CN109966996A - A kind of system using the melting state in big data analysis prediction hot melt adhesive production process - Google Patents
A kind of system using the melting state in big data analysis prediction hot melt adhesive production process Download PDFInfo
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- CN109966996A CN109966996A CN201910142033.2A CN201910142033A CN109966996A CN 109966996 A CN109966996 A CN 109966996A CN 201910142033 A CN201910142033 A CN 201910142033A CN 109966996 A CN109966996 A CN 109966996A
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 29
- 239000004831 Hot glue Substances 0.000 title claims abstract description 28
- 238000002844 melting Methods 0.000 title claims abstract description 22
- 230000008018 melting Effects 0.000 title claims abstract description 22
- 238000007405 data analysis Methods 0.000 title claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 54
- 238000009472 formulation Methods 0.000 claims abstract description 41
- 239000000203 mixture Substances 0.000 claims abstract description 41
- 238000007726 management method Methods 0.000 claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 17
- 238000012545 processing Methods 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims abstract description 7
- 230000002452 interceptive effect Effects 0.000 claims abstract description 5
- 238000005457 optimization Methods 0.000 claims abstract description 5
- 239000002131 composite material Substances 0.000 claims abstract description 4
- 230000005540 biological transmission Effects 0.000 claims description 11
- 238000013500 data storage Methods 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 6
- 239000000155 melt Substances 0.000 claims description 6
- 239000000284 extract Substances 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 4
- 238000005065 mining Methods 0.000 claims description 4
- 238000003756 stirring Methods 0.000 claims description 4
- 239000012895 dilution Substances 0.000 claims description 3
- 238000010790 dilution Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 238000012986 modification Methods 0.000 claims description 3
- 230000004048 modification Effects 0.000 claims description 3
- 238000009825 accumulation Methods 0.000 claims description 2
- 230000003993 interaction Effects 0.000 claims description 2
- 241000208340 Araliaceae Species 0.000 claims 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 claims 1
- 235000003140 Panax quinquefolius Nutrition 0.000 claims 1
- 235000008434 ginseng Nutrition 0.000 claims 1
- 239000000126 substance Substances 0.000 abstract description 3
- 238000013480 data collection Methods 0.000 abstract description 2
- 235000021050 feed intake Nutrition 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012824 chemical production Methods 0.000 description 1
- 230000001427 coherent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 239000012847 fine chemical Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J6/00—Heat treatments such as Calcining; Fusing ; Pyrolysis
- B01J6/005—Fusing
Abstract
The present invention relates to industrial data collections and chemical industry fine processing technique field, especially a kind of system using the melting state in big data analysis prediction hot melt adhesive production process, including data acquisition module, data memory module, formulation management module, analysis engine module, execution module and self-learning module, data acquisition module, data memory module, formulation management module, analysis engine module, there are interactive relations between execution module and self-learning module, data acquisition module, data memory module, analysis engine module, formulation management module, execution module successively interacts, realize the overall process converted from physical state to digital state, data memory module, self-learning module and formulation management module successively interact, it realizes and periodically calculates, optimization of C/C composites parameter, the present invention is extracted valuable by the analysis of big data Data ensure that standard consistency, method of discrimination are that real-time online is run, more time-effectiveness, but also have scalability.
Description
Technical field
The present invention relates to industrial data collection and chemical industry fine processing technique field more particularly to a kind of utilization big datas point
The system of melting state in analysis prediction hot melt adhesive production process.
Background technique
In chemical industry retrofit field, the physical factor for influencing production is numerous and be difficult to finely control, be difficult to realize it is complete from
Dynamicization process, most of is all manual operation, so that the quality and experience of producing line worker is directly concerning the quality of product, and with
The development of society, scientific and technological progress, it is higher and higher to fine chemical product quality requirement, and worker's treatment and welfare require also to get over
Come it is higher, it is increasing so as to cause plant produced pressure, judge that the method for melting state is by producing in producing line at present
Certain several node extracts a small amount of product in the process, artificially two touches three at a glance and takes a sample test mode, which differentiates result directly again
Worker decides, and fine or not superiority and inferiority depends on the experience of worker, great risk is increased in this way for Produce on a large scale, so needing one kind
The system of melting state in good, high-efficient, the versatile big data analysis prediction hot melt adhesive production process of consistency.
