Crane structure parameter stress analysis method and system

Abstract

The invention relates to the technical field of crane stress analysis, in particular to a crane structure parameter stress analysis method and system. The method comprises the following steps: constructing an accurate three-dimensional structure simulation model by obtaining crane device data and operation logs, and carrying out crane operation analogue simulation based on the model; performing boom structure division on the simulation data, respectively obtaining simulation data of the truss boom type crane and the telescopic boom type crane, evaluating stress coupling increment of the truss boom type crane and telescopic boom type mechanical conduction response characteristics, and comprehensively detecting dynamic mechanical response of the crane; based on the dynamic response data, identifying the breakage risk of crane components, determining the chain type degradation condition of the components, and evaluating the operation stability gradient attenuation of the crane in combination with the three-dimensional structure model; carrying out structural mechanics optimization treatment according to the stability attenuation condition; through crane stress analysis, the crane can run more stably and efficiently.

Description

Technical Field

[0001] This invention relates to the field of crane stress analysis technology, and in particular to a method and system for stress analysis of crane structural parameters. Background Technology

[0002] As a key piece of equipment for heavy equipment handling and structural hoisting, the stress analysis of crane structural parameters has always been a core technical issue in engineering safety and operation and maintenance optimization. In complex operating environments, the loads borne by crane structures exhibit dynamic changes, diverse force paths, and are often accompanied by nonlinear coupling and structural heterogeneity. Traditional static stress analysis methods are insufficient to fully reveal the true stress state and fatigue risk evolution process of key crane components. Existing technologies mostly use simplified stress models for finite element simulation or static load analysis of crane boom systems, lacking in-depth analysis of the stress differences of various boom structures (such as truss booms and telescopic booms) under dynamic conditions. They also fail to establish a three-dimensional structural modeling and refined simulation process based on operation logs and device structural data, making it difficult to achieve accurate mechanical assessment of the crane structure throughout its entire life cycle. Furthermore, traditional crane stress analysis suffers from inaccurate detection of the crane's dynamic mechanical response and inaccurate detection of the chain degradation of crane components. Summary of the Invention

[0003] Therefore, it is necessary to provide a method and system for analyzing the stress of crane structural parameters to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a method for analyzing the stress parameters of a crane structure includes the following steps:

[0005] Step S1: Obtain crane device data and crane operation log; construct a three-dimensional structural simulation model of the crane based on the crane operation log and crane device data; perform crane operation simulation based on the three-dimensional structural simulation model of the crane to obtain crane operation simulation data;

[0006] Step S2: Divide the crane boom structure according to the crane operation simulation data to obtain simulation data of truss boom crane and telescopic boom crane; evaluate the force coupling increment of truss boom crane according to the truss boom crane simulation data; determine the mechanical transmission response characteristics of telescopic boom crane according to the telescopic boom crane simulation data; detect the dynamic mechanical response data of crane according to the force coupling increment of truss boom crane and the mechanical transmission response characteristics of telescopic boom crane.

[0007] Step S3: Detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; determine the chain degradation status of crane components based on the fracture risk status of crane components.

[0008] Step S4: Determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; optimize the mechanical structure of the crane based on the operational stability gradient decay to obtain the optimized mechanical data of the crane structure.

[0009] This method acquires crane device data and operation logs to construct an accurate three-dimensional structural simulation model, enabling high-precision simulation and analysis of the crane's operating status and significantly improving the dynamic capture capability of the crane's stress characteristics. Through detailed classification and mechanical response analysis of truss boom and telescopic boom structures, it accurately reveals the stress coupling and mechanical transmission characteristics under different structural forms, enhancing the ability to identify and quantify complex stress states. Based on dynamic mechanical response data, it detects component fracture risks, achieving early warning of potential failures of key components, further refining the analysis to component chain degradation, and systematically revealing the transmission path and trend of structural degradation. Using the three-dimensional simulation model to determine the operational stability gradient decay, it achieves a quantitative assessment of the overall structural stability and guides targeted optimization of the mechanical structure, greatly improving the crane's structural safety and operational accuracy, extending equipment lifespan, and enhancing operational reliability and the scientific basis of maintenance decisions. The tightly integrated technical chain ensures the systematic and comprehensive nature of structural stress analysis, promoting the accuracy and intelligence of crane structural parameter stress analysis. Therefore, this invention is an optimization of traditional crane stress analysis, which solves the problems of inaccurate detection of crane dynamic mechanical response and inaccurate detection of chain degradation of crane components. It improves the accuracy of detecting crane dynamic mechanical response and chain degradation of crane components.

[0010] The present invention also provides a crane structural parameter stress analysis system for performing the crane structural parameter stress analysis method described above. The crane structural parameter stress analysis system includes:

[0011] The simulation module is used to acquire crane device data and crane operation logs; a three-dimensional structural simulation model of the crane is constructed based on the crane operation logs and crane device data; and the crane operation simulation is performed based on the three-dimensional structural simulation model to obtain crane operation simulation data.

[0012] The dynamic mechanical response detection module is used to divide the crane boom structure based on crane operation simulation data to obtain simulation data for truss boom cranes and telescopic boom cranes; to evaluate the force coupling increment of the truss boom crane based on the truss boom crane simulation data; to determine the mechanical transmission response characteristics of the telescopic boom crane based on the telescopic boom crane simulation data; and to detect the dynamic mechanical response data of the crane based on the force coupling increment and the mechanical transmission response characteristics of the telescopic boom crane.

[0013] The component chain degradation determination module is used to detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; and to determine the chain degradation status of crane components based on the fracture risk status of crane components.

[0014] The mechanical structure optimization module is used to determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; and to perform mechanical structure optimization processing on the crane based on the operational stability gradient decay to obtain the mechanical optimization data of the crane structure.

[0015] The crane structural parameter stress analysis system of the present invention can realize the stress analysis method of arbitrary crane structural parameters of the present invention. It is used as a medium for the operation and signal transmission between various modules to complete the stress analysis method of crane structural parameters. The internal modules of the system cooperate with each other. By accurately constructing a three-dimensional structural simulation model of the crane and combining dynamic mechanical response analysis, it can monitor and evaluate the stress state of the crane, the risk of component fracture and the whole process of chain degradation, guide structural optimization, and significantly improve the operational stability and safety of the crane. Attached Figure Description

[0016] Figure 1 A schematic diagram illustrating the steps of a method for analyzing the stress parameters of a crane structure.

[0017] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S3.

[0018] Figure 3 for Figure 1 A detailed flowchart illustrating the implementation steps of step S4.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0021] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0022] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] To achieve the above objectives, please refer to Figures 1 to 3 A method for analyzing the stress parameters of a crane structure, comprising the following steps:

[0024] Step S1: Obtain crane device data and crane operation log; construct a three-dimensional structural simulation model of the crane based on the crane operation log and crane device data; perform crane operation simulation based on the three-dimensional structural simulation model of the crane to obtain crane operation simulation data;

[0025] In this embodiment of the invention, crane device data is acquired through multiple types of data acquisition devices deployed on the crane structure itself. This includes boom length, segment connection method, main beam cross-sectional dimensions, weld joint type, hoisting mechanism layout parameters, steel elastic modulus, yield strength, axis deviation, number and distribution coordinates of connecting hinge points, etc. Simultaneously, crane operation log data is collected, including records of lifting weight, operating angle, slewing radius, operating frequency, lifting speed, operating time, ambient wind speed level, and operating terrain slope. The data is organized using a structured data format, archived and stored in a MySQL database, and a unique index tag is set to bind the device structure data and operation logs. Subsequently, using the ABAQUS finite element analysis tool, the above structural parameters and operation data are imported to establish a complete three-dimensional structural simulation model of the crane, including the boom, lifting points, tower body, and foundation support. During model construction, geometric entity information is input based on structural design drawings and dimensional specifications. By explicitly defining material properties and connection boundary conditions, the actual connection type and force transmission path are accurately reproduced in the model. The model is subjected to load conditions and time series inputs recorded in the operation log, and crane operation simulations are run through steady-state and transient analysis modules. After each simulation under load conditions, structural stress data, strain distribution, and nodal displacement information are extracted, and the results for all simulation steps are exported in CSV format to form a crane operation simulation dataset. This simulation data will serve as the input for subsequent boom structure classification and stress analysis.

[0026] Step S2: Divide the crane boom structure according to the crane operation simulation data to obtain simulation data of truss boom crane and telescopic boom crane; evaluate the force coupling increment of truss boom crane according to the truss boom crane simulation data; determine the mechanical transmission response characteristics of telescopic boom crane according to the telescopic boom crane simulation data; detect the dynamic mechanical response data of crane according to the force coupling increment of truss boom crane and the mechanical transmission response characteristics of telescopic boom crane.

[0027] In this embodiment of the invention, the obtained crane operation simulation data is imported into a Python programming environment, and a structural feature recognition algorithm is called to classify the boom structure type based on the boom connection method, cross-section type, and structural node density. The judgment criteria are as follows: those with more than 10 connection nodes and containing spatial triangular truss units are classified as truss booms; those with a continuous segment telescopic member ratio greater than 1.5 and no internal triangular support structure are classified as telescopic booms. During the classification process, a clustering algorithm is introduced to statistically analyze the force transmission path length, and the K-means clustering method is used to delineate the force characteristics exhibited by different boom structures, resulting in simulation data for truss boom cranes and telescopic boom cranes. The two types of data are then further processed. For the truss boom crane simulation data, a custom coupling increment evaluation function in MATLAB is called. Based on the rate of change of force synchronization between nodes and the local stress concentration coefficient of the structure, the increase in the coupling degree of the node-member system in continuous simulation time steps is calculated, and a force coupling increment data matrix for truss boom cranes is generated. For simulation data of telescopic boom cranes, mechanical transmission response characteristic parameters of the telescopic boom are calculated based on the stress wave propagation time difference of component units, mechanical hysteresis, and structural stiffness matrix response rate. These parameters include response delay time, local compliance coefficient, and stress transmission path non-uniformity. Using the truss boom's stress coupling increment and the telescopic boom's transmission response characteristics as input parameters, a joint analysis model is constructed. The overall stress response of the crane structure is mapped in a unified structural coordinate system. Dynamic response data of each component is output in the form of three-dimensional stress cloud diagrams and time-series stress curves, thus obtaining the crane's dynamic mechanical response data, providing a basis for subsequent structural fracture and degradation analysis.

