A multi-party data supervision system based on blockchain technology

Abstract

The present invention relates to the field of data analysis technology, and in particular to a multi-party data supervision system based on blockchain technology, comprising: a control terminal, which is the main control end of the system and is used to issue execution commands; a construction module, which is used to obtain gas user distribution parameters and construct a gas user distribution topology; an identification module, which is used to traverse the gas user distribution topology constructed in the construction module and identify the parent and child nodes in the gas user distribution topology; the present invention constructs a gas user topology to perform distributed synchronous management of gas users, ensure that the gas user's usage information can be monitored by the system, and when the gas user's gas usage habits change, the gas supply terminal staff can, based on the system, promptly detect the gas user whose gas usage habits have changed, and then when the gas users collectively change their gas usage habits, the gas supply terminal staff can promptly perform adaptive scheduling of the gas stored in the gas supply terminal.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a multi-party data supervision system based on blockchain technology. Background Art

[0002] In recent years, with the rapid development of China's economy, the acceleration of China's urbanization process and the improvement of environmental protection requirements, the demand for gas as a clean energy has continued to increase. Gas consumption has increased year by year, and China has become one of the largest gas consumers in the world;

[0003] In order to meet the growing demand for gas consumption, the construction of gas pipelines has been promoted. Infrastructure such as long-distance pipelines and urban gas pipelines has been continuously improved, which has improved the gas supply capacity and safety.

[0004] However, changes in gas users' usage habits will also pose a certain degree of threat to the daily operation safety of gas supply terminals. However, due to the large number of gas users, the daily management of gas users is cumbersome, and the stable operation and maintenance of gas supply terminals is difficult to carry out;

[0005] To this end, we propose a multi-party data supervision system based on blockchain technology to solve the above problems. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a multi-party data supervision system based on blockchain technology, which solves the technical problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] A multi-party data supervision system based on blockchain technology, including:

[0009] The control terminal is the main control terminal of the system and is used to issue execution commands; the construction module is used to obtain gas user distribution parameters and construct a gas user distribution topology; the identification module is used to traverse the gas user distribution topology constructed in the construction module and identify the child and parent nodes in the gas user distribution topology; the analysis module is used to select an analysis target in the gas user distribution topology and perform a gas use safety status analysis on the analysis target; the determination module is used to receive the gas use safety status analysis result of the analysis target, set a safety determination threshold, apply the safety determination threshold and compare the analysis result to determine whether the gas use status of the analysis target is safe; the feedback module is used to monitor the determination result of whether the gas use status of the analysis target in the determination module is safe, and when the determination result is negative, feedback the relevant information of the analysis target with the determination result negative to the control terminal;

[0010] The control terminal is interactively connected to a construction module via a wireless network, the construction module is interactively connected to an upload unit, i.e., a creation unit, via a wireless network, the construction module is interactively connected to an identification module via a wireless network, the identification module is electrically connected to a reconstruction unit via a medium, the reconstruction unit is interactively connected to the construction module via a wireless network, the identification module is interactively connected to an analysis module, a determination module, and a feedback module via a wireless network, and the analysis module is interactively connected to a logic unit and a transmission unit via a wireless network;

[0011] After the feedback module feeds back the analysis target related information with a negative determination result to the control terminal, the system end user accesses the system through a wireless network and reads the feedback information in the system control terminal.

[0012] Furthermore, the creation module is provided with submodules at a lower level, including:

[0013] An uploading unit, used for uploading gas user distribution parameters and transmitting the gas user distribution parameters to the building module;

[0014] A creation unit, used to traverse the gas user distribution topology constructed in the construction module, create a cloud database at the corresponding position of each gas user in the gas user distribution topology, and store gas user usage parameters;

[0015] Among them, the gas user distribution parameters include: gas user location information, gas transmission direction of the gas pipeline where the gas user location information is located. When constructing the gas user distribution topology, the construction module constructs the gas user distribution topology based on the gas user distribution parameters. The gas user usage parameters include: the start and stop time of gas users using gas, and the gas usage within the start and stop time thresholds of gas users using gas. The cloud database used to store the gas user usage parameters is bound to the corresponding position of the gas user in the gas user distribution topology by setting a hyperlink.

[0016] Furthermore, the identification module is internally provided with submodules, including:

[0017] A reconstruction unit is used to receive the identification result of the child and parent nodes of the gas user distribution topology in the identification module, extract the parent node in the gas user distribution topology, and transmit the extracted parent node to the construction module;

[0018] After the reconstruction unit transmits the extracted parent node to the construction module, the construction module runs again to construct a structural topology representing the gas main based on the received parent node.

[0019] Furthermore, the analysis module is provided with submodules at the lower level, including:

[0020] Logic unit, used to set the analysis target selection logic;

[0021] A transmission unit, used to obtain the analysis result of the gas usage safety status of the analysis target by the analysis module, transmit the analysis result to a cloud database storing gas user usage parameters, and store it in the cloud database;

[0022] When the analysis results are transmitted to the cloud database, the analysis target of the analysis result source is simultaneously identified, the corresponding cloud database is determined based on the analysis target, and the analysis results are further stored in the cloud database corresponding to the analysis target.

[0023] Furthermore, the analysis target selection logic set in the logic unit is expressed as:

[0024] Logic 1: The gas main structure topology and gas user distribution topology are taken as the first choice target and the second choice target of the analysis target respectively;

[0025] Logic2: Select a specified number of analysis targets from the first selection target, and perform gas use safety status analysis on the analysis targets based on the gas use safety status analysis logic;

[0026] Logic3: Obtain the analysis result of the gas use safety status of the analysis target in the judgment module. When the judgment result is no, end. When the judgment result is yes, jump to Logic2 and run again with the second selected target.

[0027] Furthermore, when a specified number of analysis targets are selected in the selected targets in the Logic2, the specified number of selected analysis targets is manually set by the system end user, and the number of selected analysis targets is not less than three groups;

[0028] Among them, during the continuous operation of the system, among the analysis targets selected in each system operation, the same analysis targets shall not exceed 20% of the total number of analysis target selections.

[0029] Furthermore, the gas use safety status analysis logic of the analysis target is expressed as:

[0030]

[0031] Where: k(a) is the gas safety status performance value of the analysis target a; n is the analysis target set that does not include the analysis target a; SIMM(a,b i ) is the similarity between the gas usage statistics corresponding to the analysis target a and the gas usage statistics corresponding to the i-th group of analysis targets b; The closed area formed by the minimum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b; The closed area formed by the minimum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b;

[0032] Among them, the larger the value of k(a), the safer the target gas usage status is, and vice versa. The similarity between the two sets of statistical graphs is determined based on the height and slope of the line segments in the statistical graphs. When fitting the two sets of statistical graphs, the starting points or end points of the line segments in the two sets of statistical graphs are overlapped to complete the fitting operation.

[0033] Furthermore, in the gas use safety status analysis stage, the analysis target corresponds to the analysis target hyperlink in the gas main structure topology or the gas user distribution topology, the location analysis target corresponds to the cloud database, the gas start and stop time and the gas usage data within the threshold of each gas start and stop time of the gas user are obtained in the cloud database, and based on the gas start and stop time and the gas usage within the threshold of each gas start and stop time of the gas user, a gas usage statistical chart of the analysis target is generated;

[0034] The gas usage statistics graph of the analysis target is a line graph, the horizontal axis of the gas usage statistics graph of the analysis target represents time, and the vertical axis represents gas usage.

[0035] Furthermore, the analysis target related information fed back in the feedback module is a gas usage statistical graph corresponding to the analysis target.

[0036] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0037] The present invention provides a multi-party data supervision system based on blockchain technology. During operation, the system performs distributed and synchronous management of gas users by constructing a gas user topology, thereby ensuring that the gas user's usage information can be monitored by the system in real time. Further, when the gas user's gas usage habits change, the gas supply terminal staff can, based on the system, promptly detect the gas user whose gas usage habits have changed. Further, when the gas users change their gas usage habits in a concentrated manner, the gas supply terminal staff can promptly adaptively dispatch the gas stored in the gas supply terminal, thereby ensuring the stable operation and maintenance of the gas supply terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 This is a structural diagram of a multi-party data supervision system based on blockchain technology;

[0040] Figure 2 Display of daily inspection background data for gas users in this invention Figure 1 ;

[0041] Figure 3 Display of daily inspection background data for gas users in this invention Figure 2 ;

[0042] Figure 4 This is the architecture diagram of the on-chain regulatory system;

[0043] Figure 5 It is a schematic diagram of the digital identity of the inspection data structure;

[0044] Figure 6 This is a schematic diagram of the multi-party supervision data model;

[0045] The numbers in the figure represent: 1. control terminal; 2. construction module; 21. upload unit; 22. creation unit; 3. identification module; 31. reconstruction unit; 4. analysis module; 41. logic unit; 42. transmission unit; 5. judgment module; 6. feedback module. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0047] The present invention will be further described below in conjunction with the embodiments.

[0048] Embodiment 1:

[0049] A multi-party data supervision system based on blockchain technology in this embodiment, such as Figure 1 As shown, including:

[0050] Control terminal 1 is the main control terminal of the system and is used to issue execution commands;

[0051] Construction module 2 is used to obtain gas user distribution parameters and construct a gas user distribution topology;

[0052] Create module 2, which has submodules, including:

[0053] An uploading unit 21 is used to upload gas user distribution parameters and transmit the gas user distribution parameters to the building module 2;

[0054] A creation unit 22 is used to traverse the gas user distribution topology constructed in the construction module 2, create a cloud database at the corresponding position of each gas user in the gas user distribution topology, and store gas user usage parameters;

[0055] Among them, the gas user distribution parameters include: gas user location information, gas transmission direction of the gas pipeline where the gas user location information is located, when constructing the gas user distribution topology, the construction module 2 constructs the gas user distribution topology based on the gas user distribution parameters, and the gas user usage parameters include: the start and stop time of gas users using gas, and the gas usage within each start and stop time threshold of gas users using gas. The cloud database used to store the gas user usage parameters is bound to the corresponding position of the gas user in the gas user distribution topology by setting a hyperlink;

[0056] Identification module 3, used to traverse the gas user distribution topology constructed in construction module 2, and identify the child and parent nodes in the gas user distribution topology;

[0057] The identification module 3 is internally provided with submodules, including:

[0058] The reconstructing unit 31 is used to receive the identification result of the child and parent nodes of the gas user distribution topology in the identification module 3, extract the parent node in the gas user distribution topology, and transmit the extracted parent node to the construction module 2;

[0059] After the reconstruction unit 31 transmits the extracted parent node to the construction module 2, the construction module 2 runs again to construct a structural topology representing the gas main based on the received parent node;

[0060] An analysis module 4 is used to select an analysis target in the gas user distribution topology and perform a gas use safety status analysis on the analysis target;

[0061] The analysis module 4 is provided with submodules at the lower level, including:

[0062] Logic unit 41, used to set analysis target selection logic;

[0063] The transmission unit 42 is used to obtain the analysis result of the gas usage safety status of the analysis target by the analysis module 4, transmit the analysis result to the cloud database storing the gas user usage parameters, and store it in the cloud database;

[0064] When the analysis result is transmitted to the cloud database, the analysis target of the analysis result source is simultaneously identified, the corresponding cloud database is determined based on the analysis target, and the analysis result is further stored in the cloud database corresponding to the analysis target;

[0065] The determination module 5 is used to receive the analysis result of the gas use safety status of the analysis target, set the safety determination threshold, and compare the safety determination threshold with the analysis result to determine whether the gas use status of the analysis target is safe;

[0066] Feedback module 6, used for monitoring the determination result of whether the gas usage status of the analysis target in determination module 5 is safe, and when the determination result is negative, feeding back the analysis target related information of which the determination result is negative to control terminal 1;

[0067] The control terminal 1 is interactively connected to the construction module 2 through a wireless network, the construction module 2 is interactively connected to the upload unit 21, i.e., the creation unit 22 through a wireless network, the construction module 2 is interactively connected to the identification module 3 through a wireless network, the identification module 3 is electrically connected to the reconstruction unit 31 through a medium, the reconstruction unit 31 is interactively connected to the construction module 2 through a wireless network, the identification module 3 is interactively connected to the analysis module 4, the determination module 5, and the feedback module 6 through a wireless network, and the analysis module 4 is interactively connected to the logic unit 41 and the transmission unit 42 through a wireless network;

[0068] After the feedback module 6 feeds back the analysis target related information with a negative determination result to the control terminal 1 , the system end user accesses the system through the wireless network and reads the feedback information in the control terminal 1 of the system.

[0069] In this embodiment, the control terminal 1 controls the construction module 2 to obtain gas user distribution parameters and construct a gas user distribution topology. The upload unit 21 is synchronized with uploading the gas user distribution parameters and transmits the gas user distribution parameters to the construction module 2. The creation unit 22 traverses the gas user distribution topology constructed in the construction module 2 in real time, creates a cloud database at the corresponding position of each gas user in the gas user distribution topology, and stores the gas user usage parameters. The identification module 3 further traverses the gas user distribution topology constructed in the construction module 2 to identify the child and parent nodes in the gas user distribution topology. The reconstruction unit 31 synchronously receives the child and parent node identification results of the gas user distribution topology in the identification module 3, extracts the parent node in the gas user distribution topology, and transmits the extracted parent node to the construction module 2. The analysis module 4 is post-operated. In the gas user distribution topology, an analysis target is selected, and a gas use safety status analysis is performed on the analysis target. The logic unit 41 synchronously sets the analysis target selection logic, and the transmission unit 42 obtains the analysis result of the gas use safety status of the analysis target by the analysis module 4 in real time, and transmits the analysis result to the cloud database storing the gas user usage parameters, and stores it in the cloud database. Then, the determination module 5 receives the analysis result of the gas use safety status of the analysis target, sets a safety determination threshold, and compares the safety determination threshold with the analysis result to determine whether the gas use status of the analysis target is safe. Finally, the feedback module 6 monitors the determination result of whether the gas use status of the analysis target in the determination module 5 is safe. When the determination result is negative, the control terminal 1 is fed back with the relevant information of the analysis target with the determination result being negative.

[0070] See also Figure 4 As shown, based on the system in the above embodiment:

[0071] The modules and related systems are distributed in the enterprise intranet and government network. On the enterprise intranet side, it includes the gas company inspection business system and the intermediate library. The inspection system regularly pushes the inspection data of the day to the intermediate library to avoid tight coupling between the on-chain supervision system and each inspection business system.

[0072] On the government network side, it includes the main part of the on-chain supervision system, the digital identity service for inspection data, the blockchain hub, and the smart gas platform. The on-chain supervision system for gas inspection can be deployed independently or integrated into the smart gas platform as a module. It is developed based on microservice technology and consists of blockchain services, visualization services, and data docking services. The main responsibilities of the blockchain service are (1) writing the inspection data Hash to the distributed ledger; (2) Hash verification, calculating the hash of the inspection data using the SHA256 algorithm, and comparing the Hash value with the corresponding Hash in the distributed ledger. The main responsibility of the visualization service is to visualize the inspection progress, plan, and inspection pipeline coverage rate in one picture. The main responsibility of the data docking service is to dock with the gas company's inspection business system, and regularly extract and update the inspection search and retrieval data.

