A BIM-based underground comprehensive pipe gallery intelligent operation and maintenance management system

Abstract

This invention belongs to the field of underground utility tunnel operation and maintenance technology. It provides a BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels, comprising: acquiring real-time environmental parameters and surface temperature data of upper-level pipelines within the tunnel, and marking condensate generation nodes on the pipeline surface; based on the three-dimensional coordinates and surface geometry of the condensation zone in the BIM model, dividing the dripping surface or converging dripping points and constructing a three-dimensional dripping space model; calculating the shortest horizontal distance between the sensor and the boundary of the dripping model according to the sensor's height, and classifying and screening suspected sensors affected by condensate; dynamically calculating the condensate generation rate, cumulative volume, and surface tension dripping threshold value by combining temperature, humidity, wind speed, and pipeline material parameters to determine whether actual dripping has occurred; confirming suspected sensors that meet the dripping conditions as target sensors, automatically marking them as false condensate alarms and intercepting maintenance work orders when they trigger water immersion alarms.

Description

Technical Field

[0001] This invention belongs to the field of underground utility tunnel operation and maintenance technology, specifically a BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels. Background Technology

[0002] To achieve intelligent operation and maintenance of underground utility tunnels, existing technologies generally adopt BIM-based intelligent operation and maintenance management systems. By deploying devices such as water immersion sensors and cable insulation monitoring sensors, alarms such as pipeline leaks and insulation breakdowns are triggered based on abnormal signals from a single sensor, thereby avoiding safety hazards.

[0003] However, during the rainy season and periods of sudden temperature drop, a large amount of condensation can easily form on the surface of cold water pipes and ventilation openings in the utility tunnel due to the temperature and humidity difference. The condensation drips down and splashes onto the sensors below, causing the sensors to output abnormal signals.

[0004] The existing system's alarm judgment logic does not consider the environmental interference factor of condensate water, and directly judges the fault based on the signal of a single sensor, which leads to a large number of false positives and has significant technical defects: false alarms crowd out the alarm channel, interfere with the operation and maintenance personnel's judgment of the real fault, require manual point-by-point verification, consume a lot of manpower and time costs, significantly reduce operation and maintenance efficiency, and can easily cover up the real fault, causing safety accidents and threatening the safe and stable operation of the utility tunnel.

[0005] Currently, existing technologies lack effective solutions and can only eliminate false alarms through manual verification. They cannot fundamentally distinguish between condensate water interference and actual faults, making it difficult to meet the needs of intelligent and efficient operation and maintenance of utility tunnels. Therefore, a targeted technical solution is urgently needed to address these pain points. To this end, this invention provides a BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0007] The technical solution adopted by this invention to solve its technical problem is: One of the objectives of this invention is to provide a BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels, comprising the following modules: Condensation node identification module: acquires real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines, and marks the condensate generation node areas on the surface of the upper pipelines; The drip space modeling module obtains the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model. Based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, the condensate generation node area is divided into dispersed drip surfaces or converged drip points as the initial starting point, and a three-dimensional drip space model with volume is constructed downwards. Suspected sensor screening module: Calculates the shortest horizontal distance between each sensor and the boundary of the three-dimensional drip space model at the corresponding height, and screens out suspected sensors affected by condensation based on the shortest horizontal distance; False alarm identification and marking module: Based on real-time environmental parameters and pipeline surface temperature data, calculate the condensate generation rate and current cumulative volume in the condensate generation node area, and determine whether dripping will occur. If so, the suspected sensor is identified as the target sensor, and it is marked as a condensate false alarm when a water immersion alarm is received from the target sensor.

[0008] As a further improvement of the present invention, the specific process of obtaining real-time environmental parameters within the utility tunnel is as follows: Real-time environmental parameters include: real-time ambient temperature inside the utility tunnel, real-time relative humidity inside the utility tunnel, real-time ambient wind speed inside the tunnel, and surface temperature data of the upper pipelines. The real-time ambient temperature and relative humidity inside the pipe gallery are obtained by an ambient temperature and humidity sensor, the real-time ambient wind speed inside the pipe gallery is obtained by an air speed sensor, and the surface temperature data of the upper pipes is obtained by a temperature sensor attached to the surface of the upper pipes.

[0009] As a further improvement of the present invention, the specific process of marking the condensate generation node area on the surface of the upper pipeline is as follows: The ambient dew point temperature under the current pipe gallery environment is calculated using the Magnus formula, and the surface temperature data of the upper pipeline is compared with the ambient dew point temperature in real time. If the surface temperature data is less than or equal to the ambient dew point temperature, the surface area of ​​the upper pipeline monitored by the temperature sensor will be marked as a condensate generation node area in the pipe gallery BIM model.

