A prefabricated component hoisting equipment monitoring and early warning and process management method and system based on a BIM model and intelligent hardware

Abstract

This invention discloses a method and system for monitoring, early warning, and process management of prefabricated component hoisting equipment based on BIM models and smart hardware, belonging to the fields of intelligent construction of prefabricated buildings, IoT monitoring, and construction safety control technology. The method acquires the design and installation parameters of the prefabricated components to be hoisted, and collects component posture data, hoisting equipment operation data, and construction environment data during the hoisting process. It performs time synchronization, anomaly removal, coordinate transformation, and normalization processing on the multi-source data, calculates component posture deviation, equipment operation deviation, and environmental interference coefficients, and calculates a comprehensive risk assessment value based on fusion weights. Furthermore, it combines preset threshold judgment rules to determine the equipment operation risk and on-site environmental risk during component hoisting operations, and generates risk warning information and auxiliary handling prompts based on equipment operating status, component management information, and environmental conditions. The system includes a component basic information management module, a BIM model data management module, an equipment data acquisition module, an environmental data acquisition module, an edge processing module, a data analysis module, a risk warning module, a communication module, and a management platform module. This invention enables prefabricated component information management, BIM model data management, intelligent hardware access for mechanical equipment, equipment operation parameter monitoring, risk warning, and process recording, forming a closed-loop management system of "data acquisition - parameter display - risk assessment - manual review - process archiving," thereby improving the information management level, equipment status perception capability, and quality traceability capability of prefabricated component hoisting operations.

Description

Technical Field

[0001] This invention relates to the fields of intelligent construction of prefabricated buildings, Internet of Things monitoring, construction safety control and component installation quality management, and in particular to a method and system for monitoring, early warning and process management of prefabricated component hoisting equipment based on BIM model and intelligent hardware. Background Technology

[0002] Prefabricated construction, which involves factory prefabrication and on-site assembly, improves construction efficiency, reduces on-site wet work, and enhances the level of industrialization in engineering. For projects such as prefabricated subway stations, underground structures, bridge structures, and large public buildings, prefabricated components are typically characterized by their large size, heavy weight, high lifting difficulty, complex installation nodes, and high precision requirements. The on-site lifting and installation process of these components directly affects the quality of structural formation, the quality of node connections, and construction safety.

[0003] In the current prefabricated component installation process, component posture adjustment and installation accuracy control mainly rely on total stations, levels, manual observation, and the experience judgment of on-site workers. This method has problems such as reliance on manual measurement, insufficient real-time performance, low installation and adjustment efficiency, lack of correlation analysis between equipment status and component posture, failure to fully incorporate the impact of the construction environment into installation risk assessment, and difficulty in completely tracing installation process data.

[0004] Therefore, it is necessary to propose an information management method and system for prefabricated component hoisting operations that can combine prefabricated component management, BIM model data management, mechanical equipment operation status monitoring, and on-site environmental monitoring, so as to realize component information management, equipment status monitoring, risk warning, manual review, and process quality archiving. Summary of the Invention

[0005] Purpose of the invention

[0006] The purpose of this invention is to provide a monitoring, early warning, and process management method and system for prefabricated component hoisting equipment based on BIM models and smart hardware. This system addresses the problems of existing prefabricated component installation processes, such as reliance on manual measurement, insufficient real-time attitude monitoring, lack of linkage analysis between equipment status and component attitude, difficulty in quantifying the impact of the construction environment, unintuitive risk warnings, lack of correlation between equipment monitoring data and component management data, and difficulty in tracing process data.

[0007] Technical solution

[0008] To achieve the above objectives, the present invention provides a method for monitoring, early warning and process management of prefabricated component hoisting equipment based on multi-source sensor data fusion, comprising the following steps.

[0009] S1: Obtain the basic information and design installation parameters of the prefabricated components to be hoisted.

[0010] Before hoisting, the management platform obtains the basic information of the component to be hoisted based on the component number, QR code, or BIM model component code. This basic information includes the component number, component type, component dimensions, component weight, the project location to which the component belongs, the designed installation position, and the allowable installation deviation. The design installation parameters include the design axis, design elevation, design verticality, design attitude angle, installation sequence, hoisting plan, and allowable installation deviation threshold.

