Safety belt locking state dynamic sensing early warning method and early warning device

Abstract

The application provides a safety belt locking state dynamic sensing early warning method and early warning device. The early warning method comprises the following steps: obtaining safety information of a safety belt, the safety information comprising first state information for representing a work state of a worker and second state information for representing a work state of a mounting belt; determining safety belt state information of the safety belt based on the first state information; determining safety belt safety information of the safety belt based on the second state information; and generating early warning information of the safety belt based on the safety belt state information and the safety belt safety information. The early warning method can accurately evaluate the safety risk level, significantly improve the safety and monitoring capability of high-altitude work, avoid the situation that a high-altitude worker mistakenly releases all safety belts or releases the safety belt protection when habitually violating the regulations to shift, ensure that the worker continuously works under the protection of the safety belt, and eliminate the risk of high-altitude falling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power equipment high-altitude operation safety equipment, in particular to a safety belt locking state dynamic sensing and early warning method and device. BACKGROUND

[0002] In the power industry, the maintenance and repair work of power transmission and transformation lines often requires personnel to work at high altitudes. To ensure the safety of high-altitude workers, safety belts are essential protective equipment.

[0003] In order to facilitate work, the safety belt and the backup safety belt are usually used alternately. When the worker needs to move position, the backup safety belt needs to be tied first, and then the working safety belt is untied, so that the worker is always in the protection state of the safety belt during the entire operation process, ensuring the flexibility of the operation while realizing uninterrupted safety protection. However, if the operation is wrong, the working safety belt is untied first, and then the backup safety belt is tied, which will appear a short period of unprotected state.

[0004] At present, although there is a belt state monitoring device in the prior art, the D-shaped buckle of the safety belt and the micro switch can detect the hanging state, but cannot judge whether the lock is completely closed or the rope tension is appropriate. If the worker operates improperly and the lock is not completely tightened, or the rope is too loose, the monitoring device may not accurately identify these potential dangers. At the same time, the existing monitoring system sends state information to the ground terminal through the micro switch, but in a complex high-altitude environment, the signal may be disturbed or delayed, and the real-time performance and reliability of information transmission cannot be satisfied. In addition, under the condition of simultaneous operation of multiple people, it is also impossible to realize accurate monitoring and rapid response of each worker.

[0005] Therefore, the existing technology has the technical problem that the belt state monitoring device cannot accurately and timely sense the state of the safety belt, and cannot meet the safety requirements of high-altitude operation. SUMMARY

[0006] The main purpose of the present application is to provide a safety belt locking state dynamic sensing and early warning method and device to solve the technical problem that the existing technology has a belt state monitoring device that cannot accurately and timely sense the state of the safety belt, and cannot meet the safety requirements of high-altitude operation.

[0007] In order to achieve the above object, according to one aspect of the present application, a safety belt locking state dynamic sensing and early warning method is provided, comprising: obtaining safety information of a safety belt, wherein the safety belt comprises a first safety belt and a second safety belt, the safety information comprises first state information for representing a working state of a worker and second state information for representing a working state of the safety belt, the first state information at least comprises acceleration and angular velocity of the worker, and the second state information at least comprises tension information of the safety belt, closing pressure and closing angle inside a safety belt buckle; determining safety belt state information of the safety belt based on the first state information; determining safety belt safety information of the safety belt based on the second state information, wherein the safety belt safety information comprises first safety information and / or second safety information; and generating early warning information of the safety belt based on the safety belt state information and the safety belt safety information.

[0008] In some embodiments, determining the working state information of the safety belt based on the first state information comprises: activating an electronic switching device based on the first state information, and obtaining force state data; and determining the safety belt state information of the safety belt based on the force state data.

[0009] In some embodiments, determining the first safety information of the safety belt based on the second state information comprises: determining a locking state of the safety belt based on the second state information; and determining the first safety information of the safety belt based on the locking state.

[0010] In some embodiments, determining the second safety information of the safety belt based on the second state information comprises: determining a real-time stress state of the safety belt based on the second state information; and determining the second safety information of the safety belt based on the real-time stress state.

[0011] In some embodiments, the method further comprises generating a worker misoperation early warning prompt information based on the safety belt state information, comprising the following steps: determining a first locking state of the first safety belt and a second locking state of the second safety belt based on the safety belt state information; and generating and sending a locking state error prompt information when the first locking state and the second locking state are both in an unlocked state.

[0012] In some embodiments, after determining the early warning information of the safety belt based on the safety belt state information and the safety belt safety information, the method further comprises: generating safety control information based on the early warning information.

[0013] In some embodiments, the determining the safety belt state information of the safety belt based on the first state information further comprises: evaluating a safety state of the worker, and updating the state information of the safety belt based on the evaluation result.

[0014] According to another aspect of the present application, the present application further provides a safety belt locking state dynamic sensing early warning device, comprising: an acquisition module, configured to acquire safety information of a safety belt, wherein the safety belt comprises a first safety belt and a second safety belt, the safety information comprises first state information for representing a working state of a worker and second state information for representing a working state of an installation belt, the first state information at least comprises acceleration and angular velocity of the worker, and the second state information at least comprises tension information of the safety belt, closing pressure inside a safety belt buckle and a closing angle; a first determination module, configured to determine safety belt state information of the safety belt based on the first state information; a second determination module, configured to determine safety belt safety information of the safety belt based on the second state information, wherein the safety belt safety information comprises the first safety information and / or the second safety information; and a generation module, configured to generate early warning information of the safety belt based on the safety belt state information and the safety belt safety information.

[0015] According to another aspect of the present application, the present application further provides a storage medium, which stores a computer program, and the computer program is executed by a processor to implement steps of the safety belt locking state dynamic sensing early warning method according to any one of the preceding aspects.

[0016] According to another aspect of the present application, the present application further provides an electronic device, which at least comprises a memory and a processor, the memory stores a computer program, and the processor implements steps of the safety belt locking state dynamic sensing early warning method according to any one of the preceding aspects when executing the computer program stored in the memory.

[0017] The safety belt locking state dynamic sensing early warning method provided by the present application can realize automatic switching of the safety belt, accurately monitor the closing state of the safety belt buckle by acquiring safety information of the safety belt and determining safety belt state information of the safety belt based on the first state information; can accurately evaluate the safety risk level by determining safety belt safety information of the safety belt based on the second state information, generating early warning information of the safety belt based on the safety belt state information and the safety belt safety information, significantly improve the safety and monitoring capability of the aerial work, and avoid the situation that the aerial worker mistakenly releases all safety belts or releases the safety belt protection when habitually violating the regulations in actual application, ensure that the worker continuously works under the protection of the safety belt, and eliminate the risk of aerial falling. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which form a part of the present application, are used to provide further understanding of the present application, and the illustrative embodiments of the present application and their description serve the purpose of explaining the present application. The present application is not limited by the accompanying drawings.

[0019] Figure 1 A flowchart showing the steps of the seat belt locking state dynamic perception and warning method provided by the present invention is shown;

[0020] Figure 2 A schematic diagram showing the steps of determining the operating status information of the safety belt based on the first status information provided by the present invention is shown;

[0021] Figure 3 A schematic diagram of determining the first safety information of the seat belt based on the second state information provided by the present invention is shown;

[0022] Figure 4 A schematic diagram of determining the second safety information of the seat belt based on the second state information provided by the present invention is shown;

[0023] Figure 5 A flowchart of the steps for generating operator misoperation warning prompt information based on seat belt status information provided by the present invention is provided;

[0024] Figure 6 A structural block diagram of the seat belt locking state dynamic sensing and warning device provided by the present disclosure;

[0025] Figure 7 A schematic structural diagram of an electronic device provided in the present disclosure. DETAILED DESCRIPTION

[0026] The specific embodiments of the present disclosure are described in detail below with reference to the accompanying drawings, but are not intended to limit the present disclosure.

[0027] It should be understood that various modifications may be made to the embodiments disclosed herein. Therefore, the above description should not be considered as limiting, but merely as an example of an embodiment. Other modifications within the scope and spirit of the present disclosure will occur to those skilled in the art.

[0028] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the general description of the present disclosure given above and the detailed description of the embodiments given below, serve to explain the principles of the present disclosure.

[0029] These and other characteristics of the present disclosure will become apparent from the following description of a preferred form of embodiment given as a non-limiting example with reference to the accompanying drawings.

[0030] It should also be understood that although the present disclosure has been described with reference to certain specific examples, those skilled in the art will be able to realize many other equivalent forms of the present disclosure that have the characteristics recited in the claims and are therefore within the scope of protection defined thereby.

[0031] The above and other aspects, features, and advantages of the present disclosure will become more apparent when viewed in conjunction with the following detailed description, taken in conjunction with the accompanying drawings.

[0032] Specific embodiments of the present disclosure are described below with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely examples of the present disclosure, which can be embodied in various ways. Well-known and / or repetitive functions and structures are not described in detail to avoid obscuring the present disclosure unnecessarily. Therefore, specific structural and functional details disclosed herein are not intended to limit, but merely as a basis for the claims and a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriate detailed structure.

[0033] It should be noted that the terms "first", "second", and the like, in the description and in the claims of the present disclosure and above-described drawings, are used to distinguish similar objects and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the data thus used can be interchanged, where appropriate, to enable the embodiments of the present disclosure described herein to be carried out in sequences other than those illustrated or described herein. Moreover, the terms "comprise" and "have", and any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a list of steps or units is not necessarily limited to those steps or units that are clearly listed, but can include other steps or units not clearly listed or inherent to such processes, methods, products, or apparatus.

[0034] The present specification can use the phrases "in one embodiment", "in another embodiment", "in yet another embodiment", or "in other embodiments", which can refer to one or more of the same or different embodiments of the present disclosure.

[0035] The present disclosure is further described below with reference to the accompanying drawings and specific embodiments.

[0036] In the process of electric power aerial work, in order to ensure the safety of the aerial work personnel, the alternating use of safety belts and backup safety belts is usually adopted, so as to ensure the flexibility of work while realizing uninterrupted safety protection. However, if the operation is wrong in this process, the working safety belt is first unfastened, and then the backup safety belt is fastened, which will appear a short period of unprotected state. At the same time, the existing monitoring method detects the hanging state through the cooperation of the D-shaped buckle of the safety belt and the micro switch, but cannot judge whether the lock buckle is completely closed or the rope tension is appropriate. This leads to the technical problem that the installation of the belt state monitoring device cannot accurately and timely perceive the state of the safety belt, and cannot meet the safety requirement of the aerial work.

[0037] In order to solve the technical problems in the prior art that the state monitoring device cannot accurately and timely perceive the state of the safety belt, and cannot meet the safety requirement of high-altitude operation, the application provides a safety belt locking state dynamic perception and early warning method and device.

[0038] Embodiment 1

[0039] Figure 1 The safety belt locking state dynamic perception and early warning method provided by the application is shown in the step flowchart. Figure 1 As shown in the figure, the safety belt locking state dynamic perception and early warning method comprises the following steps:

[0040] S101, obtaining safety information of a safety belt, wherein the safety belt comprises a first safety belt and a second safety belt, the safety information comprises first state information for representing a working state of an operator and second state information for representing a working state of the safety belt, the first state information at least comprises acceleration and angular velocity of the operator, and the second state information at least comprises tension information of the safety belt, closing pressure and closing angle in a safety belt buckle.

[0041] In this step, the safety information of the safety belt is obtained, wherein the safety belt comprises a first safety belt and a second safety belt, and the safety information comprises first state information for representing a working state of an operator and second state information for representing a working state of the safety belt.

[0042] Specifically, the operator realizes uninterrupted protection in the operation process through switching of the first safety belt and the second safety belt. In the operation process, the safety information of the safety belt is obtained, wherein the safety information comprises first state information for representing a working state of an operator and second state information for representing a working state of the safety belt.

