Building standard floor electromechanical pipeline modular arrangement sequence optimization method

Abstract

The invention provides a building standard floor electromechanical pipeline modular arrangement sequence optimization method, and belongs to the technical field of building construction, and the method comprises the steps: firstly building a fine building BIM model, and dividing an electromechanical system into small modules; then analyzing the relationship between the modules, and determining a necessary sequence and a variable sequence; a weighted directed graph network is established for the variable sequence, and a heuristic function is defined. And searching an optimal arrangement path in the network by adopting an improved A * algorithm, and generating a detailed arrangement scheme. And finally, collision detection and simulation installation are carried out in the BIM model, and the feasibility of the scheme is verified. If problems exist, weight adjustment and optimization are returned until a final scheme is obtained. According to the optimization method, the BIM technology, the graph theory and the heuristic search algorithm are combined, electromechanical pipeline arrangement in a complex building can be effectively optimized, and the technical problem that in the prior art, modular arrangement sequence optimization of electromechanical pipelines of a building standard floor is difficult to achieve quickly and efficiently is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of building construction, and in particular relates to a method for optimizing the modular arrangement sequence of mechanical and electrical pipelines of a standard floor of a building. Background Art

[0002] In the field of construction engineering, the electromechanical pipeline system is a key infrastructure, and its reasonable layout has an important impact on the construction progress, usage function and operation efficiency of the entire construction project. The traditional electromechanical pipeline layout method mainly relies on the experience of engineers, and usually adopts a natural top-down layout order, that is, the main pipeline is installed first, then the branch pipeline, and finally the equipment is connected. Although this empirical layout method is simple and intuitive, it is difficult to take into account various actual constraints, which easily leads to dense pipeline layout, frequent collisions, low construction efficiency, and difficulty in optimizing energy consumption performance.

[0003] With the development of building information modeling (BIM) technology, three-dimensional visualization design and simulation analysis of building mechanical and electrical systems have become possible. Some researchers have tried to optimize pipeline layout based on BIM models by using qualitative analysis or trial-and-error calculation methods. However, these methods are usually limited to the optimization of a certain subsystem, and it is difficult to take into account the integrity and coordination of the entire mechanical and electrical system. Other scholars have proposed using artificial intelligence algorithms, such as genetic algorithms and ant colony algorithms, to find the optimal solution for pipeline layout, but these methods often have high computational complexity and strict requirements on initial solutions and parameter settings, making them difficult to promote and apply in actual projects.

[0004] In other words, the existing technology has the technical problem of being difficult to quickly and efficiently achieve the optimization of the modular layout sequence of mechanical and electrical pipelines on standard floors of buildings. Summary of the invention

[0005] In view of this, the present invention provides a method for optimizing the modular layout sequence of mechanical and electrical pipelines in a standard building layer, which can solve the technical problem in the prior art that it is difficult to quickly and efficiently optimize the modular layout sequence of mechanical and electrical pipelines in a standard building layer.

[0006] The present invention is achieved in that:

[0007] A first aspect of the present invention provides a method for optimizing the modular layout sequence of mechanical and electrical pipelines in a standard building layer, which comprises the following steps:

[0008] S10. Establish a detailed 3D BIM model of the building standard layer, including structure, space division, and functional division;

[0009] S20, subdividing the electromechanical pipeline system into multiple small modules;

[0010] S30, analyzing the spatial relationship and functional dependence between the small modules, and determining the small module pairs that must be arranged in order;

[0011] S40, for small modules without a necessary arrangement order, establish a directed graph network model, in which nodes represent each small module and edges represent possible arrangement orders;

[0012] S50, assigning a weight to each edge in the directed graph network model;

[0013] S60, defining a heuristic function with the necessary arrangement order as a constraint condition, for evaluating the estimated cost from the current arrangement state to the target state;

[0014] S70, using an improved A* algorithm to search for an optimal layout path in the directed graph network model according to the heuristic function, wherein the optimal layout path represents the precise layout order of all small modules;

[0015] S80, generating a detailed small module arrangement sequence plan according to the searched optimal path, including the specific location, installation order and connection relationship of each small module;

[0016] S90, perform collision detection and simulate installation in the BIM model to verify the feasibility of the layout plan. If any problems are found, return to step S50 for local adjustment and optimization until the final optimization plan is obtained.

[0017] On the basis of the above technical solution, the modular layout order optimization method of mechanical and electrical pipelines of a building standard layer of the present invention can also be improved as follows:

[0018] The electromechanical pipeline system is subdivided into a plurality of small modules, specifically including:

[0019] The small modules of the water supply subsystem include at least: risers, cross pipes, branches, and valves;

[0020] The small modules of the drainage subsystem include at least: sewage pipe, rainwater pipe, and ventilation pipe;

[0021] The small modules of the HVAC subsystem include at least: air ducts, water pipes, air conditioning units, and air vents;

[0022] The small modules of the electrical subsystem include at least: strong current cable duct, weak current bridge, distribution box, and switch;

[0023] The small modules of the fire protection subsystem include at least: fire protection pipes, sprinkler heads, and smoke detectors.

[0024] Furthermore, the small module pairs that must be arranged in order at least include: trunk pipelines take precedence over branch pipelines; gravity flow pipelines take precedence over pressure pipelines; rigid pipelines take precedence over flexible pipelines.

[0025] Furthermore, the weight factors include: spatial distance between small modules; installation difficulty coefficient; potential collision risk; convenience of maintenance and repair; and impact on energy efficiency.

[0026] Furthermore, the heuristic function considers the following factors: the number of remaining unarranged small modules; the complexity of the arranged small modules; the overall coordination of the current arrangement plan; and the estimated workload required to complete the arrangement.

[0027] The directed graph network model is specifically expressed as follows:

[0028] G = (V, E);

[0029] Among them, V represents the vertex set, which represents each small module; E represents the edge set, which represents the possible arrangement order.

[0030] For each edge in the network, the weight function is defined as follows:

[0031] w(e ij )=αd ij +βc ij +γr ij +δm ij +ηe ij ;

[0032] In the formula, w(e ij ) is the edge e ij The weight of ij is the spatial distance between modules i and j (meters); c ij is the installation difficulty coefficient, with a value range of [0,1]; r ij is the potential collision risk, with a value range of [0,1]; m ij For the convenience of maintenance and repair, the value range is [0,1]; e ij is the influence of energy efficiency, and its value range is [0,1]; α, β, γ, δ, η are weight coefficients, and they satisfy α+β+γ+δ+η=1.

[0033] Parameter acquisition method:

[0034] 1.d ij : Calculated by the Euclidean distance between the center points of two modules in the BIM model:

[0035]

[0036] Among them, (x i ,y i ,z i ) and (x j ,y j ,z j ) are the center coordinates of modules i and j respectively.

[0037] 2.c ij : Determined by expert scoring method, taking into account factors such as the complexity of the installation process and the required tools and equipment.

[0038] 3.r ij : Calculation based on historical data and simulation analysis:

[0039]

[0040] Among them, N ij is the number of potential collision points between modules i and j, and λ is the collision risk coefficient.

[0041] 4.m ij : Calculated through reachability analysis:

[0042]

[0043] Among them, A ij is the accessible area of ​​modules i and j, A total is the total accessible area under ideal conditions.

[0044] 5.e ij :Calculated through energy consumption simulation:

[0045]

[0046] Among them, E ij is the system energy consumption after the arrangement of modules i and j, E min and E max are the minimum and maximum energy consumption among all possible layout schemes, respectively.

[0047] Next, define the heuristic function:

[0048] h(n)=ω1f(n)+ω2g(n)+ω3c(n)+ω4w(n);

[0049] Where h(n) is the heuristic function value of node n; f(n) is the number of remaining unarranged small modules; g(n) is the complexity of the arranged small modules; c(n) is the overall coordination of the current arrangement scheme; w(n) is the estimated workload required to complete the arrangement; ω1, ω2, ω3, ω4 are weight coefficients, and they satisfy ω1+ω2+ω3+ω4=1.

[0050] The sub-functions are defined as follows:

[0051] 1. Number of small modules remaining to be arranged:

[0052] f(n)=|V|-|V n |;

[0053] Among them, |V| is the total number of modules, |V n | is the number of modules that have been arranged.

[0054] 2. Complexity of small modules arranged:

[0055]

[0056] Among them, V n A collection of laid out modules.

[0057] 3. Overall coordination of the current layout plan:

[0058]

[0059] in, is the average weight of all laid out edges.

[0060] 4. Estimate the amount of work required to complete the layout:

[0061]

[0062] Among them, k1, k2 are coefficients, (VV n ) is a collection of unarranged modules.

[0063] The constraints of the heuristic function include:

[0064] 1. Order constraints must be arranged:

[0065]

[0066] Among them, M is a set of module pairs with a certain arrangement order, and rank(i) represents the arrangement order of module i.

[0067] 2. Space constraints:

[0068]

[0069] Among them, d min The minimum safe distance.

[0070] 3. Functional dependency constraints:

[0071]

[0072] Among them, D is a set of functionally dependent module pairs.

[0073] 4.Total volume constraints:

[0074] ∑ i∈V vol(i)≤Vol total ;

[0075] Where, vol(i) is the volume of module i, Vol total is the total volume of available space.

[0076] 5. Energy efficiency constraints:

[0077] E total ≤F max ;

[0078] Among them, E total is the total energy consumption of the system, E max is the maximum allowable energy consumption.

[0079] Based on the above definition, the objective function of the improved A* algorithm can be expressed as:

[0080] F(n)=G(n)+h(n);

[0081] Among them, G(n) is the actual cost from the starting node to the current node n, and the calculation method is:

[0082]

[0083] Among them, P n is the path from the starting node to node n.

[0084] The goal of the algorithm is to find the path that minimizes F(n), that is:

[0085] minF(n),st constraints 1-5.

[0086] Furthermore, the step of verifying the feasibility of the arrangement scheme specifically includes:

[0087] Conduct collision detection on the spatial arrangement of each small module to ensure there is no mutual interference;

[0088] Simulate the installation sequence of each module to ensure there are no installation obstacles;

[0089] Check the coordination with the building structure and functional space.

[0090] Further, if a problem is found, the process returns to step S50 to perform local adjustment and optimization, and performs local adjustment and optimization, including:

[0091] Adjust the weight assigned to each edge in the directed graph network model;

[0092] Adjust the weight of each sub-function in the heuristic function;

[0093] Either or both of the above two adjustment methods.

[0094] Compared with the prior art, the method for optimizing the modular arrangement sequence of mechanical and electrical pipelines on a standard floor of a building provided by the present invention has the following beneficial effects:

[0095] 1. Improve the efficiency of pipeline layout. The traditional top-down empirical layout method is difficult to take into account various practical constraints, which easily leads to dense pipeline layout, frequent collisions, and low construction efficiency. The method of the present invention divides the pipeline system into multiple small modules, establishes a directed graph network model, and uses an improved A* algorithm for optimization search. It can quickly find the optimal layout sequence that meets multiple constraints such as space, function, and energy consumption, greatly improving the efficiency of pipeline construction.

[0096] 2. Optimize the energy consumption performance of the system. The existing pipeline layout method is difficult to take into account energy consumption factors, which often leads to problems such as redundant pipeline length and unreasonable direction, thereby reducing the overall energy efficiency level of the system. While optimizing the layout sequence, the method of the present invention also fully considers the energy consumption factor. By reasonably arranging the length and direction of the pipeline, the energy consumption of the entire electromechanical system is finally optimized, and the operating energy efficiency of the building is greatly improved.

[0097] 3. Improve the maintainability of pipelines. Under the traditional layout method, the pipeline system is often complicated to arrange, which is not conducive to the subsequent maintenance and management. The present invention divides the system into multiple small modules and optimizes their arrangement order, so that the spatial position and installation relationship between the modules are more reasonable, which greatly improves the maintainability of the overall system and can greatly reduce the manpower and material investment in daily maintenance.

[0098] 4. Applicable to the entire life cycle of a building. The method of the present invention is based on a sophisticated BIM model and can be applied not only to the design optimization of pipeline systems, but also to various stages of the entire life cycle, such as construction and operation and maintenance. In the construction stage, it can provide detailed guidance for on-site pipeline installation; in the operation and maintenance stage, it can provide reliable disassembly and assembly solutions for fault repair and system transformation.

[0099] In summary, the present invention solves the technical problem in the prior art that it is difficult to quickly and efficiently optimize the modular layout sequence of mechanical and electrical pipelines on a standard floor of a building. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 A flow chart of the method provided by the present invention;

[0101] Figure 2 This is the impact diagram of modularity on system complexity;

[0102] Figure 3 This is a comparison chart of pipeline layout efficiency before and after optimization;

[0103] Figure 4 It is a comparison chart of the iterative convergence process of the optimization algorithm and the traditional method;

[0104] Figure 5 This is a performance comparison chart of different algorithms. DETAILED DESCRIPTION

[0105] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0106] like Figure 1 As shown, it is a flow chart of a modular layout sequence optimization method for mechanical and electrical pipelines of a standard building layer provided by the present invention. The method comprises the following steps:

[0107] S10. Establish a detailed 3D BIM model of the building standard layer, including structure, space division, and functional division;

[0108] S20, subdividing the electromechanical pipeline system into multiple small modules;

[0109] S30, analyzing the spatial relationship and functional dependence between the small modules, and determining the small module pairs that must be arranged in order;

[0110] S40, for small modules without a necessary arrangement order, establish a directed graph network model, in which nodes represent each small module and edges represent possible arrangement orders;

[0111] S50, assigning a weight to each edge in the directed graph network model;

[0112] S60, defining a heuristic function with a necessary arrangement order as a constraint condition, for evaluating the estimated cost from the current arrangement state to the target state;

[0113] S70, using an improved A* algorithm to search for an optimal layout path in the directed graph network model according to a heuristic function, where the optimal layout path represents the precise layout order of all small modules;

[0114] S80, generating a detailed small module arrangement sequence plan according to the searched optimal path, including the specific location, installation order and connection relationship of each small module;

[0115] S90, perform collision detection and simulate installation in the BIM model to verify the feasibility of the layout plan. If any problems are found, return to step S50 for local adjustment and optimization until the final optimization plan is obtained.

[0116] The specific implementation methods of the above steps are described in detail below:

[0117] Step S10: Establish a detailed 3D BIM model of the building standard layer

[0118] First, use BIM modeling software such as Revit or ArchiCAD to build a detailed 3D BIM model of the building standard layer based on the architectural engineering drawings and related technical data. The model should include the following:

[0119] 1) The structural system of a building, including main structural columns, beams, floor slabs, etc.

[0120] 2) Functional zoning, such as the division of areas for different uses such as residential, office, and commercial.

[0121] 3) The spatial structure inside the building, such as rooms, corridors, stairs, etc.

[0122] 4) Layout information of building equipment systems, including preliminary location and dimensions of pipelines, equipment and facilities.

[0123] In the process of establishing the BIM model, it is necessary to ensure the geometric accuracy of the model, the integrity and reliability of the attribute information, and provide a reliable data basis for the subsequent optimization of the mechanical and electrical pipeline layout.

[0124] Step S20: Divide the electromechanical pipeline system into multiple small modules

[0125] For typical electromechanical pipeline systems in construction projects, such as water supply, drainage, HVAC, electrical, fire protection, etc., they are subdivided into the following small modules:

[0126] 1) Water supply subsystem: risers, horizontal pipes, branches, valves, etc.

[0127] 2) Drainage subsystem: sewage pipe, rainwater pipe, ventilation pipe, etc.

[0128] 3) HVAC subsystem: air ducts, water pipes, air conditioning units, air vents, etc.

[0129] 4) Electrical subsystem: high-voltage cable ducts, low-voltage cable bridges, distribution boxes, switches, etc.

[0130] 5) Fire protection subsystem: fire protection pipes, sprinkler heads, smoke detectors, etc.

[0131] Dividing the entire electromechanical system into these small modules that can be installed independently is conducive to optimizing the layout sequence and improving installation efficiency. It is also convenient for subsequent maintenance and management.

[0132] Step S30: Analyze the spatial relationship and functional dependency between small modules

[0133] Through in-depth analysis of the BIM model, the necessary arrangement order relationship between the small modules is identified, which mainly includes the following categories:

[0134] 1) Trunk pipelines take precedence over branch pipelines: Main pipelines should be installed and arranged before branch pipelines.

[0135] 2) Gravity flow pipelines take precedence over pressure pipelines: Gravity flow pipelines such as sewage pipes and rainwater pipes should be laid out before pressure pipelines such as water pipes.

[0136] 3) Rigid pipes take precedence over flexible pipes: for example, metal pipelines should be laid out before plastic hoses.

[0137] These inevitable arrangement order relationships need to be used as hard constraints for subsequent optimization algorithms.

[0138] Step S40: Establishing a directed graph network model

[0139] For small modules that do not have a necessary arrangement order, a directed graph network model G = (V, E) can be established to describe them. Among them:

[0140] V represents a node set, each node represents a small module;

[0141] E represents the edge set, and each edge represents a possible arrangement order between two modules.

[0142] This forms a directed acyclic graph (DAG) structure, which is used to represent the layout relationship between the small modules of the electromechanical pipeline system.

[0143] Step S50: Assign weights to each edge in the network model

[0144] In order to reflect the advantages and disadvantages of the layout between each small module, it is necessary to set the edge e in the network model. ij Assign a weight w(e ij ), the calculation formula is as follows:

[0145] w(e ij )=αd ij +βr ij +γr ij +δm ij +ηe ij ;

[0146] in:

[0147] d ij is the spatial distance between modules i and j (meters);

[0148] c ij The installation difficulty coefficient has a value range of [0,1], and the larger the value, the more difficult the installation is;

[0149] r ij is the potential collision risk, with a value range of [0,1], and a larger value indicates a higher collision risk;

[0150] m ijFor the convenience of maintenance and repair, the value range is [0,1], and the larger the value, the easier it is to maintain;

[0151] e ij It is the impact of energy efficiency, and its value range is [0,1]. The larger the value, the greater the impact of energy consumption.

[0152] α, β, γ, δ, η are weight coefficients, satisfying α+β+γ+δ+η=1.

[0153] These parameters are obtained as follows:

[0154] 1)d ij Calculated by the Euclidean distance between the center points of two modules in the BIM model;

[0155] 2)c ij Determined by expert scoring method, taking into account factors such as installation process complexity and required tools and equipment;

[0156] 3)r ij Based on historical data and simulation analysis, the specific formula is: Where N ij is the number of potential collision points between modules i and j, and λ is the collision risk coefficient;

[0157] 4)m ij Through reachability analysis and calculation, the specific formula is m ij =A ij / A total , where A ij is the accessible area of ​​modules i and j, A total is the total accessible area under ideal conditions;

[0158] 5)e ij Through energy consumption simulation calculation, the specific formula is e ij =(E ij -E min ) / (E max -E min ), where E ij is the system energy consumption after the arrangement of modules i and j, E min and E max are the minimum and maximum energy consumption among all possible layout schemes, respectively.

[0159] Step S60: Define a heuristic function

[0160] In order to quickly find the optimal arrangement order of small modules in a directed graph network model, the following heuristic function h(n) is defined:

[0161] h(n)=ω1f(n)+ω2g(n)+ω3c(n)+ω4w(n);

[0162] in:

[0163] f(n) is the number of remaining unarranged small modules;

[0164] g(n) is the complexity of the arranged small modules;

[0165] c(n) is the overall coordination of the current layout scheme;

[0166] w(n) is the estimated amount of work required to complete the layout;

[0167] ω1, ω2, ω3, ω4 are weight coefficients, satisfying ω1+ω2+ω3+ω4=1.

[0168] The specific definitions are as follows:

[0169] 1) The number of small modules remaining unarranged f(n) = |V| - |V n |, where |V| is the total number of modules, |V n | is the number of modules that have been arranged.

[0170] 2) Complexity of small modules that have been arranged Where V n A collection of laid out modules.

[0171] 3) Overall coordination of the current layout plan in is the average weight of all laid out edges.

[0172] 4) Estimate the amount of work required to complete the layout Where k1, k2 are coefficients, (VV n ) is a collection of unarranged modules.

[0173] This heuristic function can better reflect the quality of the current layout plan and provide valuable guidance for subsequent optimal path search.

[0174] Step S70: Using the improved A* algorithm to search for the optimal layout path

[0175] In the directed graph network model G = (V, E), the improved A* algorithm is used to search for the optimal arrangement order of small modules. The objective function of the algorithm is:

[0176] F(n)=G(n)+h(n);

[0177] Among them, G(n) is the actual cost from the starting node to the current node n, and the calculation formula is:

[0178]

[0179] P n is the path from the starting node to node n.

[0180] The goal of the algorithm is to find the path that minimizes F(n) while satisfying the following constraints:

[0181] 1) Order constraints must be arranged: Where M is a set of module pairs that must be arranged in order, and rank(i) represents the arrangement order of module i.

[0182] 2) Space constraints: where d min The minimum safe distance.

[0183] 3) Functional dependency constraints: Where D is a set of functionally dependent module pairs.

[0184] 4) Total volume constraint:∑ i∈V vol(i)≤Vol total , where vol(i) is the volume of module i, Vol total is the total volume of available space.

[0185] 5) Energy efficiency constraint: E total ≤E max , where E total is the total energy consumption of the system, E max is the maximum allowable energy consumption.

[0186] In this way, we can find the optimal arrangement sequence of small modules for the overall system while satisfying various practical constraints.

[0187] Step S80: Generate a detailed small module layout plan

[0188] According to the optimal path searched in step S70, a detailed small module arrangement sequence plan can be generated, including:

[0189] 1) The specific location coordinates of each small module;

[0190] 2) The installation order of each small module;

[0191] 3) The connection relationship between each small module.

[0192] This layout plan not only reflects the optimized sequence between modules, but also involves the specific installation position and connection method of each module, providing detailed construction drawings and guidance for the subsequent actual construction of the pipeline system.

[0193] Step S90: BIM model collision detection and installation simulation

[0194] Finally, it is necessary to perform collision detection and installation simulation on the layout plan generated in step S80 in the BIM model to verify its feasibility.

[0195] Specifically include:

[0196] 1) Perform collision detection on the spatial layout of each small module to ensure there is no mutual interference;

[0197] 2) Simulate the installation sequence of each module to ensure there are no installation obstacles;

[0198] 3) Check the coordination with the building structure and functional space.

[0199] If a problem is found, it is necessary to return to step S50 to locally adjust and optimize the weight factors until a final feasible optimization solution is obtained.

[0200] Through these nine steps, a building mechanical and electrical pipeline layout method based on BIM technology and intelligent optimization algorithm was established. This method can fully consider various constraints, effectively optimize the overall layout of the pipeline system, and improve construction efficiency and operation energy efficiency.

[0201] Specifically, the principle of the present invention is: first, use BIM technology to establish a detailed three-dimensional model including building structure, functional zoning and preliminary equipment layout; then subdivide the entire pipeline system into multiple small modules that can be installed independently; analyze the necessary layout order relationship between each module, and establish a directed graph network model that can reflect their advantages and disadvantages; finally, use the improved A* algorithm to quickly search for the overall optimal pipeline layout order under the premise of meeting various constraints.

[0202] Specifically, in step S10, a detailed three-dimensional model including the structural system, functional divisions, internal space and preliminary layout information of the equipment system is established using BIM modeling software such as Revit, ArchiCAD, etc., based on architectural engineering drawings and related technical data. This BIM model provides a reliable data basis for subsequent pipeline layout optimization.

[0203] In step S20, the entire electromechanical pipeline system is subdivided into multiple small modules, such as the riser, horizontal pipe, branch pipe, valve, etc. of the water supply subsystem; the sewage pipe, rainwater pipe, vent pipe, etc. of the drainage subsystem; the air duct, water pipe, air conditioning unit, vent, etc. of the HVAC subsystem; the strong power line trough, weak power bridge, distribution box, switch, etc. of the electrical subsystem; and the fire protection pipe, sprinkler head, smoke detector, etc. of the fire protection subsystem. This modular pipeline layout method not only helps to optimize the layout order of the pipelines, but also facilitates the subsequent maintenance and management.

[0204] In step S30, the necessary arrangement order relationship between the small modules is analyzed, mainly including: the trunk pipeline should be arranged before the branch pipeline; the gravity flow pipeline should be arranged before the pressure pipeline; the rigid pipeline should be arranged before the flexible pipeline. These necessary arrangement order relationships need to be used as hard constraints for the subsequent optimization algorithm.

[0205] For small modules without a necessary arrangement order, a directed graph network model G = (V, E) is established in step S40 to describe them. The node set V represents each small module, and the edge set E represents the possible arrangement order between two modules. In this way, a directed acyclic graph (DAG) structure is formed to characterize the arrangement relationship between the components of the electromechanical pipeline system.

[0206] In order to quantify the pros and cons of the arrangement between modules, in step S50, for each edge e in the network model, ij Assign weight w(e ij ), the calculation formula is: w(e ij )=αd ij +βc ij +γr ij +δm ij +ηe ij Here, d ij is the distance between modules, c ij is the installation difficulty, r ij is the collision risk, m ij For maintenance convenience, ij is the influence of energy consumption, and α, β, γ, δ, η are the corresponding weight coefficients. By reasonably allocating the weights of these parameters, the advantages and disadvantages of the layout of each small module can be fully reflected.

[0207] In step S60, a heuristic function h(n) is defined, whose components include: the number of remaining unarranged modules f(n), the complexity of arranged modules g(n), the overall coordination of the current solution c(n), and the estimated workload w(n) required for completion, etc. This heuristic function can better reflect the quality of the current arrangement solution and provide valuable guidance for subsequent optimal path search.

[0208] Finally, in step S70, the improved A* algorithm is used to search for the optimal path in the directed graph network model G = (V, E). The objective function of the algorithm is F(n) = G(n) + h(n), where G(n) is the actual cost from the starting node to the current node n. During the search process, multiple constraints such as the necessary layout order, space, functional dependency, total volume, and energy efficiency must be met at the same time. In this way, the layout order of small modules that makes the overall system optimal can be found under the premise of meeting various practical constraints.

[0209] Compared with the traditional top-down empirical layout method, the method of the present invention makes full use of BIM technology to carry out fine modeling of building space and equipment systems, and subdivides the pipeline system into small modules that can be installed independently, establishes a directed graph network model that reflects the advantages and disadvantages of the layout between each module, and uses an improved A* algorithm to quickly find the overall optimal pipeline layout sequence under the premise of meeting various constraints.

[0210] In order to better understand and implement the present invention, an embodiment of a specific application scenario of the present invention is provided below: a high-rise office building project is in the design stage of the electromechanical pipeline system, with a construction area of ​​about 25,000 square meters, 18 floors above ground and 2 floors underground. According to the preliminary design plan, the main function of the building is office use. In addition to basic water supply and drainage, heating and ventilation, power and lighting systems, it also includes intelligent subsystems such as office automation and fire alarm. In order to improve the layout efficiency and operating energy efficiency of the pipeline system, the project party decided to adopt the small modular layout sequence optimization method of the building electromechanical pipeline proposed in the present invention for design.

[0211] 1. Build a BIM model

[0212] First, the design team used Autodesk Revit software to build a detailed 3D BIM model of the office building based on architectural engineering drawings and related technical data. The model includes the building structure system, functional divisions, internal space layout, and preliminary mechanical and electrical equipment system layout, providing a reliable data basis for subsequent pipeline optimization.

[0213] Table 1 Main information of BIM model

[0214] project Parameter Value Building Area <![CDATA[25000m 2 ]]> Number of floors above ground 18th floor Number of underground floors 2nd floor Key Features Office Main systems Water supply and drainage, heating and ventilation, power and lighting, office automation, fire alarm

[0215] 2. Pipeline system segmentation and modularization

[0216] According to the requirements of the invention, the design team divided the entire electromechanical pipeline system into the following five small modules:

[0217] 1. Water supply subsystem module: including risers, cross pipes, branches, valves, etc.;

[0218] 2. Drainage subsystem module: including sewage pipes, rainwater pipes, ventilation pipes, etc.;

[0219] 3. HVAC subsystem module: including air ducts, water pipes, air conditioning units, air vents, etc.;

[0220] 4. Electrical subsystem module: including strong current cable duct, weak current bridge, distribution box, switch, etc.;

[0221] 5. Fire protection subsystem module: including fire protection pipes, sprinkler heads, smoke detectors, etc.

[0222] This modular pipeline layout method helps to optimize the layout order of pipelines and facilitates future maintenance and management; Figure 2 As shown in the figure, the impact of the modularization approach on the complexity of the five major electromechanical systems is demonstrated. The horizontal axis represents different systems (water supply and drainage, HVAC, electrical, fire protection and intelligentization), and the vertical axis represents the system complexity index (0-100). Each system has two bar graphs, blue represents the complexity before modularization, and orange represents the complexity after modularization. It can be clearly seen from the figure that after modularization, the complexity of all systems has been significantly reduced. For example, the complexity of the HVAC system has dropped from 90 to 65, a decrease of 27.8%. This reduction in complexity means that the system becomes easier to manage and optimize. Modularization not only simplifies the system structure, but also provides a better entry point for subsequent optimization algorithms. By decomposing the complex overall problem into multiple relatively independent sub-problems, local optimization can be performed more effectively while ensuring the quality of the global optimal solution. This reduction in complexity also directly affects the design efficiency and construction difficulty, laying the foundation for the smooth progress of the entire project.

[0223] 3. Analysis of the necessary arrangement sequence

[0224] Through further analysis, the design team determined the following necessary pipeline layout order relationships:

[0225] 1. Trunk pipes should be laid out before branch pipes. For example, water supply risers should be installed before branch pipes on each floor, and drainage mains should be laid out before branch pipes on each floor.

[0226] 2. Gravity flow pipelines should be laid out before pressure pipelines. For example, gravity flow pipelines such as rainwater pipes and sewage pipes should be installed before pressure pipelines such as water supply pipes.

[0227] 3. Rigid pipes should be laid out before flexible pipes. For example, metal pipes should be installed before plastic hoses.

[0228] These inevitable arrangement order relationships will serve as hard constraints for subsequent optimization algorithms.

[0229] 4. Directed Graph Network Model Construction

[0230] For small modules with no necessary arrangement order, the design team established a directed graph network model G = (V, E) to describe it:

[0231] 1. The node set V represents each small module, totaling 85.

[0232] 2. The edge set E represents the possible arrangement order between two modules, with a total of 312 edges.

[0233] In order to quantify the pros and cons of the layout between modules, the design team calculated the ij Assigned weight w(e ij ), the specific calculation formula is as follows:

[0234] w(e ij )=0.3d ij +0.2c ij +0.2r ij +0.15m ij +0.15e ij ;

[0235] in:

[0236] d ij is the spatial distance between modules i and j (meters);

[0237] c ij is the installation difficulty coefficient, which ranges from [0,1] according to the expert scoring results;

[0238] r ij is the potential collision risk, and its value range is [0,1] according to simulation analysis;

[0239] m ij For the convenience of maintenance and repair, the value range is [0,1] according to the accessibility analysis;

[0240] e ij It is the impact of energy efficiency, and the value range is [0,1] according to the energy consumption simulation.

[0241] In this way, a directed graph network model is established which can better reflect the advantages and disadvantages of the layout between small modules.

[0242] 5. Heuristic function definition

[0243] In order to quickly find the overall optimal arrangement order of small modules in the directed graph network model, the design team defined the following heuristic function h(n):

[0244] h(n)=0.3f(n)+0.2g(n)+0.3c(n)+0.2w(n);

[0245] in:

[0246] f(n) is the number of remaining unarranged small modules;

[0247] g(n) is the complexity of the arranged small modules;

[0248] c(n) is the overall coordination of the current layout scheme;

[0249] w(n) is the estimated amount of work required to complete the layout.

[0250] The specific calculation method of each sub-function is as follows:

[0251] 1. The number of small modules remaining unarranged f(n) = |V| - |V n |, where |V| is the total number of modules, |V n | is the number of modules that have been arranged.

[0252] 2. Complexity of small modules arranged Where V n A collection of laid out modules.

[0253] 3. Overall coordination of the current layout plan in is the average weight of all laid out edges.

[0254] 4. Estimate the amount of work required to complete the layout Where (VV n ) is a collection of unarranged modules.

[0255] This heuristic function can better reflect the quality of the current layout plan and provide valuable guidance for subsequent optimal path search.

[0256] 6. A* Algorithm Optimization

[0257] Finally, the design team used the improved A* algorithm to search for the optimal path in the directed graph network model G = (V, E). The objective function of the algorithm is:

[0258] F(n)=G(n)+h(n);

[0259] Among them, G(n) is the actual cost from the starting node to the current node n, and the calculation formula is:

[0260]

[0261] P n is the path from the starting node to node n.

[0262] During the search process, the following constraints must be met at the same time:

[0263] 1. Order constraints must be arranged: Where M is a set of module pairs that must be arranged in order, and rank(i) represents the arrangement order of module i.

[0264] 2. Space constraints: Meters, that is, the minimum safety distance between modules is 0.5 meters.

[0265] 3. Functional dependency constraints: Where D is a set of functionally dependent module pairs.

[0266] 4. Total volume constraint:∑ i∈V vol(i)≤12,000 cubic meters, that is, the total volume of usable space does not exceed 12,000 cubic meters.

[0267] 5. Energy efficiency constraint: E total ≤1.2×10 6 kWh / year, that is, the annual energy consumption of the system does not exceed 1.2 million kWh.

[0268] By improving the A* algorithm and satisfying the above constraints, the design team successfully found the optimal arrangement sequence of small modules. This optimization scheme not only reflects the arrangement order of each module, but also provides detailed information such as the specific location coordinates, installation sequence and connection relationship of each module, providing a reliable basis for the subsequent pipeline system construction. Figure 3 As shown, the changes in the time required for each stage before and after optimization in the pipeline layout process are compared. The horizontal axis represents the five main stages of pipeline layout (scheme design, construction drawing design, pipeline integration, collision detection, construction simulation), and the vertical axis represents the time required for each stage (days). The blue column represents the time before optimization, and the green column represents the time after optimization. The figure clearly shows the significant efficiency improvement brought about by the method of the present invention. In all stages, the time required after optimization is significantly reduced. Especially in the pipeline integration stage, the time was reduced from 25 days to 15 days, a decrease of 40%. This efficiency improvement stems from multiple innovative points of the method of the present invention:

[0269] 1. Modular design simplifies the complexity of the system and greatly reduces the workload at each stage.

[0270] 2. The optimization algorithm based on graph theory can quickly find the approximate optimal solution, reducing the time for repeated modifications.

[0271] 3. The use of BIM technology for collision detection and construction simulation greatly improves the efficiency of these stages.

[0272] Figure 4 The figure shows the convergence comparison between the method of the present invention and the traditional method (multi-objective optimization model + particle algorithm) during the optimization process. The figure contains two Y axes: the left Y axis (blue) represents the degree of optimization (0-100%), and the right Y axis (red) represents the number of conflicts. The X axis represents the number of iterations (1-100). There are four curves in the figure: the blue and cyan curves represent the changes in the degree of optimization of the method of the present invention and the traditional method, respectively, and the red and orange curves represent the changes in the number of conflicts of the method of the present invention and the traditional method, respectively.

[0273] The following key points can be observed from the figure:

[0274] 1. Optimization degree: The optimization degree of the method of the present invention (blue curve) increases significantly faster than that of the traditional method (cyan curve). After about 40 iterations, the method has reached an optimization degree of more than 90%, while the traditional method requires more than 100 iterations to reach a similar level.

[0275] 2. Number of conflicts: The proposed method (red curve) also performs well in reducing the number of conflicts. The number of conflicts decreases rapidly and approaches zero in a relatively small number of iterations. In contrast, the number of conflicts in the traditional method (orange curve) decreases more slowly.

[0276] 3. Convergence speed: The method of the present invention shows a faster convergence speed in both optimization degree and conflict reduction, which means that it can obtain a high-quality solution in a shorter time.

[0277] This fast convergence characteristic is derived from the improved A* algorithm and the carefully designed heuristic function used in the method of the present invention. By effectively utilizing the characteristic information of the problem, the algorithm can quickly find a solution close to the global optimum while effectively avoiding the local optimum. This not only improves the efficiency of optimization, but also ensures the quality of the obtained pipeline layout solution.

[0278] To facilitate understanding, the steps of the traditional method, i.e., multi-objective optimization model + particle algorithm, to solve the modular layout order optimization problem of mechanical and electrical pipelines on standard floors of buildings are explained here. Specifically, multiple construction plans with different layout orders are constructed, the objective function of each construction plan is calculated, and multiple objective functions are combined into a multi-objective optimization selection model. The particle algorithm is used to select the optimal point, and the corresponding layout order is selected and improved according to the optimal point to form an optimized construction plan.

[0279] Figure 5 The performance of the method of the present invention and several other commonly used algorithms in four key indicators are compared: optimization efficiency, layout rationality, construction feasibility and maintenance convenience. As can be seen from the figure, the method of the present invention is significantly better than other algorithms in all indicators. In particular, in terms of optimization efficiency, the score of the present method reaches 95 points, which is much higher than the 60 points of the traditional method. This comprehensive performance advantage comes from the fact that the present method combines the advantages of BIM technology, graph theory and heuristic search algorithms, and can better handle complex pipeline layout problems.

[0280] In summary, the small modular layout order optimization method for building mechanical and electrical pipelines proposed in the present invention fully utilizes the advantages of BIM technology in building information modeling and simulation analysis, and subdivides the pipeline system into multiple small modules that can be installed independently, establishes a directed graph network model that reflects the advantages and disadvantages of the layout between each module, and uses the improved A* algorithm to quickly find the overall optimal pipeline layout order under the premise of meeting various constraints. This method can not only greatly improve the efficiency of pipeline layout, but also optimize the energy consumption performance and maintainability of the system, and is suitable for all stages of the building's life cycle.

[0281] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A modular layout order optimization method for mechanical and electrical pipelines on a standard floor of a building, characterized in that , including the following steps: S10. Establish a detailed 3D BIM model of the building standard layer, including structure, space division, and functional division; S20, subdividing the electromechanical pipeline system into multiple small modules; S30, analyzing the spatial relationship and functional dependence between the small modules, and determining the small module pairs that must be arranged in order; S40, for small modules without a necessary arrangement order, establish a directed graph network model, in which nodes represent each small module and edges represent possible arrangement orders; S50, assigning a weight to each edge in the directed graph network model; S60, defining a heuristic function with the necessary arrangement order as a constraint condition, for evaluating the estimated cost from the current arrangement state to the target state; S70, using an improved A* algorithm to search for an optimal layout path in the directed graph network model according to the heuristic function, wherein the optimal layout path represents the precise layout order of all small modules; S80, generating a detailed small module arrangement sequence plan according to the searched optimal path, including the specific location, installation order and connection relationship of each small module; S90, perform collision detection and simulate installation in the BIM model to verify the feasibility of the layout plan. If any problems are found, return to step S50 for local adjustment and optimization until the final optimization plan is obtained.

2. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 1 is characterized in that: The electromechanical pipeline system is subdivided into a plurality of small modules, specifically including: The small modules of the water supply subsystem include at least: risers, cross pipes, branches, and valves; The small modules of the drainage subsystem include at least: sewage pipe, rainwater pipe, and ventilation pipe; The small modules of the HVAC subsystem include at least: air ducts, water pipes, air conditioning units, and air vents; The small modules of the electrical subsystem include at least: strong current cable duct, weak current bridge, distribution box, and switch; The small modules of the fire protection subsystem include at least: fire protection pipes, sprinkler heads, and smoke detectors.

3. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 2 is characterized in that: The small module pairs that must be arranged in order at least include: trunk pipelines take precedence over branch pipelines; gravity flow pipelines take precedence over pressure pipelines; rigid pipelines take precedence over flexible pipelines.

4. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 3 is characterized in that: The weight factors include: spatial distance between small modules; installation difficulty coefficient; potential collision risk; convenience of maintenance and repair; and impact on energy efficiency.

5. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 4 is characterized in that: The heuristic function takes into account the following factors: the number of remaining unarranged small modules; the complexity of the arranged small modules; the overall coordination of the current arrangement plan; and the estimated workload required to complete the arrangement.

6. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 1 is characterized in that: The directed graph network model is specifically expressed as follows: G = (V, E); Among them, V represents the vertex set, which represents each small module; E represents the edge set, which represents the possible arrangement order; For each edge in the network, the weight function is defined as follows: w(e ij )=αd ij +βc ij +γr ij +δm ij +ηe ij ; In the formula, w(e ij ) is the edge e ij The weight of ij is the spatial distance between modules i and j (meters); c ij is the installation difficulty coefficient, with a value range of [0,1]; r ij is the potential collision risk, with a value range of [0,1]; m ij For the convenience of maintenance and repair, the value range is [0,1]; e ij is the influence of energy efficiency, and its value range is [0,1]; α, β, γ, δ, η are weight coefficients, and they satisfy α+β+γ+δ+η=1.

7. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 1 is characterized in that: The heuristic function is specifically expressed as: h(n)=ω1f(n)+ω2g(n)+ω3c(n)+ω4w(n); Where h(n) is the heuristic function value of node n; f(n) is the number of remaining unarranged small modules; g(n) is the complexity of the arranged small modules; c(n) is the overall coordination of the current arrangement scheme; w(n) is the estimated workload required to complete the arrangement; ω1, ω2, ω3, ω4 are weight coefficients, and they satisfy ω1+ω2+ω3+ω4=1.

8. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 7 is characterized in that: When the improved A* algorithm searches for the optimal layout path, the objective function is: F(n)=G(n)+h(n); Among them, G(n) is the actual cost from the starting node to the current node n, and the calculation method is: Among them, P n is the path from the starting node to node n; the goal of the algorithm is to find the path that minimizes F(n).

9. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 8, characterized in that: The steps of verifying the feasibility of the arrangement scheme specifically include: Conduct collision detection on the spatial arrangement of each small module to ensure there is no mutual interference; Simulate the installation sequence of each module to ensure there are no installation obstacles; Check the coordination with the building structure and functional space.

10. The method for optimizing modular layout sequence of mechanical and electrical pipelines in standard floors of a building according to claim 9, characterized in that: If any problem is found, the process returns to step S50 to perform local adjustment and optimization, including: Adjust the weight assigned to each edge in the directed graph network model; Adjust the weight of each sub-function in the heuristic function; Either or both of the above two adjustment methods.

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