Quick connection and positioning construction technology of prefabricated components of fabricated building

Abstract

The application discloses a quick connection and positioning construction process of prefabricated components of fabricated buildings, which takes a building information model as the only data source and sequentially executes the following steps: digital pre-matching and dynamic instruction generation, component state synchronization and on-site coordinate calibration, dynamic hoisting and multi-stage positioning under real-time guidance, self-adaptive connection and state self-locking, and installation quality online sensing and closed-loop verification. Through multi-stage intelligent positioning of fusion of vision, optics and non-contact force field, the components are precisely positioned at the millimeter level. By using the self-adaptive connection node of the built-in sensing and driving element, the error is automatically compensated and high-strength locking is completed. Based on the real-time acquisition of multi-dimensional physical quantity data, the quality is determined online and a traceable digital file is formed, and all data are gathered into a project digital twin for overall performance simulation and construction dynamic optimization. The application realizes full-process digitalization, and significantly improves the installation precision, operation efficiency and quality controllability of fabricated buildings.

Description

Technical Field

[0001] This invention belongs to the field of industrial and mining engineering construction technology in the advanced environmental protection industry, and specifically relates to a rapid connection and positioning construction process for prefabricated components of assembled buildings. Background Technology

[0002] While prefabricated buildings have become an important direction for building industrialization due to their standardization and efficiency, and are particularly valued in advanced environmental protection industrial parks and industrial and mining engineering projects, the final stage of on-site installation has consistently hindered the full realization of their advantages. Currently, the on-site connection and positioning of prefabricated components mainly rely on manual hoisting, visual alignment, and manual fixing, leading to an irreconcilable contradiction between construction accuracy, efficiency, and quality stability. This contradiction is even more pronounced in large-span, high-load structures in industrial and mining engineering projects, and also affects the core demands of advanced environmental protection industrial projects for green, rapid, and high-quality construction. Specifically, installation accuracy heavily relies on the personal experience of hoisting operators and installation workers, easily leading to accumulated errors that affect structural safety and subsequent decoration; temporary support systems are cumbersome, and high-altitude operations such as component positioning, adjustment, and fixing are time-consuming and pose significant safety risks; complex on-site wet operations further prolong the time of key processes, and are affected by factors such as ambient temperature, making it difficult to guarantee quality uniformity. This conflicts with the clean and low-carbon construction concepts advocated by advanced environmental protection industries and the complex and harsh environments often faced by industrial and mining engineering projects.

[0003] From a technical perspective, existing mainstream connection technologies such as grouting sleeves, welding, and bolting still fundamentally adhere to the traditional construction logic of positioning first, then alignment, and slow fixing. For example, the widely used grouting sleeve connection requires multiple steps in its construction process, including initial positioning, setting up multi-directional bracing, fine-tuning, sealing, grouting, curing, and bracing removal. This long and interconnected chain of processes has become a key factor restricting the large-scale promotion of prefabricated construction technology in industrial and mining engineering projects. It also struggles to meet the stringent standards of advanced environmental protection projects regarding construction cycles and resource consumption. Furthermore, there is an inherent contradiction between precision control, operational efficiency, and connection reliability: pursuing high precision requires repeated adjustments, sacrificing efficiency; while rushing to meet deadlines may lead to quality issues due to incomplete grouting or inadequate fine-tuning. In addition, welding and bolting also face challenges such as high skill requirements for operators, scattered quality control points, and high labor intensity. These problems are further amplified in the field or under special working conditions of industrial and mining engineering projects.

[0004] To improve the situation, the industry has made numerous attempts, such as introducing BIM technology for construction simulation, using total stations for assisted measurement and positioning, and developing various new connectors. However, these improvements are mostly localized optimizations and have failed to form a systematic solution. Information gaps still exist between the BIM model and actual on-site construction; measurement and positioning require interrupting hoisting operations for separate procedures; and new connectors often fail to simultaneously address the fundamental issue of how to achieve rapid and accurate alignment. Therefore, developing a systematic construction process integrating intelligent positioning, adaptive connection, and streamlined operation to achieve a synergistic improvement in accuracy, efficiency, and quality has become an urgent need to promote the upgrading of prefabricated building technology and better serve advanced environmental protection industries and complex industrial and mining engineering construction. This is not only an inherent requirement for improving the level of building industrialization but also a strategic need to respond to the green development of advanced environmental protection industries and help improve the quality and efficiency of industrial and mining engineering construction. Summary of the Invention

[0005] The purpose of this invention is to introduce a rapid connection and positioning construction process for prefabricated components in prefabricated buildings, thereby solving the problem of difficulty in coordinating precision, efficiency and quality in prefabricated buildings.

[0006] This invention introduces a rapid connection and positioning construction process for prefabricated components in assembled buildings, comprising the following steps: S1. Digital pre-matching and instruction generation: Based on the building information model of the project, extract the theoretical spatial coordinates, geometric dimensions and connection node information of the target prefabricated components, and generate digital installation instructions that include hoisting path, placement logic sequence and installation accuracy. S2. Component status synchronization and on-site environment calibration: Before the component is lifted, its actual physical properties are bound to the virtual model in the digital installation instructions by scanning the unique coded identifier integrated on the component; at the same time, at least three non-collinear fixed reference points are set at the construction site to establish a spatial coordinate system that is consistent with the building information model. S3. Real-time guided dynamic hoisting and multi-level positioning: During the hoisting process, the spatial pose data of the component is acquired in real time and compared with the target path in the digital installation instructions to generate dynamic adjustment instructions to guide the hoisting equipment to move; when the component approaches the target position, coarse positioning achieved by image recognition, fine positioning achieved by optical ranging, and final micron-level alignment achieved by non-contact force field guidance are executed in sequence. S4. Adaptive connection and state self-locking: When the component comes into contact with the lower structure through the final micron-level alignment, the adaptive coupling mechanism set in the connection node is triggered. The adaptive coupling mechanism can automatically compensate for construction errors and guide the component to reach the preset posture. Then, it automatically performs physical locking action to form a permanent or temporary fixed connection. S5. Online sensing and closed-loop verification of installation quality: During and after the physical locking action is performed, multi-dimensional physical quantity data reflecting the connection status are collected in real time and transmitted to the central control system. The central control system automatically compares and analyzes the real-time data with the pre-stored theoretical thresholds, determines the installation quality based on the analysis results, and generates a traceable digital archive of installation quality.

