Dynamic safety assessment method for hoisting construction

Abstract

The invention relates to the technical field of hoisting construction dynamic safety assessment, and particularly discloses a hoisting construction dynamic safety assessment method, which comprises the following steps of: acquiring operation parameters of a hoisting system in real time through a multi-modal sensor array, and generating a hoisting dynamic parameter set; the lifting dynamic parameter set comprises pressure distribution data of each lifting point, lifting appliance attitude angle data and load space position data; based on the hoisting dynamic parameter set, force system dynamic balance analysis is executed, and the force system unbalance degree of the crane is obtained through analysis; and when the force system unbalance degree of the crane is larger than a set threshold value, an unbalance active correction mechanism is triggered, and unbalance correction is conducted on the crane through adjustment of the electro-hydraulic proportional valve. And the safety and the efficiency of hoisting operation can be obviously improved. The automatic unbalance correction mechanism not only reduces the accident risk, but also improves the operation flexibility and response speed, and provides powerful technical support for modern hoisting operation.

Description

Technical Field

[0001] The invention belongs to the technical field of dynamic safety assessment of hoisting construction and relates to a dynamic safety assessment method for hoisting construction. Background Art

[0002] With the increasing complexity of modern construction projects, multi-point lifting has become a common method for installing and transporting large components. However, the coordinated operation of multiple lifting points significantly increases the risk of force imbalance during the lifting process. An imbalance at any one lifting point can cause instability in the entire lifting system, leading to safety accidents. Therefore, real-time monitoring of the force status of each lifting point and the timely identification and correction of imbalances are crucial to ensuring construction safety and improving operational efficiency. Through effective monitoring methods, construction personnel can dynamically adjust the force conditions of each lifting point during the lifting process to ensure even load distribution and avoid serious consequences such as tipping, damage, or personal injury caused by force imbalance.

[0003] However, current technologies for monitoring force imbalance during multi-point collaborative hoisting operations still have several flaws and drawbacks. First, existing monitoring systems typically rely on traditional sensors and manual monitoring methods, lacking real-time capabilities and automation. For example, many systems can only monitor a single lifting point, failing to provide comprehensive analysis and real-time feedback across multiple lifting points. This limitation makes it difficult for managers to fully understand the force status of each lifting point in complex hoisting environments, potentially leading to undetected imbalances at critical moments and increasing the risk of accidents. Summary of the Invention

[0004] In view of the above problems in the prior art, the present invention provides a dynamic safety assessment method for hoisting construction, which is used to solve the above technical problems.

[0005] In order to achieve the above-mentioned and other purposes, the technical solutions adopted by the present invention are as follows: The present invention provides a method for dynamic safety assessment of hoisting construction, which comprises the following steps: S1: Real-time acquisition of lifting system operating parameters through a multimodal sensor array to generate a lifting dynamic parameter set, which includes pressure distribution data of each lifting point, spreader attitude angle data, and load spatial position data. The pressure distribution data includes the real-time three-dimensional force components (F_x, F_y, F_z) of each lifting point; the spreader attitude angle data includes the pitch angle θ and roll angle φ of the hook assembly; and the load spatial position data includes the coordinate deviation of the load geometric center in the global coordinate system (ΔX, ΔY, ΔZ). S2: Based on the lifting dynamic parameter set, a three-dimensional mechanical characteristic data set of multiple lifting points is constructed, and a dynamic balance analysis of the force system is performed. Based on the three-dimensional mechanical characteristic data set, the total axial loads in each space are synthesized to generate a total lifting load vector. Then, a three-dimensional moment synthesis matrix is constructed. Based on the total lifting load vector and the three-dimensional moment synthesis matrix, a mechanical equivalent solution is performed to generate the overall resultant eccentricity of the crane, and finally the imbalance degree of the crane force system is analyzed. S3: When the imbalance of the crane's force system is greater than the set threshold, the active imbalance correction mechanism is triggered, and the crane's imbalance is corrected through adjustment of the electro-hydraulic proportional valve.

[0006] Exemplarily, step S1 includes the following steps: Step S11: Arrange a pressure sensor array on the inner side of the load-bearing beam at the hanging point to collect the instantaneous value of the vertical force at each hanging point in real time to generate an initial pressure data set; Step S12: Based on the initial pressure data set, abnormal pressure fluctuation detection is performed on the lifting points. When the pressure difference between adjacent lifting points exceeds a preset tolerance threshold, the inertial measurement unit wake-up command is triggered to obtain the real-time pitch angle θ and roll angle φ of the lifting device; Step S13: Combine the pitch angle θ and the roll angle φ to convert the vertical force value of each suspension point into a three-dimensional force component: the X-axis component F_x = F_z × tanθ; the Y-axis component F_y = F_z × tanφ; the Z-axis component F_z retains the original pressure sensor data F_z, thereby generating a three-dimensional pressure distribution data set for each suspension point; Step S14: Install a laser scanning module at the load end, calculate the spatial coordinate deviation (ΔX, ΔY, ΔZ) of the load's geometric center relative to the hoisting origin using a point cloud registration algorithm, fuse the attitude angle data to optimize the coordinate accuracy, and generate the load's spatial position data; Step S15: Integrate and package the three-dimensional pressure distribution data set, pitch angle / roll angle data, and load space coordinate data to generate a lifting dynamic parameter set.

[0007] Exemplarily, the operation logic of step S14 is: Step S141: Preset a feature marker point array on the load surface and collect real-time three-dimensional point cloud data of the load's outer contour through a laser scanning module; Step S142: performing point cloud registration matching on the real-time 3D point cloud data and the preset load design model, and screening out a valid point cloud set corresponding to the feature marker points; Step S143: Based on the valid point cloud set, calculate the real-time coordinate value of each mark point in the hoisting global coordinate system, and take the arithmetic average of the coordinates of all mark points to obtain the current load geometric center coordinates (W_x, W_y, W_z); Step S144: Read the pitch angle θ and roll angle φ in the spreader attitude angle data, and perform attitude correction compensation on the geometric center coordinates using the coordinate rotation matrix: The corrected X-axis coordinates are: ΔX=W_x-L×sinθ, the corrected Y-axis coordinates are: ΔY=W_y-L×sinφ, and the corrected Z-axis coordinates are ΔZ=W_z, where L is the length of the sling chain. Step S145: The stability of the corrected coordinate data is verified by variance analysis. When the coordinate deviation of three consecutive scans is less than the set accuracy threshold, the final load space position data (ΔX, ΔY, ΔZ) is generated.

