A method and system for managing construction quality of engineering projects

Abstract

The present invention relates to the technical field of engineering project management, specifically to a method and system for engineering project construction quality management, comprising the following steps: extracting multiple design information of a target building based on project construction drawing information, simulating and analyzing the stress distribution of the building structure under various loads by constructing a building information model, evaluating the stability of the target building design, identifying and marking design defects, and obtaining simulation analysis results. In the present invention, by extracting design information and constructing a building information model, the stability of the building design is evaluated, design problems are identified at an early stage, the actual solidification rate of concrete is calculated, the quality of concrete is detected, rework and cost overruns caused by concrete quality problems are reduced, ultrasonic waves are used to detect defects in prefabricated components, the safety and quality of construction are improved, and by measuring actual construction images and comparing and analyzing them with design drawings, construction deviations are quantified to achieve efficient management of the construction quality of the target project.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering project management, and in particular to an engineering project construction quality management method and system. Background Art

[0002] The field of engineering project management technology focuses on improving the execution efficiency and quality control of engineering projects, covering multiple process management from project initiation to completion, including cost estimation, project scheduling, schedule scheduling, resource allocation, risk management, and quality assurance, to ensure that projects are completed on time, on budget, and in accordance with predetermined quality standards. It combines a variety of digital tools and software, including project management software, automated monitoring systems, and data analysis technology to achieve precise engineering project management and decision support, and ensure the successful delivery of engineering projects.

[0003] Among them, a construction project quality management method focuses on improving and ensuring the efficiency and effectiveness of quality control during the construction process, including quality monitoring tools, audit processes and compliance inspections, and technical support for optimizing construction quality through real-time data analysis. Combined with a systematic quality management process, it prevents construction defects and identifies potential problems early, reduces rework and cost overruns, improves the overall quality and benefits of the project, improves building safety and long-term durability, ensures that the project complies with regulatory requirements and industry standards, improves project quality, optimizes resource utilization, and reduces the risk of cost and time delays.

[0004] Traditional engineering project construction quality management technology relies on regular reviews and post-quality inspections in construction quality management, and cannot achieve real-time monitoring and immediate intervention, resulting in untimely discovery and handling of problems, and difficulty in responding quickly to immediate changes in the construction process, increasing project risks. The quality control of concrete and a variety of key building materials is intermittent and lacks continuous data support, which limits the ability to fully evaluate the status of materials and increases the risk of unqualified component quality. The management of construction deviations relies on manual measurement and visual inspection, which makes it difficult to ensure accuracy and reliability, affecting the project's engineering quality. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a construction quality management method and system for an engineering project.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for construction quality management of an engineering project, comprising the following steps:

[0007] S1: Based on the project construction drawing information, extract multiple design information of the target building, construct a building information model, simulate and analyze the stress distribution of the building structure under various loads, evaluate the stability of the target building design, identify and mark design defects, and obtain simulation analysis results;

[0008] S2: Based on the simulation analysis results, the water content of the concrete is monitored to evaluate the progress of the hydration reaction, the actual solidification rate of the concrete is calculated, and the actual solidification rate is compared with the preset solidification rate of the target concrete mix ratio to identify abnormal solidification rate data and generate concrete test results;

[0009] S3: Based on the concrete test results, ultrasonic testing is performed on the prefabricated components, cracks, defects, and bubbles in the prefabricated components are identified by analyzing the reflected waves of the ultrasonic waves in the components, and the quality test results of the prefabricated components are output;

[0010] S4: Based on the prefabricated component quality inspection results, the actual construction image of the target building is analyzed, the geometric dimension information of the target building is measured, and compared with the design drawings, the construction deviation is detected and quantified, and the construction quality management results are generated.

[0011] As a further solution of the present invention, the simulation analysis results include a stress distribution evaluation data set, a stability level, and defect location information; the concrete detection results include a solidification rate calculation result, hydration progress evaluation information, and abnormal data identification; the prefabricated component quality inspection results include crack detection information, bubble detection results, and load assessment information; the construction quality management results include dimensional deviation data, deviation quantification analysis results, and early warning message sending records.

[0012] As a further solution of the present invention, the step of obtaining the stress distribution is specifically as follows:

[0013] S111: Based on the project construction drawings, extract the building structure design parameters, including the elastic modulus of the material and the geometric parameters of multiple structural parts, to obtain the basic structure parameter data;

[0014] S112: constructing a building information model using the basic structural parameter data, including simulating the building structure and mapping material properties into the model to generate a building model construction result;

[0015] S113: Based on the building model construction result, the formula:

[0016] ;

[0017] Calculate the stress distribution of the building structure under target load;

[0018] in, is stress, is the applied load, is the distance between the target point and the fulcrum, is the vertical distance from the neutral axis, is the moment of inertia, is the shear force, is the static moment, is the material width.

[0019] As a further solution of the present invention, the steps of obtaining the simulation analysis results are specifically as follows:

[0020] S121: Based on the stress distribution, by formula:

[0021] ;

[0022] Calculate safety scores to assess the stability of building structures;

[0023] in, represents the safety score, represents the actual stress, represents the allowable stress, Indicates the actual deformation. Indicates the allowable deformation;

[0024] S122: Based on the stability of the building structure, by analyzing the performance of the building structure under various loads, risk areas are identified, design defects are marked, and simulation analysis results are obtained.

[0025] As a further solution of the present invention, the step of obtaining the actual solidification rate is specifically:

[0026] S211: Based on the simulation analysis result, the moisture content of the concrete is monitored in real time by a moisture sensor to generate moisture content time series data;

[0027] S212: Based on the water content time series data, evaluating the progress of the hydration reaction through the real-time water content data;

[0028] S213: Based on the progress of the hydration reaction, the formula is used:

[0029] ;

[0030] Calculate the actual setting rate of concrete;

[0031] in, represents the solidification rate, is the percentage of hydration reaction at the initial monitoring time point, is the percentage of hydration reaction at the end of monitoring time point, and are the initial and final monitoring time points, respectively.

[0032] As a further solution of the present invention, the steps of obtaining the concrete test results are specifically as follows:

[0033] S221: Based on the actual solidification rate, extract the solidification rate of the target concrete mix under various temperature and humidity conditions to obtain preset solidification rate data;

[0034] S222: Based on the preset solidification rate data, the formula:

[0035] ;

[0036] Calculate the setting rate deviation of concrete;

[0037] in, Indicates the percentage of solidification rate deviation, is the actual solidification rate, is the preset target solidification rate, is the average temperature during the measurement period, is the average humidity during the measurement period, is the adjustment factor;

[0038] S223: Based on the setting rate deviation, by comparing with a preset deviation threshold, abnormal concrete is identified and batch information is recorded to generate a concrete test result.

[0039] As a further solution of the present invention, the steps for obtaining the quality inspection results of the prefabricated components are specifically as follows:

[0040] S311: Based on the concrete detection result, the prefabricated component is detected by ultrasonic detection equipment, signal data of reflected waves are received and recorded, and an ultrasonic signal data set is generated;

[0041] S312: Based on the ultrasonic signal data set, by formula:

[0042] ;

[0043] Calculate abnormal signal strength;

[0044] in, It represents the total strength of abnormal signals accumulated from all detection points. For the The signal strength of each detection point, is the reference signal strength, is the total number of detection points, Indicates the index of the detection point;

[0045] S313: Based on the abnormal signal strength, the quality of the target prefabricated components is evaluated, unqualified prefabricated components are identified and marked, and prefabricated component quality inspection results are generated.

[0046] As a further solution of the present invention, the steps for obtaining the construction quality management results are specifically as follows:

[0047] S411: Based on the prefabricated component quality inspection result, collect and analyze the actual construction image of the target building, measure the actual geometric dimensions of the target building, and generate building dimension measurement data;

[0048] S412: Based on the building dimension measurement data, the formula:

[0049] ;

[0050] Calculate the degree of dimensional deviation;

[0051] in, Indicates The weighted deviation degree of each size point, For the The importance weight of each size point, For the Actual measurement size points, For the A reference dimension point on the design drawing. For the Design tolerance of each dimension point, Function to calculate deviations outside tolerance;

[0052] S413: Based on the degree of dimensional deviation, use the formula:

[0053] ;

[0054] Calculate the total deviation degree of the target building to obtain the total construction deviation;

[0055] in, is the total construction deviation, is the total number of measurement points;

[0056] S414: Based on the total construction deviation, the coordinate data and deviation degree information of multiple dimensional deviation positions are recorded to generate a construction quality management result.

[0057] A construction project quality management system, the construction project quality management system is used to implement the above-mentioned construction project quality management method, the system comprises:

[0058] The design information extraction module extracts multiple design information of the target building based on the project construction drawings, identifies multiple architectural elements in the target building design, and constructs a building information model;

[0059] The stress simulation analysis module simulates and analyzes the stress distribution under various load conditions based on the building information model, evaluates the structural stability of the building, identifies design defects, and obtains simulation analysis results;

[0060] Based on the simulation analysis results, the solidification rate comparison module monitors the moisture content of the concrete under construction, evaluates the progress of the hydration reaction, calculates the actual concrete solidification rate, and compares and analyzes it with the preset solidification rate, identifies and marks concrete batches with abnormal solidification rates, and generates concrete test results;

[0061] The ultrasonic detection module performs ultrasonic detection on the prefabricated component based on the concrete detection result, analyzes the reflected wave and identifies the component defects, and obtains the prefabricated component quality detection result;

[0062] The construction deviation detection module collects and analyzes the actual images of the construction site based on the prefabricated component quality inspection results, measures the actual geometric dimensions of the building and compares them with the design drawings, quantifies the construction deviations, and sends early warning information to management personnel to obtain construction quality management results.

[0063] Compared with the prior art, the advantages and positive effects of the present invention are:

[0064] In the present invention, by extracting design information and constructing a building information model, the stability of the building design is evaluated, design problems are identified at an early stage, the actual solidification rate of concrete is calculated to detect the quality of concrete, and rework and cost overruns caused by concrete quality problems are reduced. Ultrasonic waves are used to detect defects in prefabricated components to improve the safety and quality of construction. By measuring actual construction images and comparing and analyzing them with design drawings, construction deviations are quantified to achieve efficient management of the construction quality of the target project. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0066] Figure 2 is a flow chart of calculating stress distribution of the present invention;

[0067] Figure 3 A flow chart of obtaining simulation analysis results of the present invention;

[0068] Figure 4 The flow chart of calculating the actual solidification rate of the present invention;

[0069] Figure 5A flow chart of obtaining concrete test results according to the present invention;

[0070] Figure 6 A flow chart of obtaining the quality inspection results of prefabricated components according to the present invention;

[0071] Figure 7 The present invention provides a flow chart for generating construction quality management results. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0073] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0074] See also Figure 1 The present invention provides a technical solution, a method for construction quality management of an engineering project, comprising the following steps:

[0075] S1: Based on the project construction drawing information, extract multiple design information of the target building, construct a building information model, simulate and analyze the stress distribution of the building structure under various loads, evaluate the stability of the target building design, identify and mark design defects, and obtain simulation analysis results;

[0076] S2: Based on the simulation analysis results, the water content of concrete is monitored to evaluate the progress of hydration reaction, the actual solidification rate of concrete is calculated, and compared with the preset solidification rate of the target concrete mix ratio, abnormal solidification rate data is identified, and concrete test results are generated;

[0077] S3: Based on the concrete test results, ultrasonic testing is performed on the prefabricated components. By analyzing the reflected waves of the ultrasonic waves in the components, cracks, defects, and bubbles in the prefabricated components are identified, and the quality test results of the prefabricated components are output;

[0078] S4: Based on the quality inspection results of prefabricated components, the actual construction images of the target building are analyzed, the geometric dimension information of the target building is measured, and compared with the design drawings, the construction deviations are detected and quantified, and the construction quality management results are generated.

[0079] The simulation analysis results include stress distribution evaluation data sets, stability levels, and defect location information; the concrete inspection results include solidification rate calculation results, hydration progress evaluation information, and abnormal data identification; the prefabricated component quality inspection results include crack detection information, bubble detection results, and load assessment information; the construction quality management results include dimensional deviation data, deviation quantification analysis results, and early warning message sending records.

[0080] See also Figure 2 , the specific steps for obtaining stress distribution are:

[0081] S111: Based on the project construction drawings, extract the building structure design parameters, including the elastic modulus of the material and the geometric parameters of multiple structural parts, to obtain the basic structure parameter data;

[0082] In sub-step S111, the building structure design parameters are extracted in detail through the project construction drawings, including the elastic modulus of the material, the thickness of the load-bearing wall, the height and width of the beam, and the cross-sectional dimensions of the column. The target data supports the calculation of the maximum force and expected stress distribution that the structural part can withstand. The geometric parameterization method is used to ensure that the design parameters accurately reflect the physical characteristics of the building, provide necessary input for model construction, and ensure the accuracy and practicality of subsequent simulation analysis. The results are the basic structural parameter data.