[0007] This invention organically combines five steps—digital pre-matching, real-time guidance, adaptive connection, and online verification—to construct a closed-loop intelligent installation process from virtual planning to physical implementation. This process changes the traditional work mode that relies on manual experience and repeated adjustments, replacing subjective judgment with systematic digital instructions and automatic control. As a result, it achieves a synergistic improvement in installation accuracy, work efficiency, and process safety, providing a brand-new, highly controllable, and high-quality solution for prefabricated building construction.

[0008] According to the optimization of the rapid connection and positioning construction process of the present invention, the multi-level positioning in step S3 specifically includes: (a) Coarse positioning stage: The preset visual feature code on the component is captured by the image acquisition device, and its positional deviation from the target projection contour is calculated to guide the component to move to a range where the deviation is less than the first threshold. (b) Fine positioning stage: Based on coarse positioning, the precise distance of a specific edge or corner of the component relative to the benchmark markers on the construction site is obtained using a ranging device. The three-dimensional translation and rotation deviation of the component is calculated by an algorithm and guided to be adjusted to a range where the deviation is less than a second threshold, and the second threshold is less than the first threshold. (c) Final Alignment Stage: When the component descends to a set distance from the target surface, non-contact guiding units located at the bottom of the component and the top of the supporting structure are activated. The controllable force field generated by these units automatically corrects any remaining deviations and smoothly guides the component into the preset guiding structure without rigid contact, achieving precise positioning with deviations less than a third threshold, which is less than the second threshold. This solution achieves the best balance between positioning accuracy and robustness through a phased, progressive positioning strategy of image recognition → optical ranging → non-contact force field guidance. Coarse positioning efficiently handles large-scale deviations, fine positioning performs refined calibration, and the final force field guidance flexibly overcomes minor deviations and swaying, ensuring that the component's posture before final contact is highly compliant with requirements. This reduces the risk of hard collisions and reliance on mechanical adjustment mechanisms, making millimeter-level or even micrometer-level precise positioning possible in complex construction environments.

[0009] According to the optimized rapid connection and positioning construction process of the present invention, the adaptive connection and state self-locking process in step S4 is as follows: the conical or wedge-shaped guide at the bottom of the component, guided by the final micron-level alignment, is inserted into the corresponding bearing interface of the lower structure; the bearing interface is provided with a buffer medium capable of elastic or plastic deformation, and a constraint mechanism surrounding the buffer medium; when the guide is inserted to a predetermined depth, the constraint mechanism is triggered to move, causing it to contract radially to press the buffer medium and the guide, forming a friction-type or shape-fit type mechanical lock. This solution achieves a balance between fault tolerance and high-strength connection. The design of the guide and the bearing interface with the buffer medium allows for a certain range of residual deviation in the final alignment stage of the component. This deviation can be automatically absorbed and compensated during the insertion process, while the subsequent radial contraction locking of the constraint mechanism can firmly fix the component and utilize the deformation of the buffer medium to generate uniform contact pressure, effectively improving the stiffness and fatigue performance of the node connection.

[0010] According to the optimized rapid connection and positioning construction process of the present invention, the multi-dimensional physical quantity data reflecting the connection status in step S5 includes at least: compressive stress at the connection interface, the final three-dimensional coordinates and attitude angles of the component after installation, and the effective stroke or preload of the locking mechanism. The closed-loop verification means that if all the real-time data are within the corresponding theoretical threshold range, the system confirms the installation is qualified and archives the data; if any data exceeds the limit, the system immediately issues an alarm containing the deviation type and value, and records the installation as pending review. This transforms quality control from traditional post-installation sampling to full-process, data-driven real-time monitoring and immediate feedback. By collecting multi-dimensional physical quantities and automatically comparing them with theoretical thresholds, the system can instantly determine whether the installation quality of each connection node is qualified and generate an unalterable digital archive. This not only enables early detection and warning of quality problems, avoiding defect accumulation, but also forms a complete quality traceability chain, providing a reliable data foundation for project acceptance and subsequent operation and maintenance.

[0011] According to the optimized rapid connection and positioning construction process of this invention, the digital installation instructions in step S1 are dynamically generated. The generation logic includes: dynamically adjusting the theoretical target coordinates of subsequent components to be installed based on actual measurement data of already installed components, in order to eliminate or control accumulated construction errors in real time. This solution endows the construction system with adaptive adjustment capabilities, enabling it to proactively respond to and eliminate error accumulation during construction. By dynamically correcting subsequent instructions based on the measured data of already installed components, the entire installation process becomes a continuously self-optimizing system, thereby ensuring the final overall shape and position accuracy of large or complex structures and solving the key problem of error transmission in prefabricated buildings.

[0012] According to the optimized rapid connection and positioning construction process of the present invention, the component status synchronization in step S2 further includes: scanning and reading the radio frequency tag or memory embedded in the component to obtain the component's production batch, material strength, curing date, and dedicated quality inspection report information, and storing this information in the digital archive in association with the installation record. This achieves transparent management of the entire building component process. By associating the installation record with the component's original production data, it not only improves the integrity of quality traceability but also provides a basis for root cause analysis of potential performance problems, while providing data support for structural analysis and full life cycle management based on actual component performance.

[0013] According to the optimized rapid connection and positioning construction process of the present invention, during the hoisting process in step S3, the system monitors the component's acceleration, wind speed, and distance from surrounding obstacles in real time. If the monitored values ​​exceed the safety threshold, it automatically sends a deceleration or pause command to the hoisting equipment until the monitored values ​​return to normal. This solution upgrades the safety guarantee of the intelligent installation process from static protection to dynamic proactive prevention and control. By monitoring the motion status and environmental risks in real time and automatically intervening in equipment actions when limits are exceeded, it significantly reduces the risk of hoisting safety accidents caused by improper operation, sudden wind changes, or spatial conflicts, ensuring the safety of personnel and equipment working at heights, and making the high-speed automated construction process more reliable and controllable.

