CN113810489A

CN113810489A - Industrial internet control system and method

Info

Publication number: CN113810489A
Application number: CN202111078177.XA
Authority: CN
Inventors: 杨国宇; 李铭锋
Original assignee: Guangdong Sanshui Institute Of Hefei University Of Technology
Current assignee: Guangdong Sanshui Institute Of Hefei University Of Technology
Priority date: 2021-09-14
Filing date: 2021-09-14
Publication date: 2021-12-17

Abstract

The invention relates to an industrial internet control system and a method, which at least comprise a perception identification module (1) used for collecting data in an industrial production field, wherein under the condition that the perception identification module (1) transmits collected industrial internet data to a data transmission module (2), the data transmission module (2) carries out message queue authority authentication and compresses related industrial internet data in a differential mode, and transmits the compressed industrial internet data to a data platform (3) in a byte stream mode, wherein the data transmission module (2) at least comprises a data compression unit (21) and a message queue management unit (22), and the data compression unit (21) can compress the collected industrial internet data in a segmented mode in a periodic segmentation mode; the message queue management unit (22) carries out data returning and management in a mode of normative theme and device authority management.

Description

Industrial internet control system and method

Technical Field

The invention relates to the technical field of industrial internet, in particular to an industrial internet control system and method.

Background

The industrial internet is used as a key infrastructure for linking a whole industrial system, a whole industrial chain and a whole value chain and supporting industrial intelligent development, is a new business state and an application mode formed by deep fusion of a new generation of information technology and manufacturing industry, and is a core carrier for expanding the internet from the consumption field to the production field and from virtual economy to entity economy. The industrial internet is a product of deep integration of a new generation of information communication technology and modern industrial technology, is an important carrier for digitalization, networking and intellectualization of manufacturing industry, and is a high point of a new round of industry competition all over the world. The digital production management and control system based on the industrial internet is used as a new-generation industrial internet system, gradually embodies the function of the system in the transformation and upgrading of manufacturing enterprises, and provides important reference value for the informatization process of a digital workshop. The traditional production management and control system is difficult to manage equipment in a whole manner, is developed for certain products in a specific field, and is large in system redundancy, high in coupling and low in cohesion, and an extensible mode is lacked in functions. In terms of external connection, an interface for linking systems of each stage is lacking. This may result in difficulty in achieving the intended target.

According to the display of the 'report on the industrial internet security situation in the first half of 2020', the security monitoring results of the industrial internet platform, the industrial enterprise and the internet equipment are displayed from 1 month and 1 day of 2020 to 6 months and 30 days of 2020, and the malicious network behaviors are accumulatively monitored and found for 1356.3 ten thousands of times, which relates to 2039 family enterprises. The attack mode mainly comprises three types of abnormal flow, illegal external connection and botnet, which are more than 300 ten thousand times, and the total number of the abnormal flow, the illegal external connection and the botnet accounts for 81 percent of the total number of the malicious behaviors. The abnormal flow contains a large amount of scanning and sniffing behaviors, which shows that most of the current network attacks aiming at the industrial internet are information collection before the attacks, and the potential safety hazard cannot be ignored.

The existing management and control system does not reasonably optimize data in the aspect of data transmission, and the huge data volume causes the problems of too high bandwidth cost, low transmission efficiency and the like. In the aspect of data management, a data processing platform for dynamic analysis and universality of heterogeneous data is lacked. At the application service layer, an efficient device reverse control mechanism is lacking.

Chinese patent CN109491301A discloses an industrial inter-networking intelligent controller based on an edge computing system architecture, wherein a logic control device is respectively connected with a data acquisition device, a data analysis device and an internet transmission device; the data acquisition device acquires equipment data at the edge side; the data analysis device calculates and analyzes the equipment data at the edge side to obtain an analysis result; the internet transmission device is used for uploading the analysis result and transmitting the control information to the logic control device. Data acquisition and analysis are placed on the edge side close to a data source, so that operation is dispersed on the edge side, the problem that the transmission rate of a data path between industrial equipment and a cloud end is limited is solved, particularly, the phenomena of network blockage, slow processing beat, low efficiency and the like caused by poor data throughput of the traditional PLC are solved, and perfect integration of edge calculation and cloud calculation is realized by matching with an internet transmission device. However, the patent does not effectively authenticate data, and cannot guarantee whether the access device is safe or not.

Therefore, the problems that the data transmission aspect of the industrial internet control system is not reasonably optimized, the bandwidth cost is too high due to huge data volume, the transmission efficiency is low and the like are solved; in the aspect of data management, a data processing platform for dynamic analysis and general use of heterogeneous data is lacked; at an application service layer, an efficient device reverse control mechanism is lacked; the control system is frequently attacked abnormally, and the problem of safety implication exists.

Furthermore, on the one hand, due to the differences in understanding to the person skilled in the art; on the other hand, since the inventor of the present invention has studied a lot of documents and patents when making the present invention, but the space is not limited to the details and contents listed in the detailed description, however, the present invention is by no means characterized in these prior art, but the present invention has been provided with all the features of the prior art, and the applicant reserves the right to increase the related prior art in the background art.

Disclosure of Invention

Aiming at the defects of the prior art, the technical scheme provided by the invention is that the industrial internet control system at least comprises a perception identification module used for acquiring data in an industrial production field, and under the condition that the perception identification module transmits the acquired industrial internet data to a data transmission module, the data transmission module performs message queue authority authentication, compresses the associated industrial internet data in a differential mode, and transmits the compressed industrial internet data to a data platform in a byte stream mode, wherein the data transmission module at least comprises a data compression unit and a message queue management unit, and the data compression unit can perform segmented compression on the acquired industrial internet data in a periodic segmentation mode; and the message queue management unit carries out data return and management in a mode of standard theme and equipment authority management. The method has the advantages that the efficient compression algorithm and the equipment authentication module are arranged, so that the safety of system access is guaranteed, and meanwhile, the data transmission efficiency is improved. In addition, based on the characteristics of cloud computing, a dynamic and extensible data processing service is designed for heterogeneous industrial data, so that a user can acquire needed data more accurately, quickly and effectively, can learn about abnormal conditions in time and can perform remote control, a reverse control module of the equipment improves reverse control efficiency, and an interface display and a user interaction interface design are performed on a data processing result. The redundancy problem of data transmission, the dynamic analysis problem of heterogeneous data and the efficient reverse control problem of equipment are solved, and the reliability and the stability of the functions of the whole system are improved.

According to a preferred embodiment, the data transmission module selectively accesses the sensing identification module to an industrial internet system in a wired or wireless manner and transmits the collected related data to the data platform, and the data transmission module completes compression and transmission of industrial internet data in a manner of standardizing management rules of data transmission.

According to a preferred embodiment, the data compression unit performs compression of the cycle data in such a way that the data collected by the individual perception data modules within a set cycle time are aggregated, wherein the data compression unit performs data feature extraction in the form of bytes of differential data. The method has the advantages that the industrial internet data needing to be transmitted are compressed in advance, so that the bandwidth resource occupation and the network cost of the industrial internet data are reduced during transmission. In addition, the data compression unit accurately and effectively extracts the change characteristics in a differential mode, so that iterative processing and IO processing occupying time do not exist in compression operation, a third-party calculation library is not needed, the calculation time is very fast, the data can be uploaded in time, and the delay is low.

According to a preferred embodiment, the message queue management unit completes the distribution operation of the industrial internet data by introducing a theme mode, and tracks the source of the data and the working state of the corresponding perception identification module by establishing a normalized main body mode.

According to a preferred embodiment, the device authority management of the message queue management unit is to perform authority management on the perceptual identification module in a manner that the perceptual identification module is defined to perform data transmission according to a specification, so as to screen out a terminal device with a wrong configuration and/or a terminal device with illegal access.

According to a preferred embodiment, the data platform temporarily stores the received data in a data aggregation manner, and a trigger condition for data storage is preset, so that when the temporarily stored data reaches the preset trigger condition, the data platform writes the temporarily stored data in the memory into the database at one time. The method has the advantages that after data aggregation, the connection times of the database are greatly reduced, and the data storage efficiency is improved.

According to a preferred embodiment, the data platform can also transmit the classified and stored data to a data analysis module, and the data analysis module can carry out deep analysis and optimization on the data; the data analysis module can perform dynamic and configurable analysis on the continuously growing and changing heterogeneous industrial sensing data and provide a data alarm service with a low error rate. The advantage is that the coupling between the services is low, which embodies the advantages of the micro-service architecture.

According to a preferred embodiment, the control system further comprises an application service module, and the application service module is connected with the data platform through a preset interactive interface, so that a terminal user can acquire, upload and control the system through the application service module.

The application also provides an industrial internet control method, which comprises the following steps:

s1: the sensing identification module is used for acquiring data and transmitting the acquired industrial Internet data to the data transmission module;

s2: the data transmission module receives the data, issues the data to a message queue server, and performs message queue authority authentication;

s3: the background of the data transmission module subscribes to a corresponding theme, and data compression is performed after the data are acquired and the compressed data are uploaded to a data platform;

s4: the data platform receives the data uploaded by the data transmission module and completes storage and management of the data;

s5: the data analysis module analyzes and alarms and judges the data stored by the data platform;

s6: the application service module presents a data visualization chart to a user through a system page, and the user can issue a control instruction to the equipment through the application service module to realize reverse control.

According to a preferred embodiment, the data transmission module at least comprises a data compression unit and a message queue management unit, wherein the data compression unit can perform segmented compression on the acquired industrial internet data in a periodic segmentation manner; and the message queue management unit carries out data returning and management in a mode of standard theme and equipment authority management. The method has the advantages that the efficient compression algorithm and the equipment authentication module are arranged, so that the safety of system access is guaranteed, and meanwhile, the data transmission efficiency is improved. In addition, based on the characteristics of cloud computing, a dynamic and extensible data processing service is designed for heterogeneous industrial data, so that a user can accurately, quickly and effectively acquire required data, timely learn about abnormal conditions and remotely control the abnormal conditions, a reverse control module of the equipment improves reverse control efficiency, and an interface display and a user interaction interface design are carried out on a data processing result. The redundancy problem of data transmission, the dynamic analysis problem of heterogeneous data and the efficient reverse control problem of equipment are solved, and the reliability and the stability of the functions of the whole system are improved.

Drawings

FIG. 1 is a workflow diagram of a preferred embodiment of an industrial Internet control system and method of the present invention;

fig. 2 is a schematic view of a huffman tree constructed by the industrial internet control system and method of the present invention.

List of reference numerals

1: perception identification module 2: the data transmission module 3: data platform

4: the data analysis module 5: the application service module 21: data compression unit

22: message queue management 31: the data processing unit 51: reverse control unit

52: the visualization module 53: processing terminal

Detailed Description

The following detailed description is made with reference to the accompanying drawings.

Example 1

The application provides an industrial internet control system, which comprises a perception identification module 1, a data transmission module 2, a data platform 3, a data analysis module 4 and an application service module 5.

