A construction project quality supervision and early warning system based on big data

Abstract

The present invention belongs to the field of construction project quality supervision and early warning, and specifically discloses a construction project quality supervision and early warning system based on big data, which includes: a prefabricated component qualification judgment module, a prefabricated component installation quality analysis module, a concrete filling quality analysis module, an assembled housing quality judgment module, and a database; by combining dimension measurement, three-dimensional model comparison and surface damage analysis, a multi-angle evaluation of the quality of prefabricated components is achieved, and the accuracy and adequacy of the evaluation are improved; by analyzing the structural integrity and surface damage degree of each prefabricated component, safety hazards caused by dimensional deviation or structural defects can be avoided, potential quality problems can be discovered and repaired in a timely manner, and the durability reduction and maintenance cost increase caused by surface damage can be reduced.

Description

Technical Field

[0001] The present invention belongs to the field of construction project quality supervision and early warning, and relates to a construction project quality supervision and early warning system based on big data. Background Art

[0002] Traditional construction project quality supervision mainly relies on on-site inspection and experience judgment of supervisors. This method has many shortcomings, such as strong subjectivity, low efficiency, and difficulty in comprehensive coverage. With the expansion of the scale and complexity of construction projects, traditional supervision methods can no longer meet the needs of modern construction project quality management. Therefore, it is necessary to introduce a more scientific, efficient and comprehensive quality supervision method.

[0003] Although the existing construction project quality supervision and early warning system meets certain needs, it still has limitations, which are specifically reflected in: 1. When detecting the quality of prefabricated parts of prefabricated houses, the existing technology lacks efficient real-time analysis and early warning, resulting in the quality problems of prefabricated parts of prefabricated houses cannot be dealt with immediately when the problems first appear, which increases the difficulty and cost of problem solving and cannot effectively avoid the accumulation and expansion of prefabricated parts quality problems.

[0004] 2. During the assembly process of prefabricated parts of prefabricated houses, the existing technology lacks immediate data analysis and feedback, resulting in the inability to monitor the installation position and other specific conditions of the prefabricated parts in real time. It is often necessary to wait until the installation is completed and conduct an overall inspection to discover problems, which not only delays the opportunity to correct the problem, but also greatly increases the number and complexity of rework. Summary of the invention

[0005] In view of this, in order to solve the problems raised in the above background technology, a construction project quality supervision and early warning system based on big data is proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a construction project quality supervision and early warning system based on big data, including: a prefabricated part qualification judgment module: used to collect the length, width, height and angle images of each prefabricated part of the prefabricated house, and analyze the structural integrity and surface damage degree of each prefabricated part of the prefabricated house respectively, and then analyze the quality qualification index of each prefabricated part of the prefabricated house, screen out unqualified prefabricated parts, and issue early warning.

[0007] Prefabricated parts installation quality analysis module: used to collect the target three-dimensional model of each prefabricated part of the prefabricated house, the installation position of the center point of each prefabricated part, the gap width between each prefabricated part and its adjacent prefabricated part, and the propagation time, amplitude and frequency of the reflected wave at each connection part between each prefabricated part and its adjacent prefabricated part, respectively analyze the position conformity of each prefabricated part of the prefabricated house, the matching degree between adjacent prefabricated parts and the tightness index of the connection structure, and then analyze the installation quality qualification index of the prefabricated parts

[0008] Concrete filling quality analysis module: The acoustic wave detector is used to send acoustic waves to each collection point of the concrete and measure the sound velocity and the humidity value of each collection point of each prefabricated part and its adjacent prefabricated parts, respectively analyzing the distribution uniformity index of concrete filling and the leakage degree index of concrete filling, and then analyzing the quality qualification index θ of concrete filling.

[0009] Prefabricated housing quality determination module: used to analyze the comprehensive quality index of prefabricated housing according to the installation quality index of prefabricated parts and the quality index of concrete filling, and then judge whether the quality of prefabricated housing is qualified and issue early warning.

[0010] Database: used to store the center point position of the prefabricated house, the standard length, width, height of each prefabricated component, the standard installation position of the center point of each prefabricated component, the standard three-dimensional model of each prefabricated component and the allowable humidity value of each prefabricated component.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention realizes a multi-angle evaluation of the quality of prefabricated parts by combining dimensional measurement, three-dimensional model comparison and surface damage analysis, thereby improving the accuracy and adequacy of the evaluation. By analyzing the structural integrity and surface damage degree of each prefabricated part, it can avoid safety hazards caused by dimensional deviation or structural defects, timely discover and repair potential quality problems, reduce the durability reduction and maintenance cost increase caused by surface damage, and analyze the quality status of the prefabricated parts in real time during the detection process. Once a quality problem is found, an early warning is immediately issued, so that the construction unit can respond quickly and take measures to effectively avoid the accumulation and expansion of quality problems.