[0014] According to the optimized rapid connection and positioning construction process of the present invention, after step S4 is completed, for wet connection nodes requiring grouting, the system will automatically calculate and prompt the optimal grouting material ratio and dosage based on the node gap data obtained from online sensing, and monitor the grout filling degree and solidification state through pre-embedded sensors during the grouting process. This solution seamlessly extends the intelligent advantages of rapid dry connection to the necessary wet operation stage. By calculating the material dosage and ratio based on measured gap data, the precise application of grouting material is achieved, avoiding waste and incomplete compaction. At the same time, the monitoring of filling degree and solidification state ensures the final quality of the wet connection node, making up for the shortcomings of traditional grouting operations that rely on manual experience and have large quality fluctuations, forming a complete dry-wet combined connection quality assurance system.

[0015] This invention also introduces a construction quality control method for prefabricated buildings based on the aforementioned construction process, comprising: at the project level, compiling the digital archives of the installation quality of all components to construct a digital twin of the project's construction quality; based on the digital twin, simulating and verifying the overall structural stress performance to identify potential weak points; and based on the identification results, generating targeted local reinforcement schemes or subsequent installation adjustment suggestions, forming a closed-loop quality management system from single-point installation to overall performance. This construction quality control method elevates the installation quality data of a single component to the level of overall project structural performance evaluation and optimization. By constructing a quality digital twin and performing simulation verification, it can proactively identify systemic risks or weak points, thereby guiding targeted reinforcement in design or construction. This achieves a strategic shift in quality management from post-inspection to pre-prediction and in-process control, improving the overall reliability and economy of the project.

[0016] This invention also introduces a collaborative control system for executing the above-mentioned construction processes. The system includes at least: a planning and simulation module for executing S1; a data binding and coordinate calibration module for executing S2; a real-time perception and guided decision-making module for executing S3; a connection process control module for executing S4; and a quality judgment and data management module for executing S5. The modules exchange information and coordinate instructions through a unified digital model and data interface, ensuring seamless digital integration from planning to verification. This invention, through a modular software architecture, solidifies the aforementioned processes into an executable and replicable standardized digital system. The various professional modules work collaboratively based on a unified data model, ensuring seamless information flow and eliminating information silos. This system is not only a carrier of the processes but also constitutes an open intelligent construction platform that can integrate various devices and algorithms, promoting the evolution of construction management towards high integration and automation.

[0017] Compared with the prior art, the beneficial effects of the present invention are:

[0018] 1. At the core technology level, this invention achieves a breakthrough in prefabricated construction, particularly suitable for industrial and mining engineering projects with extremely high requirements for precision and reliability. By integrating a multi-mode intelligent positioning system combining vision, laser, and electromagnetic technologies, the installation accuracy of components is generally improved from centimeter-level in traditional processes to millimeter-level, eliminating the accumulation of human error, ensuring structural safety and the flatness of subsequent processes, and meeting the stringent requirements of advanced environmental protection facilities for precise construction. Simultaneously, adaptive rapid connection nodes and standardized installation processes shorten the average on-site operation time for single components, significantly reducing the duration of high-altitude and high-risk operations, thus improving the inherent safety level of on-site construction in industrial and mining engineering projects. Furthermore, by utilizing built-in sensors in the nodes to achieve visualized and data-driven judgment of connection quality, hidden works are made transparent, resulting in a stable increase in the first-time pass rate. This provides technical assurance for the quality traceability valued in advanced environmental protection projects, ultimately achieving a unified improvement in precision, efficiency, and quality reliability.

[0019] 2. At the engineering management level, this invention brings significant cost reduction, efficiency improvement, and process optimization benefits to advanced environmental protection industries and industrial and mining engineering construction projects. The process of this invention greatly reduces reliance on the experience of highly skilled hoisting and installation workers, shifting the core work from physical labor and experience to monitoring and confirmation. This results in significant savings in labor costs. The standardization and predictability of the construction process make project progress control more precise, and the overall construction period can be shortened. This is crucial for the construction of advanced environmental protection industrial parks that pursue investment efficiency and for industrial and mining engineering construction projects with strict deadlines. Furthermore, precise positioning and rapid dry connection reduce secondary operations such as on-site adjustments, cutting, and repairs, effectively reducing material loss and construction waste generation. This not only aligns with the green construction and circular economy concepts advocated by advanced environmental protection industries but also improves the efficiency of material management and environmental friendliness on-site in industrial and mining engineering construction, demonstrating outstanding full life-cycle economic benefits.

[0020] 3. At the industry development level, this invention provides key technological support for the deep industrialization and digital transformation of prefabricated buildings, powerfully promoting their deep integration and innovative application in both advanced environmental protection industries and industrial and mining engineering construction. The full-process digital construction log generated by this technology can seamlessly connect with project management platforms, serving as a crucial data entry point for intelligent construction and meeting the needs of advanced environmental protection industries for full-process digital management of projects. It drives the transformation of construction methods from decentralized, extensive manual operations to centralized, refined, and process-oriented operations, a transformation that aligns with the modular and prefabricated development trend of industrial and mining engineering construction. Therefore, this technology lays a solid technical foundation for the future development of larger-scale and more efficient modular buildings, and has significant strategic value in leading the technological upgrading of advanced environmental protection infrastructure construction and complex industrial and mining engineering construction. Attached Figure Description

[0021] Figure 1 This is a system architecture diagram of the rapid connection and positioning construction process for prefabricated building components of the present invention;

[0022] Figure 2 This is a flowchart illustrating the rapid installation process of the present invention.

[0023] Figure 3 This is a flowchart of the multi-level positioning process in this invention;

[0024] Figure 4 This is a block diagram of the adaptive connection and state self-locking control logic in this invention;

[0025] Figure 5 This is a block diagram of the closed-loop quality control and digital twin data flow in this invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0027] like Figure 1-5 The rapid connection and positioning construction process for prefabricated components of assembled buildings of the present invention is a systematic installation method integrating digital modeling, intelligent sensing and adaptive control, specifically including the following steps:

[0028] S1. Digital Pre-matching and Instruction Generation: Based on the building information model of the project, extract the theoretical spatial coordinates, geometric dimensions, weight distribution, center of gravity position, and connection node types and tolerance requirements of the target prefabricated components. Generate a digital installation instruction set containing hoisting trajectory, aerial attitude adjustment points, positioning logic sequence, docking fault tolerance range, and graded accuracy indicators through path optimization algorithm. This instruction set can dynamically adapt to the performance of different hoisting equipment and on-site working conditions.

