048] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0049] Figure 1 This is a flowchart of a real-time early warning method for abnormal physiological states based on key events during flight, as described in an embodiment of the present invention.

[0050] Figure 2 This is a schematic diagram of a real-time early warning system module for abnormal physiological states based on key events during flight, as described in an embodiment of the present invention. Detailed Implementation

[0051] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0052] Example 1

[0053] A specific embodiment of the present invention discloses a real-time early warning method for abnormal physiological states based on key events during flight, such as... Figure 1 As shown, it includes the following steps:

[0054] Step S1: Obtain flight parameter data and physiological parameter data of the pilot during the simulated flight; obtain the pilot's resting baseline physiological parameter data;

[0055] Step S2: Based on the flight parameter data during the simulated flight process, calculate the dynamic energy quantification index during the simulated flight process;

[0056] Step S3: Identify the types of key events during the simulated flight process based on flight parameter data and dynamic energy quantification indicators;

[0057] Step S4: Based on the physiological parameter data during the simulated flight, the resting baseline physiological parameter data, and the types of key events during the simulated flight, identify the pilot's physiological state and issue a real-time warning if any abnormality is found.

[0058] Step S1 includes steps S11-S12.

[0059] Step S11: Obtain flight parameter data and physiological parameter data during the pilot's simulated flight.

[0060] The flight parameter data includes flight speed, flight altitude, normal overload, yaw angle, pitch angle, roll angle, flight acceleration, rate of change of yaw angle, rate of change of pitch angle, and rate of change of roll angle; the acquisition of flight parameter data during pilot simulated flight includes:

[0061] The flight data acquisition device collects flight speed, flight altitude, normal overload, heading angle, pitch angle, roll angle, and flight acceleration.

[0062] Based on the heading angle, pitch angle, and roll angle, the rates of change of heading angle, pitch angle, and roll angle are calculated.

[0063] Flight parameter data is acquired through the data acquisition device built into the simulator.

[0064] Based on the pilot's wearable physiological monitoring device (wearable smart device), real-time physiological parameter data including blood oxygen, heart rate and respiratory rate are obtained during the pilot's simulated flight.

[0065] This wearable physiological monitoring device includes an electrocardiogram (ECG) sensor, a respiration sensor, and a blood oxygen sensor. Worn on the pilot's head, it enables human-computer interaction and acquires electronic data for subsequent processing. All three sensors are intelligent.

[0066] Blood oxygen monitoring is achieved using a blood oxygen sensor. For example, a PPG (photoplethysmography) sensor is used, located on the helmet's forehead band and integrated into the temple area of ​​a pilot's flight helmet. Brain-computer interaction is used to measure blood oxygen levels (i.e., blood oxygen saturation).

[0067] Heart rate monitoring uses an electrocardiogram sensor embedded in an anti-G flight suit (chest position) to obtain heart rate values.

[0068] Respiratory rate monitoring uses a respiratory sensor integrated into the flight suit belt to obtain the respiratory rate.

[0069] The acquired flight parameter data and physiological parameter data are timestamped.

[0070] Step S12: Obtain the pilot's resting baseline physiological parameter data.

[0071] The acquisition of pilot resting baseline physiological parameter data includes:

[0072] Based on the pilot's wearable physiological monitoring device, the pilot's blood oxygen, heart rate and respiratory rate are collected during a preset period in the pilot's resting state;

[0073] Based on the pilot's blood oxygen, heart rate, and respiratory rate during a preset period, the mean blood oxygen, heart rate, and respiratory rate during rest are calculated and used as the pilot's baseline physiological parameter data at rest.

[0074] Based on wearable physiological monitoring devices, the pilot's resting baseline physiological parameters are obtained under normal conditions, i.e., when the pilot is at rest.

[0075] For example, physiological parameter data is collected every hour under normal conditions, calculating the average heart rate, average respiratory rate, and average blood oxygen saturation under normal conditions. The specific duration of collecting physiological parameter data under normal conditions will vary depending on the specific application requirements.

