Abnormal physiological state real-time early warning method and system based on key events in flight

Abstract

The invention relates to an abnormal physiological status real-time early warning method and system based on key events in flight, belongs to the field of aviation medical diagnosis and identification, and solves the problems of insufficient key event automatic identification and lack of pilot physiological status real-time early warning in existing simulated flight training. Comprising the following steps: acquiring flight parameter data and physiological parameter data in a simulated flight process of a pilot; pilot resting reference physiological parameter data are obtained; calculating an energy quantitative index in the simulated flight process based on the flight parameter data in the simulated flight process; performing identification based on the flight parameter data and the energy quantitative index in the simulated flight process to obtain the type of the key event in the simulated flight process; and based on the physiological parameter data in the simulated flight process, the resting reference physiological parameter data and the types of the key events in the simulated flight process, identifying the physiological state of the pilot, and if the physiological state is abnormal, performing real-time early warning. And the real-time early warning of the abnormal physiological state in the air of the pilot is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aviation medical diagnosis, identification and electronic data digital processing, and particularly relates to a real-time abnormal physiological state early warning method and system based on key events in flight. BACKGROUND

[0002] In the field of aviation biomedical engineering industry, the physiological state diagnosis of pilots is crucial for flight safety. During flight, pilots face sudden situations such as severe weather, flight special services, etc., and their physical and mental states will change dramatically, often producing tension and anxiety. Due to differences in experience and emotional adjustment ability, flight training and flight safety will be affected to varying degrees. Moderate emotional state can improve attention and stimulate potential; excessive emotional stress can lead to confusion and difficulty in decision-making, which can easily lead to flight accidents.

[0003] Currently, real-time abnormal early warning in flight involves real-time physiological data transmission. Existing methods usually focus on the recording and post-processing analysis of flight data, lack real-time processing and analysis capabilities, and cannot dynamically evaluate real-time environmental changes and aircraft energy changes, resulting in insufficient accuracy and reliability of early warning. The existing methods have limited ability in data fusion and multi-modal analysis, and it is difficult to fully utilize the synergistic effect of flight parameters and physiological parameters obtained by wearable smart devices. SUMMARY

[0004] In view of the above analysis, the embodiments of the present application aim to provide a real-time abnormal physiological state early warning method and system based on key events in flight, to solve the technical problems of insufficient automatic identification of key events in flight and lack of real-time early warning of pilots' physiological state.

[0005] The purpose of the present application is mainly realized through the following technical solutions:

[0006] The present application provides a real-time abnormal physiological state early warning method based on key events in flight, comprising the following steps:

[0007] Obtain flight parameter data and physiological parameter data of pilots during simulated flight process; obtain resting baseline physiological parameter data of pilots;

[0008] Calculate dynamic energy quantitative index during simulated flight process based on flight parameter data during simulated flight process;

[0009] Identify based on flight parameter data and dynamic energy quantitative index during simulated flight process to obtain the type of key events during simulated flight process;

[0010] Based on the physiological parameter data in the simulation flight process, the resting baseline physiological parameter data and the type of key events in the simulation flight process, the physiological state of the pilot is identified, and real-time warning is performed if it is abnormal.

[0011] Further, the flight parameter data includes flight speed, flight height, normal overload, heading angle, pitch angle, roll angle, flight acceleration, heading angle change rate, pitch angle change rate and roll angle change rate; the flight parameter data of the pilot in the simulation flight process is obtained, including:

[0012] The flight speed, flight height, normal overload, heading angle, pitch angle, roll angle and flight acceleration are collected by a flight data collection device.

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

[0014] Further, the dynamic energy quantization index in the simulation flight process is calculated, including the calculation of kinetic energy, potential energy, total energy, energy change rate and dynamic energy index in the flight process; wherein,

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

[0016] Based on the current mass of the aircraft and the current flight height, the potential energy at the current time is calculated.

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

[0018] Based on the total energy at the current time in the simulation flight process, the maximum total energy in the flight process and the minimum energy in the taxiing stage, the dynamic energy index at the current time in the simulation flight process is calculated.

[0019] Further, the dynamic energy index EI at the current time in the simulation flight process is calculated as follows: t

[0020]

[0021] Wherein, E total,t is the total energy at the current time t; E min is the minimum energy in the taxiing stage; m fuel,t is the remaining fuel mass at the current time; m payload,t is the remaining load mass at the current time; E max (m fuel,t ,m payload,t ) is the maximum total energy in the flight process; m t ​is the current time mass of the aircraft; V t is the current time simulated flight speed; g is the acceleration of gravity; H t is the current time simulated flight height; V 滑行_min is the minimum speed during taxiing flight; m0 is the inherent mass of the aircraft.

