A hoisting construction process with fall arrestor for prefabricated buildings

Abstract

This invention relates to the field of building construction technology and discloses a hoisting construction process with fall arrest locking for prefabricated buildings, comprising the following steps: S1, pre-hoisting preparation and intelligent verification; S2, component hooking and status self-check; S3, lifting and full-process active fall arrest monitoring; S4, judgment and execution of multi-level fall arrest locking mechanism; S5, precise positioning and intelligent assisted docking; S6, safe unlocking and installation confirmation; S7, data recording and process iteration. This invention, by introducing an intelligent decision and control unit, a multi-sensor fusion perception system, and a multi-level fall arrest locking mechanism, achieves intelligent monitoring and active safety protection throughout the entire hoisting process. It significantly improves hoisting safety by implementing a layered response from risk warning to emergency locking through three-level fall arrest locking, especially in the event of electrical control failure, where it can still quickly lock through purely mechanical means, effectively preventing fall accidents.

Description

Technical Field

[0001] This invention relates to the field of building construction technology, and more specifically to a hoisting construction process with anti-fall lock for prefabricated buildings. Background Technology

[0002] The hoisting and installation of prefabricated buildings is a crucial part of on-site operations, and its safety and precision directly affect the quality and progress of the project.

[0003] Traditional hoisting processes generally rely on manual experience for operation and monitoring, lacking systematic and intelligent safety protection and precise control measures. The hoisting process suffers from insufficient monitoring of component posture, stress balance, and path deviation, making it prone to component swaying, collisions, and even falls due to operational errors, wind disturbances, and mechanical failures. The positioning stage often relies on visual inspection and manual adjustment, resulting in low alignment efficiency, large errors, and impacting connection quality. Furthermore, existing fall protection measures are mostly single mechanical or electrical locking mechanisms with limited response speed and reliability, lacking a tiered and collaborative active protection mechanism, and failing to achieve full-process data traceability and continuous process optimization. Therefore, there is an urgent need for a hoisting construction process that integrates intelligent sensing, multi-level fall protection, and precise control to improve the safety, accuracy, and intelligence level of prefabricated building construction. Summary of the Invention

[0004] To overcome the shortcomings of existing hoisting technologies, which generally rely on manual experience for operation and monitoring, lack systematic and intelligent safety protection and precise control methods, and are prone to component swaying, collision, or even falling accidents due to operational errors, wind disturbances, mechanical failures, etc., this invention provides a hoisting construction process with anti-fall lock for prefabricated buildings to solve the problems existing in the background technology.

[0005] This invention provides the following technical solution: a hoisting construction process with fall arrestor for prefabricated buildings, comprising the following steps: S1, Pre-lifting preparation and intelligent verification: Before lifting the component, the information of the component to be lifted is entered into the intelligent decision and control unit by scanning the component identification code; the lifting system presets the optimal lifting path and swing suppression strategy based on this information, and sets the trigger threshold for the multi-level anti-fall locking mechanism based on the component type and weight. S2, Component hook and status self-check: The operator connects the lifting device to the preset lifting point of the component and starts the system self-check program; the intelligent sensing system monitors in real time whether the force on each lifting point is balanced and whether the sling is vertical, and checks whether each locking unit in the multi-level anti-fall locking mechanism is in a standby ready state; the system allows the lifting command to be executed only after all self-check items pass. S3, Enhancement and Full-Process Active Fall Protection Monitoring: Throughout the entire process of component movement, the intelligent sensing system works continuously, collecting real-time information on the component's spatial position, motion acceleration, attitude angle, force on the suspension point, and distance to surrounding obstacles; the intelligent decision and control unit compares and analyzes this real-time data with the preset path and trigger threshold in step S1; S4, Judgment and Execution of Multi-level Fall Protection Locking Mechanism: During the full monitoring of step S3, if the intelligent decision and control unit determines that an abnormal state has occurred, the corresponding multi-level fall protection locking mechanism will be triggered according to the type and severity of the abnormality. S5, Precise Positioning and Intelligent Assisted Docking: After the component is moved above the installation position, the hoisting system switches to precise positioning mode; the visual recognition module and millimeter-wave radar work together to guide the component to descend slowly, and provide real-time feedback on the alignment deviation between the component's embedded parts and the reserved steel bars or connectors in the lower structure until the preset docking accuracy range is reached; S6, Safety Unlocking and Installation Confirmation: After the system confirms that the component has been temporarily supported from below or initially stabilized by the installers, the intelligent decision and control unit releases the locking status of the multi-level anti-fall locking mechanism in sequence according to the safety sequence, and completes the unhooking of the lifting device; S7, Data Recording and Process Iteration: The sensor data, control commands, abnormal events and operation time of the entire hoisting process are encrypted and stored in the data management module to form a unique "hoisting digital file" for the component, which is used for quality traceability and subsequent process parameter optimization.

