Industrial Internet Data Storage Method, System, Storage Medium and Electronic Device

Abstract

The present invention relates to the technical field of industrial Internet, and particularly relates to a method for storing industrial Internet data based on blockchain, including: obtaining sensor data of industrial equipment, filtering the sensor data to obtain data to be processed; sending the data to be processed to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ); the edge server receives the trained adaptive neural network data filtering model on the blockchain node of the cloud server, uses the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored; forwards the data to be stored to the blockchain node of the cloud server for association storage based on the grouping label.

Description

[0001] This application is a divisional application of a Chinese patent application filed with the Chinese Patent Office on February 21, 2022, with the application number 202210155546.9 and the invention title "Industrial Internet Data Storage Method, System and Storage Medium Based on Blockchain". Technical Field

[0002] The present invention relates to the technical field of industrial Internet, and particularly relates to an industrial Internet data storage method, system, computer-readable storage medium and electronic device based on blockchain. Background Art

[0003] With the advent of the industrial Internet era, more and more attention has been paid to how to process the large amount of big data generated in the industrial production and manufacturing process.

[0004] At the same time, with the development of the industrial Internet, big data and cloud computing are required in many fields, especially in the industrial production process, and various industrial data generated therein need to be processed through big data or cloud computing methods. However, in the process of industrial data processing in related fields, the data volume is huge, and generally the data is uniformly processed and then stored. The current processing and storage methods have the problem of low efficiency. Summary of the Invention

[0005] Embodiments of the present application provide an industrial Internet data storage method, system, computer-readable storage medium and electronic device based on blockchain, which can at least improve the efficiency of data processing and storage to a certain extent.

[0006] According to the first aspect of the embodiments of the present application, an industrial Internet data storage method based on blockchain is provided, including: obtaining sensor data of industrial equipment, filtering the sensor data to obtain data to be processed; sending the data to be processed to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1≤i≤M, M is a positive integer; n is the number of sensors included in the grouping label, and n is a positive integer greater than or equal to 1; the edge server receives the self-adaptive neural network data filtering model trained on the blockchain node of the cloud server, and uses the self-adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored; forwarding the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

[0007] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage method further includes: when a query instruction is received, determining whether the query instruction is an abnormal confirmation instruction; if so, calculating the probability of abnormal sensor grouping according to a preset algorithm, and determining an abnormal group according to the abnormal probability of the grouping label; and searching for corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal group.

[0008] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage method further includes: when abnormal sensor data is determined, creating a corresponding block and storing the abnormal sensor data on the blockchain; the blockchain is associated through a block header; each block includes a block header, block metadata, and block data; wherein, the block header includes a block number, the current block Hash, and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key, and signature of the writing program; and the block data includes abnormal sensor data.

[0009] According to the second aspect of the embodiments of the present application, a blockchain-based industrial Internet data storage system is provided, including: an acquisition module configured to acquire sensor data of industrial equipment, filter the sensor data to obtain data to be processed; an upload module configured to send the data to be processed to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1≤i≤M, M is a positive integer; n is the number of sensors included in the grouping label, and n is a positive integer greater than or equal to 1; a filtering module configured to receive, by the edge server, an adaptive neural network data filtering model trained on a blockchain node of a cloud server, and use the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored; a storage module configured to forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

[0010] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage system further includes: a first determination module configured to, when a query instruction is received, determine whether the query instruction is an abnormal confirmation instruction; a second determination module configured to, if so, calculate the probability of abnormal sensor grouping according to a preset algorithm, and determine an abnormal group according to the abnormal probability of the grouping label;

[0011] A search module, configured to search for corresponding abnormal sensor data according to the grouping tags of the sensors grouped by abnormality.

[0012] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage system further includes: a first creation module, configured to create a corresponding block when abnormal sensor data is determined, and store the abnormal sensor data on the blockchain; wherein, the blockchain is associated through a block header; each block includes a block header, block metadata, and block data; wherein, the block header includes a block number, the current block Hash, and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key, and signature of the writing program; the block data includes abnormal sensor data.

[0013] According to the third aspect of the embodiments of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the industrial Internet data storage method as described in the first aspect.

[0014] According to the fourth aspect of the embodiments of the present application, there is provided an electronic device, including: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the industrial Internet data storage method as described in the first aspect.