[0029] S2. Component Status Synchronization and On-site Environment Calibration: Before the components are lifted, the unique identification code of the components and their actual physical attributes are bound to the corresponding entities in the BIM model through radio frequency identification, QR code or UWB positioning tag scanning, to complete the object-model consistency mapping; at the same time, total stations, laser trackers or UWB positioning base station networks are deployed on the construction site, and a construction control network with high precision alignment with the coordinate system of the building information model is established through resection and coordinate transformation algorithms, so as to achieve spatial unity between virtual planning and physical environment;

[0030] S3. Real-time guided dynamic hoisting and multi-level positioning: During hoisting, the real-time six-degree-of-freedom pose of the component is perceived by fusion of inertial measurement unit, vision sensor and wireless ranging equipment. The swaying noise is eliminated by filtering algorithm and compared with the preset path model prediction to generate dynamic adjustment instructions containing speed, direction and attitude corrections, driving the crane intelligent control system to achieve smooth tracking transportation. When approaching the target position, the following are executed in sequence: ① Coarse positioning based on machine vision, which obtains the large deviation between the component and the target through feature matching; ② Fine positioning based on lidar or total station, which achieves millimeter-level pose calibration through multi-point cloud registration and adjustment calculation; ③ Final alignment based on electromagnetic or pneumatic guide field, which achieves micron-level adaptive correction and soft landing guidance before contact through non-contact compliant control.

[0031] S4. Adaptive Connection and State Self-Locking: After the component makes initial contact with the substructure through final alignment, the intelligent coupling mechanism embedded in the connection node is triggered. This mechanism is usually composed of shape memory alloy drive components, piezoelectric ceramic fine adjusters, or hydraulic adaptive jaws. It can automatically compensate for axial deviation, elevation error, and planar misalignment based on real-time feedback of contact force and displacement signals, guiding the component to achieve the theoretical design posture. Subsequently, the servo motor, linear actuator, or high-strength bolt automatic tightening system built into the node performs physical locking according to the preset torque or displacement program, forming a semi-rigid or rigid connection with the design load-bearing capacity.

[0032] S5. Online Sensing and Closed-Loop Verification of Installation Quality: During and after the locking process, multi-dimensional physical quantities such as pressure distribution, relative slippage, preload attenuation, and final orientation of components at the connection interface are collected in real time through embedded fiber optic grating sensors, piezoelectric arrays, or micro-strain gauges. The data is preprocessed by edge computing nodes and then uploaded to the central control system. The system performs real-time comparison and trend analysis based on the digital twin model and the design allowable threshold, automatically determines the installation quality level, and outputs a traceable digital archive containing timestamps, sensor data, deviation curves, and three-dimensional deviation cloud maps. Based on the results, it can trigger iterative optimization instructions for process parameters, forming a closed-loop quality control link of installation-measurement-evaluation-feedback.

[0033] In this invention, the multi-level positioning in step S3 is a progressive pose control method that converges step by step from macro to micro, and its specific implementation process includes:

[0034] (a) Coarse Positioning Stage: In this initial stage, high-resolution image acquisition equipment deployed on the hoisting equipment or fixed stations continuously captures visual feature codes prefabricated on the surface of the prefabricated component, which have high contrast and resistance to light interference. Through visual recognition and image processing algorithms, the pixel coordinates of the feature code center in the image coordinate system are calculated in real time. Based on the pre-calibrated camera parameters and the coordinates of the on-site control network, the projection deviation and yaw angle deviation of the component's current centroid and the target installation position in the horizontal plane are calculated. The system then generates a first-level path correction command to guide the hoisting equipment to move the component to a larger allowable deviation range, which is defined as the first threshold. This range aims to quickly eliminate most of the initial pose errors, laying the foundation for fine operation.

[0035] (b) Fine Positioning Stage: Initiated after coarse positioning is achieved, this stage employs an active ranging device with higher absolute accuracy. The operator or automated system guides the ranging device to target predefined, geometrically defined edge reference points or corner reflection targets on the component, while simultaneously targeting permanent or temporary reference markers precisely measured at the construction site. Multiple sets of precise slope distance, horizontal angle, and vertical angle data are acquired through multi-point measurements. Using algorithms such as spatial resection or least-squares fitting, the precise three-dimensional translational and rotational deviations of the component in its current suspended state are calculated in real time. The system then generates a second-level adjustment command containing micro-motion speed and direction, driving the fine-tuning mechanism of the hoisting equipment for fine posture correction until all deviations converge to a more stringent second threshold range. This stage aims to achieve the basic accuracy requirements for structural installation.

[0036] (c) Final Alignment Stage: When the component descends to a preset critical distance from the target contact surface, the coarse and fine positioning systems pause outputting major adjustment commands and instead activate dedicated non-contact guiding units installed at the bottom of the component and the top of the substructure. These units typically operate based on the principles of controllable electromagnetic fields, uniform air films, or ultrasonic standing waves, creating a soft force field between the component and the target that senses relative position and generates directional adjustment forces. This force field sensitively detects the remaining minute parallelism errors and center offsets between the component's bottom surface and the target surface, automatically generating corrective torques or guiding forces. This allows the component to float just before contact, autonomously and smoothly correcting the final millimeter-level or even sub-millimeter-level deviations. With the assistance of this force field, the component is smoothly and centrally guided to its final physical guide structure entrance, achieving a shock-free and jam-free introduction, completing precise positioning with a deviation less than the third threshold, creating ideal conditions for subsequent connection actions. The entire process embodies a hierarchical and intelligent positioning concept, from visual general guidance to geometrically precise measurement and then to smooth physical field docking.

