Photovoltaic support installation data simulation management system and method

Abstract

The present invention discloses a photovoltaic support installation data simulation management system and method, and relates to the field of virtual installation technology. The present invention regards each participant as a data node, allocates a storage block to each data node, and connects all storage blocks to build a blockchain network; uses common information to set a common verification, and the user of each data node in the blockchain network can read the data of all nodes according to the common verification; extracts the individual characteristics of each data node, sets an independent verification, and each data node reads and writes the installation data generated by itself according to the independent verification; selects a 3D modeling tool, and uses the collected operation data to build a virtual installation model; the user inputs the installation data stored in the blockchain network in real time into the virtual installation model to perform virtual installation.

Description

Technical Field

[0001] The present invention relates to the field of virtual installation technology, and in particular to a photovoltaic support installation data simulation management system and method. Background Art

[0002] With the development of social economy, the consumption of traditional fossil energy is increasing, leading to serious energy crisis and environmental pollution problems. As a clean and renewable energy, solar energy has received widespread attention, and solar photovoltaic power generation systems have been widely used, which provides an application basis for the simulation management of photovoltaic bracket installation data, prompting people to improve power generation efficiency through accurate bracket installation simulation; the continuous development of computer technology, numerical simulation technology and related engineering software makes it possible to perform accurate data simulation of photovoltaic bracket installation. Through these technologies, mathematical models of photovoltaic brackets and photovoltaic components, solar radiation, geographical environment and other factors can be established to achieve simulation and evaluation of different installation schemes. Although the installation data processing of photovoltaic brackets is becoming more and more intelligent, due to the large number of participants required for the installation of photovoltaic brackets, the data and information between different participants are not interoperable, resulting in slow data circulation and untimely updates; it is easy to produce "data island phenomenon", and if the data is shared, it will cause data damage and loss, so how to make the installation data both shareable and ensure data security is crucial. Summary of the invention

[0003] The object of the present invention is to provide a photovoltaic support installation data simulation management system and method to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A photovoltaic support installation data simulation management method, the method comprising the following steps:

[0006] S100, collect all participants in the historical photovoltaic support installation, take each participant as a data node, extract the installation data generated in each data node, allocate a storage block to each data node, store the extracted installation data in each data node in a separate storage block, and connect all storage blocks to build a blockchain network;

[0007] Furthermore, the specific steps to connect all storage blocks to build a blockchain network are as follows:

[0008] S101. Collect all participants in the historical photovoltaic bracket installation, take each participant as a data node, extract the installation data generated in each data node, pre-process the installation data generated by each extracted data node, and use the hash algorithm to convert all installation data into hash data. The formula is: ;

[0009] In the formula, S_ha represents the hash value calculated for each installation data, SHA-256 represents the type of hash algorithm used, and date represents the original data before the installation data to be calculated is converted; the hash algorithm is used to convert all installation functions into hash data: , Indicates that the 1st, 2nd, 3rd, ..., nth data node generates the hash data after the installation data is converted, and n is a positive integer;

[0010] S102. After all installation data are converted into hash data, a storage block is allocated to each data node, and the hash data of each converted installation data and the original data of each installation data before conversion are connected to construct a data element, and all constructed data elements are uploaded to the corresponding storage block for storage; then the storage blocks of each data node are connected to construct a blockchain and generate a blockchain network.

[0011] Compared with the traditional single storage method, the data is stored in different blocks composed of multiple nodes, which effectively reduces the risk of data loss or damage caused by the failure of a single storage device or node. Each node in the blockchain network has equal status and does not need to rely on a centralized management agency. Nodes of different participants can directly share and update data, reducing intermediate links and communication costs, improving the efficiency and timeliness of data sharing, and facilitating the collaborative work of all parties in the photovoltaic bracket installation project.

[0012] S200, analyzing the installation data generated by all data nodes, extracting common information, and using the common information to set a common verification, so that the user of each data node in the blockchain network can read the data of all nodes based on the common verification; extracting the individual characteristics of each data node, setting an independent verification, and each data node reads and writes the installation data generated by itself based on the independent verification;

[0013] Furthermore, in the blockchain network, each data node can read the data of all nodes according to the shared verification in the following specific steps:

[0014] S201, extract the installation data in each data node, analyze each installation data, and obtain the information existing in each installation data: , represents the 1st, 2nd, 3rd, ..., mth type of information in each installation data, where m is a positive integer; count the types of information in all installation data, and extract the common information types in n installation data as , Indicates the 1st, 2nd, 3rd, ..., kth common information existing in the extracted n installation data; calculates the reasonable range of each common information, the formula is:

[0015] ;

[0016] In the formula, represents the upper limit of the reasonable range of each common information calculated, Indicates the lower limit of the reasonable range of each common information calculated, represents the average value of each common information in n installation data, represents each common information value in the i-th installation data, and n represents the total number of installation data;

[0017] S202, using the calculated upper and lower limits of the variation range of each common information to form a reasonable range for each common information: , let the reasonable range of each common information be , Indicates the reasonable range of the 1st, 2nd, 3rd, ..., kth common information to be calculated, and sets a common verification as:

[0018] ;

[0019] In the formula, Share indicates the shared verification that is set. It means taking the intersection of the reasonable ranges of the 1st, 2nd, 3rd, ..., kth common information;

[0020] S203. When the user needs to read the installation data in the blockchain network, the information value corresponding to each type of common information is input into the shared verification. When the shared verification is satisfied, the user identity is judged to be passed and the installation data in the blockchain network can be viewed.

[0021] Setting up shared verification in the blockchain network allows users at different nodes during the installation process to read all installation data, but not rewrite it, avoiding the "data island" phenomenon at each node, enhancing the transparency of the installation data, and preventing outsiders from reading the installation data. The data on the blockchain is open and transparent to all nodes, and any node can query and verify the authenticity and legitimacy of the data.

[0022] The specific steps for each data node to read and write the installation data generated by itself based on independent verification are:

[0023] S211, analyzing the information in each installation data extracted in S201, extracting the unique information type in each installation data, taking the unique information type as the independent feature of the corresponding installation data, and assuming that the independent feature in each installation data is , represents the 1st, 2nd, 3rd, ..., hth independent features in each extracted installation data, where h is a positive integer; extract the information content of each independent feature in the installation data, and calculate the proportion of each independent feature in the total information content of the installation data. The formula is: ;

[0024] In the formula, It represents the proportion of the j-th independent feature information in the total information in the installation data. represents the information content of the jth independent feature in the installation data, Indicates the total amount of information in the installation data;

[0025] S212. Build independent verification using the calculated information ratio of each independent feature. When a user needs to read and write the installation data in a data node in the blockchain network, the user provides the independent features of the corresponding data node, and calculates the information ratio of each independent feature provided, and compares it with the corresponding independent feature information ratio in the independent verification. When the information ratio of all independent features provided is equal to the corresponding independent feature information ratio in the independent verification, the verification is judged to be passed, and the user is allowed to read and write the installation data in the data node. After the user reads and writes, the corresponding hash value is changed using the hash algorithm and the reading and writing are recorded.

[0026] In blockchain, data is usually encrypted before being stored in blocks. The data in each block has a corresponding encrypted hash value, and only authorized users who have passed independent verification can read and write the installation data, thereby effectively preventing unauthorized access and tampering of the data and protecting the privacy and security of the data.

[0027] S300, collecting historical records of abnormalities of photovoltaic brackets during installation, classifying all abnormal records to obtain different abnormal states, extracting abnormal factors causing abnormalities according to abnormal state data of the photovoltaic brackets; and calculating abnormal thresholds of each abnormal state using the abnormal factors of each abnormal state;

[0028] Furthermore, the specific steps of calculating the abnormal threshold of each abnormal state respectively using the abnormal factors of each abnormal state are:

[0029] S301, collecting the records of abnormal photovoltaic brackets during installation, extracting all installation data before and after the abnormality in each record, and calculating the difference of all installation data before and after the abnormality, the formula is: , where Sc represents the calculated installation data difference, S represents the installation data value before the abnormality occurs, and S' represents the installation data value after the abnormality occurs; the installation data type corresponding to the maximum value of the installation data difference is extracted as the abnormal factor Si;

[0030] S302, calculate all the abnormal factors of the collected historical abnormal records, classify the records with the same abnormal factors into the same abnormal type, and obtain the abnormal type when installing the photovoltaic bracket: , It represents the 1st, 2nd, 3rd, ..., pth abnormality type that occurs when installing the photovoltaic bracket, where p is a positive integer; the abnormality threshold is calculated using the abnormal factors of each abnormality type, and the formula is:

[0031] ;

[0032] In the formula, In represents the calculated abnormal threshold, Sip represents the average value of the abnormal factor, Sist represents the standard deviation of the abnormal factor, Xsi represents the information content of the abnormal factor, and Za represents the total information content of the installation data;

[0033] The abnormal threshold of each abnormal type is calculated, and the abnormal threshold of p abnormal types is obtained as follows: , Indicates the calculated anomaly thresholds of the 1st, 2nd, 3rd, ..., pth anomaly types.

[0034] S400, collecting the operation data of the photovoltaic bracket installation in the historical records, selecting a 3D modeling tool, and using the collected operation data to build a virtual installation model; the user inputs the installation data stored in the blockchain network in real time into the virtual installation model to perform virtual installation;

[0035] Furthermore, the specific steps for the user to input the installation data stored in the blockchain network in real time into the virtual installation model are:

[0036] S401. Collect the operation data when installing the photovoltaic bracket in the historical records, select a 3D modeling tool, input the operation data into the modeling tool, and construct a virtual installation step; input the installation data in the blockchain network into the 3D modeling tool, and construct a virtual installation scene and a virtual photovoltaic bracket device; combine the constructed virtual installation steps, virtual installation scenes, and virtual photovoltaic bracket devices to obtain a virtual installation model, and the user performs installation in the virtual installation model according to the installation data stored in the blockchain network.

[0037] S500. When the user uses the virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and uses the abnormal threshold of each abnormal state to judge each abnormal factor, whether there is a risk in the user's virtual installation and issue a warning; after the warning, the user adjusts the installation method until there is no warning, and uses the installation method without warning to perform real installation.

[0038] Furthermore, the specific steps of using the abnormal threshold of each abnormal state to judge each abnormal factor are as follows:

[0039] S501. When the user uses the virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and collects all real-time abnormal factors in the virtual installation process. , represents the first, second, third, ..., pth real-time abnormal factors in the collected virtual installation process; the real-time abnormal factors are judged by using the abnormal threshold of each abnormal type. When the virtual installation is judged to have the risk of the e-th abnormal type, the virtual installation model issues an early warning; after the early warning, the user adjusts the installation method until there is no early warning, and uses the installation method without early warning to perform real installation.

[0040] Through virtual installation models, various possible situations can be simulated before actual installation. Since risks can be discovered in the virtual stage, the installation plan can be adjusted in time to avoid large-scale rework or modification after problems are discovered after actual installation. This not only reduces material waste and increased labor costs, but also avoids long-term economic losses caused by photovoltaic bracket failure or poor power generation efficiency. During the virtual installation process, the installation steps and sequence can be optimized. By simulating the difficulty of operation, time cost and safety risks under different installation sequences, the most reasonable installation process can be determined. This helps to improve the efficiency of actual installation, reduce installation time, reduce labor costs, and improve installation quality and safety.

[0041] A photovoltaic support installation data simulation management system, the photovoltaic support installation data simulation management system includes a data collection module, a blockchain network construction module, a verification module, a threshold calculation module, a virtual installation model construction module and an early warning module;

[0042] The data collection module is used to collect historical data on the participants, operation data and abnormal data of photovoltaic bracket installation;

[0043] The blockchain network construction module is used to set each participant who installed the photovoltaic bracket in the collected history as a data node, allocate different storage blocks to store the installation data of each data node, and connect all blocks to build a blockchain network;

[0044] The verification module is used to set up common verification and independent verification in the blockchain network. The user reads the installation data in the blockchain network through common verification and reads and writes the installation data in the blockchain network through independent verification.

[0045] The threshold calculation module is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, classify abnormal types according to the abnormal factors, and calculate the abnormal threshold of each abnormal type using the abnormal factors;

[0046] The virtual installation model building module is used to input the operation data and installation data when installing the photovoltaic bracket into the 3D modeling tool to build a virtual installation model;

[0047] The warning module is used to determine whether there is an abnormal risk in the user's virtual installation and issue a warning when the user performs virtual installation in the virtual installation model.

[0048] The verification module includes a common verification unit and an independent verification unit;

[0049] The common verification unit is used to analyze the installation data generated by all data nodes, extract common points, and use the common points to set a common verification. The user of each data node in the blockchain network can read the data of all nodes according to the common verification;

[0050] The independent verification unit is used to extract the individual features of each data node and set an independent verification. Each data node reads and writes the installation data generated by itself according to the independent verification.

[0051] The threshold calculation module includes an abnormal classification unit and a threshold calculation unit;

[0052] The abnormal classification unit is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, and classify the abnormal types according to the abnormal factors;

[0053] The threshold calculation unit is used to calculate the abnormality threshold of each abnormality type by using the abnormality factors.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. The present invention sets up shared verification in the blockchain network, which allows users of different nodes in the installation process to read all installation data, but cannot rewrite it, avoiding the "data island" phenomenon of each node, enhancing the transparency of the installation data, and also preventing outsiders from reading the installation data.

[0056] 2. In the blockchain of the present invention, data is usually encrypted before being stored in the block. The data in each block has a corresponding encrypted hash value, and only authorized users who have passed independent verification can read and write the installation data, thereby effectively preventing the data from being accessed and tampered with by unauthorized persons, and protecting the privacy and security of the data.

[0057] 3. The present invention determines the most reasonable installation process by simulating the operational difficulty, time cost and safety risk under different installation sequences. This helps to improve the efficiency of actual installation, reduce installation time, reduce labor costs, and improve installation quality and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A module distribution diagram of a photovoltaic support installation data simulation management system of the present invention;

[0059] Figure 2 A schematic diagram of the steps of a photovoltaic support installation data simulation management method of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution.

[0062] A photovoltaic support installation data simulation management method, the method comprising the following steps:

[0063] S100, collect all participants in the historical photovoltaic support installation, take each participant as a data node, extract the installation data generated in each data node, allocate a storage block to each data node, store the extracted installation data in each data node in a separate storage block, and connect all storage blocks to build a blockchain network;

[0064] The specific steps to connect all storage blocks to build a blockchain network are:

[0065] S101. Collect all participants in the historical photovoltaic bracket installation, take each participant as a data node, extract the installation data generated in each data node, pre-process the installation data generated by each extracted data node, and use the hash algorithm to convert all installation data into hash data. The formula is: ;

[0066] In the formula, S_ha represents the hash value calculated for each installation data, SHA-256 represents the type of hash algorithm used, and date represents the original data before the installation data to be calculated is converted; the hash algorithm is used to convert all installation functions into hash data: , Indicates that the 1st, 2nd, 3rd, ..., nth data node generates the hash data after the installation data is converted, and n is a positive integer;

[0067] S102. After all installation data are converted into hash data, a storage block is allocated to each data node, and the hash data of each converted installation data and the original data of each installation data before conversion are connected to construct a data element, and all constructed data elements are uploaded to the corresponding storage block for storage; then the storage blocks of each data node are connected to construct a blockchain and generate a blockchain network.

[0068] Compared with the traditional single storage method, the data is stored in different blocks composed of multiple nodes, which effectively reduces the risk of data loss or damage caused by the failure of a single storage device or node. Each node in the blockchain network has equal status and does not need to rely on a centralized management agency. Nodes of different participants can directly share and update data, reducing intermediate links and communication costs, improving the efficiency and timeliness of data sharing, and facilitating the collaborative work of all parties in the photovoltaic bracket installation project.

[0069] S200, analyzing the installation data generated by all data nodes, extracting common information, and using the common information to set a common verification, so that the user of each data node in the blockchain network can read the data of all nodes based on the common verification; extracting the individual characteristics of each data node, setting an independent verification, and each data node reads and writes the installation data generated by itself based on the independent verification;

[0070] In the blockchain network, each data node can read the data of all nodes according to the shared verification. The specific steps are as follows:

[0071] S201, extract the installation data in each data node, analyze each installation data, and obtain the information existing in each installation data: , represents the 1st, 2nd, 3rd, ..., mth type of information in each installation data, where m is a positive integer; count the types of information in all installation data, and extract the common information types in n installation data as , Indicates the 1st, 2nd, 3rd, ..., kth common information existing in the extracted n installation data; calculates the reasonable range of each common information, the formula is:

[0072] ;

[0073] In the formula, represents the upper limit of the reasonable range of each common information calculated, Indicates the lower limit of the reasonable range of each common information calculated, represents the average value of each common information in n installation data, represents each common information value in the i-th installation data, and n represents the total number of installation data;

[0074] S202, using the calculated upper and lower limits of the variation range of each common information to form a reasonable range for each common information: , let the reasonable range of each common information be , Indicates the reasonable range of the 1st, 2nd, 3rd, ..., kth common information to be calculated, and sets a common verification as:

[0075] ;

[0076] In the formula, Share indicates the shared verification that is set. It means taking the intersection of the reasonable ranges of the 1st, 2nd, 3rd, ..., kth common information;

[0077] S203. When the user needs to read the installation data in the blockchain network, the information value corresponding to each type of common information is input into the shared verification. When the shared verification is satisfied, the user identity is judged to be passed and the installation data in the blockchain network can be viewed.

[0078] Setting up shared verification in the blockchain network allows users at different nodes during the installation process to read all installation data, but not rewrite it, avoiding the "data island" phenomenon at each node, enhancing the transparency of the installation data, and preventing outsiders from reading the installation data. The data on the blockchain is open and transparent to all nodes, and any node can query and verify the authenticity and legitimacy of the data.

[0079] The specific steps for each data node to read and write the installation data generated by itself based on independent verification are:

[0080] S211, analyzing the information in each installation data extracted in S201, extracting the unique information type in each installation data, taking the unique information type as the independent feature of the corresponding installation data, and assuming that the independent feature in each installation data is , represents the 1st, 2nd, 3rd, ..., hth independent features in each extracted installation data, where h is a positive integer; extract the information content of each independent feature in the installation data, and calculate the proportion of each independent feature in the total information content of the installation data. The formula is:

[0081] ;

[0082] In the formula, It represents the proportion of the j-th independent feature information in the total information in the installation data. represents the information content of the jth independent feature in the installation data, Indicates the total amount of information in the installation data;

[0083] S212. Build independent verification using the calculated information ratio of each independent feature. When a user needs to read and write the installation data in a data node in the blockchain network, the user provides the independent features of the corresponding data node, and calculates the information ratio of each independent feature provided, and compares it with the corresponding independent feature information ratio in the independent verification. When the information ratio of all independent features provided is equal to the corresponding independent feature information ratio in the independent verification, the verification is judged to be passed, and the user is allowed to read and write the installation data in the data node. After the user reads and writes, the corresponding hash value is changed using the hash algorithm and the reading and writing are recorded.

[0084] In blockchain, data is usually encrypted before being stored in blocks. The data in each block has a corresponding encrypted hash value, and only authorized users who have passed independent verification can read and write the installation data, thereby effectively preventing unauthorized access and tampering of the data and protecting the privacy and security of the data.

[0085] S300, collecting historical records of abnormalities of photovoltaic brackets during installation, classifying all abnormal records to obtain different abnormal states, extracting abnormal factors causing abnormalities according to abnormal state data of the photovoltaic brackets; and calculating abnormal thresholds of each abnormal state using the abnormal factors of each abnormal state;

[0086] The specific steps of calculating the abnormal threshold of each abnormal state using the abnormal factors of each abnormal state are as follows:

[0087] S301, collecting the records of abnormal photovoltaic brackets during installation, extracting all installation data before and after the abnormality in each record, and calculating the difference of all installation data before and after the abnormality, the formula is: , where Sc represents the calculated installation data difference, S represents the installation data value before the abnormality occurs, and S' represents the installation data value after the abnormality occurs; the installation data type corresponding to the maximum value of the installation data difference is extracted as the abnormal factor Si;

[0088] S302, calculate all the abnormal factors of the collected historical abnormal records, classify the records with the same abnormal factors into the same abnormal type, and obtain the abnormal type when installing the photovoltaic bracket: , It represents the 1st, 2nd, 3rd, ..., pth abnormality type that occurs when installing the photovoltaic bracket, where p is a positive integer; the abnormality threshold is calculated using the abnormal factors of each abnormality type, and the formula is:

[0089] ;

[0090] In the formula, In represents the calculated abnormal threshold, Sip represents the average value of the abnormal factor, Sist represents the standard deviation of the abnormal factor, Xsi represents the information content of the abnormal factor, and Za represents the total information content of the installation data;

[0091] The abnormal threshold of each abnormal type is calculated, and the abnormal threshold of p abnormal types is obtained as follows: , Indicates the calculated anomaly thresholds of the 1st, 2nd, 3rd, ..., pth anomaly types.

[0092] S400, collecting the operation data of the photovoltaic bracket installation in the historical records, selecting a 3D modeling tool, and using the collected operation data to build a virtual installation model; the user inputs the installation data stored in the blockchain network in real time into the virtual installation model to perform virtual installation;

[0093] Furthermore, the specific steps for the user to input the installation data stored in the blockchain network in real time into the virtual installation model are:

[0094] S401. Collect the operation data when installing the photovoltaic bracket in the historical records, select a 3D modeling tool, input the operation data into the modeling tool, and construct a virtual installation step; input the installation data in the blockchain network into the 3D modeling tool, and construct a virtual installation scene and a virtual photovoltaic bracket device; combine the constructed virtual installation steps, virtual installation scenes, and virtual photovoltaic bracket devices to obtain a virtual installation model, and the user performs installation in the virtual installation model according to the installation data stored in the blockchain network.

[0095] S500. When the user uses the virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and uses the abnormal threshold of each abnormal state to judge each abnormal factor, whether there is a risk in the user's virtual installation and issue a warning; after the warning, the user adjusts the installation method until there is no warning, and uses the installation method without warning to perform real installation.

[0096] The specific steps of using the abnormal threshold of each abnormal state to judge each abnormal factor are as follows:

[0097] S501. When the user uses the virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and collects all real-time abnormal factors in the virtual installation process. , represents the first, second, third, ..., pth real-time abnormal factors in the collected virtual installation process; the real-time abnormal factors are judged by using the abnormal threshold of each abnormal type. When the virtual installation is judged to have the risk of the e-th abnormal type, the virtual installation model issues an early warning; after the early warning, the user adjusts the installation method until there is no early warning, and uses the installation method without early warning to perform real installation.

[0098] Through virtual installation models, various possible situations can be simulated before actual installation. Since risks can be discovered in the virtual stage, the installation plan can be adjusted in time to avoid large-scale rework or modification after problems are discovered after actual installation. This not only reduces material waste and increased labor costs, but also avoids long-term economic losses caused by photovoltaic bracket failure or poor power generation efficiency. During the virtual installation process, the installation steps and sequence can be optimized. By simulating the difficulty of operation, time cost and safety risks under different installation sequences, the most reasonable installation process can be determined. This helps to improve the efficiency of actual installation, reduce installation time, reduce labor costs, and improve installation quality and safety.

[0099] A photovoltaic support installation data simulation management system, the photovoltaic support installation data simulation management system includes a data collection module, a blockchain network construction module, a verification module, a threshold calculation module, a virtual installation model construction module and an early warning module;

[0100] The data collection module is used to collect historical data on the participants, operation data and abnormal data of photovoltaic bracket installation;

[0101] The blockchain network construction module is used to set each participant who installed the photovoltaic bracket in the collected history as a data node, allocate different storage blocks to store the installation data of each data node, and connect all blocks to build a blockchain network;

[0102] The verification module is used to set up common verification and independent verification in the blockchain network. The user reads the installation data in the blockchain network through common verification and reads and writes the installation data in the blockchain network through independent verification.

[0103] The threshold calculation module is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, classify abnormal types according to the abnormal factors, and calculate the abnormal threshold of each abnormal type using the abnormal factors;

[0104] The virtual installation model building module is used to input the operation data and installation data when installing the photovoltaic bracket into the 3D modeling tool to build a virtual installation model;

[0105] The warning module is used to determine whether there is an abnormal risk in the user's virtual installation and issue a warning when the user performs virtual installation in the virtual installation model.

[0106] The verification module includes a common verification unit and an independent verification unit;

[0107] The common verification unit is used to analyze the installation data generated by all data nodes, extract common points, and use the common points to set a common verification. The user of each data node in the blockchain network can read the data of all nodes according to the common verification;

[0108] The independent verification unit is used to extract the individual features of each data node and set an independent verification. Each data node reads and writes the installation data generated by itself according to the independent verification.

[0109] The threshold calculation module includes an abnormal classification unit and a threshold calculation unit;

[0110] The abnormal classification unit is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, and classify the abnormal types according to the abnormal factors;

[0111] The threshold calculation unit is used to calculate the abnormality threshold of each abnormality type by using the abnormality factors.

[0112] Embodiment: Now a blockchain network is set up for a photovoltaic bracket installation project to store installation data, and data node 1, data node 2, and data node 3 are obtained; common information obtained from the installation data is installation time, installation area, and workload; the reasonable range of the three common points is [December-May], [400,900], and [1500,3000]; first, a user in data node 2 needs to view the installation data in data node 3, and enters three common information of August, 489, and 2330; it is determined that the user is a personnel of this installation project, and is allowed to view the installation data in data node 3;

[0113] The independent features extracted from data node 1 are installation temperature and soil density. The information content of the two independent features is calculated to account for 0.12 and 0.23. When the user in data node 1 needs to update the installation data, the real-time information content of the two independent features input accounts for 0.1224 and 0.2399. The user is verified as the installer of data node 1 and is allowed to read and write installation data.

[0114] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A photovoltaic support installation data simulation management method, characterized in that: The method comprises the following steps: S100, collect all participants in the historical photovoltaic support installation, take each participant as a data node, extract the installation data generated in each data node, allocate a storage block to each data node, store the extracted installation data in each data node in a separate storage block, and connect all storage blocks to build a blockchain network; S200, analyzing the installation data generated by all data nodes, extracting common information, and using the common information to set a common verification, so that the user of each data node in the blockchain network can read the data of all nodes based on the common verification; extracting the individual characteristics of each data node, setting an independent verification, and each data node reads and writes the installation data generated by itself based on the independent verification; In the blockchain network, each data node can read the data of all nodes according to the shared verification. The specific steps are as follows: S201, extract the installation data in each data node, analyze each installation data, and obtain the information existing in each installation data: , represents the 1st, 2nd, 3rd, ..., mth type of information in each installation data, where m is a positive integer; count the types of information in all installation data, and extract the common information types in n installation data as , Indicates the 1st, 2nd, 3rd, ..., kth common information existing in the extracted n installation data; calculates the reasonable range of each common information, the formula is: ; In the formula, represents the upper limit of the reasonable range of each common information calculated, Indicates the lower limit of the reasonable range of each common information calculated, represents the average value of each common information in n installation data, represents each common information value in the i-th installation data, and n represents the total number of installation data; S202, using the calculated upper and lower limits of the variation range of each common information to form a reasonable range for each common information: , let the reasonable range of each common information be , Indicates the reasonable range of the 1st, 2nd, 3rd, ..., kth common information to be calculated, and sets a common verification as: ； In the formula, Share indicates the shared verification that is set. It means taking the intersection of the reasonable ranges of the 1st, 2nd, 3rd, ..., kth common information; S203. When the user needs to read the installation data in the blockchain network, the information value corresponding to each type of common information is input into the shared verification. When the shared verification is satisfied, the user identity is determined to be passed, and the installation data in the blockchain network can be viewed; The specific steps for each data node to read and write the installation data generated by itself based on independent verification are: S211, analyzing the information in each installation data extracted in S201, extracting the unique information type in each installation data, taking the unique information type as the independent feature of the corresponding installation data, and assuming that the independent feature in each installation data is , represents the 1st, 2nd, 3rd, ..., hth independent features in each extracted installation data, where h is a positive integer; extract the information content of each independent feature in the installation data, and calculate the proportion of each independent feature in the total information content of the installation data. The formula is: ； In the formula, It represents the proportion of the j-th independent feature information in the total information in the installation data. represents the information content of the jth independent feature in the installation data, Indicates the total amount of information in the installation data; S212. Use the calculated information ratio of each independent feature to build an independent verification. When a user needs to read and write the installation data in a data node in the blockchain network, the user provides the independent features of the corresponding data node, and calculates the information ratio of each independent feature provided, and compares it with the corresponding independent feature information ratio in the independent verification. When the information ratio of all independent features provided is equal to the corresponding independent feature information ratio in the independent verification, the verification is judged to be passed, allowing the user to read and write the installation data in the data node; after the user reads and writes, the corresponding hash value is changed using the hash algorithm and the reading and writing are recorded; S300, collecting historical records of abnormalities of photovoltaic brackets during installation, classifying all abnormal records to obtain different abnormal states, extracting abnormal factors causing abnormalities according to abnormal state data of the photovoltaic brackets; and calculating abnormal thresholds of each abnormal state using the abnormal factors of each abnormal state; S400, collecting the operation data of the photovoltaic bracket installation in the historical records, selecting a 3D modeling tool, and using the collected operation data to build a virtual installation model; the user inputs the installation data stored in the blockchain network in real time into the virtual installation model to perform virtual installation; S500. When the user uses the virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and uses the abnormal threshold of each abnormal state to judge each abnormal factor, whether there is a risk in the user's virtual installation and issue a warning; after the warning, the user adjusts the installation method until there is no warning, and uses the installation method without warning to perform real installation.

2. A photovoltaic support installation data simulation management method according to claim 1, characterized in that: The specific steps of connecting all storage blocks to build a blockchain network in S100 are: S101. Collect all participants in the historical photovoltaic bracket installation, take each participant as a data node, extract the installation data generated in each data node, pre-process the installation data generated by each extracted data node, and use the hash algorithm to convert all installation data into hash data. The formula is: ； In the formula, S_ha represents the hash value calculated for each installation data, SHA-256 represents the type of hash algorithm used, and date represents the original data before the installation data to be calculated is converted; the hash algorithm is used to convert all installation functions into hash data: , Indicates that the 1st, 2nd, 3rd, ..., nth data node generates the hash data after the installation data is converted, and n is a positive integer; S102. After all installation data are converted into hash data, a storage block is allocated to each data node, and the hash data of each converted installation data and the original data of each installation data before conversion are connected to construct a data element, and all constructed data elements are uploaded to the corresponding storage block for storage; then the storage blocks of each data node are connected to construct a blockchain and generate a blockchain network.

3. A photovoltaic support installation data simulation management method according to claim 1, characterized in that: The specific steps of calculating the abnormal threshold of each abnormal state by using the abnormal factors of each abnormal state in S300 are as follows: S301, collecting the records of abnormal photovoltaic brackets during installation, extracting all installation data before and after the abnormality in each record, and calculating the difference of all installation data before and after the abnormality, the formula is: , where Sc represents the calculated installation data difference, S represents the installation data value before the abnormality occurs, and S' represents the installation data value after the abnormality occurs; the installation data type corresponding to the maximum value of the installation data difference is extracted as the abnormal factor Si; S302, calculate all the abnormal factors of the collected historical abnormal records, classify the records with the same abnormal factors into the same abnormal type, and obtain the abnormal type when installing the photovoltaic bracket: , It represents the 1st, 2nd, 3rd, ..., pth abnormality type that occurs when installing the photovoltaic bracket, where p is a positive integer; the abnormality threshold is calculated using the abnormal factors of each abnormality type, and the formula is: ； In the formula, In represents the calculated abnormal threshold, Sip represents the average value of the abnormal factor, Sist represents the standard deviation of the abnormal factor, Xsi represents the information content of the abnormal factor, and Za represents the total information content of the installation data; The abnormal threshold of each abnormal type is calculated, and the abnormal threshold of p abnormal types is obtained as follows: , Indicates the calculated anomaly thresholds of the 1st, 2nd, 3rd, ..., pth anomaly types.

4. A photovoltaic support installation data simulation management method according to claim 1, characterized in that: The specific steps in S400 for the user to input the installation data stored in the blockchain network in real time into the virtual installation model are: S401. Collect the operation data when installing the photovoltaic bracket in the historical records, select a 3D modeling tool, input the operation data into the modeling tool, and construct a virtual installation step; input the installation data in the blockchain network into the 3D modeling tool, and construct a virtual installation scene and a virtual photovoltaic bracket device; combine the constructed virtual installation steps, virtual installation scenes, and virtual photovoltaic bracket devices to obtain a virtual installation model, and the user performs installation in the virtual installation model according to the installation data stored in the blockchain network.

5. A photovoltaic support installation data simulation management method according to claim 4, characterized in that: The specific steps of using the abnormal threshold of each abnormal state to judge each abnormal factor in S500 are: S501. When a user uses a virtual installation model to perform virtual installation, the virtual installation model monitors each abnormal factor in the user's installation process in real time, and collects all real-time abnormal factors in the virtual installation process as follows: , represents the first, second, third, ..., pth real-time abnormal factors in the collected virtual installation process; the real-time abnormal factors are judged by using the abnormal threshold of each abnormal type. When the virtual installation is judged to have the risk of the e-th abnormal type, the virtual installation model issues an early warning; after the early warning, the user adjusts the installation method until there is no early warning, and uses the installation method without early warning to perform real installation.

6. A photovoltaic support installation data simulation management system using a photovoltaic support installation data simulation management method according to any one of claims 1 to 5, characterized in that: The photovoltaic support installation data simulation management system includes a data collection module, a blockchain network construction module, a verification module, a threshold calculation module, a virtual installation model construction module and an early warning module; The data collection module is used to collect historical data on the participants, operation data and abnormal data of photovoltaic bracket installation; The blockchain network construction module is used to set each participant who installed the photovoltaic bracket in the collected history as a data node, allocate different storage blocks to store the installation data of each data node, and connect all blocks to build a blockchain network; The verification module is used to set up common verification and independent verification in the blockchain network. The user reads the installation data in the blockchain network through common verification and reads and writes the installation data in the blockchain network through independent verification. The threshold calculation module is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, classify abnormal types according to the abnormal factors, and calculate the abnormal threshold of each abnormal type using the abnormal factors; The virtual installation model building module is used to input the operation data and installation data when installing the photovoltaic bracket into the 3D modeling tool to build a virtual installation model; The warning module is used to determine whether there is an abnormal risk in the user's virtual installation and issue a warning when the user performs virtual installation in the virtual installation model.

7. A photovoltaic support installation data simulation management system according to claim 6, characterized in that: The verification module includes a common verification unit and an independent verification unit; The common verification unit is used to analyze the installation data generated by all data nodes, extract common points, and use the common points to set a common verification. The user of each data node in the blockchain network can read the data of all nodes according to the common verification; The independent verification unit is used to extract the individual features of each data node and set an independent verification. Each data node reads and writes the installation data generated by itself according to the independent verification.

8. A photovoltaic support installation data simulation management system according to claim 6, characterized in that: The threshold calculation module includes an abnormal classification unit and a threshold calculation unit; The abnormal classification unit is used to calculate the installation data when abnormalities occurred in the installation of photovoltaic brackets in the history, extract abnormal factors, and classify the abnormal types according to the abnormal factors; The threshold calculation unit is used to calculate the abnormality threshold of each abnormality type by using the abnormality factors.

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