[0008] Exemplarily, step S12 includes the following steps: Step S121: extracting the vertical pressure value F_i of each hanging point at the current moment from the initial pressure data set, where i is the number of each hanging point, i=1, 2, ..., N; N represents the total number of hanging points; Step S122: Calculate the real-time pressure difference between adjacent hanging points, and take the absolute value to finally obtain the real-time pressure difference absolute value |ΔF_j| between each adjacent hanging point, where j is the number of each adjacent hanging point and the value range of j is 1 to N-1; Step S123: Filter out the maximum value max(|ΔF_j|) from |ΔF_j|, compare it with the preset tolerance threshold F_th, and generate an abnormal fluctuation flag signal when max(|ΔF_j|)>F_th; Step S124: triggering an inertial measurement unit wake-up command according to the abnormal fluctuation mark signal, and synchronously collecting the angular velocity ω_x, ω_y, ω_z and acceleration a_z data of the spreader in the three axes; Step S125: Convert ω_x, ω_y, ω_z, and a_z into pitch angle θ and roll angle φ through a quaternion solution algorithm. The specific process is as follows: Step S1251: Calculate the initial tilt angle θ_0 = arctan(a_x / a_z) and the initial roll angle φ_0 = arctan(a_y / a_z) using accelerometer data; Step S1252: Integrate the gyroscope angular velocity data to obtain an angular variation, wherein the angular variation is divided into a pitch angle variation Δθ=∫ω_ydt and a roll angle variation Δφ=∫ω_xdt; Step S1253: Using a complementary filtering algorithm to fuse θ_0 and Δθ, a final pitch angle θ = α × θ_0 + (1-α)(θ_prev + Δθ) is obtained, where α is the filter coefficient and θ_prev is the angle value of the previous cycle. Step S1254: Similarly, calculate the roll angle φ=α×φ_0+(1-α)(φ_prev+Δφ).

[0009] Exemplarily, step S2 includes the following steps: Step S21: extracting the real-time three-dimensional force components (F_x, F_y, F_z) and load spatial position data (ΔX, ΔY, ΔZ) of each lifting point in the lifting dynamic parameter set, and constructing a multi-lifting point three-dimensional mechanical characteristic data set; Step S22: synthesizing the total loads in each spatial axis based on the three-dimensional mechanical characteristic data set to generate a total hoisting load vector; and simultaneously correcting the spatial coordinate system transformation parameters according to the hoisting device attitude angle (θ, φ) to construct a three-dimensional moment synthesis matrix; Step S23: Performing a mechanical equivalent calculation based on the total hoisting load vector and the three-dimensional moment synthesis matrix: extracting the vertical total load component from the total hoisting load vector, where the vertical total load component is the sum of the absolute values of the Z-axis force components of each hoisting point; calculating the transverse coordinate of the equivalent resultant force application point: transverse moment synthesis value / vertical total load component; calculating the longitudinal coordinate of the equivalent resultant force application point: longitudinal moment synthesis value / vertical total load component; wherein the transverse moment synthesis value is derived from the moment component in the X-axis direction of the three-dimensional moment synthesis matrix, and the longitudinal moment synthesis value is derived from the moment component in the Y-axis direction of the three-dimensional moment synthesis matrix; Step S24: Calculate the Euclidean distance between the equivalent resultant force application point and the load geometric center coordinate deviation (ΔX, ΔY, ΔZ) to generate the overall resultant force eccentricity of the crane; Step S25: Based on the sum of the absolute values of the deviations between the three-dimensional force components (F_x, F_y, F_z) of each suspension point and their theoretical axial components, combined with the eccentricity of the overall resultant force of the crane, the crane's force system imbalance is calculated using a deviation weighted calculation formula.

[0010] Exemplarily, the operation of step S22 includes the following steps: Step S221: performing spatial axial mechanical decomposition on the three-dimensional mechanical feature data set to separate the transverse force component set F_x, the longitudinal force component set F_y, and the vertical force component set F_z of each hanging point; Step S222: Calculate the total transverse load ΣF_x, the total longitudinal load ΣF_y, and the total vertical load ΣF_z based on the spatial axial decomposition results, and synthesize the total hoisting load vector V = (ΣF_x, ΣF_y, ΣF_z); Step S223: Based on the spreader attitude angle θ, a pitch angle compensation correction is performed on the lateral offset of the hook to generate a lateral coordinate system correction coefficient C_x = ΔX·cosθ; based on the spreader roll angle φ, a roll angle compensation correction is performed on the longitudinal offset of the hook to generate a longitudinal coordinate system correction coefficient C_y = ΔY·sinφ; Step S224: constructing a vertical coordinate compensation factor D_z=ΔZ using the load space position deviation ΔZ; Step S225: Perform dynamic compensation calculation on the three-dimensional moment using the coordinate correction parameters (C_x, C_y, D_z), where: The total lateral moment M_x=Σ(F_y·D_z-F_z·C_y); The total longitudinal moment M_y=Σ(F_z·C_x-F_x·D_z); The total vertical moment M_z=Σ(F_x·C_y-F_y·C_x); Step S226: Construct the sum of the compensated lateral, longitudinal and vertical moments into a three-dimensional moment synthesis matrix [M_x, M_y, M_z].

[0011] Exemplarily, step S25 includes the following steps: Step S251: Perform axial theoretical force matching on the three-dimensional force components (F_x, F_y, F_z) of each lifting point, where the transverse theoretical force F'_x = total lifting load / total number of lifting points, the longitudinal theoretical force F'_y = 0, and the vertical theoretical force F'_z = total lifting load / total number of lifting points; Step S252: Calculate the lateral force deviation value ΔF_x=|F_x-F'_x|, the longitudinal force deviation value ΔF_y=|F_y-F'_y|, and the vertical force deviation value ΔF_z=|F_z-F'_z| of each hanging point to generate a three-dimensional force deviation feature set; Step S253: quantify the axial deviation contribution of the three-dimensional force deviation feature set; wherein the lateral deviation contribution Q_x = ∑ΔF_x / (total number of hanging points × F'_x); the longitudinal deviation contribution Q_y = ∑ΔF_y / (total number of hanging points × F'_z); and the vertical deviation contribution Q_z = ∑ΔF_z / (total number of hanging points × F'_z); Step S254: dynamically weighting the axial deviation contribution based on the crane's overall resultant force eccentricity E to calculate the crane's imbalance assessment coefficient K = 1 + E × (Q_x + Q_y) / (Q_z + safety threshold); Step S255: The crane's force system imbalance is finally generated through the formula: crane's force system imbalance = Q_z × K.

