CN115796604A - BIM model-based project full-life-cycle digital management early warning system - Google Patents
BIM model-based project full-life-cycle digital management early warning system Download PDFInfo
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Abstract
The invention discloses a BIM model-based project full-life-cycle digital management early warning system, which relates to the technical field of project full-life-cycle management, and comprises a data entry module, a data classification module and an abnormity supervision and analysis module, wherein the data entry module is used for entering data in the process of project progress into a BIM model; the data classification module is used for classifying data in the BIM into qualitative analysis data and quantitative analysis data, the qualitative analysis data comprise characteristic data of a construction team and characteristic data of an operation team, and the quantitative analysis data comprise characteristic data of building materials, construction progress, building parameters and environmental influence; the invention can integrate multiple groups of related data in the project cycle process of the building, early warn the building construction and use states in different stages of the project, and improve the efficiency, comprehensiveness and intelligence of project risk assessment.
Description
Technical Field
The invention relates to the technical field of project full-life-cycle management, in particular to a project full-life-cycle digital management early warning system based on a BIM (building information modeling).
Background
The core of BIM is to provide a complete building engineering information base consistent with the actual situation for a virtual building engineering three-dimensional model by establishing the model and utilizing the digital technology. The information base not only contains geometric information, professional attributes and state information describing building components, but also contains state information of non-component objects (such as space and motion behaviors), and can help to realize integration of building information from design, construction and operation of a building to the end of the whole life cycle of the building.
In the prior art, BIM is generally used for storing data in a building project process by using the model, and a user generally uses the model to acquire data or refer to the data, for example, in the prior document with application number 201610049724.4, a BIM engineering project element management method and system based on BIM are disclosed, and in the prior document, elements of an engineering project are only classified and stored by using BIM.
Disclosure of Invention
The invention aims at solving one of the technical problems in the prior art to at least a certain extent, and in order to achieve the aim, the invention provides a project full-life-cycle digital management early warning system based on a BIM (building information modeling) model, which comprises a data entry module, a data classification module and an abnormity supervision and analysis module, wherein the data entry module is used for entering data in the project progress process into the BIM model;
the data classification module is used for classifying data in the BIM into qualitative analysis data and quantitative analysis data, the qualitative analysis data comprise characteristic data of a construction team and characteristic data of an operation team, and the quantitative analysis data comprise characteristic data of building materials, construction progress, building parameters and environmental influences;
the abnormal supervision and analysis module comprises a weight setting unit, a period dividing unit and an analysis unit, wherein the period dividing unit is used for carrying out stage division on the project full life cycle and dividing the project full life cycle into a construction stage and a use stage; the weight setting unit is used for setting weight for the classified data based on the stage division of the project full life cycle; the analysis unit is used for analyzing and calculating data in the BIM model of each stage to obtain a project management reference value of the building of each stage, comparing the project management reference value of the building of each stage with a corresponding project management standard value, and outputting a corresponding early warning signal according to a comparison result.
Further, the data entry module comprises a basic data entry unit and a change data entry unit, the basic data entry unit is used for entering characteristic data of a construction team, an operation team, building materials and building parameters, and the change data entry unit is used for entering characteristic data of construction progress and environmental influence;
the change data entry unit comprises an update data entry port and an environment database, the environment database is in data connection with the update data entry port, and the update data entry port is used for entering construction progress data; the environment database stores environment influence data outside the building and records the environment influence data into the update data entry port.
Further, the data classification module is configured with a data feature selection policy, where the data feature selection policy includes: selecting defects of a design team and defects of a construction team as characteristic data of the construction team; the design team defects comprise the times of the quality design defects of the building and the quality design defect grades of the building; the building quality design defect grades comprise a first-level design defect, a second-level design defect and a third-level design defect; the construction team defects comprise the number of times of quality construction defects of the building and the grade of the quality construction defects of the building; the quality construction defect grades of the buildings comprise a first-level construction defect, a second-level construction defect and a third-level construction defect;
selecting the operation score and the operation duration as the characteristic data of the operation team;
selecting the proportion of the core material as the characteristic data of the building material;
selecting the ratio of the actual construction completion degree to the expected construction completion degree as characteristic data of construction progress, and setting the ratio of the actual construction completion degree to the expected construction completion degree as the construction progress ratio;
selecting the height of a building as characteristic data of building parameters;
and selecting the amount of strong wind weather, rainfall and high and low temperature days as characteristic data of environmental influence.
Further, the weight setting unit is configured with a weight setting policy including: setting a first-level construction team coefficient, a first-level operation team coefficient, a first-level construction material coefficient, a first-level construction progress ratio coefficient, a first-level construction parameter coefficient and a first-level environmental influence coefficient for characteristic data of construction teams, operation teams, construction materials, construction progress ratios, construction parameters and environmental influences respectively in a construction stage, wherein the sum of the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient and the first-level environmental influence coefficient is greater than zero, and the sum of the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient and the first-level environmental influence coefficient is equal to 1;
and setting a second-level construction team coefficient, a second-level operation team coefficient, a second-level construction material coefficient, a second-level construction progress ratio coefficient, a second-level construction parameter coefficient and a second-level environmental influence coefficient for the characteristic data of the construction team, the operation team, the construction material, the construction progress ratio, the construction parameters and the environmental influence respectively in the use stage, wherein the sum of the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction material coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient and the second-level environmental influence coefficient is more than zero, and is equal to 1.
Further, the analysis unit is configured with a basic computation policy, which includes: respectively setting the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects to the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects;
respectively setting the number of the quality construction defects of the building with the first-level construction defects, the second-level construction defects and the third-level construction defects as the number of the first-level construction defects, the number of the second-level construction defects and the number of the third-level construction defects;
setting a first-level index for the number of first-level design defects and the number of first-level construction defects, a second-level index for the number of second-level design defects and the number of second-level construction defects, a third-level index for the number of third-level design defects and the number of third-level construction defects,
adding the number of the first-level design defects and the number of the first-level construction defects, then giving a first-level index to obtain a first-level defect reference value, adding the number of the second-level design defects and the number of the second-level construction defects, then giving a second-level index to obtain a second-level defect reference value, adding the number of the third-level design defects and the number of the third-level construction defects, and then giving a third-level index to obtain a third-level defect reference value; adding the primary defect reference value, the secondary defect reference value and the tertiary defect reference value to obtain a negative influence value of the characteristic data of the construction team, and comparing the negative influence value of the characteristic data of the construction team with a standard reference value of the characteristic data of the construction team to obtain a proportional value of the characteristic data of the construction team;
multiplying the selected operation score by the operation duration to obtain an operation team characteristic data forward influence value, and comparing the operation team characteristic data standard reference value with the operation team characteristic data forward influence value to obtain an operation team characteristic data proportion value;
comparing the standard proportion of the core material with the proportion of the core material to obtain a building material characteristic data proportion value;
setting the reciprocal of the construction progress ratio as a construction progress characteristic data proportion value;
comparing the height of the building with a height standard reference value to obtain a building parameter characteristic data proportional value;
setting a rainfall days conversion ratio for rainfall, multiplying the rainfall with the rainfall days conversion ratio to obtain rainfall conversion days, adding the rainfall conversion days, the windy weather quantity and the high and low temperature days to obtain an environmental days influence value, and comparing the environmental days influence value with an environmental days influence reference value to obtain an environmental influence characteristic data proportional value.
Further, the analysis unit is further configured with a build phase impact analysis strategy comprising: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a first-level construction team coefficient, a first-level operation team coefficient, a first-level building material coefficient, a first-level construction progress ratio coefficient, a first-level building parameter coefficient and a first-level environmental influence coefficient respectively, and then adding to obtain a project management reference value in a construction stage;
and subtracting the project management standard value from the project management reference value in the construction stage to obtain a construction stage project early warning value, and outputting a construction stage early warning signal when the construction stage project early warning value is greater than or equal to a first management threshold value, wherein the project management standard value is set to be 1, and the value range of the first management threshold value is 0.1-0.5.
Further, the analysis unit is further configured with a usage phase impact analysis policy, the usage phase impact analysis policy including: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a second-level construction team coefficient, a second-level operation team coefficient, a second-level building material coefficient, a second-level construction progress ratio coefficient, a second-level building parameter coefficient and a second-level environmental influence coefficient respectively, and then adding to obtain a project management reference value in a use stage;
and subtracting the item management standard value from the item management reference value in the use stage to obtain an item early warning value in the use stage, and outputting an item early warning signal in the use stage when the item early warning value in the use stage is greater than or equal to a second management threshold value, wherein the value range of the second management threshold value is 0.15-0.5.
The invention has the beneficial effects that: according to the data classification method, corresponding data support can be provided for data analysis of different periodic stages of a project of a building through data entry, and data in a BIM can be divided into qualitative analysis data and quantitative analysis data through a data classification module; then, carrying out stage division on the project full life cycle, and dividing the project full life cycle into a construction stage and a use stage; setting weights for the classified data based on the stage division of the project full life cycle; the method can integrate multiple groups of related data in the project cycle process of the building, early warn the building construction and use states in different stages of the project, and improve the efficiency, comprehensiveness and intelligence of project risk assessment.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
FIG. 1 is a functional block diagram of a management early warning system of the present invention;
FIG. 2 is a functional block diagram of the data entry module 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 and 2, a project full-life-cycle digital management early warning system based on a BIM model includes a data entry module, a data classification module, and an anomaly supervision and analysis module.
Referring to fig. 2, the data entry module is configured to enter data in a project progress process into a BIM model; the data entry module comprises a basic data entry unit and a change data entry unit, the basic data entry unit is used for entering characteristic data of a construction team, an operation team, building materials and building parameters, and the change data entry unit is used for entering characteristic data of construction progress and environmental influence; the change data entry unit comprises an update data entry port and an environment database, the environment database is continuously updated according to the storage of the environment data, the environment database is in data connection with the update data entry port, and the update data entry port is used for entering construction progress data; the environment database stores environment influence data outside the building, inputs the environment influence data into the update data and records the updated data into the port, and the environment database stores historical environment data of the area where the building is located and sets the part of the historical environment data associated with the technical scheme of the invention as the environment influence data.
The data classification module is used for classifying data in the BIM into qualitative analysis data and quantitative analysis data, the qualitative analysis data comprise characteristic data of a construction team and characteristic data of an operation team, and the quantitative analysis data comprise characteristic data of building materials, construction progress, building parameters and environmental influence; the qualitative analysis data represents evaluation indexes biased to subjectivity, for example, the strength of a construction team, but the qualitative analysis data can be converted through specific quantitative indexes, for example, when the characteristic data factors of an operation team are considered, the operation score and the operation duration are selected as the characteristic data of the operation team, the quantifiable data of the subjective evaluation of the operation team can be converted through the operation score and the operation duration, and therefore digital support is provided for the management of the whole life cycle of a project.
The data classification module is configured with a data characteristic selection strategy, and the data characteristic selection strategy comprises the following steps: selecting the defects of a design team and the defects of a construction team as characteristic data of the construction team; the design team defects comprise the times of the quality design defects of the building and the quality design defect grades of the building; the building quality design defect grades comprise a first-level design defect, a second-level design defect and a third-level design defect; the construction team defects comprise the times of the quality construction defects of the building and the quality construction defect grade of the building; the quality construction defect grades of the buildings comprise a first-level construction defect, a second-level construction defect and a third-level construction defect; the number of times of the building quality design defects and the number of times of the building quality construction defects are obtained according to historical data of a design team and a construction team respectively, and the building quality design defects and the building quality construction defects both represent defects which affect the construction quality of a building; the quality construction defect of the building can be the construction problem of a construction team in the construction process, and particularly can be poor solidification effect caused by incomplete mixing of construction materials; the above-mentioned defect problem can be obtained from the inspection report of the team after the delivery of the building; the building quality design defect grade and the building quality construction defect grade are graded after the quality influence of the defects on the building is graded, the building quality design defect grade and the building quality construction defect grade are respectively set to be a first grade, a second grade and a third grade, the severity of the defects of the first grade is higher than that of the defects of the second grade, and the severity of the defects of the second grade is higher than that of the defects of the third grade.
Selecting the operation score and the operation duration as the characteristic data of the operation team; the operation scoring is set according to the integral scoring of an operation team by a user in the existing database, the operation time is set according to the forming time limit of the operation team, for example, when the operation team is a property company, different scoring is carried out on different property companies, a scoring standard that five points are full is adopted, and the operation time is the forming time limit of the property company.
Selecting the proportion of the core material as the characteristic data of the building material; wherein the ratio of the core material is the ratio of the used mass of the core material to the total estimated mass of the building; the concrete core material is the reinforcing steel bar, and in the building construction process of concrete structure, the quality of building can be promoted better to the collocation of reinforcing steel bar and concrete, and the use proportion of reinforcing steel bar becomes positive correlation with the quality, if reduce the proportion of reinforcing steel bar in building material, or the thickness and the intensity of reinforcing steel bar are not enough, all can influence the whole construction quality of building.