[0011] S2 collects component posture data, hoisting equipment operation data, and construction environment data.

[0012] Inertial measurement units (IMUs) are deployed on hoisting equipment, assembly equipment, lifting tools, temporary auxiliary measuring devices for components, or at detachable installation locations on the surface of components to collect pitch, roll, and azimuth angles during the component hoisting process. The IMUs may include triaxial accelerometers, triaxial gyroscopes, and magnetometers. Load sensors, stroke sensors, speed sensors, stress sensors, and limit sensors are deployed on gantry cranes, assembly trolleys, or other hoisting auxiliary equipment to collect operational data from the hoisting equipment. Environmental sensors are deployed at the construction site to collect data on construction environment conditions such as wind speed and humidity.

[0013] S3, preprocesses the collected data.

[0014] The edge processing terminal receives data collected by various sensors and synchronizes it according to a unified time base. Data with different sampling frequencies is aligned according to a preset time window. The edge processing terminal performs data cleaning and outlier removal on the collected data. Data exceeding the physical range, exceeding a preset mutation threshold, or continuously lost data is marked and corrected using adjacent valid values, the sliding window mean, or model predictions. Simultaneously, the edge processing terminal performs coordinate transformation on the component attitude data, converting the attitude data from the sensor coordinate system to the construction site coordinate system or the component installation coordinate system.

[0015] S4 performs multi-source sensor data fusion calculations.

[0016] To avoid line breakage issues in different Word versions, formulas in this implementation are represented using linear formula blocks. Each line within a formula block is a complete and readable linear expression, facilitating copying, editing, and further conversion into professional formula format by an agent within Word.

[0017] (1) Representation of component attitude angle:

[0018]

[0019] Table 1 Definition of component attitude parameters

[0020] symbol meaning Remark Current moment component attitude angle set Data acquired by inertial measurement unit and obtained through coordinate transformation Current pitch angle / roll angle / azimuth angle Used to describe the real-time attitude of a component Design attitude angle set Determined by component design and installation parameters Design pitch angle / roll angle / azimuth angle As a benchmark for attitude deviation calculation

[0021] (2) Calculation of component attitude deviation:

[0022]

[0023] in, represents the component attitude deviation value; represents the weighting coefficients for pitch angle, roll angle, and azimuth angle, respectively. These weighting coefficients can be preset according to different component types, installation accuracy requirements, and construction stages.

[0024] (3) Representation of the operating status of hoisting equipment:

[0025]

[0026] Table 2 Definition of Equipment Operating Parameters

[0027] symbol meaning Remark Current lifting weight Data collected by the load sensor Current lifting height or stroke Acquired by stroke sensors or equipment control system Current running speed Acquired by speed sensor or equipment control system Current stress state Data collected by stress, cylinder pressure, or force sensors Limit trigger state If not triggered, use 0; if triggered, use 1. Equipment planned status variables or safety baseline status variables Determined by the hoisting plan or equipment safety parameters Planned lifting weight or permissible lifting weight benchmark value Determined by the hoisting plan, component weight, or equipment safety parameters. Planned lifting height, target travel distance, or safety reference height Determined by the hoisting plan, installation location, or equipment safety parameters. Planned operating speed or safe reference speed Determined by the hoisting plan or equipment safety parameters Planned stress state or safety benchmark stress value Determined by equipment parameters, hoisting plan, or safety threshold.

[0028] (4) Calculation of equipment operating deviation:

[0029]

[0030] in, This refers to the equipment operating deviation value; These are the weighting coefficients for lifting weight, lifting height or stroke, operating speed, stress state, and limit state, respectively. , , These are the normalized parameters for the corresponding parameters.

[0031] (5) Calculation of environmental interference coefficient:

[0032]

[0033] in, Environmental interference coefficient; This refers to the current wind speed; The maximum permissible wind speed.

