Industrial Internet data storage method, system and electronic device based on blockchain

Abstract

The present invention relates to the field of industrial Internet technology, and in particular to a blockchain-based industrial Internet data storage method, comprising: obtaining sensor data of industrial equipment, filtering and processing the sensor data to obtain data to be processed; sending the data to be processed to an edge server, grouping and associating the data 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 ); 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 uploaded data, and obtains the data to be stored; forwards the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

Description

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

[0002] The present invention relates to the field of industrial Internet technology, and specifically 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, how to deal with the large amount of big data generated by the industrial production and manufacturing process has received more and more attention.

[0004] At the same time, with the development of industrial Internet, big data and cloud computing are needed in many fields, especially in the process of industrial production, where various industrial data generated need to be processed through big data or cloud computing. However, in the process of industrial data processing in related fields, the amount of data is huge, and the data is generally processed and stored in a unified manner. The current processing and storage methods have the problem of low efficiency. Summary of the invention

[0005] The 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 improve the efficiency of data processing and storage at least to a certain extent.

[0006] According to the first aspect of the embodiment of the present application, a blockchain-based industrial Internet data storage method is provided, including: obtaining sensor data of industrial equipment, filtering and processing the sensor data to obtain data to be processed; sending the data to be processed to an edge server, grouping and associating the data 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≤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 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 uploaded data, and obtains the data to be stored; forwards the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag.

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

[0008] In some embodiments of the present application, based on the above scheme, searching for corresponding abnormal sensor data according to the grouping label of the abnormally grouped sensor includes: performing a hash operation on the grouping label using K 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 serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID i is the grouping label with serial number i, 1≤i≤I, I is an integer greater than 1; get the array corresponding to the grouping label, and determine whether the array meets the following judgment conditions: for any value of k, the equation ARRAY[HashKey k ]==Value_1, where ARRAY is the query array and Value_1 is a preset first value; if the array does not meet the judgment condition, it is determined that the grouping tag is not found in the sensor database of the server.

[0009] In some embodiments of the present application, based on the aforementioned scheme, the blockchain-based industrial Internet data storage method further includes: when no sensor data is stored in the edge server, the following assignment operation is performed for any value of m: ARRAY[m]=Value_2; wherein 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value; when sensor data exists in the edge server, the grouping label in the sensor data is extracted; and the grouping label is hashed using K independent hash functions according to the following formula: HashKeyExist k =Hash k (FZID Exist); where FZID Exist is the grouping tag, HashKeyExist k is the hash value of the sequence number k obtained by the operation; for any value of k, the following assignment operation is performed: ARRAY[HashKeyExistk ]=Value_1.

[0010] According to the second aspect of the embodiment 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 and process the sensor data, and obtain data to be processed; an upload module, configured to send the data to be processed to an edge server, group and associate the data, and 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 ), wherein 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 filtering module is configured as an edge server to receive the adaptive neural network data filtering model trained on the blockchain node of the cloud server, and use the adaptive neural network data filtering model to filter the uploaded data to obtain the data to be stored; the storage module is configured to forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag.

[0011] In some embodiments of the present application, based on the aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a first determination module, configured to determine whether the query instruction is an abnormality confirmation instruction when receiving a 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 abnormal probability of the grouping label; a search module, configured to search for corresponding abnormal sensor data according to the grouping label of the sensor in the abnormal group.

[0012] In some embodiments of the present application, based on the above solution, the search module includes: a computing unit configured to perform a hash operation on the grouping tag 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 serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID iis a grouping tag with serial number i, 1≤i≤I, and I is an integer greater than 1; the judgment unit is configured to obtain the array corresponding to the grouping tag and judge whether the array satisfies the following judgment conditions: for any value of k, the equation ARRAY[HashKey k ]==Value_1, wherein ARRAY is the query array and Value_1 is a preset first value; the determination unit is configured to determine that the grouping tag is not found in the sensor database of the server if the array does not meet the determination condition.

[0013] In some embodiments of the present application, based on the aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a first assignment module, configured to perform the following assignment operation for any value of m when no sensor data is stored in the edge server: ARRAY[m]=Value_2; wherein 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value; an extraction module, configured to extract the grouping label in the sensor data when there is sensor data in the edge server; and an operation module, configured to perform a hash operation on the grouping label using K independent hash functions according to the following formula: HashKeyExist k =Hash k (FZID Exist); where FZID Exist is the grouping tag, HashKeyExist k is the hash value of the sequence number k obtained by the operation; the first assignment module is configured to perform the following assignment operation for any value of k: ARRAY[HashKeyExist k ]=Value_1.

[0014] According to a third aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the industrial Internet data storage method as described in the first aspect is implemented.

[0015] According to a fourth aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the industrial Internet data storage method as described in the first aspect.

[0016] In the blockchain-based industrial Internet data storage method provided in some embodiments of the present application, the sensor data of the industrial equipment is obtained, the sensor data is filtered to obtain the data to be processed; the data to be processed is sent to the edge server, grouped and associated 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 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 uploaded data to obtain the data to be stored; forwards the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag. This solution filters the acquired sensor data in the industrial production process and then uploads it to the edge server for grouping and association to obtain the data to be uploaded; then filters the uploaded data through the adaptive neural network data filtering model of the edge server to obtain the data to be stored; and sends the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag, thereby improving the data processing efficiency and data storage efficiency based on the characteristics of the edge server, the cloud server and the blockchain, and also facilitating the traceability of the data.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A flowchart of an industrial Internet data storage method based on blockchain according to an embodiment of the present application is schematically shown;

[0020] Figure 2 Another flowchart of a blockchain-based industrial Internet data storage method according to an embodiment of the present application is schematically shown;

[0021] Figure 3A schematic diagram of the sensor data format stored on a blockchain of an industrial Internet data storage method based on blockchain according to an embodiment of the present application is schematically shown;

[0022] Figure 4 Another schematic diagram schematically shows the sensor data format stored on the blockchain of the industrial Internet data storage method based on blockchain according to an embodiment of the present application;

[0023] Figure 5 A schematic diagram of an industrial Internet data storage system based on blockchain according to an embodiment of the present application is schematically shown;

[0024] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of 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 comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0026] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0027] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may 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.

[0028] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0029] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0030] Figure 1 A flowchart of an industrial Internet data storage method based on blockchain according to an embodiment of the present application is shown. The industrial Internet data storage method based on blockchain can be executed by a server, which includes an edge server and a cloud server. Figure 1 As shown, the blockchain-based industrial Internet data storage method includes at least steps S110 to S140, which are described in detail as follows:

[0031] Step S110: Acquire sensor data of industrial equipment, filter the sensor data, and obtain data to be processed.

[0032] For step S110, optionally, the industrial equipment in this embodiment includes lathes, milling machines, grinders, punching machines, flexible manufacturing lines, PLCs, machining centers, robots, laser machines, industrial computers, tool setting instruments, cutting machines, welding machines and other industrial equipment. In order to monitor the working status of industrial equipment, various types of sensors are provided. The data of these sensors are obtained, and the sensor data is filtered and processed to obtain the data to be processed.

[0033] Step S120: Send the data to be processed to the edge server, group and associate them, and 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; n is the number of sensors included in the grouping tag, and n is a positive integer greater than or equal to 1.

[0034] For step S120, the data to be processed is sent to the edge server, where the data to be processed is grouped, and then the sensor data in the same group is placed under the same grouping label through grouping labels, and each grouping label corresponds to at least one sensor. For example, grouping label FZID6 corresponds to the sensor data of sensor 61, sensor 62, and sensor 63. Associating multiple sensors with grouping labels facilitates the management of sensor data and the tracing of data if anomalies occur later. 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, and M is a positive integer.

[0035] Among them, the data transmission after the data is sent can be via wired or wireless methods, among which the above-mentioned wireless connection methods may include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0036] Step S130: The edge server receives the adaptive neural network data filtering model trained 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.

[0037] refer to Figure 2 In step S130, the grouping labels and corresponding sensor data are filtered using the adaptive neural network data filtering model to obtain data to be stored, including:

[0038] Step S1301: Based on the preset load of the edge server, and according to the approved load and approved energy consumption of the sensors, a first grouping of sensors is determined.

