Quality detection and acceptance method for concealed works and related equipment

Abstract

The application discloses a concealed engineering quality detection and acceptance method and related equipment, and the method comprises the following steps: obtaining the component level identification of a target component, and binding the construction process data of the target component with the component level identification to generate a component level data packet; according to a preset spatial level relationship, aggregating the component level data packets of all target components belonging to the same space to be checked to generate a room level data packet corresponding to the space to be checked; in response to an acceptance request for the space to be checked, calling the corresponding room level data packet for acceptance determination, and generating a processing record associated with the space to be checked according to the acceptance determination result.

Description

Technical Field

[0001] This application belongs to the technical field of acceptance management system, specifically relating to a method for quality inspection and acceptance of concealed works, a device for quality inspection and acceptance of concealed works, an electronic device, and a computer-readable storage medium. Background Technology

[0002] In the field of building construction, the construction quality of concealed works (such as pipelines laid in walls and floors, waterproofing layers, etc.) is directly related to the safety and durability of buildings. Since these works will be permanently covered in subsequent processes, they are difficult to inspect directly once sealed. Therefore, it is crucial to conduct effective acceptance inspections and maintain reliable records before they are covered.

[0003] Currently, the acceptance of concealed works mainly relies on archived images taken before covering, with manual spot checks or partial destructive inspections conducted during acceptance. This method has significant drawbacks: the images lack a structured connection with specific spatial locations and component information, making information traceability difficult; sampling inspections cannot achieve comprehensive coverage, leaving potential quality issues; and unstructured image data cannot be automatically identified and judged by the system, making the entire acceptance process inefficient and reliant on manual experience, hindering standardized and traceable comprehensive quality management. Summary of the Invention

[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method for quality inspection and acceptance of concealed works, which can solve problems such as the difficulty in non-destructive verification of quality during acceptance, the lack of correlation between construction data and components and space, and incomplete coverage of sampling acceptance in related technologies.

[0005] To achieve the above objectives, a first aspect of the present invention proposes a method for quality inspection and acceptance of concealed works, comprising: acquiring the component-level identifier of a target component, binding the construction process data of the target component with the component-level identifier, and generating a component-level data package; aggregating the component-level data packages of all target components belonging to the same space to be inspected according to a preset spatial hierarchy, and generating a room-level data package corresponding to the space to be inspected; in response to an acceptance request for the space to be inspected, retrieving the corresponding room-level data package for acceptance judgment, and generating a processing record associated with the space to be inspected based on the acceptance judgment result.

[0006] In some embodiments, before obtaining the component-level identifier of the target component, the method further includes: assigning a spatial-level identifier to the space to be verified, assigning a component-level identifier to the target component, and establishing a hierarchical association between the verification spatial unit and the target component in the building information model or spatial relational database, based on a pre-unified spatial and component classification coding standard.

[0007] In some embodiments, obtaining the component-level identifier of the target component and binding the construction process data of the target component with the component-level identifier to generate a component-level data package includes: scanning a QR code or RFID tag attached to the target component with a terminal device to obtain the component-level identifier of the target component; collecting construction process data related to the target component; wherein the construction process data includes structured detection parameters and unstructured image data; and packaging the component-level identifier and the construction process data to generate a component-level data package.

[0008] In some embodiments, the component-level data package may also include component-level identifiers, the time of data collection for construction processes, and operator information.

[0009] In some embodiments, the method further includes: analyzing the monitoring video stream collected by fixed cameras set in the construction area, and using image recognition technology to automatically capture key node images related to the installation of the target component; binding the identified key node images with the corresponding component-level identifier of the target component as unstructured image data.

[0010] In some embodiments, the method further includes: performing an acceptance judgment on the space to be verified based on room-level data packets; generating a rectification task in response to an unqualified acceptance judgment result; wherein the rectification task is automatically associated with a space-level identifier and at least one component-level identifier marked as unqualified.

[0011] In some embodiments, the method further includes: binding the component-level identifier of the target component to the supply chain information of the target component; and retrieving the supply chain information corresponding to the target component in response to the acceptance judgment result of the target component corresponding to the component-level identifier being unqualified.

[0012] The concealed works quality inspection and acceptance method according to an embodiment of the present invention includes: obtaining the component-level identifier of the target component, binding the construction process data of the target component with the component-level identifier, and generating a component-level data package; aggregating the component-level data packages of all target components belonging to the same space to be inspected according to a preset spatial hierarchy, and generating a room-level data package corresponding to the space to be inspected; in response to an acceptance request for the space to be inspected, retrieving the corresponding room-level data package for acceptance judgment, and generating a processing record associated with the space to be inspected according to the acceptance judgment result. Therefore, this application can solve the problems in related technologies such as the difficulty of non-destructive quality verification during acceptance, the lack of correlation between construction data and components and space, and the incomplete coverage of sampling acceptance. Any unqualified component can be quickly located to its specific location, responsible party, and all related data, realizing full-coverage digital acceptance of concealed works quality, eliminating the quality risk blind spots caused by sampling, and ensuring that the construction quality of every concealed component can be verified. At the same time, this application integrates quantitative testing parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration, greatly reducing the complexity and labor intensity of acceptance work, improving acceptance efficiency and accuracy, and thus ensuring the construction quality of concealed works in building engineering.

[0013] To achieve the above objectives, a second aspect of the present invention provides a concealed works quality inspection and acceptance device, comprising: an acquisition module configured to acquire the component-level identifier of a target component and bind the construction process data of the target component with the component-level identifier to generate a component-level data package; a construction module configured to aggregate the component-level data packages of all target components belonging to the same space to be inspected according to a preset spatial hierarchy relationship to generate a room-level data package corresponding to the space to be inspected; and an acceptance module configured to, in response to an acceptance request for the space to be inspected, retrieve the corresponding room-level data package for acceptance judgment and generate a processing record associated with the space to be inspected based on the acceptance judgment result.

[0014] The concealed works quality inspection and acceptance device according to an embodiment of the present invention includes: an acquisition module configured to acquire the component-level identifier of a target component and bind the construction process data of the target component with the component-level identifier to generate a component-level data package; a construction module configured to aggregate the component-level data packages of all target components belonging to the same space to be inspected according to a preset spatial hierarchy relationship to generate a room-level data package corresponding to the space to be inspected; and an acceptance module configured to, in response to an acceptance request for the space to be inspected, retrieve the corresponding room-level data package for acceptance judgment and generate a processing record associated with the space to be inspected based on the acceptance judgment result. Therefore, this application can solve the problems in related technologies such as the difficulty of non-destructive quality verification during acceptance, the lack of correlation between construction data and components and space, and the incomplete coverage of sampling acceptance. Any unqualified component can be quickly located to its specific location, responsible party, and all related data, realizing full-coverage digital acceptance of concealed works quality, eliminating the quality risk blind spots caused by sampling, and ensuring that the construction quality of every concealed component can be verified. At the same time, this application integrates quantitative testing parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration, greatly reducing the complexity and labor intensity of acceptance work, improving acceptance efficiency and accuracy, and thus ensuring the construction quality of concealed works in building engineering.

[0015] To achieve the above objectives, a third aspect of the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a program or instructions executable on the processor, and the program or instructions, when executed by the processor, implement the steps of the concealed works quality inspection and acceptance method as described above.

[0016] The electronic device according to embodiments of the present invention, by executing the above-described method for quality inspection and acceptance of concealed works, can solve the problems in related technologies such as difficulty in non-destructive verification of quality, lack of correlation between construction data and components and space, and incomplete coverage of sampling acceptance. Any unqualified component can be quickly located to its specific position, responsible party, and all associated data, realizing full-coverage digital acceptance of concealed works quality, eliminating the quality risk blind spots caused by sampling, and ensuring that the construction quality of each concealed component can be verified. At the same time, this application integrates quantitative detection parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration, greatly reducing the complexity and labor intensity of acceptance work, improving acceptance efficiency and accuracy, thereby ensuring the construction quality of concealed works in building engineering.

[0017] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium on which a program or instructions are stored, and when the program or instructions are executed by a processor, the steps of the concealed works quality inspection and acceptance method as described above are implemented.

[0018] According to the computer-readable storage medium of the present invention, by executing the above-described method for quality inspection and acceptance of concealed works, the problems in related technologies, such as difficulty in non-destructive verification of quality, lack of correlation between construction data and components and space, and incomplete coverage of sampling acceptance, can be solved. Any unqualified component can be quickly located to its specific position, responsible party, and all associated data, realizing full-coverage digital acceptance of concealed works quality, eliminating the quality risk blind spots caused by sampling, and ensuring that the construction quality of each concealed component can be verified. At the same time, this application integrates quantitative detection parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration, greatly reducing the complexity and labor intensity of acceptance work, improving acceptance efficiency and accuracy, and thus ensuring the construction quality of concealed works in building engineering.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0020] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating a method for quality inspection and acceptance of concealed works in an embodiment of this application; Figure 2 This is a schematic diagram illustrating the specific process of a method for quality inspection and acceptance of concealed works in an embodiment of this application; Figure 3 This is a schematic diagram of a concealed works quality inspection and acceptance device in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0021] Reference numerals: Concealed works quality inspection and acceptance device 300, acquisition module 301, construction module 302, acceptance module 303, processor 410, memory 420, input / output interface 430, communication interface 440, bus 450. Detailed Implementation

[0022] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0023] It should be understood that the steps described in the method embodiments of this application may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this application is not limited in this respect.

[0024] As described in the background section, in the field of building engineering, the construction quality of concealed works (such as pipelines laid in walls and floors, waterproofing layers, etc.) is directly related to the safety and durability of buildings. Since they will be permanently covered in subsequent processes, it is difficult to directly inspect them once they are sealed. Therefore, it is crucial to conduct effective acceptance and keep reliable records before they are covered.

[0025] Currently, the industry's commonly used acceptance method is pre-coverage image archiving and post-construction sampling verification. Specifically, before covering concealed works, the construction party typically takes photos or records videos as process documentation and archives them. During the project acceptance phase, acceptance personnel, as needed, retrieve these stored image data for manual sampling and comparison, or, based on experience, perform destructive drilling on questionable areas to conduct physical inspections. The essence of this technical solution is reliance on post-construction, discrete image recording and human experience for sampling verification.

[0026] However, this existing technical solution has the following significant drawbacks: Information isolation and difficulty in tracing: Archived image data is usually stored independently and lacks a systematic and structured connection with specific building locations and component codes, forming "information silos". When it is necessary to trace the construction records of a specific location (such as a section of pipeline in a room), the retrieval efficiency is low, and it is difficult to accurately locate the problems found to specific construction components and corresponding responsible persons, making it difficult to guarantee both the efficiency and accuracy of acceptance.

[0027] Limited acceptance coverage: Relying on manual spot checks, due to cost and time constraints, cannot achieve 100% verification of all concealed works, resulting in numerous blind spots in quality inspection. The quality status of unchecked parts remains unknown, creating long-term quality risks for the project and increasing the risk and cost of later maintenance.

[0028] The acceptance process cannot be automated: Because the archived core data (images) is unstructured, computer systems struggle to automatically identify its content, analyze key parameters (such as pipeline spacing and interface processes), and compare them with specifications. The entire acceptance judgment relies heavily on the personal experience and sense of responsibility of the acceptance personnel, making standardized and large-scale automated analysis and management impossible, thus hindering the overall efficiency and objectivity of the acceptance work.

[0029] To address the shortcomings of existing methods for accepting concealed works, the concealed works quality inspection and acceptance method of this invention solves problems such as difficulties in non-destructive verification, weak data correlation, incomplete acceptance coverage, and low efficiency by binding components and data, spatial hierarchy aggregation, and digital acceptance design. It achieves accurate traceability and full-coverage digital acceptance of concealed works quality, avoids quality risks and resource waste caused by sampling acceptance, improves acceptance efficiency and result accuracy, and ensures the construction quality of concealed works in building engineering.

[0030] Concealed works refer to the parts of the interior decoration project that are covered by subsequent construction (such as those enclosed in the walls or ceilings), such as water and electricity pipelines, waterproofing layers, and insulation layers.

[0031] The following is for reference. Figures 1-2 This application describes a method for quality inspection and acceptance of concealed works.

[0032] refer to Figure 1 This is a flowchart illustrating a method for quality inspection and acceptance of concealed works according to an embodiment of this application. The method for quality inspection and acceptance of concealed works according to an embodiment of this application may include the following steps: Step S101: Obtain the component-level identifier of the target component, and bind the construction process data of the target component with the component-level identifier to generate a component-level data package.

[0033] Specifically, the component-level identifier is a unique identification code, which can be selected from one or more combinations of QR codes, RFID electronic tags, or BIM model component IDs. Construction process data can include at least component specifications, material batch information, installation time, operator information, quality self-inspection / mutual inspection records, and key process image data.

[0034] Step S102: According to the preset spatial hierarchy, aggregate the component-level data packets of all target components belonging to the same space to be verified to generate room-level data packets corresponding to the space to be verified.

[0035] Specifically, the spatial hierarchy is a multi-level tree structure of "building-floor-functional zone-room". Aggregation operations may include data collection, index creation, and lightweight processing to form a fast retrieval structure for the room-level data packages.

[0036] Step S103: In response to the acceptance request for the space to be verified, the corresponding room-level data packet is retrieved for acceptance judgment, and a processing record associated with the space to be verified is generated based on the acceptance judgment result.

[0037] Specifically, acceptance criteria can include manual inspection, automatic comparison based on preset rules, or human-computer interaction and collaboration. Processing records can include the acceptance space identifier, acceptance time, judgment result (pass / rectification / re-inspection), a list of discovered issues (associated with specific component-level identifiers), rectification requirements, and final closure status. As an optional embodiment, before obtaining the component-level identifier of the target component, the method further includes: assigning a space-level identifier to the space to be verified and a component-level identifier to the target component based on a pre-unified space and component classification coding standard, and establishing a hierarchical association between the verification space unit and the target component in the building information model or spatial relational database.

[0038] Specifically, different identifiers are bound to different functional areas and component types of the building project. Space-level identifiers are assigned to the spaces to be verified according to the hierarchy of buildings, floors, and rooms. Component-level identifiers are assigned to the target components according to the component types and installation locations such as pipelines and waterproof structures. This ensures that each space and component has a traceable identity code. After the identifier assignment is completed, these codes are synchronized to the Building Information Model (BIM) or spatial relational database. By binding the spatial location of the model with the component attributes, a hierarchical association between the verification space unit and the target component is established, ensuring that the space unit to which any component belongs can be quickly located during subsequent acceptance.

[0039] It should be noted that this application provides a spatial hierarchical system standard for regulating the definition, coding, and association of data objects throughout the entire building lifecycle. It ensures the consistency and associativity of data across different systems at each stage, from design and construction to operation and maintenance, and is the core foundation for achieving data interoperability in this application.

[0040] Specifically, S1 (Spatial Level 1), the city-level spatial unit, is the highest level in the spatial hierarchy, used at the enterprise level to identify and manage projects located in different cities (e.g., S1-HZ represents all projects in a certain city). S2 (Spatial Level 2), the project cluster-level spatial unit, refers to a project cluster consisting of multiple sub-projects or plots within the same city (e.g., S2-HZ-SC represents "a project cluster in a certain district of a certain city"). S3 (Spatial Level 3), the individual building-level spatial unit, refers to an independent, fully functional individual building within a project cluster, such as a residential building or a commercial building (e.g., S3-HZ-SC-001-T2 represents "the T2 office building in a project cluster in a certain district of a certain city"). S4 (Spatial Level 4), the floor-level spatial unit, refers to a specific floor within an individual building (e.g., S4-F11 represents "the 11th floor"). S5 (Spatial Level 5), room-level spatial unit, is the core operational level involved in this application. It refers to the smallest spatial unit within a floor that has an independent function or can be independently identified, such as an office, an apartment, or a equipment room (e.g., S5-R2307 represents "room 2307"). It is the basic unit for linking and querying acceptance data. S6 (Spatial Level 6), component-level spatial unit, refers to the physical components or equipment that make up a room, such as a window, an air conditioning unit, or a section of pipe (e.g., S6-FAC-AHU-041 represents "air conditioning unit numbered 041"). In the query, one can penetrate from the S5 spatial unit level to its contained S6 component level.

[0041] S5 Room ID refers to the unique identifier for a "room-level" spatial unit in the spatial hierarchy standard. S6 Component ID refers to the unique identifier for a "component-level" entity (such as a pipe section or an insulation board) that constitutes a space in the spatial hierarchy standard. BIM (Building Information Modeling) is a digital representation process that includes various physical and functional characteristics of a building. Specifically, it refers to a BIM model that has embedded S1-S6 standard codes; it serves as the data carrier and object source for intelligent queries. In this application embodiment, assigning a spatial-level identifier to the space to be verified is equivalent to assigning an S5 Room ID to the space to be verified, and assigning a component-level identifier to the target component is equivalent to assigning an S6 Component ID to the target component.

[0042] As an optional embodiment, the component-level identifier of the target component is obtained, and the construction process data of the target component is bound to the component-level identifier to generate a component-level data package. This includes: scanning the QR code or RFID tag attached to the target component with a terminal device to obtain the component-level identifier of the target component; collecting construction process data related to the target component; wherein the construction process data includes structured detection parameters and unstructured image data; and packaging the component-level identifier and the construction process data to generate a component-level data package.

[0043] Structured testing parameters refer to quantifiable data measured by professional instruments and recorded through standardized processes, such as component dimensional deviations, material strength, and pressure test values. This type of data provides objective quantitative evidence for whether the component quality meets specifications. Unstructured video data includes construction process photos, videos of key procedures, and images of the component's condition before concealment. This type of data can intuitively restore the component's construction process, installation details, and surrounding environment, making up for the limitation of structured data, which can only reflect the results and not the process. If only structured / unstructured data is recorded, it is difficult to fully support the quality control and traceability needs of concealed works. In the event of subsequent quality disputes or the need to trace responsibility, the video data can be used to restore the actual construction scene and verify whether the operation meets the specifications. Structured and unstructured data complement each other, so that the component-level data package contains accurate quantitative indicators and complete process records, providing comprehensive and reliable data support for subsequent acceptance verification, quality traceability, and responsibility determination.

[0044] Specifically, refer to Figure 2 This is a schematic diagram illustrating the specific process of a concealed works quality inspection and acceptance method in this application embodiment. By scanning the QR code or RFID tag attached to the surface of the component with a mobile terminal, the unique identification code of the component can be quickly read. This method eliminates the need for manual input, avoids coding errors, and can adapt to the complex working environment of the construction site. After the bathroom pipeline is laid in a residential project, the construction personnel only need to scan the QR code or RFID tag at the pipeline interface to accurately locate the coding information of the pipeline. Even if the pipeline is subsequently covered by the wall, its complete construction data can be traced through the code. In the data collection stage, structured test parameters and unstructured image data are collected simultaneously, which can record the component quality status from two dimensions: quantitative indicators and visual evidence. For roof waterproof components, structured data such as the pressure value and seepage time of the water tightness test are collected as a quantitative basis for quality judgment. The entire process of waterproof membrane laying is filmed as evidence of construction compliance, ensuring the comprehensiveness of quality information. Finally, the code and various data are integrated into a component-level data package, so that each data package has a unique correspondence with a specific component.

[0045] As an optional embodiment, the component-level data package also includes component-level identifiers, the time of data collection for construction processes, and operator information.

[0046] Specifically, in the pre-embedded pipeline work in residential walls, after the construction personnel complete the pipeline inspection data collection, the terminal will simultaneously record the collection time, operator information (including employee number, name, etc.) and associate it with the corresponding component-level data package. The collection time can be matched with the time node of data collection and component construction to ensure that the collected data is the true quality state of the component before it is concealed. If a component quality problem is found later, the specific operator can be quickly traced through the data package to clarify the boundary of responsibility. This information provides comprehensive information support for subsequent acceptance verification and quality accountability.

[0047] As an optional embodiment, the method further includes: analyzing the monitoring video stream collected by fixed cameras set up in the construction area, and using image recognition technology to automatically capture key node images related to the installation of the target component; binding the identified key node images with the corresponding component-level identifier of the target component as unstructured image data.

[0048] Specifically, fixed cameras will be set up in the construction area according to the work procedures to collect real-time monitoring video streams of the entire installation process of the target components. The system will automatically analyze the video content through image recognition technology, capture key nodes in the component installation, and eliminate the need for manual shooting or cropping of core process scenes such as pipeline interface welding and waterproof membrane overlapping. The system will automatically associate the identified key node images with the corresponding component-level identifiers through scene positioning and time matching, and store them in the component-level data package as unstructured image data, providing a more comprehensive visual basis for quality judgment.

[0049] The system receives all component-level data packets from the construction site in real time. Based on the preset spatial hierarchy, the system automatically identifies and aggregates all component-level data packets belonging to the same space to be verified by reading the identification information in the component-level data packets. After structuring and integrating these data according to construction procedures and component types, it generates room-level data packets (i.e., room-level digital twins) for the corresponding space to be verified, forming a complete digital twin data packet for the space. When residents report repairs, maintenance personnel can directly retrieve the room-level data packets, quickly see through the walls, grasp the quality status of all hidden works in the space, accurately locate internal pipeline problems, and improve maintenance efficiency.

[0050] It should be noted that a digital twin refers to a digital model created in an information system that corresponds to a physical entity object (S6 component) and contains its entire lifecycle data.

[0051] As an optional embodiment, the method further includes: performing an acceptance judgment on the space to be verified based on the room-level data packet; generating a rectification task in response to the acceptance judgment result being unqualified; wherein the rectification task is automatically associated with a space-level identifier and at least one component-level identifier marked as unqualified.

[0052] Specifically, inspectors do not need to check the data of individual components one by one. They can directly retrieve the room-level data package of the space to be inspected to obtain complete quality information of all hidden works in the space. In the inspection of bathrooms in residential projects, inspectors can view the test data and image data of all hidden components such as water supply and drainage pipelines and waterproof structures through the room-level data package. If the waterproofing water tightness test parameters are found to be substandard and the component is deemed unqualified, the unqualified waterproof component can be selected on the terminal device (which can be directly associated with the component-level identifier) ​​to generate a rectification order. After receiving the operation instruction, the system automatically generates a rectification task. The task title and content include the space-level identifier of the bathroom and the component-level identifier of the unqualified waterproof component. Finally, the system automatically pushes the task to the pre-designated waterproofing construction responsible person.

[0053] As an optional embodiment, the method further includes: binding the component-level identifier of the target component with the supply chain information of the target component; and retrieving the supply chain information corresponding to the target component in response to the acceptance judgment result of the target component corresponding to the component-level identifier being unqualified.

[0054] Specifically, the supply chain information such as the manufacturer, product batch, and specifications of the target component is bound to the component-level identifier. When the acceptance personnel find that the pressure test parameters of a certain section of water supply and drainage pipe do not meet the standards through room-level data package verification, after the terminal device marks the component as unqualified, the system can directly retrieve the corresponding supply chain information through the component-level identifier of the pipe. If it is verified that there are common quality problems in the same batch of products, the same batch of pipes used in the project can be investigated as soon as possible to avoid more unqualified components being left in the concealed works.

[0055] Traditional methods of project acceptance rely on sampling verification, resulting in coverage of less than 5%. Each household's acceptance process typically takes 2 hours. If problems arise later, rework incurs high costs for tasks like chiseling and repair. This application's digital acceptance method, however, completes acceptance for each household in just 0.5 hours, increasing efficiency by 75%. Furthermore, this solution achieves 100% component-level inspection, nearly 100% quality risk detection, and virtually eliminates delivery risks. Through precise positioning and non-destructive testing, rework costs are kept extremely low, saving over a million yuan per project. The post-acceptance complaint rate for concealed works decreases by over 80%, significantly improving customer satisfaction and reducing post-delivery disputes.

[0056] In summary, the concealed works quality inspection and acceptance method provided in this application includes: obtaining the component-level identifier of the target component, binding the construction process data of the target component with the component-level identifier, and generating a component-level data package; aggregating the component-level data packages of all target components belonging to the same space to be inspected according to a preset spatial hierarchy, and generating a room-level data package corresponding to the space to be inspected; responding to an acceptance request for the space to be inspected, retrieving the corresponding room-level data package for acceptance judgment, and generating a processing record associated with the space to be inspected based on the acceptance judgment result. Therefore, this application can solve the problems in related technologies such as the difficulty of non-destructive quality verification during acceptance, the lack of correlation between construction data and components and space, and the incomplete coverage of sampling acceptance. Any unqualified component can be quickly located to its specific location, responsible party, and all related data, realizing full-coverage digital acceptance of concealed works quality, eliminating the quality risk blind spots caused by sampling, and ensuring that the construction quality of every concealed component can be verified. At the same time, this application integrates quantitative testing parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration, greatly reducing the complexity and labor intensity of acceptance work, improving acceptance efficiency and accuracy, and thus ensuring the construction quality of concealed works in building engineering.

[0057] It should be noted that the method of this embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this embodiment, and the multiple devices will interact with each other to complete the above method.

[0058] It should be noted that the above description describes some embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0059] refer to Figure 3 This is a schematic diagram of a concealed engineering quality inspection and acceptance device in an embodiment of this application.

[0060] The concealed works quality inspection and acceptance device 300 includes: acquisition module 301, construction module 302, and acceptance module 303.

[0061] The acquisition module 301 is configured to acquire the component-level identifier of the target component, bind the construction process data of the target component with the component-level identifier, and generate a component-level data package; The construction module 302 is configured to aggregate the component-level data packets of all target components belonging to the same space to be verified according to a preset spatial hierarchy, and generate a room-level data packet corresponding to the space to be verified. The acceptance module 303 is configured to respond to an acceptance request for the space to be verified, retrieve the corresponding room-level data packet for acceptance judgment, and generate a processing record associated with the space to be verified based on the acceptance judgment result.

[0062] The acquisition module 301 is also configured as follows: Before obtaining the component-level identifier of the target component, the method also includes: Based on a pre-unified spatial and component classification coding standard, spatial-level identifiers are assigned to the spaces to be verified, component-level identifiers are assigned to the target components, and a hierarchical association between the verification spatial units and the target components is established in the building information model or spatial relational database.

[0063] Optionally, the acquisition module 301 is also configured as follows: Obtain the component-level identifier of the target component, bind the construction process data of the target component with the component-level identifier, and generate a component-level data package, including: The component-level identification of the target component can be obtained by scanning the QR code or RFID tag attached to the target component with a terminal device. Collect construction process data related to the target component; the construction process data includes structured detection parameters and unstructured image data; Package the component-level identifiers and construction process data to generate a component-level data package.

[0064] Optionally, the acquisition module 301 is also configured as follows: The component-level data package also includes component-level identifiers, the time of data collection for the construction process, and operator information.

[0065] Optionally, the acquisition module 301 is also configured as follows: By analyzing the surveillance video streams collected by fixed cameras set up in the construction area, image recognition technology is used to automatically capture key node images related to the installation of the target components. The identified key node images are bound to the corresponding component-level identifiers of the target components, and used as unstructured image data.

[0066] Acceptance module 303 is also configured as follows: Acceptance judgment is performed on the space to be verified based on room-level data packets; In response to a non-compliance acceptance result, a rectification task is generated; the rectification task is automatically associated with a space-level identifier and at least one component-level identifier that is marked as non-compliance.

[0067] Optionally, the acceptance module 303 is also configured as follows: Bind the component-level identifier of the target component to the supply chain information of the target component; In response to the failure of the acceptance judgment of the target component corresponding to the component-level identifier, the supply chain information corresponding to the target component is retrieved.

[0068] The concealed works quality inspection and acceptance device provided in this application can solve the problems in related technologies, such as the difficulty in non-destructive verification of quality, lack of correlation between construction data and components and space, and incomplete coverage of sampling acceptance. Any unqualified component can be quickly located, and the responsible party and related full data can be identified. This achieves full-coverage digital acceptance of concealed works quality, eliminates the quality risk blind spots caused by sampling, and ensures that the construction quality of every concealed component can be verified. At the same time, this application integrates quantitative testing parameters and unstructured image data, eliminating the need for manual on-site destructive verification or fragmented data integration. This significantly reduces the complexity and labor intensity of the acceptance work, improves the efficiency and accuracy of acceptance, and thus guarantees the construction quality of concealed works in building engineering.

[0069] refer to Figure 4 The diagram below is a block diagram of an electronic device according to some embodiments of the present invention. It illustrates a more specific hardware structure of an electronic device provided in this application embodiment. The device may include: a processor 410, a memory 420, an input / output interface 430, a communication interface 440, and a bus 450. The processor 410, memory 420, input / output interface 430, and communication interface 440 are internally connected to each other via the bus 450.

[0070] The processor 410 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0071] The memory 420 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 420 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 420 and is called and executed by the processor 410.

[0072] Input / output interface 430 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0073] The communication interface 440 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0074] Bus 450 includes a pathway for transmitting information between various components of the device, such as processor 410, memory 420, input / output interface 430, and communication interface 440.

[0075] It should be noted that although the above-described device only shows the processor 410, memory 420, input / output interface 430, communication interface 440, and bus 450, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0076] The electronic devices described above are used to implement the corresponding concealed works quality inspection and acceptance methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding concealed works quality inspection and acceptance method embodiments, which will not be repeated here.

[0077] Based on the same concept, corresponding to the concealed works quality inspection and acceptance method provided in any of the above embodiments, this application also provides a computer-readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, it implements the concealed works quality inspection and acceptance method as in the first aspect.

[0078] The aforementioned computer-readable storage medium can be any available medium or data storage device that a computer can access, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0079] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the corresponding concealed works quality inspection and acceptance method in any of the foregoing embodiments, and have the beneficial effects of the corresponding concealed works quality inspection and acceptance method embodiments, which will not be repeated here.

[0080] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0081] From the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0082] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other implementations under the guidance of this application without departing from the spirit and scope of the claims. All of these implementations are within the protection scope of this application.

Claims

1. A method for detecting and accepting the quality of a concealed work, characterized in that, The method comprises: obtaining a component-level identifier of a target component, and binding construction process data of the target component with the component-level identifier to generate a component-level data package; according to a preset spatial hierarchy, aggregating component-level data packages of all target components belonging to a same to-be-checked space to generate a room-level data package corresponding to the to-be-checked space; in response to an acceptance request for the to-be-checked space, calling the corresponding room-level data package for acceptance determination, and generating a processing record associated with the to-be-checked space according to an acceptance determination result.

2. The concealed work quality detection acceptance method according to claim 1, characterized in that, Before the obtaining of the component-level identifier of the target component, the method further comprises: based on a pre-unified space and component classification coding standard, assigning a space-level identifier to the to-be-checked space and a component-level identifier to the target component, and establishing a hierarchical association between the to-be-checked space unit and the target component in a building information model or a spatial relationship database.

3. The method for concealed construction quality detection and acceptance according to claim 1, characterized in that, The obtaining of the component-level identifier of the target component, and the binding of the construction process data of the target component with the component-level identifier to generate a component-level data package comprises: scanning a two-dimensional code or an RFID tag attached to the target component through a terminal device to obtain the component-level identifier of the target component; collecting construction process data related to the target component; wherein the construction process data comprises structured detection parameters and unstructured image data; packaging the component-level identifier and the construction process data to generate the component-level data package.

4. The method for concealed construction quality detection and acceptance according to claim 3, characterized in that, The component-level data package further comprises collection time of the component-level identifier and the construction process data and operator information.

5. The method for concealed construction quality detection and acceptance according to claim 3, characterized in that, The method further comprises: automatically intercepting key node pictures related to installation of the target component by analyzing monitoring video streams collected by fixed cameras arranged in a construction area through image recognition technology; binding the recognized key node pictures with the component-level identifier of the corresponding target component as the unstructured image data.

6. The concealed work quality detection acceptance method according to claim 1, wherein, The method further comprises: performing acceptance determination on the to-be-checked space based on the room-level data package; in response to an unqualified acceptance determination result, generating a rectification task; wherein the rectification task is automatically associated with the space-level identifier and at least one component-level identifier marked as unqualified.

7. The concealed work quality detection acceptance method according to claim 6, wherein, The method further comprises: binding the component-level identifier of the target component with supply chain information of the target component; in response to an unqualified acceptance determination result of a target component corresponding to the component-level identifier, calling the supply chain information corresponding to the target component.

8. A concealed work quality detection and acceptance device, characterized by, The method comprises: an obtaining module configured to obtain a component-level identifier of a target component, and bind construction process data of the target component with the component-level identifier to generate a component-level data package; a building module configured to aggregate component-level data packages of all target components belonging to a same to-be-checked space according to a preset spatial hierarchy to generate a room-level data package corresponding to the to-be-checked space; and a processing module configured to, in response to an acceptance request for the to-be-checked space, call the corresponding room-level data package for acceptance determination, and generate a processing record associated with the to-be-checked space according to an acceptance determination result. The acceptance module is configured to, in response to an acceptance request for the space to be verified, retrieve the corresponding room-level data packet for acceptance judgment, and generate a processing record associated with the space to be verified based on the acceptance judgment result.

9. An electronic device, comprising: include: A processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions being executed by the processor to implement the steps of the concealed works quality inspection and acceptance method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the concealed works quality inspection and acceptance method as described in any one of claims 1 to 7.

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