A method and system for protected conveying of lightweight gypsum boards

Abstract

The present application provides a kind of light gypsum board protection conveying method and system, it is related to material transportation protection technical field, method includes: receiving basic conveying information;Carrying out loading scheme matching, obtain K kind of K loading strategies of available vehicle type;With outside dimension limit value, axle load limit value and emission grade as traffic constraint condition, carry out path screening, obtain K group of alternative conveying path;Call K group of road section working condition attribute sequence, construct K group of dynamic transport load spectrum model;Carrying out plate structure damage boundary analysis, obtain K damage boundary threshold function;Carrying out the whole chain risk transmission simulation of fusion loading and unloading link risk, screening positioning target protection conveying path.The present application solves the technical problem that the light gypsum board transportation of prior art often relies on simple path selection and loading scheme, ignores the influence of various actual factors on plate damage, leading to higher damage risk in the process of transportation.

Description

Technical Field

[0001] This invention relates to the field of material transportation protection technology, specifically to a protective transportation method and system for lightweight gypsum board. Background Technology

[0002] Lightweight gypsum board is widely used in home decoration and commercial buildings as a building and decoration material due to its lightweight, easy cutting and good sound insulation properties. Lightweight gypsum board usually has a large area and a thin structure, making it susceptible to impact, vibration and deformation during transportation. Therefore, how to effectively protect and avoid damage during transportation has become an important issue in the transportation of gypsum board.

[0003] Existing lightweight gypsum board transportation often relies on simple route selection and loading schemes, usually ignoring the impact of various practical factors on the board damage, such as road conditions and loading and unloading impacts. This results in a high risk of damage during transportation, and the boards are easily damaged by impacts, vibrations, or overloading, especially in loading and unloading and on complex transportation routes. Summary of the Invention

[0004] This application provides a protective conveying method and system for lightweight gypsum board, aiming to solve the technical problem that the transportation of lightweight gypsum board in the prior art often relies on simple route selection and loading schemes, ignoring the impact of various actual factors on the damage to the board, resulting in a high risk of damage during transportation.

[0005] The first aspect disclosed in this application provides a protective transportation method for lightweight gypsum board. The method includes: receiving basic transportation information, wherein the basic transportation information includes transportation start and end points, board type, board specifications, and board quantity; matching loading schemes in a vehicle pool based on the board specifications and board quantity to obtain K loading strategies for K available vehicle types; using the external dimension limits, axle load limits, and emission levels of the K available vehicle types as traffic constraints, performing path screening with the transportation start and end points as endpoints to obtain K sets of candidate transportation paths; retrieving K sets of road segment working condition attribute sequences for the K sets of candidate transportation paths from a road infrastructure database to construct K sets of dynamic transportation load road spectrum models; performing structural damage boundary analysis of the board based on the board type and board specifications under the K loading strategies to obtain K damage boundary threshold functions; using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transportation load road spectrum models, performing a full-chain risk transmission simulation that integrates loading and unloading risks to screen and locate target protective transportation paths.

[0006] The second aspect of this application discloses a protective conveying system for lightweight gypsum board. The system is used in the aforementioned protective conveying method for lightweight gypsum board. The system includes: an information receiving module for receiving basic conveying information, wherein the basic conveying information includes the transport start and end points, board type, board specifications, and board quantity; a loading scheme matching module for matching loading schemes in a vehicle pool based on the board specifications and board quantity to obtain K loading strategies for K available vehicle types; and a path filtering module for using the external dimension limits, axle load limits, and emission levels of the K available vehicle types as traffic constraints to select a path from the transport start and end points. The system filters the endpoints to obtain K sets of candidate transport routes; the model building module retrieves the K sets of road segment working condition attribute sequences of the K sets of candidate transport routes from the road infrastructure database to construct K sets of dynamic transport load road spectrum models; the damage boundary analysis module performs structural damage boundary analysis of the plate material under the K loading strategies based on the plate material type and specifications to obtain K damage boundary threshold functions; the risk transmission simulation module uses the K damage boundary threshold functions as safety criteria and combines the K sets of dynamic transport load road spectrum models to perform full-chain risk transmission simulation that integrates loading and unloading risks, and filters and locates target protection transport routes.

[0007] One or more technical solutions provided in this application have at least the following beneficial effects: By receiving and processing basic transport information, foundational data is provided for subsequent loading schemes, route planning, and risk assessment. Based on the specifications and quantity of the sheet metal, loading schemes are matched within a vehicle pool to ensure the selection of suitable vehicle models for transportation. The resulting K loading strategies effectively utilize the load and space of each vehicle, guaranteeing transportation efficiency and safety. Route selection is performed using vehicle dimensions, axle load, and emission standards as constraints. By comprehensively considering these constraints, it is ensured that vehicles will not encounter traffic obstacles due to excessive size or weight during transportation, and that environmental requirements are met, ensuring that the transportation scheme complies with regulations. Dynamic transport load road spectrum models are constructed by retrieving road segment operating condition attributes from the road infrastructure database. These models can help... This system helps assess the physical impacts that vehicles and sheet metal may suffer under different road conditions, thereby improving the safety and stability of transportation. Based on the type and specifications of the sheet metal and loading strategies, it performs structural damage boundary analysis, obtaining K damage boundary threshold functions. These functions provide a safe load-bearing limit for each transportation route, accurately determining the maximum load the sheet metal will bear during transportation and providing a basis for subsequent risk assessment, ensuring that the sheet metal is not damaged due to overloading or impact. Combining the damage boundary threshold functions and a dynamic transportation load spectrum model, it conducts full-chain risk transmission simulation, accurately quantifying the comprehensive risk of each route, identifying potential risk points in advance, optimizing route selection, and avoiding damage, making the transportation process more efficient, safe, and economically viable.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of a protective conveying method for lightweight gypsum board provided in an embodiment of this application.

[0010] Figure 2 This is a schematic diagram of a protective conveying system for lightweight gypsum board provided in an embodiment of this application.

[0011] Explanation of reference numerals in the attached figures: Information receiving module 10, loading scheme matching module 20, path filtering module 30, model building module 40, damage boundary analysis module 50, risk transmission simulation module 60. Detailed Implementation

[0012] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0013] Example 1, as Figure 1 As shown in the embodiment of this application, a protective conveying method for lightweight gypsum board is provided, the method comprising: A100: Receive basic transport information, wherein the basic transport information includes transport start and end points, board type, board specifications, and board quantity.