[0043] The first state information at least comprises acceleration and angular velocity of the operator; the first state information can be measured by an inertial measurement unit arranged in the safety belt. Of course, the first state information can also be measured by an acceleration sensor and an angular velocity sensor arranged separately outside the safety belt.

[0044] The second state information at least comprises tension information of the safety belt, closing pressure and closing angle in the safety belt buckle. In order to facilitate data acquisition, a pressure sensor and an angle sensor are arranged in the safety belt buckle to obtain closing force and closing angle data. Specifically, the pressure sensor can be arranged on the abutting surface of the elastic closing abutment of the buckle.

[0045] In order to obtain more accurate data, the data collected by the pressure sensor and the angle sensor can be filtered by a Kalman filtering algorithm. Such a setting is conducive to obtaining more smooth and accurate force and angle data.

[0046] For example, in the safety belt buckle monitoring process, each data point collected by the pressure sensor and the angle sensor contains a 32-bit timestamp; the data processing unit uses a 5-point moving average filter with a filter window size of 50 ms, effectively eliminating noise above 20 Hz. The abnormality determination algorithm uses a double threshold method, with a force threshold of 200 N ± 10 N and an angle threshold of 5° ± 0.5°, and a 1-second duration judgment is introduced to avoid false positives caused by transient fluctuations.

[0047] The tension information of the safety belt can be obtained by the tension detection device. The tension detection device can use a foil strain gauge with a sensitivity of 2 mV / V / ε arranged in a full-bridge circuit to improve measurement accuracy. The data acquisition circuit samples at a frequency of 100 Hz and converts the analog signal to a digital signal through a 24-bit ADC, with a resolution of 0.1 N. A 5-point window median filter is used to further effectively remove transient peak interference and improve data accuracy. In addition, a Kalman filtering algorithm can be used to process the data. In the Kalman filtering algorithm, the state vector includes tension and tension rate, the observation noise covariance matrix is set according to the strain gauge specification, and the process noise covariance matrix is determined through experiments.

[0048] S102, determining the safety belt state information of the safety belt based on the first state information.

[0049] After completing the above step S101, in this step, the safety belt state information of the safety belt is determined based on the first state information, wherein the safety belt state information is used to represent the working state of the first safety belt and the second safety belt during the operation process, and the working state at least includes the force state of the currently stressed safety belt.

[0050] Further, as shown in Figure 2 The determination of the working state information of the safety belt based on the first state information includes the following steps:

[0051] S201, activating the electronic switching device based on the first state information and obtaining force state data.

[0052] In this step, the electronic switching device is activated based on the first state information. The electronic switching device is used to realize automatic switching between the first safety belt and the second safety belt during the operation of the operator.

[0053] Specifically, the worker wears a smart safety belt containing an inertial measurement unit during work, which collects 100 times of acceleration and angular velocity data per second, so that the working state of the worker can be determined through the acceleration and angular velocity, for example, the worker is in a motion state or a static state.

[0054] When the acceleration and angular velocity exceed the preset switching threshold, that is, the position change amplitude of the worker exceeds the preset threshold, the electronic switching device is automatically activated, triggering the safety belt switching program, and starting to record the force state data of the current safety belt.

[0055] S202, determining the safety belt state information of the safety belt based on the force state data.

[0056] After the electronic switching device is activated, the safety belt state information of the safety belt is determined based on the force state data in this step.

[0057] Specifically, the force state data of the current safety belt is recorded. The electronic switching device receives the force state data of the safety belt, evaluates the current safety belt force index using a multi-level safety threshold, for example, the multi-level safety threshold can include a warning threshold of 2000N, a danger threshold of 3000N and a critical threshold of 4000N. When the force exceeds the warning threshold but is lower than the danger threshold, a prompt warning is issued; when the force exceeds the danger threshold, the switching program is triggered to switch the force safety belt from the first safety belt to the second safety belt, and the second safety belt locking mechanism is started to ensure that the second safety belt is in a ready state.

[0058] In order to further ensure the safety of the worker during work, the determination of the safety belt state information based on the first state information further comprises:

[0059] The safety state of the worker is evaluated, and the state information of the safety belt is updated based on the evaluation result.

[0060] Specifically, the electronic switching device calls a pre-trained random forest classifier to evaluate the safety state of the worker according to the force curve slope change rate data, and the input features include the safety belt force state, the position change speed and the acceleration. When the evaluation result shows that the worker is in a high-risk state, the safety belt locking instruction is triggered, a warning signal is sent to the monitoring center, and the second safety belt is immediately started to realize seamless switching and ensure uninterrupted protection throughout the process.

[0061] Wherein, the Kalman filtering algorithm uses a state vector [F, v] to represent the safety belt force F and the stretching speed v, and the observation equation is established based on the sensor measurement value. The filtered data is used to calculate the force curve slope, and if the slope change rate exceeds the preset value 0.5N / s 2, a potential fall risk is determined. The random forest classifier uses 1000 decision trees, and the input features include the smoothed seatbelt force, position change velocity, and acceleration.

[0062] The classifier outputs a safety state probability, and the first seatbelt is locked and the second seatbelt is activated when the high-risk state probability exceeds 80%. During the switching process, the first seatbelt and the second seatbelt are forced at the same time, ensuring a seamless transition, and the total switching time does not exceed 100 milliseconds. The entire process is controlled by an embedded processor with a processing frequency of 1 kHz, ensuring real-time response. Real-time communication is maintained with the monitoring center through an industrial Internet of Things module, with a data transmission delay of less than 50 milliseconds, ensuring the timeliness of remote monitoring and emergency response.

[0063] S103, determining seatbelt safety information of the seatbelt based on the second state information, wherein the seatbelt safety information includes first safety information and / or second safety information.

[0064] After completing the above step S102, in this step, the seatbelt safety information of the seatbelt is determined based on the second state information, wherein the seatbelt safety information includes first safety information and / or second safety information.

[0065] Further, Figure 3 A flowchart of the step of determining the first safety information of the seatbelt based on the second state information is shown, as shown in the figure, determining the first safety information of the seatbelt based on the second state information includes the following steps:

[0066] S301, determining the locking state of the seatbelt based on the second state information.

[0067] After obtaining the second state information, in this step, the locking state of the seatbelt is determined based on the second state information.

[0068] Specifically, the force and angle data of the lock are obtained through the pressure sensor and angle sensor located inside the seatbelt lock, and whether the lock is completely closed is judged according to the preset threshold, so as to obtain the locking state of the seatbelt, wherein the locking state includes normal state and abnormal state.

[0069] In order to improve the accuracy of the data, Kalman filtering algorithm is used to filter the data collected by the pressure sensor and angle sensor, so as to obtain more smooth and accurate force and angle data. According to the preset force threshold and angle threshold, whether the lock is completely closed is judged by fuzzy comprehensive evaluation method. If the force or angle is abnormal, i.e. the force is lower than the preset force threshold or the angle does not reach the preset angle threshold, it is determined as abnormal state.

[0070] In the locking state judgment process, the support vector machine (SVM) algorithm can be used to train the historical data to obtain the force and angle model when the lock is normally closed, which is used for subsequent real-time data anomaly judgment.

[0071] In actual application, the high-precision sensor is used to monitor the closing state of the seat belt buckle in real time, and each data point contains a 32-bit timestamp. The data processing unit uses a 5-point moving average filter with a filter window size of 50 ms to effectively eliminate noise above 20 Hz. The abnormality determination algorithm uses a double-threshold method, with a force threshold of 200 N ± 10 N and an angle threshold of 5° ± 0.5°, and a 1-second duration judgment is introduced to avoid false positives caused by transient fluctuations.

[0072] S302, determining first safety information of the safety belt based on the locking state.

[0073] After completing the above step S301, in this step, the first safety information of the safety belt is determined based on the locking state, wherein the first safety information includes first warning information of the safety belt.

[0074] Specifically, when it is determined that the lock is in an abnormal state, an alarm signal is triggered, and the alarm signal is transmitted to the single-chip microcomputer through the CAN bus protocol. After receiving the alarm signal, the single-chip microcomputer transmits the alarm signal to the ground terminal through the wireless communication module, sends the warning information to the ground worker, and prompts the worker that the safety belt state is abnormal. At the same time, the single-chip microcomputer can also control the buzzer to emit an alarm sound to remind the worker that the safety belt lock is not completely closed.

[0075] In order to improve the safety performance, the state monitoring module checks the abnormal flag every 10 ms, and uses a state machine to manage different levels of alarms. The alarm signal priority division adopts a decision tree algorithm, wherein the emergency level trigger condition is set as force < 100 N or angle > 10°, the warning level trigger condition is set as 100 N ≤ force < 200 N or 5° < angle ≤ 10°, and the attention level trigger condition is set as 200 N ≤ force < 250 N or 3° < angle ≤ 5°. By setting different warning levels, different safety prompts are provided to the worker.

[0076] Further, Figure 4 A step flow chart for determining second safety information of the safety belt based on the second state information is shown in the figure. Figure 4 As shown, determining the second safety information of the safety belt based on the second state information includes the following steps:

[0077] S401, determining the real-time stress state of the safety belt based on the second state information.

[0078] In this step, the real-time stress state of the safety belt is determined based on the second state information.

[0079] Specifically, the rope stress data of the safety belt is collected in real time by the strain gauge, and the rope parameters such as the elastic modulus, tensile strength, diameter, and length of the rope material are obtained, and the safety load range of the rope is determined based on the rope parameters, so as to determine the stress state of the safety belt.

[0080] The sampling frequency of the strain gauge is set to 100 Hz, the data is converted into digital signals by a 24-bit analog-to-digital converter, and stored in the buffer of the detection device, and the median filter is used to remove outliers. The data processing unit reads the stress data from the buffer, uses the Kalman filter algorithm to process the data, and combines the pre-obtained rope material, elastic modulus, tensile strength, diameter, and length parameters to calculate the real-time stress state of the rope by Hooke's law. At the same time, the elastic modulus of the rope is adjusted in real time according to the temperature and humidity sensor data.

[0081] In one specific embodiment of the present application, the rope parameters are obtained by table lookup method, the temperature range is-20℃ to 50℃, the humidity range is 0% to 100% RH, and the step size is 5℃ and 10% RH respectively. The elastic modulus adjustment range is ±10% of the nominal value. The safety load lookup table is pre-generated based on finite element analysis, considering the rope diameter of 5mm to 20mm, the length of 1m to 100m, and the material including nylon, polyester and steel wire rope, forming a total of 1000 data points. The real-time stress calculation uses the generalized Hooke's law.

[0082] S402, determining the second safety information of the safety belt based on the real-time stress state.

[0083] After completing the above step S401, in this step, the second safety information of the safety belt is determined based on the real-time stress state, wherein the second safety information includes second warning information.

[0084] Specifically, according to the rope parameters and the stress-strain curve, the safety load range of the rope can be determined by table lookup, and the current stress state is compared with the safety load range in real time, and according to the position of the stress state relative to the safety load range, the second safety information of the safety belt is determined. For example, three levels of mild, moderate, and severe warnings can be set according to the overload degree, and the warning information, duration, and position information are compressed and encrypted, and the transmission priority is set according to the warning level, and sent to the monitoring center through the wireless transmission module.

[0085] The pre-warning classification is determined according to the relative relationship between the stress state and the safe load, for example, when the stress state is at 80%-90% of the safe load, it is a mild pre-warning; when the stress state is at 90%-100% of the safe load, it is a moderate pre-warning; and when the stress state is greater than 100% of the safe load, it is a severe pre-warning. The data compression adopts a lossless compression algorithm LZMA, and the compression ratio can reach 2:1. Encryption adopts the AES-256 algorithm, and the key is automatically updated every hour. Wireless transmission adopts LoRa technology, the working frequency band is 470MHz, and the transmission distance can reach 5km.

[0086] In S104, the pre-warning information of the safety belt is determined based on the safety belt state information and the safety belt safety information.

[0087] In the step S103, the pre-warning information of the safety belt is determined based on the operation state information and the safety belt safety information.

[0088] Specifically, the safety belt state information, the first safety information and the second safety information obtained in the foregoing steps are summarized, the position of the operator and the rope information are combined, the safety risk level of the operator and the equipment is accurately evaluated, and the intuitive display is realized through the man-machine interface.

[0089] In the process of data processing, the data can be directly displayed, or the original data can be cleaned to obtain a standardized data set. For the standardized data set, a distributed information filtering algorithm is used for spatio-temporal fusion to generate a unified state estimation vector. If the state estimation vector exceeds the preset safety threshold, the comprehensive safety risk score is calculated according to the pre-set risk level division standard, and the risk level is judged.

[0090] To improve the stability of the device operation, the ground terminal adopts a high-performance industrial computer, equipped with an Inteli7-10700 processor and 32 GB of memory, and can receive multi-source heterogeneous data at a real-time sampling rate of 100 Hz. The data preprocessing module uses a 5x5 window median filter for denoising, and z-score standardization normalizes the data to the range of [-1, 1]. The distributed information filtering algorithm uses 5 sub-filters, each responsible for different sensor data, and the state vector contains 15 variables. The prediction step of the Kalman filter uses a uniform acceleration motion model, and the measurement noise covariance matrix of the update step is dynamically adjusted according to the sensor accuracy. The Bayesian network contains 20 nodes, and the parameters are learned using maximum likelihood estimation. The timestamp alignment uses a sliding window method with a window size of 100 ms. The analytic hierarchy process constructs a 4-layer structure containing 12 risk factors, and the weights are determined by a 9-point scale method. OpenGL rendering uses Vertex Buffer Object technology, rendering 60 frames per second, and the scene contains 1000 polygon models. The human-machine interface uses a 15-inch capacitive touch screen with a resolution of 1920x1080 and supports 10-point touch control. The voice control uses an offline speech recognition engine with a vocabulary of 5000 words and an accuracy of 95%.

[0091] In another embodiment of the present application, in order to further improve the safety of the operating personnel, the method further comprises generating operating personnel misoperation warning prompt information based on safety belt state information, Figure 5 The steps of generating operating personnel misoperation warning prompt information based on safety belt state information provided by the present application are shown in the flow chart Figure 5 As shown, the steps include:

[0092] S501, determining the first locking state of the first safety belt and the second locking state of the second safety belt based on the safety belt state information.

[0093] In this step, the locking state of the first safety belt and the locking state of the second safety belt are determined based on the safety belt state information. The working state of the safety belt is obtained by the gyroscope or tension sensor arranged on the first safety belt and the second safety belt, wherein the acquisition frequency is not less than 20 times per second, the distal end continuously judges the locking state of the two safety belts, and at least one of the first safety belt and the second safety belt is in the locking state during the operation of the operating personnel, thereby ensuring the operation safety of the operating personnel.

[0094] S502, when the first locking state and the second locking state are both in the unlocked state, generating and sending a locking state error prompt information.

[0095] In this step, when the first locking state and the second locking state are both in the unlocked state, a locking state error prompt information is generated and sent.

[0096] Specifically, when the logic determines that both the first locking state and the second locking state are in the unlocked state, it is considered that the first safety belt and the second safety belt are in the unfastened state due to the operation error of the worker, and a locking state error prompt information is generated and sent to the worker. The locking state prompt information can be sent to the worker through a buzzer or a signal lamp.

[0097] Further, after determining the pre-warning information of the safety belt based on the safety belt state information and the safety belt safety information, the method further comprises: generating safety control information based on the pre-warning information.

[0098] Specifically, after determining the pre-warning information, safety control information is generated based on the pre-warning information. A high-altitude work safety knowledge base is established using knowledge graph technology, and risk pre-warning and disposal suggestions are provided for guardians through an inference engine to assist in formulating safety control measures. The knowledge graph construction module uses a Neo4j graph database and an OpenKG tool set to extract key concepts and relationships from multiple sources of text such as high-altitude work safety specifications, accident cases, and expert experience, to construct a high-altitude work safety knowledge graph containing entity types such as equipment, environment, personnel, risk, and measures, and to realize the fusion of real-time data and static knowledge through a dynamic graph update algorithm. The inference engine, based on the constructed knowledge graph, uses a hybrid inference framework combining rule-based reasoning and case-based reasoning to analyze multi-dimensional data, identify potential risk factors and dangerous scenarios by matching similar historical cases and applying predefined safety rules.

[0099] In one specific embodiment of the present application, the Neo4j graph database stores a knowledge graph of 100,000 nodes and 500,000 relationships, and the OpenKG tool set realizes 80% accuracy of entity recognition and relationship extraction. The dynamic graph update algorithm is updated every 10 seconds to ensure the timeliness of the knowledge. The hybrid inference framework contains 500 IF-THEN rules and 1000 historical cases, uses the Rete algorithm for rule matching and the K-nearest neighbor algorithm for case retrieval, and the comprehensive accuracy reaches 85%. The AHP risk assessment model is constructed in a 4-layer structure containing 20 evaluation indexes with a consistency ratio CR<0.1. The decision tree generation algorithm uses CART pruning with a tree depth limit of 5 layers and a leaf node number of no more than 50. The human-computer interaction interface supports a 15-inch touch screen and voice control with a response time of less than 100 ms.

[0100] In order to ensure the timeliness of signal transmission between the operating personnel and the ground monitoring personnel, multi-modal information fusion is adopted in the signal transmission process, integrating multiple transmission methods such as wireless communication, visible light communication and sound wave communication to ensure the reliability of wireless transmission, adaptively selecting the optimal transmission channel according to the degree of environmental interference, obtaining the frequency, bandwidth and transmission power parameters of the wireless signal, judging the signal-to-noise ratio and error rate of the transmission link, so as to improve the real-time performance and reliability of information transmission, and ensure that the ground terminal receives the equipment state and personnel safety data in time.

[0101] Among them, the multi-modal information acquisition module simultaneously obtains the intensity, frequency and bandwidth data of the wireless signal (2.4GHz sampling), visible light signal (100MHz sampling) and sound wave signal (44.1kHz sampling), converts the analog signal into digital signal through high-speed sampling circuit, and stores it in the buffer. The environmental interference evaluation unit uses wavelet transform algorithm to perform time-frequency analysis on the collected signal, calculates the signal-to-noise ratio (signal power to noise power ratio) and interference intensity of each channel, and judges the current environment type and interference degree by combining the pre-set environment feature library, and continuously updates the environment feature library through online learning mechanism. The channel selection optimizer calculates the transmission efficiency score of each channel according to the environmental interference evaluation result, and the state transition equation considers the factors such as signal intensity, bandwidth, power consumption and time delay, the objective function is to maximize the transmission efficiency, and the optimal transmission channel combination is selected. The adaptive transmission controller dynamically adjusts the frequency, bandwidth and transmission power of the wireless signal according to the selected channel combination, configures the modulation method of visible light communication and the encoding format of sound wave communication, improves the transmission reliability through forward error correction coding, realizes the real-time transmission of equipment state and personnel safety data, and uses pseudo-random bit sequence for error rate estimation, uses data buffer and interpolation mechanism to ensure transmission continuity when channel switching.

[0102] Specifically, the multi-modal information acquisition module uses high-performance ADC chip, the wireless signal is collected at a sampling rate of 2.4GHz, the quantization accuracy is 16 bits; the visible light signal is collected at a sampling rate of 100MHz, the quantization accuracy is 14 bits; the sound wave signal is collected at a sampling rate of 44.1kHz, the quantization accuracy is 24 bits. The environmental interference evaluation unit uses db4 wavelet basis function for 5-level wavelet decomposition to extract the energy features of each frequency band. The signal-to-noise ratio is calculated by the formula 20*log10(P signal / P noise ) where P signal and P noiserespectively, are the root mean square power of signal and noise. The environmental feature library initially contains 100 typical scenes, and online learning and updating are achieved through the K-means clustering algorithm, and the clustering center is updated once every 24 hours. The state space of the dynamic programming algorithm of the channel selection optimizer is all combinations of {Wi-Fi, 4G, visible light, sound wave}, and the state transition cost considers the switching delay (typical value 50 ms) and energy consumption (Wi-Fi 100 mW, 4G 500 mW, visible light 50 mW, sound wave 10 mW). The objective function is to maximize the throughput to energy consumption ratio, and the Viterbi algorithm is used to solve the optimal path. The adaptive transmission controller uses adaptive modulation and coding for wireless signals, visible light communication uses OOK / PPM / VPPM three modulation modes, and sound wave communication uses FSK / PSK encoding. Forward error correction uses LDPC code, and the code rate can be adaptively adjusted between 1 / 2 and 9 / 10. The bit error rate estimation uses a M sequence with a length of 2^15-1, and is estimated once per second. The data buffer uses a double buffering mechanism, and the buffer size is 1MB. The three times spline interpolation algorithm is used to maintain data continuity when switching channels.

[0103] The safety belt locking state dynamic perception early warning method provided by the application can realize automatic switching of the safety belt, accurately monitor the closing state of the safety belt lock, accurately evaluate the safety risk level, significantly improve the safety and monitoring ability of high-altitude operation, and avoid the situation of high-altitude operation personnel misoperating to unfasten all safety belts or unfastening safety belts when habitually violating regulations to shift, thereby ensuring that the operation personnel continuously operate under the protection of the safety belt and eliminating the risk of high-altitude falling.

[0104] Embodiment 2

[0105] To better implement the above method, the second aspect of the present disclosure also provides a safety belt locking state dynamic perception early warning device, which can be integrated on an electronic device.

[0106] For example, as shown in Figure 6 The early warning device 200 can include an acquisition module 210, a first determination module 220, a second determination module 230, and a generation module 240, as follows:

[0107] (1) An acquisition module 210 is configured to acquire safety information of a safety belt, wherein the safety belt comprises a first safety belt and a second safety belt, the safety information comprises first state information for representing a working state of a worker and second state information for representing a working state of an installation belt, the first state information at least comprises acceleration and angular velocity of the worker, and the second state information at least comprises tension information of the safety belt, closing pressure inside a safety belt buckle, and a closing angle.

[0108] (2) A first determination module 220 is configured to determine safety belt state information of the safety belt based on the first state information.

[0109] (3) A second determination module 230 is configured to determine safety belt safety information of the safety belt based on the second state information, wherein the safety belt safety information comprises first safety information and / or second safety information.

[0110] (4) A generation module 240 is configured to generate early warning information of the safety belt based on the safety belt state information and the safety belt safety information.

[0111] Further, the acquisition module 210 comprises a detection unit and a correction unit, wherein the detection unit is configured to detect magnetic flux around a safety belt buckle, and the correction unit is configured to acquire current environment information, wherein the environment information at least comprises temperature and humidity, and correct the magnetic flux based on the environment information.

[0112] Further, the first determination module 220 comprises a first determination unit and a second determination unit, wherein the first determination unit is configured to determine a change rate of the magnetic flux around the safety belt buckle based on the safety parameter information, and the second determination unit is configured to determine state information of the safety belt buckle based on the change rate of the magnetic flux.

[0113] Further, the alarm device 200 further comprises an update module, which is configured to update the safety level based on pressure information of a clamping groove of the safety belt buckle.

[0114] The update module comprises a first acquisition unit, a verification unit, and an update unit, wherein the first acquisition unit is configured to acquire pressure information of a clamping groove of the safety belt buckle, the verification unit is configured to verify the safety level based on the pressure information, and the update unit is configured to update the safety level when the pressure information is inconsistent with the safety level.

[0115] The safety belt locking state dynamic perception early warning device provided by the application can realize automatic switching of the safety belt, accurately monitor the closing state of the safety belt buckle, accurately evaluate the safety risk level, and significantly improve the safety and monitoring capability of high-altitude operation, thereby avoiding the situation that the high-altitude operator mistakenly releases all safety belts or releases the safety belt protection when habitually violating the regulations, ensuring that the operator continuously operates under the protection of the safety belt, and eliminating the risk of falling from a high altitude.

[0116] Embodiment 3

[0117] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions or by related hardware controlled by the instructions, which can be stored in a computer readable storage medium and loaded and executed by a processor.

[0118] To this end, the third embodiment of the present disclosure provides a storage medium, which is a computer readable medium and stores a computer program, and the computer program is executed by a processor to implement the method provided by the embodiments of the present disclosure, including the following steps S11 to S14:

[0119] S11, obtaining safety information of a safety belt, wherein the safety belt includes a first safety belt and a second safety belt, the safety information includes first state information for representing a working state of an operator and second state information for representing a working state of an installed belt, the first state information at least includes acceleration and angular velocity of the operator, and the second state information at least includes tension information of the safety belt, closing pressure and closing angle inside the safety belt buckle;

[0120] S12, determining safety belt state information of the safety belt based on the first state information;

[0121] S13, determining safety belt safety information of the safety belt based on the second state information, wherein the safety belt safety information includes first safety information and / or second safety information;

[0122] S14, generating early warning information of the safety belt based on the safety belt state information and the safety belt safety information.

[0123] Further, the computer program is executed by the processor to implement other methods provided by any one of the above embodiments of the present disclosure.

[0124] By applying the storage medium provided by the present invention, the safety information of the seat belt is obtained by executing the dynamic perception and warning method for the seat belt locking status, and the seat belt status information of the seat belt is determined based on the first status information, so as to realize automatic switching of the seat belt and accurately monitor the closing status of the seat belt buckle; the seat belt safety information of the seat belt is determined based on the second status information, and the warning information of the seat belt is generated based on the seat belt status information and the seat belt safety information, so as to accurately evaluate the safety risk level and significantly improve the safety and monitoring capabilities of high-altitude operations. In actual application, it can avoid the situation in which high-altitude workers accidentally unfasten all seat belts or unfasten the seat belt protection when habitually shifting in violation of regulations, thereby ensuring that workers continue to work under the protection of seat belts and eliminating the risk of falling from heights.

[0125] Example 4

[0126] A fourth embodiment of the present disclosure provides an electronic device, such as Figure 7 As shown, the electronic device includes at least a memory 310 and a processor 320. The memory 310 stores a computer program. The processor 320 implements the method provided by any embodiment of the present disclosure when executing the computer program on the memory 310. Exemplarily, the method executed by the electronic device computer program is as follows:

[0127] S21, obtaining safety information of the safety belt, wherein the safety belt includes a first safety belt and a second safety belt, and the safety information includes first status information for representing a working status of an operator and second status information for representing a working status of the installation belt, wherein the first status information includes at least acceleration and angular velocity of movement of the operator, and the second status information includes at least tension information of the safety belt, closing pressure inside the safety belt buckle, and closing angle;

[0128] S22, determining seat belt status information of the seat belt based on the first status information;

[0129] S23, determining seat belt safety information of the seat belt based on the second state information, wherein the seat belt safety information includes first safety information and / or second safety information;

[0130] S24: Generate the seat belt warning information based on the seat belt status information and the seat belt safety information.

[0131] In specific implementation, the acquisition module 210 , the first determination module 220 , the second determination module 230 and the generation module 240 are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.

[0132] The electronic device provided by the application can obtain safety information of the safety belt by executing the safety belt locking state dynamic sensing and early warning method, and determine safety belt state information of the safety belt based on the first state information, so as to realize automatic switching of the safety belt and accurately monitor the closing state of the safety belt buckle. The safety belt safety information of the safety belt is determined based on the second state information, the early warning information of the safety belt is generated based on the safety belt state information and the safety belt safety information, the safety risk level can be accurately evaluated, the safety and monitoring capability of the aerial work are significantly improved, the situation that the aerial work personnel mistakenly operate to unfasten all safety belts or unfasten the safety belts for habitual violation of regulations when shifting can be avoided in actual application, the work personnel can be ensured to continuously work under the protection of the safety belt, and the risk of falling from a high altitude is eliminated.

[0133] The storage medium can be included in the electronic device, or can exist separately and not be assembled into the electronic device.

[0134] The storage medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device is caused to: obtain at least two internet protocol addresses; send a node evaluation request including the at least two internet protocol addresses to a node evaluation device, wherein the node evaluation device selects an internet protocol address from the at least two internet protocol addresses and returns; receive the internet protocol address returned by the node evaluation device; and wherein the obtained internet protocol address indicates an edge node in a content distribution network.

[0135] Alternatively, the storage medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device is caused to: receive a node evaluation request including at least two internet protocol addresses; select an internet protocol address from the at least two internet protocol addresses; return the selected internet protocol address; and wherein the received internet protocol address indicates an edge node in a content distribution network.

[0136] Computer program code for carrying out operations of the present disclosure can be written in any one or combination of the following programming languages or combinations thereof: object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as the "C" programming language or similar programming languages. The program code can execute entirely on the passenger computer, partly on the passenger computer, as a stand-alone software package, partly on the passenger computer and partly on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the passenger computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0137] Note that the storage medium described above in the present disclosure can be either a computer readable signal medium or a computer readable storage medium or any combination thereof. The computer readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination thereof. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program used by or in connection with an instruction execution system, apparatus or device. In the present disclosure, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave in a propagated transmission, where the data signal contains the computer readable program code. Such a propagated transmission can take place in various forms, including but not limited to electro-magnetic, optical, or any suitable combination thereof. The computer readable signal medium can also be any medium that can be used to store the program and which can be read by an instruction execution system, apparatus or device, or any combination thereof. The program code contained in the storage medium can be transmitted as a data signal in any suitable format, including but not limited to wireless, wireline, optical, or any suitable combination thereof.

[0138] The computer program product of the first aspect can include one or more non-transitory computer-readable media storing instructions that, when executed, cause one or more processors to perform the operations of the method of the first aspect. The computer program product of the first aspect can include a computer-readable medium storing instructions that, when executed, cause one or more processors to perform the operations of the method of the first aspect.

[0139] The units described in the embodiments of the present disclosure can be implemented by software, or by hardware, or by a combination of software and hardware. In some cases, the names of the units do not constitute a limitation on the units themselves.

[0140] The functions described in this document can be implemented in part or in whole using one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Program-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs).

[0141] In the context of the present disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more of: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0142] The above description merely illustrates the preferred embodiments of the disclosure and a principle of applied technologies. It should be understood by those skilled in the art that the disclosed range of the disclosure is not limited to the technical solutions formed by the specific combinations of the technical features described above, and should also cover other technical solutions formed by the combinations of the technical features described above or their equivalent features without departing from the above disclosed concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features with similar functions disclosed in the disclosure (but not limited to) should be covered.

[0143] In addition, although each operation is described in a particular order, this should not be understood as requiring the operations to be performed in the specific order shown or in a sequential order. In certain circumstances, multitasking and parallel processing can be advantageous. Similarly, although several implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the disclosure. Certain features described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented separately or in any suitable subcombination. For the purposes of the present disclosure, the term "coupled" and its derivatives refer to any direct or indirect communication between entities, which can be

[0144] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

[0145] The above describes in detail the plurality of embodiments of the disclosure, but the disclosure is not limited to these specific embodiments, and those skilled in the art can make various modifications and embodiments on the basis of the concept of the disclosure, and these modifications and embodiments should fall within the scope of the disclosure claimed.

Claims

1. A method for dynamic perception and early warning of seat belt locking status, characterized in that: include: Obtaining safety information of the safety belt, wherein the safety belt includes a first safety belt and a second safety belt, and the safety information includes first status information for representing a working status of an operator and second status information for representing a working status of the installation belt, wherein the first status information includes at least acceleration and angular velocity of movement of the operator, and the second status information includes at least tension information of the safety belt, closing pressure inside the safety belt buckle, and closing angle; determining, based on the first status information, seatbelt status information of the seatbelt; including: the seatbelt status information is used to characterize the working status of the first and second seatbelts during operation, the working status including the stress state of the current stress-bearing seatbelt; activating an electronic switching device based on the first status information, the electronic switching device being used to automatically switch between the first and second seatbelts during the operation of the operator; when the acceleration and angular velocity exceed a preset switching threshold, the electronic switching device is automatically activated, triggering a seatbelt switching program, and starting to record the stress state data of the current seatbelt; the electronic switching device receives the seatbelt stress state data, evaluates the current seatbelt stress index using a multi-level safety threshold, and issues a prompt warning when the stress exceeds a warning threshold but is lower than a danger threshold; when the stress exceeds the danger threshold, triggering a switching program to switch the stress-bearing seatbelt from the first seatbelt to the second seatbelt, and activating a second seatbelt locking mechanism to ensure that the second seatbelt is in a ready state; evaluating the safety status of the operator, and updating the seatbelt status information based on the evaluation result; determining seatbelt safety information of the seatbelt based on the second state information, wherein the seatbelt safety information includes first safety information and second safety information; The seat belt warning information is generated based on the seat belt status information and the seat belt safety information.

2. The seat belt locking state dynamic perception and warning method according to claim 1, characterized in that: Determining first safety information of the seat belt based on the second state information includes: determining a locking state of the seat belt based on the second state information; First safety information of the seat belt is determined based on the locking state.

3. The seat belt locking state dynamic perception and warning method according to claim 1, characterized in that: Determining second safety information of the seat belt based on the second state information includes: determining a real-time stress state of the seat belt based on the second state information; Second safety information of the seat belt is determined based on the real-time stress state.

4. The seat belt locking state dynamic perception and warning method according to claim 1, characterized in that: The method further includes generating operator misoperation warning information based on the safety belt status information, including the following steps: determining a first locking state of the first seat belt and a second locking state of the second seat belt based on the seat belt state information; When the first locking state and the second locking state are both unlocked states, a locking state error prompt message is generated and sent.

5. The seat belt locking state dynamic perception and warning method according to claim 1, characterized in that: After determining the seat belt warning information based on the seat belt status information and the seat belt safety information, the method further includes: generating safety management information based on the warning information.

6. A seat belt locking state dynamic sensing and warning device, characterized in that: include: an acquisition module, configured to acquire safety information of the safety belt, wherein the safety belt includes a first safety belt and a second safety belt, and the safety information includes first status information for representing a working status of an operator and second status information for representing a working status of the installation belt, wherein the first status information includes at least acceleration and angular velocity of movement of the operator, and the second status information includes at least tension information of the safety belt, closing pressure inside the safety belt buckle, and closing angle; a first determining module, configured to determine seatbelt status information of the seatbelt based on the first status information; the seatbelt status information is used to characterize the operating status of the first and second seatbelts during operation, the operating status including the stress state of the current stress-bearing seatbelt; an electronic switching device is activated based on the first status information; the electronic switching device is configured to automatically switch between the first and second seatbelts during operation; when the acceleration and angular velocity exceed a preset switching threshold, the electronic switching device is automatically activated, triggering a seatbelt switching program and beginning to record the current seatbelt stress state data; the electronic switching device receives the seatbelt stress state data, evaluates the current seatbelt stress index using a multi-level safety threshold, and issues a warning when the stress exceeds a warning threshold but is below a danger threshold; and when the stress exceeds the danger threshold, triggers a switching program to switch the stress-bearing seatbelt from the first seatbelt to the second seatbelt and activates the second seatbelt locking mechanism to ensure that the second seatbelt is in a ready state; evaluates the safety status of the operator, and updates the seatbelt status information based on the evaluation result; a second determining module, configured to determine seat belt safety information of the seat belt based on the second state information, wherein the seat belt safety information includes first safety information and / or second safety information; A generating module generates the seat belt warning information based on the seat belt status information and the seat belt safety information.

7. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the seat belt locking state dynamic perception and warning method according to any one of claims 1 to 5 are implemented.

8. An electronic device comprising at least a memory and a processor, wherein the memory stores a computer program, wherein: The processor implements the steps of the seat belt locking state dynamic perception and warning method according to any one of claims 1 to 5 when executing the computer program on the memory.

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