[0010] As a further improvement of the present invention, the specific process of obtaining the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery in the pipe gallery BIM model is as follows: Obtain the BIM model of the utility tunnel and extract the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the utility tunnel.

[0011] As a further improvement of the present invention, the specific process of dividing the initial starting point is as follows: Extract the surface geometric parameters of the condensate generation node area in the pipe gallery BIM model, including surface inclination and surface curvature; If the surface tilt angle is less than or equal to the horizontal tilt angle threshold and the surface curvature is less than or equal to the flat curvature threshold, then the condensate generation node area is divided into a dispersed dripping surface. If the surface tilt angle is greater than the horizontal tilt angle threshold, or the surface curvature is greater than the flat curvature threshold, then the condensate generation node area is divided into a convergence drip point. If the condensate generation node area is divided into a dispersed dripping surface, then the overall geometric boundary profile of the condensate generation node area is taken as the initial starting point. If the condensate generation node area is divided into convergence and dripping points, then the lowest point of the condensate generation node area is extracted as the initial starting point.

[0012] As a further improvement of the present invention, the specific process of constructing the three-dimensional droplet space model with volume is as follows: If the initial starting point is the convergence point of the droplet, then the lowest point is taken as the vertex, the downward direction of gravity is taken as the axis, and the natural diffusion angle is taken as the semi-cone angle to generate a three-dimensional droplet space model. If the initial starting point is a dispersed dripping surface, then the geometric boundary contour is used as the top surface, and the overall geometric boundary contour is discretized and sampled according to the preset boundary sampling step size to obtain the set of discrete boundary points; Each discrete point in the boundary discrete point set is linearly swept outward along the downward direction of gravity and according to the natural diffusion angle to generate a three-dimensional droplet space model.

[0013] As a further improvement of the present invention, the specific process of calculating the shortest horizontal distance between each sensor and the boundary of the three-dimensional droplet space model at the corresponding height is as follows: Extract the three-dimensional spatial coordinates of each sensor in the BIM model of the utility tunnel. The three-dimensional spatial coordinates include the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate. Using the Z-axis coordinate of the sensor as the reference height, a horizontal tangent plane is generated in the BIM model of the utility tunnel; Geometrically intersect the horizontal cutting plane with the three-dimensional droplet space model to obtain the local horizontal cross section at the reference height; Within the horizontal tangent plane, the shortest horizontal distance between the sensor's coordinates and the outer edge of the local horizontal cross-section is calculated using the two-dimensional Euclidean distance formula. If the sensor is located inside the local horizontal cross-section, the shortest horizontal distance is recorded as zero.

[0014] As a further improvement of the present invention, the specific process for screening out suspected sensors affected by condensate is as follows: Calculate the maximum distance between two points on a local horizontal cross-section and use it as the sensor's dynamic judgment threshold; If the shortest horizontal distance is less than or equal to the dynamic judgment threshold, the sensor will be marked as a suspected sensor affected by condensation. If the shortest horizontal distance is greater than the dynamic judgment threshold but less than or equal to twice the dynamic judgment threshold, the sensor will be marked as a suspected sensor affected by condensation. If the shortest horizontal distance is greater than twice the dynamic judgment threshold, the sensor will be marked as a sensor unaffected by condensation.

[0015] As a further improvement of the present invention, the specific process of confirming the suspected sensor as the target sensor is as follows: Based on the real-time ambient temperature and real-time relative humidity in the pipe gallery, the real-time absolute humidity parameter in the pipe gallery is calculated, and the condensation temperature difference between the surface temperature data of the upper pipeline and the ambient dew point temperature is calculated. The real-time absolute humidity parameter, condensation temperature difference and surface area of ​​the condensate generation node area in the pipe gallery are obtained, and the condensate generation rate of the condensate generation node area is calculated. Set a dynamic monitoring time window, and calculate the condensate generation rate by time integration within the dynamic monitoring time window to obtain the initial cumulative amount of condensate. The surface evaporation rate is calculated based on the real-time ambient wind speed, real-time ambient temperature and real-time relative humidity in the pipe gallery. The current cumulative volume of the condensate generation node area is obtained by subtracting the evaporation amount of the surface evaporation rate within the same dynamic monitoring time window from the initial cumulative amount of condensate. The surface tension coefficient and solid-liquid contact angle of the pipeline material are obtained. Based on the surface tension coefficient, solid-liquid contact angle and gravitational acceleration, the maximum volume of water droplets on the surface of the pipeline material is calculated as the critical value of surface tension droplet. If the current accumulated volume is greater than the surface tension dripping critical value, it is determined that a substantial dripping phenomenon has occurred in the condensate generation node area, and the suspected sensor is confirmed as the target sensor.

[0016] As a further improvement of the present invention, the specific operation process of marking the water immersion alarm received from the target sensor as a false alarm of condensation is as follows: When a water immersion alarm is received from the target sensor, the maintenance work order generated for the water immersion alarm is intercepted, and the water immersion alarm is marked as a false alarm for condensation.

[0017] The second objective of this invention is to provide a BIM-based intelligent operation and maintenance management method for underground integrated utility tunnels, comprising the following steps: Step S10: Obtain real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines, and mark the condensate generation node areas on the surface of the upper pipelines; Step S20: Obtain the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model. Based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, divide the condensate generation node area into a dispersed dripping surface or a converged dripping point as the initial starting point, and construct a three-dimensional dripping space model with volume downwards. Step S30: Calculate the shortest horizontal distance between each sensor and the boundary of the three-dimensional drip space model at the corresponding height, and screen out the suspected sensors affected by condensation based on the shortest horizontal distance; Step S40: Based on real-time environmental parameters and pipeline surface temperature data, calculate the condensate generation rate and current cumulative volume in the condensate generation node area, and determine whether dripping will occur. If so, confirm the suspected sensor as the target sensor, and mark it as a false condensate alarm when a water immersion alarm is received from the target sensor.

[0018] The beneficial effects of this invention are as follows: 1. By using BIM spatial modeling and physical calculations of temperature and humidity, the system accurately identifies condensate interference areas, automatically marks false alarms, eliminates the need for manual point-by-point verification, significantly reduces invalid maintenance work orders, and saves manpower and time costs. Based on the inclination angle and curvature of the pipeline surface, it distinguishes between dispersed dripping surfaces and converging dripping points, and constructs a three-dimensional dripping envelope space with volume by combining material roughness, which completely covers all interference paths such as direct dripping, secondary splashing, and surface runoff, with no blind spots in identification.

[0019] 2. Employing dynamic horizontal slicing and graded distance judgment logic highly matched with sensors, it automatically adapts to on-site conditions such as pipe gallery size, pipeline material, and wind speed fluctuations. The judgment results are more in line with the actual project, with sufficient safety redundancy. Through triple physical calculations of condensation generation rate, evaporation loss, and surface tension critical value, it accurately determines whether water droplets are actually dripping, neither shielding real leaks nor ignoring condensation interference, ensuring the monitoring system is rigorous and reliable. Attached Figure Description

[0020] The invention will now be further described with reference to the accompanying drawings.

[0021] Figure 1 This is a system module diagram of an intelligent operation and maintenance management system for underground integrated utility tunnels based on BIM, according to the present invention. Figure 2 This is a flowchart illustrating the steps of an intelligent operation and maintenance management method for underground integrated utility tunnels based on BIM, as described in this invention. Detailed Implementation

[0022] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments. Example

[0023] like Figure 1 As shown in the embodiment of the present invention, an intelligent operation and maintenance management system for underground integrated utility tunnels based on BIM belongs to operation and maintenance scheduling management. By integrating the three-dimensional spatial information of the utility tunnel BIM, multi-source environmental sensor data, and the physical mechanism of condensation mass transfer, it realizes the identification of pipeline condensation areas, modeling of drip space, screening of disturbed sensors, and intelligent identification of false alarms of water immersion alarms. It includes the following modules: Condensation node identification module: acquires real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines, and marks the condensate generation node areas on the surface of the upper pipelines; In some specific embodiments, the process by which the condensation node identification module acquires real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines is as follows: Data is collected by various monitoring sensors deployed within the utility tunnel. The real-time ambient temperature and relative humidity inside the pipe gallery are obtained by an ambient temperature and humidity sensor; the real-time ambient wind speed inside the pipe gallery is obtained by an air speed sensor; and the surface temperature data of the upper pipes is obtained by a temperature sensor attached to the surface of the upper pipes. The real-time environmental parameters include: real-time ambient temperature inside the pipe gallery, real-time relative humidity inside the pipe gallery, real-time ambient wind speed inside the gallery, and surface temperature data of the upper pipeline. In some specific embodiments, the process of marking the condensate generation node area on the surface of the upper pipeline in the condensate node identification module is as follows: Based on the real-time environmental parameters, the ambient dew point temperature under the current utility tunnel environment is calculated using the Magnus formula. For example, the specific process of calculating the ambient dew point temperature under the current pipe gallery environment is as follows: The dew point temperature is solved step by step using the Magnus formula. First, the corresponding saturated vapor pressure is calculated based on the real-time ambient temperature inside the pipe gallery. The actual water vapor pressure in the environment is calculated by combining the real-time relative humidity inside the pipe gallery. The ambient dew point temperature is calculated by back-calculating the actual saturated water vapor pressure. ,in, This refers to the real-time ambient temperature inside the utility tunnel, in degrees Celsius. Real-time relative humidity inside the utility tunnel, in percentage. The saturated vapor pressure corresponding to the real-time ambient temperature inside the corridor, in kilopascals. This is the actual saturated water vapor pressure, in kilopascals. To solve for the obtained ambient dew point temperature in degrees Celsius, It is a natural exponential function. It is the natural logarithm function; The surface temperature data of the upper pipeline is compared with the ambient dew point temperature in real time. If the surface temperature data is less than or equal to the ambient dew point temperature, it is determined that the pipeline surface area where the temperature sensor is located meets the condensation conditions, and the upper pipeline surface area monitored by the temperature sensor is marked as a condensate generation node area in the pipe gallery BIM model. Those skilled in the art should understand that the Magnus formula is an empirical formula for calculating dew point temperature with high accuracy based on ambient temperature and relative humidity. When the surface temperature of the pipeline drops to or below the dew point temperature, the water vapor in the air around the pipeline will reach saturation, thereby precipitating liquid water on the pipeline surface. It should be noted that, due to the narrow and long interior space of the utility tunnel and the existence of local microclimate differences, by accurately comparing the real-time calculated ambient dew point temperature with the actual surface temperature of the pipeline, the physical area where condensation actually occurs can be dynamically and accurately delineated in the utility tunnel BIM model, providing an accurate spatial starting point for subsequent drip analysis. The drip space modeling module obtains the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model. Based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, the condensate generation node area is divided into dispersed drip surfaces or converged drip points as the initial starting point, and a three-dimensional drip space model with volume is constructed downwards. In some specific embodiments, the specific process of obtaining the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model in the drip space modeling module is as follows: Obtain the BIM model of the pipe gallery, and extract the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery; In some specific embodiments, in the drip space modeling module, the specific process of dividing the condensate generation node area into dispersed drip surfaces or converging drip points as the initial starting point, based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, is as follows: Extract the surface geometric parameters of the condensate generation node area in the BIM model of the pipe gallery, including the surface inclination angle and surface curvature; If the surface tilt angle is less than or equal to the horizontal tilt angle threshold and the surface curvature is less than or equal to the flat curvature threshold, then the condensate generation node area is divided into a dispersed dripping surface. If the surface tilt angle is greater than the horizontal tilt angle threshold, or the surface curvature is greater than the flat curvature threshold, it is determined that the water droplets physically converge under the action of gravity and surface tension, and the condensate generation node area is divided into convergence droplet points. Determine the initial starting point based on the partitioning results: If the condensate generation node area is divided into a dispersed dripping surface, then the overall geometric boundary contour of the condensate generation node area is taken as the initial starting point. If the condensate generation node area is divided into convergence and dripping points, then the local lowest point of the condensate generation node area in the direction of gravity is extracted as the initial starting point. In some specific embodiments, the process of constructing a three-dimensional droplet space model with volume in the droplet space modeling module is as follows: In the BIM model of the utility tunnel, an initial starting point is obtained, and a vertically downward center drop trajectory is generated along the direction of the gravitational acceleration vector, with the initial starting point as the top. Extract the material roughness of the upper-level pipeline in the BIM model of the utility tunnel, and match the corresponding natural diffusion angle based on the material roughness; Using the central drop trajectory as the central axis, a three-dimensional geometric expansion is carried out outward along the downward direction of gravity according to the natural diffusion angle to construct a three-dimensional drop space model with volume; For example, the specific process of matching the corresponding natural diffusion angle based on the material roughness is as follows: Obtain the material roughness of the upper-level pipelines in the BIM model of the utility tunnel, and then use a quantitative correlation model between roughness and natural diffusion angle. The corresponding natural diffusion angle is calculated. The natural diffusion angle is determined by the micro-roughness of the pipeline surface. The greater the roughness, the stronger the surface tension tearing unevenness when the water droplets fall off, the greater the fall offset range, and the larger the natural diffusion angle. For the final solution of the natural spread angle, The base diffusion angle is the inherent offset angle corresponding to a smooth material, and its value is [value missing]. , This is a roughness angle correction factor, a constant, with a value of [value missing]. , For pipeline surface roughness parameters stored in the BIM model, units: ; If the initial starting point is the convergence point of the droplet, then take the local lowest point as the vertex, take the downward direction of gravity as the axis, and rotate and sweep according to the natural diffusion angle as the semi-cone angle to generate an inverted cone-shaped three-dimensional droplet space model. If the initial starting point is a dispersed dripping surface, then the overall geometric boundary contour is used as the top surface, and the overall geometric boundary contour is discretized and sampled according to the preset boundary sampling step size to obtain a set of discrete boundary points; each discrete point in the set of discrete boundary points is linearly swept outward along the downward direction of gravity and according to the natural diffusion angle to generate a downward diverging platform-shaped three-dimensional dripping space model. It should be noted that the boundary sampling step size is a distance threshold preset based on the grid accuracy of the utility tunnel BIM model (for example, set to 1 cm to 5 cm). Since the overall geometric boundary contour in the BIM model is mathematically a continuous curve or polyline, the computer cannot directly perform infinite sweep calculations on the continuous line segment. Therefore, this solution uses a preset boundary sampling step size to cut the continuous boundary contour at equal intervals and extract a set of boundary discrete points with clear coordinates. Those skilled in the art should understand that through this discretization sampling, BIM software (such as the secondary development interface of Revit or Navisworks) can use these discrete points as a reference to uniquely and definitively execute an outward linear sweep algorithm, ultimately generating a frustum-like envelope volume that is smaller at the top and larger at the bottom by these sweep lines. This not only eliminates the ambiguity in the geometric generation logic, but also significantly reduces the computational power consumption of 3D spatial modeling, fully ensuring the feasibility of the technical solution. Suspected sensor screening module: Calculates the shortest horizontal distance between each sensor and the boundary of the three-dimensional drip space model at the corresponding height, and screens out suspected sensors affected by condensation based on the shortest horizontal distance; In some specific embodiments, the process of calculating the shortest horizontal distance between each sensor and the boundary of the three-dimensional droplet space model at the corresponding height in the suspected sensor screening module is as follows: Extract the three-dimensional spatial coordinates of each sensor in the utility tunnel in the utility tunnel BIM model. The three-dimensional spatial coordinates include the X-axis coordinate, the Y-axis coordinate, and the Z-axis coordinate representing the height. For each sensor, a horizontal tangent plane is generated in the BIM model of the utility tunnel, with its corresponding Z-axis coordinate as the reference height. By geometrically intersecting the horizontal cutting plane with the three-dimensional drip space model, a local horizontal cross-section at the reference height is obtained. Within the horizontal tangent plane, the shortest horizontal distance between the coordinate point of the sensor and the outer edge of the local horizontal cross-section is calculated using the two-dimensional Euclidean distance formula; if the sensor is located inside the local horizontal cross-section, the shortest horizontal distance is recorded as zero. In some specific embodiments, the process of filtering suspected sensors affected by condensation water in the suspected sensor screening module based on the shortest horizontal distance is as follows: Calculate the maximum distance between two points on the local horizontal cross-section and use it as the dynamic judgment threshold specific to this sensor; If the calculated shortest horizontal distance is less than or equal to the dynamic judgment threshold, the sensor is marked as a suspected sensor affected by condensation. If the calculated shortest horizontal distance is greater than the dynamic judgment threshold but less than or equal to twice the dynamic judgment threshold, then the sensor is marked as a suspected sensor affected by condensation. If the calculated shortest horizontal distance is greater than twice the dynamic judgment threshold, then the sensor is marked as a sensor unaffected by condensation.

[0024] It should be noted that, since the cross-sectional area of ​​the three-dimensional droplet space model (inverted cone or downwardly diverging frustum) gradually increases with decreasing height, this scheme abandons the traditional globally unified threshold and innovatively introduces a dynamic slicing logic based on elevation matching. By extracting a local horizontal cross-section at the same height as the sensor to calculate the dynamic judgment threshold, it can adapt to different droplet models.

[0025] Those skilled in the art will understand that this dynamic judgment logic closely aligns with the splashing principle in fluid mechanics: the lower the sensor's position, the greater the kinetic energy accumulated by the falling water droplets, and the wider the secondary splash radius and spread range after hitting the support or ground; thus, the captured local horizontal cross-sectional span (i.e., the dynamic judgment threshold) is naturally larger. Using a graded distance judgment logic, when the shortest horizontal distance is between the dynamic judgment threshold and twice the dynamic judgment threshold, the sensor is located in the edge of the spillway of accumulated water along the support surface or the drift of tiny water mists. To ensure absolute safety and redundancy of the false alarm prevention mechanism, this area is also included in the category of suspected sensors, thereby achieving precise and rigorous elimination of condensate interference in physical space.

[0026] False alarm identification and marking module: Based on real-time environmental parameters and pipeline surface temperature data, calculate the condensate generation rate and current cumulative volume in the condensate generation node area, and determine whether dripping will occur. If so, the corresponding suspected sensor is identified as the target sensor, and it is marked as a condensate false alarm when a water immersion alarm is received from the target sensor.

[0027] In some specific embodiments, the false alarm identification and marking module calculates the condensate generation rate and current cumulative volume in the condensate generation node area based on real-time environmental parameters and pipeline surface temperature data, and determines whether dripping will occur. The specific process is as follows: Based on the real-time ambient temperature and real-time relative humidity in the pipe gallery from the real-time environmental parameters, the real-time absolute humidity parameter in the pipe gallery is calculated; and the condensation temperature difference between the surface temperature data of the upper pipeline and the ambient dew point temperature is calculated, where the condensation temperature difference = ambient dew point temperature - surface temperature data of the upper pipeline. The real-time absolute humidity parameters, the condensation temperature difference, and the surface area of ​​the condensate generation node area in the pipe gallery are obtained, and the condensate generation rate in the condensate generation node area is calculated using the condensation mass transfer model. The process for obtaining the surface area of ​​the condensate generation node region is as follows: The BIM model of the utility tunnel is obtained, and the geometric mesh boundary of the continuous surface area marked as the condensate generation node area is extracted. Based on the geometric mesh boundary, the actual physical area of ​​the continuous surface area is calculated using the polygon area integration algorithm, and it is used as the surface area of ​​the condensate generation node area. For example, the specific process for calculating the condensate generation rate in the condensate generation node region is as follows: The condensate formation rate is calculated using the convective mass transfer formula, specifically: in, For the rate of condensate formation, The convective mass transfer coefficient (determined by the real-time ambient wind speed inside the pipe gallery). The surface area of ​​the condensate generation node region. This refers to the real-time absolute humidity parameters within the utility tunnel. To determine the saturated absolute humidity corresponding to the pipeline surface temperature, we first calculate the saturated vapor pressure corresponding to the pipeline surface temperature data using Magnus's formula, and then convert it using the ideal gas law. The formula is as follows: , The mass transfer concentration difference is driven by the condensation temperature difference; A dynamic monitoring time window is set, and the condensate generation rate is calculated by time integration within the dynamic monitoring time window to obtain the initial cumulative amount of condensate. For example, the specific process of calculating the initial cumulative amount of condensate by performing time integral calculation on the condensate generation rate is as follows: Set the dynamic monitoring time window as The initial accumulation of condensate within the dynamic monitoring time window was calculated using the definite integral formula. ,in, This is the initial accumulated amount of condensate. The rate of condensate formation varies over time. The density of liquid water, To monitor the start time, The current moment; Simultaneously, the surface evaporation rate is calculated based on the real-time ambient wind speed, real-time ambient temperature, and real-time relative humidity in the pipe gallery. The current cumulative volume of the condensate generation node area is obtained by subtracting the evaporation amount of the surface evaporation rate within the same dynamic monitoring time window from the initial cumulative amount of condensate. For example, the specific process for calculating the surface evaporation rate and the current cumulative volume is as follows: Surface evaporation rate was calculated using an aerodynamic evaporation model. ,in, For surface evaporation rate, The evaporation coefficient is... The surface area of ​​the condensate generation node region. The saturated vapor pressure at the pipeline surface temperature. This represents the actual water vapor pressure in the environment. This refers to the real-time ambient wind speed inside the utility tunnel. This refers to the wind speed influence coefficient. Then calculate the current accumulated volume. ,in, This refers to the current cumulative volume of the condensate generation node region; The BIM model of the utility tunnel is analyzed to obtain the surface tension coefficient and solid-liquid contact angle of the pipeline material. Based on the surface tension coefficient, the solid-liquid contact angle and the gravitational acceleration, the maximum volume in which a water droplet can maintain its adhesion on the surface of the pipeline material is calculated and used as the critical value for surface tension droplet. For example, the specific process for calculating the critical value of surface tension droplet is as follows: Based on the principles of fluid statics and surface tension balance, when a water droplet is about to fall, the components of gravity and surface tension along the contact line reach equilibrium, as shown in the formula: ,in, This is the critical value for surface tension droplet formation. The density of liquid water, It is the acceleration due to gravity. The surface tension coefficient of the pipeline material. The solid-liquid contact angle is... Let be the equivalent contact radius of the water droplet on the pipe surface; we obtain the solution by rearranging terms: ; The current accumulated volume is compared with the surface tension drop threshold in real time; If the current accumulated volume is greater than the surface tension dripping threshold, it is determined that a substantial dripping phenomenon has occurred in the condensate generation node area, and the corresponding suspected sensor screened in the suspected sensor screening module is confirmed as the target sensor. In some specific embodiments, in the false alarm identification and marking module, if a false alarm is detected, the corresponding suspected sensor is confirmed as the target sensor. The specific process of marking it as a condensate false alarm when a water immersion alarm is received from the target sensor is as follows: When a water immersion alarm signal is received from the target sensor, the system intercepts the routine pipeline leak emergency repair work order generated in response to the water immersion alarm signal and marks the alarm signal as a condensate false alarm in the system. It should be noted that condensation is a dynamic process that accumulates over time, and changes in airflow within the pipe gallery can cause the condensate to re-evaporate. By dynamically integrating the amount of condensate generated versus the amount of evaporation, the current cumulative volume of condensate on the pipe surface can be most accurately determined. Those skilled in the art should understand that whether a water droplet can fall depends on the physical interplay between gravity and surface tension. The critical value for surface tension-induced dripping is highly correlated with the pipeline material. Only when the current accumulated volume exceeds this critical value will a real physical dripping occur. This step, through this physical quantitative comparison, accurately pinpoints the physical moment when the water droplet hits the sensor below, completely eliminating the logical loophole of the system prematurely blocking the alarm as soon as the pipeline fogs up, thus ensuring the rigor of the pipeline corridor security monitoring. Example

[0028] like Figure 2 As shown, based on the specific implementation process of Embodiment 1, the present invention provides a BIM-based intelligent operation and maintenance management method for underground integrated utility tunnels, including the following steps: Step S10: Obtain real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines, and mark the condensate generation node areas on the surface of the upper pipelines; Step S20: Obtain the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model. Based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, divide the condensate generation node area into a dispersed dripping surface or a converged dripping point as the initial starting point, and construct a three-dimensional dripping space model with volume downwards. Step S30: Calculate the shortest horizontal distance between each sensor and the boundary of the three-dimensional drip space model at the corresponding height, and screen out the suspected sensors affected by condensation based on the shortest horizontal distance; Step S40: Based on real-time environmental parameters and pipeline surface temperature data, calculate the condensate generation rate and current cumulative volume in the condensate generation node area, and determine whether dripping will occur. If so, confirm the suspected sensor as the target sensor, and mark it as a false condensate alarm when a water immersion alarm is received from the target sensor.

[0029] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels, characterized in that: include: Condensation node identification module: acquires real-time environmental parameters within the pipe gallery and surface temperature data of the upper pipelines, and marks the condensate generation node areas on the surface of the upper pipelines; The drip space modeling module obtains the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model. Based on the surface geometry of the condensate generation node area in the pipe gallery BIM model, the condensate generation node area is divided into dispersed drip surfaces or converged drip points as the initial starting point, and a three-dimensional drip space model with volume is constructed downwards. Suspected sensor screening module: Calculates the shortest horizontal distance between each sensor and the boundary of the three-dimensional drip space model at the corresponding height, and screens out suspected sensors affected by condensation based on the shortest horizontal distance; False alarm identification and marking module: Based on real-time environmental parameters and pipeline surface temperature data, calculate the condensate generation rate and current cumulative volume in the condensate generation node area, and determine whether dripping will occur. If so, the suspected sensor is identified as the target sensor, and it is marked as a condensate false alarm when a water immersion alarm is received from the target sensor.

2. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process for obtaining real-time environmental parameters within the utility tunnel is as follows: Real-time environmental parameters include: real-time ambient temperature inside the utility tunnel, real-time relative humidity inside the utility tunnel, real-time ambient wind speed inside the tunnel, and surface temperature data of the upper pipelines. The real-time ambient temperature and relative humidity inside the pipe gallery are obtained by an ambient temperature and humidity sensor, the real-time ambient wind speed inside the pipe gallery is obtained by an air speed sensor, and the surface temperature data of the upper pipes is obtained by a temperature sensor attached to the surface of the upper pipes.

3. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process of marking the condensate generation node area on the surface of the upper pipeline is as follows: The ambient dew point temperature under the current pipe gallery environment is calculated using the Magnus formula, and the surface temperature data of the upper pipeline is compared with the ambient dew point temperature in real time. If the surface temperature data is less than or equal to the ambient dew point temperature, the surface area of ​​the upper pipeline monitored by the temperature sensor will be marked as a condensate generation node area in the pipe gallery BIM model.

4. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process for obtaining the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the pipe gallery BIM model is as follows: Obtain the BIM model of the utility tunnel and extract the three-dimensional spatial coordinates of the condensate generation node area and each sensor in the utility tunnel.

5. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific division process of the initial starting point is as follows: Extract the surface geometric parameters of the condensate generation node area in the pipe gallery BIM model, including surface inclination and surface curvature; If the surface tilt angle is less than or equal to the horizontal tilt angle threshold and the surface curvature is less than or equal to the flat curvature threshold, then the condensate generation node area is divided into a dispersed dripping surface. If the surface tilt angle is greater than the horizontal tilt angle threshold, or the surface curvature is greater than the flat curvature threshold, then the condensate generation node area is divided into a convergence drip point. If the condensate generation node area is divided into a dispersed dripping surface, then the overall geometric boundary profile of the condensate generation node area is taken as the initial starting point. If the condensate generation node area is divided into convergence and dripping points, then the lowest point of the condensate generation node area is extracted as the initial starting point.

6. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process of constructing a three-dimensional droplet space model with volume is as follows: If the initial starting point is the convergence point of the droplet, then the lowest point is taken as the vertex, the downward direction of gravity is taken as the axis, and the natural diffusion angle is taken as the semi-cone angle to generate a three-dimensional droplet space model. If the initial starting point is a dispersed dripping surface, then the geometric boundary contour is used as the top surface, and the overall geometric boundary contour is discretized and sampled according to the preset boundary sampling step size to obtain the set of discrete boundary points; Each discrete point in the boundary discrete point set is linearly swept outward along the downward direction of gravity and according to the natural diffusion angle to generate a three-dimensional droplet space model.

7. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process for calculating the shortest horizontal distance between each sensor and the boundary of the three-dimensional droplet space model at the corresponding height is as follows: Extract the three-dimensional spatial coordinates of each sensor in the BIM model of the utility tunnel. The three-dimensional spatial coordinates include the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate. Using the Z-axis coordinate of the sensor as the reference height, a horizontal tangent plane is generated in the BIM model of the utility tunnel; Geometrically intersect the horizontal cutting plane with the three-dimensional droplet space model to obtain the local horizontal cross section at the reference height; Within the horizontal tangent plane, the shortest horizontal distance between the sensor's coordinates and the outer edge of the local horizontal cross-section is calculated using the two-dimensional Euclidean distance formula. If the sensor is located inside the local horizontal cross-section, the shortest horizontal distance is recorded as zero.

8. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process for screening out suspected sensors affected by condensation is as follows: Calculate the maximum distance between two points on a local horizontal cross-section and use it as the sensor's dynamic judgment threshold; If the shortest horizontal distance is less than or equal to the dynamic judgment threshold, the sensor will be marked as a suspected sensor affected by condensation. If the shortest horizontal distance is greater than the dynamic judgment threshold but less than or equal to twice the dynamic judgment threshold, the sensor will be marked as a suspected sensor affected by condensation. If the shortest horizontal distance is greater than twice the dynamic judgment threshold, the sensor will be marked as a sensor unaffected by condensation.

9. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific process for identifying a suspected sensor as the target sensor is as follows: Based on the real-time ambient temperature and real-time relative humidity in the pipe gallery, the real-time absolute humidity parameter in the pipe gallery is calculated, and the condensation temperature difference between the surface temperature data of the upper pipeline and the ambient dew point temperature is calculated. The real-time absolute humidity parameter, condensation temperature difference and surface area of ​​the condensate generation node area in the pipe gallery are obtained, and the condensate generation rate of the condensate generation node area is calculated. Set a dynamic monitoring time window, and calculate the condensate generation rate by time integration within the dynamic monitoring time window to obtain the initial cumulative amount of condensate. The surface evaporation rate is calculated based on the real-time ambient wind speed, real-time ambient temperature and real-time relative humidity in the pipe gallery. The current cumulative volume of the condensate generation node area is obtained by subtracting the evaporation amount of the surface evaporation rate within the same dynamic monitoring time window from the initial cumulative amount of condensate. The surface tension coefficient and solid-liquid contact angle of the pipeline material are obtained. Based on the surface tension coefficient, solid-liquid contact angle and gravitational acceleration, the maximum volume of water droplets on the surface of the pipeline material is calculated as the critical value of surface tension droplet. If the current accumulated volume is greater than the surface tension dripping threshold, it is determined that a substantial dripping phenomenon has occurred in the condensate generation node area, and the suspected sensor is confirmed as the target sensor.

10. The BIM-based intelligent operation and maintenance management system for underground integrated utility tunnels according to claim 1, characterized in that, The specific procedure for marking a water immersion alarm received from the target sensor as a false alarm is as follows: When a water immersion alarm is received from the target sensor, the maintenance work order generated for the water immersion alarm is intercepted, and the water immersion alarm is marked as a false alarm for condensation.

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