CN117519005A - Workshop equipment data acquisition system based on MES - Google Patents
Workshop equipment data acquisition system based on MES Download PDFInfo
- Publication number
- CN117519005A CN117519005A CN202311385326.6A CN202311385326A CN117519005A CN 117519005 A CN117519005 A CN 117519005A CN 202311385326 A CN202311385326 A CN 202311385326A CN 117519005 A CN117519005 A CN 117519005A
- Authority
- CN
- China
- Prior art keywords
- data
- equipment
- module
- analysis
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 claims abstract description 44
- 238000004458 analytical method Methods 0.000 claims abstract description 36
- 238000004519 manufacturing process Methods 0.000 claims abstract description 35
- 238000005457 optimization Methods 0.000 claims abstract description 33
- 238000000034 method Methods 0.000 claims abstract description 27
- 238000003860 storage Methods 0.000 claims abstract description 27
- 230000008569 process Effects 0.000 claims abstract description 14
- 238000000513 principal component analysis Methods 0.000 claims abstract description 12
- 238000004891 communication Methods 0.000 claims description 23
- 239000011159 matrix material Substances 0.000 claims description 20
- 230000007246 mechanism Effects 0.000 claims description 18
- 238000005265 energy consumption Methods 0.000 claims description 13
- 238000007726 management method Methods 0.000 claims description 10
- 230000007613 environmental effect Effects 0.000 claims description 8
- 238000007619 statistical method Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 3
- 238000013523 data management Methods 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims 8
- 238000013139 quantization Methods 0.000 claims 1
- 238000012423 maintenance Methods 0.000 abstract description 4
- 230000002159 abnormal effect Effects 0.000 abstract description 3
- 206010063385 Intellectualisation Diseases 0.000 abstract description 2
- 238000004590 computer program Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 238000012351 Integrated analysis Methods 0.000 description 5
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 230000009467 reduction Effects 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 239000013598 vector Substances 0.000 description 4
- 230000004075 alteration Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000001816 cooling Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013479 data entry Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31282—Data acquisition, BDE MDE
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention relates to a workshop equipment data acquisition system based on MES, in particular to the field of industrial Internet, which comprises a data acquisition module, a data cloud storage module, a monitoring analysis module, an optimization alarm module and a shared cooperation module, wherein the workshop equipment data is acquired in real time through automatic equipment and sensors, the running state and performance index of the equipment are monitored in real time, the equipment data and production plans and process parameters are associated and analyzed, the digitization and the intellectualization of the production process are realized, the bottleneck and the optimization point in the production process are obtained through the analysis of the equipment data, the production scheduling and the process parameters are optimized, the production efficiency and the quality are improved, the running data of the equipment are monitored by utilizing a principal component analysis algorithm, the abnormal and fault modes of the equipment are identified, maintenance measures are taken in advance, and the equipment downtime and the maintenance cost are reduced.
Description
Technical Field
The invention relates to the field of industrial Internet, in particular to a workshop equipment data acquisition system based on MES.
Background
Currently, the manufacturing industry is faced with global competing challenges and continuous changes in market demands, and with the development of industrial automation and informatization, the automation and intelligent degree of a production workshop is improved, and the production demands cannot be met by the traditional data acquisition mode.
The traditional workshop equipment data has data entry errors and delay risks, errors are easy to occur in the data recording, transmitting and storing processes, follow-up data analysis and decision support are influenced, data traceability optimization is lacked, and production efficiency and quality control are influenced.
The workshop equipment data acquisition system based on the MES is used for acquiring the workshop equipment data in real time through the automatic equipment and the sensor, monitoring the running state and performance index of the equipment in real time, finding out the equipment faults and abnormal conditions in time, acquiring the workshop equipment optimization scheme and the prediction result and feeding back to the equipment control system.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a workshop equipment data acquisition system based on MES, which solves the problems in the background art through a data cloud storage module, a monitoring analysis module and an optimization alarm module.