[0012] Exemplarily, step S3 includes the following process: Step S31: establishing a force system imbalance threshold comparison mechanism, and generating an electro-hydraulic regulation trigger signal when the force system imbalance is greater than the set threshold; Step S32: extracting the real-time deviation value of the three-dimensional force components (F_x, F_y, F_z) of the suspension point according to the electro-hydraulic adjustment trigger signal, and calculating the hydraulic adjustment amount ΔL of each suspension point using the formula: adjustment compensation amount = force system imbalance degree × (actual force component - theoretical force component) / theoretical force component; Step S33: Perform spatial angle vector decomposition of the hydraulic adjustment variable ΔL based on the spreader attitude angle (θ, φ) to generate a pulse width modulation signal for the electro-hydraulic proportional valve: the lateral adjustment component PWM_x = ΔL·cosθ; the longitudinal adjustment component PWM_y = ΔL·sinφ; Step S34: Drive the corresponding outrigger cylinder for displacement compensation according to the pulse width modulation signal: the lateral compensation execution time T_x = PWM_x / (maximum cylinder speed × safety factor); the longitudinal compensation execution time T_y = PWM_y / (maximum cylinder speed × safety factor); Step S35: After the compensation is completed, the lifting dynamic parameter set is collected again to verify the imbalance of the secondary force system until the set threshold is met and the correction cycle is terminated.

[0013] As described above, the present invention provides a method for dynamic safety assessment of hoisting construction, which has at least the following beneficial effects: The present invention uses a multimodal sensor array to collect the operating parameters of the hoisting system in real time and generates a set of hoisting dynamic parameters. It has significant technical advantages and necessity and can effectively improve the safety and efficiency of hoisting operations. First of all, the generation of the hoisting dynamic parameter set, including the pressure distribution data of each hoisting point, the sling attitude angle data and the load space position data, provides comprehensive real-time data support for hoisting operations. The real-time monitoring of these data allows operators to clearly understand the working status of the hoisting system and identify potential safety hazards in a timely manner. For example, pressure distribution data can help determine the stress conditions of the hoisting points and prevent hoisting accidents caused by uneven loads; while sling attitude angle data helps ensure the stability of the sling during operation and avoid dangers caused by tilting or swinging.

[0014] Secondly, dynamic force balance analysis based on the lifting dynamic parameter set enables real-time assessment of the crane's force system imbalance. This process is critical to ensuring the safety of lifting operations. Force system imbalance can cause serious accidents such as crane tipping and instability during operation, posing significant risks to personal and equipment safety. By monitoring and analyzing the crane's force system status in real time, the management system can quickly respond when the imbalance exceeds a set threshold, triggering an active imbalance correction mechanism. This automated response mechanism effectively reduces the need for manual intervention and improves the system's response speed and accuracy.

[0015] When the active imbalance correction mechanism is triggered, the crane's load is adjusted via an electro-hydraulic proportional valve to restore it to a balanced state. Compared to traditional manual adjustment methods, this automated correction method not only improves adjustment accuracy but also significantly reduces the time required. Continued operation of an unbalanced crane can not only damage the equipment but also pose a safety threat to the operator. The combination of real-time monitoring and an automatic correction mechanism can prevent accidents immediately, ensuring the safety of lifting operations.

[0016] In summary, using a multimodal sensor array to collect real-time lifting dynamic parameters and performing dynamic force balance analysis based on this data can significantly improve the safety and efficiency of lifting operations. The automated imbalance correction mechanism not only reduces the risk of accidents but also increases operational flexibility and responsiveness, providing strong technical support for modern lifting operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention. DETAILED DESCRIPTION

[0019] The above contents described below in conjunction with the implementation of the present invention are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall fall within the scope of protection of the present invention. Example

[0020] See also Figure 1 As shown, a method for dynamic safety assessment of hoisting construction includes the following steps: S1: Real-time acquisition of lifting system operating parameters through a multimodal sensor array to generate a lifting dynamic parameter set, which includes pressure distribution data of each lifting point, spreader attitude angle data, and load spatial position data. The pressure distribution data includes the real-time three-dimensional force components (F_x, F_y, F_z) of each lifting point; the spreader attitude angle data includes the pitch angle θ and roll angle φ of the hook assembly; and the load spatial position data includes the coordinate deviation of the load geometric center in the global coordinate system (ΔX, ΔY, ΔZ). Step S1 includes the following steps: Step S11: Arrange a pressure sensor array on the inner side of the load-bearing beam at the hanging point to collect the instantaneous value of the vertical force at each hanging point in real time to generate an initial pressure data set; Step S12: Based on the initial pressure data set, abnormal pressure fluctuation detection is performed on the lifting points. When the pressure difference between adjacent lifting points exceeds a preset tolerance threshold, the inertial measurement unit wake-up command is triggered to obtain the real-time pitch angle θ and roll angle φ of the lifting device; Step S13: Combine the pitch angle θ and the roll angle φ to convert the vertical force value of each suspension point into a three-dimensional force component: the X-axis component F_x = F_z × tanθ; the Y-axis component F_y = F_z × tanφ; the Z-axis component F_z retains the original pressure sensor data F_z, thereby generating a three-dimensional pressure distribution data set for each suspension point; Step S14: Install a laser scanning module at the load end, calculate the spatial coordinate deviation (ΔX, ΔY, ΔZ) of the load's geometric center relative to the hoisting origin using a point cloud registration algorithm, fuse the attitude angle data to optimize the coordinate accuracy, and generate the load's spatial position data; Step S15: Integrate and package the three-dimensional pressure distribution data set, pitch angle / roll angle data, and load space coordinate data to generate a lifting dynamic parameter set.

[0021] In the embodiment of the present invention, a high-precision resistive strain gauge pressure sensor is embedded in the key stress-bearing position of each load-bearing beam of the hoisting system, and the original pressure signal in the vertical direction of each hanging point is continuously collected. The time series pressure data set is generated after the mechanical vibration noise is eliminated by the Kalman filter algorithm; when the absolute value of the pressure difference between adjacent hanging points exceeds the preset threshold value for three sampling cycles continuously, the system automatically activates the micro inertial measurement unit on the top of the sling, and uses the quaternion solution algorithm to calculate the pitch angle θ and roll angle φ of the hook assembly in real time, wherein the pitch angle θ is obtained by the ratio of the Z-axis and X-axis components of the accelerometer through the inverse tangent function, and the roll angle φ is obtained by dynamic analysis of the Y-axis and Z-axis components; based on the acquired attitude angle data, each hanging point is The vertical pressure F_z is converted to the spatial coordinate system respectively, where the X-axis component F_x is calculated by multiplying F_z by the tangent value of the pitch angle, and the Y-axis component F_y is obtained by multiplying F_z by the tangent value of the roll angle, thereby constructing a pressure topology network containing a three-dimensional force vector; a reflective marker array is simultaneously arranged on the load surface, and a phase laser scanner is used to obtain the load contour point cloud data. The real-time point cloud is aligned with the design model through an iterative nearest point algorithm, and the geometric center coordinates are rotated and transformed and compensated with the attitude angle data to calculate the actual spatial position deviation value of the load; finally, the three-dimensional pressure distribution, dual-axis attitude angle and spatial deviation coordinates are aligned and packaged according to the timestamp to form a lifting dynamic parameter set.