Summary of the invention
The purpose of the present invention is to solve the low disadvantage of artificial discriminant approach versatility exists in the prior art, and mention
A kind of system using the melting state in big data analysis prediction hot melt adhesive production process out.
To achieve the goals above, present invention employs following technical solutions:
A kind of system using the melting state in big data analysis prediction hot melt adhesive production process is designed, including data are adopted
Collection module, data memory module, formulation management module, analysis engine module, execution module and self-learning module, the data are adopted
Collect to exist between module, data memory module, formulation management module, analysis engine module, execution module and self-learning module and hand over
Mutual relation, the data acquisition module include PLC module, data processing module and data transmission module, and the PLC module passes through
The hardware corridor of itself is by hot melt adhesive producing line related physical information collection, then by information data transmission to data processing module,
The data processing module easily filtered information data, divide or dilution processing, the data transmission module will be located
The data that information data transmission after reason is brought to data memory module, the data storage module reception acquisition module, are pressed
Certain rule is stored, and the analysis engine module is by calling the formulation parameter of corresponding product in formulation management module to do mould
Shape parameter extracts valuable information to data carry out analysis mining in corresponding data area in data memory module, described to hold
Row module receives the information of analysis engine module, and is converted into the signal that can be performed accordingly, such as prompt text or warning lamp
Signal, the self-learning module are periodically to be optimized according to the data in data storage module to formulation data in formulation management
Modification.
Preferably, the data acquisition module, data memory module, analysis engine module, formulation management module, execution mould
Block successively interacts, and realizes the overall process converted from physical state to digital state.
Preferably, the data memory module, self-learning module and formulation management module successively interact, and realize periodically meter
It calculates, optimization of C/C composites parameter, the data acquisition module, formulation management module application are in hot melt adhesive fine chemistry industry production technology.
Preferably, the data acquisition module, data memory module, formulation management module, analysis engine module, execution mould
Interactive relation between block and self-learning module is mainly used in hot melt adhesive production process, and hot melt adhesive production process includes the
It once feeds intake, melts, feeds intake for the second time for the first time, melt for second, go out the big stage of kettle five, to identical object in different phase
Reason factor does different weight analysis, and main physical factors have weight of material, reactor temperature, reaction kettle vibration, stir current
With accumulation duration, it can guarantee that same producing line produces multiple product and do not interfere with each other by formulation management module, formulation parameter is first
Default default value, periodically optimizes undated parameter subsequently through self-learning module, plays effect more better with effect.
Preferably, in the analysis engine module analysis data procedures, primary focus analysis melts and second for the first time
Data in two stages are melted, corresponding melting status information is timely feedbacked out, identical physical factor is done not in different phase
Then same weight analysis establishes different analysis models, to extract more valuable data.
A kind of system using the melting state in big data analysis prediction hot melt adhesive production process proposed by the present invention, has
Beneficial effect is:
1, the present invention extracts valuable data by the analysis of big data, fundamentally avoids artificial differentiation
The behavior of melting state, ensure that standard consistency；
2, method of discrimination of the invention is real-time online operation, can be according to production process real-time update state, than tradition
Worker's timing sampling observation timeliness is higher；
3, system of the invention can be applied under the scene of same producing line production different product, be convenient for expanding to other lifes very much
In producing line.
Detailed description of the invention
Fig. 1 is proposed by the present invention a kind of to predict that the melting state in hot melt adhesive production process is using big data analysis
System block diagram；
Fig. 2 is proposed by the present invention a kind of to predict that the melting state in hot melt adhesive production process is using big data analysis
The analysis model figure of the engine analysis module of system.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.
Referring to Fig.1-2, a kind of system using the melting state in big data analysis prediction hot melt adhesive production process, including
Data acquisition module, data memory module, formulation management module, analysis engine module, execution module and self-learning module, data
Exist between acquisition module, data memory module, formulation management module, analysis engine module, execution module and self-learning module
Interactive relation, data acquisition module include PLC module, data processing module and data transmission module, and PLC module passes through itself
Hardware corridor is by hot melt adhesive producing line related physical information collection, then by information data transmission to data processing module, at data
Reason module easily filtered information data, is divided or dilution processing, data transmission module general treated information data
It is transferred to data memory module, data storage module receives the data that acquisition module is brought, stored by certain rule.
Analysis engine module is by calling the formulation parameter of corresponding product in formulation management module to do model parameter to data
Data carry out analysis mining in corresponding data area in memory module, extract valuable information, and execution module receives analysis and draws
The information of module is held up, and is converted into the signal that can be performed accordingly, for example prompt text or warning modulating signal, self-learning module are
Modification periodically is optimized to formulation data in formulation management according to the data in data storage module.
Wherein, data acquisition module, data memory module, analysis engine module, formulation management module, execution module be successively
The overall process converted from physical state to digital state, data memory module, self-learning module and formulation management mould are realized in interaction
Block successively interacts, and realizes periodically calculating, optimization of C/C composites parameter, data acquisition module, formulation management module application are in hot melt adhesive essence
Thin chemical production technology, data acquisition module, data memory module, formulation management module, analysis engine module, execution module and
Interactive relation between self-learning module is mainly used in hot melt adhesive production process, and hot melt adhesive production process includes for the first time
Feed intake, melt, feed intake for the second time for the first time, second melting, big stage of kettle five out, in different phase to identical physics because
Element does different weight analysis, and main physical factors have weight of material, reactor temperature, reaction kettle vibration, stir current and tire out
Product duration can guarantee that same producing line produces multiple product and do not interfere with each other by formulation management module, and formulation parameter is first preset
Default value periodically optimizes undated parameter subsequently through self-learning module, plays effect more better with effect, analysis engine module
It analyzes in data procedures, primary focus analysis melts for the first time and second melts data in two stages, timely feedbacks out phase
Status information should be melted, different weight analysis are done to identical physical factor in different phase, then establish different analysis moulds
Type, to extract more valuable data.
Workflow: firstly, what corresponding three physical factors for choosing a kettle in the producing line for having multiple reaction kettles generated
Data are illustrated, and are included the following steps；
S1: M05 reactor temperature in producing line, stirring torque, the production used time three are acquired by PLC hardware module in real time
Principal element data value, the frequency acquired in real time voluntarily determine that acquisition interval is maintained at 15s/ times according to actual needs, should
Step is completed by data acquisition module；
S2: data decimation second stage collected in S1 (melting for the first time) certain rule is stored, is
Subsequent offer is not only valuable but also coherent data, the step are completed by data storage module；
S3: production used time (t) reaches setting duration (T) and triggers analysis engine module afterwards, by calling formulation management module
Formulation parameter (minimum temperature tp, Steady Torque fluctuation range value tn, the torque monitor value tnM, guard time T of interior corresponding product
Deng) parameter logistic of analysis model (see attached drawing 2) is done according to data progress analysis mining, refinement in corresponding data area in memory module
Valuable information out；
As shown in Fig. 2, and time trigger analysis engine module, be for the first time setting duration, behind every 2min timing
Triggering is primary.Every time after triggering, analysis engine module reads in nearest a period of time 5min corresponding data item data as sample,
Again through multi-layer data algorithm process, finally to treated, data carry out respective logic judgement.If meeting condition, analysis is exported
As a result, continuing timing analysis below, until there is the stage of the condition of satisfaction within a certain period of time when being unsatisfactory for.It otherwise, is more than product
It is formulated the guard time of setting, the information of failure can be exported；
S4: execution module receives the information of analysis engine module, and is converted into the information that can be exported by corresponding hardware, such as
HMI pops up " material has melted " prompt text or the glittering amber light of warning lamp etc., while backstage records the complete of event generation
Information.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (5)
1. a kind of system using the melting state in big data analysis prediction hot melt adhesive production process, including data acquisition module
Block, data memory module, formulation management module, analysis engine module, execution module and self-learning module, the data acquisition module
There is interaction between block, data memory module, formulation management module, analysis engine module, execution module and self-learning module to close
System, which is characterized in that the data acquisition module includes PLC module, data processing module and data transmission module, the PLC
Module passes through the hardware corridor of itself by hot melt adhesive producing line related physical information collection, then by information data transmission at data
Module is managed, the data processing module easily filtered information data, is divided or dilution processing, the data transmission mould
Treated information data transmission is arrived data memory module, the number that the data storage module reception acquisition module is brought by block
According to, stored by certain rule, the analysis engine module by call formulation management module in corresponding product formula ginseng
Number does model parameter to data carry out analysis mining in corresponding data area in data memory module, extracts valuable information,
The execution module receives the information of analysis engine module, and is converted into the signal that can be performed accordingly, for example, prompt text or
Warn modulating signal, the self-learning module be periodically according to the data in data storage module to formulation data in formulation management into
Row optimization modification.
2. a kind of melting state using in big data analysis prediction hot melt adhesive production process according to claim 1 is
System, which is characterized in that the data acquisition module, analysis engine module, formulation management module, executes mould at data memory module
Block successively interacts, and realizes the overall process converted from physical state to digital state.
3. a kind of melting state using in big data analysis prediction hot melt adhesive production process according to claim 1 is
System, which is characterized in that the data memory module, self-learning module and formulation management module successively interact, realization periodically calculating,
Optimization of C/C composites parameter, the data acquisition module, formulation management module application are in hot melt adhesive fine chemistry industry production technology.
4. a kind of melting state using in big data analysis prediction hot melt adhesive production process according to claim 1 is
System, which is characterized in that the data acquisition module, formulation management module, analysis engine module, executes mould at data memory module
Interactive relation between block and self-learning module is mainly used in hot melt adhesive production process, and hot melt adhesive production process includes the
It once feeds intake, melts, feeds intake for the second time for the first time, melt for second, go out the big stage of kettle five, to identical object in different phase
Reason factor does different weight analysis, and main physical factors have weight of material, reactor temperature, reaction kettle vibration, stir current
With accumulation duration, it can guarantee that same producing line produces multiple product and do not interfere with each other by formulation management module, formulation parameter is first
Default default value, periodically optimizes undated parameter subsequently through self-learning module, plays effect more better with effect.
5. a kind of melting state using in big data analysis prediction hot melt adhesive production process according to claim 4 is
System, which is characterized in that in the analysis engine module analysis data procedures, primary focus analysis melts for the first time and second molten
Data in two stages are solved, corresponding melting status information is timely feedbacked out, difference is done to identical physical factor in different phase
Then weight analysis establishes different analysis models, to extract more valuable data.
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| CN201910142033.2A CN109966996A (en) | 2019-02-26 | 2019-02-26 | A kind of system using the melting state in big data analysis prediction hot melt adhesive production process |
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| CN201910142033.2A CN109966996A (en) | 2019-02-26 | 2019-02-26 | A kind of system using the melting state in big data analysis prediction hot melt adhesive production process |
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| US10054364B2 (en) * | 2016-02-18 | 2018-08-21 | Leica Biosystems Nussloch Gmbh | Melting apparatus for metered melting of paraffin |
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2019
- 2019-02-26 CN CN201910142033.2A patent/CN109966996A/en active Pending
Patent Citations (11)
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|---|---|---|---|---|
| CN1173542A (en) * | 1997-06-13 | 1998-02-18 | 冶金工业部自动化研究院 | Blast furnace operating consulting system |
| CN1403593A (en) * | 2002-10-17 | 2003-03-19 | 浙江大学 | Blast furnace smelt controlling method with intelligent control system |
| CN1765611A (en) * | 2004-11-12 | 2006-05-03 | 侯金来 | Plastic jetting-moulding machine control device and method |
| CN1605958A (en) * | 2004-11-16 | 2005-04-13 | 冶金自动化研究设计院 | Combined modeling method and system for complex industrial process |
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Application publication date: 20190705 |
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