Evaluation management method, device and equipment for energy engineering construction quality
By combining historical construction data with genetic algorithm optimization and real-time data evaluation, the problem of a single method for evaluating the construction quality of energy projects has been solved, and dynamic and accurate construction quality management has been achieved.
Patent Information
- Application Number
- CN202511103959.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-07
- Publication Date
- 2025-11-18
AI Technical Summary
Existing technologies lack comprehensive methods for assessing the construction quality of energy projects, resulting in low management efficiency.
By acquiring historical construction data, performing random combinations and genetic algorithm optimization, the optimal data combination and its weights are determined. Combined with real-time data, evaluation and similarity judgment are performed to achieve dynamic and targeted quality assessment.
It improves the scientific rigor and rationality of construction quality assessment, reduces assessment bias, enables timely detection of quality deficiencies, optimizes the management process, and enhances assessment management efficiency.
Smart Images
Figure CN120975633A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of energy engineering construction, in particular to an energy engineering construction quality evaluation management method, device and equipment. BACKGROUND
[0002] Energy engineering construction refers to the construction and construction process of various energy facilities for meeting energy demand, optimizing energy structure and improving energy utilization efficiency. Various energy facilities include but are not limited to power facilities such as power plants, substations and transmission lines, renewable energy facilities such as wind power plants, solar photovoltaic power stations, biomass power stations, geothermal power stations and hydropower stations, oil and gas facilities such as oil field development and natural gas pipelines, and hydrogen energy facilities.
[0003] The evaluation and management of energy engineering construction quality is crucial for energy engineering construction. In related technologies, only specific energy engineering construction quality is evaluated, and the evaluation method is single, which leads to the management of only specific energy engineering construction quality. When tracing the energy engineering construction quality, the data reflecting the overall quality of the energy engineering construction cannot be obtained, resulting in low efficiency of the management of energy engineering construction quality. SUMMARY
[0004] Therefore, the present application provides an energy engineering construction quality evaluation management method, device and equipment to solve the problem of single evaluation method and inability to track evaluation results in related technologies.
[0005] In a first aspect, the present application provides a method for evaluating and managing construction quality of energy engineering, comprising: obtaining historical energy engineering construction data of a plurality of energy engineering construction processes; randomly combining target energy engineering construction data corresponding to a plurality of management objects in the historical energy engineering construction data to obtain a plurality of energy engineering construction data combinations; selecting an optimal energy engineering construction data combination from the plurality of energy engineering construction data combinations and determining a target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination; evaluating the quality of each target energy engineering construction process according to real-time target energy engineering construction data of a plurality of target energy engineering construction processes and the target weight to obtain a target construction quality value corresponding to each target energy engineering construction process; the real-time target energy engineering construction data is real-time energy engineering construction data related to the optimal energy engineering construction data combination; determining whether the plurality of target energy engineering construction processes are similar according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data; and storing the real-time target energy engineering construction data and the target construction quality value of similar target energy engineering construction processes together and storing the real-time target energy engineering construction data and the target construction quality value of dissimilar target energy engineering construction processes separately according to the determination result.
[0006] The application randomly combines target energy engineering construction data corresponding to various management objects in historical energy engineering construction data, obtains various energy engineering construction data combinations, selects optimal energy engineering construction data combination from the various energy engineering construction data combinations, can mine the optimal energy engineering construction data combination that is more suitable for actual construction quality evaluation requirements, filters out the reference basis with the most value for quality evaluation from historical experience, helps to improve the scientificity and rationality of quality evaluation, and reduces evaluation deviation caused by blind data selection. The application determines the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination, can reflect the importance difference of data corresponding to different management objects in quality evaluation, makes the target construction quality value obtained in subsequent quality evaluation highlight the key influencing factors, and makes the target construction quality value more accurately reflect the actual construction quality. The application evaluates the quality of each target energy engineering construction process according to real-time target energy engineering construction data and target weight of multiple target energy engineering construction processes, obtains the target construction quality value corresponding to each target energy engineering construction process, realizes dynamic and targeted evaluation of construction quality, can timely find the quality advantages and disadvantages in the construction process, and compared with related technologies, the application can make the target construction quality value corresponding to each target energy engineering construction process more accurate through more accurate optimal energy engineering construction data combination and target weight. The application judges whether multiple target energy engineering construction processes are similar according to the target construction quality value corresponding to each target energy engineering construction process and real-time target energy engineering construction data, can classify multiple target energy engineering construction processes according to similarity, stores the real-time target energy engineering construction data and corresponding target construction quality value of similar target energy engineering construction processes together according to the judgment result, stores the real-time target energy engineering construction data and corresponding target construction quality value of dissimilar target energy engineering construction processes in a classified manner, optimizes the energy engineering construction quality management process, can timely find the difference reasons of energy engineering construction quality, facilitates batch analysis and tracing of similar energy engineering construction quality, can clearly distinguish the data of different energy engineering construction quality, and improves the efficiency of energy engineering construction quality evaluation management.
[0007] In an optional implementation, the target energy engineering construction data corresponding to each management object in the historical energy engineering construction data is randomly combined to obtain a plurality of energy engineering construction data combinations, including: classifying the historical energy engineering construction data according to the management objects to obtain a plurality of target energy engineering construction data; randomly selecting each target energy engineering construction data, and combining the selected data to obtain a plurality of energy engineering construction data combinations.
[0008] In an optional implementation, the optimal energy engineering construction data combination is selected from the plurality of energy engineering construction data combinations, including: taking the plurality of energy engineering construction data combinations as an initial population, performing cross variation processing on the individuals in the initial population according to their fitness, to obtain a target population; performing fitness analysis on the target population, returning to the cross variation processing step, and repeatedly iterating until a preset termination condition is reached, to obtain the optimal energy engineering construction data combination.
[0009] In an optional implementation, the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination is determined, including: obtaining the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination according to the quotient of the data quantity of each target energy engineering construction data and the total data quantity.
[0010] In an optional implementation, the quality of each target energy engineering construction process is evaluated according to the real-time target energy engineering construction data and the target weight of the plurality of target energy engineering construction processes, to obtain a target construction quality value corresponding to each target energy engineering construction process, including: obtaining real-time energy engineering construction data of the plurality of target energy engineering construction processes, and selecting real-time target energy engineering construction data related to the optimal energy engineering construction data combination from the real-time energy engineering construction data; obtaining a construction quality value corresponding to each management object according to the product of the sum of the data corresponding to each management object in the real-time target energy engineering construction data and the corresponding target weight; summing the construction quality values corresponding to the plurality of management objects to obtain a target construction quality value corresponding to each target energy engineering construction process.
[0011] In one optional implementation, based on the target construction quality value and real-time target energy project construction data corresponding to each target energy project construction process, it is determined whether multiple target energy project construction processes are similar, and whether the absolute value of the difference between the target construction quality values corresponding to any two target energy project construction processes is less than a first preset value; if the absolute value of the difference between the target construction quality values corresponding to any two target energy project construction processes is less than the first preset value, the Euclidean distance between the real-time target energy project construction data corresponding to these two target energy project construction processes is determined; if the Euclidean distance between the real-time target energy project construction data corresponding to these two target energy project construction processes is less than a second preset value, then the two target energy project construction processes are determined to be similar.
[0012] Secondly, the present invention provides an energy engineering construction quality assessment and management device, comprising: a historical data classification unit, used to acquire historical energy engineering construction data of multiple energy engineering construction processes, and randomly combine target energy engineering construction data of different management objects in the historical energy engineering construction data to obtain multiple energy engineering construction data combinations; an assessment index design unit, used to select the optimal energy engineering construction data combination from the multiple energy engineering construction data combinations, and determine the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination; and a quality assessment unit, used to assess the quality of each target energy engineering construction process based on the real-time target energy engineering construction data and target weights. The quality of the construction process is evaluated to obtain the target construction quality value corresponding to each target energy project construction process; real-time target energy project construction data is the real-time energy project construction data related to the optimal combination of energy project construction data; a similarity judgment unit is used to determine whether multiple target energy project construction processes are similar based on the target construction quality value corresponding to each target energy project construction process and the real-time target energy project construction data; an evaluation data management unit is used to store the real-time target energy project construction data and corresponding target construction quality values of similar target energy project construction processes together, and to classify and store the real-time target energy project construction data and corresponding target construction quality values of dissimilar target energy project construction processes.
[0013] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the energy engineering construction quality assessment and management method of the first aspect or any corresponding embodiment described above.
[0014] In a fourth aspect, the present application provides a computer readable storage medium, having stored thereon computer instructions for causing a computer to execute the energy engineering construction quality evaluation management method of the first aspect or any of the corresponding embodiments thereof.
[0015] In a fifth aspect, the present application provides a computer program product comprising computer instructions for causing a computer to execute the energy engineering construction quality evaluation management method of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the specific embodiments or the related art, the drawings needed to be used in the specific embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.
[0017] Figure 1 FIG. 1 is a flowchart of an energy engineering construction quality evaluation management method according to an embodiment of the present application.
[0018] Figure 2 FIG. 2 is a flowchart of another energy engineering construction quality evaluation management method according to an embodiment of the present application.
[0019] Figure 3 FIG. 3 is a flowchart of an energy engineering construction quality evaluation management system according to an embodiment of the present application.
[0020] Figure 4 FIG. 4 is a structural block diagram of an energy engineering construction quality evaluation management device according to an embodiment of the present application.
[0021] Figure 5 FIG. 5 is a hardware structure diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION
[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the scope of protection of the present application.
[0023] According to the embodiment of the present application, an energy engineering construction quality evaluation management method is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.
[0024] In the present embodiment, an energy engineering construction quality evaluation management method is provided, which can be used in a computer device, Figure 1 The flowchart of the energy engineering construction quality evaluation management method according to the embodiment of the present application is shown in FIG. 1, which includes the following steps: Figure 1
[0025] In step S101, historical energy engineering construction data of a plurality of energy engineering construction processes is obtained, and target energy engineering construction data corresponding to a plurality of management objects in the historical energy engineering construction data is randomly combined to obtain a plurality of energy engineering construction data combinations.
[0026] The energy engineering construction process is the whole process of energy engineering from the beginning to the completion, construction and supporting management activities; the historical energy engineering construction data is various objective records and quantitative data generated in the whole process from construction preparation to construction implementation, until completion and acceptance of the energy engineering that has been completed or is in the past construction stage.
[0027] In some optional embodiments, the target energy engineering construction data corresponding to the plurality of management objects in the historical energy engineering construction data is randomly combined to obtain a plurality of energy engineering construction data combinations, including: classifying the historical energy engineering construction data according to the management objects to obtain a plurality of target energy engineering construction data; randomly selecting each target energy engineering construction data, and combining the selected data to obtain a plurality of energy engineering construction data combinations.
[0028] The management objects include construction material management objects, construction personnel management objects, construction progress management objects and quality evaluation management objects; the plurality of target energy engineering construction data obtained by classifying the historical energy engineering construction data according to the management objects includes: historical construction material management data, historical construction personnel management data, historical construction progress management data and historical construction finished product quality evaluation value management data.
[0029] For example, the historical construction material management data can be denoted as: a1, a2,..., a n ; the historical construction personnel management data can be denoted as: b1, b2,..., b n ; historical construction progress management data can be recorded as: c1, c2,..., c n ; historical construction product quality evaluation value management data can be recorded as: d1, d2,..., d n .
[0030] In some optional embodiments, random selection is performed in each target energy engineering construction data, and the selected data is randomly combined to obtain a plurality of energy engineering construction data combinations. Exemplarily, the energy engineering construction data combinations can be: a1, a2, and b1; a1, b1, and b2; a1, b1, and c1; and other energy engineering construction data combinations.
[0031] Step S102, selecting an optimal energy engineering construction data combination from the plurality of energy engineering construction data combinations, and determining the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination.
[0032] In some optional embodiments, the plurality of energy engineering construction data combinations are input into a preset genetic algorithm for optimization to obtain the optimal energy engineering construction data combination.
[0033] Specifically, selecting the optimal energy engineering construction data combination from the plurality of energy engineering construction data combinations includes: taking the plurality of energy engineering construction data combinations as an initial population, performing cross mutation processing according to the fitness of individuals in the initial population to obtain a target population; performing fitness analysis on the target population, returning to the cross mutation processing step, and repeatedly iterating until a preset termination condition is reached to obtain the optimal energy engineering construction data combination.
[0034] Exemplarily, a1, a2, and b1; a1, b1, and b2; a1, b1, and c1; and other energy engineering construction data combinations are taken as the initial population, the fitness values of individuals in the initial population are determined and sorted, wherein the expression for determining the fitness value of an individual is:
[0035] f(x)=g(x)
[0036] Wherein, f(x) is the fitness function, g(x) is the objective function, and the expression of the objective function can be:
[0037]
[0038] Wherein, max is the maximum value, ω i is the evaluation quality value of the i-th category of target energy engineering construction data, and n is the total number of categories of target energy engineering construction data.
[0039] Exemplarily, the individual fitness of a1, a2 and b1 is d i , the individual fitness of a1, b1 and b2 is d j , the individual fitness of b2; a1, b1 and c1 is d k , and so on, wherein the individual fitnesses are ranked as follows: d i > d j > d k .
[0040] In some optional embodiments, the individuals with the optimal fitness values are selected for crossover, and the individuals with the middle third of the fitness values are selected for mutation to generate a target population. Exemplarily, a1, a2 and b1 are processed by crossover, and a1, b1 and b2, a1, b1 and c1 and other individuals with the middle third of the fitness values are processed by mutation to obtain the target population.
[0041] In some optional embodiments, the fitness values of the target population are calculated and ranked, and the above-mentioned crossover and mutation steps are repeated until a set maximum number of iterations is reached, and the optimal energy engineering construction data combination is output.
[0042] Exemplarily, the optimal energy engineering construction data combination is a1, a2 and b1, wherein a1 and a2 belong to historical construction material management data, and b1 belongs to historical construction personnel management data.
[0043] In some optional embodiments, determining the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination comprises: obtaining the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination according to the quotient of the data quantity of each target energy engineering construction data and the total data quantity.
[0044] In some optional embodiments, determining the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination comprises: inputting the optimal energy engineering construction data combination into a preset weight generation model to obtain the target weight corresponding to each target energy engineering construction data; the preset weight generation model is used to assign a weight to each target energy engineering construction data, and the more data quantity, the greater the weight, and the total weight is 1.
[0045] Exemplarily, if the optimal energy project construction data combination is a1, a2 and b1, wherein a1 and a2 belong to historical construction material management data, and b1 belongs to historical construction personnel management data, the number of data of the historical construction material management data is two, the target weight is large, which can be 0.7 exemplarily, and the number of data of the historical construction personnel management data is one, the target weight is small, which can be 0.3 exemplarily.
[0046] In step S103, the quality of each target energy project construction process is evaluated according to the real-time target energy project construction data of the multiple target energy project construction processes and the target weight, and a target construction quality value corresponding to each target energy project construction process is obtained. The real-time target energy project construction data is real-time energy project construction data related to the optimal energy project construction data combination.
[0047] In some optional embodiments, the quality of each target energy project construction process is evaluated according to the real-time target energy project construction data of the multiple target energy project construction processes and the target weight, and a target construction quality value corresponding to each target energy project construction process is obtained, which includes: obtaining real-time energy project construction data of the multiple target energy project construction processes, and selecting real-time target energy project construction data related to the optimal energy project construction data combination from the real-time energy project construction data; obtaining a construction quality value corresponding to each management object according to the product of the sum of data corresponding to each management object in the real-time target energy project construction data and the corresponding target weight; and summing the construction quality values corresponding to the multiple management objects to obtain a target construction quality value corresponding to each target energy project construction process.
[0048] Exemplarily, the real-time energy project construction data of the multiple target energy project construction processes can include: real-time construction material management data: e1, e2,..., e n ; real-time construction personnel management data: f1, f2,..., f n ; real-time construction progress management data: g1, g2,..., g n ; and real-time construction finished product quality evaluation value management data: h1, h2,..., h n If the real-time target energy project construction data selected from the real-time energy project construction data related to the optimal energy project construction data combination is the real-time construction material management data and the real-time construction personnel management data, the formula for determining the target construction quality value is:
[0049] M = 0.7 * (e1 + e2 +... + e n)+0.3*(f1+f2+.......+f n )
[0050] wherein M is a target construction quality value, e1, e2,...., e n is real-time construction material management data, f1, f2,...., f n is real-time construction personnel management data, and 0.7 and 0.3 are target weights.
[0051] In some optional embodiments, a determination process of the real-time target energy engineering construction data and the target construction quality value is stored.
[0052] In step S104, whether the target energy engineering construction processes are similar is determined according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data.
[0053] In some optional embodiments, whether the absolute value of the difference between the target construction quality values corresponding to each two target energy engineering construction processes is less than a first preset value is determined; if the absolute value of the difference between the target construction quality values corresponding to each two target energy engineering construction processes is less than the first preset value, the Euclidean distance between the real-time target energy engineering construction data corresponding to the two target energy engineering construction processes is determined; if the Euclidean distance between the real-time target energy engineering construction data corresponding to the two target energy engineering construction processes is less than a second preset value, the two target energy engineering construction processes are determined to be similar.
[0054] In step S105, the real-time target energy engineering construction data and the corresponding target construction quality value of the similar target energy engineering construction processes are stored together according to the determination result, and the real-time target energy engineering construction data and the corresponding target construction quality value of the dissimilar target energy engineering construction processes are stored separately.
[0055] The energy engineering construction quality evaluation management method provided in the embodiment combines the target energy engineering construction data corresponding to various management objects in the historical energy engineering construction data randomly to obtain various energy engineering construction data combinations, selects an optimal energy engineering construction data combination from the various energy engineering construction data combinations, and can mine the optimal energy engineering construction data combination that is more suitable for actual construction quality evaluation requirements, filter the reference basis with the greatest value for quality evaluation from historical experience, and help improve the scientificity and rationality of quality evaluation and reduce evaluation deviation caused by blind data selection. The embodiment determines the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination, can reflect the importance difference of the data corresponding to different management objects in quality evaluation, makes the target construction quality value obtained during subsequent quality evaluation highlight the key influencing factors, and makes the target construction quality value more accurately reflect the actual construction quality. The embodiment evaluates the quality of each target energy engineering construction process according to the real-time target energy engineering construction data and the target weight of the multiple target energy engineering construction processes, obtains the target construction quality value corresponding to each target energy engineering construction process, realizes dynamic and targeted evaluation of construction quality, can discover the quality advantages and disadvantages in the construction process in a timely manner, and compared with related technologies, the embodiment can make the target construction quality value corresponding to each target energy engineering construction process more accurate through the more accurate optimal energy engineering construction data combination and the target weight. The embodiment judges whether the multiple target energy engineering construction processes are similar according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data, can classify the multiple target energy engineering construction processes according to the similarity, stores the real-time target energy engineering construction data and the corresponding target construction quality value of the similar target energy engineering construction processes together according to the judgment result, stores the real-time target energy engineering construction data and the corresponding target construction quality value of the dissimilar target energy engineering construction processes in a classified manner, optimizes the energy engineering construction quality management process, can discover the difference reasons of the energy engineering construction quality in a timely manner, facilitates batch analysis and tracing of similar energy engineering construction quality, can clearly distinguish the data of different energy engineering construction quality, and improves the efficiency of energy engineering construction quality evaluation management.
[0056] An energy engineering construction quality evaluation management method is provided in the embodiment, which can be used for a computer device, Figure 2 is a flowchart of another energy engineering construction quality evaluation management method according to the embodiment of the present application, as Figure 2 shown, the flowchart includes the following steps:
[0057] Step S201, obtain historical energy engineering construction data of a plurality of energy engineering construction processes, randomly combine target energy engineering construction data corresponding to a plurality of management objects in the historical energy engineering construction data, and obtain a plurality of energy engineering construction data combinations. For details, please refer to Figure 1 Step S101 of the embodiment shown will not be described here.
[0058] Step S202, select an optimal energy engineering construction data combination from the plurality of energy engineering construction data combinations, and determine the target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination. For details, please refer to Figure 1 Step S102 of the embodiment shown will not be described here.
[0059] Step S203, according to the real-time target energy engineering construction data of a plurality of target energy engineering construction processes and the target weight, the quality of each target energy engineering construction process is evaluated, and the target construction quality value corresponding to each target energy engineering construction process is obtained; the real-time target energy engineering construction data is the real-time energy engineering construction data related to the optimal energy engineering construction data combination. For details, please refer to Figure 1 Step S103 of the embodiment shown will not be described here.
[0060] Step S204, according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data, it is judged whether the plurality of target energy engineering construction processes are similar.
[0061] Specifically, the above step S204 includes:
[0062] Step S2041, it is judged whether the absolute value of the difference between the target construction quality values corresponding to each two target energy engineering construction processes is less than a first preset value.
[0063] For example, if the target construction quality values corresponding to the two target energy engineering construction processes to be judged are respectively: the first target construction quality value A corresponding to the first target energy engineering construction process, and the second target construction quality value B corresponding to the second target energy engineering construction process, it is judged whether |A-B| is less than the first preset value C. The first preset value can be set according to the actual situation. For example, the first preset value is 0.02.
[0064] Step S2042, if the absolute value of the difference between the target construction quality values corresponding to each two target energy engineering construction processes is less than the first preset value, the Euclidean distance between the real-time target energy engineering construction data corresponding to the two target energy engineering construction processes is determined.
[0065] If the absolute value of the difference between the target construction quality values corresponding to every two target energy project construction processes is greater than or equal to the first preset value, it is determined that the two target energy project construction processes are not similar.
[0066] For example, if the first real-time construction material management data corresponding to the first target energy project construction process is e 11 , e 12 ,..., e 1n , the first real-time construction personnel management data is f 11 , f 12 ,..., f 1n , the second real-time construction material management data corresponding to the second target energy project construction process is e 21 , e 22 ,..., e 2n , and the second real-time construction personnel management data is f 21 , f 22 ,..., f 2n , they are converted into vectors to obtain the first real-time construction material management data vector {e 11 , e 12 ,..., e 1n}, the first real-time construction personnel management data vector {f 11 , f 12 ,..., f 1n}, the second real-time construction material management data vector {e 21 , e 22 ,..., e 2n}, and the second real-time construction personnel management data vector {f 21 , f 22 ,..., f 2n}.
[0067] The formula of the Euclidean distance is determined as follows:
[0068]
[0069] wherein d is the Euclidean distance, x is an n-dimensional vector, which can be the first real-time construction material management data vector or the first real-time construction personnel management data vector, and y is an n-dimensional vector, which can be the second real-time construction material management data vector or the second real-time construction personnel management data vector.
[0070] Step S2043, if the Euclidean distance between the real-time target energy engineering construction data corresponding to the two target energy engineering construction processes is less than the second preset value, it is determined that the two target energy engineering construction processes are similar.
[0071] Wherein, the greater the Euclidean distance, the more similar the two target energy engineering construction processes, the smaller the Euclidean distance, the less similar the two target energy engineering construction processes, and the second preset value can be set according to actual conditions.
[0072] Step S205, according to the judgment result, the real-time target energy engineering construction data and the corresponding target construction quality value of the similar target energy engineering construction process are stored together, and the real-time target energy engineering construction data and the corresponding target construction quality value of the dissimilar target energy engineering construction process are stored separately. For details, please refer to Figure 1 Step S105 of the embodiment shown in the embodiment is not repeated here.
[0073] In the embodiment of the application, first, the preset genetic algorithm is used to design indexes for evaluating the energy engineering construction quality and target weights of each index based on the historical energy engineering construction data of different categories, and then the energy engineering construction quality value is evaluated based on the designed indexes and weight factors by real-time acquisition of the energy engineering construction data, and then the data of the evaluated energy engineering construction quality value is tracked and managed, so that the difference reasons of the energy engineering construction quality can be found in time, and the energy engineering construction quality is evaluated specially, and the evaluation is dynamic based on real-time data, and the evaluation accuracy is high.
[0074] In the embodiment, an energy engineering construction quality evaluation management method is provided, which can be used for computer equipment, Figure 3 is a flowchart of the working process of the energy engineering construction quality evaluation management system according to the embodiment of the application, as Figure 3 shown, the system comprises a historical data acquisition module 301, a historical data classification module 302, an evaluation index design module 303, an evaluation index weight design module 304, a real-time data acquisition module 305, a quality evaluation module 306 and an evaluation data management module 307.
[0075] The historical data acquisition module 301 is used to acquire historical energy engineering construction data, and the historical energy engineering construction data includes historical construction material management data, historical construction personnel management data, historical construction progress management data and historical construction product quality evaluation value management data.
[0076] The historical data classification module 302 is configured to classify the collected historical energy engineering construction data, and the collected historical energy engineering construction data is classified according to historical construction material management data, historical construction personnel management data, historical construction progress management data and historical construction finished product quality evaluation value management data.
[0077] The evaluation index design module 303 is configured to take a plurality of data in the classified historical energy engineering construction data, combine the data according to different categories, select, based on a genetic algorithm, historical energy engineering construction data of an optimal category combination for evaluating the construction quality of the energy engineering, and take the category label of the historical energy engineering construction data of the optimal category combination as an index for evaluating the construction quality of the energy engineering.
[0078] The evaluation index weight design module 304 is configured to design a weight factor of the evaluation index based on the number of category historical energy engineering construction data in the historical energy engineering construction data of the optimal category combination for evaluating the construction quality of the energy engineering selected by the genetic algorithm, and the weight factor is higher when the number is larger.
[0079] The real-time data collection module 305 is configured to collect, in real time, data related to the evaluation index in the energy engineering construction data.
[0080] The quality evaluation module 306 is configured to evaluate a current energy engineering construction quality value based on the data related to the evaluation index in the real-time collected energy engineering construction data and the designed evaluation index weight factor.
[0081] The evaluation data management module 307 is configured to save, in real time, an evaluation process and a result of the current energy engineering construction quality value, and manage based on the saved evaluation process and result of the energy engineering construction quality value.
[0082] In the embodiment, similar evaluated energy engineering construction quality values are saved together, dissimilar evaluated energy engineering construction quality values are classified and saved, and if originally similar two energy engineering construction quality values change and become dissimilar, the reason is analyzed based on the similarity change between the evaluation index data between the evaluated energy engineering construction quality values.
[0083] In the embodiment, an energy engineering construction quality evaluation management device is also provided, which is configured to implement the above-described embodiments and preferred embodiments, and details are not repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, implementation of hardware or a combination of software and hardware is also possible and is contemplated.
[0084] The embodiment provides an energy engineering construction quality evaluation management device, which comprises: Figure 4
[0085] A historical data classification unit 401 is configured to acquire historical energy engineering construction data of multiple energy engineering construction processes, randomly combine target energy engineering construction data of different management objects in the historical energy engineering construction data, and obtain multiple energy engineering construction data combinations.
[0086] An evaluation index design unit 402 is configured to select an optimal energy engineering construction data combination from the multiple energy engineering construction data combinations, and determine a target weight corresponding to each target energy engineering construction data in the optimal energy engineering construction data combination.
[0087] A quality evaluation unit 403 is configured to evaluate the quality of each target energy engineering construction process according to real-time target energy engineering construction data of the multiple target energy engineering construction processes and the target weight, and obtain a target construction quality value corresponding to each target energy engineering construction process; the real-time target energy engineering construction data is real-time energy engineering construction data related to the optimal energy engineering construction data combination.
[0088] A similarity judgment unit 404 is configured to judge whether the multiple target energy engineering construction processes are similar according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data.
[0089] An evaluation data management unit 405 is configured to store the real-time target energy engineering construction data and the corresponding target construction quality value of similar target energy engineering construction processes together according to the judgment result, and store the real-time target energy engineering construction data and the corresponding target construction quality value of dissimilar target energy engineering construction processes separately.
[0090] In some optional embodiments, the historical data classification unit 401 is a unit arranged in a historical data classification module 302, the evaluation index design unit 402 is a unit arranged in an evaluation index design module 303, the quality evaluation unit 403 is a unit arranged in a quality evaluation module 306, and the evaluation data management unit 405 is a unit arranged in an evaluation data management module 307.
[0091] In some optional embodiments, the historical data classification unit 401 comprises:
[0092] A classification subunit is configured to classify the historical energy engineering construction data according to management objects, and obtain multiple target energy engineering construction data.
[0093] Random selection subunit, configured to randomly select each kind of target energy engineering construction data, combine the selected data, and obtain a plurality of energy engineering construction data combinations.
[0094] In some optional embodiments, the evaluation index design unit 402 includes:
[0095] Crossing and mutation subunit, configured to take the plurality of energy engineering construction data combinations as initial populations, perform crossing and mutation processing on individuals in the initial populations according to individual fitness, and obtain a target population.
[0096] Iterative iteration subunit, configured to perform fitness analysis on the target population, return to the step of crossing and mutation processing, and iteratively iterate until a preset termination condition is reached, to obtain an optimal energy engineering construction data combination.
[0097] Weight determination subunit, configured to obtain a target weight corresponding to each kind of target energy engineering construction data in the optimal energy engineering construction data combination, according to a quotient of a data quantity of each kind of target energy engineering construction data in the optimal energy engineering construction data combination and a total data quantity.
[0098] In some optional embodiments, the quality evaluation unit 403 includes:
[0099] Data selection subunit, configured to obtain real-time energy engineering construction data of a plurality of target energy engineering construction processes, and select real-time target energy engineering construction data related to the optimal energy engineering construction data combination from the real-time energy engineering construction data.
[0100] Quality value determination subunit, configured to obtain a construction quality value corresponding to each management object, according to a product of a sum of data corresponding to each management object in the real-time target energy engineering construction data and a corresponding target weight.
[0101] Target construction quality value determination subunit, configured to sum the construction quality values corresponding to the plurality of management objects, and obtain a target construction quality value corresponding to each target energy engineering construction process.
[0102] In some optional embodiments, the similarity judgment unit 404 includes:
[0103] First judgment subunit, configured to judge whether an absolute value of a difference between the target construction quality values corresponding to each two target energy engineering construction processes is less than a first preset value.
[0104] The Euclidean distance determination subunit is used to determine the Euclidean distance between the real-time target energy project construction data corresponding to the construction processes of two target energy projects, based on the fact that the absolute value of the difference between the target construction quality values corresponding to the construction processes of two target energy projects is less than a first preset value.
[0105] The second judgment subunit is used to determine that the construction processes of the two target energy projects are similar if the Euclidean distance between the real-time target energy project construction data corresponding to the construction processes of the two target energy projects is less than a second preset value.
[0106] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.
[0107] In this embodiment, the energy engineering construction quality assessment and management device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.
[0108] This invention also provides a computer device having the above-described features. Figure 4 The device shown is for assessing and managing the construction quality of energy engineering projects.
[0109] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.
[0110] The processor 10 can be a central processor, a network processor, or a combination thereof. The processor 10 can further include hardware chips. The hardware chips can be application specific integrated circuits, programmable logic devices, or a combination thereof. The programmable logic devices can be complex programmable logic devices, field programmable logic gate arrays, general array logic, or any combination thereof.
[0111] The memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods illustrated in the above embodiments.
[0112] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs required by at least one function, and the like. The data storage area can store data created according to the use of the computer device, and the like. In addition, the memory 20 can include a high-speed random access memory, and can further include a non-transitory memory such as at least one disk storage device, a flash memory device, or other non-transitory solid state memory device. In some alternative embodiments, the memory 20 can optionally include a memory disposed remotely from the processor 10, which can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.
[0113] The memory 20 can include a volatile memory such as a random access memory, and can also include a non-volatile memory such as a flash memory, a hard disk, or a solid state disk. The memory 20 can further include a combination of the above-mentioned types of memories.
[0114] The computer device further includes a communication interface 30 for communication of the computer device with other devices or communication networks.
[0115] The embodiments of the present application also provide a computer readable storage medium. The above-mentioned methods according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded to a local storage medium through network downloading, so that the methods described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can further include a combination of the above-mentioned types of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods illustrated in the above embodiments are implemented.
[0116] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, can invoke or provide the method and / or technical solutions according to the present application. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source files, executable files, installation package files, etc., and accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.
[0117] Although the embodiments of the present application are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.
Claims
1. An evaluation management method of construction quality of energy engineering construction, characterized by, The method comprises: acquiring historical energy engineering construction data of a plurality of energy engineering construction processes, randomly combining target energy engineering construction data corresponding to a plurality of management objects in the historical energy engineering construction data to obtain a plurality of energy engineering construction data combinations; selecting an optimal energy engineering construction data combination from the plurality of energy engineering construction data combinations, and determining target weights corresponding to each of the target energy engineering construction data in the optimal energy engineering construction data combination; evaluating the quality of each target energy engineering construction process according to real-time target energy engineering construction data of the target energy engineering construction process and the target weights to obtain a target construction quality value corresponding to each target energy engineering construction process; the real-time target energy engineering construction data is real-time energy engineering construction data related to the optimal energy engineering construction data combination; judging whether the plurality of target energy engineering construction processes are similar according to the target construction quality value corresponding to each target energy engineering construction process and the real-time target energy engineering construction data; storing the real-time target energy engineering construction data and the target construction quality value of similar target energy engineering construction processes together and storing the real-time target energy engineering construction data and the target construction quality value of dissimilar target energy engineering construction processes separately according to the judgment result.
2. The method of claim 1, wherein, The method comprises: classifying the historical energy engineering construction data according to management objects to obtain a plurality of target energy engineering construction data; randomly selecting each target energy engineering construction data and combining the selected data to obtain a plurality of energy engineering construction data combinations.
3. The method according to claim 1 or 2, characterized in that, The method comprises: taking the plurality of energy engineering construction data combinations as an initial population, performing cross variation processing on the fitness of individuals in the initial population to obtain a target population; performing fitness analysis on the target population, returning to the cross variation processing step, and repeatedly iterating until a preset termination condition is reached to obtain the optimal energy engineering construction data combination.
4. The method according to claim 1 or 2, characterized in that, The method comprises: obtaining the target weights corresponding to each of the target energy engineering construction data in the optimal energy engineering construction data combination according to the quotient of the data quantity of each of the target energy engineering construction data in the optimal energy engineering construction data combination and the total data quantity.
5. The method according to claim 1 or 2, characterized in that, The process of evaluating the quality of each target energy project construction process based on real-time target energy project construction data and target weights, to obtain a target construction quality value corresponding to each target energy project construction process, includes: Acquire real-time energy project construction data of multiple target energy project construction processes, and select real-time target energy project construction data related to the optimal combination of energy project construction data from the real-time energy project construction data; The construction quality value corresponding to each management object is obtained by multiplying the sum of the data corresponding to each management object in the real-time target energy project construction data with the corresponding target weight; The construction quality values corresponding to various management objects are summed to obtain the target construction quality value corresponding to each target energy project construction process.
6. The method of claim 1 or 2, wherein, The step of determining whether multiple target energy project construction processes are similar based on the target construction quality value corresponding to each target energy project construction process and the real-time target energy project construction data includes: Determine whether the absolute value of the difference between the target construction quality values corresponding to each of the two target energy project construction processes is less than a first preset value; If the absolute value of the difference between the target construction quality values corresponding to each of the two target energy project construction processes is less than the first preset value, the Euclidean distance between the real-time target energy project construction data corresponding to the two target energy project construction processes is determined. If the Euclidean distance between the real-time target energy project construction data corresponding to the construction processes of the two target energy projects is less than a second preset value, then the two target energy project construction processes are judged to be similar.
7. An energy engineering construction quality evaluation management device characterized by comprising: The device includes: The historical data classification unit is used to acquire historical energy project construction data for multiple energy project construction processes, and to randomly combine target energy project construction data with different management objects in the historical energy project construction data to obtain multiple energy project construction data combinations. The evaluation index design unit is used to select the optimal combination of energy engineering construction data from a variety of energy engineering construction data combinations, and to determine the target weight corresponding to each of the target energy engineering construction data in the optimal combination of energy engineering construction data. A quality assessment unit is used to assess the quality of each of the target energy project construction processes based on real-time target energy project construction data and the target weights, thereby obtaining a target construction quality value corresponding to each target energy project construction process; the real-time target energy project construction data is real-time energy project construction data related to the optimal combination of energy project construction data; The similarity judging unit is configured to judge whether a plurality of target energy engineering construction processes are similar according to the real-time target energy engineering construction data and the corresponding target construction quality value of each target energy engineering construction process; The evaluation data management unit is configured to store the real-time target energy engineering construction data and the corresponding target construction quality value of similar target energy engineering construction processes together according to the judging result, and store the real-time target energy engineering construction data and the corresponding target construction quality value of dissimilar target energy engineering construction processes separately.
8. A computer device, comprising: The energy engineering construction quality evaluation management method comprises the following steps: The memory and the processor are in communication connection with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the energy engineering construction quality evaluation management method according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a computer to execute the energy engineering construction quality evaluation management method according to any one of claims 1 to 6.
10. A computer program product, characterised in that, The computer instructions are used for causing a computer to execute the energy engineering construction quality evaluation management method according to any one of claims 1 to 6.