Park intelligent supervision and prediction system and method based on digital twinning

Abstract

The invention discloses an intelligent park supervision and prediction system and method based on digital twinning, and belongs to the technical field of intelligent parks. Comprising an information collection module used for collecting environment information, a site mapping module, a prediction analysis module, a result output module and an early warning module, the information collection module periodically collects temperature and humidity, illumination and environment PH value information in a real scene, and the site mapping module divides a park into a plurality of site subareas; and the environment information collected by the information collection module is correspondingly distributed to different site partitions, and the prediction analysis module performs analogue simulation on each partition. The digital twinborn technology is used for modeling a park scene, information of cables can be visually displayed on the digital park, supervision and management are more convenient, problem points in lines can be found in time, timely troubleshooting and timely maintenance are achieved, and the fire safety is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent parks, and particularly relates to a park intelligent supervision and prediction system and method based on digital twin. Background Technique

[0002] Digital twin is a technology that uses data such as physical models, sensor updates, and operation history to integrate multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, and complete mapping in the virtual space, so as to reflect the entire life cycle process of the corresponding physical equipment. Digital twin is a generally applicable theoretical technology system that can be applied in many fields and has been widely used in fields such as product design, product manufacturing, medical analysis, and engineering construction.

[0003] In an intelligent park, digital twin technology can be used to build a digital model of the park and realize functions such as park scene monitoring, fire safety forecasting, and energy-saving control; in the fire supervision and prediction of the park, digital twin technology can simulate the park scene in the digital space through the collected information and give an early warning before a disaster occurs to ensure the personal and property safety within the park site. However, for the fire supervision and prediction of cable aging safety in the park, the existing supervision and prediction systems are more of an input-output of a framework model. When it comes to the supervision and prediction of line aging in the actual scene, since the operation scenarios of different cables in the park site are different, for example, some cables are exposed outdoors and some are installed indoors, and the aging and damage of the cables cannot be accurately observed by visual sensors. This makes the prediction nodes of disasters very inaccurate when making supervision and prediction, and it is impossible to accurately and effectively eliminate the fire safety hazards within the site. Summary of the Invention

[0004] The purpose of the present invention is to provide a park intelligent supervision and prediction system and method based on digital twin to solve the problems in the use of the existing intelligent park cable aging supervision and prediction system mentioned in the above background technique.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A park intelligent supervision and prediction system based on digital twin, including an information collection module for collecting environmental information, a site mapping module, a prediction and analysis module, a result output module, and an early warning module;

[0006] The information collection module periodically collects temperature, humidity, light, and environmental pH value information in the real scene. The site mapping module divides the park into multiple site partitions and correspondingly distributes the environmental information collected by the information collection module to different site partitions. The prediction and analysis module performs simulation on each partition respectively and transmits the prediction results to the result output module and the early warning module.

[0007] Preferably, the site mapping module includes a digital park built based on the modeling of the real park, and the digital park contains cable wiring consistent with that of the real park.

[0008] Preferably, the site mapping module divides at least one building in the digital park into at least two site partitions.

[0009] Preferably, the information collection module is set on the real park, at least one group of information collection modules is set in each site partition, the information collection module is arranged in parallel with the cables in the site partition, and the information collection module integrates a temperature and humidity sensor, a light intensity sensor and a pH value sensor.

[0010] Preferably, the prediction and analysis module includes a timing module and a counting module.

[0011] A digital twin-based intelligent supervision and prediction method for parks includes the following steps:

[0012] S1. The site mapping module establishes a digital park model based on the real park and divides the digital park into multiple site partitions;

[0013] S2. Install several groups of information collection modules in the corresponding real park within the site partition. The information collection module periodically collects the environmental information of the real park and transmits the collected environmental information to the corresponding site partition within the digital park model;

[0014] S3. The prediction and analysis module records the total number of cycles t1 of the environmental information collected by the information collection module. The cycles in which the collected environmental information does not meet the suitable environmental conditions for cable use are recorded as bad cycles. Record the number of bad cycles t2 in different site partitions, obtain the ratio of the bad cycle t2 to the total number of cycles t1 in different site partitions, and simulate the aging rate of the cables in different site partitions through the environmental information of different site partitions within the total cycle;

[0015] S4. The prediction and analysis module predicts the future environmental information of the cables in the site partition according to the ratio of the bad cycle t2 to the total number of cycles t1 in the site partition, and predicts the service life of the cables in the site partition;

[0016] S5. The warning module issues a warning when the cable use time in the real park is greater than the predicted service life.

[0017] Further, a cycle for the information collection module to collect information is one day or one week, and the number of prediction samples is at least one year.

[0018] Further, multiple aging rates are set according to the ratio of the bad cycle t2 to the total number of cycles t1. The higher the proportion of the bad cycle t2, the lower the predicted service life.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0020] First, by using digital twin technology to model the park scene, the information of the cables can be intuitively displayed on the digital park, making supervision and management more convenient. It can timely detect the problem points in the lines, conduct timely inspections and repairs, and greatly improve fire safety;

[0021] Second, the park is divided into site zones. By collecting the environmental information in different site zones, the aging condition of the cables in different site zones can be predicted. The division of site zones makes the prediction more accurate. At the same time, the inspection and repair points can be narrowed down, so that the subsequent potential hazard investigation can be implemented in specific sites, greatly reducing the management and prevention costs;

[0022] Third, the site zone prediction can reflect the aging degree of the cables at different positions. Timely inspections and investigations are carried out on the cables whose aging degree does not meet the expectations. Detecting problems at an early stage is conducive to nipping potential safety hazards in the bud. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Refer to Figure 1 , a digital twin-based intelligent supervision and prediction system and method for a park, including an information collection module, a site mapping module, a prediction and analysis module, a result output module, and an early warning module for collecting environmental information;

[0026] The information collection module periodically collects the temperature, humidity, light, and environmental pH value information in the real scene. The site mapping module divides the park into multiple site zones and correspondingly distributes the environmental information collected by the information collection module to different site zones. The prediction and analysis module conducts simulation for each zone respectively and transmits the prediction results to the result output module and the early warning module.

[0027] Carry out aging supervision and prediction of cables in the park, that is, supervise and predict the service life of cables in the supervision and prediction scenario. Digital twin technology is used to supervise and predict the aging problem of cables. There are two problems in its use. First, the aging of cables occurs inside the cables, and the aging information of cables cannot be accurately observed from the outside. Digital twin technology based on sensor perception cannot identify and observe the internal aging problem of cables. Second, the laying positions of cables are different. The environments of cables in different positions in the park are different, and the aging progress is also different. When supervising and predicting the aging progress of cables, it is impossible to distinguish cables in different positions. The aging rates of different positions of cables are different, resulting in low accuracy of supervision and prediction, unable to accurately predict the aging condition of cables, and then there is a risk of line aging and fire.

[0028] In this technical solution, the park is divided into multiple different site partitions. The information collection module is used to periodically collect the environmental information in the site and transmit the collected information to the digital park. Then, the prediction and analysis module is used to perform simulation on different site partitions respectively, so as to obtain the aging progress in different site partitions. Finally, the safety of the lines in the park is judged and analyzed, and early warnings are given to high-risk positions in the park in a timely manner.

[0029] In this solution, the aging simulation data of cables comes from the aging test experiment of cables in the real scenario. In the aging test experiment, a standard environment is recorded as the standard group, and strong acid, strong base, high humidity, high temperature, etc. are taken as the control experimental groups respectively. Then, the aging rate of the cable compared with the standard environment in different environments is obtained. In the simulation, based on the experimental data in the laboratory and combined with the environmental information obtained by the information collection module, the aging situation of the cables in this site partition is simulated, and the service life of the cables in this site area is predicted.

[0030] Furthermore, the site mapping module includes a digital park built according to the model of the real park, and the digital park contains the same cable wiring as the real park.

[0031] The digital park is modeled according to the real park, and the cable wiring is marked on the digital park, so as to facilitate the division of the park into multiple different site partitions. At the same time, the aging progress of the predicted cables can be marked by the depth of the cable color. Specifically, the cables with high aging degree are marked as dark colors, and the cables with low aging degree are marked as light colors, so that it can be clearly displayed on the digital park model, and the aging situation of the lines in the park buildings can be intuitively observed. At the same time, the aging depth map of the lines can also reflect the aging degree of the cables in different positions, and timely inspection and troubleshooting are carried out on the cables with aging degree not meeting the expectations.

[0032] Furthermore, the site mapping module divides at least one building in the digital park into two site partitions.

[0033] Through this technical solution, in a supervision prediction, theoretically, the more site partitions the digital park is divided into, the higher the accuracy of the prediction. However, at the same time, more information collection modules need to be set up to collect the environmental information in different site partitions accordingly. Therefore, in the coarsest prediction, different buildings in the park are made independent of each other, and only indoor and outdoor areas are divided. In a prediction with higher accuracy requirements, the cables on each wall need to be divided to improve the prediction accuracy.

[0034] Furthermore, the information collection modules are set on the real park. At least one set of information collection modules is set in each group of site partitions. The information collection modules are arranged in parallel with the cables in the site partitions. The information collection modules are integrated with temperature and humidity sensors, light intensity sensors, and pH value sensors.

[0035] The information collection modules are installed closely to the cables to obtain the usage environment information of the cables with high precision. The information collection modules are integrated with temperature and humidity sensors, light intensity sensors, and pH value sensors, which can simultaneously sense the temperature and humidity, acidity and alkalinity, and light intensity in the environment. The information collection modules are set according to the divided site partitions to ensure coverage of each site partition in the park. In the case of a large area of the divided site partitions, multiple sets of information collection modules should be set in the site partitions to reduce the deviation of the collected information and ensure the accuracy of the prediction.

[0036] Furthermore, the prediction analysis module includes a timing module and a counting module.

[0037] The timing module is used to monitor the usage duration of the cables in the park, and the counting module is used to record the cycle numbers of the information collection modules.

[0038] An intelligent supervision prediction method for a park based on digital twin includes the following steps:

[0039] S1. The site mapping module establishes a digital park model based on the real park and divides the digital park into multiple site partitions;

[0040] S2. Install several groups of information collection modules in the corresponding real park within the site partitions. The information collection modules periodically collect the environmental information of the real park and transmit the collected environmental information to the corresponding site partitions in the digital park model;

[0041] S3. The prediction analysis module records the total cycle number t1 of the environmental information collected by the information collection modules. The cycles in which the collected environmental information does not meet the suitable environmental conditions for cable usage are recorded as bad cycles. Record the number of bad cycles t2 in different site partitions, obtain the ratio of the bad cycle t2 to the total cycle number t1 in different site partitions, and simulate the aging rate of the cables in different site partitions through the environmental information of different site partitions within the total cycle.

[0042] S4. The prediction and analysis module predicts the future environmental information of the cables in the site partition according to the ratio of the severe period t2 to the total number of periods t1 in the site partition, and predicts the service life of the cables in the site partition.

[0043] S5. The warning module issues a warning when the actual cable usage time in the park is greater than the predicted service life.

[0044] In this solution, a standard operating condition is set for the operating environment of the cables first. When the environmental information of the cables collected by the information collection module is within this standard condition (the standard condition set in this solution is a temperature of 0 - 30 degrees Celsius, an air humidity of less than 40%, and a pH value between 5 - 9), it indicates that the cables are aging normally. When the obtained cables are not in the environmental range, it is determined that the cables are in a severe period during this detection cycle; when predicting the aging of the cables, based on the proportion of the cables in the severe period, the future environmental information of the cables in the site partition can be predicted and simulated, so as to predict the future aging degree of the cables.

[0045] Furthermore, the cycle for the information collection module to collect information is one day or one week, and the number of prediction samples should be at least one year.

[0046] The more data sources the information collection module has, the more accurate the prediction of the cables in the site partition will be. That is, the data supervision is realized by using the information collection module, and the aging progress of the cables is predicted through the supervised data. The information collection module transmits the environmental information once a day or once a week. At the same time, the information collection module should collect information at multiple time points within one cycle. Specifically, when the cycle is one day, the information collection module should obtain the environmental information once in the morning, noon, and evening at different time points in one day. When the cycle is one week, the information collection module should obtain the environmental information once a day, thereby improving the accuracy of the environmental information within the cycle; when predicting the aging degree of the cables by using the environmental information, considering the differences in different seasons, the supervised environmental information should cover a whole year to improve the accuracy of the prediction.

[0047] Furthermore, multiple aging rates are set according to the ratio of the severe period t2 to the total number of periods t1. The higher the proportion of the severe period t2, the lower the predicted service life.

[0048] Through this technical solution, multiple gears are set for the cable aging prediction based on the ratio of the severe period t2 to the total number of periods t1, and different aging coefficients are set for different gears, so as to predict the future aging progress of the cables; for the aging prediction of the cables, not only can the aging situation of the cables in this time period be predicted, but also the service life of the cables can be predicted through the aging coefficient, and a warning can be issued in time when the cable usage duration reaches the predicted service life.

[0049] Working principle: Use digital twin technology to establish a digital park of the park. At the same time, divide different locations in the park into different site partitions, and set information collection modules in the corresponding real parks of different site partitions, so as to periodically collect the environmental information in the real park and send the collected park information to the corresponding site partitions. Use the prediction analysis module to perform simulation on different site partitions respectively, so as to obtain the aging progress in different site partitions. Finally, judge and analyze the safety of the lines in the park, and give early warnings to high-risk positions in the park in time, and conduct inspections and troubleshooting in time. This technical solution can refine the supervision and prediction of the aging of cables according to the installation location and use environment of the cables, with high accuracy of supervision and prediction and better use effect.

[0050] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0051] In the description of the present invention, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In the present invention, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine the different embodiments or examples described in the present invention and the features of different embodiments or examples.

[0052] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A park intelligent supervision and prediction system based on digital twins, characterized by: It includes an information collection module for collecting environmental information, a site mapping module, a prediction and analysis module, a result output module and an early warning module; The information collection module periodically collects temperature, humidity, light and environmental pH information in the real scene. The site mapping module divides the park into multiple site partitions, and distributes the environmental information collected by the information collection module to different site partitions. The prediction and analysis module simulates each partition separately and passes the prediction results to the result output module and the early warning module.

2. According to claim 1, a digital twin-based park intelligent supervision and prediction system is characterized by: The site mapping module includes a digital park built based on the modeling of the real park, and the digital park includes cable wiring consistent with the real park.

3. According to claim 1, the park intelligent supervision and prediction system based on digital twins is characterized by: The site mapping module divides a building in the digital park into at least two site partitions.

4. According to claim 1, the park intelligent supervision and prediction system based on digital twins is characterized by: The information collection module is set in the actual park, and at least one group of information collection modules is set in each group of site partitions. The information collection module is arranged in parallel with the cables in the site partitions. The information collection module integrates temperature and humidity sensors, light intensity sensors and pH value sensors.

5. The park intelligent supervision and prediction system based on digital twin according to claim 1 is characterized by: The prediction and analysis module includes a timing module and a counting module.

6. A method for intelligent supervision and prediction of a park based on digital twins, characterized in that: The following steps are involved: S1, the site mapping module establishes a digital park model based on the real park and divides the digital park into multiple site partitions; S2. Install several groups of information collection modules in the real parks corresponding to the site partitions. The information collection modules periodically collect environmental information of the real parks and transmit the collected environmental information to the corresponding site partitions in the digital park model. S3, the prediction and analysis module records the total number of cycles t1 of environmental information collected by the information collection module, the cycle in which the collected environmental information does not meet the suitable environmental conditions for cable use is recorded as a bad cycle, the number of bad cycles t2 in different site partitions is recorded, and the proportion of bad cycles t2 in different site partitions to the total number of cycles t1 is obtained. Through the environmental information of different site partitions in the total cycle, the aging rate of cables in different site partitions is simulated; S4, the prediction and analysis module predicts the future environmental information of the cables in the site partition according to the ratio of the severe period t2 to the total period t1 in the site partition, and predicts the service life of the cables in the site partition; S5. The warning module issues a warning when the cable usage time in the actual park exceeds the predicted service life.

7. The method for intelligent supervision and prediction of a park based on digital twins according to claim 6 is characterized by: The information collection module collects information in one cycle of one day or one week, and the prediction sample number is at least one year.

8. The method for intelligent supervision and prediction of a park based on digital twins according to claim 6 is characterized by: Multiple aging rates are set according to the ratio of the severe cycle t2 to the total number of cycles t1. The higher the ratio of the severe cycle t2, the lower the predicted service life.

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