CN-121990166-A - Intelligent collaborative protection method, system, equipment and medium for low-altitude falling

CN121990166ACN 121990166 ACN121990166 ACN 121990166ACN-121990166-A

Abstract

The application relates to an intelligent collaborative protection method, system, equipment and medium for low-altitude falling. The method comprises the steps of establishing a reliable link, acquiring a flight state data packet, adjusting the warning level of a falling judgment algorithm of the wearable safety equipment and the judgment sensitivity threshold value of the falling judgment algorithm based on a system health state code in the flight state data packet, carrying out cooperative falling judgment based on local sensor data of the wearable safety equipment and a real-time flight state data packet, generating a trigger decision, and generating a protection instruction to instruct to execute multiple protection and cooperative actions such as airbag triggering, audible and visual alarm, information feedback and the like when the trigger decision is high-confidence confirmation falling. By means of the method, the original information island state of the wearable equipment can be thoroughly broken through by fusing the local motion information of the wearing end and the global state information of the aircraft end, the accuracy and timeliness of the identification of the complex low-altitude falling scene are remarkably improved, and the risks of false alarm and missing alarm are greatly reduced.

Inventors

ZHENG YUJIE
ZHONG KANG
Gan Kailun

Assignees

深圳市名网邦科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260305

Claims (8)