[0022] The operation logic of step S14 is: Step S141: Preset a feature marker point array on the load surface and collect real-time three-dimensional point cloud data of the load's outer contour through a laser scanning module; Step S142: performing point cloud registration matching on the real-time 3D point cloud data and the preset load design model, and screening out a valid point cloud set corresponding to the feature marker points; Step S143: Based on the valid point cloud set, calculate the real-time coordinate value of each mark point in the hoisting global coordinate system, and take the arithmetic average of the coordinates of all mark points to obtain the current load geometric center coordinates (W_x, W_y, W_z); Step S144: Read the pitch angle θ and roll angle φ in the spreader attitude angle data, and perform attitude correction compensation on the geometric center coordinates using the coordinate rotation matrix: The corrected X-axis coordinates are: ΔX=W_x-L×sinθ, the corrected Y-axis coordinates are: ΔY=W_y-L×sinφ, and the corrected Z-axis coordinates are ΔZ=W_z, where L is the length of the sling chain. Step S145: The stability of the corrected coordinate data is verified by variance analysis. When the coordinate deviation of three consecutive scans is less than the set accuracy threshold, the final load space position data (ΔX, ΔY, ΔZ) is generated.

[0023] In an embodiment of the present invention, high-reflectivity marker balls are attached to the four corners and center of the outer surface of the load to form a feature point array. A phased laser scanner is used to obtain three-dimensional point cloud data of the load contour, and the point cloud clusters corresponding to the marker balls are screened out using a reflection intensity threshold. An iterative closest point algorithm is used to spatially align the real-time scanned point cloud with a preset load CAD model, and the spatial coordinates of each marker ball vertex are automatically identified and extracted. The arithmetic mean of the X / Y / Z coordinate values of all valid marker points is calculated as the initial coordinates of the load's geometric center. At the same time, based on the pitch and roll angle data fed back in real time by the micro-electromechanical inertial measurement unit installed on the top of the sling, dynamic compensation calculation of the geometric coordinates is performed in combination with the sling chain length parameter. That is, the horizontal displacement component caused by the sling tilt is subtracted from the X-axis coordinate value, the lateral offset is compensated similarly in the Y-axis direction, and the Z-axis coordinate maintains the original vertical measurement value. Finally, the standard deviation of the coordinate data after three consecutive compensations is calculated and analyzed. When the fluctuation amplitudes of the three axes are all less than the set millimeter-level accuracy threshold, the final spatial position deviation data after attitude correction is generated.

[0024] Step S12 includes the following steps: Step S121: extracting the vertical pressure value F_i of each hanging point at the current moment from the initial pressure data set, where i is the number of each hanging point, i=1, 2, ..., N; N represents the total number of hanging points; Step S122: Calculate the real-time pressure difference between adjacent hanging points, and take the absolute value to finally obtain the real-time pressure difference absolute value |ΔF_j| between each adjacent hanging point, where j is the number of each adjacent hanging point and the value range of j is 1 to N-1; Step S123: Filter out the maximum value max(|ΔF_j|) from |ΔF_j|, compare it with the preset tolerance threshold F_th, and generate an abnormal fluctuation flag signal when max(|ΔF_j|)>F_th; Step S124: triggering an inertial measurement unit wake-up command according to the abnormal fluctuation mark signal, and synchronously collecting the angular velocity ω_x, ω_y, ω_z and acceleration a_z data of the spreader in the three axes; Step S125: Convert ω_x, ω_y, ω_z, and a_z into pitch angle θ and roll angle φ through a quaternion solution algorithm. The specific process is as follows: Step S1251: Calculate the initial tilt angle θ_0 = arctan(a_x / a_z) and the initial roll angle φ_0 = arctan(a_y / a_z) using accelerometer data; Step S1252: Integrate the gyroscope angular velocity data to obtain an angular variation, wherein the angular variation is divided into a pitch angle variation Δθ=∫ω_ydt and a roll angle variation Δφ=∫ω_xdt; Step S1253: Using a complementary filtering algorithm to fuse θ_0 and Δθ, a final pitch angle θ = α × θ_0 + (1-α)(θ_prev + Δθ) is obtained, where α is the filter coefficient and θ_prev is the angle value of the previous cycle. Step S1254: Similarly, calculate the roll angle φ=α×φ_0+(1-α)(φ_prev+Δφ).

[0025] In an embodiment of the present invention, a piezoresistive sensor array is used to acquire vertical pressure data at each suspension point in real time. A sliding average filter algorithm is used to eliminate transient mechanical vibration noise and form a pressure time series. The pressure difference between adjacent suspension points is continuously calculated and its absolute value is taken. When the pressure difference between any pair of adjacent points exceeds a preset safety threshold and persists for three sampling cycles, the system automatically activates the micro-inertial navigation module on the top of the spreader to synchronously collect X / Y axis angular velocity and Z axis acceleration data. An initial pitch angle estimate is calculated using an inverse tangent function based on the ratio of the accelerometer's Z-axis to X-axis components, and the initial roll angle is dynamically analyzed based on the Y-axis and Z-axis components. A time integration operation is performed on the gyroscope angular velocity data to accumulate the attitude angle change of the spreader within the current cycle. A complementary filtering algorithm is used to fuse the low-frequency stable angle information measured by the accelerometer with the high-frequency dynamic data of the gyroscope, with the acceleration data weighted to 0.02 and the gyroscope integral data weighted to 0.98. This eliminates the gyroscope's zero drift error and suppresses motion interference from the accelerometer. Finally, dynamically compensated pitch and roll angle data are output.

