CN116483009A - Industrial data acquisition and processing system based on Internet - Google Patents
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Abstract
The invention relates to the technical field of transmission and communication of digital information, and particularly discloses an industrial data acquisition and processing system based on the Internet, which comprises an industrial data acquisition module, a data transmission module and a data input/output module, wherein the industrial data acquisition module is connected with an IO interface of an industrial numerical control terminal through a sensor, acquires various data in an industrial environment, uploads the various data to an industrial data cloud platform by adopting a 4G/5G wireless network to perform cloud storage and cloud processing, and is connected with the data transmission module through an industrial intelligent gateway to perform data input/output; according to the invention, the real-time monitoring record alarm module is added, the data consistency of the industrial data acquisition module and the data transmission module is detected in real time by using the installation software, the data transmission is not interfered, the information is not lost, the function of effective information is extracted, the acquired and transmitted data is further processed and analyzed by the data processing analysis module, the algorithm model is built, and the accuracy of the data is improved.
Description
Technical Field
The invention relates to the technical field of digital information transmission and communication, in particular to an industrial data acquisition and processing system based on the Internet.
Background
Along with the global trend of internet coverage, in order to promote economic development, internet technology has been incorporated into computer networks, and local communication networks of different scales, independent operation and independent management suitable for various industries and enterprises are woven through protocol connection, so that industrial data can be connected and interacted through the network, and information can be quickly and conveniently transferred, and information sharing is realized.
Industrial data are data collected from industrial production in terms of operation, manufacturing, quality control, equipment maintenance, including information on production line yield, cost, quality, energy consumption, equipment maintenance, personnel attendance, etc., as well as information on sensors, controllers, their operational status data in industrial automation systems; by collecting the industrial data information and analyzing and applying the industrial data, enterprises are assisted to optimize the production flow, improve the efficiency, reduce the cost, improve the quality and the reliability, and simultaneously, more accurate data support can be provided for enterprise operation decisions.
The existing industrial data acquisition and processing system based on the Internet is characterized in that a communication protocol, an electric wire communication network port and a data acquisition card of an industrial intelligent numerical control equipment terminal are utilized to be connected, an IO interface of the data acquisition terminal is utilized to be connected with numerical control equipment, acquired data is uploaded to a cloud platform for further processing through 4G/5G, but the problems of acquisition data transmission interference, information deletion and delay exist, the problems that effective information extraction and processing of received data are difficult, the positioning trend is inaccurate, the single influence on decision maker judgment of an information feedback form exists, and therefore the problems of low data accuracy, low operation efficiency, low information utilization rate and abnormal influence on the rapid industrial development of feedback data are caused.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides an industrial data acquisition and processing system based on the Internet, which increases the real-time monitoring function of industrial data acquisition and transmission by adopting a real-time monitoring record alarm module; the characteristic data is effectively extracted through the industrial data processing and analyzing functions added by the data processing and analyzing module, and the function of accurately analyzing the industrial data is realized, so that the problems in the background technology are solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: the industrial data acquisition and processing system based on the Internet comprises an industrial data acquisition module, wherein the industrial data acquisition module is connected with an industrial numerical control terminal IO interface through a sensor, acquires various data in an industrial environment, uploads the various data to an industrial data cloud platform by adopting a 4G/5G wireless network to perform cloud storage and cloud processing, and is connected with a data transmission module through an industrial intelligent gateway to perform data input and output;
the data transmission module is used for receiving the data acquired by the industrial data acquisition module, transmitting the data to the data processing analysis module by utilizing a wireless communication protocol to perform data preprocessing and uploading the data to the industrial data cloud platform to perform data backup;
the system comprises a real-time monitoring recording alarm module, a storage distributed recording module and a data transmission module, wherein the real-time monitoring recording alarm module is used for installing one or more of FineBI, diffDog, beyond computer, apache NiFi and Zabbix software in the system, effectively ensuring the information accuracy of monitoring collected data in the system, improving the accuracy and reliability of the data, monitoring abnormal data to alarm by utilizing the storage distributed recording, and detecting whether the data in the data sources of the industrial data collection module and the data transmission module are consistent or not, so as to avoid data collision, repetition and omission;
the data processing analysis module is used for processing, calculating and analyzing the data generated in the industrial process by utilizing a statistical analysis technology, a machine learning technology and a signal processing technology, extracting valuable information and rules in the data, receiving the industrial data transmitted by the data transmission module, establishing model calculation, processing and analysis, and transmitting the industrial data to the data display feedback module for graphic visual signal feedback to a decision maker of industrial management;
the industrial data cloud platform receives and processes industrial data of the industrial data acquisition module, the data transmission module and the data processing and analyzing module through a wireless network, so that the full-flow processing of acquisition, storage, management, analysis and display of the industrial data is realized;
and the data display feedback module displays visual information of industrial collection, processing, analysis and monitoring through a display screen of the computer, and displays the industrial data information in a diversified mode in the form of charts, reports and animations.