[0034] (6) Calculation of comprehensive risk assessment value:

[0035]

[0036] Where R is the comprehensive risk assessment value; These are the fusion weighting coefficients for component posture, equipment operation, and construction environment, respectively. Preferably, when high component installation accuracy is required, the weighting coefficient is increased. Value; when the operating risk of the hoisting equipment is high, increase Value selection; when the on-site wind speed is high or the environmental changes are significant, increase the value. Values.

[0037] Algorithm flowchart (used to replace large blocks of formulas, ensuring stable Word formatting):

[0038] step Input data Processing logic Output A1 Attitude Deviation Calculation Current attitude angle Design attitude angle Calculate the differences in pitch, roll, and azimuth angles separately, and sum them according to their weights. Component attitude deviation value A2 Equipment Deviation Calculation Lifting weight, stroke, speed, force, limit status Compare the equipment operating parameters with planned or safety benchmark values, normalize them, and then sum them according to their weights. Equipment operating deviation value A3 Environmental Interference Calculation Current wind speed Permissible wind speed Calculate the ratio of the current wind speed to the upper limit of the permissible wind speed. Environmental interference coefficient A4 Comprehensive Risk Calculation According to fusion weight Weighted summation. Comprehensive risk assessment value R A5 Risk Level Revision R; Single-item forced threshold First, classify the system into normal, warning, and danger categories using R; if any mandatory threshold is exceeded, it will be directly corrected to danger. Revised risk level A6 Risk Warning and Assistance Response Prompt Generation Risk level; Equipment status; Component management information; Environmental status Output equipment abnormality prompts, component status prompts, environmental risk prompts, review prompts, or work suspension prompts according to preset rules. Risk warning information and auxiliary handling tips

[0039] S5, determine the risk level and perform mandatory threshold correction.

[0040] The risk level of component hoisting is determined based on the comprehensive risk assessment value R, and then corrected using individual mandatory thresholds. To avoid the comprehensive risk assessment value from having an average effect on individual extreme risk factors, the system directly corrects the risk level to a dangerous state when any key parameter exceeds the mandatory threshold.

[0041] (7) Risk level determination rules:

[0042] <![CDATA[If , it is determined as a normal state; if if , it is determined as a dangerous state.]]>

[0043] (8) Single-item mandatory threshold rule:

[0044] Or the limit state is triggered

[0045] in, The first risk threshold, This is the second risk threshold; These are the maximum permissible deviations for pitch angle, roll angle, and azimuth angle, respectively. The maximum allowable lifting weight; Maximum allowed operating speed; The maximum permissible wind speed.

[0046] S6 generates risk warning information and auxiliary handling prompts.

[0047] The risk warning module generates risk warning information and auxiliary handling prompts based on risk level, equipment operating status, component management information, and environmental conditions. These risk warning information and auxiliary handling prompts are used to alert on-site personnel to abnormal parameters, verify on-site conditions, and take safety measures. They do not directly limit the control actions of specific mechanical equipment, nor do they require automatic linkage with the hoisting equipment control system.

[0048] Risk warning and auxiliary handling prompts rule table:

[0049] Triggering conditions Judgment meaning Output early warning information and auxiliary handling prompts Component status parameters exceed preset threshold Output component status anomaly prompts and manual review prompts; The reverse deviation of the component roll angle exceeds the preset threshold. Outputs a warning of excessive roll angle deviation, the current deviation value, and a manual review prompt; The positive deviation of the component's pitch angle exceeds the preset threshold. Outputs a warning of excessive positive pitch angle deviation, the current deviation value, and a prompt for manual review; The reverse deviation of the component's pitch angle exceeds the preset threshold. Output pitch angle reverse deviation exceeding limit warning, current deviation value, and manual review prompt; The azimuth deviation of the component exceeds the preset threshold. Outputs azimuth deviation exceeding limit warning, current deviation value, and manual review prompt; And the rate of change of attitude angle increases The hoisting equipment's operating speed exceeded a preset threshold and its attitude changed abnormally. Output device operating speed abnormality warning, attitude change abnormality prompt, and manual review prompt; The on-site wind speed exceeded the upper limit of the permitted operation. Output environmental risk warnings, current wind speed values, and operational condition verification prompts; Abnormal lifting weight, force or limit Abnormal equipment operation Output device operation abnormality warning, abnormal parameter prompts, and equipment status verification prompts.

