BIM-based 3D virtual inspection method and system for power plant equipment

Abstract

The present invention discloses a 3D virtual inspection method and system for power plant equipment based on BIM, which relates to the technical field of power plant inspection. The method includes: obtaining the BIM modeling data set of power plant equipment through a data interface, and performing model simulation to output a BIM power plant equipment model; reading the historical SIS operation data of power plant equipment based on this model, conducting peak operation period analysis, clustering the equipment in the same peak period to form multiple groups of equipment; planning inspection paths for each group of equipment, generating inspection path items, and sending them to the inspection management terminal for inspection feedback. The present invention solves the technical problems of the existing power plant equipment inspection method, such as low efficiency, incomplete coverage, and difficulty in accurately identifying the equipment failure risks during peak operation periods, and achieves the technical effects of 3D virtual inspection based on BIM, realizing intelligent path planning and peak period analysis, and improving the inspection efficiency and risk identification accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of power plant inspection, and in particular to a BIM-based three-dimensional virtual inspection method and system for power plant equipment. Background Art

[0002] With the development of the power industry and the continuous improvement of equipment management efficiency, the traditional inspection method of power plant equipment has gradually exposed many problems. For example, traditional manual inspection is not only inefficient and inaccurate, but also prone to omissions or misjudgments due to factors such as complex equipment and poor working environment. In addition, the operating load of power plant equipment is large, and failures occur periodically and at peak times, which requires the inspection method to be reasonably planned and arranged according to the working characteristics of different equipment. Therefore, how to conduct equipment inspections efficiently and accurately in power plants, reduce human errors, and improve inspection coverage and efficiency has become a technical problem that needs to be solved urgently in the power industry. Summary of the invention

[0003] The present application provides a BIM-based three-dimensional virtual inspection method and system for power plant equipment, which is used to solve the technical problems that existing power plant equipment inspection methods are inefficient, have incomplete coverage, and are difficult to accurately identify equipment failure risks during peak operating hours.

[0004] The first aspect of the present application provides a BIM-based three-dimensional virtual inspection method for power plant equipment, the method comprising: obtaining a BIM modeling data set of power plant equipment through a data interface; performing model simulation according to the BIM modeling data set of the power plant equipment, and outputting a BIM power plant equipment model; calling the BIM power plant equipment model to read a historical SIS operation data set of each power plant equipment, performing a peak operation period analysis on each power plant equipment according to the historical SIS operation data set, clustering power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment; performing inspection path planning for each group of power plant equipment in the multiple groups of power plant equipment, generating inspection path items, and sending the inspection path items to the inspection management end for inspection feedback.

[0005] In the second aspect of the present application, a 3D virtual inspection system for power plant equipment based on BIM is provided. The system includes: a modeling data set acquisition module for acquiring a BIM modeling data set of power plant equipment through a data interface; a model simulation module for performing model simulation according to the BIM modeling data set of power plant equipment and outputting a BIM power plant equipment model; a peak operation period analysis module for calling the BIM power plant equipment model to read the historical SIS operation data sets of each power plant equipment, analyzing the peak operation periods of each power plant equipment according to the historical SIS operation data sets, and clustering the power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment; an inspection path planning module for planning an inspection path for each group of power plant equipment in the multiple groups of power plant equipment, generating an inspection path item, and sending the inspection path item to an inspection management terminal for inspection feedback.

[0006] In the third aspect of the present application, an electronic device is provided, including: a processor coupled to a memory for storing a program, which when executed by the processor causes the system to execute the method according to any one of the first aspect.

[0007] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0008] The 3D virtual inspection method and system for power plant equipment based on BIM provided in the present application relate to the technical field of power plant inspection. By acquiring BIM modeling data of power plant equipment and performing simulation, combining historical SIS data to analyze peak operation periods, clustering equipment according to the same peak period, planning inspection paths for each group of equipment, generating inspection path items and sending them to the inspection management terminal for inspection feedback, it solves the technical problems of low efficiency, incomplete coverage of the existing power plant equipment inspection method, and difficulty in accurately identifying the equipment failure risk during peak operation periods, realizes 3D virtual inspection based on BIM, realizes intelligent path planning and peak period analysis, improves inspection efficiency and risk identification accuracy, and reduces the risk of equipment failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0010] Figure 1Schematic diagram of the process of the 3D virtual inspection method for power plant equipment based on BIM provided by the embodiments of the present application;

[0011] Figure 2 Schematic diagram of the structure of the 3D virtual inspection system for power plant equipment based on BIM provided by the embodiments of the present application;

[0012] Figure 3 The present application provides a schematic diagram of the structure of an electronic device.

[0013] Explanation of reference numerals: Modeling data set acquisition module 11, model simulation module 12, peak operation period analysis module 13, inspection path planning module 14, electronic device 300, memory 301, processor 302, communication interface 303, bus architecture 304. Detailed implementation manners

[0014] The present application provides a 3D virtual inspection method and system for power plant equipment based on BIM, which is used to solve the technical problems of low efficiency, incomplete coverage of the existing power plant equipment inspection method, and difficulty in accurately identifying the equipment failure risk during peak operation periods.

