High-altitude sliding dynamic monitoring system and method for steel transfer layer for decorative ceiling based on multi-sensor fusion

Abstract

The invention provides a system and a method for dynamically monitoring high-altitude slippage of a steel transfer layer for a decorative ceiling based on multi-sensor fusion, and belongs to the technical field of metering and assembling of the steel transfer layer for the decorative ceiling. The monitoring system comprises a multi-source sensor module, a data transmission module, a data fusion processing module, a state monitoring analysis module, a closed-loop control early warning module and a visual interaction module. The multi-source sensor collects data such as displacement, stress and temperature, and a dynamic monitoring model is constructed through transmission and fusion processing. According to the method, monitoring is realized through equipment deployment, data acquisition and transmission, fusion processing, state analysis and closed-loop control. According to the system and the method, real-time high-precision monitoring is realized based on a multi-sensor fusion technology, fine adjustment, deceleration or shutdown instructions are output based on monitoring results, early warning is generated, a'monitoring-analysis-control 'closed loop is formed, the safety and the stability of high-altitude sliding construction of the steel conversion layer for the decorative ceiling are effectively guaranteed, and the construction period is shortened. The sliding construction method is suitable for sliding construction scenes of the steel transfer layer for the large-span decorative suspended ceiling.

Description

Technical Field

[0001] This invention relates to the construction and assembly technology of steel transition layers for decorative ceilings, belonging to the field of measurement and assembly technology of steel transition layers for decorative ceilings, and particularly to a high-altitude sliding dynamic monitoring system and method for steel transition layers for decorative ceilings based on multi-sensor fusion. Background Technology

[0002] Large-span steel transfer layers (steel structures) are widely used in projects such as enclosed sheds in open-air material yards, roofs of transportation hubs, and large stadiums due to their high space utilization and strong load-bearing capacity. The high-altitude sliding method, as the core technology for constructing such structures, divides the structure into strip or block units, pre-assembles them on the ground, and then slides them along tracks to the designed position, significantly reducing the intensity of high-altitude work. This method has become one of the mainstream solutions for the construction of large-span steel transfer layers. Ceiling steel structure transfer layers are internal steel frame structures provided when the hangers are too long, the counter-support cannot meet the specifications, or the ceiling space is too large. Their main purpose is to shorten the hanger length, ensure the safety of the ceiling, and facilitate the layout of equipment and pipelines. According to regulations, when the ceiling height exceeds three meters, a transfer layer must be installed to reinforce the joists used in the ceiling and prevent breakage due to excessive stress.

[0003] To achieve the sliding installation of large-span steel structures, various sliding mechanisms or monitoring methods have been developed in the existing technology. For example, a sliding machine for large-span steel structures is disclosed in authorized patent CN104863374B, and a real-time monitoring mechanism for high-altitude sliding of large-span steel structures based on multi-sensor fusion is disclosed in patent application CN202510554103.0. These technologies can partially solve the problem of significant safety hazards caused by deformation and damage to large-span steel structures during the sliding construction process.

[0004] However, current high-altitude slip monitoring technologies for large-span steel structures based on multi-sensor fusion mostly only achieve the single function of "data acquisition - anomaly early warning," without linkage with structural protection components. These technologies have significant shortcomings in the monitoring and control of high-altitude slip in steel structures, especially steel transition layers used in decorative ceilings: First, when anomalies such as structural deformation or excessive stress are detected, there is a lack of linkage mechanism with the protective actuators, making immediate support or adjustment impossible; they can only provide early warnings without substantial protection. Second, the data from multiple sensors lacks effective fusion processing; each parameter is analyzed independently, making it difficult to reflect the correlation of structural states, leading to incomplete monitoring. Third, the sensors do not adhere well to the structural surface, making them highly susceptible to environmental interference and resulting in low data accuracy. Fourth, the lack of closed-loop feedback after control command output prevents dynamic adjustments based on actual execution effects, easily causing control lag or over-adjustment. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes a high-altitude sliding dynamic monitoring system and method for steel transition layers used in decorative ceilings based on multi-sensor fusion.

[0006] In a first aspect of the present invention, a high-altitude sliding dynamic monitoring system for steel conversion layers used in decorative ceilings based on multi-sensor fusion is proposed. The monitoring system includes a multi-source sensor module, a data transmission module, a data fusion processing module, a state monitoring and analysis module, a closed-loop control and early warning module, and a visualization and interaction module. The multi-source sensor module is used to collect displacement, stress, temperature, slipper positioning, and steel column status data during the high-altitude sliding process of the steel conversion layer for decorative ceiling. The data transmission module receives data output from the multi-source sensor module and transmits the data to the data fusion processing module in real time. The data fusion processing module constructs the correlation between various monitoring data based on the received data to obtain the fusion processing result; The status monitoring and analysis module analyzes whether the slippage state of the steel transition layer for decorative ceilings meets preset conditions based on the fusion processing results. The closed-loop control early warning module outputs action adjustment commands to the sliding control device based on the status monitoring and analysis results, and generates early warning information at the same time; The visualization interaction module receives and displays monitoring data, status analysis results, and early warning information; The action adjustment instructions include: for the sliding drive equipment, adjusting the operating parameters to ensure sliding synchronization; for the prestressing control equipment, adjusting the tensioning-related parameters; and for the unloading equipment, controlling the unloading action rhythm.

[0007] The multi-source sensor module also includes a prestress monitoring sensor for collecting prestress state data of the steel conversion layer for decorative ceilings. The prestress monitoring sensor is connected to the data transmission module and synchronously outputs prestress tension and loss-related data to the data fusion processing module.

[0008] The data transmission module includes a wired transmission unit and a wireless transmission unit; the wired transmission unit is used to connect to fixedly deployed sensors to achieve stable data transmission; the wireless transmission unit is used to connect to mobile or high-altitude deployed sensors to adapt to the spatial environment of sliding construction of steel conversion layers for decorative ceilings.

