CN106952032A - A kind of equipment manufacture big data management system - Google Patents
A kind of equipment manufacture big data management system Download PDFInfo
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Abstract
The present invention provides a kind of equipment manufacture big data management system, energy consumption for the energy consumption node to enterprise is managed, including system management module, production monitoring management module, data information management module, accident emergency management module and accident emergency management module.The present invention is analyzed and processed by gathering the multi-energy data of each energy resource consumption node in real time to the multi-energy data of collection, and the prioritization scheme of using energy source is formulated according to energy consumption data, so as to realize the consumption of the reduction energy, avoid the target of waste.
Description
Technical field
The present invention relates to a kind of data management system, and in particular to a kind of equipment manufacture big data management system.
Background technology
With the development and the expansion of manufacturing industry scale of social economy, equipment manufacture is used as national industrialized level and state
The important symbol of border competitiveness, the energy management problem of manufacturing enterprise progressively turns into national development strategy and national long-term interest
Key issue.In recent years, information-based energy management plays more and more important effect in equipment Manufacturing energy conservation.
However, the informationization of energy management at present is primarily directed to business operation aspect, the mass data business produced during this,
In decision-making etc., other links are not utilized effectively, and lack analyzing and diagnosing operation.Under the current big data epoch, traditional energy
Information system management has been subjected to the influence of big data thought, and the decision support based on data analysis incorporates equipment manufacturing
The energy management thought of enterprise, these improve the level of equipment Manufacturing energy management, optimize enterprise's industrial structure, carry
High operating efficiency simultaneously creates the wealth of society.
The content of the invention
For above-mentioned technical problem, the present invention provides a kind of big data in equipment manufacture and effectively managed, with
Ensure that prepare manufacturing enterprise wastes minimum during energy use, cuts operating costs, and then realize that energy-conservation subtracts simultaneously
Row, the target of environmental protection.
The technical solution adopted by the present invention is：
Embodiments of the invention provide a kind of equipment manufacture big data management system, for the energy consumption node to enterprise
Energy consumption is managed, including system management module, production monitoring management module, data information management module, accident emergency
Management module and accident emergency management module, wherein, the system management module includes：Data backup unit, for system
In be used for forecast analysis data backed up；Role-security allocation unit, for distributing authority according to different roles；User
Role's allocation unit, for distributing role for user, make it that the user of each entrance system is owned by the role of oneself；And
Log unit is checked, for providing daily record look facility；The production monitoring management module uses distributed frame, in power consumption section
Point sets data collection station and long-range substation, and the data collection station real-time data collection simultaneously passes back to system by long-range substation
Real-time data base in, including flow network, inductor and Sensor Network are monitored respectively flow network monitoring unit, inductor
Monitoring unit and Sensor Network monitoring unit；The data information management module includes：Energy computation unit, according to production unit,
Product and the aspect of energy consumption equipment three are produced, the consumption of all kinds of energy mediums is provided different in the period of, and can be to energy consumption
Plan information delete accordingly, changes, inquires about work；Editing equipment management unit, the essential information for management equipment
And the corresponding relation set up between measuring equipment；Measuring parameter administrative unit, for increasing, deleting, change, inquiring about metering ginseng
Several essential informations；Production report administrative unit, newly-built, modification for providing form, meets the form lattice required by user
Formula；The accident emergency management module includes：System journal unit；Fault diagnosis alarm unit, it is defeated when system has failure
Go out alarm signal to be alarmed；Failure voice reports unit, and failure alarm signal is exported in the way of voice；Failure emergency plan
Unit, emergent solution is provided for failure；The accident emergency management module includes：Energy consumption query unit makes there is provided the energy
Statistical information, according to production unit, production product, the aspect of energy consumption equipment three, all kinds of energy of statistics are situated between different in the period of
The consumption of matter, and generate corresponding statistical report form；Energy consumption predicting unit, analysis production unit, production product, energy consumption equipment three
All kinds of energy matter plan Expenditure Levels and actual consumption situation of individual aspect, according to different energy consumption prediction algorithm prediction production lists
Position, production product, three aspects of energy consumption equipment to all kinds of energy mediums following different times use Expenditure Levels；Energy matter
Administrative unit is measured, using the statistical analysis technique of big data from the multi-energy data of historical data base extraction process enterprise long term accumulation
Data, finds out the key factor of influence energy, and improvement is optimized to enterprise energy system, promotes recycling for the energy.
