Bending moment-free multi-hoisting point static counter dynamic hoisting method and system

Abstract

The application discloses a no-bending moment multi-hoisting point static-to-dynamic hoisting method and system, and belongs to the technical field of large structure hoisting. The method combines static mechanical planning before hoisting with dynamic closed-loop control during hoisting. Firstly, the hoisting points are calculated and adjusted to initial optimal positions according to module parameters. After hoisting, the force of each hoisting point and the module posture are monitored in real time, and the crane action and the hoisting point position are dynamically adjusted through a cooperative control system to realize force balance and posture correction, and finally the module is shifted, turned over and precisely positioned. The system comprises a servo-controlled crane, an adaptive sling with an adjustable hoisting point unit, a real-time monitoring system and a multi-hoisting point cooperative control system. The application actively suppresses the bending moment of the module during the whole hoisting process, and significantly improves the operation safety, precision and automation level.

Description

Technical Field

[0001] This invention relates to the field of large component hoisting technology, and more specifically, to a method and system for static-to-dynamic hoisting with multiple lifting points without bending moment. Background Technology

[0002] In shipbuilding, large steel structure installation, chemical module assembly, and heavy equipment handling, the overall hoisting of large modules is a critical construction step. These modules are typically characterized by their large size, heavy weight, relatively limited structural rigidity, and potential deviation of their center of gravity from their geometric center. During hoisting, uneven stress distribution at the lifting points or loss of module posture can generate enormous additional bending moments and shear stresses within the module. This unexpected stress can not only lead to permanent deformation or structural damage to the module itself but also significantly increase the safety risks of slings, lifting equipment, and hoisting devices, potentially even causing major accidents.

[0003] Currently, traditional methods for multi-point lifting of large modules mainly rely on operator experience and simple mechanical synchronization. Common practices include using fixed-spaced lifting beams or balance beams to distribute the load, or using multiple cranes to perform rough synchronization through unified command signals. These methods have significant limitations: First, fixed lifting equipment cannot dynamically adjust the lifting points according to the specific dimensions and center of gravity of the module, making it difficult to achieve ideal load distribution and eliminate initial bending moments. Second, during the entire dynamic process of lifting, shifting, turning, and lowering, reliance on manual observation and intervention makes it impossible to perceive and adjust the stress changes at each lifting point and the spatial posture of the module in real time and accurately, resulting in weak dynamic bending moment control. Third, the lack of systematic closed-loop control leads to lag in adjustments to cope with emergencies (such as instantaneous load transfer or wind interference), and the safety margin relies entirely on an excessively large design safety factor, resulting in poor economic efficiency.

[0004] As modular construction technology evolves towards larger, heavier, and more precise structures, higher demands are placed on the accuracy, safety, and automation of the hoisting process. The industry urgently needs a high-precision hoisting method and supporting system capable of intelligently adapting to different hoisting objects and automatically maintaining a near-moment-free stress state for the modules throughout the entire process. The core technical challenge lies in deeply integrating pre-hoisting static mechanical planning with dynamic real-time control during the hoisting process. Through high-precision monitoring, high-speed collaborative calculation, and accurate execution, this approach aims to achieve automatic balancing of forces at multiple hoisting points and stable closed-loop control of the module's attitude, fundamentally overcoming the shortcomings of traditional methods that rely on experience, have inefficient control, and carry high risks.

[0005] This invention addresses the shortcomings of the prior art described above. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a static-to-dynamic hoisting method and system with multiple lifting points and no bending moment.

[0007] To achieve the above objectives, the innovative aspects of this invention are as follows: It includes the following steps:

[0008] S1: Preparation before hoisting: Connect the multi-point adaptive lifting tool to the lifting lugs of the module to be hoisted, input the weight, size and center of gravity position parameters of the module to be hoisted in the human-machine interface, and start the various subsystems including the real-time monitoring system, the multi-point collaborative control system and the hoisting power system.

[0009] S2: Initial lifting point position adjustment: The multi-lifting point collaborative control system calculates the initial optimal position of each adjustable lifting point unit based on the input module parameters, with the goal of minimizing the overall bending moment of the lifted module, through the built-in force analysis model, and controls it to move to that position.

[0010] In step S2, the adjustable suspension point unit moves along the guide rail fixed to the main load-bearing frame via a drive mechanism; the guide rail is equipped with sliding auxiliary components to reduce friction and protective components for dust prevention.

[0011] The adjustable lifting point unit includes: a core load-bearing component for directly bearing the lifting load; a drive adjustment component connected to the core load-bearing component for driving the adjustable lifting point unit to move along the guide rail; and a positioning and locking component for locking the adjustable lifting point unit after it has moved to the target position.

[0012] S3: Initial Lifting Stress and Attitude Monitoring: Multiple servo-controlled cranes in the lifting power system synchronously and slowly lift the module to a preset height above the ground and then pause. Real-time stress data of each lifting point and tilt angle and displacement attitude data of the module are collected through a real-time monitoring system.

[0013] S4: Force Equilibrium and Attitude Closed-Loop Control: The multi-suspension point collaborative control system executes force equilibrium control and attitude closed-loop control based on the data collected in step S3. Force equilibrium control includes: calculating the deviation between the actual force and the ideal equilibrium force at each suspension point; if the deviation exceeds a first adaptive threshold, the deviation is reduced by adjusting the action of the corresponding servo-controlled crane or the position of the adjustable suspension point unit. Attitude closed-loop control includes: calculating the deviation between the module's real-time attitude and the target attitude; if the deviation exceeds a second adaptive threshold, the attitude is corrected by adjusting the action of the corresponding servo-controlled crane. The first and second adaptive thresholds are dynamically calculated and determined by the system based on the module weight, dimensions, and center of gravity position parameters input in step S1.

[0014] The first adaptive threshold and the second adaptive threshold are adaptively adjusted according to the weight and size of the suspended module: for modules with a weight greater than a preset value or a length greater than a preset length, the first adaptive threshold is narrowed, while the second adaptive threshold remains unchanged or is narrowed.

[0015] S5: Module shifting / turning: Based on the preset target position and posture parameters, the collaborative control system plans the motion trajectory of each servo-controlled crane, and under the closed-loop control of continuously performing step S4, the control module completes the shifting or turning action.

[0016] S6: Lowering and positioning: Hoist the module to the target position and lower it, continuously performing closed-loop control of step S4 during the lowering process.

[0017] Furthermore, the real-time monitoring system includes force sensors installed at each lifting point and attitude sensors installed on the lifted module. The force sensors and attitude sensors transmit data to the multi-lifting-point collaborative control system via an industrial Ethernet network using the Modbus TCP protocol. The system is also equipped with an industrial wireless module based on the LoRa or WiFi 6 protocol as a redundant communication link.

[0018] Furthermore, the multiple servo-controlled cranes in the hoisting power system are servo-controlled crawler cranes, and their hoisting mechanisms are equipped with high-precision encoders; the multi-point collaborative control system uses shielded twisted-pair cables with the PROFINETIO protocol to send control commands containing hoisting speed, position positioning and synchronization offset to the servo controllers of each servo-controlled crane in a fixed frame structure of "Header+Data+Checksum".

[0019] In force balance control, adjusting the servo-controlled crane's actions involves adjusting its lifting speed.

[0020] This invention provides a system for a hoisting method, characterized in that it includes:

[0021] The hoisting power system includes multiple servo-controlled cranes that can be independently controlled;

[0022] A multi-point adaptive spreader is used to connect the lifted module to the lifting power system. It includes a main load-bearing frame, a guide rail set on the main load-bearing frame, and several adjustable lifting point units that can move along the guide rail.

[0023] The real-time monitoring system is used to collect force data at each lifting point and attitude data of the lifted module in real time through force sensors and attitude sensors.

[0024] The multi-lifting-point collaborative control system communicates with the real-time monitoring system and the lifting power system. It includes a human-machine interface, a force balance control algorithm module, an attitude closed-loop control algorithm module, and a servo controller. The system receives monitoring data, dynamically calculates the force and attitude control thresholds, and outputs control commands through the closed-loop control algorithm to collaboratively control the movement of each servo-controlled crane and the position of the adjustable lifting point unit.

[0025] Furthermore, the drive adjustment component is an electric hoist or a servo cylinder; the basic guide rail component of the guide rail is made of high-strength wear-resistant material, the sliding auxiliary component is a roller group embedded in the bottom of the adjustable lifting point unit, and the protective component is a retractable dust cover covering the guide rail.

[0026] Furthermore, the hoisting power system has a servo-controlled crane with a hoisting speed control accuracy of ±0.01m / s, a position control accuracy of ±5mm, and a multi-machine synchronous offset of no more than 0.5mm.

[0027] Furthermore, the collaborative control system communicates in real time with the servo controllers of each servo-controlled crane using the PROFINETIO protocol, and controls the drive adjustment components of the adjustable lifting point unit using the CANopen protocol; sensor data from the real-time monitoring system is uploaded via the ModbusTCP protocol.

[0028] The technical effects and advantages of this invention are as follows:

[0029] 1. This invention achieves near-moment-free hoisting of large modules, fundamentally improving safety and structural integrity. Through a "static-to-dynamic" control strategy, it first performs static mechanical calculations based on module parameters to plan the initial optimal lifting point positions, optimizing load distribution from the outset. Then, throughout the hoisting process, high-frequency real-time monitoring and closed-loop control dynamically adjust the force on each lifting point and the module's attitude. This combined static and dynamic approach continuously and proactively suppresses additional bending moments within the module to extremely low levels, effectively avoiding permanent deformation or structural damage caused by uneven stress or attitude deviation. It significantly reduces the risk of overloading the module itself, slings, and lifting equipment during hoisting, fundamentally ensuring safety and reliability.

[0030] 2. This invention achieves intelligent and high-precision automation in the hoisting process, significantly reducing reliance on manual experience and improving operational efficiency. Through an integrated collaborative control system, high-precision sensors, and servo drive equipment, this invention constructs a complete perception-decision-execution closed loop. The system can automatically execute the entire process control from initial positioning, force leveling, attitude correction to path tracking, processing complex data in real time and making precise adjustments, raising the control precision of lifting speed, position synchronization, and attitude stability to levels far exceeding those of manual operation. This not only reduces the stringent requirements on operator experience and skills, minimizing the risk of human error and operational delays, but also makes hoisting operations more standardized and predictable, thereby significantly improving the overall efficiency and success rate of hoisting large and complex modules. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the overall structure of the hoisting tooling system of the present invention.

[0032] Figure 2 This is a schematic diagram of the multi-point adaptive lifting device in this invention.

[0033] Figure 3 This is a cross-sectional structural diagram of the adjustable suspension point unit in this invention.

[0034] Figure 4 This is a block diagram of the communication architecture of the tooling system of the present invention.

[0035] Figure 5 This is a flowchart of the "static-to-dynamic" hoisting control method of the present invention.

[0036] Explanation of the labels in the diagram:

[0037] 1-Lifted module; 21-Main load-bearing frame; 22-Adjustable lifting point unit; 221-Core load-bearing component; 222-Drive adjustment component; 223-Positioning and locking component; 23-Guide slide rail; 231-Roller assembly; 232-Retractable dust cover; 31-Force sensor; 32-Attitude sensor; 4-Multi-lifting point collaborative control system; 51-Servo-controlled crane; 7-Lifting lug. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0039] First embodiment: Module "static-to-dynamic" hoisting method with no bending moment and multi-point coordinated control.

[0040] This embodiment provides a moment-free, multi-point static-to-dynamic lifting method, suitable for high-precision, low-stress lifting operations of large structural modules (such as precast building components, ship hull sections, and large equipment). This method achieves a near-moment-free, balanced stress state for the module throughout the entire lifting process through a control strategy that combines static (theoretical modeling and planning) and dynamic (real-time monitoring and closed-loop adjustment) approaches.

[0041] The overall process of the method is as follows: Figure 5 As shown, the main steps include:

[0042] S1: Preparations before hoisting

[0043] The module 1 to be lifted is connected to the multi-point adaptive spreader via the lifting lug 7. The operator inputs key parameters such as the weight, geometric dimensions, and center of gravity of the module 1 to be lifted into the human-machine interface (part of the multi-point collaborative control system 4). Subsequently, the various subsystems of the system are activated, including the real-time monitoring system, the multi-point collaborative control system 4, and the lifting power system 5.

[0044] S2: Initial lifting point position adjustment

[0045] The multi-suspension point collaborative control system 4 calculates the load based on the input parameters of the suspended module 1 by calling its built-in force analysis model. This model aims to minimize the overall bending moment of the module and determines the initial optimal spatial position of each adjustable lifting point unit 22 on the main load-bearing frame 21. After the calculation is completed, the control system issues commands to the drive adjustment components 222 of each adjustable lifting point unit 22, driving them to move along the guide rail 23 to the designated initial position.

[0046] S3: Initial Lifting Stress and Attitude Monitoring

[0047] Multiple servo-controlled cranes 51 in the lifting power system 5 synchronously and slowly lift the suspended module 1, raising it to a relatively low preset height (e.g., 100-200mm) off the ground before pausing the lifting. During this stage, key data is collected through a real-time monitoring system: force sensors 31 installed on each adjustable lifting point unit 22 measure the real-time force at each lifting point; attitude sensors 32 installed at key locations of the suspended module 1 (such as the four corners or near the center of gravity) measure the module's tilt angle, displacement, and other attitude data.

[0048] S4: Force Equilibrium and Attitude Closed-Loop Control

[0049] The multi-suspension point collaborative control system 4 receives the real-time data collected in step S3 and executes force balance control and attitude closed-loop control in parallel.

[0050] Force balance control: The system calculates the deviation between the actual force on each lifting point and the ideal balanced force calculated based on the model. If the force deviation of any lifting point exceeds the first adaptive threshold, the system will dynamically distribute the load and reduce the force deviation by adjusting the lifting speed of the corresponding servo-controlled crane 51 or fine-tuning the position of the corresponding adjustable lifting point unit 22.

[0051] Attitude closed-loop control: The system calculates the deviation between the real-time attitude (such as tilt angle) of the suspended module 1 and the preset target attitude (usually horizontal). If the attitude deviation exceeds the second adaptive threshold, the system will correct the module attitude by adjusting the lifting action (such as single-point lifting) of the corresponding servo-controlled crane 51.

[0052] The first and second adaptive thresholds are not fixed values, but are dynamically calculated and determined by the multi-suspension point collaborative control system 4 based on the module weight, dimensions, and center of gravity position parameters input in step S1. For example, the first adaptive threshold (force tolerance) can be set between ±2% and ±5% of the total module weight, and the second adaptive threshold (attitude deviation) can be set between ±0.5° and ±2° of the attitude angle. The specific values ​​are dynamically adjusted according to the module's center of gravity offset, aspect ratio, and weight. For example, for modules weighing over 50 tons or longer than 20 meters, the first adaptive threshold is narrowed to ±1% to ±2% of the total module weight, and the second adaptive threshold is narrowed to ±0.5° to ±1° of the attitude angle. The above preset values ​​and adjustment ranges can be set by the user in the human-machine interface according to project requirements.

[0053] The preset values ​​can be set according to the actual needs of the project. For example, in a typical application scenario, the preset weight value can be 50 tons and the preset length value can be 20 meters. The specific values ​​can be adjusted by the operator according to the characteristics of the module.

[0054] S5: Module relocation / flipping

[0055] After initial leveling and force balancing are completed, the multi-point lifting control system 4 plans the coordinated motion trajectory of each servo-controlled crane 51 according to the preset target position and attitude parameters (such as a 90-degree rotation). During module relocation or overturning, the system continuously performs the force balancing and attitude closed-loop control described in step S4 to ensure stability and safety during the dynamic process.

[0056] S6: Deployment in place

[0057] The module is hoisted to its final target position, and multiple servo-controlled cranes 51 are simultaneously lowered. During the lowering process, the closed-loop control described in step S4 continues until the module is stably positioned, completing the entire hoisting operation.

[0058] The core of the method of this invention lies in "static-to-dynamic" control: initial planning and path setting are based on a static mechanical model ("static"), and high-frequency real-time monitoring and closed-loop control are combined to deal with dynamic changes and uncertainties in the hoisting process ("dynamic"), thereby achieving high-precision and low-stress hoisting of large modules.

[0059] Second embodiment: Tooling system for implementing the hoisting method

[0060] This embodiment provides a system for implementing the above-described hoisting method, such as... Figure 1 The diagram illustrates the physical layout and connections of the tooling system. The system mainly includes: a lifting module 1 connected via a multi-point adaptive spreader, a lifting power system 5, a real-time monitoring system, and a multi-point collaborative control system 4 as the control core. The lifting module 1 is connected to the multi-point adaptive spreader via its lifting lugs 7, and the multi-point adaptive spreader is connected to multiple servo-controlled cranes 51 in the lifting power system 5 via slings and other connecting components.

[0061] I. Multi-point adaptive lifting device

[0062] like Figure 2 As shown, the multi-point adaptive lifting device includes a main load-bearing frame 21, a guide rail 23, and several adjustable lifting point units 22.

[0063] The main load-bearing frame 21 is a rigid steel structure used to bear all hoisting loads.

[0064] The guide rail 23 is fixedly installed on the main load-bearing frame 21, and its basic guide rail components are made of high-strength wear-resistant materials.

[0065] like Figure 3 As shown in the cross-sectional structure, each adjustable suspension point unit 22 specifically includes:

[0066] Core load-bearing component 221: used for direct connection of slings or shackles to bear lifting loads, such as a cast steel lug or pulley block structure with an integrated force sensor interface.

[0067] Drive adjustment component 222: Connected to the core load-bearing component 221, it is used to drive the movement of the entire unit. This component can be an electric hoist or a servo cylinder, and its specific drive form is, for example, a gear and rack mechanism, a ball screw mechanism, or a chain drive mechanism driven by a servo motor.

[0068] Positioning and locking component 223: When the adjustable lifting point unit 22 moves to the target position, this component securely locks it onto the guide rail 23 to prevent slippage during lifting, for example, a pin-type locking mechanism, hydraulic clamp or electromagnetic brake.

[0069] To reduce friction, the guide rail 23 is provided with a sliding auxiliary component, specifically a roller assembly 231 embedded in the bottom of the adjustable suspension point unit 22 (see...). Figure 3 Meanwhile, a retractable dust cover 232 is provided above the guide rail 23 as a protective component (see...). Figure 3 This prevents dust and debris from entering and affecting the accuracy of the motion.

[0070] II. Lifting Power System 5

[0071] The hoisting power system 5 includes multiple independently controllable servo-controlled cranes 51. Preferably, a servo-controlled crawler crane is used, with its hoisting mechanism equipped with a high-precision encoder. This system has high-precision control capabilities: hoisting speed control accuracy can reach ±0.01m / s, position control accuracy can reach ±5mm, and when multiple cranes work together, the synchronization offset is no greater than 0.5mm.

[0072] III. Real-time Monitoring System

[0073] The real-time monitoring system is used to collect key physical quantities during the hoisting process:

[0074] Force sensor 31: Installed between each adjustable lifting point unit 22 and the sling, used to measure the load of each lifting point in real time.

[0075] Attitude sensor 32: Installed on the suspended module 1, used to measure the module's three-dimensional tilt angle and displacement in real time.

[0076] Sensor data is uploaded to the multi-suspension point collaborative control system 4 via a communication network. Industrial Ethernet based on the Modbus TCP protocol is preferably used for data transmission, and an industrial wireless module based on LoRa or WiFi 6 protocol is provided as a redundant communication link to ensure communication reliability.

[0077] IV. Multi-point Cooperative Control System

[0078] The multi-suspension point collaborative control system 4 is the brain of the entire tooling system.

[0079] System components: including human-machine interface, force balance control algorithm module, attitude closed-loop control algorithm module and servo controller.

[0080] Control Logic: The system receives data uploaded by the real-time monitoring system and performs real-time calculations and coordination through the force balance control algorithm module (aiming at minimizing bending moment) and the attitude closed-loop control algorithm module (based on PID control). The servo controller outputs the integrated algorithm to generate precise control commands.

[0081] Command issued:

[0082] Control commands are sent to the servo controllers of each servo-controlled crane 51 in the hoisting power system 5, and transmitted via shielded twisted-pair cable using the PROFINETIO protocol. The commands adopt a fixed frame structure of "Header+Data+Checksum" and include parameters such as hoisting speed, target position, and synchronization offset.

[0083] Position adjustment commands are sent to the drive adjustment components 222 of each adjustable lifting point unit 22 in the multi-lifting-point adaptive lifting device, and the control is performed using the CANopen protocol.

[0084] Closed-loop and adaptive control: The system receives status feedback from the actuator to form closed-loop control. At the same time, the system dynamically calculates and adjusts the first adaptive threshold (allowable force deviation value) and the second adaptive threshold (allowable attitude deviation value) based on the parameters of the suspended module 1 to achieve adaptive control.

[0085] V. System Communication Architecture and Data Flow

[0086] like Figure 4 As shown in the communication architecture diagram, the various components of this tooling system interact and control each other through a layered, redundant communication network, forming an efficient "monitoring-calculation-execution-feedback" closed loop. Its workflow is as follows:

[0087] 1. Data Acquisition: The force sensor 31 installed on the adjustable lifting point unit 22 and the attitude sensor 32 installed on the suspended module 1 collect force and attitude data in real time, and upload them to the multi-lifting point collaborative control system 4 via an industrial Ethernet network based on the Modbus TCP protocol.

[0088] 2. Collaborative processing: The force balance control algorithm module and attitude closed-loop control algorithm module in control system 4 analyze and process the data, and the servo controller generates control commands.

[0089] 3. Command Issuance and Execution: Speed ​​and position control commands issued to the servo-controlled crane 51 are transmitted via the PROFINETIO protocol; position adjustment commands issued to the drive adjustment component 222 of the adjustable lifting point unit 22 are transmitted via the CANopen protocol. All commands adopt a frame structure of "Header+Data+Checksum".

[0090] 4. Feedback and Closed Loop: Each actuator (servo-controlled crane 51, adjustable lifting point unit 22) feeds back status information to the control system 4 for dynamic correction. The system control cycle is ≤10ms and has redundant communication links for wired and wireless (LoRa / WiFi6).

[0091] 5. Adaptive threshold: The system dynamically calculates the first adaptive threshold (force deviation) and the second adaptive threshold (attitude deviation) based on the module parameters to achieve intelligent adjustment.

[0092] This architecture ensures Figure 5 The method flow shown is executed precisely and in real time.

[0093] Through the coordinated operation of the above subsystems, this tooling system can accurately execute the hoisting method described in the first embodiment, realizing moment-free, high-precision, and intelligent hoisting operations for large modules.

[0094] Finally, the following points should be noted: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installation", "connection", and "linkage" should be interpreted broadly, and can be mechanical or electrical connections, or internal connections between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may change.

[0095] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0096] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for static-to-dynamic hoisting with multiple lifting points and no bending moment, characterized in that: Includes the following steps: S1: Preparation before hoisting: Connect the multi-point adaptive lifting tool to the lifting lugs of the module to be hoisted, input the weight, size and center of gravity position parameters of the module to be hoisted in the human-machine interface, and start the various subsystems including the real-time monitoring system, the multi-point collaborative control system and the hoisting power system. S2: Initial lifting point position adjustment: The multi-lifting point collaborative control system calculates the initial optimal position of each adjustable lifting point unit based on the input module parameters, with the goal of minimizing the overall bending moment of the lifted module, through the built-in force analysis model, and controls it to move to that position. In step S2, the adjustable suspension point unit moves along a guide rail fixed to the main load-bearing frame via a drive mechanism; the guide rail is provided with sliding auxiliary components to reduce friction and protective components for dust prevention. The adjustable lifting point unit includes: a core bearing component for directly bearing the lifting load; a drive adjustment component connected to the core bearing component for driving the adjustable lifting point unit to move along the guide rail; and a positioning and locking component for locking the adjustable lifting point unit after it has moved to the target position. S3: Initial Lifting Stress and Attitude Monitoring: Control multiple servo-controlled cranes in the lifting power system to synchronously and slowly lift the module to a preset height above the ground and then pause. Collect real-time stress data of each lifting point and tilt angle and displacement attitude data of the module through the real-time monitoring system. S4: Force Equilibrium and Attitude Closed-Loop Control: The multi-suspension point collaborative control system performs force equilibrium control and attitude closed-loop control based on the data collected in step S3. The force equilibrium control includes: calculating the deviation between the actual force and the ideal equilibrium force at each suspension point; if the deviation exceeds a first adaptive threshold, the deviation is reduced by adjusting the action of the corresponding servo-controlled crane or the position of the adjustable suspension point unit. The attitude closed-loop control includes: calculating the deviation between the real-time attitude of the module and the target attitude; if the deviation exceeds a second adaptive threshold, the attitude is corrected by adjusting the action of the corresponding servo-controlled crane. The first and second adaptive thresholds are dynamically calculated and determined by the system based on the module weight, dimensions, and center of gravity position parameters input in step S1. The first adaptive threshold and the second adaptive threshold are adaptively adjusted according to the weight and size of the suspended module: for modules with a weight greater than a preset value or a length greater than a preset length, the first adaptive threshold is narrowed, while the second adaptive threshold remains unchanged or is narrowed. S5: Module shifting / turning: Based on the preset target position and posture parameters, the collaborative control system plans the motion trajectory of each servo-controlled crane, and under the closed-loop control described in step S4, the control module completes the shifting or turning action. S6: Lowering and positioning: Hoist the module to the target position and lower it, continuously performing the closed-loop control described in step S4 during the lowering process.

