Festival light scene digital restoration data analysis system and method based on digital twinning

Abstract

The application relates to the technical field of digital twinning, in particular to a festival light scene digital restoration data analysis system and method based on digital Li, which analyzes festival light viewing danger conditions through the position connection structure conditions and the position viewing crowd conditions of festival lights, predicts festival light operation abnormities through the connection of the festival light operation conditions and the connection structure conditions, predicts maintenance abnormities through the viewing danger condition analysis results and the viewing danger condition analysis results, and carries out festival light maintenance early warning according to the obtained maintenance abnormal prediction results. Through the "data quantization risk-accurate decision-dynamic regulation" chain, the application realizes early prediction of festival light stability and fire abnormity, and improves the real-time performance of festival light danger maintenance.

Description

Technical Field

[0001] This application relates to the field of digital restoration technology, and in particular to a data analysis system and method for digital restoration of festive lantern landscapes based on digital restoration. Background Technology

[0002] With the increasing number of urban cultural activities and festivals, festival lights, as important decorative and lighting facilities, are playing an increasingly important role. However, during operation, festival lights pose certain safety hazards due to their complex connection structure and large flow of viewers, such as electrical faults, structural damage, and fire risks. These risks may not only threaten the safety of the audience but also lead to economic losses and negative social impacts. Therefore, it is urgent to conduct systematic monitoring and prediction of the safe operation of festival lights.

[0003] Currently, traditional methods of monitoring festival lights mainly rely on manual inspections and experience-based judgment, which lack systematicity and scientific rigor, making it difficult to effectively respond to emergencies. In addition, existing safety early warning systems often only monitor single factors and cannot comprehensively consider factors such as the connection structure, operating status, and pedestrian flow of festival lights, thus making it difficult to accurately predict potential dangers.

[0004] To address the aforementioned issues, this technical solution proposes a data analysis system and method for digital restoration of festive lantern landscapes based on digital twins. This system dynamically assesses the operational status of the festive lanterns by analyzing the connection structures at various locations and combining this with real-time monitoring of visitor flow. Specifically, the system quantifies the data and establishes a risk assessment model to achieve accurate decision-making regarding potential hazards to the festive lanterns. Summary of the Invention

[0005] This application provides a data analysis system and method for digital restoration of festive lighting landscapes based on digital twins to overcome the defects and shortcomings of existing technologies.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] In a first aspect, this application provides a data analysis method for digital restoration of festive light landscapes based on digital twins, including the following steps:

[0008] S1. Obtain the operational status of the festival lanterns, the flow of viewers at each location, and the connection structure of the festival lanterns, and construct a digital twin model;

[0009] S2. Analyze the viewing hazards of the festival lanterns by examining the connection structure at each location and the flow of people at each location, and obtain the results of the viewing hazard analysis.

[0010] S3. By comparing the operation status of the festival lights with the connection structure, predict the abnormal operation of the festival lights and obtain the prediction results.

[0011] S4. Based on the results of the viewing hazard analysis in S2 and S3, predict maintenance anomalies.

[0012] S5. Provide early warning for the maintenance of festival lights based on the obtained maintenance anomaly prediction results.

[0013] In one implementation of this application, the operation status of the festival lanterns includes the current and temperature data of the lanterns at each location during operation, acquired through a signal acquisition terminal. The visitor flow at each location is the average visitor flow at each location in the previous period, acquired through a visitor flow acquisition terminal. The connection structure of the festival lanterns includes the design strength of the connecting components and the displacement and image data of the connecting components. The design strength of the connecting components is obtained through the connection strength of the design materials. The displacement data of the connecting components is obtained through the position at the start time and the real-time position. The image data is acquired through an image data acquisition terminal. It is also necessary to collect the ignition point of the design materials. Based on the collected data, a digital twin model of the festival lanterns in the scenic area is constructed. The digital twin model displays the operation status of the corresponding festival lantern, the visitor flow at each location, and the connection structure of the festival lantern at the corresponding location.

[0014] In one implementation of this application, the analysis of potential hazards during the viewing of festive lanterns in step S2 includes the following specific steps:

[0015] S21. Obtain the connection structure information of each position of the festival lantern, and perform anomaly analysis of the connection components in each region based on the design strength of the connection components, the displacement of the connection components and image data.

[0016] The connection component anomaly analysis includes the following specific details:

[0017] S211. Obtain the displacement of the connecting components in the corresponding area and the image data of the corresponding area to perform deformation anomaly analysis in the corresponding area. In this step, deformation anomaly analysis is performed by the displacement of the connecting components in the corresponding area and the oxidation status.

[0018] S212. Obtain the deformation anomaly analysis results and the design strength data of the connecting components in the corresponding area, and perform anomaly analysis of the connecting components in the corresponding area. The anomaly analysis method for the connecting components in the corresponding area is: divide the strength standard value by the quotient of the design strength data of the connecting components in the corresponding area, and then multiply it by the deformation anomaly analysis results to obtain the anomaly analysis results of the connecting components in the corresponding area. This step obtains accurate connection anomaly results of the connecting components by analyzing the design connection strength and deformation anomaly analysis results of the corresponding area.

[0019] S22. Assess viewing risks based on changes in the anomaly analysis results of connection components in each region;

[0020] The viewing hazard assessment includes the following specific components:

[0021] The analysis results of the connection component anomaly in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period are obtained. The viewing hazard assessment result is obtained by weighted summation of the connection component anomaly analysis results in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period.

[0022] S23. Obtain the viewing hazard assessment results of the corresponding area and the viewing traffic situation of the corresponding area to conduct a viewing hazard analysis of the festival lanterns;

[0023] The hazard analysis for viewing festival lanterns includes the following specific components: obtaining the hazard assessment results for the corresponding area and the visitor flow in the corresponding area; and multiplying the hazard assessment results for the corresponding area by the standardized visitor flow in the corresponding area to obtain the hazard analysis results for viewing festival lanterns.

[0024] In one implementation of this application, step S3, predicting abnormal operation of the festive lights, includes the following specific steps:

[0025] S31. Obtain the voltage, current and temperature data of the festival lights in the corresponding area, as well as the ignition point data of the materials of the connecting components in the corresponding area;

[0026] S32. Based on the current and temperature data of the festival lights in the corresponding area, and the ignition point data of the connecting components in the corresponding area, an analysis of the hazard situation of the festival lights in the corresponding area is conducted. The formula for the hazard situation analysis of the festival lights in the corresponding area is as follows: Where Tc is the temperature near the festival light, Tm is the ignition temperature of the connecting component, T is the cycle time, It is the current of the festival light at time t, Im is the rated current of the festival light, and dt is the time integration constant. In this step, by analyzing the heat generated during the operation of the festival light and the current operation, the thermal impact of the festival light on the connecting component and the festival light during the operation is analyzed, and then the connection safety and fire safety of the connecting component and the festival light are assessed.

[0027] S33. Based on the connection anomaly results of the corresponding area connection components and the analysis results of the dangerous situation of the corresponding area festival lights, predict the abnormal operation of the festival lights. The method for predicting the abnormal operation of the festival lights is as follows: multiply the connection anomaly results of the corresponding area connection components and the analysis results of the dangerous situation of the corresponding area festival lights to obtain the prediction result of the abnormal operation of the corresponding area festival lights.

[0028] In one implementation of this application, maintaining anomaly prediction in step S4 includes the following specific content:

[0029] The obtained results of the hazard analysis for the festive lanterns and the prediction results of the abnormal operation of the festive lanterns are weighted and summed to obtain the prediction results of the maintenance anomalies.

[0030] In one implementation of this application, step S5 involves issuing a maintenance warning for the festive lights based on the obtained maintenance anomaly prediction results, including the following specific details:

[0031] The ratio of the obtained maintenance anomaly prediction result to the maintenance anomaly threshold is calculated. If the ratio is greater than or equal to 1, it indicates that the corresponding festive light landscape is abnormal and needs maintenance. If the ratio is less than 1, it indicates that the corresponding festive light landscape does not need maintenance. All locations that need maintenance are sent to the maintenance end in descending order of the maintenance anomaly prediction result. The maintenance end performs maintenance on the festive light landscape according to the descending order.

[0032] Secondly, this application also provides a data analysis system for the digital restoration of festive light landscapes based on digital twins, including:

[0033] The data acquisition module is used to acquire information on the operation of the festival lanterns, the flow of visitors at various locations, and the connection structure of the festival lanterns, and to build a digital twin model.

[0034] The viewing hazard analysis module analyzes the viewing hazards of the festival lanterns by considering the connection structure at each location and the flow of people at each location, and obtains the viewing hazard analysis results.

[0035] The anomaly prediction module predicts anomalies in the operation of the festival lights by considering the relationship between the operation status and the connection structure. The prediction results are then obtained.

[0036] The maintenance anomaly prediction module predicts maintenance anomalies based on the results of the viewing hazard analysis.

[0037] The maintenance early warning module provides early warnings for the maintenance of festival lights based on the obtained maintenance anomaly prediction results.

[0038] It also includes a control module, used to control the operation of other modules;

[0039] It also includes an instruction issuing module for issuing maintenance instructions.

[0040] Then, this application provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a digital twin-based method for analyzing data of digital restoration of festive light landscapes by calling the computer program stored in the memory.

[0041] Finally, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a data analysis method for digital restoration of festive light landscapes based on digital twins.

[0042] Compared with the prior art, this application has the following advantages and beneficial effects:

[0043] This application analyzes the viewing hazards of festival lanterns by examining the connection structures at each location and the flow of visitors at each location. It predicts operational anomalies by analyzing the relationship between the operation of the lanterns and the connection structures, and predicts maintenance anomalies based on the results of the viewing hazard analysis. Based on the obtained maintenance anomaly predictions, it provides early warnings for lantern maintenance. This application, through the approach of "data-quantified risk - precise decision-making - dynamic control," achieves early prediction of the stability and fire anomalies of festival lanterns, improving the real-time nature of hazardous maintenance of festival lanterns. Attached Figure Description

[0044] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0045] Figure 1 This is a schematic diagram of the overall process of an embodiment of the method of this application;

[0046] Figure 2 This is a flowchart illustrating the process of embodiment S2 of the method in this application;

[0047] Figure 3 This is a flowchart illustrating the process of embodiment S3 of the method in this application;

[0048] Figure 4 This is a schematic diagram of the structure of an embodiment of the system in this application. Detailed Implementation

[0049] The technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of this application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0050] Example 1. As... Figures 1 to 3As shown, this embodiment provides a data analysis method for digital restoration of festive light landscapes based on digital twins, specifically including the following steps:

[0051] S1. Obtain the operational status of the festival lanterns, the flow of viewers at each location, and the connection structure of the festival lanterns, and construct a digital twin model;

[0052] In this embodiment, the operation status of the festival lights includes the current and temperature data of the festival lights at each location during operation, which are acquired through a signal acquisition terminal. By analyzing the operational anomalies of the festival lights during operation using these data, fire anomaly analysis can also be performed at the corresponding locations by combining these data with the flammability of the connection structures at the corresponding locations. The viewing traffic at each location is the average viewing traffic at each location in the previous period, which is acquired through a traffic flow acquisition terminal. The connection structure status of the festival lights includes the design strength of the connection components, as well as the displacement and image data of the connection components. The design strength of the connection components is obtained through the connection strength of the design materials. The displacement data of the connection components is obtained through the position at the initial moment and the real-time position. The image data is acquired through an image data acquisition terminal. It is also necessary to collect the ignition point of the design materials for fire anomaly analysis. Based on the collected data, a digital twin model of the festival lights in the scenic area is constructed. The digital twin model displays the operation status of the corresponding festival lights, the viewing traffic at each location, and the connection structure status of the festival lights at the corresponding locations.

[0053] S2. Analyze the viewing hazards of the festival lanterns by examining the connection structure at each location and the flow of people at each location, and obtain the results of the viewing hazard analysis.

[0054] In this embodiment, S21, the connection structure of each position of the festival lantern is obtained, and anomaly analysis of the connection components in each region is performed based on the design strength of the connection components, the displacement of the connection components and image data.

[0055] The connection component anomaly analysis includes the following specific details:

[0056] S211. Obtain the displacement of the connecting components in the corresponding region and the image data of the corresponding region to perform deformation anomaly analysis in the corresponding region. The deformation anomaly analysis formula is as follows: Where N is the number of pixels in the corresponding region's connecting components, zi is the real-time pixel value of the i-th pixel in the corresponding region's connecting component image, and zim is the initial pixel value of the i-th pixel in the corresponding region's connecting component image. By analyzing the changes in pixel values, the oxidation anomaly of the connecting components is analyzed. The oxidation of the connecting components can cause the connection to break, which in turn can cause the lamp frame to collapse. In order to avoid the previous formula being 0 and affecting the calculation of the subsequent formula, a constant term is added, exp() is the power of the natural constant e, Xr is the displacement of the corresponding region's connecting components, and Xm is the safe displacement value of the connecting components, that is, the structural displacement value that does not affect the structural safety. Since the existing structures are equipped with buffer functions, the safe displacement value is the maximum value of the buffer function distance. In this step, the deformation anomaly is analyzed by the displacement and oxidation of the corresponding region's connecting components.

[0057] S212. Obtain the deformation anomaly analysis results and the design strength data of the connecting components in the corresponding area, and perform anomaly analysis of the connecting components in the corresponding area. The anomaly analysis method for the connecting components in the corresponding area is: divide the strength standard value by the quotient of the design strength data of the connecting components in the corresponding area, and then multiply it by the deformation anomaly analysis results to obtain the anomaly analysis results of the connecting components in the corresponding area. This step obtains accurate connection anomaly results of the connecting components by analyzing the design connection strength and deformation anomaly analysis results of the corresponding area.

[0058] S22. Assess viewing risks based on changes in the anomaly analysis results of connection components in each region;

[0059] The viewing hazard assessment includes the following specific components:

[0060] The analysis results of the connection component anomaly in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period are obtained. The viewing hazard assessment result is obtained by weighted summation of the connection component anomaly analysis results in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period.

[0061] This step introduces the changes in the anomaly analysis results. The amount of change represents the magnitude of the change in the degree of anomaly of the connection component in the previous cycle, which can reflect the changing trend of the connection component's state. Specifically, the anomaly analysis results of the connection component only represent the average degree of anomaly within a cycle and cannot reflect the changing trend within the cycle.

[0062] S23. Obtain the viewing hazard assessment results of the corresponding area and the viewing traffic situation of the corresponding area to conduct a viewing hazard analysis of the festival lanterns;

[0063] The hazard analysis for viewing the festival lanterns includes the following specific components: obtaining the hazard assessment results for the corresponding area and the visitor flow in the corresponding area; multiplying the hazard assessment results for the corresponding area by the standardized visitor flow in the corresponding area to obtain the hazard analysis results for viewing the festival lanterns. Since the higher the population density in the corresponding area, the more likely it is that people will be squeezed and collide with the connecting components of the corresponding area. Under the premise of high population density, the dangers of festival lanterns are more likely to cause injuries to people. Therefore, the impact of visitor flow on viewing hazards is considered here. The standardization method for the standardized visitor flow in the corresponding area is: the visitor flow in the corresponding area divided by the maximum safe flow of the scenic area.

[0064] S3. By comparing the operation status of the festival lights with the connection structure, predict the abnormal operation of the festival lights and obtain the prediction results.

[0065] In this embodiment, the abnormal operation prediction of the festival lights in step S3 includes the following specific steps:

[0066] S31. Obtain the voltage, current and temperature data of the festival lights in the corresponding area, as well as the ignition point data of the materials of the connecting components in the corresponding area;

[0067] S32. Based on the current and temperature data of the festival lights in the corresponding area, and the ignition point data of the connecting components in the corresponding area, an analysis of the hazard situation of the festival lights in the corresponding area is conducted. The formula for the hazard situation analysis of the festival lights in the corresponding area is as follows: Where Tc is the temperature near the festival light, Tm is the ignition temperature of the connecting component, T is the cycle time, It is the current of the festival light at time t, Im is the rated current of the festival light, and dt is the time integration constant. In this step, by analyzing the heat generated during the operation of the festival light and the current operation, the thermal impact of the festival light on the connecting component and the festival light during the operation is analyzed, and then the connection safety and fire safety of the connecting component and the festival light are assessed.

[0068] S33. Based on the connection anomaly results of the corresponding area's connecting components and the analysis results of the corresponding area's festival lights' dangerous conditions, predict the abnormal operation of the festival lights. The method for predicting the abnormal operation of the festival lights is as follows: multiply the connection anomaly results of the corresponding area's connecting components and the analysis results of the corresponding area's festival lights' dangerous conditions to obtain the predicted result of the abnormal operation of the corresponding area's festival lights. Since the connection anomaly of the connecting components will affect the stable operation of the festival lights, and the heat generated by the festival lights and the connection tension will also have a negative impact on the firmness of the connecting components, the future abnormal operation of the festival lights in the corresponding area will be jointly affected by the connection anomaly results of the corresponding area's connecting components and the analysis results of the corresponding area's festival lights' dangerous conditions.

[0069] S4. Based on the results of the viewing hazard analysis in S2 and S3, predict maintenance anomalies.

[0070] In this embodiment, maintaining anomaly prediction in step S4 includes the following specific contents:

[0071] The obtained results of the hazard analysis for the festive lanterns and the prediction results of the abnormal operation of the festive lanterns are weighted and summed to obtain the prediction results of the maintenance anomalies. Since the hazard analysis results for the festive lanterns represent the connection hazard status of the connecting components, while the prediction results of the abnormal operation of the festive lanterns represent the prediction results of the abnormal operation of the festive lanterns, it is obviously beneficial to analyze whether maintenance is required by using the connection hazard status of the connecting components and the prediction results of the abnormal operation of the festive lanterns.

[0072] S5. Provide early warning for the maintenance of festival lights based on the obtained maintenance anomaly prediction results;

[0073] In this embodiment, step S5 involves issuing a maintenance warning for the festive lights based on the obtained maintenance anomaly prediction results, including the following specific details:

[0074] The ratio of the obtained maintenance anomaly prediction result to the maintenance anomaly threshold is calculated. If the ratio is greater than or equal to 1, it indicates that the corresponding festive light landscape is abnormal and needs maintenance. If the ratio is less than 1, it indicates that the corresponding festive light landscape does not need maintenance. All locations that need maintenance are sent to the maintenance end in descending order of the maintenance anomaly prediction result. The maintenance end performs maintenance on the festive light landscape according to the descending order.

[0075] Meanwhile, the setting parameters (such as weights and thresholds) in this embodiment are obtained by those skilled in the art through experiments using historical data. The specific experimental method is as follows: obtain at least 500 sets of historical festival lantern operation status, visitor flow at each location, and connection structure of the festival lanterns; obtain the result of whether a dangerous accident of the festival lanterns will occur in the next cycle; and import the historical data into the embodiment of this application to calculate the maintenance anomaly prediction result. The maintenance anomaly prediction result and the judgment result of whether a dangerous accident of the festival lanterns will occur in the next cycle are imported into fitting software for iterative fitting of the data, and the set parameter values ​​that meet the maximum judgment accuracy are output. It should be noted that the fitting software here is preferably MATLAB fitting software.

[0076] In this embodiment, it should be noted that it has the following advantages: by analyzing the connection structure of each location of the festival lantern and the flow of people viewing it, the hazard situation of the festival lantern can be analyzed; by analyzing the relationship between the operation of the festival lantern and the connection structure, the abnormal operation of the festival lantern can be predicted; by analyzing the results of the viewing hazard situation analysis, the maintenance anomaly can be predicted; and by analyzing the obtained maintenance anomaly prediction results, the festival lantern maintenance early warning can be issued. This application, through the approach of "data-quantified risk - precise decision-making - dynamic control", realizes the early prediction of the stability and fire anomalies of the festival lantern, and improves the real-time performance of the dangerous maintenance of the festival lantern.

[0077] Example 2. (As shown) Figure 4 As shown, this embodiment provides a data analysis system for digital restoration of festival lantern landscapes based on digital twins, including: a data acquisition module, used to acquire the operation status of the festival lanterns, the flow of viewers at each location, and the connection structure of the festival lanterns, and to construct a digital twin model;

[0078] The viewing hazard analysis module analyzes the viewing hazards of the festival lanterns by considering the connection structure at each location and the flow of people at each location, and obtains the viewing hazard analysis results.

[0079] The anomaly prediction module predicts anomalies in the operation of the festival lights by considering the relationship between the operation status and the connection structure. The prediction results are then obtained.

[0080] The maintenance anomaly prediction module predicts maintenance anomalies based on the results of the viewing hazard analysis.

[0081] The maintenance early warning module provides early warnings for the maintenance of festival lights based on the obtained maintenance anomaly prediction results.

[0082] It also includes a control module, used to control the operation of other modules;

[0083] It also includes an instruction issuing module for issuing maintenance instructions. Figure 4 The arrows in the diagram indicate the data transmission direction for each module.

[0084] Example 3. An electronic device according to an embodiment of this application includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a data analysis method for digital restoration of festival lantern landscapes based on digital twins by calling the computer program stored in the memory. It should be noted that all computer programs for the data analysis method for digital restoration of festival lantern landscapes based on digital twins are implemented using C language.

[0085] Example 4. This example proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored;

[0086] When the computer program runs on the computer device, it causes the computer device to perform the above-mentioned data analysis method for digital restoration of festive lantern landscapes based on digital twins.

[0087] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for IoT devices and media are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0088] The systems, media, and methods provided in this application are one-to-one correspondences. Therefore, the systems and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be repeated here.

[0089] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0093] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0094] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0095] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0096] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A data analysis method for digital restoration of festive light landscapes based on digital twins, characterized in that, Includes the following steps: S1. Obtain the operational status of the festival lanterns, the flow of viewers at each location, and the connection structure of the festival lanterns, and construct a digital twin model; S2. Analyze the viewing hazards of the festival lanterns by examining the connection structure at each location and the flow of people at each location, and obtain the results of the viewing hazard analysis. The analysis of potential hazards associated with viewing festive lanterns includes the following specific steps: S21. Obtain the connection structure information of each position of the festival lantern, and perform anomaly analysis of the connection components in each region based on the design strength of the connection components, the displacement of the connection components and image data. S22. Assess viewing risks based on changes in the anomaly analysis results of connection components in each region; The viewing hazard assessment includes the following specific contents: The analysis results of the connection component anomaly in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period are obtained. The viewing hazard assessment result is obtained by weighted summation of the connection component anomaly analysis results in the corresponding area in real time and the changes in the connection component anomaly analysis results in the previous period. S23. Obtain the viewing hazard assessment results of the corresponding area and the viewing traffic situation of the corresponding area to conduct a viewing hazard analysis of the festival lanterns; S3. By comparing the operation status of the festival lights with the connection structure, predict the abnormal operation of the festival lights and obtain the prediction results. The abnormal operation prediction of the festival lights includes the following specific steps: S31. Obtain the voltage, current and temperature data of the festival lights in the corresponding area, as well as the ignition point data of the materials of the connecting components in the corresponding area; S32. Analyze the hazardous situation of festival lights in the corresponding area based on the current and temperature data of the festival lights in the corresponding area, as well as the ignition point data of the materials of the connecting components in the corresponding area. S33. Based on the connection anomaly results of the corresponding area connection components and the analysis results of the dangerous situation of the corresponding area festival lights, predict the abnormal operation of the festival lights. The method for predicting the abnormal operation of the festival lights is: multiply the connection anomaly results of the corresponding area connection components and the analysis results of the dangerous situation of the corresponding area festival lights to obtain the prediction result of the abnormal operation of the corresponding area festival lights. S4. Based on the analysis results of viewing hazards in S2 and the prediction results of operational anomalies in S3, maintenance anomalies are predicted. S5. Provide early warning for the maintenance of festival lights based on the obtained maintenance anomaly prediction results.

2. The method for analyzing digital restoration data of festive lantern landscapes based on digital twins according to claim 1, characterized in that, The maintenance anomaly prediction includes the following specific contents: The obtained results of the analysis of dangerous situations in the festive lantern viewing area and the prediction results of abnormal operation of the festive lanterns are weighted and summed to obtain the prediction results of maintenance anomalies, because the results of the dangerous situation analysis of the festive lantern viewing area are the connection dangerous situations of the connecting components.

3. The method for analyzing digital restoration data of festive lantern landscapes based on digital twins according to claim 1, characterized in that, The method for issuing early warnings for the maintenance of festive lights based on the obtained maintenance anomaly prediction results includes the following specific content: The ratio of the obtained maintenance anomaly prediction result to the maintenance anomaly threshold is calculated. If the ratio is greater than or equal to 1, it indicates that the corresponding festive light landscape is abnormal and needs maintenance. If the ratio is less than 1, it indicates that the corresponding festive light landscape does not need maintenance. All locations that need maintenance are sent to the maintenance end in descending order of the maintenance anomaly prediction result. The maintenance end performs maintenance on the festive light landscape according to the descending order.

4. The method for analyzing digital restoration data of festive lantern landscapes based on digital twins according to claim 1, characterized in that, The anomaly analysis of the connection components includes the following specific details: S211. Obtain the displacement of the connecting components in the corresponding region and the image data of the corresponding region to perform deformation anomaly analysis in the corresponding region. The deformation anomaly analysis formula is as follows: Where N is the number of pixels in the corresponding region's connecting component, zi is the real-time pixel value of the i-th pixel in the corresponding region's connecting component image, zim is the initial pixel value of the i-th pixel in the corresponding region's connecting component image, exp() is the power of the natural constant e, Xr is the displacement of the corresponding region's connecting component, and Xm is the safety value of the displacement of the connecting component. S212. Obtain the deformation anomaly analysis results and the design strength data of the connecting components in the corresponding area, and perform anomaly analysis of the connecting components in the corresponding area. The anomaly analysis method for the connecting components in the corresponding area is: divide the strength standard value by the quotient of the design strength data of the connecting components in the corresponding area, and then multiply it by the deformation anomaly analysis results to obtain the anomaly analysis results of the connecting components in the corresponding area.

5. A data analysis system for digital restoration of festive lantern landscapes based on digital Li Sheng, implemented based on the data analysis method for digital restoration of festive lantern landscapes based on digital Li Sheng as described in any one of claims 1-4, characterized in that, The system includes: The data acquisition module is used to acquire information on the operation of the festival lanterns, the flow of visitors at various locations, and the connection structure of the festival lanterns, and to build a digital twin model. The viewing hazard analysis module analyzes the viewing hazards of the festival lanterns by considering the connection structure at each location and the flow of people at each location, and obtains the viewing hazard analysis results. The anomaly prediction module predicts anomalies in the operation of the festival lights by considering the relationship between the operation status and the connection structure. The prediction results are then obtained. The maintenance anomaly prediction module predicts maintenance anomalies based on the results of the viewing hazard analysis. The maintenance early warning module provides early warnings for the maintenance of festival lights based on the obtained maintenance anomaly prediction results. It also includes a control module, used to control the operation of other modules; It also includes an instruction issuing module for issuing maintenance instructions.

6. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the method for analyzing digitally restored festive lantern landscape data based on digital twins as described in any one of claims 1-4 by calling the computer program stored in the memory.

Images