[0009] The data fusion processing module also associates with the BIM model of the steel conversion layer for decorative ceilings, maps the spatial location of the fused monitoring data with the components in the BIM model, forms a monitoring dataset with spatial identification, and transmits it to the status monitoring and analysis module.

[0010] The closed-loop control early warning module includes a multi-level response unit, which outputs different levels of adjustment commands based on the degree of abnormality of the status monitoring and analysis results: a parameter fine-tuning command is output for mild abnormalities, a slip deceleration command is output for moderate abnormalities, and an emergency stop command is output for severe abnormalities.

[0011] In a second aspect of the invention, a method for high-altitude sliding dynamic monitoring of steel transition layers for decorative ceilings based on multi-sensor fusion is also proposed, the method comprising the following steps: Step 1: Deploy multi-source sensors, sliding control equipment, and data transmission equipment in the high-altitude sliding construction area of ​​the steel transition layer for decorative ceiling, and establish communication connections between the various devices; Step 2: Simultaneously collect displacement, stress, temperature, slipper positioning, and steel column status data during the sliding process of the steel transition layer for decorative ceiling using multi-source sensors, and transmit the data to the data processing terminal in real time via data transmission equipment; Step 3: The data processing unit performs fusion processing on the received multi-source data to establish the correlation between the monitoring data and the slippage status of the steel transition layer used in the decorative ceiling; Step 4: Based on the fusion processing results, analyze whether the current slippage state of the steel transition layer for decorative ceilings meets the preset requirements and determine whether there are any abnormalities; Step 5: Based on the status analysis results, output the corresponding adjustment command to the sliding control device, generate and display the warning information, and return to Step 2.

[0012] In actual execution, step 3, before the fusion process, also includes data preprocessing: correcting stress monitoring data based on temperature data, removing outliers from each sensor's data, and ensuring data validity before performing the fusion process.

[0013] In step 4, the state analysis also includes the prestress state data of the steel transfer layer for decorative ceiling, and combined with displacement, stress and prestress data, to comprehensively judge the overall stress and deformation state of the steel transfer layer for decorative ceiling during the sliding process.

[0014] In step 5, if the status analysis result is a severe anomaly, an emergency stop command is output, an on-site audible and visual alarm is triggered, and the monitoring data and time when the anomaly occurs are recorded and stored in the data recording unit.

[0015] In a third aspect of the invention, an electronic terminal device is also proposed, comprising a memory and a processor. The memory stores computer program instructions, and when the processor executes the computer program instructions, the high-altitude sliding dynamic monitoring method for steel conversion layers in decorative ceilings based on multi-sensor fusion described in the second aspect is realized.

[0016] Compared with the prior art, the present invention has at least the following advantages: 1. Comprehensive monitoring dimensions and accurate data: Data such as displacement, stress, temperature, and prestress are collected by multi-source sensors. The data is preprocessed with temperature correction and outlier removal before fusion, avoiding the one-sidedness of single parameters and environmental interference. It accurately captures the full-dimensional state of slippage of the steel transition layer for decorative ceilings, providing a reliable data foundation for subsequent analysis.

[0017] 2. More accurate data association and analysis: The data fusion processing module associates the steel conversion layer BIM model of the decorative ceiling with the data, realizing the mapping of monitoring data with the spatial position of components. The state analysis combines multiple parameters such as displacement, stress, and prestress, rather than independent analysis, which can more accurately judge the overall stress and deformation state of the structure and improve the reliability of the state assessment.

[0018] 3. High safety of hierarchical closed-loop control: The closed-loop control early warning module is equipped with multi-level response units, which can fine-tune for minor abnormalities, decelerate for moderate abnormalities, and shut down and sound and light alarms for severe abnormalities. It also records data and time when abnormalities occur, which can match countermeasures in a timely manner, avoid the risk from escalating, and ensure the safety of sliding construction.

[0019] 4. Strong adaptability of transmission methods: The data transmission module contains wired and wireless units. Fixed sensors use wired connections to ensure stability, while mobile / high-altitude sensors use wireless connections to adapt to changes in the construction space, ensuring real-time and uninterrupted data transmission during the sliding process, without being limited by the construction environment.

[0020] 5. Good ease of use and traceability: The visualization module intuitively displays monitoring data and analysis results, making it convenient for personnel to view; key information is recorded when anomalies occur, supporting subsequent tracing; the method is executed cyclically for monitoring, enabling continuous dynamic control, and balancing ease of operation with traceability throughout the entire construction process.

[0021] Further advantages of the present invention will be further detailed in the Specific Embodiments section in conjunction with the accompanying drawings. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the functional modules or sub-equipment that constitute the high-altitude sliding dynamic monitoring system for the steel conversion layer of decorative ceiling based on multi-sensor fusion according to the present invention; Figure 2 yes Figure 1A schematic diagram of data control interaction between some functional units of the high-altitude sliding motion monitoring system for steel conversion layers of decorative ceilings based on multi-sensor fusion; Figure 3 This is a schematic diagram of the steps of a high-altitude sliding dynamic monitoring method for a steel conversion layer for decorative ceilings based on multi-sensor fusion, according to an embodiment of the present invention. Figure 4 It is to achieve Figure 3 A schematic diagram of the software / hardware architecture of the high-altitude sliding dynamic monitoring method for steel conversion layers used in decorative ceilings based on multi-sensor fusion. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments identical to those described in this application. Rather, they are merely examples of apparatuses and methods identical to some aspects of this application as detailed in the appended claims.

[0025] In specific embodiments of this application, if user-related data is involved, user permission or consent must be obtained when the embodiments of this application are applied to specific products or technologies, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0026] Figure 1 This is a schematic diagram of the functional modules or sub-devices that constitute the high-altitude sliding dynamic monitoring system for the steel conversion layer of decorative ceiling based on multi-sensor fusion according to the present invention.

[0027] Overall, Figure 1 The monitoring system includes a multi-source sensor module, a data transmission module, a data fusion processing module, a status monitoring and analysis module, a closed-loop control and early warning module, and a visualization and interaction module; more specifically, it also includes a multi-level response unit, a sliding drive device, a prestressing control device, and a steel column unloading device, etc. exist Figure 1 Based on this, see further Figure 2 , Figure 2 yes Figure 1 This diagram illustrates the data control interaction between some functional units of the high-altitude sliding dynamic monitoring system for steel conversion layers in decorative ceilings based on multi-sensor fusion.

