CN112050759A - Intelligent detection and management system for acceptance of construction engineering quality based on big data analysis - Google Patents
Intelligent detection and management system for acceptance of construction engineering quality based on big data analysis Download PDFInfo
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/02—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring thickness
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- G—PHYSICS
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/04—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring contours or curvatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/08—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring roughness or irregularity of surfaces
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06395—Quality analysis or management
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
Abstract
The invention discloses a building engineering quality acceptance intelligent detection management system based on big data analysis, which comprises an outer wall detection point arrangement module, an outer wall structure layer thickness detection module, a storage database, an outer wall structure quality coefficient analysis module, an outer wall flatness analysis module, an outer wall structure detection terminal, a central server and a display terminal, wherein the outer wall structure is detected through the designed outer wall structure detection terminal to obtain outer wall structure parameters, and simultaneously, the outer wall structure quality influence coefficient and the wall flatness coefficient are intelligently analyzed to obtain an outer wall comprehensive quality evaluation coefficient, thereby realizing effective detection of the outer wall quality parameters of a building, being capable of intelligently evaluating the comprehensive quality of the outer wall of the building, simultaneously, the obtained outer wall comprehensive quality evaluation coefficient realizes the quantification of the outer wall of the building, and provides parameter basis for whether the outer wall of the building meets the acceptance requirements or not, the defects in the manual acceptance process mentioned in the background art are avoided.
Description
Technical Field
The invention belongs to the technical field of acceptance management of constructional engineering, and particularly relates to an intelligent detection and management system for quality acceptance of constructional engineering based on big data analysis.
Background
Along with the development of economy in recent years, more and more people choose to settle in cities, the rapid development of the urban residential building industry is stimulated to a great extent, a large amount of building construction exists in each area of the city, the acceptance of the quality of the building engineering is an important link of the construction of the building engineering, the important role of the acceptance of the quality of the building engineering in the construction of the building engineering is mainly reflected in the aspect of ensuring the quality of the engineering and providing engineering data, and the acceptance accuracy of the acceptance link of the quality of the building engineering not only influences the production and operation activities and the daily life of people, but also influences the safety of lives and properties of people.
The current work of checking and accepting the quality of the building engineering is basically that checking and accepting personnel detect all parameters of the outer wall of the building engineering by adopting corresponding instruments so as to evaluate whether all the parameters meet the checking and accepting requirements, and then manually evaluate the quality qualification of the outer wall of the building according to all the parameters of the obtained outer wall, wherein the checking and accepting method has the following defects:
1. in the detection process, a plurality of instruments are used for detection, so that the equipment cost is high, and some instruments may damage the outer wall in the detection process;
2. the obtained parameters of the exterior wall of the building project only reflect whether the corresponding parameters meet the acceptance requirements or not, and the comprehensive quality of the exterior wall cannot be evaluated.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides an intelligent detection and management system for checking and accepting the quality of the building engineering based on big data analysis for a building outer wall.
The purpose of the invention can be realized by the following technical scheme:
an intelligent detection and management system for quality acceptance of building engineering based on big data analysis comprises an outer wall detection point arrangement module, an outer wall structure layer thickness detection module, a storage database, an outer wall structure quality coefficient analysis module, an outer wall flatness analysis module, an outer wall structure detection terminal, a central server and a display terminal, wherein the outer wall structure layer thickness detection module is respectively connected with the outer wall detection point arrangement module, the outer wall flatness analysis module and the outer wall structure quality coefficient analysis module;
the outer wall detection point arrangement module is used for uniformly arranging detection points on the horizontal side and the vertical side of the outer wall of the building to be detected, and a plurality of horizontal detection points arranged on the horizontal side of the outer wall of the building are marked in sequence from one end of the horizontal side to the other end of the outer wall, wherein the horizontal detection points are marked as l1, l2, …, li, … and ln; marking a plurality of vertical detection points arranged on the vertical side of the building from one end of the vertical side of the outer wall close to the ground to the other end in sequence, wherein the vertical detection points are marked as h1, h2, …, hj, … and hm in sequence;
the outer wall structure layer thickness detection module is used for detecting the structure layer thickness of each detection point through an outer wall structure detection terminal for divided horizontal detection points and vertical monitoring points, and the detection steps are as follows:
s1: an X-ray detector is arranged in the outer wall structure detection terminal, the X-ray detector in the detection terminal emits X-rays to the detection points to be detected by moving the outer wall structure detection device to the detection points, and the emitted rays penetrate through the outer wall and are imaged and recorded by a ray film to obtain the outer wall film of each detection point;
s2: putting the obtained radiographic film into a darkroom for processing to obtain the outer wall radiographic film of each detection point;
s3: according to the difference of gray values displayed in the ray negative by each structural layer of the internal structure of the outer wall, the distribution area of each structural layer of the outer wall can be distinguished from the obtained ray negative of each detection point of the outer wall, and the distribution area profile is identified according to the identified distribution area of each structural layer;
s4: the identified distribution area contour of each structural layer of the outer wall is used as a boundary between the structural layers, the thickness of each structural layer is obtained according to the distribution area contour of each structural layer, the thickness of each structural layer of each obtained detection point forms a detection point structural layer thickness set, wherein the thickness set of the detection point structural layers of the horizontal detection points is Tsl(tsl1,tsl2,...,tsli,...,tsln)，tsli is the thickness of the s-th structural layer of the li-th horizontal detection point, and the thickness of the detection point structural layers of the vertical detection points is tsh(tsh1,tsh2,...,tshj,...,tshm)，tshj represents the thickness of the s structural layer of the hj vertical detection point, s represents the structural layer, s is sw, sp, sm, sw, sp and sm represent the heat preservation layer, the waterproof layer and the coating layer respectively, and the obtained thickness set of the structural layer of the detection point is sent to the outer wall structure quality coefficient analysis module and the outer wall flatness analysis module respectively;
the outer wall structure quality coefficient analysis module receives the detection point structure layer thickness set sent by the outer wall structure layer thickness detection module, carries out mean value calculation on thickness values detected by different horizontal detection points corresponding to the same structure layer in the detection point structure layer thickness set of the horizontal detection points to obtain the thickness mean value of each structure layer on the horizontal side of the outer wall, and records the thickness mean value as the thickness mean value of each structure layer on the horizontal side of the outer wall
Comparing the thickness standard values of the structural layers on the horizontal side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the horizontal side of the outer wall; correspondingly, the outer wall structure quality coefficient analysis module calculates the mean value of the thickness values detected by different vertical detection points corresponding to the same structural layer in the thickness set of the detection point structural layers of the vertical detection points to obtain the thickness mean value of each structural layer at the vertical side of the outer wall, and the thickness mean values are respectively recorded as
Comparing the thickness standard values of the structural layers on the vertical side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the vertical side of the outer wall; according to the obtained thickness contrast value of each structural layer on the horizontal side of the outer wall and the thickness contrast value of each structural layer on the vertical side of the outer wall, counting the quality influence coefficient of the outer wall structure, and sending the quality influence coefficient to a central server;
outer wall roughness analysis module receives outer wall structural layer thickness detection moduleThe thickness of each structural layer of each horizontal detection point in the detection point structural layer thickness set of the horizontal detection points is accumulated to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of each horizontal detection point forms a horizontal detection point outer wall total thickness set TGeneral assemblyl(tGeneral assemblyl1,tGeneral assemblyl2,...,tGeneral assemblyli,...,tGeneral assemblyln); similarly, the outer wall flatness analysis module accumulates the thicknesses of the structural layers of each vertical detection point in the detection point structural layer thickness set of the vertical detection points to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of each vertical detection point forms a vertical detection point outer wall total thickness set TGeneral assemblyh(tGeneral assemblyh1,tGeneral assemblyh2,...,tGeneral assemblyhj,...,tGeneral assemblyhm)；
Meanwhile, the outer wall flatness analysis module extracts the standard total thickness of the horizontal side and the standard total thickness of the vertical side of the outer wall stored in the storage database, compares the acquired total thickness set of the outer wall of the horizontal detection point and the acquired total thickness set of the outer wall of the vertical detection point with the corresponding standard values respectively to obtain a total thickness comparison difference value set delta of the outer wall of the horizontal detection pointGeneral assemblyl(ΔtGeneral assemblyl1,ΔtGeneral assemblyl2,...,ΔtGeneral assemblyli,...,ΔtGeneral assemblyln) and vertical detection point outer wall total thickness contrast difference value set delta TGeneral assemblyh(ΔtGeneral assemblyh1,ΔtGeneral assemblyh2,...,ΔtGeneral assemblyhj,...,ΔtGeneral assemblyhm), respectively counting the flatness coefficient of the horizontal side wall surface and the flatness coefficient of the vertical side wall surface of the outer wall according to the obtained comparison difference set of the total thickness of the outer wall, and sending the coefficients to a central server;
the storage database stores the thickness standard values of all structural layers on the horizontal side of the outer wall and the thickness standard values of all structural layers on the vertical side of the outer wall, and stores the standard total thickness of the horizontal side of the outer wall and the standard total thickness of the vertical side of the outer wall, wherein each structural layer of the wall surface comprises a heat preservation layer, a waterproof layer and a coating layer, and stores an outer wall structure quality correction coefficient, an outer wall horizontal side wall surface flatness correction coefficient and an outer wall vertical side wall surface flatness correction coefficient;
the central server receives the outer wall structure quality influence coefficient sent by the outer wall structure quality coefficient analysis module, the outer wall horizontal side wall surface flatness coefficient and the vertical side wall surface flatness coefficient sent by the outer wall flatness analysis module respectively, counts the outer wall comprehensive quality evaluation coefficient and sends the outer wall comprehensive quality evaluation coefficient to the display terminal;
and the display terminal receives and displays the comprehensive quality evaluation coefficient of the outer wall sent by the central server.
Furthermore, the horizontal detection points of the outer wall are arranged by dividing the horizontal distance L of the horizontal side of the outer wall into a plurality of horizontal sections according to the preset horizontal detection point distance intervals, and each horizontal detection point is respectively arranged at the end point position of each horizontal section.
Further, the thickness average value calculation formula of each structural layer on the horizontal side of the outer wall is
In the formula, tsli is the thickness of the s structural layer of the li horizontal detection point, and the thickness mean value calculation formula of each structural layer at the vertical side of the outer wall is
tshj denotes the thickness of the s-th structural layer of the hj-th vertical detection point, where s ═ sw, sp, sm.
Further, the calculation formula of the external wall structure quality influence coefficient is
Respectively expressed as the average thickness of the heat-insulating layer, the waterproof layer and the coating layer on the horizontal side of the outer wall,
are respectively shown as outerAverage thickness of insulating layer, waterproof layer and coating layer on vertical side of wall, Tsw0l、Tsp0l、Tsm0l is respectively expressed as the standard thickness of the horizontal side heat-insulating layer, the waterproof layer and the coating layer of the outer wall, Tsw0h、Tsp0h、Tsm0h is respectively expressed as the standard thickness of the heat-insulating layer, the waterproof layer and the coating layer on the vertical side of the outer wall.
Further, the calculation formula of the flatness coefficient of the horizontal side wall surface of the outer wall is
ΔtGeneral assemblyli is expressed as the difference between the total thickness of the outer wall at the li-th horizontal detection point and the standard total thickness of the outer wall at the horizontal side of the outer wall, tGeneral assemblyli represents the total thickness of the outer wall at the li-th horizontal detection point.
Further, the calculation formula of the flatness coefficient of the vertical side wall surface of the outer wall is
ΔtGeneral assemblyhj is the difference between the total thickness of the outer wall at the hj-th vertical detection point and the standard total thickness of the outer wall at the vertical side of the outer wall, and tGeneral assemblyhj represents the total thickness of the outer wall at the hj-th vertical detection point.
Further, the calculation formula of the comprehensive quality evaluation coefficient of the outer wall is
Formula (III) A, Bl、BhRespectively expressed as an outer wall structure quality correction coefficient, an outer wall horizontal side wall surface evenness correction coefficient and an outer wall vertical side wall surface evenness correction coefficient, wherein eta is expressed as an outer wall structure quality influence coefficient, and sigma is expressed as an outer wall structure quality influence coefficientlExpressed as the flatness coefficient of the horizontal side wall surface of the outer wall, sigmahExpressed as the flatness coefficient of the vertical side wall surface of the outer wall.
Further, outer wall structure test terminal includes motor, rolling dish, haulage wire rope, locomotive, leading pulley and detects the car, the motor passes through motor support mounting on the left support of locomotive, and the output shaft of motor is connected with the rolling dish, and haulage wire rope one end is fixed on the rolling dish, and the wire rope other end passes the inside chamber way and the leading pulley of locomotive in proper order and detects car looks fixed connection, and leading pulley installs on the support on removal side right side, detects the car and presses close to mutually with waiting to detect the building outer wall face.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the invention, the detection points of the building outer wall to be detected are arranged through the outer wall detection point arrangement module, the outer wall structure of each detection point is detected by adopting the outer wall structure detection terminal, the thickness and the total thickness of each structural layer of the outer wall of each detection point are obtained, meanwhile, the outer wall structure quality influence coefficient and the wall surface flatness coefficient are intelligently analyzed, and further, the outer wall comprehensive quality evaluation coefficient is obtained, so that the effective detection of the quality parameters of the building outer wall is realized, the comprehensive quality of the building outer wall can be intelligently evaluated, meanwhile, the obtained outer wall comprehensive quality evaluation coefficient can quantify the quality condition of the building outer wall, a parameter basis is provided for whether the building outer wall meets the acceptance requirement, and the defects in the manual acceptance process mentioned in the background art are avoided.
(2) According to the invention, the plurality of detection points are distributed on the outer wall of the building to be detected, and the thickness detection of the outer wall structure is respectively carried out on each detection point, so that the detection error caused by a single detection point is avoided, the detected data is more consistent with the real numerical value, and effective data support is provided for the subsequent statistics of the quality influence coefficient of the outer wall structure.
(3) According to the invention, the outer wall structure detection terminal is designed, the moving distance of the outer wall structure detection terminal is adjusted according to the distance between adjacent detection points, and the outer wall structure detection terminal is moved to the corresponding detection point position to carry out outer wall structure detection on the detection point.
(4) According to the invention, the X-ray detector is arranged in the outer wall structure detection terminal, and the X-ray detector is emitted to each detection point to obtain the outer wall structure thickness of each detection point, so that the outer wall is not damaged in the detection process, and the obtained ray negative can accurately reflect the structural characteristics of the outer wall, thereby facilitating the visual understanding of the acceptance staff.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be derived on the basis of these drawings without inventive effort.
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a schematic diagram of the internal structural layers of the exterior wall of the present invention.
Fig. 3 is a front view of the structure of the outer wall structure detection terminal of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, an intelligent detection and management system for quality acceptance of construction engineering based on big data analysis comprises an outer wall detection point arrangement module, an outer wall structure layer thickness detection module, an outer wall structure quality coefficient analysis module, a storage database, an outer wall flatness analysis module, an outer wall structure detection terminal, a central server and a display terminal, wherein the outer wall structure layer thickness detection module is respectively connected with the outer wall detection point arrangement module, the outer wall flatness analysis module and the outer wall structure quality coefficient analysis module, the central server is respectively connected with the outer wall structure quality coefficient analysis module and the outer wall flatness analysis module, and the display terminal is connected with the central server.
The outer wall detection point arrangement module is used for dividing the outer wall of the building to be detected into a plurality of horizontal sides and a plurality of vertical sides according to a planar gridding mode, and uniformly arranging detection points on each horizontal side and each vertical side, the outer wall horizontal detection point arrangement method is characterized in that the horizontal distance L of each horizontal side of the outer wall is divided into a plurality of horizontal sections according to the preset horizontal detection point distance interval, each horizontal detection point of each horizontal side is respectively arranged at the end point position of each horizontal section, the plurality of horizontal detection points arranged on each horizontal side of the outer wall of the building are marked in sequence from one end of the horizontal side of the outer wall to the other end of the outer wall, and the horizontal detection points are marked as L1, L2, …, li, … and ln in sequence; the method for arranging the vertical detection points of the outer wall comprises the steps of dividing the vertical distance H of each vertical side of the outer wall into a plurality of vertical sections according to the preset vertical detection point distance intervals, respectively arranging each vertical detection point of each vertical side at the end point position of each vertical section, marking the plurality of vertical detection points of each vertical side arranged on the vertical side of the building according to the sequence from one end, close to the ground, of the outer wall to the other end, and sequentially marking the vertical detection points as H1, H2, …, hj, … and hm, wherein the smaller the distance interval value between the horizontal detection point distance interval and the vertical detection point distance interval is, the more detection points are obtained, the more corresponding detection data are obtained, and the reliability of the finally obtained quality coefficient is higher.
In the preferred embodiment, the detection points are distributed on the building outer wall to be detected, the outer wall structure thickness detection is respectively carried out on each detection point, the detection error caused by a single detection point is avoided, the detected data are more consistent with real numerical values, and effective data support is provided for the subsequent statistics of the outer wall structure quality influence coefficient.
The outer wall structure layer thickness detection module is used for detecting the structure layer thickness of each detection point through an outer wall structure detection terminal for divided horizontal detection points and vertical monitoring points, and the detection steps are as follows:
s1: an X-ray detector is arranged in the outer wall structure detection terminal, the X-ray detector in the detection terminal emits X-rays to the detection points to be detected by moving the outer wall structure detection device to the detection points, and the emitted rays penetrate through the outer wall and are imaged and recorded by a ray film to obtain the outer wall film of each detection point;
s2: putting the obtained radiographic film into a darkroom for processing to obtain the outer wall radiographic film of each detection point;
s3: according to the difference of gray values displayed in the ray negative by each structural layer of the internal structure of the outer wall, the distribution area of each structural layer of the outer wall can be distinguished from the obtained ray negative of each detection point of the outer wall, and the distribution area profile is identified according to the identified distribution area of each structural layer;
s4: the identified distribution area contour of each structural layer of the outer wall is used as a boundary between the structural layers, the thickness of each structural layer is obtained according to the distribution area contour of each structural layer, the thickness of each structural layer of each obtained detection point forms a detection point structural layer thickness set, and the thickness set of the detection point structural layers of the horizontal detection points at each horizontal side is Ts il(ts il1,ts il2,...,ts ilk,...,ts ilp)，ts ilk represents the thickness of the s structural layer of the li horizontal detection point, and the thickness of the detection point structural layers of the vertical detection point is ts jh(ts jh1,ts jh2,...,ts jhf,...,ts jhq)，ts jhf represents the thickness of the s-th structural layer of the hj-th vertical detection point, s represents a structural layer, s is sw, sp, sm, sw, sp and sm respectively represent a heat preservation layer, a waterproof layer and a coating layer, and the obtained thickness set of the structural layer of the detection point is respectively sent to an outer wall structure quality coefficient analysis module and an outer wall flatness analysis module.
According to the preferred embodiment, the characteristics of high sensitivity and no destructiveness of the X-ray detector are utilized, the X-ray is emitted to each detection point to obtain the outer wall structure thickness of each detection point, relevant data are provided for the quality coefficient analysis and the flatness analysis of the outer wall structure, the obtained ray film can accurately reflect the structural characteristics of the outer wall, and the ray film is convenient for the acceptance staff to visually know.
The outer wall structure quality coefficient analysis module receives a detection point structure layer thickness set sent by the outer wall structure layer thickness detection module, and for the same node in the detection point structure layer thickness set of the horizontal detection pointThe thickness values detected by different horizontal detection points corresponding to the structural layers are subjected to mean value calculation, and the thickness mean value calculation formula of each structural layer on the horizontal side of the outer wall is
In the formula tsli is the thickness of the s structural layer of the li horizontal detection point to obtain the thickness average value of each structural layer at the horizontal side of the outer wall, s is sw, sp, sm, and the thickness average value of the heat-insulating layer, the thickness average value of the waterproof layer and the thickness average value of the coating layer at the horizontal side of the outer wall are respectively recorded as
Comparing the thickness standard values of the structural layers on the horizontal side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the horizontal side of the outer wall; correspondingly, the outer wall structure quality coefficient analysis module calculates the mean value of the thickness values detected by different vertical detection points corresponding to the same structural layer in the thickness set of the detection point structural layers of the vertical detection points to obtain the thickness mean value of each structural layer at the vertical side of the outer wall, and the calculation formula of the thickness mean value of each structural layer at the vertical side of the outer wall is
tshj is the thickness of the s structural layer of the hj vertical detection point, and the obtained thickness mean value of the heat-insulating layer, the waterproof layer and the coating layer on the vertical side of the outer wall are respectively recorded as
Comparing the thickness standard values of the structural layers on the vertical side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the vertical side of the outer wall; according to the obtained thickness contrast value of each structural layer on the horizontal side and the thickness contrast value of each structural layer on the vertical side of the outer wall, the influence coefficient of the quality of the outer wall structure is counted
The outer wall flatness analysis module receives the detection point structure layer thickness set sent by the outer wall structure layer thickness detection module, the thickness of each structure layer of each horizontal detection point in the detection point structure layer thickness set of the horizontal detection points is accumulated to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of each horizontal detection point forms a horizontal detection point outer wall total thickness set TGeneral assemblyl(tGeneral assemblyl1,tGeneral assemblyl2,...,tGeneral assemblyli,...,tGeneral assemblyln); similarly, the outer wall flatness analysis module accumulates the thicknesses of the structural layers of each vertical detection point in the detection point structural layer thickness set of the vertical detection points to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of each vertical detection point forms a vertical detection point outer wall total thickness set TGeneral assemblyh(tGeneral assemblyh1,tGeneral assemblyh2,...,tGeneral assemblyhj,...,tGeneral assemblyhm)；
Meanwhile, the outer wall flatness analysis module extracts the standard total thickness of the horizontal side and the standard total thickness of the vertical side of the outer wall stored in the storage database, compares the acquired total thickness set of the outer wall of the horizontal detection point and the acquired total thickness set of the outer wall of the vertical detection point with the corresponding standard values respectively to obtain a total thickness comparison difference value set delta of the outer wall of the horizontal detection pointGeneral assemblyl(ΔtGeneral assemblyl1,ΔtGeneral assemblyl2,...,ΔtGeneral assemblyli,...,ΔtGeneral assemblyln) and vertical detection point outer wall total thickness contrast difference value set delta TGeneral assemblyh(ΔtGeneral assemblyh1,ΔtGeneral assemblyh2,...,ΔtGeneral assemblyhj,...,ΔtGeneral assemblyhm) respectively counting the flatness coefficients of the horizontal side walls of the outer wall according to the obtained total thickness contrast difference set of the outer wall
ΔtGeneral assemblyli is expressed as the difference between the total thickness of the outer wall at the li-th horizontal detection point and the standard total thickness of the outer wall at the horizontal side of the outer wall, tGeneral assemblyli represents the total thickness of the outer wall at the li-th horizontal detection point and the flatness coefficient of the vertical side wall surface
ΔtGeneral assemblyhj is the difference between the total thickness of the outer wall at the hj-th vertical detection point and the standard total thickness of the outer wall at the vertical side of the outer wall, and tGeneral assemblyhj is the total thickness of the outer wall of the hj-th vertical detection point, the counted flatness coefficient of the horizontal side wall surface of the outer wall and the flatness coefficient of the vertical side wall surface provide relevant coefficients for the subsequent comprehensive quality evaluation of the outer wall, and the outer wall flatness analysis module sends the counted flatness coefficient of the horizontal side wall surface of the outer wall and the calculated flatness coefficient of the vertical side wall surface of the outer wall to the central server.
The storage database stores the thickness standard values of all structural layers on the horizontal side of the outer wall and the thickness standard values of all structural layers on the vertical side of the outer wall, stores the standard total thickness of the horizontal side of the outer wall and the standard total thickness of the vertical side of the outer wall, wherein each structural layer of the wall surface comprises a heat preservation layer, a waterproof layer and a coating layer, and stores the structural quality correction coefficient of the outer wall, the horizontal side wall surface flatness correction coefficient of the outer wall and the vertical side wall surface flatness correction coefficient of the outer wall.
The central server respectively receives the outer wall structure quality influence coefficient sent by the outer wall structure quality coefficient analysis module, the outer wall horizontal side wall surface flatness coefficient and the vertical side wall surface flatness coefficient sent by the outer wall flatness analysis module, and counts the outer wall comprehensive quality evaluation coefficient
Formula (III) A, Bl、BhRespectively expressed as an outer wall structure quality correction coefficient, an outer wall horizontal side wall surface evenness correction coefficient and an outer wall vertical side wall surface evenness correction coefficient, wherein eta is expressed as an outer wall structure quality influence coefficient, and sigma is expressed as an outer wall structure quality influence coefficientlExpressed as the flatness coefficient of the horizontal side wall surface of the outer wall, sigmahThe evaluation coefficient is expressed as an outer wall vertical side wall surface flatness coefficient, the higher the outer wall comprehensive quality evaluation coefficient is, the higher the quality of outer wall construction is, when the acceptance requirement value of the outer wall comprehensive quality evaluation coefficient is reached, the outer wall meets the acceptance requirement, and the central server sends the statistical outer wall comprehensive quality evaluation coefficient to the display terminal.
The display terminal receives the comprehensive quality evaluation coefficient of the outer wall sent by the central server and displays the comprehensive quality evaluation coefficient, so that the acceptance personnel can visually know the comprehensive quality of the outer wall to be accepted, and a reference basis is provided for judging whether the outer wall meets the acceptance requirements.
Referring to fig. 3, outer wall structure test terminal includes motor 1, rolling disc 2, traction wire rope 3, locomotive 4, guide pulley 5 and detects car 6, motor 1 passes through motor support mounting on the left support of locomotive 4, and the output shaft of motor 1 is connected with the one end of rolling disc 2, and 3 one ends of traction wire rope are fixed on rolling disc 2, and the 3 other ends of traction wire rope pass the inside chamber way and guide pulley 5 of locomotive 4 in proper order and detect car 6 looks fixed connection, and guide pulley 5 installs on the support on locomotive 4 right side, detects car 6 and presses close to mutually with the building outer wall face that waits to detect.
In the detection process, the motor 1 is started, the motor 1 rotates forwards to drive the steel wire rope 3 wound on the winding disc 2 to rotate so as to control the other end of the winding disc 2 to unwind the steel wire rope 3, the detection vehicle 6 is pulled to move downwards to each vertical detection point by the unfolded steel wire rope 3 sequentially passing through the interior of the moving vehicle 4 and the guide pulley 5, when the pulled detection vehicle 6 is found not to be at the target detection point position, if the pulled detection vehicle is lower than the target detection point position, the motor 1 is controlled to rotate reversely, so that the winding disc 2 continuously winds the steel wire rope 3, the detection vehicle 6 is continuously pulled up until the steel wire rope is pulled up to the position of the target detection point, if the steel wire rope is higher than the position of the target detection point, the motor 1 is controlled to rotate forwards, so that the rolling disc 2 expands the steel wire rope 3 to promote the detection vehicle 6 to be pulled down continuously until the detection vehicle is pulled down to the position of a target detection point, when the horizontal detection points are required to be detected, the whole detection terminal of the outer wall structure is moved to the position of each horizontal detection point.
According to the preferred embodiment, the outer wall structure detection terminal is designed, the moving distance of the outer wall structure detection terminal is adjusted according to the distance between the adjacent detection points, the outer wall structure detection terminal is moved to the corresponding detection point position to detect the outer wall structure of the detection point, the whole process is simple to operate, the detection point can accurately reach the detection point positions, meanwhile, the thickness of each structural layer of the obtained detection point provides relevant data for the quality coefficient analysis and the flatness analysis of the outer wall structure, and the cost of a detection instrument is reduced.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (8)
1. The utility model provides a building engineering quality inspection intelligent detection management system based on big data analysis which characterized in that: the system comprises an outer wall detection point arrangement module, an outer wall structure layer thickness detection module, a storage database, an outer wall structure quality coefficient analysis module, an outer wall flatness analysis module, an outer wall structure detection terminal, a central server and a display terminal, wherein the outer wall structure layer thickness detection module is respectively connected with the outer wall detection point arrangement module, the outer wall flatness analysis module and the outer wall structure quality coefficient analysis module;
the outer wall detection point arrangement module is used for uniformly arranging detection points on the horizontal side and the vertical side of the outer wall of the building to be detected, and a plurality of horizontal detection points arranged on the horizontal side of the outer wall of the building are marked in sequence from one end of the horizontal side to the other end of the outer wall, wherein the horizontal detection points are marked as l1, l2, …, li, … and ln; marking a plurality of vertical detection points arranged on the vertical side of the building from one end of the vertical side of the outer wall close to the ground to the other end in sequence, wherein the vertical detection points are marked as h1, h2, …, hj, … and hm in sequence;
the outer wall structure layer thickness detection module is used for detecting the structure layer thickness of each detection point through an outer wall structure detection terminal for divided horizontal detection points and vertical monitoring points, and the detection steps are as follows:
s1: an X-ray detector is arranged in the outer wall structure detection terminal, the X-ray detector in the detection terminal emits X-rays to the detection points to be detected by moving the outer wall structure detection device to the detection points, and the emitted rays penetrate through the outer wall and are imaged and recorded by a ray film to obtain the outer wall film of each detection point;
s2: putting the obtained radiographic film into a darkroom for processing to obtain the outer wall radiographic film of each detection point;
s3: according to the difference of gray values displayed in the ray negative by each structural layer of the internal structure of the outer wall, the distribution area of each structural layer of the outer wall can be distinguished from the obtained ray negative of each detection point of the outer wall, and the distribution area profile is identified according to the identified distribution area of each structural layer;
s4: the identified distribution area contour of each structural layer of the outer wall is used as a boundary between the structural layers, the thickness of each structural layer is obtained according to the distribution area contour of each structural layer, the thickness of each structural layer of each obtained detection point forms a detection point structural layer thickness set, wherein the thickness set of the detection point structural layers of the horizontal detection points is Tsl(tsl1,tsl2,...,tsli,...,tsln)，tsli is the thickness of the s-th structural layer of the li-th horizontal detection point, and the thickness of the detection point structural layers of the vertical detection points is tsh(tsh1,tsh2,...,tshj,...,tshm)，tshj represents the thickness of the s-th structural layer of the hj-th vertical detection point, s represents the structural layer, and s ═ sw, sp, sm, sw, sp, sm respectively represent the heat preservation layer, the waterproof layer and the coating layerRespectively sending the acquired thickness set of the detection point structure layer to an outer wall structure quality coefficient analysis module and an outer wall flatness analysis module;
the outer wall structure quality coefficient analysis module receives the detection point structure layer thickness set sent by the outer wall structure layer thickness detection module, carries out mean value calculation on thickness values detected by different horizontal detection points corresponding to the same structure layer in the detection point structure layer thickness set of the horizontal detection points to obtain the thickness mean value of each structure layer on the horizontal side of the outer wall, and records the thickness mean value as the thickness mean value of each structure layer on the horizontal side of the outer wall
Comparing the thickness standard values of the structural layers on the horizontal side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the horizontal side of the outer wall; correspondingly, the outer wall structure quality coefficient analysis module calculates the mean value of the thickness values detected by different vertical detection points corresponding to the same structural layer in the thickness set of the detection point structural layers of the vertical detection points to obtain the thickness mean value of each structural layer at the vertical side of the outer wall, and the thickness mean values are respectively recorded as
Comparing the thickness standard values of the structural layers on the vertical side of the outer wall in the storage database to obtain thickness comparison values of the structural layers on the vertical side of the outer wall; according to the obtained thickness contrast value of each structural layer on the horizontal side of the outer wall and the thickness contrast value of each structural layer on the vertical side of the outer wall, counting the quality influence coefficient of the outer wall structure, and sending the quality influence coefficient to a central server;
the outer wall flatness analysis module receives the detection point structure layer thickness set sent by the outer wall structure layer thickness detection module, the thickness of each structure layer of each horizontal detection point in the detection point structure layer thickness set of the horizontal detection points is accumulated to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of each horizontal detection point forms a horizontal detection point outer wall total thickness set TGeneral assemblyl(tGeneral assemblyl1,tGeneral assemblyl2,...,tGeneral assemblyli,...,tGeneral assemblyln); similarly, the outer wall flatness analysis module collects the thickness of each detection point structure layer of the vertical detection pointsThe thicknesses of all structural layers of the vertical detection points are accumulated to obtain the total thickness of the outer wall, and the obtained total thickness of the outer wall of all the vertical detection points forms a total thickness set T of the outer wall of the vertical detection pointsGeneral assemblyh(tGeneral assemblyh1,tGeneral assemblyh2,...,tGeneral assemblyhj,...,tGeneral assemblyhm)；
Meanwhile, the outer wall flatness analysis module extracts the standard total thickness of the horizontal side and the standard total thickness of the vertical side of the outer wall stored in the storage database, compares the acquired total thickness set of the outer wall of the horizontal detection point and the acquired total thickness set of the outer wall of the vertical detection point with the corresponding standard values respectively to obtain a total thickness comparison difference value set delta of the outer wall of the horizontal detection pointGeneral assemblyl(ΔtGeneral assemblyl1,ΔtGeneral assemblyl2,...,ΔtGeneral assemblyli,...,ΔtGeneral assemblyln) and vertical detection point outer wall total thickness contrast difference value set delta TGeneral assemblyh(ΔtGeneral assemblyh1,ΔtGeneral assemblyh2,...,ΔtGeneral assemblyhj,...,ΔtGeneral assemblyhm), respectively counting the flatness coefficient of the horizontal side wall surface and the flatness coefficient of the vertical side wall surface of the outer wall according to the obtained comparison difference set of the total thickness of the outer wall, and sending the coefficients to a central server;
the storage database stores the thickness standard values of all structural layers on the horizontal side of the outer wall and the thickness standard values of all structural layers on the vertical side of the outer wall, and stores the standard total thickness of the horizontal side of the outer wall and the standard total thickness of the vertical side of the outer wall, wherein each structural layer of the wall surface comprises a heat preservation layer, a waterproof layer and a coating layer, and stores an outer wall structure quality correction coefficient, an outer wall horizontal side wall surface flatness correction coefficient and an outer wall vertical side wall surface flatness correction coefficient;
the central server receives the outer wall structure quality influence coefficient sent by the outer wall structure quality coefficient analysis module, the outer wall horizontal side wall surface flatness coefficient and the vertical side wall surface flatness coefficient sent by the outer wall flatness analysis module respectively, counts the outer wall comprehensive quality evaluation coefficient and sends the outer wall comprehensive quality evaluation coefficient to the display terminal;
and the display terminal receives and displays the comprehensive quality evaluation coefficient of the outer wall sent by the central server.
2. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the method for arranging the horizontal detection points of the outer wall comprises the steps of dividing the horizontal distance L of the horizontal side of the outer wall into a plurality of horizontal sections according to the preset horizontal detection point distance intervals, respectively arranging each horizontal detection point at the end point position of each horizontal section, and dividing the vertical distance H of the vertical side of the outer wall into a plurality of vertical sections according to the preset vertical detection point distance intervals, and respectively arranging each vertical detection point at the end point position of each vertical section.
3. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the thickness average value calculation formula of each structural layer on the horizontal side of the outer wall is
In the formula tsli is the thickness of the s structural layer of the li horizontal detection point, and the thickness mean value calculation formula of each structural layer at the vertical side of the outer wall is
tshj denotes the thickness of the s-th structural layer of the hj-th vertical detection point, where s ═ sw, sp, sm.
4. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the calculation formula of the external wall structure quality influence coefficient is
5. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the calculation formula of the flatness coefficient of the horizontal side wall surface of the outer wall is
ΔtGeneral assemblyli is expressed as the difference between the total thickness of the outer wall at the li-th horizontal detection point and the standard total thickness of the outer wall at the horizontal side of the outer wall, tGeneral assemblyli represents the total thickness of the outer wall at the li-th horizontal detection point.
6. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the calculation formula of the flatness coefficient of the vertical side wall surface of the outer wall is
ΔtGeneral assemblyhj is the difference between the total thickness of the outer wall at the hj-th vertical detection point and the standard total thickness of the outer wall at the vertical side of the outer wall, and tGeneral assemblyhj represents the total thickness of the outer wall at the hj-th vertical detection point.
7. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the calculation formula of the comprehensive quality evaluation coefficient of the outer wall is
Formula (III) A, Bl、BhRespectively expressed as an outer wall structure quality correction coefficient, an outer wall horizontal side wall surface evenness correction coefficient and an outer wall vertical side wall surface evenness correction coefficient, wherein eta is expressed as an outer wall structure quality influence coefficient, and sigma is expressed as an outer wall structure quality influence coefficientlExpressed as the flatness coefficient of the horizontal side wall surface of the outer wall, sigmahExpressed as the flatness coefficient of the vertical side wall surface of the outer wall.
8. The intelligent detection and management system for acceptance of construction engineering quality based on big data analysis according to claim 1, characterized in that: the outer wall structure detection terminal includes motor, rolling dish, traction wire rope, locomotive, guide pulley and detects the car, the motor passes through the motor support mounting on the left support of locomotive, and the output shaft of motor is connected with the rolling dish, and traction wire rope one end is fixed on the rolling dish, and the wire rope other end passes the inside chamber way and the guide pulley of locomotive in proper order and detects car looks fixed connection, and guide pulley installs on the support on removal side right side, detects the car and presses close to mutually with waiting to detect the building outer wall face.
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