[0022] Further, based on the flight parameter data and the energy quantization index during the simulated flight process, the types of key events during the simulated flight process are obtained, including:

[0023] If the flight speed, pitch angle, roll angle, dynamic energy index and energy change rate are simultaneously located within the preset threshold range of the taxiing key event, the climbing key event or the cruising key event, the taxiing key event, the climbing key event or the cruising key event is identified;

[0024] If the flight speed, flight height, normal overload, pitch angle, roll angle, flight acceleration, dynamic energy index and energy change rate are simultaneously located within the preset threshold range of the take-off key event, the take-off key event is identified;

[0025] If the normal overload, flight height, heading angle change rate, pitch angle change rate, roll angle change rate, dynamic energy index and energy change rate are simultaneously located within the preset threshold range of the attack key event or the avoidance key event, the attack key event or the avoidance key event is identified;

[0026] If the flight speed, flight height, pitch angle, roll angle, dynamic energy index and energy change rate are simultaneously located within the preset threshold range of the descending key event, the descending key event is identified;

[0027] If the flight speed, flight height, pitch angle, flight acceleration, dynamic energy index and energy change rate are simultaneously located within the preset threshold range of the landing key event, the landing key event is identified.

[0028] Further, the pilot's resting baseline physiological parameter data is obtained, including:

[0029] Based on the wearable physiological monitoring device of the pilot, the blood oxygen, heart rate and respiration rate of the pilot in a resting state within a preset period are collected;

[0030] Based on the blood oxygen, heart rate and respiration rate of the pilot in a resting state within a preset period, the mean value of blood oxygen, the mean value of heart rate and the mean value of respiration rate in a resting state are calculated as the pilot's resting baseline physiological parameter data.

[0031] Further, based on the wearable physiological monitoring device of the pilot, the physiological parameter data including blood oxygen, heart rate and respiration rate of the pilot during the simulated flight process are obtained in real time;

[0032] Based on the real-time acquired blood oxygen, heart rate and respiratory rate, and the pilot's resting baseline physiological parameter data, the blood oxygen change rate, heart rate change rate and respiratory rate change rate are calculated;

[0033] Based on the blood oxygen change rate, heart rate change rate and respiratory rate change rate, whether the pilot's physiological state in the corresponding key event is abnormal is identified.

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

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

[0036] The present application provides a kind of based on the abnormal physiological state of real-time early warning system of key event in flight, comprising:

[0037] Multi-modal data acquisition module, for obtaining the flight parameter data and physiological parameter data in the process of pilot simulation flight;Resting baseline physiological parameter data of pilot is obtained;

[0038] Dynamic energy analysis module, for calculating energy quantization index in the process of simulation flight based on the flight parameter data in the process of simulation flight;

[0039] Flight key event identification module, for identifying based on the flight parameter data and energy quantization index in the process of simulation flight, obtain the type of key event in the process of simulation flight;

[0040] Physiological state identification module, for identifying pilot physiological state based on the physiological parameter data in the process of simulation flight, resting baseline physiological parameter data and the type of key event in the process of simulation flight, if abnormal, real-time early warning is carried out.

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

[0042] 1. The dynamic energy index realizes precise state quantification, through real-time calculation of kinetic energy, potential energy, total energy, energy change rate and dynamic energy index in simulated flight, combined with dynamic compensation of fuel consumption, breaking through the limitation of traditional static threshold, accurately quantifying the energy change trend of the aircraft (such as energy accumulation before attack, severe fluctuation when avoiding), and the dynamic energy index reflects the energy state change of the aircraft in the simulated flight process. The present application can dynamically evaluate the physiological load state of the pilot according to the real-time environmental changes and the performance of the aircraft, thereby providing more accurate abnormal physiological state early warning;

[0043] 2. The present application can more accurately and automatically identify key events in flight by real-time processing and analyzing flight parameters and physiological parameters, and evaluate the physiological state of the pilot accordingly, thereby improving the accuracy and reliability of the early warning system;

[0044] 3. The present application utilizes the synergistic effect of flight parameters and physiological parameters during flight to perform multi-modal data processing, comprehensively analyze the physiological state of the pilot, and provide real-time monitoring and early warning of the physiological state of the pilot throughout the flight;

[0045] 4. When the physiological state of the pilot is abnormal, the present application triggers a voice or visual alarm in real time, and automatically takes over the flight when necessary, which can minimize the safety risk and has important value for assisting flight training and ensuring flight safety;

[0046] 5. The present application can adapt to different flight conditions, including severe weather and special flight tasks, thereby improving the effectiveness of flight training and ensuring flight safety.