[0006] Preferably, the multi-level fall arrest mechanism in step S4 includes three levels of locking that operate sequentially. The first level is a warning and active correction locking mechanism, which is triggered when the component's attitude angle exceeds the limit, the path deviation is greater than the allowable value, or the force imbalance exceeds 30%. The system actively corrects the deviation by adjusting the speed difference of the hoist and outputs an audible and visual warning. The second level is an inertial-triggered mechanical hard locking mechanism, which completes a purely mechanical locking action independently of the electronic control system within 80 milliseconds when an abnormal vertical downward acceleration greater than 0.5g is directly sensed, locking the sling or boom. The third level is a final safety locking mechanism, which uses a burst-type locking pin as the actuating element. When the electronic control part of the system completely fails and the second-level locking does not achieve the expected effect, it is triggered by the backup power supply or directly by the sensor signal to provide a final locking guarantee.

[0007] Preferably, the core data for the intelligent verification in step S1 and the active fall protection monitoring in step S3 comes from a multi-sensor fusion intelligent sensing system. The intelligent sensing system includes an inertial measurement unit arranged on the hook or lifting device; a force sensor installed at the lifting point; a millimeter-wave radar installed on the lifting host or independent measuring station; and a high frame rate industrial camera installed under the lifting device.

[0008] Preferably, the intelligent assisted docking in step S5 specifically involves the visual recognition module using image recognition technology to capture and calculate the pixel deviation between the pre-embedded sleeve at the bottom of the component and the protruding steel bar of the lower structure in real time. Combined with the precise distance data measured by millimeter-wave radar, the alignment deviation is displayed in real time on the control interface.

[0009] Preferably, the status self-check in step S2 includes a periodic trigger test of the fall arrestor mechanism itself.

[0010] Preferably, the data in step S7 is stored locally and then uploaded to a cloud server via the network.

[0011] Preferably, during the movement in step S3, the intelligent decision and control unit executes a prediction-based collision avoidance strategy.

[0012] Preferably, this process is applicable to a variety of prefabricated components, including precast shear wall panels, precast columns, precast beams and precast floor slabs; for different types of components, the digital twin model called in step S1 and the locking parameters set are different.

[0013] Preferably, for wall panels with large areas and significant wind load effects, the model will focus on calculating wind resistance and setting a more sensitive attitude angle threshold; for column members with a slenderness ratio, the model will focus on controlling their sway amplitude and setting a more stringent rotation angle threshold.

[0014] Preferably, the hoisting system is equipped with an emergency manual over-control module. In extreme cases of automatic system failure, on-site commanders can send encrypted commands directly through a physically isolated dedicated emergency handheld terminal to prioritize triggering the second-level mechanical hard lock, or force the system to switch to the basic mode fully controlled by an experienced driver, ensuring that the construction process is not interrupted under safe and controlled conditions.

[0015] The beneficial effects of this invention are: This invention achieves intelligent monitoring and proactive safety protection throughout the entire hoisting process by introducing an intelligent decision-making and control unit, a multi-sensor fusion sensing system, and a multi-level anti-fall locking mechanism. It significantly improves hoisting safety by employing a three-level anti-fall locking system (early warning and correction, mechanical hard locking, and ultimate safety locking) to provide a layered response from risk warning to emergency locking. Especially in the event of electrical control failure, it can still quickly lock through purely mechanical means, effectively preventing fall accidents. It improves hoisting accuracy and efficiency. The intelligent assisted docking system based on vision and millimeter-wave radar can provide real-time feedback on alignment deviations and automatically enter a micro-motion mode, enabling rapid and accurate placement of components. It achieves digital management and continuous optimization of the construction process by recording data throughout the entire process through a "hoisting digital archive," supporting quality traceability and self-learning iteration of process parameters. It possesses good adaptability and robustness, calling corresponding digital twin models and locking parameters for different component types, and includes an emergency manual over-control module that can switch to manual operation mode in case of system failure, ensuring construction continuity and controllability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the overall process of the present invention and the core components on which each step depends.

[0018] Figure 2 This is a schematic diagram of the three-level locking mechanism included in the multi-level fall prevention locking mechanism of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] This invention provides a hoisting construction process with fall arrestor for prefabricated buildings, comprising the following steps: S1, Pre-lifting preparation and intelligent verification: Before lifting the component, the information of the component to be lifted is entered into the intelligent decision and control unit by scanning the component identification code. The information includes the component type, theoretical weight, three-dimensional dimensions, center of gravity position and target installation coordinates. The lifting system presets the optimal lifting path and swing suppression strategy based on this information, and sets the trigger threshold for the multi-level anti-fall locking mechanism based on the component type and weight. S2, Component hook and status self-check: The operator connects the lifting device to the preset lifting point of the component and starts the system self-check program; the intelligent sensing system monitors in real time whether the force on each lifting point is balanced and whether the sling is vertical, and checks whether each locking unit in the multi-level anti-fall locking mechanism is in a standby ready state; the system allows the lifting command to be executed only after all self-check items pass. S3, Enhancement and Full-Process Active Fall Protection Monitoring: Throughout the entire process of component movement, the intelligent sensing system works continuously, collecting real-time information on the component's spatial position, motion acceleration, attitude angle, force on the suspension point, and distance to surrounding obstacles; the intelligent decision and control unit compares and analyzes this real-time data with the preset path and trigger threshold in step S1; S4, Judgment and Execution of Multi-level Fall Protection Locking Mechanism: During the full monitoring of step S3, if the intelligent decision and control unit determines that an abnormal state has occurred, the corresponding multi-level fall protection locking mechanism will be triggered according to the type and severity of the abnormality. S5, Precise Positioning and Intelligent Assisted Docking: After the component is moved above the installation position, the hoisting system switches to precise positioning mode; the visual recognition module and millimeter-wave radar work together to guide the component to descend slowly, and provide real-time feedback on the alignment deviation between the component's embedded parts and the reserved steel bars or connectors in the lower structure until the preset docking accuracy range is reached; S6, Safety Unlocking and Installation Confirmation: After the system confirms that the component has been temporarily supported from below or initially stabilized by the installers, the intelligent decision and control unit releases the locking status of the multi-level anti-fall locking mechanism in sequence according to the safety sequence, and completes the unhooking of the lifting device; S7, Data Recording and Process Iteration: The sensor data, control commands, abnormal events and operation time of the entire hoisting process are encrypted and stored in the data management module to form a unique "hoisting digital file" for the component, which is used for quality traceability and subsequent process parameter optimization.

[0021] Specifically, the multi-level fall arrest mechanism in step S4 includes three levels of locking that operate sequentially. The first level is a warning and active correction locking mechanism, triggered when the component's attitude angle exceeds the limit, the path deviation exceeds the allowable value, or the force imbalance exceeds 30%. The system actively corrects the deviation by adjusting the speed difference of the hoist and outputs an audible and visual warning. The second level is an inertial-triggered mechanical hard locking mechanism, which, when an abnormal vertical downward acceleration greater than 0.5g is directly sensed, completes a purely mechanical locking action independently of the electronic control system within 80 milliseconds, locking the sling or boom. The third level is a final safety locking mechanism, using a burst-type locking pin as the actuating element. When the electronic control part of the system completely fails and the second-level locking does not achieve the expected effect, it is triggered by the backup power supply or directly by the sensor signal to provide a final locking guarantee.

[0022] Specifically, the core data for intelligent verification in step S1 and active fall protection monitoring in step S3 comes from a multi-sensor fusion intelligent sensing system. This system includes an inertial measurement unit (IMU) mounted on the hook or lifting device to monitor the component's triaxial acceleration, angular velocity, and the resulting attitude angles in real time; force sensors installed at the lifting points to sample the real-time load at each point at high frequency and calculate the force balance ratio; millimeter-wave radar installed on the lifting host or independent measuring station to non-contactly measure the real-time distance between the component and surrounding buildings, tower cranes, and scaffolding; and a high-frame-rate industrial camera installed under the lifting device for visual positioning and identification in step S5.

[0023] Specifically, the intelligent assisted docking in step S5 involves the visual recognition module using image recognition technology to capture and calculate the pixel deviation between the pre-embedded sleeve at the bottom of the component and the protruding steel bar of the lower structure in real time. Combined with the precise distance data measured by millimeter-wave radar, the alignment deviation is displayed in real time on the control interface. When the deviation value enters the range of ±10mm, the system enters the micro-motion mode, which automatically increases the control accuracy of the mechanism by an order of magnitude until the component is guided to complete the precise sleeve or grout placement.

[0024] Specifically, the status self-check in step S2 includes a periodic trigger test of the fall arrestor mechanism itself. Before starting work each day or after changing the type of component, the system controls the lifting equipment to raise the standard test counterweight to a safe height of 1 meter above the ground, and then simulates an abnormal signal to sequentially trigger each level of the locking mechanism to perform short-term action tests. The test results are recorded and compared with historical data. Only after confirming its effectiveness can the actual component be lifted.

[0025] Furthermore, the data from step S7 is stored locally while being uploaded to a cloud server via the network. The server-side algorithm continuously trains and optimizes the path planning algorithm and locking trigger threshold in the digital twin model using historical hoisting data, and periodically sends the optimized model parameters to the intelligent decision-making and control unit of the on-site hoisting system to achieve self-learning and continuous iterative optimization of the process.

[0026] Furthermore, during the movement in step S3, the intelligent decision and control unit executes a prediction-based collision avoidance strategy. The system not only monitors the current real-time distance but also predicts the trajectory in the next 2-5 seconds based on the component's speed and direction. If the predicted trajectory will interfere with an obstacle, the system will decelerate in advance or automatically plan an obstacle avoidance path and display avoidance suggestions on the interface, thereby reducing the probability of triggering emergency locking from a proactive prevention perspective.

[0027] Furthermore, the hoisting system is equipped with an emergency manual over-control module. In extreme cases of automatic system failure, on-site commanders can send encrypted commands directly through a physically isolated dedicated emergency handheld terminal to prioritize triggering the second-level mechanical hard lock, or force the system to switch to the basic mode fully controlled by an experienced driver, ensuring that the construction process is not interrupted under safe and controlled conditions.

[0028] In addition, this process is applicable to a variety of prefabricated components, including precast shear wall panels, precast columns, precast beams and precast floor slabs. For different types of components, the digital twin model called in step S1 and the locking parameters set are different. For wall panels with large area and significant wind load influence, the model will focus on calculating wind resistance and set a more sensitive attitude angle threshold. For column components with a slenderness ratio, the model will focus on controlling its swing amplitude and set a more stringent rotation angle threshold.

[0029] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A hoisting construction process with fall arrestor for prefabricated buildings, characterized in that, Includes the following steps: S1, Pre-lifting preparation and intelligent verification: Before lifting the component, the information of the component to be lifted is entered into the intelligent decision and control unit by scanning the component identification code; the lifting system presets the optimal lifting path and swing suppression strategy based on this information, and sets the trigger threshold for the multi-level anti-fall locking mechanism based on the component type and weight. S2, Component hook and status self-check: The operator connects the lifting device to the preset lifting point of the component and starts the system self-check program; the intelligent sensing system monitors in real time whether the force on each lifting point is balanced and whether the sling is vertical, and checks whether each locking unit in the multi-level anti-fall locking mechanism is in a standby ready state; the system allows the lifting command to be executed only after all self-check items pass. S3, Enhanced and Full-Process Active Fall Protection Monitoring: Throughout the entire process of component movement, the intelligent sensing system works continuously to collect information in real time on the component's spatial position, motion acceleration, attitude angle, force on the suspension point, and distance to surrounding obstacles; The intelligent decision and control unit compares and analyzes these real-time data with the preset paths and trigger thresholds in step S1; S4, Judgment and Execution of Multi-level Fall Protection Locking Mechanism: During the full monitoring of step S3, if the intelligent decision and control unit determines that an abnormal state has occurred, the corresponding multi-level fall protection locking mechanism will be triggered according to the type and severity of the abnormality. S5, Precise Positioning and Intelligent Assisted Docking: After the component is moved above the installation position, the hoisting system switches to precise positioning mode; the visual recognition module and millimeter-wave radar work together to guide the component to descend slowly, and provide real-time feedback on the alignment deviation between the component's embedded parts and the reserved steel bars or connectors in the lower structure until the preset docking accuracy range is reached; S6, Safety Unlocking and Installation Confirmation: After the system confirms that the component has been temporarily supported from below or initially stabilized by the installers, the intelligent decision and control unit releases the locking status of the multi-level anti-fall locking mechanism in sequence according to the safety sequence, and completes the unhooking of the lifting device; S7, Data Recording and Process Iteration: The sensor data, control commands, abnormal events and operation time of the entire hoisting process are encrypted and stored in the data management module to form a unique "hoisting digital file" for the component, which is used for quality traceability and subsequent process parameter optimization.

2. The hoisting construction process with fall arrestor for prefabricated buildings according to claim 1, characterized in that, The multi-level fall arrest mechanism in step S4 includes three levels of locking that operate sequentially. The first level is a warning and active correction locking mechanism, triggered when the component's attitude angle exceeds the limit, the path deviation exceeds the allowable value, or the force imbalance exceeds 30%. The system actively corrects the deviation by adjusting the speed difference of the hoist and outputs an audible and visual warning. The second level is an inertial-triggered mechanical hard locking mechanism, which, when an abnormal vertical downward acceleration greater than 0.5g is directly sensed, completes a purely mechanical locking action independently of the electrical control system within 80 milliseconds, locking the sling or boom. The third level is a final safety locking mechanism, using a burst-type locking pin as the actuating element. When the system's electrical control part completely fails and the second-level locking does not achieve the expected effect, it is triggered by the backup power supply or directly by the sensor signal to provide a final locking guarantee.

3. The hoisting construction process with fall arrestor for prefabricated buildings according to claim 2, characterized in that, The core data for the intelligent verification in step S1 and the active fall protection monitoring in step S3 comes from a multi-sensor fusion intelligent sensing system. The intelligent sensing system includes an inertial measurement unit deployed on the hook or lifting device; a force sensor installed at the lifting point; a millimeter-wave radar installed on the lifting host or independent measuring station; and a high frame rate industrial camera installed under the lifting device.

4. The hoisting construction process with fall arrestor for prefabricated buildings according to claim 3, characterized in that, The intelligent assisted docking in step S5 specifically involves the visual recognition module using image recognition technology to capture and calculate the pixel deviation between the pre-embedded sleeve at the bottom of the component and the protruding steel bars of the lower structure in real time. Combined with the precise distance data measured by millimeter-wave radar, the alignment deviation is displayed in real time on the control interface.

5. A hoisting construction process with fall arrestor for prefabricated buildings according to claim 4, characterized in that, The status self-check in step S2 includes a periodic trigger test of the fall arrestor mechanism itself.

6. A hoisting construction process with fall arrestor for prefabricated buildings according to claim 5, characterized in that, The data from step S7 is stored locally while being uploaded to a cloud server via the network.

7. A hoisting construction process with fall arrestor for prefabricated buildings according to claim 6, characterized in that, During the movement in step S3, the intelligent decision and control unit executes a prediction-based collision avoidance strategy.

8. A hoisting construction process with fall arrestor for prefabricated buildings according to claim 7, characterized in that, This process is applicable to a variety of prefabricated components, including precast shear wall panels, precast columns, precast beams and precast floor slabs; for different types of components, the digital twin model called in step S1 and the locking parameters set are different.

9. A hoisting construction process with anti-fall locking for prefabricated buildings according to claim 8, characterized in that, For wall panels with large areas and significant wind load effects, the model will focus on calculating wind resistance and setting a more sensitive attitude angle threshold; for column members with a slenderness ratio, the model will focus on controlling their sway amplitude and setting a more stringent rotation angle threshold.

10. A hoisting construction process with fall arrestor for prefabricated buildings according to claim 9, characterized in that, The hoisting system is equipped with an emergency manual over-control module. In extreme cases of automatic system failure, on-site commanders can send encrypted commands directly through a physically isolated dedicated emergency handheld terminal to prioritize triggering the second-level mechanical hard lock, or force the system to switch to the basic mode under the full control of an experienced driver, ensuring that the construction process is not interrupted under safe and controlled conditions.

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