A power engineering project management method, device, equipment and storage medium

Abstract

The application discloses a kind of electric power engineering project management method, device, equipment and storage medium.The method comprises: obtaining the multi-source perception data corresponding to target electric power engineering project, wherein the multi-source perception data includes: progress perception data, quality perception data and safety perception data;Intelligent analysis processing is carried out to the multi-source perception data, and the project execution characteristic information corresponding to target electric power engineering project is determined;The original execution state data corresponding to target electric power engineering project is determined, and the original execution state data is updated based on project execution characteristic information, to determine the target execution state data corresponding to target electric power engineering project, so that project manager carries out project management based on the target execution state data.The application can realize intelligent and efficient electric power engineering project management, improve the efficiency, timeliness and accuracy of data acquisition, meet the real-time management needs of electric power engineering project, and improve the accuracy of project management quality evaluation.

Description

Technical Field

[0001] This invention relates to the field of power engineering project management technology, and in particular to a power engineering project management method, apparatus, equipment and storage medium. Background Technology

[0002] Power engineering projects are characterized by long cycles, numerous stages, and complex stakeholders. The efficiency and quality of project management directly affect project progress, construction safety, and delivery quality.

[0003] Currently, traditional power engineering project management mainly relies on a static management model based on manual reports, periodic inspections, and experience-based judgment. However, the data collection efficiency, timeliness, and accuracy of traditional power engineering project management methods are low, thus failing to meet the real-time management needs of projects, affecting the accuracy of project management quality assessment, and directly impacting project progress, construction safety, and delivery quality. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and storage medium for power engineering project management, enabling intelligent and efficient power engineering project management, greatly improving the efficiency, timeliness, and accuracy of data acquisition, meeting the real-time management needs of power engineering projects, thereby improving the accuracy of project management quality assessment and avoiding impacts on project progress, construction safety, and delivery quality.

[0005] According to one aspect of the present invention, a method for managing power engineering projects is provided, the method comprising: Acquire multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data; The multi-source sensing data is intelligently analyzed to determine the project execution characteristic information corresponding to the target power engineering project; The original execution status data corresponding to the target power engineering project is determined, and the original execution status data is updated based on the project execution characteristic information to determine the target execution status data corresponding to the target power engineering project, so that project managers can perform project management based on the target execution status data.

[0006] According to another aspect of the present invention, a power engineering project management device is provided, the device comprising: The data acquisition module is used to acquire multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data; The data parsing module is used to intelligently analyze and process the multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project; The status update module is used to determine the original execution status data corresponding to the target power engineering project, update the original execution status data based on the project execution feature information, and determine the target execution status data corresponding to the target power engineering project, so that project managers can perform project management based on the target execution status data.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the power engineering project management method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the power engineering project management method according to any embodiment of the present invention.

[0009] The technical solution of this invention acquires multi-source sensing data corresponding to a target power engineering project. This multi-source sensing data includes progress sensing data, quality sensing data, and safety sensing data, providing a comprehensive and reliable data foundation for intelligent early warning and scientific decision-making in project management. Intelligent parsing processing of the multi-source sensing data determines the project execution characteristic information corresponding to the target power engineering project, reducing a large amount of heterogeneous data to project-level semantic features, which helps improve subsequent processing efficiency. The original execution status data corresponding to the target power engineering project is determined, and the original execution status data is updated based on the project execution characteristic information to determine the target execution status data corresponding to the target power engineering project. This allows project managers to manage the project based on the target execution status data, greatly improving project management efficiency. This invention, by acquiring multi-source sensing data corresponding to a target power engineering project, parsing it to obtain project execution characteristic information, and finally updating the original execution status data based on the project execution characteristic information, achieves intelligent and efficient power engineering project management. This greatly improves the efficiency, timeliness, and accuracy of data collection, meets the real-time management needs of power engineering projects, thereby improving the accuracy of project management quality assessment and avoiding impacts on project progress, construction safety, and delivery quality.

[0010] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart of a power engineering project management method provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart of a power engineering project management method provided in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the structure of a power engineering project management device according to Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the power engineering project management method of this invention. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0014] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0015] Example 1 Figure 1 This document provides a flowchart of a power engineering project management method according to Embodiment 1 of the present invention. This embodiment is applicable to the management of power engineering projects. The method can be executed by a power engineering project management device, which can be implemented in hardware and / or software. This power engineering project management device can be configured in an electronic device. Figure 1 As shown, the method includes: S110. Obtain multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data.