[0076] The mean blood oxygen saturation (SP0), mean heart rate (HR0), and mean respiratory rate (RR0) under normal conditions were calculated and used as the baseline physiological parameters for pilots at rest.

[0077] The purpose of step S1 is to simultaneously acquire the pilot's real-time flight parameter data, physiological parameter data, and resting baseline physiological data through the flight data acquisition device and wearable physiological monitoring device, providing a multimodal data foundation for subsequent key event identification and real-time early warning of abnormal physiological states of the pilot.

[0078] Step S2, specifically.

[0079] Based on flight parameter data during simulated flight, dynamic energy quantification indicators are calculated during simulated flight.

[0080] Calculate dynamic energy quantification indicators during simulated flight, including kinetic energy, potential energy, total energy, rate of energy change, and dynamic energy index; among which,

[0081] Based on the current flight speed and the current mass of the aircraft, the kinetic energy at the current moment is calculated.

[0082] Based on the aircraft's current mass and current flight altitude, the potential energy at the current moment is calculated.

[0083] Based on the kinetic energy and potential energy at the current moment, the total energy at the current moment is calculated, and the rate of change of energy is obtained based on the total energy at the current moment.

[0084] Based on the total energy at the current moment during the simulated flight, the maximum total energy during the flight, and the minimum energy during the taxiing phase, the dynamic energy index at the current moment during the simulated flight is calculated.

[0085] Based on real-time acquired flight speed V t Flight altitude H t Calculate the dynamic energy quantification index during the simulated flight process.

[0086] The kinetic energy at time t during the simulated flight is as follows:

[0087]

[0088] The potential energy at time t during the simulated flight is as follows:

[0089] E p,t =m t gH t Formula (2)

[0090] The total energy at time t during the simulated flight is as follows:

[0091] E total,t =E k,t +E p,t Formula (3)

[0092] Rate of change of energy during simulated flight as follows:

[0093]

[0094] The dynamic energy index EI at the current moment during the simulated flight process. t The calculation is as follows:

[0095]

[0096] Among them, E total,t E represents the total energy at the current time t. min The minimum energy required for the gliding phase; m fuel,t m represents the remaining fuel mass at the current moment. payload,t E represents the remaining load mass at the current moment. max (m fuel,t ,m payload,t ) represents the maximum total energy during flight; m t V represents the current mass of the aircraft. t The simulated flight speed at the current moment; g is the acceleration due to gravity; H t The simulated flight altitude at the current moment; V 滑行_min m0 represents the minimum speed during taxiing; m0 represents the inherent mass of the aircraft.

[0097] The minimum energy required for the gliding phase is as follows:

[0098]

[0099] For the gliding phase, H 地面 ≈0, therefore,

[0100] The remaining fuel mass at the current moment is calculated as follows:

[0101]

[0102] Where, m fruel,initial The initial fuel mass is the total amount of fuel added before flight, which is set through ground crew records or onboard system initialization; the integral term flow sensor outputs the instantaneous fuel consumption rate Rate(t) at a high frequency (e.g., 10Hz), in kg / s, and the total consumption is obtained by integrating over time.

[0103] The fuel mass flow rate of the engine at time t is measured in real time by a sensor. For example, Rate(t) is output at a frequency of 10 Hz by a fuel flow sensor (such as a Coriolis mass flow meter).

[0104] Real-time updates, for example, m updates per second. fruel,tIn practical applications, it can be modified according to specific needs.

[0105] The cumulative consumption is calculated using either the trapezoidal or rectangular method, as follows:

[0106]

[0107] Where Δt = 0.1s (10Hz sampling), Rate(t) i Rate(t) i-1 ) are respectively t i and t i-1 The instantaneous fuel consumption rate at time n; n is the number of time sampling points.

[0108] For the remaining load mass m at the current moment payload,t For example, cargo hold weight sensors are used to obtain the weight.

