Power pipe jacking path optimization method and system based on multi-objective optimization

Abstract

The invention relates to the field of electric power pipe jacking path optimization, and discloses an electric power pipe jacking path optimization method and system based on multi-objective optimization, and the method comprises the steps: constructing a three-dimensional underground space model according to a BIM design drawing, geological radar data, existing pipeline coordinates and obstacle coordinates of an area where an electric power pipe jacking path is located; generating a plurality of alternative power pipe jacking paths in the three-dimensional underground space model based on safety constraint conditions of the power pipe jacking paths; and based on the economical efficiency target, the construction period target, the environmental protection target and the operation and maintenance target, screening the plurality of alternative power pipe jacking paths to obtain an optimized target power pipe jacking path. According to the method, the construction path of the power pipe jacking can consider factors such as construction cost, construction period and maintenance cost, and the optimization effect of the power pipe jacking path is improved.

Description

Technical Field

[0001] The present application relates to the technical field of power pipe jacking path optimization, and more specifically, to a power pipe jacking path optimization method and system based on multi-objective optimization. Background Art

[0002] Electric power pipe jacking construction is a trenchless underground pipeline laying technology. The core principle of electric power pipe jacking construction is to use hydraulic jacking equipment to push prefabricated pipe sections from the starting well into the ground to form an underground pipe corridor. Traditional construction methods usually adopt manual guidance or simple mechanical assisted operation modes. Before construction, the jacking parameters need to be manually calculated based on geological survey data, and the jacking machine posture needs to be adjusted based on experience. The jacking machine head mostly adopts an open or grid extrusion structure, relying on the operator to monitor the soil pressure, correction angle and jacking speed in real time. Especially in complex formations, frequent shutdowns are required to deal with obstacles or adjust the trajectory. During the construction process, the sealing of the pipe joint interface depends on rubber ring waterstop or grouting reinforcement, and the control of surface settlement mainly relies on empirical estimation and subsequent remedial measures. It has limitations such as low accuracy, large efficiency fluctuations, and high safety risks.

[0003] Furthermore, traditional guidance and measurement techniques for power pipe jacking often rely on manual positioning using optical theodolites or laser targets, resulting in data feedback lags and, particularly during long-distance jacking, cumulative errors. Construction requires a large number of personnel for collaborative underground operations, which is labor-intensive and environmentally challenging. Furthermore, when pipe jacking traverses sensitive areas, traditional methods are unable to adequately control disturbances to the surrounding soil, which can easily lead to ground collapse or pipeline displacement, resulting in high maintenance costs. These methods are less adaptable to soft soils, sandy layers, or water-rich formations, often requiring auxiliary dewatering, grouting, or ground reinforcement, further increasing construction time and costs, making them difficult to meet the demands of modern power engineering for efficiency, environmental protection, and intelligence. Currently, methods exist that automatically detect collisions between cable lines and survey data to ensure that cable lines meet safety distance requirements for various underground facilities. However, these methods struggle to balance construction costs, duration, and maintenance costs for power pipe jacking. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for optimizing the path of power pipe jacking based on multi-objective optimization, which solves the technical problem that the construction path of power pipe jacking is difficult to take into account factors such as construction cost, construction period and maintenance cost, and achieves the technical effect that the construction path of power pipe jacking can take into account factors such as construction cost, construction period and maintenance cost.

[0005] An embodiment of the present application provides a method for optimizing a power pipe jacking path based on multi-objective optimization, the method comprising: constructing a three-dimensional underground space model based on a BIM design drawing of the area where the power pipe jacking path is located, geological radar data, existing pipeline coordinates, and obstacle coordinates; generating multiple alternative power pipe jacking paths within the three-dimensional underground space model based on safety constraints of the power pipe jacking path; screening the multiple alternative power pipe jacking paths based on economic goals, construction period goals, environmental protection goals, and operation and maintenance goals to obtain an optimized target power pipe jacking path.

[0006] In a possible implementation method, based on the economic goal, construction period goal, environmental protection goal and operation and maintenance goal, multiple alternative power pipe jacking paths are screened to obtain the optimized target power pipe jacking path, including: obtaining the material cost index, labor cost index, equipment cost index and construction risk index corresponding to the economic goal of each alternative power pipe jacking path, and constructing an economic goal matrix according to the material cost index, labor cost index, equipment cost index and construction risk index corresponding to the economic goal of each alternative power pipe jacking path; obtaining the construction period index, approval period index and emergency period index corresponding to the construction period goal of each alternative power pipe jacking path, and constructing a construction period target matrix according to the construction period index, approval period index and emergency period index corresponding to the construction period goal of each alternative power pipe jacking path; obtaining the carbon emission index and ecological impact index corresponding to the environmental protection goal of each alternative power pipe jacking path, and constructing an environmental protection target matrix according to the carbon emission index and ecological impact index corresponding to the environmental protection goal of each alternative power pipe jacking path; obtaining the inspection index corresponding to the operation and maintenance goal of each alternative power pipe jacking path. The maintenance and operation indicators and expected failure rate indicators are used to construct an operation and maintenance target matrix based on the maintenance and operation indicators and expected failure rate indicators corresponding to the operation and maintenance targets of each alternative power pipe jacking path; through the cost detection unit, the cost control factor is determined based on the economic target matrix and the construction period target matrix. The cost control factor represents the cost of each alternative power pipe jacking path. When the cost control factor is larger, the cost is larger; through the benefit detection unit, the benefit target factor is determined based on the environmental protection target matrix and the operation and maintenance target matrix. The benefit target factor represents the benefit of each alternative power pipe jacking path. When the benefit target factor is larger, the benefit is larger; obtain the project priority control attribute of the area where the power pipe jacking path is located. The project priority control attributes include cost priority and benefit priority; when the project priority control attribute is cost priority, determine the alternative power pipe jacking path corresponding to the minimum cost control factor among all cost control factors as the target power pipe jacking path; when the project priority control attribute is benefit priority, determine the alternative power pipe jacking path corresponding to the maximum benefit target factor among all benefit target factors as the target power pipe jacking path.

[0007] In another possible implementation, the method also includes: obtaining a short-term maintenance cost factor and a long-term maintenance cost factor of the area where the power pipe jacking path is located, the short-term maintenance cost factor representing the average maintenance cost of the power pipelines in the area where the power pipe jacking path is located in the short term, and the long-term maintenance cost factor representing the average maintenance cost of the power pipelines in the area where the power pipe jacking path is located in the long term; determining the product of the cost control factor and the short-term maintenance cost factor as a modified cost control factor; determining the product of the benefit target factor and the long-term maintenance cost factor as a modified benefit target factor; when the project priority control attribute is cost priority, determining the alternative power pipe jacking path corresponding to the minimum modified cost control factor among all modified cost control factors as the target power pipe jacking path; when the project priority control attribute is benefit priority, determining the alternative power pipe jacking path corresponding to the maximum modified benefit target factor among all modified benefit target factors as the target power pipe jacking path.