1. An intelligent collaborative protection method for low-altitude falling is characterized by comprising the following steps: Establishing a real-time data communication link between a wearable safety device and a low-altitude aircraft, and periodically receiving a flight status data packet from the low-altitude aircraft through the real-time data communication link, wherein the flight status data packet comprises aircraft altitude, speed, attitude and system health status codes; Adjusting an alert level of a fall judgment algorithm of the wearable safety device and a judgment sensitivity threshold of the fall judgment algorithm based on the system health status code in the flight status data packet to obtain an adjusted alert level and an adjusted judgment sensitivity threshold; Based on the local sensor data of the wearable safety equipment and the real-time flight state data packet, carrying out cooperative falling judgment to generate a trigger decision; and generating a protection instruction when the trigger decision is high-confidence confirmation falling, wherein the protection instruction is used for indicating to execute related protection work, and the protection work comprises the steps of controlling the action of a gas generating device of the wearable safety equipment to expand an air bag, starting a local audible and visual alarm and sending trigger confirmation information to the low-altitude aircraft through the real-time data communication link.
2. The method of claim 1, wherein said adjusting the alert level of the fall determination algorithm and the determination sensitivity threshold of the fall determination algorithm for the wearable security device based on the system health status code in the flight status data packet results in an adjusted alert level and an adjusted determination sensitivity threshold, comprising: Judging whether the current low-altitude aircraft is in a serious fault state or not based on the system health status code in the flight status data packet and a preset serious fault alarm code list in the wearable safety equipment, and obtaining a judgment result; if the judgment result shows that the current low-altitude aircraft is in the serious fault state, setting an internal collaborative alert state variable of the wearable safety equipment from a conventional alert state to a first-level alert state, and obtaining the adjusted alert level; And adjusting a key detection threshold parameter in the falling judgment algorithm in response to the adjusted warning level to obtain the adjusted judgment sensitivity threshold, wherein the adjustment comprises the steps of reducing the composite acceleration module length threshold from a first conventional value to a second higher sensitivity value and reducing the angular velocity module length threshold from a third conventional value to a fourth higher sensitivity value.
3. The method of claim 1, wherein the collaborative fall determination based on the local sensor data of the wearable security device and the real-time flight status data packet, generating a trigger decision, comprises: Collecting original data of a local sensor of the wearable safety equipment, and carrying out filtering and compensating pretreatment on the original data to obtain pretreated data, wherein the local sensor comprises an inertial measurement unit and a barometer; based on the preprocessed data, calculating to obtain a local feature vector sequence, wherein the local feature vector sequence comprises a synthetic acceleration module length, a weightlessness index and an angular velocity module length; analyzing the real-time flight state data packet to obtain an aircraft state evidence, wherein the aircraft state evidence comprises an aircraft real-time altitude, an altitude descent rate and a fault warning sign; based on the local feature vector sequence, generating a local falling suspected degree detection result by detecting a composite mode of continuous weightlessness followed by abnormal angular velocity increase; Judging whether the low-altitude aircraft has strong abnormal evidence based on the aircraft state evidence to obtain an aircraft strong abnormal evidence existence judging result, wherein the strong abnormal evidence is a high cliff descent or an aircraft active collision warning signal; And generating the trigger decision by combining a preset fusion decision rule based on the local falling suspected degree detection result and the aircraft strong abnormal evidence existence judgment result.
4. The method of claim 3, wherein the generating the trigger decision based on the local fall plausibility detection result and the aircraft strong anomaly evidence presence determination result in combination with a preset fusion decision rule comprises: If the local falling suspected degree judgment result is suspected falling or falling is confirmed, and the strong abnormal evidence existence judgment result of the aircraft is that the strong abnormal evidence exists, generating the trigger decision with high confidence; If the local falling suspected degree judgment result is suspected falling or falling is confirmed, but the strong abnormal evidence existence judgment result of the aircraft is that the strong abnormal evidence does not exist, acquiring the current collaborative alert state variable; If the collaborative alert state variable is a primary alert state, generating the trigger decision with high confidence; if the collaborative alert state variable is a conventional alert state, continuously monitoring an impact signal and aircraft confirmation abnormal information in a preset confirmation waiting window to obtain a monitoring result; if the monitoring result is that the local impact signal or the aircraft confirmation abnormal information is monitored in the preset confirmation waiting window period, generating the trigger decision with high confidence; And if the monitoring result is that the local impact signal or the aircraft confirmation abnormal information is not monitored in the preset confirmation waiting window period, generating the trigger decision with zero confidence coefficient.
5. The method of claim 3, wherein generating a local fall plausibility detection result based on the local feature vector sequence by detecting a composite pattern of continuous weightlessness followed by an abnormal angular velocity increase comprises: Judging whether the weightlessness index in the local feature vector sequence meets a continuous weightlessness condition or not to obtain a first judgment result, wherein the continuous weightlessness condition is that the weightlessness index is continuously lower than a preset dynamic threshold value for a preset duration; If the first judgment result is that the weightlessness index meets the continuous weightlessness condition, judging whether the angular velocity module length in the local feature vector sequence meets an abnormal angular velocity increasing condition or not to obtain a second judgment result, wherein the abnormal angular velocity increasing condition is that a preset dynamic angular velocity threshold value is exceeded in a time window after the weightlessness stage; If the second judgment result is that the angular velocity module length meets the abnormal angular velocity increasing condition, generating the local falling suspected degree judgment result of suspected falling; Judging whether the synthesized acceleration module length in the local feature vector sequence has a peak value exceeding a preset extremely high impact threshold value or not based on the local falling suspected degree judgment result of the suspected falling, and obtaining a third judgment result; And if the third judging result is that the synthesized acceleration module has a peak value exceeding a preset extremely high impact threshold value, generating the local falling suspected degree judging result for confirming falling.
6. An intelligent collaborative protection system for low altitude falls, the system comprising: the system comprises a data acquisition module, a control module and a control module, wherein the data acquisition module is used for establishing a real-time data communication link between a wearable safety device and a low-altitude aircraft and periodically receiving a flight state data packet from the low-altitude aircraft through the real-time data communication link; wherein the flight status data packet includes aircraft altitude, speed, attitude and system health status codes; The algorithm adjustment module is used for adjusting the warning level of the falling judgment algorithm of the wearable safety equipment and the judgment sensitivity threshold value of the falling judgment algorithm based on the system health status code in the flight status data packet to obtain the adjusted warning level and the adjusted judgment sensitivity threshold value; The decision generation module is used for carrying out cooperative falling judgment based on the local sensor data of the wearable safety equipment and the real-time flight state data packet to generate a trigger decision; The protection triggering module is used for generating a protection instruction when the triggering decision is high-confidence confirmation falling, wherein the protection instruction is used for indicating to execute relevant protection work, and the protection work comprises the steps of controlling the gas generating device of the wearable safety equipment to act so as to expand an air bag, starting a local audible and visual alarm and sending triggering confirmation information to the low-altitude aircraft through the real-time data communication link.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.