[0026] S2: Based on the lifting dynamic parameter set, a three-dimensional mechanical characteristic data set of multiple lifting points is constructed, and a dynamic balance analysis of the force system is performed. Based on the three-dimensional mechanical characteristic data set, the total axial loads in each space are synthesized to generate a total lifting load vector. Then, a three-dimensional moment synthesis matrix is constructed. Based on the total lifting load vector and the three-dimensional moment synthesis matrix, a mechanical equivalent solution is performed to generate the overall resultant eccentricity of the crane, and finally the imbalance degree of the crane force system is analyzed. Step S2 includes the following steps: Step S21: extracting the real-time three-dimensional force components (F_x, F_y, F_z) and load spatial position data (ΔX, ΔY, ΔZ) of each lifting point in the lifting dynamic parameter set, and constructing a multi-lifting point three-dimensional mechanical characteristic data set; Step S22: synthesizing the total loads in each spatial axis based on the three-dimensional mechanical characteristic data set to generate a total hoisting load vector; and simultaneously correcting the spatial coordinate system transformation parameters according to the hoisting device attitude angle (θ, φ) to construct a three-dimensional moment synthesis matrix; Step S23: Performing a mechanical equivalent calculation based on the total hoisting load vector and the three-dimensional moment synthesis matrix: extracting the vertical total load component from the total hoisting load vector, where the vertical total load component is the sum of the absolute values of the Z-axis force components of each hoisting point; calculating the transverse coordinate of the equivalent resultant force application point: transverse moment synthesis value / vertical total load component; calculating the longitudinal coordinate of the equivalent resultant force application point: longitudinal moment synthesis value / vertical total load component; wherein the transverse moment synthesis value is derived from the moment component in the X-axis direction of the three-dimensional moment synthesis matrix, and the longitudinal moment synthesis value is derived from the moment component in the Y-axis direction of the three-dimensional moment synthesis matrix; Step S24: Calculate the Euclidean distance between the equivalent resultant force application point and the load geometric center coordinate deviation (ΔX, ΔY, ΔZ) to generate the overall resultant force eccentricity of the crane; Step S25: Based on the sum of the absolute values of the deviations between the three-dimensional force components (F_x, F_y, F_z) of each suspension point and their theoretical axial components, combined with the eccentricity of the overall resultant force of the crane, the crane's force system imbalance is calculated using a deviation weighted calculation formula.

[0027] In an embodiment of the present invention, the lifting dynamic parameter set is acquired in real time by an array of three-dimensional force sensors installed at the lifting points, and the force components in the three axes of x, y, and z and the load space offset at each lifting point are measured synchronously. The construction process of the three-dimensional mechanical characteristic data set first performs spatiotemporal alignment processing on the mechanical parameters of each lifting point, integrates the force data at different sampling moments into a unified coordinate system through a timestamp synchronization mechanism, and eliminates the acquisition delay error between sensors through a spatial interpolation compensation method. When synthesizing the total spatial axial load, the system adopts the principle of static equilibrium and performs algebraic superposition calculations on each axial force component: the total lateral load is determined by the algebraic sum of the x-axis components of each lifting point, the total longitudinal load is obtained by accumulating the y-axis components, and the total vertical load is the sum of the absolute values of the z-axis components. The final total lifting load vector represents the overall force state of the system in the form of a three-dimensional vector. The attitude angle parameters of the hoist are acquired in real time through the inertial measurement unit, and the quaternion coordinate system transformation method is used to spatially compensate the original torque data. In specific implementation, a three-dimensional rotation matrix is first constructed based on the hook pitch angle and roll angle. Then, the torque components in the local coordinate system of the lifting point are converted into global coordinate system components through matrix mapping. The lateral torque composite value is calculated by projecting the x-axis component of the rotation matrix, and the longitudinal torque is obtained by multiplying the y-axis component of the rotation matrix with the original torque. The three-dimensional torque composite matrix thus constructed fully represents the spatial torque distribution characteristics of the lifting system. During the mechanical equivalent solution process, the system uses the total vertical load as the reference quantity. This reference quantity is calculated by the absolute value and z-axis force component of each lifting point to ensure that negative force interference is eliminated when the hoist attitude changes. Then, the lateral torque composite value and the longitudinal torque composite value are divided by the total vertical load component to obtain the precise spatial coordinates of the equivalent resultant force application point. The sliding window mean filter algorithm is used in the calculation to eliminate dynamic jitter errors. The Euclidean distance model is used to generate the crane's overall resultant force eccentricity. Three-dimensional spatial distance calculations are performed based on the coordinate deviation between the equivalent action point and the load's geometric center. An overshoot protection mechanism is introduced during the calculation process, and a second-order low-pass filter algorithm is automatically activated to smooth trajectory fluctuations when sudden position offsets are detected. The final force system imbalance assessment module is implemented by integrating multidimensional parameters. First, the absolute axial deviations of the three-dimensional force components at each lifting point and their theoretical values are accumulated. The lateral theoretical value is the uniform distribution of the total hoisting load, and the longitudinal theoretical value is set to zero to match the ideal force distribution. The ratio of the sum of the axial deviations to the theoretical value is then normalized to convert it into a baseline imbalance coefficient. Finally, a linear weighted algorithm is used to generate the comprehensive force system imbalance, combining the spatial amplification effect of the overall resultant force eccentricity.

[0028] The operation of step S22 includes the following steps: Step S221: performing spatial axial mechanical decomposition on the three-dimensional mechanical feature data set to separate the transverse force component set F_x, the longitudinal force component set F_y, and the vertical force component set F_z of each hanging point; Step S222: Calculate the total transverse load ΣF_x, the total longitudinal load ΣF_y, and the total vertical load ΣF_z based on the spatial axial decomposition results, and synthesize the total hoisting load vector V = (ΣF_x, ΣF_y, ΣF_z); Step S223: Based on the spreader attitude angle θ, a pitch angle compensation correction is performed on the lateral offset of the hook to generate a lateral coordinate system correction coefficient C_x = ΔX·cosθ; based on the spreader roll angle φ, a roll angle compensation correction is performed on the longitudinal offset of the hook to generate a longitudinal coordinate system correction coefficient C_y = ΔY·sinφ; Step S224: constructing a vertical coordinate compensation factor D_z=ΔZ using the load space position deviation ΔZ; Step S225: Perform dynamic compensation calculation on the three-dimensional moment using the coordinate correction parameters (C_x, C_y, D_z), where: The total lateral moment M_x = Σ(F_y·D_z-F_z·C_y), which is the cumulative value of the product of the longitudinal force component and the vertical compensation factor at each hanging point minus the cumulative value of the product of the vertical force component and the longitudinal correction coefficient; The total longitudinal moment M_y=Σ(F_z·C_x-F_x·D_z); The total vertical moment M_z=Σ(F_x·C_y-F_y·C_x), which is the cumulative value of the interaction between the lateral force component and the longitudinal correction coefficient; Step S226: Construct the sum of the compensated lateral, longitudinal and vertical moments into a three-dimensional moment synthesis matrix [M_x, M_y, M_z].