[0039] Step S1302: Based on the remaining load of the edge server and according to the workload and working energy consumption of the sensors, a second grouping of sensors is determined.

[0040] For steps S1301 and S1302, the pre-grouping can first determine the preliminary grouping of the sensors, and then determine the final grouping according to the actual workload and working energy consumption of the sensors, and use the grouping label as the identity label of the sensor, so that grouping is not based on each sensor but based on the grouping label, which greatly reduces the amount of calculation.

[0041] Optionally, the load-related information includes any one or more of machine load information, machine configuration information, and data volume load information. In an optional implementation, the load-related information includes machine load information, machine configuration information, and data volume load information.

[0042] Step S1303: Based on the first grouping and the second grouping, determine whether the sensor grouping needs to be adjusted.

[0043] Step S1304: If yes, adjust the sensors from the first group to the second group to obtain the third group; or adjust the sensors from the second group to the first group to obtain the fourth group.

[0044] Step S1305: If the third group is obtained, further process the sensor data in each ID set in the third group.

[0045] Step S1306: If the fourth group is obtained, further process the sensor data in each ID set in the fourth group.

[0046] For steps S1303 to S1306, the grouping is adjusted according to the actual situation to obtain the optimal grouping and data structure, and then the data to be stored is obtained.

[0047] It should be noted that the adaptive neural network data filtering model can be trained on the blockchain node of the cloud server, and the data to be stored and the corresponding initial sensor data obtained in steps S1301 to S1306 can be used as output and input respectively to further optimize and iterate the parameters of the adaptive neural network data filtering model.

[0048] Step S140: forwarding the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

[0049] In step S140, the data to be stored in each edge server is forwarded to the blockchain node of the cloud server, and associated storage is performed based on the grouping label. The filtering processing in the edge server can be parallelized, which improves the efficiency of data processing. The data is uniformly stored on the blockchain node of the cloud service, which is easy to manage, improves storage efficiency, and facilitates data traceability.

[0050] In the blockchain-based industrial Internet data storage method provided in some embodiments of the present application, the sensor data of the industrial equipment is obtained, the sensor data is filtered to obtain the data to be processed; the data to be processed is sent to the edge server, grouped and associated 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 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 uploaded data to obtain the data to be stored; forwards the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag. This solution filters the acquired sensor data in the industrial production process and then uploads it to the edge server for grouping and association to obtain the data to be uploaded; then filters the uploaded data through the adaptive neural network data filtering model of the edge server to obtain the data to be stored; and sends the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping tag, thereby improving the data processing efficiency and data storage efficiency based on the characteristics of the edge server, the cloud server and the blockchain, and also facilitating the traceability of the data.

[0051] 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 industrial Internet data storage method based on blockchain further includes:

[0052] Step S150: When a query instruction is received, determine whether the query instruction is an abnormality confirmation instruction.

[0053] Step S160: If yes, the probability of sensor grouping being abnormal is calculated according to a preset algorithm, and the abnormal group is determined according to the abnormal probability of the grouping label.

[0054] Among them, the preset algorithm is as follows:

[0055]

[0056] Where m is the serial number of the sensor node, 1≤m≤M, M is the number of sensor nodes, FzYcProb i is the distribution vector of the i-th group.

[0057] FWf m is the preset weight vector corresponding to the mth sensor node, FqV i，m is the probability value of the abnormality of the i-th group including m sensor nodes.

[0058] Step S170: searching for corresponding abnormal sensor data according to the grouping labels of the abnormally grouped sensors.

[0059] In some embodiments of the present application, based on the above solution, searching for corresponding abnormal sensor data according to the grouping label of the abnormally grouped sensor includes:

[0060] Step S1701: Use K independent hash functions to perform hash operations on the grouping labels according to the following formula: k =Hash k (FZID i ), where FZID i is the grouping label, Hash k is the hash function with serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID i is the grouping label with serial number i, 1≤i≤I, I is an integer greater than 1;

[0061] Step S1702: Get the array corresponding to the grouping tag and determine whether the array satisfies the following judgment conditions: For any value of k, the equation ARRAY[HashKey k ] == Value_1, where ARRAY is the query array and Value_1 is the preset first value;

[0062] Step S1703: If the array does not satisfy the judgment condition, it is determined that the grouping tag is not found in the sensor database of the server.

[0063] In some embodiments of the present application, based on the aforementioned solution, the industrial Internet data storage method based on blockchain further includes:

[0064] Step S180: When no sensor data is stored in the edge server, the following assignment operation is performed for any value of m: ARRAY[m]=Value_2; wherein 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value.

[0065] Step S190: When there is sensor data in the edge server, extract the grouping label in the sensor data; perform hash operation on the grouping label using K independent hash functions according to the following formula: HashKeyExist k =Hash k (FZIDExist); where FZIDExist is the grouping label, HashKeyExist k is the hash value of the sequence number k obtained by the operation; for any value of k, the following assignment operation is performed: ARRAY[HashKeyExist k ]=Value_1.

[0066] In some embodiments of the present application, based on the aforementioned scheme, the industrial Internet data storage method based on blockchain also 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 a block header; each block includes a block header, block metadata and block data; wherein the block header includes the block number, the current block Hash and the previous block Hash; the block metadata includes the block creation time, the certificate, public key and signature of the write program; the block data includes abnormal sensor data. In this embodiment, the block data only includes abnormal sensor data, which further improves the efficiency of storage and the efficiency of finding abnormal sensor data.

[0067] Specifically, Figure 3 This is a schematic diagram of the sensor data format stored on the blockchain of the blockchain-based industrial Internet data storage method. Among them, three nodes are illustrated. The data format stored on each node on the blockchain is the same, and sensor data is stored. The format of sensor data on different blockchain platforms will be different, but basically all of them are composed of blocks. Sensor data. Specifically, the block header contains the block number, the current block Hash (the Hash of all sensors contained in the current block), and the Hash of the previous block; the block metadata includes the block creation time, the certificate, public key and signature of the write 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.

[0068] In some embodiments of the present application, based on the aforementioned scheme, the industrial Internet data storage method based on blockchain also 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 a block header; each block includes a block header, block metadata, and block data; wherein the block header includes a block number, a current block hash, and a previous block hash; the block metadata includes a block creation time, a certificate, a public key, and a signature of a write program; the block data includes abnormal sensor data and normal sensor data. The block data includes abnormal sensor data and normal sensor data, making the sensor data more comprehensive.

[0069] Specifically, Figure 4This is another schematic diagram of the sensor data format stored on the blockchain of the industrial Internet data storage method based on blockchain. Among them, three nodes are illustrated. The data format stored on each node on the blockchain is the same, and sensor data is stored. The format of sensor data on different blockchain platforms will be different, but basically all of them are composed of blocks. Sensor data. Specifically, the block header contains the block number, the current block Hash (the Hash of all sensors contained 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 write 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.

[0070] Please refer to Figure 5 As shown, the following introduces an embodiment of the industrial Internet data storage system based on blockchain of the present application, which can be used to execute the industrial Internet data storage method based on blockchain in the embodiment of the present application. It is understandable 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 embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the industrial Internet data storage method based on blockchain mentioned above in the present application.

[0071] Reference Figure 5 As shown, according to an embodiment of the present application, a blockchain-based industrial Internet data storage system 500 includes:

[0072] The acquisition module 510 is configured to acquire sensor data of industrial equipment, filter the sensor data, and obtain data to be processed.

[0073] The upload module 520 is configured to send the data to be processed to the edge server, group and associate them, and 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, and M is a positive integer.

[0074] The filtering module 530 is configured as an edge server receiving a trained adaptive neural network data filtering model on a blockchain node of a cloud server, and using the adaptive neural network data filtering model to filter the data to be uploaded to obtain data to be stored.

[0075] The storage module 540 is configured to forward the data to be stored to the blockchain node of the cloud server for associated storage based on the grouping label.

[0076] In some embodiments of the present application, based on the aforementioned scheme, the filtering module includes: a first determination unit, configured to determine a first group of sensors based on a 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 group of sensors based on the remaining load of the edge server, according to the workload and working energy consumption of the sensors; a third determination unit, configured to determine whether it is necessary to adjust the sensor group based on the first group and the second group; the first group adjustment unit, configured to adjust the sensor from the first group to the second group to obtain a third group if so; or adjust the sensor from the second group to the first group to obtain a fourth group; the second group adjustment unit, configured to further process the sensor data in each ID set in the third group if the third group is obtained; the third group adjustment unit, configured to further process the sensor data in each ID set in the fourth group if the fourth group is obtained.

[0077] In some embodiments of the present application, based on the aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a first determination module, configured to determine whether the query instruction is an abnormality confirmation instruction when receiving a 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 abnormal probability of the grouping label; a search module, configured to search for corresponding abnormal sensor data according to the grouping label of the sensor in the abnormal group.

[0078] In some embodiments of the present application, based on the above solution, the search module includes: a computing unit configured to perform a hash operation on the grouping tag 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 serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID i is a grouping tag with serial number i, 1≤i≤I, and I is an integer greater than 1; the judgment unit is configured to obtain the array corresponding to the grouping tag and judge whether the array satisfies the following judgment conditions: for any value of k, the equation ARRAY[HashKey k]==Value_1, wherein ARRAY is the query array and Value_1 is a preset first value; the determination unit is configured to determine that the grouping 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 aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a first assignment module, configured to perform the following assignment operation for any value of m when no sensor data is stored in the edge server: ARRAY[m]=Value_2; wherein 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value; an extraction module, configured to extract the grouping label in the sensor data when there is sensor data in the edge server; and an operation module, configured to perform a hash operation on the grouping label using K independent hash functions according to the following formula: HashKeyExist k =Hash k (FZID Exist); where FZID Exist is the grouping tag, HashKeyExist k is the hash value of the sequence number k obtained by the operation; the first assignment module is 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 aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a first creation module, which is 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 linked through a 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 previous block Hash; the block metadata includes the block creation time, the certificate, public key and signature of the write program; the block data includes the abnormal sensor data.

[0081] In some embodiments of the present application, based on the aforementioned scheme, the blockchain-based industrial Internet data storage system also includes: a second creation module, which is configured to create a corresponding block when abnormal sensor data is determined, and store the abnormal sensor data on the blockchain; the blockchain is linked through a 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 previous block Hash; the block metadata includes the block creation time, the certificate, public key and signature of the write program; the block data includes abnormal sensor data and normal sensor data.

[0082] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment 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 bring any limitation to the functions and scope of use of the embodiments of the present application.

[0084] like Figure 6 As 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 part 608 to the random access memory (RAM) 603, such as executing the method described in the above embodiment. 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 through a bus 606. An input / output (I / O) interface 605 is also connected to the bus 606.

[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 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. A drive 610 is also connected to the I / O interface 605 as needed. 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 needed so that a computer program read therefrom is installed into the storage section 608 as needed.

[0086] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which 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 a network through a communication section 609, and / or installed from a removable medium 611. When the computer program is executed by a 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 embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0088] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0089] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0090] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a 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-mentioned various optional implementations.

[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 embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0092] It should be noted that, although several modules or units of the equipment 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 two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0093] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be 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 (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0094] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. 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 knowledge or customary technical means in the art that are not disclosed in the present application.

[0095] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A blockchain-based industrial Internet data storage method, characterized in that: include: Obtain sensor data from industrial equipment, filter and process the sensor data to obtain data to be processed; Sending the data to be processed to the edge server, grouping and associating them, and obtaining data to be uploaded; 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 the 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; When receiving a query instruction, determining whether the query instruction is an abnormality confirmation instruction; If so, the probability of sensor grouping being abnormal is calculated according to a preset algorithm, and the abnormal grouping is determined according to the abnormal probability of the grouping label; Among them, 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, FzYcProb i is the distribution vector of the i-th group; FWf m is the preset weight vector corresponding to the mth sensor node, FqV i,m is the probability value of the abnormality of the i-th group including m sensor nodes; The corresponding abnormal sensor data is searched according to the grouping label of the abnormally grouped sensor.

2. The blockchain-based industrial Internet data storage method according to claim 1, wherein the step of searching for corresponding abnormal sensor data according to the grouping label of the abnormally grouped sensor comprises: K independent hash functions are used to perform hash operations on the group labels according to the following formula: HashKey k =Hash k (FZID i ); Among them, FZID i is the grouping label, Hash k is the hash function with serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID i is the grouping label with serial number i, 1≤i≤I, I is an integer greater than 1; Get the array corresponding to the grouping label and determine whether the array satisfies the following judgment conditions: For any value of k, the equation ARRAY[HashKey k ] == Value_1, where ARRAY is the query array and Value_1 is the preset first value; If the array does not satisfy the judgment condition, it is determined that the grouping tag is not found in the sensor database of the server.

3. The industrial Internet data storage method based on blockchain as claimed in claim 2 is characterized in that: Also includes: When no sensor data is stored in the edge server, the following assignment operation is performed for any value of m: ARRAY[m]=Value_2 Wherein, 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value; When sensor data exists in the edge server, extracting grouping tags in the sensor data; According to the following formula, K independent hash functions are used to perform hash operations on the group labels: HashKeyExist k =Hash k (FZIDExist); Among them, FZIDExist is the grouping label, HashKeyExist k is the hash value of the sequence number k obtained by the operation; For any value of k, the following assignment operation is performed: ARRAY[HashKeyExist k ]=Value_1。 4. An industrial Internet data storage system based on blockchain, characterized in that: include: An acquisition module is configured to acquire sensor data of industrial equipment, filter and process the sensor data, and obtain data to be processed; An upload module is configured to send the data to be processed to an edge server, group and associate the data, and obtain data to be uploaded; The filtering module is configured to receive the trained adaptive neural network data filtering model on the blockchain node of the cloud server at the edge server, and use the adaptive neural network data filtering model to filter the uploaded data to obtain the data to be stored; A storage module is configured to forward the data to be stored to a blockchain node of a cloud server for associated storage based on a grouping tag; A first determination module is configured to determine whether the query instruction is an abnormal confirmation instruction when receiving the query instruction; The second determination module is configured to calculate the probability of sensor grouping being abnormal according to a preset algorithm, and determine the abnormal grouping according to the abnormal 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, FzYcProb i is the distribution vector of the i-th group; FWf m is the preset weight vector corresponding to the mth sensor node, FqV i,m is the probability value of the abnormality of the i-th group including m sensor nodes; The search module is configured to search for corresponding abnormal sensor data according to the grouping labels of the abnormally grouped sensors.

5. The industrial Internet data storage system based on blockchain as claimed in claim 4, characterized in that: The search module includes: The operation unit is configured to use K independent hash functions to perform hash operations on the grouping labels according to the following formula: k =Hash k (FZID i ), where FZID i is the grouping label, Hash k is the hash function with serial number k, HashKey k is the hash value of the sequence number k obtained by the operation, 1≤k≤K, K is an integer greater than 1; FZID i is the grouping label with serial number i, 1≤i≤I, I is an integer greater than 1; The judgment unit is 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, where ARRAY is the query array and Value_1 is the preset first value; The determination unit is configured to determine that the grouping tag is not found in the sensor database of the server if the array does not meet the determination condition.

6. The industrial Internet data storage system based on blockchain as claimed in claim 5, characterized in that: The blockchain-based industrial Internet data storage system also includes: The first assignment module is configured to perform the following assignment operation for any value of m when no sensor data is stored in the edge server: ARRAY[m]=Value_2; wherein 1≤m≤M, M is the number of sensors in the array, and Value_2 is a preset second value; an extraction module, configured to extract grouping tags from the sensor data when the sensor data exists in the edge server; The operation module is configured to use K independent hash functions to perform hash operations on the grouping labels according to the following formula: k =Hash k (FZIDExist); where FZIDExist is the grouping label, HashKeyExist k is the hash value of the sequence number k obtained by the operation; the first assignment module is configured to perform the following assignment operation for any value of k: ARRAY[HashKeyExist k ]=Value_1.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the industrial Internet data storage method as described in any one of claims 1 to 3 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the industrial Internet data storage method as described in any one of claims 1 to 3.

Images