The technical scheme for solving the technical problems is as follows: the system comprises a data acquisition module, a data cloud storage module, a monitoring analysis module, an optimization alarm module and a sharing cooperation module;
and a data acquisition module: the production workshop data acquisition module is used for acquiring the running state, energy consumption and output of equipment, the temperature and humidity of the equipment in real time, and is integrally connected with the production workshop equipment system, and comprises two subunits of hardware equipment and software programs;
and the data cloud storage module is used for: uploading equipment data to a cloud storage platform, storing the equipment data in a remote server, providing an advanced data management function, and controlling the application range of the data by setting data access rights;
and a monitoring analysis module: the method comprises the steps of constructing a data display, query and analysis platform, realizing monitoring and analysis of real-time data, carrying out trend analysis on provided historical data by utilizing remote access, querying and screening equipment data according to requirements, and obtaining data in a specific time period and data of specific equipment;
and (3) an optimization alarm module: extracting effective information through analysis of historical data for statistical analysis, feeding back an optimization scheme and a prediction result to a device control system through a principal component analysis algorithm, realizing automatic adjustment and optimization, and presetting a threshold to trigger an alarm mechanism;
and a sharing cooperation module: by providing standardized data interfaces, other systems of the exchange integrated production workshop are provided with data sharing and authority management mechanisms, and cooperation between different departments and supply chain links is promoted.
In a preferred embodiment, the data acquisition module acquires the running state, energy consumption, output and equipment temperature and humidity of the equipment in real time, and is integrally connected with a production workshop equipment system, and the data acquisition module comprises two subunits of hardware equipment and software programs:
hardware equipment: the method comprises the steps of installing temperature sensors for measuring equipment and environmental temperature of a production workshop, monitoring equipment heat and cooling effect, installing humidity sensors for measuring humidity levels around the equipment, monitoring working humidity environmental conditions of the production workshop equipment, utilizing data collectors to convert real-time data collected by the sensors into digital signals, utilizing the data collectors to sample analog signals output by the sensors at certain time intervals in the conversion process, quantifying discrete values through analog signal amplitude values, dividing the discrete values into a plurality of intervals through continuous changes, mapping signal amplitude values in each interval into a digital value, encoding the digital signals, converting the digital signals into binary form, transmitting the data to a cloud platform through a data collecting card for storage processing and analysis, wherein the data collecting card is provided with a plurality of input and output channels for connecting the sensors and an actuator, the input channels are responsible for receiving the analog signals of the sensors, the output channels send control signals and the analog signals, are provided with clock signal sources, acquiring sampling time intervals and speed, and configuring a built-in buffer area for temporarily storing the data in the collection process.
Software program: the Modbus serial communication protocol is determined to carry out data transmission and communication through simple command and response message formats, a plurality of physical layer interfaces are utilized to connect equipment data interfaces, including serial interfaces and Ethernet, different communication interfaces are compatible through a gateway, a data acquisition program is developed according to the communication protocol to read equipment running state, energy consumption and output data, communication is carried out, command sending and response receiving are carried out, data acquisition frequency is set, and the time interval for periodically acquiring equipment data is controlled.
In a preferred embodiment, the data cloud storage module invokes the data acquisition module to configure different types and formats of data of the device, provides an authentication mechanism to obtain access tokens and keys by using a cloud data center, provides an API and SDK tool communication data acquisition module to obtain the device to generate data by using a local network connection, provides a highly extensible storage space by using a cloud data center high availability and redundancy backup mechanism, the API invokes to execute different operations by sending requests, including uploading data, querying data and deleting data, the SDK tool encapsulates API call details for simplifying the integration and interaction process with a cloud service, invokes the data cloud storage module to process the data transmission, encapsulates specific formats and transmits the data in parallel in different modes, including HTTP requests, message queues and WebSocket, generates an API key by using a cloud data center management interface and issues application programs and devices needing to access the cloud data center, sends the API requests to sign for proving the identity and legality of the requests, adds time stamps and random number features in communication traffic for verifying the validity of data packets.
In a preferred embodiment, the monitoring analysis module displays a monitoring interface by using a construction platform, displays the state of data through a digital indicator, including the running state, energy consumption, output and temperature and humidity of the device, displays the data change by using a chart form, and the integrated analysis system interface selects different time ranges and data types for analysis, connects a cloud data center to generate reports and indexes for summarizing and summarizing the data, searches the data according to specific conditions, including the time ranges, the device types and the geographic positions, allows a user to screen and sort the data according to specific fields and standards, acquires the historical data of the device by using the cloud data center and the device sensor, calculates the average value of the data in a certain fixed time period by using an average movement algorithm to smooth the data and reveal the trend, the average movement algorithm selects a time window, applies the data sequence of the device to the time window, sequentially slides the window and calculates the average value of the data in each window according to the window size, uses the data points to represent the average value of the data in the time window, and draws the trend of the data intuitively, wherein the specific formula is as follows:
wherein MA represents a moving average, X i And (3) representing the ith data point in the time window, wherein n represents the size of the time window, judging the overall trend of the equipment operation according to the trend of the moving average line, analyzing and displaying equipment problems based on the trend, including equipment performance reduction and fault risk increase, taking corresponding measures to repair the equipment and avoid potential faults, and adjusting a production plan based on the prediction result of the trend analysis.