[0028] The data transmission module receives data output from the multi-source sensor module and transmits the data to the data fusion processing module in real time. The data fusion processing module constructs the correlation between various monitoring data based on the received data to obtain the fusion processing result; The status monitoring and analysis module analyzes whether the slippage state of the steel transition layer for decorative ceilings meets preset conditions based on the fusion processing results. The closed-loop control early warning module outputs action adjustment commands to the sliding control device based on the status monitoring and analysis results, and generates early warning information at the same time; The visualization interaction module receives and displays monitoring data, status analysis results, and early warning information; The action adjustment instructions include: for the sliding drive equipment, adjusting the operating parameters to ensure sliding synchronization; for the prestressing control equipment, adjusting the tensioning-related parameters; and for the unloading equipment, controlling the unloading action rhythm.

[0029] The closed-loop control early warning module includes a multi-level response unit, which outputs different levels of adjustment commands based on the degree of abnormality of the status monitoring and analysis results: a parameter fine-tuning command is output for mild abnormalities, a slip deceleration command is output for moderate abnormalities, and an emergency stop command is output for severe abnormalities.

[0030] The multi-source sensor module also includes a prestress monitoring sensor for collecting prestress state data of the steel conversion layer for decorative ceilings. The prestress monitoring sensor is connected to the data transmission module and synchronously outputs prestress tension and loss-related data to the data fusion processing module.

[0031] The data transmission module includes a wired transmission unit and a wireless transmission unit; the wired transmission unit is used to connect to fixedly deployed sensors to achieve stable data transmission; the wireless transmission unit is used to connect to mobile or high-altitude deployed sensors to adapt to the spatial environment of sliding construction of steel conversion layers for decorative ceilings.

[0032] The data fusion processing module also associates with the BIM model of the steel conversion layer for decorative ceilings, maps the spatial location of the fused monitoring data with the components in the BIM model, forms a monitoring dataset with spatial identification, and transmits it to the status monitoring and analysis module.

[0033] Next, to better understand the system implementation, we will combine the specific functions of each functional unit module (sub-device) and the interaction relationship of data input / output control flow to introduce the specific implementation method, working principle and corresponding improvement technology effects of the above system implementation.

[0034] I. Multi-source sensor module.

[0035] In the technical solution of this application, this module mainly solves the technical problem of "one-sided monitoring dimensions and missing key parameters".

[0036] Multi-source sensor modules supplement key monitoring parameters through differentiated deployment, avoiding misjudgments of status due to missed monitoring items in existing technologies. Specifically, this includes: 1. Core parameter acquisition sensors: displacement sensor (monitors the three-dimensional position change of the steel transition layer for decorative ceiling), stress sensor (captures the force on key members), temperature sensor (records the ambient temperature to correct stress data), slipper positioning sensor (tracks the real-time position of the slipper), and steel column (I-beam) status sensor (monitors the deformation and bearing capacity of the steel column (I-beam), covering the basic state of the structure during the sliding process: displacement-force-support. 2. New prestress monitoring sensor: To address the deficiency of existing technologies that do not include prestress data, this sensor is linked with the prestressing tensioning equipment for the steel conversion layer of decorative ceilings to synchronously collect prestressing tension values ​​and loss data (such as real-time force values ​​during tensioning and losses during long-term slippage), and uploads them in real time through a data transmission module to supplement key parameters for overall structural stress analysis and avoid hidden risks caused by prestress anomalies.

[0037] All sensors are deployed according to the principle of "full coverage of the sliding path and densification of key parts". For example, the sliding shoe positioning sensor moves synchronously with the sliding shoe, and the prestressing sensor is integrated near the tensioning end anchor to ensure that data acquisition is synchronized with the structure's dynamics.

[0038] II. Data transmission module.

[0039] In the technical solution of this application, this module mainly solves the technical problem of "complex construction space and unstable data transmission".

[0040] The data transmission module is designed for "high-altitude + mobile" construction scenarios involving the high-altitude sliding of steel transition layers for decorative ceilings. It adopts a "wired + wireless" dual-unit collaborative design, overcoming the limitations of existing single transmission methods. 1. Wired transmission unit: Connects to fixedly deployed sensors (such as steel column (I-beam) status sensors and ground reference displacement sensors), and achieves stable data transmission through shielded cables to avoid data packet loss caused by high-altitude electromagnetic interference and ensure the continuity of data at fixed monitoring points; 2. Wireless transmission unit: It adopts an anti-interference 4G / 5G DTU module to connect to sensors deployed in mobile or high-altitude environments (such as the sliding shoe positioning sensor that moves with the sliding unit and the stress sensor on the truss). It adapts to the dynamic changes in sensor position during the sliding process and supports encrypted data transmission to prevent signal interference from multiple devices in the construction environment and ensure that the data from the mobile monitoring point is not interrupted.

[0041] Both units have a data storage function. If the transmission is temporarily interrupted, the data can be cached and retransmitted after the transmission is restored to avoid data loss.

[0042] III. Data Fusion Processing Module.

[0043] In the technical solution of this application, this module mainly solves the technical problem of "isolated and unrelated data, making it difficult to locate problems".