[0109] Flight speed is measured in km / h, flight altitude in meters (m), and flight acceleration in meters per second (m / s²). 2 .

[0110] For the simulated flight altitude H at the current time t t The unit is meters. In practical applications, Converting the height unit from meters to kilometers makes the calculation results more reasonable, thus avoiding excessively large or small height values.

[0111] Step S2 is used to dynamically calculate kinetic energy, potential energy, total energy, energy change rate, and dynamic energy index based on real-time flight parameter data. The dynamic energy index is used to quantify the flight state, providing energy dimension features to support the identification of key events in step S3.

[0112] Step S3, specifically.

[0113] Based on flight parameter data and energy quantification indicators during simulated flight, the types of key events during the simulated flight process are identified, including:

[0114] If the flight speed, pitch angle, roll angle, dynamic energy index, and energy change rate are all within the preset threshold range of taxiing critical event, climb critical event, or cruise critical event, then they are identified as taxiing critical event, climb critical event, or cruise critical event.

[0115] If the flight speed, flight altitude, normal overload, pitch angle, roll angle, flight acceleration, dynamic energy index, and energy change rate are all within the preset threshold range of takeoff critical events, then they are identified as takeoff critical events.

[0116] If the normal overload, flight altitude, rate of change of heading angle, rate of change of pitch angle, rate of change of roll angle, dynamic energy index, and rate of change of energy are all within the preset threshold range of attack critical event or evasion critical event, then it is identified as attack critical event or evasion critical event.

[0117] If the flight speed, flight altitude, pitch angle, roll angle, dynamic energy index, and energy change rate are all within the preset threshold range of a critical descent event, then it is identified as a critical descent event.

[0118] If the flight speed, flight altitude, pitch angle, flight acceleration, dynamic energy index, and energy change rate are all within the preset threshold range of landing critical events, then it is identified as a landing critical event.

[0119] The identified key events include eight types: taxiing, takeoff, climb, cruise, attack, evasion, descent, and landing. The specific identification methods are as follows:

[0120] (1) Identification of critical gliding events:

[0121] Taxiing refers to the process by which an aircraft moves from its parking position to the runway before takeoff.

[0122] Flight speed V during gliding t Gradually increasing, ranging from 0-180 km / h, pitch angle A pitch,t Located between 0 and 2°, roll angle A roll,t It lies between -1° and +1°.

[0123]

[0124] The total energy is close to the minimum value E min The rate of energy change approaches 0, and the dynamic energy index is between 0 and 10%.

[0125]

[0126] If the conditions of formulas (9)-(10) are met simultaneously, the aircraft is identified as being in a critical taxiing event.

[0127] (2) Identification of critical takeoff events:

[0128] Takeoff refers to the process of an aircraft taxiing from the ground to leaving the ground and accelerating upwards. The takeoff phase is a crucial stage of flight, directly impacting flight safety. During takeoff, pilots experience a significant backward thrust, and their entire mental and physical state is under high tension.

[0129] Takeoff speed V t Gradually increasing, ranging from 180-300 km / h; flight altitude H tGradually ascending, reaching 500m; flight overload G t Located between 1 and 1.2g; pitch angle A pitch,t Located between 0 and 15°; roll angle A roll,t Located between -2° and 2°; flight acceleration A t It is greater than 0 within a certain period of time.

[0130]

[0131] The unit for flight altitude is meters (m); A t Flight acceleration, measured in m / s² 2 .

[0132] Kinetic energy and potential energy increase synchronously, the rate of energy change rises rapidly and is significantly positive, ranging from 5% to 20% / s, and the energy index is between 10% and 30%.

[0133]

[0134] For example, a certain time period is set to 10 seconds, but in specific applications, it can be modified according to specific needs.

[0135] If the conditions of formulas (11)-(12) are met simultaneously, the aircraft is identified as being in a critical takeoff event.

[0136] (3) Identification of key climbing events:

[0137] Climb refers to the process by which an aircraft begins to ascend to its cruising altitude after leaving the ground.

