Garden landscape bim model construction method and system based on data fusion

Abstract

The present application relates to the technical field of dynamic modeling, in particular to a kind of garden landscape BIM model construction method and system based on data fusion.Utilize single-point pressure sensor to collect transient pressure decay sequence after valve, calculate global flow resistance multiplier;Combined with the geometric parameters of pipe network in BIM model, generate each pipe segment resistance correction coefficient through non-uniform weight distribution model based on pipe diameter;Further, calculate the residual pressure of each dripper end through forward hydraulic simulation, and generate three-dimensional critical irrigation elevation surface, realize the low-cost, high-precision differentiation of effective irrigation area and water shortage risk area in BIM model.

Description

Technical Field

[0001] This invention relates to the field of dynamic modeling technology, specifically to a method and system for constructing a landscape BIM model based on data fusion. Background Technology

[0002] Micro-irrigation systems are the infrastructure for maintaining plant survival in modern vertical greening projects. In actual operation, the pipe network is prone to physical degradation (clogging) due to biofilm growth or the deposition of microparticles. This clogging typically exhibits non-uniform spatial distribution: due to the fluid boundary layer effect, the small terminal branch pipes are extremely sensitive to the deposit layer, and their flow resistance increases much more significantly than that of the large main pipes. This non-uniformity leads to a "gravity amplification effect," meaning that even when the pump station outlet pressure reading remains normal, plants located at higher elevations or at the end of the pipe network may have already experienced water shortages due to excessive head loss in local pipe sections.

[0003] Existing BIM-based operation and maintenance systems for landscaping typically only record the geometric dimensions and static design parameters of pipelines, lacking the ability to perceive the dynamic physical state within the pipeline network. In terms of monitoring methods, traditional solutions often rely on pressure sensors installed at pump stations or at the bottom of main pipelines. While this single-point monitoring data is inexpensive, it only reflects macroscopic pressure and cannot identify the aforementioned hidden faults such as "main pipeline unobstructed, terminal blockage." While a distributed sensor network can provide precise location, its construction and maintenance costs are extremely high, making it unsuitable for large-scale landscaping projects. Therefore, current technology lacks a method that can utilize limited single-point monitoring data while simultaneously combining pipeline network topology to analyze the blockage situation of landscaping pipelines in the BIM model at low cost, reconstruct non-uniform physical degradation, and thus effectively distinguish water shortage risk areas in the landscaping. Summary of the Invention

[0004] To address the technical challenge of existing technologies that struggle to utilize limited single-point monitoring data while simultaneously incorporating pipeline topology to cost-effectively analyze the blockage status of garden landscape pipelines within BIM models, reconstruct non-uniform physical degradation, and effectively differentiate water shortage risk zones in garden landscapes, this invention aims to provide a data fusion-based method and system for constructing garden landscape BIM models. The specific technical solution adopted is as follows: This invention proposes a method for constructing a BIM model of a garden landscape based on data fusion, the method comprising: Obtain the geometric inner diameter, pipe length, rated flow rate, and corresponding source working pressure and pressure decay sequence of each pipe segment in the garden landscape pipeline network; wherein each pipe segment corresponds to two dripper nodes on both sides; based on the time-series decay of the source working pressure and pressure decay sequence, determine the global flow resistance ratio; Based on the reference deviation of the geometric inner diameter, the pipe diameter blockage weight of each pipe segment is obtained; the theoretical flow resistance per unit length of each pipe segment is weighted and fused according to the pipe diameter blockage weight, and the energy conservation correction factor is calculated; based on the global flow resistance ratio and the energy conservation correction factor, the resistance correction coefficient of each pipe segment is generated by weighted scaling using the pipe diameter blockage weight; based on the pressure data and resistance correction coefficient of each pipe segment, the terminal residual pressure of each dripper node is calculated through forward hydraulic simulation. The risk zones of water shortage in the garden landscape pipeline network are distinguished based on the residual pressure at the end of each dripper node.

[0005] Furthermore, the method for obtaining the source working pressure includes: The arithmetic mean of all measured pressure values ​​within a preset time period prior to the pressure decay sequence is taken as the source working pressure.

[0006] Furthermore, the global flow resistance ratio calculation method includes: Based on the difference between the measured pressure value and the preset static steady pressure at each moment in the pressure decay sequence, the instantaneous drive difference at each moment is determined; based on the difference between the source working pressure and the preset static steady pressure, the initial effective pressure difference is determined; a fitting model is constructed based on the instantaneous drive difference and the initial effective pressure difference, the fitting model including: obtaining the instantaneous drive difference at each moment based on the product between the initial effective pressure difference and the exponential decay factor; the exponential decay factor is negatively correlated with the acquisition time and positively correlated with the pressure decay time constant; regression fitting is performed on the fitting model based on the measured pressure value at each moment in the pressure decay sequence to obtain the pressure decay time constant, and the pressure decay time constant is standardized to obtain the global flow resistance ratio.