[0014] Transportation origin and destination points include the starting and ending points of the transportation. This information is the basis for calculating the transportation route and selecting the appropriate vehicle type. The origin and destination points affect the choice of route and the timeliness of transportation. Plate type refers to the type of plate material being transported. Different types of plate material will affect the loading method, transportation safety requirements, etc. Plate specifications refer to the physical properties of the plate material, such as size and thickness. Specifications will affect the design of the loading plan, especially in terms of space utilization and stability. Plate quantity refers to the number of plate materials being transported. Different quantities will affect the selection of vehicle type, loading strategy, and route planning.

[0015] A200: Based on the specifications and quantity of the sheet metal, load schemes are matched in the vehicle pool to obtain K load strategies for K available vehicle models.

[0016] Based on the specifications and quantity of the sheet metal, a suitable vehicle model is selected. The vehicle model pool contains various types of vehicles, and the selection of a suitable vehicle must meet the following conditions: the vehicle's load capacity should meet the requirements of the sheet metal quantity; the vehicle's cargo box dimensions should be able to accommodate all the sheet metal, and space utilization should be optimized as much as possible. Based on the net cargo box dimensions of the selected vehicle model and the specifications of the sheet metal, a loading scheme is designed. Specifically, an appropriate stacking method, such as layering or laying flat, is selected to ensure the stability of the sheet metal during transportation and to prevent damage due to improper stacking. Considering the limitations of the vehicle's cargo box space, stacking arrays and layer height combinations of the sheet metal are enumerated to ensure that the loading scheme maximizes the use of vehicle space and achieves optimal stability. Multiple loading schemes are screened using the vehicle model's rated load capacity to ensure that each loading scheme meets weight and volume requirements. Finally, K loading strategies are obtained, which specifically describe how many vehicles are used and how the sheet metal is stacked. In this embodiment, an overall design is adopted to bind available vehicle models to dedicated route groups. The K loading strategies obtained through the above matching correspond to an independent available vehicle model. In the subsequent route selection steps, alternative route groups that meet the traffic constraints will be matched separately for each available vehicle model. Therefore, the "K types of XX" or "K groups of XX" mentioned in all subsequent steps, such as K groups of alternative transport routes, K groups of road segment working condition attribute sequences, and K groups of dynamic transport load road spectrum models, are all related technical parameters corresponding to the K types of available vehicle models, and each parameter corresponds one-to-one with an available vehicle model.

[0017] A300: Using the external dimensions, axle load, and emission levels of the K available vehicle types as traffic constraints, path selection is performed with the transportation start and end points as endpoints to obtain K sets of alternative transportation routes.

[0018] The feasibility of the selected routes is constrained by the external dimensions, axle load limits, and emission levels of the selected K available vehicle types. External dimensions refer to the vehicle's length, width, and height; route selection must ensure that the road width and height can accommodate these dimensions. Axle load limits refer to the maximum weight per axle load; some roads have axle load restrictions, so routes that meet these requirements must be selected. Emission levels affect environmental protection regulations; some areas may restrict the passage of high-emission vehicles. Based on the origin and destination points, route selection is performed within the road network. Specifically, basic road network topology data is retrieved from a geographic information database to obtain all possible routes between the origin and destination. Routes that meet the traffic constraints are then selected to obtain K sets of alternative transport routes.

[0019] A400: Retrieve the K-group road segment condition attribute sequence of the K-group alternative transport routes from the road infrastructure database, and construct the K-group dynamic transport load road spectrum model.

[0020] For each candidate transport route, topology analysis is performed to obtain the identifiers of all road segments along the route. Based on these identifiers, static attributes of each road segment, such as pavement type, pavement smoothness, and design speed, as well as dynamic traffic flow data, such as real-time speed and traffic density, are retrieved from the road infrastructure database. Pavement smoothness level and design speed data are extracted from the static attributes to generate a basic vertical vibration spectrum, representing the vibrations that the pavement may experience during vehicle travel. The locations and parameters of speed bumps and pavement damage points are extracted from the static attributes and mapped to generate an impact event parameter set. These parameters reflect the sudden events that vehicles may encounter when passing through these road segments. Based on the dynamic traffic flow data, a travel speed curve is generated to represent the speed changes of vehicles along the entire route. The basic vertical vibration spectrum and discrete impact event parameter set are time-series synthesized with the dynamic traffic flow sequence to obtain a dynamic transport load spectrum model for each route. This model reflects the dynamic load impacts that different routes will experience during transport, providing a foundation for subsequent risk assessment.

[0021] In this embodiment, during the A300 route selection step, a corresponding route group that meets the traffic constraints of each available vehicle type has been selected separately. Therefore, each available vehicle type corresponds to only one set of exclusive alternative routes. There is no scenario where one loading strategy corresponds to multiple sets of independent routes or one set of routes corresponds to multiple loading strategies. The real decision space is K available vehicle types-routes, not a full combination of K×K. Therefore, in this embodiment, K is used to refer to all related indicators.

[0022] A500: Based on the plate type and specifications, perform structural damage boundary analysis of the plate under the K loading strategies to obtain K damage boundary threshold functions.

[0023] Based on the selected sheet material type and specifications, the mechanical properties of the sheet material are analyzed, as these directly affect the potential damage modes during transportation. Corresponding physical property models are constructed to simulate the external loads and deformations the sheet material may experience during transportation. For the selected K loading strategies, dynamic load conditions are applied based on factors such as loading method and stacking height. These loads include external factors such as vibration and impact that may occur during transportation. The stress-strain response of the sheet material under multidimensional dynamic loads is calculated using the finite element method (FEM). By simulating the sheet material's response under different conditions, the stress-strain spectrum under each loading strategy is obtained. Based on the simulation results, the damage to the sheet material is assessed, and the critical damage point is extracted to obtain the critical damage envelope for different loading strategies. Based on the critical damage envelope, a damage boundary threshold function is constructed as a safety criterion for whether damage occurs during transportation. This function reflects the maximum load the sheet material can withstand during transportation.

[0024] A600: Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, a full-chain risk transmission simulation of the risk in the loading and unloading process is performed to screen and locate the target protection transport path.

[0025] K damage boundary threshold functions were obtained as safety criteria, combined with K sets of dynamic transport load path spectrum models. These models represent load changes on different paths and simulate factors such as vibration and impact during vehicle transportation. When conducting full-chain risk transmission simulation, not only the risks during transportation but also the risks during loading and unloading are considered. For example, the mechanical impact and vibration that the sheet metal will suffer during loading and unloading all affect the final damage result. Through full-chain risk transmission simulation, the dynamic transport load path spectrum models and damage boundary threshold functions are combined to simulate the risk transmission process throughout the entire transport chain. Through simulation calculation, the comprehensive risk value of each path is quantified. Based on the simulation results, the path with the lowest damage risk is selected as the target protection transport path to ensure that the sheet metal is protected from damage during transportation as much as possible.