[0138] Flight speed V during climb t Gradually increasing, ranging from 300-800 km / h; flight altitude H t Gradually increasing, located between 500-8000m; pitch angle A pitch,t Located between 5 and 20°; roll angle A roll,t It is located between -10° and 10°.

[0139]

[0140] Potential energy dominates energy growth, with a positive rate of change but lower than that of the takeoff stage, ranging from 1% / s to 5% / s, and a dynamic energy index ranging from 30% to 70%.

[0141]

[0142] If the conditions of formulas (13)-(14) are met simultaneously, the aircraft is identified as being in a critical climb event.

[0143] (4) Identification of critical cruise events:

[0144] Cruise refers to the process of an aircraft flying level in the air without any maneuvering.

[0145] Cruise speed V t The speed gradually decreases, remaining between 800-1200 km / h; flight altitude H t Located between 8000-12000m; pitch angle A pitch,t Located between -10° and 10°; roll angle A roll,t It lies between 0 and 10°.

[0146]

[0147] The rate of energy change approaches ±1% / s, the dynamic energy index is close to stable, and the energy index changes by 30%-60%.

[0148]

[0149] Simultaneously satisfying the conditions of formulas (15)-(16), the aircraft is identified as being in a critical cruise event.

[0150] (5) Identification of critical attack events:

[0151] Attack primarily refers to the process of flight from taxiing on the ground to taking off and accelerating upwards. The attack phase is a crucial means of achieving mission objectives and is critical to the success or failure of the flight. During an attack, the pilot will be in a relatively tense state.

[0152] Based on roll angle A roll,t Pitch angle A pitch,t and heading angle A yaw,t Calculate the roll angle change rate W roll,t Pitch angle change rate W pitch,t and heading angle W yaw,t ,as follows:

[0153]

[0154] Overload G during attack t Located between 1-2G; flight altitude H t Located between 5000-10000m; Roll angle change rate W roll,t The speed is 0–5° / s.

[0155] Pitch angle change rate W pitch,t The speed is 0.5–10° / s.

[0156] Rate of change of heading angle W yaw,t The value is 0–3° / s.

[0157]

[0158] The energy change rate during the attack is -5% / s to 10% / s, and the dynamic energy index is 60% to 90%.

[0159]

[0160] Determine G t Located between 1-2G, flight altitude H t If the value is between 5000-10000m and any one of the roll angle change rate, pitch angle change rate, or heading angle change rate meets the requirements and simultaneously satisfies formula (19), it is identified as a critical attack event in flight.

[0161] (6) Avoiding critical event identification:

[0162] Evasion, or dodging, refers to the pilot's use of a series of maneuvers to control the aircraft and achieve an evasive maneuver. Evasion is the most critical phase of the entire flight, affecting flight safety and the success or failure of the mission. During the evasion phase, the pilot's physical and mental state undergoes the most significant changes.

[0163] Normal overload G during evasion t Located between 3-4G; flight altitude H t Located between 5000-10000m; Roll angle change rate W roll,t The pitch angle change rate is 30–300° / s; W pitch,t The rate of change of heading angle is 10–50° / s; W yaw,t The speed is 5–30° / s.

[0164]

[0165] The energy fluctuates violently, with an energy change rate greater than 10% / s and a dynamic energy index of 60%-90%.

[0166]

[0167] If the normal overload is between 3-4G, the flight altitude is between 5000m-10000m, and any one of the roll angle change rate, pitch angle change rate, or heading angle change rate meets the requirements and simultaneously satisfies formula (21), it is identified as a critical avoidance event in flight.

[0168] (7) Identification of critical events during descent:

[0169] Descent refers to the aircraft descending from cruising altitude to approach altitude.

[0170] During descent, the flight speed gradually decreases, ranging from 250 to 800 km / h; the flight altitude gradually decreases, ranging from 250 to 1000 m; the pitch angle gradually decreases, ranging from -10 to -2°; and the roll angle is between 0 and 10°.

