CN116362629B - Intelligent PC building quality monitoring and management method and system - Google Patents
Intelligent PC building quality monitoring and management method and system Download PDFInfo
- Publication number
- CN116362629B CN116362629B CN202310640109.0A CN202310640109A CN116362629B CN 116362629 B CN116362629 B CN 116362629B CN 202310640109 A CN202310640109 A CN 202310640109A CN 116362629 B CN116362629 B CN 116362629B
- Authority
- CN
- China
- Prior art keywords
- component
- evaluation value
- determining
- hole
- crack
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007726 management method Methods 0.000 title claims abstract description 35
- 238000012544 monitoring process Methods 0.000 title claims abstract description 26
- 238000011156 evaluation Methods 0.000 claims abstract description 228
- 238000010276 construction Methods 0.000 claims abstract description 94
- 238000013441 quality evaluation Methods 0.000 claims abstract description 64
- 238000000034 method Methods 0.000 claims abstract description 48
- 238000009434 installation Methods 0.000 claims abstract description 36
- 239000004567 concrete Substances 0.000 claims abstract description 26
- 230000008569 process Effects 0.000 claims abstract description 20
- 238000003908 quality control method Methods 0.000 claims abstract description 10
- 238000004590 computer program Methods 0.000 claims description 9
- 230000003746 surface roughness Effects 0.000 claims description 9
- 238000013210 evaluation model Methods 0.000 claims description 8
- 238000013528 artificial neural network Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 4
- 230000007547 defect Effects 0.000 claims description 4
- 238000013178 mathematical model Methods 0.000 claims description 4
- 238000012216 screening Methods 0.000 claims description 4
- 238000003860 storage Methods 0.000 claims description 4
- 238000005266 casting Methods 0.000 description 5
- 239000002245 particle Substances 0.000 description 5
- 239000011178 precast concrete Substances 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000011900 installation process Methods 0.000 description 2
- 238000012843 least square support vector machine Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 241000282461 Canis lupus Species 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000010327 methods by industry Methods 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000011150 reinforced concrete Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30132—Masonry; Concrete
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Primary Health Care (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention provides a PC building quality intelligent monitoring management method and system, which belong to the technical field of on-line approval and specifically comprise the following steps: determining the weight of the PC component through the type of the PC component, determining the comprehensive evaluation value by combining the image evaluation value and the initial evaluation value, and determining the secondary evaluation value through the comprehensive evaluation value of the PC component, the weight sum of the problem component and the weight sum of the suspected problem component; setting up a PC building through the PC component, determining a construction quality evaluation value of the PC building based on the installation deviation of the vertical component, the installation deviation of the horizontal component and the parameter deviation value of the concreted concrete in the setting up process, determining a comprehensive construction quality evaluation value by combining the number of the problem component and the suspected problem component and the secondary evaluation value, and outputting construction quality control measures based on the comprehensive construction quality evaluation value, so that the reliability of PC building quality management is further improved.
Description
Technical Field
The invention belongs to the technical field of construction quality management, and particularly relates to an intelligent PC (personal computer) building quality monitoring and management method and system.
Background
The assembled concrete building, namely the PC building, is the core of building industrialization, is also a main form for promoting the building industrialization in China, and compared with the traditional cast-in-situ mode, the construction mode realizes the industrial production of components, field programming lap joint and process informatization management, reduces the environmental pollution of field operation, is convenient to construct, saves manpower resources, has high production efficiency and high building quality, but how to realize intelligent monitoring and management on the construction quality of the PC building becomes a technical problem to be solved urgently.
In order to realize intelligent monitoring and management of construction quality of PC buildings, the quality influence parameters in the construction process of PC buildings are often monitored in real time by setting an Internet of things monitoring device in the prior art, so that intelligent management and control of the construction quality level are realized, but the following technical problems exist:
the confirmation of the quality of the individual PC members of the PC building by first combining the dimensions, surface defects, and the like is neglected, and in actual construction process engineering, although the quality of the individual PC members is not problematic, there is a possibility that the quality of the construction cannot be satisfied after the combination, and therefore, if the analysis result of the quality of the individual PC members cannot be first combined, there is a possibility that the final quality of the construction cannot be satisfied.
When the construction quality is estimated by neglecting construction error parameters such as installation deviation of vertical members, installation deviation of horizontal members and the like in the combined construction process and parameters of concrete poured by grouting, and PC construction is performed, if only construction deviation of a single member is considered and the parameters of the concrete poured by grouting are not considered, accurate monitoring and management of the construction quality of PC construction can not be accurately realized.
Aiming at the technical problems, the invention provides a PC building quality intelligent monitoring and management method and system.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
in a first aspect, the invention provides a PC building quality intelligent monitoring and management method.