[0012] (2) The present invention analyzes multi-angle images of each prefabricated component of the assembled house and combines them with the installation position data of the center point to evaluate the conformity of the actual installation position of the prefabricated component with the design requirements with high precision, ensuring that the installation error is within a controllable range. During the assembly process, the position conformity, matching degree and tightness of the connection structure of the prefabricated components can be analyzed in real time, and deviations in the installation process can be discovered and corrected in time to avoid subsequent rework and cost increase. In addition, through precise installation quality control, rework and material waste caused by improper installation can be reduced, thereby reducing construction costs.

[0013] (3) The present invention can fully and accurately evaluate multiple key quality indicators of concrete filling through the two technical means of acoustic wave detection and humidity measurement. Acoustic wave detection is used to analyze the distribution uniformity of concrete, while humidity measurement is used to detect potential leakage problems. The two complement each other, greatly improving the accuracy and reliability of quality assessment, and can timely discover uneven distribution or leakage problems in the concrete filling process, providing early warning for engineering personnel, helping to take corresponding measures to repair or adjust before the problem worsens, thereby avoiding greater quality problems and economic losses in the later stage.

[0014] (4) The present invention is used to analyze the comprehensive quality index of the prefabricated house according to the installation quality index of the prefabricated parts and the quality index of the concrete filling, and then judge whether the quality of the prefabricated house is qualified and issue an early warning. It can fully evaluate the overall quality of the prefabricated house, avoid focusing on only one link and ignoring other key factors, and can find out the weak links in the construction process, further optimize the construction process, improve construction efficiency, reduce construction costs, and issue early warnings in time to prevent problems from expanding and reduce subsequent maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention provides a construction project quality supervision and early warning system based on big data, including: a prefabricated part qualification judgment module, a prefabricated part installation quality analysis module, a concrete filling quality analysis module, an assembled housing quality judgment module, and a database.

[0019] The prefabricated parts installation quality analysis module is respectively connected to the prefabricated parts qualification judgment module, the database and the concrete filling quality analysis module; the concrete filling quality analysis module is respectively connected to the prefabricated parts installation quality analysis module and the prefabricated housing quality judgment module; the database is respectively connected to the prefabricated parts qualification judgment module and the prefabricated parts installation quality analysis module.

[0020] The prefabricated parts qualification judgment module is used to collect the length, width, height and angle images of each prefabricated part of the prefabricated house, respectively analyze the structural integrity and surface damage degree of each prefabricated part of the prefabricated house, and then analyze the quality qualification index of each prefabricated part of the prefabricated house, screen out unqualified prefabricated parts, and issue early warning.

[0021] Furthermore, the analyzing the structural integrity of each prefabricated component of the prefabricated house includes: measuring the length, width and height of each prefabricated component of the prefabricated house by a laser rangefinder.

[0022] The standard length, width and height of each prefabricated component of the prefabricated house are extracted from the database.

[0023] Subtract the length, width and height of each prefabricated part of the prefabricated house from the length, width and height of the standard, and obtain the difference in length, width and height of each prefabricated part of the prefabricated house, which are recorded as ΔL j , ΔW j and ΔH j , where j represents the number corresponding to the j-th pre-component, j=1,2,3...J.

[0024] Analyze the dimensional conformity of each prefabricated component of the prefabricated house j , Where ΔL′ j , ΔW′ j and ΔH′ j They respectively represent the allowable differences in length, width and height of the j-th prefabricated component of the prefabricated house.

[0025] The prefabricated parts of the assembled house are scanned by a laser scanner to obtain a target three-dimensional model of the prefabricated parts of the assembled house.

[0026] The standard three-dimensional models of each prefabricated component of the prefabricated house are extracted from the database.

[0027] The 3D model of each prefabricated component of the prefabricated house is compared with the standard 3D model to obtain the matching degree of the 3D model of each prefabricated component of the prefabricated house, which is recorded as M j .

[0028] Analyze the structural integrity of each prefabricated component of the prefabricated house j , j =C j *α1+Mj *α2, where α1 and α2 represent the weights corresponding to the set prefabricated part size conformity and three-dimensional model matching degree, respectively, and α1+α2=1.

[0029] As a preferred embodiment, the α1 and α2 can be set to 0.6 and 0.4 respectively. The dimensional conformity of the prefabricated parts is a key factor in ensuring that they can be correctly installed and meet the design requirements. If the size does not meet the requirements, it will directly affect the overall structural stability and safety of the prefabricated house. Although the three-dimensional model matching plays an important auxiliary role in modern building design and construction, it does not directly affect the structural performance as much as the dimensional conformity. Therefore, the weight corresponding to the dimensional conformity of the prefabricated parts is greater than the weight corresponding to the three-dimensional model matching.

