CN114819628A - Visual engineering supervision system - Google Patents
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Abstract
The invention discloses a visual engineering supervision system, which mainly comprises a data checking module, a data storage module, a data acquisition module, a BIM analysis module, a risk evaluation module, a target analysis module and an alarm module, wherein the data checking module checks and analyzes construction data to obtain supervision errors, the target analysis module carries out threshold judgment and analysis according to the supervision errors, then utilizes the construction data in the time period to carry out influence factor index analysis to obtain target analysis results, the risk prediction module analyzes the data according to the target analysis results to obtain risk prediction results, meanwhile, the BIM analysis module directly carries out risk prediction analysis according to the construction data uploaded by the data acquisition module to obtain platform prediction results and risk prediction results which are compared to obtain comparison results, and the data analysis in the engineering project construction process is supervised through the comparison results, the accuracy of risk prediction and data analysis decision is improved, and the quality safety management of engineering projects is enhanced.
Description
Technical Field
The invention relates to the technical field of engineering project management, in particular to a visual engineering supervision system.
Background
In the construction process of the engineering project, along with the characteristics of long time and large engineering quantity, a large amount of manpower and material resources are consumed for realizing the supervision and management process of the whole engineering project, and the artificial detection and analysis are accompanied with calculation errors; in the prior art, the BIM technology can already carry out supervision, sharing, scheduling and decision-making according to construction information in an engineering project, but an engineering supervision department is taken as an important department in a project management system, independence exists in the process of supervising and managing the engineering project according to collected construction data, and the slow decision-making speed of managers can cause the problems of untimely information communication, inadequate instruction issuing and huge quality; although the BIM technical platform can achieve the functions of information sharing and target decision-making, when constructors and managers have different proficiency in technology and project construction is influenced by extreme changes, the speed of information sharing still influences the decision-making of a project management system, and in order to continuously improve the informatization level of project supervision and the speed and accuracy of decision-making of project supervision departments in the project management system and quickly solve the problem of decision-making in project caused in a sudden change environment, the invention provides a visual project supervision system.
Disclosure of Invention
In view of the above situation and in order to overcome the defects of the prior art, an object of the present invention is to provide a visual project supervision system, in which a target analysis module analyzes the indicators of the influence factors affecting the quality of the project to obtain corresponding target analysis results, a risk assessment module performs data compensation according to the target analysis results of the target analysis module, performs risk prediction to obtain a risk assessment result, and compares the risk assessment result with the platform prediction result of a BIM analysis module.
The technical scheme for solving the problem is that the visual engineering supervision system comprises a data verification module, a data storage module, a data acquisition module, a BIM analysis module, a risk assessment module, a target analysis module and an alarm module, wherein the data acquisition module acquires data in engineering project construction to obtain construction data, and the construction data is sent to a data storage module for storage, a BIM analysis module, a risk evaluation module and a target analysis module analyze the construction data in the project process to obtain a risk evaluation result, a data verification module performs data verification analysis on the construction data in the analysis process to obtain a supervision error, a risk evaluation module performs risk evaluation by combining the supervision error, the BIM analysis module carries out comparison analysis on the risk evaluation result of the prediction analysis and the prediction result of the BIM analysis module to obtain a comparison result, and the alarm module thinks that a manager sends an alarm signal according to the comparison result;
the specific analysis process of the system is as follows:
1) the data acquisition module acquires construction data of each stage in the construction process of the engineering project to obtain construction data, the acquired construction data are sent to the data storage module, the data verification module performs data verification on the acquired actual construction data, and the actual construction data are analyzed according to the time, the frequency and the information quantity of the acquired data to obtain supervision errors;
2) the target analysis module receives the supervision errors, analyzes the supervision errors in different time periods, and when the fluctuation range of the supervision errors exceeds a set threshold value, analyzes the influence factor indexes of the time periods corresponding to the target analysis module;
3) the risk evaluation module receives a target analysis result and performs quality prediction on the quality of the engineering project in different time periods by combining the supervision error to obtain a risk evaluation result, the BIM analysis module performs risk prediction according to the construction data collected by the data collection module to obtain a platform prediction result, the target analysis result comprises a continuous change parameter, an intermittent change parameter and an extreme value solution, the risk evaluation module performs continuous processing on construction data of interval change according to the supervision error and the interval change parameter to obtain a continuous change value, then sets predicted influence parameters according to the continuous change parameter, the continuous change value and the extreme value solution, the risk evaluation module performs risk prediction evaluation on the construction data in the next time period according to the influence parameters and the supervision error to obtain a risk evaluation result, and the BIM analysis module performs comparison according to the risk evaluation result and the platform prediction result to obtain a comparison result of comparative analysis, the BIM analysis module selects a core influence factor index according to a target analysis result of the target analysis module and compares a risk evaluation result with a platform prediction result;
4) the alarm module is used for issuing alarm information, when the comparison result of the risk assessment module and the BIM analysis module exceeds a set threshold value, the BIM analysis module sends an alarm signal to the alarm module, and the alarm module informs the supervision department of management according to the alarm signal.
The data checking module checks and analyzes the construction data of the data acquisition module to obtain an acquisition checking result, checks and analyzes the acquired specific data content to obtain a content checking result, and finally performs error analysis on the acquisition checking result and the content checking result respectively obtained by data content checking and acquisition checking of the construction data to obtain a total supervision error;
the specific analysis process is as follows:
step one, a data checking module extracts construction data for a time period t i The number of collection classes in is recorded as Q i At Q i Class Collection Categories including n i Class continuous collection of class and Q i -n i Newly adding collection type, and recording the time period of data collection as t i (i ∈ K), K denotes the total number of time periods that have been collected, numberAnalyzing the change of the corresponding acquisition type quantity in K time periods according to a verification module, and calculating the change rate lambda of the data quantity acquired corresponding to the continuous acquisition types in different time periods K And calculating the number of newly added acquisition types in the adjacent time period, and calculating the growth rate beta of the number of newly added acquisition types i ；
Step two, calculating the growth rate beta of the number of newly added collection types in K time periods i Total rate of change
Thirdly, the data verification module analyzes and compares the data content of the construction data, compares and judges the comparison result in a threshold value, when the comparison result exceeds the threshold value of the data error, the acquired data is abnormal, the data verification module sends the abnormal data to the BIM analysis module, and when the comparison result is within the threshold value, the data verification module conducts further verification;
step four, the comparison result comprises the comparison index e of k data contents j (j ∈ k), the actual error of each comparison index from the threshold is ε j According to the actual error and the change rate lambda K And the total rate of change beta to calculate a total error epsilon,
ε＝λ K (1-β)∑(e j +ε j )，
and step five, the errors epsilon in different time periods are different, the data verification module performs combined analysis on the errors epsilon and the analysis errors of the BIM analysis module to obtain a total supervision error, and the supervision error is sent to the target analysis module and the risk assessment module.
The target analysis module judges the supervision error after receiving the supervision error, the target analysis module retrieves a judgment threshold value of the supervision error from the data storage module and judges the supervision error according to the judgment threshold value, when the supervision error exceeds the judgment threshold value, the target analysis module analyzes data contents corresponding to construction data of newly-added collection types and continuously-collected types at the time end corresponding to the supervision error, firstly, influence factor indexes of the two types of construction data are respectively extracted, a target function is established according to an influence-irascibility index, influence analysis is carried out on the influence factor indexes according to the target function to obtain a continuous change parameter and an interval change parameter, the target analysis module respectively establishes a mathematical analysis equation in an n-dimensional space according to the continuous change parameter and the interval change parameter to calculate the extreme value solution of the equation in a critical state, and the target analysis module sends the target analysis results of the two types of data to the risk assessment module.
The BIM analysis module is a management center used for realizing information integration and data analysis, the BIM analysis module carries out data analysis according to construction data and carries out data evaluation prediction according to the generated construction data to obtain a platform prediction result, the BIM analysis module receives a risk evaluation result obtained by carrying out risk evaluation according to a target analysis result of the target analysis module by the risk evaluation module, and then compares the risk evaluation result with the platform prediction result to obtain a comparison result of comparison analysis, and in the comparison process, the BIM analysis module compares the risk evaluation result corresponding to an influence factor index corresponding to the target analysis result with the platform prediction result in the same time period.
The data acquisition module acquires construction data generated in the construction process of an engineering project, the acquisition process of the construction data comprises a continuous acquisition process and an intermediate acquisition process, the continuous acquisition process is the acquisition process of the construction data of which the data acquisition module is constant according to the updating frequency, the acquisition process of the construction data of which the acquisition and updating frequency is not a constant value is the intermediate acquisition process for the first time, the data of different acquisition processes are classified according to the updating frequency, the updating time, the updating data quantity and the data type of the construction data acquisition, and the data storage module performs distributed storage on the construction data acquired by the data acquisition module.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages;
1. the data acquisition module of the system acquires construction data in the engineering project construction process, the data verification module performs data verification on the construction data acquired by the data acquisition module, the verification process of the data verification module comprises data content verification and data acquisition process verification, the data acquisition module performs verification analysis on the acquired data representing the data acquisition process to obtain an acquisition verification result, the acquired specific data content is subjected to verification analysis to obtain a content verification result, finally, the data verification module performs error analysis on the acquisition verification result and the content verification result respectively obtained by the data content verification and the acquisition verification of the construction data to obtain a total supervision error, the supervision error obtained by the verification analysis is utilized to improve the integrity of original data, and the problems that the degree of proficiency of constructors and managers in the technology is uneven and the data acquisition error caused by extreme changes of project construction are solved, the accuracy of target decision analysis is improved.
2. The target analysis module carries out threshold judgment and analysis according to the supervision error, judges a time period corresponding to the supervision error according to the judgment threshold of the supervision error, then carries out influence factor index analysis by utilizing construction data in the time period to obtain a target analysis result, analyzes the fluctuation range of different influence factor indexes, and calculates the optimal extreme value solution according to a target function, the risk prediction module carries out analysis on the data analyzed by the target analysis module and the data verification module by utilizing a risk prediction algorithm to obtain a risk prediction result, meanwhile, the BIM analysis module directly carries out risk prediction analysis according to the construction data uploaded by the data acquisition module to obtain a platform prediction result, finally, the BIM analysis module compares the risk prediction result with the platform prediction result to obtain a comparison result, and supervises the data analysis in the construction process of the engineering project through the comparison result, the accuracy of data analysis decision is improved.
Drawings
FIG. 1 is an overall block diagram of the system;
FIG. 2 is an overall flow diagram of the present system;
Detailed Description
The foregoing and other aspects, features and advantages of the invention will be apparent from the following more particular description of embodiments of the invention, as illustrated in the accompanying drawings in which reference is made to figures 1-2. The structural contents mentioned in the following embodiments are all referred to the attached drawings of the specification.
A visual project supervision system comprises a data checking module, a data storage module, a data acquisition module, a BIM analysis module, a risk evaluation module, a target analysis module and an alarm module, wherein the BIM technology occupies an important position in the engineering project construction process, the BIM technology is used for visually managing construction data in an engineering project, the information island problem in the engineering project construction data management process is effectively avoided, managers analyze the construction data by using the BIM technology and make decisions according to data analysis results, but in the actual engineering project construction, the visual management of the construction data of the engineering project still has the problems of untimely information communication and unbalanced BIM technology mastering level, which causes a fault on the visual management decision of the engineering project, when the BIM analysis module analyzes the acquired construction data, the accuracy of the collected data determines the accuracy of data analysis, the BIM technical level of constructors masters different data collection errors caused by difference and also influences the process of visual management of engineering project data, the data collection module collects the data in the engineering project construction to obtain construction data, and the construction data is sent to a data storage module for storage, a BIM analysis module, a risk evaluation module and a target analysis module analyze the construction data in the project process to obtain a risk evaluation result, a data verification module performs data verification analysis on the construction data in the analysis process to obtain a supervision error, a risk evaluation module performs risk evaluation by combining the supervision error, the BIM analysis module carries out comparison analysis on the risk evaluation result of the prediction analysis and the prediction result of the BIM analysis module to obtain a comparison result, and the alarm module thinks that a manager sends an alarm signal according to the comparison result;
the specific analysis process of the system is as follows:
1) the data acquisition module acquires construction data of each stage in the construction process of an engineering project to obtain construction data, and transmits the acquired construction data to the data storage module, when the technical level of constructors is uneven, the construction data acquired by the data acquisition module has deviation, the data acquisition module records a timestamp when the data is recorded and the information amount of the construction data, the data verification module performs data verification on the acquired actual construction data and analyzes the time, frequency and information amount according to the acquired data to obtain supervision errors, and the data verification module respectively verifies the construction data acquisition process and the construction data;
2) the target analysis module receives the supervision errors and analyzes the supervision errors in different time periods, the supervision errors of the data verification modules in different time periods are different, the target analysis module judges the supervision errors again according to a set threshold value, different influence factor indexes in the engineering project are analyzed through the judgment of the supervision errors by the threshold value, the set threshold value is obtained by the BIM analysis module performing target analysis on construction data of the engineering project completed by construction according to a linear programming equation,
S a ＝a 1 x 1 +a 2 x 2 +a 3 x 3 +…+a n x n ，
a 1 、a 2 、a 3 ...a n is x 1 ，x 2 ，x 3 ...x n Coefficient of (1), S a Threshold values, x, for supervision errors in different time periods 1 ，x 2 ，x 3 ...x n The method comprises the steps of carrying out linear analysis on different time periods of construction data of a constructed engineering project by using a linear regression analysis method for influencing parameters of a threshold value, when the fluctuation range of a supervision error exceeds a set threshold value, analyzing influence factor indexes of the time period corresponding to a target analysis module, firstly extracting the influence factor indexes influencing the engineering project from the construction data in the time period by using the target analysis module, carrying out target analysis on different influence factor indexes to obtain target analysis results, establishing a target function according to the influence processes of the different influence factor indexes by using the target analysis module, analyzing by using the target function to obtain the target analysis results, classifying the influence factor indexes according to the target analysis results, wherein the target analysis results comprise the influence factor indexes of each influence factor index under actual states and ideal statesThe target analysis module obtains the change characteristics of the influence factor indexes reflecting the safe construction in the data according to the established error and the analysis of the target function of the construction data, reflects the influence degree through the analysis of the fluctuation range, and analyzes the influence factor indexes through the comparison of the fluctuation range in an ideal state and the fluctuation range in the actual construction process;
3) analyzing the fluctuation of different influence factor indexes in the construction data according to the target analysis result of the target analysis module, analyzing the influence factors, processing the construction data according to the target analysis result, then evaluating by the wind direction evaluation module to obtain a risk evaluation result, under the influence of different influence factors, the influence fluctuation and the fluctuation range of the influence factors are different, the risk prediction result is different, the influence of different constructors on the mastery level of the BIM analysis technology is overcome, the risk evaluation module receives the target analysis result and carries out quality prediction on the quality of different time periods of the engineering project by combining the supervision error to obtain the risk evaluation result, meanwhile, the BIM analysis module carries out risk prediction according to the construction data collected by the data collection module to obtain a platform prediction result, and the target analysis result comprises continuous variation parameters, Intermittent variation parameters and extreme value solutions, wherein the continuous variation parameters and the intermittent variation parameters represent parameters representing influence ranges obtained by analyzing an objective function established according to influence factor indexes, for example, the influence of construction data on a construction period is utilized to analyze, the time consumed by sub-stages of different engineering projects is different, the construction period is analyzed according to the existing data, and the influence factor of the influence factor on the objective function of the construction period is r
T ime ＝maxf j ，
Wherein f is j Completion time for j-th job (j ═ 1, 2)，......)，maxf j Denotes f j Maximum value of (d), minf j Denotes f j The minimum value of the data is analyzed by using the construction period to obtain the influence factor, the influence factor and the fluctuation range are analyzed, the risk evaluation module carries out continuous processing on construction data of interval change according to the supervision error and the interval change parameter to obtain a continuous change value, predicted influence parameters are set according to the continuous change parameter, the continuous change value and the extreme value solution, the risk evaluation module carries out risk prediction evaluation on the construction data in the next time period according to the influence parameter and the supervision error to obtain a risk evaluation result, the BIM analysis module carries out comparison according to the risk evaluation result and the platform prediction result to obtain a comparison result of comparative analysis, the BIM analysis module selects a core influence factor index according to a target analysis result of the target analysis module and compares the risk evaluation result and the platform prediction result;
4) the alarm module is used for issuing alarm information, when the comparison result of the risk assessment module and the BIM analysis module exceeds a set threshold value, the BIM analysis module sends an alarm signal to the alarm module, and the alarm module informs the supervision department of management according to the alarm signal.
The data checking module checks and analyzes the construction data of the data acquisition module to obtain an acquisition checking result, checks and analyzes the acquired specific data content to obtain a content checking result, and finally performs error analysis on the acquisition checking result and the content checking result respectively obtained by data content checking and acquisition checking of the construction data to obtain a total supervision error;
the specific analysis process is as follows:
step one, a data checking module extracts construction data for a time period t i The number of collection classes in is recorded as Q i At Q i Class Collection Categories including n i Class continuous collection of class and Q i -n i Newly adding collection type, and recording the time period of data collection as t i (i ∈ K), K denotes the period of time that has been collectedThe data verification module analyzes the change of the corresponding collection type quantity in K time periods, and calculates the change rate lambda of the data quantity collected corresponding to the continuous collection type in different time periods K And calculating the number of newly added acquisition types in the adjacent time period, and calculating the growth rate beta of the number of newly added acquisition types i ；
Step two, calculating the growth rate beta of the number of newly added collection types in K time periods i Total rate of change
Thirdly, the data verification module analyzes and compares the data content of the construction data, compares and judges the comparison result with a threshold value, when the comparison result exceeds the threshold value of the data error, the acquired data is abnormal, the data verification module sends the abnormal data to the BIM analysis module, and when the comparison result is within the threshold value, the data verification module conducts further verification;
step four, the comparison result comprises the comparison index e of k data contents j (j ∈ k), the actual error of each comparison index from the threshold is ε j According to the actual error and the change rate lambda K And the total rate of change beta to calculate a total error epsilon,
ε＝λ K (1-β)∑(e j +ε j )，
and step five, the errors epsilon in different time periods are different, the data verification module performs combined analysis on the errors epsilon and the analysis errors of the BIM analysis module to obtain a total supervision error, and the supervision error is sent to the target analysis module and the risk assessment module.
The target analysis module receives the supervision error, judges the supervision error, calls a judgment threshold value of the supervision error from the data storage module, judges the supervision error according to the judgment threshold value, analyzes data contents corresponding to construction data of newly-added acquisition types and continuously-acquired types at the time end corresponding to the supervision error when the supervision error exceeds the judgment threshold value, firstly extracts influence factor indexes of the two types of construction data respectively, establishes a target function according to an influence-irascibility index, performs influence analysis on the influence factor indexes according to the target function to obtain continuous variation parameters and interval variation parameters, establishes mathematical analysis equations in an n-dimensional space according to the continuous variation parameters and the intermittent variation parameters respectively, and calculates extreme value solutions of the equations in a critical state, and the target analysis module sends the target analysis results of the two types of data to the risk assessment module.
The supervision and management of the engineering project is an important guarantee for realizing the high-quality completion of the engineering project, so that the effect of precise management is achieved, the information communication among all subsystems in an engineering project management system is improved, the problem of information isolated island in the engineering supervision process can be well avoided by the application of the BIM technology, the informatization level of the engineering supervision is continuously provided, the BIM technology realizes the information visualization application in the engineering supervision process, the problems are quickly found and processed in the dynamic implementation process, a multi-target analysis model of the engineering project management system of the BIM technology is an assumed specified condition, the optimal result is obtained by analyzing through an algorithm in mathematical analysis, the result of the BIM technology analysis is influenced by the algorithm and analysis data, the original data obtained by data acquisition and the algorithm of the data analysis can influence the analysis result, and the mastered levels of the BIM technology are uneven, the BIM analysis result is different from the actual result, in order to reduce the difference, the system carries out comparative analysis on the wind direction evaluation module and the prediction result of the BIM analysis module, the BIM analysis module is a management center for realizing information integration and data analysis, the BIM analysis module carries out data analysis according to construction data, the BIM analysis module receives the risk evaluation result obtained by the risk evaluation module according to the target analysis result of the target analysis module, then comparing the risk evaluation result with the platform prediction result to obtain a comparison result of comparison analysis, in the comparison process, the BIM analysis module compares the risk evaluation result corresponding to the influence factor index corresponding to the target analysis result with the platform prediction result in the same time period.
The data acquisition module acquires construction data generated in the construction process of an engineering project, the acquisition process of the construction data comprises a continuous acquisition process and an intermediate acquisition process, the continuous acquisition process is the acquisition process of the construction data of which the data acquisition module is constant according to the updating frequency, the acquisition process of the construction data of which the acquisition and updating frequency is not a constant value is the intermediate acquisition process for the first time, the data of different acquisition processes are classified according to the updating frequency, the updating time, the updating data quantity and the data type of the construction data acquisition, and the data storage module performs distributed storage on the construction data acquired by the data acquisition module.
When the system is used specifically, the system mainly comprises a data checking module, a data storage module, a data acquisition module, a BIM analysis module, a risk evaluation module, a target analysis module and an alarm module, wherein the data acquisition module acquires construction data in construction of an engineering project and sends the construction data to the data storage module for storage, the data checking module performs data checking on the construction data acquired by the data acquisition module, acquires a checking result by checking and analyzing the acquired data representing the data acquisition process, acquires specific data content by checking and analyzing the acquired specific data content to acquire a content checking result, and finally the data checking module performs error analysis on the acquiring checking result and the content checking result respectively acquired by checking and acquiring the data content of the construction data to acquire a total administrative error, the method comprises the steps that a target analysis module judges and analyzes a threshold value according to a supervision error, influence factor index analysis is carried out by utilizing construction data in the time period to obtain a target analysis result, the fluctuation range of different influence factor indexes is analyzed, an optimal extreme value solution is calculated according to a target function, a risk prediction module analyzes data analyzed by the target analysis module and a data verification module by utilizing a risk prediction algorithm to obtain a risk prediction result, a BIM (building information modeling) analysis module directly carries out risk prediction analysis according to the construction data uploaded by a data acquisition module to obtain a platform prediction result, finally the BIM analysis module compares the risk prediction result with the platform prediction result to obtain a comparison result, data analysis in the construction process of an engineering project is supervised by the comparison result, and the accuracy of data analysis decision is improved.
While the invention has been described in further detail with reference to specific embodiments thereof, it is not intended that the invention be limited to the specific embodiments thereof; for those skilled in the art to which the present invention pertains and related technologies, the extension, operation method and data replacement should fall within the protection scope of the present invention based on the technical solution of the present invention.
Claims (5)
1. A visual project supervision system is characterized by comprising a data verification module, a data storage module, a data acquisition module, a BIM analysis module, a risk assessment module, a target analysis module and an alarm module, wherein the data acquisition module acquires data in the construction of a project to obtain construction data, and the construction data is sent to a data storage module for storage, a BIM analysis module, a risk evaluation module and a target analysis module analyze the construction data in the project process to obtain a risk evaluation result, a data verification module performs data verification analysis on the construction data in the analysis process to obtain a supervision error, a risk evaluation module performs risk evaluation by combining the supervision error, the BIM analysis module carries out comparison analysis on the risk evaluation result of the prediction analysis and the prediction result of the BIM analysis module to obtain a comparison result, and the alarm module thinks that a manager sends an alarm signal according to the comparison result;
the specific analysis process of the system is as follows:
1) the data acquisition module acquires construction data of each stage in the construction process of the engineering project to obtain construction data, the acquired construction data are sent to the data storage module, the data verification module performs data verification on the acquired actual construction data, and the actual construction data are analyzed according to the time, the frequency and the information quantity of the acquired data to obtain supervision errors;
2) the target analysis module receives the supervision errors, analyzes the supervision errors in different time periods, and when the fluctuation range of the supervision errors exceeds a set threshold value, analyzes the influence factor indexes of the time periods corresponding to the target analysis module;
3) the risk evaluation module receives a target analysis result and performs quality prediction on the quality of the engineering project in different time periods by combining the supervision error to obtain a risk evaluation result, the BIM analysis module performs risk prediction according to the construction data collected by the data collection module to obtain a platform prediction result, the target analysis result comprises a continuous change parameter, an intermittent change parameter and an extreme value solution, the risk evaluation module performs continuous processing on construction data of interval change according to the supervision error and the interval change parameter to obtain a continuous change value, then sets predicted influence parameters according to the continuous change parameter, the continuous change value and the extreme value solution, the risk evaluation module performs risk prediction evaluation on the construction data in the next time period according to the influence parameters and the supervision error to obtain a risk evaluation result, and the BIM analysis module performs comparison according to the risk evaluation result and the platform prediction result to obtain a comparison result of comparative analysis, the BIM analysis module selects a core influence factor index according to a target analysis result of the target analysis module and compares a risk evaluation result with a platform prediction result;
4) the alarm module is used for issuing alarm information, when the comparison result of the risk assessment module and the BIM analysis module exceeds a set threshold value, the BIM analysis module sends an alarm signal to the alarm module, and the alarm module informs the supervision department of management according to the alarm signal.
2. The visual project supervision system according to claim 1, wherein the data checking module checks and analyzes the supervision error of the construction data of the data acquisition module, and first, the data checking module checks and analyzes the acquisition data representing the data acquisition process to obtain an acquisition checking result, then checks and analyzes the acquired specific data content to obtain a content checking result, and finally, the data checking module performs error analysis on the acquisition checking result and the content checking result respectively obtained by data content checking and acquisition checking of the construction data to obtain a total supervision error;
the specific analysis process is as follows:
step one, a data checking module extracts construction data for a time period t i The number of collection classes in the system is recorded as Q i At Q i Class Collection Categories including n i Class continuous collection of class and Q i -n i Newly adding collection type, and recording the time period of data collection as t i (i belongs to K), wherein K represents the total number of the collected time periods, the data verification module analyzes the change of the corresponding collection type number in the K time periods, and calculates the change rate lambda of the data quantity collected corresponding to the continuous collection types in different time periods K And calculating the number of newly added acquisition types in the adjacent time period, and calculating the growth rate beta of the number of newly added acquisition types i ；
Step two, calculating the growth rate beta of the number of newly added collection types in K time periods i Total rate of change
Thirdly, the data verification module analyzes and compares the data content of the construction data, compares and judges the comparison result in a threshold value, when the comparison result exceeds the threshold value of the data error, the acquired data is abnormal, the data verification module sends the abnormal data to the BIM analysis module, and when the comparison result is within the threshold value, the data verification module conducts further verification;
step four, the comparison result comprises the comparison index e of k data contents j (j ∈ k), the actual error of each comparison index from the threshold is ε j According to the actual error and the change rate lambda K And the total rate of change beta to calculate a total error epsilon,
ε＝λ K (1-β)∑(e j +ε j )，
and step five, the errors epsilon in different time periods are different, the data verification module performs combined analysis on the errors epsilon and the analysis errors of the BIM analysis module to obtain a total supervision error, and the supervision error is sent to the target analysis module and the risk assessment module.
3. The visual project supervision system according to claim 1, wherein the target analysis module judges the supervision error after receiving the supervision error, the target analysis module retrieves a judgment threshold of the supervision error from the data storage module and judges the supervision error according to the judgment threshold, when the supervision error exceeds the judgment threshold, the target analysis module analyzes the data content corresponding to the construction data classified into the newly added collection type and the continuously collected type at the time end corresponding to the supervision error, first extracts the influencing factor indexes of the two types of construction data respectively, establishes a target function according to an influencing anger index, and then carries out influence analysis on the influencing factor indexes according to the target function to obtain a continuously changing parameter and an intermediate end changing parameter, and then establishes a mathematical analysis equation in an n-dimensional space respectively according to the continuously changing parameter and the discontinuously changing parameter, and calculating an extreme value solution of the equation in the critical state, and sending a target analysis result of the two types of data to the risk evaluation module by the target analysis module.
4. The visual engineering supervision system according to claim 1, wherein the BIM analysis module is a management center for implementing information integration and data analysis, the BIM analysis module performs data analysis according to construction data, performs data evaluation prediction according to already generated construction data to obtain a platform prediction result, receives a comparison result of a comparison analysis by comparing a risk evaluation result with a platform prediction result after the risk evaluation module performs risk evaluation according to a target analysis result of a target analysis module to obtain a risk evaluation result, and compares the risk evaluation result with the platform prediction result to obtain the comparison result, and in the comparison process, the BIM analysis module compares the risk evaluation result corresponding to the influence factor index corresponding to the target analysis result with the platform prediction result in the same time period.
5. The visual project supervision system according to claim 1, wherein the data acquisition module acquires construction data generated during the construction process of a project, the acquisition process of the construction data includes a continuous acquisition process and an inter-end acquisition process, the continuous acquisition process is an acquisition process of the construction data of which the data acquisition module is constant according to the update frequency, the acquisition process of the construction data of which the acquisition and update frequency is not a constant value is performed for the first time as the inter-end acquisition process, the data of different acquisition processes are classified according to the update frequency, the update time, the update data amount and the data type of the construction data acquisition, and the data storage module performs distributed storage on the construction data acquired by the data acquisition module.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115766501A (en) * | 2022-11-04 | 2023-03-07 | 四川川交路桥有限责任公司 | Tunnel construction data management system and method based on big data |
| CN117868996A (en) * | 2024-03-04 | 2024-04-12 | 山东科瑞特自动化装备有限责任公司 | Mining goaf multi-parameter monitoring system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160078698A1 (en) * | 2014-09-16 | 2016-03-17 | Honeywell International Inc. | System and Method for Auto-Configuration of Devices in BIM Using Bluetooth Low Energy Devices |
| CN113591187A (en) * | 2021-07-21 | 2021-11-02 | 珠海市交通勘察设计院有限公司 | Road and bridge design method and system based on BIM real scene model |
| CN113762791A (en) * | 2021-09-13 | 2021-12-07 | 郑州铁路职业技术学院 | Railway engineering cost management system |
| CN113780823A (en) * | 2021-09-14 | 2021-12-10 | 杭州显宏信息工程咨询有限公司 | Intelligent project supervision system and supervision method based on image acquisition system |
| CN113919568A (en) * | 2021-10-12 | 2022-01-11 | 郑州亚欧交通职业学院 | Subway construction monitoring system based on Internet of things |
-
2022
- 2022-04-25 CN CN202210440294.4A patent/CN114819628B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160078698A1 (en) * | 2014-09-16 | 2016-03-17 | Honeywell International Inc. | System and Method for Auto-Configuration of Devices in BIM Using Bluetooth Low Energy Devices |
| CN113591187A (en) * | 2021-07-21 | 2021-11-02 | 珠海市交通勘察设计院有限公司 | Road and bridge design method and system based on BIM real scene model |
| CN113762791A (en) * | 2021-09-13 | 2021-12-07 | 郑州铁路职业技术学院 | Railway engineering cost management system |
| CN113780823A (en) * | 2021-09-14 | 2021-12-10 | 杭州显宏信息工程咨询有限公司 | Intelligent project supervision system and supervision method based on image acquisition system |
| CN113919568A (en) * | 2021-10-12 | 2022-01-11 | 郑州亚欧交通职业学院 | Subway construction monitoring system based on Internet of things |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115766501A (en) * | 2022-11-04 | 2023-03-07 | 四川川交路桥有限责任公司 | Tunnel construction data management system and method based on big data |
| CN115766501B (en) * | 2022-11-04 | 2023-08-25 | 四川川交路桥有限责任公司 | Tunnel construction data management system and method based on big data |
| CN117868996A (en) * | 2024-03-04 | 2024-04-12 | 山东科瑞特自动化装备有限责任公司 | Mining goaf multi-parameter monitoring system |
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