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0016] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0017] Embodiment 1, as Figure 1 shown, the present application provides a 3D virtual inspection method for power plant equipment based on BIM, and the method includes:

[0018] P10: Obtain the BIM modeling data set of power plant equipment through the data interface.

[0019] Specifically, obtain the BIM modeling dataset of power plant equipment from the power plant equipment management system through a data interface. Specifically, the data interface uses a standardized communication protocol (such as an API interface or Web Service) to interact with the power plant equipment management system to ensure the timeliness and accuracy of data. The BIM modeling dataset includes, but is not limited to, the three-dimensional geometric model of power plant equipment, spatial location information, equipment attributes (such as equipment type, specification parameters, operating status, etc.), and the topological relationship between equipment. As shown in Table 1:

[0020]

[0021] These data are the basis for constructing the BIM power plant equipment model and provide necessary technical support for subsequent model simulation and virtual inspection. Obtaining the BIM modeling dataset through the data interface not only realizes the automated collection of data but also avoids errors that may be caused by manual input, improving the efficiency and reliability of data processing. In addition, the data interface also supports the integration of multi-source data, such as data docking with the SIS system, video monitoring system, etc., further enriching the content of the BIM modeling dataset and providing comprehensive data support for subsequent peak operation period analysis and inspection path planning.

[0022] P20: Perform model simulation according to the BIM modeling dataset of power plant equipment and output the BIM power plant equipment model.

[0023] Optionally, perform model simulation based on the obtained BIM modeling dataset of power plant equipment and output a complete BIM power plant equipment model. The core of this process is to convert the equipment information in the BIM dataset into a three-dimensional simulation model, which can intuitively display the geometric shape, structural characteristics, and operating parameters of power plant equipment, thus providing detailed visual support for subsequent analysis and operation.

[0024] First, use BIM modeling software (such as Revit, Navisworks, etc.) to parse the BIM modeling dataset and extract the three-dimensional geometric information, spatial location, and attribute data of the equipment; second, construct a three-dimensional virtual model of the power plant equipment according to the extracted data to ensure that the model is consistent with the actual equipment in terms of geometric accuracy, spatial relationship, and attribute information; finally, perform optimization processing on the model, including simplifying complex geometric structures, optimizing rendering effects, and adding interactive functions to improve the usability and visualization effect of the model.

[0025] In addition, the BIM power plant equipment model can not only truly reflect the physical state of power plant equipment, but also support dynamic data binding. For example, it associates the real-time operation data of equipment (such as temperature, pressure, vibration, etc.) with the model to achieve real-time monitoring and visual display of equipment status. Moreover, the model simulation process also supports multi-dimensional analysis, such as the thermal distribution and stress distribution of equipment, providing technical support for the evaluation of equipment operation status and fault warning.

[0026] After the simulation is completed, a complete BIM power plant equipment model is output. This model contains the three-dimensional geometric information of all equipment and has interactivity, allowing users to view various angles, details of the equipment, and the interrelationships with other equipment, providing a necessary basis for subsequent equipment status analysis, fault prediction, maintenance planning, and inspection path planning.

[0027] P30: Call the BIM power plant equipment model to read the historical SIS operation data sets of each power plant equipment, perform peak operation period analysis on each power plant equipment according to the historical SIS operation data sets, and cluster the power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment.

[0028] Furthermore, step P30 of the embodiment of the present application further includes:

[0029] P31: Perform peak operation period analysis on each power plant equipment according to the historical SIS operation data sets, obtain time characteristics and parameter characteristics, and identify the peak operation periods of each power plant equipment according to the time characteristics and parameter characteristics; P32: Among them, the time characteristics include peak period length, frequency, and duration variance, and the parameter characteristics include peak parameter values, parameter change rates, and load resistance capabilities.

[0030] It should be understood that by calling the BIM power plant equipment model, the historical SIS operation data sets of each power plant equipment are read through its built-in data interface. The historical SIS operation data sets include the key parameters (such as temperature, pressure, flow rate, power, etc.) of the equipment during historical operation and their time series data as shown in Table 2:

[0031]

[0032] Based on the historical SIS operation data sets, adopt peak operation period analysis technology to deeply analyze the operation status of each power plant equipment and identify its peak operation periods. The purpose of this process is to identify the operation characteristics of the equipment at different time periods, especially the peak operation periods with high load and high risk, to help optimize the inspection and maintenance plans of the equipment.

[0033] First, analyze the peak operation periods of power plant equipment based on historical SIS operation datasets. This analysis mainly focuses on the performance of equipment during different operation periods, especially during periods of heavy load or prone to failure. The historical SIS datasets include operation data of equipment, such as parameters like power, pressure, temperature, failure records, and load conditions, etc. Through the analysis of these data, the system can identify the peak operation periods of equipment and mark the high-risk states where equipment is prone to failure or anomalies during certain periods.

[0034] During the analysis process, extract time features and parameter features to assist in identifying peak operation periods. Time features include the length, frequency, and duration variance of peak periods. The length of the peak period refers to the time that the equipment operates continuously under high load, the frequency indicates the frequency of the equipment experiencing peak operation states, and the duration variance reflects the stability or volatility of the peak period, which helps to evaluate whether the equipment operates in a changing load environment. Parameter features include peak parameter values, parameter change rates, and the load resistance ability of the equipment. The peak parameter value refers to the maximum operation parameter reached by the equipment during the peak period, the change rate indicates the response speed of the equipment under high load, and the load resistance ability evaluates the stable operation ability of the equipment under high load.