2. The moment-free multi-point static-to-dynamic hoisting method according to claim 1, characterized in that: The real-time monitoring system includes force sensors installed at each lifting point and attitude sensors installed on the lifted module. The force sensors and attitude sensors transmit data to the multi-lifting-point collaborative control system via an industrial Ethernet network using the Modbus TCP protocol. The system is also equipped with an industrial wireless module based on the LoRa or WiFi 6 protocol as a redundant communication link.

3. The moment-free multi-point static-to-dynamic hoisting method according to claim 1, characterized in that: The multiple servo-controlled cranes in the hoisting power system are servo-controlled crawler cranes, and their hoisting mechanisms are equipped with high-precision encoders. The multi-point collaborative control system uses shielded twisted-pair cables with the PROFINETIO protocol to send control commands containing hoisting speed, position positioning, and synchronization offset to the servo controllers of each servo-controlled crane in a fixed frame structure of "Header+Data+Checksum". In the force balance control, adjusting the action of the servo-controlled crane means adjusting its lifting speed.

4. A system for implementing the hoisting method according to any one of claims 1-3, characterized in that: include: The hoisting power system includes multiple servo-controlled cranes that can be independently controlled; A multi-point adaptive lifting device is used to connect the lifted module to the lifting power system. It includes a main load-bearing frame, a guide rail disposed on the main load-bearing frame, and a plurality of adjustable lifting point units that can move along the guide rail. The real-time monitoring system is used to collect force data at each lifting point and attitude data of the lifted module in real time through force sensors and attitude sensors. The multi-lifting-point collaborative control system is communicatively connected to the real-time monitoring system and the lifting power system. It includes a human-machine interface, a force balance control algorithm module, an attitude closed-loop control algorithm module, and a servo controller. The system is used to receive monitoring data, dynamically calculate force and attitude control thresholds, and output control commands through the closed-loop control algorithm to collaboratively control the actions of each servo-controlled crane and the position of the adjustable lifting point unit.

5. The system according to claim 4, characterized in that: The drive adjustment component is an electric hoist or a servo cylinder; the base guide rail component of the guide rail is made of high-strength wear-resistant material; the sliding auxiliary component is a roller group embedded in the bottom of the adjustable lifting point unit; and the protective component is a retractable dust cover covering the guide rail.

6. The system according to claim 4, characterized in that: The hoisting power system has a servo-controlled crane with a hoisting speed control accuracy of ±0.01m / s, a position control accuracy of ±5mm, and a multi-machine synchronous offset of no more than 0.5mm.

7. The system according to claim 4, characterized in that: The collaborative control system communicates in real time with the servo controllers of each servo-controlled crane using the PROFINETIO protocol, and controls the drive adjustment components of the adjustable lifting point unit using the CANopen protocol; the sensor data of the real-time monitoring system is uploaded via the ModbusTCP protocol.

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