[0047] In the present application, the above technical solutions can be combined with each other to realize more preferred combination schemes. Other features and advantages of the present application will be described in the subsequent specification, and some advantages will become apparent from the specification or by implementing the present application. The purpose and other advantages of the present application can be achieved and obtained from the contents specifically pointed out in the specification and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings are included to provide a better understanding of the embodiments, and are not considered limiting to the present application, wherein the same reference numerals represent the same components throughout the drawings.

[0049] Figure 1 A flow chart of a real-time early warning method for abnormal physiological state based on key events in flight in an embodiment of the present application;

[0050] Figure 2 A module schematic diagram of a real-time early warning system for abnormal physiological state based on key events in flight in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present application will be described in detail below with reference to the drawings, which form a part of this application. The drawings illustrate embodiments of the application and, together with the description, serve to explain the principles of the application, and to enable the skilled in the art to make and use the application.

[0052] Embodiment one

[0053] In one embodiment of the present application, a real-time warning method for abnormal physiological state based on in-flight key events is disclosed, as shown in the following steps: Figure 1

[0054] Step S1, obtaining flight parameter data and physiological parameter data of a pilot during a simulation flight process; obtaining resting baseline physiological parameter data of the pilot;

[0055] Step S2, calculating a dynamic energy quantization index during the simulation flight process based on the flight parameter data during the simulation flight process;

[0056] Step S3, identifying based on the flight parameter data and the dynamic energy quantization index during the simulation flight process to obtain a type of key events during the simulation flight process;

[0057] Step S4, identifying a pilot physiological state based on the physiological parameter data during the simulation flight process, the resting baseline physiological parameter data, and the type of key events during the simulation flight process, and performing real-time warning if abnormal.

[0058] Step S1 includes steps S11-S12.

[0059] Step S11, obtaining flight parameter data and physiological parameter data of a pilot during a simulation flight process.

[0060] The flight parameter data includes 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 obtaining of the flight parameter data of the pilot during the simulation flight process includes:

[0061] The flight speed, flight altitude, normal overload, heading angle, pitch angle, roll angle, and flight acceleration are collected by a flight data collection device.

[0062] The heading angle change rate, pitch angle change rate, and roll angle change rate are calculated based on the heading angle, pitch angle, and roll angle.

[0063] The flight parameter data is obtained by a data collection device on the simulator.

[0064] ​The wearable physiological monitoring device (wearable smart device) based on the pilot acquires physiological parameter data of the pilot during the simulation flight process in real time, including blood oxygen, heart rate and respiratory rate.

[0065] The wearable physiological monitoring device includes an electrocardiogram sensor, a respiration sensor and a blood oxygen sensor, which are worn on the head of the pilot, perform human-computer interaction, acquire electronic data for subsequent processing. The electrocardiogram sensor, the respiration sensor and the blood oxygen sensor are all smart sensors.

[0066] Blood oxygen monitoring is achieved by using a blood oxygen sensor. For example, a PPG (photoplethysmography, reflective multi-wavelength photoplethysmogram) sensor is used, which is located on the forehead band of the helmet, integrated into the temple part of the pilot's flight helmet, performs brain-computer interaction, and measures the blood oxygen value (i.e. blood oxygen saturation).

[0067] Heart rate monitoring is achieved by using an electrocardiogram sensor embedded in an anti-overload flight suit (chest position) to obtain a heart rate value.

[0068] Respiratory rate monitoring is achieved by using a respiration sensor integrated into the waistband of the flight suit to obtain the respiratory rate.

[0069] The acquired flight parameter data and physiological parameter data are time-stamped.

[0070] Step S12, acquiring the pilot's resting baseline physiological parameter data.

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

[0072] The wearable physiological monitoring device based on the pilot collects the blood oxygen, heart rate and respiratory rate of the pilot in a resting state within a preset period.

[0073] Based on the blood oxygen, heart rate and respiratory rate of the pilot in a resting state within a preset period, the mean blood oxygen, mean heart rate and mean respiratory rate in a resting state are calculated as the pilot's resting baseline physiological parameter data.

[0074] Based on the wearable physiological monitoring device, the pilot's resting baseline physiological parameter data is acquired in the normal state, i.e. the pilot is in a resting state.

[0075] For example, the physiological parameter data collection period in the normal state is 1 hour, and the mean heart rate, mean respiratory rate and mean blood oxygen in the normal state are calculated. The length of time for collecting physiological parameter data in the normal state can be changed according to specific application requirements.

[0076] The mean blood oxygen SP0, mean heart rate HR0 and mean respiratory rate RR0 in the normal state are calculated as the pilot's resting baseline physiological parameter data.

