Power plant equipment three-dimensional virtual inspection method and system based on BIM

Abstract

The invention discloses a BIM-based power plant equipment three-dimensional virtual inspection method and system, and relates to the technical field of power plant inspection, and the method comprises the steps: obtaining a BIM modeling data set of power plant equipment through a data interface, carrying out model simulation, and outputting a BIM power plant equipment model; reading historical SIS operation data of power plant equipment based on the model, performing peak operation period analysis, and clustering the equipment in the same peak period to form a plurality of groups of equipment; routing inspection path planning is carried out on each group of equipment, routing inspection path items are generated and sent to the routing inspection management end, and routing inspection feedback is carried out. The technical problems that an existing power plant equipment inspection method is low in efficiency and incomplete in coverage, and equipment fault risks in the peak operation period are difficult to accurately recognize are solved, and the technical effects that BIM-based three-dimensional virtual inspection is achieved, intelligent path planning and peak period analysis are achieved, and the inspection efficiency and the risk recognition precision are improved are achieved.

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] The second aspect of the present application provides a BIM-based three-dimensional virtual inspection system for power plant equipment, the system comprising: a modeling data set acquisition module, the modeling data set acquisition module is used to acquire the BIM modeling data set of power plant equipment through a data interface; a model simulation module, the model simulation module is used to perform model simulation according to the BIM modeling data set of the power plant equipment, and output a BIM power plant equipment model; a peak operation period analysis module, the peak operation 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 period analysis on each power plant equipment according to the historical SIS operation data set, cluster the power plant equipment in the same peak operation period interval to obtain multiple groups of power plant equipment; an inspection path planning module, the inspection path planning module is used to perform inspection path planning 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.

[0006] According to a third aspect of the present application, an electronic device is provided, comprising: a processor, the processor being coupled to a memory, the memory being used to store a program, and when the program is executed by the processor, the system is enabled to execute any one of the methods described in the first aspect.

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

[0008] The present application provides a three-dimensional virtual inspection method and system for power plant equipment based on BIM, which relates to the technical field of power plant inspection. The method and system obtain BIM modeling data of power plant equipment and perform simulation, analyze peak operation time periods in combination with historical SIS data, cluster the equipment according to the same peak time period, plan inspection paths for each group of equipment, generate inspection path items and send them to the inspection management end for inspection feedback. The method solves the technical problems of low efficiency, incomplete coverage, and difficulty in accurately identifying equipment failure risks during peak operation periods in existing power plant equipment inspection methods, realizes three-dimensional virtual inspection based on BIM, realizes intelligent path planning and peak time period analysis, improves inspection efficiency and risk identification accuracy, and reduces the technical effect of equipment failure risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1A schematic diagram of a process flow of a three-dimensional virtual inspection method for power plant equipment based on BIM provided in an embodiment of the present application;

[0011] Figure 2 A schematic diagram of the structure of a three-dimensional virtual inspection system for power plant equipment based on BIM provided in an embodiment of the present application;

[0012] Figure 3 A structural schematic diagram of an electronic device is provided for the present application.

[0013] Explanation of the 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 DESCRIPTION

[0014] 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.

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, 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 "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices.

[0017] Embodiment 1, as Figure 1 As shown, the present application provides a three-dimensional virtual inspection method for power plant equipment based on BIM, the method comprising:

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

[0019] Specifically, the BIM modeling dataset of the power plant equipment is obtained from the power plant equipment management system through the 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 real-time and accuracy of the data. The BIM modeling dataset includes but is not limited to the three-dimensional geometric model of the power plant equipment, spatial location information, equipment attributes (such as equipment type, specification parameters, operating status, etc.) and topological relationships between equipment. As shown in Table 1:

[0020]

[0021] These data are the basis for building the BIM power plant equipment model, and provide the necessary technical support for subsequent model simulation and virtual inspection. Obtaining the BIM modeling data set through the data interface not only realizes the automatic collection of data, but also avoids the errors that may be caused by manual input, and improves 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 SIS systems, video surveillance systems, etc., further enriching the content of the BIM modeling data set, and providing comprehensive data support for subsequent peak operation period analysis and inspection route planning.

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

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

[0024] First, the BIM modeling data set is parsed using BIM modeling software (such as Revit, Navisworks, etc.) to extract the three-dimensional geometric information, spatial position and attribute data of the equipment; second, a three-dimensional virtual model of the power plant equipment is constructed based on 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, the model is optimized, including simplifying complex geometric structures, optimizing rendering effects and adding interactive functions to improve the usability and visualization of the model.

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

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

[0027] P30: Call the BIM power plant equipment model to read the historical SIS operation data set of each power plant equipment, perform peak operation time 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 interval to obtain multiple groups of power plant equipment.

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

[0029] P31: 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; P32: Wherein, 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 capacity.

[0030] It should be understood that the BIM power plant equipment model is called to read the historical SIS operation data set of each power plant equipment through its built-in data interface. The historical SIS operation data set includes key parameters (such as temperature, pressure, flow, 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 set, the peak operation period analysis technology is used to conduct in-depth analysis of the operating status of each power plant equipment and identify its peak operation period. The purpose of this process is to identify the operating characteristics of the equipment in different time periods, especially the high-load and high-risk peak operation periods, to help optimize the equipment inspection and maintenance plan.

[0033] First, the peak operation period of the power plant equipment is analyzed based on the historical SIS operation data set. This analysis focuses on the performance of the equipment in different operation periods, especially during periods with heavy loads or prone to failure. The historical SIS data set includes the equipment's operating data, such as power, pressure, temperature and other parameters, fault records and load conditions. By analyzing these data, the system can identify the peak operation period of the equipment and identify the high-risk state of the equipment that is prone to failure or abnormality during certain periods.

[0034] During the analysis, time features and parameter features are extracted to help identify peak operating periods. Time features include the length, frequency, and duration variance of the peak period. The length of the peak period refers to the time that the equipment continues to operate under high load, the frequency indicates how often the equipment experiences peak operating conditions, and the duration variance reflects the stability or volatility of the peak period, which helps to assess whether the equipment is operating in a changing load environment. Parameter features include peak parameter values, parameter change rates, and the equipment's load resistance. The peak parameter value refers to the maximum operating 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 evaluates the equipment's ability to operate stably under high load.

[0035] Based on these time characteristics and parameter characteristics, the power plant equipment is clustered and analyzed. The equipment is divided into different groups according to its performance during peak operation periods. The equipment in each group has similar operating characteristics such as load and pressure during peak periods. Through cluster analysis, the power plant equipment is effectively grouped according to its operating status during peak periods, providing an important basis for subsequent inspection route planning, equipment maintenance and fault prediction. This analysis not only helps identify the peak hours of equipment, but also can formulate personalized maintenance and inspection strategies based on the peak operating characteristics of different equipment, reduce the risk of failures and improve the operating efficiency of equipment.

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

[0037] P33: Setting a multi-level peak operation time interval; P34: Comparing the peak operation time of each power plant equipment with the multi-level peak operation time interval, dividing each power plant equipment into multiple groups of power plant equipment.

[0038] Optionally, the power plant equipment in the same peak operation time interval is further clustered to obtain multiple groups of power plant equipment. To this end, a multi-level peak operation time interval is first set so that the equipment can be grouped more finely according to its different peak operation time periods. The setting of these multi-level peak operation time intervals takes into account factors such as the load characteristics, operation mode, and possible failure risks of the equipment. By setting different time intervals, the operating status of the equipment under different peak load conditions can be accurately reflected.

[0039] Next, the peak operating hours of each power plant equipment are compared with the set multi-level peak operating hour intervals, the peak operating hours of each equipment are matched with the corresponding intervals, and the equipment is divided into multiple peak operating hour intervals. Through this comparison, the equipment will be assigned to one or more peak operating hour intervals to form multiple groups. It should be noted that in this process, power plant equipment within a group can appear repeatedly, because the equipment may exhibit relatively similar operating characteristics in multiple peak operating hour intervals. Therefore, some equipment may appear in multiple groups, reflecting its commonalities and differences under different peak operating hours.

[0040] Through this multi-level division of peak operation time intervals, the equipment can be grouped more carefully according to its performance in different peak periods, providing a more accurate basis for subsequent inspection route planning, equipment management and fault prediction. This grouping method makes the equipment in 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: Perform inspection path planning 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.

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

[0043] P41: 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, wherein 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 the 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 of the corresponding group and store it in the inspection path item.

[0044] It should be understood that the inspection paths are planned for the generated multiple groups of power plant equipment, corresponding inspection path items are generated, and the items are sent to the inspection management end 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, thereby improving inspection efficiency and reducing unnecessary time waste.

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

[0046] Next, the inspection path is planned based on the relative position information of all inspection nodes in each group of power plant equipment. By comprehensively considering the spatial position of the equipment nodes, a path planning algorithm (such as Dijkstra algorithm, A* algorithm or genetic algorithm) is used to generate a preliminary inspection path as the first inspection path, and the time loss data of the path is calculated. 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. According to factors such as the distance between equipment, the complexity of the inspection path, and the inspection priority of the equipment, the path can be optimized and the time loss data required for the inspection can be calculated to evaluate the efficiency and feasibility of the inspection path.

[0047] Next, the first inspection path generated is evaluated. If the time loss data of the path is less than the preset time loss standard, the path is output and saved as the inspection path of the corresponding group. If the calculation result shows that the time loss of the path is too large, the system will adjust or re-plan until the preset time loss standard is met. Finally, the inspection path that meets the requirements will be stored in the inspection path project as a reference for the actual inspection operation. As shown in Table 3:

[0048]

[0049] This process can ensure that the inspection path of each power plant equipment is optimized, that is, under the premise of ensuring the comprehensiveness of the inspection, it can minimize unnecessary time waste, improve inspection efficiency, and reduce the burden of manual inspection. By sending the inspection path project to the inspection management end, the inspection personnel can conduct efficient inspections according to the path provided by the system and provide timely feedback on 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 the 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 perform node number interval optimization for a single inspection path, and obtain the node number interval optimal solution; P43-3a: Plan the inspection path 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 store the multiple inspection path encodings in the inspection path item.

[0052] Optionally, if the time loss data is greater than or equal to a 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, the number of nodes in the inspection path is dynamically adjusted to reduce time loss and improve inspection efficiency.

[0053] Exemplarily, when the calculated time loss data is greater than or equal to the preset time loss data, a first optimization instruction is obtained. 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, focusing on optimizing various parameters of the inspection path, especially the adjustment of the number of nodes.

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

[0055] Furthermore, the optimized node number interval optimal solution is used to plan the inspection path for each group of power plant equipment. By adjusting the number of nodes and replanning 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 solution, which is encoded and stored 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 inspectors, so that they can select the most appropriate path for inspection according to actual conditions.

[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 more efficient and reasonable inspection path selection. This not only improves the efficiency of the inspection, but also reduces the time waste that may occur during the inspection process, ensuring that equipment maintenance work can be carried out more smoothly.

[0057] Further, 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: 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 multiple inspection personnel whose status is idle to be inspected to allocate the multiple inspection paths; 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.

[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 allocation to ensure efficient allocation of multiple inspection paths and real-time feedback from the inspection personnel.

[0060] First, connect to the personnel management module of the inspection management end to identify the status of the inspection personnel in the module. This status is used to identify whether each inspection personnel is idle. According to the status of each inspection personnel, the inspection management module compares the status of the personnel to be inspected with their idle status, thereby selecting multiple idle inspection personnel. Then, multiple inspection paths are allocated to the selected idle inspection personnel to ensure that each inspection path has a corresponding inspection personnel to execute. The allocation process can be optimized and matched according to the skill level of the inspection personnel, historical inspection records, and path complexity to improve inspection efficiency and accuracy.

[0061] Then, the selected multiple inspectors start the inspection according to the assigned inspection path and provide feedback during the inspection process. During the inspection process, the inspectors record the inspection data, including equipment operation status, fault information, abnormal conditions, etc., through mobile terminals or inspection management systems. 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, multiple groups of inspection feedback data are associated with the equipment information in the BIM model to achieve visual display of faults. Visual display includes marking the location, fault type, severity and other information of the faulty equipment in the BIM model, and presenting it intuitively through color, icons or text prompts, so that managers can quickly locate and handle problems. Through this process, power plant managers can view the operating status of equipment in real time, discover potential faults and take timely repair measures.

[0064] By combining the status of inspection personnel with the inspection route allocation, it not only ensures the effective allocation of inspection tasks, but also monitors the operating status of equipment in real time and provides fault prompts through visual means, further improving the intelligence 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 based on 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 accompanying loss of each inspection path within the multiple groups of power plant equipment based on the multiple topology 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.

[0067] In a possible embodiment of the present application, after obtaining the relative position information of each device in each group of power plant equipment, a power plant equipment topology network can also be constructed based on 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 devices 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 relationship between the devices, and can intuitively reflect the spatial distribution and connection relationship of the power plant equipment, ensuring that the inspection path planning not only takes into account the distribution of the equipment, but also pays attention to the logical and physical relationship between the equipment.

[0068] Next, the power plant equipment topology network is divided according to the obtained multiple groups of power plant equipment, and multiple topology subnetworks are output. Each topology subnetwork corresponds to a group of power plant equipment, which are spatially related and have similar inspection characteristics. By dividing the equipment topology network, the system can allocate the equipment to different subnetworks according to the physical location relationship of each group of equipment, ensuring that the inspection path of each group of equipment can shorten the path length as much as possible and reduce unnecessary movement during the inspection process.

[0069] Next, according to the divided multiple topological subnetworks, the path concomitant loss is calculated for the inspection paths within each group of power plant equipment. Path concomitant loss refers to the additional time loss caused by the location of the equipment, the connection relationship between the equipment, and the design of the inspection path during the inspection process. The concomitant loss of each path can be calculated based on the layout of each inspection path, the relative position of the equipment, and the connectivity between the equipment. By analyzing the path characteristics and equipment relationships in the topological subnetwork, the concomitant loss value of each inspection path can be quantified. After the calculation is completed, the concomitant loss set of all paths will be obtained, and the inspection path items will be updated according to the size of these losses. The update process includes optimizing and adjusting the inspection paths with high concomitant losses, such as replanning the path order, adding inspection nodes, or reducing path intersections, in order to reduce concomitant losses and improve inspection efficiency. The updated inspection paths will be adjusted and optimized to ensure that the time loss of each path is minimized and the inspection efficiency is maximized.

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

[0071] Further, the path associated loss of the first group of power plant equipment is calculated, and step P44b of the embodiment of the present application further includes:

[0072] P44-1b: Obtain the first topological subnetwork corresponding to the first group of power plant equipment; P44-2b: Obtain the first group of inspection paths for the first group of power plant equipment, the number of paths in the first group of inspection paths being 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 subnetwork, 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: Perform variance calculation on the number of nodes to obtain a set of path associated losses.

[0073] Optionally, when calculating the path accompanying loss of the first group of power plant equipment, first, it is necessary to obtain the first topological subnetwork corresponding to the first group of power plant equipment. This topological subnetwork defines the connectivity between these devices based on the physical location and mutual relationship of the power plant equipment. Each subnetwork contains the spatial layout and network structure of related equipment, providing key data support for path calculation. Next, obtain the first group of inspection paths for 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 path is planned according to the equipment distribution and inspection requirements. Each path contains multiple inspection nodes, which are used to guide the specific inspection routes of the inspectors.

[0074] Furthermore, any one of the first group of inspection paths is selected, and other nodes whose relative distance to the inspection node on the inspection path is less than a preset distance are identified on the path. The preset distance refers to the distance range of adjacent devices that the inspection personnel can check along the way when performing the inspection task. By calculating the distance between the inspection node and the adjacent nodes, the number of nodes that have not been inspected on the inspection path but can be checked along the way is identified. Repeat the above process until the set of node quantities corresponding to the first group of inspection paths is obtained. This set of node quantities reflects the underutilized inspection opportunities on each inspection path.

[0075] Finally, the variance of the obtained number of nodes is calculated to obtain the path loss set. The variance of the number of nodes can reflect the inspection balance between various devices on the inspection path. If the variance is large, it means that there may be an unbalanced distribution of inspection points on the inspection path, that is, there is a large optimization space 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 accompanying loss of the inspection path can be quantified and a path loss set can be generated, thus providing a basis for path optimization.

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

[0077] Further, the inspection path item is updated according to the loss size of the path accompanying loss set. Step P44b of the embodiment of the present application further includes:

[0078] 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.

[0079] It should be understood that the inspection path can be further adjusted and the inspection process can be optimized based on the calculated path accompanying loss set, so as to complete the equipment inspection task more efficiently.

[0080] First, based on the loss size in the path loss set, evaluate the optimization requirements of each inspection path and identify the inspection paths with higher loss. If the loss of a certain inspection path is large, that is, the variance of the path is high, it means that there may be an unbalanced distribution of checkpoints on the path, or the relative positions of the inspection nodes between devices are too dispersed, resulting in more time loss during the inspection process. At this time, adjustments can be made to the inspection path to reduce time loss and improve 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 node 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 are not 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 have the greatest improvement in inspection efficiency and the least impact on path complexity, and incorporate them into the inspection path. Finally, update the inspection path project, generate an optimized inspection path, and recalculate its accompanying losses 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 the time waste and redundancy of the inspection path will be reduced. This update process can effectively reduce the accompanying losses of the inspection path, improve the utilization rate and inspection efficiency of the inspection path, and thus improve 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 the data interface, performs model simulation, and outputs the BIM power plant equipment model. Based on the model, the historical SIS operation data of the power plant equipment is read, and peak operation period analysis is performed. Equipment in the same peak period is clustered to form multiple groups of equipment. Inspection paths are planned for each group of equipment, and inspection path items are generated. These are sent to the inspection management end for inspection feedback.

[0085] The technical effect of achieving BIM-based three-dimensional virtual inspection, realizing intelligent route planning and peak period analysis, and improving inspection efficiency and risk identification accuracy has been achieved.

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

[0087] The modeling data set acquisition module 11 is used to acquire the BIM modeling data set of power plant equipment through a data interface.

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

[0089] The peak operation period analysis module 13 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 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 period interval to obtain multiple groups of power plant equipment.

[0090] The inspection path planning module 14 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.

[0091] Furthermore, the peak operation time period analysis module 13 is further configured to perform the following steps:

[0092] According to the historical SIS operation data set, the peak operation period of each power plant equipment is analyzed to obtain time characteristics and parameter characteristics, and the peak operation period of each power plant equipment is identified according to the time characteristics and parameter characteristics; wherein 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 capacity.

[0093] Furthermore, the peak operation time period analysis module 13 is further configured to perform the following steps:

[0094] A multi-level peak operation time interval is set; the peak operation time of each power plant equipment is compared with the multi-level peak operation time interval, and each power plant equipment is divided into 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, wherein 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 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, output the first inspection path as the inspection path of 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 perform node number interval optimization for a single inspection path, and obtain a node number interval optimal solution; in the node number interval optimal solution, perform inspection path planning for each group of power plant equipment, output multiple inspection paths for each group of power plant equipment, and store the multiple inspection path encodings in the inspection path project.

[0099] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0100] A personnel management module is connected to the inspection management end, the inspection personnel status in the personnel management module is identified, and multiple inspection personnel whose status is idle are selected to allocate the multiple inspection paths; the multiple inspection personnel perform inspection feedback according to the allocated 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] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0102] According to the relative position information of each power plant equipment, a power plant equipment topology network is constructed; the power plant equipment topology network is divided according to the multiple groups of power plant equipment, and multiple topology sub-networks corresponding to the multiple groups of power plant equipment are output; according to the multiple topology sub-networks, path accompanying losses are calculated for each inspection path within the multiple groups of power plant equipment, and a path accompanying loss set is obtained, and the inspection path item is updated according to the loss size of the path accompanying loss set.

[0103] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0104] Obtain a first topological subnetwork corresponding to a first group of power plant equipment; obtain a first group of inspection paths for the first group of power plant equipment, wherein 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 within the first group of inspection paths, and on the first topological 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; perform variance calculation on the number of nodes to obtain a set of path associated losses.

[0105] Furthermore, the inspection path planning module 14 is also used to perform the following steps:

[0106] 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.

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

[0108] Through the above detailed description of the three-dimensional virtual inspection method of power plant equipment based on BIM, those skilled in the art can clearly understand the three-dimensional virtual inspection method and system of power plant equipment based on BIM in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. 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 method part description.

[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 apparent to those skilled in the art, and the general principles defined herein may 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 conform to the widest scope consistent with the principles and novel features disclosed herein.

[0110] Example electronic devices: Reference below Figure 3 To describe the electronic device of the embodiment of the present application.

[0111] Based on the same inventive concept as the BIM-based three-dimensional virtual inspection method for power plant equipment in the aforementioned 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 to a memory, the memory is used to store a program, when the program is executed by the processor, the system executes the steps of the method described in Example 1.

[0112] The electronic device 300 includes: a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 may be interconnected via the bus architecture 304; the bus architecture 304 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0113] The processor 302 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0114] The communication interface 303 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), wired access networks, etc.

[0115] The memory 301 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, 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 is not limited thereto. The memory may exist independently and be connected to the processor via the bus architecture 304. The memory may also be integrated with the processor.

[0116] The memory 301 is used to store computer execution instructions for executing the solution of the present application, and the execution is controlled by the processor 302. The processor 302 is used to execute the computer execution instructions stored in the memory 301, thereby realizing the BIM-based three-dimensional virtual inspection method for power plant equipment provided in the above embodiment of the present application.

[0117] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying 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.

[0118] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0119] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

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; An inspection path is planned for each group of power plant equipment in the multiple groups of power plant equipment, an inspection path item is generated, and the inspection path item is sent to the inspection management end for inspection feedback.

2. The method according to claim 1, characterized in that An inspection path is planned for each group of power plant equipment in the plurality of groups of power plant equipment, the method comprising: 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.

3. The method according to claim 2, 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.

4. The method according to claim 3, 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.

5. 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.

6. The method according to claim 5, 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.

7. The method according to claim 2, 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.

8. The method according to claim 7, 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.

9. The method according to claim 7, 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.

10. The BIM-based three-dimensional virtual inspection system for power plant equipment is characterized by: 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.

11. 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 9.

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