[0026] Furthermore, using the external dimensions, axle load limits, and emission standards of the K available vehicle types as traffic constraints, route selection is performed with the transportation start and end points as endpoints to obtain K sets of alternative transport routes. The method includes: A310: Retrieve basic road network topology data from the geographic information database using the transportation origin and destination points as endpoints; A320: Use the latitude and longitude coordinate vectors of the transportation origin and destination points as origin and destination constraints, and enumerate path combinations in the basic road network topology to obtain multiple initial candidate paths; A330: Collect road attribute data at the road segment level from the multiple initial candidate paths to obtain multiple road attribute constraint sequences; A340: Traverse the multiple road attribute constraint sequences to perform bottleneck constraint analysis and extract multiple path constraint characteristic vectors; A350: Use the external dimension limits, axle load limits, and emission levels of the K types of available vehicle models as traffic constraints, compare the multiple path constraint characteristic vectors to perform trafficability evaluation, and aggregate the multiple initial candidate paths into the K groups of alternative transportation paths.

[0027] Based on the origin and destination of the transportation, relevant basic road network topology data is retrieved from the geographic information database. The topology data includes information such as road connection relationships, road segment lengths, and road surface types.

[0028] The latitude and longitude coordinates of the transportation origin and destination are used as the origin and destination constraints for route planning. That is, the origin and destination of the route are determined, and all route selections must satisfy the connection between these two points. Based on the basic road network topology data, the routes are combined and enumerated to generate multiple candidate routes from the origin to the destination. These routes will vary due to factors such as traffic conditions and road conditions.

[0029] The initial candidate routes are further refined into multiple road segments, the differences between which will affect the overall transportation conditions. Road attribute data is collected for each road segment, including road geometry data, road load-bearing capacity data, and traffic and environmental protection data. The collected road attribute data for each road segment forms a road attribute constraint sequence, which represents the specific situation of all road segments on each route.

[0030] Road attribute constraints include road geometric constraints, road load-bearing constraints, and traffic and environmental constraints. Within each initial path, certain sections may have severe bottlenecks that limit the overall path's traffic capacity. For example, regarding road geometric constraints, some roads have width or height limitations, unable to accommodate oversized or overheight vehicles; regarding road load-bearing constraints, some sections cannot support excessively heavy vehicles due to limitations in bridge or pavement load-bearing capacity. After analyzing bottleneck constraints, constraint characteristic vectors are extracted for each path. These vectors include the characteristics of all key bottlenecks on each path, such as restrictive load-bearing capacity, width, and height. These constraint characteristic vectors are used in the subsequent traffic assessment process.

[0031] Each available vehicle type has specific traffic constraints. External dimension limits include restrictions on the length, width, and height of the vehicle, which determine whether the vehicle can pass through certain narrow roads. Axle load limits refer to the maximum weight that each vehicle type can bear on each axle, affecting whether it can pass through bridges or road sections with limited load-bearing capacity. Emission levels affect traffic in certain areas; for example, some low-emission zones do not allow high-emission vehicles to enter.

[0032] The accessibility constraints, such as the external dimensions, axle load, and emission rating of each available vehicle model, are compared with the constraint characteristic vector of each path to check if any constraints render a path impassable. For example, if a path has size restrictions on bridges or tunnels, and the selected vehicle model's external dimensions exceed these restrictions, the path does not meet the access requirements. A accessibility assessment is performed on each initial path to determine if it is suitable for the selected vehicle model. If a path meets all access constraints for the vehicle model, it is considered accessible. After completing the path accessibility assessment, all paths that meet the access requirements are aggregated into K groups of candidate transport paths.

[0033] Furthermore, the method involves retrieving the K sets of road segment condition attribute sequences from the K sets of alternative transport routes from the road infrastructure database, and constructing a K-set dynamic transport load road spectrum model. A410: Perform path topology analysis on the K groups of candidate transport routes to obtain the K groups of transport segment identification sequences; A420: Use the K groups of transport segment identification sequences as search conditions to retrieve the K groups of static attribute sequences and K groups of dynamic traffic flow sequences from the road infrastructure database to construct the K groups of road segment working condition attribute sequences; A430: Extract pavement smoothness level and design speed data from the K groups of static attribute sequences and map them to generate the K groups of foundation vertical vibration spectra; A440: Extract the coordinates and parameters of speed bumps and pavement damage points from the K groups of static attribute sequences and map them to generate the K groups of discrete impact event parameter sets; A450: Use the K groups of travel speed curves generated by the K groups of dynamic traffic flow sequences as a time reference, couple the K groups of foundation vertical vibration spectra and the K groups of discrete impact event parameter sets, and perform segmented time-series load synthesis to generate the K groups of dynamic transport load road spectrum models.

[0034] Each alternative transport path consists of multiple road segments. The purpose of path topology parsing is to decompose each path into multiple specific road segments and assign an identifier, such as a road segment ID, to each road segment. After parsing, a road segment identifier sequence is generated for each path. This sequence records all road segment identifiers from the starting point to the end point.

[0035] Using the obtained K sets of road segment identifier sequences as query criteria, detailed information for each road segment is retrieved from the road infrastructure database. This information includes static attributes and dynamic traffic flow information. Static attribute data includes fixed information for each road segment, such as pavement type, segment length, pavement smoothness, design speed, and structural characteristics of bridges and tunnels. This data is fixed and does not change over time. Dynamic traffic flow data includes information such as traffic volume, speed, and traffic density for each road segment within a specific time period. This data changes with traffic conditions and reflects the actual traffic situation. Combining the static attributes and dynamic traffic flow data yields a sequence of road segment performance attributes for each path. These performance attributes provide necessary data support for subsequent analysis.

[0036] Road surface smoothness grade refers to the degree of smoothness of the road surface, expressed by measuring the unevenness or bumpiness of the road surface. Poor smoothness will cause greater vibration when vehicles are driving. Design speed is the predetermined vehicle speed during road design, reflecting the road's capacity and safety. Based on road surface smoothness grade and design speed data, using engineering models, such as vibration theory models, this information is mapped onto a vertical vibration spectrum. The vertical vibration spectrum describes the vertical vibration caused by road surface unevenness or other factors during vehicle operation. The generation of the vibration spectrum can quantify the vibration intensity, which helps to assess the impact and damage to the materials during transportation. Finally, K sets of basic vertical vibration spectra are obtained, each set of spectra corresponding to an alternative transport path, reflecting the vibration impact of different paths during transportation.