[0007] Furthermore, the method for obtaining the pipe diameter blockage weight includes: The normalized value of the geometric inner diameter of each pipe segment is nonlinearly amplified by exponentiation based on a preset clogging non-uniformity factor to obtain the theoretical pipe diameter blockage weight; the minimum value between the theoretical pipe diameter blockage weight and the preset weight saturation threshold is selected as the pipe diameter blockage weight.

[0008] Furthermore, the method for calculating the energy conservation correction factor includes: Based on the rated flow rate and geometric inner diameter of each pipe segment, calculate the theoretical flow resistance per unit length of each pipe segment; multiply the theoretical flow resistance per unit length of each pipe segment by the pipe segment length to obtain the pipe resistance of that pipe segment; calculate the sum of the pipe resistances of all pipe segments to obtain the total design resistance; use the pipe diameter blockage weight to weight the total design resistance to obtain the weighted virtual total resistance; use the total design resistance as the numerator and the weighted virtual total resistance as the denominator, and obtain the energy conservation correction factor through ratio calculation.

[0009] Furthermore, the method for obtaining the theoretical flow resistance per unit length includes: The theoretical flow resistance per unit length of each pipe segment is calculated using the Hassen-Williams formula, based on the rated flow rate and geometric inner diameter of each segment.

[0010] Furthermore, the formula for calculating the drag correction coefficient includes: Based on the global flow resistance ratio and the energy conservation correction factor, the overall pipe segment baseline value is determined. The overall pipe segment baseline value is then weighted according to the pipe diameter blockage weight of each pipe segment to determine the resistance correction coefficient corresponding to each pipe segment.

[0011] Furthermore, the method for calculating the residual pressure at the end includes: For each dripper node, obtain the water flow path from the water source to the dripper node; calculate the total pressure loss of the water flow path; and calculate the residual pressure at the end of each dripper node based on the source working pressure, the total pressure loss, and the preset rated pressure.

[0012] Furthermore, the method for calculating the total pressure loss includes: For each pipe segment in the water flow path, the gravitational potential energy loss of the pipe segment is used as the reference value. The product of the theoretical flow resistance per unit length and the pipe segment length is weighted and fused according to the resistance correction coefficient as a correction term. The sum of the reference value and the correction term is used as the pressure loss of each pipe segment. The total pressure loss is obtained based on the pressure loss of all pipe segments included in the water flow path.

[0013] This invention also proposes a data fusion-based landscape BIM model construction system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the data fusion-based landscape BIM model construction method.

[0014] The present invention has the following beneficial effects: This invention acquires pressure data and analyzes its gradient distribution characteristics to calculate the global flow resistance ratio, quantifying the macroscopic degree of blockage in the pipe network system. It obtains the theoretical flow resistance per unit length and the blockage weight per pipe diameter for each pipe segment, and calculates the energy conservation correction factor based on the weighted fusion of theoretical flow resistances. This accurately quantifies the high sensitivity of fine pipes to blockage, achieving a high-fidelity non-uniform mapping from the macroscopic blockage coefficient to the microscopic pipe segment resistance. By generating a resistance correction coefficient for each pipe segment, it ensures that while amplifying the resistance of the end pipe segments, the total resistance of the entire network remains strictly consistent with the measured macroscopic data. Finally, it calculates the residual pressure at the end of each dripper node through forward hydraulic simulation, accurately reproducing the actual flow of water in a non-uniformly blocked pipe network. Based on the residual pressure at the end, it analyzes the location of the water shortage critical point, effectively distinguishing water shortage risk zones. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating a method for constructing a landscape BIM model based on data fusion, as provided in one embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a data fusion-based BIM model construction method and system for garden landscapes proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following describes in detail, with reference to the accompanying drawings, a specific scheme for a data fusion-based BIM model construction method for garden landscape provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a method for constructing a landscape BIM model based on data fusion, according to an embodiment of the present invention. The method includes: S101: Obtain the geometric inner diameter, pipe length, rated flow rate, and corresponding source working pressure and pressure decay sequence of each pipe segment in the garden landscape pipeline network; wherein each pipe segment corresponds to two dripper nodes on both sides; based on the time-series decay of the source working pressure and pressure decay sequence, determine the global flow resistance ratio.

[0021] Since existing BIM operation and maintenance systems only contain static design parameters and lack dynamic perception capabilities, and traditional single-point steady-state pressure monitoring cannot reflect the contradiction of non-uniform sludge spatial distribution, this invention obtains the geometric inner diameter, pipe length, rated flow rate of each pipe segment in the landscape pipeline network from the BIM model, as well as the source working pressure and pressure decay sequence collected from pressure sensors deployed in the pipeline network. The measured pressure data is coupled with the static parameters in the BIM model under the laws of fluid mechanics. Based on the time-series decay of the source working pressure and pressure decay sequence, the global flow resistance ratio is determined, thereby realizing the analysis of the non-uniform state of the entire pipeline network using single-point observed pressure data.