[0030] The specific process of obtaining the 3D model matching degree of each prefabricated component of the prefabricated house is: importing the 3D model of each prefabricated component of the prefabricated house and the standard 3D model into the 3D model comparison software to obtain the 3D model matching degree of each prefabricated component of the prefabricated house.

[0031] Furthermore, the analysis of the degree of surface damage of each prefabricated component of the prefabricated house includes: performing color threshold segmentation processing on each angle image of each prefabricated component of the prefabricated house to obtain the grayscale value of each pixel in each angle image of each prefabricated component of the prefabricated house, and comparing the grayscale value of each pixel with the grayscale value interval of the pixel corresponding to the damaged area. If the grayscale value of a pixel belongs to the grayscale value interval of the pixel corresponding to the damaged area, the pixel is marked as a damaged pixel, and the number of damaged pixels on the surface of each prefabricated component of the prefabricated house is screened and counted, which is recorded as P. j , and then obtain the total number of pixels on the surface of each prefabricated part of the prefabricated house, recorded as P′ j , analyze the surface damage degree of each prefabricated component of the prefabricated house ψ j ,

[0032] As a preferred embodiment, the specific setting process of the grayscale value interval of the pixel points corresponding to the damaged area is: based on the known damaged position pictures of each prefabricated component of the prefabricated house, the grayscale image of the damaged position is extracted, and then the grayscale values ​​corresponding to the grayscale images of each damaged position of each prefabricated component of the prefabricated house are compared and statistically obtained The corresponding grayscale interval is then used as the grayscale value interval of the pixel points corresponding to the damaged area of ​​each prefabricated component of the prefabricated house.

[0033] Furthermore, the specific process of screening out unqualified prefabricated parts is: analyzing the quality qualification index ξ of each prefabricated part of the prefabricated house j , Wherein β1 and β2 represent the weights corresponding to the structural integrity and surface damage degree of the set prefabricated part, respectively, and β1+β2=1.

[0034] The quality qualification index of each prefabricated part of the prefabricated house is compared with the preset quality qualification threshold of the prefabricated parts of the prefabricated house. If the quality qualification index of a prefabricated part of the prefabricated house is less than the preset quality qualification threshold of the prefabricated part, the quality of the prefabricated part of the prefabricated house is unqualified, and then the unqualified prefabricated parts are screened out and an early warning is issued.

[0035] As a preferred embodiment, the β1 and β2 can be set to 0.7 and 0.3 respectively. Structural integrity is the core element of the quality of prefabricated parts, which is directly related to the overall structural stability and safety of prefabricated houses. If the structure of the prefabricated parts is incomplete, there may be safety hazards, affecting the service life and safety of the entire house. Although the degree of surface damage has a certain impact on the aesthetics and durability of the prefabricated parts, it does not directly affect the performance of the prefabricated parts as much as the structural integrity. Therefore, the weight corresponding to the structural integrity of the prefabricated parts is greater than the weight corresponding to the degree of surface damage.

[0036] The present invention realizes a multi-angle evaluation of the quality of prefabricated parts by combining dimensional measurement, three-dimensional model comparison and surface damage analysis, thereby improving the accuracy and adequacy of the evaluation. By analyzing the structural integrity and the degree of surface damage of each prefabricated part, it can avoid safety hazards caused by dimensional deviation or structural defects, timely discover and repair potential quality problems, reduce the durability reduction and maintenance cost increase caused by surface damage, and analyze the quality status of the prefabricated parts in real time during the detection process. Once a quality problem is found, an early warning is immediately issued, so that the construction unit can respond quickly and take measures to effectively avoid the accumulation and expansion of quality problems.

[0037] The prefabricated component installation quality analysis module is used to collect the target three-dimensional model of each prefabricated component of the prefabricated house, the installation position of the center point of each prefabricated component, the gap width between each prefabricated component and its adjacent prefabricated component, and the propagation time, amplitude and frequency of the reflected wave of each connection part between each prefabricated component and its adjacent prefabricated component, respectively analyze the position conformity of each prefabricated component of the prefabricated house, the matching degree between adjacent prefabricated components and the tightness index of the connection structure, and then analyze the installation quality qualification index of the prefabricated component

[0038] Furthermore, the analysis of the position conformity of each prefabricated component of the prefabricated house includes: collecting the installation position of the center point of each prefabricated component of the prefabricated house by a total station, substituting it into a three-dimensional coordinate system to obtain the position coordinates of the center point of each prefabricated component of the prefabricated house.

[0039] The standard installation positions of the center points of the prefabricated components of the assembled house are extracted from the database, and substituted into the three-dimensional coordinate system to obtain the standard position coordinates of the center points of the prefabricated components of the assembled house.

[0040] Substitute the position coordinates of the center points of each prefabricated component of the prefabricated house and the standard position coordinates into the distance formula to obtain the distance from the installation position of the center point of each prefabricated component of the prefabricated house to the standard installation position, which is recorded as D j .

[0041] According to the images of various angles of each prefabricated component of the prefabricated house, the target three-dimensional model of each prefabricated component of the prefabricated house is obtained by integration.

[0042] Extract each feature point from the target 3D model and the standard 3D model of each prefabricated part of the prefabricated house, and obtain the deviation distance of each feature point in the target 3D model and the standard 3D model of each prefabricated part of the prefabricated house, which is recorded as K jn , where n represents the number corresponding to the nth feature point, n = 1, 2, 3, ... N.

[0043] Analyze the position conformity of each prefabricated component of the prefabricated house j , Where D0 and K0 and K1 represent the allowable distance difference between the installation position of the prefabricated center point and the standard installation position and the weight corresponding to the distance deviation index, respectively. represents the weights corresponding to the allowable deviation distance and distance deviation index of the feature points in the set three-dimensional model of the prefabricated part and the standard three-dimensional model, respectively, and N represents the total number of feature points.

[0044] As a preferred embodiment, the and They can be set to 0.6 and 0.4 respectively. The installation position of the center point of the prefabricated part directly determines the structural stability and functionality of the entire prefabricated house. If there is a large deviation in the installation position, it may lead to loose connections between prefabricated parts, uneven force, and even cause safety hazards. Although the distance deviation of the feature point does not directly affect the overall structural stability and functionality as the center point installation position deviation, it plays an important role in ensuring the matching degree between the prefabricated parts and the design model, optimizing the construction process and improving construction efficiency. Therefore, the weight corresponding to the distance deviation index from the installation position of the center point of the prefabricated part to the standard installation position is greater than the weight corresponding to the distance deviation index of the feature point in the three-dimensional model of the prefabricated part and the standard three-dimensional model.

[0045] The process of establishing the three-dimensional coordinate system is as follows: extracting the center point position of the prefabricated house from the database, defining the center point position of the prefabricated house as a fixed point as the origin of the three-dimensional coordinate system, setting the three-dimensional coordinate system with the x-axis along the length direction of the prefabricated house, the y-axis along the width direction of the prefabricated house, and the z-axis perpendicular to the surface of the prefabricated house and pointing upward.

[0046] The specific process of obtaining the deviation distance of each feature point in the target three-dimensional model and the standard three-dimensional model of each prefabricated part of the prefabricated house is as follows: each feature point in the target three-dimensional model and the standard three-dimensional model of each prefabricated part of the prefabricated house is substituted into the three-dimensional coordinate system to obtain its three-dimensional coordinate, and each feature point in the target three-dimensional model and the standard three-dimensional model of each prefabricated part of the prefabricated house is matched through model comparison software to obtain corresponding feature point pairs that are successfully matched, and then the pairs are substituted into the distance formula to obtain the deviation distance of each feature point in the target three-dimensional model and the standard three-dimensional model of each prefabricated part of the prefabricated house.

[0047] Furthermore, the matching degree between adjacent prefabricated parts of the prefabricated house includes: measuring the gap width between each monitoring point set on each prefabricated part of the prefabricated house and its adjacent prefabricated part by a feeler gauge, screening out the maximum gap width between each prefabricated part of the prefabricated house and its adjacent prefabricated part, and taking it as the gap width between each prefabricated part of the prefabricated house and its adjacent prefabricated part, recorded as G j .

[0048] Analyze the matching degree of each prefabricated component of the prefabricated house with its adjacent prefabricated componentsγ j , Wherein G0 represents the allowable gap width between a set preform and its adjacent preforms.

[0049] As a preferred embodiment, the specific setting method of the monitoring points is as follows: for common prefabricated parts such as plates, beams, columns, etc., monitoring points can be set at key positions such as their long sides, short sides, diagonals, etc.; for flat prefabricated parts such as wall panels, monitoring points can be set at their four corner points, center points and edges.

[0050] Furthermore, the analysis of the connection structure tightness index of each prefabricated component of the prefabricated house includes: obtaining the propagation time, amplitude and frequency of the reflected wave at each connection position between each prefabricated component of the prefabricated house and its adjacent prefabricated components through ultrasonic detection equipment.

[0051] The predicted propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated component of the assembled house and its adjacent prefabricated components are obtained by finite element analysis software.

[0052] The propagation time, amplitude and frequency of each connection between each prefabricated part of the prefabricated house and its adjacent prefabricated parts are compared with the propagation time, amplitude and frequency of the predicted reflected wave, and the difference between the propagation time, amplitude and frequency of each connection between each prefabricated part of the prefabricated house and its adjacent prefabricated parts and the propagation time, amplitude and frequency of the predicted reflected wave is obtained, which are recorded as and Wherein, i represents the number corresponding to the i-th connection part, i=1,2,3,...I.

[0053] The connection structure tightness index of each prefabricated component of the assembled house j , in and They respectively represent the differences in the allowable propagation time, allowable amplitude and allowable frequency of the reflected wave at the ith connection part of the jth preform, δ1, δ2 and δ3 respectively represent the weights corresponding to the deviation coefficients of the set propagation time, amplitude and frequency of the reflected wave, and δ1+δ2+δ3=1.

[0054] As a preferred embodiment, the weights corresponding to the deviation coefficients of the propagation time, amplitude and frequency of the reflected wave can be set to 0.4, 0.3 and 0.3 respectively. The propagation time is usually an important indicator reflecting the tightness of the connection structure. A longer propagation time may mean that there are larger gaps or loose areas in the connection, which has a more significant impact on the tightness. The amplitude reflects the attenuation degree of ultrasonic energy and is also closely related to the quality of the connection, but its importance may be slightly lower than that of the propagation time. The frequency reflects the characteristics of the material and the state of the connection to a certain extent. Therefore, the weight corresponding to the deviation coefficient of the propagation time of the reflected wave is greater than the weights corresponding to the deviation coefficients of the amplitude and frequency.

[0055] The specific process of obtaining the propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts is: placing an ultrasonic probe on each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts, starting an ultrasonic detection device to emit ultrasonic waves to the detection position, receiving the reflected waves at each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts, and obtaining the propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts.

[0056] The specific process of obtaining the predicted propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts is as follows: a finite element model of each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts is established by finite element analysis software, and the propagation of ultrasonic waves in each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts is simulated, thereby obtaining the predicted propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated part of the prefabricated house and its adjacent prefabricated parts.

[0057] Furthermore, the specific calculation formula for analyzing the installation quality qualification index of the prefabricated parts is: Where J represents the total number of prefabricated parts, κ1, κ2 and κ3 represent the weights corresponding to the set position conformity of prefabricated parts, the matching degree between adjacent prefabricated parts and the tightness index of the connection structure, respectively, and κ1+κ2+κ3=1.

[0058] As a preferred embodiment, the κ1, κ2 and κ3 can be set to 0.4, 0.3 and 0.3 respectively. The position conformity of the prefabricated parts directly determines the overall structural stability and functionality of the prefabricated house. If there is a large deviation in the position of the prefabricated parts, it may lead to problems such as uneven structural force and loose connection, thereby affecting the overall quality. The matching degree between adjacent prefabricated parts determines whether the connection between them is tight and smooth. If the matching degree is not good, it may cause gaps, misalignment and other problems at the connection, affecting the stability and aesthetics of the overall structure. The tightness of the connection structure is the key to ensuring a stable connection between prefabricated parts. If the connection structure is not tight, it may cause safety hazards such as loosening and falling of the prefabricated parts. Therefore, the weight corresponding to the position conformity of the prefabricated parts is greater than the weights corresponding to the matching degree between adjacent prefabricated parts and the tightness index of the connection structure.

[0059] The present invention analyzes multi-angle images of each prefabricated component of the assembled house and combines the installation position data of the center point to evaluate the conformity of the actual installation position of the prefabricated component with the design requirements with high precision, ensuring that the installation error is within a controllable range. During the assembly process, the position conformity, matching degree and tightness of the connection structure of the prefabricated components can be instantly analyzed, and deviations in the installation process can be discovered and corrected in time to avoid subsequent rework and cost increase. In addition, through precise installation quality control, rework and material waste caused by improper installation can be reduced, thereby reducing construction costs.

[0060] The concrete filling quality analysis module is used for the acoustic wave detector to send acoustic waves to each collection point of the concrete and measure the sound velocity and the humidity value of each collection point of each prefabricated part and its adjacent prefabricated parts, respectively analyze the distribution uniformity index of concrete filling and the leakage degree index of concrete filling, and then analyze the quality qualification index θ of concrete filling.

[0061] Furthermore, the analysis of the quality index of concrete filling includes: sending sound waves to each sampling point of the concrete through an acoustic wave detector and measuring the sound velocity to obtain the sound velocity of each sampling point of the concrete, substituting it into an average formula to obtain the average sound velocity of the concrete.

[0062] Substitute the collected sound velocities of concrete and the average sound velocity of concrete into the standard deviation formula to obtain the standard deviation sound velocity of concrete.

[0063] Compare the standard deviation sound velocity of concrete with the average sound velocity, and get the ratio of the standard deviation sound velocity of concrete to the average sound velocity, which is used as the coefficient of variation of the sound velocity of concrete, denoted as s.

[0064] Analyze the distribution uniformity index T of concrete filling, Where s0 represents the reference sound velocity variation coefficient of the set concrete.

[0065] Collecting points are arranged on the contact surface between each prefabricated part and its adjacent prefabricated part, and the humidity values ​​of each collecting point between each prefabricated part and its adjacent prefabricated part are collected by a hygrometer, and the maximum humidity value between each prefabricated part and its adjacent prefabricated part is selected and taken as the humidity value between each prefabricated part and its adjacent prefabricated part, which is recorded as E j .

[0066] Extract the allowable humidity value of each prefabricated part from the database and record it as E′ j .

[0067] Analyze the leakage index B of concrete filling, Where C represents the total number of collection points.

[0068] Analyze the quality index of concrete filling θ, Wherein η1 and η2 represent the weights corresponding to the set distribution uniformity index and leakage degree index of concrete filling, and η1+η2=1.

[0069] As a preferred embodiment, η1 and η2 can be expressed as 0.6 and 0.4 respectively. The uniformity of concrete filling is directly related to its strength, durability and working performance. The leakage degree is an important indicator to measure whether leakage occurs during the concrete filling process. Therefore, the weight corresponding to the distribution uniformity index of concrete filling is greater than the weight corresponding to the leakage degree index.

[0070] The present invention can fully and accurately evaluate multiple key quality indicators of concrete filling through two technical means, namely, acoustic wave detection and humidity measurement. Acoustic wave detection is used to analyze the distribution uniformity of concrete, while humidity measurement is used to detect potential leakage problems. The two complement each other, greatly improving the accuracy and reliability of quality assessment, and can timely discover uneven distribution or leakage problems in the concrete filling process, providing early warning for engineering personnel, helping to take corresponding measures to repair or adjust before the problem worsens, thereby avoiding greater quality problems and economic losses in the later stage.

[0071] The prefabricated housing quality determination module is used to analyze the comprehensive quality qualification index of the prefabricated housing according to the installation quality qualification index of the prefabricated parts and the quality qualification index of the concrete filling, and then determine whether the quality of the prefabricated housing is qualified and issue an early warning.

[0072] Furthermore, the determination of whether the quality of the prefabricated house is qualified includes: analyzing the comprehensive quality index μ of the prefabricated house, Where ε1 represents the weight corresponding to the set prefabricated parts installation quality index, ε2 represents the weight corresponding to the set concrete filling quality index, and ε1+ε2=1.

[0073] The comprehensive quality qualification index of the prefabricated house is compared with the preset comprehensive quality qualification index threshold of the prefabricated house. If the comprehensive quality qualification index of the prefabricated house is less than the preset comprehensive quality qualification index threshold of the prefabricated house, the comprehensive quality of the prefabricated house is unqualified and an early warning is issued.

[0074] As a preferred embodiment, the ε1 and ε2 can be set to 0.6 and 0.4 respectively. The installation quality of prefabricated parts is the core of the quality of prefabricated houses. The installation accuracy and connection firmness of prefabricated parts directly affect the structural stability and safety of the entire house. The quality of concrete filling has an important impact on the overall quality and durability of prefabricated houses. Qualified concrete filling can ensure the stability and durability of the structure and resist damage from various natural and man-made factors. Therefore, the weight corresponding to the installation quality index of prefabricated parts is greater than the weight corresponding to the quality qualification index of concrete filling.

[0075] The present invention is used to analyze the comprehensive quality qualification index of the prefabricated house according to the installation quality qualification index of the prefabricated parts and the quality qualification index of the concrete filling, and then judge whether the quality of the prefabricated house is qualified and issue an early warning. It can fully evaluate the overall quality of the prefabricated house, avoid focusing on only one link and ignoring other key factors, and can find out the weak links in the construction process, further optimize the construction process, improve construction efficiency, reduce construction costs, and issue early warnings in time, which can prevent the problem from expanding and reduce the subsequent maintenance costs.

[0076] Database: used to store the center point position of the prefabricated house, the standard length, width, height of each prefabricated component, the standard installation position of the center point of each prefabricated component, the standard three-dimensional model of each prefabricated component and the allowable humidity value of each prefabricated component.

[0077] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A construction project quality supervision and early warning system based on big data, characterized by: include: Prefabricated parts qualification determination module: used to collect the length, width, height and angle images of each prefabricated part of the prefabricated house, analyze the structural integrity and surface damage degree of each prefabricated part of the prefabricated house, and then analyze the quality qualification index of each prefabricated part of the prefabricated house, screen out unqualified prefabricated parts, and issue early warning; Prefabricated parts installation quality analysis module: used to collect the target three-dimensional model of each prefabricated part of the prefabricated house, the installation position of the center point of each prefabricated part, the gap width between each prefabricated part and its adjacent prefabricated parts, and the propagation time, amplitude and frequency of the reflected wave at each connection part between each prefabricated part and its adjacent prefabricated parts, respectively analyze the position conformity of each prefabricated part of the prefabricated house, the matching degree between adjacent prefabricated parts and the tightness index of the connection structure, and then analyze the installation quality qualification index of the prefabricated parts ; Concrete filling quality analysis module: The acoustic wave detector sends acoustic waves to each collection point of the concrete and measures the sound velocity and the humidity value of each collection point of each prefabricated part and its adjacent prefabricated parts, respectively analyzing the distribution uniformity index of concrete filling and the leakage degree index of concrete filling, and then analyzing the quality qualification index of concrete filling. ; Prefabricated housing quality determination module: used to analyze the comprehensive quality index of prefabricated housing according to the installation quality index of prefabricated parts and the quality index of concrete filling, and then judge whether the quality of prefabricated housing is qualified and issue early warning; Database: used to store the center point position of the prefabricated house, the standard length, width, height of each prefabricated component, the standard installation position of the center point of each prefabricated component, the standard three-dimensional model of each prefabricated component and the allowable humidity value of each prefabricated component; The quality index of concrete filling analysis includes: The sonic wave detector sends sonic waves to each sampling point of the concrete and measures the sound velocity to obtain the sound velocity of each sampling point of the concrete, and substitutes it into the average formula to obtain the average sound velocity of the concrete; Substitute the collected sound velocity of concrete and the average sound velocity of concrete into the standard deviation formula to obtain the standard deviation sound velocity of concrete; The standard deviation sound velocity of concrete is compared with the average sound velocity, and the ratio of the standard deviation sound velocity of concrete to the average sound velocity is obtained, which is used as the coefficient of variation of the sound velocity of concrete, denoted as ; Analyzing the distribution uniformity index of concrete filling , ,in Indicates the reference sound velocity variation coefficient of the set concrete; Collecting points are arranged on the contact surface between each prefabricated part and its adjacent prefabricated part, and the humidity values ​​of each collecting point between each prefabricated part and its adjacent prefabricated part are collected by a hygrometer, and the maximum humidity value between each prefabricated part and its adjacent prefabricated part is selected and taken as the humidity value between each prefabricated part and its adjacent prefabricated part, recorded as , Indicates The number corresponding to each prefabricated component, ; Extract the allowable humidity value of each prefabricated part from the database and record it as ; Analyze the leakage index of concrete filling , ; Analyze the quality index of concrete filling , ,in and represents the weights corresponding to the set distribution uniformity index and leakage degree index of concrete filling, and .

2. The construction engineering quality supervision and early warning system based on big data according to claim 1 is characterized by: The analysis of the structural integrity of each prefabricated component of the prefabricated house includes: Measure the length, width and height of each prefabricated component of the prefabricated house by using a laser rangefinder; Extracting the standard length, width and height of each prefabricated component of the prefabricated house from the database; Subtract the length, width and height of each prefabricated part of the prefabricated house from the length, width and height of the standard, and obtain the difference in length, width and height of each prefabricated part of the prefabricated house, which are recorded as , and ; Analyze the dimensional conformity of each prefabricated component of the prefabricated house , ,in , and Respectively represent the first The allowable difference in length, width and height of each prefabricated part; The camera collects images of various angles of each prefabricated component of the prefabricated house, and integrates them to obtain a three-dimensional model of each prefabricated component of the prefabricated house; Extracting standard three-dimensional models of various prefabricated components of the prefabricated house from the database; The 3D model of each prefabricated component of the prefabricated house is compared with the standard 3D model to obtain the matching degree of the 3D model of each prefabricated component of the prefabricated house, which is recorded as ; Analyze the structural integrity of each prefabricated component of the prefabricated house , ,in and They represent the weights corresponding to the size conformity of the set prefabricated parts and the matching degree of the three-dimensional model, and .

3. The construction engineering quality supervision and early warning system based on big data according to claim 2 is characterized by: The analysis of the degree of surface damage of each prefabricated component of the prefabricated house includes: The color threshold segmentation process is performed on the images of each angle of each prefabricated part of the prefabricated house to obtain the grayscale value of each pixel in the images of each angle of each prefabricated part of the prefabricated house, and the grayscale value of each pixel is compared with the grayscale value interval of the pixel corresponding to the damaged area. If the grayscale value of a pixel belongs to the grayscale value interval of the pixel corresponding to the damaged area, the pixel is marked as a damaged pixel. The number of damaged pixels on the surface of each prefabricated part of the prefabricated house is screened and counted, which is recorded as , and then obtain the total number of pixels on the surface of each prefabricated part of the assembled house, recorded as , analyze the surface damage degree of each prefabricated component of the prefabricated house , .

4. The construction engineering quality supervision and early warning system based on big data according to claim 3 is characterized by: The specific process of screening out unqualified prefabricated parts is as follows: Analyze the quality index of each prefabricated component of prefabricated housing , ,in and They represent the weights corresponding to the structural integrity and surface damage degree of the prefabricated parts, respectively, and ; The quality qualification index of each prefabricated part of the prefabricated house is compared with the preset quality qualification threshold of the prefabricated parts of the prefabricated house. If the quality qualification index of a prefabricated part of the prefabricated house is less than the preset quality qualification threshold of the prefabricated part, the quality of the prefabricated part of the prefabricated house is unqualified, and then the unqualified prefabricated parts are screened out and an early warning is issued.

5. The construction engineering quality supervision and early warning system based on big data according to claim 4 is characterized by: The analysis of the position conformity of each prefabricated component of the prefabricated house includes: The installation positions of the center points of the prefabricated components of the assembled house are collected by a total station, and the installation positions are substituted into a three-dimensional coordinate system to obtain the position coordinates of the center points of the prefabricated components of the assembled house; Extracting the standard installation position of the center point of each prefabricated component of the assembled house from the database, substituting it into the three-dimensional coordinate system to obtain the standard position coordinates of the center point of each prefabricated component of the assembled house; Substitute the position coordinates of the center points of each prefabricated component of the prefabricated house and the standard position coordinates into the distance formula to obtain the distance from the installation position of the center point of each prefabricated component of the prefabricated house to the standard installation position, which is recorded as ; Scanning the prefabricated parts of the assembled house by a laser scanner to obtain a target three-dimensional model of the prefabricated parts of the assembled house; Each feature point is extracted from the target 3D model and the standard 3D model of each prefabricated component of the prefabricated house, and the deviation distance of each feature point in the target 3D model and the standard 3D model of each prefabricated component of the prefabricated house is obtained, which is recorded as ,in Indicates The number corresponding to the feature point, ; Analyze the position conformity of each prefabricated component of the prefabricated house , ,in and They respectively represent the allowable distance difference between the installation position of the set prefabricated component center point and the standard installation position and the weight corresponding to the distance deviation index. and represents the weights corresponding to the allowable deviation distance and distance deviation index of the feature points in the set three-dimensional model of the prefabricated part and the standard three-dimensional model, respectively, and , Indicates the total number of feature points.

6. The construction engineering quality supervision and early warning system based on big data according to claim 5 is characterized by: The matching degree between adjacent prefabricated components of the prefabricated house includes: The gap width between each monitoring point set on each prefabricated part of the prefabricated house and its adjacent prefabricated parts is measured by a feeler gauge, and the maximum gap width between each prefabricated part of the prefabricated house and its adjacent prefabricated parts is selected and used as the gap width between each prefabricated part of the prefabricated house and its adjacent prefabricated parts, recorded as ; Analyze the matching degree between each prefabricated component of the prefabricated house and its adjacent prefabricated components , ,in Indicates the allowable gap width between the set prefab and its adjacent prefabs.

7. The construction engineering quality supervision and early warning system based on big data according to claim 6 is characterized by: The analysis of the connection structure tightness index of each prefabricated component of the prefabricated house includes: The propagation time, amplitude and frequency of the reflected waves at each connection point between each prefabricated component of the prefabricated house and its adjacent prefabricated components are obtained by ultrasonic testing equipment; By using finite element analysis software, the propagation time, amplitude and frequency of the predicted reflected waves at each connection point between each prefabricated component of the prefabricated house and its adjacent prefabricated components are obtained; The propagation time, amplitude and frequency of each connection between each prefabricated part of the prefabricated house and its adjacent prefabricated parts are compared with the propagation time, amplitude and frequency of the predicted reflected wave, and the difference between the propagation time, amplitude and frequency of each connection between each prefabricated part of the prefabricated house and its adjacent prefabricated parts and the propagation time, amplitude and frequency of the predicted reflected wave is obtained, which are recorded as , and ,in Indicates The number corresponding to the connection part, ; The connection structure tightness index of each prefabricated component of the prefabricated house , ,in , and Respectively represent Prefabricated part No. The difference in the allowable propagation time, allowable amplitude and allowable frequency of the reflected wave at each connection point, , and They represent the weights corresponding to the deviation coefficients of the propagation time, amplitude and frequency of the set reflected wave, respectively, and .

8. The construction engineering quality supervision and early warning system based on big data according to claim 7 is characterized by: The specific calculation formula for analyzing the installation quality qualification index of the prefabricated parts is: ,in Indicates the total number of prefabricated parts, , and They represent the weights corresponding to the set prefabricated parts position conformity, the matching degree between adjacent prefabricated parts and the connection structure tightness index, respectively, and .

9. The construction engineering quality supervision and early warning system based on big data according to claim 1 is characterized by: The determination of whether the quality of the prefabricated housing is qualified includes: Analyze the comprehensive quality index of prefabricated housing , ,in Indicates the weight corresponding to the set prefabricated installation quality index, represents the weight corresponding to the set quality index of concrete filling, and ; The comprehensive quality qualification index of the prefabricated house is compared with the preset comprehensive quality qualification index threshold of the prefabricated house. If the comprehensive quality qualification index of the prefabricated house is less than the preset comprehensive quality qualification index threshold of the prefabricated house, the comprehensive quality of the prefabricated house is unqualified and an early warning is issued.

Images