The intelligent PC building quality monitoring and managing method is characterized by comprising the following steps:
s11, determining an initial evaluation value of a PC component of a PC building through dimensional deviation, surface roughness, surface crack data and hole data of the PC component;
s12, acquiring a surface image of the PC component, determining crack characteristics and hole characteristics of the surface image by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and obtaining an image evaluation value based on the crack characteristics and the hole characteristics;
S13, determining the weight of the PC component through the type of the PC component, determining the comprehensive evaluation value by combining an image evaluation value and an initial evaluation value, determining the number of the problem component and the suspected problem component through the comprehensive evaluation value, determining the secondary evaluation value by combining the comprehensive evaluation value of the PC component, the weight sum of the problem component and the weight sum of the suspected problem component, and judging whether the secondary evaluation value meets the requirement, if yes, entering a step S14, and if no, outputting quality does not meet the requirement;
s14, constructing a PC building through the PC component, determining a construction quality evaluation value of the PC building based on the installation deviation of the vertical component and the installation deviation of the horizontal component in the construction process, combining the parameter deviation value of the poured concrete, determining a comprehensive construction quality evaluation value by combining the number of the problem component and the suspected problem component and the secondary evaluation value, and outputting construction quality control measures based on the comprehensive construction quality evaluation value.
The further technical scheme is that the surface crack data comprises the number of cracks and the number of cracks at different positions of the PC component, and the hole data comprises the number of holes and the number of holes at different positions of the PC component.
The further technical scheme is that the crack characteristics comprise crack trend, crack width, crack length and crack depth; the hole features include hole area, hole number, hole depth.
The further technical scheme is that the determination of the comprehensive evaluation value specifically comprises the following steps:
determining the weight of the PC component through the type of the PC component, and determining a comprehensive evaluation value by combining an image evaluation value and an initial evaluation value;
determining the role of the PC component in the PC building by the type of the PC component, and determining the weight of the PC component based on the role of the PC component in the PC building;
judging whether the image evaluation value or the initial evaluation value is larger than a preset evaluation value, if so, determining a comprehensive evaluation value of the maximum value of the image evaluation value and the initial evaluation value and the weight of the PC component, and if not, entering the next step;
and determining a comprehensive basic evaluation value based on the image evaluation value and the initial evaluation value and adopting a mathematical model based on an analytic hierarchy process, and determining the comprehensive evaluation value based on the product of the weight of the PC component and the comprehensive basic evaluation value.
The further technical scheme is that when the sum of the number of the problem components and the number of the suspected problem components is larger than a preset number, the PC components are determined to not meet the quality requirement.
The further technical scheme is that the comprehensive construction quality evaluation value is determined by combining the number of the problem components and the suspected problem parts and the secondary evaluation value, and specifically comprises the following steps:
and determining the comprehensive construction quality evaluation value by adopting an evaluation model based on a neural network algorithm through the construction quality evaluation value, the number of the problem components and the suspected problem components and the secondary evaluation value.
The further technical scheme is that the construction quality evaluation value is based on to carry out the output of construction quality control measures, and the method specifically comprises the following steps:
when the comprehensive construction quality evaluation value meets the requirement, no construction quality management and control measures need to be output;
and outputting construction quality control measures when the comprehensive construction quality evaluation value does not meet the requirement, and continuing construction after the quality defect is eliminated.
In a second aspect, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: and the processor executes the intelligent PC building quality monitoring and management method when running the computer program.
In a third aspect, the present invention provides a computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform a PC building quality intelligent monitoring management method as described above.
The invention has the beneficial effects that:
the initial evaluation value of the PC component is determined based on the dimensional deviation, the surface roughness, the surface crack data and the hole data of the PC component, so that the quality evaluation of the PC component is realized from the structural characteristics of the PC component, and a foundation is laid for further quality management of PC buildings.
The crack characteristics and the hole characteristics of the surface image are determined by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and an image evaluation value is obtained based on the crack characteristics and the hole characteristics, so that further analysis on the quality of the PC component from the angle of the image is realized, and the reliability of the quality of the PC component is further ensured.
The number of the problem components and the suspected problem components is determined through the comprehensive evaluation value, and the comprehensive evaluation value of the PC components, the weight sum of the problem components, the weight sum of the suspected problem components and the secondary evaluation value are combined to determine, so that the overall quality state of all the PC components is evaluated from multiple angles, the influence on the quality and safety of the PC building after construction and installation due to the fact that the single quality problem is not large is avoided, and the safety and quality of the PC building are further guaranteed.
The PC component is used for building the PC building, the construction quality evaluation value of the PC building is determined based on the installation deviation of the vertical component and the installation deviation of the horizontal component in the building process, the parameter deviation value of the concreting is combined, and the comprehensive construction quality evaluation value is determined by combining the number of the problem components and the suspected problem components and the secondary evaluation value, so that the safety of the PC building is considered, the error condition of the PC component in the installation process and the parameter of the concreting are considered, the reliability of quality management of the PC building is ensured, and the overall evaluation of the quality of the PC building is realized.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below;
drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings;
FIG. 1 is a flow chart of a method for intelligent monitoring and management of PC building quality;
FIG. 2 is a flowchart of a method of initial evaluation value determination;
FIG. 3 is a flowchart of a method of image evaluation value determination;
FIG. 4 is a flow chart of a method of secondary evaluation value determination;
fig. 5 is a flowchart of a method of construction quality evaluation value determination;
FIG. 6 is a block diagram of a computer system.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
In order to solve the above problems, according to one aspect of the present invention, as shown in fig. 1, there is provided a PC building quality intelligent monitoring and management method according to one aspect of the present invention, which is characterized by comprising:
S11, determining an initial evaluation value of a PC component of a PC building through dimensional deviation, surface roughness, surface crack data and hole data of the PC component;
specifically, the PC (precast concrete) component is a component applied to the fields of construction, traffic, water conservancy and the like, and belongs to a concrete product processed and produced in a factory in a standardized and mechanized manner; and PC building refers to Precast Concrete (Precast Concrete) building. The precast concrete is processed and formed in a PC factory, and various reinforced concrete components with high strength, good compactness and high precision can be produced according to drawing requirements.