[0083] S112: Using the basic structural parameter data, constructing a building information model, including simulating the building structure, and mapping the material properties into the model to generate a building model construction result;

[0084] In sub-step S112, the basic structural parameter data is used to apply finite element analysis to construct a building information model. The model is constructed in combination with the material elastic modulus and geometric parameters to ensure that the physical properties of the multiple structural components in the model are consistent with the actual situation. Structural load simulation is performed, including static loads, dynamic loads and environmental influences such as wind pressure and seismic force. The performance of the building under the expected use conditions is evaluated to ensure the design reliability and safety. The building model construction results are generated to provide a scientific basis for construction quality management and risk assessment.

[0085] S113: Based on the building model, the results are constructed by the formula:

[0086] ;

[0087] Calculate the stress distribution of the building structure under target load;

[0088] in, is stress, obtained through stress analysis, reflecting the stress state of the material under the target load. is the applied load, obtained from the load data, is the distance between the target point and the fulcrum, extracted from the design drawing, is the vertical distance from the neutral axis, extracted directly from the structural details of the architectural design drawings. is the moment of inertia, obtained from the basic structural parameter data, and used to calculate the physical quantity of resistance to bending. is the shear force, obtained based on the load distribution and support response analysis, is the static moment, calculated by multiplying the shear force and the lever arm distance, and is used to describe the moment under shear. is the material width, obtained from the design drawing;

[0089] Calculation example:

[0090] set up , , , , , , ,calculate :

[0091] ;

[0092] ;

[0093] ;

[0094] ;

[0095] The calculation results show that the stress value under the given load and structural parameters is 6750.75 The numerical value reflects the stress state of the building structure under the target load conditions, and the calculation process is used to evaluate whether the safety of the structure meets the design specification requirements.

[0096] See also Figure 3 , the specific steps for obtaining simulation analysis results are:

[0097] S121: Based on stress distribution, through the formula:

[0098] ;

[0099] Calculate safety scores to assess the stability of building structures;

[0100] in, It represents the safety score, which reflects the safety status of the structure under given conditions. Represents actual stress, which is the stress data obtained from the design parameter data set by stress analysis software. represents the allowable stress, obtained from building material standards and specifications, Indicates the actual deformation, obtained through sensor data or simulation test, It represents the allowable deformation, which is obtained from the design specification;

[0101] Calculation example:

[0102] set up , , , , calculate the safety score :

[0103] Calculate the ratio of actual stress to allowable stress:

[0104] ;

[0105] Calculate the ratio of actual deformation to allowed deformation:

[0106] ;

[0107] Calculate the safety score:

[0108] ;

[0109] Calculation results It reflects the safety status of the structure under given load and material performance conditions. A value less than 1 indicates that the structure is safe under current conditions and has not reached the ultimate stress and ultimate deformation of the material. The calculation process is used to evaluate the overall stability and safety of the building structure.

[0110] S122: Based on the stability of the building structure, by analyzing the performance of the building structure under various loads, identifying risk areas, marking design defects, and obtaining simulation analysis results;

[0111] In sub-step S122, the stability of the building structure is evaluated. The finite element method is used to simulate and analyze the response of the building structure under various load conditions, including gravity, wind pressure, seismic force and snow load. Material properties such as elastic modulus and yield strength and performance changes under different environmental conditions are considered. The building structure is decomposed into a grid model, and appropriate physical and mechanical properties are assigned to each node and element. For each load, the corresponding force and pressure are applied to the model, and the induced stress and deformation are calculated. The overall and local response capabilities of the structure are evaluated, and areas where stress exceeds the safety limit of the material are identified as potential risk areas. The defect identification tool in the structural analysis software is used to mark design defects in risk areas, record excessive stress concentration, unreasonable load distribution or potential structural weaknesses, ensure that the construction team takes preventive or reinforcement measures during implementation to avoid or reduce the impact of defects, and generate structural stability analysis results that describe the specific location and nature of each identified risk area and defect.

[0112] See also Figure 4 , the steps to obtain the actual solidification rate are as follows:

[0113] S211: Based on the simulation analysis results, the moisture content of the concrete is monitored in real time through a moisture sensor to generate moisture content time series data;

[0114] In sub-step S211, based on the simulation analysis results, moisture sensors are deployed in key concrete pouring areas to monitor and record the moisture content of concrete in real time. Each sensor uploads data to the central monitoring system at a regular interval to ensure data continuity and accuracy. Capacitive or resistive moisture measurement technology is used to accurately measure the moisture changes inside the concrete. The collected data is automatically converted into a time series format and stored in a database to provide basic data for subsequent analysis, generate moisture content time series data, and record the moisture changes in each stage from pouring to solidification.

[0115] S212: Based on the water content time series data, evaluating the progress of the hydration reaction through the real-time water content data;

[0116] In sub-step S212, the obtained moisture content time series data is used to adopt a hydration reaction rate analysis model based on the principle of chemical kinetics to calculate the progress of the hydration reaction in the concrete, analyze the relationship between the hydration heat release and time, and evaluate the reaction rate. The model analyzes the moisture content data at each time point based on the known concrete mix ratio and initial hydration conditions to estimate the current degree of hydration. In the process, real-time data processing software is used to quickly calculate the data to confirm whether the hydration reaction proceeds according to the predetermined path. The evaluation result is the progress of the hydration reaction, which provides key decision support information and guides subsequent construction and maintenance work.

[0117] S213: Based on the progress of the hydration reaction, the formula is used:

[0118] ;

[0119] Calculate the actual setting rate of concrete;

[0120] in, It represents the solidification rate, reflecting the progress change of the hydration reaction per unit time. is the percentage of hydration reaction at the initial monitoring time point, is the percentage of hydration reaction at the end of monitoring time point, and are the time points of initial and final monitoring, respectively, obtained from the data records;

[0121] Calculation example:

[0122] set up , , time from arrive , i.e. 6 hours, calculate the actual solidification rate:

[0123] Calculate the percent change in hydration reaction:

[0124] ;

[0125] Calculate time difference (in hours):

[0126] ;

[0127] Substitute the formula to calculate the actual solidification rate :

[0128] ;

[0129] The calculation results of the formula show that the progress of the hydration reaction of concrete increases by about 3.33% per hour. The value reflects the solidification rate of concrete during the observation period, indicating the rapid progress of the hydration reaction of concrete within 6 hours. The formula is used to evaluate whether the concrete solidifies at the expected rate.

[0130] See also Figure 5 , the specific steps for obtaining concrete test results are:

[0131] S221: based on the actual solidification rate, extracting the solidification rate of the target concrete mix under various temperature and humidity conditions to obtain preset solidification rate data;

[0132] In sub-step S221, based on the actual solidification rate obtained, database query and data processing technology are used to extract preset solidification rate data related to the target concrete mix ratio. The data includes theoretical solidification rates under various temperature and humidity conditions. By accessing the material science database stored in the cloud server, the concrete type and the corresponding solidification behavior parameters are identified, and the relevant data of the target concrete mix ratio is retrieved, including the solidification rate under standardized test conditions, to generate preset solidification rate data. The target data provides a standard reference value for subsequent analysis to ensure the accuracy and scientificity of the evaluation.

[0133] S222: Based on the preset solidification rate data, the formula:

[0134] ;

[0135] Calculate the setting rate deviation of concrete;

[0136] in, It represents the coagulation rate deviation percentage, which is used to evaluate the deviation between the actual coagulation rate and the target coagulation rate. is the actual solidification rate, obtained through actual test data of concrete, is the preset target solidification rate, obtained from the engineering quality control manual, is the average temperature during the measurement period, obtained through the environmental monitoring system, is the average humidity during the measurement period, obtained through the environmental monitoring system, is the adjustment factor;

[0137] Calculation example:

[0138] set up , , , , , calculate the solidification rate deviation:

[0139] Calculate the temperature and humidity adjustment factors:

[0140] ;

[0141] Calculate the difference between the actual solidification rate and the adjusted target rate:

[0142] ;

[0143] Calculate the solidification rate deviation:

[0144] ;

[0145] The formula calculation results show that the setting rate deviation is 26%, indicating that the actual setting rate is slightly lower than the expected target after adjustment. The calculation process is used to monitor and evaluate the quality of concrete in engineering practice.

[0146] S223: Based on the setting rate deviation, by comparing with a preset deviation threshold, identifying abnormal concrete and recording batch information, and generating concrete test results;

[0147] In sub-step S223, the obtained solidification rate data is used in combination with the actual measured solidification rate, and the deviation between the two is calculated. The set deviation threshold is applied for comparison. The absolute difference between the actual solidification rate and the preset rate is calculated using difference calculation and threshold judgment, and compared with the preset threshold. If the difference exceeds the threshold, it is identified as an abnormality. The steps include automatic data capture, real-time calculation, and result classification. After the abnormality is identified, the relevant concrete batch information is recorded and marked as a batch that requires special inspection or processing. The concrete test results are generated. The results list the specific information of all abnormal batches, including batch number, measurement time, actual and preset solidification rate data, providing key information for project quality management and ensuring the timeliness and effectiveness of quality control measures.

[0148] See also Figure 6 , the specific steps for obtaining the quality inspection results of prefabricated components are as follows:

[0149] S311: Based on the concrete detection result, the prefabricated component is detected by ultrasonic detection equipment, signal data of the reflected wave is received and recorded, and an ultrasonic signal data set is generated;

[0150] In sub-step S311, based on the concrete test results, ultrasonic testing equipment is deployed to test the prefabricated components. The process involves setting up the equipment to transmit ultrasonic waves at appropriate test points and receiving ultrasonic signals reflected by the internal structure of the components. High-frequency ultrasonic probes and signal receivers are used to ensure signal clarity and transmission efficiency. The steps include adjusting the probe position to cover key parts of the components, controlling the transmission frequency and receiving sensitivity to adapt to materials of different types and densities, and the received signals are analyzed by signal processing software, converted into digital data, and recorded in the ultrasonic signal data set. The target data set reflects the structural integrity of the components, such as changes in wave velocity and the intensity of echoes, providing an empirical basis for subsequent quality assessment.

[0151] S312: Based on the ultrasonic signal data set, the formula:

[0152] ;

[0153] Calculate abnormal signal strength;

[0154] in, It represents the total strength of abnormal signals accumulated from all detection points and is used to evaluate the scale of defects in prefabricated components. For the The signal strength of each detection point is obtained by measuring the reflected wave signal strength at each detection point using ultrasonic detection equipment. The reference signal strength is determined by the average signal strength of the undamaged area of ​​the component and is obtained by pre-determining the reflected wave signal of the normal area. is the total number of detection points, which is set according to the size of the prefabricated component and the preset detection resolution. Represents the index of the detection point, which is used to iterate all the detection points to cumulatively calculate the total strength of the abnormal signal;

[0155] Calculation example:

[0156] Set the total number of detection points , reference signal strength The measured signal strength is , calculate the total strength of abnormal signals:

[0157] ;

[0158] ;

[0159] Calculation results It means that the total defect signal strength score detected in the inspected prefabricated components is 21. The value indicates that there are defects of a certain scale in the components. The value is used to compare with the preset threshold to evaluate whether the components meet the quality standards and identify unqualified prefabricated components;

[0160] S313: Based on the abnormal signal strength, the quality of the target prefabricated component is evaluated, unqualified prefabricated components are identified and marked, and the prefabricated component quality inspection results are generated;

[0161] In sub-step S313, the obtained ultrasonic signal data set is used to apply signal analysis technology to evaluate the structural quality of prefabricated components, including using Fourier transform to analyze the reflected waveform and identify abnormal signal strength, such as abnormal signal amplitude or abnormal wave velocity indicating potential cracks, voids or other structural defects. By comparing with the standard signal pattern, it is determined whether the signal of each detection point is within the normal range. The identification of abnormal signals is based on a preset threshold. Signals exceeding the threshold trigger the unqualified marking process. The corresponding component position and specific abnormality type are recorded in the quality inspection report. The prefabricated component quality inspection results are generated, listing all unqualified components and specific defect types, providing necessary quality control data, and guiding subsequent treatment measures or construction adjustments.

[0162] See also Figure 7, the specific steps for obtaining construction quality management results are:

[0163] S411: Based on the prefabricated component quality inspection results, collect and analyze the actual construction images of the target building, measure the actual geometric dimensions of the target building, and generate building dimension measurement data;

[0164] In sub-step S411, image data of the target building construction site is collected using image capture equipment, such as a high-definition camera equipped with a drone, including setting appropriate flight paths and camera parameters to ensure comprehensive coverage of all parts of the building. The collected images are analyzed by image processing software, and edge detection and image registration techniques are applied to accurately measure the actual geometric dimensions of the building. The measurement data is refined to determine parameters such as the length, width, and height of each structural element and compared with the design drawings. The generated building dimension measurement data provides detailed actual building geometric information, providing a data basis for subsequent analysis.

[0165] S412: Based on the building size measurement data, the formula:

[0166] ;

[0167] Calculate the degree of dimensional deviation;

[0168] in, Indicates The weighted deviation degree of each size point, For the The importance weight of each size point, For the Actual measurement size points, For the A reference dimension point on the design drawing. For the Design tolerance of each dimension point, Function to calculate deviations outside tolerance;

[0169] Calculation example:

[0170] Set the target size deviation position - , mm, mm, calculate the degree of deviation:

[0171] ;

[0172] result It means that the actual size of this dimension point exceeds the allowable tolerance range by 25% compared with the design size. The value is used to evaluate the construction quality and take measures to make adjustments if necessary.

[0173] S413: Based on the degree of dimensional deviation, use the formula:

[0174] ;

[0175] Calculate the total deviation degree of the target building to obtain the total construction deviation;

[0176] in, is the total construction deviation, is the total number of measurement points;

[0177] Calculation example:

[0178] There are three size deviation positions in the setting project. They are , , , calculate the total construction deviation:

[0179] ;

[0180] result It means that the deviation degree of all measurement points is 0.45. The value is used to help the project management team understand the overall construction quality;

[0181] S414: Based on the total construction deviation, the coordinate data and deviation degree information of multiple size deviation positions are recorded to generate a construction quality management result;

[0182] In sub-step S414, based on the building dimension measurement data, the difference between the actual dimension and the designed dimension is calculated through structural analysis software, including the dimension difference value and related coordinate data. The software sets the coordinate data of multiple dimension deviation positions, analyzes the degree of deviation, and evaluates it according to the preset deviation threshold. The dimension deviation exceeding the threshold is automatically identified as a potential risk point by the system. The generated construction quality management results record in detail all identified dimension deviations and location information, providing the management team with key quality control and risk management tools.

[0183] A construction project quality management system, which is used to implement the above-mentioned construction project quality management method, and includes:

[0184] The design information extraction module extracts multiple design information of the target building based on the project construction drawings, identifies multiple architectural elements in the target building design, and constructs a building information model;

[0185] The stress simulation analysis module is based on the building information model to simulate and analyze the stress distribution under various load conditions, evaluate the structural stability of the building, identify design defects, and obtain simulation analysis results;

[0186] Based on the simulation analysis results, the solidification rate comparison module monitors the moisture content of the concrete under construction, evaluates the progress of the hydration reaction, calculates the actual concrete solidification rate, and compares and analyzes it with the preset solidification rate, identifies and marks concrete batches with abnormal solidification rates, and generates concrete test results;

[0187] The ultrasonic detection module performs ultrasonic detection on prefabricated components based on the concrete detection results, analyzes the reflected waves and identifies component defects to obtain the quality detection results of prefabricated components;

[0188] The construction deviation detection module collects and analyzes the actual images of the construction site based on the quality inspection results of prefabricated components, measures the actual geometric dimensions of the building and compares them with the design drawings, quantifies the construction deviations, and sends early warning information to managers to obtain construction quality management results.

[0189] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A construction project quality management system, characterized in that: The system comprises: The design information extraction module extracts multiple design information of the target building based on the project construction drawings, identifies multiple architectural elements in the target building design, and constructs a building information model; The stress simulation analysis module simulates and analyzes the stress distribution under various load conditions based on the building information model, evaluates the structural stability of the building, identifies design defects, and obtains simulation analysis results; Based on the simulation analysis results, the solidification rate comparison module monitors the moisture content of the concrete under construction, evaluates the progress of the hydration reaction, calculates the actual concrete solidification rate, and compares and analyzes it with the preset solidification rate, identifies and marks concrete batches with abnormal solidification rates, and generates concrete test results; The ultrasonic detection module performs ultrasonic detection on the prefabricated component based on the concrete detection result, analyzes the reflected wave and identifies the component defects, and obtains the prefabricated component quality detection result; The construction deviation detection module collects and analyzes the actual images of the construction site based on the prefabricated component quality inspection results, measures the actual geometric dimensions of the building and compares them with the design drawings, quantifies the construction deviations, and sends early warning information to the management personnel to obtain the construction quality management results; The steps of obtaining the stress distribution are specifically as follows: Based on the project construction drawings, extract the building structure design parameters, including the elastic modulus of the material and the geometric parameters of multiple structural parts, and obtain the basic structural parameter data; Using the infrastructure parameter data, constructing a building information model, including simulating the building structure, and mapping material properties into the model to generate a building model construction result; Based on the building model construction results, through the formula: ； Calculate the stress distribution of the building structure under target load; in, is the stress distribution, F is the applied load, is the distance between the target point and the fulcrum, y is the vertical distance from the neutral axis, is the moment of inertia, V is the shear force, Q is the static moment, and b is the material width; The steps for obtaining the simulation analysis results are specifically as follows: Based on the stress distribution, the formula: ； Calculate safety scores to assess the stability of building structures; Among them, S represents the safety score, represents the actual stress, represents the allowable stress, Indicates the actual deformation. Indicates the allowable deformation; Based on the stability of the building structure, the performance of the building structure under various loads is analyzed, risk areas are identified, design defects are marked, and simulation analysis results are obtained; The specific steps for obtaining the actual solidification rate are: Based on the simulation analysis results, the moisture content of the concrete is monitored in real time through a moisture sensor to generate moisture content time series data; Based on the water content time series data, evaluating the progress of the hydration reaction through real-time water content data; Based on the hydration reaction progress, the formula is used: ； Calculate the actual setting rate of concrete; in, The actual solidification rate is is the percentage of hydration reaction at the initial monitoring time point, is the percentage of hydration reaction at the end of monitoring time point, and are the initial and final monitoring time points, respectively; The steps for obtaining the concrete test results are specifically as follows: Based on the actual solidification rate, the solidification rate of the target concrete mix under various temperature and humidity conditions is extracted to obtain preset solidification rate data; Based on the preset solidification rate data, by the formula: ； Calculate the setting rate deviation of concrete; in, represents the solidification rate deviation, is the actual solidification rate, is the preset target solidification rate, T is the average temperature during the measurement period, H is the average humidity during the measurement period, and C is the adjustment factor; Based on the setting rate deviation, by comparing with a preset deviation threshold, abnormal concrete is identified and batch information is recorded to generate concrete test results; The steps for obtaining the quality inspection results of the prefabricated components are specifically as follows: Based on the concrete detection results, the prefabricated components are detected by ultrasonic detection equipment, signal data of reflected waves are received and recorded, and an ultrasonic signal data set is generated; Based on the ultrasonic signal data set, the formula: ； Calculate abnormal signal strength; Where D represents the accumulated abnormal signal strength from all detection points, is the signal strength of the i-th detection point, is the reference signal strength, n is the total number of detection points, and i represents the index of the detection point; Based on the abnormal signal strength, the quality of the target prefabricated component is evaluated, unqualified prefabricated components are identified and marked, and prefabricated component quality inspection results are generated; The steps for obtaining the construction quality management results are specifically as follows: Based on the prefabricated component quality inspection results, actual construction images of the target building are collected and analyzed, actual geometric dimensions of the target building are measured, and building dimension measurement data are generated; Based on the building size measurement data, the formula: ； Calculate the degree of dimensional deviation; in, Indicates the degree of size deviation of the jth size point, is the importance weight of the j-th size point, is the jth actual measurement size point, is the reference dimension point on the jth design drawing, is the design tolerance of the jth dimension point, Function to calculate deviations outside tolerance; Based on the degree of dimensional deviation described, the formula is used: ； Calculate the total deviation degree of the target building to obtain the total construction deviation; in, is the total construction deviation, m is the total number of measurement points; Based on the total construction deviation, the coordinate data and deviation degree information of multiple dimensional deviation positions are recorded to generate a construction quality management result.

2. The engineering project construction quality management system according to claim 1, characterized in that: The simulation analysis results include stress distribution evaluation data sets, stability levels, and defect location information; the concrete inspection results include solidification rate calculation results, hydration progress evaluation information, and abnormal data identification; the prefabricated component quality inspection results include crack detection information, bubble detection results, and load assessment information; the construction quality management results include dimensional deviation data, deviation quantification analysis results, and early warning message sending records.

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