[0037] In this invention, the adaptive connection and state self-locking process in step S4 is a method for the final consolidation of physical nodes based on intelligent triggering and active constraints. The specific process is as follows:

[0038] The bottom of the component is pre-equipped with a precision-machined conical or wedge-shaped guide. Under the guidance force field or physical guidance generated during the final micron-level alignment stage, the wedge-shaped guide begins to make initial contact and guide the component to the corresponding bearing interface pre-set on the top surface of the lower structure. The inner wall of the bearing interface is lined with a layer of high-performance elastic or elastoplastic buffer medium, which is usually made of modified rubber, polyurethane composite material, or metal rubber. Its design has specific nonlinear stiffness characteristics, which can undergo large deformation in the early stage of compression to absorb and compensate for residual misalignment and impact energy, and then provide significantly increased radial resistance.

[0039] Surrounding the outside of this buffer medium is an integrated high-response constraint mechanism, which can consist of multiple circumferentially distributed friction pads / locking flaps controlled by shape memory alloy drive blocks, piezoelectric ceramic actuators or micro hydraulic cylinders. When the guide part of the component overcomes the initial resistance of the buffer medium and inserts into and reaches the preset trigger depth in the bearing interface, the sensing signal is immediately emitted.

[0040] This signal triggers the constraint mechanism to move, driving all its locking elements to generate a synchronous radial inward contraction movement in a very short time. This contraction is not a simple rigid clamping, but rather, according to a preset pressure-displacement curve, it applies a continuously increasing and evenly distributed radial clamping force to the internal buffer medium and the already wrapped guide part. This force causes the buffer medium to undergo further controllable deformation, which not only completely eliminates all assembly gaps, but also generates a huge normal contact pressure on the surface of the guide part.

[0041] Ultimately, the enormous static friction provided by the highly compressed buffer medium, and / or the shape fit formed by the interference fit or mechanical interlock between the guide part and the locking element / receiving interface structure, together constitute a high-strength, high-rigidity mechanical locking state. This state can reliably transmit shear force, pull-out force and bending moment, realizing a permanent or detachable fixed connection between the component and the substructure. The whole process reflects the intelligent transformation from flexible introduction and error compensation to active triggering and rigid locking.

[0042] In this invention, the multidimensional physical quantity data used for real-time evaluation and verification of connection quality in step S5 is a comprehensive monitoring dataset composed of multi-sensor fusion, which systematically includes at least the following core parameters and their derived indicators:

[0043] Mechanical state data of the connection interface: Through an embedded thin-film pressure sensor array or fiber optic grating sensor network, the compressive stress distribution cloud map of the contact surface of the connection node is collected and plotted in real time to obtain the average stress, peak stress and stress uniformity coefficient, so as to directly reflect the sufficiency of locking and the integrity of contact.

[0044] Final spatial orientation data of components: Using a total station, laser tracker or vision measurement system, the final three-dimensional coordinates and attitude angles of the components are measured immediately after locking and compared with the design coordinates to calculate the installation positioning deviation. This data is the direct basis for evaluating the installation geometric accuracy.

[0045] Locking mechanism execution process data: Monitor and record the real-time curves of the effective stroke, output preload or torque of the locking mechanism. By analyzing the curve characteristics, it can be determined whether the locking action is completed according to the preset logic, and whether there are any abnormalities such as slippage or overload.

[0046] The closed-loop verification described above is an automated decision-making and feedback process driven by rules and models.

[0047] Acceptance Assessment and Archiving: The central control system synchronizes and automatically compares the aforementioned real-time streaming data with the theoretical threshold ranges of each parameter pre-set based on the BIM model and structural design specifications. If the values ​​of all data streams at all key time points remain within their corresponding allowable ranges, the system automatically determines that the installation is qualified. Subsequently, the system encrypts and signs the complete data package of this installation and archives it into an immutable digital archive of installation quality, forming a quality record that can be traced for life.

[0048] Anomaly Alarms and Handling: If any physical quantity exceeds its theoretical threshold at any time, the system will immediately trigger a multi-level alarm. The alarm information not only includes the specific parameters of the deviation, the value exceeding the limit, and the time of occurrence, but also conducts preliminary diagnosis of the deviation type through correlation analysis. At the same time, the system automatically marks the installation as pending review and can execute a series of linked controls according to preset rules, such as pausing subsequent automated processes, locking relevant equipment, highlighting the problem node in the digital twin model, and pushing the alarm information to the handheld terminals of relevant technical personnel to guide on-site verification or intervention. All alarms and subsequent handling processes are also fully recorded, forming a closed-loop management evidence chain.

[0049] This process achieves a fully automated closed loop from data perception to quality judgment and action feedback, upgrading quality control from traditional result sampling to real-time, digital, traceable, and precise management covering the entire process.

[0050] In this invention, the digital installation instructions in step S1 are not static, unchanging preset files, but rather the output of a dynamically generated system with real-time feedback and adaptive optimization capabilities. Its core generation logic is a closed-loop control process of measurement-analysis-decision, specifically including:

[0051] Before generating installation instructions for subsequent components to be installed, the system will acquire and integrate high-precision actual measurement data of components that have been installed on site in real time. These data come from the quality verification process described in step S5 and include the final actual three-dimensional coordinates, attitude angles, and actual deviation values ​​of key connection nodes of each installed component. The error propagation analysis and compensation algorithm built into the central control system will continuously learn and model these data streams.

[0052] The algorithm of this invention first identifies and quantifies the cumulative trends and spatial distribution patterns of systematic and random errors generated during construction. Based on this analysis, the system dynamically predicts the impact of current errors on the theoretical positions of subsequent components to be installed, and proactively performs intelligent compensation and adjustment of the theoretical target coordinates of subsequent components.

[0053] For example, if analysis reveals a linearly increasing slight deviation in the X-direction of a certain column of installed components, the system will perform a reverse pre-offset correction on the theoretical X-coordinate value of the next component in that column when generating the installation instruction. This correction is not a simple equal-value cancellation, but rather an algorithmic optimization adjustment of the theoretical spatial relationship of the entire installation sequence. The aim is to interrupt or minimize the progressive transmission and accumulation of errors at the source, ensuring the overall straightness and closure accuracy of the building.