[0044] The data fusion processing module overcomes the limitations of data isolation in existing technologies by using "data association + spatial mapping," thereby enhancing data value. 1. Construct a multi-parameter correlation model: Based on the mechanical properties of the steel transfer layer for decorative ceilings, establish a coupling relationship model between displacement, stress, temperature, and prestress. For example, correct stress monitoring values ​​through temperature data (eliminate the interference of temperature deformation on mechanical parameters), and correlate displacement changes through prestress data (determine whether the displacement anomaly is caused by prestress loss), avoiding the one-sided interpretation of a single data dimension. Taking the correction of stress monitoring values ​​using temperature data (eliminating the interference of temperature deformation on mechanical parameters) as an example, the essence of correcting stress monitoring values ​​using temperature data is to separate "temperature stress" from "actual working stress." Steel, as a material that expands and contracts with temperature, will deform due to temperature changes. When the steel transition layer used in decorative ceilings is constrained by steel columns (I-beams), sliding shoes, etc., and cannot deform freely, additional "temperature stress" will be generated. This results in the "measured stress" collected by the sensor being the sum of "temperature stress + actual working stress." The core of the correction is to calculate the temperature stress using the thermophysical parameters of the steel and remove it from the measured value to obtain the "corrected stress" that reflects the true stress state of the structure.

[0045] 2. BIM Model Spatial Mapping: The fused monitoring data is spatially mapped at the component level to the BIM model of the steel transfer layer for the decorative ceiling. For example, the stress data and corresponding displacement data of a truss are bound to the specific member number and coordinates of that truss in the BIM model, forming a spatially labeled dataset of "data + location". During subsequent state analysis, the physical components corresponding to abnormal data can be directly located in the BIM model, solving the pain point of existing technologies that "only know the data is abnormal, but do not know the location".

[0046] IV. Status Monitoring and Analysis Module. In the technical solution of this application, this module primarily addresses the technical problem of "one-sided status judgment and inaccurate hazard identification." The condition monitoring and analysis module replaces the single-parameter judgment of existing technologies with "multi-parameter comprehensive analysis," improving the accuracy of condition assessment. 1. Multi-dimensional data integration and analysis: Based on the "displacement-stress-prestress-temperature" related dataset output by the data fusion processing module, the structural status is comprehensively judged. For example, when the displacement data is at a critical value, it is combined with the prestress loss data for judgment: if the prestress loss is less than 5%, it may be caused by temporary construction loads; if the prestress loss is greater than 8%, it should be judged as an abnormal displacement caused by insufficient prestress, so as to avoid misjudgment based solely on displacement data. 2. Dynamic adaptation of preset conditions: Different preset conditions are set for different stages of sliding (assembly, sliding, unloading). For example, the sliding stage focuses on displacement synchronization and stress peak, while the unloading stage focuses on the stress on the steel column (I-beam) and changes in structural posture, avoiding misjudgment or omission caused by the use of uniform thresholds in existing technologies.

[0047] V. Closed-loop control and early warning module. In the technical solution of this application, this module mainly solves the technical problem of "ungraded control and untimely emergency response".

[0048] The closed-loop control and early warning module achieves a "monitoring-control" closed loop, which is lacking in existing technologies, through "tiered response + precise control design," balancing safety and construction efficiency. 1. Precise triggering of multi-level response units: Minor anomalies (such as slip synchronization deviation ≤2mm, prestress loss ≤3%): output parameter fine-tuning instructions, such as adjusting the cylinder extension speed of the slip drive device to correct the synchronization deviation; or adjusting the tension increment of the prestress control device to compensate for the small prestress loss. Moderate abnormality (such as slip synchronization deviation of 2-5mm, stress reaching 90% of design value): Output slip deceleration command to reduce slip speed to reduce deformation accumulation, and prompt on-site personnel to check; Severe anomalies (such as displacement > 10mm, stress exceeding design value, prestress loss > 8%): Output emergency stop command, cut off power to sliding drive, prestress control, and steel column (I-beam) unloading equipment, and trigger on-site audible and visual alarms to prompt personnel to evacuate; 2. Targeted Equipment Control: Different action adjustment commands are output for different sliding control equipment—focusing on "synchronization" for sliding drive equipment (such as adjusting the pressure of the cylinders on both sides), focusing on "tensioning loss compensation" for prestressed control equipment (such as adjusting the tensioning pressure and holding time), and focusing on "unloading rhythm" for steel column (I-beam) unloading equipment (such as slowing down the cylinder return speed), avoiding the "one-size-fits-all" control method of existing technologies and achieving precise risk control.

[0049] VI. Visual Interaction Module. In the technical solution of this application, this module mainly addresses the technical problem of "unintuitive information display and low decision-making efficiency".

[0050] The visual interaction module optimizes information delivery through "intuitive presentation and hierarchical display," adapting to different user needs: For construction management personnel: Display spatial monitoring data with BIM model (such as abnormal components highlighted in red), hierarchical early warning information (different colors indicate early warning levels), and control command execution status to facilitate quick problem location and determination of handling priorities; For on-site operators: Simplify the display of core early warning information (such as "severe anomaly - stop immediately") and equipment status, avoid interference from complex data, ensure rapid transmission of emergency instructions, and solve the problem of information overload or lack of focus in existing technologies.

[0051] Based on the above system implementation, Figures 3-4 Further, method embodiments corresponding to the system embodiments are shown.

[0052] First see Figure 3 , Figure 3 This is a schematic diagram illustrating the steps of a high-altitude sliding dynamic monitoring method for a steel conversion layer for decorative ceilings based on multi-sensor fusion, according to an embodiment of the present invention.

[0053] exist Figure 3 The method includes steps 1 to 5, and the specific implementation of each step is as follows: Step 1: Deploy multi-source sensors, sliding control equipment, and data transmission equipment in the high-altitude sliding construction area of ​​the steel transition layer for decorative ceiling, and establish communication connections between the various devices; Step 2: Simultaneously collect displacement, stress, temperature, slipper positioning, and steel column (I-beam) status data during the sliding process of the steel transition layer for decorative ceiling using multi-source sensors, and transmit the data to the data processing terminal in real time via data transmission equipment; Step 3: The data processing unit performs fusion processing on the received multi-source data to establish the correlation between the monitoring data and the slippage status of the steel transition layer used in the decorative ceiling; Step 4: Based on the fusion processing results, analyze whether the current slippage state of the steel transition layer for decorative ceilings meets the preset requirements and determine whether there are any abnormalities; Step 5: Based on the state analysis results, output the corresponding adjustment command to the sliding control device, generate and display the early warning information, and return to Step 2. In actual execution, Step 3, before fusion processing, also includes data preprocessing: correcting stress monitoring data based on temperature data, removing outliers from each sensor's data, and ensuring data validity before performing fusion processing.