[0077] The step S1 is to synchronously acquire the real-time flight parameter data, physiological parameter data of the pilot and the resting reference physiological data through the flight data acquisition device and the wearable physiological monitoring equipment, so as to provide a multi-modal data basis for subsequent key event identification and real-time warning of abnormal physiological state of the pilot.

[0078] The step S2 is specifically.

[0079] The dynamic energy quantization index in the simulation flight process is calculated based on the flight parameter data in the simulation flight process.

[0080] The dynamic energy quantization index in the simulation flight process includes kinetic energy, potential energy, total energy, energy change rate and dynamic energy index in the flight process; wherein,

[0081] The current kinetic energy is calculated based on the current flight speed and the current mass of the aircraft;

[0082] The current potential energy is calculated based on the current mass of the aircraft and the current flight height;

[0083] 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.

[0084] The dynamic energy index at the current time in the simulation flight process is calculated based on the total energy at the current time in the simulation flight process, the maximum total energy in the flight process and the minimum energy in the taxiing stage.

[0085] The dynamic energy quantization index in the simulation flight process is calculated based on the real-time acquired flight speed V t , flight height H t .

[0086] The kinetic energy at time t in the simulation flight is as follows:

[0087]

[0088] The potential energy at time t in the simulation flight process is as follows:

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

[0090] The total energy at time t in the simulation flight process is as follows:

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

[0092] Energy rate of change during simulated flight As follows:

[0093]

[0094] The dynamic energy index EI at the current time during the simulated flight t , calculated as follows:

[0095]

[0096] where E total,t is the total energy at the current time t; E min is the minimum energy during taxiing; m fuel,t is the remaining fuel mass at the current time; m payload,t is the remaining payload mass at the current time; E max (m fuel,t , m payload,t ) is the maximum total energy during the flight; m t is the mass of the aircraft at the current time; V t is the simulated flight speed at the current time; g is the gravitational acceleration; H t is the simulated flight altitude at the current time; V 滑行_min is the minimum speed during taxiing; m0 is the inherent mass of the aircraft.

[0097] For the minimum energy during taxiing, as follows:

[0098]

[0099] For the taxiing phase, H 地面 ≈ 0, so,

[0100] For the remaining fuel mass at the current time, calculated as follows:

[0101]

[0102] where m fruel,initial is the initial fuel mass, the total amount of fuel added before the flight, set by ground service records or on-board system initialization; the flow sensor outputs the instantaneous fuel consumption rate Rate(t) at a high frequency (e.g., 10 Hz) in units of kg / s, which is integrated over time to obtain the total consumption.

[0103] The fuel mass flow rate of the engine at time t is measured in real time by a sensor. Exemplarily, Rate(t) is output by a fuel flow sensor (e.g., a Coriolis mass flowmeter) at a frequency of 10 Hz.

[0104] Real-time update, exemplarily, update m fruel,tIn practical applications, modifications can be made according to specific needs.

[0105] The cumulative consumption is calculated by trapezoidal method or rectangular method as follows:

[0106]

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

[0108] For the remaining load mass m payload,t at the current time, exemplarily, a cargo hold weight sensor is used to obtain.

[0109] The unit of flight speed is km / h, the unit of flight height is m, and the unit of flight acceleration is m / s 2 .

[0110] For the simulated flight height H t at the current time t, the unit is meter, and in practical applications, The height unit is converted from meter to kilometer, so that the calculation result is more reasonable, to avoid too large or too small height value.

[0111] The function of step S2 is to dynamically calculate kinetic energy, potential energy, total energy, energy change rate and dynamic energy index based on real-time flight parameter data, to quantify flight state by using dynamic energy index, and to provide energy dimension feature support for key event identification of step S3.

[0112] Step S3, specifically.

[0113] Based on the flight parameter data and energy quantization index in the simulated flight process, the types of key events in the simulated flight process are obtained, including:

[0114] If the flight speed, pitch angle, roll angle, dynamic energy index and energy change rate are simultaneously located in the preset threshold range of the taxiing key event, the climbing key event or the cruising key event, the taxiing key event, the climbing key event or the cruising key event is identified;

[0115] If the flight speed, flight height, normal overload, pitch angle, roll angle, flight acceleration, dynamic energy index and energy change rate are simultaneously located in the preset threshold range of the take-off key event, the take-off key event is identified;

[0116] If the normal overload, flight height, heading angle rate of change, pitch angle rate of change, roll angle rate of change, dynamic energy index and energy rate of change are simultaneously located in the preset threshold range of the attack key event or the avoidance key event, the attack key event or the avoidance key event is identified;

[0117] If the flight speed, flight height, pitch angle, roll angle, dynamic energy index and energy rate of change are simultaneously located in the preset threshold range of the descent key event, the descent key event is identified.

[0118] If the flight speed, flight height, pitch angle, flight acceleration, dynamic energy index and energy rate of change are simultaneously located in the preset threshold range of the landing key event, the landing key event is identified.

[0119] The identified key events include eight kinds of taxiing, taking off, climbing, cruising, attacking, avoiding, descending and landing, and the specific identification method is as follows:

[0120] (1) Taxiing key event identification:

[0121] The taxiing of the aircraft refers to the process from the parking position to the runway before taking off.

[0122] The flight speed V gradually increases and is located between 0-180 Km / h, the pitch angle A is located between 0-2°, the roll angle A is located between -1°-+1°. t pitch,t roll,t

[0123]

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

[0125]

[0126] The conditions of formulas (9)-(10) are simultaneously satisfied, and it is identified that the aircraft is in the taxiing key event.

[0127] (2) Taking off key event identification:

[0128] The taking off of the aircraft refers to the process from the ground taxiing to leaving the ground and accelerating upward. The taking off stage is an important stage of flight, which is related to flight safety. During the taking off process, the pilot will feel a significant backward thrust, and the whole body and mind state is in a state of high tension.

[0129] The flight speed V gradually increases and is located between 180-300 Km / h, the flight height H gradually increases and is located between 0-1000m, the pitch angle A is located between 0-2°, the roll angle A is located between -1°-+1°. t t ​​​​​Gradually increases to 500 m; flight overload G t Between 1-1.2 g; pitch angle A pitch,t Between 0-15°; roll angle A roll,t Between -2-2°; flight acceleration A t Greater than 0 in a certain period of time.

[0130]

[0131] Wherein, the flight height unit is m; A t Flight acceleration, unit: m / s 2 .

[0132] Kinetic energy and potential energy increase synchronously, energy change rate increases rapidly, which is a significant positive value, located in 5-20% / s, energy index is located in 10%-30%.

[0133]

[0134] Exemplarily, a certain period of time is set to 10 seconds, which can be modified according to specific needs in specific applications.

[0135] Meanwhile, formula (11)-(12) conditions are met, and it is identified that the airplane is in the take-off key event.

[0136] (3) Climb key event identification:

[0137] Climb refers to the process of climbing to the cruising altitude after the airplane leaves the ground.

[0138] Flight speed V t Gradually increases, located between 300-800 Km / h; flight height H t Gradually increases, located between 500-8000 m; pitch angle A pitch,t Located between 5-20°; roll angle A roll,t Located between -10-10°.

[0139]

[0140] Potential energy dominates energy growth, energy change rate is positive but lower than that in the take-off stage, located in 1% / s-5% / s, dynamic energy index is located in 30%-70%.

[0141]

[0142] Meanwhile, formula (13)-(14) conditions are met, and it is identified that the airplane is in the climb key event.

[0143] (4) Cruise key event identification:

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

[0145] Flight speed V t Gradually decreases, between 800-1200Km / h; flight height H t Between 8000-12000m; pitch angle A pitch,t Between -10~10°; roll angle A roll,t Between 0±10°.

[0146]

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

[0148]

[0149] Meanwhile, the formula (15)-(16) conditions are met, and the aircraft is identified to be in the cruise critical event.

[0150] (5) Attack critical event identification:

[0151] Attack mainly refers to the process of flying from taxiing on the ground to leaving the ground and accelerating to rise. The attack stage is the key means to complete the task target and is related to the success or failure of the flight. During the attack process, the pilot will be in a relatively tense state.

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

[0153]

[0154] The overload G t during attack is between 1-2G; flight height H t is between 5000-10000m; roll angle change rate W roll,t is 0~5° / s;

[0155] Pitch angle change rate W pitch,t is 0.5~10° / s;

[0156] Heading angle change rate W yaw,t is 0~3° / s.

[0157]

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

[0159]

[0160] Judgment G t Located between 1-2G, flight height H t Located between 5000-10000m, and any one of the roll angle rate of change, the pitch angle rate of change, the heading angle rate of change meets the requirements, and at the same time meets formula (19), identified as the attack key event in flight.

[0161] (6) Evasion key event recognition:

[0162] Evasion, mainly refers to the pilot through a series of maneuvering actions to control the aircraft movement to achieve the purpose of evasion. Evasion is the most critical stage in the whole flight process, which is related to flight safety and the success of the task. In the evasion stage, the physical and mental state of the pilot changes most significantly.

[0163] Normal overload G at the time of evasion t Located between 3-4G; flight height H t Located between 5000-10000m; roll angle rate of change W roll,t 30-300° / s; pitch angle rate of change W pitch,t 10-50° / s; heading angle rate of change W yaw,t 5-30° / s.

[0164]

[0165] Energy fluctuation, energy rate of change greater than 10% / s, dynamic energy index 60%-90%.

[0166]

[0167] Normal overload located between 3-4G, flight height located between 5000m-10000m, any one of the roll angle rate of change, the pitch angle rate of change, the heading angle rate of change meets the requirements, and at the same time meets formula (21), identified as the evasion key event in flight.

[0168] (7) Descent key event recognition:

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

[0170] The flight speed gradually decreases, is between 250-800Km / h, the flight height gradually decreases, is between 250-1000m, the pitch angle gradually decreases, is between -10--2°, and the roll angle is between 0±10°.

[0171]

[0172] The potential energy decreases, the speed remains or slightly decreases, the energy change rate is negative, is between -5% / s--1% / s, and the dynamic energy index is 30%-80%.

[0173]

[0174] When the conditions of formula (22)-(23) are met simultaneously, the key event in flight is identified as a descending key event.

[0175] (8) Landing key event identification:

[0176] The flight landing mainly refers to the stage from the cruising state to the ground sliding of the aircraft state. The aircraft landing has high complexity and high risk. The acceleration change, environmental stimulation and operation pressure of the process have a great influence on the physical and mental state of the pilot.

[0177] The flight speed gradually decreases, is between 0-250Km / h, the flight height gradually decreases, is from 500m to 0, the pitch angle is between -5~3°, and the flight acceleration is less than 0 in a certain time period.

[0178]

[0179] The energy rapidly decreases, the energy change rate is negative, is between -10% / s--5% / s, the dynamic energy index is between 0%-30%, and the final energy tends to be the reference of the sliding stage.

[0180]

[0181] The flight speed gradually decreases, the flight height gradually decreases, the flight acceleration is less than 0 in a certain time period, and the conditions of formula (24)-(25) are met simultaneously, so that the key event in flight is identified as a landing key event.

[0182] Based on the key event automatic identification method in the application, eight key event states of sliding, taking off, climbing, cruising, attacking, avoiding, descending and landing in the whole simulation flight process can be identified. The key event automatic identification method can realize the identification of the whole flight process.

[0183] The step S3 is to avoid single index misjudgment by multi-parameter threshold joint judgment (flight state parameter and dynamic energy index), to realize accurate identification of key events in the whole flight cycle, and to provide event context basis for physiological state early warning.

[0184] The step S4, in particular.

[0185] Based on the wearable physiological monitoring device of the pilot, the physiological parameter data of the pilot during the simulation flight process, including blood oxygen, heart rate and respiratory rate, are obtained in real time.

[0186] Based on the real-time obtained blood oxygen, heart rate and respiratory rate, and the pilot's resting baseline physiological parameter data, the blood oxygen change rate, heart rate change rate and respiratory rate change rate are calculated.

[0187] Based on the blood oxygen change rate, heart rate change rate and respiratory rate change rate, whether the physiological state of the pilot in the corresponding key event is abnormal is identified.

[0188] Based on the type of the key event, if the blood oxygen change rate, heart rate change rate and respiratory rate change rate are all within the blood oxygen change rate preset threshold range, heart rate change rate preset threshold range and respiratory rate change rate preset threshold range corresponding to the type of the key event, the physiological state of the pilot is normal, otherwise it is abnormal.

[0189] (1) Abnormal identification in taxiing phase

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

[0191]

[0192] Based on formulas (26)-(27), during the taxiing key event, whether the physiological state of the pilot is normal or abnormal is identified.

[0193] (2) Abnormal identification in take-off phase

[0194] When the key event is take-off, the blood oxygen change rate is within 30%, the heart rate change rate is within 25%, and the respiratory rate is within 20%, the physiological state of the pilot is normal; otherwise, the physiological state of the pilot is abnormal.

[0195]

[0196] Based on formulas (28)-(29), during the take-off key event, whether the physiological state of the pilot is normal or abnormal is identified.

[0197] (3) Abnormal identification in climbing phase

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

[0199]

[0200] Based on the formulas (30)-(31), during the climb key event process, whether the pilot physiological state is normal or abnormal is identified.

[0201] (4) Abnormal identification in the cruising phase

[0202] When the key event is cruising, if the blood oxygen change rate is within 30%, the heart rate change rate is within 20%, and the respiratory rate is within 10%, the pilot physiological state is normal; otherwise, the pilot physiological state is abnormal.

[0203]

[0204] Based on the formulas (32)-(33), during the cruising key event process, whether the pilot physiological state is normal or abnormal is identified.

[0205] (5) Abnormal identification in the attack phase

[0206] When the key event is attack, if the blood oxygen change rate is within 30%, the heart rate change rate is within 30%, and the respiratory rate is within 30%, the pilot physiological state is normal; otherwise, the pilot physiological state is abnormal.