[0015] In the blockchain-based industrial Internet data storage method provided by some embodiments of the present application, sensor data of industrial equipment is obtained, the sensor data is filtered to obtain data to be processed; the data to be processed is sent to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping tag corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping tag FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in), where \(1\leq i\leq M\), \(M\) is a positive integer; \(n\) is the number of sensors included in the grouping label, and \(n\) is a positive integer greater than or equal to 1. The edge server receives the adaptive neural network data filtering model trained on the blockchain node of the cloud server, uses the adaptive neural network data filtering model to filter the data to be uploaded, and obtains the data to be stored. The data to be stored is forwarded to the blockchain node of the cloud server for associated storage based on the grouping label. In this solution, during the industrial production process, the acquired sensor data is filtered and then uploaded to the edge server for grouping and association to obtain the data to be uploaded. Then, the data to be uploaded is filtered by the adaptive neural network data filtering model of the edge server to obtain the data to be stored. The data to be stored is sent to the blockchain node of the cloud server for associated storage based on the grouping label, thereby improving the data processing efficiency and data storage efficiency based on the characteristics of the edge server, cloud server, and blockchain. In addition, it is also convenient for data traceability.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. Brief Description of the Drawings

[0017] The drawings here are incorporated into the specification and form a part of this specification, showing the embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 Schematically shows a flowchart of a blockchain-based industrial Internet data storage method according to an embodiment of this application;

[0019] Figure 2 Schematically shows another flowchart of a blockchain-based industrial Internet data storage method according to an embodiment of this application;

[0020] Figure 3 Schematically shows a schematic diagram of the sensor data format stored on the blockchain of a blockchain-based industrial Internet data storage method according to an embodiment of this application;

[0021] Figure 4 Schematically shows another schematic diagram of the sensor data format stored on the blockchain of a blockchain-based industrial Internet data storage method according to an embodiment of this application;

[0022] Figure 5Schematically shown is a schematic diagram of a blockchain-based industrial Internet data storage system according to an embodiment of the present application;

[0023] Figure 6 Shown is a schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application. Detailed implementation manners

[0024] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0025] In addition, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will recognize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be employed. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0026] The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the drawings are only illustrative and do not necessarily include all the content and operations / steps, nor do they necessarily have to be executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0028] The implementation details of the technical solutions of the embodiments of the present application are elaborated in detail below:

[0029] Figure 1 Shown is a flowchart of a blockchain-based industrial Internet data storage method according to an embodiment of the present application. The blockchain-based industrial Internet data storage method can be executed by a server, and the server includes an edge server and a cloud server. Referring to Figure 1 As shown, the blockchain-based industrial Internet data storage method at least includes steps S110 to S140, which are introduced in detail as follows:

[0030] Step S110: Obtain the sensor data of the industrial equipment, filter the sensor data to obtain the data to be processed.

[0031] For step S110, optionally, the industrial equipment in this embodiment includes industrial equipment such as lathes, milling machines, grinding machines, punching machines, flexible manufacturing lines, PLCs, machining centers, robots, laser machines, industrial computers, tool setting instruments, cutting machines, and welding machines. In order to monitor the working status of industrial equipment, various types of sensors are set. Obtain the data of these sensors and filter the sensor data to obtain the data to be processed.

[0032] Step S120: Send the data to be processed to the edge server for grouping and association to obtain the data to be uploaded; where each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1 ≤ i ≤ M, M is a positive integer; n is the number of sensors included in the grouping label, and n is a positive integer greater than or equal to 1; n is the number of sensors included in the grouping label, and n is a positive integer greater than or equal to 1.

[0033] For step S120, send the data to be processed to the edge server, group the data to be processed in the edge server, and then through the grouping label, make the sensor data in the same group under the same grouping label. Each grouping label corresponds to at least one sensor. For example, the grouping label FZID6 corresponds to the sensor data of sensors 61, 62, and 63. Associate multiple sensors with the grouping label to facilitate the management of sensor data and the tracing of data in case of subsequent anomalies. Specifically, the data structure of the data to be uploaded can be: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1 ≤ i ≤ M, M is a positive integer.

[0034] Among them, the data transmission after data sending can be through wired or wireless means. Among them, the above wireless connection methods can include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other currently known or future-developed wireless connection methods.

[0035] Step S130: The edge server receives the trained adaptive neural network data filtering model on the blockchain node of the cloud server, and uses the adaptive neural network data filtering model to filter the data to be uploaded to obtain the data to be stored.

[0036] Reference Figure 2 , in step S130, using the adaptive neural network data filtering model to filter the grouping labels and the corresponding sensor data to obtain the data to be stored, including:

[0037] Step S1301: Based on the preset load of the edge server, determine the first grouping of sensors according to the approved load and approved energy consumption of the sensors.

[0038] Step S1302: Based on the remaining load of the edge server, determine the second grouping of sensors according to the working load and working energy consumption of the sensors.

[0039] For steps S1301 and S1302, where pre-grouping can first determine the preliminary grouping situation of the sensors, and then determine the final grouping situation according to the actual working load and working energy consumption of the sensors, and based on the grouping label as the identity label of the sensor, so that the grouping is not based on each sensor but on the grouping label, greatly reducing the calculation amount.

[0040] Optionally, the relevant information of the load includes any one or more of machine load information, machine configuration information, and data volume load information. In an alternative implementation, the relevant information of the load includes machine load information, machine configuration information, and data volume load information.

[0041] Step S1303: Based on the first grouping and the second grouping, determine whether it is necessary to adjust the group of the sensors.

[0042] Step S1304: If so, adjust the sensors from the first grouping to the second grouping to obtain the third grouping; or from the second grouping to the first grouping to obtain the fourth grouping.

[0043] Step S1305: If the third grouping is obtained, further process the sensor data in each ID set in the third grouping.

[0044] Step S1306: If the fourth grouping is obtained, further process the sensor data in each ID set in the fourth grouping.

[0045] For steps S1303 to S1306, adjust the grouping according to the actual situation to obtain the optimal grouping and data structure, and then obtain the data to be stored.

[0046] It should be noted that when training the adaptive neural network data filtering model on the blockchain node of the cloud server, the data to be stored and the corresponding initial sensor data obtained in steps S1301 to S1306 can also be used as the output and input respectively to further optimize and iterate the parameters of the adaptive neural network data filtering model.

[0047] Step S140: Forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

[0048] In step S140, the data to be stored in each edge server is forwarded to the blockchain node of the cloud server for associated storage based on the grouping label. The filtering process in the edge server can be parallel, which improves the data processing efficiency. Unified storage on the blockchain node of the cloud service is convenient for management, improves the storage efficiency, and is also convenient for data traceability.

[0049] In the method for storing industrial Internet data based on blockchain provided in some embodiments of the present application, sensor data of industrial equipment is obtained, the sensor data is filtered to obtain data to be processed; the data to be processed is sent to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1≤i≤M, M is a positive integer; n is the number of sensors included in the grouping label, and n is a positive integer greater than or equal to 1; the edge server receives the trained adaptive neural network data filtering model on the blockchain node of the cloud server, and uses the adaptive neural network data filtering model to filter the data to be uploaded to obtain the data to be stored; the data to be stored is forwarded to the blockchain node of the cloud server for associated storage based on the grouping label. In this solution, during the industrial production process, the obtained sensor data is filtered and then uploaded to the edge server for grouping and association to obtain the data to be uploaded; then, the data to be uploaded is filtered by the adaptive neural network data filtering model of the edge server to obtain the data to be stored; and the data to be stored is sent to the blockchain node of the cloud server for associated storage based on the grouping label, thereby improving the data processing efficiency and data storage efficiency based on the characteristics of the edge server, the cloud server, and the blockchain. In addition, it is also convenient for data traceability.

[0050] In some embodiments of the present application, based on the foregoing solution, in some embodiments of the present application, based on the foregoing solution, the method for storing industrial Internet data based on blockchain further includes:

[0051] Step S150: When a query instruction is received, determine whether the query instruction is an exception confirmation instruction.

[0052] Step S160: If so, calculate the probability of sensor grouping exception according to a preset algorithm, and determine the abnormal grouping according to the exception probability of the grouping label.

[0053] Among them, the preset algorithm is as follows:

[0054]

[0055] Among them, m is the serial number of the sensor node, 1 ≤ m ≤ M, M is the number of sensor nodes, and FzYcProb i is the distribution vector of the i-th group.

[0056] FzYcWtVec m is the preset weight vector corresponding to the m-th sensor node, FzYcProb i,m is the probability value of the i-th group including m sensor nodes being abnormal.

[0057] Step S170: Search for the corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal grouping.

[0058] In some embodiments of the present application, based on the foregoing solution, the searching for the corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal grouping includes:

[0059] Step S1701: Perform hash operations on the grouping label respectively using K mutually independent hash functions according to the following formula: HashKey k = Hash k (FZID i ); where FZID i is the grouping label, Hash k is the hash function with the serial number k, HashKey k is the hash value with the serial number k obtained by the operation, 1 ≤ k ≤ K, K is an integer greater than 1; FZID i is the grouping label with the serial number i, 1 ≤ i ≤ I, I is an integer greater than 1;

[0060] Step S1702: Obtain the array corresponding to the grouping label, and determine whether the array meets the following judgment condition: for any value of k, the equation ARRAY[HashKey k == Value_1 holds, where ARRAY is the query array and Value_1 is a preset first numerical value;

[0061] Step S1703: If the array does not meet the judgment condition, it is determined that the grouped tag is not found in the sensor database of the server.

[0062] In some embodiments of the present application, based on the foregoing solution, the industrial Internet data storage method based on the blockchain further includes:

[0063] Step S180: When there is no sensor data stored in the edge server, for any value of m, the following assignment operation is performed: ARRAY[m]=Value_2; where 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value.

[0064] Step S190: When there is sensor data in the edge server, extract the grouped tag in the sensor data; perform hash operations on the grouped tag using K mutually independent hash functions according to the following formula: HashKeyExist k =Hash k (FZIDExist); where FZIDExist is the grouped tag, and HashKeyExist k is the hash value with the serial number k obtained by the operation; for any value of k, the following assignment operation is performed: ARRAY[HashKeyExist k =Value_1.

[0065] In some embodiments of the present application, based on the foregoing solution, the industrial Internet data storage method based on the blockchain further includes: when abnormal sensor data is determined, a corresponding block is created, and the abnormal sensor data is stored on the blockchain; the blockchain is associated through block headers; each block includes a block header, block metadata, and block data; where the block header includes a block number, the current block Hash, and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key, and signature of the writing program; the block data includes abnormal sensor data. In this embodiment, the block data only includes abnormal sensor data, which further improves the storage efficiency and also improves the efficiency of finding abnormal sensor data.

[0066] Specifically, Figure 3It is a schematic diagram of the sensor data format stored on the blockchain of the blockchain-based industrial Internet data storage method. Among them, 3 nodes are schematically shown. The data formats stored on each node of the blockchain are the same, and what is stored is sensor data. The data formats of sensor data on different blockchain platforms will be different, but basically, the sensor data is composed of blocks. Specifically, the block header contains the block number, the current block Hash (the Hash of all sensors included in the current block), and the Hash of the previous block; the block metadata contains the block creation time, the certificate, public key, and signature of the writing program, etc. The block data contains a set of abnormal sensor data (such as abnormal sensor 1, abnormal sensor 2, abnormal sensor 3, etc.), and the sensor data is written when the block is created.

[0067] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage method further includes: when abnormal sensor data is determined, creating a corresponding block and storing the abnormal sensor data on the blockchain; the blockchain is associated through the block header; each block includes a block header, block metadata, and block data; wherein, the block header contains the block number, the current block Hash, and the Hash of the previous block; the block metadata contains the block creation time, the certificate, public key, and signature of the writing program; the block data includes abnormal sensor data and normal sensor data. The block data including abnormal sensor data and normal sensor data makes the sensor data more comprehensive.

[0068] Specifically, Figure 4 It is another schematic diagram of the sensor data format stored on the blockchain of the blockchain-based industrial Internet data storage method. Among them, 3 nodes are schematically shown. The data formats stored on each node of the blockchain are the same, and what is stored is sensor data. The data formats of sensor data on different blockchain platforms will be different, but basically, the sensor data is composed of blocks. Specifically, the block header contains the block number, the current block Hash (the Hash of all sensors included in the current block), and the Hash of the previous block; the block metadata contains the block creation time, the certificate, public key, and signature of the writing program, etc. The block data contains a set of abnormal sensor data (such as abnormal sensor 1, abnormal sensor 2, normal sensor 3, normal sensor 4, etc.), and the sensor data is written when the block is created. A set of sensor data includes normal data and abnormal data.

[0069] Please refer to Figure 5As shown below, an embodiment of the industrial Internet data storage system based on blockchain of the present application will be introduced, which can be used to execute the industrial Internet data storage method based on blockchain in the embodiments of the present application. It can be understood that the system can be a computer program (including program code) running in a computer device. For example, the system is an application software; the system can be used to execute the corresponding steps in the method provided in the embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the embodiments of the industrial Internet data storage method based on blockchain above in the present application.

[0070] Referring to Figure 5 As shown, an industrial Internet data storage system 500 based on blockchain according to an embodiment of the present application includes:

[0071] An acquisition module 510, configured to acquire sensor data of industrial equipment, filter the sensor data to obtain data to be processed.

[0072] An upload module 520, configured to send the data to be processed to an edge server for grouping and association to obtain data to be uploaded; wherein, each grouping label corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping label FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1≤i≤M and M is a positive integer.

[0073] A filtering module 530, configured to receive an adaptive neural network data filtering model trained on a blockchain node of a cloud server by the edge server, and use the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored.

[0074] A storage module 540, configured to forward the data to be stored to a blockchain node of a cloud server for associated storage based on the grouping label.

[0075] In some embodiments of the present application, based on the foregoing solution, the filtering module includes: a first determination unit configured to determine a first grouping of sensors based on the preset load of the edge server, according to the approved load and approved energy consumption of the sensors; a second determination unit configured to determine a second grouping of sensors based on the remaining load of the edge server, according to the working load and working energy consumption of the sensors; a third determination unit configured to determine whether it is necessary to adjust the grouping of the sensors based on the first grouping and the second grouping; a first grouping adjustment unit configured to, if so, adjust the sensors from the first grouping to the second grouping to obtain a third grouping; or adjust them from the second grouping to the first grouping to obtain a fourth grouping; a second grouping adjustment unit configured to, if the obtained grouping is the third grouping, further process the sensor data in each ID set in the third grouping; a third grouping adjustment unit configured to, if the obtained grouping is the fourth grouping, further process the sensor data in each ID set in the fourth grouping.

[0076] In some embodiments of the present application, based on the foregoing solution, the industrial Internet data storage system based on blockchain further includes: a first determination module configured to determine whether the query instruction is an abnormal confirmation instruction when receiving the query instruction; a second determination module configured to, if so, calculate the probability of sensor grouping abnormality according to a preset algorithm, and determine the abnormal grouping according to the abnormality probability of the grouping label.

[0077] A search module configured to search for corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal grouping.

[0078] In some embodiments of the present application, based on the foregoing solution, the search module includes: an operation unit configured to perform hash operations on the grouping label respectively using K mutually independent hash functions according to the following formula: HashKey k =Hash k (FZID i ); where FZID i is the grouping label, Hash k is the k-th hash function, HashKey k is the k-th hash value obtained by the operation, 1 ≤ k ≤ K, K is an integer greater than 1; FZID i is the i-th grouping label, 1 ≤ i ≤ I, I is an integer greater than 1; a judgment unit configured to obtain the array corresponding to the grouping label and judge whether the array satisfies the following judgment condition: for any value of k, the equation ARRAY[HashKey k== Value_1 holds true for all, where ARRAY is the query array and Value_1 is a preset first numerical value; a determination unit configured to determine that the grouped tag is not found in the sensor database of the server if the array does not meet the determination condition.

[0079] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage system further includes: a first assignment module configured to, when no sensor data is stored in the edge server, perform the following assignment operation for any value of m: ARRAY[m] = Value_2; where 1 ≤ m ≤ M, M is the number of sensors in the array, and Value_2 is a preset second numerical value; an extraction module configured to extract the grouped tag from the sensor data when there is sensor data in the edge server; an operation module configured to perform a hash operation on the grouped tag using K mutually independent hash functions according to the following formula: HashKeyExist k = Hash k (FZIDExist); where FZIDExist is the grouped tag and HashKeyExist k is the hash value with serial number k obtained by the operation; a first assignment module configured to perform the following assignment operation for any value of k: ARRAY[HashKeyExist k = Value_1.

[0080] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage system further includes: a first creation module configured to create a corresponding block when abnormal sensor data is determined and store the abnormal sensor data on the blockchain; where the blockchain is associated through block headers; each block includes a block header, block metadata, and block data; where the block header includes a block number, the current block Hash, and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key, and signature of the writing program; and the block data includes abnormal sensor data.

[0081] In some embodiments of the present application, based on the foregoing solution, the blockchain-based industrial Internet data storage system further includes: a second creation module configured to create a corresponding block when abnormal sensor data is determined and store the abnormal sensor data on the blockchain; the blockchain is associated through block headers; each block includes a block header, block metadata, and block data; where the block header includes a block number, the current block Hash, and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key, and signature of the writing program; and the block data includes abnormal sensor data and normal sensor data.

[0082] Figure 6 The structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0083] It should be noted that Figure 6 The computer system 600 of the electronic device shown is only an example, and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0084] As Figure 6 shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage section 608 into the random access memory (RAM) 603, such as executing the method described in the above embodiments. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. The input / output (I / O) interface 605 is also connected to the bus 604.

[0085] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. The drive 610 is also connected to the (Input / Output, I / O) interface 605 as required. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as required, so that the computer program read from it can be installed into the storage section 608 as required.

[0086] In particular, according to an embodiment of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0087] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The computer program included on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0088] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes may occur in a different order from that marked in the accompanying drawings. For example, two consecutively represented boxes may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, as well as the combination of boxes in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0089] The units involved in the embodiments described in the present application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the unit itself.

[0090] According to one aspect of the present application, there is provided a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various alternative implementation manners.

[0091] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the one or more programs are executed by an electronic device, the electronic device implements the methods described in the above embodiments.

[0092] It should be noted that although several modules or units of devices for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0093] Those skilled in the art can easily understand from the description of the above embodiments that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0094] After considering the specification and practicing the embodiments disclosed herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application.

[0095] It should be understood that the present application is not limited to the exact structures already described and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A blockchain-based industrial Internet data storage method, characterized in that, including: Obtain sensor data of industrial equipment, filter the sensor data to obtain data to be processed; Send the data to be processed to the edge server for grouping and association to obtain the data to be uploaded; wherein, each grouping tag corresponds to at least one sensor; the data structure of the data to be uploaded is: grouping tag FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1 ≤ i ≤ M, M is a positive integer; n is the number of sensors included in the grouping tag, and n is a positive integer greater than or equal to 1; The edge server receives the trained adaptive neural network data filtering model on the blockchain node of the cloud server, and uses the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored; Forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label; When receiving a query instruction, determine whether the query instruction is an anomaly confirmation instruction; If so, calculate the probability of sensor grouping anomaly according to a preset algorithm, and determine the abnormal grouping according to the anomaly probability of the grouping label; Wherein, the preset algorithm is as follows: where m is the serial number of the sensor node, 1 ≤ m ≤ M, M is the number of sensor nodes, and FzYcProb i is the distribution vector of the i-th group; FzYcWtVec m is the preset weight vector corresponding to the m-th sensor node, FzYcProb i,m is the probability value of the i-th group anomaly including m sensor nodes; Search for corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal grouping; When the abnormal sensor data is determined, create a corresponding block and store the abnormal sensor data on the blockchain; the blockchain is associated through the block header; each block includes a block header, block metadata and block data; wherein, the block header contains the block number, the current block Hash and the Hash of the previous block; the block metadata contains the block creation time, the certificate, public key and signature of the writing program; the block data includes the abnormal sensor data.

2. An industrial Internet data storage system based on blockchain, characterized in that, including: An acquisition module, configured to obtain sensor data of industrial equipment, filter the sensor data to obtain data to be processed; An upload module, configured to send the data to be processed to the edge server, group and associate them to obtain data to be uploaded; Among them, each group tag corresponds to at least one sensor; the data structure of the data to be uploaded is: group tag FZID i , (CGQ i1 , CGQ i2 , ……, CGQ in ), where 1 ≤ i ≤ M, M is a positive integer; n is the number of sensors included in the group tag, and n is a positive integer greater than or equal to 1; A filtering module, configured to receive the trained adaptive neural network data filtering model on the blockchain node of the cloud server by the edge server, and use the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored; A storage module, configured to forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label; A first determination module, configured to determine whether the query instruction is an anomaly confirmation instruction when receiving a query instruction; A second determination module, configured to, if so, calculate the probability of sensor grouping anomaly according to a preset algorithm, and determine the abnormal grouping according to the anomaly probability of the grouping label; wherein, the preset algorithm is as follows: where m is the serial number of the sensor node, 1 ≤ m ≤ M, and M is the number of sensor nodes, and FzYcProb i is the distribution vector of the i-th group; FzYcWtVec m is the preset weight vector corresponding to the m-th sensor node, FzYcProb i,m is the probability value of the i-th group anomaly including m sensor nodes; A search module, configured to search for corresponding abnormal sensor data according to the grouping label of the sensors in the abnormal grouping; A first creation module, configured to create a corresponding block and store the abnormal sensor data on the blockchain when the abnormal sensor data is determined; wherein, the blockchain is associated through the block header; each block includes a block header, block metadata and block data; wherein, the block header contains the block number, the current block Hash and the Hash of the previous block; the block metadata contains the block creation time, the certificate, public key and signature of the writing program; the block data includes the abnormal sensor data.

3. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, implements the industrial Internet data storage method as described in claim 1.

4. An electronic device, characterized in that, including: One or more processors; A storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the industrial Internet data storage method as described in claim 1.

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