[0029] In this embodiment of the present invention, the raw data collected by the three-dimensional force sensor array installed at the suspension points is first spatially aligned and preprocessed to eliminate sampling time differences between different suspension points. Subsequently, axial isolation technology is used to independently classify the three-dimensional force components of each suspension point according to the spatial coordinate direction: the transverse component set F_x corresponds to the force data of the suspension point in the x-axis direction, the longitudinal component set F_y represents the load distribution in the y-axis direction, and the vertical component set F_z reflects the load-bearing status of each suspension point in the z-axis direction. During the total load vector synthesis stage, the system uses algebraic accumulation to horizontally superimpose and sum the transverse component sets to obtain the total transverse load, vertically accumulate the longitudinal component sets to obtain the total longitudinal load, and calculate the total vertical load of the vertical component sets using absolute value accumulation. The resulting total hoisting load vector fully represents the spatial mechanical distribution characteristics of the hoisting system. To address spatial coordinate system deviations caused by the spreader's attitude angle, the system employs an attitude compensation algorithm. The hook's pitch angle θ, acquired in real time by a high-precision inclinometer, is used to calculate lateral offset corrections. The specific correction factor is determined by multiplying the lateral position deviation ΔX by the cosine of the pitch angle. Similarly, the longitudinal correction factor is calculated by multiplying the sine of the hook's roll angle φ by the longitudinal position deviation ΔY. This correction method effectively eliminates spatial coordinate projection errors caused by spreader swing. The vertical coordinate compensation factor directly uses the original value of the load's spatial position deviation ΔZ, preserving the true physical characteristics of load height variations. In the dynamic compensation calculation of three-dimensional moments, the system uses the principle of spatial vector orthogonal decomposition to address the coupling relationship between the force components and correction parameters at each suspension point: the sum of the lateral moments is calculated by subtracting the cumulative value of the product of the vertical force components and the longitudinal correction coefficient from the cumulative value of the product of the longitudinal force components and the vertical compensation factor at each suspension point; the sum of the longitudinal moments is calculated by subtracting the cumulative value of the interaction between the vertical force components and the lateral correction coefficient from the cumulative value of the lateral force components and the vertical compensation factor; and the sum of the vertical moments is calculated by accumulating the spatial coupling effect of the lateral force components and the longitudinal correction coefficient. The final constructed three-dimensional moment synthesis matrix uses spatial multi-dimensional parameter fusion technology to normalize and encode the dynamically compensated calibrated lateral, longitudinal, and vertical moment values, forming a resolvable matrix data structure.

[0030] Step S25 includes the following steps: Step S251: Perform axial theoretical force matching on the three-dimensional force components (F_x, F_y, F_z) of each lifting point, where the transverse theoretical force F'_x = total lifting load / total number of lifting points, the longitudinal theoretical force F'_y = 0, and the vertical theoretical force F'_z = total lifting load / total number of lifting points; Step S252: Calculate the lateral force deviation value ΔF_x=|F_x-F'_x|, the longitudinal force deviation value ΔF_y=|F_y-F'_y|, and the vertical force deviation value ΔF_z=|F_z-F'_z| of each hanging point to generate a three-dimensional force deviation feature set; Step S253: quantify the axial deviation contribution of the three-dimensional force deviation feature set; wherein the lateral deviation contribution Q_x = ∑ΔF_x / (total number of hanging points × F'_x); the longitudinal deviation contribution Q_y = ∑ΔF_y / (total number of hanging points × F'_z); and the vertical deviation contribution Q_z = ∑ΔF_z / (total number of hanging points × F'_z); Step S254: Dynamically weight the contribution of the axial deviation based on the crane's overall resultant force eccentricity E to calculate the crane's unbalance assessment coefficient K = 1 + E × (Q_x + Q_y) / (Q_z + safety threshold), where the safety threshold is 5% of the theoretical hoisting load. Step S255: The crane's force system imbalance is finally generated through the formula: crane's force system imbalance = Q_z × K.

[0031] In the embodiment of the present invention, during the specific implementation, the actual stress state of each lifting point of the lifting system is first matched with an idealized model: the lateral theoretical stress is set according to the algebraic average distribution value of the total lifting load in the dimension of the number of lifting points, the longitudinal theoretical stress is set to zero to eliminate the interference of the lateral force on the ideal stress, and the vertical theoretical stress is determined according to the vertical bearing capacity of each lifting point divided by the total lifting load. The actual stress deviation analysis adopts the absolute value cumulative difference method. The system calculates the absolute deviation between the actual stress and the theoretical value in the three-dimensional direction of each lifting point. The lateral deviation reflects the uneven distribution of horizontal stress between the lifting points, the longitudinal deviation characterizes the abnormal lateral load of the system, and the vertical deviation reflects the load-bearing stability of the lifting. In the process of quantifying the deviation contribution, the contribution coefficients of the lateral, longitudinal and vertical directions to the overall imbalance state are obtained by ratio processing the sum of the axial deviations with the product of the corresponding theoretical value and the number of lifting points. The vertical theoretical value is used as the reference value for the calculation of the longitudinal deviation contribution to ensure the validity of the data when the longitudinal theoretical stress is zero. The dynamic weighted processing step innovatively introduces the eccentricity of the total resultant force as a spatial amplification factor. This eccentricity is multiplied by the sum of the horizontal deviation contributions. A proportional calculation is performed based on the vertical deviation contributions and a preset proportional safety threshold of the theoretical lifting load, generating a comprehensive assessment coefficient. The final force system imbalance is calculated by multiplying the vertical contributions by the comprehensive assessment coefficient.

[0032] S3: When the imbalance of the crane's force system is greater than the set threshold, the active imbalance correction mechanism is triggered, and the crane's imbalance is corrected through adjustment of the electro-hydraulic proportional valve.

[0033] Step S3 includes the following process: Step S31: establishing a force system imbalance threshold comparison mechanism, and generating an electro-hydraulic regulation trigger signal when the force system imbalance is greater than the set threshold; Step S32: extracting the real-time deviation value of the three-dimensional force components (F_x, F_y, F_z) of the suspension point according to the electro-hydraulic adjustment trigger signal, and calculating the hydraulic adjustment amount ΔL of each suspension point using the formula: adjustment compensation amount = force system imbalance degree × (actual force component - theoretical force component) / theoretical force component; Step S33: Perform spatial angle vector decomposition of the hydraulic adjustment variable ΔL based on the spreader attitude angle (θ, φ) to generate a pulse width modulation signal for the electro-hydraulic proportional valve: the lateral adjustment component PWM_x = ΔL·cosθ; the longitudinal adjustment component PWM_y = ΔL·sinφ; Step S34: Drive the corresponding outrigger cylinder for displacement compensation according to the pulse width modulation signal: the lateral compensation execution time T_x = PWM_x / (maximum cylinder speed × safety factor); the longitudinal compensation execution time T_y = PWM_y / (maximum cylinder speed × safety factor); Step S35: After the compensation is completed, the lifting dynamic parameter set is collected again to verify the imbalance of the secondary force system until the set threshold is met and the correction cycle is terminated.