[0037] Speed ​​bumps are road structures used to control vehicle speed. Their type, length, shape, and location all contribute to instantaneous impacts on vehicles. Road surface defects, such as potholes, cracks, and fissures, cause impacts when vehicles pass over them, especially at high speeds. Using the extracted coordinates and parameters of speed bumps and road surface defects, impact event parameter sets are generated. These parameter sets describe the impact force generated each time a speed bump is passed, or the vibration and impact generated when a vehicle passes a road surface defect. These impact event parameter sets provide supplementary data for the dynamic load model of the road path, especially when assessing damage to sheet metal during transportation. Ultimately, K discrete impact event parameter sets are obtained, reflecting sudden impact situations on different roads.

[0038] The travel speed curves are generated based on the dynamic traffic flow sequence. These curves show the vehicle's speed at different time points, reflecting its motion on different road segments and time periods. As a time reference, these curves help simulate load changes over different time periods. The generated K sets of foundation vertical vibration spectra and K sets of discrete impact event parameter sets are coupled with the travel speed curves. This means that each time point of the travel speed curve is combined with the corresponding vibration spectrum and impact event data, forming a complete load time series. The foundation vertical vibration spectrum provides dynamic data related to the vibration of vehicles traveling on the road surface, while discrete impact events simulate instantaneous impacts caused by factors such as speed bumps and damaged road surfaces. By combining the effects of dynamic traffic flow, vibration spectrum, and impact events, segmented time-series load synthesis is performed. This means that within each speed interval, dynamic loads, vibrations, and impact factors are synthesized in chronological order to obtain the total load on the vehicle during each time period. Finally, the generated K sets of dynamic transport load road spectrum models reflect all the dynamic load influences that different routes may experience during transport. These models provide the basic data for subsequent risk assessment and damage analysis.

[0039] Furthermore, using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, a full-chain risk transmission simulation of the loading and unloading process is performed to screen and locate the target protection transport path. The method includes: A610: Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, risk transmission simulation is performed to quantify the K sets of comprehensive risk values; A620: The K sets of comprehensive risk values ​​are traversed using a preset risk threshold to screen the K sets of feasible protective transport paths; A630: By introducing transport time windows, loading and unloading time windows, and transport costs, under the K sets of feasible protective transport paths, multi-objective Pareto optimization decisions are made on the K loading strategies to screen and locate the target protective transport path.

[0040] K damage boundary threshold functions are used as safety criteria. These functions define the maximum load that the sheet metal can withstand under different loading conditions. Once this load is exceeded, the sheet metal may be damaged. Using K sets of dynamic transport load spectrum models, combined with the damage boundary threshold functions, a full-link risk transmission simulation is performed. By simulating load and stress changes during transport, the potential damage risk to the sheet metal during the entire transport process is predicted. The simulation yields a comprehensive risk value for each path. These values ​​reflect the magnitude of the risk of sheet metal damage during transport on different paths; a higher comprehensive risk value indicates a greater risk of damage on that path.

[0041] A preset risk threshold is set, representing the maximum acceptable risk range. This threshold is determined based on transportation safety requirements and conditions. All K groups of comprehensive risk values ​​are iterated over. If the comprehensive risk value of a route exceeds the threshold, that route is considered infeasible and cannot be used as a protective transport route. Through this screening process, K groups of feasible protective transport routes with risk values ​​below the threshold are obtained. These routes offer higher safety for the sheet metal during transportation.

[0042] The transport time window refers to the constraint that the transport task must be completed within a specific time. This time window affects route selection and the timeliness of the transport process. The loading and unloading time window refers to the requirement that the loading and unloading of the materials must be completed within a specific time, affecting the total transport time. Transport cost refers to the costs incurred when selecting transport routes and loading strategies, including fuel costs, driver costs, and toll fees. Using a multi-objective Pareto optimization method, based on multiple objectives such as the transport time window, loading and unloading time window, and transport cost, the method optimizes route and loading strategy decisions. This method can find a balance point among multiple objectives and select the optimal protective transport route. After optimization, target protective transport routes are selected. These routes not only minimize the risks during transport but also achieve the best balance in terms of time and cost.

[0043] In this embodiment, after risk screening, K available vehicle-route combinations that meet the risk requirements are obtained. Each available vehicle-route combination already includes a determined loading strategy and a corresponding protective transport route. Therefore, the decision variables for Pareto optimization are these K available vehicle models, rather than separately handling route selection and loading strategy selection. The three optimization objectives in this embodiment are: normalized comprehensive risk value, obtained by dividing the comprehensive risk value obtained from the full-chain simulation by a preset risk threshold; normalized total time, obtained by normalizing the actual total transportation and loading / unloading time combined with time window constraints and penalty calculations; and normalized transportation cost, obtained by dividing the total cost including road and bridge tolls, fuel costs, and vehicle depreciation by a preset cost ceiling. The Pareto front is obtained using the commonly used NSGA-II algorithm in this field, and the optimal compromise solution is finally selected. The time window only serves as an auxiliary constraint in the risk screening stage and participates in the calculation as an optimization objective in the optimization stage.

[0044] Furthermore, using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models to perform risk transmission simulation, the method quantifies the K sets of comprehensive risk values. The method includes: A611: Based on the plate type and specifications as the mechanical properties, and according to the stacking methods of the K loading strategies and the selection of loading and unloading equipment, construct K mechanical impact load spectra under loading and unloading conditions; A612: Perform segmented time-series integration of the K mechanical impact load spectra and K sets of dynamic transport load path spectrum models to construct K sets of full-chain dynamic load spectra; A613: Using the K damage boundary threshold functions as safety criteria, perform time-frequency domain joint risk transmission simulation of the K sets of full-chain dynamic load spectra to quantify the K sets of comprehensive risk values.

[0045] Based on the type and specifications of the sheet metal, the mechanical influences on it during transportation and handling are analyzed. This includes the sheet's stiffness, strength, and modulus of elasticity, which determine its response to external loads, especially the impacts encountered during handling. Different stacking methods affect the stability of the sheet metal during transportation; for example, layered stacking and staggered stacking lead to different impact responses. The operating methods and impact forces of handling equipment such as forklifts and cranes also significantly affect the sheet metal, with different equipment and operating methods resulting in different types of mechanical impacts. Based on these factors, mechanical impact load spectra are designed for the sheet metal under each loading strategy. These spectra describe the various mechanical impacts the sheet metal encounters during handling, including impact forces caused by equipment operation and instantaneous impacts during sheet stacking. The time-load relationships of these mechanical impact loads, i.e., the mechanical impact load spectra, are obtained through experimental simulation or computational models.

[0046] The mechanical impact load spectrum and dynamic transport load path spectrum models are integrated chronologically. The dynamic load of each path is divided into different time periods, and each time period may be affected by both mechanical impact and dynamic transport loads simultaneously. For each path, the mechanical impact load spectrum is first mapped to the time-series data in the dynamic transport load path spectrum model to ensure temporal alignment. For example, a path may encounter equipment-induced impacts at one time period, while another time period may be mainly affected by road vibrations. The mechanical impact load and dynamic transport load are then merged to obtain the full-chain dynamic load spectrum for each path. The full-chain dynamic load spectrum represents the load changes of all road segments and all loading and unloading stages throughout the entire transport process from the start to the end point.

[0047] In this embodiment, the timing connection logic of loading and unloading impact and route transportation is as follows: the mechanical impact load spectrum of the loading stage is placed at the beginning timing position of the full-chain load spectrum of the corresponding available vehicle type, the dynamic transportation load spectrum corresponding to the transportation route is placed at the middle timing position after the loading impact, and the mechanical impact load spectrum of the unloading stage is placed at the end timing position of the full-chain load spectrum. The three are integrated in segments according to the actual operation process of loading-transportation-unloading to form a complete full-chain dynamic load spectrum.

[0048] The full-chain dynamic load spectrum of each path is combined with the damage boundary threshold function as the basis for risk analysis, ensuring the safety of the sheet material is assessed on different paths. Time-frequency domain co-simulation is performed by combining the temporal and frequency domain characteristics of the full-chain dynamic load spectrum. The time-domain simulation focuses on the impact of load changes over time, while the frequency-domain simulation focuses on the impact and vibration responses at different frequencies. Through simulation, the actual risk transmission of the sheet material during transportation is simulated, and the potential damage scenarios in each path are assessed. Based on the simulation results, the comprehensive risk value for each path is calculated. This value reflects the total risk of damage to the sheet material along the path; a higher comprehensive risk value indicates a greater risk of damage occurring on that path.

[0049] Furthermore, based on the specifications and quantity of the sheet metal, loading schemes are matched within the vehicle pool to obtain K loading strategies for K available vehicle models. The method includes: A210: Construct a three-dimensional loading space model based on the net dimensions of the cargo box of the first available vehicle model; A220: Construct a single-plate physical property model based on the plate specifications; A230: Under the constraint of the number of plates, and with the goal of satisfying the preset volume utilization rate, enumerate the stacking array and layer height combination of the single-plate physical property model within the three-dimensional loading space model to obtain K initial candidate loading schemes; A240: After screening the load feasibility of the K initial candidate loading schemes using the rated load of the K available vehicle models, conduct a multi-objective loading quality evaluation based on space utilization rate, stacking stability, and comprehensive protection cost to select the first loading strategy.

[0050] The net cargo box dimensions refer to the actual usable loading space within a vehicle, expressed as length, width, and height. These dimensions are constrained by the vehicle's structure and determine the maximum volume of goods that can be loaded. Based on the net cargo box dimensions of the first available vehicle model, a 3D model is created to simulate the loading space inside the vehicle's cargo box. This model demonstrates the vehicle's actual loading space and how loading optimization is performed based on the dimensions of the sheet metal.

[0051] Sheet specifications refer to the dimensions of the sheet material, such as length, width, and thickness, as well as its physical properties, such as density, modulus of elasticity, and strength. Sheets with different specifications will exhibit different mechanical properties when subjected to mechanical loads. Based on the sheet specifications, a single-sheet physical property model is constructed to simulate the deformation and response of the sheet material under different external loads, including the sheet's stiffness, strength, and bending resistance.

[0052] The quantity of pallets is one of the fundamental conditions for loading scheme design. It is necessary to optimize the loading layout and space utilization as much as possible while ensuring that the number of pallets does not exceed the available space. The preset volume utilization rate is a target parameter, representing the effective utilization of the cargo loading space. A high volume utilization rate means that the loading space is used more fully, thereby improving transportation efficiency and reducing transportation costs. In the 3D loading space model, stacking arrays and layer height combinations are enumerated. Here, stacking array refers to the arrangement of pallets in the cargo compartment, such as flat placement or staggered stacking, while layer height refers to the vertical height between each layer of pallets. The design of the stacking array should consider the size and weight of the pallets, as well as the ease of loading and unloading, ensuring that the pallets are not damaged due to improper stacking. The design of the layer height combination needs to ensure that the spacing between each layer is appropriate to maximize the loading capacity while not exceeding the vehicle's load and size limitations. Through the enumeration of stacking arrays and layer height combinations, K loading schemes are generated. These schemes meet the requirements for the number of pallets and volume utilization rate, and provide preliminary plans for subsequent load selection and loading quality evaluation.

[0053] Each available vehicle type has a rated load capacity, representing the maximum weight the vehicle can carry during transportation. When screening initial loading options, it is necessary to ensure that the total weight of each loading option does not exceed the rated load capacity of that vehicle type. By evaluating the total weight of the initial loading options, feasible options that meet the load limits are selected. This step eliminates options that do not meet the load limits, ensuring the safety and economy of loading.

[0054] A multi-objective loading quality evaluation is conducted. Space utilization rate is used to evaluate the space utilization of each scheme, i.e., the effective utilization of loading space. The higher the space utilization rate, the higher the loading efficiency. Stacking stability reflects whether the plates are prone to sliding or tilting during transportation, leading to damage or transportation risks. Schemes with higher stability have better stacking methods and layer height designs. Comprehensive protection cost includes all protection costs during the loading process, such as plate packaging, reinforcement measures, and additional transportation costs. The goal of this factor is to minimize damage and costs and ensure transportation safety. In the multi-objective evaluation process, all feasible loading schemes are comprehensively scored, and the optimal scheme is selected. That is, after considering space utilization rate, stacking stability, and protection cost, the scheme with the lowest risk and the best economy is selected, which is the first loading strategy.

[0055] Furthermore, based on the K suspension characteristics of the K available vehicle models, after frequency domain correction of the K sets of basic vertical vibration spectra, the K sets of discrete impact event parameter sets are coupled to perform segmented time-series load synthesis to generate the K sets of dynamic transport load road spectrum models.

[0056] The suspension systems of different vehicle models have a significant impact on the vehicle's vibration response. The stiffness and elasticity of the suspension determine the vehicle's reaction to vibrations or impacts during transportation. For each available vehicle model, the vibration spectrum is frequency-domain corrected based on its suspension characteristics. The suspension system affects the vehicle's transmission characteristics of road vibrations; therefore, by correcting the foundation's vertical vibration spectrum, the vibration response of the vehicle under different road sections and loading conditions can be simulated more accurately. The corrected foundation vertical vibration spectrum is coupled with a discrete impact event parameter set. After coupling, the influence of the synchronous vibration spectrum and impact events can reflect all the impacts and vibrations encountered by the sheet metal during transportation.

[0057] The vibration spectrum and impact event data are segmented into time-series loads. In this process, the vibration and impact data are merged in chronological order to form time-series loads, which simulate the load changes in actual transportation. Finally, K sets of dynamic transportation load road spectrum models are obtained. These models describe all the dynamic load conditions that vehicles may encounter during transportation on each route.

[0058] It is worth noting that the suspension characteristic correction in this step is a post-refinement adjustment of the basic vertical vibration spectrum generated in step A400, and it still serves the construction of the dynamic transport load road spectrum model: since it is necessary to extract all K sets of basic vibration spectra first, and then combine them with the suspension characteristics of the corresponding K types of vehicles for batch frequency domain correction, the correction step is set after the damage boundary analysis (A500). The corrected road spectrum is the final dynamic transport load road spectrum model used for risk simulation, and the original basic vibration spectrum is only an intermediate extraction result.

[0059] Furthermore, based on the plate type and specifications, damage boundary analysis of the plate structure is performed under the K loading strategies to obtain K damage boundary threshold functions. The method includes: A510: Retrieve standard mechanical performance parameters based on the plate type, inject them into the single-plate property model, and construct the plate reference mechanical model; A520: Apply multi-dimensional dynamic load conditions to the plate reference mechanical model according to the K loading strategies, and perform finite element simulation to obtain K sets of single-plate level stress-strain response spectra; A530: Spatially align the K sets of single-plate level stress-strain response spectra, extract and summarize the time-domain peak values, obtain K sets of stress-strain extreme value feature sets, perform multi-criteria damage assessment, and extract K sets of damage critical envelopes; A540: Parametrically represent the K sets of damage critical envelopes, and output the K damage boundary threshold functions.

[0060] Based on the type of sheet material, standard mechanical property parameters for that type of sheet material are retrieved from relevant standards or material databases. These parameters include: modulus of elasticity, describing the stiffness of the sheet material; ultimate tensile strength, the maximum stress the sheet material can withstand, exceeding which will lead to cracking or damage; density, the mass density of the sheet material, used to calculate its weight and load-bearing capacity; tensile strength, flexural strength, etc., which help determine the sheet material's performance under external forces. These mechanical property parameters are then incorporated into a single-sheet physical property model, which models the sheet material based on physical and mechanical principles, simulating its mechanical response under different load conditions. Based on these parameters, a baseline mechanical model of the sheet material is constructed. This model provides the foundation for subsequent finite element analysis and damage assessment, reflecting the deformation, stress distribution, and failure modes of the sheet material under different loading and transportation conditions.

[0061] Based on K loading strategies, different dynamic load conditions are applied, including: mechanical impact, such as impact caused by equipment operation during loading and unloading; vibration load, i.e., vibration caused by the road surface during transportation; and gravity load, i.e., the weight of the plates themselves and the load from their stacking. The stacking method and layer height combination of each loading strategy affect the load distribution, thus having different effects on the stress and strain responses of the plates. Finite element simulation is performed on the plate's baseline mechanical model to simulate the stress and strain responses of the plates under these multi-dimensional dynamic load conditions. The finite element method can accurately simulate complex mechanical behavior, especially under multiple dynamic loads, and can analyze the stress distribution and deformation of the plates in local areas. The simulation yields the single-plate-level stress-strain response spectrum for each loading strategy. This spectrum represents the stress change process of the plate under different loads over time, reflecting the mechanical response during transportation.

[0062] Because the stress-strain responses under different loading strategies and dynamic load conditions have different time scales and amplitudes, spatial alignment of each set of single-plate-level stress-strain response spectra is required to allow for comparison of responses under different strategies at the same time point. Time-domain peak extraction is performed on each stress-strain response spectrum to identify the maximum stress and strain values ​​at each moment during the entire transportation process. These peaks represent the stress and strain limits of the plate under different loads. The extracted peaks are organized into a stress-strain extreme value feature set, which provides data on the maximum stress and strain encountered by the plate during transportation, serving as a reference for subsequent damage assessment. Based on the stress-strain extreme value feature set and combined with the mechanical performance standards of the plate, a multi-criteria damage assessment is conducted. The damage assessment is based on multiple factors, such as stress concentration and deformation degree, to assess the damage risk of the plate during transportation. Through the assessment, a critical damage envelope is obtained for each loading strategy, representing the critical state at which the plate will suffer damage under specific load and stress conditions. Stress or strain values ​​exceeding this envelope will lead to plate failure or severe damage.

[0063] The K sets of damage critical envelopes are parameterized. Each damage critical envelope is a critical value curve for plate damage under specific conditions. Through parameterization, these envelopes are transformed into standardized damage judgment formulas or functions. After parameterization, K damage boundary threshold functions are output. These functions define the maximum safe threshold that the plate can withstand under different loading strategies and under different loads and stresses. Exceeding this threshold will cause damage or failure of the plate.

[0064] Furthermore, the road attribute constraints include road geometric constraints, road load-bearing constraints, and traffic and environmental constraints.

[0065] Road geometric constraints include the width, height, turning radius, and gradient of a road segment. These constraints determine whether specific vehicles, especially oversized and overweight vehicles, can pass through certain road segments. Road load-bearing constraints refer to the load-bearing capacity of a road or road segment, such as pavement strength and the load limits of bridges and tunnels. These constraints directly affect whether heavy-duty vehicles can pass safely. Environmental constraints refer to constraints related to environmental protection, such as emission standards, environmental protection zones, and low-emission zones. Different roads will have emission standard restrictions set according to environmental requirements, and high-emission vehicles may not be able to pass.

[0066] Example 2, based on the same inventive concept as the protective conveying method for lightweight gypsum board in the foregoing examples, such as... Figure 2 As shown in the figure, this application provides a protective conveying system for lightweight gypsum board, the system comprising: Information receiving module 10 is used to receive basic transportation information, including transportation start and end points, plate type, plate specifications, and plate quantity; loading scheme matching module 20 is used to perform loading scheme matching in the vehicle pool based on the plate specifications and plate quantity to obtain K loading strategies for K available vehicle types; path filtering module 30 is used to perform path filtering with the transportation start and end points as endpoints based on the external dimension limits, axle load limits, and emission levels of the K available vehicle types as traffic constraints to obtain K sets of alternative transportation paths; model building module 40 uses... The system retrieves the K sets of road segment working condition attribute sequences of the K sets of alternative transport routes from the road infrastructure database to construct a K-set dynamic transport load road spectrum model; the damage boundary analysis module 50 is used to perform structural damage boundary analysis of the plate material under the K loading strategies based on the plate material type and specifications to obtain K damage boundary threshold functions; the risk transmission simulation module 60 is used to perform full-chain risk transmission simulation of the integrated loading and unloading risk based on the K damage boundary threshold functions as safety criteria and combined with the K-set dynamic transport load road spectrum model to screen and locate target protection transport routes.

[0067] Furthermore, the path filtering module 30 is used to perform the following operation steps: Using the transportation origin and destination points as endpoints, basic road network topology data is retrieved from a geographic information database. The latitude and longitude coordinates of the origin and destination points are used as origin-destination constraints. Path combination enumeration is performed on the basic road network topology to obtain multiple initial candidate paths. Road segment-level road attribute data is collected from these multiple initial candidate paths to obtain multiple road attribute constraint sequences. Bottleneck constraint analysis is performed by traversing these multiple road attribute constraint sequences to extract multiple path constraint characteristic vectors. The external dimensions, axle load limits, and emission levels of the K available vehicle types are used as traffic constraints. The trafficability is evaluated by comparing the multiple path constraint characteristic vectors to aggregate the multiple initial candidate paths into the K groups of alternative transportation paths.

[0068] Furthermore, the model building module 40 is used to perform the following operation steps: The K groups of candidate transport routes are analyzed for topology to obtain a K group of transport segment identification sequences. Using these K group transport segment identification sequences as search criteria, the K group of static attribute sequences and K group of dynamic traffic flow sequences are retrieved from the road infrastructure database to form the K group of road segment working condition attribute sequences. Road surface smoothness level and design speed data are extracted from the K group of static attribute sequences and mapped to generate a K group of foundation vertical vibration spectra. The coordinates and parameters of speed bumps and road surface damage points are extracted from the K group of static attribute sequences and mapped to generate a K group of discrete impact event parameter sets. Using the K group of travel speed curves generated from the K group of dynamic traffic flow sequences as a time reference, the K group of foundation vertical vibration spectra and the K group of discrete impact event parameter sets are coupled to perform segmented time-series load synthesis, generating the K group of dynamic transport load road spectrum models.

[0069] Furthermore, the risk transmission simulation module 60 is used to perform the following operation steps: Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, risk transmission simulation is performed to quantify the K sets of comprehensive risk values. The K sets of comprehensive risk values ​​are traversed using a preset risk threshold to screen the K sets of feasible protective transport paths. By introducing transport time windows, loading and unloading time windows, and transport costs, multi-objective Pareto optimization decisions are made on the K loading strategies under the K sets of feasible protective transport paths to screen and locate the target protective transport path.

[0070] Furthermore, the risk transmission simulation module 60 is used to perform the following operation steps: Based on the plate type and specifications as the mechanical properties, and according to the stacking methods of the K loading strategies and the selection of loading and unloading equipment, K mechanical impact load spectra under loading and unloading conditions are constructed. The K mechanical impact load spectra and K sets of dynamic transportation load path spectrum models are integrated in a segmented time sequence to construct K sets of full-chain dynamic load spectra. Using the K damage boundary threshold functions as safety criteria, the K sets of full-chain dynamic load spectra are subjected to time-frequency domain joint risk transmission simulation to quantify the K sets of comprehensive risk values.

[0071] Furthermore, the loading scheme matching module 20 is used to perform the following operation steps: A three-dimensional loading space model is constructed based on the net dimensions of the cargo box of the first available vehicle model; a single-plate physical property model is constructed based on the plate specifications; under the constraint of the number of plates, and with the goal of satisfying the preset volume utilization rate, the stacking array and layer height combination of the single-plate physical property model are enumerated within the three-dimensional loading space model to obtain K initial candidate loading schemes; after screening the load feasibility of the K initial candidate loading schemes using the rated load of the K available vehicle models, a multi-objective loading quality evaluation based on space utilization rate, stacking stability, and comprehensive protection cost is performed to select the first loading strategy.

[0072] Furthermore, based on the K suspension characteristics of the K available vehicle models, after frequency domain correction of the K sets of basic vertical vibration spectra, the K sets of discrete impact event parameter sets are coupled to perform segmented time-series load synthesis to generate the K sets of dynamic transport load road spectrum models.

[0073] Furthermore, the damage boundary analysis module 50 is used to perform the following operation steps: Based on the type of sheet material, standard mechanical performance parameters are retrieved and injected into the single-plate property model to construct a reference mechanical model for the sheet material. According to the K loading strategies, multi-dimensional dynamic load conditions are applied to the reference mechanical model of the sheet material for finite element simulation, resulting in K sets of single-plate-level stress-strain response spectra. The K sets of single-plate-level stress-strain response spectra are spatially aligned, and time-domain peak values ​​are extracted and summarized to obtain K sets of stress-strain extreme value feature sets. Multi-criteria damage assessment is then performed to extract K sets of damage critical envelopes. The K sets of damage critical envelopes are parameterized, and the K damage boundary threshold functions are output.

[0074] Furthermore, the road attribute constraints include road geometric constraints, road load-bearing constraints, and traffic and environmental constraints.

[0075] Through the foregoing detailed description of a protective conveying method for lightweight gypsum board, those skilled in the art can clearly understand the protective conveying system for lightweight gypsum board in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A protective conveying method for lightweight gypsum board, characterized in that, The method includes: Receive basic transport information, wherein the basic transport information includes transport start and end points, board type, board specifications and board quantity; Based on the specifications and quantity of the sheet metal, loading schemes are matched in the vehicle pool to obtain K loading strategies for K available vehicle models; Using the external dimensions, axle load, and emission levels of the K available vehicle types as traffic constraints, path selection is performed with the transportation start and end points as endpoints to obtain K sets of alternative transportation routes; The K-group road segment condition attribute sequences of the K-group alternative transport routes are retrieved from the road infrastructure database to construct a K-group dynamic transport load road spectrum model. Based on the plate type and specifications, the plate structure damage boundary analysis is performed under the K loading strategies to obtain K damage boundary threshold functions; Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, a full-chain risk transmission simulation of the risk in the loading and unloading process is performed to screen and locate the target protection transport path.