[0035] Based on these time features and parameter features, conduct cluster analysis on power plant equipment. The equipment is divided into different groups according to its performance during peak operation periods. The operation features such as load and pressure of the equipment within each group are similar during peak periods. Through cluster analysis, the power plant equipment is effectively grouped according to its operation states during peak periods, providing an important basis for subsequent inspection path planning, equipment maintenance, and fault prediction. This analysis not only helps to identify the peak periods of equipment but also enables the formulation of personalized maintenance and inspection strategies for different equipment according to their peak operation characteristics, reducing the risk of failures and improving the operation efficiency of equipment.

[0036] Furthermore, cluster the power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment. Step P30 of the embodiment of the present application further includes:

[0037] P33: Set multiple levels of peak operation period intervals; P34: Compare the peak operation periods of each power plant equipment with the multiple levels of peak operation period intervals, and divide each power plant equipment to obtain multiple groups of power plant equipment.

[0038] Optionally, further cluster the power plant equipment in the same peak operation time period range to obtain multiple groups of power plant equipment. To this end, first set multiple peak operation time period ranges so that the equipment can be more finely grouped according to its different peak operation time periods. The setting of these multiple peak operation time period ranges takes into account factors such as the load characteristics, operation modes, and possible failure risks of the equipment. By setting different time period ranges, the operation status of the equipment under different peak load conditions can be accurately reflected.

[0039] Next, compare the peak operation time periods of each power plant equipment with the set multiple peak operation time period ranges, match the peak operation time period of each equipment with the corresponding range, and divide the equipment into multiple peak operation time period ranges. Through this comparison, the equipment will be assigned to one or more peak operation time period ranges, forming multiple groups. It should be noted that in this process, the power plant equipment within a group can appear repeatedly because the equipment may exhibit relatively similar operation characteristics in multiple peak operation time period ranges. Therefore, some equipment may appear in multiple groups, reflecting its commonalities and differences under different peak operation time periods.

[0040] Through this division of multiple peak operation time period ranges, the equipment can be more carefully grouped according to its performance in different peak time periods, providing a more accurate basis for subsequent inspection path planning, equipment management, and fault prediction. This grouping method makes the equipment within each group have similar peak operation characteristics, which helps to take more targeted measures in equipment maintenance and risk control to ensure the safe and stable operation of power plant equipment.

[0041] P40: Plan the inspection path for each group of power plant equipment in the multiple groups of power plant equipment, generate an inspection path item, and send the inspection path item to the inspection management end for inspection feedback.

[0042] Furthermore, step P40 of the embodiment of the present application further includes:

[0043] P41: Invoke the BIM power plant equipment model to obtain the relative position information of each power plant equipment in each group of power plant equipment, where each power plant equipment corresponds to an inspection node; P42: Combine the relative position information of all inspection nodes in each group of power plant equipment to obtain a first inspection path and the time loss data of the first inspection path; P43: If the time loss data is less than the preset time loss data, output the first inspection path as the inspection path corresponding to the group and store it in the inspection path item.

[0044] It should be understood that for the generated multiple groups of power plant equipment, inspection path planning is carried out to generate corresponding inspection path items, and these items are sent to the inspection management terminal for inspection feedback. The key to this process is to optimize the inspection path according to the specific conditions of each group of power plant equipment, so as to improve the inspection efficiency and reduce unnecessary time waste.

[0045] First, call the BIM power plant equipment model to obtain the relative position information of each equipment in each group of power plant equipment. In the BIM model, each component of the power plant equipment has a clear spatial position, so the relative position of each equipment can be accurately obtained. The position of each equipment can correspond to an inspection node, which represents the inspection point or target of the equipment during the inspection process, including the spatial coordinates of the equipment (such as X, Y, Z coordinates) and its specific position description in the power plant (such as floor, area, etc.). The inspection node of each equipment is the basic data to ensure that the inspection personnel check the equipment in sequence.

[0046] Next, combine the relative position information of all inspection nodes in each group of power plant equipment to carry out inspection path planning. By comprehensively considering the spatial positions of the equipment nodes, path planning algorithms (such as Dijkstra algorithm, A* algorithm or genetic algorithm) are used to generate a preliminary inspection path as the first inspection path, and calculate the time loss data of this path. The time loss data refers to the quantitative data of time waste or reduced inspection efficiency caused by unreasonable inspection paths or excessive distances between equipment during the inspection process. The path can be optimized according to factors such as the distance between equipment, the complexity of the inspection path, and the inspection priority of the equipment, and the time loss data required for the inspection can be calculated to evaluate the efficiency and feasibility of the inspection path.

[0047] Then, evaluate the generated first inspection path. If the time loss data of this path is less than the preset time loss standard, the path is output and saved as the inspection path for the corresponding group. If the calculation result shows that the time loss of the path is too large, the system will make adjustments or re-plan until the preset standard of time loss is met. Finally, the qualified inspection path will be stored in the inspection path item as a reference for actual inspection operations. As shown in Table 3:

[0048]

[0049] This process can ensure that the inspection path of each power plant equipment is optimized, that is, on the premise of ensuring the comprehensiveness of the inspection, it minimizes unnecessary time waste, improves the inspection efficiency, and reduces the burden of manual inspection. By sending the inspection path item to the inspection management terminal, the inspection personnel can carry out efficient inspections according to the path provided by the system and timely feedback the inspection results to ensure the stable operation and safety of the equipment.

[0050] Further, if the time loss data is greater than or equal to the preset time loss data, the embodiment of the present application further includes step P43a, and step P43a further includes:

[0051] P43-1a: If the time loss data is greater than or equal to the preset time loss data, obtain a first optimization instruction; P43-2a: According to the first optimization instruction, introduce a random number of nodes and calculate the difference between the current time loss data and the preset time loss data to optimize the node number interval of a single inspection path, and obtain an optimal solution for the node number interval; P43-3a: Plan inspection paths for each group of power plant equipment in the optimal solution of the node number interval, output multiple inspection paths for each group of power plant equipment, and encode and store the multiple inspection paths in the inspection path project.

[0052] Optionally, if the time loss data is greater than or equal to the preset time loss data standard, the inspection path can be further optimized to ensure that the time loss of the inspection is minimized. For example, by introducing an optimization mechanism to dynamically adjust the number of nodes in the inspection path, the time loss can be reduced and the inspection efficiency can be improved.

[0053] Exemplarily, first, when the calculated time loss data is greater than or equal to the preset time loss data, obtain a first optimization instruction. The purpose of this instruction is to guide the system to further adjust the path during the inspection path optimization process so that the time loss meets the set standard. By obtaining the optimization instruction, the system can enter the optimization mode and focus on optimizing various parameters of the inspection path, especially the adjustment of the number of nodes.

[0054] Next, according to the obtained first optimization instruction, introduce a random number of nodes and calculate the difference between the current time loss data of the inspection path and the preset time loss data. This difference reflects the optimization space of the inspection path. The larger the difference, the more the inspection path can be further optimized. The system will optimize the node number interval based on the current path, try different numbers of inspection nodes, calculate the time loss data according to the changes in these node numbers, and select an optimal solution for the node number interval, that is, the time loss of the inspection path is the smallest within this interval.

[0055] Further, using the optimized optimal solution of the node number interval, plan inspection paths for each group of power plant equipment. By adjusting the number of nodes and re-planning the inspection path according to the optimal solution, multiple possible inspection paths are output for each group of power plant equipment. Each path represents a possible optimization plan. Encode and store these paths in the inspection path project for subsequent selection and use. The generation of these feasible inspection paths takes into account factors such as time loss, inspection efficiency, and the distance between equipment, providing multiple alternative paths for the inspection personnel, so that the most suitable path can be selected for inspection according to the actual situation.

[0056] Through this optimization step, the node settings of the inspection path can be adjusted more flexibly, ensuring that the time loss during the inspection process is controlled within the preset range, and providing a more efficient and reasonable inspection path selection. This not only improves the inspection efficiency but also reduces the possible time waste during the inspection process, ensuring that the equipment maintenance work can proceed more smoothly.

[0057] Furthermore, after outputting multiple inspection paths for each group of power plant equipment, step P40 of the embodiment of the present application further includes:

[0058] P44: Connect to the personnel management module of the inspection management terminal, identify the status of the inspection personnel in the personnel management module, and assign the multiple inspection paths to multiple inspection personnel whose status is idle; P45: The multiple inspection personnel perform inspection feedback according to the assigned inspection paths, output multiple groups of inspection feedback data, and upload the multiple groups of inspection feedback data to the BIM power plant equipment model for fault visualization display.

[0059] Specifically, after outputting multiple inspection paths for each group of power plant equipment, the status of the inspection personnel can be further combined with the inspection path assignment to ensure the efficient assignment of multiple inspection paths and the real-time feedback of the inspection personnel.

[0060] First, connect to the personnel management module of the inspection management terminal and identify the status of the inspection personnel in this module. This status is used to identify whether each inspection personnel is in an idle state. The inspection management module compares the status of the personnel to be inspected with their idle status based on the status of each inspection personnel, so as to select multiple idle inspection personnel. Then, assign multiple inspection paths to the selected idle inspection personnel to ensure that each inspection path has a corresponding inspection personnel to execute. The assignment process can be optimized and matched according to the skill level of the inspection personnel, historical inspection records, and path complexity to improve the inspection efficiency and accuracy.

[0061] Next, the selected multiple inspection personnel start to perform inspections according to the assigned inspection paths and give feedback during the inspection process. During the inspection process, the inspection personnel record inspection data through a mobile terminal or an inspection management system, including equipment operation status, fault information, abnormal situations, etc. The inspection feedback data is stored in a structured form and uploaded to the BIM power plant equipment model in real time. As shown in Table 4:

[0062]

[0063] Finally, associate multiple groups of inspection feedback data with the equipment information in the BIM model to achieve visual display of faults. The visual display includes marking information such as the location, fault type, and severity of the faulty equipment in the BIM model, and presenting it intuitively through methods such as colors, icons, or text prompts, which facilitates managers to quickly locate and handle problems. Through this process, the power plant managers can view the operating status of the equipment in real time, detect potential faults, and take repair measures in a timely manner.

[0064] By combining the status of the inspection personnel with the allocation of inspection paths, not only is the effective allocation of inspection tasks ensured, but also the operating status of the equipment can be monitored in real time and fault prompts can be given through visualization means, further improving the intelligent level of power plant equipment operation and maintenance management.

[0065] Further, after obtaining the relative position information of each power plant equipment in each group of power plant equipment, step P40 of the embodiment of the present application further includes:

[0066] P42b: Construct a power plant equipment topology network according to the relative position information of each power plant equipment; P43b: Divide the power plant equipment topology network according to the multiple groups of power plant equipment, and output multiple topology sub-networks corresponding to the multiple groups of power plant equipment; P44b: Calculate the path adjoint loss for each inspection path in the multiple groups of power plant equipment according to the multiple topology sub-networks, obtain a set of path adjoint losses, and update the inspection path items according to the loss magnitudes of the set of path adjoint losses.

[0067] In a possible embodiment of the present application, after obtaining the relative position information of each equipment in each group of power plant equipment, a power plant equipment topology network can also be constructed according to the relative position information of each power plant equipment. The power plant equipment topology network is established based on the physical position relationship between the equipment and their connectivity in the overall layout of the power plant, which can help the system understand the spatial layout of the equipment and the association between each equipment, and can intuitively reflect the spatial distribution and connection relationship of the power plant equipment, ensuring that the inspection path planning not only considers the distribution of the equipment, but also pays attention to the logical and physical relationships between the equipment.

[0068] Next, divide the power plant equipment topology network according to the obtained multiple groups of power plant equipment, and output multiple topology sub-networks. Each topology sub-network corresponds to a group of power plant equipment, and these equipment are spatially related and have similar inspection characteristics. By dividing the equipment topology network, the system can allocate the equipment to different sub-networks according to the physical position relationship of each group of equipment, ensuring that the inspection paths of each group of equipment can minimize the path length and reduce unnecessary movement during the inspection process.

[0069] Next, based on the divided multiple topological sub-networks, calculate the path adjoint loss for the inspection paths within each group of power plant equipment. The path adjoint loss refers to the additional time loss during the inspection process due to the equipment positions, the connection relationships between equipment, and the design of the inspection paths. The adjoint loss of each path can be calculated according to the layout of each inspection path, the relative positions of the equipment, and the connectivity between the equipment. By analyzing the path characteristics and equipment relationships in the topological sub-network, the adjoint loss value of each inspection path is quantified. After the calculation, a set of adjoint losses for all paths is obtained, and the inspection path items are updated according to the magnitudes of these losses. The update process includes optimizing and adjusting the inspection paths with high adjoint losses, such as re-planning the path order, adding inspection nodes, or reducing path intersections, to reduce the adjoint loss and improve the inspection efficiency. The updated inspection paths are adjusted and optimized to ensure that the time loss of each path is minimized and the inspection efficiency is maximized.

[0070] Through these steps, the refined management and optimization of the inspection paths can be achieved, further improving the efficiency and reliability of the power plant equipment inspection.

[0071] Further, when calculating the path adjoint loss of the first group of power plant equipment, step P44b of this embodiment of the present application further includes:

[0072] P44-1b: Obtain the first topological sub-network corresponding to the first group of power plant equipment; P44-2b: Obtain the first group of inspection paths of the first group of power plant equipment, and the number of paths in the first group of inspection paths is a positive integer greater than or equal to 1; P44-3b: Select any inspection path within the first group of inspection paths, and on the first topological sub-network, identify the number of nodes whose relative distance to the inspection nodes on the inspection path is less than a preset distance until a set of node numbers corresponding to the first group of inspection paths is obtained; P44-4b: Calculate the variance of the node numbers to obtain a set of path adjoint losses.

[0073] Optionally, when calculating the path adjoint loss of the first group of power plant equipment, first, it is necessary to obtain the first topological sub-network corresponding to the first group of power plant equipment. This topological sub-network defines the connectivity between these equipment based on the physical positions and mutual relationships of the power plant equipment. Each sub-network contains the spatial layout and network structure of the relevant equipment, providing key data support for path calculation. Next, obtain the first group of inspection paths of the first group of power plant equipment. The number of paths in the first group of inspection paths is a positive integer greater than or equal to 1. The inspection paths are planned according to the equipment distribution and inspection requirements, and each path contains multiple inspection nodes to guide the specific inspection routes of the inspection personnel.

[0074] Further, select any one of the first group of inspection paths, and identify other nodes on this path whose relative distance from the inspection nodes on the inspection path is less than a preset distance. The preset distance refers to the distance range of adjacent devices that can be inspected conveniently by the inspection personnel when performing the inspection task. By calculating the distance between the inspection nodes and the adjacent nodes, the number of nodes that are not inspected but can be inspected conveniently on the inspection path is identified. Repeat the above process until the node number set corresponding to the first group of inspection paths is obtained. This node number set reflects the underutilized inspection opportunities on each inspection path.