[0054] The essence of this dynamic generation logic is to transform traditional construction based on fixed blueprint coordinates into dynamic adaptive construction based on the actual completed state, making the installation instructions an intelligent plan that can continuously self-calibrate as the project progresses, thereby achieving the goal of high-precision construction.

[0055] In this invention, the component status synchronization step S2 goes far beyond simple identity binding. It constructs a channel for the migration and fusion of physical component lifecycle data into the digital space. The core of this process lies in scanning or sensing the unique data carrier embedded inside the component using a dedicated reading and writing device. This carrier can be a passive tag, an active sensor tag, or a miniature encrypted memory, which stores the component's full-dimensional identity and history information.

[0056] The information acquired synchronously includes at least: production traceability data, such as unique number, production batch, production line number, concrete mix design number, and the supplier and batch number of the main raw materials.

[0057] Quality attribute data: such as the compressive strength and modulus of elasticity of concrete measured in the laboratory, the yield strength and elongation of steel bars, and the factory inspection tolerances of key dimensions.

[0058] Process data: such as pouring date, demolding time, temperature-humidity-time curve of steam curing, and storage location and duration of finished products.

[0059] Exclusive document data: such as structural performance calculation sheets, third-party quality inspection reports, certificates of conformity, and electronic files of the final version of fabrication drawings including design changes.

[0060] After reading this data, the system does not store it in isolation, but treats it as a key attribute, deeply associates it with and integrates it into the BIM model entity corresponding to the component; at the same time, this information will be timestamped and logically associated with all subsequent installation records generated for the component.

[0061] All these static attributes and dynamic process data are structured and encapsulated and stored in the aforementioned installation quality digital archive, and even in the more macroscopic project digital twin. This establishes an immutable digital identity card and resume for each component that runs through the entire process of design, production, logistics, installation and operation and maintenance. This provides a solid data foundation for achieving accurate quality traceability, performance evaluation and future intelligent maintenance. This process marks the transformation of the managed object from a physical component to an intelligent product carrying a complete digital gene.

[0062] In this invention, during the entire hoisting process in step S3, the system integrates an active, multi-dimensional fusion safety situation awareness and intelligent intervention subsystem to perform millisecond-level real-time monitoring and risk assessment of key dynamic parameters affecting hoisting stability and operational safety. This system uses inertial measurement units and dynamic tilt sensors integrated into the hook, slings, or component body to collect the component's triaxial linear acceleration, angular acceleration, and sway amplitude in real time; it continuously acquires instantaneous wind speed, wind direction, and gust rate of change at the operational height using ultrasonic / laser anemometers installed at the tower crane boom or on-site; and it constructs a real-time point cloud map using lidar, depth cameras, or millimeter-wave radar deployed around the hoisting path to continuously calculate the minimum dynamic spatial distance between the component's outline and surrounding permanent structures, temporary facilities, construction machinery, and personnel.

[0063] The system has a built-in dynamic safety threshold model. This dynamic safety threshold model is not a fixed value, but rather an adaptive calculation that takes into account the weight, size, hoisting stage and current attitude of the component. All monitoring data streams are input into the central risk assessment engine in real time for fusion analysis.

[0064] Once the system determines that any monitored value or a combination of indicators exceeds the safety threshold for the current stage, it will immediately trigger a tiered proactive control response:

[0065] Warning and speed reduction: First, an audible and visual warning is sent to the crane operator's cab and the ground command terminal, and a deceleration command is automatically generated to smoothly reduce the operating speed.

[0066] Conditional Hover: If the parameters continue to deteriorate or directly reach a higher risk threshold, the system will automatically send a pause command to the control system of the hoisting equipment, causing the equipment to enter a conditional hovering state.

[0067] Safe Recovery: While paused, the system continuously monitors risk parameters. The pause will only be lifted and operation will be recommended or permitted to resume in controlled mode once all monitored data have stably recovered to within the safety threshold for a preset time, and after system self-check or operator confirmation.

[0068] The above process realizes the transformation from passive alarm to active intervention. By embedding intelligence, the safety defense line is moved forward, effectively preventing major safety risks caused by loss of control of motion, sudden changes in wind load or spatial collision, ensuring the inherent safety of high-altitude hoisting operations. All safety events and intervention logs are fully recorded and incorporated into digital archives for subsequent analysis and process optimization.

[0069] In this invention, after the initial mechanical locking of the component is completed in step S4, for nodes that are required by design to use wet connections such as grouting sleeves and grout anchor lap joints, the system will initiate a highly integrated, data-driven intelligent grouting assistance and quality monitoring subprocess.

[0070] First, the system accesses precise node gap data obtained through online sensing in S5. This includes, but is not limited to, the measured three-dimensional dimensions of the sleeve's inner cavity, the width and distribution of the annular gap between the reinforcing bar and the sleeve wall, and the volume of the sealed cavity at the joint. Based on this high-precision geometric data, and combined with the grout material's material property database, the system's embedded dedicated algorithm automatically calculates and optimizes the grout material's mix proportion and precise theoretical dosage to suit the current specific working conditions. Simultaneously, it generates a recommended mixing process. This information is pushed in real-time to the grouting operator's smart terminal or the controller of the automatic mixing equipment.

[0071] During the grouting process, the network of miniature sensors embedded in key parts of the sleeve begins to function. This network may include:

[0072] Resistivity / capacitance sensors or ultrasonic propagation time sensors are used to monitor the filling degree of the slurry in real time, determine whether the entire cavity is filled, and identify the location of any possible air pockets or defects.

[0073] Temperature and pressure sensors monitor changes in hydration heat and internal pressure.

[0074] Photoelectric sensors or vibration viscosity sensors are used to indirectly assess the fluidity of slurry and its initial and final setting states.

[0075] These sensor data are transmitted back to the central control system in real time. The system uses data fusion and trend analysis to dynamically plot the filling-time curve and setting state diagram, comparing them with standard curing curves. If insufficient filling, grouting interruption, or abnormal setting is detected, the system immediately issues an early warning and can coordinate with the grouting equipment for supplementary grouting or adjustment. This upgrades traditional grouting operations, which rely on manual experience, to precise, visual, real-time controllable, and traceable digital operations. It ensures that the compactness and long-term durability of wet connection nodes fully meet design requirements, and all grouting process data is incorporated into the node's full lifecycle digital archive.

[0076] This invention also introduces a construction quality control method for prefabricated buildings based on the above-mentioned rapid installation process. This method realizes full-chain digital quality control from micro-details to macro-structure, and specifically includes the following steps:

[0077] Step 1: Construct an integrated digital twin of project construction quality. At the project level, the installation quality digital archives of all installed and under-installation components are automatically aggregated. This archive integrates heterogeneous data from multiple sources, including geometric accuracy, mechanical condition, material history, and process logs. Through data cleaning, format standardization, and spatiotemporal alignment, this dynamically updated actual construction data is deeply integrated and bound to the original design BIM model to construct a digital twin of project construction quality. This twin not only reflects the state of the structure but also accurately presents it, serving as the sole reliable data source for advanced quality analysis and decision-making.

[0078] Step Two: Structural Overall Performance Simulation Verification and Weakness Identification Based on Digital Twin. Using the aforementioned digital twin as input, integrated finite element analysis or other structural calculation engines are invoked to perform structural overall stress performance simulation verification based on the actual construction state. The verification is based not only on the original design loads but also comprehensively considers the additional internal forces caused by actual installation deviations, the true stiffness of connection nodes, and the actual properties of component materials. By comparing and analyzing the response differences under various load conditions, potential weak points and systemic risk areas with stress concentration, excessive displacement, or insufficient safety reserves are accurately identified, achieving a leap from compliance acceptance to performance prediction.

[0079] Step 3: Generate and implement targeted improvement strategies to form a closed-loop quality management system. Based on the identification results of Step 2, the system automatically or assistedly generates multi-level, executable targeted improvement strategies. For minor existing deviations, local reinforcement schemes can be generated. For subsequent parts that have not yet been constructed, dynamic suggestions for subsequent installation adjustments are generated, such as adjusting the installation posture of subsequent components, correcting the construction process parameters of connection nodes, or fine-tuning the positioning coordinates of subsequent components within the design allowable range to optimize the overall stress. All these strategies are fed back to the design, production, and on-site construction stages in the form of structured instructions or revised drawings.

[0080] Therefore, this method constitutes a complete closed-loop quality management system of data acquisition → model building → performance evaluation → decision optimization → feedback execution. It elevates quality control from the post-event inspection of a single component to the proactive prediction and continuous optimization of the overall structural performance, ensuring the safety, reliability and economy of the final product of prefabricated buildings.

[0081] This invention also introduces a collaborative control system for executing the aforementioned rapid installation process of prefabricated buildings. It is an integrated intelligent construction platform based on a cloud-edge-device architecture and centered on a unified digital twin model. This system achieves fully digital drive and closed-loop control of the process through the collaborative work of the following highly specialized functional modules:

[0082] Planning and Simulation Module: This module carries the functionality of process step S1. It imports and parses the project's full-discipline BIM model and incorporates path planning, clash detection, and installation sequence optimization algorithms. Its core capability lies in its ability to dynamically generate and simulate a set of executable digital installation instructions, including spatial trajectories, logical sequences, and quality control points, based on real-time updated site conditions and resource status.

[0083] Data Binding and Coordinate Calibration Module: This module is responsible for executing process step S2. It provides interfaces with various identification technologies to achieve unique binding of physical component identities, attributes, and BIM model objects. Simultaneously, it integrates control and data processing algorithms for high-precision measuring instruments to rapidly establish, maintain, and dynamically calibrate the global coordinate system at the construction site, ensuring spatial consistency between the virtual and physical worlds.

[0084] Real-time perception and guidance decision-making module: This module is the core of process step S3. It integrates and merges real-time data streams from multiple heterogeneous sensors such as vision sensors, lidar, IMU, and anemometers. By running sensor fusion algorithms, state estimation algorithms, and real-time path replanning algorithms, this module can not only accurately perceive the dynamic state of components and the environment, but also make millisecond-level guidance decisions, generate and issue adjustment commands to the hoisting equipment control system, and achieve safe and accurate dynamic hoisting and multi-level positioning.

[0085] Connection Process Control Module: This module is specifically designed for executing process step S4. It communicates directly with the controller, sensors, and actuators built into the intelligent connection node. Based on predetermined control logic and real-time feedback mechanical signals, this module precisely controls the triggering timing, force, and stroke of adaptive coupling and locking actions, ensuring a reliable and controllable connection process and recording a complete execution log.

[0086] Quality Assessment and Data Management Module: This module corresponds to process step S5. It constructs the core quality database for the project, receiving and processing multi-dimensional physical quantity data from the entire installation process in real time. Through its built-in rule engine and data analysis model, it automatically performs online assessment, grading, and alarm functions for installation quality. More importantly, it is responsible for building and maintaining a traceable digital archive of installation quality from individual components to the entire project, serving as the data foundation for forming a quality closed loop.

[0087] The modules mentioned above do not operate in isolation, but rather through a unified central data bus and standardized application programming interfaces for efficient information exchange and command coordination. All modules revolve around and operate on the same authoritative data source—the project's digital twin model—ensuring seamless data flow and one-way traceability throughout the entire process from planning and design, simulation, on-site execution to quality verification. This truly achieves full-process digital integration. The system constitutes an open and scalable intelligent construction operating system, providing a core digital enabling platform for high-precision and high-efficiency construction of prefabricated buildings.

[0088] In summary, this invention proposes a complete intelligent installation process and collaborative control system for prefabricated buildings, achieving a fundamental transformation in construction methods from reliance on manual experience to data-driven closed-loop control. This solution uses a building information model (BIM) as the sole data source, generating dynamic installation instructions through digital pre-matching. It integrates multiple sensors throughout the entire process for intelligent guidance and precise positioning. Its core innovation lies in the deep integration of adaptive connection mechanisms and online quality perception, enabling each node to automatically compensate for errors, achieve high-strength locking, and verify performance in real time during installation, forming an instant quality closed loop of installation-measurement-evaluation. Ultimately, all process data converge into a traceable digital twin, which not only guides subsequent construction adjustments but also allows for proactive verification and optimization of overall structural performance. This invention constructs a new intelligent construction paradigm that connects the entire chain from virtual planning to physical construction, significantly improving the construction accuracy, efficiency, safety, and quality controllability of prefabricated buildings.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit the technical solutions. Although the applicant has described the present invention in detail with reference to preferred embodiments, those skilled in the art should understand that any modifications or equivalent substitutions made to the technical solutions of the present invention cannot depart from the spirit and scope of the present invention and should be covered within the scope of the claims of the present invention.

Claims

1. A rapid connection and positioning construction process for prefabricated components in prefabricated buildings, characterized in that, Includes the following steps: S1. Digital pre-matching and instruction generation: Based on the building information model of the project, extract the theoretical spatial coordinates, geometric dimensions and connection node information of the target prefabricated components, and generate digital installation instructions that include hoisting path, placement logic sequence and installation accuracy. S2. Component status synchronization and on-site environment calibration: Before the component is lifted, its actual physical properties are bound to the virtual model in the digital installation instructions by scanning the unique coded identifier integrated on the component; at the same time, at least three non-collinear fixed reference points are set at the construction site to establish a spatial coordinate system that is consistent with the building information model. S3. Real-time guided dynamic hoisting and multi-level positioning: During the hoisting process, the spatial pose data of the component is acquired in real time and compared with the target path in the digital installation instructions to generate dynamic adjustment instructions to guide the hoisting equipment to move; when the component approaches the target position, coarse positioning achieved by image recognition, fine positioning achieved by optical ranging, and final micron-level alignment achieved by non-contact force field guidance are executed in sequence. S4. Adaptive connection and state self-locking: When the component comes into contact with the lower structure through the final micron-level alignment, the adaptive coupling mechanism set in the connection node is triggered. The adaptive coupling mechanism can automatically compensate for construction errors and guide the component to reach the preset posture. Then, it automatically performs physical locking action to form a permanent or temporary fixed connection. S5. Online sensing and closed-loop verification of installation quality: During and after the physical locking action is performed, multi-dimensional physical quantity data reflecting the connection status are collected in real time and transmitted to the central control system. The central control system automatically compares and analyzes the real-time data with the pre-stored theoretical thresholds, determines the installation quality based on the analysis results, and generates a traceable digital archive of installation quality.

2. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, The multi-level positioning in step S3 specifically includes: (a) Coarse positioning stage: The preset visual feature code on the component is captured by the image acquisition device, and its positional deviation from the target projection contour is calculated to guide the component to move to a range where the deviation is less than the first threshold. (b) Fine positioning stage: Based on coarse positioning, the precise distance of a specific edge or corner of the component relative to the benchmark markers on the construction site is obtained using a ranging device. The three-dimensional translation and rotation deviation of the component is calculated by an algorithm and guided to be adjusted to a range where the deviation is less than a second threshold, and the second threshold is less than the first threshold. (c) Final alignment stage: When the component descends to a set distance from the target surface, the non-contact guiding units located at the bottom of the component and the top of the supporting structure are activated. The controllable force field generated by these units enables the component to automatically correct the remaining deviation and smoothly guide it into the preset guiding structure in a state of no rigid contact, so as to achieve precise positioning with a deviation less than the third threshold, wherein the third threshold is less than the second threshold.

3. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, The adaptive connection and state self-locking process in step S4 is as follows: the conical or wedge-shaped guide at the bottom of the component is inserted into the corresponding bearing interface of the lower structure under the guidance of the final micron-level alignment; the bearing interface is provided with a buffer medium that can undergo elastic or plastic deformation, and a constraint mechanism surrounding the buffer medium; when the guide is inserted to a predetermined depth, the constraint mechanism is triggered to move, causing it to contract radially and thus press the buffer medium and the guide to form a friction-type or shape-fit type mechanical lock.

4. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1 or 3, characterized in that, The multidimensional physical quantity data reflecting the connection status in step S5 includes at least: compressive stress at the connection interface, final three-dimensional coordinates and attitude angles of the component after installation, and effective stroke or preload of the locking mechanism; the closed-loop verification means that if all the real-time data are within the corresponding theoretical threshold range, the system confirms that the installation is qualified and archives the data; if any data exceeds the limit, the system immediately issues an alarm containing the deviation type and value, and records the installation as pending review.

5. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, The digital installation instructions in step S1 are dynamically generated. The generation logic includes: dynamically adjusting the theoretical target coordinates of subsequent components to be installed based on the actual measurement data of the components already installed on site, so as to eliminate or control the cumulative construction error in real time.

6. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, The component status synchronization in step S2 also includes: scanning and reading the radio frequency tag or memory embedded in the component to obtain the component's production batch, material strength, maintenance date and exclusive quality inspection report information, and storing this information in the digital archive in association with the installation record.

7. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, During the hoisting process in step S3, the system monitors the component's acceleration, wind speed, and distance from surrounding obstacles in real time. If the monitored value exceeds the safety threshold, it automatically sends a deceleration or pause command to the hoisting equipment until the monitored value returns to normal.

8. The rapid connection and positioning construction process for prefabricated components of assembled buildings according to claim 1, characterized in that, After step S4 is completed, for wet connection nodes that require grouting, the system will automatically calculate and prompt the optimal grouting material ratio and dosage based on the node gap data obtained from the online sensing, and monitor the grout filling degree and solidification state of the grout through pre-embedded sensors during the grouting process.

9. A method for quality control of prefabricated building construction based on the construction process described in any one of claims 1 to 8, characterized in that, include: At the project level, the installation quality digital archives of all components are compiled to construct a digital twin of the project construction quality; based on the digital twin, the overall structural stress performance is simulated and verified to identify potential weak points; based on the identification results, targeted local reinforcement schemes or subsequent installation adjustment suggestions are generated to form a closed-loop quality management from single-point installation to overall performance.

10. A collaborative control system for executing the construction process according to any one of claims 1 to 8, characterized in that, The system includes at least: a planning and simulation module for executing S1; a data binding and coordinate calibration module for executing S2; a real-time perception and guided decision-making module for executing S3; a connection process control module for executing S4; and a quality judgment and data management module for executing S5. The modules exchange information and coordinate instructions with each other through a unified digital model and data interface to ensure the digital connection of the entire process from planning to verification.

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