[0016] The target power engineering project can refer to a specific power engineering project currently underway that requires digital management, such as a new substation construction project, a transmission line relocation project, or a photovoltaic / wind farm grid connection project. Multi-source sensing data refers to the collective term for raw data from various sources and sensing / collection channels at the project site, which can include: progress sensing data, quality sensing data, and safety sensing data. Progress sensing data refers to data reflecting the progress of the project. Quality sensing data refers to data reflecting whether the completed construction / process meets specifications. Safety sensing data refers to data reflecting on-site personal and environmental safety risks.

[0017] Specifically, by deploying various sensing devices (such as GPS locators, cameras, inspection equipment, and environmental monitoring equipment) at the construction site, three types of data are collected in real time: progress sensing data (such as personnel attendance data, machinery operation time, and material arrival records), quality sensing data (such as concrete strength test data), and safety sensing data (such as images of violations and environmental monitoring values). By obtaining multi-source sensing data corresponding to the target power engineering project, the efficiency, accuracy, and timeliness of data collection can be greatly improved, thereby providing a complete and objective data foundation for subsequent analysis and avoiding decision-making biases due to missing information.

[0018] For example, progress perception data may include: video surveillance data (video streams or keyframe images of the construction site), construction machinery location data (real-time location and operating status of machinery such as excavators and cranes), personnel attendance data (entry and exit times and identity information of construction personnel), and material data (material arrival, consumption, and inventory data). Quality perception data may include: engineering dimensional data (component dimensions and installation deviation data), material testing data (material strength and performance parameter data), electrical testing data (insulation, grounding, and continuity test data of electrical equipment), and construction process record data (images or videos of construction operations). Safety perception data may include: personnel safety equipment data (images of wearing safety helmets, safety belts, and protective clothing), environmental monitoring data (temperature, humidity, dust concentration, and harmful gas concentration in the construction area), hazardous behavior detection data (images or alarm signals of violations, intrusions into dangerous areas), and fire monitoring data (smoke, flames, and fire equipment status data).

[0019] S120. Perform intelligent analysis and processing on multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project.

[0020] Among them, project execution characteristic information refers to the structured and quantifiable features extracted after intelligent analysis of multi-source sensing data, which are project status signals that project managers can directly understand.

[0021] Specifically, the collected multi-source sensing data is intelligently analyzed and processed to extract project execution feature information corresponding to the target power engineering project. The intelligent analysis and processing includes at least one of image recognition processing, sensor data analysis and processing, and text information extraction and processing. This can transform raw data into quantifiable management indicators, automatically discover hidden risks (such as minor progress deviation trends), reduce the workload of manual investigation, improve the timeliness of anomaly warnings, and make the feature information interpretable and have decision-making guidance value.

[0022] For example, S120 may include: performing image recognition processing on image-type sensing data in multi-source sensing data to determine first project feature information; performing data parsing processing on sensor-type sensing data in multi-source sensing data to determine second project feature information; performing text information extraction processing on text-type sensing data in multi-source sensing data to determine third project feature information; and determining the first project feature information, second project feature information, and third project feature information as project execution feature information corresponding to the target power engineering project.

[0023] Specifically, multi-source sensing data can be further divided into image-based sensing data, sensor-based sensing data, and text-based sensing data. Image recognition processing is performed on image-based sensing data within multi-source sensing data. This image recognition processing includes: construction progress recognition, construction quality recognition, safety equipment recognition, and hazardous behavior recognition. Construction progress recognition can utilize pre-trained deep learning models to identify the type of construction activity (e.g., tying rebar, pouring concrete, installing equipment), the type and quantity of construction machinery, and the number of construction workers in the image, calculating the percentage of construction progress. Construction quality recognition can identify whether the construction process is standardized (e.g., whether the rebar tying spacing is qualified), whether the component installation is in place, and whether the construction operation meets the standards. Safety equipment recognition refers to using target detection models to identify whether construction workers in the image are correctly wearing safety helmets, safety belts, and other safety equipment, and to statistically analyze the safety equipment wearing rate. Hazardous behavior recognition identifies hazardous behaviors in the image (e.g., not wearing safety belts while working at height, illegally entering dangerous areas, illegally operating equipment), generating hazardous behavior alarm information. The results of each recognition process constitute the first project feature information. Data parsing and processing are performed on sensor-type sensing data from multi-source sensing data. This includes data format conversion, outlier filtering, data fusion, and threshold comparison. Data format conversion converts raw sensor data into a standard format. Outlier filtering filters out abnormal data caused by sensor malfunctions or interference. Data fusion improves data reliability by fusing data from multiple similar sensors. Threshold comparison compares the processed sensor data with preset thresholds to generate normal / abnormal status indicators, i.e., the second item feature information. Text-type sensing data from multi-source sensing data undergoes text information extraction. This includes key field information extraction and structured information storage. Natural language processing technology is used to extract key field information (such as material name, quantity, time, and detection results) from the text, and the extracted information is structured and stored to obtain the third item feature information. The first, second, and third item feature information are then used as the project execution feature information corresponding to the target power engineering project, transforming raw data into quantifiable management indicators with interpretability and decision-making guidance value.

[0024] For example, intelligent analysis of sensory data could involve the server receiving image data and using a pre-trained deep learning model for identification. Specifically, it could identify the number of construction workers in the image as 15, the construction activity as "rebar tying," and the safety helmet wearing rate as 93% (14 workers wearing helmets, 1 worker not wearing one). The server could also receive and analyze environmental monitoring data, specifically: temperature: 28℃ (normal); humidity: 65% (normal); dust concentration: 8mg / m³. 3 (Exceeds the standard, threshold 5mg / m³) 3 ).

[0025] S130. Determine the original execution status data corresponding to the target power engineering project, update the original execution status data based on the project execution characteristic information, and determine the target execution status data corresponding to the target power engineering project so that project managers can manage the project based on the target execution status data.

[0026] The original execution status data can refer to the historical execution status data recorded for the corresponding project in the project management system. Execution status data includes: progress status data, quality status data, and safety status data. The target execution status data can refer to the data obtained by correcting the original execution status data with project execution characteristic information, reflecting the latest execution status of the target power engineering project at the current moment.

[0027] Specifically, the historical execution status data (previous reported values ​​for progress / quality / safety) of the target project is read from the project management system. The parsed project execution characteristic information is used as the basis for correction to update the historical execution status data. Finally, real-time target execution status data that integrates multi-source perception is output, which can eliminate the lag and subjective bias of manual reporting, making the status more realistic and reliable, and improving project management efficiency.

[0028] For example, updating the original execution status data could be as follows: updating the civil construction phase progress: rebar binding completion rate 75%; updating personnel input: current construction personnel 15; updating safety status: safety helmet wearing rate 93%, with 1 person not wearing a safety helmet; updating environmental status: dust concentration exceeds the standard.

[0029] For example, the step S130, "updating the original execution status data based on project execution feature information and determining the target execution status data corresponding to the target power engineering project", may include: determining the candidate execution status data corresponding to the target power engineering project based on project execution feature information; updating the original execution status data based on the candidate execution status data and determining the target execution status data corresponding to the target power engineering project.

[0030] Specifically, execution status data includes: progress status data, quality status data, and safety status data. Candidate progress status data can be determined based on the analysis results corresponding to the progress perception data in the project execution characteristic information. For example, based on the construction activity identification results, the completion percentage of each construction task can be calculated; based on construction machinery and personnel data, the input of construction resources can be assessed; based on material consumption data, the material usage status can be updated; and a progress deviation analysis can be generated: comparing the actual progress with the planned progress and calculating the progress deviation value. Candidate quality status data can be determined based on the analysis results corresponding to the quality perception data in the project execution characteristic information. For example, based on engineering dimension measurement data, it can be determined whether the component dimensions are qualified and the pass rate can be calculated; based on material testing data, the material quality status can be recorded; based on the construction process identification results, it can be determined whether the construction process is standardized; and a quality problem list can be generated: recording non-conformities, problem descriptions, and responsible units. Candidate safety status data can be determined based on the analysis results corresponding to the safety perception data in the project execution characteristic information. For example, based on the safety equipment identification results, the safety equipment wearing rate is calculated; based on environmental monitoring data, it is determined whether environmental indicators exceed standards; based on the hazardous behavior detection results, hazardous behavior events are recorded; and a safety status index is calculated, which integrates indicators such as safety equipment wearing rate, environmental indicator compliance rate, and hazardous behavior occurrence rate. The candidate progress status data, candidate quality status data, and candidate safety status data are jointly determined as the candidate execution status data corresponding to the target power engineering project. The original execution status data in the project system is directly updated based on the candidate execution status data to determine the target execution status data corresponding to the target power engineering project. This can meet the real-time management needs of power engineering projects and help improve the accuracy of project management quality assessment.

[0031] It should be noted that after determining the target execution status data corresponding to the target power engineering project, safety and environmental warning information can be automatically generated based on the target execution status data. For example, safety warning: One person was detected not wearing a safety helmet; location: entrance to the construction area; environmental warning: Dust concentration exceeds the standard (8mg / m³). 3 >5mg / m 3 It is recommended to turn on dust suppression equipment. Early warning information will be pushed to the on-site safety manager and management platform, allowing for timely detection of project issues and reducing rework and losses.

[0032] In this embodiment, by acquiring multi-source sensing data corresponding to the target power engineering project, including progress sensing data, quality sensing data, and safety sensing data, a comprehensive and reliable data foundation can be provided for intelligent early warning and scientific decision-making in project management. Intelligent parsing and processing of the multi-source sensing data determines the project execution characteristic information corresponding to the target power engineering project, reducing a large amount of heterogeneous data to project-level semantic features, which helps improve subsequent processing efficiency. The original execution status data corresponding to the target power engineering project is determined, and the original execution status data is updated based on the project execution characteristic information to determine the target execution status data corresponding to the target power engineering project. This allows project managers to manage the project based on the target execution status data, improving project management efficiency. This invention, by acquiring multi-source sensing data corresponding to the target power engineering project, parsing it to obtain project execution characteristic information, and finally updating the original execution status data based on the project execution characteristic information, achieves intelligent and efficient power engineering project management, greatly improving the efficiency, timeliness, and accuracy of data collection, meeting the real-time management needs of power engineering projects, thereby improving the accuracy of project management quality assessment and avoiding impacts on project progress, construction safety, and delivery quality.

[0033] Example 2 Figure 2 This is a flowchart of a power engineering project management method provided in Embodiment 2 of the present invention. This embodiment optimizes the step "acquiring multi-source sensing data corresponding to the target power engineering project" based on the above embodiments. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0034] See Figure 2 Another power engineering project management method provided in this embodiment specifically includes the following steps: S210. Determine the sensing device network corresponding to the target power engineering project, wherein the sensing device network includes: progress sensing devices, quality sensing devices and safety sensing devices.

[0035] Among them, the sensing device network can refer to a collection of devices that organize all the hardware devices involved in sensing according to business logic around a specific power engineering project.

[0036] Specifically, based on the characteristics of the target power engineering project (such as substations, overhead lines, and cable tunnels) and management needs, three types of sensing devices (progress sensing devices, quality sensing devices, and safety sensing devices) can be planned and deployed. All sensing devices form a sensing device network with topological relationships, which helps to improve the targeting and accuracy of data collection and facilitates subsequent scheduling and management according to business dimensions.

[0037] It should be noted that the sensing device network includes: progress sensing devices, quality sensing devices, and safety sensing devices. Progress sensing devices include video surveillance equipment, construction machinery positioning equipment, personnel attendance equipment, and material entry / exit identification equipment deployed in the construction area, used to collect information related to construction progress. Quality sensing devices include engineering dimension measuring equipment (such as laser rangefinders), material testing equipment (such as rebar detectors and concrete strength testing equipment), and electrical equipment testing equipment, used to collect information related to construction quality. Safety sensing devices include safety equipment identification cameras, environmental monitoring sensors (such as temperature, humidity, dust, and harmful gas concentration monitoring equipment), hazardous area intrusion detection equipment, and fire monitoring equipment, used to collect information related to construction safety.