[0034] In an embodiment of the present invention, the force system imbalance threshold comparison mechanism implements real-time monitoring via an embedded control system. When the lifting system's intelligent monitoring module detects that the force system imbalance exceeds a preset safety threshold, the system immediately initiates the electro-hydraulic adjustment trigger signal generation process. The electro-hydraulic adjustment trigger signal is transmitted to the hydraulic adjustment controller via an industrial fieldbus. During this process, the system synchronously reads the real-time three-dimensional force component data for each lifting point. For each lifting point, the system dynamically calculates the hydraulic adjustment compensation based on the deviation ratio between the actual force component and the theoretical force component, combined with the current force system imbalance. Specifically, the force system imbalance is used as the adjustment gain coefficient, and the required cylinder displacement compensation for each lifting point is linearly adjusted based on the percentage deviation of the actual force component from the theoretical value. In the spatial angle vector decomposition step, the system obtains the pitch and roll angle data of the spreader in real time. Using the triangular projection principle, the cylinder axial compensation is decomposed into lateral and longitudinal adjustment components. The lateral adjustment component is scaled by the cosine value of the pitch angle, and the longitudinal adjustment component is scaled by the sine value of the roll angle. These components generate the pulse width modulation waveform signal corresponding to the electro-hydraulic proportional valve. When a pulse-width modulated signal drives the electro-hydraulic proportional valve via the PID control module, the system dynamically calculates the duration of lateral and longitudinal compensation movements based on the maximum cylinder velocity parameter and a preset safety factor. This duration is calculated using the inverse relationship between the modulation signal amplitude and the cylinder velocity, ensuring a smooth and controllable cylinder displacement compensation process. After a single adjustment, the system automatically triggers the secondary collection of the lifting dynamic parameter set and the force imbalance calculation module. Through an iterative closed-loop control mechanism, it continuously optimizes the force distribution at each lifting point until the force imbalance falls within the safety threshold.

[0035] It should be noted that the intervals and thresholds are set for ease of comparison. The threshold size depends on the amount of sample data and the cardinality set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless calculations, derived from software simulations of the most recent real-world conditions using large amounts of data. The preset parameters in the formulas are set by those skilled in the art based on actual conditions.

[0036] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0037] It should be understood that determining B based on A does not mean determining B based solely on A. B can also be determined based on A and / or other information.

[0038] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0039] Finally: 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 in the scope of protection of the present invention.

Claims

1. A method for dynamic safety assessment of hoisting construction, characterized in that: The following steps are involved: S1: Using a multimodal sensor array to collect lifting system operating parameters in real time, generating a lifting dynamic parameter set, wherein the lifting dynamic parameter set includes pressure distribution data of each lifting point, sling attitude angle data, and load spatial position data; S2: constructing a three-dimensional mechanical characteristic data set of multiple lifting points based on the lifting dynamic parameter set, performing dynamic balance analysis of the force system, synthesizing the total axial loads in each space based on the three-dimensional mechanical characteristic data set, and generating a total lifting load vector; Then, a three-dimensional moment synthesis matrix is constructed, and a mechanical equivalent solution is performed based on the total hoisting load vector and the three-dimensional moment synthesis matrix, thereby generating the overall resultant eccentricity of the crane, and finally analyzing the imbalance of the crane's force system; S3: When the imbalance of the crane's force system is greater than the set threshold, the active imbalance correction mechanism is triggered, and the crane's imbalance is corrected through adjustment of the electro-hydraulic proportional valve.

2. A method for dynamic safety assessment of hoisting construction according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Arrange a pressure sensor array on the inner side of the load-bearing beam at the hanging point to collect the instantaneous value of the vertical force at each hanging point in real time to generate an initial pressure data set; Step S12: Based on the initial pressure data set, abnormal pressure fluctuation detection is performed on the lifting points. When the pressure difference between adjacent lifting points exceeds a preset tolerance threshold, the inertial measurement unit wake-up command is triggered to obtain the real-time pitch angle θ and roll angle φ of the lifting device; Step S13: Combine the pitch angle θ and the roll angle φ to convert the vertical force value of each suspension point into a three-dimensional force component: the X-axis component F_x = F_z × tanθ; the Y-axis component F_y = F_z × tanφ; the Z-axis component F_z retains the original pressure sensor data F_z, thereby generating a three-dimensional pressure distribution data set for each suspension point; Step S14: Install a laser scanning module at the load end, calculate the spatial coordinate deviation (ΔX, ΔY, ΔZ) of the load's geometric center relative to the hoisting origin using a point cloud registration algorithm, fuse the attitude angle data to optimize the coordinate accuracy, and generate the load's spatial position data; Step S15: Integrate and package the three-dimensional pressure distribution data set, pitch angle / roll angle data, and load space coordinate data to generate a lifting dynamic parameter set.

3. A method for dynamic safety assessment of hoisting construction according to claim 2, characterized in that: The operation logic of step S14 is: Step S141: Preset a feature marker point array on the load surface and collect real-time three-dimensional point cloud data of the load's outer contour through a laser scanning module; Step S142: performing point cloud registration matching on the real-time 3D point cloud data and the preset load design model, and screening out a valid point cloud set corresponding to the feature marker points; Step S143: Based on the valid point cloud set, calculate the real-time coordinate value of each mark point in the hoisting global coordinate system, and take the arithmetic average of the coordinates of all mark points to obtain the current load geometric center coordinates (W_x, W_y, W_z); Step S144: Read the pitch angle θ and roll angle φ in the spreader attitude angle data, and perform attitude correction compensation on the geometric center coordinates using the coordinate rotation matrix: The corrected X-axis coordinates are: ΔX=W_x-L×sinθ, the corrected Y-axis coordinates are: ΔY=W_y-L×sinφ, and the corrected Z-axis coordinates are ΔZ=W_z, where L is the length of the sling chain. Step S145: The stability of the corrected coordinate data is verified by variance analysis. When the coordinate deviation of three consecutive scans is less than the set accuracy threshold, the final load space position data (ΔX, ΔY, ΔZ) is generated.

4. A method for dynamic safety assessment of hoisting construction according to claim 2, characterized in that: Step S12 includes the following steps: Step S121: extracting the vertical pressure value F_i of each hanging point at the current moment from the initial pressure data set, where i is the number of each hanging point, i=1, 2, ..., N; N represents the total number of hanging points; Step S122: Calculate the real-time pressure difference between adjacent hanging points, and take the absolute value to finally obtain the real-time pressure difference absolute value |ΔF_j| between each adjacent hanging point, where j is the number of each adjacent hanging point and the value range of j is 1 to N-1; Step S123: Filter out the maximum value max(|ΔF_j|) from |ΔF_j|, compare it with the preset tolerance threshold F_th, and generate an abnormal fluctuation flag signal when max(|ΔF_j|)>F_th; Step S124: triggering an inertial measurement unit wake-up command according to the abnormal fluctuation mark signal, and synchronously collecting the angular velocity ω_x, ω_y, ω_z and acceleration a_z data of the spreader in the three axes; Step S125: Convert ω_x, ω_y, ω_z, and a_z into a pitch angle θ and a roll angle φ through a quaternion solution algorithm.