Selecting the ratio of the actual construction completion degree to the expected construction completion degree as characteristic data of construction progress, and setting the ratio of the actual construction completion degree to the expected construction completion degree as the construction progress ratio; the actual construction completion degree is obtained through field investigation, the specific characteristic data can be obtained through judging the number of building floors and the construction stage of a building, and the expected construction completion degree is obtained through a construction target preset in a project.
Selecting the height of a building as characteristic data of building parameters; in the actual construction process, the higher the height of the building, the greater the difficulty in building the building, the greater the possibility of building flaws generated in the construction process, and after the building is built, the higher the height of the building, the more significantly the building is affected by external force, for example, the swing amplitude of a super high-rise building in windy weather is obviously higher than that of a low-rise building, and the loss of the super high-rise building is also obviously increased.
Selecting the amount of strong wind weather, the amount of rainfall and the number of high and low temperature days as characteristic data of environmental influence, wherein the amount of strong wind weather, the amount of rainfall and the number of high and low temperature days are obtained through historical weather of an area where a building is located, the data of the previous year can be selected as reference in practical application, the specific amount of strong wind weather is set as the number of days when the wind power of the area in one year is greater than or equal to 6-level wind power, the amount of rainfall is set as the total rainfall of the area in one year, the number of high and low temperature days is the number of days when the highest temperature of the area in one year exceeds 35 ℃ and the lowest temperature of the area is lower than-5 ℃, the larger the amount of rainfall is higher than the erosion of a wall body of the building, and the smaller the amount of rainfall is smaller, the problem that the building is subjected to dry cracking is caused; the larger the wind power is, the higher the influence on the shaking of a high-rise building is, and the effect of wind power erosion is also larger; the more hot weather and cold weather, the higher the effect on the expansion and contraction of the building.
The anomaly supervision and analysis module comprises a weight setting unit, a period division unit and an analysis unit, wherein the period division unit is used for carrying out stage division on the project full life cycle and dividing the project full life cycle into a construction stage and a use stage; the full life cycle of the project can be a part of the cycle process of the building from the dead to the dead, and can also be consistent with the full life cycle of the building; for example: the full life cycle of the project may be the period from design to build delivery of the building or the period from design to end of the life of the building, and the full life cycle of the project in this application is the period from design to end of the life of the building.
The weight setting unit is used for setting weights for the classified data based on the stage division of the project full life cycle, the weight setting unit is configured with a weight setting strategy, and the weight setting strategy comprises the following steps: setting a first-level construction team coefficient, a first-level operation team coefficient, a first-level construction material coefficient, a first-level construction progress ratio coefficient, a first-level construction parameter coefficient and a first-level environment influence coefficient for the construction team, the operation team, the construction material, the construction progress ratio, the construction parameter and the characteristic data of the environmental influence respectively in the construction stage, wherein the sum of the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient and the first-level environment influence coefficient is equal to 1; the first-level construction team coefficient, the first-level operation team coefficient, the first-level building material coefficient, the first-level construction progress ratio coefficient, the first-level building parameter coefficient and the first-level environment influence coefficient are all larger than zero, and the first-level construction team coefficient, the first-level operation team coefficient, the first-level building material coefficient, the first-level construction progress ratio coefficient, the first-level building parameter coefficient and the first-level environment influence coefficient respectively represent the influence proportion of corresponding characteristic data in a construction stage. In the specific setting, the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient, and the first-level environmental influence coefficient are respectively set to a1, a2, a3, a4, a5, and a6, and further, a1 is set to 0.2, a2 is set to 0.1, a3 is set to 0.3, a4 is set to 0.2, a5 is set to 0.1, and a6 is set to 0.1.
Setting a second-level construction team coefficient, a second-level operation team coefficient, a second-level construction material coefficient, a second-level construction progress ratio coefficient, a second-level construction parameter coefficient and a second-level environment influence coefficient for the construction team, the operation team, the construction material, the construction progress ratio, the construction parameter and the characteristic data of the environmental influence respectively in a use stage, wherein the sum of the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient and the second-level environment influence coefficient is equal to 1, the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction parameter coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient and the second-level environment influence coefficient are all larger than zero, and the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction material coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient and the second-level environment influence coefficient respectively represent the influence ratio of the corresponding characteristic data in the use stage; in the construction stage and the use stage, the influence of the construction team, the operation team, the construction materials, the construction progress ratio, the construction parameters and the characteristic data of the environmental influence on the building is different, for example, the construction team, the construction materials and the construction progress ratio influence the construction quality, so the influence of the construction team, the construction materials and the construction progress ratio is large in the construction stage; in the use stage, the continuous maintenance stage for the building is mainly adopted, so the influence of the operation team, the building parameters and the environmental influence is greater. In the specific setting, the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction material coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient, and the second-level environmental influence coefficient are respectively set to b1, b2, b3, b4, b5, and b6, further, b1 is set to 0.1, b2 is set to 0.2, b3 is set to 0.1, b4 is set to 0.1, b5 is set to 0.2, and b6 is set to 0.3.
The analysis unit is used for analyzing and calculating data in the BIM model of each stage to obtain a project management reference value of the building of each stage, comparing the project management reference value of the building of each stage with a corresponding project management standard value, and outputting a corresponding early warning signal according to a comparison result.
The analysis unit is configured with a basic calculation strategy, and the basic calculation strategy comprises the following steps: respectively setting the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects to the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects; respectively setting the number of the quality construction defects of the building with the first-level construction defects, the second-level construction defects and the third-level construction defects as the number of the first-level construction defects, the number of the second-level construction defects and the number of the third-level construction defects; the method comprises the steps of setting a first-level index for the number of first-level design defects and the number of first-level construction defects, setting a second-level index for the number of second-level design defects and the number of second-level construction defects, and setting a third-level index for the number of third-level design defects and the number of third-level construction defects, wherein the defect severity of the first-level design defects, the second-level design defects and the third-level design defects is gradually reduced, and the defect severity of the first-level construction defects, the second-level construction defects and the third-level construction defects is gradually reduced, so that when the method is specifically set, the first-level index is larger than the second-level index, the second-level index is larger than the third-level index, the first-level index, the second-level index and the third-level index are respectively set to be Z1, Z2 and Z3, and further Z1 is set to be 2 and Z1.
Adding the number of the first-level design defects and the number of the first-level construction defects, then giving a first-level index to obtain a first-level defect reference value, adding the number of the second-level design defects and the number of the second-level construction defects, then giving a second-level index to obtain a second-level defect reference value, adding the number of the third-level design defects and the number of the third-level construction defects, then giving a third-level index to obtain a third-level defect reference value, adding the first-level defect reference value, the second-level defect reference value and the third-level defect reference value to obtain a construction team characteristic data negative influence value, comparing the construction team characteristic data negative influence value with a construction team characteristic data standard reference value to obtain a construction team characteristic data proportional value, and calculating the construction team characteristic data negative influence value through a formula, wherein the calculation process is specifically:
P js =（S1 sj +S1 sg ） Z1 +（S2 sj +S2 sg ） Z2 +（S3 sj +S3 sg ） Z3 ；
wherein, P js For negative influence values of the construction team feature data, S1 sj Designing the number of defects for one level, S1 sg For the number of first-stage construction defects, S2 sj Designing the number of defects for two levels, S2 sg For the number of second-stage construction defects, S3 sj Designing the number of defects for three levels, S3 sg For the number of construction defects of three levels, for example, when Z1 is 3, Z2 is 2, and Z1 is 1, S1 is obtained sj 、S1 sg 、S2 sj 、S2 sg 、S3 sj And S3 sg When the values are 1, 2 and 2, respectively, P is obtained js For 28, the standard reference value of the characteristic data of the construction team is set by referring to the average level in the actual process, specifically, the standard reference value can be set to 25, and the ratio value of the characteristic data of the construction team is 1.12. When the proportional value is obtained, two digits after the decimal point are selected for rounding.
Multiplying the selected operation score by the operation duration to obtain an operation team characteristic data forward influence value, and comparing the operation team characteristic data standard reference value with the operation team characteristic data forward influence value to obtain an operation team characteristic data proportion value; in specific implementation, the obtained operation score of the operation team is 4.5, the operation duration is 5, the obtained forward influence value of the characteristic data of the operation team is 22.5, the standard reference value of the characteristic data of the operation team is set according to the average level of the operation team and can be specifically set to be 25, and the obtained proportion value of the characteristic data of the operation team is 1.11.
Comparing the standard proportion of the core material with the proportion of the core material to obtain a building material characteristic data proportion value; the standard proportion of the core material is set by referring to the existing average level of the building material, for example, the proportion of the reinforcing steel bars of the core material in the existing average level of the building material is 10%, wherein the proportion can be used as a judgment standard according to the manufacturing cost, the standard proportion of the core material can be specifically set to be 10%, the proportion of the obtained core material is 8% in specific implementation, and the obtained characteristic data proportion value of the building material is 1.25.
Setting the reciprocal of the construction progress ratio as a construction progress characteristic data proportion value; during specific implementation, the obtained actual construction completion degree is 30%, the expected construction completion degree is 40%, the construction progress ratio is 0.75, the reciprocal of the construction progress ratio is 1.33, and the construction progress characteristic data proportion value is 1.33;
comparing the height of the building with a height standard reference value to obtain a building parameter characteristic data proportional value; in specific implementation, the height standard reference value is set to be 150m, the height of the building is 220m, and the obtained building parameter characteristic data proportion value is 1.47.
Setting a rainfall day conversion ratio for rainfall, and multiplying the rainfall by the rainfall day conversion ratio to obtain rainfall conversion days, wherein in specific implementation, the annual rainfall is 600mm as a basic standard, and 600mm can be converted into 50 days correspondingly, so that the corresponding rainfall conversion ratio is approximately equal to 0.08, for example, the annual rainfall in the area is 800m, and the obtained rainfall conversion days are 64;
and adding the rainfall conversion days, the amount of strong wind weather and the high and low temperature days to obtain an environmental day influence value, and comparing the environmental day influence value with an environmental day influence reference value to obtain an environmental influence characteristic data proportion value. In specific implementation, the rainfall conversion days are 64, the gale weather quantity is 50, the high and low temperature days are 50, the obtained environmental day influence value is 164, the environmental day influence reference value is set to be 150, and the obtained environmental influence characteristic data proportion value is 1.09.
The analysis unit is further configured with a build phase impact analysis strategy comprising: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a first-level construction team coefficient, a first-level operation team coefficient, a first-level building material coefficient, a first-level construction progress ratio coefficient, a first-level building parameter coefficient and a first-level environmental influence coefficient respectively and then adding to obtain a project management reference value in a construction stage; calculating the project management reference value in the construction stage according to the values obtained in the concrete implementation, wherein a1 is set to be 0.2, a2 is set to be 0.1, a3 is set to be 0.3, a4 is set to be 0.2, a5 is set to be 0.1, a6 is set to be 0.1, the construction team characteristic data proportion value is 1.12, the operation team characteristic data proportion value is 1.11, the construction material characteristic data proportion value is 1.25, the construction progress characteristic data proportion value is 1.33, the construction parameter characteristic data proportion value is 1.47, the environmental impact characteristic data proportion value is 1.09, and the concrete calculation process is as follows:
0.2*1.12+0.1*1.11+0.3*1.25+0.2*1.33+0.1*1.47+0.1*1.09=1.232；
and subtracting the project management reference value from the project management reference value in the construction stage to obtain a construction stage project early warning value, and outputting a construction stage early warning signal when the construction stage project early warning value is greater than or equal to a first management threshold value, wherein the project management reference value is set to be 1, the project management reference value refers to the existing database, the average value of the project management reference values of a plurality of buildings reaching the standard is obtained, and the value range of the first management threshold value is 0.1-0.5. In specific implementation, the first management threshold is set to be 0.2,1.232-1=0.232 and 0.232> -0.2, so that a building stage early warning signal is output.
The analysis unit is further configured with a usage phase impact analysis strategy comprising: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a second-level construction team coefficient, a second-level operation team coefficient, a second-level building material coefficient, a second-level construction progress ratio coefficient, a second-level building parameter coefficient and a second-level environmental influence coefficient respectively, and then adding to obtain a project management reference value in a use stage; calculating the project management reference value in the use stage according to the values obtained in the concrete implementation, wherein b1 is set to be 0.1, b2 is set to be 0.2, b3 is set to be 0.1, b4 is set to be 0.1, b5 is set to be 0.2, b6 is set to be 0.3, the construction team characteristic data proportion value is 1.12, the operation team characteristic data proportion value is 1.11, the construction material characteristic data proportion value is 1.25, the construction progress characteristic data proportion value is 1.33, the construction parameter characteristic data proportion value is 1.47, the environmental impact characteristic data proportion value is 1.09, and the concrete calculation process is as follows:
0.1*1.12+0.2*1.11+0.1*1.25+0.1*1.33+0.2*1.47+0.3*1.09=1.213；
and subtracting the project management standard value from the project management reference value in the use stage to obtain a project early warning value in the use stage, and outputting a use stage early warning signal when the project early warning value in the use stage is greater than or equal to a second management threshold value, wherein the value range of the second management threshold value is 0.15-0.5, and in specific implementation, the second management threshold value is set to be 0.2,1.213-1=0.213 and 0213>, and the use stage early warning signal is output at the moment.
The working principle is as follows: according to the data input method, data in a project progress process can be input into a BIM through a data input module, corresponding data can be provided for data analysis of different periodic stages of a project of a building through continuous data input, and the data in the BIM can be divided into qualitative analysis data and quantitative analysis data through a data classification module; then, carrying out stage division on the project full life cycle, and dividing the project full life cycle into a construction stage and a use stage; setting weights for the classified data based on the stage division of the project full life cycle; the data in the BIM model of each stage are analyzed and calculated to obtain the project management reference value of the building of each stage, the project management reference value of the building of each stage is compared with the corresponding project management standard value, the corresponding early warning signal is output according to the comparison result, multiple groups of related data in the project cycle process of the building can be integrated, and therefore early warning is conducted on the building construction and use states of different stages of the project.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied in the medium. The storage medium may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implementing, and for example, a plurality of units or components may be combined or integrated into another system, or some characteristic data may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
Claims (7)
1. A project full life cycle digital management early warning system based on a BIM model is characterized by comprising a data entry module, a data classification module and an abnormity supervision and analysis module, wherein the data entry module is used for entering data in the project progress process into the BIM model;
the data classification module is used for classifying data in the BIM into qualitative analysis data and quantitative analysis data, the qualitative analysis data comprise characteristic data of a construction team and characteristic data of an operation team, and the quantitative analysis data comprise characteristic data of building materials, construction progress, building parameters and environmental influence;
the abnormal supervision and analysis module comprises a weight setting unit, a period dividing unit and an analysis unit, wherein the period dividing unit is used for carrying out stage division on the whole life cycle of the project and dividing the whole life cycle of the project into a construction stage and a use stage; the weight setting unit is used for setting weight for the classified data based on the stage division of the project full life cycle; the analysis unit is used for analyzing and calculating data in the BIM model of each stage to obtain a project management reference value of the building of each stage, comparing the project management reference value of the building of each stage with a corresponding project management standard value, and outputting a corresponding early warning signal according to a comparison result.
2. The BIM model-based project full-life-cycle digital management and early-warning system as claimed in claim 1, wherein the data entry module comprises a basic data entry unit and a change data entry unit, the basic data entry unit is used for entering characteristic data of construction teams, operation teams, building materials and building parameters, and the change data entry unit is used for entering characteristic data of construction progress and environmental impact;
the change data entry unit comprises an update data entry port and an environment database, the environment database is in data connection with the update data entry port, and the update data entry port is used for entering construction progress data; the environment database stores environment influence data outside the building and records the environment influence data into the update data entry port.
3. The BIM-model-based project full-life-cycle digital management early warning system as claimed in claim 1, wherein the data classification module is configured with a data feature selection strategy, the data feature selection strategy comprising: selecting the defects of a design team and the defects of a construction team as characteristic data of the construction team; the design team defects comprise the times of the quality design defects of the building and the quality design defect grades of the building; the building quality design defect grades comprise a first-level design defect, a second-level design defect and a third-level design defect; the construction team defects comprise the times of the quality construction defects of the building and the quality construction defect grade of the building; the quality construction defect grades of the buildings comprise a first-level construction defect, a second-level construction defect and a third-level construction defect;
selecting the operation score and the operation duration as the characteristic data of the operation team;
selecting the proportion of the core material as the characteristic data of the building material;
selecting the ratio of the actual construction completion degree to the expected construction completion degree as characteristic data of construction progress, and setting the ratio of the actual construction completion degree to the expected construction completion degree as the construction progress ratio;
selecting the height of a building as characteristic data of building parameters;
and selecting the amount of strong wind weather, rainfall and high and low temperature days as characteristic data of environmental influence.
4. The BIM model-based project full-life-cycle digital management early warning system as claimed in claim 3, wherein the weight setting unit is configured with a weight setting strategy, the weight setting strategy comprising: setting a first-level construction team coefficient, a first-level operation team coefficient, a first-level construction material coefficient, a first-level construction progress ratio coefficient, a first-level construction parameter coefficient and a first-level environmental influence coefficient for characteristic data of construction teams, operation teams, construction materials, construction progress ratios, construction parameters and environmental influences respectively in a construction stage, wherein the sum of the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient and the first-level environmental influence coefficient is greater than zero, and the sum of the first-level construction team coefficient, the first-level operation team coefficient, the first-level construction material coefficient, the first-level construction progress ratio coefficient, the first-level construction parameter coefficient and the first-level environmental influence coefficient is equal to 1;
and setting a second-level construction team coefficient, a second-level operation team coefficient, a second-level construction material coefficient, a second-level construction progress ratio coefficient, a second-level construction parameter coefficient and a second-level environmental influence coefficient for the characteristic data of the construction team, the operation team, the construction material, the construction progress ratio, the construction parameters and the environmental influence respectively in the use stage, wherein the sum of the second-level construction team coefficient, the second-level operation team coefficient, the second-level construction material coefficient, the second-level construction progress ratio coefficient, the second-level construction parameter coefficient and the second-level environmental influence coefficient is more than zero, and is equal to 1.