[0171]

[0172] Potential energy decreases, velocity remains constant or decreases slightly, energy change rate is negative, ranging from -5% / s to 1% / s, and dynamic energy index is 30%-80%.

[0173]

[0174] If the conditions of formulas (22)-(23) are met simultaneously, it is identified as a critical descent event during flight.

[0175] (8) Identification of critical landing events:

[0176] Flight landing primarily refers to the phase where an aircraft transitions from cruise to taxiing on the ground. Aircraft landing is highly complex and risky. The changes in acceleration, environmental stimuli, and operational stress during this process can significantly impact the pilot's physical and mental state.

[0177] During landing, the flight speed gradually decreases, ranging from 0 to 250 km / h; the flight altitude gradually decreases, from 500 m to 0; the pitch angle is between -5 and 3°; and the flight acceleration is less than 0 for a certain period of time.

[0178]

[0179] The energy decreases rapidly, with a negative rate of change ranging from -10% / s to 5% / s. The dynamic energy index ranges from 0% to 30%, and the energy eventually approaches the baseline of the gliding phase.

[0180]

[0181] If the flight speed gradually decreases, the flight altitude gradually decreases, and the flight acceleration is less than 0 within a certain period of time, and the conditions of formulas (24)-(25) are met simultaneously, then it is identified as a critical landing event in flight.

[0182] Based on the automatic critical event identification method of this invention, eight critical event states can be identified throughout the entire simulated flight process: taxiing, takeoff, climb, cruise, attack, evasion, descent, and landing. This automatic critical event identification method can achieve identification throughout the entire flight process.

[0183] The purpose of step S3 is to avoid misjudgment by a single indicator by jointly judging multiple parameter thresholds (flight status parameters and dynamic energy index), and to achieve accurate identification of key events throughout the flight cycle, providing event context for physiological state early warning.

[0184] Step S4, specifically.

[0185] Based on the pilot's wearable physiological monitoring device, real-time physiological parameter data including blood oxygen, heart rate and respiratory rate are obtained during the pilot's simulated flight.

[0186] Based on real-time acquired blood oxygen, heart rate, and respiratory rate, as well as the pilot's resting baseline physiological parameter data, the rate of change of blood oxygen, heart rate, and respiratory rate were calculated.

[0187] The abnormality of a pilot's physiological state during a critical event is identified based on the changes in blood oxygen saturation, heart rate, and respiratory rate.

[0188] Based on the type of critical event, if the blood oxygen change rate, heart rate change rate, and respiratory rate change rate are all within the preset threshold ranges for blood oxygen change rate, heart rate change rate, and respiratory rate change rate corresponding to the type of critical event, then the pilot's physiological state is normal; otherwise, it is abnormal.

[0189] (1) Anomaly identification during the gliding phase

[0190] When the critical event is taxiing, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 15%, and the respiratory rate is within 15%, then the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0191]

[0192] Based on formulas (26)-(27), during critical taxiing events, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0193] (2) Anomaly identification during takeoff phase

[0194] When the critical event is takeoff, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 25%, and the respiratory rate is within 20%, then the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0195]

[0196] Based on formulas (28)-(29), during the critical takeoff event, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0197] (3) Anomaly identification during the climbing phase

[0198] When the critical event is climb, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 20%, and the respiratory rate is within 15%, then the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0199]

[0200] Based on formulas (30)-(31), during the critical climb event, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0201] (4) Anomaly identification during cruise phase

[0202] When the critical event is cruise, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 20%, and the respiratory rate is within 10%, then the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0203]

[0204] Based on formulas (32)-(33), during critical cruise events, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0205] (5) Anomaly identification during the attack phase

[0206] When the critical event is an attack, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 30%, and the respiratory rate is within 30%, then the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0207]

[0208] Based on formulas (34)-(35), during the attack on critical events, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0209] (6) Anomaly detection during the evasion phase