[0028] Step S3: Detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; determine the chain degradation status of crane components based on the fracture risk status of crane components.

[0029] In this embodiment of the invention, the dynamic mechanical response data of the crane is imported into the ANSYS structural fracture assessment module, and fracture risk is identified based on the material properties and stress history of different components. For boom-type components, the location of the principal bending moment and the stress-time curve at the midpoint of the component are extracted, and the risk of crack initiation is judged by comparing the critical yield strength and fatigue limit. For connectors, a crack propagation analysis module based on stress concentration factors is used to calculate the fracture growth rate of the structural unit under multiple loading cycles, and the crack length is predicted by combining the Paris-Erdogan formula. At the same time, a component connection path analysis model based on topological dependency graph is constructed to identify the connection relationship and force transmission path between components. High fracture risk components are backtracked, and the continuous failure trend caused by the failure of a single component is identified by combining the preceding and following force transmission paths and the loading time window of adjacent components, forming complete chain degradation path information. The system automatically marks the path segments with risks and key node components, generating a structural path diagram and fault propagation table of the chain degradation of crane components. This data is treated as an irreversible degradation input factor in subsequent structural stability analysis.

[0030] Step S4: Determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; perform mechanical structural optimization processing on the crane based on the operational stability gradient decay to obtain the crane structural mechanical optimization data.

[0031] In this embodiment of the invention, the three-dimensional structural simulation model of the crane and the component chain degradation data constructed in Embodiment 3 are imported using the SolidWorks and ANSYS co-simulation platform. Degradation path information is superimposed on the three-dimensional structure to identify the location of the failed component in the overall structure and the corresponding force transmission chain distribution. Then, based on three indicators—the change in support node displacement, the degree of local imbalance of the structural stiffness matrix, and the amplitude of modal frequency variation—gradient quantization analysis is performed on the stability of the entire structure in the degraded state, generating a crane operation stability gradient decay dataset. According to the structural stability assessment results, regions in the force path where the stability gradient decay exceeds 25% are optimized and reconstructed. The optimization process uses the finite element topology optimization method, reconfiguring the material distribution under the conditions of satisfying volume constraints and strength, and selecting the reconstruction path with the fastest structural stiffness recovery speed for optimization design. Specific operations include adjusting the truss node positions, strengthening the thickness of the connecting plates, and adding transverse support components. After optimization, the optimized model is rerun for stress simulation, and the optimized node stiffness matrix and stability response data are extracted to form crane structural mechanics optimization data, which is used to guide subsequent structural adjustments and safety acceptance.

[0032] Preferably, step S1 includes the following steps:

[0033] Step S11: Obtain crane device data and crane operation log;

[0034] In this embodiment of the invention, sensor arrays deployed on multiple nodes of the crane's main structure, slewing platform, boom, tower, and hoisting mechanism collect crane device data. The collected data includes, but is not limited to: slewing structure radius, boom length and cross-sectional dimensions, main beam wall thickness, number and distribution of connectors, working range of hydraulic telescopic cylinders, slewing bearing structure type, counterweight weight, and hoisting mechanism parameters (such as wire rope diameter, drum size, and rated lifting height). It also includes static structural attributes for material identification, such as steel batch number, elastic modulus, Poisson's ratio, and yield strength. Simultaneously, crane operation log information stored in the local control system PLC logs and SCADA system records is extracted. The operation logs include parameters such as operation time, lifting frequency, single load weight, load center of gravity coordinates, operating radius variation, lifting speed and acceleration curves, ambient wind speed and direction, and lifting point offset amplitude. After connecting to a local industrial switch via a CAN bus, the real-time collected data is written to a structured database through a data gateway, forming a uniquely numbered set of device and operation data, providing raw data support for subsequent structural identification and operational condition assessment.

[0035] Step S12: Collect the structural parameters of the crane device based on the crane device data;

[0036] In this embodiment of the invention, based on the collected crane device data, a reverse structural configuration recognition method is used to collect and process its structural parameters. During this process, a finite connection graph is constructed based on the node position information measured by sensors and the topological connection relationships of components. Components are identified and encoded using graph theory methods, extracting key geometric parameters including boom structure length, number of segments, connecting pin diameter, component tilt angle, slewing center offset, and outrigger spacing. The structural parameter extraction uses the SolidWorks API interface to construct a three-dimensional parameter sketch from the original sensor measurements and automatically converts it into a structural parameter table based on parametric modeling rules. All parameters in the table are uniformly represented in SI units to ensure numerical consistency. Furthermore, for implicit parameters that cannot be directly measured, such as the moment of inertia of the cross section and the slenderness ratio of local instability, inverse calculations are performed using theoretical formulas, and the results are compared and corrected based on on-site inspection reports. This completes the comprehensive collection of structural parameters, forming a set of device structural parameters that can be directly used for simulation model construction.

[0037] Step S13: Evaluate the complexity of the crane's operating conditions based on the crane's operation log and the crane's structural parameters to obtain the complexity of the crane's operating conditions;

[0038] In this embodiment of the invention, the collected crane operation logs and device structural parameters are input into the working condition complexity assessment engine. The working condition assessment is based on a multi-factor coupling analysis method, establishing a quantitative index system for working condition complexity from five categories of indicators: the degree of drastic fluctuation in operating load, the range of lifting point offset, the frequency of changes in the operating cycle, the rate of change of lifting speed and lifting angle, and the coefficient of change of the ratio of lifting weight to boom length. By introducing the entropy weight method to assign weights to each type of indicator, a multi-index weighted assessment model for working condition complexity is constructed. Each operation log is scored according to the above weights, and combined with the mechanism complexity parameters included in the device structural parameters (such as boom degrees of freedom, total number of connecting components, number of segmented forms, etc.), the working condition complexity score of the crane within a specific operating cycle is calculated. The score ranges from 0 to 1, with higher values ​​indicating more complex working conditions. The working condition complexity curve within the entire operating cycle is evaluated using a floating window method, outputting the crane's operating condition complexity data to provide context-driven information for subsequent model construction.

[0039] Step S14: Based on the complexity of the crane's operating conditions and the structural parameters of the crane device, construct a three-dimensional structural simulation model of the crane to obtain the three-dimensional structural simulation model of the crane.

[0040] In this embodiment of the invention, based on the obtained structural parameters and operational complexity data of the crane device, a three-dimensional structural simulation model of the crane is constructed using the CATIA and ANSYS Workbench joint modeling platform. In CATIA, the aforementioned structural parameters are input using a parametric modeling method to construct a complete three-dimensional geometric solid model including the boom, tower, slewing platform, outriggers, hook system, and wire rope drum system. The geometric model is then imported into the ANSYS platform. Material property parameters are set in the Static Structural module, and boundary conditions are defined: the positions of fixed support nodes, the point of application of the load, and the loading method are set according to the complexity of the operational conditions (e.g., higher frequency of lifting load results in stronger time-varying load). Several typical representative scenarios, such as operational conditions 1, 2, and 3, are set. The model is meshed using 10-node tetrahedral elements, with a minimum mesh size of 5mm and a maximum of 20mm, ensuring a balance between accuracy and computational speed. After completing the above settings, the model's topology and physical information are extracted to form a complete three-dimensional structural simulation model of the crane, providing a geometric and physical boundary foundation for subsequent simulations.

[0041] Step S15: Perform crane operation simulation based on the crane's three-dimensional structural simulation model to obtain crane operation simulation data.

[0042] In this embodiment of the invention, the constructed three-dimensional structural simulation model of the crane is imported into the ANSYS Mechanical simulation environment, and the simulation scenarios are set according to the complexity of the working conditions. Load conditions are applied to each working condition: the lifting weight is set to 300kN, the loading position is located at the center 1 / 3 of the main boom, the working angle is 45°, and the ground support uses spring supports to simulate soil foundation deformation. A dynamic load input sequence is applied, which is generated based on the lifting and slewing speeds recorded in the operation log, corresponding to the application of instantaneous time-series loads. During the simulation, a nonlinear solver is used to control the time step, outputting structural response parameters every 0.1s, with the total simulation duration set to 60s. After the simulation, data including nodal displacements, component stress and strain, support reactions, maximum strain energy density, and relative displacements of connectors are extracted and output as multi-column CSV data, constituting the crane operation simulation data. This data is used for subsequent stress analysis, fracture detection, and structural optimization processing, and is the basic data set for bearing the full life-cycle information of the structural response.

[0043] Preferably, step S14 includes the following steps:

[0044] Step S141: Perform crane structure division processing based on the crane device structural parameters to obtain fixed crane structure data and mobile crane structure data;

[0045] In this embodiment of the invention, the crane structure is classified based on the structural parameters of the crane device. Key parameter information such as the main boom structure type, chassis device layout, slewing system structure, outrigger type and its arrangement, and drive method are extracted from the acquired crane device data. A rule-based structural classification method is used to analyze the crane structure. If the outrigger type is anchored, the chassis is a fixed platform structure, and the walking mechanism is trackless or wheeled, and the drive method is a fixed electric drive device, then it is classified as fixed crane structure data. If the structural parameters include retractable outriggers, wheeled or tracked walking mechanisms, and the drive method is vehicle-mounted diesel engine drive, then it is classified as mobile crane structure data. The component lists and structural layout parameter data of the two types of structures are output as fixed crane structure data and mobile crane structure data, respectively.