Description

Intelligent collaborative protection method, system, equipment and medium for low-altitude falling Technical Field The invention belongs to the technical field of intelligent safety protection and cooperative control, and particularly relates to an intelligent cooperative protection method, system, equipment and medium for low-altitude falling. Background With the vigorous development of low-altitude economy and the gradual application of manned aircraft such as electric vertical take-off and landing aircraft, the safety protection problem of passengers in the flight process is increasingly emphasized. For this reason, airbag-integrated wearable safety devices have emerged, which typically incorporate inertial sensors that determine whether to trigger airbag deployment by detecting human motion conditions, in order to provide close-fitting protection for the occupant in the event of a sudden fall. In the conventional art, such wearable safety devices operate as stand-alone personal protective equipment. The working mode of the device mainly depends on local motion data acquired by sensors such as an accelerometer and a gyroscope carried by the device. The control algorithm of the device analyzes these local data based on preset thresholds and modes to determine if a dangerous condition such as a fall or fall has occurred and to determine if to activate the air bag. However, in the conventional technology, there is a significant limitation in a specific and complex application scenario of low-altitude flight. Due to the lack of effective information interaction between the equipment and the aircraft body, an 'information island' is formed, so that the auxiliary decision cannot be made by using more accurate and global state information (such as accurate altitude, speed and system fault early warning) of the aircraft end. The three outstanding problems are that normal flight maneuver and real uncontrolled falling are difficult to distinguish only by local motion information, the recognition accuracy is limited, risks of false alarm and false omission coexist, the protection action is completely started after the sensor senses the impact, early warning and pre-preparation cannot be carried out according to the fault sign of the aircraft, the response time is passive, and the whole triggering link depends on a single electronic sensing and control system and lacks effective redundancy guarantee when the electronic system fails. Disclosure of Invention Based on the above, it is necessary to provide a low-altitude fall intelligent cooperative protection method capable of realizing information cooperation between devices, improving judgment accuracy and timeliness, and enhancing overall reliability of a system. In a first aspect, the application provides an intelligent collaborative protection method for low-altitude falling, comprising the following steps: Establishing a real-time data communication link between the wearable safety device and the low-altitude aircraft, and periodically receiving a flight status data packet from the low-altitude aircraft through the real-time data communication link, wherein the flight status data packet comprises aircraft altitude, speed, attitude and system health status codes; Based on the system health status code in the flight status data packet, adjusting the warning level of the falling judgment algorithm and the judgment sensitivity threshold of the falling judgment algorithm of the wearable safety device to obtain an adjusted warning level and an adjusted judgment sensitivity threshold; Based on local sensor data and real-time flight state data packets of the wearable safety equipment, carrying out cooperative falling judgment to generate a trigger decision; When the triggering decision is high-confidence confirmation falling, a protection instruction is generated, wherein the protection instruction is used for indicating to execute relevant protection work, and the protection work comprises the steps of controlling the action of a gas generating device of the wearable safety equipment to deploy an air bag, starting a local audible and visual alarm and sending triggering confirmation information to the low-altitude aircraft through a real-time data communication link. Further, adjusting the alert level of the fall determination algorithm and the determination sensitivity threshold of the fall determination algorithm for the wearable security device based on the system health status code in the flight status data packet, resulting in an adjusted alert level and an adjusted determination sensitivity threshold, comprising: judging whether the current low-altitude aircraft is in a serious fault state or not based on a system health state code in the flight state data packet and a preset serious fault alarm code list in the wearable safety equipment, and obtaining a judgment result; If the judgment result shows that the current low-altitude aircraft is in a serious fault state