[0073] The distributed digital identity service is to mark the inspection data of each gas company with an identifier (DID) to represent a digital identity, which can achieve global uniqueness. At the same time, it identifies the sovereignty and control of each gas company over its own data information. In an environment across multiple departments and systems, identity authentication and information sharing can be selectively performed, thereby achieving better privacy protection.

[0074] The blockchain hub is composed of blockchain network nodes distributed in multiple government departments, which work together to perform multiple functions, including verifying transactions, maintaining the shared ledger of the blockchain, participating in consensus, and executing smart contract code. The blockchain hub relies on the characteristics of distributed ledgers and passwords in decentralized nodes that cannot be tampered with to provide a trusted distributed data network for upper-level applications. The blockchain hub includes multiple business sub-chains. The gas inspection data supervision described in this article belongs to the smart urban management line and is only a sub-chain in the blockchain hub.

[0075] Here, we will explain the data flow and interaction between the inspection business system, the inspection chain supervision system, the distributed digital identity service and the blockchain hub from the perspective of the overall business of chain supervision of inspection data.

[0076] (1) Generation of original inspection data: Gas company staff formulate inspection plans in the inspection system, execute the inspection plans, and combine the punch-in records at each inspection point and the hidden danger information found during the inspection process into inspection data. The inspection system pushes incremental inspection data to the corresponding intermediate database on a regular basis (once a day);

[0077] (2) Inspection data metadata and hash push: Extract metadata and calculate hash values ​​for inspection data in the enterprise intermediate database, and push metadata and hash values ​​to the distributed digital identity service on the government network side on a regular basis (once a day);

[0078] (3) Digital identity identification: Digital identity identification is generally divided into two processes: 1. Digital identity subject registration. When the gas enterprise inspection system and inspection check-in point are first connected, digital identity subject registration is required. 2. After registration is completed, the data generated by the inspection system or inspection point can be digitally identified.

[0079] (4) Construction of inspection data supervision model: After the inspection data completes the digital identity identification in the previous step, it is finally gathered in the on-chain supervision system. Then, the following steps are required to complete the construction of the model: 1. Write the digital identity and hash into the distributed ledger in the form of key / value through smart contracts; 2. Abstract the inspection metadata and convert it into a data index; 3. Establish a multi-layer composite association relationship of digital identity->blockchain hash->data index->original data;

[0080] (5) Inspection data verification: 1. The staff of the government functional department initiates a verification request, and the system initiates a remote authorization call to the corresponding enterprise inspection system based on the digital identity and identification. After authorization, the corresponding original data is returned and the hash value is calculated. 2. At the same time, the system queries the data hash value in the distributed ledger through the smart contract based on the digital identity, and compares the hash value in the ledger with the hash value calculated from the original data to see if they are consistent.

[0081] See also Figure 5 , Figure 6 As shown, based on the system in the above embodiment:

[0082] The inspection data structure is not a single data entity, but a combination of multiple data entities, including gas enterprise entities, inspection plan entities, inspection point entities, inspection record entities, and hidden danger information entities. As shown in the figure below, with the support of the digital identity system, each gas enterprise and inspection point is a digital identity entity (DID User) with a unique digital identity identifier for the entire network. Each inspection plan, inspection record, and hidden danger information is a digital identity credential (DID Credential), each generated by the corresponding digital identity entity. The inspection plan entity is the digital identity credential of the gas enterprise entity, and the inspection record and hidden danger information are the digital identity credential of the inspection point entity. In addition, there is a subordinate / parent-child relationship between the gas enterprise entity and the inspection point entity. The gas enterprise entity is the father node and the inspection point entity is the child node. It is also easy to understand from the real scene that a gas enterprise usually has multiple inspection points. When formulating an inspection plan, it is necessary to include multiple inspection points. During the execution of the planned task, it is necessary to record the information of each inspection point and report the hidden danger information of the inspection point.

[0083] Secondly, the multi-party supervision data model is also a distributed data structure, which requires data not to be out of the domain supervision. It is a multi-party participation data structure, such as Figure 3 As shown in the figure, the overall data structure includes original data, index data and evidence data. The original data is fixed on the enterprise side, the index data is distributed on the platform side, and the ledger data is stored on the distributed ledger.

[0084] Original data: Original data is directly generated by the enterprise inspection system. As a data asset of the gas enterprise, it is also sensitive and can only be stored and processed locally. The original data is stored on the enterprise data center buffer (DMZ) server to ensure that the data does not cross a specific geographical domain. This helps reduce the risk of cross-domain data transmission. As shown in the figure below, the original data is a complete backup of the inspection data with all attributes. Within the enterprise, each inspection point, inspection record, and hidden danger information has a unique code corresponding to it.

[0085] Index data: Index data is the extraction and mapping of the original data on the enterprise side. It is also the data structure that is truly stored inside the on-chain system, as shown in the figure below, which consists of some original data attributes and digital identities. The former is convenient for system users to query and retrieve, and the latter is used to uniquely identify the entire network. Index data is the core part of the multi-party data model in this article, and plays an important role in connecting the original data on the enterprise side externally and the evidence data of the distributed ledger internally.

[0086] Ledger data: Ledger data is a data structure stored on the blockchain distributed ledger. Figure 3 As shown in the figure, it consists of a digital identity certificate and a data fingerprint Hash (the original data is calculated by the SHA256 function), which is written to the distributed ledger in the form of a data transaction through a key / value pair. The ledger data cannot be changed and is associated with the index data through the digital identity field.

[0087] Embodiment 2:

[0088] In terms of specific implementation, based on Example 1, this example refers to Figure 1 A multi-party data supervision system based on blockchain technology in Example 1 is further described in detail:

[0089] The analysis target selection logic set in the logic unit 41 is expressed as:

[0090] Logic 1: The gas main structure topology and gas user distribution topology are taken as the first choice target and the second choice target of the analysis target respectively;

[0091] Logic2: Select a specified number of analysis targets from the first selection target, and perform gas use safety status analysis on the analysis targets based on the gas use safety status analysis logic;

[0092] Logic 3: Obtain the gas use safety status analysis result of the analysis target in the determination module 5. When the determination result is no, the process ends. When the determination result is yes, the process jumps to Logic 2 and runs again with the second selected target.

[0093] When selecting a specified number of analysis targets in Logic2 and Select Targets, the specified number of selected analysis targets is manually set by the system end user, and the number of selected analysis targets is not less than three groups;

[0094] Among them, during the continuous operation of the system, among the analysis targets selected in each system operation, the same analysis targets shall not exceed 20% of the total number of analysis target selections.

[0095] Through the above settings, the analysis target selection logic set in the logic unit 41 is further limited, providing necessary operation logic support for the operation of subsequent modules in the system.

[0096] Embodiment 3:

[0097] In terms of specific implementation, based on Example 1, this example refers to Figure 1 A multi-party data supervision system based on blockchain technology in Example 1 is further described in detail:

[0098] The analysis logic of the gas use safety status of the analysis target is expressed as:

[0099]

[0100] Where: k(a) is the gas safety status performance value of the analysis target a; n is the analysis target set that does not include the analysis target a; SIMM(a,b i ) is the similarity between the gas usage statistics corresponding to the analysis target a and the gas usage statistics corresponding to the i-th group of analysis targets b; The closed area formed by the minimum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b; The closed area formed by the minimum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b;

[0101] The larger the value of k(a), the safer the target gas usage state is; conversely, the less safe it is. The similarity of the two sets of statistical graphs is determined based on the height and slope of the line segments in the statistical graphs. When fitting the two sets of statistical graphs, the starting points or end points of the line segments in the two sets of statistical graphs are overlapped to complete the fitting operation.

[0102] The analysis target is in the gas use safety status analysis stage. The analysis target hyperlink is corresponding to the gas main structure topology or gas user distribution topology. The location analysis target corresponds to the cloud database. The gas start and stop time and the gas usage data within the threshold of each gas start and stop time of the gas user are obtained in the cloud database. Based on the gas start and stop time and the gas usage within the threshold of each gas start and stop time of the gas user, a gas usage statistical chart of the analysis target is generated.

[0103] The gas usage statistics chart of the analysis target is a line chart, the horizontal axis of which represents time, and the vertical axis represents gas usage;

[0104] The analysis target related information fed back in the feedback module 6 is the gas usage statistics chart corresponding to the analysis target.

[0105] Through the above settings, the analysis logic of the gas usage safety status of the analysis target is optimally limited, and the system operation logic is further provided to improve the system operation and ensure that the system provides stable and continuous maintenance and management to gas users and gas supply background.

[0106] To sum up, during the operation of the system in the above embodiment, distributed and synchronous management of gas users is performed by constructing a gas user topology, ensuring that the gas user's usage information can be monitored by the system in real time, and then when the gas user's gas usage habits change, the gas supply terminal staff can, based on the system, promptly detect the gas users whose gas usage habits have changed, and then when the gas users' gas usage habits change in a concentrated manner, the gas supply terminal staff can promptly adaptively dispatch the gas stored in the gas supply terminal to ensure the stable operation and maintenance of the gas supply terminal.

[0107] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-party data supervision system based on blockchain technology, characterized in that: include: The control terminal (1) is the main control terminal of the system and is used to issue execution commands; A construction module (2) is used to obtain gas user distribution parameters and construct a gas user distribution topology; The building module (2) is provided with submodules at the lower level, including: An uploading unit (21), used for uploading gas user distribution parameters, and transmitting the gas user distribution parameters to the building module (2); A creation unit (22) is used to traverse the gas user distribution topology constructed in the construction module (2), create a cloud database at the corresponding position of each gas user in the gas user distribution topology, and store gas user usage parameters; The gas user distribution parameters include: gas user location information, and the gas transmission direction of the gas pipeline where the gas user location information is located. When constructing the gas user distribution topology, the construction module (2) constructs the gas user distribution topology based on the gas user distribution parameters. The gas user usage parameters include: the start and stop time of the gas user, and the gas usage within the start and stop time threshold of the gas user. The cloud database used to store the gas user usage parameters is bound to the corresponding position of the gas user in the gas user distribution topology by setting a hyperlink. An identification module (3) is used to traverse the gas user distribution topology constructed in the construction module (2) and identify the child and parent nodes in the gas user distribution topology; The identification module (3) is internally provided with submodules, including: A reconstruction unit (31) is used to receive the child and parent node identification results of the gas user distribution topology in the identification module (3), extract the parent node in the gas user distribution topology, and transmit the extracted parent node to the construction module (2); After the reconstruction unit (31) transmits the extracted parent node to the construction module (2), the construction module (2) runs again to construct a structural topology representing the gas main based on the received parent node; An analysis module (4) is used to select an analysis target in the gas user distribution topology and perform a gas use safety status analysis on the analysis target; The analysis module (4) is provided with submodules at the lower level, including: A logic unit (41), used for setting analysis target selection logic; A transmission unit (42) is used to obtain the analysis result of the gas usage safety status of the analysis target by the analysis module (4), transmit the analysis result to a cloud database storing gas user usage parameters, and store it in the cloud database; When the analysis result is transmitted to the cloud database, the analysis target of the analysis result source is simultaneously identified, the corresponding cloud database is determined based on the analysis target, and the analysis result is further stored in the cloud database corresponding to the analysis target; The analysis target selection logic set in the logic unit (41) is expressed as: Logic 1: The gas main structure topology and gas user distribution topology are taken as the first choice target and the second choice target of the analysis target respectively; Logic2: Select a specified number of analysis targets from the first selection target, and perform gas use safety status analysis on the analysis targets based on the gas use safety status analysis logic; Logic 3: Obtain the gas use safety status analysis result of the analysis target in the determination module (5). When the determination result is negative, the process ends. When the determination result is positive, the process jumps to Logic 2 and runs again with the second selected target. The gas use safety status analysis logic of the analysis target is expressed as follows: Where: k(a) is the gas safety status performance value of the analysis target a; n is the analysis target set that does not include the analysis target a; SIMM(a,b i ) is the similarity between the gas usage statistics corresponding to the analysis target a and the gas usage statistics corresponding to the i-th group of analysis targets b; The closed area formed by the minimum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b; The closed area formed by the maximum interleaving under the fitting state is the gas usage statistical graph corresponding to the analysis target a and the gas usage statistical graph corresponding to the i-th group of analysis target b; The larger the value of k(a), the safer the target gas usage state is; conversely, the less safe it is. The similarity of the two sets of statistical graphs is determined based on the height and slope of the line segments in the statistical graphs. When fitting the two sets of statistical graphs, the starting points or end points of the line segments in the two sets of statistical graphs are overlapped to complete the fitting operation. A determination module (5) is used to receive the analysis result of the gas use safety status of the analysis target, set a safety determination threshold, and compare the safety determination threshold with the analysis result to determine whether the gas use status of the analysis target is safe; A feedback module (6) is used to monitor the determination result of whether the gas usage status of the analysis target in the determination module (5) is safe, and when the determination result is negative, to feed back to the control terminal (1) the relevant information of the analysis target whose determination result is negative; After the feedback module (6) feeds back the analysis target related information with a judgment result of "no" to the control terminal (1), the system end user accesses the system through a wireless network and reads the feedback information in the system control terminal (1).

2. According to claim 1, a multi-party data supervision system based on blockchain technology is characterized in that: When a specified number of analysis targets are selected in the selected targets in the Logic2, the specified number of selected analysis targets is manually set by the system end user, and the number of selected analysis targets is not less than three groups; Among them, during the continuous operation of the system, among the analysis targets selected in each system operation, the same analysis targets shall not exceed 20% of the total number of analysis target selections.

3. According to claim 1, a multi-party data supervision system based on blockchain technology is characterized in that: The analysis target corresponds to the analysis target hyperlink in the gas main structure topology or the gas user distribution topology during the gas use safety status analysis phase, and the location analysis target corresponds to the cloud database. The gas start and stop time and the gas usage data within the threshold of each gas start and stop time used by the gas user are obtained in the cloud database. Based on the gas start and stop time and the gas usage within the threshold of each gas start and stop time used by the gas user, a gas usage statistical chart of the analysis target is generated; The gas usage statistics graph of the analysis target is a line graph, the horizontal axis of the gas usage statistics graph of the analysis target represents time, and the vertical axis represents gas usage.

4. According to claim 1, a multi-party data supervision system based on blockchain technology is characterized in that: The analysis target related information fed back in the feedback module (6) is a gas usage statistical graph corresponding to the analysis target.

5. According to claim 1, a multi-party data supervision system based on blockchain technology is characterized in that: The control terminal (1) is interactively connected to a construction module (2) via a wireless network; the construction module (2) is interactively connected to an upload unit (21) and a creation unit (22) at a lower level via a wireless network; the construction module (2) is interactively connected to an identification module (3) via a wireless network; the identification module (3) is electrically connected to a reconstruction unit (31) via a medium; the reconstruction unit (31) is interactively connected to the construction module (2) via a wireless network; the identification module (3) is interactively connected to an analysis module (4), a determination module (5) and a feedback module (6) via a wireless network; the analysis module (4) is interactively connected to a logic unit (41) and a transmission unit (42) at a lower level via a wireless network.

Images