[0210] When the critical event is evasive maneuver, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 40%, and the respiratory rate is within 30%, the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0211]

[0212] Based on formulas (36)-(37), during the process of avoiding critical events, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0213] (7) Anomaly identification during the descent phase

[0214] When the critical event is descent, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 20%, and the respiratory rate is within 15%, the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0215]

[0216] Based on formulas (38)-(39), during critical descent events, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0217] (8) Anomaly identification during landing phase

[0218] When the critical event is descent, if the rate of change in blood oxygen is within 30%, the rate of change in heart rate is within 30%, and the respiratory rate is within 25%, the pilot's physiological state is normal; otherwise, the pilot's physiological state is abnormal.

[0219]

[0220] Based on formulas (40)-(41), during the landing critical event, it is possible to identify whether the pilot's physiological state is normal or abnormal.

[0221] If the pilot's physiological state is abnormal, voice and visual alarms will be triggered, and automatic flight takeover will be initiated.

[0222] During flight, if the pilot's physiological state becomes abnormal, the system will provide voice prompts and display information on the equipment, while simultaneously notifying the ground control center.

[0223] The purpose of step S4 is to achieve accurate physiological state monitoring throughout the entire flight phase by comparing the rate of change of the pilot's physiological parameters with the dynamic thresholds corresponding to critical events in real time, and to trigger graded early warning and automatic intervention mechanisms when abnormalities occur, so as to ensure flight safety.

[0224] Example 2

[0225] Another embodiment of the present invention discloses a real-time early warning system for abnormal physiological states based on critical events during flight, thereby realizing the real-time early warning method for abnormal physiological states based on critical events during flight described in Embodiment 1. The specific implementation methods of each module are as described in the corresponding descriptions in Embodiment 1.

[0226] like Figure 2 As shown, the system includes a multimodal data acquisition module M1, a dynamic energy analysis module M2, a flight critical event identification module M3, and a physiological state identification module M4.

[0227] The multimodal data acquisition module M1 is used to acquire flight parameter data and physiological parameter data of the pilot during simulated flight; and to acquire the pilot's resting baseline physiological parameter data.

[0228] The dynamic energy analysis module M2 is used to calculate the energy quantification index during the simulated flight process based on the flight parameter data during the simulated flight process;

[0229] The Flight Critical Event Identification Module M3 is used to identify the types of critical events during the simulated flight process based on flight parameter data and energy quantification indicators.

[0230] The physiological state recognition module M4 is used to identify the pilot's physiological state based on the physiological parameter data during the simulated flight, the resting baseline physiological parameter data, and the types of key events during the simulated flight. If there is an abnormality, a real-time warning will be issued.

[0231] In summary, the real-time early warning method and system for abnormal physiological states based on critical events during flight, as described in this embodiment of the invention, have the following beneficial effects:

[0232] 1. This invention achieves precise state quantification through a dynamic energy index. By calculating kinetic energy, potential energy, total energy, energy change rate, and dynamic energy index in real time during simulated flight, combined with dynamic fuel consumption compensation, it overcomes the limitations of traditional static thresholds and accurately quantifies the trend of aircraft energy changes (such as energy storage before an attack or violent fluctuations during evasion). The dynamic energy index reflects the changes in the aircraft's energy state during simulated flight. This invention can dynamically assess the pilot's physiological load state based on real-time environmental changes and aircraft performance, thereby providing more accurate early warnings of abnormal physiological states.

[0233] 2. By processing and analyzing flight parameters and physiological parameters in real time, this invention can more accurately and automatically identify key events in flight and assess the pilot's physiological state accordingly, thereby improving the accuracy and reliability of the early warning system.

[0234] 3. This invention utilizes the synergistic effect of flight parameters and physiological parameters during flight to collect multimodal data, comprehensively analyze the pilot's physiological state, and provide real-time monitoring and early warning of the pilot's physiological state throughout the flight process;

[0235] 4. When the present invention detects an abnormal physiological state of the pilot, it triggers a voice or visual alarm in real time and performs automatic flight takeover when necessary, which can minimize safety risks and has important value for assisting flight training and ensuring flight safety.