Alternatively, the flow network is including the material stream using material as carrier, using the energy as the energy stream of carrier and to believe
Cease the information flow for carrier；The inductor includes being arranged in multiple collecting devices of data collection station, by long-range substation come
It is controlled, the equipment condition information and energy resource consumption information in flow network is gathered by collecting device；The Sensor Network by
The enterprise's basic information system got up by network connection is constituted, for carrying out monitoring in real time to flow network and inductor and from stream
Network and inductor obtain data and data are analyzed, and the result based on data analysis optimizes control to flow network.
Alternatively, multiple dimensioned state monitoring method and/or Ganglia distributed monitoring systems based on big data are realized
Real-time monitoring to flow network and inductor.
Alternatively, the multiple dimensioned state monitoring method based on big data realizes the real-time monitoring to flow network and inductor
Including：
Big data in system is divided into modeling data and Condition Monitoring Data, the side of data modeling or modelling by mechanism is utilized
Method sets up object, the dynamic operation condition benchmark model and steady state condition benchmark model of equipment, and service data then is substituted into above-mentioned two
Individual model, the prediction for obtaining system is exported and compared with actual operating data, is obtained stable state residual error and dynamic residual, is based on afterwards
The thought of Information Granulating, stable state residual error and dynamic residual is divided into the information of different length, and use asynchronous letter to information
Breath fusion obtains merging residual error, and finally by the multiscale analysis to merging residual error, structural regime monitoring signals are excellent to run
Change, Predictive Maintenance provides technical basis.
Alternatively, the real-time monitoring to flow network and inductor is realized based on Ganglia distributed monitoring systems to be included：
One main gmond service, equipment running status information and the energy for gathering each node are set on each energy consumption node
Main gmond services on consumption information, each energy consumption node are in communication with each other, and the gmetad of Ganglia servers collects each section
The information of the main gmond service collections of point, and be stored in database, and be shown by web server.
Alternatively, the accident emergency management module is changed by node state, or refers to preset reference value, to simulation
The output of amount, calculating point, average value, rate of change are scanned and compared, and judge whether state change is abnormal, and alarm signal is pressed
Importance according to failure accident carries out grade classification, if confirming, a certain node exceedes limit value set in advance, is alarmed simultaneously
Display alarm information.
Alternatively, the accident emergency management module is alarmed by voice or film flicker, and provides the place being consistent
Reason measure, and fault message is shown by the color change of graphic monitoring picture, pop-up window and form.
Alternatively, the real-time data base is service-oriented Technical Architecture.
The equipment manufacture big data management system that the present invention is provided has advantages below：Utilization ratio to the energy, disappear
The collection of the information datas such as water consumption is flat, the running status of economic effect, conditions of demand and equipment meets real-time and objectivity
Requirement, energy situation carried out analyze comprehensively, monitored, diagnosis and evaluated, is seamlessly connected with company each information subsystem；Have
Accident analysis ability, fast reaction forms emergency preplan；The load of the forecast analysis energy, consumption；Organically blend distribution system,
Water system, dynamical system, realize programming count and generate the automatic management of form；Adapt to Centralizing inspection, unified allocation of resources
Management needs；The prioritization scheme of using energy source is formulated according to energy consumption data, so as to realize the consumption of the reduction energy, avoid wave
The target taken.
Brief description of the drawings
Fig. 1 is the structural representation of the equipment manufacture big data management system of the present invention.
Embodiment
To make the technical problem to be solved in the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing and tool
Body embodiment is described in detail.
Fig. 1 is the structural representation of the equipment manufacture big data management system of the present invention.As shown in figure 1, the present invention
Equipment manufacture big data management system is used to be managed the energy consumption of the energy consumption node of enterprise, including system administration mould
Block, production monitoring management module, data information management module and accident emergency management module.Each module is introduced below.
<System management module>
System management module includes：Data backup unit, for being backed up to the data in system for forecast analysis；
Role-security allocation unit, for distributing authority according to different roles, obtains system journal, it is ensured that system safety；User angle
Color allocation unit, for distributing role for user, make it that the user of each entrance system is owned by the role of oneself；And look into
Log unit is seen, for providing daily record look facility.The relevant information that system record is logged in and exited every time, saves as a note
Record, and with a unique login ID.System can also record the operational circumstances after User logs in simultaneously.Pass through system operatio
Daily record can inquire about User logs in and operational circumstances, significant for the analysis of causes after system administration, failure etc..
In addition, system management module also includes parameter set unit, system parameter setting includes setting up and maintenance system makes
Basic data, including teams and groups' coding, order of classes or grades at school coding, process section coding, Database Connection Parameters, produces day separation etc.,
And the alarm upper and lower limit of each technological parameter etc..System can set corresponding operating right according to the importance of parameter, only
The user of appropriate level could modify to it.
<Production monitoring management module>
Production monitoring management module uses distributed frame, and data collection station and long-range substation, institute are set in energy dissipation node
State data collection station real-time data collection and passed back to by long-range substation in the real-time data base of system, including respectively to drift net
Flow network monitoring unit, inductor monitoring unit and Sensor Network monitoring unit that network, inductor and Sensor Network are monitored.Sensing
Net is monitored in real time to inductor and flow network, and the real time information collected is passed back to the data center of system, and by being
System carry out the activity such as data analysis and parameter setting, then by Sensor Network come dynamic regulation network state with optimal control drift net
Network, while the quantity of state of Sensor Network and inductor is once again passed in information system, the intelligence of the Highgrade integration so generated
Can energy management information system, the information interaction between support supplier and consumer, reduction energy resource consumption.
The flow network is including the material stream using material as carrier, using the energy as the energy stream of carrier and using information as carrier
Information flow.Specifically, flow network is one group of transmission assembly, these components be connected with each other the continuous material of support (such as water,
Electricity, air) or discrete object (such as equipment, people) movement, be the energy distribution and consumption system core.Flow network is economic work
Dynamic center, the sustainable development of enterprise can be supported by improving its utilization ratio.Flow network should include controller, to support dynamic
Optimization, realizes the change of Convection states.
Equipment Manufacturing energy resource system includes transformation and distribution system, dynamical system, water system, HVAC system and secondary energy
Source distributing system etc., has a flow network of various forms in manufacturing process, and the main energy needed for during this this
Source --- electric power, natural gas and water, steam etc. rely on the carrier network of the various energy, are present in flow network.In plant equipment
, it is necessary to which the flow network of monitoring mainly includes during the manufacturing：Material stream i.e. by carrier of material, using the energy as carrier
Energy stream and using information as the information flow of carrier.
Material stream is the main body being processed in manufacturing process, is the processing implementation process of main matter product, various materials
Flowed along the track of product life cycle.
Energy stream is the driving force of manufacture production process, chemical reaction medium, the performer of thermal medium.Using vapour system as
Example, vapour system flow network is the important support system of enterprise's production process, and optimization enterprise's steam flow network is dynamic flat to realize
Weighing apparatus has higher researching value to machine-building production, energy-conservation.For equipment Manufacturing, carry out scientific and rational steam
Vapour is produced and using analysis, for instructing steam scheduling, reduction to diffuse, the energy being saved, with practical significance.Produce as desired
Steam can both avoid steam production excessive and cause energy waste, and steam can be avoided largely to diffuse and pollute again.
Information flow is then material Flow Behavior, the reflection of energy Flow Behavior and external environment information and artificial adjustment information
Summation, such as market demand, the requirement of client, commodity price, the research and development situation of a certain product.
The inductor includes the multiple collecting devices for being arranged in data collection station, is controlled by long-range substation,
The equipment condition information and energy resource consumption information in flow network are gathered by collecting device.Specifically, inductor be can be by
Remote control can perceive and data reporting object.Inductor is essential in energy demand management, and they can be carried
For the information of energy resource consumption, energy consumption use cost and the influence produced to environment are more intuitively understood.In fact, in order to preferably
Energy demand management is carried out, inductor generally requires to be controlled by remotely.
Enterprise's various information system can gather the situation of material stream, information flow, and pass through intranet and light ether
Net is transferred to data center；Various ammeters, Instrument for Pressure, data acquisition monitoring device, security control facility etc., these constitute dress
The energy resource system inductor of standby manufacturing enterprise.Thus, during enterprise operation, material stream, information flow and the feelings of energy resource consumption
Condition etc. can be induced body-sensing and know, the form that professional and technical personnel or intelligent information system analysis are formed after data processing
Information, identification equipment state, the problems such as judging suspected fault position and nature of trouble；State modulator is carried out, detailed set is formulated
Standby periodical repair plan, makes equipment farthest be repaired in good time, realizes to Energy Saving Control and optimum management, has given play to optimal warp
Ji benefit simultaneously ensures safety in production.
The Sensor Network is made up of the enterprise's basic information system got up by network connection, for flow network and sensing
Body carries out monitoring in real time and obtains data from flow network and inductor and data are analyzed, the result pair based on data analysis
Flow network optimizes control, and material stream, energy stream and the information flow of primary convective network are monitored on-line, for material
Stream, by monitoring the information systems such as ERP, MES, follows the trail of material change, different traffic programs is taken, to reach the mesh of energy-saving and emission-reduction
's；For energy stream, for Administrative Area, using automated intelligent control technology, to avoid energy waste；For producing region,
The integrated information fed back according to office's energy management information system, the reasonably optimizing production schedule, to reach the target of energy-saving and emission-reduction；It is right
In information flow, periodically look back the granularity of information gathering, carry out cost accounting, to reach the section of maximum with minimum Technical investment
Can effect.
Specifically, Sensor Network can be made up of the equipment for being dispersed in different location, can report the state or environment bar of object
Part, such as temperature, composition of air, the position and speed information of mobile object.Information system by analyze Sensor Network provide data,
Determine the prioritization scheme of flow network.In equipment Manufacturing, ERP, MES, PCS, equipment are automatically controlled etc. by enterprise by optical fiber
Industry basic information system is connected, and forms Sensor Network, flow network and inductor are monitored in real time.Sensor Network enters to data
Row is obtained, stores and analyzed, and the gathered data of passback is analyzed and processed by data center, is always remained at the use for ensuring the energy
Efficient state.According to investigations, fuel energy is the main energy sources of equipment Manufacturing consumption, averagely account for that the energy uses 60% with
On, use data back to data center it by Sensor Network, analyzed with reference to other information system data, according to circumstances
Adjustment provisioning policy, and carry out remote control to it in time, both improves handling, considerable energy-saving benefit is brought again.
The real-time monitoring in point location is performed to flow networks such as water pipe, electric wire, natural gas lines respectively, returned data is analyzed, judges pipeline
Whether there is leakage phenomenon, periodic maintenance is changed to real-time monitoring, pinpoints the problems and corrects in time.So, the energy is both improved
Utilization rate, has reached the Ecological Target of energy information again, while optimizing the Distribution utilization of the equipment Manufacturing energy.
The present invention can be based on big data multiple dimensioned state monitoring method and/or Ganglia distributed monitoring systems come real
Now to the real-time monitoring of flow network and inductor.
Wherein, the multiple dimensioned state monitoring method based on big data realizes the real-time monitoring bag to flow network and inductor
Include：
Big data in system is divided into modeling data and Condition Monitoring Data, the side of data modeling or modelling by mechanism is utilized
Method sets up object, the dynamic operation condition benchmark model and steady state condition benchmark model of equipment, and service data then is substituted into above-mentioned two
Individual model, the prediction for obtaining system is exported and compared with actual operating data, is obtained stable state residual error and dynamic residual, is based on afterwards
The thought of Information Granulating, stable state residual error and dynamic residual is divided into the information of different length, and use asynchronous letter to information
Breath fusion obtains merging residual error, and finally by the multiscale analysis to merging residual error, structural regime monitoring signals are excellent to run
Change, Predictive Maintenance provides technical basis.
The real-time monitoring to flow network and inductor is realized based on Ganglia distributed monitoring systems to be included：Each
One main gmond service is set on energy consumption node, equipment running status information and energy resource consumption letter for gathering each node
Main gmond services on breath, each energy consumption node are in communication with each other, and the gmetad of Ganglia servers collects the master of each node
The information of gmond service collections, and be stored in database, and be shown by web server.The present invention utilizes Ganglia
It is more convenient intuitively to check each node related service volume real-time running state to collect indicator-specific statistics data.
<Data information management module>
Data information management module, including energy computation unit, measuring parameter administrative unit and production report administrative unit.
Wherein, energy computation unit is according to production unit, production product and the aspect of energy consumption equipment three, advises different in the period of
The consumption of fixed all kinds of energy mediums, and energy consumption plan information can be carried out deleting accordingly, change, inquire about work.
Editing equipment management unit is used for the essential information and the corresponding relation between foundation and measuring equipment of management equipment,
Including device name, model, the purchase date, manufacturer, power consumption species, input power, power output, equipment state, use list
The increase of the essential informations such as position, operator, remarks, deletion, modification, inquiry；Measuring parameter administrative unit, for increasing, deleting,
Modification, the essential information of inquiry measuring parameter, essential information include measuring parameter title, parameter physical significance, measurement type, institute
Belong to unit, remarks etc.；Production report administrative unit, newly-built, modification for providing form, meets the form lattice required by user
Formula.Realize from different data sources and read report data, and report data is handled.Applicable report output is provided to represent
Mode, realizes the printout function of form.
<Accident emergency management module>
Accident emergency management module, including：System journal unit, for preserving system journal；Fault diagnosis alarm unit,
When system has failure, output alarm signal is alarmed；Failure voice reports unit, and failure report is exported in the way of voice
Alert signal；Failure emergency plan unit, emergent solution is provided for failure.Accident emergency management module is become by node state
Change, or refer to preset reference value, output, calculating point to the industrial data collected, i.e. analog quantity, average value, change speed
Rate, which is scanned, to be compared, and judges whether state change is abnormal, and alarm signal is carried out into rank point according to the importance of failure accident
Class, if confirming, a certain node exceedes limit value set in advance, and progress is alarmed and display alarm information.Voice or picture can be passed through
Flicker is alarmed, and provides the treatment measures being consistent, and passes through the color change of graphic monitoring picture, pop-up window and table
Case form shows fault message.
<Energy basic management module>
Energy basic management module, including：Energy consumption query unit, energy forecast unit and energy quality administrative unit.
Wherein, energy consumption query unit provides the statistical information that the energy is used, and is set according to production unit, production product, energy consumption
Standby three aspect, the consumption of all kinds of energy mediums of statistics different in the period of, and corresponding statistical report form is generated, with energy consumption system
Meter and energy-saving analysis and energy cost analysis and forecast function.
Wherein, in terms of the effect of energy energy consumption statistic and examination is according to examination unit, examination product, energy consumption equipment three,
Different period (moon/season/year or production cycle) counts the consumption of all kinds of energy mediums, and generates corresponding statistical report form and enter
Row examination, including examination unit (nonproductive unit) energy consumption statistic and examination, examination product energy consumption statistics examination and energy consumption equipment
Energy consumption statistic and examination.
(1) examination unit (nonproductive unit) energy consumption statistic and examination：To each examination unit measurement all kinds of energy of meter
The energy consumption of medium, (moon, season, year) consumption is counted respectively in units of the time, is generated actual consumption, is formed form；With determining
Volume energy consumption is compared, generation examination bar chart.(2) examination product energy consumption statistics examination：To examination product according to production week
Phase, count actual production, actual all kinds of energy medium consumption respectively in units of case and counted respectively, generate actual consumption,
Form form；It is compared with quota energy consumption, generation examination bar chart.(3) energy consumption equipment energy consumption statistic and examination：To each
Energy consumption equipment measure all kinds of energy mediums of meter energy consumption, in units of the time (moon, season, year, production cycle) carry out respectively
Statistics, generates actual consumption, forms form；It is compared with quota energy consumption, generation examination bar chart.The effect of energy-saving analysis
It is, according to examination unit, examination product, three aspects of energy consumption equipment, to analyze it and determine than amount of energy saving, determine than fractional energy savings, year-on-year energy-conservation
Amount, the situation of year-on-year fractional energy savings.Specific analytical method includes：
Determine than amount of energy saving=(actual volume of consumption per unit product-quota unit consumption) * outputs of current period；
Determine than fractional energy savings=(actual volume of consumption per unit product-quota unit consumption)/actual volume of consumption per unit product；
Year-on-year amount of energy saving=(actual volume of consumption per unit product-last issue actual volume of consumption per unit product) * outputs of current period；
Year-on-year fractional energy savings=(actual volume of consumption per unit product-last issue actual volume of consumption per unit product)/actual volume of consumption per unit product；
Energy Efficiency Ratio=power output/input power of energy conversion equipment.
(1) unit (nonproductive unit) energy-saving analysis is examined：Each examination unit is surveyed according to above-mentioned Analysis Method of Saving Energy
The consumption calculations analysis of all kinds of energy mediums of scale meter.
(2) product energy-saving analysis is examined：According to above-mentioned Analysis Method of Saving Energy to each examination all kinds of energy medium of product
Consumption calculations are analyzed.
(3) energy consumption equipment energy-saving analysis：All kinds of energy of meter are measured to each energy consumption equipment according to above-mentioned Analysis Method of Saving Energy
The consumption calculations analysis of source medium., for all kinds of energy medium Expenditure Levels of energy consumption equipment, it can be pressed with computing device Energy Efficiency Ratio
According to different computational methods, (various energy inputs convert into standard coal summation with exporting the ratio value-based algorithm of emphasis equipment, the various energy
Input and the ratio value-based algorithm of output emphasis equipment) calculate Energy Efficiency Ratio.
The effect of energy cost analysis is that analysis is with for the moment according to examination unit, examination product, the aspect of energy consumption equipment three
Phase and the consumption of different times (moon/season/year or production cycle) all kinds of energy mediums, and generate corresponding pie chart, block diagram or
Curve map.
(1) unit source cost analysis is examined：Analyze contemporaneity, the same various all kinds of energy medium consumption of examination unit
Situation (is converted into standard coal), uses histogram graph representation.Analyze different times, the same various all kinds of energy medium consumption of examination unit
Situation, is represented with broken line graph, and analyzes its trend.
(2) examination product energy cost analysis：Analyze contemporaneity, identical product (case) energy (water, electricity, coal, gas, vapour)
Unit consumption situation (is converted into standard coal), uses histogram graph representation.Analyze different times, all kinds of energy medium unit consumption of identical product (case)
Situation, is represented with broken line graph, and analyzes its trend.
(3) energy consumption equipment energy cost is analyzed：Analyze contemporaneity, the same various all kinds of energy medium consumption of energy consumption equipment
Situation (is converted into standard coal), uses histogram graph representation.Analyze different times, the same various all kinds of energy medium consumption of energy consumption equipment
Situation, is represented with broken line graph, and analyzes its trend.
Energy consumption predicting unit is by analyzing production unit, production product, based on all kinds of energy matter of three aspects of energy consumption equipment
Expenditure Levels and actual consumption situation are drawn, production unit, production product, energy consumption equipment are predicted according to different energy consumption prediction algorithms
Three aspects to all kinds of energy mediums following different times use Expenditure Levels；The effect of energy consumption prediction is that analysis examination is single
Position, examination product, all kinds of energy medium plan Expenditure Levels of three aspects of energy consumption equipment and actual consumption situation, according to difference
Energy consumption prediction algorithm (gray prediction, neural network prediction, time series forecasting), prediction examination unit, examination product, energy consumption
Use Expenditure Levels of three aspects of equipment to the following different times of all kinds of energy mediums.
(1) specific energy consumption forecast analysis is examined：It is each to each examination unit measurement meter according to above-mentioned energy consumption Forecasting Methodology
The consumption of class energy medium is predicted analysis.
(2) product energy consumption forecast analysis is examined：Each all kinds of energy of examination product is situated between according to above-mentioned energy consumption Forecasting Methodology
The consumption of matter is predicted analysis.
(3) energy consumption equipment energy consumption forecast analysis：It is each to each energy consumption equipment measurement meter according to above-mentioned energy consumption Forecasting Methodology
The consumption of class energy medium is predicted analysis.
Energy quality administrative unit, it is long-term from historical data base extraction process enterprise using the statistical analysis technique of big data
The multi-energy data data of accumulation, finds out the key factor of influence energy, and improvement is optimized to enterprise energy system, promotes the energy
Recycle.
In the present invention, service-oriented Technical Architecture (Service-Oriented can be used in the real-time data base
Architecture, SOA).The present invention is classified to data, is cleaned, exchanged and shared using service-oriented Technical Architecture,
And flexible loose couplings serviced component is abstracted into, according to data flow and business rule, by operation flow, by service application point
Solution is into separate unit component, data package of the secondary encapsulation into standard.So as to provide high flexible, it is configurable managed
, be easy to extension multi-energy data Governance framework.Basic step is as follows：
(1) determine and understand data flow and business demand, carry out relative role distribution；
(2) understand operation flow, according to serviced component and business demand processing data, resolve into business unit (business section
Point), the dependence between node is determined, critical path is generated；
(3) according to critical path by each service node composition function unit, with reference to general service component and normal data mould
Type, is packaged into business-driven service component；
(4) interpolation data stream and business demand processing schedule job in Autosys job scheduling frameworks.
In addition, the present invention also can realize data management using magnanimity sensing data management system.Magnanimity sensing data pipe
Reason system, by database deployment beyond the clouds, the data that thousands of sensor is sent can be obtained simultaneously, carry out storage tube
Reason.User need to only have a computer or mobile device that can be surfed the Net, it is possible to be linked into calculating central database, monitoring is passed
Sensor.The alarm threshold value set according to user is monitored incoming data by data center, if it exceeds warning line, it will send report
Mobile terminal of the alert message to user.Meanwhile, user can be in any place any time by monitoring the situation of sensor.
The above is the preferred embodiment of the present invention, it is noted that for those skilled in the art
For, on the premise of principle of the present invention is not departed from, some improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (8)
1. a kind of equipment manufacture big data management system, it is characterised in that the energy consumption for the energy consumption node to enterprise
It is managed, including system management module, production monitoring management module, data information management module, accident emergency management module
With accident emergency management module,
Wherein, the system management module includes：Data backup unit, for being carried out to the data in system for forecast analysis
Backup；Role-security allocation unit, for distributing authority according to different roles；User role allocation unit, for for user
Role is distributed, make it that the user of each entrance system is owned by the role of oneself；And log unit is checked, for providing day
Will look facility；
The production monitoring management module uses distributed frame, and data collection station and long-range substation, institute are set in energy dissipation node
State data collection station real-time data collection and passed back to by long-range substation in the real-time data base of system, including respectively to drift net
Flow network monitoring unit, inductor monitoring unit and Sensor Network monitoring unit that network, inductor and Sensor Network are monitored；
The data information management module includes：Energy computation unit, according to production unit, production product and energy consumption equipment tripartite
Face, the consumption of all kinds of energy mediums is provided different in the period of, and energy consumption plan information can be carried out deleting accordingly,
Modification, inquiry work；Editing equipment management unit, essential information and pair between foundation and measuring equipment for management equipment
It should be related to；Measuring parameter administrative unit, the essential information for increasing, deleting, change, inquiring about measuring parameter；Production report pipe
Unit is managed, newly-built, modification for providing form meet the statement form required by user；
The accident emergency management module includes：System journal unit；Fault diagnosis alarm unit, when there is failure in system,
Output alarm signal is alarmed；Failure voice reports unit, and failure alarm signal is exported in the way of voice；Failure answers quick-acting prescription
Case unit, emergent solution is provided for failure；
The accident emergency management module includes：Energy consumption query unit is single according to production there is provided the statistical information that the energy is used
Position, production product, the aspect of energy consumption equipment three, the consumption of all kinds of energy mediums of statistics different in the period of, and generate corresponding
Statistical report form；Energy consumption predicting unit, analysis production unit, production product, all kinds of energy matter plans of three aspects of energy consumption equipment
Expenditure Levels and actual consumption situation, production unit, production product, energy consumption equipment three are predicted according to different energy consumption prediction algorithms
Individual aspect to all kinds of energy mediums following different times use Expenditure Levels；Energy quality administrative unit, utilizes big data
Statistical analysis technique from the multi-energy data data of historical data base extraction process enterprise long term accumulation, find out influence can pass
Key factor, improvement is optimized to enterprise energy system, promotes recycling for the energy.
2. equipment manufacture big data management system according to claim 1, it is characterised in that the flow network include with
Material is the material stream of carrier, using the energy as the energy stream of carrier and using information as the information flow of carrier；
The inductor includes the multiple collecting devices for being arranged in data collection station, is controlled, passed through by long-range substation
Collecting device gathers the equipment condition information and energy resource consumption information in flow network；
The Sensor Network is made up of the enterprise's basic information system got up by network connection, for entering to flow network and inductor
Row monitoring in real time simultaneously obtains data from flow network and inductor and data is analyzed, and the result based on data analysis is to drift net
Network optimizes control.
3. equipment manufacture big data management system according to claim 2, it is characterised in that many chis based on big data
State monitoring method and/or Ganglia distributed monitoring systems is spent to realize the real-time monitoring to flow network and inductor.
4. equipment manufacture big data management system according to claim 3, it is characterised in that many chis based on big data
Degree state monitoring method includes to realize the real-time monitoring to flow network and inductor：
Big data in system is divided into modeling data and Condition Monitoring Data, built using the method for data modeling or modelling by mechanism
Vertical object, the dynamic operation condition benchmark model and steady state condition benchmark model of equipment, then substitute into above-mentioned two mould by service data
Type, the prediction for obtaining system is exported and compared with actual operating data, stable state residual error and dynamic residual is obtained, afterwards based on information
The thought of granulation, is divided into the information of different length, and information is melted using asynchronous information by stable state residual error and dynamic residual
Conjunction obtains merging residual error, and finally by the multiscale analysis to merging residual error, structural regime monitoring signals are running optimizatin, pre-
Know that maintenance provides technical basis.
5. equipment manufacture big data management system according to claim 3, it is characterised in that based on Ganglia distributions
Formula monitoring system includes to realize the real-time monitoring to flow network and inductor：
One main gmond service is set on each energy consumption node, for gather each node equipment running status information and
Main gmond services on energy resource consumption information, each energy consumption node are in communication with each other, and the gmetad of Ganglia servers collects often
The information of the main gmond service collections of individual node, and be stored in database, and be shown by web server.
6. the equipment manufacture big data management system according to claim 4 or 5, it is characterised in that the accident emergency
Management module is changed by node state, or refers to preset reference value, output, calculating point to analog quantity, average value, change
Speed, which is scanned, to be compared, and judges whether state change is abnormal, and alarm signal is carried out into rank according to the importance of failure accident
Classification, if confirming, a certain node exceedes limit value set in advance, and progress is alarmed and display alarm information.
7. equipment manufacture big data management system according to claim 6, it is characterised in that the accident emergency management
Module is alarmed by voice or film flicker, and provides the treatment measures being consistent, and passes through the face of graphic monitoring picture
Color change, pop-up window and form show fault message.
8. equipment manufacture big data management system according to claim 1, it is characterised in that the real-time data base is
Service-oriented Technical Architecture.
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| CN109840713A (en) * | 2019-02-19 | 2019-06-04 | 保定智通自动化技术有限公司 | Integrated lean production system |
| CN109918817B (en) * | 2019-03-13 | 2023-04-14 | 安徽海螺集团有限责任公司 | Production line energy consumption analysis method based on time-varying data |
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| CN112904749A (en) * | 2019-12-04 | 2021-06-04 | 国网江苏省电力有限公司电力科学研究院 | Comprehensive energy information acquisition and monitoring system and method based on ubiquitous Internet of things |
| CN112270458A (en) * | 2020-09-15 | 2021-01-26 | 广东韶钢松山股份有限公司 | Energy refined management and control method and device, computer equipment and storage medium |
| CN113282658A (en) * | 2021-07-26 | 2021-08-20 | 深圳百胜扬工业电子商务平台发展有限公司 | Working quality assessment data processing method and device, storage medium and electronic equipment |
| CN114002965B (en) * | 2021-10-12 | 2023-03-24 | 红石阳光（北京）科技股份有限公司 | Intelligent building's property management system based on thing networking |
| CN114002965A (en) * | 2021-10-12 | 2022-02-01 | 红石阳光（北京）科技股份有限公司 | Intelligent building's property management system based on thing networking |
| CN115097797A (en) * | 2022-07-21 | 2022-09-23 | 南京科控奇智能科技有限公司 | Distributed energy cloud management and control system based on internet |
| CN115293466A (en) * | 2022-10-09 | 2022-11-04 | 工业云制造(四川)创新中心有限公司 | Cloud manufacturing method and system for manufacturing nodes through virtual intelligent configuration based on cloud |
| CN116645234A (en) * | 2023-05-24 | 2023-08-25 | 中南大学 | Equipment manufacturing equipment management system based on meta universe |
| CN117666519A (en) * | 2024-02-01 | 2024-03-08 | 博诚经纬软件科技有限公司 | MES intelligent manufacturing management method and system based on big data |
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