[0050] The aforementioned risk warning information and auxiliary handling prompts are intended to assist on-site personnel in identifying abnormal states and conducting manual verification. They do not directly limit the control actions of specific mechanical equipment, nor do they require the system to automatically link with the hoisting equipment control system.

[0051] S7, provide feedback on the handling results and form a closed-loop record.

[0052] The system sends component installation deviations, comprehensive risk assessment values, risk levels, risk warning information, and auxiliary handling prompts to on-site display terminals, mobile terminals, equipment operation terminals, or management platforms. On-site personnel adjust the component hoisting posture, hoisting height, horizontal position, or hoisting speed according to correction instructions. After adjustment, the system continues to collect component posture data, equipment operation data, and environmental data, re-performs integrated calculations and risk assessments, until the component installation deviation meets the preset allowable deviation threshold. The management platform associates and stores the component number, hoisting time, installation location, equipment operation curve, environmental data, risk warning records, and on-site handling records, forming a component hoisting operation process management archive.

[0053] 3. System Solution

[0054] The component basic information management module is used to manage component number, component type, component size, component weight, design installation location, design axis, design elevation, design attitude angle, and allowable installation deviation.

[0055] The attitude data acquisition module is used to collect pitch angle, roll angle and azimuth angle during the component hoisting process.

[0056] The equipment data acquisition module is used to collect data on the lifting weight, lifting height or stroke, running speed, limit status, and stress status of gantry cranes, assembly trolleys, or other lifting equipment.

[0057] The environmental data acquisition module is used to collect wind speed and humidity data at the hoisting site.

[0058] The edge processing module is used to perform time synchronization, anomaly removal, data cleaning, coordinate transformation, and normalization on the collected data.

[0059] The communication module is used to enable data transmission between sensing devices, edge processing terminals, management platforms, and field display terminals via 4G, 5G, wireless LAN, or wired networks.

[0060] The data fusion and analysis module is used to calculate component attitude deviation, equipment operation deviation, environmental interference coefficient, and comprehensive risk assessment value based on component attitude data, equipment operation data, and environmental data.

[0061] The risk warning module is used to generate risk levels, risk warning information, and auxiliary handling prompts based on equipment operating parameters, component management information, environmental parameters, and preset thresholds.

[0062] The management platform module is used to display information on precast components, BIM model data, mechanical equipment operating status, environmental status, risk level, early warning information and handling records, and to store data on component management and equipment monitoring processes.

[0063] 4. Beneficial effects

[0064] First, by integrating component posture data, hoisting equipment operation data, and construction environment data, this invention achieves continuous and real-time monitoring of the hoisting process of prefabricated components, reducing reliance on manual measurement and experience-based judgment.

[0065] Secondly, this invention not only monitors the posture of components, but also simultaneously collects the lifting weight, stroke, speed, limit and stress status of the hoisting equipment, which can correlate the equipment operating status with the component installation deviation to improve the accuracy of hoisting risk identification.

[0066] Third, this invention calculates a comprehensive risk assessment value by taking the component posture deviation value, the equipment operation deviation value, and the environmental interference coefficient, and combines it with the single-item mandatory threshold judgment rule to avoid the single comprehensive score from masking local extreme risk factors, thereby improving the engineering safety of risk assessment.

[0067] Fourth, this invention can generate risk warning information and auxiliary handling prompts based on equipment operating status, component management information and environmental conditions, forming a management closed loop of "data collection - parameter display - risk judgment - manual review - process recording", thereby improving the information management level of hoisting operations and the ability to identify on-site risks.

[0068] Fifth, this invention can link and store prefabricated component information, BIM model data, equipment operating parameters, environmental data, risk warning records, and on-site handling records to form a component hoisting operation process management archive, providing data support for quality traceability, safety review, and construction management.