[0075] Finally, calculate the variance of the obtained node numbers to obtain the path adjoint loss set. The variance of the node numbers can reflect the inspection balance among various devices in the inspection path. If the variance is large, it indicates that there may be an uneven distribution of inspection points in the inspection path, that is, there is a large room for optimization in the planning of the inspection path. Some devices may be inspected multiple times, while other devices may not be inspected in time. Through variance calculation, the adjoint loss of the inspection path can be quantified and the path adjoint loss set can be generated, thereby providing a basis for path optimization.

[0076] Through these steps, the adjoint loss of each inspection path can be accurately calculated, providing data support for subsequent path optimization, thereby improving the inspection efficiency and resource utilization rate.

[0077] Further, update the inspection path item according to the loss magnitude of the path adjoint loss set. Step P44b of the embodiment of the present application further includes:

[0078] Updating the inspection path item according to the loss magnitude of the path adjoint loss set includes incorporating inspection nodes whose relative distance from the inspection nodes on the selected inspection path is less than a preset distance on the selected inspection path.

[0079] It should be understood that, further, according to the calculated path adjoint loss set, the inspection path can be adjusted and the inspection process can be optimized to more efficiently complete the inspection task of the device.

[0080] First, according to the loss magnitude in the path adjoint loss set, evaluate the optimization requirements of each inspection path and identify the inspection paths with higher adjoint losses. If the loss of a certain inspection path is large, that is, the variance of the path is high, it indicates that there may be an uneven distribution of inspection points in the path, or the relative positions between the inspection nodes among the devices are too scattered, resulting in more time loss during the inspection process. At this time, the inspection path can be adjusted to reduce the time loss and improve the inspection efficiency.

[0081] Exemplarily, the specific implementation of the incorporation process includes the following steps: First, identify neighboring nodes whose relative distance to the inspection nodes on the current inspection path is less than a preset distance. The neighboring nodes refer to device nodes that are spatially close to the inspection path and have not been included in the current inspection path. Next, evaluate the impact of incorporating these neighboring nodes on the inspection path, including factors such as path length, inspection time, and resource consumption. Then, select the neighboring nodes that maximize the improvement in inspection efficiency and minimize the impact on path complexity, and incorporate them into the inspection path. Finally, update the inspection path items, generate an optimized inspection path, and recalculate its associated loss to ensure that the optimization effect meets expectations.

[0082] Through this adjustment, the inspection path will be more reasonable, the coverage of equipment inspection will be wider, and time waste and redundancy of the inspection path will be reduced. This update process can effectively reduce the associated loss of the inspection path, improve the utilization rate and inspection efficiency of the inspection path, thereby enhancing the overall management level of power plant equipment inspection.

[0083] In summary, the embodiments of the present application have at least the following technical effects:

[0084] This application obtains the BIM modeling data set of power plant equipment through a data interface, performs model simulation, outputs a BIM power plant equipment model, reads the historical SIS operation data of power plant equipment based on this model, conducts peak operation period analysis, clusters the equipment in the same peak period to form multiple groups of equipment, plans the inspection path for each group of equipment, generates inspection path items, and sends them to the inspection management terminal for inspection feedback.

[0085] It achieves the technical effects of three-dimensional virtual inspection based on BIM, realizing intelligent path planning and peak period analysis, and improving inspection efficiency and risk identification accuracy.

[0086] Embodiment 2, based on the same inventive concept as the method for three-dimensional virtual inspection of power plant equipment based on BIM in the foregoing embodiment, as Figure 2 shown, this application provides a system for three-dimensional virtual inspection of power plant equipment based on BIM. The system in the embodiments of this application and the method embodiments are based on the same inventive concept. Among them, the system includes:

[0087] A modeling data set acquisition module 11, which is used to obtain the BIM modeling data set of power plant equipment through a data interface.

[0088] A model simulation module 12, which is used to perform model simulation according to the BIM modeling data set of power plant equipment and output a BIM power plant equipment model.

[0089] Peak operation period analysis module 13, which is used to call the BIM power plant equipment model to read the historical SIS operation data sets of each power plant equipment, perform peak operation period analysis on each power plant equipment according to the historical SIS operation data sets, and cluster the power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment.

[0090] Inspection path planning module 14, which is used to plan the inspection path for each group of power plant equipment in the multiple groups of power plant equipment, generate inspection path items, and send the inspection path items to the inspection management terminal for inspection feedback.

[0091] Furthermore, the peak operation period analysis module 13 is also used to perform the following steps:

[0092] Perform peak operation period analysis on each power plant equipment according to the historical SIS operation data sets, obtain time characteristics and parameter characteristics, and identify the peak operation periods of each power plant equipment according to the time characteristics and parameter characteristics; wherein, the time characteristics include peak period length, frequency, and duration variance, and the parameter characteristics include peak parameter value, parameter change rate, and load resistance ability.

[0093] Furthermore, the peak operation period analysis module 13 is also used to perform the following steps:

[0094] Set multiple levels of peak operation period intervals; compare the peak operation periods of each power plant equipment with the multiple levels of peak operation period intervals, and divide each power plant equipment to obtain multiple groups of power plant equipment.

[0095] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0096] Call the BIM power plant equipment model to obtain the relative position information of each power plant equipment in each group of power plant equipment, where each power plant equipment corresponds to an inspection node; combine the relative position information of all inspection nodes in each group of power plant equipment to obtain the first inspection path and the time loss data of the first inspection path; if the time loss data is less than the preset time loss data, output the first inspection path as the inspection path for the corresponding group and store it in the inspection path item.

[0097] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0098] If the time loss data is greater than or equal to the preset time loss data, obtain a first optimization instruction; according to the first optimization instruction, introduce a random number of nodes and calculate the difference between the current time loss data and the preset time loss data to optimize the node number interval of a single inspection path, and obtain an optimal solution for the node number interval; plan inspection paths for each group of power plant equipment in the node number interval optimal solution, output multiple inspection paths for each group of power plant equipment, and encode and store the multiple inspection paths in the inspection path project.

[0099] Further, the inspection path planning module 14 is further configured to perform the following steps:

[0100] Connect to the personnel management module of the inspection management terminal, identify the status of the inspection personnel in the personnel management module, select multiple inspection personnel with the status of being idle as the status of the to-be-inspected personnel, and assign the multiple inspection paths; the multiple inspection personnel perform inspection feedback according to the assigned inspection paths, output multiple groups of inspection feedback data, and upload the multiple groups of inspection feedback data to the BIM power plant equipment model for fault visualization display.

[0101] Further, the inspection path planning module 14 is further configured to perform the following steps:

[0102] Construct a power plant equipment topology network according to the relative position information of each power plant equipment; divide the power plant equipment topology network according to the multiple groups of power plant equipment, and output multiple topology sub-networks corresponding to the multiple groups of power plant equipment; calculate the path accompanying loss for each inspection path in the multiple groups of power plant equipment according to the multiple topology sub-networks, obtain a path accompanying loss set, and update the inspection path project according to the loss magnitude of the path accompanying loss set.

[0103] Further, the inspection path planning module 14 is further configured to perform the following steps:

[0104] Obtain the first topology sub-network corresponding to the first group of power plant equipment; obtain the first group of inspection paths of the first group of power plant equipment, and the number of paths in the first group of inspection paths is a positive integer greater than or equal to 1; select any inspection path in the first group of inspection paths, and on the first topology sub-network, identify the number of nodes whose relative distance to the inspection nodes on the inspection path is less than the preset distance until the node number set corresponding to the first group of inspection paths is obtained; calculate the variance of the node numbers to obtain a path accompanying loss set.

[0105] Further, the inspection path planning module 14 is further configured to perform the following steps:

[0106] Updating the inspection path item according to the loss magnitude of the path - associated loss set, including incorporating inspection nodes with a relative distance less than a preset distance from the inspection nodes on the selected inspection path into the inspection path.

[0107] Embodiment 3: Based on the same inventive concept as the BIM - based three - dimensional virtual inspection method for power plant equipment in the foregoing embodiment, the present application also provides a computer - readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, the method in Embodiment 1 is implemented.

[0108] Through the foregoing detailed description of the BIM - based three - dimensional virtual inspection method for power plant equipment in this specification, those skilled in the art can clearly know the BIM - based three - dimensional virtual inspection method and system in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated herein. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0109] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0110] Exemplary electronic device:

[0111] Next, refer to Figure 3 to describe the electronic device of the embodiments of the present application.

[0112] Based on the same inventive concept as the BIM - based three - dimensional virtual inspection method for power plant equipment in the foregoing embodiment, the present application also provides a BIM - based three - dimensional virtual inspection system for power plant equipment, including: a processor, the processor is coupled with a memory, and the memory is used to store a program. When the program is executed by the processor, the system is enabled to execute the steps of the method described in Embodiment 1.

[0113] The electronic device 300 includes: a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 may further include a bus architecture 304. Among them, the communication interface 303, the processor 302, and the memory 301 can be interconnected through the bus architecture 304; the bus architecture 304 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus architecture 304 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0114] The processor 302 can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application solution.

[0115] The communication interface 303 uses any device of the transceiver type for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), wired access network, etc.

[0116] The memory 301 can be a ROM or other types of static storage devices that can store static information and instructions, a RAM or other types of dynamic storage devices that can store information and instructions, or it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but not limited to this. The memory can exist independently and be connected to the processor through the bus architecture 304. The memory can also be integrated with the processor.

[0117] Among them, the memory 301 is used to store computer execution instructions for implementing the solution of this application, and is controlled by the processor 302 to execute. The processor 302 is used to execute the computer execution instructions stored in the memory 301, so as to implement the 3D virtual inspection method for power plant equipment based on BIM provided in the above embodiments of this application.

[0118] It should be noted that the above sequence of embodiments of this application is only for description and does not represent the advantages or disadvantages of the embodiments. And the above specific embodiments of this specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0119] The above are only the preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this application shall be included within the protection scope of this application.

[0120] This specification and the drawings are only exemplary descriptions of this application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art can make various changes and modifications to this application without departing from the scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application is intended to include these changes and modifications.

Claims

1. A three-dimensional virtual inspection method for power plant equipment based on BIM, characterized in that: The method comprises: Obtain the power plant equipment BIM modeling data set through the data interface; Perform model simulation according to the power plant equipment BIM modeling data set, and output a BIM power plant equipment model; The BIM power plant equipment model is called to read the historical SIS operation data set of each power plant equipment, and the peak operation time period analysis is performed on each power plant equipment according to the historical SIS operation data set, and the power plant equipment in the same peak operation time period is clustered to obtain multiple groups of power plant equipment; Performing inspection path planning for each group of power plant equipment in the multiple groups of power plant equipment, generating inspection path items, and sending the inspection path items to the inspection management terminal for inspection feedback; The method for planning an inspection path for each group of power plant equipment in the multiple groups of power plant equipment includes: Calling the BIM power plant equipment model to obtain relative position information of each power plant equipment in each group of power plant equipment, wherein each power plant equipment corresponds to an inspection node; Combining the relative position information of all inspection nodes in each group of power plant equipment, obtaining a first inspection path and time loss data of the first inspection path; If the time loss data is less than the preset time loss data, the first inspection path is output as the inspection path of the corresponding group and stored in the inspection path item.

2. The method according to claim 1, characterized in that If the time loss data is greater than or equal to the preset time loss data, obtaining a first optimization instruction; According to the first optimization instruction, a random number of nodes is introduced and the difference between the current time loss data and the preset time loss data is calculated to perform interval optimization of the number of nodes in a single inspection path, and obtain an interval optimal solution for the number of nodes; In the node quantity interval optimal solution, inspection paths are planned for each group of power plant equipment, multiple inspection paths for each group of power plant equipment are output, and the multiple inspection path codes are stored in the inspection path project.

3. The method according to claim 2, characterized in that After outputting multiple inspection paths for each group of power plant equipment, the method includes: Connecting to the personnel management module of the inspection management terminal, identifying the status of the inspection personnel in the personnel management module, and selecting a plurality of inspection personnel whose status is idle to be inspected to allocate the plurality of inspection paths; The multiple inspection personnel perform inspection feedback according to the assigned inspection routes, output multiple groups of inspection feedback data, and upload the multiple groups of inspection feedback data to the BIM power plant equipment model for fault visualization.

4. The method according to claim 1, characterized in that Analyze the peak operation period of each power plant equipment according to the historical SIS operation data set, obtain time characteristics and parameter characteristics, and identify the peak operation period of each power plant equipment according to the time characteristics and parameter characteristics; The time characteristics include the peak period length, frequency and duration variance, and the parameter characteristics include peak parameter value, parameter change rate and load resistance.

5. The method according to claim 4, characterized in that The power plant equipment in the same peak operation period is clustered to obtain multiple groups of power plant equipment, the method comprising: Set up multiple peak operation time intervals; The peak operation time period of each power plant equipment is compared with the multi-level peak operation time period intervals, and each power plant equipment is divided into multiple groups of power plant equipment.

6. The method according to claim 1, characterized in that After obtaining the relative position information of each power plant equipment in each group of power plant equipment, the method further includes: Construct a power plant equipment topology network based on the relative location information of each power plant equipment; Dividing the power plant equipment topology network according to the multiple groups of power plant equipment, and outputting multiple topology sub-networks corresponding to the multiple groups of power plant equipment; Calculate the path accompanying loss of each inspection path within the multiple groups of power plant equipment according to the multiple topological sub-networks, obtain a path accompanying loss set, and update the inspection path item according to the loss size of the path accompanying loss set.

7. The method according to claim 6, characterized in that The method for calculating the path adjoint losses of the first group of power plant equipment includes: Obtaining a first topology sub-network corresponding to a first group of power plant equipment; Obtaining a first group of inspection paths for the first group of power plant equipment, where the number of paths in the first group of inspection paths is a positive integer greater than or equal to 1; Select any inspection path in the first group of inspection paths, and on the first topology subnetwork, identify the number of nodes whose relative distance to the inspection node on the inspection path is less than a preset distance, until a set of node numbers corresponding to the first group of inspection paths is obtained; The variance of the number of nodes is calculated to obtain a set of path loss.

8. The method according to claim 6, characterized in that The inspection path item is updated according to the loss size of the path accompanying loss set, including incorporating into the selected inspection path an inspection node whose relative distance to the inspection node on the inspection path is less than a preset distance.

9. The BIM-based three-dimensional virtual inspection system for power plant equipment is characterized by: The system is used to execute the method according to any one of claims 1 to 8, and the system comprises: A modeling data set acquisition module, wherein the modeling data set acquisition module is used to acquire a power plant equipment BIM modeling data set through a data interface; A model simulation module, the model simulation module is used to perform model simulation according to the power plant equipment BIM modeling data set and output a BIM power plant equipment model; A peak operation time period analysis module, the peak operation time period analysis module is used to call the BIM power plant equipment model to read the historical SIS operation data set of each power plant equipment, perform peak operation time period analysis on each power plant equipment according to the historical SIS operation data set, and cluster the power plant equipment in the same peak operation time period interval to obtain multiple groups of power plant equipment; The inspection path planning module is used to plan the inspection path for each group of power plant equipment in the multiple groups of power plant equipment, generate inspection path items, and send the inspection path items to the inspection management end for inspection feedback.

10. An electronic device, characterized in that: include: A processor, the processor is coupled to a memory, the memory is used to store a program, when the program is executed by the processor, the system is enabled to perform the steps of the method according to any one of claims 1 to 8.

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