[0054] In step 4, the state analysis also includes the prestress state data of the steel transfer layer for decorative ceiling, and combined with displacement, stress and prestress data, to comprehensively judge the overall stress and deformation state of the steel transfer layer for decorative ceiling during the sliding process.

[0055] In step 5, if the status analysis result is a severe anomaly, an emergency stop command is output, an on-site audible and visual alarm is triggered, and the monitoring data and time when the anomaly occurs are recorded and stored in the data recording unit.

[0056] Next, we will describe the key deployments for implementing the above method in more specific terms: Multi-source sensor deployment Following the principle of "densification of key areas and full coverage of the sliding path," the steel transition layer for decorative ceilings is deployed in a differentiated manner based on the characteristics of the sliding stage. Displacement sensors: Laser displacement sensors are used, with one sensor every 10m along both sides of the sliding track (to monitor track flatness), and two sensors each at the mid-span of the truss and at the support (to monitor vertical / lateral displacement). The accuracy is set to ±0.1mm, and the sampling frequency is 5Hz. Stress sensors: Strain gauge stress sensors are used and are attached to the surface of key load-bearing components such as the lower chord and web members of the truss (no less than 5 per truss), avoiding welds and bolt holes. Temperature calibration is performed after attachment (reference temperature 20℃). Temperature sensor: A thermocouple sensor is used, which is placed close to the stress sensor (spacing ≤10cm) to synchronously collect the surface temperature of the component. The sampling frequency is the same as that of the stress sensor (5Hz). Slipper positioning sensor: It combines an IMU and GPS or a miniature total station, and is integrated on the top of each slipper to track the slipper's position in real time; Steel column (I-beam) status sensor: A pressure sensor is used and installed on the top of the steel column (I-beam) support cylinder to monitor the bearing capacity of the steel column (I-beam); Prestress monitoring sensor: An anchor cable force sensor is used, which is connected in series between the anchor and the tie rod at the prestressing tensioning end to collect tension value and loss data in real time.

[0057] Deployment of Slip Control Equipment and Data Transmission Equipment Sliding control equipment: Sliding drive equipment (hydraulic cylinders) are evenly distributed along the track (1 set every 20m), prestressing control equipment (tensioning jacks) are set corresponding to the prestressing tie rods, and steel column (I-beam) unloading equipment (hydraulic unloading valve) is integrated into the steel column (I-beam) support cylinder; Data transmission equipment: The wired transmission unit (industrial Ethernet switch) is deployed in the ground control box and connects to fixed sensors (such as steel column (I-beam) pressure sensors); the wireless transmission unit (4G / 5G DTU) is deployed on the top of the sliding unit and connects to moving sensors (such as sliding shoe positioning sensors), with a transmission rate of ≥1Mbps to ensure no data delay.

[0058] Communication connection establishment A dual-link design with "wired as the primary and wireless as the secondary" is adopted: fixed devices are connected via shielded network cables (to resist electromagnetic interference), and mobile devices are connected to the ground control terminal via encrypted wireless signals; after power-on, the devices are debugged: the communication stability between the sensors and the transmission devices is tested one by one (sending test data packets with a packet loss rate of <0.1%), and the control devices are verified to receive commands (outputting simulated fine-tuning commands with a device response delay of ≤0.5s). Only after the debugging is successful can the next step be carried out.

[0059] By using the clock synchronization module at the ground control terminal, the sampling clocks of all sensors and transmission devices are calibrated (error ≤ 1ms) to ensure that data such as displacement, stress, and temperature are collected at the same timestamp (e.g., once every 200ms, i.e., 5Hz frequency). It adopts a dual mode of "timed trigger + event trigger": timed acquisition during normal sliding; when the shoe synchronization deviation is >2mm or the stress reaches the mild threshold, high-frequency acquisition (frequency increased to 10Hz) is triggered to capture abnormal details.

[0060] The standardized format of "timestamp-sensor ID-data value-checksum" (e.g., "2025-XX-XX15:30:00.200|ST-01|280MPa|0x12") is adopted. The checksum is used to determine whether the data transmission is complete. The transmission device has a built-in data buffer (capacity ≥1GB). If the wireless signal is interrupted (e.g., due to obstruction), the buffered data will be retransmitted after the signal is restored. The wired transmission unit is equipped with redundant links. When a single link fails, it will automatically switch to the backup link to avoid data loss.

[0061] The next step is the multi-source data fusion processing, which mainly includes: Data preprocessing: Ensure the validity of the original data, mainly including temperature-corrected stress data (such as the aforementioned correction according to the formula of steel thermophysical properties to eliminate temperature interference), outlier removal, data completion, etc.

[0062] Based on this, establish relationships.

[0063] Regarding the prestress-displacement relationship, in a prestressed tubular truss, prestress loss will lead to truss deflection (increased displacement). The correlation model is as follows: ; In the formula: Additional displacement (mm) caused by prestress loss. Where is the prestress loss value (kN), L is the truss span (mm), E is the elastic modulus (206 GPa), and I is the moment of inertia of the truss section (mm). 4 ).

[0064] In one example, if an increase in displacement is detected =3mm, calculated according to the formula It should be approximately 50kN. If the prestressing sensor's measured loss... =80kN, it can be determined that the abnormal displacement is mainly due to insufficient prestress, and prestress should be added first.

[0065] Regarding the displacement-stress coupling relationship, in one scenario, based on beam bending theory, there is a linear correlation between the mid-span displacement of the truss and the stress in the lower chord: ; Mid-span displacement ; therefore,

[0066] In the formula: y is the stress of the lower chord (MPa), E is the elastic modulus (206GPa), y is the distance from the centroid of the lower chord section to the edge (mm), d is the mid-span displacement (mm), and L is the truss span (mm).

[0067] In one example, if the displacement data shows d=8mm, calculate according to the formula. The pressure should be approximately 220 MPa. If the measured and corrected stress is 250 MPa, it can be preliminarily determined that the stress is abnormal (possibly caused by local load concentration), providing a basis for subsequent analysis.