[0069] Sixth, this invention is applicable to various prefabricated component hoisting and installation scenarios, such as large prefabricated side walls, roof slabs, columns, and beams, and has strong engineering applicability and promotional value. Attached Figure Description

[0070] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0071] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0072] Figure 3 This is a schematic diagram of the multi-source sensor data fusion and analysis process of the present invention.

[0073] Figure 4 This is a schematic diagram of the risk level assessment and forced threshold correction process of the present invention.

[0074] Figure 5 This is a schematic diagram of the risk warning information and auxiliary handling prompt generation process of the present invention.

[0075] Figure 6 This is a schematic diagram of the data structure for the component hoisting operation process management archive of the present invention. Detailed Implementation Plan

[0076] Example 1: Hoisting and Installation of Prefabricated Side Wall Components

[0077] This embodiment takes the hoisting and installation of prefabricated subway station side wall components as an example. Before hoisting the side wall components, construction personnel enter or retrieve the basic information of the components in the management platform, including component number, component type, component weight, component dimensions, designed installation location, designed axis, designed elevation, and allowable installation deviation. The components are bound to the component information in the platform through QR codes or BIM model component codes.

[0078] Before the lifting operation begins, inertial measurement units (IMUs) are installed at temporary measurement locations on the lifting equipment, assembly auxiliary equipment, or components. The IMUs are used to collect the pitch, roll, and azimuth angles of the sidewall components during the lifting process. Load sensors, stroke sensors, speed sensors, and limit sensors are installed on the gantry crane to collect data on the operating status of the lifting equipment. Wind speed sensors are installed at the construction site to monitor the lifting environment.

[0079] Data collected by each sensor is transmitted to the edge processing terminal via the communication module. The edge processing terminal aligns the attitude data, equipment operation data, and environmental data according to a unified timestamp, and removes and corrects abnormal data. Subsequently, the edge processing terminal converts the attitude data in the sensor coordinate system to the attitude data in the construction site coordinate system.

[0080] The data fusion analysis module calculates the component attitude deviation value based on the side wall component attitude data, calculates the equipment operation deviation value based on the gantry crane's lifting weight, stroke, speed and limit status, calculates the environmental interference coefficient based on wind speed data, and further calculates the comprehensive risk assessment value.

[0081] When the system determines that the relevant status parameters, equipment operating parameters, or environmental parameters of the sidewall components exceed preset thresholds, the on-site display terminal displays the corresponding abnormal parameters, risk level, and auxiliary handling prompts. These prompts are intended to remind on-site personnel to manually verify and take safe handling measures based on the construction plan, equipment status, and on-site conditions; they do not directly limit the specific mechanical equipment control actions.

[0082] After hoisting is completed, the management platform binds the component information, equipment operation curve, environmental data, risk warning records, and on-site handling records of the component with the component number to form a component hoisting operation process management file.

[0083] Example 2: Hoisting and Installation of Prefabricated Roof Slab Components

[0084] This embodiment takes the hoisting and installation of prefabricated roof slab components as an example. During the hoisting process of the roof slab components, the inertial measurement unit collects data on the changes in the attitude angle of the roof slab components, the assembly trolley collects data on the cylinder stroke, force state, and moving speed, and the gantry crane collects data on the lifting weight and stroke.

[0085] The system calculates the current hoisting height deviation based on the design elevation and installation position of the top plate components, combined with the travel data of the hoisting equipment; it calculates the horizontal attitude deviation of the top plate based on the pitch and roll angles collected by the inertial measurement unit; and it judges whether there is a risk of uneven stress on the top plate components based on the force data of the hydraulic cylinders of the assembly trolley.

[0086] When abnormalities occur in the relevant status parameters of the roof slab components and the equipment operating parameters, the system, based on the equipment operating data, determines that there may be risks of uneven loading, uneven stress, or abnormal operation. The system then displays the abnormal parameters, risk level, and auxiliary handling prompts on the on-site display terminal and management platform. After on-site personnel manually verify and handle the situation based on the construction plan and the actual equipment status, the system records the verification and handling results and continues to collect equipment operating data and on-site status data.

[0087] Example 3: Management of the association between component information, BIM model data and equipment monitoring data

[0088] In this embodiment, the management platform pre-enters basic information of prefabricated components and uploads or associates existing BIM model data. Each prefabricated component can be identified by its component number, QR code, or BIM model component code, which can be used to query component type, design location, component size, component weight, installation location, and related quality records.

[0089] After the mechanical equipment is equipped with smart hardware, the management platform receives and displays the equipment's operating status and parameters, and associates and stores the equipment monitoring records with the corresponding project, work area, or component management records. In this embodiment, the BIM model is primarily used for component data management, model viewing, and code association; it is not limited to real-time digital twin mapping, nor is it required that the on-site equipment operating status drive BIM model changes in real time. In the event of subsequent quality or safety management issues, component data, equipment operating parameters, risk warning records, and on-site handling records can be retrieved through component numbers, equipment numbers, or work records.

[0090] Industrial applicability

[0091] This invention is applicable to prefabricated buildings, prefabricated subway stations, prefabricated underground structures, prefabricated bridges, and other large prefabricated component hoisting and installation scenarios. Through this invention, prefabricated component information management, BIM model data management, mechanical equipment operation status monitoring, risk warning, and process recording can be achieved, improving the information management level, equipment status perception capability, and quality traceability capability of prefabricated component hoisting operations, and possessing significant industrial application value.

Claims

1. A method for monitoring, early warning, and process management of prefabricated component hoisting equipment based on multi-source sensor data fusion, characterized in that, Includes the following steps: S1, Obtain the basic information and design installation parameters of the prefabricated component to be hoisted. The basic information includes at least the component number, component type, component weight, component size, and design installation location. The design and installation parameters include at least the design axis, design elevation, design attitude angle, and installation allowable deviation threshold. S2, During the hoisting of prefabricated components, collect component attitude data, hoisting equipment operation data, and construction environment data; wherein, the component attitude data includes at least pitch angle, roll angle, and azimuth angle, the hoisting equipment operation data includes at least lifting weight, hoisting height or stroke, operating speed, limit status, and stress status, and the construction environment data includes at least wind speed; S3, perform time synchronization, data cleaning, outlier removal, coordinate transformation and normalization on the component posture data, hoisting equipment operation data and construction environment data to form a multi-source sensor dataset in the same time sequence; S4. Based on the multi-source sensor dataset, calculate the component attitude deviation value, equipment operation deviation value, and environmental interference coefficient respectively, and calculate the comprehensive risk assessment value based on the component attitude deviation value, equipment operation deviation value, and environmental interference coefficient. S5. Determine the risk level of the prefabricated component hoisting process based on the comprehensive risk assessment value, and modify the risk level by combining the single mandatory threshold judgment results of component posture deviation, hoisting equipment operating parameters and construction environment parameters. S6. Based on the corrected risk level, component attitude deviation direction, equipment operating status and environmental status, generate risk warning information and auxiliary handling prompts. The risk warning information and auxiliary handling prompts include at least attitude deviation prompts, equipment status abnormality prompts, environmental risk prompts, review prompts or work suspension prompts. S7. The risk warning information and auxiliary handling prompts are sent to the on-site display terminal and management platform, so that on-site operators can review and handle them in conjunction with the construction plan, equipment status and on-site conditions, and record the handling process and results.

2. The method according to claim 1, characterized in that, In step S2, the component attitude data is acquired by an inertial measurement unit, which includes one or more of a triaxial accelerometer, a triaxial gyroscope, and a magnetometer.

3. The method according to claim 1, characterized in that, In step S2, the operating data of the hoisting equipment is collected by sensors installed on the gantry crane, assembly trolley, lifting tool or hoisting auxiliary equipment. The sensors include one or more of the following: load sensor, stroke sensor, speed sensor, stress sensor and limit sensor.

4. The method according to claim 1, characterized in that, In step S3, the time synchronization includes: using the timestamp received by the edge processing terminal or the timestamp collected by the sensor as a unified time reference, and aligning data with different sampling frequencies according to a preset time window.

5. The method according to claim 1, characterized in that, In step S3, the outlier removal includes: when the sensor-collected value exceeds the physical range, exceeds the preset mutation threshold, or the continuous loss time exceeds the preset time threshold, the corresponding collected value is marked as abnormal data, and corrected using adjacent valid data, sliding window mean, or model prediction value.

6. The method according to claim 1, characterized in that, In step S4, the component attitude deviation value is calculated based on the difference between the current component attitude angle and the design attitude angle. The component attitude angle includes pitch angle, roll angle and azimuth angle.

7. The method according to claim 1, characterized in that, In step S4, the equipment operation deviation value is calculated based on the difference between the current equipment operation status quantity and the equipment planned status quantity or safety benchmark status quantity. The equipment operation status quantity includes the lifting weight, lifting height or stroke, operating speed, force status and limit trigger status.

8. The method according to claim 1, characterized in that, In step S4, the comprehensive risk assessment value is calculated by weighting the component attitude deviation value, equipment operation deviation value and environmental interference coefficient according to the preset fusion weight.

9. The method according to claim 1, characterized in that, In step S5, the risk level includes at least normal, warning, and danger; when the comprehensive risk assessment value is less than the first risk threshold, it is determined to be normal. When the comprehensive risk assessment value is greater than or equal to the first risk threshold and less than the second risk threshold, it is judged as an early warning; When the comprehensive risk assessment value is greater than or equal to the second risk threshold, it is judged as dangerous.

10. The method according to claim 1, characterized in that, In step S5, the single-item forced threshold judgment includes: when any parameter among the component pitch angle deviation, roll angle deviation, azimuth angle deviation, load, running speed, stress state, limit state or wind speed exceeds the corresponding forced threshold, the risk level is directly corrected to dangerous.

11. The method according to claim 1, characterized in that, In step S6, the auxiliary handling prompts are generated based on the direction of component attitude deviation; when the roll angle deviation exceeds a preset threshold, the roll deviation direction and verification prompts are output; when the pitch angle deviation exceeds a preset threshold, the pitch deviation direction and verification prompts are output; when the azimuth angle deviation exceeds a preset threshold, the azimuth angle deviation direction and verification prompts are output.

12. The method according to claim 1, characterized in that, In step S7, the management platform associates and stores the component number, hoisting time, installation location, equipment operation curve, environmental data, risk warning records and on-site handling records to form a component hoisting operation process management file.

13. A monitoring, early warning, and process management system for prefabricated component hoisting equipment based on multi-source sensor data fusion, characterized in that, include: The component basic information management module is used to store the component number, component type, component weight, component size, design installation location, and allowable installation deviation of the prefabricated components to be hoisted. The attitude data acquisition module is used to collect pitch angle, roll angle and azimuth angle during the hoisting process of prefabricated components; the equipment data acquisition module is used to collect the lifting weight, hoisting height or stroke, running speed, limit status and stress status of the hoisting or assembly equipment; the environmental data acquisition module is used to collect the wind speed at the hoisting site; the edge processing module is used to perform time synchronization, data cleaning, anomaly removal, coordinate transformation and normalization processing on attitude data, equipment data and environmental data. The data fusion and analysis module is used to calculate component attitude deviation values, equipment operation deviation values, environmental interference coefficients, and comprehensive risk assessment values. The risk warning module is used to determine the risk level based on equipment operating parameters, component management information, environmental parameters and preset thresholds, and generate risk warning information and auxiliary handling prompts. The communication module is used to realize data transmission between the equipment data acquisition module, environmental data acquisition module, edge processing module, management platform and field display terminal; the management platform module is used to display precast component information, BIM model data, mechanical equipment operating status, environmental status, risk level, early warning information and handling records, and store component management and equipment monitoring process data.

14. The system according to claim 13, characterized in that, The attitude data acquisition module includes an inertial measurement unit, which is installed on hoisting equipment, assembly equipment, lifting tools, temporary auxiliary measuring devices for components, or a detachable installation location on the surface of the component.

15. The system according to claim 13, characterized in that, The management platform module includes a component installation process quality archive sub-module, which is used to associate and store component number, hoisting time, installation location, equipment operation curve, risk warning record and on-site handling record.

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