According to the embodiment shown in fig. 1, the sensing and identifying module 1 performs data acquisition and transmits the acquired industrial internet data to the data transmission module 2. The data transmission module 2 receives the data and issues the data to the message queue server, thereby completing the message queue authority authentication. And the data transmission module 2 compresses the authenticated data and uploads the data to the data platform 3. And the data platform 3 receives the data uploaded by the data transmission module 2 and completes the storage and management of the data. The data analysis module 4 performs operations such as analysis and alarm judgment on the data stored by the data platform 3. The application service module 5 presents a data visualization chart to the user according to the analysis result of the data analysis module 4. In addition, the user can directly issue a control instruction to the device through the application service module 5, so as to realize reverse control. The perception identification module 1 is responsible for collecting data of field intelligent equipment, the kernel of the perception identification module lies in an intelligent equipment technology and an intelligent sensing technology, physical information world data collection is achieved through the intelligent equipment and the intelligent sensing technology, and various industrial data of the intelligent equipment are collected through the intelligent sensing technology. The data transmission module 2 is responsible for connecting the perception identification module 1 and the data platform 3, and is used as an intermediate layer of two layers to solve the problem of data transmission. Selectively transmitting the production data to the Internet platform in a wired or wireless mode by accessing the intelligent equipment into the Internet system. The data transmission module 2 also performs efficient and reasonable data compression on the industrial internet sensing data so as to ensure efficient data transmission under the trend of continuous expansion of data scale. And standardized data transmission management is carried out, and the expandability of the system is enhanced. The data platform 3 is responsible for gathering all industrial data information under the system, provides data storage and operation analysis service, and serves as the 'brain' of the whole industrial internet platform system. And receiving and storing the data gathered by the perception identification module 1, and providing strong calculation power for a data analysis layer. The data platform 3 also enables dynamic, configurable storage of growing and changing heterogeneous industrial sensory data. The data analysis module 4 is responsible for deep analysis and optimization of data. As a tool of an industrial internet platform, the industrial data collected by the perception identification module 1 can be efficiently analyzed and optimized through strong calculation power provided by the industrial internet platform, so that the production management achieves the purpose of being more intelligent. The data analysis module 4 can perform dynamic and configurable analysis on the growing and changing heterogeneous industrial sensing data and can provide data alarm service with low error rate. The application service module 5 can realize the reverse control function of the equipment, improve the execution efficiency and state tracking of the reverse control, and provide basic management backstage and user interaction interfaces of registration, configuration and the like of the equipment. The application service module 5 is also connected with the data platform 3 through a preset interactive interface, so that a terminal user can perform remote information acquisition and uploading, system control and other services through the application service module 5.

Preferably, the perception identification module 1 obtains the raw data required by the data analysis module 4 by not simply acquiring the identity code, the operation state, the production information and other industrial data of the smart object. The sensory knowledge identification module 1 can complete the acquisition of information such as the identification, state, position and scene of an object according to instructions and self-circulation. The identification of the object refers to the unique code owned by each intelligent object and belonging to the intelligent object, and the real-time state of the object is obtained through tracking of the code. Preferably, the encoding technology may be two-dimensional codes, bar codes, RFID, and the like. Preferably, the state acquisition of the object refers to the acquisition of state information of the intelligent object by a sensor. The physical state data of the machine is an indispensable part for industrial big data analysis, and the running state and the running trend of the equipment can be known through the analysis and optimization of the data. The sensor is a device for sensing an output signal converted from a physical quantity inside the smart object as a technical basis for state acquisition. Preferably, the positioning and acquiring of the object position are performed by means of position positioning, and the acquired data information includes two-dimensional or three-dimensional coordinates. For example, satellite positioning, WiFi positioning, radar positioning, bluetooth positioning, base station positioning, and the like. Preferably, the scene information recording is the recording of production scenes by imaging means, wherein the images are stored as new directions of information, and the content of the images is far more than that of the traditional text information. Preferably, the image recording apparatus may employ a CMOS image sensor and a vision camera.

Preferably, the data transmission module 2 completes transmission of the data collected by the sensing and identifying module 1 to the data platform 3 through wireless communication and/or limited optical fiber. The data transmission module 2 completes real-time transmission of high concurrency and high real-time quantity of industrial fields acquired by the perception identification module 1 according to a data preprocessing mode of data compression and the like of original industrial internet data acquired by the perception identification module 1. Preferably, the data transmission module 2 uses an OPC unified architecture (OPCUA) conforming to the IEC62541 standard as a protocol standard for interfacing between the management and control system and the field control layer, so that the data transmission module 2 can access different intelligent devices, systems and products through a unified communication means on the premise of ensuring information security and stable information exchange. Massive field data acquired by the perception identification module 1 are normalized by means of a protocol conversion technology. The data transmission module 2 can establish a uniform access interface, high communication, reliability, redundancy, high compatibility and a standard safety model for the diversified sensing identification module 1, so that a uniform information model and data are realized, and the problems of connection and access between different standard devices are effectively solved.

Preferably, the data transmission module 2 includes a data compression unit 21 and a message queue management unit 22. The data compression unit 21 is used for pre-compressing the industrial internet data to be transmitted, so that the bandwidth resource occupation and the network cost of the industrial internet of things data during transmission are reduced. Preferably, the data compression unit 21 can perform multiple acquisition according to a policy of the industrial internet wireless sensor network, and the data collection method of single uploading after data aggregation compresses and uploads the data in each uploading period, so as to reduce the transmission volume of each uploading period. The acquisition period aiming at the industrial internet sensing data is less than the uploading period, but the uploading period cannot be too long in order to ensure the timeliness of the data; data is transmitted in a byte stream form; the data has the characteristics of continuous and slow data change trend, the data compression unit 21 firstly performs accurate and effective extraction of change characteristics in a differential byte transposition compression mode, realizes high-efficiency compression of slowly-changing physical characteristic data, and simultaneously ensures low delay of the data; and then, performing data characteristic extraction on the byte form of the differential data, and compressing by using the characteristic that a small-value bit stream 0 item is more. Preferably, the differential algorithm has a better compression performance on slowly varying physical characteristic data such as temperature, humidity, device current, etc. The compression algorithm provided by the data compression unit 21 has small calculation amount and simple calculation content, and does not occupy a large amount of CPU resources like the algorithm similar to wavelet transformation, so that the power consumption is low. In addition, iterative processing and IO processing occupying time do not exist in the compression operation of the data compression unit 21, and a third-party calculation library is not needed, so that the calculation time is fast, the data can be uploaded in time, and the delay is low. The data compression unit 21 can compress slowly-changing industrial sensing data to 15% -67%, and has high compression efficiency.

Preferably, before data compression, the data compression unit 21 further needs to filter invalid data points in data collected by the sensor terminal device, so as to distinguish abnormal data caused by device failure and misoperation in the industrial production process, and thus selectively complete useful data screening and further compression transmission. Preferably, the data uploaded in a periodic fashion after multiple acquisitions is a data set belonging to equidistant observation data. Preferably, for the uncertainty and instability of the existing internet communication, the requirement of continuous transmission of the broken network needs to be considered in the process of transmitting the industrial sensing data, so that the integrity of the data in a certain monitoring time period can be maintained.

In addition, the power supply of the power grid has the problem of inevitable voltage sag, which is sporadic and non-global. Therefore, for industrial sensing data located in different transformer loops, the characteristic of multi-acquisition cycle transmission of the industrial sensing data faces three risks of acquisition, transmission and storage caused by voltage sag. In particular, when the compensation transmission of data backlog caused by network disconnection, power failure and communication faults occurs, a problem of simultaneous transmission of a large amount of concurrent data occurs. After the voltage sag, the server cannot determine which data is reliable and which data needs to be discarded, so that the cleaned data needs to be sent. The data compression unit 21 can find out obvious abnormal data caused by voltage sag from the accumulated industrial sensing data, preprocess (data cleaning) the data in a mode of 'rebuilding, recovering or discarding', and upload the data in batches, so that the situation that the accumulated data is larger than the data quantity contained in a single uploading period to cause certain transmission obstruction to a transmission channel and delay of subsequent data uploading can be avoided, and a transformer which is easily interfered by the voltage sag can be determined by extracting a record of data cleaning afterwards, and the arrangement mode of a voltage-stabilized power supply in an enterprise is further optimized. In this way, the data compression unit 21 is arranged and the analysis of the data cleaning records thereof can greatly reduce the ineffective installation of the UPS or the diesel generator. In addition, incremental weights can be provided to the data cleansing records in terms of reconstruction, recovery, or discard, whereby the scale of the voltage sag (e.g., duration, magnitude of voltage drop, and sensors involved and their monitoring objects) can be determined in stages.

Preferably, the data transmission module 2 is further required to perform supplementary uploading for data loss caused by unstable transmission while ensuring real-time and synchronous transmission of the data of interest in the transmission process of the industrial sensing data, so as to uniformly compress and upload the complete industrial sensing data on the time axis.

Preferably, the data transmission module 2 is further required to perform supplementary uploading for data loss caused by unstable transmission while ensuring real-time and synchronous transmission of the data of interest in the transmission process of the industrial sensing data, so as to uniformly compress and upload the complete industrial sensing data on the time axis. Preferably, the data that the data transmission module 2 needs to upload in time includes a plurality of data that are collected in real time at equal intervals and need to be compressed uniformly according to a certain period and data that are accumulated to a certain extent due to temporary network interruption, temporary power interruption and temporary communication failure. Preferably, the data compression unit 21 may adjust a communication request period and a timestamp of the tagged data according to the amount of the stacked data to speed up the data compression frequency and efficiency, thereby speeding up the synchronous uploading of the stacked data and the real-time data. For example, when there is no data backlog, the data compression unit 21 can integrate and arrange 10 data collected in real time according to an instruction or a mechanism to form a single-time uploading data set for compression, so as to reduce the size of a transmission data packet and improve the transmission efficiency and speed; when data accumulation is caused by short-term network disconnection, power failure and communication faults, the data compression unit 21 can set two different data sets in the same compressed data packet. The first data set is used to record data normally acquired during the time period and the second data set is used to record at least partially stacked data. Preferably, the data transmission module 2 can selectively adjust the time period of the real-time data according to the amount of the accumulated data, so as to adjust the amount of the real-time data uploaded at a single time, so that the spare capacity of the compressed data packet can be used for accommodating the accumulated data, so that the accumulated data and the real-time data can be uploaded to the data platform 3 synchronously, and then whether the collected data of the collecting device can be monitored in real time is normal or not can be rapidly supplemented with the data missing in the history, so that the data information on the time axis is complete. Preferably, the number of data uploaded by the data compression unit 21 at a time may include at least 32 data without changing the data frame structure, so that when the number of data compressed by the data transmission module 2 is 10 initially, a data set of 1-22 data values can be added to quickly supplement the uploaded accumulated historical data.

The message queue management unit 22 performs data returning and management by means of the formulation of a normalized Topic (Topic) and device authority management. Preferably, the message queue management unit 22 implements unique identification of the device by unifying specification of message topics. In the existing message queue service system using MQTT as a transmission protocol, a strict Topic specification is lacked, and Topic is equivalent to a channel of a message queue, and the high-efficiency communication of data can be ensured only by the strict use specification. In addition, the prior art cannot uniformly manage the authority of the device to enter the message queue channel under the condition that a large amount of heterogeneous data is mixed. Preferably, when the sensing and identifying module 1 sends an uploading demand of the industrial internet data, the data transmission module 2 issues the uploading demand to the server of the message queue management unit 22, and uploads the industrial internet data after obtaining the message queue authority authentication, so that the message source can be tracked, and the standard management of the sensing device is facilitated. Preferably, the message queue management unit 22 can effectively allocate data by introducing the Topic. The establishment of the standardized theme can ensure that the management and control system can accurately track the source of the data when receiving the data, and acquire the working state of the data source management equipment. Preferably, by introducing Topic in the message queue management unit 22, the relevant industrial internet data can be reached only when published and subscribed topics can be matched by the user, otherwise the data cannot be received. Preferably, Topic can be used to isolate multiple data segments that need to be represented, and wildcards # and + # are set for the subscriber's Topic, where # can match any string, and + can match any string that does not contain/which provides convenience for the scenario that multiple topics need to be subscribed to simultaneously. The message queue server is generally installed in a public network environment, so that any device capable of connecting with the internet can conveniently upload data. Simple character strings can be used as Topic in daily tests, but a uniform Topic specification is required in the process of designing a management and control system. Preferably, for data transmission between the device side and the server side, the message queue management unit 22 completes matching of Topic in the data transmission process through a customized specification theme. For example, the Topic format specification is/{ section }/{ use }/{ datatype }/{ gseq }/{ nseq }. Preferably, a detailed explanation of each part of the Topic format specification is as shown in table 1 below:

table 1 subject specification

Preferably, there are four versions for the application segment, one for each different functional module. Further preferably, the usage rules are as shown in table 2.

TABLE 2 usage segments of different functional modules

For example, the topic is/project a/data/temp/001/0001, which means that a sensor node with the sequence number of 0001 at the a project factory issues temp-type data through an industrial gateway with the sequence number of 001, and the data content is in the payload of the message. Preferably, the message queue telemetry transmission protocol is an upper layer protocol based on TCP, and the sensor device generally cannot be directly used as a client to connect with the cloud, so that the sensor device is connected with the server through an industrial gateway, and the corresponding industrial gateway is used for proxy transmission of data packets for all sensors under the sensor device. Preferably, at the cloud platform end, a user only needs to subscribe/project a/data/temp/# subject when needing to acquire all temp data under the project a, and changes the application segment into JSON to be released to the server again after the data is taken and analyzed. Preferably, the cmd and ack usage segments are directed to the reverse control module separately. Through the above Topic specification, it can be ensured that the management and control system can accurately track the source of the data when receiving the data, and the online state of the device can be managed according to the data source.

Preferably, the device authority management of the message queue management unit 22 is to perform authority management on the data acquisition device in a manner of ensuring that the data acquisition device performs data transmission according to the specification, so as to effectively screen out devices with configuration errors and devices with illegal access. Rights management includes identity authentication and subscription publishing rights of the device.

(1) Identity authentication

Identity authentication is mainly to prevent access of illegal devices. Because the data platform 3 is arranged in the public network environment, although convenience is brought to the access of the equipment, the probability of the invasion of illegal equipment is increased. Therefore, each device needs to be registered in a server, metadata information of the device is stored in a database, and the information contains a unique serial number of the device and a user name and a password specially generated for the device. When the subsequent equipment is connected with the data platform 3, the user name and the password are required to be carried for identity authentication, and only the equipment passing the authentication can be connected with the data platform 3. The identity authentication ensures that only equipment registered on the cloud platform can be accessed to the data platform 3, and guarantees are provided for the safety and reliability of the data source.

(2) Authority authentication

Subscription-publishing rights authentication of a device is primarily to prevent the irregular use of legitimate devices. If the device after identity authentication publishes data on the topic of another device, this may cause a data source identification error, and cause more errors, so it is necessary to manage the right of the device to subscribe to a published topic. The authority authentication is mainly to compare whether the username in the connection information as the processing terminal 53 is consistent with the nseq in the subject to be operated. And the use segment is used as auxiliary judgment to finally obtain the result of the equipment authority authentication.

Preferably, the data transmission module 2 transmits the industrial data collected by the perception identification module 1 to the data platform 3 for data storage and classification management. The data analysis module 4 can extract industrial data stored in the data platform 3 according to requirements or instructions and analyze and optimize the industrial data, so that machine intelligence is given to the industrial information system. Preferably, the processing of industrial internet data by the data analysis module 4 includes centralized processing of non-real-time data, centralized processing of real-time data, and separate processing of image data. The ultimate goal of industrial internet modern data analysis is to obtain machine intelligence. Preferably, machine intelligence includes three aspects of connotations: deductive ability, problem solving ability, and self-organizing learning ability.

Preferably, when receiving the compressed data uploaded by the data transmission module 2, the data platform 3 further decompresses the compressed data through the data processing unit 31 and then performs classified storage. Preferably, the data platform 3 selects the MVSOL database as the data management tool of the control system. Aiming at the characteristics of large concurrency of industrial Internet data and short single data, the data platform 3 stores and establishes an asynchronous programming model by adopting a data aggregation mode.

(1) Data aggregation storage

The storage process of the database is that firstly, a socket connection is established between a client program and the database, user identity authentication is carried out, and then after the authentication is passed, an operation instruction of the database is sent to the database through the connection. The data processing unit 31 compiles and runs the instructions, finally realizes the insertion of data, and then needs to release connection resources. It can be seen from this flow that the major time of the database insertion operation is for network IO and file IO, which is necessary for storing data and can only be optimized on network IO, and if the insertion of multiple pieces of data is aggregated into a single insertion statement, network IO can be reduced. Thereby reducing the time required for data insertion. The data platform 3 temporarily stores the received data in a data aggregation manner, and sets a storage trigger condition, for example: when the temporary data exceeds 30 seconds or the temporary data amount is more than 10M, the data in the memory can be written into the database once. After data aggregation, the connection times of the database are greatly reduced, and the data storage efficiency is improved.

(2) Asynchronous programming model

The concurrency type is generally divided into a calculation intensive type and an IO intensive type, the calculation intensive type is a service with high occupation of processor resources such as a CPU or a GPU, and the calculation intensive type is a calculation intensive service such as deep learning. The IO-intensive service is mainly an operation on IO, and although a large amount of calculation is not needed, disk reading and writing, network delay and the like are more time-consuming, and the data storage service is a typical IO-intensive service. For IO intensive services, if a sequentially executed programming model is used, a block may form because IO takes too long. The traditional system usually adopts a multithreading mode to realize non-blocking operation, but the multithreading needs switching of a large number of cpu contexts and creation of cpu execution handles, and the efficiency is low. In recent years, a programming model of asynchronous IO emerges, and optimization is specially made for IO intensive service. The asynchronous programming model and the multithreading model are both non-blocking programs and have high execution efficiency, and do not need to wait for long IO execution, but the multithreading model needs to open up a plurality of threads and apply for more resources, and compared with the asynchronous programming model, the asynchronous programming model does not need extra overhead and is lighter.

Preferably, the data analysis module is capable of parsing the industrial internet data stored in the data platform 3 in a dynamic configuration-based manner. The data analysis module 4 carries out shunting and buffering on industrial field mass production data, and carries out application of an algorithm after the system and the server interact. The machine learning algorithm is generally applied to a control layer of the system, the data analysis module 4 packages the data analysis algorithm, the data interface is connected, data extraction is carried out, and the data extracted through the algorithm is applied to a view layer to be displayed. The view layer combines the algorithm to realize different display interface effects, including trend chart, histogram, pie chart, table, etc. The machine learning algorithm and the front-end functional plug-in are used interactively, so that the data can be analyzed optimally, and the data required by research can be obtained. The data analysis module 4 performs external storage instead of program internal static assignment in a key value pair mode by flexibly configuring data types and analysis rules, so that heterogeneous data of different data types can be analyzed according to the same set of analysis spear engine, and respective analysis rules are stored in a database. Preferably, dynamic parsing requires that the parsed portions be pulled from the program as separate services. The input to the service is byte stream data and the output is a structured string. For different types of byte stream data, respective analysis modes are required, so that the most core function of the analysis service is the design of an analysis engine, and binary data is analyzed by using a text rule.

Preferably, the data analysis module 4 is also capable of detecting the status of the equipment according to data in the data platform 3 for a continuous period of time and giving an alarm in case of data abnormality and equipment failure. Preferably, the data analysis module 4 performs abnormal data analysis using threshold determination based on a sliding window. And when the data analysis module 4 judges that the data exceeds the preset threshold value, an alarm prompt is sent to a responsible person. The data analysis module 4 integrates the advantages of the cloud platform and the micro service, only needs to judge whether the current value exceeds a threshold value for the alarm service, and delivers the mail and the short message after the judgment is successful to the specific mail and short message service, and the services are low in coupling, so that the advantages of the micro service framework are reflected.

Preferably, the application service module 5 comprises at least a reverse control unit 51 and a visualization module 52, a processing terminal 53. The inverse control unit 51 is capable of controlling the configuration of the apparatus, such as the sampling frequency modification of the sensors, etc. The configuration of the device needs to be stored and managed in the cloud, and the table used at this time is t _ config, and the structure of the table is shown in table 3.

Table 3 table structure of t _ config

Preferably, the configuration of the sensor devices constituting the perceiving recognition module 1 is generally not directly obtained from the backward control unit 51, since the sensor devices themselves cannot be directly connected to the backward control unit 51, and therefore an industrial gateway is required as a proxy. The general sensor configuration is existed in the industrial gateway, and the gateway directly controls the working state of the sensor. The gateway temporarily stores the configuration of all the sensors under it, and as a representative of these devices, it is connected to the reverse control unit 51. When the reverse control unit 51 issues a new configuration, the gateway receives the configuration and compares it with the currently stored configuration, updates the storage if it is different, and notifies the designated sensor to make a configuration change. After receiving the CMD packet, the gateway also needs to send an ACK packet to the cloud platform to ensure that the cloud platform receives feedback and does not continue to retransmit the CMD packet. The CMD packet itself is sent in the format of a JSON string. Preferably, the application service module 5 further comprises a visualization module 52 and a processing terminal 53. Visualization module 52 enables review of industrial internet data and review of data analysis results. In addition, the processing terminal 53 can also receive prompt information when the production system has a fault or an abnormal early warning, perform corresponding production control operation, and help a user to perform remote industrial production control. Preferably, the processing terminal 53 can also perform index data that is automatically monitored by a system such as a threshold value, so that a user can conveniently perform personalized setting according to the own requirement, and the terminal user can perform services such as remote information acquisition, uploading and system control.

Example 2

This embodiment is a further improvement of embodiment 1, and repeated contents are not described again.

In an actual industrial internet system, industrial internet data generally needs to be analyzed and predicted based on mass data, so that sensing data often has the characteristics of large data volume and frequent data transmission, and the bandwidth occupied by the data is large. The cloud platform is often established in a public network environment, and the sensor end mostly uses 4G or WiFi for uploading data. This results in data uploads that occupy network traffic resources, which are typically paid for. The data is compressed in advance and then transmitted, so that the bandwidth resource can be saved, and the network cost is reduced.

Preferably, the differential algorithm of the data compression unit 21 mainly includes the steps of differential processing, complementary code processing, transposition processing, huffman coding, data merging, and the like. The purpose of the difference processing is to extract the change characteristic of the data, and according to the characteristic that the change trend of the sensing data is slow, amplitude values of data change before and after difference can be extracted, and the absolute values of the amplitude values are small. And compressing the data before uploading the data each time, wherein the compressed data are a plurality of pieces of data acquired in the uploading period. Preferably, the data to be uploaded is subjected to differential processing, the processing mode is that each piece of data subtracts the previous piece of data, and the first piece of data is kept unchanged, so that the representation of the variation trend of the data is completed by utilizing the differential processing, that is, the original array is processed by the differential processing to obtain a first compressed array. Preferably, the compression process comprises: first, the number n of data and the single data size m of the present cycle are extracted, as well as the first data a 0. And then differentiating the data a to obtain the difference value of the continuous data. And then, carrying out complement processing on the difference value, converting the difference value into a binary matrix, and converting the matrix. Each row of the matrix is then converted to a positive integer of uint (n-1), and the set of positive integers is encoded into a binary string using a static Huffman coding table for uint (n-1). And finally, splicing the binary code and the total four parts of data of n, m and a0 stripped in the first step according to a pre-selected data frame structure to finally form the binary byte code to be transmitted. Preferably, the number of data n and the size m of a single data byte are combined into one byte at the time of compression processing. And when the number of data uploaded at a single time exceeds 32 and 5 bits cannot be represented, adjusting and configuring the conventional data frame structure according to the actual single-time uploading order.

The purpose of the complement processing is to unify the binary characteristics of positive and negative numbers. The first compressed array after the difference processing has a characteristic of small numerical value, strictly speaking, the absolute value of the number is small, and in the computer representation, positive numbers and negative numbers have different representation modes and thus have different characteristics. Preferably, binary representation is used in the computer for any integer. The complementary code processing unifies the characteristics of positive numbers and negative numbers with small absolute values on binary representation, namely, the high bits of the binary representation have a plurality of 0's. The positive and negative numbers differ in the sign bit, which is 0 for positive numbers and 1 for negative numbers. And the complement processing processes the differentiated first compressed array to obtain a new second compressed array. Preferably, the second compressed array does not represent each element by a separate number, but rather represents each element in the form of a binary code.

The purpose of the transposition process is to convert the characteristic that the high order bits contain more 0 values into the characteristic that the finally transmitted data contain more 0 values. The transposed matrix recombines the bit codes of each row into an unsigned integer, and a new sequence t can be obtained. Preferably, the new array t obtained after the transpose process has the following characteristics:

(1) the number of elements of array t depends on the data type of the original data, so t has 8 elements if the original data is encoded using int 8. If the original data is encoded using int16, t has 16 elements.

(2) The elements of the array t contain more 0 entries, which is caused by the column characteristics of the matrix B.

The purpose of huffman coding is to compress the data obtained in the previous step, which contains more 0-item redundancy. The Huffman coding is a variable length coding, and uses different frequencies of the different numbers, uses shorter codes for the numbers with higher frequency of appearance, and uses longer codes for the numbers with lower frequency of appearance, thereby achieving the effect of compressing the data volume.

The data transmission scenario is not well satisfied with classical huffman coding. Data compression of an industrial internet scene is generally data for a single uploading period, the data generally has only 10-30 groups of data, and the size of an encoding table per se can be larger than that of original data, so that the dynamic encoding is not suitable for data transmission of the internet of things. Consider building a static huffman coding table that performs better for most scenes. For the transposed array t, the most obvious characteristic is that 0 entries are more, and it is not assumed that the average probability of 0 occurrence exceeds 50% in the process of encoding data for many times, but the average probability of occurrence of other numbers is the same. Thus, when the huffman tree is constructed, 0 is always located under the root node, and other digits have the same length, and if the uint (x) is coded, the huffman tree is constructed as shown in fig. 2. According to FIG. 2, the right sub-tree of the root node of the Huffman tree of uint (x) is a binary code tree of all numbers except 0, i.e. 0 corresponds to a code of 0, and the codes of other numbers are just the binary codes of own uint (x) value plus 1. Based on the rule, the coding table of the agent (x) is a static table, and the sending end and the receiving end can independently generate the coding table without carrying the coding table for sending, so that the data volume transmitted after compression can be greatly reduced.

When the first data is transmitted by performing compression coding of other data except the first data by huffman coding. On the data receiving side, the data needs to be analyzed in the format of "u" (x), and since x is n-1, n needs to be transmitted. In order to strip the first data and the subsequent data, the byte number m occupied by the first data is also required to be known. The four parts n, m, a and s constitute the last transmitted data. The data merging operation is to merge the byte codes of the four parts of data to form the finally transmitted data.

Preferably, the decompression process of the data receiving end is the inverse process of the compression process, and mainly includes data splitting, huffman decoding, transposition processing, complement processing and superposition processing. Preferably, the compressed data transmitted during data splitting is composed of n, m, a and s, and the splitting is also performed according to the data type. Preferably, the huffman decoding is the inverse process of the huffman coding, and according to the split n, the s is decoded by using the corresponding huffman coding table of the uint (n-1), so that the array t before the huffman coding can be obtained. Preferably, the inverse operation of the transposition is also transposition, i.e. the transposition of the matrix transposition is itself, so the array T is transformed into the matrix T. Preferably, the inverse of the complementary operation is also a complementary operation, i.e. the complement of the complement is also itself. And (4) complementing the numbers represented by each row of the transposed matrix to obtain an array, wherein the array is a differential array. Preferably, the difference of the data obtained after the complement processing needs to be superimposed on the basis of the first data obtained by the splitting processing to restore the original data.

Example 3

The present application also provides a control method of an industrial internet, which includes:

(1) the perception identification module 1 carries out data acquisition and transmits the acquired industrial internet data to the data transmission module 2.

(2) And the data transmission module 2 receives the data, issues the data to the message queue server, and performs message queue authority authentication.

(3) The background of the data transmission module 2 subscribes to a corresponding theme, and data compression is performed after data acquisition and the compressed data is uploaded to a data platform.

(4) And the data platform 3 receives the data uploaded by the data transmission module 2 and completes the storage and management of the data.

(4) The data analysis module 4 performs operations such as analysis and alarm judgment on the data stored by the data platform 3.

(5) The application service module 5 presents the data visualization chart to the user through the system page.

In addition, the user can directly issue a control instruction to the device through the application service module 5, so that reverse control is realized.

It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and drawings are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents.

Claims

1. An industrial internet control system at least comprises a perception identification module (1) used for data collection in an industrial production site, and is characterized in that under the condition that the perception identification module (1) transmits collected industrial internet data to a data transmission module (2), the data transmission module (2) performs message queue authority authentication and compresses related industrial internet data in a differential mode, and transmits the compressed industrial internet data to a data platform (3) in a byte stream mode, wherein,

the data transmission module (2) at least comprises a data compression unit (21) and a message queue management unit (22), wherein the data compression unit (21) can perform segmented compression on the collected industrial Internet data in a periodic segmentation manner; the message queue management unit (22) carries out data returning and management in a mode of normative theme and device authority management.

2. The industrial internet control system according to claim 1, wherein the data transmission module (2) selectively connects the perception identification module (1) to an industrial internet architecture in a wired or wireless manner and transmits the collected related data to the data platform (3), and the data transmission module (2) completes compression and transmission of industrial internet data in a manner of specifying management rules of data transmission.

3. The industrial internet control system according to claim 1, wherein the data compression unit (21) performs compression of the periodic data in such a manner that the data collected by the individual sensing recognition modules (1) within a set period time are aggregated, wherein the data compression unit (21) performs data feature extraction in the form of bytes of differential data.

4. The industrial internet control system according to claim 1, wherein the message queue management unit (22) completes the distribution operation of industrial internet data by introducing themes, and tracks the source of the data and the working state of the corresponding perception identification module (1) by establishing a normalized subject mode.

5. The industrial internet control system according to claim 1, wherein the device authority management of the message queue management unit (22) is to perform the authority management on the sensing recognition module (1) in a manner of limiting the sensing recognition module (1) to perform data transmission according to the specification, so as to screen out the terminal device with wrong configuration and/or the terminal device with illegal access.

6. The industrial internet control system according to claim 5, wherein the data platform (3) temporarily stores the received data in a data aggregation manner, and is preset with a trigger condition for data storage, so that when the temporarily stored data reaches the preset trigger condition, the data platform (3) writes the temporarily stored data in the memory into the database at one time.

7. The industrial internet control system according to one of the previous claims, characterized in that the data platform (3) is also able to transmit its sorted stored data to a data analysis module (4), the data analysis module (4) being able to carry out in-depth analysis and optimization of the data; the data analysis module (4) can perform dynamic and configurable analysis on the continuously growing and changing heterogeneous industrial sensing data and provide a data alarm service with a low error rate.

8. Industrial internet control system according to one of the previous claims, characterized in that it further comprises an application service module (5), said application service module (5) being connected to said data platform (3) through a preset interactive interface, enabling end users to perform remote information acquisition, upload and system control through said application service module (5).

9. An industrial internet control method is characterized by comprising

S1: the perception identification module (1) collects data and transmits the collected industrial internet data to the data transmission module (2);

s2: the data transmission module (2) receives the data, issues the data to a message queue server, and performs message queue authority authentication;

s3: the background of the data transmission module (2) subscribes to a corresponding theme, compresses data after acquiring the data and uploads the compressed data to a data platform;

s4: the data platform (3) receives the data uploaded by the data transmission module (2) and completes data storage and management;

s5: the data analysis module (4) analyzes and alarms and judges the data stored by the data platform (3);

s6: the application service module (5) presents a data visualization chart to a user through a system page, and the user can issue a control instruction to the equipment through the application service module (5) to realize reverse control.

10. The industrial internet control system and method according to one of the preceding claims, wherein the data transmission module (2) comprises at least a data compression unit (21) and a message queue management unit (22), the data compression unit (21) can compress the collected industrial internet data in segments in a periodic partitioning manner; the message queue management unit (22) carries out data returning and management in a mode of normative theme and device authority management.