[0022] In this embodiment of the invention, to construct a mathematical model capable of supporting fluid calculations, the system first needs to extract the topological relationships and geometric attributes of the pipe network from the static BIM file and calculate the rated flow rate of each pipe segment under design conditions. Specifically, the system reads the BIM data file of the landscape architecture (e.g., an IFC format standard file), and constructs a directed acyclic graph structure by parsing the pipe segments and fittings entities and their connection relationships, using the water source point of the landscape architecture pipe network as the root node and all drippers as leaf nodes. For each pipe segment in the directed acyclic graph structure, corresponding physical parameters are associated. These physical parameters include at least the geometric inner diameter (internal flow diameter of the pipe segment, in meters) and the length (geometric length of the pipe segment along the centerline, in meters) of each pipe segment, and the rated flow rate is calculated. In a specific implementation of this embodiment, the system uses a post-order traversal algorithm, accumulating from the leaf nodes to the root node to calculate the rated flow rate of each pipe segment under design conditions. The rated flow rate is equal to the sum of the rated irrigation flow rates of all leaf nodes (drippers) downstream of that pipe segment. The post-order traversal algorithm is a well-known technique in the field of traversal, and its calculation process will not be described in detail here.

[0023] It should be noted that, to ensure the collected data accurately reflects the physical degradation characteristics of the pipe network, the pressure sensor should be installed on the main pipe of the irrigation zone to be tested, and strictly downstream of the solenoid control valve of that zone. If the system is equipped with a main check valve, the sensor should be located upstream of the check valve (on the pipe network side). This arrangement ensures that even after the solenoid valve closes and cuts off the water supply, the sensor remains connected to the inside of the pipe network, capturing the pressure dissipation process caused by water flowing out through the end drippers, rather than capturing water hammer fluctuations or pressure holding states on the pumping station side. Simultaneously, for the transient process from the end of the irrigation cycle and the closing of the solenoid valve until the internal pressure of the pipe network stabilizes to static pressure or is emptied, the system monitors the electromagnetic control signal of the irrigation controller in real time. When the control signal is detected to change from "on" to "off," the system marks this moment as the system trigger moment, activates the pressure sensor, collects pressure values ​​in real time, and arranges these pressure values ​​in chronological order to construct a pressure decay sequence; pressure data is collected according to the preset frequency band that satisfies the Nyquist sampling theorem based on the system trigger moment. In one specific implementation of this invention, the preset frequency band is set to 50Hz to ensure that pressure data can be collected completely and accurately during the pressure decay process after the valve is closed.

[0024] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the source working pressure includes: The arithmetic mean of all measured pressure values ​​within a preset time period preceding the pressure decay sequence is taken as the source working pressure. The source working pressure characterizes the effective driving pressure applied to the pipeline inlet under steady-state irrigation conditions before valve closure.

[0025] It should be noted that, in one specific implementation of the present invention, in order to obtain the true steady-state value by smoothing the random pressure fluctuations for a sufficient duration, and at the same time ensure that the pressure value can accurately represent the system drive state at the moment of valve closure, the preset time period is set to 10 seconds.

[0026] Preferably, in some possible implementations of the embodiments of the present invention, the global flow resistance ratio calculation method includes: Although the discharge velocity of a pipeline network is physically influenced by hydrostatic pressure, pipe elasticity, and fluid volume, these factors can be considered constants or slow variables at the same installation height within the same system. Therefore, this invention equates the pipeline discharge process to a first-order RC discharge circuit model, employs an exponential decay model to quantify the characteristics of the discharge process, and extracts the time constant to characterize the change in flow resistance.

[0027] Specifically, based on the difference between the measured pressure value and the preset static stable pressure at each moment in the pressure decay sequence, the instantaneous driving difference at each moment is determined; based on the difference between the source working pressure and the preset static stable pressure, the initial effective pressure difference is determined; a fitting model is constructed based on the instantaneous driving difference and the initial effective pressure difference, the fitting model including: obtaining the instantaneous driving difference at each moment based on the product between the initial effective pressure difference and the exponential decay factor; the exponential decay factor is negatively correlated with the acquisition time and positively correlated with the pressure decay time constant; the system iteratively solves the fitting model based on the measured pressure value at each moment in the pressure decay sequence to minimize the sum of squared residuals, thereby obtaining the pressure decay time constant under the current operating condition. The larger the pressure decay time constant, the slower the water flow discharge under the same pressure difference drive, i.e., the larger the equivalent flow resistance of the pipe network. In order to eliminate the influence of inherent system properties (such as pipe network volume and static pressure difference) on the time constant, and simply extract the resistance increment caused by siltation, this invention standardizes the pressure decay time constant to obtain the global flow resistance ratio.

[0028] As an example, in a specific implementation of this invention, the fitting model can be expressed as: in, Represents the first in the pressure decay sequence The measured pressure value at any given time; This indicates pressure at the source of the work; Indicates the static pressure at the end of the discharge; This represents the pressure decay time constant to be solved, in seconds; Indicates the first The instantaneous driving difference at any given moment is obtained by subtracting the static water steady pressure at the end of the discharge from the measured pressure value. This removes the inherent static pressure reference of the system, allowing the data to purely reflect the dynamic discharge process determined by the flow resistance. This represents the initial effective pressure difference, reflecting the initial amplitude of the decay process; This indicates the time from the system trigger moment (i.e., the valve closing moment) to the [missing information]. The time interval between moments; The exponential decay factor represents the decrease in pressure over time. Increasing the time constant slows down this decay, making the exponential decay factor remain larger over the same period of time. This is consistent with the physical property that the greater the flow resistance, the slower the flow. is a natural constant. Since the pipeline leakage process physically follows the exponential decay law of a first-order linear system, this formula uses an exponential decay factor to weight the initial effective pressure difference, thereby obtaining the instantaneous driving difference.