[0207]

[0208] Based on the formulas (34)-(35), during the attack key event process, whether the pilot physiological state is normal or abnormal is identified.

[0209] (6) Abnormal identification in the evasion phase

[0210] When the key event is evasion, if the blood oxygen change rate is within 30%, the heart rate change rate is within 40%, and the respiratory rate is within 30%, the pilot physiological state is normal; otherwise, the pilot physiological state is abnormal.

[0211]

[0212] Based on the formulas (36)-(37), during the evasion key event process, whether the pilot physiological state is normal or abnormal is identified.

[0213] (7) Abnormal identification in the descending phase

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

[0215]

[0216] Based on formulas (38)-(39), during the descent key event process, whether the pilot physiological state is normal or abnormal is identified.

[0217] (8) Abnormal identification in landing phase

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

[0219]

[0220] Based on formulas (40)-(41), during the landing key event process, whether the pilot physiological state is normal or abnormal is identified.

[0221] When the pilot physiological state is abnormal, voice and visual alarms are triggered, and automatic flight takeover is performed.

[0222] During flight, when the pilot physiological state is abnormal, device voice prompts and device displays are performed, and the ground control center is notified.

[0223] The function of step S4 is to realize accurate physiological state monitoring in the whole flight phase by comparing the pilot physiological parameter change rate with the dynamic threshold corresponding to the key event in real time, and to trigger a graded early warning and automatic intervention mechanism when abnormal to ensure flight safety.

[0224] Embodiment two

[0225] Another embodiment of the application discloses a real-time early warning system for abnormal physiological state based on key events in flight, thereby realizing the real-time early warning method for abnormal physiological state based on key events in flight in embodiment one. The specific implementation of each module is described with reference to the corresponding description in embodiment one.

[0226] As shown in Figure 2 The system includes a multi-modal data acquisition module M1, a dynamic energy analysis module M2, a flight key event identification module M3, and a physiological state identification module M4.

[0227] The multi-modal data acquisition module M1 is used to acquire flight parameter data and physiological parameter data of the pilot during the simulation flight process, and to acquire the resting baseline physiological parameter data of the pilot.

[0228] a dynamic energy analysis module M2 configured to calculate an energy quantification index during the simulated flight based on the flight parameter data during the simulated flight;

[0229] a flight critical event identification module M3 configured to identify a type of critical event during the simulated flight based on the flight parameter data during the simulated flight and the energy quantification index;

[0230] a physiological state identification module M4 configured to identify a 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 event during the simulated flight, and to provide a real-time warning if the physiological state is abnormal.

[0231] In summary, the method and system for real-time warning of abnormal physiological state based on critical events during flight according to the embodiments of the present application have the following advantages:

[0232] 1. The dynamic energy index can accurately quantify the state by calculating the kinetic energy, potential energy, total energy, energy change rate, and dynamic energy index during the simulated flight in real time, combining with dynamic compensation of fuel consumption, breaking through the limitations of traditional static threshold, accurately quantifying the energy change trend of the aircraft (such as energy accumulation before attack, and dramatic fluctuations when avoiding), and the dynamic energy index reflecting the energy state change of the aircraft during the simulated flight. The present application can dynamically evaluate the physiological load state of the pilot according to real-time environmental changes and aircraft performance, thereby providing more accurate abnormal physiological state warning;

[0233] 2. The present application can more accurately and automatically identify critical events during flight by real-time processing and analyzing flight parameters and physiological parameters, and evaluate the physiological state of the pilot accordingly, thereby improving the accuracy and reliability of the warning system;

[0234] 3. The present application utilizes the synergistic effect of flight parameters and physiological parameters during flight, performs multi-modal data analysis, and comprehensively analyzes the physiological state of the pilot, thereby providing real-time monitoring and warning of the physiological state of the pilot during the entire flight process;

[0235] 4. When the physiological state of the pilot is identified as abnormal, the present application triggers a voice or visual alarm in real time, and automatically takes over the flight when necessary, which can minimize the safety risk, and has important value for assisting flight training and ensuring flight safety;

[0236] 5. The present application can adapt to different flight conditions, including severe weather and special flight tasks, thereby improving the effectiveness of flight training and flight safety.

[0237] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiment methods can be completed by instructing the relevant hardware by a computer program, and the program can be stored in a computer readable storage medium. The computer readable storage medium is a disk, an optical disk, a read-only memory, a random access memory, etc.