In a preferred embodiment, the optimization alarm module extracts effective information by analyzing historical data to perform statistical analysis, prepares data to perform workshop original data standardization, calculates covariance matrixes among features according to data sets, reflects correlation among features by using the covariance matrixes, wherein non-diagonal elements represent covariance among two features, diagonal elements represent variance of each feature, decomposes covariance matrix features, is used for obtaining feature values and corresponding feature vectors, selects first k feature vectors as new feature spaces according to the size of the feature values, and is used for realizing dimension reduction of original data, and the principal component analysis comprises standardization, covariance and feature decomposition, wherein the specific formulas are as follows:
C*V＝λ*V
wherein X' represents a normalized data matrix, η n 、σ n Mean and standard deviation of the nth variable, x n Representing the value of the nth observation sample on each variable, C representing the covariance matrix, m representing the number of rows of the data matrix X of the m samples, V representing the eigenvector matrix of the covariance matrix C, lambda representingThe characteristic value of the covariance matrix C, a preset temperature monitoring index and a corresponding threshold value, a normal working temperature range is 20-40 ℃, an alarm is triggered when the set temperature exceeds 40 ℃ and is lower than 20 ℃, the preset humidity monitoring index and the corresponding threshold value, the relative humidity range is 40-60%, the alarm is triggered when the set humidity is lower than 40% and higher than 60%, a monitoring rule is created by combining a cloud data center, a monitoring index and threshold value range optimization scheme is input, and the optimization scheme and a prediction result are fed back to an equipment control system for realizing automatic adjustment and optimization.
In a preferred embodiment, the sharing collaboration module uses industry standard data format and universal data exchange standard to exchange different system information defining data interface input and output parameters, including data field, format and access mode, establishes data sharing mechanism and adopts real-time data transmission and periodical data update, controls authority to different users and roles by setting authority management mechanism, limits access and operation to data, divides different authority levels, including read-only authority, editing authority and management authority, and integrates related workshop departments and equipment to sign data sharing protocol.
In a preferred embodiment, the method specifically comprises the following steps:
101. the method comprises the steps of collecting equipment and production workshop environment information data through various sensors, data collectors and data collecting cards of hardware equipment, determining a communication protocol by utilizing a software program, realizing compatibility of different communication interfaces through a gateway, and acquiring the running state, energy consumption and yield of the equipment;
102. providing a highly extensible storage space by utilizing a cloud data center high-availability and redundant backup mechanism, generating an API key through a cloud data center management interface, and distributing application programs and equipment which need to access the cloud data center;
103. setting up a platform display monitoring interface, displaying the state of data through a digital indicator, selecting different time ranges and data types by an integrated analysis system interface for analysis, calculating the average value of the data in a certain fixed time period by using an average moving algorithm to smooth the data and reveal trends;
104. analyzing historical data, statistically analyzing the extracted effective information, feeding back an optimization scheme and a prediction result to a device control system by utilizing principal component analysis, setting an environmental information data threshold value and creating a monitoring rule by combining with a cloud data center, and realizing automatic adjustment and optimization;
105. the input and output parameters of the data interface are defined by exchanging different system information by utilizing industry standard data formats and common data exchange standards, limiting access and operation to the data, and dividing different authority levels.
The beneficial effects of the invention are as follows: the workshop equipment data acquisition system is used for realizing remote monitoring and control of equipment, correlating and analyzing equipment data with production plans and technological parameters, realizing digitization and intellectualization of a production process, acquiring bottleneck and optimization points in the production process through analysis of the equipment data, optimizing production scheduling and technological parameters, improving production efficiency and quality, monitoring operation data of the equipment by using a principal component analysis algorithm, identifying abnormal and fault modes of the equipment, taking maintenance measures in advance, and reducing equipment downtime and maintenance cost.
Drawings
FIG. 1 is a flow chart of a system of the present invention;
FIG. 2 is a block diagram of the system architecture of the present invention.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In the description of the present application, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the description of the present application, the term "for example" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "for example" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Example 1
The embodiment provides a workshop equipment data acquisition system based on MES as shown in FIG. 1, which specifically comprises the following steps:
101. the method comprises the steps of collecting equipment and production workshop environment information data through various sensors, data collectors and data collecting cards of hardware equipment, determining a communication protocol by utilizing a software program, realizing compatibility of different communication interfaces through a gateway, and acquiring the running state, energy consumption and yield of the equipment;
102. providing a highly extensible storage space by utilizing a cloud data center high-availability and redundant backup mechanism, generating an API key through a cloud data center management interface, and distributing application programs and equipment which need to access the cloud data center;
103. setting up a platform display monitoring interface, displaying the state of data through a digital indicator, selecting different time ranges and data types by an integrated analysis system interface for analysis, calculating the average value of the data in a certain fixed time period by using an average moving algorithm to smooth the data and reveal trends;
104. analyzing historical data, statistically analyzing the extracted effective information, feeding back an optimization scheme and a prediction result to a device control system by utilizing principal component analysis, setting an environmental information data threshold value and creating a monitoring rule by combining with a cloud data center, and realizing automatic adjustment and optimization;
105. the input and output parameters of the data interface are defined by exchanging different system information by utilizing industry standard data formats and common data exchange standards, limiting access and operation to the data, and dividing different authority levels.
Example 2
The embodiment provides a workshop equipment data acquisition system based on MES as shown in fig. 2, which specifically comprises: the system comprises a data acquisition module, a data cloud storage module, a monitoring analysis module, an optimization alarm module and a sharing cooperation module;
and a data acquisition module: the production workshop data acquisition module is used for acquiring the running state, energy consumption and output of equipment, the temperature and humidity of the equipment in real time, and is integrally connected with the production workshop equipment system, and comprises two subunits of hardware equipment and software programs;
and the data cloud storage module is used for: uploading equipment data to a cloud storage platform, storing the equipment data in a remote server, providing an advanced data management function, and controlling the application range of the data by setting data access rights;
and a monitoring analysis module: the method comprises the steps of constructing a data display, query and analysis platform, realizing monitoring and analysis of real-time data, carrying out trend analysis on provided historical data by utilizing remote access, querying and screening equipment data according to requirements, and obtaining data in a specific time period and data of specific equipment;
and (3) an optimization alarm module: extracting effective information through analysis of historical data for statistical analysis, feeding back an optimization scheme and a prediction result to a device control system through a principal component analysis algorithm, realizing automatic adjustment and optimization, and presetting a threshold to trigger an alarm mechanism;
and a sharing cooperation module: by providing a standardized data interface, exchanging other systems of an integrated production workshop, setting a data sharing and authority management mechanism, and promoting cooperative work between different departments and supply chain links;
101. the method comprises the steps of collecting equipment and production workshop environment information data through various sensors, data collectors and data collecting cards of hardware equipment, determining a communication protocol by utilizing a software program, realizing compatibility of different communication interfaces through a gateway, and acquiring the running state, energy consumption and yield of the equipment;
in this embodiment, what needs to be specifically described is a data acquisition module, where the data acquisition module acquires, in real time, an operating state, energy consumption, output, and equipment temperature and humidity of an apparatus, and is integrally connected to a production workshop equipment system, and the data acquisition module includes two subunits including a hardware device and a software program:
hardware equipment: the method comprises the steps of installing temperature sensors for measuring equipment and environmental temperature of a production workshop, monitoring equipment heat and cooling effect, installing humidity sensors for measuring humidity levels around the equipment, monitoring working humidity environmental conditions of the production workshop equipment, utilizing data collectors to convert real-time data collected by the sensors into digital signals, utilizing the data collectors to sample analog signals output by the sensors at certain time intervals in the conversion process, quantifying discrete values through analog signal amplitude values, dividing the discrete values into a plurality of intervals through continuous changes, mapping signal amplitude values in each interval into a digital value, encoding the digital signals, converting the digital signals into binary form, transmitting the data to a cloud platform through a data collecting card for storage processing and analysis, wherein the data collecting card is provided with a plurality of input and output channels for connecting the sensors and an actuator, the input channels are responsible for receiving the analog signals of the sensors, the output channels send control signals and the analog signals, are provided with clock signal sources, acquiring sampling time intervals and speed, and configuring a built-in buffer area for temporarily storing the data in the collection process.
Software program: the Modbus serial communication protocol is determined to carry out data transmission and communication through simple command and response message formats, a plurality of physical layer interfaces are utilized to connect equipment data interfaces, including serial interfaces and Ethernet, different communication interfaces are compatible through a gateway, a data acquisition program is developed according to the communication protocol to read equipment running state, energy consumption and output data, communication is carried out, command sending and response receiving are carried out, data acquisition frequency is set, and the time interval for periodically acquiring equipment data is controlled.
102. Providing a highly extensible storage space by utilizing a cloud data center high-availability and redundant backup mechanism, generating an API key through a cloud data center management interface, and distributing application programs and equipment which need to access the cloud data center;
in this embodiment, a specific need is to specify a data cloud storage module, where the data cloud storage module invokes a data acquisition module to configure data of different types and formats of devices, an authentication mechanism is provided by using a cloud data center to obtain an access token and a key, an AP I and SDK tool communication data acquisition module is provided to obtain the data by using a local network connection to obtain the device, a cloud data center high availability and a redundancy backup mechanism are used to provide a highly extensible storage space, the API call performs different operations by sending a request, including uploading the data, querying the data, deleting the data, the SDK tool encapsulates API call details, is used to simplify an integration and interaction process with a cloud service, invokes the data cloud storage module to process the data transmission, encapsulates a specific format and uses different modes to transmit the data in parallel, including HTTP requests, message queues, webSocket, generates an AP I key by using a cloud data center management interface and issues an application program and a device that need to access the cloud data center, sends an API request to sign, is used to prove the identity and validity of the request, and adds a time stamp and a random number feature in communication traffic, and is used to verify the validity of a data packet.
103. Setting up a platform display monitoring interface, displaying the state of data through a digital indicator, selecting different time ranges and data types by an integrated analysis system interface for analysis, calculating the average value of the data in a certain fixed time period by using an average moving algorithm to smooth the data and reveal trends;
in this embodiment, a specific description is to be provided for a monitoring analysis module, the monitoring analysis module displays a monitoring interface by using a construction platform, displays a data state through a digital indicator, including an operating state of a device, energy consumption, output, and temperature and humidity of the device, displays a data change in a chart form, selects different time ranges and data types for analysis by using an integrated analysis system interface, connects a cloud data center to generate a report and an index for summarizing and summarizing data, searches data according to specific conditions, including a time range, a device category and a geographic position, allows a user to screen and sort the data according to specific fields and standards, acquires historical data of the device by using the cloud data center and a device sensor, calculates an average value of the data in a certain fixed time period by using an average movement algorithm to smooth the data and reveal a trend, selects a time window by using the average movement algorithm, sequentially slides the time window by using a device data sequence according to the window size, and calculates the average value of the data in each window, and intuitively displays the trend of the data in a graph by using the data point to represent the average value of the data in the time window, which is specifically expressed by the formula:
wherein MA represents a moving average, X i And (3) representing the ith data point in the time window, wherein n represents the size of the time window, judging the overall trend of the equipment operation according to the trend of the moving average line, analyzing and displaying equipment problems based on the trend, including equipment performance reduction and fault risk increase, taking corresponding measures to repair the equipment and avoid potential faults, and adjusting a production plan based on the prediction result of the trend analysis.
104. Extracting effective information through analysis of historical data for statistical analysis, feeding back an optimization scheme and a prediction result to an equipment control system through principal component analysis, setting an environmental information data threshold value and creating a monitoring rule by combining a cloud data center, and realizing automatic adjustment and optimization;
in this embodiment, it is specifically to be described that an optimization alarm module performs statistical analysis by analyzing historical data to extract effective information, prepares data for workshop raw data standardization, calculates covariance matrices between features according to data sets, and reflects correlation between features by using the covariance matrices, wherein off-diagonal elements represent covariance between two features, diagonal elements represent variance of each feature, decomposes covariance matrix features, is used for obtaining feature values and corresponding feature vectors, and selects the first k feature vectors as new feature spaces according to the size of the feature values, is used for realizing dimension reduction of the raw data, and the principal component analysis includes standardization, covariance, feature decomposition, and the specific formulas thereof are as follows:
C*V＝λ*V
wherein X' represents a normalized data matrix, η n 、σ n Mean and standard deviation of the nth variable, x n The method comprises the steps of representing the value of an nth observation sample on each variable, wherein C represents a covariance matrix, m represents the number of rows of a data matrix X of m samples, V represents a eigenvector matrix of the covariance matrix C, lambda represents the eigenvalue of the covariance matrix C, presetting a temperature monitoring index and a corresponding threshold value, triggering an alarm when the normal working temperature range is 20-40 ℃, the set temperature exceeds 40 ℃ and is lower than 20 ℃, presetting a humidity monitoring index and a corresponding threshold value, triggering an alarm when the relative humidity range is 40-60%, and the set humidity is lower than 40% and higher than 60%, creating a monitoring rule by combining a cloud data center, inputting the monitoring index and a threshold value range optimization scheme, and feeding the optimization scheme and a prediction result back to an equipment control system for realizing automatic adjustment and optimization.
105. Exchanging different system information defining data interface input and output parameters by utilizing industry standard data format and general data exchange standard, limiting access and operation to data, and dividing different authority levels;
in this embodiment, it is specifically to be described that the shared collaboration module uses industry standard data format and general data exchange standard to exchange input and output parameters of different system information definition data interfaces, including data fields, formats and access modes, establishes a data sharing mechanism, adopts real-time data transmission and regular data update, performs authority control on different users and roles by setting an authority management mechanism, limits access and operation on data, divides different authority levels, including read-only authority, editing authority and management authority, and integrates related workshop departments and equipment to sign a data sharing protocol.
In the foregoing embodiments, the descriptions of the embodiments are focused on, and for those portions of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. The workshop equipment data acquisition system based on the MES is characterized by comprising a data acquisition module, a data cloud storage module, a monitoring analysis module, an optimization alarm module and a sharing cooperation module;
and a data acquisition module: the production workshop data acquisition module is used for acquiring the running state, energy consumption and output of equipment, the temperature and humidity of the equipment in real time, and is integrally connected with the production workshop equipment system, and comprises two subunits of hardware equipment and software programs;
and the data cloud storage module is used for: uploading equipment data to a cloud storage platform, storing the equipment data in a remote server, providing an advanced data management function, and controlling the application range of the data by setting data access rights;
and a monitoring analysis module: the method comprises the steps of constructing a data display, query and analysis platform, realizing monitoring and analysis of real-time data, carrying out trend analysis on provided historical data by utilizing remote access, querying and screening equipment data according to requirements, and obtaining data in a specific time period and data of specific equipment;
and (3) an optimization alarm module: extracting effective information through analysis of historical data for statistical analysis, feeding back an optimization scheme and a prediction result to a device control system through a principal component analysis algorithm, realizing automatic adjustment and optimization, and presetting a threshold to trigger an alarm mechanism;
and a sharing cooperation module: by providing standardized data interfaces, other systems of the exchange integrated production workshop are provided with data sharing and authority management mechanisms, and cooperation between different departments and supply chain links is promoted.
2. The MES-based plant data collection system of claim 1, wherein: the data acquisition module measures equipment environment information data through a hardware sensor, a data acquisition device and a data acquisition card, utilizes an analog-to-digital converter to carry out model signal quantization discrete values, determines a communication protocol through a software program, realizes compatibility of different communication interfaces through a gateway, and is used for acquiring equipment running state, energy consumption and output.
3. The MES-based plant data collection system of claim 1, wherein: the data cloud storage module calls the data acquisition module to configure data of different types and formats of equipment, an authentication mechanism is provided by the cloud data center to acquire an access token and a key, and an API and SDK tool communication data acquisition module is provided.
4. The MES-based plant data collection system of claim 1, wherein: the monitoring analysis module displays a monitoring interface by using a construction platform, displays the state of data through a digital indicator, is connected with a cloud data center to generate a report and indexes for summarizing and summarizing the data, and calculates the average value of the data in a certain fixed time period by using an average movement algorithm to smooth the data and reveal the trend.
5. The MES-based plant data collection system of claim 4, wherein: the average moving algorithm selects a time window, applies a data sequence of equipment to the time window, sequentially slides the window according to the size of the window, calculates the average value of the data in each window, uses the data points to represent the average value of the data in the time window, draws a graph to intuitively display the trend of the data, and has the specific formula as follows:
wherein MA represents a moving average, X i Indicating the ith data point in the time window and n indicates the size of the time window.
6. The MES-based plant data collection system of claim 1, wherein: the optimizing alarm module analyzes historical data, performs statistical analysis on extracted effective information, utilizes a principal component analysis algorithm to reflect correlation among features, presets environment data information monitoring indexes and corresponding thresholds, inputs monitoring indexes and threshold range optimizing schemes, and feeds back the optimizing schemes and predicting results to the equipment control system for realizing automatic adjustment and optimization.
7. The MES-based plant data collection system of claim 6, wherein: the process of monitoring the index and the corresponding threshold value of the preset environmental data information is as follows: the method comprises the steps of presetting a temperature monitoring index and a corresponding threshold, triggering an alarm when the normal working temperature ranges from 20 ℃ to 40 ℃ and the set temperature exceeds 40 ℃ and is lower than 20 ℃, presetting a humidity monitoring index and a corresponding threshold, setting the relative humidity range to be 40% -60%, and triggering an alarm when the set humidity is lower than 40% and higher than 60%.
8. The MES-based plant data collection system of claim 1, wherein: the principal component analysis comprises standardization, covariance and characteristic decomposition, and the specific formulas are as follows:
C*V＝λ*V
wherein X' represents a normalized data matrix, η n 、σ n Mean and standard deviation of the nth variable, x n The value of the nth observation sample on each variable is represented, C represents a covariance matrix, m represents the number of rows of a data matrix X of m samples, V represents a eigenvector matrix of the covariance matrix C, and lambda represents the eigenvalue of the covariance matrix C.
9. The MES-based plant data collection system of claim 1, wherein: the shared collaboration module exchanges input and output parameters of different system information definition data interfaces using industry standard data formats and common data exchange standards, restricts access and operation to data, and divides different permission levels.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311385326.6A CN117519005A (en) | 2023-10-25 | 2023-10-25 | Workshop equipment data acquisition system based on MES |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311385326.6A CN117519005A (en) | 2023-10-25 | 2023-10-25 | Workshop equipment data acquisition system based on MES |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117519005A true CN117519005A (en) | 2024-02-06 |
Family
ID=89744740
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311385326.6A Pending CN117519005A (en) | 2023-10-25 | 2023-10-25 | Workshop equipment data acquisition system based on MES |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117519005A (en) |
-
2023
- 2023-10-25 CN CN202311385326.6A patent/CN117519005A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10656627B2 (en) | Managing big data in process control systems | |
| CN105487500B (en) | Streaming data for analysis in a process control system | |
| US10311015B2 (en) | Distributed big data in a process control system | |
| JP6784595B2 (en) | Distributed big data, process control device, distributed big data support method, process control device in process control system | |
| CN112488558A (en) | Energy consumption monitoring and analyzing system based on industrial internet | |
| CN110430260A (en) | Robot cloud platform based on big data cloud computing support and working method | |
| DE102014103353A1 (en) | Collecting and Providing Data to a Big Data Machine in a Process Control System | |
| CN103941693A (en) | System for intelligently monitoring factory environment quality | |
| CN110995783B (en) | Remote monitoring system | |
| Dhabliya | Delay-tolerant sensor network (DTN) implementation in cloud computing | |
| CN111091240A (en) | Public institution electric power energy efficiency monitoring system and service method | |
| CN117371952B (en) | Multi-project collaborative management system | |
| CN114666224A (en) | Dynamic allocation method, device, equipment and storage medium for business resource capacity | |
| US20240056463A1 (en) | Method and system to detect abnormal message transactions on a network | |
| CN114024801A (en) | Industrial edge computing service gateway | |
| CN112422663B (en) | Data centralization system of industrial Internet of things and data aggregation, processing and storage method | |
| CN105634141A (en) | Power regulation and control information real-time monitoring and security early warning mobile transmission system and method | |
| CN117641157A (en) | Meter reading method of electricity consumption information acquisition terminal | |
| CN117221069A (en) | Management method and device based on micro-server architecture | |
| CN117519005A (en) | Workshop equipment data acquisition system based on MES | |
| CN116260738A (en) | Equipment monitoring method and related equipment | |
| CN116910144A (en) | Computing power network resource center, computing power service system and data processing method | |
| CN114006945A (en) | Intelligent grouping distribution method of Internet of things data and Internet of things platform | |
| CN115118722A (en) | Intelligent water quality monitoring system based on edge calculation | |
| CN117834454B (en) | Internet of things equipment protocol adaptive quick access method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |