Human-ergonomic-based mobile lifting platform man-machine collaborative space optimization method and system

Abstract

The application discloses a mobile lifting platform man-machine collaborative space optimization method and system based on human ergonomics, and relates to the technical field of building construction automation and intelligent engineering machinery; the method comprises the following steps: a multi-objective optimization model based on spatial three-dimensional analysis is established, the height stay sequence of the mobile lifting platform is taken as a decision variable, three-dimensional anti-collision and accessibility filtering rules are designed as constraint conditions of any task point during execution of a construction task, and a target function comprises maximizing the number of completed tasks, maximizing human ergonomics performance, and minimizing mobile lifting platform power energy consumption cost; an intelligent simulation calculation algorithm driven by a non-dominated sorting genetic algorithm is adopted, global optimization of the multi-objective optimization model is performed based on large-scale batch construction tasks, and an optimal discrete mobile lifting platform height stay sequence is obtained. The application realizes control of construction operation safety risks, reduction of mechanical energy consumption, and improvement of construction production efficiency through an information-based method.

Description

Technical Field

[0001] This invention belongs to the field of construction automation and intelligent engineering machinery technology, and particularly relates to a human-machine collaborative space optimization method and system for mobile lifting platforms based on ergonomics. Background Technology

[0002] Mobile lifting work platforms (MEWPs, such as scissor lifts) are widely used in high-altitude construction operations such as steel structure construction and electromechanical pipeline installation. Their main function is to lift workers, tools, and materials to a predetermined working height. The operator's working height and ergonomic spatial envelope directly affect construction productivity and safety.

[0003] However, current research on mobile platform spatial planning has certain limitations:

[0004] (1) Idealization of collision avoidance model. Existing research focuses on 2D path planning in a plane. When facing complex construction site confined spaces (such as dense suspended pipelines and steel beams), the lack of rigorous three-dimensional physical entity collision avoidance and accessibility boundary models can easily lead to rigid body collisions between the platform and the components above or to the side during vertical lifting.

[0005] (2) Energy consumption models fail to reflect physical reality. Existing algorithms typically employ static height models where the higher the absolute height, the greater the energy consumption penalty. However, in the actual physical world, hydraulic scissor lifts feature hydraulic locking and zero energy consumption during hovering. Their main energy consumption and mechanical wear originate from the frequent start-stop cycles of the motor. Existing models cannot guide the equipment to perform reasonable stationary batch processing operations to reduce the number of start-stop cycles.

[0006] (3) Neglecting ergonomics and human-machine collaboration mechanisms. Traditional planning only determines whether the task point is within the work area, without considering the serious impact of the relative height difference between the operation point and the worker's feet on the comfort and efficiency of physiological postures (such as bending over, tilting the head back, etc.), resulting in low actual labor productivity under the theoretically optimal planning scheme.

[0007] In summary, traditional planning methods relying on human experience or simple two-dimensional geometric deduction are no longer sufficient to meet the refined management and control requirements of modern intelligent construction and construction informatization. In the context of the current digital transformation of the construction industry, there is an urgent need for a human-machine collaborative information computing method and system that integrates three-dimensional spatial data, mechanical dynamics characteristics, and ergonomics. By introducing mathematical modeling and multi-objective intelligent heuristic algorithms, the complex physical environment of construction operations can be transformed into a computable and optimizable digital model, thereby providing scientific information-based decision support for equipment scheduling and spatial planning on construction sites. This is not only key to breaking through the efficiency and safety bottlenecks of traditional high-altitude construction operations, but also a requirement for upgrading traditional construction machinery to digital and intelligent management and control.

[0008] Furthermore, current construction workers primarily rely on their own experience to position and operate the hoists, which not only poses a high risk of collisions but also significantly reduces work efficiency and increases mechanical wear due to frequent starts and stops. Addressing the spatial planning issues of mobile hoisting equipment on construction sites necessitates a three-dimensional spatial study and analysis of the equipment's physical boundaries and lifting height sequences. Therefore, there is an urgent need to propose a multi-objective spatial optimization method that comprehensively considers three-dimensional collision avoidance envelopes, dynamic start-stop energy consumption, and ergonomics. This has significant practical implications for intelligent scheduling of engineering equipment and improving the efficiency of high-altitude operations.

[0009] In response, this invention proposes a three-dimensional spatial optimization method for mobile lifting work platforms (such as scissor lifts) on construction sites based on human ergonomics and human-machine collaboration. This method uses information technology to control construction operation safety risks, reduce mechanical energy consumption, and improve construction production efficiency. Summary of the Invention

[0010] The purpose of this invention is to provide a human-machine collaborative space optimization method and system for mobile lifting platforms based on ergonomics, in order to solve the problems mentioned in the background art, such as the inability of traditional planning methods to meet the needs of refined management and control of building construction, and the fact that construction workers rely on their own experience to operate the lifting platform, which poses a risk of collision and significantly reduces work efficiency and increases mechanical wear.

[0011] To achieve the above objectives, the present invention employs the following technical solution: In its first aspect, this invention proposes a human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics, comprising the following steps: Establish a multi-objective optimization model based on spatial three-dimensional analysis; design the decision variables and constraints of the multi-objective optimization model, taking the height dwell sequence of the mobile lifting platform as the decision variable, and design three-dimensional collision avoidance and accessibility filtering rules as constraints for any task point when performing construction tasks; and establish the objective function of the multi-objective optimization model, which includes maximizing the number of tasks that can be completed, maximizing human ergonomics, and minimizing the power energy consumption cost of the mobile lifting platform. Simulation optimization: An intelligent simulation calculation algorithm driven by a non-dominated sorting genetic algorithm is adopted. Based on large-scale batch construction tasks, global optimization is performed on the multi-objective optimization model to automatically retrieve and obtain the optimal discrete mobile lifting platform height dwell sequence.

[0012] Preferably, the decision variable is a set of discrete sequences of the stationary height of the mobile lifting platform:

[0013] in, This represents the set of height-based stopping sequences of a mobile lifting platform. Indicates the first Platform height during the next work stop; Indicates the sequence number of the equipment lifting operation; This indicates the maximum number of times the platform height can be adjusted.

[0014] Preferably, the three-dimensional collision avoidance and accessibility filtering rules are as follows: For any task point , This indicates the construction task points to be executed. Indicates the construction task point Absolute coordinates in three-dimensional space; This indicates the center parking coordinates of the mobile lifting platform within the working area. This indicates the physical structural length of the mobile lifting platform. This indicates the physical width of the mobile lifting platform; This indicates the effective safe working distance for a person standing at the edge of the platform and extending beyond the guardrail. Based on 3D collision avoidance, any task point The following conditions must be met simultaneously for allocation: X-axis projection coverage: ; Y-axis physical collision avoidance detection: ; Y-axis safe reach limit: ; Z-axis limit constraint: ; in, Indicates the first Platform height during the execution of this task This indicates the fixed limit safety height within the preset work space.

[0015] Preferably, maximizing the number of tasks that can be completed is specifically as follows:

[0016] in, This indicates the total number of construction tasks that the mobile lifting platform can successfully cover and support; This indicates the total number of construction tasks to be performed within the planned area; Indicates the first One construction task point; Represents a binary decision variable, when the task... When the above three-dimensional collision avoidance and accessibility filtering rules are met and the area is within a highly effective construction zone, Otherwise, it is 0.

[0017] Preferably, maximizing ergonomics means defining human work comfort based on the absolute height of the task. With platform height Relative vertical height difference It was decided to design a piecewise function for human posture ergonomics scores under different construction task conditions. The ergonomic performance is as follows:

[0018] in, This represents the global average performance score for all covered tasks. This indicates the total number of construction tasks to be performed within the planned area. Indicates the first One construction task point; This indicates the sequence number of the lifting operation of the mobile lifting platform. This indicates the maximum number of times the platform height can be adjusted.

[0019] Furthermore, the piecewise function for human posture ergonomics score In a standing construction posture facing directly forward or diagonally downward, the optimal range for this posture is within chest height, specifically: Define the ergonomic height threshold: the safe height limit for guardrails is... This indicates the height of the guardrail from the platform; the height of the chest cavity relative to the platform. The height of the face relative to the platform is The height of the top of the head relative to the platform is ;

[0020] in, This parameter represents the residual productivity decay when the user is in different high-altitude working posture zones. like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

[0021] Furthermore, the piecewise function for human posture ergonomics score When working from a downward or slightly upward angle, the optimal range for this posture is at face height, specifically: Define the ergonomic height threshold: the safe height limit for guardrails is... This indicates the height of the guardrail from the platform; the height of the chest cavity relative to the platform. The height of the face relative to the platform is The height of the top of the head relative to the platform is ;

[0022] in, , This parameter represents the residual productivity decay when the user is in different high-altitude working posture zones. like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

[0023] Preferably, the energy consumption cost of minimizing the mobile lifting platform is comprised of the fixed instantaneous losses during motor start-up and shutdown. Displacement loss due to work done against gravity Composition, then:

[0024] in, This represents the overall dynamic energy consumption cost of the mobile lifting platform after completing the height dwell sequence planning; , This indicates the platform height compared to the previous one; For step indicator function, when When the function is set to 1, it triggers the start / stop cost; when... When the function is set to 0, it does not incur any start / stop or displacement costs.

[0025] Preferably, the simulation optimization is as follows: First, complete the initialization and randomly generate the initial population for the height dwell sequence scheme; Then, by using 3D collision avoidance and accessibility filtering rules to filter out unqualified tasks, and calculating the objective function value corresponding to each height dwell sequence scheme, the total number of tasks, the global average human ergonomics score, and the total power consumption cost can be completed. Subsequently, high-fitness high-stay sequence schemes were evaluated and retained through non-dominated sorting and crowding distance calculation; Finally, crossover and mutation operations are performed to generate new high-stay sequence schemes for the next generation, until the maximum number of iterations is reached.

[0026] In a second aspect, this invention proposes a human-machine collaborative space optimization system for a mobile lifting platform based on ergonomics, comprising: A multi-objective optimization model based on three-dimensional spatial analysis is used to describe the relationship between the three-dimensional envelope, height dwell sequence, task coverage, work efficiency, and energy consumption of a mobile lifting platform. The simulation-based optimization module is used to find the optimal height dwell scheme that satisfies multiple objectives such as collision safety, labor productivity, and equipment operating costs.

[0027] Compared with the prior art, the beneficial effects of the present invention are: (1) This invention establishes a comprehensive optimization framework integrating multiple objectives: The method in this invention establishes a multi-objective model to describe the relationship between the three-dimensional envelope of the lifting platform, the height dwell sequence, and task coverage, work efficiency, and energy consumption cost. Based on this model, a simulation optimization module based on a heuristic algorithm was further developed to find the optimal height dwell point scheme that satisfies multiple objectives such as collision safety, labor productivity, and equipment operating cost. The developed model was implemented in a pipeline construction project to prove the effectiveness of the method.

[0028] (2) This invention innovatively proposes a three-dimensional collision avoidance and accessibility filtering rule, eliminating planning dead spots in complex spaces: Traditional spatial planning is mostly limited to two-dimensional planar paths, ignoring the physical interference in complex three-dimensional environments. This invention constructs a vertically rigid "collision avoidance safety surface" by introducing the physical width of the platform, and superimposes the "safety reach extension distance" of the operator, achieving a dual decoupling of physical entity collision avoidance and effective human accessibility. This rule not only ensures that the lifting equipment achieves "absolute zero collision" when lifting in confined spaces with dense pipelines, but also maximizes the use of the worker's safe working envelope to cover edge task points, solving the problems of equipment and structure conflicts and workers' inability to reach the work surface in traditional construction scheduling.

[0029] (3) This invention creates a piecewise function based on human ergonomics scores to achieve physiological adaptation between work posture and machine scheduling: Traditional path optimization usually follows the principle of shortest distance, which can easily lead to workers being forced to adopt anti-human postures such as excessive bending or long-term head tilting and tiptoeing, which are prone to fatigue. This invention uses the relative vertical height difference between the task point and the platform as the core independent variable, giving the mathematical model the connotation of "human physiology". This piecewise function can accurately quantify the degree of productivity decline of workers in different relative height ranges (such as the optimal chest area and the extreme attenuation area of ​​the head) according to different construction postures (such as applying force directly in front or looking up). This guides the optimization algorithm to actively find a moderate hovering height that allows most task points to fall in the worker's "most comfortable operating area".

[0030] (4) The present invention forms a spontaneous "strategic batch processing", which significantly extends the mechanical life and reduces energy consumption: Thanks to the synergistic effect of the above-mentioned ergonomic piecewise function and dynamic start-stop energy consumption penalty, the system of the present invention can spontaneously make "strategic batch processing" decisions, that is, allow workers to sacrifice a small degree of extreme posture comfort at a single hovering height and merge fragmented processes with similar heights into a unified work batch. This greatly reduces the ineffective frequent start-stop (i.e., mechanical vibration) caused by the hydraulic lifting motor for a very small height difference, which not only significantly reduces the instantaneous starting current energy consumption and mechanical valve wear, but also ensures the continuity and safety of high-altitude workers. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the safe construction area in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram illustrating the relationship between relative height zoning and ergonomic performance based on ergonomics in Embodiment 1 of the present invention; Figure 3 This is the pipeline space model used in Embodiment 2 of the present invention; Figure 4 This is a side view of the platform height optimization result in Embodiment 2 of the present invention; Figure 5 This is a diagram showing the three-dimensional spatial optimization result of the lifting platform in Embodiment 2 of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] Example 1: The human-machine collaborative space optimization method for mobile lifting platforms based on ergonomics includes the following steps: Step 1: Determine the decision variables and constraints of the mathematical model.

[0034] The present invention aims to establish a multi-objective optimization model based on spatial three-dimensional analysis to optimize the height dwell sequence of mobile lifting equipment (such as scissor lifts), so as to minimize the energy consumption caused by frequent start-stop of the equipment and maximize the work efficiency of high-altitude workers while ensuring absolute zero collision.

[0035] Parking position of the given lifting platform plane and the preset fixed limit safety height within the area Given the premise of (i.e., an insurmountable ceiling for the equipment), the model's decision variables are a set of discrete platform height dwell sequences: (1) In the formula, This represents the set of height-based stopping sequences of a mobile lifting platform. Indicates the first Platform height during the next work stop; Indicates the sequence number of the equipment lifting operation; This indicates the maximum number of times the platform height can be adjusted.

[0036] To ensure safety, three-dimensional collision avoidance and accessibility filtering rules are established. For any task point... To be eligible for allocation, the following conditions must be met simultaneously: Figure 1 As shown: ① X-axis projection coverage: ( (for platform length). ② Y-axis solid collision avoidance detection: (The task must not be located within the lifting surface of the machine to avoid vertical collisions.) (platform width). ③ Y-axis safety achievable limit: ( (to allow workers to extend the effective reach of the guardrail). ④ Z-axis limit constraint: Platform height for task execution .

[0037] In the formula, Indicates the construction task points to be executed; Indicates the construction task point Absolute coordinates in three-dimensional space; This indicates the center parking coordinates of the mobile lifting platform within the working area; This indicates the physical structural length of the mobile lifting platform; This indicates the physical width of the mobile lifting platform, used to avoid vertical collisions during machine lifting. This indicates the effective safe working distance for operators to extend beyond the guardrail when standing at the edge of the platform; This indicates the fixed limit safety height within the preset work space (i.e., the physical ceiling that the equipment platform cannot exceed).

[0038] Step 2: Establishment of a multi-objective optimization model.

[0039] To achieve a balance between different optimization objectives during construction, an optimization model with three objective functions is established: Objective 1: Maximize the number of achievable tasks ( ); The objective function aims to maximize the number of processes that the equipment can support.

[0040] (2) In the formula, This indicates the total number of construction tasks that the platform can successfully cover and support; This indicates the total number of construction tasks to be performed within the planned area; Indicates the first One construction task point; Represents a binary decision variable, when the task... When the above three-dimensional anti-collision filtering rules are met and the area is within the highly effective operating zone, Otherwise, it is 0.

[0041] Objective 2: Maximize work efficiency ( ); This invention overcomes the traditional construction operation principle of "shortest absolute distance," because in actual high-altitude operations, placing the equipment platform too close to the task point can actually force workers into extremely uncomfortable postures such as crouching. Therefore, this optimization aims to maximize worker productivity, and this method uses the absolute height of the task... With platform height Relative vertical height difference Using anthropological and force-exertion characteristics as the core independent variable, the workspace is divided into different ergonomic performance zones (e.g., Figure 2 (As shown). Define the ergonomic height threshold: the safe height limit of the guardrail is... This indicates the height of the guardrail from the platform; the height of the chest cavity relative to the platform. The height of the face relative to the platform is The height of the top of the head relative to the platform is .

[0042] (3) In the formula, This represents the global average performance score for all covered tasks. Indicates task Assigned platform height The piecewise function of work posture efficiency score during operation.

[0043] The calculation process is as follows: (1) Situation 1 (Standing posture facing directly forward or diagonally downward, corresponding to) P t =1 or 2): In such working conditions (e.g., tightening lower bolts, assembling vertical structural components), workers primarily rely on their backs and arms to apply downward or forward pushing and pulling pressure. When there is a relative height difference... d When the worker is near the "chest height", the spine is in a neutral position, the shear force is minimal, and the arm is within the optimal biomechanical force envelope.

[0044] Therefore, the optimal working area is set at the safe height of the guardrail. Up to chest cavity height between( As the height difference continues to increase, exceeding the chest height and reaching the face or even the top of the head, workers must raise their arms or even stand on tiptoe and tilt their heads back for extended periods, leading to rapid fatigue of the shoulder and neck muscles and a significant decrease in productivity. Therefore, the system triggers a linear decay penalty function based on geometric proportions.

[0045] (4) like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

[0046] (2) Case 2 (Upward construction posture facing directly upward or diagonally upward, corresponding to) P t =3): In such work conditions (such as welding horizontal pipelines at the top, installing electromechanical equipment on the ceiling, etc.), workers mainly perform delicate operations by lifting upwards or looking up. If the task point is below the face (close to the chest or guardrail), the worker's view will be blocked by their own arms, and they must bend over and flex their neck to look up, which can easily cause cervical strain.

[0047] To ensure an unobstructed view and sufficient upward force exertion on the arms, the relatively optimal range for this posture must be shifted upwards, setting the face height ( The optimal operating height is determined by the distance from the face; the closer the distance, the higher the efficiency. Similarly, when the task point is above the face and close to the limit of the top of the head, the worker will face severe overstretching fatigue, triggering the upper-level decay penalty function.

[0048] The specific function expression is as follows: (5) like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

[0049] In the above formula, d Indicates the absolute height of the task h t platform pedal height h s The relative vertical difference between them ( d = h t - h s ); P t Indicates task t Construction type attributes (such as) P t =1 or 2 indicates bolts and vertical welding. P t =3 is for horizontal welding). H gr This indicates the safety height limit of the guardrail in ergonomic settings (i.e., the height from the platform step to the guardrail, which is the minimum workable limit). H chest This indicates the optimal working height of the operator's chest relative to the platform in ergonomic settings; H face This indicates the height limit of the operator's face relative to the platform in ergonomic settings. H head This indicates the maximum reachable height of the operator's head relative to the platform in ergonomic settings; α 1, α 2, β 1 represents the residual productivity decay parameter when working in different high-altitude posture zones. In this method, these values ​​are 14%, 68.3%, and 61.15%, respectively. These parameter values ​​are exemplary parameters derived from empirical statistical data on ergonomics in building engineering and the proportions of standard human geometric dimensions. The specific acquisition logic is as follows: α 1 represents that when the working point deviates from the chest and reaches the face or even the top of the head under the downward force posture, the arm will have to be raised for a long time without support. Based on the empirical statistics of fatigue in high-altitude work, the productivity is expected to drop significantly by about 86%. Therefore, the remaining efficiency retention benchmark is 1 - 86% = 14%.

[0050] α 2 represents the worker's need to bend over and lower their head to operate when the work point is below face level and close to the guardrail, while in an upward-looking posture. This attenuation ratio is quantified and extrapolated using the proportion of distances within the human body structure; its calculation logic is as follows: α2 = 1 - (distance from guardrail to foot / distance from face to foot) × 100%. Substituting standard human height and guardrail height parameters, the calculated value is approximately 68.3%.

[0051] β 1 represents the productivity reduction when the working height is at the limit of overhead extension. Based on empirical statistics of efficiency reduction caused by limit extension, the estimated efficiency reduction is about 38.85%, so the remaining efficiency threshold is set as 1 - 38.85% = 61.15%.

[0052] It should be noted that the 14%, 68.3%, and 61.15% figures provided herein are merely exemplary values ​​used to illustrate the calculation process and simulation effectiveness of this invention. In practical applications, those skilled in the art can dynamically calibrate and replace the values ​​based on the labor intensity of different jobs, average worker body size data, or fatigue statistics collected by wearable electromyography sensors. Changes to the specific values ​​do not depart from the scope of protection of this invention.

[0053] Objective 3: Minimize the cost of power consumption ( ); A kinematic energy consumption model for the hydraulic drive characteristics of a scissor lift. The cost consists of the fixed instantaneous losses during motor start-up and shutdown (…). ) and displacement loss due to work done to overcome gravity ( )composition: (6) in, F 3 represents the overall comprehensive dynamic energy consumption cost of the mobile lifting platform after completing the height sequence planning; The fixed costs of starting and stopping the platform motor (such as the instantaneous high current loss and mechanical wear during motor startup); The energy cost per unit height the platform ascends; h s and h s-1 These represent the current and previous platform station heights, respectively. For step indicator function, when h s > h s-1 When the function is set to 1, it triggers the start / stop cost; when... h s = h s-1 When the equipment is operating continuously in place and processing multiple tasks in batches, the function takes a value of 0 and does not incur start-up, stop, or displacement costs.

[0054] Step 3: Simulation optimization.

[0055] Based on the constructed multi-objective mathematical model, this invention further develops an intelligent simulation computing module driven by the Non-Dominated Sorting Genetic Algorithm (NSGA-II). This module is dedicated to performing global optimization on complex spatial planning models and can automatically retrieve and determine the optimal discrete platform hovering sequence for large-scale batch construction tasks. The system ultimately outputs not only a Pareto optimal solution set that balances multiple indicators, but also simultaneously completes a three-dimensional spatial visualization of the mapping relationship between equipment physical envelope and work tasks.

[0056] (a) Input data; Simulation data input includes project data (all processes) Coordinates and their types), configuration data (platform physical dimensions) and The reachable extension range of workers Ergonomic height threshold (etc.), and the preset fixed limit safety height of the working environment. .

[0057] (ii) Optimization process; This simulation optimization module was built using Matlab. The optimization steps are as follows: (1) Read and process the three-dimensional coordinate data of the task to complete the initialization; (2) The initial population of the random height sequence scheme is generated, and a forced isolation distance is introduced during initialization to ensure that the platform stations do not overlap; (3) Use "collision avoidance and reachability filtering rules" to filter out unqualified tasks, and then calculate the objective function value corresponding to each solution, i.e., the total number of covered tasks ( F 1) Overall average work efficiency score ( F 2) and the total cost of dynamic energy consumption ( F 3); (4) Through non-dominated ranking and crowding distance calculation, evaluate and retain planning schemes with high fitness; (5) Perform crossover and mutation operations (including targeted gene injection to the ideal height of the uncovered task) to generate new sequence schemes for the next generation until the maximum number of iterations is reached.

[0058] (III) Result Output; Through optimization, the optimal spatial planning scheme set results are output, including: (1) the discrete height stationary point sequence of the lifting platform; (2) the index values ​​of each objective function; and (3) the clustering task subset supported by each stationary point height.

[0059] Example 2: The developed model was implemented in a large-scale underground pipeline construction project, such as Figure 3As shown. Multiple discrete high-altitude task coordinate points were selected, and the physical parameters of the scissor lift were set as follows: length... ,width Workers can reach width The ergonomic height boundaries are set at 1120mm, 1261mm, 1639.9mm, and 1710mm, respectively, with an environmental limit safety height of 20000mm. Start-up and shutdown stationary energy consumption costs. Set it to 500.

[0060] Table 1 shows the input data for the pipeline operations in the case study. The relevant input data includes the spatial coordinates of each operation. ), Process type. Among them, the process execution posture is 1, which indicates a standing posture, and 2, which indicates a squatting posture.

[0061] Table 1 Simulation Input Data (Unit: mm)

[0062] The optimization calculations were performed using the established NSGA-II simulation module, and the system successfully output the optimal solution of the multi-objective Pareto front.

[0063] In the side view of the simulation results ( Figure 4 ) and 3D visualization ( Figure 5 In the diagram, colored dots represent supported processes, with their color matching the platform color that supports that process. Gray dots represent unsupported processes, i.e., orphan points. The results show that, based on the model's 3D collision avoidance and accessibility filtering rules, the equipment platform perfectly avoids all solid components during lifting, achieving zero physical interference. In this simulation, a total of 8 platform heights were pre-set. The final simulation output of the optimized platform height sequence is: [1719, 2938, 3580, 5246, 6632, 7423, 9949, 10516] mm. Under this height sequence, the simulation optimization target result is: Target... F 1 (Number of tasks) is 44, objective F 2 (Efficiency Performance) is 0.9160, Target F 3. The overall energy cost is 13.32. This optimized height sequence covers multiple tasks within its upper and lower ranges, thereby avoiding frequent device start-ups and shutdowns, and achieving... F 1 (Number of tasks) F 2 (Efficiency) and F The optimal balance between the three (energy consumption) targets.

[0064] The above description is only for the purpose of helping to understand the method and core essence of the present invention, but the scope of protection of the present invention is not limited thereto. For those skilled in the art, any equivalent substitutions or modifications made within the technical scope disclosed in the present invention, based on the technical solution and inventive concept, should be covered within the scope of protection of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A human-machine collaborative space optimization method for mobile lifting platforms based on ergonomics, characterized in that, Includes the following steps: Establish a multi-objective optimization model based on spatial three-dimensional analysis; design the decision variables and constraints of the multi-objective optimization model, taking the height dwell sequence of the mobile lifting platform as the decision variable, and design three-dimensional collision avoidance and accessibility filtering rules as constraints for any task point when performing construction tasks; and establish the objective function of the multi-objective optimization model, which includes maximizing the number of tasks that can be completed, maximizing human ergonomics, and minimizing the power energy consumption cost of the mobile lifting platform. Simulation optimization: An intelligent simulation calculation algorithm driven by a non-dominated sorting genetic algorithm is adopted. Based on large-scale batch construction tasks, global optimization is performed on the multi-objective optimization model to automatically retrieve and obtain the optimal discrete mobile lifting platform height dwell sequence.

2. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 1, characterized in that, The specific rules for 3D collision avoidance and accessibility filtering are as follows: For any task point , This indicates the construction task points to be executed. Indicates the construction task point Absolute coordinates in three-dimensional space; This indicates the center parking coordinates of the mobile lifting platform within the working area. This indicates the physical structural length of the mobile lifting platform. This indicates the physical width of the mobile lifting platform; This indicates the effective safe working distance for a person standing at the edge of the platform and extending beyond the guardrail. Based on 3D collision avoidance, any task point The following conditions must be met simultaneously for allocation: X-axis projection coverage: ; Y-axis physical collision avoidance detection: ; Y-axis safe reach limit: ; Z-axis limit constraint: ; in, Indicates the first Platform height during the execution of this task This indicates the fixed limit safety height within the preset work space.

3. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 1, characterized in that, The method for maximizing the number of tasks that can be completed is as follows: in, This indicates the total number of construction tasks that the mobile lifting platform can successfully cover and support; This indicates the total number of construction tasks to be performed within the planned area; Indicates the first One construction task point; Represents a binary decision variable, when the task... When the above three-dimensional collision avoidance and accessibility filtering rules are met and the area is within a highly effective construction zone, Otherwise, it is 0.

4. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 1, characterized in that, To maximize ergonomics, the human work comfort level is defined by the absolute height of the task. With platform height Relative vertical height difference It was decided to design a piecewise function for human posture ergonomics scores under different construction task conditions. The ergonomic performance is as follows: in, This represents the global average performance score for all covered tasks. This indicates the total number of construction tasks to be performed within the planned area. Indicates the first One construction task point; This indicates the sequence number of the lifting operation of the mobile lifting platform. This indicates the maximum number of times the platform height can be adjusted.

5. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 4, characterized in that, The piecewise function of human posture ergonomics score In a standing construction posture facing directly forward or diagonally downward, the optimal range for this posture is within chest height, specifically: Define the ergonomic height threshold: the safe height limit for guardrails is... This indicates the height of the guardrail from the platform; The height of the thoracic cavity relative to the plateau The height of the face relative to the platform is The height of the top of the head relative to the platform is ; in, This parameter represents the residual productivity decay when the user is in different high-altitude working posture zones. like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

6. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 4, characterized in that, The piecewise function of human posture ergonomics score When working from a downward or slightly upward angle, the optimal range for this posture is at face height, specifically: Define the ergonomic height threshold: the safe height limit for guardrails is... This indicates the height of the guardrail from the platform; The height of the thoracic cavity relative to the plateau The height of the face relative to the platform is The height of the top of the head relative to the platform is ; in, , This parameter represents the residual productivity decay when the user is in different high-altitude working posture zones. like or Then move to the next one in the optimization process. ,Right now ;like Then move to the next one in the optimization process. ,Right now .

7. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 1, characterized in that, The energy consumption cost of minimizing the mobile lifting platform is determined by the fixed instantaneous loss during motor start-up and shutdown. Displacement loss due to work done against gravity Composition, then: in, This represents the overall dynamic energy consumption cost of the mobile lifting platform after completing the height dwell sequence planning; , This indicates the platform height compared to the previous one; For step indicator function, when When the function is set to 1, it triggers the start / stop cost; when... When the function is set to 0, it does not incur any start / stop or displacement costs.

8. The human-machine collaborative space optimization method for a mobile lifting platform based on ergonomics as described in claim 1, characterized in that, The simulation optimization is as follows: First, complete the initialization and randomly generate the initial population for the height dwell sequence scheme; Then, by using 3D collision avoidance and accessibility filtering rules to filter out unqualified tasks, and calculating the objective function value corresponding to each height dwell sequence scheme, the total number of tasks, the global average human ergonomics score, and the total power consumption cost can be completed. Subsequently, high-fitness high-stay sequence schemes were evaluated and retained through non-dominated sorting and crowding distance calculation; Finally, crossover and mutation operations are performed to generate new high-stay sequence schemes for the next generation, until the maximum number of iterations is reached.

9. The human-machine collaborative space optimization system for a mobile lifting platform based on ergonomics obtained by the method according to any one of claims 1-8, characterized in that, include: A multi-objective optimization model based on three-dimensional spatial analysis is used to describe the relationship between the three-dimensional envelope, height dwell sequence, task coverage, work efficiency, and energy consumption of a mobile lifting platform. The simulation-based optimization module is used to find the optimal height dwell scheme that satisfies multiple objectives such as collision safety, labor productivity, and equipment operating costs.

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