Further, the industrial data acquisition module comprises an intelligent sensor acquisition unit, a plurality of intelligent sensors are connected with an industrial intelligent gateway in industrial numerical control equipment, and industrial data information is received and transmitted to the data transmission module through the GPRS transceiver communication unit and uploaded to the industrial data cloud platform;
the GPRS transceiver communication unit adopts an IP data network protocol in a packet switching mode, provides end-to-end wide area wireless IP connection for data information received by the sensor, and is used for converting serial port data into IP data and transmitting the IP data through a wireless communication network;
the AT instruction microcontroller unit is used for executing bidirectional data communication control of the AT instruction through a programmable program of the MCU and is used for confirming data transmission communication;
and the ARM serial port protocol storage unit adopts a data transmission protocol of serial communication, acquires the data received and collected by the intelligent sensor, stores and manages the data, and is used for realizing the mapping from the virtual storage space to the physical storage space.
Further, the AT command microcontroller unit comprises an embedded microcontroller, serial port communication, wi-Fi communication, bluetooth communication and a short message communicator; the embedded microcontroller is connected with the industrial numerical control equipment through the communicator to perform data interaction and control, and can realize parameter setting and adjustment of the industrial numerical control equipment and inquiry and control of equipment states of the industrial numerical control equipment through the AT instructions; the method integrates various communication modes, realizes a unified interface by utilizing the mode of AT instructions, reduces development difficulty and cost, is easy to popularize and maintain, realizes remote control and data interaction of the embedded equipment, improves flexibility and expansibility of the equipment while ensuring reliability of various interfaces, can be used as a standard interface of the embedded equipment, is suitable for various embedded equipment, and brings higher flexibility and expansibility.
Further, the real-time monitoring record alarm module comprises an intelligent monitoring unit and monitoring software for controlling the industrial data acquisition and transmission process, such as FineBI is industrial data visualization and analysis software, various acquired data are integrated together, and the data are displayed to decision makers of enterprises in a chart, report and animation mode; the Beyond computer is used for comparing the difference of the acquired and transmitted data in the industrial data acquisition module and the data transmission module, quickly and accurately finding out the difference of the data, reducing the source of inaccuracy of the data and improving the accuracy of subsequent data processing analysis;
the memory recording unit is used for storing historical data through MRU in the computer, and particularly can buffer and record the transmission path, the size and the modification time of the data information, so that the data information can be loaded faster when a subsequent decision maker opens and accesses the data information;
the detector alarm unit adopts a sensor technology to monitor and alarm the abnormal parameter data of the numerical control equipment in the industrial data, can automatically send out alarm sound, and informs an industrial decision maker in a computer graphic feedback mode through an indicator lamp and a call center, so as to quickly find potential safety hazards in the industrial environment.
Further, the data transmission module comprises a DTU transmission unit, and data acquired by the intelligent sensor field connection industrial numerical control equipment are respectively transmitted to the industrial data cloud platform and the data processing analysis module in a wireless and wired mode to carry out data processing in the next step;
and the ARP cache protocol unit adopts a mapping mode to convert an IP logical address into a corresponding NAC physical address and is used for directly transmitting data by combining with the GPRS transceiver communication unit.
Furthermore, the data processing and analyzing module comprises an artificial intelligent algorithm processing unit, and adopts machine learning, integrated learning, data mining, deep learning and natural language processing technologies for simulating, extending and expanding intelligent theory and method of people to research industrial big data.