[0236] 5. This invention can adapt to different flight conditions, including severe weather and special flight missions, thereby improving the effectiveness of flight training and flight safety.

[0237] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0238] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for real-time warning of abnormal physiological state based on in-flight key events, characterized in that, The method comprises the following steps: acquiring flight parameter data and physiological parameter data of a pilot during a simulated flight process; acquiring resting baseline physiological parameter data of the pilot; calculating a dynamic energy quantification index during the simulated flight process based on the flight parameter data during the simulated flight process; identifying a type of a key event during the simulated flight process based on the flight parameter data during the simulated flight process and the dynamic energy quantification index; identifying a physiological state of the pilot based on the physiological parameter data during the simulated flight process, the resting baseline physiological parameter data, and the type of the key event during the simulated flight process, and giving a real-time warning if the physiological state is abnormal; calculating the dynamic energy quantification index during the simulated flight process, which comprises calculating kinetic energy, potential energy, total energy, energy change rate, and dynamic energy index during the flight process; wherein, the kinetic energy at the current moment is calculated based on the current flight speed and the current mass of the aircraft; the potential energy at the current moment is calculated based on the current mass of the aircraft and the current flight altitude; the total energy at the current moment is calculated based on the kinetic energy at the current moment and the potential energy at the current moment, and the energy change rate is calculated based on the total energy at the current moment; the dynamic energy index at the current moment during the simulated flight process is calculated based on the total energy at the current moment, the maximum total energy during the flight process, and the minimum energy in the taxiing phase; a dynamic energy index of a current time point in the simulated flight process is calculated as follows: ； in, For the current moment Total energy; This represents the minimum energy required for the gliding phase. This represents the remaining fuel mass at the current moment. The remaining load mass at the current moment; This represents the maximum total energy during flight. The mass of the aircraft at the current moment; Simulated flight speed at the current moment; It is the acceleration due to gravity; Simulated flight altitude at the current moment; This is the minimum speed during gliding flight; This refers to the inherent mass of the aircraft.

2. The real-time alerting method based on in-flight key events for abnormal physiological states according to claim 1, characterized in that, the flight parameter data comprises flight speed, flight altitude, normal overload, heading angle, pitch angle, roll angle, flight acceleration, heading angle change rate, pitch angle change rate, and roll angle change rate; the acquisition of the flight parameter data of the pilot during the simulated flight process comprises: collecting flight speed, flight altitude, normal overload, heading angle, pitch angle, roll angle, and flight acceleration by using a flight data collection device; calculating the heading angle change rate, the pitch angle change rate, and the roll angle change rate based on the heading angle, the pitch angle, and the roll angle.

3. The real-time alerting method based on in-flight key events for abnormal physiological states according to claim 1, characterized in that, identifying the type of the key event during the simulated flight process based on the flight parameter data during the simulated flight process and the energy quantification index, which comprises: if the flight speed, the pitch angle, the roll angle, the dynamic energy index, and the energy change rate are simultaneously within the preset threshold range of the taxiing key event, the climbing key event, or the cruising key event, the key event is identified as the taxiing key event, the climbing key event, or the cruising key event; if the flight speed, the flight altitude, the normal overload, the pitch angle, the roll angle, the flight acceleration, the dynamic energy index, and the energy change rate are simultaneously within the preset threshold range of the take-off key event, the key event is identified as the take-off key event; if the normal overload, the flight altitude, the heading angle change rate, the pitch angle change rate, the roll angle change rate, the dynamic energy index, and the energy change rate are simultaneously within the preset threshold range of the attack key event or the avoidance key event, the key event is identified as the attack key event or the avoidance key event; if the flight speed, the flight altitude, the pitch angle, the roll angle, the dynamic energy index, and the energy change rate are simultaneously within the preset threshold range of the descending key event, the key event is identified as the descending key event. If the flight speed, flight height, pitch angle, flight acceleration, dynamic energy index and energy change rate are simultaneously within the preset threshold range of the landing critical event, it is identified as a landing critical event.

4. The real-time alerting method based on in-flight key events for abnormal physiological states according to claim 1, characterized in that, The pilot resting baseline physiological parameter data is obtained by: Based on the wearable physiological monitoring device of the pilot, the physiological parameter data including blood oxygen, heart rate and respiratory rate of the pilot during the simulated flight process is obtained in real time; Based on the blood oxygen, heart rate and respiratory rate of the pilot in the resting state within the preset period, the mean values of blood oxygen, heart rate and respiratory rate in the resting state are calculated as the pilot resting baseline physiological parameter data.

5. The real-time alerting method based on in-flight key events for abnormal physiological states according to claim 4, characterized in that, Based on the wearable physiological monitoring device of the pilot, the physiological parameter data including blood oxygen, heart rate and respiratory rate of the pilot during the simulated flight process is obtained in real time; Based on the real-time obtained blood oxygen, heart rate and respiratory rate, and the pilot resting baseline physiological parameter data, the blood oxygen change rate, heart rate change rate and respiratory rate change rate are calculated; Based on the blood oxygen change rate, heart rate change rate and respiratory rate change rate, it is determined whether the physiological state of the pilot in the corresponding critical event is abnormal.

6. The real-time alerting method based on in-flight key events for abnormal physiological states according to claim 5, characterized in that, Based on the type of the critical event, if the blood oxygen change rate, heart rate change rate and respiratory rate change rate are all within the preset threshold range of the blood oxygen change rate, heart rate change rate and respiratory rate change rate corresponding to the type of the critical event, the physiological state of the pilot is normal, otherwise it is abnormal.

7. The real-time alerting method of abnormal physiological state based on in-flight key events according to any one of claims 1-6, characterized in that, If the physiological state of the pilot is abnormal, voice and visual alarms are triggered, and automatic flight takeover is performed.

8. A real-time warning system for abnormal physiological conditions based on in-flight key events, characterized in that, It comprises: A multi-modal data acquisition module for obtaining flight parameter data and physiological parameter data of a pilot during simulated flight; Obtain the pilot resting baseline physiological parameter data; A dynamic energy analysis module for calculating an energy quantization index during the simulated flight based on the flight parameter data during the simulated flight; A flight critical event identification module for identifying the type of critical events in the simulated flight process based on the flight parameter data and the energy quantization index during the simulated flight; A physiological state identification module for identifying the physiological state of the pilot based on the physiological parameter data during the simulated flight, the resting baseline physiological parameter data and the type of critical events in the simulated flight process, and performing real-time warning if it is abnormal. The dynamic energy quantization index during the simulated flight is calculated, including the kinetic energy, potential energy, total energy, energy change rate and dynamic energy index during the flight; wherein, The current kinetic energy is calculated based on the current flight speed and the current mass of the aircraft; The current potential energy is calculated based on the current mass of the aircraft and the current flight height; The total energy at the current time is calculated based on the current kinetic energy and the current potential energy, and the energy change rate is calculated based on the total energy at the current time; The dynamic energy index at the current time during the simulated flight is calculated based on the total energy at the current time, the maximum total energy during the flight and the minimum energy in the taxiing phase. a dynamic energy index of a current time point in the simulated flight process is calculated as follows: ； in, For the current moment Total energy; This represents the minimum energy required for the gliding phase. This represents the remaining fuel mass at the current moment. The remaining load mass at the current moment; This represents the maximum total energy during flight. The mass of the aircraft at the current moment; Simulated flight speed at the current moment; It is the acceleration due to gravity; Simulated flight altitude at the current moment; This is the minimum speed during gliding flight; This refers to the inherent mass of the aircraft.

Images