[0029] It should be noted that, in one specific implementation of this invention, the static water stabilization pressure at the end of the discharge refers to the final stable pressure value after the discharge process ends. For pressure-compensated dripper systems equipped with anti-drip (checkback) function, this value is the physical checkback opening pressure of the dripper; for dripper systems with free drainage, this value is the local atmospheric pressure or relative zero pressure. In this embodiment of the invention, it is set to 0.01 MPa.

[0030] As an example, in a specific implementation of this invention, the reference decay time constant represents the decay time constant under clean pipe network conditions, while the pressure decay time constant reflects the characteristic time constant obtained by fitting the pressure decay curve after valve closure collected in real time under the current operating conditions. Both are measured values ​​under the same pipe network structure and the same static pressure reference; dividing them effectively eliminates the influence of constants such as static pressure and volume. Therefore, the pressure decay time constant is used as the numerator, and the reference decay time constant is used as the denominator, and the global flow resistance ratio is obtained through ratio calculation. The global flow resistance ratio purely reflects the degree of increase in the average fluid damping of the entire system relative to the initial state. Furthermore, since the physical degradation (clogging) of the pipe network due to biofilm growth, particle deposition, etc., during operation is irreversible, this leads to an increase in flow resistance, so the global flow resistance ratio is always greater than or equal to 1. The reference decay time constant represents the pressure decay time constant under ideal clean pipe network conditions; this parameter can be obtained by calling the system hydraulic calculation engine during the first run.

[0031] It should be noted that, in one specific implementation of this invention, considering that there is no reference decay time constant in the database when the system is first run, the system calls the built-in hydraulic calculation engine to construct a virtual hydraulic model based on the pipe network topology, pipe segment geometric parameters (length, inner diameter), and material roughness coefficient in the BIM model, and calculates the theoretical decay time constant under theoretical conditions.

[0032] Specifically, the absolute value of the difference between the theoretical decay time constant and the pressure decay time constant is used as the numerator, and the theoretical decay time constant is used as the denominator. A ratio calculation is performed to obtain the relative deviation between the two. If the relative deviation is within a preset reasonable range (in this embodiment, the preset reasonable range is set to...), then... If the system is determined to be in a healthy initial state, the measured theoretical decay time constant is stored in the database as a reference decay time constant, and the current global flow resistance ratio is set to 1. If the relative deviation between the two exceeds the preset reasonable range, it is determined that the system may have construction defects or initial blockage. The system outputs an abnormal alarm to prompt manual inspection and does not perform benchmark storage for the time being.

[0033] S102: Based on the reference deviation of the geometric inner diameter, obtain the pipe diameter blockage weight for each pipe segment; calculate the energy conservation correction factor by weighting and fusing the theoretical flow resistance per unit length of each pipe segment according to the pipe diameter blockage weight; generate the resistance correction coefficient for each pipe segment by weighting and scaling using the pipe diameter blockage weight based on the global flow resistance ratio and the energy conservation correction factor; calculate the terminal residual pressure of each dripper node through forward hydraulic simulation based on the pressure data and resistance correction coefficient of each pipe segment.

[0034] Clogging within pipe networks typically occurs physically uniformly, but the resulting hydraulic effects are spatially non-uniform. For the same deposit thickness, the flow area ratio of narrow pipes decreases drastically, leading to an exponential increase in flow resistance; the impact on wider pipes is negligible. To quantify this physical phenomenon of "narrow pipes being more prone to clogging" in a mathematical model, the system introduces a pipe diameter clogging weight. Based on the baseline deviation of the geometric inner diameter, the pipe diameter clogging weight for each pipe segment is obtained. The global flow resistance ratio obtained in step S101 macroscopically limits the increase in total system energy loss. Directly applying the pipe diameter clogging weight for resistance correction may result in a calculated total system resistance far exceeding the actual measured value. Therefore, a normalization factor must be introduced to satisfy energy conservation constraints. Thus, this invention uses the pipe diameter clogging weight to weightedly fuse the theoretical flow resistance per unit length of each pipe segment, calculating an energy conservation correction factor. Finally, based on the global flow resistance ratio and the energy conservation correction factor, the pipe diameter clogging weight is used for weighted scaling to generate the resistance correction coefficient for each pipe segment. Since the pipeline network is an interconnected system, the water supply of a dripper does not depend solely on the pipe segment it is directly connected to, but rather on the combined effect of all pipe segments along the entire water supply path from the water source to the dripper. Therefore, this invention, for each dripper, uses the pressure data and resistance correction coefficient of each pipe segment to simulate the actual flow process of water in a non-uniformly clogged pipeline network, thereby obtaining the residual pressure at the end of each dripper node. This elevates the calculation results from a purely data-driven level to a BIM spatial visualization level, thus transforming the invisible flow resistance risk into an intuitive geometric surface.

[0035] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the pipe diameter blockage weight includes: According to the Hagen-Poiseuille law, in laminar or near-laminar flow conditions, the flow resistance of a pipe is inversely proportional to the fourth power of its diameter. This means that the smaller the pipe diameter, the more sensitive it is to changes in the thickness of the sediment layer. However, considering the significant differences in pipe diameters in garden micro-irrigation systems (e.g., from main pipes to capillaries), directly applying the fourth power relationship may result in an excessively large weight value for capillaries, leading to numerical overflow or the failure of the normalization factor in subsequent calculations. Therefore, this embodiment introduces a weight calculation model with numerical truncation protection.

[0036] Specifically, the normalized value of the geometric inner diameter of each pipe segment is nonlinearly amplified by exponentiation based on a preset clogging non-uniformity factor to obtain the theoretical pipe diameter blockage weight; the minimum value between the theoretical pipe diameter blockage weight and the preset weight saturation threshold is selected as the pipe diameter blockage weight.

[0037] As an example, in a specific implementation of this invention, the formula for calculating the pipe diameter blockage weight can be expressed as: in, Indicates the first Pipeline diameter blockage weight; This indicates the inner diameter of the baseline main pipe, specifically the inner diameter of the main riser pipe connecting to the pump station outlet (which can be directly obtained from the BIM data file). Indicates the first The geometric inner diameter of the pipe section; This represents the non-uniformity factor of sludge, used to measure the degree of unevenness in the distribution of sludge. This indicates a preset weight saturation threshold, used to prevent [the following text is incomplete and likely refers to a different topic]... The formula utilizes the fact that the minimum value causes numerical divergence. This ratio amplifies the vulnerability of narrow tubes, demonstrating that for the same deposition layer thickness, the flow area ratio of narrow tubes decreases drastically, leading to an exponential increase in flow resistance, while the effect on thicker tubes is negligible. Based on the Hagen-Poiseuille law, in laminar or near-laminar flow conditions, the flow resistance of a pipe is inversely proportional to the fourth power of its diameter. The theoretical pipe diameter blocking weight is used as the minimum value between the theoretical pipe diameter blocking weight and the preset weight saturation threshold. This prevents the algorithm from crashing due to extreme physical parameters (such as the occurrence of a few extremely thin pipes, which could lead to an excessively large pipe diameter blocking weight), and ensures that the system operates stably and reliably in real complex engineering environments.

[0038] It should be noted that, in one specific implementation of this invention, based on fluid dynamics theory, the non-uniformity factor of clogging is... The value is set to 4, but in actual engineering, it can be adjusted within the range of [2,4] according to the physical properties of the sediment (such as hard particles or soft biofilms); preset weight saturation threshold. This is an engineering experience parameter with a value range of [50, 100]. In this embodiment of the invention, it is set to 80, but it can be adjusted within the range of [50, 100] according to the specific implementation scenario.

[0039] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the energy conservation correction factor includes: Based on the rated flow rate and geometric inner diameter of each pipe segment, calculate the theoretical flow resistance per unit length of each pipe segment; multiply the theoretical flow resistance per unit length of each pipe segment by the pipe segment length to obtain the pipe resistance of that pipe segment; calculate the sum of the pipe resistances of all pipe segments to obtain the total design resistance; use the pipe diameter blockage weight to weight the total design resistance to obtain the weighted virtual total resistance; use the total design resistance as the numerator and the weighted virtual total resistance as the denominator, and obtain the energy conservation correction factor through ratio calculation.

[0040] As an example, in one specific implementation of this invention, the energy conservation correction factor... The calculation formula can be expressed as: in, This indicates the total number of pipe segments in the garden landscape pipeline network; Indicates the first The theoretical flow resistance per unit length of a pipe section is used as a benchmark to characterize the physical resistance of the pipe section under ideal clean conditions. Indicates the first The length of the pipe section; Indicates the first The pipe segment's diameter and blockage weight. In this formula... The first Theoretical flow resistance per unit length of pipe section and the first The product of pipe segment lengths represents the pipe resistance of that segment; the numerator term... The total design resistance is represented by the sum of the pipe resistances of all pipe segments. This measures the total theoretical flow resistance of the entire pipe network under designed clean conditions and serves as a benchmark for system energy loss. According to Poiseuille's law, the flow resistance of a circular pipe is inversely proportional to the fourth power of the pipe diameter. To quantify this resistance growth mechanism dominated by narrow pipes, the denominator term... Using the pipe diameter blockage weight as a constraint, the total design resistance is weighted to obtain the weighted virtual total resistance. Finally, the ratio of the total design resistance to the weighted virtual total resistance is used as the energy conservation correction factor, which reflects the proportional relationship between the theoretical growth potential and the actual observed growth rate if the resistance growth is entirely driven by the thin pipe sensitivity.

[0041] It should be noted that in irrigation networks, since the design flow rate is positive, all parameters in the denominator are greater than zero, so the denominator cannot be equal to zero. Furthermore, in the calculation of pipe diameter blockage weight, a preset weight saturation threshold is introduced to truncate the denominator, preventing it from expanding indefinitely. This ensures that the energy conservation correction factor does not approach zero, thus maintaining the validity of the calculation.

[0042] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the theoretical flow resistance per unit length includes: The theoretical flow resistance per unit length of each pipe segment is calculated using the Hassen-Williams formula, based on the rated flow rate and geometric inner diameter of each segment.

[0043] It should be noted that the Hassen-Williams formula mentioned above is a technical means well known to those skilled in the art for calculating the head loss of water supply networks, i.e., the flow resistance of pipelines. The specific meaning of the formula will not be elaborated here.

[0044] Preferably, in some possible implementations of the embodiments of the present invention, the formula for calculating the drag correction coefficient includes: In order to resolve a single macroscopic monitoring indicator into microscopic physical state parameters of each pipe segment in the entire network, this invention determines the overall pipe segment baseline value based on the global flow resistance ratio and the energy conservation correction factor, and weights the overall pipe segment baseline value according to the pipe diameter blockage weight of each pipe segment to determine the resistance correction coefficient corresponding to each pipe segment.

[0045] As an example, in a specific implementation of this invention, the formula for calculating the drag correction coefficient can be expressed as: in, Indicates the first Resistance correction factor for the pipe section; Indicates the first Pipeline diameter blockage weight; Indicates the global flow resistance ratio; This represents the energy conservation correction factor; the formula is passed through Measure the absolute increase in the overall flow resistance of the system compared to the clean state; The absolute increment multiple is calibrated using an energy conservation correction factor, which represents the calibrated unit increment. The calibrated unit increment is non-uniformly amplified and distributed according to the pipe diameter blockage weight of each pipe segment to obtain the overall resistance correction increment; finally, the basic correction coefficient (i.e., 1) and the overall resistance correction increment are superimposed to obtain the resistance correction coefficient of each pipe segment, thus realizing the non-uniform redistribution of the flow resistance increment.

[0046] It should be noted that when the global flow resistance ratio is equal to 1, it indicates that the system is in a healthy state without blockage; therefore, regardless of the weight, the resistance correction coefficient is 1, that is, the resistance does not increase; when the global flow resistance ratio is greater than 1, it indicates that the system is in a blocked state. At this time, the resistance correction coefficient of the end cap will be significantly greater than the global flow resistance ratio, while the resistance correction coefficient of the main pipe will be slightly greater than the global flow resistance ratio.

[0047] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the residual pressure at the end includes: Since the pipeline network is an interconnected system, the water supply of a dripper does not depend solely on the pipe section it is directly connected to, but rather on the combined effect of all pipe sections along the entire water supply path from the water source to the dripper. Therefore, this invention obtains the water flow path from the water source to the dripper node for each dripper node; calculates the total pressure loss of the water flow path; and calculates the residual pressure at the end of each dripper node based on the source working pressure, the total pressure loss, and the preset rated pressure.

[0048] As an example, in a specific implementation of this invention, the system performs a breadth-first traversal along the water flow direction (from the root node to each leaf node) according to the directed acyclic graph structure constructed in step S101 to obtain the water flow path from the water source to the dripper node. Then for any dripper node Residual pressure at the end The calculation formula can be expressed as: in, This indicates pressure at the source of the work; Indicates the first The total pressure loss of the dripper is used to measure the total loss of water's gravitational potential energy and the friction caused by pipe blockage during the entire flow process. For the first recorded in the BIM model The minimum rated pressure required for a dripper to operate normally is used to characterize the minimum pressure at which water flows to the dripper to meet normal operating requirements. Using this as a subtraction, it can distinguish whether the dripper can perform normal sprinkler irrigation. This formula determines the pressure loss of water from the water source to the dripper node by analyzing the total pressure loss along the entire water flow path and the minimum rated pressure of the target dripper, thus obtaining the residual pressure at the dripper node.

[0049] It should be noted that if the residual pressure at the end is greater than or equal to 0, it indicates that the water flow energy is sufficient and the dripper can be opened for normal irrigation; if the residual pressure at the end is less than 0, it indicates that under the current clogging conditions, the water flow energy is insufficient to overcome gravity and resistance to reach the height and open the dripper, and this node is determined to be a water shortage risk point.

[0050] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the total pressure loss includes: For any dripper node, since its water flow path includes multiple pipe segments, and each pipe segment has a different geometric inner diameter, the pressure loss caused by each segment is also different. Therefore, in order to measure the total pressure loss of the entire water flow path, this invention uses the gravitational potential energy loss of each pipe segment in the water flow path as a benchmark value, and performs a weighted fusion of the product of the theoretical flow resistance per unit length and the pipe segment length according to the resistance correction coefficient as a correction term; the sum of the benchmark value and the correction term is the pressure loss of each pipe segment; and the total pressure loss is obtained based on the pressure loss of all pipe segments included in the water flow path.

[0051] As an example, in one specific implementation of this invention, for any droplet node... The total pressure loss along its water flow path The calculation formula can be expressed as: in, Represents the dripper node The corresponding pipe segment index included in the water flow path, i.e. ; This indicates the total number of pipe segments included in the water flow path; The density of water; It is the acceleration due to gravity; Indicates the first The elevation increment of a pipe segment is specifically the vertical height difference between the outlet node and the inlet node of the pipe segment, in meters (with the direction against gravity defined as positive), which can be obtained from the attribute data of the pipe segment in the BIM model. Indicates the first Resistance correction factor for the pipe section; Indicates the first Theoretical flow resistance per unit length of the pipe section; Indicates the first The length of the pipe segment. In this formula... It is the gravitational potential energy loss obtained from the water pressure formula. It is the main energy consumption item of the vertical greening system and directly reflects the pressure reduction effect of the height difference. Indicates the first The total theoretical frictional resistance of the pipe section under clean design conditions; This represents the pressure energy consumed by the water flow to overcome the friction of the inner wall of the pipe. By accumulating the gravitational potential energy loss and pressure energy of all sections included in the entire water flow path, the total pressure loss on the entire water flow path is obtained. This discretizes the complex continuous problem of pipeline hydraulic calculation into the accumulation of the two basic energy losses (gravity loss and pressure loss) of each section of the pipeline on the irrigation path.

[0052] S103: Differentiate water shortage risk areas in the garden landscape pipeline network based on the residual pressure at the end of each dripper node.

[0053] The residual pressure at the end of each dripper calculated in step S102 measures the degree of water shortage caused by pipe blockage. Therefore, the residual pressure at the end of each dripper can provide real-time early warning of the blockage situation in the garden landscape pipe network.

[0054] Specifically, in this embodiment of the invention, in order to identify continuous risk areas, the system extracts the residual pressure at the end of each dripper and the three-dimensional coordinates of each dripper in the BIM model, constructing a discrete point set. The function value at each coordinate of the discrete point set is the residual pressure at the end of the corresponding dripper, and the discrete point set is reconstructed into a continuous pressure scalar field. Considering that the pressure distribution of the vertical greening system has a strong gradient change characteristic in the vertical direction (Z-axis) (dominantly due to gravity), while the change in the horizontal direction (XY plane) is mainly determined by the pipeline topology and frictional resistance, the system adopts a three-dimensional interpolation algorithm that takes into account the elevation gradient to construct a pipeline scalar field. The function value at each coordinate in the pipeline scalar field is the residual pressure at the end of each spatial coordinate obtained by spatial interpolation of the discrete point set.

[0055] It should be noted that during the interpolation process, the system assigns a higher weighting attenuation factor to the vertical distance (Z-axis direction) to accurately reflect the dominance of gravity on the pressure field. The interpolation calculation covers the bounding box space containing the entire garden landscape vegetation, generating a high-resolution voxelized pressure data grid.

[0056] It should be noted that other interpolation algorithms, such as anisotropic kriging, can also be used in other implementations of the present invention, which are not limited or elaborated here.

[0057] Furthermore, the system generates a scalar field of the pipeline network. The system executes the MarchingCubes algorithm. It searches for isosurfaces where the residual pressure at the end is zero, i.e., those satisfying... The set of all spatial points constitutes the critical irrigation elevation surface. Physically, this surface represents the ultimate hydraulic boundary under current operating conditions where water flow can overcome gravity and network resistance to reach the dripper opening threshold. In areas with unobstructed networks, due to low frictional resistance, the surface height is primarily controlled by the source pressure, exhibiting a gentle shape. In areas with densely packed and severely clogged end pipes, the increased frictional resistance leads to greater head loss, causing the surface to concave significantly in certain areas.

[0058] It should be noted that the moving cube algorithm is a well-known technique in the field of science, and its specific process and meaning will not be elaborated here.

[0059] The system converts the generated critical irrigation elevation surface into a geometric object in the BIM standard format (such as IfcSurface in the IFC standard) and inserts it into the current BIM model view. In the BIM visualization interface, the garden facade is segmented according to the critical irrigation elevation surface. The lower area of ​​the critical irrigation elevation surface is defined as the "effective irrigation zone," and the upper area is defined as the "water shortage risk zone." This allows for a direct perception of the current irrigation capacity boundary and effective differentiation of water shortage risk zones.

[0060] In summary, this invention acquires pressure data and analyzes its gradient distribution characteristics to calculate the global flow resistance ratio, quantifying the macroscopic degree of blockage in the pipe network system. By acquiring the theoretical flow resistance per unit length and the blockage weight per pipe diameter for each pipe segment, and then weighting and fusing the theoretical flow resistance based on these weights to calculate the energy conservation correction factor, it accurately quantifies the high sensitivity of the thin pipe to blockage, achieving a high-fidelity non-uniform mapping from the macroscopic blockage coefficient to the microscopic pipe segment resistance. By generating a resistance correction coefficient for each pipe segment, it ensures that while amplifying the resistance of the end pipe segments, the total resistance of the entire network remains strictly consistent with the measured macroscopic data. Finally, by calculating the residual pressure at the end of each dripper node through forward hydraulic simulation, it accurately reproduces the actual flow of water in a non-uniformly blocked pipe network. Based on the residual pressure at the end, it analyzes the location of the water shortage critical point, effectively distinguishing water shortage risk areas.

[0061] Based on the same inventive concept, the present invention also proposes a landscape BIM model construction system based on data fusion, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the landscape BIM model construction method based on data fusion.

[0062] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for constructing a landscape BIM model based on data fusion, characterized in that, The method includes: Obtain the geometric inner diameter, pipe length, rated flow rate, and corresponding source working pressure and pressure decay sequence of each pipe segment in the garden landscape pipeline network; wherein each pipe segment corresponds to two dripper nodes on both sides; based on the time-series decay of the source working pressure and pressure decay sequence, determine the global flow resistance ratio; Based on the reference deviation of the geometric inner diameter, the pipe diameter blockage weight of each pipe segment is obtained; the theoretical flow resistance per unit length of each pipe segment is weighted and fused according to the pipe diameter blockage weight, and the energy conservation correction factor is calculated; based on the global flow resistance ratio and the energy conservation correction factor, the resistance correction coefficient of each pipe segment is generated by weighted scaling using the pipe diameter blockage weight; based on the pressure data and resistance correction coefficient of each pipe segment, the terminal residual pressure of each dripper node is calculated through forward hydraulic simulation. The risk zones of water shortage in the garden landscape pipeline network are distinguished based on the residual pressure at the end of each dripper node.

2. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The method for obtaining the source working pressure includes: The arithmetic mean of all measured pressure values ​​within a preset time period prior to the pressure decay sequence is taken as the source working pressure.

3. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The global flow resistance ratio calculation method includes: Based on the difference between the measured pressure value and the preset static steady pressure at each moment in the pressure decay sequence, the instantaneous drive difference at each moment is determined; based on the difference between the source working pressure and the preset static steady pressure, the initial effective pressure difference is determined; a fitting model is constructed based on the instantaneous drive difference and the initial effective pressure difference, the fitting model including: obtaining the instantaneous drive difference at each moment based on the product between the initial effective pressure difference and the exponential decay factor; the exponential decay factor is negatively correlated with the acquisition time and positively correlated with the pressure decay time constant; regression fitting is performed on the fitting model based on the measured pressure value at each moment in the pressure decay sequence to obtain the pressure decay time constant, and the pressure decay time constant is standardized to obtain the global flow resistance ratio.

4. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The method for obtaining the pipe diameter blockage weight includes: The normalized value of the geometric inner diameter of each pipe segment is nonlinearly amplified by exponentiation based on a preset clogging non-uniformity factor to obtain the theoretical pipe diameter blockage weight; the minimum value between the theoretical pipe diameter blockage weight and the preset weight saturation threshold is selected as the pipe diameter blockage weight.

5. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The calculation method for the energy conservation correction factor includes: Based on the rated flow rate and geometric inner diameter of each pipe segment, calculate the theoretical flow resistance per unit length of each pipe segment; multiply the theoretical flow resistance per unit length of each pipe segment by the pipe segment length to obtain the pipe resistance of that pipe segment; calculate the sum of the pipe resistances of all pipe segments to obtain the total design resistance; use the pipe diameter blockage weight to weight the total design resistance to obtain the weighted virtual total resistance; use the total design resistance as the numerator and the weighted virtual total resistance as the denominator, and obtain the energy conservation correction factor through ratio calculation.

6. The method for constructing a landscape BIM model based on data fusion according to claim 5, characterized in that, The method for obtaining the theoretical flow resistance per unit length includes: The theoretical flow resistance per unit length of each pipe segment is calculated using the Hassen-Williams formula, based on the rated flow rate and geometric inner diameter of each segment.

7. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The formula for calculating the drag correction factor includes: Based on the global flow resistance ratio and the energy conservation correction factor, the overall pipe segment baseline value is determined. The overall pipe segment baseline value is then weighted according to the pipe diameter blockage weight of each pipe segment to determine the resistance correction coefficient corresponding to each pipe segment.

8. The method for constructing a landscape BIM model based on data fusion according to claim 1, characterized in that, The method for calculating the residual pressure at the end includes: For each dripper node, obtain the water flow path from the water source to the dripper node; calculate the total pressure loss of the water flow path; and calculate the residual pressure at the end of each dripper node based on the source working pressure, the total pressure loss, and the preset rated pressure.

9. A method for constructing a landscape BIM model based on data fusion according to claim 8, characterized in that, The method for calculating the total pressure loss includes: For each pipe segment in the water flow path, the gravitational potential energy loss of the pipe segment is used as the reference value. The product of the theoretical flow resistance per unit length and the pipe segment length is weighted and fused according to the resistance correction coefficient as a correction term. The sum of the reference value and the correction term is used as the pressure loss of each pipe segment. The total pressure loss is obtained based on the pressure loss of all pipe segments included in the water flow path.

10. A landscape BIM model building system based on data fusion, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for constructing a garden landscape BIM model based on data fusion as described in any one of claims 1 to 9.

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