The surface crack data includes the number of cracks and the number of cracks at different positions of the PC member, and the hole data includes the number of holes and the number of holes at different positions of the PC member.
Specifically, the PC member may be divided into different positions according to the structure of the PC member, and the number of cracks and holes in the different positions may be counted.
As shown in fig. 2, the method for determining the initial evaluation value is as follows:
s21, acquiring the size deviation of the PC component, determining whether the PC component is a problem component or not based on the size deviation, if so, determining an initial evaluation value of the PC component based on the size deviation, and if not, proceeding to step S22;
When the dimensional deviation is large, it is determined that it belongs to the problem member.
S22, acquiring surface crack data of the PC component, determining a core position, an important position and a general position of the PC component according to the type of the PC component, determining a crack problem evaluation value of the PC component based on the number of cracks of the core position, the number of cracks of the important position and the number of cracks of the general position of the PC component, combining the number of cracks of the PC component, determining whether the PC component is a problem component based on the crack problem evaluation value, if yes, determining an initial evaluation value of the PC component based on the crack problem evaluation value, and if no, proceeding to step S23;
it can be understood that the core position, the important position and the general position of different PC components are different, and specifically, the determination of the core position, the important position and the general position of the PC components can be performed according to a preset corresponding relationship.
S23, acquiring hole data of the PC component, determining a core position, an important position and a general position of the PC component according to the type of the PC component, determining a hole problem evaluation value of the PC component based on the hole number of the core position, the hole number of the important position and the hole number of the general position of the PC component, combining the hole number of the PC component, determining whether the PC component is a problem component or not based on the hole problem evaluation value, if yes, determining an initial evaluation value of the PC component based on the hole problem evaluation value, and if no, entering step S24;
S24, determining an initial evaluation value of the PC component by the hole problem evaluation value and the crack problem evaluation value of the PC component and combining the dimensional deviation and the surface roughness of the PC component.
It should be further noted that, the determination of the initial evaluation value of the PC component based on the dimensional deviation specifically includes:
determining a maximum deviation allowable value of the PC component based on the type of the PC component, taking the ratio of the maximum deviation allowable value to the size deviation as a deviation ratio, carrying out correction deviation ratio by the deviation ratio and a preset quantity, and taking the correction deviation ratio as an initial evaluation value of the PC component, wherein the preset quantity is determined according to the type of the PC component.
In this embodiment, by first determining the initial evaluation value of the PC member based on the dimensional deviation, the surface roughness, the surface crack data, and the hole data of the PC member, the quality evaluation of the PC member from the structural features of the PC member is realized, which also lays a foundation for further quality management of the PC building.
S12, acquiring a surface image of the PC component, determining crack characteristics and hole characteristics of the surface image by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and obtaining an image evaluation value based on the crack characteristics and the hole characteristics;
It should be further noted that the fracture characteristics include fracture trend, fracture width, fracture length, and fracture depth; the hole features include hole area, hole number, hole depth.
As shown in fig. 3, the method for determining the image evaluation value is as follows:
s31, acquiring a surface image of the PC component, converting the surface image into a gray level image, determining the crack trend of the PC component by adopting a minimum circumscribed rectangle method, determining the crack width and the crack length of the PC component according to the pixel characteristics of the gray level image, and screening the attention crack by combining the crack width and the crack length;
s32, determining a fracture image evaluation value of the PC component based on the number of noted fractures of the PC component, the number of fractures, the average value of fracture widths and the average value of fracture lengths, combining the maximum value and the average value of the number of fractures in a unit area of the PC component and the maximum value and the average value of the number of noted fractures in the unit area, and determining whether the PC component is a problem component based on the fracture image evaluation value, if so, determining the image evaluation value of the PC component based on the fracture image evaluation value, and if not, proceeding to step S33;
S33, determining the hole area and the hole number of the PC component according to the pixel characteristics of the gray level image, and screening the attention holes by combining the hole areas;
s34, determining a hole image evaluation value of the PC component based on the number of the noted holes of the PC component, the average value of the hole areas of the noted holes, the average value of the number of the holes and the average value of the hole areas of the holes, and the maximum value and the average value of the number of the holes in the unit area, and combining the maximum value and the average value of the number of the noted holes in the unit area of the PC component, and determining whether the PC component is a problem component based on the hole image evaluation value, if yes, determining the image evaluation value of the PC component based on the hole image evaluation value, and if not, proceeding to step S33;
it should be noted that, the evaluation value of the hole image is determined by adopting an evaluation model of GWO-LSSVM algorithm, wherein the specific steps of the construction of the evaluation model are as follows:
and 1, preprocessing data. And carrying out standardized processing on input data formed by combining the maximum value and the average value of the number of the attention holes in the unit area of the PC component and the maximum value and the average value of the number of the holes in the unit area of the PC component so as to uniformly distribute the input data in the interval [0,1 ].