5. A method for dynamic safety assessment of hoisting construction according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: extracting the real-time three-dimensional force components (F_x, F_y, F_z) and load spatial position data (ΔX, ΔY, ΔZ) of each lifting point in the lifting dynamic parameter set, and constructing a multi-lifting point three-dimensional mechanical characteristic data set; Step S22: synthesizing the total axial loads in each space based on the three-dimensional mechanical characteristic data set to generate a total hoisting load vector; At the same time, the spatial coordinate system transformation parameters are corrected according to the spreader attitude angle (θ, φ) to construct a three-dimensional moment synthesis matrix; Step S23: performing a mechanical equivalent solution based on the total hoisting load vector and the three-dimensional moment synthesis matrix: extracting a vertical total load component from the total hoisting load vector, where the vertical total load component is the sum of the absolute values of the Z-axis force components of each hoisting point; Calculate the lateral coordinates of the equivalent resultant force action point: the resultant value of the lateral moment / the total load component in the vertical direction; Calculate the longitudinal coordinate of the equivalent resultant force action point: longitudinal moment resultant value / total vertical load component; The lateral moment synthesis value is derived from the moment component in the X-axis direction of the three-dimensional moment synthesis matrix, and the longitudinal moment synthesis value is derived from the moment component in the Y-axis direction of the three-dimensional moment synthesis matrix; Step S24: Calculate the Euclidean distance between the equivalent resultant force application point and the load geometric center coordinate deviation (ΔX, ΔY, ΔZ) to generate the overall resultant force eccentricity of the crane; Step S25: Based on the sum of the absolute values of the deviations between the three-dimensional force components (F_x, F_y, F_z) of each suspension point and their theoretical axial components, combined with the eccentricity of the overall resultant force of the crane, the crane's force system imbalance is calculated using a deviation weighted calculation formula.

6. A method for dynamic safety assessment of hoisting construction according to claim 5, characterized in that: The operation of step S22 includes the following steps: Step S221: performing spatial axial mechanical decomposition on the three-dimensional mechanical feature data set to separate the transverse force component set F_x, the longitudinal force component set F_y, and the vertical force component set F_z of each hanging point; Step S222: Calculate the total transverse load ΣF_x, the total longitudinal load ΣF_y, and the total vertical load ΣF_z based on the spatial axial decomposition results, and synthesize the total hoisting load vector V = (ΣF_x, ΣF_y, ΣF_z); Step S223: Based on the spreader attitude angle θ, a pitch angle compensation correction is performed on the lateral offset of the hook to generate a lateral coordinate system correction coefficient C_x = ΔX·cosθ; based on the spreader roll angle φ, a roll angle compensation correction is performed on the longitudinal offset of the hook to generate a longitudinal coordinate system correction coefficient C_y = ΔY·sinφ; Step S224: constructing a vertical coordinate compensation factor D_z=ΔZ using the load space position deviation ΔZ; Step S225: Perform dynamic compensation calculation on the three-dimensional torque using the coordinate correction parameters (C_x, C_y, D_z), where: The total lateral moment M_x=Σ(F_y·D_z-F_z·C_y); The total longitudinal moment M_y=Σ(F_z·C_x-F_x·D_z); The total vertical moment M_z=Σ(F_x·C_y-F_y·C_x); Step S226: Construct the sum of the compensated lateral, longitudinal and vertical moments into a three-dimensional moment synthesis matrix [M_x, M_y, M_z].

7. A method for dynamic safety assessment of hoisting construction according to claim 5, characterized in that: Step S25 includes the following steps: Step S251: Perform axial theoretical force matching on the three-dimensional force components (F_x, F_y, F_z) of each lifting point, where the transverse theoretical force F'_x = total lifting load / total number of lifting points, the longitudinal theoretical force F'_y = 0, and the vertical theoretical force F'_z = total lifting load / total number of lifting points; Step S252: Calculate the lateral force deviation value ΔF_x=|F_x-F'_x|, the longitudinal force deviation value ΔF_y=|F_y-F'_y|, and the vertical force deviation value ΔF_z=|F_z-F'_z| of each hanging point to generate a three-dimensional force deviation feature set; Step S253: quantify the axial deviation contribution of the three-dimensional force deviation feature set; wherein the lateral deviation contribution Q_x = ∑ΔF_x / (total number of hanging points × F'_x); the longitudinal deviation contribution Q_y = ∑ΔF_y / (total number of hanging points × F'_z); and the vertical deviation contribution Q_z = ∑ΔF_z / (total number of hanging points × F'_z); Step S254: dynamically weighting the axial deviation contribution based on the crane's overall resultant force eccentricity E to calculate the crane's imbalance assessment coefficient K = 1 + E × (Q_x + Q_y) / (Q_z + safety threshold); Step S255: The crane's force system imbalance is finally generated through the formula: crane's force system imbalance = Q_z × K.

8. A method for dynamic safety assessment of hoisting construction according to claim 1, characterized in that: Step S3 includes the following process: Step S31: establishing a force system imbalance threshold comparison mechanism, and generating an electro-hydraulic regulation trigger signal when the force system imbalance is greater than the set threshold; Step S32: extracting the real-time deviation value of the three-dimensional force components (F_x, F_y, F_z) of the suspension point according to the electro-hydraulic adjustment trigger signal, and calculating the hydraulic adjustment amount ΔL of each suspension point using the formula: adjustment compensation amount = force system imbalance degree × (actual force component - theoretical force component) / theoretical force component; Step S33: Perform spatial angle vector decomposition of the hydraulic adjustment variable ΔL based on the spreader attitude angle (θ, φ) to generate a pulse width modulation signal for the electro-hydraulic proportional valve: the lateral adjustment component PWM_x = ΔL·cosθ; the longitudinal adjustment component PWM_y = ΔL·sinφ; Step S34: Drive the corresponding outrigger cylinder for displacement compensation according to the pulse width modulation signal: the lateral compensation execution time T_x = PWM_x / (maximum cylinder speed × safety factor); the longitudinal compensation execution time T_y = PWM_y / (maximum cylinder speed × safety factor); Step S35: After the compensation is completed, the lifting dynamic parameter set is collected again to verify the imbalance of the secondary force system until the set threshold is met and the correction cycle is terminated.

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