Monitoring Method, Device, Electronic Equipment and Storage Medium for Construction Quality

Abstract

The present invention discloses a method, device, electronic device and storage medium for monitoring construction quality, which relates to the technical field of construction quality monitoring. The monitoring method obtains the target construction node to be monitored for the quality of a photovoltaic engineering project, obtains the corresponding construction record document for this node and the construction data to be monitored according to the target construction node, obtains the construction compliance rate of the target construction node according to the construction record document, and obtains the construction quality score of the target construction node according to the construction data. According to the construction compliance rate and the construction quality score, the quality monitoring result of the target construction node is determined. This method monitors the construction quality of the target construction node from two dimensions of the construction record document and the construction data, and the use of RPA robots can achieve fully automatic online monitoring, meeting the timeliness requirements of photovoltaic engineering project monitoring, improving the accuracy of monitoring, and thus taking into account the timeliness and accuracy of photovoltaic engineering project construction quality monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of construction quality monitoring, and in particular to a construction quality monitoring method, device, electronic equipment and storage medium. Background Art

[0002] The "dual carbon" strategy advocates a green, environmentally friendly, and low-carbon lifestyle. Accelerating the pace of reducing carbon emissions will help guide green technology innovation and improve the global competitiveness of industry and economy. It is necessary to continue to promote the adjustment of industrial structure and energy structure, vigorously develop renewable energy, accelerate the planning and construction of large-scale wind power and photovoltaic base projects in deserts, Gobi and wasteland areas, and strive to balance economic development and green transformation.

[0003] A distributed photovoltaic system is a rooftop power station that is combined with the user's roof or part of the user's building. If there are quality problems with the power station, it may not only cause damage to the internal equipment of the power station, but also endanger the personal safety and property safety of the power station and surrounding personnel; secondly, the power generated by the distributed photovoltaic system is mostly consumed nearby. If there are quality problems with the power station, it may cause damage to the electrical equipment; thirdly, the distributed photovoltaic system obtains economic benefits based on power generation. If there are quality problems with the power station, it will affect the power generation of the entire power station, and then affect the income of the entire power station. Monitoring the construction quality of photovoltaic projects is of great significance. At present, manual monitoring is mostly used for construction quality. The monitoring results are limited by the limitations of manual monitoring, resulting in insufficient monitoring quality.

[0004] Therefore, how to balance timeliness and accuracy in the construction quality monitoring of photovoltaic engineering projects is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a construction quality monitoring method, device, electronic equipment and storage medium, which take into account both the timeliness and accuracy of photovoltaic project construction quality monitoring.

[0006] The embodiment of the present invention provides the following solution:

[0007] In a first aspect, an embodiment of the present invention provides a method for monitoring construction quality, which is applied to an RPA robot to monitor the construction quality of a photovoltaic project. The method includes:

[0008] Obtain the target construction nodes for quality monitoring of photovoltaic engineering projects;

[0009] According to the target construction node, obtain the construction record document corresponding to the node and the construction data that needs to be monitored;

[0010] Obtain the construction compliance rate of the target construction node according to the construction record document, and obtain the construction quality score of the target construction node according to the construction data;

[0011] Determine the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score.

[0012] In an alternative embodiment, obtain the construction record document corresponding to the node according to the target construction node, and the construction data to be monitored, including:

[0013] Determine the document record item and the data record item in the preset relationship table according to the target construction node, where the preset relationship table is a correspondence table between different construction nodes and corresponding record items;

[0014] Determine the construction record document in the construction database according to the document record item, and determine the construction data in the construction database according to the data record item.

[0015] In an alternative embodiment, the construction data includes photovoltaic panel efficiency, MPPT quality, energy loss, material accuracy, material integrity, material registration score, installation quality score, installation stability score, installation material score, commissioning accuracy, and parameter setting score; obtaining the construction quality score of the target construction node according to the construction data includes:

[0016] When the target construction node is the material registration node, obtain the material registration quality of the material registration node according to the material accuracy, material integrity, and material registration score;

[0017] According to the formula: Obtain the first quality score Q1 of the material registration node, where E is the photovoltaic panel efficiency, M is the MPPT quality, L is the energy loss, MR is the material registration quality, and n is the preset weight;

[0018] When the target construction node is the bracket installation node, obtain the comprehensive quality score of the bracket installation node according to the installation quality score, installation stability score, and installation material score;

[0019] According to the formula Obtain the second quality score Q2 of the bracket installation node, where SCI is the comprehensive quality score;

[0020] When the target construction node is the equipment commissioning node, obtain the equipment commissioning quality of the equipment commissioning node according to the commissioning accuracy and parameter setting score;

[0021] According to the formula Obtain the third quality score Q3 of the equipment commissioning node, where EC is the equipment commissioning quality.

[0022] In an alternative embodiment, the construction data further includes operation stability, fault handling score, standardization score, safety score, reliability score, integrity score, operation performance score, and record quality score; after obtaining the third quality score of the equipment commissioning node, the method further includes:

[0023] When the target construction node is the trial operation node, according to the operation stability and fault handling score, obtain the trial operation quality of the trial operation node;

[0024] According to the formula Obtain the fourth quality score Q4 of the trial operation node, where TO is the trial operation quality;

[0025] When the target construction node is the pre-acceptance node, according to the standardization score, safety score, and reliability score, obtain the pre-acceptance quality of the pre-acceptance node;

[0026] According to the formula Obtain the fifth quality score Q5 of the pre-acceptance node, where IA is the pre-acceptance quality;

[0027] When the target construction node is the final acceptance node, according to the integrity score, operation performance score, and record quality score, obtain the final acceptance quality of the final acceptance node;

[0028] According to the formula Obtain the sixth quality score Q6 of the final acceptance node, where FA is the final acceptance quality.

[0029] In an alternative embodiment, before obtaining the quality score of the material registration node, bracket installation node, or equipment commissioning node, the method further includes:

[0030] According to the formula Obtain the preset weight n, where m is the number of construction data for calculating the construction quality score, and λi is the data value of each construction data, 0 < λi ≤ 1.

[0031] In an alternative embodiment, obtaining the construction compliance rate of the target construction node according to the construction record document includes:

[0032] According to the document type of the construction record document, extract the corresponding construction standard document from the construction database;

[0033] Compare the construction record document with the construction standard document in text, and determine the comparison result as the construction compliance rate.

[0034] In an alternative embodiment, determining the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score includes:

[0035] Determine the warning level in the preset rating table according to the construction compliance rate and the construction quality score;

[0036] Fill in the construction compliance rate, the construction quality score, and the warning level at the corresponding positions in the preset quality evaluation template;

[0037] Determine the filling result of the quality evaluation template as the quality monitoring result.

[0038] In a second aspect, an embodiment of the present invention further provides a monitoring device for construction quality, which is applied to an RPA robot to monitor the construction quality of a photovoltaic engineering project. The device includes:

[0039] An acquisition module, configured to acquire a target construction node for which quality monitoring is to be implemented in a photovoltaic engineering project;

[0040] A first acquisition module, configured to obtain the construction record document corresponding to the node and the construction data that needs to be monitored according to the target construction node;

[0041] A second acquisition module, configured to obtain the construction compliance rate of the target construction node according to the construction record document, and obtain the construction quality score of the target construction node according to the construction data;

[0042] A determination module, configured to determine the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score.

[0043] In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor and a memory. The memory is coupled to the processor, and the memory stores instructions. When the instructions are executed by the processor, the electronic device executes the steps of any method in the first aspect.

[0044] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of any method in the first aspect are implemented.

[0045] Compared with the prior art, a monitoring method, device, electronic device, and storage medium for construction quality of the present invention have the following advantages:

[0046] The monitoring method of the present invention obtains the target construction nodes to be monitored for the quality of a photovoltaic engineering project, obtains the corresponding construction record documents and the construction data to be monitored for each node according to the target construction nodes, obtains the construction compliance rate of the target construction nodes according to the construction record documents, and obtains the construction quality score of the target construction nodes according to the construction data. Based on the construction compliance rate and the construction quality score, the quality monitoring result of the target construction node is determined. Based on the characteristics of the construction of photovoltaic engineering projects, this method monitors the construction quality of target construction nodes from two dimensions: construction record documents and construction data, which will not cause redundant monitoring. Using a more comprehensive monitoring scope, it improves the accuracy of construction quality monitoring. At the same time, the use of RPA robots can achieve fully automated online monitoring, eliminating the negligence and errors existing in manual monitoring, meeting the timeliness requirements of photovoltaic engineering project monitoring, and further improving the accuracy of monitoring. During the entire life cycle of photovoltaic engineering projects, the quality of each construction node can be monitored in a timely and accurate manner, thus taking into account both the timeliness and accuracy of the construction quality monitoring of photovoltaic engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of this specification. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0048] Figure 1 It is a flowchart of the construction quality monitoring method provided by an embodiment of the present invention;

[0049] Figure 2 It is a logical schematic diagram of the construction quality monitoring method provided by an embodiment of the present invention;

[0050] Figure 3 It is a structural schematic diagram of the construction quality monitoring device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art belong to the scope protected by the embodiments of the present invention.

[0052] Please refer to Figure 1 , Figure 1The flowchart of a construction quality monitoring method provided by an embodiment of the present invention. The monitoring method uses RPA (Robotic Process Automation) to monitor the construction quality of a photovoltaic engineering project. The monitoring method can be run on the monitoring terminal of the photovoltaic engineering project. The monitoring terminal can be a PC (Personal Computer) device, a server, etc., as long as it can run the monitoring method, and no specific limitation is made here. The monitoring method includes:

[0053] S11. Obtain the target construction node for which the construction quality of the photovoltaic engineering project is to be monitored.

[0054] Specifically, the construction process of the photovoltaic engineering project includes, in the order of construction, a material registration node, a bracket installation node, an equipment commissioning node, a trial operation node, a preliminary acceptance node, and a final acceptance node according to the construction sequence. The target construction node can be any node in the construction process of the photovoltaic engineering project. The target construction node can be defined based on the monitoring requirements of the monitoring personnel; or a monitoring instruction can be input to the RPA robot based on the construction progress, and the RPA robot obtains the target construction node in response to the monitoring requirements. After obtaining the target construction node, step S12 is entered.

[0055] S12. Obtain the construction record document corresponding to the node and the construction data to be monitored according to the target construction node.

[0056] Specifically, since the construction tasks implemented at each construction node are different, the monitoring objects to be monitored also have differences. During the construction process, the construction personnel record the operation results of the construction to the corresponding construction record documents, such as construction documents, construction reports, construction logs, and on-site construction images. Similarly, during the construction process, relevant construction data can be collected based on various installed sensors, such as light sensors, temperature sensors, current sensors, voltage sensors, etc. The sensors are installed at different positions to obtain key construction data. For example, the installed angle sensor can measure the installation angle of the photovoltaic panel, the temperature sensor can monitor the temperature change of the battery module, and the current and voltage sensors can record the current and voltage changes of the photovoltaic power generation system.

[0057] In practical applications, since the construction data is collected in real time during the construction process, there may be some problems with the collected raw data, such as noise, outliers, or data missing. Therefore, before subsequent analysis, the raw data needs to be preprocessed.

[0058] The steps of data preprocessing include operations such as data cleaning, denoising, outlier detection, and data correction.

[0059] First, perform data cleaning to remove duplicate data, invalid data, or error data to ensure data quality.

[0060] Then, perform noise removal on the data. Adopt filtering techniques or smoothing algorithms to remove the noise in the data and improve the accuracy and stability of the construction data.

[0061] Next, conduct outlier detection to identify and process the outliers in the data. Outliers may be caused by sensor failures, equipment malfunctions, or other abnormal situations. By applying statistical methods or model-based methods, these outliers can be detected and processed to ensure the reliability and consistency of the construction data.

[0062] Finally, perform data correction to adjust the data to a unified unit and standard. For example, perform unit conversion on temperature data and calibrate current and voltage data for subsequent data analysis and modeling.

[0063] The data collected in the above manner can be stored in a dedicated construction database. Based on the target construction node, extract the corresponding construction data of this node from the construction database for subsequent analysis and processing.

[0064] Exemplarily, obtain the construction record document corresponding to the target construction node and the construction data to be monitored, including:

[0065] First step, determine the document record item and data record item in the preset relationship table according to the target construction node. The preset relationship table is a correspondence table between different construction nodes and corresponding record items. Since the monitoring content required at different construction nodes is different, to reduce monitoring redundancy, a preset relationship table can be established according to the monitoring requirements of each node, and the document record item and data record item of this node can be determined through the preset relationship table.

[0066] Second step, determine the construction record document in the construction database according to the document record item, and determine the construction data in the construction database according to the data record item. The construction database can be a local database or a cloud database, as long as it can store construction data. The sensors and monitoring devices are connected through the Internet of Things (IoT) technology center server or cloud platform. The construction data can be transmitted by wired or wireless means to ensure the timely and accurate collection of relevant data during the construction process. During the data collection process, factors such as the location layout of sensors, data sampling frequency, and data storage capacity need to be considered to ensure the full acquisition of key data during the construction process. After obtaining the construction record document and construction data, enter step S13.

[0067] S13. Obtain the construction compliance rate of the target construction node according to the construction record document, and obtain the construction quality score of the target construction node according to the construction data.

[0068] Specifically, the construction compliance rate characterizes the gap between the construction quality determined based on the construction record documents and the quality standards, and can be expressed as a percentage; the construction quality score characterizes the gap between the construction quality determined based on the construction data and the quality standards, and can also be expressed as a percentage. When determining the construction compliance rate and the construction quality score, the RPA robot can be implemented based on a preset model. For example, keywords, data, and construction images in the construction record documents are extracted and input into the preset model, and the construction compliance rate is obtained based on the output result of the preset model. The preset model can be a convolutional neural network model, which is trained through a training sample set to meet the application requirements and then used for construction quality monitoring.

[0069] Exemplarily, obtaining the construction compliance rate of the target construction node according to the construction record documents includes:

[0070] In the first step, according to the document type of the construction record document, the corresponding construction standard document is extracted from the construction database. The RPA robot needs to access the construction database of the photovoltaic engineering project and can use login credentials and automation scripts to simulate logging in. The robot must securely store and manage these credentials to ensure data security. The connection method can be using an API key, username and password, or single sign-on (SSO), etc., depending on the requirements of the document storage system, as long as it can connect to the construction database. After successful login, the RPA robot needs to navigate to the document repository, such as a project management platform, document management system, or shared folder. This requires simulating the operations of the user interface, including navigating to a specific page or directory. The robot should be able to handle different types of document storage systems, including web applications, FTP servers, cloud storage services, etc. The RPA robot needs to be able to filter and download the required documents according to specified conditions. The filtering conditions can include date range, project name, document type, keywords, etc. This involves searching for documents or applying filters to accurately locate and download relevant documents. It should be ensured that the obtained documents are up-to-date and relevant to monitoring construction quality. The downloaded documents are usually in image (such as scanned files) or PDF format. The RPA robot needs to be able to download these files from the document storage system to a local location for storage. The download process should include file naming and classification for subsequent processing.

[0071] In the second step, text comparison is performed on the construction record document and the construction standard document, and the comparison result is determined as the construction compliance rate. The RPA robot can use the OCR (Optical Character Recognition) tool to convert the image text in the document into editable text data. The OCR tool performs text recognition operations on each downloaded document. Before performing OCR, the robot needs to configure the OCR tool and set appropriate languages, fonts, scanning resolutions, and other parameters to ensure accurate text recognition. The text data will be extracted from the document processed by OCR. This includes the body text, titles, paragraphs, and other text elements of the document. The extracted text data needs to be accurate for further text analysis and processing. The robot needs to identify and classify different parts in the document, such as dates, locations, problem descriptions, etc. Text delimiters (e.g., line breaks or specific punctuation marks) and keyword recognition can be used to determine the position of each information segment. Correctly positioning and identifying text parts helps subsequent information extraction and analysis. The robot compares the text data of the construction record document obtained above with the construction standard document and calculates the construction compliance rate according to the requirements.

[0072] Keyword matching and rule matching are the keys to realizing the standard comparison of construction documents. Keyword matching relies on a predefined keyword list to detect standard terms in the document. Rule matching, on the other hand, matches problem descriptions and levels according to predefined rules. The combination of these two technologies can effectively determine whether the problems in the construction document meet national standards, thus calculating the construction compliance rate.

[0073] It should be noted that since the recorded content of the construction record document includes text data and digital data, the RPA robot can also extract corresponding data to update the construction data when parsing the construction record document. For example, to make the construction quality monitoring more accurate, more data can be extracted from the construction record document as construction data.

[0074] Exemplarily, the construction data includes photovoltaic panel efficiency, MPPT quality, energy loss, material accuracy, material integrity, material registration score, installation quality score, installation stability score, installation material score, commissioning accuracy, and parameter setting score; the construction quality score of the target construction node is obtained according to the construction data, including:

[0075] The photovoltaic panel efficiency characterizes the power generation efficiency of the photovoltaic panel. The photovoltaic panel efficiency E can be calculated by the formula E = (P / Q × R) × 100%, where P is the actual output power of the power generation system and can be read from the power generation meter; Q is the radiation intensity under standard test conditions and can be calculated by the IEC61215 international test standard; R is the area of the photovoltaic panel and can be determined from the construction drawings of the photovoltaic engineering project.

[0076] The quality of MPPT (Maximum Power Point Tracking) characterizes the control accuracy of the maximum power point of the power generation system. The MPPT quality M can be calculated by the formula M = 1 - (P / S) × 100%, where P is the actual output power of the power generation system, and S is the theoretical output power of the power generation system at the maximum power point, which can be determined by optimizing the curve of the S-MPPT software.

[0077] The energy loss characterizes the power conversion loss caused by various factors such as the environment to the power generation system. The energy loss L can be calculated by the formula L = T + U + V + W + X, where T is the energy loss rate caused by shading to the power generation system, determined by long-term monitoring; U is the energy loss rate caused by temperature influence, determined by the thermostat; V is the energy loss rate caused by air pollution, determined by air quality monitoring; W is the energy loss rate caused by line loss, measured by the line loss meter; X is the energy loss rate caused by the aging of photovoltaic modules, determined by the photovoltaic material table.

[0078] When the target construction node is the material registration node, the material registration quality is highly correlated with the quality score of this node. The material registration quality of the material registration node can be obtained based on material accuracy, material integrity, and material registration score. For example, according to the formula: MR = (Y + Z + A) / 3, the material registration quality MR is calculated, where Y is the material accuracy, Z is the material integrity, and A is the material registration score, and all three can be determined by comparing with the on-site inspection form. After obtaining the material registration quality, according to the formula: Obtain the first quality score Q1 of the material registration node, where E is the efficiency of the photovoltaic panel, M is the MPPT quality, L is the energy loss, MR is the material registration quality, and n is the preset weight. The power generation quality of the photovoltaic power generation system is affected by multiple factors such as the efficiency E of the photovoltaic panel and the MPPT quality M. The formula models the multiplicative effect of the light intensity E and the MPPT quality M using the log function, which conforms to the physical meaning of the combined influence of the two on the quality, so the first quality score of the material registration node can be accurately obtained.

[0079] When the target construction node is the bracket installation node, the comprehensive quality score is highly correlated with the quality score of this node. The comprehensive quality score of the bracket installation node is obtained based on the installation quality score, installation stability score, and installation material score; the comprehensive quality score can also be determined based on the average value of the three. The installation quality score, installation stability score, and installation material score can be determined by the on-site inspection form. After obtaining the comprehensive quality score, according to the formula Obtain the second quality score Q2 of the bracket installation node, where SCI is the comprehensive quality score.

[0080] When the target construction node is the equipment debugging node, the equipment debugging quality of the equipment debugging node is obtained according to the debugging accuracy and parameter setting scores. The equipment debugging quality can be determined based on the average value of the debugging accuracy and parameter setting scores, and the debugging accuracy and parameter setting scores can be determined by comparing the equipment manual with the site. After obtaining the equipment debugging quality, according to the formula The third quality score Q3 of the equipment debugging node is obtained, where EC is the equipment debugging quality.

[0081] In practical applications, since the construction quality monitoring needs to run through the entire construction life cycle, the quality scores determined based on the above methods are relatively limited. Based on this, to ensure more comprehensive monitoring, in a specific implementation, the construction data also includes operation stability, fault handling score, standardization score, safety score, reliability score, integrity score, operation performance score, and record quality score. After obtaining the third quality score of the equipment debugging node, the method further includes:

[0082] When the target construction node is the trial operation node, the trial operation quality of the trial operation node is obtained according to the operation stability and fault handling scores. The operation stability can be determined based on the recorded data of the monitoring system, the fault handling score can be determined based on the maintenance records, and the trial operation quality can be determined based on the average value of the operation stability and fault handling scores. According to the formula The fourth quality score Q4 of the trial operation node is obtained, where TO is the trial operation quality.

[0083] The light intensity E has the characteristic of periodic fluctuation over time. The formula uses the cosh function to describe the periodic convergence characteristic of the MR influence, corresponding to the change law of the photovoltaic panel efficiency E over time. In addition, the monitoring quality is also related to environmental factors such as energy loss and the site. The formula uses the arctan function to bond the energy loss L, the comprehensive quality score SCI, etc., considering the comprehensive effect formed by their common influence, so that the calculation of the quality score of the trial operation node can be more accurate.

[0084] When the target construction node is the pre-acceptance node, the pre-acceptance quality of the pre-acceptance node is obtained according to the standardization score, safety score, and reliability score. The standardization score, safety score, and reliability score can be determined based on the preliminary acceptance form, and then the pre-acceptance quality can be determined based on the average value of the three. According to the formula The fifth quality score Q5 of the pre-acceptance node is obtained, where IA is the pre-acceptance quality.

[0085] When the target construction node is the final acceptance node, the final acceptance quality of the final acceptance node is obtained according to the integrity score, the operation performance score, and the record quality score. The integrity score, the operation performance score, and the record quality score are determined by querying the final inspection form, and the final acceptance quality is determined based on the average of the three; according to the formula Obtain the sixth quality score Q6 of the final acceptance node, where FA is the final acceptance quality. The coth and tanh functions respectively characterize the variation characteristics of the pre-acceptance quality IA and the final acceptance quality FA factors with conditions, which are consistent with the actual situation, so the quality score of the final acceptance node can be accurately calculated.

[0086] It should be noted that the data determined by the above construction data through the form can also be parsed and extracted by the RPA robot from the construction record document; x in each formula is a set containing all parameters. The quality score calculation formula is selected through functions, which successfully captures each influencing factor in the text analysis and the physical connection between them, establishes a quantitative model with a tight system logic, accurately describes the regularity of the quality score affected by multiple factors, and can ensure the accuracy of the quality score through the calculation of logarithmic, trigonometric, and hyperbolic functions. After the integral operation, the preset weight n is finally used as the denominator of the exponent for root extraction, and the calculated quality score is between 0 and 1. The preset weight can be freely set based on the experience of technical personnel or based on calibration experiments.

[0087] In actual application, there is a problem of insufficient accuracy in the preset weight determined based on the conventional method. Based on this, in a specific implementation manner, before obtaining the quality score of the material registration node, the bracket installation node, or the equipment commissioning node, the method further includes:

[0088] According to the formula Obtain the preset weight n, where m is the number of data of the construction data for calculating the construction quality score, λi is the data value of each construction data, and 0 < λi ≤ 1. n can be obtained by random sampling of the verschiedene function. In the random sampling formula, the distribution of n is obtained by summing after randomly sampling each λi. λi can be regarded as the initial weight of different influencing factors in the model. The weights randomly distributed after the random change of λi are summed to obtain the final distribution of n. Therefore, n integrates the composite contribution degree of each influencing factor considering random errors. When the value of n is large, it means that each influencing factor is significant and the influence on the result is enhanced; on the contrary, when n is small, the influence of the change of each factor on the result is relatively weakened. λi ~ N(0,1), λi represents the random value of the influencing factor in the model, and N(0,1) means that λi is randomly sampled according to the standard normal distribution, which can well simulate the actual random volatility of the influencing factor. After obtaining the construction compliance rate and the construction quality score, enter step S14.

[0089] S14. Determine the quality monitoring results of the target construction node based on the construction compliance rate and the construction quality score.

[0090] Specifically, since the construction compliance rate and the construction quality score monitor the construction quality from different dimensions, when determining the quality monitoring results, corresponding weights can be configured to determine the quality monitoring results. For example, a first weight coefficient is configured for the construction compliance rate, and a second weight coefficient is configured for the construction quality score. The sum of the first weight coefficient and the second weight coefficient is 1. Based on the product of the first weight coefficient and the construction compliance rate, the product of the second weight coefficient and the construction quality score is accumulated to determine the quality monitoring results. Of course, the quality monitoring results can also be directly characterized based on the construction compliance rate and the construction quality score.

[0091] Exemplarily, determining the quality monitoring results of the target construction node based on the construction compliance rate and the construction quality score includes:

[0092] The first step is to determine the warning level in the preset rating table according to the construction compliance rate and the construction quality score. Please refer to Table 1:

[0093] Construction quality score Q Construction compliance rate Warning level Q≥0.9 Above 80% Normal 0.8≤Q<0.9 60％-80％ Low level 0.7≤Q<0.8 40％-60％ Medium level Q<0.7 Below 40% High level

[0094] Table 1 divides both the construction quality score and the construction compliance rate into multiple levels, and correspondingly determines different warning levels, and reminds the monitoring personnel of the construction quality monitoring situation based on the warning levels.

[0095] The second step is to fill in the construction compliance rate, the construction quality score, and the warning level at the corresponding positions in the preset quality evaluation template. The RPA robot runs on the UiPath open-source RPA platform, obtains the quality data of each project from the construction database by calling the backend RESTful API interface, and reads the evaluation criteria from the local form file. Use the itextpdf engine to open the preset quality evaluation template, and then calculate the Q value, the construction compliance rate, and the warning level of each construction node according to the evaluation algorithm formula.

[0096] The third step is to determine the filling result of the quality evaluation template as the quality monitoring result. The RPA robot uses text extraction and insertion technologies to automatically fill in the calculation results at the specified positions in the report template, and finally outputs the generated personalized PDF report. At the same time, a reminder function can also be configured, so that the RPA robot calls the mail API function to send all reports to the monitoring personnel's email or communication APP as attachments for review. The reports and reminders generated by the automated process are available for the monitoring personnel to view and verify, and the identified problems can be further analyzed and recognized, and corresponding measures can be taken for rectification and improvement.

[0097] Next, the embodiments of the present invention will comprehensively elaborate on the monitoring method of construction quality. Please refer to Figure 2 ,Figure 2 It is a logical schematic diagram of the monitoring method. During the construction process, construction data is collected, and the collected construction data is preprocessed. The preprocessed construction data is stored in the construction database. The RPA robot performs text analysis to determine the construction compliance rate and construction quality score of the target construction node. Based on the construction compliance rate and construction quality score, the quality monitoring result is determined. When the quality monitoring result meets the construction standard, it is stored in the construction database; when it does not meet the construction standard, the construction problems are marked and recorded, and a quality report is generated to remind the monitoring personnel.

[0098] The entire complete process from data collection to report output and distribution is automatically completed by the RPA robot through workflows and scripts, realizing full automation of the report during the project life cycle. At the same time, the entire construction process is monitored online in real time, thereby improving the construction efficiency of photovoltaic engineering projects and accurately judging whether the construction process meets the standards.

[0099] Based on the same inventive concept as the monitoring method, an embodiment of the present invention further provides a monitoring device for construction quality, which is applied to the RPA robot to monitor the construction quality of photovoltaic engineering projects. Please refer to Figure 3 , Figure 3 It is a structural schematic diagram of the monitoring device. The monitoring device includes:

[0100] An acquisition module 301, configured to acquire the target construction node for which the construction quality of the photovoltaic engineering project is to be monitored;

[0101] A first obtaining module 302, configured to obtain the construction record document corresponding to the node and the construction data to be monitored according to the target construction node;

[0102] A second obtaining module 303, configured to obtain the construction compliance rate of the target construction node according to the construction record document and obtain the construction quality score of the target construction node according to the construction data;

[0103] A determination module 304, configured to determine the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score.

[0104] In an optional embodiment, the first obtaining module includes:

[0105] A first determination sub-module, configured to determine the document record item and the data record item in the preset relationship table according to the target construction node, where the preset relationship table is a correspondence table between different construction nodes and corresponding record items;

[0106] A second determination sub-module, configured to determine the construction record document in the construction database according to the document record item and determine the construction data in the construction database according to the data record item.

[0107] In an alternative embodiment, the construction data includes photovoltaic panel efficiency, MPPT quality, energy loss, material accuracy, material integrity, material registration score, installation quality score, installation stability score, installation material score, commissioning accuracy, and parameter setting score; the second acquisition module includes:

[0108] The first acquisition sub-module is configured to obtain the material registration quality of the material registration node according to the material accuracy, material integrity, and material registration score when the target construction node is the material registration node;

[0109] The second acquisition sub-module is configured to obtain the first quality score Q1 of the material registration node according to the formula: where E is the photovoltaic panel efficiency, M is the MPPT quality, L is the energy loss, MR is the material registration quality, and n is a preset weight;

[0110] The third acquisition sub-module is configured to obtain the comprehensive quality score of the bracket installation node according to the installation quality score, installation stability score, and installation material score when the target construction node is the bracket installation node;

[0111] The fourth acquisition sub-module is configured to obtain the second quality score Q2 of the bracket installation node according to the formula where SCI is the comprehensive quality score;

[0112] The fifth acquisition sub-module is configured to obtain the equipment commissioning quality of the equipment commissioning node according to the commissioning accuracy and parameter setting score when the target construction node is the equipment commissioning node;

[0113] The sixth acquisition sub-module is configured to obtain the third quality score Q3 of the equipment commissioning node according to the formula where EC is the equipment commissioning quality.

[0114] In an alternative embodiment, the construction data further includes operation stability, fault handling score, standardization score, safety score, reliability score, integrity score, operation performance score, and record quality score; the second acquisition module further includes:

[0115] The seventh acquisition sub-module is configured to obtain the trial operation quality of the trial operation node according to the operation stability and fault handling score when the target construction node is the trial operation node;

[0116] The eighth acquisition sub-module is configured to obtain the fourth quality score Q4 of the trial operation node according to the formula where TO is the trial operation quality;

[0117] The ninth acquisition sub-module is used to obtain the pre-acceptance quality of the pre-acceptance node according to the standardization score, safety score, and reliability score when the target construction node is a pre-acceptance node;

[0118] The tenth acquisition sub-module is used to obtain the fifth quality score Q5 of the pre-acceptance node according to the formula where IA is the pre-acceptance quality;

[0119] The eleventh acquisition sub-module is used to obtain the final-acceptance quality of the final-acceptance node according to the integrity score, operation performance score, and record quality score when the target construction node is a final-acceptance node;

[0120] The twelfth acquisition sub-module is used to obtain the sixth quality score Q6 of the final-acceptance node according to the formula where FA is the final-acceptance quality.

[0121] In an alternative embodiment, the second acquisition module further includes:

[0122] The thirteenth acquisition sub-module is used to obtain the preset weight n according to the formula where m is the number of construction data for calculating the construction quality score, λi is the data value of each construction data, and 0 < λi ≤ 1.

[0123] In an alternative embodiment, the second acquisition module includes:

[0124] An extraction sub-module for extracting the corresponding construction standard document from the construction database according to the document type of the construction record document;

[0125] A third determination sub-module for performing text comparison on the construction record document and the construction standard document and determining the comparison result as the construction compliance rate.

[0126] In an alternative embodiment, the determination module includes:

[0127] A fourth determination sub-module for determining the warning level in a preset rating table according to the construction compliance rate and the construction quality score;

[0128] An input sub-module for filling the construction compliance rate, the construction quality score, and the warning level into the corresponding positions of a preset quality evaluation template;

[0129] A fifth determination sub-module for determining the filling result of the quality evaluation template as the quality monitoring result.

[0130] Based on the same inventive concept as the monitoring method, an embodiment of the present invention further provides an electronic device, including a processor and a memory. The memory is coupled to the processor, and the memory stores instructions that, when executed by the processor, cause the electronic device to execute the steps of any one of the monitoring methods.

[0131] Based on the same inventive concept as the monitoring method, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the steps of any one of the monitoring methods.

[0132] The technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0133] By obtaining the target construction node to be monitored for the quality of a photovoltaic engineering project, obtaining the corresponding construction record document for the node and the construction data to be monitored according to the target construction node, obtaining the construction compliance rate of the target construction node according to the construction record document, and obtaining the construction quality score of the target construction node according to the construction data, and determining the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score. Based on the characteristics of the construction of a photovoltaic engineering project, this method monitors the construction quality of the target construction node from two dimensions of the construction record document and the construction data, does not cause monitoring redundancy, uses a more comprehensive monitoring scope, and improves the accuracy of construction quality monitoring; at the same time, the use of RPA robots can achieve fully automated online monitoring, eliminate the negligence errors existing in manual monitoring, meet the timeliness requirements of photovoltaic project monitoring, and further improve the accuracy of monitoring, and can timely and accurately monitor the quality of each construction node in the whole life cycle of a photovoltaic engineering project, thus taking into account the timeliness and accuracy of the construction quality monitoring of a photovoltaic engineering project.

[0134] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0135] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (modules, systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0136] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0138] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they know the basic inventive concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0139] Obviously, those skilled in the art can make various changes and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring construction quality, characterized in that, it is applied to an RPA robot to monitor the construction quality of a photovoltaic engineering project, and the method includes: Obtain the target construction node to be monitored for quality in the photovoltaic engineering project; Obtain the construction record document corresponding to the node and the construction data to be monitored according to the target construction node; Obtain the construction compliance rate of the target construction node according to the construction record document, and obtain the construction quality score of the target construction node according to the construction data; Determine the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score; The construction data includes photovoltaic panel efficiency, MPPT quality, energy loss, material accuracy, material integrity, material registration score, installation quality score, installation stability score, installation material score, commissioning accuracy, and parameter setting score; obtaining the construction quality score of the target construction node according to the construction data includes: When the target construction node is the material registration node, obtain the material registration quality of the material registration node according to the material accuracy, the material integrity, and the material registration score; According to the formula: obtain the first quality score Q1 of the material registration node, where E is the efficiency of the photovoltaic panel, M is the MPPT quality, L is the energy loss, MR is the material registration quality, and n is the preset weight; When the target construction node is the bracket installation node, obtain the comprehensive quality score of the bracket installation node according to the installation quality score, the installation stability score, and the installation material score; According to the formula obtain the second quality score Q2 of the bracket installation node, where SCI is the comprehensive quality score; When the target construction node is the equipment commissioning node, obtain the equipment commissioning quality of the equipment commissioning node according to the commissioning accuracy and the parameter setting score; According to the formula obtain the third quality score Q3 of the device debugging node, where EC is the device debugging quality; Before obtaining the quality score of the material registration node, the bracket installation node, or the equipment commissioning node, the method further includes: According to the formula the preset weight n is obtained, where m is the number of pieces of construction data for calculating the construction quality score, λi is the data value of each piece of construction data, and 0 < λi ≤ 1.

2. The method for monitoring construction quality according to claim 1, characterized in that, obtaining the construction record document corresponding to the node and the construction data to be monitored according to the target construction node includes: Determine the document record item and the data record item in the preset relationship table according to the target construction node, wherein the preset relationship table is a correspondence table between different construction nodes and corresponding record items; Determine the construction record document in the construction database according to the document record item, and determine the construction data in the construction database according to the data record item.

3. The method for monitoring construction quality according to claim 1, characterized in that, the construction data further includes operation stability, fault handling score, standardization score, safety score, reliability score, integrity score, operation performance score, and record quality score; after obtaining the third quality score of the equipment commissioning node, the method further includes: When the target construction node is the trial operation node, obtain the trial operation quality of the trial operation node according to the operation stability and the fault handling score; According to the formula obtain the fourth quality score Q4 of the trial operation node, where TO is the trial operation quality; When the target construction node is the pre-acceptance node, obtain the pre-acceptance quality of the pre-acceptance node according to the standardization score, the safety score, and the reliability score; According to the formula obtain the fifth quality score Q5 of the pre-acceptance node, where IA is the pre-acceptance quality; When the target construction node is the final acceptance node, the final acceptance quality of the final acceptance node is obtained according to the integrity score, the operation performance score, and the record quality score. According to the formula obtain the sixth quality score Q6 of the final acceptance node, where FA is the final acceptance quality.

4. The construction quality monitoring method according to claim 1, wherein, obtaining the construction compliance rate of the target construction node from the construction record document includes: extracting the corresponding construction standard document from the construction database according to the document type of the construction record document; performing text comparison between the construction record document and the construction standard document, and determining the comparison result as the construction compliance rate.

5. The construction quality monitoring method according to claim 1, wherein, determining the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score includes: determining the warning level in a preset rating table according to the construction compliance rate and the construction quality score; filling the construction compliance rate, the construction quality score, and the warning level into the corresponding positions of a preset quality evaluation template; determining the filling result of the quality evaluation template as the quality monitoring result.

6. A construction quality monitoring device, wherein, the device is the device corresponding to any one of the monitoring methods of claims 1-5, and the monitoring device is applied to an RPA robot to monitor the construction quality of a photovoltaic engineering project. The device includes: an acquisition module for acquiring the target construction node to be subjected to quality monitoring of the photovoltaic engineering project; a first obtaining module for obtaining the construction record document corresponding to the node and the construction data to be monitored according to the target construction node; a second obtaining module for obtaining the construction compliance rate of the target construction node from the construction record document and obtaining the construction quality score of the target construction node from the construction data; a determination module for determining the quality monitoring result of the target construction node according to the construction compliance rate and the construction quality score.

7. An electronic device, wherein, it includes a processor and a memory, the memory is coupled to the processor, and the memory stores instructions that, when executed by the processor, cause the electronic device to execute the steps of the method according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, wherein, the program, when executed by a processor, implements the steps of the method according to any one of claims 1-5.

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