[0038] For example, S210 may include: establishing a target mapping relationship between each sensing device and the target power engineering project, and generating a sensing device network corresponding to the target power engineering project, wherein the target mapping relationship includes: a mapping relationship between sensing devices and project identifiers, a mapping relationship between sensing devices and project execution phases, a mapping relationship between sensing devices and construction areas, and a mapping relationship between sensing devices and responsible departments.

[0039] Among them, the target mapping relationship can refer to the queryable association table formed by binding each sensing device with different business dimensions of project management.

[0040] Specifically, a target mapping relationship is established between each sensing device and the target power engineering project, that is, the mapping relationship between sensing devices and the project management system. This includes: the mapping relationship between sensing devices and project identifiers, the mapping relationship between sensing devices and project execution stages, the mapping relationship between sensing devices and construction areas, and the mapping relationship between sensing devices and responsible departments. The mapping relationship can be stored in the device configuration database, supports dynamic adjustment, generates a complete sensing device network, realizes the precise correspondence between devices and project business dimensions, and makes each sensing data traceable to a specific stage, region, and responsible party, which facilitates auditing and accountability. At the same time, it provides a unified spatiotemporal and business label for subsequent multi-source data fusion, enhancing the accuracy and interpretability of feature analysis.

[0041] For example, the project includes the following execution phases: civil construction, electrical equipment installation, and commissioning and acceptance. During the civil construction phase, sensing devices are deployed: video surveillance cameras and personnel attendance devices are deployed at the construction area entrance; environmental monitoring sensors (temperature, humidity, dust) are deployed within the construction area; safety monitoring cameras are deployed in high-altitude work areas; and concrete strength testing equipment is deployed in the concrete pouring area. A mapping relationship is established between the sensing devices and the project execution phases, and data collection cycles and reporting rules are configured.

[0042] S220. Data is collected from the target power engineering project based on a preset acquisition mode and a sensing device network to obtain multi-source sensing data corresponding to the target power engineering project. The preset acquisition mode includes at least one of the following: active acquisition mode, triggered acquisition mode, and command acquisition mode.

[0043] Among them, the preset acquisition mode can refer to the data acquisition method that is set in advance.

[0044] Specifically, the preset acquisition modes include at least one of the following: active acquisition mode, triggered acquisition mode, and command acquisition mode. At least one acquisition mode can be selected according to the business scenario of the target power engineering project. The three modes can also be used in combination (such as active + triggered in parallel) to collect data from the target power engineering project and obtain multi-source sensing data corresponding to the target power engineering project. This can improve the timeliness and relevance of data acquisition while controlling acquisition costs.

[0045] For example, video surveillance cameras capture images of the construction site every 5 minutes and transmit the video stream in real time. Environmental monitoring sensors collect environmental data every 10 minutes and report it. Personnel attendance equipment records personnel entry and exit information in real time.

[0046] It should be noted that the meanings of each acquisition mode are as follows: Active Acquisition Mode: The sensing device actively collects data according to a preset acquisition cycle and reports it to the server. Triggered Acquisition Mode: The sensing device triggers data acquisition when it detects a specific event (such as personnel entering a construction area, equipment starting or stopping). Command Acquisition Mode: The server sends an acquisition command to the sensing device, and the device responds and returns the acquired data.

[0047] Each sensing data record in the above-mentioned categories includes the following associated information: Project Identifier: The project to which the data belongs; Execution Stage Identifier: The execution stage of the project to which the data belongs; Construction Area Identifier: The construction area where the data was collected; Sensing Device Identifier: The sensing device that collected the data; Collection Timestamp: The time when the data was collected; Raw Data: Raw sensor data or raw image data; Parsing Result Data: Feature information extracted by intelligent parsing; Status Identifier: The processing status of the data (normal / abnormal / pending review). The project sensing database in the system includes the following data tables: Device Configuration Table: Stores the configuration information and mapping relationships of sensing devices; Raw Data Table: Stores the raw data collected by sensing devices; Parsing Result Table: Stores the feature information extracted by intelligent parsing; Project Status Table: Stores project progress, quality, and safety status data; Abnormal Record Table: Stores abnormal event records.

[0048] S230. Perform intelligent analysis and processing on multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project.

[0049] S240. Determine the original execution status data corresponding to the target power engineering project, update the original execution status data based on the project execution characteristic information, and determine the target execution status data corresponding to the target power engineering project so that project managers can manage the project based on the target execution status data.

[0050] The technical solution of this embodiment determines the sensing device network corresponding to the target power engineering project. This sensing device network includes progress sensing devices, quality sensing devices, and safety sensing devices. The coverage and blind spots of each type of device are clearly defined in advance, avoiding redundant deployment or omission of key monitoring points, and facilitating subsequent scheduling and management according to business dimensions. Data is collected from the target power engineering project based on a preset collection mode and the sensing device network to obtain multi-source sensing data corresponding to the target power engineering project. The preset collection mode includes at least one of the following: active collection mode, triggered collection mode, and command collection mode, improving data timeliness and relevance while controlling collection costs. This invention divides the sensing device network into progress sensing devices, quality sensing devices, and safety sensing devices, and collects data from them. This abstracts the dispersed sensing devices into three logical clusters of "progress / quality / safety," facilitating subsequent scheduling and management according to business dimensions and helping to improve the efficiency and accuracy of data collection.

[0051] Example 3 Figure 3 This is a schematic diagram of the structure of a power engineering project management device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a data acquisition module 310, a data parsing module 320, and a status update module 330; Among them, the 310 data acquisition module is used to acquire multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data; The 320 data parsing module is used to intelligently parse and process the multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project; The 330 status update module is used to determine the original execution status data corresponding to the target power engineering project, update the original execution status data based on the project execution feature information, and determine the target execution status data corresponding to the target power engineering project, so that project managers can perform project management based on the target execution status data.

[0052] The technical solution of this invention acquires multi-source sensing data corresponding to a target power engineering project. This multi-source sensing data includes progress sensing data, quality sensing data, and safety sensing data, providing a comprehensive and reliable data foundation for intelligent early warning and scientific decision-making in project management. Intelligent parsing processing of the multi-source sensing data determines the project execution characteristic information corresponding to the target power engineering project, reducing a large amount of heterogeneous data to project-level semantic features, which helps improve subsequent processing efficiency. The original execution status data corresponding to the target power engineering project is determined, and the original execution status data is updated based on the project execution characteristic information to determine the target execution status data corresponding to the target power engineering project. This allows project managers to manage the project based on the target execution status data, greatly improving project management efficiency. This invention, by acquiring multi-source sensing data corresponding to a target power engineering project, parsing it to obtain project execution characteristic information, and finally updating the original execution status data based on the project execution characteristic information, achieves intelligent and efficient power engineering project management. This greatly improves the efficiency, timeliness, and accuracy of data collection, meets the real-time management needs of power engineering projects, thereby improving the accuracy of project management quality assessment and avoiding impacts on project progress, construction safety, and delivery quality.

[0053] Optionally, the data acquisition module 310 includes: A sensing device network determination unit is used to determine the sensing device network corresponding to the target power engineering project, wherein the sensing device network includes: progress sensing devices, quality sensing devices and safety sensing devices; The sensing data acquisition unit is used to acquire data from the target power engineering project based on a preset acquisition mode and the sensing device network, and to acquire multi-source sensing data corresponding to the target power engineering project. The preset acquisition mode includes at least one of the following: active acquisition mode, triggered acquisition mode, and command acquisition mode.

[0054] Optionally, the sensing device network determination unit is specifically used to: establish a target mapping relationship between each sensing device and the target power engineering project, and generate a sensing device network corresponding to the target power engineering project, wherein the target mapping relationship includes: a mapping relationship between sensing devices and project identifiers, a mapping relationship between sensing devices and project execution phases, a mapping relationship between sensing devices and construction areas, and a mapping relationship between sensing devices and responsible departments.

[0055] Optionally, the data parsing module 320 is specifically used for: performing image recognition processing on image-type perception data in the multi-source perception data to determine first project feature information; performing data parsing processing on sensor-type perception data in the multi-source perception data to determine second project feature information; performing text information extraction processing on text-type perception data in the multi-source perception data to determine third project feature information; and determining the first project feature information, the second project feature information, and the third project feature information as project execution feature information corresponding to the target power engineering project.

[0056] Optionally, the image recognition processing includes: construction progress recognition, construction quality recognition, safety equipment recognition, and hazardous behavior recognition; the data parsing processing includes: data format conversion, outlier filtering, data fusion processing, and threshold comparison processing; the text information extraction processing includes: key field information extraction and structured information storage.

[0057] Optionally, the status update module 330 is specifically used to: determine the candidate execution status data corresponding to the target power engineering project based on the project execution feature information; update the original execution status data based on the candidate execution status data, and determine the target execution status data corresponding to the target power engineering project.

[0058] Optionally, the execution status data includes: progress status data, quality status data, and safety status data.

[0059] The above-described device can execute the power engineering project management method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the power engineering project management method.

[0060] Example 4 Figure 4 This is a schematic diagram of the structure of an electronic device implementing the power engineering project management method of this invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0061] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0062] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0063] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as power engineering project management methods.

[0064] In some embodiments, the power engineering project management method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the power engineering project management method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the power engineering project management method by any other suitable means (e.g., by means of firmware).

[0065] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0066] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0067] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0068] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0069] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0070] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0071] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0072] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0073] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for managing power engineering projects, characterized in that, include: Acquire multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data; The multi-source sensing data is intelligently analyzed to determine the project execution characteristic information corresponding to the target power engineering project; The original execution status data corresponding to the target power engineering project is determined, and the original execution status data is updated based on the project execution characteristic information to determine the target execution status data corresponding to the target power engineering project, so that project managers can perform project management based on the target execution status data.

2. The method according to claim 1, characterized in that, The acquisition of multi-source sensing data corresponding to the target power engineering project includes: Determine the sensing device network corresponding to the target power engineering project, wherein the sensing device network includes: progress sensing devices, quality sensing devices and safety sensing devices; Data is collected from the target power engineering project based on a preset acquisition mode and the sensing device network to obtain multi-source sensing data corresponding to the target power engineering project. The preset acquisition mode includes at least one of the following: active acquisition mode, triggered acquisition mode, and command acquisition mode.

3. The method according to claim 2, characterized in that, The network of sensing devices corresponding to the target power engineering project includes: Establish a target mapping relationship between each sensing device and the target power engineering project, and generate a sensing device network corresponding to the target power engineering project. The target mapping relationship includes: the mapping relationship between sensing devices and project identifiers, the mapping relationship between sensing devices and project execution phases, the mapping relationship between sensing devices and construction areas, and the mapping relationship between sensing devices and responsible departments.

4. The method according to claim 1, characterized in that, The intelligent analysis and processing of the multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project includes: Image recognition processing is performed on the image-type sensing data in the multi-source sensing data to determine the feature information of the first item; The sensor-type sensing data in the multi-source sensing data is parsed and processed to determine the feature information of the second item; Text information extraction processing is performed on the text-type sensing data in the multi-source sensing data to determine the feature information of the third item; The first project feature information, the second project feature information, and the third project feature information are determined as the project execution feature information corresponding to the target power engineering project.

5. The method according to claim 4, characterized in that, The image recognition processing includes: construction progress recognition, construction quality recognition, safety equipment recognition, and dangerous behavior recognition; the data parsing processing includes: data format conversion, outlier filtering, data fusion processing, and threshold comparison processing; the text information extraction processing includes: key field information extraction and structured information storage.

6. The method according to claim 1, characterized in that, The step of updating the original execution status data based on the project execution feature information to determine the target execution status data corresponding to the target power engineering project includes: Based on the project execution characteristic information, the candidate execution status data corresponding to the target power engineering project are determined; The original execution status data is updated based on the candidate execution status data to determine the target execution status data corresponding to the target power engineering project.

7. The method according to claim 6, characterized in that, The execution status data includes: progress status data, quality status data, and safety status data.

8. A power engineering project management device, characterized in that, include: The data acquisition module is used to acquire multi-source sensing data corresponding to the target power engineering project, wherein the multi-source sensing data includes: progress sensing data, quality sensing data and safety sensing data; The data parsing module is used to intelligently analyze and process the multi-source sensing data to determine the project execution characteristic information corresponding to the target power engineering project; The status update module is used to determine the original execution status data corresponding to the target power engineering project, update the original execution status data based on the project execution feature information, and determine the target execution status data corresponding to the target power engineering project, so that project managers can perform project management based on the target execution status data.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the power engineering project management method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the power engineering project management method according to any one of claims 1-7.

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