[0046] Step S142: Evaluate the hardness data of the crane's operating foundation based on the complexity of the crane's operating conditions;

[0047] In this embodiment of the invention, the foundation hardness data for crane operation is evaluated based on the complexity of the crane's operating conditions. The coordinates of the operating location recorded in the crane's operation log are matched spatially with environmental data using a Geographic Information System (GIS) interface, and geological profile data for the same location is accessed from the Geological Engineering Exploration Database. Furthermore, the complexity of the operating conditions is quantified based on parameters such as load mass, operating cycle, slewing angle, and boom change frequency recorded in the operation log. A complex operating condition is defined as one with a load mass greater than 50 tons, an operating cycle exceeding 12 hours, and a slewing frequency exceeding 20 times per hour. The foundation bearing capacity data for the matched area is extracted, and the foundation hardness is calculated using Standard Penetration Test (SPT) results or Static Cone Penetration Test (CPT) values. The foundation hardness data is then converted according to the engineering geological classification method, and the unit is megapascals (MPa) to output the foundation hardness data corresponding to the crane's operating point.

[0048] Step S143: When the hardness data of the crane's working foundation is less than 30MPa, analyze the reaction force distribution of the mobile crane structure data to obtain the reaction force distribution of the mobile crane.

[0049] In this embodiment of the invention, when the ground hardness data of the crane operation is less than 30 MPa, the structural data of the mobile crane is analyzed to determine the distribution of crane reaction forces. The structural data of the mobile crane corresponding to the area with ground hardness less than 30 MPa is read, including structural parameters such as outrigger arrangement, support span, and ground pressure distribution of tracks or tires. Based on the statics theory of cantilever beams and in accordance with the "Safety Technical Specification for Construction Lifting Machinery JGJ196-2010", the magnitude and distribution of reaction forces at the outriggers or traveling devices are calculated in a two-dimensional force plane. Static equilibrium equations are established using ANSYS Mechanical APDL, and load boundary conditions such as load mass, load position, and boom angle are input to obtain the reaction force value at each grounding node. The non-uniformity of reaction force distribution (the ratio of maximum to minimum reaction force) is then calculated and used as the reaction force distribution status of the mobile crane.

[0050] Step S144: Use the hardness data of the crane's working foundation to estimate the stability of the fixed crane's operation based on the structural data of the fixed crane, and obtain the stability of the fixed crane's operation.

[0051] In this embodiment of the invention, the stability of a fixed crane is estimated by utilizing the ground hardness data of the crane's operating foundation. Based on the fixed structural parameters, parameters such as anchorage depth, platform foundation area, and distance between the slewing center and the ground are extracted. The stability is estimated using the ratio of foundation bearing capacity to foundation stress. Specifically, the load mass and maximum operating slewing angle are assumed as input conditions. Combined with the ground hardness value, the maximum stress at the bottom of the foundation is calculated and its ratio to the corresponding ground bearing capacity is analyzed. This ratio is defined as the stability coefficient. If the ratio is less than 0.6, the crane's operational stability is considered high. The evaluation result is quantified into a stability level (0-100 points), and the operational stability of the fixed crane is output.

[0052] Step S145: Evaluate the mechanical response of the crane foundation based on the operational stability of the stationary crane and the reaction force distribution of the mobile crane;

[0053] In this embodiment of the invention, the mechanical response of the crane foundation is evaluated based on the operational stability of the fixed crane and the reaction force distribution of the mobile crane. Using a finite difference method (FDM) model of the foundation, foundation hardness data is input, and the stress distribution of the fixed crane foundation and the contact reaction force data of the mobile crane are superimposed as the superstructure load conditions. This simulates the stress fluctuations and settlement responses of the two structures within the foundation, recording indicators such as the maximum settlement difference, the maximum shear stress concentration area, and the critical shear strain development rate. The output is a dataset of the foundation mechanical response, used to reflect the degree of disturbance to the foundation caused by different structural types under complex operating environments.

[0054] Step S146: Measure the boom length data of the crane device according to the structural parameters of the crane device, and identify the distribution of the crane structure's motion trajectory according to the structural parameters of the crane device;

[0055] In this embodiment of the invention, the boom length data of the crane device is measured according to the structural parameters of the crane device. The distribution of the crane's structural motion trajectory is identified based on the structural parameters, and the boom length, number of telescopic sections, and minimum and maximum extension length of each section are read from the structural parameters. The actual boom length from the hook to the center of rotation is calculated based on the real-time position record of the boom in its deployed state. If boom elevation angle data is included, the projected length is calculated using trigonometric relationships. Then, based on the spatial coordinate difference between the lifting start and landing points for each operation in the operation log, the angular change range of the boom end movement trajectory per unit time is statistically analyzed. The maximum angular coverage is extracted as the motion trajectory distribution, and the angular distribution data and boom length data are output.

[0056] Step S147: Determine the force evolution trend of the crane structure based on the distribution of the crane structure's motion trajectory and the data on the length of the crane's lever arm;

[0057] In this embodiment of the invention, when the crane structure's motion trajectory distribution exceeds 76°, and based on the crane's boom length data, the force evolution trend of the crane structure is determined. Operation records with a motion trajectory distribution exceeding 76° are extracted. Combined with the corresponding load mass and operation time, the horizontal and vertical resultant forces acting on the center of rotation, boom base, and middle section of the boom are estimated using the mechanical inversion method based on Newton-Euler equations. Then, based on the boom length data, the boom distribution of each force is corrected, forming a force evolution sequence under multiple operating conditions. The gradient and distribution range of the force values ​​at the nodes with the largest rate of change are statistically analyzed to form the force evolution trend of the crane structure, including parameters such as the peak force growth rate and force transmission inflection points.

[0058] Step S148: Construct a three-dimensional structural simulation model of the crane based on the stress evolution trend of the crane structure and the mechanical response of the crane foundation, and obtain the three-dimensional structural simulation model of the crane.

[0059] In this embodiment of the invention, a three-dimensional structural simulation model of the crane is constructed based on the stress evolution trend of the crane structure and the mechanical response of the crane foundation. A full-structure three-dimensional geometric model is established in SolidWorks according to the structural parameters, and all key components, including the main boom, auxiliary boom, turntable, slewing mechanism, and chassis, are modeled according to the actual component dimensions. Then, the stress evolution trend and foundation response data are used as boundary conditions and imported into the ANSYS Workbench platform for static and quasi-dynamic simulations, constructing a composite coupled model that includes material properties, load changes, and foundation interaction. The simulation output includes stress cloud diagrams, displacement curves, stress time series, and critical part identification data, forming a complete three-dimensional structural simulation model data file for the crane.

[0060] Preferably, step S2, which evaluates the force coupling increment of the gantry crane based on simulation data, includes:

[0061] Detect the load lifting point information of the truss boom crane based on simulation data of the truss boom crane;

[0062] In this embodiment of the invention, simulated data of a gantry crane is used as the input basis. The position coordinates of the end hook component in the boom system and the relative motion state of the hook during its lifting operation phase (e.g., hoisting, luffing) are extracted. Combined with a list of lifting operation conditions, data including lifting point number, load mass at the lifting point (unit: kN), lifting angle (unit: degrees), and three-dimensional spatial coordinates of the point of action (unit: mm) are collected. By comparing the measured data from a triaxial force sensor with the simulated data, the continuity and fluctuation boundaries of the lifting point force value time series are verified. The specific mounting position and load variation of each lifting point on the crane boom are identified, resulting in a structured load lifting point information table.

[0063] Determine the load transfer status of the crane pulley block based on the load lifting point information of the truss boom crane;

[0064] In this embodiment of the invention, based on the acquired load information of the lifting points and combined with the actual pulley block arrangement at the end of the crane boom, such as a common three-by-three ratio pulley block, the vertical load applied to each lifting point is mechanically transformed. Specifically, each pulley axle in the pulley block is numbered and managed, and key parameters such as pulley radius and guide angle are modeled in detail, forming a geometric and mechanical feature library of the pulley block. Based on the principle of static equilibrium, the vertical load concentrated at the hook is decomposed and transmitted along the cable path of the pulley block. By constructing a load distribution matrix, the magnitude and direction of the component forces borne by each pulley node are clarified, ensuring that the component forces are balanced and correspond to each other within the entire pulley block. During load transmission, considering the geometric constraints of the pulley arrangement and the changes in cable tension, the concentrated load is transformed into an equivalent load distributed at multiple points, ensuring that the stress condition of each component node along the transmission path is accurately reflected. Subsequently, for each component node in the pulley block, the magnitude of the tension or compression it bears is recorded in detail, and the spatial direction of the force is clearly defined in the form of a direction vector in three-dimensional space to ensure the completeness and accuracy of the force information. A load transformation result table of the pulley block containing "component node number - force component magnitude (in kilonewtons) - direction vector (x, y, z coordinates)" is generated. This table comprehensively reflects the mechanical transmission state inside the crane pulley block and provides accurate basic data support for the subsequent force analysis and stability assessment of the crane structure.

[0065] Based on the load transfer situation of the crane pulley block and the load transfer path of the truss boom crane;

[0066] In this embodiment of the invention, the load transformation result of the pulley block is input into the node and component connection relationship network of the truss boom crane structure. A recursive calculation method based on the principle of structural static equilibrium is used, starting from the load application position at the lifting point, and sequentially tracing the force transmission path between each node along the truss boom structure towards the root node. Specifically, the component topology table and node connection matrix are used to fully map the relationships between each node and component in the crane truss structure, clarifying the component number connected to each node and its spatial arrangement order, and determining the force transmission direction and node force distribution. During the recursive process, based on the node equilibrium conditions, the forces entering and leaving the node are vector-summed to ensure moment balance and shear force continuity at rigid nodes. For each node, the cumulative load value at that node is calculated, and it is determined which component the load is transmitted along, forming force vector direction data. The calculation is recursively pushed upstream to the root node until the truss arm root completes the backtracking of the entire force transfer path. The system generates a complete data chain including a unique path identifier (ID), the sequence number of the components along the path, the direction of force transfer (e.g., from the lifting point to the root or in the opposite direction), and the sequence of transferred loads borne by the corresponding components. This load transfer path data chain clearly reflects the mechanical coupling relationship between the main chords, web members, and vertical members within the truss arm, providing accurate input information for subsequent dynamic stress analysis and structural stability assessment.

[0067] Calculate the degree of compression increase of the upper chord of the crane based on the load transfer path of the truss boom crane;

[0068] In this embodiment of the invention, during the mechanical response analysis of a truss boom crane, a systematic screening of the main chord member nodes is conducted to determine their spatial positions in the load transfer path. Based on their structural arrangement level, they are categorized as upper chords and lower chords. For member nodes identified as upper chords, the axial force data of each member recorded in the simulation model is combined with the time series of external load application and structural response during crane operation to extract the axial force variation value of each member over a continuous time period. During data processing, a finite difference algorithm is used to calculate the axial force variation at adjacent nodes in the time series, thereby obtaining the rate of force change per unit time. To enhance the clarity of the analysis stages, the crane operation process is divided into three typical stages: the hoisting preparation stage, the load rising stage, and the load stabilization stage, and the component force response in each stage is extracted separately. Within each stage, the force change caused by the superimposed force value is quantified by comparing the component axial force under the original static load condition with the force value during the dynamic operation simulation. The calculation results for all components are output in a structured format, including the component number, the current time point, the compressive growth value within the current time period, and the corresponding growth rate, in kilonewtons and kilonewtons per second, forming a complete dataset of upper chord stress growth, providing input data support with a clear structural hierarchy and fine granularity for subsequent coupled incremental analysis.

[0069] Calculate the degree of tension increase in the lower chord of the crane based on the load transfer path of the truss boom crane;

[0070] In this embodiment of the invention, during the structural stress analysis of a truss boom crane, the lower chord members, as an important component in the load transfer path, directly affect the stress balance and stability of the overall structure due to changes in tensile stress they bear during operation. To obtain the tensile stress changes of each lower chord member at different loading stages, all lower chord members in the structural topology diagram are numbered, and those located in the main load transfer path are selected. The analysis sequence is determined based on their specific positions and spatial connection angles from the end of the boom to the root. During the simulation loading process, combined with the structural mechanics analysis results, tensile stress data of the lower chord members at different time points are extracted time-by-time, and the stress growth changes from the initial static state to each moment in the loading stage under external force are calculated. To reflect the intensity level of stress evolution, the cross-sectional dimensions and material parameters of the members are recorded simultaneously during the analysis to obtain the trend of tensile stress changes. Using the initial state as a baseline, axial tensile force and stress data at each time point are recorded, and the ratio of changes between the two states is used as a measure of the tensile force increment of the member. Simultaneously, the rate of stress change within each loading time period is calculated to obtain the stress growth rate. The analysis results are organized in a structured format, and the output includes the lower chord member number, loading time node, corresponding tensile force increment (in kN), and stress growth rate (in megapascals per second), which are used for subsequent coupling and comparison with the main chord member stress trend and web member shear force change data and for structural integrity assessment.

[0071] The growth trend of the bending moment and axial force of the main chord is determined based on the degree of increase in tension of the lower chord and the degree of increase in compression of the upper chord of the crane.

[0072] In this embodiment of the invention, during the structural stress analysis of a truss boom crane, the component assembly between the upper and lower chords is considered as a set of coupled units. Based on the previously calculated compressive growth value of the upper chord and tensile growth value of the lower chord, the mechanical response evolution process of this component assembly under continuous vertical load is systematically evaluated. During the analysis, the number, component position, connection node information, and loading time sequence of each coupled unit are uniformly paired, and then the corresponding compressive and tensile growth data are extracted for each time period. Through the stress differences and geometric relationships at the component ends, the structural deformation trend and mechanical response evolution trajectory of the upper chord under continuous load are calculated, and the coupling relationship between bending moment and axial force is determined based on this. This process adopts a component-by-component analysis method, following the simulation time sequence, and time-slicing to deduce the stress growth of each coupled unit under actual operating conditions, extracting the stress increment data for each stage, and performing fitting analysis on the rate of change of increment between each stage to obtain the correspondence between the rate of change of bending moment and the rate of change of axial force. The analysis results are output in a structured data format, including the unique number of the main chord member, the start and end times of the loading stage, the increment of bending moment (in kN·m) and axial force (in kN) within that stage, and the growth slope between the two. Based on these indicators, a complete trend growth map is constructed to represent the coupled force evolution of different components under continuous operating conditions.

[0073] Determine the alternating increase of web shear force based on the load transfer path of the truss boom crane;

[0074] In this embodiment of the invention, during the operation of a truss boom crane, the web members are typically connected between the upper and lower chords, undertaking the task of transmitting shear forces caused by changes in the load at the lifting points, structural motion, and inertial response. To accurately characterize the force evolution characteristics of the web members under dynamic loads, all web members in the truss structure need to be numbered, and their topological connection positions in the structure need to be obtained, i.e., the spatial coordinates of each web member and its connected nodes, as well as the angle information between the members. This spatial connection information can usually be extracted from the crane structural assembly drawings or 3D modeling data. After constructing the structural mechanics simulation sequence, based on the main action stages experienced by the crane during actual operation, such as lifting, extension, and rotation, the force changes between the web member nodes are extracted frame by frame in the simulation time series. Based on the nodal force vector, the difference in force direction between the nodes at both ends of the web member is calculated, thereby determining the shear force direction borne by the web member at each moment. These shear force directions are recorded in chronological order to form a shear force direction sequence for the web members. Throughout the entire operating cycle, the system continuously tracks the changes in the shear force direction of each web member. A shear force direction switch is defined as a reversal of the shear force direction from one direction to the opposite direction, or a rapid jump from one inclination angle to another. The number of shear force direction switches experienced by each web member during the entire operation is counted in this way. Combined with the total operating time, the frequency of shear force direction switches is calculated, measured in Hertz (Hz). Simultaneously, to quantify the magnitude of shear force intensity changes, the difference in shear force experienced by the web member is extracted before and after each shear force direction switch. This difference is used to measure the intensity of mechanical fluctuations experienced by the web member during a single shear force switch, serving as a measure of shear force amplitude. The amplitude data of all shear force switch events are compiled to form a shear force amplitude sequence for each web member throughout the entire operating cycle. The analysis results of the alternating growth of web member shear force are output. The data is presented in a structured format and includes the following: web member number, shear force direction sequence (direction change information arranged chronologically), shear force amplitude data (recording the shear force difference corresponding to each switch), and shear force change frequency (in Hertz, representing the number of times the shear force direction changes per unit time). The results will serve as important input for subsequent overall stress coupling assessment and fatigue life prediction of the crane.

[0075] The force coupling increment of a truss boom crane is assessed based on the growth trend of the axial force of the main chord bending moment and the alternating growth of the shear force of the web members.

[0076] In this embodiment of the invention, the growth of bending moment and axial force of the main chord members are organized, and the alternating characteristics of shear force variation of the web members over time are also incorporated to construct a force coupling increment assessment process for the truss arm structure under dynamic overall load. In this process, time series analysis is performed on the axial compressive stress and bending moment stress borne by the main chord members at each time stage to extract the increase in stress intensity during continuous operation. Furthermore, the frequency and amplitude of shear force direction switching caused by factors such as load changes at lifting points, boom swaying, and structural natural vibration during operation are refined and statistically analyzed to form an alternating shear force trajectory. The mechanical data from these two parts are uniformly incorporated into the coupled force analysis process. Through time axis alignment, increment comparison, and component number mapping, a comprehensive force increment description of each truss arm structural unit under actual working conditions is formed. In this description process, the force value variation range, directional consistency, and frequent change characteristics of the main chord members and web members at different stages are weighted and quantitatively expressed to obtain the superposition of mechanical response intensity of the structural unit within the corresponding time period. This superposition amount can be represented as the increase in the comprehensive mechanical load borne by a component or group of components in the truss arm structure within a unit time period. This serves as the basis for subsequent fatigue life estimation, structural stability deduction, and key node reinforcement judgment. The output format adopts the form of "structural unit number - coupling increment (in kilojoules) - time node" to ensure the rigor and traceability of structural identification, quantitative comparison, and long-term trend analysis.

[0077] Preferably, step S2, determining the mechanical transmission response characteristics of the telescopic boom crane based on simulation data, includes:

[0078] The load distribution of the multi-arm of the telescopic boom crane and the telescopic boom crane's telescopic state information are collected based on the simulation data of the telescopic boom crane.

[0079] In this embodiment of the invention, based on collected simulation data of a telescopic boom crane, detailed data extraction is performed on the load application and telescopic state information of each boom segment in the multi-boom structure. Specifically, the load distribution matrix and boom segment telescopic elongation data from the numerical simulation results are read to form time-series data containing the actual force magnitude (in Newtons) and telescopic stroke (in millimeters) of each boom segment. This dataset records in detail the load response and corresponding telescopic length of each boom segment at different simulation moments, ensuring an accurate description of the load and telescopic state of the multi-boom crane. This step provides a comprehensive and structured input foundation for subsequent calculations of the dynamic force response.

[0080] Calculate the dynamic constraint force of the telescopic boom locking mechanism based on the telescopic boom crane's telescopic state information;

[0081] In this embodiment of the invention, the dynamic constraint force of the telescopic boom locking mechanism is calculated based on its structural parameters and telescopic state information. Specifically, by combining the geometric dimensions, spring stiffness, and friction coefficient of key components of the locking mechanism, the variation law of the reaction force borne by the locking pin is derived through mechanical equilibrium equations. Based on the current telescopic boom's extension length and speed, the dynamic load on the locking pin is calculated using dynamic equations, including the superposition of inertial force and frictional resistance, resulting in a time-series curve of the dynamic constraint force, expressed in Newtons (N). This constraint force reflects the strength of the locking mechanism's constraint on the boom segment movement during the telescopic boom's extension and retraction process; the data is used for continuity analysis of mechanical transmission.

[0082] Calculate the frictional force on the contact surface of the boom segment based on the load distribution of the multi-arm crane and the crane's telescopic state information;

[0083] In this embodiment of the invention, based on the load distribution and telescopic state information of the multi-arm system, the frictional force on the contact surface between arm segments is calculated using the principles of contact mechanics. The specific operation process includes: extracting the normal load distribution of the contact surface of adjacent arm segments, combining the friction coefficient of the contact surface material, and calculating the frictional resistance using Coulomb's law of friction. During the calculation, the dynamic adjustment of the frictional force by the telescopic speed is considered, and a continuous curve of the frictional force changing with time is obtained using the time-step differential-integral method. The output frictional force data includes the magnitude and direction of the force, expressed in Newtons (N), providing a quantitative indicator for subsequent evaluation of motion force transmission.

[0084] The continuity of motion force transmission between arm segments is evaluated based on the frictional force of the arm segment contact surface and the dynamic constraint force of the telescopic arm locking mechanism.

[0085] In this embodiment of the invention, the continuity of force transmission between arm segments is analyzed by combining the obtained dynamic constraint force of the telescopic arm locking mechanism with the frictional force of the arm segment contact surface calculated in step S23. The specific method includes defining a force transmission continuity index, calculating the contribution rate of the sum of the locking mechanism constraint force and frictional force to the motion resistance by comparing their temporal variation trends. A frequency domain analysis method is used to perform a Fourier transform on the temporal force signal to evaluate the harmonic components in the dynamic response, thereby determining the smoothness and discontinuity characteristics of force transmission. The force transmission continuity data is expressed as a percentage, reflecting the stability of force transmission between arm segments during the telescopic arm's telescopic movement.

[0086] The influence of the load transfer path on the load distribution of a multi-arm crane is detected based on the continuity of motion force transmission between arm segments.

[0087] In this embodiment of the invention, the influence of force transmission paths is analyzed based on the continuity index of motion force transmission and the load distribution of the telescopic boom. Specifically, a load transmission path network is constructed, and a path weight allocation algorithm in graph theory is used, with force transmission continuity as a path weight adjustment factor to quantify the attenuation and enhancement trends of mechanical transmission along the path. This analysis determines the contribution of different paths to the overall force transmission effect, and the output includes path number, path weight, and transmission efficiency, reflecting the changes in load transmission in the telescopic boom structure and providing key influencing parameters for dynamic force distribution.

[0088] Based on the influence of load transfer path, load distribution of multi-arm crane, and telescopic boom crane telescopic state information, the time-varying distribution law of crane force is analyzed.

[0089] In this embodiment of the invention, the time-varying distribution law of the force on the telescopic boom is comprehensively analyzed based on the influence of the load transfer path, the load distribution of the crane's multi-arm, and the telescopic state information. Specifically, load data from multiple times and multiple boom sections are combined with path influence factors, and a weighted statistical method is used to obtain the time-varying distribution curve of the load on each boom section. This curve reflects the spatial distribution and temporal dynamic change characteristics of the force under different telescopic lengths and load conditions. The output data is a three-dimensional data matrix of time-load-position, used to describe the dynamic distribution of the force on the telescopic boom structure.

[0090] The mechanical transmission response characteristics of the telescopic boom are determined based on the time-varying distribution law of the crane's force and the degree of influence of the load transmission path.

[0091] In this embodiment of the invention, the mechanical transmission response characteristics of the telescopic boom crane are determined based on the derived time-varying force distribution law and the degree of influence of the load transfer path in step S25. Specifically, structural mechanics transmission theory and dynamic response analysis methods are comprehensively applied, and the finite difference method is used to numerically calculate the mechanical transmission response, obtaining the mechanical response curves and transmission efficiency of the telescopic boom at various times. The output mechanical transmission response characteristics include force transmission rate, transmission stability index, and force coupling increment. The data format is structural unit number, time node, and corresponding response parameters, supporting subsequent structural safety assessment and dynamic mechanical analysis.

[0092] Preferably, step S2, which involves detecting the dynamic mechanical response data of the crane based on the force coupling increment of the truss boom crane and the mechanical transmission response characteristics of the telescopic boom crane, includes:

[0093] Determine the superposition of bending moments in the load-bearing components of the gantry crane based on the force coupling increment of the gantry crane.

[0094] In this embodiment of the invention, based on the incremental force coupling data of the truss boom crane obtained in the previous steps, this data, indexed by structural unit number, contains the incremental force coupling values ​​(in kilojoules) of each structural unit at different time points. By reading the time series data of the incremental force coupling, the moment increments experienced by each load-bearing component are collected and accumulated to form a moment superposition time curve. Specifically, the principle of moment superposition in structural mechanics is adopted, and the moment components reflected in the incremental force coupling are gradually superimposed with the known static load moment over time to obtain the total superposition value of the component moment at each moment. This process uses the geometric parameters of the structural unit (section moment of inertia, section modulus, etc.) to convert the incremental coupling energy, ensuring that the physical meaning of the moment value is accurately expressed. The output results include the moment superposition curve data corresponding to each load-bearing component number, in Newton-meters, which serves as the input for subsequent critical stability threshold analysis.

[0095] Estimate the weakening of the critical stability threshold of the boom based on the superposition of bending moments in the boom-type load-bearing components.

[0096] In this embodiment of the invention, after completing the moment superposition calculation of the load-bearing members, the critical stability threshold of each load-bearing member is evaluated using structural stability theory. Based on the member's material properties (elastic modulus, yield strength), geometric dimensions (slenderness ratio, cross-sectional shape), and boundary conditions, the critical buckling load under ideal conditions is calculated. Subsequently, the moment superposition data is used as the actual load input to calculate the remaining capacity under the actual critical buckling load. The weakening condition is expressed as the ratio of the actual critical load to the ideal critical load, with a value ranging from 0 to 1. Elastic buckling theory combined with an elastoplastic correction coefficient is used to accurately determine the degree of weakening of structural stability under load.

[0097] The risk trend of local buckling of truss boom is assessed based on the weakening of the critical stability threshold of the boom and the superposition of bending moments in the load-bearing components of the boom.

[0098] In this embodiment of the invention, by combining the critical stability threshold weakening coefficient obtained in the steps with the bending moment superposition data, a time-series local buckling risk evaluation index is established using a local buckling risk analysis method. The specific method includes calculating the safety factor of each structural unit, defined as the ratio of the critical buckling load to the actual bending moment load. This index reflects the buckling criticality of the component under the current working condition. Data processing algorithms are used to perform statistical regression on the trend of the safety factor over time to determine the increasing or decreasing trend of buckling risk. During the analysis, the dynamic changes and coupling effects of the load are fully considered to ensure an accurate description of the local buckling risk trend. The output data includes "structural unit number—local buckling risk value—time node," providing basic data for structural stability monitoring.

[0099] Estimate the degree of force transmission path deviation of the telescopic boom based on the mechanical transmission response characteristics of the telescopic boom.

[0100] In this embodiment of the invention, based on the mechanical transmission response characteristic data of the telescopic boom, which includes mechanical response parameters of each structural unit at multiple time points, such as force transmission rate and transmission efficiency, the spatial and mechanical offsets of the force transmission path are calculated by comparing the normal design force transmission path with the actual measured force transmission path data. Specifically, a structural path analysis method is used to construct a three-dimensional force transmission path network diagram based on the component node coordinates and load transmission intensity. A path deviation measurement algorithm is used to calculate the geometric deviation between the current force transmission path and the design path, including node offset distance and load distribution differences. The degree of force transmission path offset is expressed as a percentage, reflecting the overall deformation and load distribution anomalies of the force transmission path. The output is a dataset of "telescopic boom structural unit number—force transmission path offset degree—time node," used for asymmetric force determination.

[0101] The asymmetric force condition of the telescopic boom is determined based on the degree of deviation in the force transmission path of the telescopic boom.

[0102] In this embodiment of the invention, the asymmetric stress state is determined by analyzing the non-uniformity of the force distribution using data on the offset degree of the force transmission path of the telescopic boom. Specifically, the force response values ​​of structural units are statistically analyzed to calculate the differences in moment and shear force on the left and right sides and top and bottom sides of each cross-section. A force deviation index is used to define the asymmetry measure, based on the degree of imbalance between cross-sectional moment and shear force, with a value range of 0 to 1. During analysis, the deviation of force distribution in the left-right and top-bottom directions is compared in conjunction with the geometric symmetry axis of the structure to identify obviously asymmetric sections. A list of structural units in the asymmetric stress state is output, along with asymmetric stress indices and time points, serving as input for unilateral local overload detection.

[0103] The local overload condition on one side of the telescopic boom is determined based on the asymmetrical force condition of the telescopic boom and the degree of deviation of the force transmission path of the telescopic boom.

[0104] In this embodiment of the invention, unilateral local overload identification is performed based on the aforementioned asymmetric force data and force transmission path offset data. Specifically, load concentration analysis is employed to calculate the peak load and its spatial distribution density within the asymmetric force section of the structural unit. By comparing the peak load with a threshold, the overload area exceeding the design limit is determined. Combined with the force transmission path offset direction, the unilateral location of the overload is identified. Data processing uses a spatial clustering algorithm to divide the overload area into multiple unilateral local blocks and quantifies the load intensity of each block.

[0105] Dynamic mechanical response data of cranes for detecting local overload on one side of telescopic boom and local buckling risk trend of truss boom type.

[0106] In this embodiment of the invention, the local overload data of a telescopic boom on one side and the local buckling risk trend data of a truss boom are comprehensively analyzed to form complete dynamic mechanical response data of the crane. Specifically, data fusion technology is used to align the time nodes of the two sets of data, and then an overlap analysis of the local overload and buckling risk areas is performed using a spatial coordinate system. A multi-factor correlation analysis method is employed to calculate the spatial overlap and temporal correlation between the overload area and the buckling risk area, generating a dynamic mechanical response report containing "structural unit number—local buckling risk value—unilateral overload strength—time node," providing detailed data support for structural safety assessment and maintenance decisions.

[0107] Preferably, step S3 includes the following steps:

[0108] Step S31: Estimate the fatigue growth of the crane's structural components based on the crane's dynamic mechanical response data;

[0109] In this embodiment of the invention, the obtained dynamic mechanical response data of the crane is used as the basic input to analyze in detail the stress change characteristics of structural components at different time points. The dynamic loads borne by each key structural component of the crane (including the main chord, web members, telescopic boom, and connecting nodes) are statistically segmented, and the stress amplitude, average stress, and number of cycles are extracted for each time period. Fatigue accumulation calculation is performed using the stress-life (SN) curve principle and the mining method to convert stress cycles in the time series into fatigue damage values. The fatigue damage value calculation is based on the fatigue performance parameters of each component material (such as fatigue limit and fatigue strength coefficient) and the number of load cycles to complete the assessment of the fatigue accumulation per unit time. Specifically, this step uses a numerical integration method based on load spectrum analysis to superimpose the fatigue damage corresponding to different stress amplitude cycles to obtain the overall fatigue growth curve.

[0110] Step S32: Determine the crack growth trend of crane components based on the crane's dynamic mechanical response data and the fatigue growth of crane structural components;

[0111] In this embodiment of the invention, by combining information on local stress concentration in the structure during dynamic mechanical response, the specific trends of crack initiation and propagation are determined. The stress state of key structural components is amplified using the stress concentration factor method to accurately identify high-stress regions where cracks occur. Subsequently, based on fatigue crack propagation theory, the Paris formula is used to describe the increase in crack length with the number of load cycles, combining the cumulative fatigue damage value with the crack propagation rate. Specifically, the initial crack length of each structural component is assigned a value, the crack propagation rate is calculated based on the range of cyclic stress intensity factors, and then the evolution of crack length over time is calculated through numerical iteration. This process, combined with the dynamic response time series, forms a crack growth time curve.

[0112] Step S33: Detect the fracture risk of crane components based on the crack growth trend of crane components and the fatigue growth of crane structural components;

[0113] In this embodiment of the invention, a fracture risk assessment index is constructed based on the crack length data obtained in Example S32 and the fatigue accumulation data in Example S31. Specifically, the fracture toughness criterion in fracture mechanics is used, combined with crack size and the material's critical crack length threshold, to determine the fracture risk. The ratio of the critical crack length to the actual crack length of the structural component is used as the fracture risk factor. The closer this factor value is to or greater than 1, the higher the fracture risk. By analyzing the change of the fracture risk factor over time, the trend change of the component's fracture risk is determined.

[0114] Step S34: Determine the chain degradation status of crane components based on the risk of crane component fracture.

[0115] In this embodiment of the invention, using the high-fracture-risk components and their spatial locations identified in Example S33, and combining them with the topological relationship of the crane structure, chain degradation is identified. Based on the structural connection relationships and mechanical transmission paths, the impact of the fracture-risk components on adjacent components is analyzed, and a topology propagation algorithm is used to transmit the fracture risk along the structural path to neighboring components. Subsequently, based on the force transmission law, the magnitude of the change in the stress state of adjacent components and the cumulative fatigue damage acceleration value caused by the failure of the fractured component are calculated. Through iterative calculation, the cascading fatigue growth and failure trend caused by the increased fracture risk of one component is identified.

[0116] Preferably, step S32 includes the following steps:

[0117] Step S321: Predict the expansion of fatigue area in the crane structure based on the fatigue growth of the crane structural components;

[0118] In this embodiment of the invention, based on the fatigue growth data of the crane structural components obtained in step S31, a quantitative analysis is performed on the relationship between the cumulative fatigue damage value and the fatigue crack area. Using the fatigue crack propagation law, the fatigue damage value is converted into the fatigue crack propagation area. Combining the crack propagation rate and crack morphology characteristics of the structural material, the change in the local fatigue crack area of ​​the structure over time is calculated. Specifically, using the surface crack morphology measurement data and the cumulative fatigue damage curve of the structural component, the microscopic crack propagation geometry is used. Crack length growth is calculated through integration, and crack area growth is estimated by combining the crack width. During data processing, corresponding crack propagation rate parameters are applied for different component material characteristics to ensure the accuracy of crack area prediction. The output fatigue area propagation data includes the component number, time node, and corresponding fatigue crack area value (unit: cm). 2 This provides data support for determining instability.

[0119] Step S322: When the fatigue area of ​​the crane structure expands to more than 10cm, determine the instability of the crane component structure;

[0120] In this embodiment of the invention, the fatigue crack area propagation data calculated in Example S321 is used to set the structural instability judgment threshold to 10cm. 2 For each structural component, the real-time measured fatigue crack area is compared with a threshold. When the fatigue crack area first exceeds 10 cm², the crack is considered closed. 2 When the stress level is reached, the component is marked as entering a structural instability state. The judgment process is based on time-series data and uses Boolean logic to determine whether the fatigue crack area exceeds a threshold, generating an instability event trigger signal. This judgment information includes the component number, the instability time point, and the instability state identifier.

[0121] Step S323: Based on the dynamic mechanical response data of the crane, detect the degree of deformation of the crane component structure to determine the instability of the crane component structure;

[0122] In this embodiment of the invention, after structural instability occurs, deformation detection is performed on the unstable component based on the dynamic mechanical response data of the crane obtained in step S2. Deformation detection uses a high-precision laser displacement sensor or fiber Bragg grating sensor to collect displacement data of key nodes of the component in real time. The data acquisition frequency is set to above 1kHz to ensure the capture of details of dynamic deformation changes. By comparing the node displacements before and after instability, the structural deformation is calculated, with the degree of deformation expressed in millimeters. The deformation calculation uses the difference method, that is, the node displacement at the current moment is subtracted from the node displacement at the reference state to obtain the actual deformation. Multiple node deformations are weighted and averaged to obtain the overall structural deformation degree.

[0123] Step S324: When the structural deformation of the crane component exceeds 7.3 mm, determine the local stress growth of the crane component;

[0124] In this embodiment of the invention, based on the structural deformation data obtained in Example S323, 7.3 mm is set as the deformation threshold. By judging the deformation threshold, the time point and corresponding component whose deformation exceeds the threshold are identified. For the component exceeding the limit, local stress growth is calculated by combining the strain data from the strain gauge sensors. Specific steps include reading the strain gauge data of the local area, converting the strain into stress, and using the elastic modulus of the material to complete the stress calculation. The local stress value is compared with the historical reference stress to obtain the stress growth amount.

[0125] Step S325: Determine the crack growth trend of the crane component based on the local stress growth of the crane component and the degree of structural deformation of the crane component.

[0126] In this embodiment of the invention, combining the local stress growth in step S324 with the structural deformation data in embodiment S323, the crack growth trend is determined using fatigue crack propagation theory. The local stress growth value is converted into a stress intensity factor range, and the crack propagation rate is comprehensively calculated by combining the influence of deformation degree on the stress field at the crack tip. The crack propagation rate is calculated using the Paris formula based on the current crack length and stress intensity factor. Through numerical integration, the crack propagation rate is accumulated over time to obtain the evolution curve of the crack length over time. This process employs a discrete time step iterative calculation method to ensure the temporal resolution of the crack growth trend.

[0127] Of particular importance, step S34 includes the following steps:

[0128] Step S341: Estimate the increasing trend of the load-bearing pressure of the crane components based on the fracture risk status of the crane components;

[0129] In this embodiment of the invention, based on the fracture risk data of crane components obtained in previous steps, fracture probability analysis is performed on each key component (such as the main boom member, connecting nodes, pulley system, etc.). Combining the fracture risk level with historical stress data, the growth trend of the component's bearing pressure is calculated using time series analysis. Specific operations include: mapping the fracture risk level to the corresponding stress threshold range; obtaining the current bearing pressure value by analyzing stress sensor data collected by the structural monitoring system; and determining the stress change trend line in the future period based on the fracture risk level. The pressure growth trend is curve-fitted using linear or nonlinear fitting algorithms (such as polynomial regression) to generate the bearing pressure growth curve for each component during subsequent operation, with the data unit being megapascals (MPa). This process is completed by an automated data processing program to ensure the continuity and accuracy of the trend estimation. The resulting bearing pressure growth trend data serves as input for subsequent steps.

[0130] Step S342: Determine the overall stress balance failure of the crane based on the increasing trend of the load-bearing pressure on the crane components;

[0131] In this embodiment of the invention, a mechanical equilibrium state assessment model for the overall crane structure is constructed based on the increasing trend of bearing pressure of each component obtained in step S341. This model calculates the force safety factor by comparing the bearing pressure of each component with its design bearing limit. A matrix force balance analysis method is used to convert the pressure data of individual components into the internal force distribution of the overall structure, identifying abnormal force points and areas of concentrated stress. Subsequently, the overall stress state of the structure is judged based on mechanical equilibrium equations (such as static equilibrium equations ∑F=0, ∑M=0). If the safety factor of any key node or component is lower than a preset critical value, it is determined that there are signs of failure in the overall force balance of the crane. This analysis process is completed with the assistance of finite element analysis software. The software inputs include the bearing pressure trend of components, structural topology, and connection strength parameters, outputting overall force balance state indicators and generating a force balance failure assessment report.

[0132] Step S343: Predict the structural damage status of the crane based on the overall force balance failure of the crane;

[0133] In this embodiment of the invention, based on the overall stress balance failure determined in step S342, a structural damage mechanics analysis method is used to predict the potential damage status of the crane structure. Specifically, fracture mechanics and fatigue life prediction techniques are employed, taking the overloaded area caused by the stress balance failure as the starting point to analyze the crack initiation and propagation trends. By combining the stress intensity factor (K) of the stress concentration area with the material fatigue limit, the damage accumulation rate and residual life are calculated. Combined with a three-dimensional structural simulation model, the damage evolution process under different load conditions is simulated to identify the damage propagation path and its impact on the overall structural stiffness and load-bearing capacity. The damage status output includes crack size, fatigue crack growth rate, and failure time point, and the data format is a structural damage assessment report.

[0134] Step S344: Determine the chain degradation status of crane components based on the damage status of the crane structure and the overall force balance failure of the crane.

[0135] In this embodiment of the invention, a chain degradation analysis model for crane components is constructed by combining the predicted structural damage status in step S343 and the overall force balance failure status in step S342. The model uses structural damage and mechanical imbalance as core variables, and employs a recursive algorithm to infer the force changes and performance degradation of adjacent components layer by layer based on the force transmission path and component connection relationships. The degree of degradation of each component is represented by a damage factor D, calculated based on the rate of force change and the cumulative effect of damage. During the analysis, the initial damaged component is first identified, and then its impact on connected components is calculated along the mechanical path, forming a chain degradation sequence. The chain degradation model outputs the degradation level of each key component and their mutual influence relationships.

[0136] Preferably, step S4 includes the following steps:

[0137] Step S41: Detect the stress redistribution during crane operation based on the chain degradation of crane components;

[0138] In this embodiment of the invention, based on the chain degradation sequence and degradation level data of crane components obtained in step S34, structural components within the influence range of chain degradation are screened to clarify the degradation transmission path and the set of affected components. For these affected structural components, high-precision strain gauges deployed at key nodes are used to collect stress data in real time, with the sampling frequency set above 1kHz to ensure complete capture of dynamic mechanical response. Through data fusion technology, the stress data of multiple nodes are spatially interpolated and weighted to reconstruct the stress distribution field of the overall structure. Using the stiffness matrix of the foundation structure obtained offline by the finite element method as an initial reference, and combined with the stiffness changes caused by chain degradation, the original stiffness matrix is ​​adjusted to the stiffness matrix under the degradation state. Based on the real-time collected stress data and the adjusted stiffness matrix, an inverse problem solving algorithm is used to obtain the stress redistribution state during crane operation.

[0139] Step S42: Detect the superposition data of nonlinear mechanical properties of the crane based on the stress redistribution during crane operation;

[0140] In this embodiment of the invention, the stress redistribution data of the crane operation obtained in Example S41 is used to extract nonlinear mechanical superposition features from key areas of the structure. Based on the redistributed stress data, the stress peak regions exceeding the linear elastic range in the structure are identified, and the stress time-series data of the nonlinear response region is extracted through threshold filtering. Time-frequency analysis methods, such as Short-Time Fourier Transform (STFT) or Wavelet Transform, are used to decompose the stress signal in the nonlinear response region into multiple scales, revealing the time-varying characteristics and nonlinear spectral components in the stress superposition process. Combining multi-point sensor data, nonlinear system identification techniques (such as Volterra series expansion) are used to model the stress superposition effect, resulting in a nonlinear mechanical superposition data matrix. This data matrix covers the nonlinear response laws of the structure under combined loads and degradation states, specifically including nonlinear stress peaks, phase hysteresis, and energy coupling indices.

[0141] Step S43: Determine the operational stability gradient decay based on the superposition data of nonlinear mechanics of the crane using the three-dimensional structural simulation model of the crane;

[0142] In this embodiment of the invention, combining the nonlinear mechanical superposition data obtained in step S42 and relying on the established high-precision three-dimensional structural simulation model, gradient decay analysis is performed on the crane's operational stability. The nonlinear mechanical superposition data is input into the three-dimensional structural simulation platform. This simulation model consists of a three-dimensional finite element mesh with fine mesh division, covering key parts such as the main boom, telescopic boom, and supporting structures. During the simulation, the actual operating state of the structure is simulated by applying dynamic loads and adjusting degenerate stiffness. The energy method and stability criteria (such as critical load calculation and bending modal analysis) are used to analyze the stability gradient change of the structure under nonlinear loads. By calculating the stability margin gradient of each structural element, a stability gradient decay distribution map is obtained, reflecting the spatial and temporal evolution of structural stability.

[0143] Step S44: Determine the degree of decrease in crane operating accuracy based on the stable gradient attenuation.

[0144] In this embodiment of the invention, the degree of crane operation accuracy attenuation is determined based on the stable gradient attenuation data in Example S43. Operation accuracy is defined as the positioning error of the crane hook or load position, which fluctuates due to structural stability. A correlation curve between stable gradient attenuation and operation accuracy error is established based on experimental calibration data or historical operation records. For the stable gradient value at each time point, an interpolation algorithm is used to calculate the corresponding percentage of operation accuracy attenuation. By mapping real-time monitoring data to the calibration curve, an operation accuracy attenuation curve is obtained, quantifying the magnitude of accuracy loss.

[0145] Step S45: Optimize the mechanical structure of the crane according to the degree of decrease in the crane's operating accuracy to obtain the optimized mechanical data of the crane structure.

[0146] In this embodiment of the invention, based on the degree of operational accuracy attenuation determined in Example S44, the crane's mechanical structure optimization process is initiated. Combining structural mechanics principles and stress analysis results, the range of structural parameters to be optimized is determined, such as boom cross-sectional dimensions, connection node stiffness, and support structure reinforcement schemes. Iterative optimization algorithms (e.g., genetic algorithms or gradient descent methods) are used for parameter optimization, with the objective function being to minimize the operational accuracy attenuation rate and improve the structural stability gradient. During the optimization process, finite element simulation results are used to provide real-time feedback on changes in mechanical response, gradually adjusting design parameters to form a set of structural parameter combinations, significantly improving operational accuracy performance. The structural mechanics optimization data includes a list of optimized structural parameters, corresponding mechanical performance indicators, and predicted operational accuracy improvement data.

[0147] Of particular importance, step S42 includes the following steps:

[0148] Step S421: Determine the stress growth of the crane connecting components based on the stress redistribution during crane operation;

[0149] In this embodiment of the invention, based on the crane's operational stress redistribution data obtained in the preceding steps, stress analysis is performed on each connecting component of the crane (including hinge nodes, welded points, bolted connections, and mechanical connectors). Stress change curves corresponding to the locations of these connecting components are extracted from the operational stress redistribution data. Strain gauges and force sensors are used to collect the stress values ​​of each connecting component in real time. By comparing with baseline stress data, the stress increase rate for each connecting component is calculated. The stress increase is expressed as the rate of change of stress per unit time, with the data unit being megapascals per hour (MPa / h). Using time-series data analysis methods, the stress change trends of each connecting component are fitted over time to obtain stress increase curves. This process is combined with finite element analysis software to simulate the stress on the connecting component structure, verifying the accuracy of the sensor-collected data and ensuring the reliability of the stress increase data. The output is quantitative data on the stress increase of the connecting components.

[0150] Step S422: Detect the loss of crane connection gaps based on the stress growth of crane connection components;

[0151] In this embodiment of the invention, based on the stress growth data of the connecting components determined in step S421, the mechanical connection gaps of each connecting component of the crane are periodically measured using gap measuring instruments (such as laser rangefinders and ultrasonic thickness gauges). The measured connection gap dimensions are compared with the initial design gap, and combined with the stress growth trend, the rate of change and degree of wear of the connection gap are determined. Specifically, high-precision non-contact measurement technology is used to monitor the minute deformations and gap expansion on the surface of the connecting components in real time. Through numerical calculation, a connection gap wear curve is obtained, reflecting the change in connection gap over time, in millimeters per hour (mm / h). At the same time, correlation analysis is performed on the connection gap change and stress growth data to verify the intrinsic relationship between gap wear and stress growth, obtaining quantitative data on connection gap wear for subsequent structural loosening prediction.

[0152] Step S423: Predict the loosening status of the crane structure based on the loss of the crane connection gap;

[0153] In this embodiment of the invention, the connection gap loss data obtained in step S422 is input into the structural loosening discrimination model. The discrimination model, based on the design tolerances and stress limits of the mechanical connectors, determines the critical threshold for the increase in connection gap. A mechanical loosening assessment algorithm is used to calculate the loosening degree index (loosening coefficient) caused by gap loss in the connecting components. This index reflects the increase in the degrees of freedom of motion of the connecting components and the decrease in the overall stiffness of the structure. The loosening status is obtained through comprehensive analysis of vibration data detected by sensors and connection gap expansion data. Combined with the spectral characteristics collected by a dynamic vibration meter, the changes in vibration frequency and the increasing trend of amplitude caused by structural loosening are identified. The structural loosening status data is output, including the loosening level, location, and range of influence, providing a basis for subsequent vibration enhancement analysis.

[0154] Step S424: Detect the transient vibration enhancement data of the crane structure based on the crane structure loosening condition and the loss of crane connection gaps;

[0155] In this embodiment of the invention, based on the structural loosening status in step S423 and the connection gap loss in step S422, accelerometers are deployed at key nodes of the crane to collect transient vibration signals of the crane structure. Using time-domain and frequency-domain analysis methods, short-time Fourier transform (STFT) and wavelet transform techniques are employed to process the transient vibration signals, extracting the amplitude, frequency, and phase characteristics. The transient vibration enhancement data reflects the sudden increase in vibration amplitude and frequency drift caused by connection loosening and increased gaps. Through correlation analysis between vibration data and connection gaps and loosening levels, the vibration enhancement magnitude is quantified, forming a structural transient vibration enhancement index. This index reflects the changing trend of the structure's dynamic response and serves as an input parameter for nonlinear mechanical superposition analysis. The output transient vibration enhancement data includes detailed information such as peak vibration amplitude, energy spectral density, and frequency distribution.

[0156] Step S425: Detect the superposition data of nonlinear mechanics of the crane based on the enhanced transient vibration data of the crane structure.

[0157] In this embodiment of the invention, based on the enhanced transient vibration data obtained in step S424, and combined with structural dynamics nonlinear analysis methods, the nonlinear mechanical superposition characteristics of the crane structure are detected. Through nonlinear system identification technology, the nonlinear response components in the vibration signal are analyzed, including harmonic distortion, frequency coupling, and multimodal vibration interactions. Using time-frequency analysis and phase space reconstruction methods, stress fluctuations and dynamic instability phenomena in the structure under nonlinear superposition are identified. During the detection process, the enhanced vibration signal and stress data are jointly input into a multiphysics coupling calculation platform to calculate the nonlinear mechanical superposition value within the structure, including peak stress superposition and dynamic load amplification factor. The results are output in the form of a nonlinear mechanical superposition quantitative index, providing a basis for structural safety assessment and maintenance decisions. This step completes the comprehensive monitoring and quantitative analysis of the crane's nonlinear dynamic response.

[0158] The present invention also provides a crane structural parameter stress analysis system for performing the crane structural parameter stress analysis method described above. The crane structural parameter stress analysis system includes:

[0159] The simulation module is used to acquire crane device data and crane operation logs; a three-dimensional structural simulation model of the crane is constructed based on the crane operation logs and crane device data; and the crane operation simulation is performed based on the three-dimensional structural simulation model to obtain crane operation simulation data.

[0160] The dynamic mechanical response detection module is used to divide the crane boom structure based on crane operation simulation data to obtain simulation data for truss boom cranes and telescopic boom cranes; to evaluate the force coupling increment of the truss boom crane based on the truss boom crane simulation data; to determine the mechanical transmission response characteristics of the telescopic boom crane based on the telescopic boom crane simulation data; and to detect the dynamic mechanical response data of the crane based on the force coupling increment and the mechanical transmission response characteristics of the telescopic boom crane.

[0161] The component chain degradation determination module is used to detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; and to determine the chain degradation status of crane components based on the fracture risk status of crane components.

[0162] The mechanical structure optimization module is used to determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; and to perform mechanical structure optimization processing on the crane based on the operational stability gradient decay to obtain the mechanical optimization data of the crane structure.

[0163] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for analyzing the stress parameters of a crane structure, characterized in that, The following steps are involved: Step S1: Obtain crane device data and crane operation log; A three-dimensional structural simulation model of the crane is constructed based on the crane operation log and crane device data; the crane operation is simulated based on the three-dimensional structural simulation model to obtain crane operation simulation data; Step S2: Divide the crane boom structure according to the crane operation simulation data to obtain simulation data of truss boom crane and telescopic boom crane; evaluate the force coupling increment of truss boom crane according to the truss boom crane simulation data; determine the mechanical transmission response characteristics of telescopic boom crane according to the telescopic boom crane simulation data; detect the dynamic mechanical response data of crane according to the force coupling increment of truss boom crane and the mechanical transmission response characteristics of telescopic boom crane. Step S3: Detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; determine the chain degradation status of crane components based on the fracture risk status of crane components. Step S4: Determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; optimize the mechanical structure of the crane based on the operational stability gradient decay to obtain the optimized mechanical data of the crane structure.

2. The method for analyzing the stress parameters of a crane structure according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Obtain crane device data and crane operation log; Step S12: Collect the structural parameters of the crane device based on the crane device data; Step S13: Evaluate the complexity of the crane's operating conditions based on the crane's operation log and the crane's structural parameters to obtain the complexity of the crane's operating conditions; Step S14: Based on the complexity of the crane's operating conditions and the structural parameters of the crane device, construct a three-dimensional structural simulation model of the crane to obtain the three-dimensional structural simulation model of the crane. Step S15: Perform crane operation simulation based on the crane's three-dimensional structural simulation model to obtain crane operation simulation data.

3. The method for analyzing the stress of crane structural parameters according to claim 2, characterized in that, Step S14 includes the following steps: Step S141: Perform crane structure division processing based on the crane device structural parameters to obtain fixed crane structure data and mobile crane structure data; Step S142: Evaluate the hardness data of the crane's operating foundation based on the complexity of the crane's operating conditions; Step S143: When the hardness data of the crane's working foundation is less than 30MPa, analyze the reaction force distribution of the mobile crane structure data to obtain the reaction force distribution of the mobile crane. Step S144: Use the hardness data of the crane's working foundation to estimate the stability of the fixed crane's operation based on the structural data of the fixed crane, and obtain the stability of the fixed crane's operation. Step S145: Evaluate the mechanical response of the crane foundation based on the operational stability of the stationary crane and the reaction force distribution of the mobile crane; Step S146: Measure the boom length data of the crane device according to the structural parameters of the crane device, and identify the distribution of the crane structure's motion trajectory according to the structural parameters of the crane device; Step S147: Determine the force evolution trend of the crane structure based on the distribution of the crane structure's motion trajectory and the data on the length of the crane's lever arm; Step S148: Construct a three-dimensional structural simulation model of the crane based on the stress evolution trend of the crane structure and the mechanical response of the crane foundation, and obtain the three-dimensional structural simulation model of the crane.

4. The method for analyzing the stress of crane structural parameters according to claim 1, characterized in that, Step S2, which evaluates the force coupling increment of the gantry crane based on simulation data, includes: Detect the load lifting point information of the truss boom crane based on simulation data of the truss boom crane; Determine the load transfer status of the crane pulley block based on the load lifting point information of the truss boom crane; Based on the load transfer situation of the crane pulley block and the load transfer path of the truss boom crane; Calculate the degree of compression increase of the upper chord of the crane based on the load transfer path of the truss boom crane; Calculate the degree of tension increase in the lower chord of the crane based on the load transfer path of the truss boom crane; The growth trend of the bending moment and axial force of the main chord is determined based on the degree of increase in tension of the lower chord and the degree of increase in compression of the upper chord of the crane. Determine the alternating increase of web shear force based on the load transfer path of the truss boom crane; The force coupling increment of a truss boom crane is assessed based on the growth trend of the axial force of the main chord bending moment and the alternating growth of the shear force of the web members.

5. The method for analyzing the stress of crane structural parameters according to claim 1, characterized in that, Step S2, which determines the mechanical transmission response characteristics of the telescopic boom crane based on simulation data, includes: The load distribution of the multi-arm of the telescopic boom crane and the telescopic boom crane's telescopic state information are collected based on the simulation data of the telescopic boom crane. Calculate the dynamic constraint force of the telescopic boom locking mechanism based on the telescopic boom crane's telescopic state information; Calculate the frictional force on the contact surface of the boom segment based on the load distribution of the multi-arm crane and the crane's telescopic state information; The continuity of motion force transmission between arm segments is evaluated based on the frictional force of the arm segment contact surface and the dynamic constraint force of the telescopic arm locking mechanism. The influence of the load transfer path on the load distribution of a multi-arm crane is detected based on the continuity of motion force transmission between arm segments. Based on the influence of load transfer path, load distribution of multi-arm crane, and telescopic boom crane telescopic state information, the time-varying distribution law of crane force is analyzed. The mechanical transmission response characteristics of the telescopic boom are determined based on the time-varying distribution law of the crane's force and the degree of influence of the load transmission path.

6. The method for analyzing the stress parameters of a crane structure according to claim 1, characterized in that, Step S2 involves detecting the crane's dynamic mechanical response data based on the force coupling increment of the gantry crane and the mechanical transmission response characteristics of the telescopic boom crane, including: Determine the superposition of bending moments in the load-bearing components of the gantry crane based on the force coupling increment of the gantry crane. Estimate the weakening of the critical stability threshold of the boom based on the superposition of bending moments in the boom-type load-bearing components. The risk trend of local buckling of truss boom is assessed based on the weakening of the critical stability threshold of the boom and the superposition of bending moments in the load-bearing components of the boom. Estimate the degree of force transmission path deviation of the telescopic boom based on the mechanical transmission response characteristics of the telescopic boom. The asymmetric force condition of the telescopic boom is determined based on the degree of deviation in the force transmission path of the telescopic boom. The local overload condition on one side of the telescopic boom is determined based on the asymmetrical force condition of the telescopic boom and the degree of deviation of the force transmission path of the telescopic boom. Dynamic mechanical response data of cranes for detecting local overload on one side of telescopic boom and local buckling risk trend of truss boom type.

7. The method for analyzing the stress parameters of a crane structure according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Estimate the fatigue growth of the crane's structural components based on the crane's dynamic mechanical response data; Step S32: Determine the crack growth trend of crane components based on the crane's dynamic mechanical response data and the fatigue growth of crane structural components; Step S33: Detect the fracture risk of crane components based on the crack growth trend of crane components and the fatigue growth of crane structural components; Step S34: Determine the chain degradation status of crane components based on the risk of crane component fracture.

8. The method for analyzing the stress of crane structural parameters according to claim 7, characterized in that, Step S32 includes the following steps: Step S321: Predict the expansion of fatigue area in the crane structure based on the fatigue growth of the crane structural components; Step S322: When the fatigue area of ​​the crane structure expands to more than 10cm, determine the instability of the crane component structure; Step S323: Based on the dynamic mechanical response data of the crane, detect the degree of deformation of the crane component structure to determine the instability of the crane component structure; Step S324: When the structural deformation of the crane component exceeds 7.3 mm, determine the local stress growth of the crane component; Step S325: Determine the crack growth trend of the crane component based on the local stress growth of the crane component and the degree of structural deformation of the crane component.

9. The method for analyzing the stress of crane structural parameters according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Detect the stress redistribution during crane operation based on the chain degradation of crane components; Step S42: Detect the superposition data of nonlinear mechanical properties of the crane based on the stress redistribution during crane operation; Step S43: Determine the operational stability gradient decay based on the superposition data of nonlinear mechanics of the crane using the three-dimensional structural simulation model of the crane; Step S44: Determine the degree of decrease in crane operating accuracy based on the stable gradient attenuation. Step S45: Optimize the mechanical structure of the crane according to the degree of decrease in the crane's operating accuracy to obtain the optimized mechanical data of the crane structure.

10. A system for analyzing the structural parameters of a crane, characterized in that, For performing the crane structural parameter stress analysis method as described in claim 1, the crane structural parameter stress analysis system includes: The simulation module is used to acquire crane device data and crane operation logs; a three-dimensional structural simulation model of the crane is constructed based on the crane operation logs and crane device data; and the crane operation simulation is performed based on the three-dimensional structural simulation model to obtain crane operation simulation data. The dynamic mechanical response detection module is used to divide the crane boom structure based on crane operation simulation data to obtain simulation data for truss boom cranes and telescopic boom cranes; to evaluate the force coupling increment of the truss boom crane based on the truss boom crane simulation data; to determine the mechanical transmission response characteristics of the telescopic boom crane based on the telescopic boom crane simulation data; and to detect the dynamic mechanical response data of the crane based on the force coupling increment and the mechanical transmission response characteristics of the telescopic boom crane. The component chain degradation determination module is used to detect the fracture risk status of crane components based on the crane's dynamic mechanical response data; and to determine the chain degradation status of crane components based on the fracture risk status of crane components. The mechanical structure optimization module is used to determine the operational stability gradient decay based on the chain degradation of crane components according to the three-dimensional structural simulation model of the crane; and to perform mechanical structure optimization processing on the crane based on the operational stability gradient decay to obtain the mechanical optimization data of the crane structure.

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