[0238] The above description is merely preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for real-time warning of abnormal physiological state based on in-flight key events, characterized in that, The application relates to a method for identifying a pilot physiological state during a simulated flight process. The method comprises the following steps: acquiring flight parameter data and physiological parameter data of a pilot during a simulated flight process; acquiring static reference 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; 2. The real-time alerting method for in-flight key event based abnormal physiological state in the air as claimed in claim 1, wherein, identifying a pilot physiological state based on the physiological parameter data during the simulated flight process, the static reference physiological parameter data and the type of the key event during the simulated flight process, and giving a real-time early warning if the pilot physiological state is abnormal. The flight parameter data comprises flight speed, flight height, normal overload, heading angle, pitch angle, roll angle, flight acceleration, heading angle change rate, pitch angle change rate and roll angle change rate; the step of acquiring the flight parameter data of the pilot during the simulated flight process comprises the following steps: collecting the flight speed, the flight height, the normal overload, the heading angle, the pitch angle, the roll angle and the flight acceleration by using a flight data acquisition device; 3. The real-time alerting method for in-flight key event based abnormal physiological state in the air as claimed in claim 2, wherein, 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. The step of calculating the dynamic energy quantification index during the simulated flight process comprises the following steps: calculating kinetic energy, potential energy, total energy, energy change rate and a dynamic energy index during the flight process; wherein, the current moment kinetic energy is calculated based on the current flight speed and the current moment mass of the airplane; the current moment potential energy is calculated based on the current moment mass of the airplane and the current flight height; 4. The method for real-time warning of abnormal physiological state in flight according to claim 3, characterized in that, a dynamic energy index EI at a current time point in the simulated flight process t is calculated as follows: Wherein, E total,t is the total energy at the current time t; E min is the minimum energy of the taxiing phase; m fuel,t is the remaining fuel mass at the current time; m payload,t is the remaining load mass at the current time; E max (m fuel,t , m payload,t ) is the maximum total energy during flight; m t is the current mass of the aircraft; V t is the simulated flight speed at the current time; g is the gravitational acceleration; H t is the simulated flight altitude at the current time; V 滑行_min is the minimum speed during taxiing flight; m0 is the inherent mass of the aircraft.

5. The method for real-time alerting of in-flight abnormal physiological state based on key events in flight as claimed in claim 3, wherein, the current moment total energy is calculated based on the current moment kinetic energy and the current moment potential energy, and the energy change rate is calculated based on the current moment total energy; the dynamic energy index of the current moment during the simulated flight process is calculated based on the current moment total energy, the maximum total energy during the flight process and the minimum energy of the taxiing stage. The step of 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 comprises the following steps: if the flight speed, the pitch angle, the roll angle, the dynamic energy index and the energy change rate are simultaneously located in 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 height, the normal overload, the pitch angle, the roll angle, the flight acceleration, the dynamic energy index and the energy change rate are simultaneously located in 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 height, 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 located in 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 height, the pitch angle, the roll angle, the dynamic energy index and the energy change rate are simultaneously located in 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.

6. The real-time alerting method for in-flight key event based abnormal physiological state in the air as claimed in claim 1, wherein, The pilot resting baseline physiological parameter data is obtained by: Based on the wearable physiological monitoring device of the pilot, the blood oxygen, heart rate and respiratory rate of the pilot in a resting state within a preset period are collected; Based on the blood oxygen, heart rate and respiratory rate of the pilot in a resting state within a preset period, the mean blood oxygen, mean heart rate and mean respiratory rate in a resting state are calculated as the pilot resting baseline physiological parameter data.

7. The real-time alerting method of in-flight key event based abnormal physiological state in the air as claimed in claim 6, wherein, Based on the wearable physiological monitoring device of the pilot, real-time physiological parameter data including blood oxygen, heart rate and respiratory rate of the pilot during simulated flight are obtained; Based on the real-time 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.

8. The method for real-time alerting of in-flight abnormal physiological state based on key events in flight according to claim 7, 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, the preset threshold range of the heart rate change rate and the preset threshold range of the respiratory rate change rate corresponding to the type of the critical event, the physiological state of the pilot is normal, otherwise it is abnormal.

9. The method of real-time alerting of in-flight abnormal physiological state based on key in-flight events of any of claims 1-8, wherein, If the physiological state of the pilot is abnormal, voice and visual alarms are triggered and automatic flight takeover is performed.

10. 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; Obtaining pilot resting baseline physiological parameter data; A dynamic energy analysis module for calculating energy quantization indicators during simulated flight based on the flight parameter data during simulated flight; A flight critical event identification module for identifying the type of critical events during simulated flight based on the flight parameter data and energy quantization indicators during simulated flight; A physiological state identification module for identifying the physiological state of the pilot based on the physiological parameter data during simulated flight, resting baseline physiological parameter data and the type of critical events during simulated flight, and performing real-time early warning if it is abnormal.

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