[0068] Furthermore, slip shoe synchronization deviation can lead to uneven stress on the truss. The related logic is: when the slip shoes on both sides are synchronized... When the stress is greater than 2mm, the stress in the web members of the truss on one side will increase. = (k is a proportionality coefficient, determined by the truss stiffness, and the actual measured calibration is 5MPa / mm).

[0069] In one embodiment, if synchronization deviation =3mm$, then the stress on one side of the web member should increase by 15MPa. If the stress sensor actually increases by 20MPa, it is necessary to determine the superposition of the slipper synchronization deviation and local stress concentration, and the synchronization should be adjusted and the condition of the component should be checked at the same time.

[0070] Based on the above-mentioned correlations, a weighted fusion algorithm is used to calculate the comprehensive state value. .

[0071] For example, the weighting during the slip phase. , Normalized data at a certain moment is .

[0072] but =0.4×0.8+0.3×0.7+0.3×0.9=0.8, providing a quantitative basis for the state analysis in step 4.

[0073] Next, we move on to step 4. The core of this step is to accurately determine the structural status based on fused data through "single parameter threshold judgment - multi-parameter comprehensive scoring - anomaly tracing".

[0074] For example, based on the design specifications and construction experience of steel transition layers for decorative ceilings, a multi-parameter three-level threshold is set (taking a 200m span truss of Q355 steel as an example), and the merged individual parameters are compared one by one: If a parameter exceeds the safety threshold, it is marked as "item to be concerned"; if it exceeds the mild / moderate / severe threshold, the corresponding abnormality level is directly marked (e.g., stress = 295MPa, marked as "moderate abnormality").

[0075] The fuzzy comprehensive evaluation algorithm is used to calculate the overall state score. The scoring weights are then adjusted based on the correlation established in step 3. If there is an abnormal correlation between displacement and prestress (e.g., an increase in displacement caused by prestress loss), then the weight of the prestress parameter should be increased. (Adjusted from 0.3 to 0.4). Based on the correlation in step 3, the cause of "moderate / severe abnormality" or "simultaneous abnormality of multiple parameters" is located: 1. Scenario 1: Displacement + Stress Dual Anomalies If the deviation between the theoretical stress calculated based on displacement and the measured stress is less than 10 MPa, it is judged as "load exceeding expectations" (such as the superposition of temporary construction loads); if the deviation is greater than 10 MPa, combined with temperature data, if the temperature fluctuation is greater than 5℃, it is judged as "temperature correction not timely"; if the temperature is stable, it is judged as "local damage to the component".

[0076] 2. Scenario 2: Displacement + Prestressing Dual Anomalies If the deviation between the theoretical displacement calculated based on prestress loss and the measured displacement is <2mm, it is determined to be "prestress deficiency is the main factor". If the deviation is greater than 2mm, it is judged as "insufficient prestress + superimposed load". Prestress should be added first, and then the load should be checked.

[0077] Finally, execute step 5: Adjust command output and early warning – to achieve “tiered risk control + closed-loop feedback”.

[0078] Based on the judgment results of step 4, output differentiated adjustment instructions and early warning information.

[0079] For example, for mild abnormalities (60≤ <80 points) Output parameter fine-tuning instructions. Output small adjustment instructions for different control devices to avoid excessive intervention in construction; for moderate anomalies (40≤... <60 points): Slip-off deceleration + local intervention command; for severe abnormalities ( <40 points): Emergency shutdown + emergency instructions.

[0080] After the command is output, return to step 2 to collect data again and verify the adjustment effect: If a slight abnormality is adjusted, the overall score will be... ≥80 points: "Adjustment effective", normal slippage restored; if moderate abnormality is observed after adjustment, score... <60 points: Upgrade instructions (e.g., change from deceleration to pause), re-analyze the cause; after handling severe anomalies, the structural status must be verified through "no-load slip test" and construction can only resume after confirming that there are no abnormalities.

[0081] It is understood that the specific parameters mentioned in the above embodiments of this application (such as time period setting, threshold time setting, number of terminals, etc.) are merely illustrative and do not constitute a specific limitation on the scope of protection of the technical solution of this invention.

[0082] Figure 4 It is to achieve Figure 3 A schematic diagram of the software / hardware architecture of the high-altitude sliding dynamic monitoring method for steel conversion layers used in decorative ceilings based on multi-sensor fusion. Figure 4 The software / hardware architecture adopts a "four-layer layered decoupling + cross-layer collaborative linkage" design, which divides the system into a device deployment layer, a data acquisition and transmission layer, a data processing layer, and a control and early warning closed-loop layer according to functional logic. Each layer independently undertakes core tasks and also deeply collaborates with data and command flows, which has significant advantages.

[0083] I. Hierarchical Functions and Collaboration Principles Equipment Deployment Layer: As the "physical foundation layer", it completes the spatial layout of multi-source sensors (displacement, stress, temperature, etc.) and sliding control equipment (drive, tension, unloading devices), and establishes a communication link between "sensors-transmission units-control equipment" to provide hardware carriers and connection channels for the system.

[0084] Data acquisition and transmission layer: As the "data entry layer", it synchronously acquires multi-dimensional data of the sliding process at a preset frequency, and reliably transmits the data to the processing end through a "wired + wireless" hybrid transmission network; it has a built-in temporary storage and verification mechanism to ensure that the original data is "not lost or distorted".

[0085] Data processing layer: As the "core computing layer", it first preprocesses the collected data (outlier removal, temperature correction, and accuracy calibration), then constructs a "monitoring data-slip state" correlation model through fusion algorithms, and finally classifies and stores the raw data, fusion results and model parameters to provide a "trustworthy feature library" for state analysis.

[0086] Control and early warning closed-loop layer: As the "execution feedback layer", it analyzes the slip state and determines the abnormality level based on the results of the processing layer, and outputs "fine-tuning / deceleration / stop" graded instructions to the control equipment; it generates a visual early warning at the same time, and feeds the control results back to the acquisition end to drive the next round of monitoring, forming a "acquisition-processing-control-feedback" closed loop.

[0087] Figure 4 The core advantages of using a layered architecture are mainly reflected in: 1. Modular decoupling reduces system complexity: The functional boundaries of each layer are clear (hardware deployment, data transmission, algorithm operation, and control execution each perform their own duties), and the technical iteration of one layer (such as replacing sensors or upgrading fusion algorithms) will not interfere with other layers, greatly improving the maintainability and scalability of the system.

[0088] 2. Clear data flow ensures closed-loop reliability: Data is collected from the "device layer", transferred to the "transmission layer", processed at the "processing layer", and finally executed and fed back at the "control layer", forming a unidirectional driving and bidirectional feedback logic, ensuring that control commands are based on reliable data and that feedback can accurately correct strategies.

[0089] 3. Adapt to engineering scenarios and respond to changing needs: Engineering sites have different requirements for "hardware flexibility", "real-time transmission", "algorithm iteration" and "timely control". The layered architecture can be optimized independently for each layer (such as adjusting the sensor density of the equipment layer according to the span, and iterating the model according to the specifications of the processing layer), so that the system can not only match complex construction scenarios, but also quickly respond to changes in technology and needs.

[0090] In the above description of the embodiments, it is understood that the block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0091] Therefore, although not shown in the accompanying drawings, more embodiments also include a computer-readable storage medium for storing computer instructions that, when executed on an electronic device, enable the implementation of a multi-sensor fusion-based high-altitude sliding dynamic monitoring method for steel conversion layers in decorative ceilings according to an embodiment of the present invention.

[0092] Similarly, although not shown in the accompanying drawings, more embodiments may also include an electronic device comprising a processor and a memory, the memory for storing instructions, and the processor for calling the instructions in the memory to cause the electronic device to execute a high-altitude sliding dynamic monitoring method for steel conversion layers for decorative ceilings based on multi-sensor fusion, according to an embodiment of the present invention.

[0093] Similarly, although not shown in the accompanying drawings, more embodiments should also include a computer program product, which includes a computer program that, when executed, implements an embodiment of the present invention of a high-altitude sliding dynamic monitoring method for steel conversion layers of decorative ceilings based on multi-sensor fusion.

[0094] Through actual simulation testing and practical engineering applications, the technical solution of this invention has the following advantages and improvements compared to existing technologies: First, this invention achieves deep fusion and precise correlation of multi-source monitoring data, overcoming the challenges of isolated multi-source data and significant environmental interference in traditional monitoring. By deploying multi-source sensors for displacement, stress, and temperature at key locations in the steel transition layer of decorative ceilings, this invention simultaneously collects data across all dimensions. It employs a temperature correction model based on the thermophysical parameters of steel to eliminate temperature interference with mechanical parameters, and combines this with the "3σ principle" to remove outliers, ensuring the validity of the original data. Based on this, multi-parameter coupled correlation models such as displacement-stress and prestress-displacement are constructed to uncover the intrinsic mechanical relationships between data, ultimately forming a fused "time-space-state" dataset. This improvement upgrades monitoring data from "fragmented and isolated" to "reliable correlation," providing a precise foundation for subsequent state analysis and avoiding misjudgments of state due to single-source data or environmental interference.

[0095] Secondly, this invention achieves a comprehensive and accurate assessment of the slippage state of steel transition layers used in decorative ceilings, overcoming the shortcomings of traditional methods such as one-sided state judgment and difficulty in tracing the source of anomalies. This invention establishes a multi-parameter hierarchical threshold system (including safety, light / medium / severe anomaly thresholds) covering key parameters such as displacement, stress, and prestress, and combines this with a fuzzy comprehensive scoring algorithm to quantify the overall state. Simultaneously, based on multi-parameter coupling relationships (such as the beam bending theory correlation between displacement and stress, and the correlation between slipper synchronization and uneven stress distribution), it performs source analysis on anomalies (such as distinguishing causes like temperature interference, insufficient prestress, and slipper asynchrony). This three-layer analysis logic of "single-parameter threshold screening + multi-parameter comprehensive scoring + anomaly source location" achieves a leap from "single-parameter judgment" to "multi-dimensional accurate assessment," enabling a comprehensive grasp of the overall structural safety state and rapid location of the root cause of anomalies, providing targeted direction for subsequent handling.

[0096] Furthermore, a closed-loop system of "monitoring-analysis-control-feedback" is constructed to address the problems of delayed response and lack of tiered handling and feedback in traditional control. Based on the state analysis results, this invention outputs multi-level control commands such as "fine-tuning (e.g., PID adjustment of the slipper shoe synchronization), deceleration, and emergency stop," matching mild, moderate, and severe anomaly levels. Simultaneously, standardized early warning information containing anomaly level, parameter details, and handling suggestions is generated and pushed to different terminals. More importantly, after the control commands are executed, effect data is collected in real time through sensors and fed back to the data processing layer for re-analysis and dynamic strategy adjustment. This closed-loop mechanism transforms the system from "passive monitoring" to "proactive risk control," ensuring both the timeliness and accuracy of anomaly response (e.g., emergency stop within 0.5 seconds for severe anomalies) and continuous optimization of control effects through feedback, significantly improving the safety and controllability of slipway construction.

[0097] Finally, a layered and decoupled hardware / software architecture is adopted to address the problems of high complexity, poor scalability, and poor adaptability in traditional systems. This invention divides the system into a "device deployment layer - data acquisition and transmission layer - data processing layer - control and early warning closed-loop layer," with clear functional boundaries for each layer: the device layer is responsible for hardware deployment and communication establishment; the transmission layer ensures real-time and reliable data flow; the processing layer focuses on algorithm calculations and data processing; and the control layer implements execution and feedback. This layered design achieves modular decoupling (technological iterations in one layer do not interfere with other layers) and, through cross-layer data and command flow collaboration, allows the system to flexibly adapt to sliding scenarios of steel transition layers for decorative ceilings of different spans and types (such as large-span trusses and tubular trusses), while reducing the difficulty of system maintenance and upgrades, providing stable and flexible architectural support for the engineering implementation of the technology.

[0098] Nevertheless, it is particularly important to note that although the present invention provides multiple embodiments, each embodiment can constitute an independent technical solution and may contribute to the prior art and solve corresponding technical problems. That is, each embodiment can solve at least one technical problem and have at least one improvement effect, but it is not required that each individual embodiment solve multiple or all technical problems or have all improvement effects.

[0099] Other technologies, principles, algorithms, or models not elaborated in detail in this application can be found in the prior art.

[0100] The foregoing has shown and described the method embodiments and systems of the present invention, but it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-altitude sliding dynamic monitoring system for steel transition layers used in decorative ceilings based on multi-sensor fusion, characterized in that, The monitoring system includes a multi-source sensor module, a data transmission module, a data fusion processing module, a status monitoring and analysis module, a closed-loop control and early warning module, and a visualization and interaction module. The multi-source sensor module is used to collect displacement, stress, temperature, slipper positioning, and steel column status data during the high-altitude sliding process of the steel conversion layer for decorative ceiling. The data transmission module receives data output from the multi-source sensor module and transmits the data to the data fusion processing module in real time. The data fusion processing module constructs the correlation between various monitoring data based on the received data to obtain the fusion processing result; The status monitoring and analysis module analyzes whether the slippage state of the steel transition layer for decorative ceilings meets preset conditions based on the fusion processing results. The closed-loop control early warning module outputs action adjustment commands to the sliding control device based on the status monitoring and analysis results, and generates early warning information at the same time; The visualization interaction module receives and displays monitoring data, status analysis results, and early warning information; The motion adjustment command includes: adjusting the operating parameters of the sliding drive device to ensure sliding synchronization; For the prestressing control equipment, adjust the tensioning-related parameters.

2. The high-altitude sliding dynamic monitoring system for steel transition layers in decorative ceilings based on multi-sensor fusion as described in claim 1, characterized in that, The multi-source sensor module also includes a prestress monitoring sensor for collecting prestress state data of the steel conversion layer for decorative ceilings. The prestress monitoring sensor is connected to the data transmission module and synchronously outputs prestress tension and loss-related data to the data fusion processing module.

3. The high-altitude sliding dynamic monitoring system for steel transition layers in decorative ceilings based on multi-sensor fusion as described in claim 1, characterized in that, The data transmission module includes a wired transmission unit and a wireless transmission unit; the wired transmission unit is used to connect to fixedly deployed sensors to achieve stable data transmission; the wireless transmission unit is used to connect to mobile or high-altitude deployed sensors to adapt to the spatial environment of sliding construction of steel conversion layers for decorative ceilings.

4. A high-altitude sliding dynamic monitoring system for steel transition layers in decorative ceilings based on multi-sensor fusion, as described in claim 1, is characterized in that... The data fusion processing module also associates with the BIM model of the steel conversion layer for decorative ceilings, maps the spatial location of the fused monitoring data with the components in the BIM model, forms a monitoring dataset with spatial identification, and transmits it to the status monitoring and analysis module.

5. A high-altitude sliding dynamic monitoring system for steel transition layers in decorative ceilings based on multi-sensor fusion, as described in claim 1, is characterized in that... The closed-loop control early warning module includes a multi-level response unit, which outputs different levels of adjustment commands based on the degree of abnormality of the status monitoring and analysis results: a parameter fine-tuning command is output for mild abnormalities, a slip deceleration command is output for moderate abnormalities, and an emergency stop command is output for severe abnormalities.

6. A method for high-altitude sliding dynamic monitoring of steel transition layers for decorative ceilings based on multi-sensor fusion, characterized in that, Includes the following steps: Step 1: Deploy multi-source sensors, sliding control equipment, and data transmission equipment in the high-altitude sliding construction area of ​​the steel transition layer for decorative ceiling, and establish communication connections between the various devices; Step 2: Simultaneously collect displacement, stress, temperature, slipper positioning, and steel column status data during the sliding process of the steel transition layer for decorative ceiling using multi-source sensors, and transmit the data to the data processing terminal in real time via data transmission equipment; Step 3: The data processing unit performs fusion processing on the received multi-source data to establish the correlation between the monitoring data and the slippage status of the steel transition layer used in the decorative ceiling; Step 4: Based on the fusion processing results, analyze whether the current slippage state of the steel transition layer for decorative ceilings meets the preset requirements and determine whether there are any abnormalities; Step 5: Based on the status analysis results, output the corresponding adjustment command to the sliding control device, generate and display the warning information, and return to Step 2.

7. A method for high-altitude sliding dynamic monitoring of steel transition layers for decorative ceilings based on multi-sensor fusion, as described in claim 6, is characterized in that... Step 3 includes data preprocessing before fusion processing: correcting stress monitoring data based on temperature data, removing outliers from each sensor's data, and ensuring data validity before fusion processing.

8. A method for high-altitude sliding dynamic monitoring of steel transition layers for decorative ceilings based on multi-sensor fusion, as described in claim 6, is characterized in that... In step 4, the state analysis also includes the prestress state data of the steel transfer layer for decorative ceiling, and combined with displacement, stress and prestress data, to comprehensively judge the overall stress and deformation state of the steel transfer layer for decorative ceiling during the sliding process.

9. A method for high-altitude sliding dynamic monitoring of steel transition layers for decorative ceilings based on multi-sensor fusion, as described in claim 6, is characterized in that... In step 5, if the status analysis result is a severe anomaly, an emergency stop command is output, an on-site audible and visual alarm is triggered, and the monitoring data and time when the anomaly occurs are recorded and stored in the data recording unit.

10. An electronic terminal device, the electronic terminal device comprising a memory and a processor, the memory storing computer program instructions, wherein when the processor executes the computer program instructions, the high-altitude sliding dynamic monitoring method of a steel conversion layer for decorative ceilings based on multi-sensor fusion as described in any one of claims 6-9 is realized.

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