The data fusion algorithm analysis unit integrates and analyzes the collected industrial data to find hidden modes and relations, so that the industrial production process is improved, and the convolutional neural network CNN and the recurrent neural network RNN in the deep learning algorithm are used for integrating and analyzing industrial big data to realize highly-automatic production.
Further, the data fusion algorithm adopts a CNN algorithm model and an RNN algorithm model, wherein the CNN algorithm model is used for filtering, edge detection and fuzzy processing of industrial data, and the calculation formula is as follows:
y i,j,k ＝∑ m,n,c w m,n,c,k x(i+m),(j+n),c+b k wherein y is i,j,k For the output value of the convolution kernel at the (i, j) position, w m,n,c,k Is the weight of the convolution kernel, x (i+m), (j+n), c is the input data, b k Is the offset; in the pooling operation, in order to improve the robustness and the calculation efficiency of the model, the data output by the convolution layer is compressed, and the calculation formula is as follows:wherein y is i,j,k For values of the pooling layer at the (i, j) position, x (i+m), (j+n), c is the value of the neuron output upstream of the pooling layer; at the full connection layer, the mapping from the input data to the tag is completed, and the calculation formula is as follows: f (x) =wx+b, where f (x) is the output, W is the weight matrix, x is the input vector, and b is the offset;
the RNN algorithm model is used for processing time series data of industrial data, avoiding gradient disappearance during back propagation, and the calculation formula is as follows during state update: h is a t ＝f(W xh x t +W hh x t-1 +b h ) Wherein, h t Is the current state, x t For input of current time step, W xh To input a weight matrix, W hh Is a state weight matrix, b h For the bias vector, f is the activation function; when the state is updated, the output calculation to the current state is performed, and the calculation formula is as follows: y is t ＝f(W hy h t +b y ) Wherein y is t To output vector W hy To output a weight matrix, b y To output a bias vector, f is the activation function.
Further, the algorithm process of the industrial data processing analysis in the data processing analysis module comprises the following steps:
data preprocessing: the method comprises the preprocessing processes of data cleaning, data sampling, data normalization and abnormal value detection, and is used for removing noise and abnormal values in data and reducing data noise and variance;
feature extraction: extracting valuable features which promote industrial development trend from the data by analyzing the data, wherein the valuable features comprise frequency, amplitude, time domain and frequency domain analysis data; analysis and prediction for later data;
data analysis: analyzing and modeling the data by using various algorithms, including regression analysis, cluster analysis, neural networks, decision trees, and data fusion; for classifying, predicting and optimizing data;
data evaluation: evaluating the result of data analysis, and checking the accuracy and reliability of the model; the evaluation methods include cross-validation, ROC curve, AUC.
Data presentation: and the data analysis results are displayed in a diversified manner in a visual mode, wherein the visual display comprises characters, charts, data reports and dynamic graphics. The processing analysis algorithm is used for comprehensively and deeply analyzing industrial data, extracting valuable features and information, providing data decision support and an optimization scheme for enterprises, and providing a more reliable and accurate basis for future prediction and analysis.
Further, the industrial data cloud platform realizes equipment remote monitoring by networking equipment in an industrial user, and an industrial gateway collects data and transmits the data, wherein the final information is summarized at an industrial cloud platform end and is used for industrial equipment remote monitoring; when equipment fails, alarm information is pushed to an equipment manager, and for the failure, the manager of industrial equipment can adjust relevant parameters at an industrial cloud platform end, so that the equipment failure is solved, and the equipment is used for remote debugging of industrial numerical control equipment; the cloud processing and cloud storage industrial gateway collects relevant data on the equipment and is used for providing a data reference basis for upgrading the industrial equipment; and the industrial decision maker is finely managed.
Further, the data display feedback module is used for establishing a plurality of visual models, converting the data into visual forms, explaining the meaning of the data according to elements in a data processing visual algorithm, displaying the data in the form of charts, reports, interactive graphs and animations, and being used for helping industrial decision makers to better understand the data, find modes and trends in the data and make better decisions.
(III) beneficial effects
The invention provides an industrial data acquisition and processing system based on the Internet, which has the following beneficial effects:
according to the invention, the real-time monitoring record alarm module is added, the data consistency of the industrial data acquisition module and the data transmission module is detected in real time by using the installation software, the functions that the data transmission is not interfered, the information is not lost, the effective information is extracted, the acquired and transmitted data is further processed and analyzed by the data processing analysis module, the algorithm model is built, the accuracy of the data is improved, the diversification of the data display feedback module is adopted, the industrial decision maker is assisted to better understand the data, the mode and trend in the data are found, and a better decision is made.
Drawings
FIG. 1 is a block diagram of an Internet-based industrial data acquisition and processing system of the present invention.
Fig. 2 is a schematic diagram of an industrial data acquisition module according to the present invention.
Fig. 3 is a schematic diagram of a real-time monitoring recording alarm module according to the present invention.
Fig. 4 is a schematic diagram of a data transmission module according to the present invention.
Fig. 5 is a schematic diagram of a data processing analysis module according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-5, the invention provides an industrial data acquisition and processing system based on the internet, which comprises an industrial data acquisition module, a data transmission module and a data input/output module, wherein the industrial data acquisition module is connected with an industrial numerical control terminal IO interface through a sensor, acquires various data in an industrial environment, uploads the various data to an industrial data cloud platform by adopting a 4G/5G wireless network for cloud storage and cloud processing, and is connected with the data transmission module through an industrial intelligent gateway for data input/output;
the data transmission module is used for receiving the data acquired by the industrial data acquisition module, transmitting the data to the data processing analysis module by utilizing a wireless communication protocol to perform data preprocessing and uploading the data to the industrial data cloud platform to perform data backup, wherein the data comprises production and manufacturing site data, production plan and production task data, quality detection data and operation data, and the production and manufacturing site data comprises physical quantities of temperature, humidity and pressure, the on-off state of a machine and fault alarm state information of equipment; the production plan and production task data comprise production order data, work order data and process route data; the quality detection data comprise product process characteristic data, detection qualification rate data and detection abnormality data; the operation data comprise equipment operation data, energy consumption data and output data;
the system comprises a real-time monitoring recording alarm module, a storage distributed recording module and a data transmission module, wherein the real-time monitoring recording alarm module is used for installing one or more of FineBI, diffDog, beyond computer, apache NiFi and Zabbix software in the system, effectively ensuring the information accuracy of monitoring collected data in the system, improving the accuracy and reliability of the data, monitoring abnormal data to alarm by utilizing the storage distributed recording, and detecting whether the data in the data sources of the industrial data collection module and the data transmission module are consistent or not, so as to avoid data collision, repetition and omission;
the data processing analysis module is used for processing, calculating and analyzing the data generated in the industrial process by utilizing a statistical analysis technology, a machine learning technology and a signal processing technology, extracting valuable information and rules in the data, receiving the industrial data transmitted by the data transmission module, establishing model calculation, processing and analysis, and transmitting the industrial data to the data display feedback module for graphic visual signal feedback to a decision maker of industrial management;
the industrial data cloud platform receives and processes industrial data of the industrial data acquisition module, the data transmission module and the data processing and analyzing module through a wireless network, so that the full-flow processing of acquisition, storage, management, analysis and display of the industrial data is realized; the method specifically comprises the steps of comprehensively monitoring an industrial environment by utilizing data received by a cloud; the method comprises the steps of storing industrial big data in a cloud by adopting a cloud distributed storage technology; and classifying, managing, backing up and recovering the industrial data by the instruction; adopting an artificial intelligence algorithm to analyze, model and predict industrial data, and providing data decision support for enterprises; and utilizing a data visualization technology to display and feed the industrial data to an enterprise decision maker in the forms of charts, reports and animations;
and the data display feedback module displays visual information of industrial collection, processing, analysis and monitoring through a display screen of the computer, and displays the industrial data information in a diversified mode in the form of charts, reports and animations.
In a preferred embodiment, the industrial data acquisition module specifically includes an intelligent sensor acquisition unit, a plurality of intelligent sensors are connected with an industrial intelligent gateway in industrial numerical control equipment, and industrial data information is received, transmitted to the data transmission module through a GPRS transceiver communication unit and uploaded to an industrial data cloud platform;
the GPRS transceiver communication unit adopts an IP data network protocol in a packet switching mode, provides end-to-end wide area wireless IP connection for data information received by the sensor, and is used for converting serial port data into IP data and transmitting the IP data through a wireless communication network;
the AT instruction microcontroller unit is used for executing bidirectional data communication control of the AT instruction through a programmable program of the MCU and is used for confirming data transmission communication;
and the ARM serial port protocol storage unit adopts a data transmission protocol of serial communication, acquires the data received and collected by the intelligent sensor, stores and manages the data, and is used for realizing the mapping from the virtual storage space to the physical storage space.
In a preferred embodiment, the AT instructs the microcontroller unit to include an embedded microcontroller, serial communication, wi-Fi communication, bluetooth communication, and short message communicator; the embedded microcontroller is connected with the industrial numerical control equipment through the communicator to perform data interaction and control, and can realize parameter setting and adjustment of the industrial numerical control equipment and inquiry and control of equipment states of the industrial numerical control equipment through the AT instructions; the method integrates various communication modes, realizes a unified interface by utilizing the mode of AT instructions, reduces development difficulty and cost, is easy to popularize and maintain, realizes remote control and data interaction of the embedded equipment, improves flexibility and expansibility of the equipment while ensuring reliability of various interfaces, can be used as a standard interface of the embedded equipment, is suitable for various embedded equipment, and brings higher flexibility and expansibility.
In a preferred embodiment, the real-time monitoring record alarm module specifically includes an intelligent monitoring unit, and monitoring software for controlling the industrial data collection and transmission process, such as FineBI is industrial data visualization and analysis software, and integrates various collected data and displays the data to decision makers of enterprises in a form of charts, reports and animation; the Beyond computer is used for comparing the difference of the acquired and transmitted data in the industrial data acquisition module and the data transmission module, quickly and accurately finding out the difference of the data, reducing the source of inaccuracy of the data and improving the accuracy of subsequent data processing analysis;
the memory recording unit is used for storing historical data through MRU in the computer, and particularly can buffer and record the transmission path, the size and the modification time of the data information, so that the data information can be loaded faster when a subsequent decision maker opens and accesses the data information;
the detector alarm unit adopts a sensor technology to monitor and alarm the abnormal parameter data of the numerical control equipment in the industrial data, can automatically send out alarm sound, and informs an industrial decision maker in a computer graphic feedback mode through an indicator lamp and a call center, so as to quickly find potential safety hazards in the industrial environment.
In a preferred embodiment, the data transmission module specifically includes a DTU transmission unit, and transmits data collected by the intelligent sensor field connection industrial numerical control device to the industrial data cloud platform and the data processing analysis module respectively in a wireless and wired mode for further data processing;
and the ARP cache protocol unit adopts a mapping mode to convert an IP logical address into a corresponding NAC physical address and is used for directly transmitting data by combining with the GPRS transceiver communication unit.
In a preferred embodiment, the data processing and analyzing module specifically includes an artificial intelligence algorithm processing unit, and adopts machine learning, ensemble learning, data mining, deep learning and natural language processing technology to simulate, extend and expand intelligent theory and method of people to study industrial big data, wherein the machine learning uses supervised learning, unsupervised learning and reinforcement learning technology to predict future industrial production data, identify industrial product defects and optimize process flow; the integrated learning adopts an algorithm to establish a prediction model to process data so as to obtain a more accurate result; the data mining combines machine learning and statistical technology to mine the hidden mode and relation of a large amount of data, and find valuable data information of industrial production; the deep learning is to train a model by adopting a neural network so as to identify images, modes and relations; natural language processing is the automatic processing of text data using language models for extracting key information of industrial data and establishing real-time monitoring.
The data fusion algorithm analysis unit integrates and analyzes the collected industrial data to find hidden modes and relations, so that the industrial production process is improved, and the convolutional neural network CNN and the recurrent neural network RNN in the deep learning algorithm are used for integrating and analyzing industrial big data to realize highly-automatic production.
In a preferred embodiment, specifically, the data fusion algorithm adopts a CNN algorithm model and an RNN algorithm model, where the CNN algorithm model is used for filtering, edge detection and blurring industrial data, and the calculation formula is as follows:
y i,j,k ＝∑ m,n,c w m,n,c,k x(i+m),(j+n),c+b k wherein y is i,j,k For the output value of the convolution kernel at the (i, j) position, w m,n,c,k Is the weight of the convolution kernel, x (i+m), (j+n), c is the input data, b k Is the offset; in the pooling operation, in order to improve the robustness and the calculation efficiency of the model, the data output by the convolution layer is compressed, and the calculation formula is as follows:wherein y is i,j,k For values of the pooling layer at the (i, j) position, x (i+m), (j+n), c is the value of the neuron output upstream of the pooling layer; at the full connection layer, the mapping from the input data to the tag is completed, and the calculation formula is as follows: f (x) =wx+b, where f (x) is the output, W is the weight matrix, x is the input vector, and b is the offset;
the RNN algorithm model is used for processing time series data of industrial data, avoiding gradient disappearance during back propagation, and the calculation formula is as follows during state update: h is a t ＝f(W xh x t +W hh x t-1 +b h ) Wherein, h t Is the current state, x t For input of current time step, W xh To input a weight matrix, W hh Is a state weight matrix, b h For the bias vector, f is the activation function; when the state is updated, the output calculation to the current state is performed, and the calculation formula is as follows: y is t ＝f(W hy h t +b y ) Wherein y is t To output vector W hy To output a weight matrix, b y To output a bias vector, f is the activation function.
In a preferred embodiment, the algorithm process of the industrial data processing analysis in the data processing analysis module specifically comprises the following steps:
data preprocessing: the method comprises the preprocessing processes of data cleaning, data sampling, data normalization and abnormal value detection, and is used for removing noise and abnormal values in data and reducing data noise and variance;
feature extraction: extracting valuable features which promote industrial development trend from the data by analyzing the data, wherein the valuable features comprise frequency, amplitude, time domain and frequency domain analysis data; analysis and prediction for later data;
data analysis: analyzing and modeling the data by using various algorithms, including regression analysis, cluster analysis, neural networks, decision trees, and data fusion; for classifying, predicting and optimizing data;
data evaluation: evaluating the result of data analysis, and checking the accuracy and reliability of the model; the evaluation methods include cross-validation, ROC curve, AUC.
Data presentation: and the data analysis results are displayed in a diversified manner in a visual mode, wherein the visual display comprises characters, charts, data reports and dynamic graphics. The processing analysis algorithm is used for comprehensively and deeply analyzing industrial data, extracting valuable features and information, providing data decision support and an optimization scheme for enterprises, and providing a more reliable and accurate basis for future prediction and analysis.
In a preferred embodiment, it is specifically described that the industrial data cloud platform is used for realizing remote monitoring of equipment by accessing the equipment into the network by an industrial user, and the industrial gateway collects data for transmission, and the final information is summarized at the industrial cloud platform end and is used for remote monitoring of industrial equipment; when equipment fails, alarm information is pushed to an equipment manager, and for the failure, the manager of industrial equipment can adjust relevant parameters at an industrial cloud platform end, so that the equipment failure is solved, and the equipment is used for remote debugging of industrial numerical control equipment; the cloud processing and cloud storage industrial gateway collects relevant data on the equipment and is used for providing a data reference basis for upgrading the industrial equipment; and the industrial decision maker is finely managed.
In a preferred embodiment, it is specifically described that the data display feedback module establishes a plurality of visualization models, converts data into a visualization form, interprets the meaning of the data according to elements in the processing data visualization algorithm, and displays the meaning in the form of charts, reports, interactive graphs and animations, so as to help industrial decision makers to better understand the data, find patterns and trends in the data, and make better decisions.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the elements is merely a division of some logic functions, and there may be additional divisions in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention, but to enable any modification, equivalent or improvement to be made without departing from the spirit and principles of the invention.
Claims (10)
1. An industrial data acquisition and processing system based on the internet is characterized in that: the system comprises an industrial data acquisition module, a data transmission module and a data input/output module, wherein the industrial data acquisition module is connected with an industrial numerical control terminal IO interface through a sensor, acquires various data in an industrial environment, uploads the data to an industrial data cloud platform through a 4G/5G wireless network to perform cloud storage and cloud processing, and is connected with the data transmission module through an industrial intelligent gateway to perform data input/output;
the data transmission module is used for receiving the data acquired by the industrial data acquisition module, transmitting the data to the data processing analysis module by utilizing a wireless communication protocol to perform data preprocessing and uploading the data to the industrial data cloud platform to perform data backup;
the real-time monitoring record alarm module is used for monitoring, analyzing and collecting industrial big data in real time and detecting whether the data in the data sources of the industrial data collection module and the data transmission module are consistent or not so as to avoid data collision, repetition and omission;
the data processing analysis module is used for receiving the industrial data transmitted by the data transmission module, establishing a model for calculation, processing and analysis, transmitting the industrial data to the data display feedback module for performing graphic visual signal feedback to a decision maker of industrial management;
the industrial data cloud platform receives and processes industrial data of the industrial data acquisition module, the data transmission module and the data processing and analyzing module through a wireless network, so that the full-flow processing of acquisition, storage, management, analysis and display of the industrial data is realized;
and the data display feedback module displays visual information of industrial collection, processing, analysis and monitoring through a display screen of the computer, and displays the industrial data information in a diversified mode in the form of charts, reports and animations.
2. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the industrial data acquisition module comprises an intelligent sensor acquisition unit, a plurality of intelligent sensors are connected with an industrial intelligent gateway in industrial numerical control equipment, and industrial data information is received, transmitted to the data transmission module through the GPRS transceiver communication unit and uploaded to the industrial data cloud platform;
the GPRS transceiver communication unit adopts an IP data network protocol in a packet switching mode, provides end-to-end wide area wireless IP connection for data information received by the sensor, and is used for converting serial port data into IP data and transmitting the IP data through a wireless communication network;
the AT instruction microcontroller unit is used for executing bidirectional data communication control of the AT instruction through a programmable program of the MCU and is used for confirming data transmission communication;
and the ARM serial port protocol storage unit adopts a data transmission protocol of serial communication, acquires the data received and collected by the intelligent sensor, stores and manages the data, and is used for realizing the mapping from the virtual storage space to the physical storage space.
3. An internet-based industrial data acquisition and processing system according to claim 2, wherein: the AT instruction microcontroller unit comprises an embedded microcontroller, serial port communication, wi-Fi communication, bluetooth communication and a short message communicator; the embedded microcontroller runs a group of AT instruction analysis libraries, is connected with the industrial numerical control equipment through the communicator to perform data interaction and control, and can realize parameter setting and adjustment of the industrial numerical control equipment and inquiry and control of equipment states of the industrial numerical control equipment through AT instructions.
4. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the real-time monitoring record alarm module comprises an intelligent monitoring unit and monitoring software for controlling the industrial data acquisition and transmission process;
the memory recording unit is used for storing historical data through MRU in the computer and can be loaded faster when a subsequent decision maker opens and accesses the data information;
and the detector alarm unit is used for monitoring and alarming the abnormal parameter data of the numerical control equipment in the industrial data by adopting a sensor technology and is used for rapidly finding potential safety hazards in the industrial environment.
5. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the data transmission module comprises a DTU transmission unit, and is used for respectively transmitting data acquired by the intelligent sensor field connection industrial numerical control equipment to the industrial data cloud platform and the data processing analysis module in a wireless and wired mode for further data processing;
and the ARP cache protocol unit adopts a mapping mode to convert an IP logical address into a corresponding NAC physical address and is used for directly transmitting data by combining with the GPRS transceiver communication unit.
6. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the data processing and analyzing module comprises an artificial intelligent algorithm processing unit, and adopts machine learning, integrated learning, data mining, deep learning and natural language processing technologies to simulate, extend and expand intelligent theory and method of people to study industrial big data.
And the data fusion algorithm analysis unit integrates and analyzes the acquired industrial data to find hidden modes and relations, so that the industrial production process is improved.
7. An internet-based industrial data acquisition and processing system according to claim 6, wherein: the data fusion algorithm adopts a CNN algorithm model and an RNN algorithm model, wherein the CNN algorithm model is used for filtering, edge detection and fuzzy processing of industrial data, and the calculation formula is as follows:
y i,j,k ＝∑ m,n,c w m,n,c,k x(i+m),(j+n),c+b k wherein y is i,j,k For the output value of the convolution kernel at the (i, j) position, w m,n,c,k Is the weight of the convolution kernel, x (i+m), (j+n), c is the input data, b k Is the offset; in the pooling operation, in order to improve the robustness and the calculation efficiency of the model, the data output by the convolution layer is compressed, and the calculation formula is as follows:wherein y is i,j,k For values of the pooling layer at the (i, j) position, x (i+m), (j+n), c is the value of the neuron output upstream of the pooling layer; at the full connection layer, the mapping from the input data to the tag is completed, and the calculation formula is as follows: f (x) =wx+b, where f (x) is the output, W is the weight matrix, x is the input vector, and b is the offset;
the RNN algorithm model is used for processing time series data of industrial data, avoiding gradient disappearance during back propagation, and the calculation formula is as follows during state update: h is a t ＝f(W xh x t +W hh x t-1 +b h ) Wherein, h t Is the current state, x t For input of current time step, W xh To input a weight matrix, W hh Is a state weight matrix, b h For the bias vector, f is the activation function; when the state is updated, the output calculation to the current state is performed, and the calculation formula is as follows: y is t ＝f(W hy h t +b y ) Wherein y is t To output vector W hy To output a weight matrix, b y To output a bias vector, f is the activation function.
8. An internet-based industrial data acquisition and processing system according to claim 6, wherein: the algorithm process of the industrial data processing analysis in the data processing analysis module comprises the following steps: data preprocessing, feature extraction, data analysis, data evaluation and data display.
9. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the industrial data cloud platform is used for remotely monitoring industrial equipment, remotely debugging industrial numerical control equipment, providing a data reference basis for upgrading the industrial equipment and carrying out fine management on an industrial decision maker.
10. An internet-based industrial data acquisition and processing system according to claim 1, wherein: the data display feedback module is used for establishing a plurality of visual models, converting the data into a visual form, and displaying the data in the form of a chart, a report, an interactive graph and an animation according to the meaning of the interpretation data of the elements in the processing data visual algorithm.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116846987A (en) * | 2023-09-01 | 2023-10-03 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Interactive interface generation method and system of industrial Internet |
| CN117055470A (en) * | 2023-09-22 | 2023-11-14 | 隆昌精机有限公司 | Intelligent Internet of things docking system applied to numerical control equipment |
| CN117176760A (en) * | 2023-09-28 | 2023-12-05 | 广州鸿蒙信息科技有限公司 | Data transmission equipment and data transmission method thereof |
| CN117411895A (en) * | 2023-12-15 | 2024-01-16 | 武汉海微科技有限公司 | Industrial production detection data processing method, device, equipment and storage medium |
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2023
- 2023-04-26 CN CN202310462792.3A patent/CN116483009A/en not_active Withdrawn
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116846987A (en) * | 2023-09-01 | 2023-10-03 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Interactive interface generation method and system of industrial Internet |
| CN116846987B (en) * | 2023-09-01 | 2023-11-07 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Interactive interface generation method and system of industrial Internet |
| CN117055470A (en) * | 2023-09-22 | 2023-11-14 | 隆昌精机有限公司 | Intelligent Internet of things docking system applied to numerical control equipment |
| CN117176760A (en) * | 2023-09-28 | 2023-12-05 | 广州鸿蒙信息科技有限公司 | Data transmission equipment and data transmission method thereof |
| CN117411895A (en) * | 2023-12-15 | 2024-01-16 | 武汉海微科技有限公司 | Industrial production detection data processing method, device, equipment and storage medium |
| CN117411895B (en) * | 2023-12-15 | 2024-03-29 | 武汉海微科技股份有限公司 | Industrial production detection data processing method, device, equipment and storage medium |
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