And 2, using a least square support vector machine model for modeling and prediction. The gray wolf optimization algorithm obtains the optimal gamma and C parameters of the least square support vector machine model through global search iterative optimization, and the hole image evaluation value is predicted after the optimal model parameters are determined.
And 3, reconstructing a predicted value. And superposing the predicted data to obtain a final prediction result.
And 4, analyzing the prediction result. And comparing and analyzing the prediction results obtained by the models, and finally obtaining the prediction model with the best effect by combining the related evaluation indexes.
S35, determining the hole depth and the crack depth of the PC component based on the surface image, determining a corrected hole image evaluation value through the average value of the hole depth, the maximum value of the hole depth and the hole image evaluation value, determining a corrected crack image evaluation value through the average value of the crack depth, the maximum value of the crack depth and the crack image evaluation value, and determining the image evaluation value of the PC component based on the corrected crack image evaluation value and the corrected hole image evaluation value.
Specifically, the image evaluation value of the PC component is determined according to the corrected fracture image evaluation value and the corrected hole image evaluation value, wherein the corrected fracture image evaluation value and the corrected hole image evaluation value are represented by a symbol X, Y, and specifically are determined in a manner shown in table 1;
Table 1 manner of determination of image evaluation values
In the embodiment, the crack characteristics and the hole characteristics of the surface image are determined by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and the image evaluation value is obtained based on the crack characteristics and the hole characteristics, so that further analysis on the quality of the PC component from the angle of the image is realized, and the reliability of the quality of the PC component is further ensured.
S13, determining the weight of the PC component through the type of the PC component, determining the comprehensive evaluation value by combining an image evaluation value and an initial evaluation value, determining the number of the problem component and the suspected problem component through the comprehensive evaluation value, determining the secondary evaluation value by combining the comprehensive evaluation value of the PC component, the weight sum of the problem component and the weight sum of the suspected problem component, and judging whether the secondary evaluation value meets the requirement, if yes, entering a step S14, and if no, outputting quality does not meet the requirement;
specifically, the determining the comprehensive evaluation value specifically includes:
determining the weight of the PC component through the type of the PC component, and determining a comprehensive evaluation value by combining an image evaluation value and an initial evaluation value;
Determining the role of the PC component in the PC building by the type of the PC component, and determining the weight of the PC component based on the role of the PC component in the PC building;
judging whether the image evaluation value or the initial evaluation value is larger than a preset evaluation value, if so, determining a comprehensive evaluation value of the maximum value of the image evaluation value and the initial evaluation value and the weight of the PC component, and if not, entering the next step;
and determining a comprehensive basic evaluation value based on the image evaluation value and the initial evaluation value and adopting a mathematical model based on an analytic hierarchy process, and determining the comprehensive evaluation value based on the product of the weight of the PC component and the comprehensive basic evaluation value.
It should be noted that the Analytic hierarchy Process (analytical Hier-arm Process) is abbreviated as AHP, and is a decision thinking method proposed by the U.S. mathematician T.L.SATTY teaching in the 70 th century, which is a qualitative and quantitative combined decision method. The idea of AHP is to decompose a complex problem into a plurality of sub-problems, determine each component of each sub-problem by quantitative method, and construct a judgment matrix by scale index.
In the prior art, how to use the construction mode and implementation mode of the mathematical model based on the analytic hierarchy process is also given in the book of data, model and decision, and in particular, in the application, the following formula is built:wherein P, C is an image evaluation value, an initial evaluation value, K 1 、K 2 Is constant and less than 1, specifically, since the accuracy of the image evaluation value is higher, it is generally K 1 Greater than K 2 J is the integrated base evaluation value.
As shown in fig. 4, the method for determining the secondary evaluation value is as follows:
s41, determining whether the PC component meets the quality requirement or not according to the number of the problem components and the suspected problem components, if so, entering a step S42, and if not, outputting that the quality does not meet the requirement;
s42, determining whether the PC component meets the quality requirement or not according to the weight sum of the problem component and the weight sum of the construction of the suspected problem, if so, entering a step S43, and if not, outputting that the quality does not meet the requirement;
s43, determining an average value of comprehensive evaluation values of the problem components and an average value of suspected problem construction through comprehensive evaluation values of the PC components, determining the problem component evaluation values of the problem components based on the average value of the comprehensive evaluation values of the problem components, the maximum value of the comprehensive evaluation values of the problem components, the number of the problem components, the weight of the problem components and the problem component evaluation values of the problem components, and determining whether the PC components meet the quality requirements or not based on the problem component evaluation values, if yes, entering step S43, and if no, outputting that the quality does not meet the requirements;
S44, determining the suspected problem component evaluation value based on the average value of the suspected problem component comprehensive evaluation values, the maximum value of the suspected problem component comprehensive evaluation values, the number of the suspected problem components, the weight of the suspected problem components and the suspected problem component evaluation value of the suspected problem components, and determining the secondary evaluation value based on the suspected problem component evaluation value and the problem component evaluation value.
When the sum of the number of the problem members and the number of the suspected problem members is greater than a preset number, it is determined that the PC member does not meet the quality requirement.
In this embodiment, the number of the problem components and the suspected problem components is determined through the comprehensive evaluation value, and the determination of the secondary evaluation value is performed by combining the comprehensive evaluation value of the PC components, the weight sum of the problem components, and the weight sum of the suspected problem components, so that the evaluation of the overall quality state of all the PC components from multiple angles is realized, the influence on the quality and safety of the PC building after construction and installation due to the fact that the single quality problem is not large is avoided, and the safety and quality of the PC building are further ensured.
S14, constructing a PC building through the PC component, determining a construction quality evaluation value of the PC building based on the installation deviation of the vertical component and the installation deviation of the horizontal component in the construction process, combining the parameter deviation value of the poured concrete, determining a comprehensive construction quality evaluation value by combining the number of the problem component and the suspected problem component and the secondary evaluation value, and outputting construction quality control measures based on the comprehensive construction quality evaluation value.
As shown in fig. 5, the method for determining the construction quality evaluation value is as follows:
s51, determining the installation deviation of the vertical member through the deviation amount of the axis position of the vertical member in the building process, dividing the vertical member into an accurate vertical member, a general vertical member and a problem vertical member based on the installation deviation of the vertical member, determining the installation quality evaluation value of the vertical member based on the number of the accurate vertical member, the number of the general vertical member and the number of the problem vertical member, judging whether the installation quality evaluation value of the vertical member meets the requirement, if yes, entering step S52, otherwise entering step S54;
s52, determining the installation deviation of the horizontal member through the deviation amount of the axis position of the horizontal member in the construction process, dividing the horizontal member into an accurate horizontal member, a general horizontal member and a problem horizontal member based on the installation deviation of the horizontal member, determining the installation quality evaluation value of the horizontal member based on the number of the accurate horizontal member, the number of the general horizontal member and the number of the problem horizontal member, judging whether the installation quality evaluation value of the horizontal member meets the requirement, if yes, entering step S53, and if not, entering step S54;
S53, dividing the usage amount of the concretes subjected to grouting into the usage amount of the concretes which meet the requirements and the usage amount of the concretes which do not meet the requirements based on the parameter deviation value of the concretes subjected to grouting, determining the casting quality evaluation value of the concretes by combining the parameter deviation value of the concretes, judging whether the casting quality evaluation value of the concretes meets the requirements, if so, determining that the construction of the PC building meets the quality requirements, and determining the installation quality evaluation value of the vertical member, the installation quality evaluation value of the horizontal member and the minimum value of the casting quality evaluation value of the concretes according to the construction quality evaluation value of the PC building, otherwise, entering step S54;
s54 determines the construction quality evaluation value of the PC building by the installation quality evaluation value of the vertical member, the installation quality evaluation value of the horizontal member, and the casting quality evaluation value of the concrete.
The method for determining the comprehensive construction quality evaluation value by combining the number of the problem members and the suspected problem parts and the secondary evaluation value specifically comprises the following steps:
and determining the comprehensive construction quality evaluation value by adopting an evaluation model based on a neural network algorithm through the construction quality evaluation value, the number of the problem components and the suspected problem components and the secondary evaluation value.
Specifically, the evaluation model based on the neural network algorithm is determined through the evaluation model based on the PSO-LSTM algorithm, wherein the specific steps of the construction of the evaluation model are as follows:
and step 1, track data preprocessing. Carrying out standardization processing on input data composed of construction quality evaluation values, the number of problem components and suspected problem components and secondary evaluation values to ensure that the input data are distributed in a [0,1] interval, carrying out repeated data rejection, abnormal value processing and the like on the standardized data, and carrying out the steps of 7:3 into training and prediction sets.
Step 2 initializes particle population X. And setting particle swarm population scale, iteration times, initial speed and position interval.
Step 3, setting the error index of the model as a fitness value, wherein the error index comprises two indexes of root mean square error (Root Mean Square Error, RMSE) and mean absolute value error (Mean Absolute Error, MAE). Wherein RMSE is generally expressed as the standard deviation of the true value from the predicted value; MAE is the average of absolute errors, typically expressed as the mean of the deviation over the samples.
And 4, updating the individual optimal position and the global optimal position of the single particle according to the change of the fitness value, and updating the position coordinates and the speed of the single particle.
And 5, iteratively updating the particle swarm until the fitness values RMSE and MAE tend to be stable, and determining the values of the optimizing parameters (alpha, epsilon and rho).
And 7, inputting the optimal parameters into an LSTM network, and predicting the comprehensive construction quality evaluation value by taking the construction quality evaluation value, the number of the problem components and the suspected problem parts and the secondary evaluation value as input data.
The construction quality evaluation value is used for evaluating the construction quality of the construction, and the construction quality evaluation value is used for controlling construction quality of the construction.
When the comprehensive construction quality evaluation value meets the requirement, no construction quality management and control measures need to be output;
and outputting construction quality control measures when the comprehensive construction quality evaluation value does not meet the requirement, and continuing construction after the quality defect is eliminated.
In this embodiment, the PC building is built by the PC component, and the construction quality evaluation value of the PC building is determined based on the installation deviation of the vertical component and the installation deviation of the horizontal component in the building process and by combining the parameter deviation value of the poured concrete, and the comprehensive construction quality evaluation value is determined by combining the number of the problem components and the suspected problem components and the secondary evaluation value, so that not only the safety of the PC building is considered, but also the error condition of the PC component in the installation process and the parameter of the poured concrete are considered, the reliability of quality management of the PC building is ensured, and meanwhile, the overall evaluation of the quality of the PC building is also realized.