[0008] In another possible implementation, the method also includes: obtaining the operation and maintenance cycle of the power pipeline in the area where the power jacking path is located, and obtaining the discount rate corresponding to the long-term maintenance cost factor within the operation and maintenance cycle, the discount rate corresponding to the long-term maintenance cost factor representing the corresponding conversion ratio of the power jacking path under long-term maintenance to short-term maintenance; determining the product of the benefit target factor, the long-term maintenance cost factor and the discount rate corresponding to the long-term maintenance cost factor as the modified benefit target factor.

[0009] In another possible implementation, the method also includes: determining multiple segmented operation and maintenance cycles in the area where the power jacking path is located based on the historical operation and maintenance cycles of existing power pipelines in the area where the power jacking path is located, and obtaining the discount rate corresponding to the long-term maintenance cost factor in the multiple segmented operation and maintenance cycles in the area where the power jacking path is located; determining the sum of the product of the long-term maintenance cost factor and the discount rate in each segmented operation and maintenance cycle as the discounted maintenance cost; and determining the product of the benefit target factor and the discounted maintenance cost as the revised benefit target factor.

[0010] In another possible implementation, the method further includes: determining the emergency construction period impact factor of each alternative power pipe jacking path according to the construction risk index of each alternative power pipe jacking path and the construction risk influencing factors of each alternative power pipe jacking path through a construction risk construction period impact model; and constructing a construction period target matrix according to the construction construction period index, approval construction period index, emergency construction period index and emergency construction period impact factor corresponding to the construction period target of each alternative power pipe jacking path.

[0011] In another possible implementation method, the method also includes: determining the construction period carbon emission impact factor of each alternative power pipe jacking path based on the emergency construction period index of each alternative power pipe jacking path and the carbon emission parameters during the construction of each alternative power pipe jacking path through a construction period carbon emission impact model; constructing an environmental protection target matrix based on the carbon emission indicators, construction period carbon emission impact factors and ecological impact indicators corresponding to the environmental protection goals of each alternative power pipe jacking path.

[0012] In another possible implementation, the method also includes: determining the construction period ecological environment impact factor of each alternative power pipe jacking path based on the emergency construction period index of each alternative power pipe jacking path and the ecological environment information of the area where each alternative power pipe jacking path is located through a construction period ecological impact model; constructing an environmental protection target matrix based on the carbon emission index, construction period carbon emission impact factor, ecological impact index and construction period ecological environment impact factor corresponding to the environmental protection target of each alternative power pipe jacking path.

[0013] In another possible implementation, the method further includes: obtaining the residential characteristics of the population in the area where the power pipe jacking path is located, and determining the noise pollution factor of each alternative power pipe jacking path based on the residential characteristics of the population through a noise diffusion model, wherein the noise pollution factor represents the noise pollution level of each alternative power pipe jacking path during construction; and determining the product of the noise pollution factor, the cost control factor, and the short-term maintenance cost factor as a modified cost control factor.

[0014] An embodiment of the present application further provides a power pipe jacking path optimization system based on multi-objective optimization, comprising a unit for executing any of the methods described above.

[0015] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0016] The embodiment of the present application provides a method for optimizing an electric pipe jacking path based on multi-objective optimization, the method comprising: constructing a three-dimensional underground space model based on the BIM design drawing, geological radar data, existing pipeline coordinates and obstacle coordinates of the area where the electric pipe jacking path is located; generating multiple alternative electric pipe jacking paths within the three-dimensional underground space model based on the safety constraints of the electric pipe jacking path; screening multiple alternative electric pipe jacking paths based on economic goals, construction period goals, environmental protection goals and operation and maintenance goals to obtain an optimized target electric pipe jacking path. The electric pipe jacking path optimization method based on multi-objective optimization in the embodiment of the present application can construct an optimized target electric pipe jacking path that meets economic goals, construction period goals, environmental protection goals and operation and maintenance goals on the basis of taking safety into consideration, thereby improving the optimization effects of the economic, construction period, environmental protection and operation and maintenance of the electric pipe jacking path. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0018] Figure 1 A schematic flow chart of a first method for optimizing a power pipe jacking path based on multi-objective optimization provided in an embodiment of the present application;

[0019] Figure 2 A schematic flow chart of a second method for optimizing a power pipe jacking path based on multi-objective optimization provided in an embodiment of the present application;

[0020] Figure 3 A schematic flow chart of a third method for optimizing a power pipe jacking path based on multi-objective optimization provided in an embodiment of the present application;

[0021] Figure 4 A schematic diagram of the logical structure of a power pipe jacking path optimization system based on multi-objective optimization provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0023] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0024] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0025] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0026] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0027] Currently, there are methods to automatically detect collisions between cable lines and survey results and ensure that cable lines meet the safety distance requirements of various underground facilities. However, the construction path of power pipe jacking is difficult to take into account factors such as construction cost, construction period, and maintenance cost.

[0028] Based on the above reasons, an embodiment of the present application provides an electric pipe jacking path optimization method based on multi-objective optimization, the method comprising: constructing a three-dimensional underground space model based on the BIM design drawing, geological radar data, existing pipeline coordinates and obstacle coordinates of the area where the electric pipe jacking path is located; generating multiple alternative electric pipe jacking paths within the three-dimensional underground space model based on the safety constraints of the electric pipe jacking path; screening multiple alternative electric pipe jacking paths based on economic goals, construction period goals, environmental protection goals and operation and maintenance goals to obtain an optimized target electric pipe jacking path. The electric pipe jacking path optimization method based on multi-objective optimization in the embodiment of the present application can construct an optimized target electric pipe jacking path that meets the economic goals, construction period goals, environmental protection goals and operation and maintenance goals on the basis of taking into account safety, thereby improving the optimization effects of the economic, construction period, environmental protection and operation and maintenance of the electric pipe jacking path.

[0029] In some scenarios, a power pipe jacking path optimization method based on multi-objective optimization in an embodiment of the present application can be applied to the path optimization of power pipeline jacking construction, which can improve the optimization effect of power pipeline jacking construction.

[0030] The following describes in detail a method for optimizing a power pipe jacking path based on multi-objective optimization provided in an embodiment of the present application with reference to specific examples.

[0031] Figure 1 The flowchart of the first method for optimizing the power pipe jacking path based on multi-objective optimization provided in the embodiment of the present application is as follows: Figure 1 As shown, the above method includes S110 to S130, and S110 to S130 are described in detail below.

[0032] S110. Construct a three-dimensional underground space model based on the BIM design drawing of the area where the power pipe jacking path is located, geological radar data, existing pipeline coordinates, and obstacle coordinates.

[0033] In the specific implementation of this method, the construction process of the three-dimensional underground space model can be completed based on the spatial registration and fusion technology of multi-source data. Specifically, the BIM design drawing can provide the structured building information model data of the underground space, including the distribution of rock and soil layers, the coordinates of underground structures, and elevation information. The geological radar data can be analyzed through electromagnetic wave reflection signals to supplement geological anomalies, aquifer distribution, and geotechnical parameters. The coordinates of existing pipelines can be imported through the geographic information system coordinate conversion interface, and the coordinates of obstacles can be extracted through on-site mapping or digitization of existing engineering drawings.

[0034] It should be understood that the BIM design drawings, geological radar data, existing pipeline coordinates, and obstacle coordinates can be aligned in the spatial coordinate system through a coordinate conversion module, and a three-dimensional modeling algorithm can be used to generate a composite model that includes geological structure layers, obstacle spatial envelopes, and pipeline topological relationships. Optionally, model construction can be achieved by integrating point cloud data with the BIM model. A three-dimensional geological surface is generated by interpolating the geological radar point cloud data, and Boolean operations are performed on the building components in the BIM model to accurately characterize the underground space characteristics of the construction area.

[0035] S120. Based on the safety constraints of the power pipe jacking path, generate multiple alternative power pipe jacking paths in the three-dimensional underground space model.

[0036] In this implementation, safety constraints can include three core parameters: path curvature, burial depth, and obstacle avoidance. Specifically, the path curvature constraint sets a minimum turning radius threshold based on the mechanical performance of the pipe jacking machine. The burial depth constraint determines the vertical safety distance based on the groundwater level and permafrost distribution. The obstacle avoidance constraint uses a three-dimensional collision detection algorithm to ensure that the path maintains a minimum safe distance from existing pipelines and obstacles.

[0037] When generating alternative paths based on constraints, a path search algorithm can be used to perform a three-dimensional path search, or a genetic algorithm can be used to generate a population of paths that meet multiple constraints. Optionally, the path generation module can set dynamic constraint parameters to automatically enhance obstacle avoidance constraint weights when detecting unusual geological areas. For example, by increasing the path deviation coefficient threshold in quicksand areas, the module can generate a set of alternative paths that meet engineering safety standards.

[0038] S130. Based on the economic goal, the construction period goal, the environmental protection goal, and the operation and maintenance goal, multiple alternative power pipe jacking paths are screened to obtain an optimized target power pipe jacking path.

[0039] Specifically, during the screening process, multiple alternative power pipe jacking paths can be screened based on economic objectives, construction schedule objectives, environmental protection objectives, and operation and maintenance objectives to obtain an optimized target power pipe jacking path. Specifically, a target weight matrix can be set to dynamically adjust the contribution of each objective function based on project priority. For example, the weight coefficient of environmental protection objectives can be increased during construction in urban core areas. Ultimately, the target power pipe jacking path is output to meet the multi-dimensional project requirements.

[0040] The beneficial effects of the above implementation method are that, through deep fusion modeling of multi-source heterogeneous data, the accuracy of underground space representation can be significantly improved, and the path planning deviation rate can be reduced compared with traditional methods; collaborative optimization is achieved by using key indicators such as economy and environmental protection, which can reduce the overall cost of the project.

[0041] The aforementioned implementation also has the beneficial effect of effectively avoiding geological risk areas with a dynamic constraint-based path generation algorithm, significantly reducing the incidence of construction safety accidents. Through the synergistic technology of three-dimensional spatial modeling, multi-constraint path generation, and multi-objective optimization and screening, it effectively addresses the problems of single-objective optimization and insufficient multi-factor coupling analysis in traditional power pipe jacking path planning.

[0042] In some implementations, in the above-mentioned S130, based on economic goals, construction period goals, environmental protection goals and operation and maintenance goals, multiple alternative power pipe jacking paths are screened to obtain an optimized target power pipe jacking path, including S131 to S133. S131 to S133 are described in detail below.

[0043] S131. Obtain the material cost index, labor cost index, equipment cost index, and construction risk index corresponding to the economic target of each alternative power pipe jacking path. Construct an economic target matrix based on the material cost index, labor cost index, equipment cost index, and construction risk index corresponding to the economic target of each alternative power pipe jacking path. Obtain the construction duration index, approval duration index, and emergency duration index corresponding to the construction duration target of each alternative power pipe jacking path. Construct a construction duration target matrix based on the construction duration index, approval duration index, and emergency duration index corresponding to the construction duration target of each alternative power pipe jacking path. Obtain the carbon emission index and ecological impact index corresponding to the environmental protection target of each alternative power pipe jacking path. Construct an environmental protection target matrix based on the carbon emission index and ecological impact index corresponding to the environmental protection target of each alternative power pipe jacking path. Obtain the maintenance and operation index and expected failure rate index corresponding to the operation and maintenance target of each alternative power pipe jacking path. Construct an operation and maintenance target matrix based on the maintenance and operation index and expected failure rate index corresponding to the operation and maintenance target of each alternative power pipe jacking path.

[0044] In the specific implementation of multi-objective optimization screening, the indicator parameters of each alternative path can be structured through a multi-dimensional data acquisition module. Specifically, the construction of the economic target matrix can be achieved based on the bill of quantities decomposition technology, where the material cost indicator can be quantified by pipe type, earthwork volume, and support structure usage. The labor cost indicator is calculated based on the work hour quota and labor unit price model. The equipment cost indicator covers the rental cost of the pipe jacking machine and the energy consumption cost. The construction risk indicator is evaluated using the risk event probability and loss product method. Optionally, the calculation of the construction risk indicator can be combined with geological radar detection data to dynamically correct the pipeline settlement risk in weak strata areas.

[0045] During the construction of the construction period target matrix, a multi-parameter coupling analysis can be implemented through the construction progress simulation engine. Construction period indicators can be based on a jacking speed prediction model, taking into account both pipe segment assembly efficiency and grouting curing time. Approval period indicators can automatically match the time required for planning and approval processes based on the policy and regulatory databases of different administrative regions. Emergency period indicators use Monte Carlo simulation to probabilistically estimate the response cycle for abnormal conditions such as sudden groundwater level changes or equipment failures. During implementation, a period correlation factor matrix can be set to automatically trigger a period overlap correction algorithm when parallel construction sections are detected.

[0046] To construct the environmental target matrix, a life cycle assessment approach can be used to model the environmental impact of the construction process. Carbon emission indicators can be calculated through the full chain of building material production, transportation emissions, and exhaust emissions from construction machinery. Ecological impact indicators utilize remote sensing image interpretation technology to perform a spatial overlay analysis of changes in vegetation coverage and the extent of water disturbance within the construction area. Optionally, the calculation of ecological impact indicators can incorporate a biodiversity index and set impact amplification factors for special ecological protection areas. For example, the ecological impact weight of paths around wetland protection areas can be increased to 1.5 times that of conventional areas.

[0047] In terms of constructing an operation and maintenance target matrix, digital twin technology can be used to achieve full lifecycle performance prediction. Inspection and maintenance indicators can be calculated based on topological characteristics such as the number of path curvature mutation points and the frequency of burial depth changes to determine the inspection difficulty coefficient. The expected failure rate indicator is predicted by combining pipe fatigue life models with soil corrosion rates.

[0048] For example, in a specific implementation, a pipeline stress monitoring data feedback mechanism may be set up to automatically trigger a dynamic update of the operation and maintenance indicators when it is detected that the displacement of the pipe joint exceeds a threshold.

[0049] S132. The cost detection unit determines a cost control factor based on the economic target matrix and the construction period target matrix. The cost control factor represents the cost of each alternative power pipe jacking path. A larger cost control factor indicates a higher cost. The benefit detection unit determines a benefit target factor based on the environmental target matrix and the operation and maintenance target matrix. The benefit target factor represents the benefit of each alternative power pipe jacking path. A larger benefit target factor indicates a higher benefit.

[0050] In this implementation, when conducting cost evaluation, the cost detection unit can determine the cost control factor based on the economic target matrix and the construction period target matrix. The cost control factor represents the cost of each alternative power pipe jacking path. The larger the cost control factor, the greater the cost. The cost of the power pipe jacking path is evaluated by the cost control factor.

[0051] In this implementation, when conducting benefit evaluation, the benefit detection unit can determine the benefit target factor based on the environmental protection target matrix and the operation and maintenance target matrix. The benefit target factor represents the benefit size of each alternative power pipe jacking path. The larger the benefit target factor, the greater the benefit. The benefit of the power pipe jacking path is evaluated through the benefit target factor.

[0052] It should be noted that the cost detection unit and the benefit detection unit can be deep learning units based on neural networks. The cost detection unit can be trained through the labeled economic target matrix, construction period target matrix and cost control factors; the benefit detection unit can be trained through the labeled environmental protection target matrix, operation and maintenance target matrix and benefit target factors.

[0053] S133. Obtain the project priority control attribute for the area where the power pipe jacking path is located. The project priority control attributes include cost priority and benefit priority. When the project priority control attribute is cost priority, determine the alternative power pipe jacking path corresponding to the minimum cost control factor among all cost control factors as the target power pipe jacking path. When the project priority control attribute is benefit priority, determine the alternative power pipe jacking path corresponding to the maximum benefit target factor among all benefit target factors as the target power pipe jacking path.

[0054] During the path decision-making phase, adaptive strategy selection can be achieved through the priority response module. When the project priority control attribute is cost-first, the alternative power pipe jacking path corresponding to the minimum cost control factor among all cost control factors is determined as the target power pipe jacking path, and the power pipeline jacking construction is carried out according to the target power pipe jacking path with the lowest cost.

[0055] Similarly, in the path decision stage, when the project priority control attribute is benefit priority, the alternative power pipe jacking path corresponding to the maximum benefit target factor among all benefit target factors is determined as the target power pipe jacking path, so that the power pipeline pipe jacking construction is carried out according to the target power pipe jacking path with the greatest benefit.

[0056] The beneficial effect of the above implementation method is that, by establishing a multi-dimensional target matrix system, the full digital expression of engineering parameters is achieved, significantly improving the objectivity and systematicness of path evaluation; through the comprehensive application of optimization algorithms, it is ensured that the final selected path not only meets the requirements of engineering economy but also conforms to the strategic goal of sustainable development, providing scientific decision-making support for complex pipe jacking construction.

[0057] In some implementations, the above method further includes S134 to S135, and S134 to S135 are described in detail below.

[0058] S134. Obtain a short-term maintenance cost factor and a long-term maintenance cost factor for the area where the power pipe jacking path is located. The short-term maintenance cost factor represents the average maintenance cost of the power pipelines in the area where the power pipe jacking path is located in the short term. The long-term maintenance cost factor represents the average maintenance cost of the power pipelines in the area where the power pipe jacking path is located in the long term.

[0059] In specific implementation, the maintenance cost analysis module can be used to dynamically evaluate the full life cycle maintenance cost of the power pipe jacking path.

[0060] For example, the short-term maintenance cost factor can be quantitatively calculated based on construction quality inspection data and geological stability parameters, where the construction quality inspection data may include indicators such as the density of pipe joints and the uniformity of the grouting layer, and the geological stability parameters can be obtained through real-time monitoring of soil moisture content and lateral pressure coefficient.

[0061] For example, the long-term maintenance cost factor can be calculated by combining the soil corrosion rate model and the pipeline stress distribution map, where the soil corrosion rate model can integrate multi-dimensional environmental parameters such as soil resistivity, pH value and chloride ion concentration.

[0062] Optionally, the calculation of the short-term maintenance cost factor can incorporate construction monitoring data, such as jacking trajectory deviation values acquired through distributed fiber optic sensing technology. When the trajectory deviation exceeds a preset threshold, the dynamic adjustment of the maintenance cost factor can be triggered. The long-term maintenance cost factor can also incorporate climate forecast data to predict pipeline deformation under freeze-thaw cycles, thereby more accurately reflecting the impact of different regional climate characteristics on pipeline durability.

[0063] S135. Determine the product of the cost control factor and the short-term maintenance cost factor as the revised cost control factor. Determine the product of the benefit target factor and the long-term maintenance cost factor as the revised benefit target factor. When the project priority control attribute is cost priority, determine the alternative power pipe jacking path corresponding to the minimum revised cost control factor among all revised cost control factors as the target power pipe jacking path. When the project priority control attribute is benefit priority, determine the alternative power pipe jacking path corresponding to the maximum revised benefit target factor among all revised benefit target factors as the target power pipe jacking path.

[0064] During the cost control factor correction process, the product of the cost control factor and the short-term maintenance cost factor can be determined as the corrected cost control factor. It should be noted that the calculation of the corrected cost control factor can also include a construction quality weighting factor, automatically increasing the contribution of the short-term maintenance cost factor when high-risk geological sections are detected. For example, when constructing in soft soil areas, the soil rheological model can be used to predict pipe segment settlement, thereby dynamically adjusting the proportional parameter of the short-term maintenance cost factor in the product calculation.

[0065] To modify the benefit target factor, the product of the benefit target factor and the long-term maintenance cost factor can be determined as the modified benefit target factor. It should be noted that the long-term maintenance cost and environmental benefits can be further coupled through a time decay function. The generation of the modified benefit target factor can be combined with the pipeline service life prediction model, where the pipeline service life prediction can be iteratively calculated based on pipe fatigue life test data and stress concentration factors.

[0066] In specific implementation, when it is detected that the path passes through a highly corrosive soil area, the maintenance cost overlay module of the anti-corrosion coating can also be automatically activated to achieve dynamic correction of the long-term maintenance cost factor.

[0067] When the project priority control attribute is cost priority, the alternative power pipe jacking path corresponding to the minimum modified cost control factor among all modified cost control factors can be determined as the target power pipe jacking path to reduce pipeline construction costs. When the project priority control attribute is benefit priority, the alternative power pipe jacking path corresponding to the maximum modified benefit target factor among all modified benefit target factors can be determined as the target power pipe jacking path to improve pipeline construction benefits.

[0068] The beneficial effect of the above implementation method is that by introducing a two-dimensional evaluation mechanism of short-term maintenance costs and long-term maintenance costs, the full life cycle consideration dimension of path optimization decision-making is effectively improved; a dynamic correction algorithm is used to achieve the organic unity of construction period costs and operation and maintenance period costs, so that the optimized path not only meets the current economic requirements but also has long-term service reliability.

[0069] In some implementations, the above method further includes S136 to S137, and S136 to S137 are described in detail below.

[0070] S136. Obtain the operation and maintenance cycle of the power pipeline in the area where the power pipe jacking path is located, and obtain the discount rate corresponding to the long-term maintenance cost factor within the operation and maintenance cycle. The discount rate corresponding to the long-term maintenance cost factor represents the corresponding conversion ratio of the power pipe jacking path under long-term maintenance to short-term maintenance.

[0071] In practice, the full lifecycle cost analysis module can be used to convert long-term maintenance costs into time-value. Specifically, the operation and maintenance cycle can be calculated based on the designed service life of the power pipeline and the average overhaul interval from historical operation and maintenance data.

[0072] It should be noted that the discount rate of the long-term maintenance cost factor can be dynamically calculated using the cash flow discounting model, where the discount rate can be determined based on the current financial market benchmark interest rate and superimposed with the risk premium parameters unique to power facility operation and maintenance.

[0073] Optionally, the discount rate calculation can be integrated into the O&M risk assessment module. By analyzing dynamic parameters such as the frequency of geological activity in the path region and trends in soil erosion rates, the base discount rate can be periodically adjusted. For example, if a path is detected crossing a seismically active zone, a risk adjustment factor can be automatically added to increase the discount rate, thereby more accurately reflecting the time-value decay characteristics of long-term maintenance costs.

[0074] In specific implementations, a dynamic discount rate adjustment mechanism can be implemented. When pipe performance degradation is detected exceeding expectations, real-time data collected by material performance monitoring sensors can trigger a dynamic update of the discount rate. For example, in a routing solution using new composite pipes, the material durability parameters in the discount rate calculation model can be automatically optimized based on the measured pipe wall thickness attenuation rate.

[0075] S137. Determine the product of the benefit target factor, the long-term maintenance cost factor, and the discount rate corresponding to the long-term maintenance cost factor as the modified benefit target factor.

[0076] To optimize benefit assessment, a benefit decay model can be established by combining the temporal distribution characteristics of operation and maintenance costs. By using the product of the long-term maintenance cost factor and the discount rate as the time-weighted coefficient, future annual maintenance expenditures can be converted into equivalent costs at the current decision point. This approach allows for a comparative analysis of the temporal and spatial distribution characteristics of environmental benefits and operation and maintenance costs within a unified dimension.

[0077] The beneficial effect of the above implementation method is that, by introducing a time-value conversion mechanism, it effectively solves the dimensional difference problem between long-term maintenance costs and short-term benefit evaluation; the adoption of a dynamic discount rate adjustment strategy can reflect the impact of changes in the engineering environment on operation and maintenance costs in real time, and can significantly improve the sophistication of cost control throughout the entire life cycle.

[0078] In some implementations, the above method further includes S138 to S139, and S138 to S139 are described in detail below.

[0079] S138. Determine multiple segmented operation and maintenance cycles for the area where the power pipe jacking path is located based on historical operation and maintenance cycles of existing power pipelines in the area where the power pipe jacking path is located, and obtain discount rates corresponding to long-term maintenance cost factors within the multiple segmented operation and maintenance cycles for the area where the power pipe jacking path is located.

[0080] In practice, a segmented lifecycle assessment model can be used to conduct a detailed analysis of the operation and maintenance costs of power pipe jacking routes. Specifically, the segmented operation and maintenance cycles can be divided based on cluster analysis results of historical operation and maintenance data, using a time series segmentation algorithm to identify high-frequency maintenance intervals and stable operation intervals.

[0081] For example, the K-means clustering method can be used to perform pattern recognition on the maintenance interval data of historical pipelines, and the operation and maintenance cycle can be divided into typical stages such as the initial commissioning period, the stable operation period, and the aging maintenance period, each of which corresponds to different maintenance cost characteristics.

[0082] Optionally, the segmented O&M cycle can be dynamically adjusted based on pipeline material degradation curves. For pipelines made of high-strength polyethylene, a segmented duration prediction model can be developed based on material creep test data; for metal pipes, segmentation criteria can be established based on electrochemical corrosion rates. In practical implementation, a convolutional neural network can be used to extract features from pipeline wall thickness monitoring data to automatically generate a segmented cycle plan that aligns with actual operating conditions.

[0083] Different economic models can be set up for different operation and maintenance phases in the discount rate calculation process. The discount rate during the initial commissioning period can be dynamically adjusted based on construction quality acceptance data. For example, if the interface welding pass rate falls below a threshold, an upward adjustment mechanism for the discount rate can be triggered. The discount rate during the stable operation period is periodically adjusted based on regional grid load fluctuation data. Precise regulation is achieved by establishing a correlation matrix between load fluctuations and maintenance costs.

[0084] S139. Determine the sum of the product of the long-term maintenance cost factor and the discount rate in each segmented operation and maintenance cycle as the discounted maintenance cost. Determine the product of the benefit target factor and the discounted maintenance cost as the revised benefit target factor.

[0085] To calculate discounted maintenance costs, a phased accumulation method can be used to integrate costs across multiple periods. Specifically, a time-weighted coefficient matrix can be set to weight the sum of the products within each segmented period according to the proportion of operation and maintenance time. For example, during the aging maintenance period, the time-weighted coefficient can be increased to enhance the impact of this phase's costs on the overall assessment. Furthermore, an inflation adjustment factor can be introduced to dynamically convert historical cost data to purchasing power parity.

[0086] During the generation of modified benefit target factors, a multidimensional benefit correlation map can be established. Specifically, when determining the sum of the products of the long-term maintenance cost factor and the discount rate within each segmented operation and maintenance cycle, the product operation can be decomposed into a dual optimization of the spatial and temporal dimensions: in the spatial dimension, sensitive facility distribution data around the route is obtained through the GIS system, and in the temporal dimension, a benefit time distribution curve is generated based on the segmented maintenance plan.

[0087] The beneficial effects of this implementation approach include accurately capturing the fluctuations in maintenance costs throughout the pipeline's lifecycle through a segmented O&M cycle division mechanism; effectively reflecting the changing economic characteristics of different O&M phases through the use of differentiated discount rate calculation models; and establishing a multi-dimensional weighted accumulation algorithm that aligns the time-value conversion of long-term maintenance costs more closely with engineering economics, significantly improving the spatiotemporal adaptability of path optimization decisions. Through the synergy of refined, phased evaluation and a dynamic adjustment mechanism, optimized decision-making support is provided for power pipe jacking projects, balancing short-term benefits with long-term sustainability.

[0088] Figure 2 The flowchart of the second method for optimizing the power pipe jacking path based on multi-objective optimization provided in the embodiment of the present application is as follows: Figure 2 As shown, the above method further includes S210 to S220, and S210 to S220 are described in detail below.

[0089] S210. Determine the emergency construction period impact factor of each alternative power pipe jacking path through the construction risk construction period impact model according to the construction risk index of each alternative power pipe jacking path and the construction risk impact factor of each alternative power pipe jacking path.

[0090] In practice, a risk-duration coupling analysis module can be used to dynamically correlate construction risks with construction period indicators. Specifically, the construction risk and construction period impact model can be a deep learning model based on a neural network, and construction risk indicators can include parameters such as geological condition risk factor, equipment failure risk factor, and operator safety risk factor.

[0091] In this implementation, when the emergency construction period impact factor is determined by the construction risk construction period impact model, the calculation of the emergency construction period impact factor can be performed in combination with the construction risk index of each alternative power pipe jacking path and the construction risk impact factor of each alternative power pipe jacking path.

[0092] Optionally, real-time monitoring data streams can be incorporated into the determination of construction risk influencing factors. For example, multi-parameter sensors installed on the pipe jacking head can collect data such as formation pressure changes and tool wear in real time to dynamically adjust risk impact weights. For areas with fluctuating groundwater levels, a nonlinear correlation model can be established between hydrogeological parameters and the emergency construction period. When the permeability coefficient exceeds a threshold, the emergency response mechanism can be automatically triggered.

[0093] S220: Construct a construction period target matrix according to the construction period indicator, approval period indicator, emergency period indicator, and emergency period influencing factor corresponding to the construction period target of each alternative power pipe jacking path.

[0094] In the process of constructing the construction period target matrix, multi-source data integration can be achieved through four-dimensional indicator fusion technology. The emergency construction period indicators can be dynamically weighted according to the emergency construction period risk influencing factors. For example, the emergency buffer time can be automatically increased when a high-risk construction section is detected. The construction period indicators, approval period indicators, emergency period indicators and emergency period influencing factors are spliced together to obtain the construction period target matrix.

[0095] It's important to note that a dynamic adjustment mechanism can be implemented to optimize matrix construction. When construction progress deviations exceed a preset threshold, real-time updates to the matrix parameters are automatically triggered. For example, a BIM progress simulation engine can be used to compare and analyze actual construction progress against planned progress. Machine learning algorithms can then dynamically optimize the weighting of various indicators to ensure the target matrix always reflects the latest project status.

[0096] The beneficial effects of the above implementation method are: by establishing a quantitative correlation model between risks and construction machinery, the accuracy and reliability of construction period prediction can be significantly improved; by adopting a multi-dimensional data fusion mechanism, the coordinated optimization of approval processes, construction progress and emergency plans can be achieved; after constructing a dynamically adjusted construction period target matrix, it can effectively deal with the uncertainty factors in complex underground projects and provide a decision-making basis that takes into account both efficiency and safety for the optimization of power pipe jacking routes.

[0097] In some implementations, the above method further includes S230 to S240, and S230 to S240 are described in detail below.

[0098] S230. Determine the construction period carbon emission impact factor of each alternative power pipe jacking path through a construction period carbon emission impact model, according to the emergency construction period index of each alternative power pipe jacking path and the carbon emission parameters during the construction of each alternative power pipe jacking path.

[0099] In practice, a construction period carbon emission impact model can be used to dynamically couple construction progress with environmental indicators. Specifically, this model can be constructed using a deep learning-based model, breaking down emergency construction period indicators into parameters such as equipment standby time, backup power activation frequency, and the intensity of rush measures. Carbon emission parameters can be derived by integrating fuel consumption data for construction machinery, carbon emission factors for power supply, and energy consumption curves for emergency lighting systems. Through data fusion models, a quantitative relationship between extended construction periods and increased carbon emissions can be established.

[0100] Alternatively, the calculation of carbon emission parameters can incorporate a real-time energy consumption monitoring system. For example, IoT sensors can collect instantaneous power data from the pipe jacking machine's hydraulic system and dynamically adjust the carbon emission coefficient based on the equipment load characteristic curve under different geological conditions. For emergency plans involving nighttime construction, a correlation model can be established between light intensity and auxiliary equipment energy consumption. When an increase in lighting duration is detected, a gradient adjustment mechanism for carbon emission parameters can be automatically triggered.

[0101] S240. Construct an environmental protection target matrix based on the carbon emission indicators, construction period carbon emission impact factors, and ecological impact indicators corresponding to the environmental protection targets of each alternative power pipe jacking path.

[0102] In this implementation, the carbon emission indicators, construction period carbon emission impact factors and ecological impact indicators corresponding to the environmental protection goals of each alternative power pipe jacking path can be directly spliced to obtain a constructed environmental protection target matrix.

[0103] As an optimization, during the construction of the environmental target matrix, a three-dimensional weighted indicator algorithm can be used to achieve a comprehensive assessment of multi-source environmental impacts. The baseline value of the carbon emission indicator can be initialized based on the national emission standards for construction machinery. The construction period carbon emission impact factor serves as a dynamic adjustment coefficient, increasing or decreasing the baseline value based on actual construction progress deviations. The calculation of ecological impact indicators can be combined with satellite remote sensing vegetation index change data to spatially model ecological degradation caused by interference factors such as construction vibration and noise.

[0104] The beneficial effects of the above implementation method are: by establishing a quantitative correlation model between construction period and carbon emissions, the full-factor coverage capability of environmental assessment is significantly improved; a dynamic weight allocation mechanism is adopted to realize the intelligent adaptation of construction progress fluctuations and environmental protection indicators, and enhance the accuracy of assessment under complex working conditions; after constructing a multi-dimensional integrated environmental protection target matrix, it can provide a decision-making basis for the optimization of power pipe jacking routes that takes into account both construction efficiency and ecological protection, and effectively promote the promotion and application of green construction technology.

[0105] In some implementations, the above method further includes S250 to S260, and S250 to S260 are described in detail below.

[0106] S250. Determine the construction period ecological environment impact factor of each alternative power pipe jacking path through a construction period ecological impact model, according to the emergency construction period index of each alternative power pipe jacking path and the ecological environment information of the area where each alternative power pipe jacking path is located.

[0107] In practice, a construction period ecological impact model can be used to achieve dynamic coordination between construction progress and ecological protection. Specifically, the construction period ecological impact model can be a deep learning model that calculates emergency construction period indicators and ecological and environmental information for the area where each alternative power pipe jacking path is located to obtain the construction period ecological and environmental impact factor for each alternative power pipe jacking path.

[0108] For example, the acquisition of ecological and environmental information can integrate vegetation coverage layers, water system buffer data and wildlife habitat heat maps in the geographic information system, and generate a three-dimensional ecological impact assessment grid through spatial interpolation algorithms.

[0109] Alternatively, high-precision remote sensing image interpretation technology can be used to process ecological and environmental information, identifying ecosystem types and grading their vulnerability within a 50-meter buffer zone around the construction path. For emergency plans involving nighttime construction, acoustic sensor networks can be used to collect construction noise propagation data and establish a quantitative relationship model between sound pressure level and the degree of disturbance to biological activity.

[0110] S260. Construct an environmental protection target matrix based on the carbon emission indicators, construction period carbon emission impact factors, ecological impact indicators, and construction period ecological environment impact factors corresponding to the environmental protection targets of each alternative power pipe jacking path.

[0111] According to the carbon emission indicators, construction period carbon emission impact factors, ecological impact indicators and construction period ecological environment impact factors corresponding to the environmental protection goals of each alternative power pipe jacking path, the carbon emission indicators, construction period carbon emission impact factors, ecological impact indicators and construction period ecological environment impact factors corresponding to the environmental protection goals of each alternative power pipe jacking path can be spliced to realize the construction of the environmental protection goal matrix.

[0112] A dynamic weighting mechanism can be used to calculate the ecological and environmental impact factors during the construction period. Specifically, seasonal adjustment parameters can be set to automatically increase the weight of ecological impact factors during the bird breeding season or plant growing season.

[0113] The beneficial effect of the above implementation method is that by establishing a quantitative correlation model between construction period and ecological protection, the temporal and spatial coverage capability of environmental assessment can be significantly improved; after constructing an environmental protection target matrix that integrates multi-source data, it can provide a scientific decision-making basis for the optimization of power pipe jacking routes that takes into account both construction efficiency and ecological sustainability.

[0114] Figure 3 The flowchart of the third method for optimizing the power pipe jacking path based on multi-objective optimization provided in the embodiment of the present application is as follows: Figure 3 As shown, the above method further includes S310 to S320, and S310 to S320 are described in detail below.

[0115] S310. Obtain residential characteristics of the area where the power pipe jacking path is located, and determine the noise pollution factor of each alternative power pipe jacking path based on the residential characteristics using a noise diffusion model. The noise pollution factor represents the noise pollution level of each alternative power pipe jacking path during construction.

[0116] In practice, a social factor integration module can be used to dynamically correlate residential characteristics with project costs. Specifically, residential characteristics can be combined with building distribution data from an urban planning database, and geo-fencing technology can be used to identify sensitive locations such as high-density residential areas, schools, and hospitals within a 200-meter buffer zone along the construction path.

[0117] In this implementation, the noise pollution factor can be calculated using a noise diffusion model based on the acoustic propagation model, combined with the noise spectrum characteristics of the pipe jacking machine model and the noise barrier setting plan to perform a spatial simulation of the equivalent sound level during the day and at night.

[0118] Optionally, analysis of residential characteristics can incorporate mobile communication signaling data, using base station positioning to generate heat maps of actual population distribution at different time periods. For example, if a path is detected crossing a mixed commercial and residential area, dynamic weighting can be set for each time period, increasing the noise pollution factor calculation weight during nighttime construction to 1.3 times that of daytime. For particularly sensitive buildings, the secondary noise impact caused by construction vibration can be calculated using a building structure vibration response model.

[0119] S320: Determine the product of the noise pollution factor, the cost control factor, and the short-term maintenance cost factor as a modified cost control factor.

[0120] After obtaining the noise pollution factor, cost control factor and short-term maintenance cost factor, the product of the noise pollution factor, cost control factor and short-term maintenance cost factor can be determined as a modified cost control factor to realize the impact of the noise pollution factor on the pipe jacking construction path.

[0121] The beneficial effects of the above implementation method are that, by integrating social residential characteristic parameters, the integrity of the social dimension of project cost assessment is significantly improved; a dynamic correlation model between noise pollution and short-term maintenance costs is established, and the impact of social coordination costs on project economics is effectively quantified.

[0122] The beneficial effect of the above implementation method is that after adopting the correction algorithm of multi-source data fusion, it can provide a decision-making basis for path optimization that takes into account both engineering benefits and social responsibility, and promote the harmonious development of engineering construction and community environment.

[0123] An embodiment of the present application further provides a power pipe jacking path optimization system based on multi-objective optimization, comprising a unit for executing any of the methods described above.

[0124] Figure 4 A schematic diagram of the logical structure of a power pipe jacking path optimization system based on multi-objective optimization provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the system 1 of this embodiment includes a processing unit 11, a storage unit 12, and a transceiver unit 13. The processing unit 11 is used to process data, the storage unit 12 is used to store data, and the transceiver unit 13 is used to send and receive data. The processing unit 11, the storage unit 12, and the transceiver unit 13 cooperate with each other to implement the above method. The beneficial effects of the embodiment of the present application have been described in the above method and will not be repeated here.

[0125] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0127] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process of the above-mentioned method embodiment by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, mobile hard drive, magnetic disk, or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0128] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0129] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0130] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0132] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for optimizing the path of electric pipe jacking based on multi-objective optimization, characterized in that: The method comprises: Construct a 3D underground space model based on the BIM design drawings, geological radar data, existing pipeline coordinates, and obstacle coordinates of the area where the power pipe jacking path is located; Based on the safety constraints of the power pipe jacking path, multiple alternative power pipe jacking paths are generated in the three-dimensional underground space model; Based on economic goals, construction period goals, environmental protection goals and operation and maintenance goals, multiple alternative power pipe jacking paths are screened to obtain the optimized target power pipe jacking path.

2. The method according to claim 1, wherein Based on economic goals, construction period goals, environmental protection goals, and operation and maintenance goals, multiple alternative power pipe jacking paths were screened to obtain the optimized target power pipe jacking path, including: Obtain the material cost index, labor cost index, equipment cost index and construction risk index corresponding to the economic target of each alternative power pipe jacking path, and construct an economic target matrix based on the material cost index, labor cost index, equipment cost index and construction risk index corresponding to the economic target of each alternative power pipe jacking path; obtain the construction period index, approval period index and emergency period index corresponding to the construction period target of each alternative power pipe jacking path, and construct a construction period target matrix based on the construction period index, approval period index and emergency period index corresponding to the construction period target of each alternative power pipe jacking path; obtain the carbon emission index and ecological impact index corresponding to the environmental protection target of each alternative power pipe jacking path, and construct an environmental protection target matrix based on the carbon emission index and ecological impact index corresponding to the environmental protection target of each alternative power pipe jacking path; obtain the maintenance and operation index and expected failure rate index corresponding to the operation and maintenance target of each alternative power pipe jacking path, and construct an operation and maintenance target matrix based on the maintenance and operation index and expected failure rate index corresponding to the operation and maintenance target of each alternative power pipe jacking path; The cost detection unit determines the cost control factor based on the economic target matrix and the construction period target matrix. The cost control factor represents the cost of each alternative power pipe jacking path. The larger the cost control factor, the greater the cost. The benefit detection unit determines the benefit target factor based on the environmental protection target matrix and the operation and maintenance target matrix. The benefit target factor represents the benefit of each alternative power pipe jacking path. The larger the benefit target factor, the greater the benefit. Obtain the project priority control attribute of the area where the power pipe jacking path is located. The project priority control attributes include cost priority and benefit priority. When the project priority control attribute is cost priority, determine the alternative power pipe jacking path corresponding to the minimum cost control factor among all cost control factors as the target power pipe jacking path. When the project priority control attribute is benefit priority, determine the alternative power pipe jacking path corresponding to the maximum benefit target factor among all benefit target factors as the target power pipe jacking path.

3. The method according to claim 2, wherein The method further comprises: Obtaining a short-term maintenance cost factor and a long-term maintenance cost factor for the area where the power pipe jacking path is located. The short-term maintenance cost factor represents the average short-term maintenance cost of the power pipelines in the area where the power pipe jacking path is located. The long-term maintenance cost factor represents the average long-term maintenance cost of the power pipelines in the area where the power pipe jacking path is located. Determine the product of the cost control factor and the short-term maintenance cost factor as the modified cost control factor; determine the product of the benefit target factor and the long-term maintenance cost factor as the modified benefit target factor; when the project priority control attribute is cost priority, determine the alternative power pipe jacking path corresponding to the minimum modified cost control factor among all modified cost control factors as the target power pipe jacking path; when the project priority control attribute is benefit priority, determine the alternative power pipe jacking path corresponding to the maximum modified benefit target factor among all modified benefit target factors as the target power pipe jacking path.

4. The method according to claim 3, wherein The method further comprises: Obtain the operation and maintenance cycle of the power pipelines in the area where the power pipe jacking path is located, and obtain the discount rate corresponding to the long-term maintenance cost factor within the operation and maintenance cycle. The discount rate corresponding to the long-term maintenance cost factor represents the conversion ratio of the power pipe jacking path from long-term maintenance to short-term maintenance. Determine the product of the benefit target factor, the long-term maintenance cost factor and the discount rate corresponding to the long-term maintenance cost factor as the revised benefit target factor.

5. The method according to claim 4, wherein The method further comprises: Determine multiple segmented operation and maintenance cycles for the area where the power pipe jacking path is located based on the historical operation and maintenance cycles of existing power pipelines in the area where the power pipe jacking path is located, and obtain the discount rates corresponding to the long-term maintenance cost factors within the multiple segmented operation and maintenance cycles in the area where the power pipe jacking path is located; Determine the sum of the product of the long-term maintenance cost factor and the discount rate in each segmented operation and maintenance cycle as the discounted maintenance cost; determine the product of the benefit target factor and the discounted maintenance cost as the revised benefit target factor.

6. The method according to claim 5, wherein The method further comprises: Through the construction risk and construction period impact model, according to the construction risk index and construction risk influencing factors of each alternative power pipe jacking path, the emergency construction period impact factor of each alternative power pipe jacking path is determined; A construction period target matrix is constructed based on the construction period indicators, approval period indicators, emergency period indicators and emergency period influencing factors corresponding to the construction period targets of each alternative power pipe jacking path.

7. The method according to claim 6, wherein The method further comprises: Through the construction period carbon emission impact model, according to the emergency construction period index of each alternative power pipe jacking path and the carbon emission parameters during the construction of each alternative power pipe jacking path, the construction period carbon emission impact factor of each alternative power pipe jacking path is determined; An environmental protection target matrix is constructed based on the carbon emission indicators, construction period carbon emission impact factors and ecological impact indicators corresponding to the environmental protection goals of each alternative power pipe jacking path.

8. The method according to claim 7, wherein The method further comprises: Through the construction period ecological impact model, according to the emergency construction period index of each alternative power pipe jacking path and the ecological environment information of the area where each alternative power pipe jacking path is located, the construction period ecological environment impact factor of each alternative power pipe jacking path is determined; An environmental protection target matrix is constructed based on the carbon emission indicators, construction period carbon emission impact factors, ecological impact indicators and construction period ecological environment impact factors corresponding to the environmental protection targets of each alternative power pipe jacking path.

9. The method according to claim 8, wherein The method further comprises: Obtain the residential characteristics of the area where the power pipe jacking path is located. Using a noise diffusion model, determine the noise pollution factor of each alternative power pipe jacking path based on these characteristics. The noise pollution factor represents the noise pollution level of each alternative power pipe jacking path during construction. The product of the noise pollution factor, the cost control factor and the short-term maintenance cost factor is determined as the modified cost control factor.

10. A multi-objective optimization-based power pipe jacking path optimization system, characterized in that: Comprising means for performing the method according to any one of claims 1 to 9.

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