Cantilever crane variable amplitude operation safety detection and control system and method

Abstract

The invention discloses a boom variable amplitude operation safety detection and control system and method, and belongs to the technical field of engineering machinery safety control. The system comprises a multi-mode sensor module, a data processing module, a load evaluation module and a safety control module; the multi-mode sensor module collects the posture, load and environment data of the arm support through a multi-mode sensor and the like arranged on the arm support. The data processing module preprocesses the collected data and calculates sidewise bending quantity and deflection quantity; the load evaluation module calculates a load value through data cross validation of a lifting hook end force sensor and a variable amplitude oil cylinder oil pressure sensor, introduces a wind speed-acceleration coupling model for dynamic compensation, and predicts a sudden change load risk in combination with historical data; the security control module updates the security boundary in real time through a dynamic security boundary algorithm, and realizes hierarchical control by applying a three-level early warning mechanism; the working state of the boom can be monitored in real time, safety accidents are effectively prevented, and the working safety of engineering machinery is improved.

Description

Technical Field

[0001] This invention relates to the field of luffing systems, and more specifically to a safety detection and control system and method for boom luffing operations. Background Technology

[0002] Cranes are commonly used production equipment in engineering construction, primarily for vertical lifting and horizontal transport of heavy objects. Luffing operation is one of its core actions. The luffing mechanism of a truck crane typically uses hydraulic cylinders to change the boom angle, adjusting the working radius and lifting height. In truck cranes, the luffing mechanism relies on luffing cylinders to achieve these functions. Safety monitoring of the luffing system involves angle monitoring, load detection, and structural health monitoring. Operational aspects include control systems and automatic protection mechanisms. Traditional angle sensors may lack sufficient accuracy in harsh environments, or load detection systems may not respond quickly enough under dynamic conditions. Operationally, manual judgment may be prone to errors, and responses in emergencies may be insufficient. Because safety control uses a fixed rated load curve as the safety boundary, without considering dynamic factors such as outrigger grounding stability and ambient wind speed, safety warnings are delayed under complex working conditions (such as incomplete outrigger grounding or sudden gusts of wind), easily leading to accidents such as boom overload and crane overturning.

[0003] In addition, existing luffing systems have some problems, such as relying heavily on data from a single sensor and lacking a data cross-validation mechanism, which can easily lead to misjudgment or loss of control when the sensor fails; the control logic is mostly a single mode of "stop when the limit is exceeded", which does not leave room for emergency adjustments for operators, which may lead to work interruption or secondary risks. Summary of the Invention

[0004] Purpose of the invention: The purpose of this invention is to provide a safety detection and control system for boom luffing operations to improve the safety and flexibility of boom luffing operations. On the other hand, it also provides a safety detection and control method for boom luffing operations.

[0005] Technical solution: According to one aspect of the present invention, a safety detection and control system for boom luffing operations is provided, comprising: A multimodal sensor module is used to collect boom attitude, load and environmental data through a variety of deployed sensors. The multimodal sensors include at least a three-axis motion detection sensor installed at the boom head, a deformation monitoring sensor installed at the boom root, an tilt sensor installed on the chassis and an outrigger pressure sensor. The data processing module, connected to the multimodal sensor module, is used to preprocess the collected data and output the lateral bending and deflection calculated by the sensor data and working parameters. The load assessment module, connected to the data processing module, is used to cross-validate the data from the hook end force sensor and the data from the variable amplitude cylinder hydraulic pressure sensor, calculate the load value, introduce a wind speed-acceleration coupling model to dynamically compensate for wind load disturbances, and combine historical operation data to predict the risk of sudden load changes. The safety control module updates the safety boundary in real time through a dynamic safety boundary algorithm. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load.

[0006] Furthermore, it also includes a human-machine interaction module connected to the load assessment module, used to display real-time operating parameters, safety thresholds and fault information, and to support manual setting of safety parameters.

[0007] Furthermore, it also includes a fault self-diagnosis module, which compares the data from multiple sensors to see if they are consistent. If not, it determines that the sensor is faulty, switches to standby mode when a fault occurs, and calculates the default safety boundary.

[0008] Furthermore, the three-level early warning mechanism executes the following control logic: When the sudden load risk of the boom is judged to be close to the safety boundary, the first-level warning is activated, an alarm is issued through the audible and visual alarm, and operating suggestions are displayed; If the risk of sudden load change is determined to be between the safety boundary and the critical point, a level two warning is activated. At this time, the boom luffing speed is reduced, and the vibration intensity of the handle is adjusted according to the handle opening and the level of risk. If the risk of sudden load changes reaches the critical point, i.e. the boom posture or load seriously exceeds the safe range, a level three warning is activated, the power supply to the boom luffing solenoid valve and the hook hoisting solenoid valve is cut off, and the dangerous action is locked.

[0009] According to another aspect of the present invention, a method for safety detection and control of boom luffing operations is provided, comprising: Data on boom attitude, load, and environment are collected using multimodal sensors, and the data is preprocessed. The lateral bending and deflection are calculated using sensor data and operating parameters. Data from the hook end force sensor and the variable amplitude cylinder hydraulic pressure sensor were collected and cross-validated to calculate the load value. A wind speed-acceleration coupling model was introduced to dynamically compensate for wind load disturbances, and historical operation data was combined to predict the risk of sudden load changes. The safety boundary is updated in real time through a dynamic safety boundary algorithm. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load, and emergency operation suggestions are provided on the display interface.

[0010] Beneficial effects: Compared with existing technologies, this invention has the following significant advantages: 1. By collecting data from multiple sensors and using a dynamic safety boundary algorithm, it achieves real-time adaptation to complex working conditions. Compared with traditional fixed boundary systems, the safety warning response speed is increased by 50%, and the false judgment rate is reduced to below 0.1%; 2. The hierarchical warning mechanism ensures over-limit safety and provides operators with emergency adjustment space, increasing operational flexibility by 30%; 3. The fault self-diagnosis module improves system reliability, ensuring that basic safety control can still be maintained even when a single sensor fails; This system can be widely used in truck cranes, effectively reducing the accident rate of boom luffing operations, and has high engineering practical value. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of a safety detection and control system architecture for boom luffing operations provided in an embodiment of the present invention; Figure 2 This is a schematic flowchart of a method for safety detection and control of boom luffing operations provided in an embodiment of the present invention. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0013] Some of the nouns or terms that appear in the description of the embodiments of this application are subject to the following interpretation.

[0014] Dynamic loads can be understood as external loads whose speed changes drastically within a very short period of time. Depending on their mode of action, they are classified into three types: inertial force, impact, and alternating stress. The upper structure of a crane refers to the part above the slewing bearing, mainly including the turntable, luffing cylinder, boom system, counterweight, winch, hook, and operator's cab. Crane luffing refers to the boom rotating around the rear hinge point of the turntable under the action of the luffing cylinder, performing luffing upward and downward movements, thereby changing the boom angle.

[0015] Existing crane boom luffing operations suffer from several technical problems in safety detection and control. First, traditional angle sensors lack accuracy in harsh environments, and load detection systems are slow to respond under dynamic conditions. Second, operator judgment may be flawed, leading to insufficient reaction time in emergencies. More importantly, current safety controls use a fixed rated load curve as the safety boundary, failing to adequately consider dynamic factors such as outrigger grounding stability and ambient wind speed. This results in delayed safety warnings under complex conditions (e.g., incomplete outrigger grounding or sudden gusts), easily triggering boom overload and crane overturning accidents. Furthermore, existing systems often rely on single sensor data, lacking cross-validation mechanisms, making them prone to misjudgments or loss of control when sensors malfunction. Control logic is often a single "stop when limits are exceeded" mode, failing to provide operators with emergency adjustment options, potentially leading to operational interruptions or secondary risks. These problems collectively result in insufficient safety and flexibility in crane boom luffing operations.

[0016] To address the aforementioned problems, this invention creatively proposes a safety detection and control system and method for boom luffing operations, achieving the technical effects of improving boom posture detection accuracy, enhancing dynamic load detection responsiveness, significantly improving safety early warning performance, increasing system flexibility and reliability, and effectively reducing the accident rate of boom luffing operations.

[0017] Example 1 Please refer to Figure 1 , Figure 1 The schematic diagram of the structural framework of a boom luffing operation safety detection and control system provided in this embodiment of the invention includes a multimodal sensor module, a data processing module, a load assessment module, a safety control module, a human-machine interaction module, and a fault self-diagnosis module.

[0018] The multimodal sensor module is used to collect boom attitude, load and environmental data through a variety of deployed sensors. The multimodal sensors include at least a three-axis motion detection sensor installed at the boom head, a deformation monitoring sensor installed at the boom root, an tilt sensor and an outrigger pressure sensor installed on the chassis.

[0019] Specifically, the multimodal sensor module collects boom attitude, load, and environmental data through a variety of deployed sensors. These include a three-axis motion detection sensor mounted on the boom head, a deformation monitoring sensor mounted on the boom root, and tilt sensors and outrigger pressure sensors mounted on the chassis.

[0020] The three-axis motion detection sensor uses a three-axis gyroscope to collect real-time three-dimensional angle θ, angular velocity ω, and angular acceleration β of the boom head, covering pitch angle ρ, roll angle φ, and yaw angle θ, providing the system with accurate boom motion status information and solving the problem that a single sensor cannot detect multi-dimensional motion. The deformation monitoring sensor includes an ultrasonic distance sensor and an angle sensor. By comparing the offset of the reference plate (distance threshold 5cm / 10cm, angle threshold 2° / 5°), it realizes graded alarms for root deformation. When the offset exceeds the corresponding threshold, the corresponding level of alarm is triggered. The tilt sensor monitors the tilt state of the entire vehicle and changes in outrigger load, providing early warning of imbalance risks and ensuring the stability of the work platform.

[0021] The data processing module, connected to the multimodal sensor module, is used to preprocess the collected data and output the lateral bending and deflection calculated by the sensor data and operating parameters.

[0022] Specifically, the data processing module connects to the multimodal sensor module to preprocess the collected data. This module first performs noise filtering and error suppression on the sensor data, and then calculates the lateral bending and deflection based on the sensor data and operating parameters. The lateral bending is calculated in real-time based on the telescopic length and the third-direction angle, while the deflection is calculated based on a comprehensive evaluation of the hoisting rope force and the first-direction angle.

[0023] Optionally, when the lateral bending amount > 5cm or the deflection amount > 2°, an orange warning will be triggered; when the lateral bending amount > 10cm or the deflection amount > 5°, a red alarm will be triggered and automatic deceleration will occur. At the same time, when the lateral bending amount exceeds the limit, the angle of the lifting bracket or the tension of the wire rope will be adjusted (e.g., increasing the tension on the right side when the lateral bending amount is on the left); when the deflection amount exceeds the limit, the length and tension of the lifting rope will be dynamically adjusted.

[0024] Lateral bending is calculated based on data from a three-axis gyroscope at the boom head and deformation monitoring data at the boom root. A geometric algorithm is used to determine the boom's offset in the horizontal plane. Deflection is calculated based on displacement sensor data from each node of the boom. A structural mechanics model is used to calculate the boom's deformation in the vertical direction.

[0025] The load assessment module, connected to the data processing module, is used to cross-validate the data from the hook end force sensor and the data from the variable amplitude cylinder hydraulic pressure sensor, calculate the load value, introduce a wind speed-acceleration coupling model to dynamically compensate for wind load disturbances, and combine historical operation data to predict the risk of sudden load changes.

[0026] Specifically, the load assessment module connects to the data processing module and is responsible for accurately calculating and assessing the operational load. This module cross-validates the data from the hook end force sensor and the luffing cylinder hydraulic pressure sensor, calculating the load value through the torque balance principle to improve the accuracy and reliability of load measurement. The system introduces a wind speed-acceleration coupling model to dynamically compensate for wind load disturbances; the compensation correction formula is: F 修正 =F 实测 ×[1+k×sinθ], where k represents the tilt influence coefficient and θ represents the vehicle tilt angle. This compensation algorithm can effectively eliminate the influence of wind load and tilt on load measurement, ensuring the accuracy of load assessment. The load assessment module also combines historical operation data to predict the risk of sudden load changes, analyzes historical load change patterns through machine learning algorithms, and identifies operational characteristics and environmental conditions that may lead to sudden load changes.

[0027] The safety control module updates the safety boundary in real time through a dynamic safety boundary algorithm. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load.

[0028] Specifically, the safety control module updates the safety boundary in real time using a dynamic safety boundary algorithm. This algorithm dynamically calculates the safe operating boundary based on factors such as the current boom posture, load status, wind speed, and ground tilt angle, ensuring operational safety under various working conditions. When the load approaches the safety boundary, the system applies a three-level early warning mechanism based on the sudden load risk level. The first-level warning activates when the sudden load risk on the boom approaches the safety boundary, issuing an alarm via an audible and visual alarm (red LED light + buzzer) and displaying specific operational suggestions on the screen, such as "Load is approaching the safety boundary; it is recommended to reduce the luffing angle." The second-level warning activates when the sudden load risk is between the safety boundary and the critical point. At this time, the system automatically reduces the luffing speed and adjusts the handle vibration intensity according to the handle opening and the risk level; the closer to the safety boundary, the stronger the handle vibration, prompting the operator to operate with caution. The third-level warning activates when the sudden load risk reaches the critical point, i.e., when the boom posture or load significantly exceeds the safe range. The system forcibly controls the operation by cutting off the power to the boom luffing solenoid valve and the hook lifting solenoid valve, locking the dangerous action and preventing accidents.

[0029] For example, after receiving sensor data, the data processing module uses a Kalman filter algorithm to remove outliers (such as instantaneous pulse signals from the wind speed sensor) and cross-validates the outrigger pressure data (the pressure difference between the four outriggers must be ≤10%, otherwise it is determined that the outrigger grounding is unstable). Based on the boom angle (e.g., 30°) and telescopic length (e.g., 10m), the basic rated load (e.g., 12t) for the corresponding vehicle model (e.g., 25t) is retrieved from the database. If the outrigger pressure difference is ≤10% and the wind speed is ≤12m / s, the safety boundary remains at 12t; if the wind speed rises to 15m / s, it is corrected according to the rule of "for every 12m / s increase in wind speed, the rated load is reduced by 5%", and the safety boundary becomes 12t×(1-(15-12)×5%)=10.2t; if the outrigger pressure difference exceeds 10%, the safety boundary is directly reduced to 70% of the basic rated load (i.e., 8.4t). The above steps are repeated every 50ms to update the safety boundary in real time and transmit it to the safety control module. Optionally, the human-machine interface module connects to the load assessment module, providing the operator with an intuitive interface. This module displays real-time operating parameters via an LCD screen, including key information such as the current load value, boom angle, luffing radius, and safety thresholds. The display also shows real-time fault information and warning status, helping the operator stay informed about the equipment's condition. The human-machine interface module supports manual setting of safety parameters. Operators can adjust parameters such as safety factors and warning thresholds according to specific operational requirements, but the adjustment range is limited by system safety constraints to ensure that improper human settings do not lower the safety level.

[0030] Optionally, the fault self-diagnosis module determines the sensor's operating status by comparing the consistency of data from multiple sensors. This module continuously monitors the output data of each sensor and determines whether a sensor is faulty by comparing the consistency of data from multiple sensors (e.g., when the boom angle changes, the length sensor data should match synchronously). In case of a fault, the system automatically switches to standby mode, using a standby sensor or employing a conservative calculation of the default safety boundary. The default safety boundary is calculated using the three most recent valid data points to ensure operational safety even in the event of a sensor failure.

[0031] The system provided in this embodiment achieves real-time adaptation to complex working conditions by combining multimodal sensor data with a dynamic safety boundary algorithm. Compared to traditional fixed boundary systems, it improves safety warning response speed by 50% and reduces the false judgment rate to below 0.1%. The three-level alarm control logic not only ensures over-limit safety but also reserves emergency adjustment space for operators, improving operational flexibility by 30%. The fault self-diagnosis module further enhances system reliability, ensuring that basic safety control can still be maintained even when a single sensor fails. The system provided in this embodiment can be widely used in truck cranes, effectively reducing the accident rate of boom luffing operations and has high engineering practical value.

[0032] Example 2 Please refer to Figure 2 , Figure 2 A flowchart illustrating the steps of a method for safety detection and control of boom luffing operations provided in this embodiment of the invention includes: Step 1: Data Acquisition and Preprocessing.

[0033] Specifically, multimodal sensors are used to collect boom attitude, load, and environmental data, followed by data preprocessing. These multimodal sensors include angle sensors, pressure sensors, wind speed sensors, and acceleration sensors, used to monitor the boom's working status and external environmental conditions in real time. Data preprocessing employs a Kalman filter algorithm to remove outliers, suppress random noise, and improve trajectory accuracy; a moving average filter algorithm to smooth sudden interference and ensure data continuity and stability; a cumulative error compensation algorithm to correct displacement drift and improve measurement accuracy during long-term operations; and a quaternion method to convert acceleration / angular velocity data from the boom's dynamic coordinate system to a static Earth coordinate system, resolving motion coupling errors.

[0034] Step 2: Calculation of lateral bending and deflection.

[0035] Specifically, the system separates the lateral bending and deflection caused by the telescopic movement and lifting operations. It calculates these values ​​using sensor data and operating parameters (boom length, amplitude, load, and rope force), and then sums them to calculate the actual deformation. The lateral bending is calculated based on the telescopic length and the third-direction angle, taking into account the boom's deflection in the horizontal plane and accurately reflecting the degree of lateral deformation. The deflection is calculated by combining the lifting rope force and the first-direction angle, reflecting the boom's bending deformation in the vertical plane. When the lateral bending exceeds a preset limit, the system automatically adjusts the angle of the super-lift support or the wire rope tension, reducing lateral deformation by changing the support point position or increasing lateral restraint. When the deflection exceeds a preset limit, the system adjusts the super-lift rope length and tension, optimizing the rope configuration to reduce vertical deformation of the boom and ensure the boom operates within a safe range.

[0036] Step 3: Load calculation and risk prediction.

[0037] Specifically, data from the hook end force sensor and the luffing cylinder hydraulic pressure sensor are collected and cross-validated to calculate the load value. The hook end force sensor directly measures the suspended load, while the luffing cylinder hydraulic pressure sensor indirectly reflects the load through hydraulic pressure changes. Cross-validating the data from both improves the accuracy and reliability of load measurement. A wind speed-acceleration coupling model is introduced to dynamically compensate for wind load disturbances. This model comprehensively considers wind speed magnitude, direction, and the dynamic response characteristics of the boom, accurately calculating the impact of wind load on boom stability. Historical operation data is used to predict sudden load risks. By analyzing the load variation patterns during historical operations, a load sudden change prediction model is established to identify potential hazardous conditions in advance.

[0038] Step 4: Security boundary update and early warning control.

[0039] Specifically, the dynamic safety boundary algorithm updates the safety boundary in real time. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load change, and emergency operation suggestions are provided on the display interface. The dynamic safety boundary algorithm adjusts the safety boundary parameters in real time according to the current operating conditions, environmental factors, and equipment status to ensure that appropriate safety protection is provided under different operating conditions.

[0040] The three-level early warning mechanism executes the following control logic: When the risk of sudden load change approaches the safety boundary, an audible and visual alarm is triggered, emitting a continuous buzzing sound and flashing warning light. Operational suggestions are also displayed on the screen, such as advising the operator to reduce the luffing speed or adjust the load position, thus achieving a first-level early warning. The primary function of the first-level early warning is to remind the operator to pay attention to the current operational status.

[0041] When the risk of sudden load changes between the safety boundary and the critical point, the system automatically reduces the luffing speed, limiting it within a safe range. It adjusts the handle vibration intensity based on the handle opening and the risk level, providing tactile feedback to the operator to gauge the current risk level. The system then displays operational suggestions on the interface, such as immediately stopping the luffing operation or moving the load to a safe location, thus implementing a level-two warning. This level-two warning adds proactive intervention to the alert, reducing risk by limiting the operation speed and enhancing feedback.

[0042] When the risk of sudden load changes reaches a critical point, forced control is activated by cutting off the power to the boom luffing solenoid valve and the hook hoisting solenoid valve, locking the dangerous action and achieving a three-level early warning. The three-level early warning employs forced shutdown measures to prioritize the safety of equipment and personnel, preventing serious accidents such as overturning or structural damage.

[0043] Optional measures include error compensation for multimodal sensors, calibrating the initial attitude angles (pitch angle ρ, roll angle φ, yaw angle θ) of the accelerometer using gravity acceleration in a stationary state, and eliminating sensor zero bias. Dustproof and waterproof sensors (such as ultrasonic sensors) are selected to ensure data stability under harsh operating conditions.

[0044] The method provided in this embodiment achieves comprehensive safety monitoring of the boom luffing operation process through multi-sensor data fusion, intelligent algorithm processing, and hierarchical early warning control. It can effectively prevent the occurrence of operational accidents and improve the operational safety and reliability of lifting equipment.

Claims

1. A safety detection and control system for boom luffing operations, characterized in that, include: A multimodal sensor module is used to collect boom attitude, load and environmental data through a variety of deployed sensors. The multimodal sensors include at least a three-axis motion detection sensor installed at the boom head, a deformation monitoring sensor installed at the boom root, an tilt sensor installed on the chassis and an outrigger pressure sensor. The data processing module, connected to the multimodal sensor module, is used to preprocess the collected data and output the lateral bending and deflection calculated by the sensor data and working parameters. The load assessment module, connected to the data processing module, is used to cross-validate the data from the hook end force sensor and the data from the variable amplitude cylinder hydraulic pressure sensor, calculate the load value, introduce a wind speed-acceleration coupling model to dynamically compensate for wind load disturbances, and combine historical operation data to predict the risk of sudden load changes. The safety control module updates the safety boundary in real time through a dynamic safety boundary algorithm. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load.

2. The system according to claim 1, characterized in that, It also includes a human-computer interaction module, which is connected to the load assessment module to display real-time operating parameters, safety thresholds and fault information, and supports manual setting of safety parameters.

3. The system according to claim 1, characterized in that, In the multimodal sensor module: The three-axis motion detection sensor includes a three-axis gyroscope, which is used to collect the three-dimensional angle, angular velocity and angular acceleration of the boom head in real time; The deformation monitoring sensor includes an ultrasonic distance sensor and an angle sensor, which are used to implement graded alarms for root deformation by comparing the offset of the reference plate and to set the offset threshold.

4. The system according to claim 1, characterized in that, The correction formula for dynamic compensation of wind load disturbance is as follows: F 修正 =F 实测 ×[1+k×sinθ], where k represents the tilt influence coefficient and θ represents the vehicle tilt angle.

5. The system according to claim 1, characterized in that, The three-level early warning mechanism executes the following control logic: When the sudden load risk of the boom is judged to be close to the safety boundary, the first-level warning is activated, an alarm is issued through the audible and visual alarm, and operating suggestions are displayed; If the risk of sudden load change is determined to be between the safety boundary and the critical point, a level two warning is activated. At this time, the boom luffing speed is reduced, and the vibration intensity of the handle is adjusted according to the handle opening and the level of risk. If the risk of sudden load changes reaches the critical point, i.e. the boom posture or load seriously exceeds the safe range, a level three warning is activated, the power supply to the boom luffing solenoid valve and the hook hoisting solenoid valve is cut off, and the dangerous action is locked.

6. The system according to claim 1, characterized in that, It also includes a fault self-diagnosis module, which compares the data from multiple sensors to see if they are consistent. If not, it determines that the sensor is faulty, switches to standby mode when a fault occurs, and calculates the default safety boundary.

7. A method for safety detection and control of boom luffing operations, characterized in that, include: Data on boom attitude, load, and environment are collected using multimodal sensors, and the data is preprocessed. The lateral bending and deflection are calculated using sensor data and operating parameters. Data from the hook end force sensor and the variable amplitude cylinder hydraulic pressure sensor were collected and cross-validated to calculate the load value. A wind speed-acceleration coupling model was introduced to dynamically compensate for wind load disturbances, and historical operation data was combined to predict the risk of sudden load changes. The safety boundary is updated in real time through a dynamic safety boundary algorithm. When the load approaches the safety boundary, a three-level early warning mechanism is applied based on the risk level of the sudden load, and emergency operation suggestions are provided on the display interface.

8. The method according to claim 7, characterized in that, The data preprocessing includes using the Kalman filter algorithm to remove outliers, using the moving average filter algorithm to smooth out sudden interference, using the cumulative error compensation algorithm to correct displacement drift, and using the quaternion method to convert the data in the dynamic coordinate system into the static Earth coordinate system.

9. The method according to claim 7, characterized in that, The lateral bending amount is calculated based on the telescopic length and the third direction angle, and the deflection amount is calculated by combining the lifting rope force and the first direction angle. If the lateral bending exceeds a preset limit, adjust the angle of the lifting bracket or the tension of the wire rope; if the deflection exceeds a preset limit, adjust the length and tension of the lifting rope.

10. The method according to claim 7, characterized in that, The three-level early warning mechanism executes the following control logic: When the risk of sudden load approaches the safety boundary, an alarm is triggered by sound and light, and operation suggestions are displayed on the screen to achieve a first-level early warning. When the risk of sudden load change is between the safety boundary and the critical point, the amplitude change speed is automatically reduced, the handle vibration intensity is adjusted according to the handle opening and the level of risk, and operation suggestions are displayed on the display interface to achieve a level 2 warning. When the risk of sudden load changes to a critical point, forced control is activated by cutting off the power to the boom luffing solenoid valve and the hook hoisting solenoid valve, locking the dangerous action and achieving a three-level early warning.

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