Production monitoring method, system and equipment, storage medium and product

Abstract

The invention discloses a production monitoring method, system and device, a storage medium and a product, and the method comprises the steps: receiving industrial production data of an industrial production side through an intelligent gateway, analyzing the operation state of an industrial production process according to the industrial production data, generating early warning information when the operation is abnormal, and achieving the supervision of production activities; in response to the data verification operation, the first data fingerprint generated by the intelligent gateway according to the industrial production data and stored in the block chain is extracted from the block chain, and the fingerprint algorithm is called to generate the second data fingerprint for the received industrial production data, so that the block chain ensures the authenticity of the first data fingerprint stored in the block chain; by comparing the second data fingerprint with the real and reliable first data fingerprint, the reliability of the second data fingerprint is verified, the authenticity of the industrial production data used for generating the second data fingerprint is further verified, it is ensured that data tampering can be found in time, and supervision of production activities is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of industrial application technology, and in particular to a production monitoring method, system, equipment, storage medium and product. Background Art

[0002] In industrial production activities, regulatory authorities need to obtain industrial production data to supervise production activities. In the prior art, a party engaged in production activities usually records industrial production data for a period of time and reports it to the regulatory authorities after data collation. In the process of supervision, data tampering is prone to occur, and the authenticity of industrial production data cannot be determined, which is not conducive to the supervision of production safety. Summary of the invention

[0003] Based on this, the present invention provides a production monitoring method, system, device, storage medium and product, which can analyze the received industrial production data through fingerprint information extracted from the blockchain to determine the authenticity of the data, which is conducive to the supervision of production safety.

[0004] To achieve the above object, an embodiment of the present invention provides a production monitoring method, comprising:

[0005] Receive industrial production data from the industrial production side through the intelligent gateway;

[0006] Analyzing the operating status of the industrial production process according to the industrial production data, and generating early warning information when the operating status is abnormal;

[0007] In response to the data verification operation, a first data fingerprint of the industrial production data is extracted from the blockchain, a fingerprint algorithm is called to generate a second data fingerprint for the industrial production data, and the first data fingerprint and the second data fingerprint are compared to determine the authenticity of the industrial production data; wherein the first data fingerprint is generated in advance by the intelligent gateway based on the industrial production data and stored in the blockchain.

[0008] As an improvement of the above solution, it also includes: based on preset display rules, displaying at least one of the industrial production data, the operating status of the industrial production process and the early warning information on a large monitoring screen.

[0009] As an improvement of the above scheme, it also includes:

[0010] Receive a signature verification result sent by the smart gateway; wherein the signature verification result is obtained by the second IoT device performing signature verification on data sent by the first IoT device, the data sent by the first IoT device carries signature information, the second IoT device serves as a data receiving end, the first IoT device serves as a data sending end, the first IoT device includes a device on the industrial production side, and the second IoT device includes the smart gateway and / or a device on the industrial production side;

[0011] Determine whether the firmware of the first IoT device has been tampered with according to the signature verification result;

[0012] The signature verification is performed on the industrial production data to determine whether the firmware of the intelligent gateway has been tampered with.

[0013] As an improvement of the above solution, the method is executed by a monitoring platform; the intelligent gateway is equipped with a data collection service, which includes a receiver, a converter and a collector; the industrial production data is obtained in the following manner:

[0014] The receiver passively receives the original production data sent from the industrial production side and sends it to the converter; the collector actively collects the original production data from the industrial production side and sends it to the converter; the converter converts the format of the original production data, obtains the industrial production data and forwards it to the monitoring platform.

[0015] As an improvement of the above solution, the industrial production data includes the identification of the monitored equipment, the value of the monitored parameter and the collection time; the primary key of the first data fingerprint and the first data fingerprint are sent by the intelligent gateway to the blockchain for storage, and the primary key of the first data fingerprint is the collection time of the industrial production data corresponding to the first data fingerprint;

[0016] In response to the data verification operation, extracting a first data fingerprint of the industrial production data from the blockchain, calling a fingerprint algorithm to generate a second data fingerprint for the industrial production data, and comparing the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data, including:

[0017] Determining an expected verification time period based on the data verification operation;

[0018] Calling a fingerprint algorithm to generate a second data fingerprint for the target industrial production data; wherein the target industrial production data is the industrial production data whose collection time falls within the expected verification time period;

[0019] The first data fingerprint corresponding to the expected verification time period is extracted from the blockchain and compared with the second data fingerprint to determine the authenticity of the target industrial production data.

[0020] As an improvement of the above solution, it also includes: classifying the industrial production data and storing industrial production data of different categories in different partitions.

[0021] To achieve the above object, an embodiment of the present invention further provides a production monitoring system, including:

[0022] An intelligent gateway is used to obtain industrial production data from the industrial production side, call a fingerprint algorithm to generate a first data fingerprint for the industrial production data, send the industrial production data to a monitoring platform, send the first data fingerprint to a blockchain for storage, and send industrial compressed data to the blockchain for storage; wherein the industrial compressed data is data obtained by compressing designated data in the industrial production data;

[0023] The monitoring platform is used to analyze the operating status of the industrial production process according to the industrial production data, and generate early warning information when the operating status is abnormal;

[0024] The monitoring platform is also used to respond to a data verification operation, call a fingerprint algorithm to generate a second data fingerprint for the industrial production data, extract the first data fingerprint from the blockchain, and compare the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data.

[0025] To achieve the above objectives, an embodiment of the present invention further provides a production monitoring device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the production monitoring method as described in any of the above embodiments is implemented.

[0026] To achieve the above objectives, an embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the production monitoring method described in any of the above embodiments.

[0027] To achieve the above objectives, an embodiment of the present invention further provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the production monitoring method as described in any of the above embodiments.

[0028] Compared with the prior art, the production monitoring method, system, device, storage medium and computer program product disclosed in the embodiments of the present invention receive industrial production data from the industrial production side through an intelligent gateway, analyze the operating status of the industrial production process according to the industrial production data, and generate early warning information when the operation is abnormal, so as to realize the supervision of production activities; in addition, in response to the data verification operation, a first data fingerprint generated by the intelligent gateway according to the industrial production data and stored in the blockchain is extracted from the blockchain, and a fingerprint algorithm is called to generate a second data fingerprint for the received industrial production data. The data of the blockchain cannot be tampered with, which ensures the authenticity of the first data fingerprint stored in the blockchain. The second data fingerprint is compared with the authentic and reliable first data fingerprint to verify the reliability of the second data fingerprint, and then the authenticity of the industrial production data used to generate the second data fingerprint is verified. When data tampering occurs, it can be discovered in time, which is conducive to effective supervision of production activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 It is a flow chart of a production monitoring method provided by one embodiment of the present invention;

[0031] Figure 2 is a functional architecture diagram of a production monitoring system provided by an embodiment of the present invention;

[0032] Figure 3 It is a hierarchical architecture diagram of a production monitoring system provided by an embodiment of the present invention;

[0033] Figure 4 is a data management flow chart provided by an embodiment of the present invention;

[0034] Figure 5 It is a structural diagram of a generation monitoring device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] See also Figure 1 , is a flow chart of a production monitoring method provided by an embodiment of the present invention. Specifically, the method is applied to a monitoring platform, and includes steps S11 to S13:

[0037] S11. Receive industrial production data from the industrial production side through the intelligent gateway.

[0038] S12. Analyze the operating status of the industrial production process according to the industrial production data, and generate warning information when the operating status is abnormal.

[0039] In one example, it is assumed that the industrial production data is the real-time vibration data of mechanical equipment, and the operating status of the industrial production process is the operating status of the mechanical equipment in the industrial production process. The analysis process of the operating status is as follows: extract signal features (such as dimensionless features, mutually dimensionless features, wavelet features or Hotelling statistics, etc.) from the real-time vibration data, and input the signal features into a pre-built time-frequency domain detector (such as a non-Gaussian early detector, a strong noise sparse detector or a sliding variable detector, etc.) to determine whether the mechanical equipment has a fault and the type of fault when a fault occurs. If the mechanical equipment fails, a warning message is generated to promptly remind the user to repair the mechanical equipment.

[0040] In another example, assuming that the industrial production data is pollutant emissions (such as sulfur dioxide emissions, carbon monoxide emissions, or nitrogen oxide emissions, etc.), the operating state of the industrial production process is a pollution state, and the pollution state analysis process is as follows: compare the pollutant emissions with the preset safe emissions; when the pollutant emissions are not greater than the safe emissions, the pollution state is normal; when the pollutant emissions are greater than the safe emissions, the pollution state is abnormal, and an early warning message is generated to prompt the user to promptly inspect and improve the industrial production process to reduce pollution.

[0041] S13. In response to the data verification operation, extract the first data fingerprint of the industrial production data from the blockchain, call the fingerprint algorithm to generate a second data fingerprint for the industrial production data, and compare the first data fingerprint and the second data fingerprint to determine the authenticity of the received industrial production data; wherein, the first data fingerprint is generated in advance by the intelligent gateway based on the industrial production data and stored in the blockchain.

[0042] Specifically, the monitoring platform is an important part of the production monitoring system, which mainly includes equipment on the industrial production side (such as sensors, various databases storing original industrial production data, etc.), intelligent gateways, monitoring platforms and blockchains. In the production monitoring system, the overall production monitoring mainly includes three steps: First, maintain basic data and real-time data. Basic data includes hazard source information, hardware equipment information, etc. Real-time data includes industrial production data collected in real time by sensors, etc. The data fingerprint of industrial production data is saved in the blockchain to ensure that the data source is credible. Second, use blockchain technology to transmit encrypted industrial production data to the cloud (monitoring platform) and provide real-time data analysis functions, such as real-time air pollution index measurement function. Third, users can extract data from the monitoring platform for secondary analysis, securely partition industrial production data, set alarm rules, and drag and drop the monitoring screen through low-code operations.

[0043] Specifically, the production monitoring system is described from different perspectives as follows:

[0044] 1. According to the function, we can get the following Figure 2The functional architecture diagram shown mainly includes the following functions: hazard source monitoring and early warning, safety risk zoning, data source management, real-time monitoring alarm and data storage management. 1. Regarding the hazard source monitoring and early warning function (this function can be configured on the monitoring platform): through pre-configured strategies, early warning of potential risks, such as the early warning when the operating status of the industrial production process is abnormal in step S12. 2. Regarding the safety risk zoning function (this function can be configured on the smart gateway and monitoring platform): (1) Use blockchain technology to transmit encrypted data to the cloud and provide real-time air pollution index measurement function. For example, in step S12, the industrial production data is real-time air pollution data, and the air pollution data is analyzed to determine the real-time air pollution index; (2) Extract the industrial production data of the monitoring platform for secondary analysis and partition the data securely. 3. Regarding the data source management function (this function can be configured on the industrial production side, smart gateway and monitoring platform): maintain basic data and real-time data. The basic data includes hazard source information, hardware equipment information, etc. The real-time data includes industrial production data collected in real time by sensors. The data fingerprint of the industrial production data is saved in the blockchain to ensure the credibility of the data source; 4. Regarding the real-time monitoring and alarm function (this function can be configured on the monitoring platform): by combining blockchain technology, the trusted authentication of the monitoring data is realized. When the data is tampered with, an alarm is generated in time, and the original data is traced back, such as step S13; 5. Regarding the data storage management function (this function can be configured on the smart gateway, monitoring platform and blockchain): use a time series database to efficiently save industrial production data (for example, the monitoring platform stores the received industrial production data), and combine blockchain technology to calculate and save fingerprints in the blockchain to realize data verification and trusted storage (for example, the smart gateway generates a first data fingerprint for the industrial production data and stores it in the blockchain).

[0045] 2. See Figure 3As shown, in the layered architecture of the production monitoring system, there are a data access layer, a data storage layer, a microservice layer, a service access layer and a presentation layer. 1. About the data access layer: The data access layer is deployed at the intelligent gateway. The data access layer can receive various types of data on the industrial production side. For example, in step S11, the intelligent gateway receives various types of industrial production data on the industrial production side as a data access layer, such as a message queue based on a lightweight message transmission protocol (Message Queuing Telemetry Transport, MQTT), a file in xls / xlsx format, or data based on various industrial protocols (such as Modbus data, OPC-UA data and Profibus data, etc.), etc., wherein Modbus is a serial communication protocol that uses ASCII or binary format for data transmission and is a commonly used connection method between industrial electronic devices; OPC-UA (OPC Unified Architecture) is an open international standard specification developed for safe and reliable data exchange in industries such as industrial automation; Profibus (Process Fieldbus) is an international, open, and independent fieldbus standard for equipment manufacturers. 2. About the data storage layer. Deploy a relational database MySQL on the industrial production side to store industrial production data. Exemplarily, in step S11, the intelligent gateway can extract industrial production data from the relational database MySQL and then upload it to the monitoring platform. The time series database InfluxDB is deployed on the monitoring platform to efficiently store the industrial production data obtained from the intelligent gateway in step S11. The data storage layer also includes a blockchain distributed storage module for storing the first data fingerprint of the industrial production data mentioned in step S13, and can also be used to store the industrial compressed data mentioned in step S14. 3. Regarding the microservice layer, it includes basic components and core components, which can be deployed on the monitoring platform. The basic components include the scaffolding Spring Boot and the microservice framework Spring Cloud, where the scaffolding is a development tool and development framework that helps developers use during the development process. When using the scaffolding, there is no need to build or write the underlying software from scratch. On the basis of the scaffolding, powerful applications can be built more efficiently; Spring Cloud is an ordered collection of a series of frameworks, which cleverly uses the development convenience of Spring Boot to simplify the development of distributed system infrastructure, allowing developers to focus more on the implementation of business logic without spending too much energy on underlying technologies. The core components include the registration center nacos, service call Feign, service fuse sentinel, load balancing Ribbon, data access mybatis-plus and distributed transaction seata.4. Regarding the service access layer, it includes the gateway Spring Gateway, Web communication WebSocket and the authentication and authorization user center (RBAC). For example, in step S11, the intelligent gateway acts as a Spring Gateway to send the industrial production data of the industrial production side to the monitoring platform; the client accesses the monitoring platform through WebSocket, and the warning information in step S12 can be transmitted to the client using WebSocket to remind the user of data abnormalities; the authentication and authorization user center provides an authentication service, and the user can perform authorization verification through the authentication and authorization user center. After the verification is passed, the user can access the relevant data. 5. The presentation layer uses HT's image engine, and the routing control Vue-router.js, the front-end component library Element-UI, the front-end framework vue.js, the HS Canvas component, the HT 2D Editor and the HT 3D Editor components are deployed in the presentation layer. It supports two-dimensional (Two-Dimensional, 2D) images and three-dimensional (Three-dimensional, 3D) images, and can flexibly adapt to multiple clients such as Web, mobile phones, and tablets. The back-end adopts a microservice architecture, and the components can be flexibly plugged in and replaced. The layered architecture of the production monitoring system has the following advantages: support for multi-tenant mode, support for local deployment, support for encrypted publishing, and provides a wealth of interfaces for users to integrate into their own platforms or websites.

[0046] It is worth noting that the functional architecture and layered architecture of the production monitoring system are not limited to the above specific examples and can be deployed according to the circumstances.

[0047] For example, see Figure 4As shown in the data management flow chart, the specific monitoring process of the production monitoring system is as follows: 1. The intelligent gateway obtains industrial production data from industrial equipment or databases on the industrial production side (i.e., industrial site), where industrial equipment includes CNC machine tools, visual equipment, various sensors, power equipment, intelligent instruments and control systems, etc. 2. The intelligent gateway (such as the industrial data acquisition gateway) generates a first data fingerprint based on the acquired industrial production data, stores the first data fingerprint in the blockchain (for example, in chronological order, for data within a certain time period (the time period is configurable), calculates the first data fingerprint through the SHA256 algorithm, and writes the first data fingerprint into the Fabric alliance chain for later data verification), and reports the industrial production data to the monitoring platform. 3. Based on cloud computing technology, the monitoring platform uses a data engine to receive the industrial production data sent by the intelligent gateway, compresses all the received industrial production data and stores them in the blockchain, analyzes the industrial production data, determines the operating status of the industrial production process, and generates warning information if the operation is abnormal. When the user needs to trace the data, a data verification operation is initiated. The monitoring platform responds to the data verification operation and uses the verification engine based on cloud computing technology to extract the first data fingerprint of the industrial production data that needs to be verified from the blockchain as the middle platform, as well as the compressed industrial production data stored in the blockchain by the monitoring platform, decompress the compressed industrial production data and generate a second data fingerprint. The two data fingerprints are compared. If the fingerprints are consistent, it means that the industrial production data sent to the monitoring platform has not been tampered with. If the fingerprints are inconsistent, it means that the industrial production data in the monitoring platform has been tampered with. The data verification results (fingerprint comparison results) are fed back to the monitoring screen for the supervisor to view. It is understandable that the industrial production data of the monitoring platform can also be stored in other storage areas besides the blockchain, which is not limited here.

[0048] In this embodiment, blockchain can effectively eliminate fraud, falsification and other behaviors in environmental pollution control due to its characteristics of open and transparent data, wide distribution, and non-tamperability and non-forgery. Compared with the existing technology, this embodiment can analyze the received industrial production data through the fingerprint information extracted from the blockchain to determine the authenticity of the data, which is conducive to the supervision of production safety.

[0049] Furthermore, the method further includes: when the first data fingerprint and the second data fingerprint are inconsistent, extracting industrial compressed data corresponding to the first data fingerprint from the blockchain; wherein the industrial compressed data is pre-compressed by the intelligent gateway for designated data in the industrial production data and stored in the blockchain. When the first data fingerprint and the second data fingerprint are inconsistent, extracting the industrial compressed data corresponding to the first data fingerprint from the blockchain to obtain real data, so that the regulatory authorities can effectively supervise production activities.

[0050] It is worth noting that the intelligent gateway can compress all industrial production data and store them in the blockchain. Preferably, based on the set rules, some industrial production data are selected for compression and stored in the blockchain. For example, industrial production data can be sampled regularly, and some industrial production data can be compressed to obtain industrial compressed data and store them in the blockchain, or different levels of industrial production data can be set, and higher-level data can be compressed and stored in the blockchain.

[0051] In one embodiment, the method further includes: based on a preset display rule, displaying at least one of the industrial production data, the operating status of the industrial production process and the early warning information on a large monitoring screen.

[0052] For example, see Figure 4 , supervisors can set display rules according to their needs. Based on the preset display rules, the monitoring platform uses cloud computing technology and data engines to drag and drop the industrial production data, operating status of the industrial production process or early warning information that need to be displayed to the monitoring screen through low-code drag and drop. Among them, the generation of the monitoring screen uses HTML5. HTML5 is a new generation of Internet standards and a language for building and presenting Internet content. The monitoring screen is developed based on standard HTML5, does not rely on any plug-ins, can be edited online, supports 2D vector graphics based on Canvas, and supports 3D models based on the 3D drawing standard WebGL. In addition, the construction of the industrial 2D / 3D data visualization application interface can be easily completed through low-code drag and drop, without programming.

[0053] In one embodiment, it further includes:

[0054] Receive a signature verification result sent by the smart gateway; wherein the signature verification result is obtained by the second IoT device performing signature verification on data sent by the first IoT device, the data sent by the first IoT device carries signature information, the second IoT device serves as a data receiving end, the first IoT device serves as a data sending end, the first IoT device includes a device on the industrial production side, and the second IoT device includes the smart gateway and / or a device on the industrial production side;

[0055] Determine whether the firmware of the first IoT device has been tampered with according to the signature verification result;

[0056] The signature verification is performed on the industrial production data to determine whether the firmware of the intelligent gateway has been tampered with.

[0057] Specifically, the following briefly introduces the signature and verification principles of IoT devices: (1) IoT device message signature mechanism: Through the use of Merkle Tree, the registration of IoT devices can be completed without exposing the private properties of the device, and the public key (or its derivative representation) is used as the identification ID of the IoT device. (2) IoT device message signature and verification: Each message in the system needs to be signed by the sending IoT device. At the receiving IoT device, the message is verified using the saved firmware hash value of the sending IoT device to verify whether the firmware running on the sending IoT device has been illegally tampered with. Furthermore, based on the trust principle of the Web, each IoT device can form a trust network. The more signatures an IoT device obtains from other reputable IoT devices, the more trustworthy the device is.

[0058] Specifically, in the production monitoring system, each IoT device is equipped with signature and signature verification functions, and the IoT devices include various devices on the industrial production side, smart gateways, and monitoring platforms. For example, the sensor collects industrial production data and signs it, and then sends it to the smart gateway. After receiving the industrial production data, the smart gateway performs signature verification. If the verification passes, it means that the firmware of the sensor has not been tampered with. If the verification fails, it means that the firmware of the sensor has been tampered with. The smart gateway signs the acquired industrial production data and uploads it to the monitoring platform. After receiving the industrial production data, the monitoring platform performs signature verification. If the verification passes, it means that the firmware of the smart gateway has not been tampered with. If the verification fails, it means that the firmware of the smart gateway has been tampered with.

[0059] In one embodiment, the method is performed by a monitoring platform; the intelligent gateway is equipped with a data collection service, and the data collection service includes a receiver, a converter, and a collector; the industrial production data of the monitoring platform is obtained in the following manner:

[0060] The receiver passively receives the original production data sent from the industrial production side and sends it to the converter; the collector actively collects the original production data from the industrial production side and sends it to the converter; the converter converts the format of the original production data, obtains the industrial production data and forwards it to the monitoring platform.

[0061] Specifically, sensors on the industrial production side collect raw production data in real time, and use 5G wireless networks to realize data transmission between the industrial production side and the smart gateway. Among them, the smart gateway deploys the industrial production data transmission method between the industrial production side and the smart gateway as a data acquisition service TransportServer. TransportServer is the server end of the RPC framework, which can provide efficient, low-level streaming services. The data acquisition service supports mainstream device data transmission protocols MQTT, Modbus, OPC, Hypertext Transfer Protocol (HTTP), and Constrained Application Protocol (CoAP). This service is used to integrate external device data (such as data collected by sensors on the industrial production side), smart gateways, and third-party systems (such as databases on the industrial production side) to perform data collection. The smart gateway implements a centralized procurement service for each protocol design. TransportServer includes data collection capabilities, command issuance capabilities, and data format conversion capabilities, and mainly includes the following three components:

[0062] 1. Receiver connector. The receiver is used to receive the original production data actively sent by the industrial production side. It provides connections and responses for multiple protocols, and performs device authority authentication according to planning requirements. Receivers may include but are not limited to MQTT receivers, HTTP receivers, COAP receivers, Modbus receivers, and Open Database Connectivity (ODBC) receivers. The MQTT receiver interacts with the industrial production side in a publish / subscribe mode, the HTTP receiver interacts with the industrial production side in a request / response mode, the COAP receiver interacts with the industrial production side in a request / response mode or an observer interaction mode, and the ODBC receiver interacts with the industrial production side in a shared database mode.

[0063] 2. Converter. The intelligent gateway is pre-set with standardized data bodies. When the intelligent gateway receives the original production data, it uses the converter to convert the original production data so that the original production data is converted into industrial production data that conforms to the set standard data format. The converted data contains standard parameter codes and equipment data attribute labels.

[0064] 3. Collector. For old sensors or third-party systems that do not actively request / push centralized procurement services but have responsiveness, a collection mode is provided. The collector polls the connected sensor or third-party system interface to actively obtain the original production data on the industrial production side.

[0065] It is understandable that the smart gateway supports real-time data and historical data access. The real-time data access method supports HTTP Post, Nats and MQTT, etc. This access method has high real-time performance and requires less bandwidth and traffic. If the accessed data is MQTT data, the MQTT Broker needs to be directly set up on the smart gateway and the access device. The MQTT Broker is responsible for receiving messages published by the access device, filtering the messages according to the topic, and then distributing them to the MQTT receiver. Historical data access supports commonly used relational databases such as MySQL, SQLServer and PostgresQL, and also supports Influxdb database and TDegnine time series database. When there are devices (such as sensors or databases) on the industrial production side that need to be connected to the smart gateway, it is necessary to configure the attributes of the access device at the smart gateway and configure the conversion rules at the converter for converting the access data. If the collector is required to collect data from the access device, it is necessary to configure the collection strategy on the collector, such as the IP address, port and collection frequency of the access device.

[0066] Compared with the prior art, the intelligent gateway of the embodiment of the present invention supports various types of equipment and various types of data access, can perform more comprehensive data collection on the industrial production side, and effectively monitor industrial production activities.

[0067] In one embodiment, the industrial production data includes the identification of the monitored equipment, the value of the monitored parameter and the collection time; the primary key of the first data fingerprint and the first data fingerprint are sent by the intelligent gateway to the blockchain for storage, and the primary key of the first data fingerprint is the collection time of the industrial production data corresponding to the first data fingerprint;

[0068] In response to the data verification operation, extracting a first data fingerprint of the industrial production data from the blockchain, calling a fingerprint algorithm to generate a second data fingerprint for the industrial production data, and comparing the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data, including:

[0069] Determining an expected verification time period based on the data verification operation;

[0070] Calling a fingerprint algorithm to generate a second data fingerprint for the target industrial production data; wherein the target industrial production data is the industrial production data whose collection time falls within the expected verification time period;

[0071] The first data fingerprint corresponding to the expected verification time period is extracted from the blockchain and compared with the second data fingerprint to determine the authenticity of the target industrial production data.

[0072] For example, assuming that the identifier of the monitored device is the device ID, and the monitored parameter value is the value of the attribute, the intelligent gateway collects raw data, such as temperature, pressure, etc., from the monitored device on the industrial production side, and records the collection time, as shown in the following table:

[0073] Table 1 Data collection sample

[0074] Device ID property Collection time Value 1234-13121-123 temperature 2024-08-05T12:21:13 52 1234-13121-123 temperature 2024-08-05T12:21:15 51 1234-13121-123 pressure 2024-08-05T12:21:13 800

[0075] Then the first data fingerprint is calculated for the collected data and saved in the blockchain. The specific method is as follows:

[0076] The data in the table is saved in the form of a list of key-value pairs, as follows:

[0077] [{"id":"1234-13121-123","property":"temperature","time":"2024-08-05T12:21:13","value":"52"},{"id":"1234-13121-123","property":"temperatu re","time":"2024-08-05T12:21:15","value":"51"},{"id":1234-13121-123","property":"pressure","time":"2024-08-05T12:21:13","value":"800"}].

[0078] Calculate SHA256 for the entire key-value pair list to obtain the first data fingerprint of this batch of data.

[0079] Then the collection time is rounded to 1 minute (which can be adjusted according to actual needs) as the primary key, such as "2024-08-05T12:21", and the first data fingerprint is used as the value and saved in the blockchain.

[0080] When a problem needs to be traced, the first data fingerprint of the corresponding period is taken out from the blockchain according to the expected tracing time period (i.e. the expected verification time period). The fingerprint of the industrial production data sent to the monitoring platform during this period (i.e. the second data fingerprint) is compared with the first data fingerprint to see if they are consistent. This can determine whether the data is untampered data.

[0081] In one embodiment, it further includes:

[0082] The industrial production data is classified, and industrial production data of different categories are stored in different partitions.

[0083] Specifically, in order to facilitate data management, the monitoring platform needs to analyze the industrial production data and allocate it to different partitions for storage. After reasonable partitioning, the efficiency of data retrieval can be improved, making it easier for the monitoring platform to extract and store industrial production data.

[0084] An embodiment of the present invention further provides a production monitoring system, comprising:

[0085] An intelligent gateway is used to obtain industrial production data from the industrial production side, call a fingerprint algorithm to generate a first data fingerprint for the industrial production data, send the industrial production data to a monitoring platform, send the first data fingerprint to a blockchain for storage, and send industrial compressed data to the blockchain for storage; wherein the industrial compressed data is data obtained by compressing designated data in the industrial production data;

[0086] The monitoring platform is used to analyze the operating status of the industrial production process according to the industrial production data, and generate early warning information when the operating status is abnormal;

[0087] The monitoring platform is also used to respond to a data verification operation, call a fingerprint algorithm to generate a second data fingerprint for the industrial production data, extract the first data fingerprint from the blockchain, and compare the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data.

[0088] In one embodiment, the monitoring platform is further used to: based on preset display rules, display at least one of the industrial production data, the operating status of the industrial production process and the early warning information on a large monitoring screen.

[0089] In one embodiment, the IoT device in the production monitoring system signs the data sent by itself and verifies the signature of the received data to determine whether the firmware of the IoT device sending the data has been tampered with; wherein the IoT device includes at least one of the smart gateway and the equipment on the industrial production side.

[0090] In one embodiment, the intelligent gateway is equipped with a data collection service, which includes a receiver, a converter, and a collector; the intelligent gateway is used to obtain industrial production data from the industrial production side, specifically including:

[0091] The receiver is used to passively receive the original production data sent from the industrial production side and send it to the converter;

[0092] The collector is used to actively collect the original production data from the industrial production side and send it to the converter;

[0093] The converter is used to convert the format of the original production data to obtain industrial production data.

[0094] In one embodiment, the industrial production data includes an identifier of a monitored device, a value of a monitored parameter, and a collection time; the intelligent gateway is further configured to use the collection time of the industrial production data corresponding to the first data fingerprint as a primary key of the first data fingerprint, so as to send the primary key of the first data fingerprint and the first data fingerprint to the blockchain for storage;

[0095] The monitoring platform specifically determines the authenticity of the industrial production data in the monitoring platform in the following manner:

[0096] Determining an expected verification time period based on the data verification operation;

[0097] Calling a fingerprint algorithm to generate a second data fingerprint for the target industrial production data in the monitoring platform; wherein the target industrial production data is the industrial production data whose collection time falls within the expected verification time period;

[0098] The first data fingerprint corresponding to the expected verification time period is extracted from the blockchain and compared with the second data fingerprint to determine the authenticity of the target industrial production data.

[0099] In one embodiment, the monitoring platform is also used to classify the industrial production data and store different categories of industrial production data in different partitions.

[0100] It is worth noting that the specific working process of the production monitoring system can refer to the working process of the production monitoring method in the above embodiment, which will not be repeated here.

[0101] Compared with the prior art, the production monitoring system disclosed in the embodiment of the present invention receives industrial production data from the industrial production side through an intelligent gateway, analyzes the operating status of the industrial production process based on the industrial production data, and generates early warning information when the operation is abnormal, thereby realizing the supervision of production activities; in addition, in response to the data verification operation, a first data fingerprint generated by the intelligent gateway based on the industrial production data and stored in the blockchain is extracted from the blockchain, and a fingerprint algorithm is called to generate a second data fingerprint for the received industrial production data. The data of the blockchain cannot be tampered with, which ensures the authenticity of the first data fingerprint stored in the blockchain. The second data fingerprint is compared with the authentic and reliable first data fingerprint to verify the reliability of the second data fingerprint, and then the authenticity of the industrial production data used to generate the second data fingerprint is verified, ensuring that data tampering can be discovered in time, which is conducive to effective supervision of production activities.

[0102] See also Figure 5 , Figure 5 is a schematic diagram of a structure of a generation monitoring device provided in an embodiment of the present invention. The generation monitoring device 20 includes a processor 21, a memory 22, and a computer program stored in the memory 22 and configured to be executed by the processor 21. When the processor 21 executes the computer program, the steps in the above-mentioned inventory method embodiment are implemented, for example Figure 1 Steps S11 to S13 described in .

[0103] Exemplarily, the computer program can be divided into one or more modules, and the one or more modules are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the production monitoring device. For example, the computer program can be divided into multiple modules. The specific working process of each module can refer to the working process of the production monitoring method described in the above embodiment, which will not be repeated here.

[0104] The generation monitoring device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The generation monitoring device may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will appreciate that the generation monitoring device may also include an input and output device, a network access device, a bus, etc.

[0105] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 21 is the control center of the generation monitoring device, and uses various interfaces and lines to connect various parts of the entire generation monitoring device.

[0106] The memory 22 can be used to store the computer program and / or module, and the processor 21 realizes various functions of the generation monitoring device by running or executing the computer program and / or module stored in the memory 22, and calling the data stored in the memory 22. The memory 22 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory 22 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0107] Wherein, if the module for generating the integrated monitoring device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor 21. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0108] An embodiment of the present invention further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the production monitoring method described in any of the above embodiments, such as steps S11 to S13.

[0109] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A production monitoring method, characterized in that: include: Receive industrial production data from the industrial production side through the intelligent gateway; Analyzing the operating status of the industrial production process according to the industrial production data, and generating early warning information when the operating status is abnormal; In response to the data verification operation, a first data fingerprint of the industrial production data is extracted from the blockchain, a fingerprint algorithm is called to generate a second data fingerprint for the industrial production data, and the first data fingerprint and the second data fingerprint are compared to determine the authenticity of the industrial production data; wherein the first data fingerprint is generated in advance by the intelligent gateway based on the industrial production data and stored in the blockchain.

2. The production monitoring method according to claim 1, characterized in that: Also includes: Based on preset display rules, at least one of the industrial production data, the operating status of the industrial production process and the early warning information is displayed on a large monitoring screen.

3. The production monitoring method according to claim 1, characterized in that: Also includes: Receive a signature verification result sent by the smart gateway; wherein the signature verification result is obtained by the second IoT device performing signature verification on data sent by the first IoT device, the data sent by the first IoT device carries signature information, the second IoT device serves as a data receiving end, the first IoT device serves as a data sending end, the first IoT device includes a device on the industrial production side, and the second IoT device includes the smart gateway and / or a device on the industrial production side; Determine whether the firmware of the first IoT device has been tampered with according to the signature verification result; The signature verification is performed on the industrial production data to determine whether the firmware of the intelligent gateway has been tampered with.

4. The production monitoring method according to claim 1, characterized in that: The method is executed by a monitoring platform; the intelligent gateway is equipped with a data collection service, which includes a receiver, a converter and a collector; the industrial production data is obtained in the following manner: The receiver passively receives the original production data sent from the industrial production side and sends it to the converter; the collector actively collects the original production data from the industrial production side and sends it to the converter; the converter converts the format of the original production data, obtains the industrial production data and forwards it to the monitoring platform.

5. The production monitoring method according to claim 1, characterized in that: The industrial production data includes the identification of the monitored equipment, the value of the monitored parameter and the collection time; the primary key of the first data fingerprint and the first data fingerprint are sent by the intelligent gateway to the blockchain for storage, and the primary key of the first data fingerprint is the collection time of the industrial production data corresponding to the first data fingerprint; In response to the data verification operation, extracting a first data fingerprint of the industrial production data from the blockchain, calling a fingerprint algorithm to generate a second data fingerprint for the industrial production data, and comparing the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data, including: Determining an expected verification time period based on the data verification operation; Calling a fingerprint algorithm to generate a second data fingerprint for the target industrial production data; wherein the target industrial production data is the industrial production data whose collection time falls within the expected verification time period; The first data fingerprint corresponding to the expected verification time period is extracted from the blockchain and compared with the second data fingerprint to determine the authenticity of the target industrial production data.

6. The production monitoring method according to claim 1, characterized in that: Also includes: The industrial production data is classified, and industrial production data of different categories are stored in different partitions.

7. A production monitoring system, characterized in that: include: An intelligent gateway is used to obtain industrial production data from the industrial production side, call a fingerprint algorithm to generate a first data fingerprint for the industrial production data, send the industrial production data to a monitoring platform, send the first data fingerprint to a blockchain for storage, and send industrial compressed data to the blockchain for storage; wherein the industrial compressed data is data obtained by compressing designated data in the industrial production data; The monitoring platform is used to analyze the operating status of the industrial production process according to the industrial production data, and generate early warning information when the operating status is abnormal; The monitoring platform is also used to respond to a data verification operation, call a fingerprint algorithm to generate a second data fingerprint for the industrial production data, extract the first data fingerprint from the blockchain, and compare the first data fingerprint with the second data fingerprint to determine the authenticity of the industrial production data.

8. A production monitoring device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the production monitoring method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the production monitoring method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the production monitoring method according to any one of claims 1 to 6 is implemented.

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