In another aspect, as shown in FIG. 6, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: and the processor executes the intelligent PC building quality monitoring and management method when running the computer program.
The intelligent PC building quality monitoring and management method specifically comprises the following steps:
determining an initial evaluation value of a PC component of a PC building from dimensional deviation, surface roughness, surface crack data, and hole data of the PC component;
acquiring a surface image of the PC component, determining crack characteristics and hole characteristics of the surface image by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and obtaining an image evaluation value based on the crack characteristics and the hole characteristics;
determining the weight of the PC component through the type of the PC component, determining the comprehensive evaluation value by combining the image evaluation value and the initial evaluation value,
determining an average value of comprehensive evaluation values of the problem components and an average value of suspected problem construction through the comprehensive evaluation values of the PC components, determining the problem component evaluation values of the problem components based on the average value of the comprehensive evaluation values of the problem components, the maximum value of the comprehensive evaluation values of the problem components, the number of the problem components and the weight of the problem components, and entering a next step when the PC components are determined to meet the quality requirements based on the problem component evaluation values;
Determining a suspected problem component evaluation value based on the average value of the comprehensive evaluation values of the suspected problem components, the maximum value of the comprehensive evaluation values of the suspected problem components, the number of the suspected problem components, the weight of the suspected problem components and the suspected problem component evaluation value of the suspected problem components, and determining a secondary evaluation value based on the suspected problem component evaluation value and the problem component evaluation value;
and determining the number of the problem components and the suspected problem components through the comprehensive evaluation value, determining a secondary evaluation value by combining the comprehensive evaluation value of the PC component, the weight sum of the problem components and the weight sum of the suspected problem components, and judging that the output quality does not meet the requirement when the secondary evaluation value is determined to not meet the requirement.
In another aspect, the present invention provides a computer storage medium having a computer program stored thereon, which when executed in a computer causes the computer to perform a PC building quality intelligent monitoring management method as described above.
The intelligent PC building quality monitoring and management method specifically comprises the following steps:
determining an initial evaluation value of a PC component of a PC building from dimensional deviation, surface roughness, surface crack data, and hole data of the PC component;
Acquiring a surface image of the PC component, determining crack characteristics and hole characteristics of the surface image by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and obtaining an image evaluation value based on the crack characteristics and the hole characteristics;
determining the weight of the PC component through the type of the PC component, determining a comprehensive evaluation value by combining an image evaluation value and an initial evaluation value, determining the number of problem components and suspected problem components through the comprehensive evaluation value, determining a secondary evaluation value by combining the comprehensive evaluation value of the PC component, the weight sum of the problem components and the weight sum of the suspected problem components, and entering the next step when the secondary evaluation value is determined to meet the requirement;
determining the installation deviation of the vertical members by the deviation amount of the axis positions of the vertical members in the building process, dividing the vertical members into accurate vertical members, general vertical members and problem vertical members based on the installation deviation of the vertical members, and determining the installation quality evaluation value of the vertical members based on the number of the accurate vertical members, the number of the general vertical members and the number of the problem vertical members;
Determining the installation deviation of the horizontal member through the deviation amount of the axis position of the horizontal member in the construction process, dividing the horizontal member into an accurate horizontal member, a general horizontal member and a problem horizontal member based on the installation deviation of the horizontal member, and determining the installation quality evaluation value of the horizontal member based on the number of the accurate horizontal member, the number of the general horizontal member and the number of the problem horizontal member;
dividing the usage amount of the concrete subjected to grouting into the usage amount of the concrete meeting the requirements and the usage amount of the concrete not meeting the requirements based on the parameter deviation value of the concrete subjected to grouting, and determining the casting quality evaluation value of the concrete by combining the parameter deviation value of the concrete;
and determining the construction quality evaluation value of the PC building through the installation quality evaluation value of the vertical component, the installation quality evaluation value of the horizontal component and the pouring quality evaluation value of the concrete, and outputting construction quality control measures based on the comprehensive construction quality evaluation value.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (8)
1. The intelligent PC building quality monitoring and managing method is characterized by comprising the following steps:
determining an initial evaluation value of a PC component of a PC building from dimensional deviation, surface roughness, surface crack data, and hole data of the PC component;
The method for determining the initial evaluation value comprises the following steps:
acquiring the size deviation of the PC component, determining whether the PC component is a problem component or not based on the size deviation, if so, determining an initial evaluation value of the PC component based on the size deviation, and if not, entering the next step;
acquiring surface crack data of the PC component, determining a core position, an important position and a general position of the PC component according to the type of the PC component, determining a crack problem evaluation value of the PC component based on the number of cracks of the core position, the number of cracks of the important position and the number of cracks of the general position of the PC component, combining the number of cracks of the PC component, determining whether the PC component is a problem component or not based on the crack problem evaluation value, if yes, determining an initial evaluation value of the PC component based on the crack problem evaluation value, and if no, entering the next step;
acquiring hole data of the PC component, determining a core position, an important position and a general position of the PC component according to the type of the PC component, determining a hole problem evaluation value of the PC component based on the hole number of the core position, the hole number of the important position and the hole number of the general position of the PC component, determining whether the PC component is a problem component or not based on the hole problem evaluation value by combining the hole number of the PC component, if yes, determining an initial evaluation value of the PC component based on the hole problem evaluation value, and if no, entering the next step;
Determining an initial evaluation value of the PC component by combining the hole problem evaluation value and the crack problem evaluation value of the PC component and the dimensional deviation and the surface roughness of the PC component;
acquiring a surface image of the PC component, determining crack characteristics and hole characteristics of the surface image by adopting a minimum circumscribed rectangle method and pixel characteristics based on the surface image, and obtaining an image evaluation value based on the crack characteristics and the hole characteristics;
the method for determining the image evaluation value comprises the following steps:
acquiring a surface image of the PC component, converting the surface image into a gray image, determining the crack trend of the PC component by adopting a minimum circumscribed rectangle method, determining the crack width and the crack length of the PC component according to the pixel characteristics of the gray image, and screening the attention crack by combining the crack width and the crack length;
determining a fracture image evaluation value of the PC component based on the number of noted fractures of the PC component, the number of fractures, the average value of fracture widths and the average value of fracture lengths, combining the maximum value and the average value of the number of fractures in a unit area of the PC component and the maximum value and the average value of the number of noted fractures in the unit area, determining whether the PC component is a problem component based on the fracture image evaluation value, if so, determining the image evaluation value of the PC component based on the fracture image evaluation value, and if not, entering the next step;
Determining the hole area and the hole number of the PC component according to the pixel characteristics of the gray level image, and screening the attention holes by combining the hole area;
determining a hole image evaluation value of the PC component based on the average value of the number of the noted holes and the hole area of the noted holes, the average value of the number of the holes and the hole area of the holes of the PC component, combining the maximum value and the average value of the number of the noted holes in the unit area of the PC component and the maximum value and the average value of the number of the holes in the unit area of the PC component, determining whether the PC component is a problem component based on the hole image evaluation value, if yes, determining the image evaluation value of the PC component based on the hole image evaluation value, and if not, entering the next step;
determining the hole depth and the crack depth of the PC component based on the surface image, determining a corrected hole image evaluation value through the average value of the hole depth, the maximum value of the hole depth and the hole image evaluation value, determining a corrected crack image evaluation value through the average value of the crack depth, the maximum value of the crack depth and the crack image evaluation value, and determining an image evaluation value of the PC component based on the corrected crack image evaluation value and the corrected hole image evaluation value;
Determining the weight of the PC component through the type of the PC component, determining the comprehensive evaluation value by combining the image evaluation value and the initial evaluation value, determining the number of the problem component and the suspected problem component through the comprehensive evaluation value, determining the secondary evaluation value by combining the comprehensive evaluation value of the PC component, the weight sum of the problem component and the weight sum of the suspected problem component, and judging whether the secondary evaluation value meets the requirement, if yes, entering the next step, and if no, outputting quality does not meet the requirement;
the determination of the comprehensive evaluation value specifically comprises the following steps:
determining the weight of the PC component through the type of the PC component, and determining a comprehensive evaluation value by combining an image evaluation value and an initial evaluation value;
determining the role of the PC component in the PC building by the type of the PC component, and determining the weight of the PC component based on the role of the PC component in the PC building;
judging whether the image evaluation value or the initial evaluation value is larger than a preset evaluation value, if so, determining a comprehensive evaluation value of the maximum value of the image evaluation value and the initial evaluation value and the weight of the PC component, and if not, entering the next step;
Based on the image evaluation value and the initial evaluation value, adopting a mathematical model based on an analytic hierarchy process to determine a comprehensive basic evaluation value, and determining the comprehensive evaluation value based on the product of the weight of the PC component and the comprehensive basic evaluation value;
setting up a PC building through the PC component, determining a construction quality evaluation value of the PC building based on the installation deviation of the vertical component and the installation deviation of the horizontal component in the setting up process and combining the parameter deviation value of the concreted concrete, determining a comprehensive construction quality evaluation value by combining the number of the problem component and the suspected problem component and the secondary evaluation value, and outputting construction quality control measures based on the comprehensive construction quality evaluation value.
2. The intelligent monitoring and management method for PC building quality according to claim 1, wherein the surface crack data includes a number of cracks and a number of cracks at different positions of the PC member, and the hole data includes a number of holes and a number of holes at different positions of the PC member.
3. The intelligent monitoring and management method for PC building quality according to claim 1, wherein the determining of the initial evaluation value of the PC component based on the dimensional deviation specifically includes:
Determining a maximum deviation allowable value of the PC component based on the type of the PC component, taking the ratio of the maximum deviation allowable value to the size deviation as a deviation ratio, carrying out correction deviation ratio by the deviation ratio and a preset quantity, and taking the correction deviation ratio as an initial evaluation value of the PC component, wherein the preset quantity is determined according to the type of the PC component.
4. The intelligent monitoring and management method for PC building quality according to claim 1, wherein the crack characteristics comprise crack trend, crack width, crack length and crack depth; the hole features include hole area, hole number, hole depth.
5. The intelligent monitoring and management method for PC building quality according to claim 1, wherein the determination of the comprehensive construction quality evaluation value by combining the number of the problem members and the suspected problem members and the secondary evaluation value comprises:
and determining the comprehensive construction quality evaluation value by adopting an evaluation model based on a neural network algorithm through the construction quality evaluation value, the number of the problem components and the suspected problem components and the secondary evaluation value.
6. The intelligent monitoring and management method for PC building quality according to claim 1, wherein the outputting of the construction quality control measure based on the comprehensive construction quality evaluation value specifically includes:
When the comprehensive construction quality evaluation value meets the requirement, no construction quality management and control measures need to be output;
and outputting construction quality control measures when the comprehensive construction quality evaluation value does not meet the requirement, and continuing construction after the quality defect is eliminated.
7. A computer system, comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor, when running the computer program, performs a PC building quality intelligent monitoring and management method as set forth in any one of claims 1-6.
8. A computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform a PC building quality intelligent monitoring management method as claimed in any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310640109.0A CN116362629B (en) | 2023-06-01 | 2023-06-01 | Intelligent PC building quality monitoring and management method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310640109.0A CN116362629B (en) | 2023-06-01 | 2023-06-01 | Intelligent PC building quality monitoring and management method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116362629A CN116362629A (en) | 2023-06-30 |
| CN116362629B true CN116362629B (en) | 2023-08-22 |
Family
ID=86939958
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310640109.0A Active CN116362629B (en) | 2023-06-01 | 2023-06-01 | Intelligent PC building quality monitoring and management method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116362629B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117057679B (en) * | 2023-10-12 | 2024-01-09 | 山东领峰保温材料有限公司 | Cement-based insulation board installation quality control system based on data processing |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008197750A (en) * | 2007-02-08 | 2008-08-28 | Shimizu Corp | Building inspection information acquiring device |
| CN103957260A (en) * | 2014-05-05 | 2014-07-30 | 哈尔滨工业大学深圳研究生院 | Assembly type concrete whole-process monitoring system based on Internet of Things |
| AU2020101854A4 (en) * | 2020-08-17 | 2020-09-24 | China Communications Construction Co., Ltd. | A method for predicting concrete durability based on data mining and artificial intelligence algorithm |
| CN114881528A (en) * | 2022-06-08 | 2022-08-09 | 中建四局安装工程有限公司 | BIM-based assembly type building quality safety control method, system, equipment and medium |
-
2023
- 2023-06-01 CN CN202310640109.0A patent/CN116362629B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008197750A (en) * | 2007-02-08 | 2008-08-28 | Shimizu Corp | Building inspection information acquiring device |
| CN103957260A (en) * | 2014-05-05 | 2014-07-30 | 哈尔滨工业大学深圳研究生院 | Assembly type concrete whole-process monitoring system based on Internet of Things |
| AU2020101854A4 (en) * | 2020-08-17 | 2020-09-24 | China Communications Construction Co., Ltd. | A method for predicting concrete durability based on data mining and artificial intelligence algorithm |
| CN114881528A (en) * | 2022-06-08 | 2022-08-09 | 中建四局安装工程有限公司 | BIM-based assembly type building quality safety control method, system, equipment and medium |
Non-Patent Citations (1)
| Title |
|---|
| "基于组合评价法的装配式混凝土建筑工程 质量评价";申海龙;《工程科技Ⅱ辑》;C038-947 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116362629A (en) | 2023-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116362629B (en) | Intelligent PC building quality monitoring and management method and system | |
| CN110008591B (en) | Continuous rigid frame bridge construction management control method based on BIM | |
| CN111241719B (en) | Method for measuring and calculating actual strength of concrete in construction site | |
| Silva et al. | Service life prediction models for exterior stone cladding | |
| CN111625988A (en) | Bridge health management analysis and prediction system and method based on deep learning | |
| CN112418921A (en) | Power demand prediction method, device, system and computer storage medium | |
| CN110570031A (en) | Method for predicting river channel split ratio of two-stage branched river network in plain | |
| Croce et al. | Evaluation of statistical parameters of concrete strength from secondary experimental test data | |
| CN114861496B (en) | Concrete mesoscopic structure chloride ion erosion model based on cold region natural environment effect | |
| CN115511467A (en) | Project management method and system based on engineering cost | |
| CN114997503A (en) | Method and system for predicting urban carbon peak time domain | |
| CN117195163B (en) | Slump prediction method and device based on concrete formula and readable medium | |
| Li et al. | RC structures life-cycle probabilistic evaluation method considering mesoscopic material uncertainty with chloride ingress | |
| CN117195083A (en) | Slump prediction method and device based on current curve and readable medium | |
| Elhishi et al. | Unboxing machine learning models for concrete strength prediction using XAI | |
| KR20030072057A (en) | Intelligent Prediction system of Concrete Strength | |
| Papadimitropoulos et al. | Modeling the influence of environmental factors on concrete evaporation rate | |
| Tai et al. | Learn curve for precast component productivity in construction | |
| CN115952901A (en) | Power load prediction method based on ensemble learning | |
| CN114547761A (en) | High-precision model-based prefabricated part steel bar optimization method and system | |
| CN112488390B (en) | Urban water discharge prediction method and system | |
| CN112926027B (en) | Foundation pit risk monitoring system based on machine learning | |
| Tang | Application of BIM technology in the reinforcement and renovation of existing building inspection projects | |
| CN110555543B (en) | Uncertainty analysis method and system for wind power plant prediction | |
| Mallya et al. | Application of Lean Principles to Improve Rebar Productivity in Heavily Reinforced Structures |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |