Dynamic monitoring method and system for engineering projects based on the entire life cycle

Abstract

The present invention relates to the technical field of engineering project management, and provides a method and system for dynamic monitoring of engineering projects based on the entire life cycle, including: obtaining an engineering project to be monitored, analyzing the project goals and project requirements corresponding to the engineering project, decomposing the project goals, obtaining project subordinate goals, and calculating the demand priority corresponding to the project requirements; collecting the engineering building entities corresponding to the engineering project and the corresponding building entity information, and using the building information model to construct a simulation engineering project of the engineering project; performing a simulated construction process of the simulation engineering project throughout the entire life cycle, determining the project risk factors corresponding to the engineering project, and calculating the risk deviation of the project risk factors to the engineering project; based on the risk deviation, formulating a dynamic monitoring strategy corresponding to the engineering project, executing the dynamic monitoring process of the engineering project, and obtaining the monitoring results. The present invention aims to improve the accuracy of dynamic monitoring of engineering projects.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering project management, and in particular to a method and system for dynamic monitoring of engineering projects based on the entire life cycle. Background Art

[0002] With the rapid development of the construction industry, the scale and complexity of engineering projects are increasing. In order to improve the project management efficiency of engineering projects, it is necessary to monitor the engineering projects in order to discover problems and cost-effectiveness issues in the engineering projects.

[0003] Traditional project management methods mainly rely on regular manual inspections and reports. Due to the time lag in data collection, management delays occur during project management, leading to errors in project decision-making. In addition, the collected data is not comprehensive enough to achieve all-round management of engineering projects, which in turn leads to low management efficiency of engineering projects. There is an urgent need for a method that can improve the accuracy of dynamic monitoring of engineering projects. Summary of the invention

[0004] The present invention provides a method and system for dynamic monitoring of engineering projects based on the entire life cycle, the main purpose of which is to improve the accuracy of dynamic monitoring of engineering projects.

[0005] To achieve the above object, the present invention provides a method for dynamic monitoring of engineering projects based on the entire life cycle, comprising:

[0006] Acquire the engineering project to be monitored, analyze the project goals and project requirements corresponding to the engineering project, decompose the project goals to obtain project subordinate goals, and calculate the demand priority corresponding to the project requirements based on the project subordinate goals;

[0007] According to the demand priority, the engineering construction entities corresponding to the engineering project and the corresponding building entity information are collected, and the building entity images corresponding to the engineering construction entities are photographed, and the building entity information and the building entity images are input into a pre-trained building information model as input data, and the building information model is used to construct a simulation engineering project of the engineering project;

[0008] Performing simulated construction processing on the simulated engineering project throughout its life cycle, and collecting construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determining the project risk factors corresponding to the engineering project, and calculating the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data;

[0009] Based on the risk deviation, a dynamic monitoring strategy corresponding to the engineering project is formulated, and according to the dynamic monitoring strategy, a dynamic monitoring process for the engineering project is performed to obtain a monitoring result.

[0010] Optionally, decomposing the project goal to obtain project subordinate goals includes:

[0011] Obtaining the project process corresponding to the project goal, and collecting process information corresponding to the project process;

[0012] Calculating information entropy corresponding to the process information;

[0013] Based on the information entropy, key project processes are screened out from the project processes;

[0014] Decompose the key project processes into objectives to obtain subordinate project objectives.

[0015] Optionally, calculating the demand priority corresponding to the project demand according to the project subordinate target includes:

[0016] Extracting the target attribute corresponding to the subordinate target of the project, and calculating the attribute weight value corresponding to the target attribute;

[0017] Extracting core target attributes from the target attributes according to the attribute weight values;

[0018] Analyze the demand functions corresponding to the project requirements, and calculate the fit index between the demand functions and the core target attributes;

[0019] According to the fit index, the demand priority corresponding to the project demand is determined.

[0020] Optionally, the calculating the fit index between the demand function and the core target attribute includes:

[0021] Vectorizing the required functions and the core target attributes respectively to obtain a function vector and an attribute vector;

[0022] Calculating the vector weights corresponding to the function vector and the attribute vector respectively to obtain the function vector weight and the attribute vector weight;

[0023] Calculate the vector interaction weight between the function vector and the attribute vector by combining the function vector weight and the attribute vector weight;

[0024] Combining the function vector, the attribute vector, the vector interaction weight, the function vector weight, and the attribute vector weight, the fit index between the required function and the core target attribute is calculated by the following formula:

[0025]

[0026] Among them, C represents the fit index between the demand function and the core target attribute, A a represents the ath vector in the function vector, f a represents the weight of the ath vector in the function vector weight, B b represents the bth vector in the attribute vector, e b represents the weight corresponding to the bth vector in the attribute vector weight, a and b represent the vector sequence numbers corresponding to the function vector and the attribute vector, n and m represent the number of vectors corresponding to the function vector and the attribute vector, respectively. ab Represents the vector interaction weight between the a-th and b-th vectors in the feature vector and the attribute vector.

[0027] Optionally, the step of inputting the building entity information and the building entity image as input data into a pre-trained building information model, and constructing a simulation project of the project using the building information model, comprises:

[0028] Utilizing the information parsing layer in the building information model to parse the building entity information to obtain entity attribute information;

[0029] Using the image screening layer in the building information model to screen the building entity image to obtain a target entity image;

[0030] Performing image optimization processing on the target entity image using the image optimization layer in the building information model to obtain an optimized entity image;

[0031] Using the feature recognition layer in the building information model to identify the building entity features corresponding to the optimized entity image, and detecting the building entity outline in the optimized entity image;

[0032] Combining the entity attribute information and the building entity characteristics, using the computational simulation layer in the building information model to calculate the performance index value corresponding to the engineering building entity;

[0033] The performance index value and the building entity outline are combined to construct a simulation project of the project using the visualization layer in the building information model.

[0034] Optionally, the identifying building entity features corresponding to the optimized entity image by using a feature recognition layer in the building information model includes:

[0035] Using the background segmentation algorithm in the feature recognition layer to perform background segmentation on the optimized entity image to obtain an entity foreground image;

[0036] Utilizing the color convolution layer in the feature recognition layer to extract entity color features corresponding to the entity foreground image;

[0037] Utilizing the texture convolution layer in the feature recognition layer to extract entity texture features corresponding to the entity foreground image;

[0038] Utilizing the morphological convolution layer in the feature recognition layer to extract entity morphological features corresponding to the entity foreground image;

[0039] Extracting entity layout features corresponding to the entity foreground image using the spatial convolution layer in the feature recognition layer;

[0040] The feature selection layer in the feature recognition layer is used to perform feature selection processing on the entity color feature, the entity texture feature, the entity morphology feature and the entity layout feature to obtain the architectural entity features of the entity foreground image.

[0041] Optionally, determining the project risk factors corresponding to the engineering project includes:

[0042] Dispatching historical project construction data corresponding to the engineering project, and identifying accident events of the historical project construction data;

[0043] Counting the event frequencies corresponding to the accident events, and extracting key accident events from the accident events based on the event frequencies;

[0044] Performing event decomposition processing on the key accident event to obtain event elements, and analyzing risk elements from the event elements;

[0045] Calculating the element correlation coefficient between the risk element and the event element, and extracting the potential risk element in the event element according to the element correlation coefficient;

[0046] The risk factors and potential risk factors are combined to obtain the project risk factors corresponding to the engineering project.

[0047] Optionally, the calculating the element correlation coefficient between the risk element and the event element includes:

[0048] Quantifying the risk factor and the event factor respectively to obtain a risk factor value and an event factor value;

[0049] According to the risk factor value and the event factor value, respectively calculating the average values ​​corresponding to the risk factor and the event factor to obtain the risk factor mean value and the event factor mean value;

[0050] According to the risk factor mean and the event factor mean, the standard deviations corresponding to the risk factor and the event factor are calculated respectively to obtain the risk standard deviation and the event standard deviation;

[0051] In combination with the risk standard deviation, the event standard deviation, the risk factor mean, the event factor mean, the risk factor value and the event factor value, the factor correlation coefficient between the risk factor and the event factor is calculated by the following formula:

[0052]

[0053] Among them, F represents the factor correlation coefficient between risk factors and event factors, Q i represents the value of the ith risk factor, represents the mean value of risk factors, W j represents the j-th event element value, represents the mean of event elements, S Q represents the risk standard deviation, S W represents the event standard deviation, i and j represent the serial numbers corresponding to the risk factor value and event factor value respectively, and x and y represent the quantities corresponding to the risk factor value and event factor value respectively.

[0054] Optionally, calculating the risk deviation of the project risk factor to the engineering project based on the project accident data and the project operation data includes:

[0055] Calculate the factor criticality of the project risk factor at each stage of the engineering project based on the project accident data;

[0056] Calculate the loss severity index corresponding to the project risk factor at each stage of the engineering project based on the project operation data;

[0057] Combining the loss severity index and the factor criticality, the risk deviation of the project risk factor to the engineering project is calculated by the following formula:

[0058]

[0059] Among them, R represents the risk deviation of project risk factors to engineering projects, H fd G represents the loss severity index corresponding to the fth factor in the project risk factor at the d stage of the project, fd It represents the criticality of the fth factor in the project risk factors at the d stage of the project, P fd It represents the probability of the fth factor in the project risk factor at the d stage of the project, f represents the serial number of the project risk factor, d represents the initial stage of the project, and h represents the total number of stages of the project.

[0060] A dynamic monitoring system for engineering projects based on the entire life cycle, characterized in that the system comprises:

[0061] The priority calculation module is used to obtain the engineering project to be monitored, analyze the project goals and project requirements corresponding to the engineering project, decompose the project goals to obtain project subordinate goals, and calculate the demand priority corresponding to the project requirements based on the project subordinate goals;

[0062] A project simulation module is used to collect the engineering construction entities and the corresponding building entity information of the engineering project according to the demand priority, and to take the building entity images corresponding to the engineering construction entities, input the building entity information and the building entity images as input data into a pre-trained building information model, and use the building information model to construct a simulation engineering project of the engineering project;

[0063] A risk deviation calculation module is used to perform simulated construction processing on the simulated engineering project throughout its life cycle, and collect construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determine the project risk factors corresponding to the engineering project, and calculate the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data;

[0064] The dynamic monitoring module is used to formulate a dynamic monitoring strategy corresponding to the engineering project based on the risk deviation degree, and execute dynamic monitoring processing on the engineering project according to the dynamic monitoring strategy to obtain a monitoring result.

[0065] By analyzing the project goals and project requirements corresponding to the engineering project, the present invention can understand the project achievement goals and the requirements that the project needs to meet. By decomposing the project goals, the project goals can be refined into more specific and executable small goals, thereby providing a basis for the subsequent calculation of demand priorities. According to the demand priorities, the present invention collects the engineering construction entities corresponding to the engineering project and the corresponding building entity information. The information of the building entities with the demand priority can be collected in detail, and the information of the building entities with low demand priority can be simply collected, thereby simplifying the information collection process, and the familiarity with the engineering project can be increased through the engineering construction entities and the corresponding building entity information. By shooting the building entity image corresponding to the engineering construction entity, it is convenient for the subsequent construction processing of the simulation engineering project of the engineering project. The present invention can obtain the data of the simulation construction process of the simulation engineering project from the beginning to the end by performing the simulation construction processing of the whole life cycle of the simulation engineering project, which provides a basis for the subsequent analysis of the project risk factors. By determining the project risk factors corresponding to the engineering project, the potential factors that have an adverse effect on the engineering project can be obtained. The present invention formulates the dynamic monitoring strategy corresponding to the engineering project based on the risk deviation, and then obtains the monitoring scheme corresponding to the process project. According to the dynamic monitoring strategy, the dynamic monitoring processing of the engineering project is performed to improve the detection accuracy of the engineering project. Therefore, the method and system for dynamic monitoring of engineering projects based on the whole life cycle provided by the embodiment of the present invention can improve the accuracy of dynamic monitoring of engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic diagram of a flow chart of a method for dynamic monitoring of an engineering project based on the entire life cycle provided by an embodiment of the present invention;

[0067] Figure 2 A functional module diagram of a full life cycle-based engineering project dynamic monitoring system provided by one embodiment of the present invention.

[0068] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0069] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0070] The embodiment of the present application provides a method for dynamic monitoring of engineering projects based on the entire life cycle. In the embodiment of the present application, the execution subject of the method for dynamic monitoring of engineering projects based on the entire life cycle includes but is not limited to at least one of the electronic devices such as the server, the terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for dynamic monitoring of engineering projects based on the entire life cycle can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0071] Reference Figure 1 FIG. 1 is a flow chart of a method for dynamic monitoring of an engineering project based on the entire life cycle provided by an embodiment of the present invention. In this embodiment, the method for dynamic monitoring of an engineering project based on the entire life cycle includes steps S1-S4.

[0072] S1. Obtain the engineering project to be monitored, analyze the project goals and project requirements corresponding to the engineering project, decompose the project goals to obtain project subordinate goals, and calculate the demand priority corresponding to the project requirements based on the project subordinate goals.

[0073] By analyzing the project goals and project requirements corresponding to the engineering project, the present invention can understand the project achievement goals and project requirements that need to be met of the engineering project, and by decomposing the project goals, the project goals can be refined into more specific and executable small goals, thereby providing a basis for the subsequent calculation of demand priorities, wherein the engineering project is a construction task carried out to achieve a specific goal, the project goals and the project requirements are respectively the achievement goals and requirements that need to be met corresponding to the engineering project, and the project subordinate goals are executable sub-goals corresponding to the project goals. Optionally, the analysis of the project goals and project requirements corresponding to the engineering project can be achieved through a brainstorming method.

[0074] As an embodiment of the present invention, the target decomposition of the project goal to obtain project subordinate goals includes: obtaining the project process corresponding to the project goal, collecting process information corresponding to the project process, calculating the information entropy corresponding to the process information, screening out key project processes from the project process based on the information entropy, and target decomposing the key project processes to obtain project subordinate goals.

[0075] Among them, the project process is the workflow corresponding to the project goal, the process information is the process description information corresponding to the project process, the information entropy represents the uncertainty corresponding to the process information, and the lower the information entropy, the more important the corresponding process information is, and the key project process is the representative process in the project process.

[0076] Optionally, the project process corresponding to the project goal can be obtained through a project plan, which is a record of the overall plan corresponding to the project process; the collection of process information corresponding to the project process can be achieved through a questionnaire survey method; the information entropy corresponding to the process information can be calculated by a Shannon entropy algorithm; the information entropy is compared with a preset information entropy, and when the information entropy is greater than the preset information entropy, the key project process is screened out from the project process, and the preset information entropy can be set to 0.8, or it can be set according to the actual application scenario; a process fishbone diagram corresponding to the key project process is constructed by using the fishbone diagram method, and the target decomposition of the key project process is achieved according to the process fishbone diagram to obtain the project subordinate target.

[0077] The present invention calculates the demand priority corresponding to the project demand based on the project subordinate target, so as to understand the importance of the project demand, thereby facilitating the subsequent collection and processing of relevant information of the engineering project, wherein the demand priority indicates the importance of the project demand.

[0078] As an embodiment of the present invention, the demand priority corresponding to the project demand is calculated based on the project subordinate target, including: extracting the target attribute corresponding to the project subordinate target, calculating the attribute weight value corresponding to the target attribute, extracting the core target attribute in the target attribute according to the attribute weight value, analyzing the demand function corresponding to the project demand, calculating the fit index between the demand function and the core target attribute, and determining the demand priority corresponding to the project demand according to the fit index.

[0079] Among them, the target attribute is the target feature description of the project subordinate target, the attribute weight value indicates the importance of the target attribute, the core target attribute is a representative attribute in the target attribute, the requirement function is the specific function realized by the project requirement, and the fit index indicates the fit degree between the requirement function and the core target attribute. Optionally, the extraction of the target attribute corresponding to the project subordinate target can be achieved through natural language processing (NLP) technology, such as syntactic analysis method; the calculation of the attribute weight value corresponding to the target attribute can be achieved through entropy weight method; according to the attribute weight value, the attribute weight values ​​corresponding to the attributes of the same nature in the target attributes are compared, and the attribute corresponding to the attribute weight value with the largest value is selected as the core target attribute; the analysis of the requirement function corresponding to the project requirement can be achieved through semantic analysis method; the fit indexes corresponding to the project requirements are summed to obtain a total index, and the requirement priority corresponding to the project requirement is set according to the value of the total index. For example, if the total indexes are 6, 8, and 10 respectively, the corresponding requirement priorities are low, medium, and high respectively.

[0080] Further, as an embodiment of the present invention, the calculation of the fit index between the demand function and the core target attribute includes: vectorizing the demand function and the core target attribute respectively to obtain a function vector and an attribute vector, respectively calculating the vector weights corresponding to the function vector and the attribute vector to obtain a function vector weight and an attribute vector weight, combining the function vector weight and the attribute vector weight, calculating the vector interaction weight between the function vector and the attribute vector, combining the function vector, the attribute vector, the vector interaction weight, the function vector weight and the attribute vector weight, and calculating the fit index between the demand function and the core target attribute by the following formula:

[0081]

[0082] Among them, C represents the fit index between the demand function and the core target attribute, A a represents the ath vector in the function vector, f a represents the weight of the ath vector in the function vector weight, B b represents the bth vector in the attribute vector, e b represents the weight corresponding to the bth vector in the attribute vector weight, a and b represent the vector sequence numbers corresponding to the function vector and the attribute vector, n and m represent the number of vectors corresponding to the function vector and the attribute vector, respectively. ab Represents the vector interaction weight between the a-th and b-th vectors in the feature vector and the attribute vector.

[0083] Among them, the function vector and the attribute vector are respectively the expression vectors corresponding to the requirement function and the core target attribute, the function vector weight and the attribute vector weight respectively represent the importance of the vectors corresponding to the function vector and the attribute vector, and the vector interaction weight represents the relative importance between the function vector and the attribute vector. Optionally, the vectorization processing of the requirement function and the core target attribute can be implemented by the word2vec algorithm; the calculation of the vector weights corresponding to the function vector and the attribute vector can be obtained by the corresponding vector feature values; the sum of the weights of the function vector weight and the attribute vector weight corresponding to the function vector and the attribute vector is calculated, and the ratio between the function vector and the weight and the sum of the weights is calculated to obtain the vector interaction weight between the function vector and the attribute vector.

[0084] S2. According to the demand priority, the engineering construction entities corresponding to the engineering project and their corresponding building entity information are collected, and the building entity images corresponding to the engineering construction entities are photographed, and the building entity information and the building entity images are input into a pre-trained building information model as input data, and the building information model is used to construct a simulation engineering project of the engineering project.

[0085] The present invention collects the engineering construction entities corresponding to the engineering project and the corresponding building entity information according to the demand priority. The information of the building entities with the demand priority can be collected in detail, and the information of the building entities with low demand priority can be simply collected, thereby simplifying the information collection process. In addition, the familiarity with the engineering project can be increased through the engineering construction entities and the corresponding building entity information. By shooting the building entity image corresponding to the engineering construction entity, the subsequent construction process of the simulation engineering project of the engineering project is facilitated, wherein the engineering construction entity is a building existing in the engineering project, the building entity information is the descriptive information corresponding to the engineering construction entity, and the building entity image is the shot image corresponding to the engineering construction entity. The collection of the engineering construction entity corresponding to the engineering project and the corresponding building entity information can be achieved through a questionnaire survey method; the building entity image corresponding to the engineering construction entity can be obtained by shooting with an unmanned aerial vehicle.

[0086] The present invention inputs the building entity information and the building entity image as input data into a pre-trained building information model, and uses the building information model to construct a project construction model of the engineering project, so as to obtain a virtual simulation body of the engineering project, which is convenient for subsequent simulation construction processing of the entire life cycle of the simulation engineering project, wherein the building information model is a neural network model for constructing a simulation body corresponding to a building, and the simulation engineering project is a simulation body of all buildings included in the engineering project.

[0087] As an embodiment of the present invention, the building entity information and the building entity image are input as input data into a pre-trained building information model, and the building information model is used to construct a simulation project of the engineering project, including: using the information parsing layer in the building information model to perform information parsing on the building entity information to obtain entity attribute information, using the image screening layer in the building information model to perform screening processing on the building entity image to obtain a target entity image, using the image optimization layer in the building information model to perform image optimization processing on the target entity image to obtain an optimized entity image, using the feature recognition layer in the building information model to identify the building entity features corresponding to the optimized entity image, and detecting the building entity contour in the optimized entity image, combining the entity attribute information and the building entity features, using the computational simulation layer in the building information model to calculate the performance index value corresponding to the engineering building entity, combining the performance index value and the building entity contour, and using the visualization layer in the building information model to construct the simulation project of the engineering project.

[0088] Among them, the information parsing layer is a neural layer for content analysis of the building entity information, which is composed of a principal component analysis algorithm. The entity attribute information is information feature description information in the building entity information, such as material characteristics. The image screening layer is a neural layer for screening and removing duplicate images and low-quality images in the building entity image, which is composed of a hash algorithm and a similarity function. The target entity image is an image obtained after removing duplicate images and low-quality images in the building entity image. The image optimization layer is a neural layer for quality optimization processing of the target entity image, which is composed of a denoising algorithm and an image enhancement algorithm, such as a Gaussian filtering algorithm and a histogram equalization algorithm. The building entity feature is an entity representation in the optimized entity image. The computational simulation layer is a neural layer for calculating the specific numerical value corresponding to the performance index of the engineering building entity in combination with the entity attribute information and the building entity feature, which is composed of various algorithms, such as a finite element analysis algorithm, a fluid dynamics algorithm, a thermodynamic calculation model, etc. The visualization layer is a neural layer for constructing a simulation engineering project of the engineering project, which is composed of a graphics rendering engine, such as OpenGL, DirectX, etc.

[0089] Further, as an optional embodiment of the present invention, the use of the feature recognition layer in the building information model to identify the building entity features corresponding to the optimized entity image includes: using the background segmentation algorithm in the feature recognition layer to perform background segmentation on the optimized entity image to obtain an entity foreground image, using the color convolution layer in the feature recognition layer to extract the entity color features corresponding to the entity foreground image, using the texture convolution layer in the feature recognition layer to extract the entity texture features corresponding to the entity foreground image, using the morphological convolution layer in the feature recognition layer to extract the entity morphological features corresponding to the entity foreground image, using the spatial convolution layer in the feature recognition layer to extract the entity layout features corresponding to the entity foreground image, and using the feature selection layer in the feature recognition layer to perform feature selection processing on the entity color features, the entity texture features, the entity morphological features and the entity layout features, respectively, to obtain the building entity features of the entity foreground image.

[0090] Among them, the background segmentation algorithm is an algorithm for performing background segmentation on the optimized entity image, such as a threshold segmentation method. The entity foreground image is an image obtained after the background in the optimized entity image is segmented and removed. The color convolution layer is a neural layer for extracting color features corresponding to the entity foreground image, which is composed of an HSV feature extraction algorithm. The texture convolution layer is a neural layer for extracting texture features corresponding to the entity foreground image, which is composed of a grayscale co-occurrence matrix. The morphological convolution layer is a neural layer for extracting morphological features corresponding to the entity foreground image, which is composed of a Sobel operator. The spatial convolution layer is a neural layer for extracting layout features corresponding to the entity foreground image, which is composed of an attention mechanism unit. The feature selection layer is a neural layer for selecting features, which is composed of an information gain function.

[0091] S3. Perform simulated construction processing on the simulated engineering project throughout its life cycle, and collect construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determine the project risk factors corresponding to the engineering project, and calculate the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data.

[0092] The present invention can obtain data of the simulated construction process of the simulated engineering project from the beginning to the end by performing simulated construction processing on the simulated engineering project throughout its life cycle, thereby providing a basis for the subsequent analysis of project risk factors. By determining the project risk factors corresponding to the engineering project, potential factors that have an adverse impact on the engineering project can be obtained, wherein the project accident data is data other than the project occurrence recorded in the construction simulation data, the project operation data is data related to the project operation recorded in the construction simulation data, and the project risk factors are potential factors that have an adverse impact on the engineering project. Furthermore, by scheduling the historical construction data of the engineering project, the construction environment and construction conditions in the historical construction data can be configured in the simulated engineering project, and the simulated construction processing of the simulated engineering project throughout its life cycle can be performed; the collection of construction simulation data during the simulated construction process can be implemented by a data collection tool, and the data collection tool is compiled in Java language; the project risk factors corresponding to the engineering project can be obtained by analyzing the historical construction data.

[0093] As an embodiment of the present invention, determining the project risk factors corresponding to the engineering project includes: scheduling historical project construction data corresponding to the engineering project, identifying accident events in the historical project construction data, counting the event frequencies corresponding to the accident events, extracting key accident events from the accident events based on the event frequencies, performing event decomposition processing on the key accident events to obtain event elements, analyzing risk elements from the event elements, calculating the element correlation coefficient between the risk elements and the event elements, extracting potential risk elements from the event elements based on the element correlation coefficient, and combining the risk elements and the potential risk elements to obtain the project risk factors corresponding to the engineering project.

[0094] Among them, the historical project construction data is the construction history record data between the process projects, the accident event is the description of the accident situation actually occurring in the target accident data, the event frequency is the number of occurrences of the accident event, the key accident event is an important event in the accident event, the event element is a component of the key accident event, the risk element is a dangerous factor in the event element, the element association coefficient represents the degree of association between the risk element and the event element, and the potential risk element is an uncertain factor in the event element that may cause adverse consequences in the future. Further, the scheduling of the historical project construction data corresponding to the engineering project can be achieved through a project database, which is a repository for storing project construction data; the identification of accident events in the target accident data can be achieved through a decision tree algorithm; when the event frequency is greater than or equal to 2, the corresponding accident event is extracted as a key accident event; the event decomposition processing of the key accident event can be achieved through an event tree analysis method; analyzing the risk element from the event element can be achieved through a bow tie analysis method; the element association coefficient is compared with a preset association coefficient, and when the element association coefficient is greater than the preset association coefficient, the corresponding event element is extracted as a potential risk element.

[0095] Further, as an optional embodiment of the present invention, the calculation of the element correlation coefficient between the risk factor and the event factor includes: quantifying the risk factor and the event factor respectively to obtain a risk factor value and an event factor value, calculating the average values ​​corresponding to the risk factor and the event factor respectively according to the risk factor value and the event factor value to obtain a risk factor mean and an event factor mean, calculating the standard deviations corresponding to the risk factor and the event factor respectively according to the risk factor mean and the event factor mean to obtain a risk standard deviation and an event standard deviation, and combining the risk standard deviation, the event standard deviation, the risk factor mean, the event factor mean, the risk factor value and the event factor value to calculate the element correlation coefficient between the risk factor and the event factor by the following formula:

[0096]

[0097] Among them, F represents the factor correlation coefficient between risk factors and event factors, Q i represents the value of the ith risk factor, represents the mean value of risk factors, W j represents the j-th event element value, represents the mean of event elements, S Q represents the risk standard deviation, S W represents the event standard deviation, i and j represent the serial numbers corresponding to the risk factor value and event factor value respectively, and x and y represent the quantities corresponding to the risk factor value and event factor value respectively.

[0098] Among them, the risk factor value and the event factor value are the expression values ​​corresponding to the risk factor and the event factor respectively. Furthermore, the quantification processing of the risk factor and the event factor can be achieved through the hierarchical analysis method. The specific steps are: determine the hierarchical structure of the risk factor and the event factor, decompose them into different levels, including the target level, the criterion level and the solution level, construct a judgment matrix, compare the importance of the elements at the same level two by two, construct a judgment matrix according to the comparison results, calculate the weight vector, and obtain the weight vector of each element by solving the eigenvector of the judgment matrix. Use the weight vector as the expression value to quantify the risk factor and the event factor; the standard deviation corresponding to the risk factor and the event factor can be achieved by a variance calculator.

[0099] The present invention calculates the risk deviation of the project risk factors on the engineering project based on the project accident data and the project operation data, so as to understand the degree of deviation of the engineering project from the expected goal caused by the project risk factors, wherein the risk deviation is the degree of deviation of the engineering project from the expected goal caused by the project risk factors.

[0100] As an embodiment of the present invention, the risk deviation of the project risk factor to the engineering project is calculated based on the project accident data and the project operation data, including: calculating the factor criticality corresponding to the project risk factor at each stage of the engineering project based on the project accident data, calculating the loss severity index corresponding to the project risk factor at each stage of the engineering project based on the project operation data, and combining the loss severity index and the factor criticality to calculate the risk deviation of the project risk factor to the engineering project by the following formula:

[0101]

[0102] Among them, R represents the risk deviation of project risk factors to engineering projects, H fd G represents the loss severity index corresponding to the fth factor in the project risk factor at the d stage of the project, fd It represents the criticality of the fth factor in the project risk factors at the d stage of the project, P fd It represents the probability of the fth factor in the project risk factor at the d stage of the project, f represents the serial number of the project risk factor, d represents the initial stage of the project, and h represents the total number of stages of the project.

[0103] Among them, the factor criticality represents the criticality corresponding to the project risk factor at each stage of the engineering project, and the loss severity index represents the degree of loss corresponding to the project risk factor at each stage of the engineering project. Optionally, the calculation of the factor criticality corresponding to the project risk factor at each stage of the engineering project can be achieved by the Bayesian network method, and the steps are: constructing a Bayesian network model, taking the project risk factors and different stages of each stage of the engineering project as nodes, and determining the probability relationship between the nodes based on the project accident data, and using Bayesian reasoning to calculate the posterior probability of each risk factor at a specific stage, and the posterior probability of the risk factor is the criticality at this stage; the calculation of the loss severity index corresponding to the project risk factor at each stage of the engineering project can be achieved by the simulation analysis method, and the specific steps are: using the project operation data to simulate the occurrence of different risk factors at different stages, predict the possible losses, and calculate the loss severity index of each risk factor at a specific stage based on the simulation results.

[0104] S4. Based on the risk deviation, a dynamic monitoring strategy corresponding to the engineering project is formulated, and according to the dynamic monitoring strategy, a dynamic monitoring process is performed on the engineering project to obtain a monitoring result.

[0105] The present invention formulates a dynamic monitoring strategy corresponding to the engineering project based on the risk deviation, and then obtains a monitoring plan corresponding to the process project. According to the dynamic monitoring strategy, dynamic monitoring processing of the engineering project is performed to improve the detection accuracy of the engineering project, wherein the dynamic monitoring strategy is a specific detection plan corresponding to the engineering project. Optionally, the formulation steps of the dynamic monitoring strategy corresponding to the engineering project are: when the risk deviation is at a low level, regular monitoring: for example, data collection and analysis are performed once a week, paying attention to the changing trend of project risk factors, routine inspection: according to the established engineering inspection process, daily inspections are performed on various links of the project to ensure that everything is operating normally, when the risk deviation is at a medium level, the monitoring frequency is strengthened: data collection and analysis of key risk factors are performed once a day or every two days, special inspections: for the occurrence of Carry out special inspections on specific areas of risk deviation, such as equipment operation status, construction process execution, etc., adjust resource allocation: appropriately increase resource investment in risk management, such as increasing safety management personnel, deploying more testing equipment, etc. When the risk deviation is at a high level, real-time monitoring: use advanced monitoring equipment and technology to monitor key risk points in real time to ensure that problems can be discovered in time, emergency shutdown: if the risk may lead to serious consequences, the relevant engineering activities should be stopped immediately, and a comprehensive risk assessment and rectification should be carried out. Establish an emergency team: an emergency team composed of project leaders, experts and personnel from relevant departments should quickly formulate and implement response measures, and report regularly: report risk status and response progress to senior management and relevant stakeholders regularly to ensure information transparency, so as to obtain the dynamic monitoring strategy corresponding to the engineering project; the dynamic monitoring and processing of the engineering project can be carried out through the real-time monitoring system.

[0106] By analyzing the project goals and project requirements corresponding to the engineering project, the present invention can understand the project achievement goals and the requirements that the project needs to meet. By decomposing the project goals, the project goals can be refined into more specific and executable small goals, thereby providing a basis for the subsequent calculation of demand priorities. According to the demand priorities, the present invention collects the engineering construction entities corresponding to the engineering project and the corresponding building entity information. The information of the building entities with the demand priority can be collected in detail, and the information of the building entities with low demand priority can be simply collected, thereby simplifying the information collection process, and the familiarity with the engineering project can be increased through the engineering construction entities and the corresponding building entity information. By shooting the building entity image corresponding to the engineering construction entity, it is convenient for the subsequent construction processing of the simulation engineering project of the engineering project. The present invention can obtain the data of the simulation construction process of the simulation engineering project from the beginning to the end by performing the simulation construction processing of the whole life cycle of the simulation engineering project, which provides a basis for the subsequent analysis of the project risk factors. By determining the project risk factors corresponding to the engineering project, the potential factors that have an adverse effect on the engineering project can be obtained. The present invention formulates the dynamic monitoring strategy corresponding to the engineering project based on the risk deviation, and then obtains the monitoring scheme corresponding to the process project. According to the dynamic monitoring strategy, the dynamic monitoring processing of the engineering project is performed to improve the detection accuracy of the engineering project. Therefore, the dynamic monitoring method of the engineering project based on the whole life cycle provided by the embodiment of the present invention can improve the accuracy of dynamic monitoring of engineering projects.

[0107] like Figure 2 1 is a functional module diagram of a full life cycle engineering project dynamic monitoring system provided by an embodiment of the present invention.

[0108] The engineering project dynamic monitoring system 100 based on the whole life cycle described in the present invention can be installed in an electronic device. According to the functions to be implemented, the engineering project dynamic monitoring system 100 based on the whole life cycle can include a priority calculation module 101, a project simulation module 102, a risk deviation calculation module 103 and a dynamic monitoring module 104. The module described in the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0109] In this embodiment, the functions of each module / unit are as follows:

[0110] The priority calculation module 101 is used to obtain the engineering project to be monitored, analyze the project objectives and project requirements corresponding to the engineering project, decompose the project objectives to obtain project subordinate objectives, and calculate the demand priority corresponding to the project requirements according to the project subordinate objectives;

[0111] The project simulation module 102 is used to collect the engineering construction entities and the corresponding building entity information of the engineering project according to the demand priority, and take the building entity images corresponding to the engineering construction entities, input the building entity information and the building entity images as input data into a pre-trained building information model, and use the building information model to construct a simulation engineering project of the engineering project;

[0112] The risk deviation calculation module 103 is used to perform simulated construction processing on the simulated engineering project throughout its life cycle, and collect construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determine the project risk factors corresponding to the engineering project, and calculate the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data;

[0113] The dynamic monitoring module 104 is used to formulate a dynamic monitoring strategy corresponding to the engineering project based on the risk deviation, and perform dynamic monitoring processing on the engineering project according to the dynamic monitoring strategy to obtain a monitoring result.

[0114] In detail, each module described in the engineering project dynamic monitoring system 100 based on the whole life cycle described in the embodiment of the present application is used in the same manner as described above. Figure 1 The technical means described in the article are the same as the dynamic monitoring method of engineering projects based on the entire life cycle, and can produce the same technical effects, so they will not be repeated here.

[0115] In the several embodiments provided by the present invention, it should be understood that the provided methods and systems can be implemented in other ways. For example, the method embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A dynamic monitoring method for engineering projects based on the entire life cycle, characterized in that: The method comprises: Acquire an engineering project to be monitored, analyze the project goal and project demand corresponding to the engineering project, decompose the project goal to obtain project subordinate goals, and calculate the demand priority corresponding to the project demand according to the project subordinate goals, wherein the calculating the demand priority corresponding to the project demand according to the project subordinate goals includes: Extracting the target attribute corresponding to the subordinate target of the project, and calculating the attribute weight value corresponding to the target attribute; Extracting core target attributes from the target attributes according to the attribute weight values; Analyze the demand functions corresponding to the project requirements, and calculate the fit index between the demand functions and the core target attributes; Determine the demand priority corresponding to the project demand according to the fit index; The step of calculating the compatibility index between the demand function and the core target attribute includes: Vectorizing the required functions and the core target attributes respectively to obtain a function vector and an attribute vector; Calculating the vector weights corresponding to the function vector and the attribute vector respectively to obtain the function vector weight and the attribute vector weight; Calculate the vector interaction weight between the function vector and the attribute vector by combining the function vector weight and the attribute vector weight; Combining the function vector, the attribute vector, the vector interaction weight, the function vector weight, and the attribute vector weight, the fit index between the required function and the core target attribute is calculated by the following formula: Among them, C represents the fit index between the demand function and the core target attribute, A a represents the ath vector in the function vector, f a represents the weight of the ath vector in the function vector weight, B b represents the bth vector in the attribute vector, e b represents the weight corresponding to the bth vector in the attribute vector weight, a and b represent the vector sequence numbers corresponding to the function vector and the attribute vector, n and m represent the number of vectors corresponding to the function vector and the attribute vector, respectively. ab Represents the vector interaction weight between the ath and bth vectors in the function vector and the attribute vector; According to the demand priority, the engineering construction entities corresponding to the engineering project and the corresponding building entity information are collected, and the building entity images corresponding to the engineering construction entities are photographed, and the building entity information and the building entity images are input into a pre-trained building information model as input data, and the building information model is used to construct a simulation engineering project of the engineering project; Performing simulated construction processing on the simulated engineering project throughout its life cycle, and collecting construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determining the project risk factors corresponding to the engineering project, and calculating the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data; Based on the risk deviation, a dynamic monitoring strategy corresponding to the engineering project is formulated, and according to the dynamic monitoring strategy, a dynamic monitoring process for the engineering project is performed to obtain a monitoring result.

2. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 1, characterized in that: Decomposing the project objectives to obtain subordinate project objectives includes: Obtaining the project process corresponding to the project goal, and collecting process information corresponding to the project process; Calculating information entropy corresponding to the process information; Based on the information entropy, key project processes are screened out from the project processes; Decompose the key project processes into objectives to obtain subordinate project objectives.

3. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 1, characterized in that: The step of inputting the building entity information and the building entity image as input data into a pre-trained building information model, and using the building information model to construct a simulation project of the project, comprises: Utilizing the information parsing layer in the building information model to parse the building entity information to obtain entity attribute information; Using the image screening layer in the building information model to screen the building entity image to obtain a target entity image; Performing image optimization processing on the target entity image using the image optimization layer in the building information model to obtain an optimized entity image; Using the feature recognition layer in the building information model to identify the building entity features corresponding to the optimized entity image, and detecting the building entity outline in the optimized entity image; Combining the entity attribute information and the building entity characteristics, using the computational simulation layer in the building information model to calculate the performance index value corresponding to the engineering building entity; The performance index value and the building entity outline are combined to construct a simulation project of the project using the visualization layer in the building information model.

4. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 3, characterized in that: The step of using the feature recognition layer in the building information model to identify the building entity features corresponding to the optimized entity image includes: Using the background segmentation algorithm in the feature recognition layer to perform background segmentation on the optimized entity image to obtain an entity foreground image; Utilizing the color convolution layer in the feature recognition layer to extract entity color features corresponding to the entity foreground image; Utilizing the texture convolution layer in the feature recognition layer to extract entity texture features corresponding to the entity foreground image; Utilizing the morphological convolution layer in the feature recognition layer to extract entity morphological features corresponding to the entity foreground image; Extracting entity layout features corresponding to the entity foreground image using the spatial convolution layer in the feature recognition layer; The feature selection layer in the feature recognition layer is used to perform feature selection processing on the entity color feature, the entity texture feature, the entity morphology feature and the entity layout feature to obtain the architectural entity features of the entity foreground image.

5. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 1, characterized in that: Determining the project risk factors corresponding to the engineering project includes: Dispatching historical project construction data corresponding to the engineering project, and identifying accident events of the historical project construction data; Counting the event frequencies corresponding to the accident events, and extracting key accident events from the accident events based on the event frequencies; Performing event decomposition processing on the key accident event to obtain event elements, and analyzing risk elements from the event elements; Calculating the element correlation coefficient between the risk element and the event element, and extracting the potential risk element in the event element according to the element correlation coefficient; The risk factors and potential risk factors are combined to obtain the project risk factors corresponding to the engineering project.

6. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 5, characterized in that: The calculating the element correlation coefficient between the risk element and the event element comprises: Quantifying the risk factor and the event factor respectively to obtain a risk factor value and an event factor value; According to the risk factor value and the event factor value, respectively calculating the average values ​​corresponding to the risk factor and the event factor to obtain the risk factor mean value and the event factor mean value; According to the risk factor mean and the event factor mean, the standard deviations corresponding to the risk factor and the event factor are calculated respectively to obtain the risk standard deviation and the event standard deviation; In combination with the risk standard deviation, the event standard deviation, the risk factor mean, the event factor mean, the risk factor value and the event factor value, the factor correlation coefficient between the risk factor and the event factor is calculated by the following formula: Among them, F represents the factor correlation coefficient between risk factors and event factors, Q i represents the value of the ith risk factor, represents the mean value of risk factors, W j represents the j-th event element value, represents the mean of event elements, S Q represents the risk standard deviation, S W represents the event standard deviation, i and j represent the serial numbers corresponding to the risk factor value and event factor value respectively, and x and y represent the quantities corresponding to the risk factor value and event factor value respectively.

7. A method for dynamic monitoring of engineering projects based on the entire life cycle as claimed in claim 1, characterized in that: Calculating the risk deviation of the project risk factor to the engineering project based on the project accident data and the project operation data includes: Calculate the factor criticality of the project risk factor at each stage of the engineering project based on the project accident data; Calculate the loss severity index corresponding to the project risk factor at each stage of the engineering project based on the project operation data; Combining the loss severity index and the factor criticality, the risk deviation of the project risk factor to the engineering project is calculated by the following formula: Among them, R represents the risk deviation of project risk factors to engineering projects, H fd G represents the loss severity index corresponding to the fth factor in the project risk factor at the d stage of the project, fd It represents the criticality of the fth factor in the project risk factors at the d stage of the project, P fd It represents the probability of the fth factor in the project risk factor at the d stage of the project, f represents the serial number of the project risk factor, d represents the initial stage of the project, and h represents the total number of stages of the project.

8. A dynamic monitoring system for engineering projects based on the entire life cycle, characterized in that: The system comprises: The priority calculation module is used to obtain the engineering project to be monitored, analyze the project goal and project demand corresponding to the engineering project, decompose the project goal to obtain the project subordinate goal, and calculate the demand priority corresponding to the project demand according to the project subordinate goal, wherein the calculation of the demand priority corresponding to the project demand according to the project subordinate goal includes: Extracting the target attribute corresponding to the subordinate target of the project, and calculating the attribute weight value corresponding to the target attribute; Extracting core target attributes from the target attributes according to the attribute weight values; Analyze the demand functions corresponding to the project requirements, and calculate the fit index between the demand functions and the core target attributes; Determine the demand priority corresponding to the project demand according to the fit index; The step of calculating the compatibility index between the demand function and the core target attribute includes: Vectorizing the required functions and the core target attributes respectively to obtain a function vector and an attribute vector; Calculating the vector weights corresponding to the function vector and the attribute vector respectively to obtain the function vector weight and the attribute vector weight; Calculate the vector interaction weight between the function vector and the attribute vector by combining the function vector weight and the attribute vector weight; Combining the function vector, the attribute vector, the vector interaction weight, the function vector weight, and the attribute vector weight, the fit index between the required function and the core target attribute is calculated by the following formula: Among them, C represents the fit index between the demand function and the core target attribute, A a represents the ath vector in the function vector, f a represents the weight of the ath vector in the function vector weight, B b represents the bth vector in the attribute vector, e b represents the weight corresponding to the bth vector in the attribute vector weight, a and b represent the vector sequence numbers corresponding to the function vector and the attribute vector, n and m represent the number of vectors corresponding to the function vector and the attribute vector, respectively. ab Represents the vector interaction weight between the ath and bth vectors in the function vector and the attribute vector; A project simulation module is used to collect the engineering construction entities and the corresponding building entity information of the engineering project according to the demand priority, and to take the building entity images corresponding to the engineering construction entities, input the building entity information and the building entity images as input data into a pre-trained building information model, and use the building information model to construct a simulation engineering project of the engineering project; A risk deviation calculation module is used to perform simulated construction processing on the simulated engineering project throughout its life cycle, and collect construction simulation data during the simulated construction process, wherein the construction simulation data includes project accident data and project operation data, determine the project risk factors corresponding to the engineering project, and calculate the risk deviation of the project risk factors to the engineering project based on the project accident data and the project operation data; The dynamic monitoring module is used to formulate a dynamic monitoring strategy corresponding to the engineering project based on the risk deviation degree, and execute dynamic monitoring processing on the engineering project according to the dynamic monitoring strategy to obtain a monitoring result.

Images