2. The protective conveying method for lightweight gypsum board as described in claim 1, characterized in that, Using the external dimensions, axle load limits, and emission standards of the K available vehicle types as traffic constraints, route selection is performed with the transportation start and end points as endpoints to obtain K sets of alternative transport routes. The method includes: Using the aforementioned transportation start and end points as endpoints, basic road network topology data is retrieved from the geographic information database; Using the latitude and longitude coordinate vectors of the transportation origin and destination points as origin and destination constraints, path combination enumeration is performed on the basic road network topology to obtain multiple initial candidate paths; Road attribute data at the segment level is collected from the multiple initial candidate paths to obtain multiple road attribute constraint sequences; Bottleneck constraint analysis is performed by traversing the multiple road attribute constraint sequences to extract multiple path constraint characteristic vectors; Using the external dimensions, axle load, and emission levels of the K available vehicle types as traffic constraints, the trafficability of the multiple path constraint characteristic vectors is evaluated to aggregate the multiple initial candidate paths into the K groups of alternative transport paths.

3. The protective conveying method for lightweight gypsum board as described in claim 1, characterized in that, The method involves retrieving K sets of road segment condition attribute sequences from the K sets of candidate transport routes from the road infrastructure database and constructing a K-set dynamic transport load road spectrum model, the method comprising: Perform path topology analysis on the K groups of candidate transport paths to obtain the K groups of transport segment identification sequences; Using the K groups of transport road segment identifier sequences as search conditions, retrieve the K groups of road segment static attribute sequences and K groups of dynamic traffic flow sequences from the road infrastructure database to form the K groups of road segment working condition attribute sequences. The road surface smoothness grade and design speed data are extracted from the static attribute sequence of the K groups of road sections, and mapped to generate the vertical vibration spectrum of the K groups of foundations; The coordinates and parameters of speed bumps and road surface damage points are extracted from the static attribute sequences of the K groups of road segments, and mapped to generate K sets of discrete impact event parameter sets. Using the K-group travel speed curves generated by the K-group dynamic traffic flow sequence transformation as the time reference, the K-group foundation vertical vibration spectrum and the K-group discrete impact event parameter set are coupled to perform segmented time-series load synthesis to generate the K-group dynamic transport load road spectrum model.

4. The protective conveying method for lightweight gypsum board as described in claim 1, characterized in that, Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models, a full-chain risk transmission simulation of the loading and unloading process is performed to screen and locate the target protection transport path. The method includes: Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load road spectrum models, risk transmission simulation is performed to quantify the K sets of comprehensive risk values; The K groups of comprehensive risk values ​​are traversed using a preset risk threshold to screen for K groups of feasible protective delivery paths; By introducing a transport time window, a loading and unloading time window, and transportation costs, a multi-objective Pareto optimization decision is made on the K loading strategies under the K groups of feasible protective transport paths to select and locate the target protective transport path.

5. The protective conveying method for lightweight gypsum board as described in claim 4, characterized in that, Using the K damage boundary threshold functions as safety criteria, and combining the K sets of dynamic transport load path spectrum models to perform risk transmission simulation, the method quantifies the K sets of comprehensive risk values. Based on the plate type and specifications as the mechanical property basis, and according to the stacking method of the K loading strategies and the selection of loading and unloading equipment, K mechanical impact load spectra under loading and unloading conditions are constructed. The K mechanical impact load spectra and K sets of dynamic transport load path spectrum models are segmented and time-series integrated to construct K sets of full-chain dynamic load spectra. Using the K damage boundary threshold functions as safety criteria, time-frequency domain joint risk transfer simulation is performed on the K sets of full-chain dynamic load spectra to quantify the K sets of comprehensive risk values.

6. The protective conveying method for lightweight gypsum board as described in claim 1, characterized in that, Based on the specifications and quantity of the sheet metal, loading schemes are matched within the vehicle pool to obtain K loading strategies for K available vehicle models. The method includes: A three-dimensional loading space model is constructed based on the net dimensions of the cargo box of the first available vehicle model; Construct a veneer property model based on the veneer specifications; Under the constraint of the number of boards, and with the goal of satisfying the preset volume utilization rate, the stacking array and layer height combination enumeration of the single board physical property model are performed in the three-dimensional loading space model to obtain K initial candidate loading schemes. After screening the load feasibility of the K initial candidate loading schemes using the rated load of the K available vehicle models, a multi-objective loading quality evaluation based on space utilization, stacking stability and comprehensive protection cost is conducted to select the first loading strategy.

7. The protective conveying method for lightweight gypsum board as described in claim 3, characterized in that, Based on the K suspension characteristics of the K available vehicle models, after frequency domain correction of the K sets of basic vertical vibration spectra, the K sets of discrete impact event parameter sets are coupled to perform segmented time-series load synthesis to generate the K sets of dynamic transport load road spectrum models.

8. The protective conveying method for lightweight gypsum board as described in claim 6, characterized in that, Based on the plate type and specifications, damage boundary analysis of the plate structure is performed under the K loading strategies to obtain K damage boundary threshold functions. The method includes: Based on the type of board material, standard mechanical performance parameters are retrieved and injected into the single-board physical property model to construct a reference mechanical model for the board material. Based on the K loading strategies, finite element simulation is performed on the plate reference mechanical model under multi-dimensional dynamic load conditions to obtain K sets of single-plate stress-strain response spectra. After spatially aligning the K sets of single-plate level stress-strain response spectra, extracting and summarizing the time-domain peak values ​​to obtain K sets of stress-strain extreme value feature sets, perform multi-criteria damage assessment and extract K sets of damage critical envelopes. The K sets of critical envelopes for damage are parameterized, and the K damage boundary threshold functions are output.

9. A protective conveying method for lightweight gypsum board as described in claim 2, characterized in that, The road attribute constraints include road geometric constraints, road load-bearing constraints, and traffic and environmental constraints.

10. A protective conveying system for lightweight gypsum board, characterized in that, For implementing the protective conveying method for lightweight gypsum board according to any one of claims 1-9, the system comprises: The information receiving module is used to receive basic transportation information, which includes transportation start and end points, board type, board specifications, and board quantity. The loading scheme matching module is used to match loading schemes in the vehicle pool based on the specifications and quantity of the sheet metal to obtain K loading strategies for K available vehicle models. The route selection module is used to select routes with the transportation start and end points as endpoints, based on the external dimensions, axle load limits and emission levels of the K available vehicle types as traffic constraints, to obtain K sets of alternative transportation routes. The model building module is used to retrieve the K sets of road segment condition attribute sequences of the K sets of alternative transport routes from the road infrastructure database and build the K sets of dynamic transport load road spectrum models. The damage boundary analysis module is used to perform structural damage boundary analysis of the plate according to the plate type and plate specifications under the K loading strategies, and obtain K damage boundary threshold functions. The risk transmission simulation module is used to perform full-chain risk transmission simulation of the loading and unloading process by combining the K damage boundary threshold functions as safety criteria and the K sets of dynamic transport load path spectrum models, and to screen and locate the target protection transport path.

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