5. The BIM model-based project full-life-cycle digital management early warning system as claimed in claim 4, wherein the analysis unit is configured with a basic computing strategy, and the basic computing strategy comprises: respectively setting the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects to the number of the first-level design defects, the number of the second-level design defects and the number of the third-level design defects;
respectively setting the number of the quality construction defects of the building with the first-level construction defects, the second-level construction defects and the third-level construction defects as the number of the first-level construction defects, the number of the second-level construction defects and the number of the third-level construction defects;
setting a first-level index for the number of first-level design defects and the number of first-level construction defects, a second-level index for the number of second-level design defects and the number of second-level construction defects, a third-level index for the number of third-level design defects and the number of third-level construction defects,
adding the number of the first-level design defects and the number of the first-level construction defects, then giving a first-level index to obtain a first-level defect reference value, adding the number of the second-level design defects and the number of the second-level construction defects, then giving a second-level index to obtain a second-level defect reference value, adding the number of the third-level design defects and the number of the third-level construction defects, and then giving a third-level index to obtain a third-level defect reference value; adding the primary defect reference value, the secondary defect reference value and the tertiary defect reference value to obtain a negative influence value of the characteristic data of the construction team, and comparing the negative influence value of the characteristic data of the construction team with a standard reference value of the characteristic data of the construction team to obtain a proportional value of the characteristic data of the construction team;
multiplying the selected operation score by the operation duration to obtain an operation team characteristic data forward influence value, and comparing the operation team characteristic data standard reference value with the operation team characteristic data forward influence value to obtain an operation team characteristic data proportional value;
comparing the standard proportion of the core material with the proportion of the core material to obtain a building material characteristic data proportion value;
setting the reciprocal of the construction progress ratio as a construction progress characteristic data proportion value;
comparing the height of the building with a height standard reference value to obtain a building parameter characteristic data proportional value;
setting a rainfall days conversion ratio for rainfall, multiplying the rainfall with the rainfall days conversion ratio to obtain rainfall conversion days, adding the rainfall conversion days, the windy weather quantity and the high and low temperature days to obtain an environmental days influence value, and comparing the environmental days influence value with an environmental days influence reference value to obtain an environmental influence characteristic data proportional value.
6. The BIM model-based project full-life-cycle digital management early warning system as claimed in claim 5, wherein the analysis unit is further configured with a construction phase impact analysis strategy, the construction phase impact analysis strategy comprising: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a first-level construction team coefficient, a first-level operation team coefficient, a first-level building material coefficient, a first-level construction progress ratio coefficient, a first-level building parameter coefficient and a first-level environmental influence coefficient respectively, and then adding to obtain a project management reference value in a construction stage;
and subtracting the project management standard value from the project management reference value in the construction stage to obtain a construction stage project early warning value, and outputting a construction stage early warning signal when the construction stage project early warning value is greater than or equal to a first management threshold value, wherein the project management standard value is set to be 1, and the value range of the first management threshold value is 0.1-0.5.
7. The BIM model-based project full-life-cycle digital management early warning system as claimed in claim 6, wherein the analysis unit is further configured with a usage phase impact analysis strategy, the usage phase impact analysis strategy comprising: multiplying the construction team characteristic data proportional value, the operation team characteristic data proportional value, the building material characteristic data proportional value, the construction progress characteristic data proportional value, the building parameter characteristic data proportional value and the environmental influence characteristic data proportional value with a second-level construction team coefficient, a second-level operation team coefficient, a second-level building material coefficient, a second-level construction progress ratio coefficient, a second-level building parameter coefficient and a second-level environmental influence coefficient respectively, and then adding to obtain a project management reference value in a use stage;
and subtracting the item management standard value from the item management reference value in the use stage to obtain an item early warning value in the use stage, and outputting an item early warning signal in the use stage when the item early warning value in the use stage is greater than or equal to a second management threshold value, wherein the value range of the second management threshold value is 0.15-0.5.
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