CN108594782A - Periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system - Google Patents
Periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system Download PDFInfo
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- CN108594782A CN108594782A CN201810685232.3A CN201810685232A CN108594782A CN 108594782 A CN108594782 A CN 108594782A CN 201810685232 A CN201810685232 A CN 201810685232A CN 108594782 A CN108594782 A CN 108594782A
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- 239000000463 material Substances 0.000 title claims abstract description 25
- 238000000137 annealing Methods 0.000 title claims abstract description 24
- 239000004411 aluminium Substances 0.000 title claims abstract description 20
- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 20
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 20
- 230000000737 periodic effect Effects 0.000 title claims abstract description 20
- 238000004519 manufacturing process Methods 0.000 claims abstract description 30
- 238000002485 combustion reaction Methods 0.000 claims abstract description 14
- 238000004092 self-diagnosis Methods 0.000 claims abstract description 14
- 238000003745 diagnosis Methods 0.000 claims abstract description 8
- 238000010586 diagram Methods 0.000 claims abstract description 3
- 238000012544 monitoring process Methods 0.000 claims abstract 2
- 238000012360 testing method Methods 0.000 claims description 57
- 238000000034 method Methods 0.000 claims description 11
- 238000007689 inspection Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 230000000630 rising effect Effects 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 abstract description 14
- 238000012797 qualification Methods 0.000 abstract description 4
- 238000009472 formulation Methods 0.000 abstract 1
- 239000000203 mixture Substances 0.000 abstract 1
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 18
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 12
- 229910052757 nitrogen Inorganic materials 0.000 description 9
- 239000003345 natural gas Substances 0.000 description 6
- 239000007789 gas Substances 0.000 description 4
- 238000007664 blowing Methods 0.000 description 3
- 238000012790 confirmation Methods 0.000 description 3
- 239000000446 fuel Substances 0.000 description 3
- 238000007789 sealing Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 1
- 206010030973 Oral discomfort Diseases 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 239000000567 combustion gas Substances 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000000178 monomer Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 230000005619 thermoelectricity Effects 0.000 description 1
- 238000010792 warming 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]
- G05B19/4185—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 the network communication
-
- 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
- G05B2219/31088—Network communication between supervisor and cell, machine group
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
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- 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 present invention discloses a kind of periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system, this intelligent self-diagnosing system is mainly used for real-time monitoring and the self diagnosis that circulating fan, combustion system, furnace body air-tightness, fire door and furnace wall temperature rise the single devices such as operating mode.The result of intelligent self-diagnosing can automatically generate the diagnosis report of equipment in the form of curve, table, block diagram and explanatory note etc., and report can export in the form of web pages, and user is facilitated to inquire.It can be very good to understand service condition, formulation maintenance and the maintenance plan of stove by intelligent self-diagnosing report user, track product quality, optimized production process etc. online, to ensure the Homes Using TV of equipment and the qualification rate of production.
Description
Technical field
The present invention relates to periodic aluminium coiled material n 2 annealing stoves, and in particular to is used in periodic aluminium coiled material n 2 annealing stove
The intelligent self-diagnosing system of apparatus for production line belongs to non-ferrous metal heat-processing equipment field.
Background technology
Periodic aluminium coiled material n 2 annealing stove is a kind of aluminium coiled material to be realized that the heat treatment of intermediate annealing or ultimate annealing is set
Standby, it needs engineer by examining or software as traditional Equipment for Heating Processing when breaking down in process of production
The methods of diagnosis goes to inquiry fault point, finds rational solution, formulates time-based maintenance plan.But such production maintenance side
Formula the shortcomings that there are following several respects：1, the uncertainty of fault point is strong；2, the malfunction elimination time is long；3, maintenance work is general
Property；4, standby redundancy is lack of pertinence.These all give the Homes Using TV of production and the qualification rate of product to bring certain influence.
With the development of industry 4.0, intelligence produces and safeguards the trend for having become equipment development.Intelligent self-diagnosing system
System be Reliability Engineering can repair equipment or repairable system use and operational process in focus.In periodic aluminium coiled material nitrogen
Introduce that intelligent self-diagnosing system pair can repair equipment or repairable system is affected very because breaking down in gas annealing furnace
It is arranged to when being unable to normal use or operation, judge to be out of order the as rapidly as possible position of generation, reason, the countermeasure for finding out processing
It applies, by shortening maintenance time, to improve the availability of equipment or system；It can also be by periodical self diagnosis in production come pre-
Anti- care and maintenance saves the cost of standby redundancy to improve the independence of equipment operation rate and maintenance.In addition, system
Self-diagnostic function can also in production real-time adjust automatically and optimization equipment production technology, ensure the quality of product.
Invention content
The present invention is to meet the intelligent production of equipment, overcomes conventional failure to safeguard inefficient disadvantage, provides a kind of satisfaction
The response of periodic aluminium coiled material n 2 annealing stove fault diagnosis is fast, time-based maintenance is with strong points, can improve the intelligence of equipment productivity
Self-diagnosable system can be changed.
The present invention specifically adopts the following technical scheme that：
A kind of periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system, it is characterised in that including：
Electric control system uses the distributed scenes I/O substation collection site sensor signal, processing with PLC cores in order to control
The logic control and operation of equipment carry out operation and parameter management using touch screen as man-machine interface operate interface to equipment；
Host computer stove group management system carries out data exchange by Ethernet and electric control system, monitors and operate each list
Body equipment, production management system and shop floor production control MES system as equipment group carry out data exchange, and provide equipment behaviour
Make the man-machine interface of system；
Shop floor production control MES system carries out data exchange, for stove group by Ethernet and host computer stove group management system
Equipment carries out the production schedule, process management, the tracking of product material information and the report of the intelligent self-diagnosing of inquiry and equipment and looks into
It askes, and self diagnosis report is exported in the form of web pages, facilitate user's far-end operation.
For the present invention based on automation control, combining informationization and intelligence make periodic aluminium coiled material n 2 annealing stove
Production information exported in the form of a web page with self diagnosis result, facilitate user to inquire.User is reported by intelligent self-diagnosing
It can be very good to understand the service condition of stove, formulate maintenance and maintenance plan, track product quality, optimized production process online
Deng to ensure the Homes Using TV of equipment and the qualification rate of production.Conventional failure maintenance mode is transformed into intelligence by the present invention
Self diagnosis mode, failure judgement position is accurate, shortens the period of repair and maintenance, improves the production efficiency of the board.
Description of the drawings
Fig. 1 is host computer key frame figure of the present invention.
Fig. 2 is air tightness test picture figure of the present invention.
Fig. 3 is fan condition test pictures figure of the present invention.
Fig. 4 is burner efficiency test picture figure of the present invention.
Fig. 5 is radiating state picture figure in furnace wall of the present invention.
Fig. 6 is inventive network system layout.
Specific implementation mode
Embodiment 1
The present embodiment is with 36 tons of n 2 annealing stove groups（4 annealing furnaces）For, elaborate periodic aluminium coiled material n 2 annealing stove
The intelligent self-diagnosing system of apparatus for production line.
As shown in fig. 6, electric control system L1 is passed through with the PLC of Siemens CPU 315-2DP cores in order to control
Profibus DP buses connect scene substation ET200M, and fan frequency converter, voltameter, flowmeter etc. turn DP by Modbus and assist
View converter is connected in profibus DP buses, and the sensor signals such as in-site modeling amount, switching value are by live substation ET200M
I/O modules（Input module and output module）Processing, wherein analog signals include mainly：1, millivolt voltage signal furnace wall temperature
Degree, fire box temperature, material temperature etc.；2, actuator, the flow-through orifice differential pressure etc. of 4 ~ 20MA of direct current signals furnace pressure, the pipeline that burns.
Touch screen（TP1200）As the man-machine interface operate interface of electric control system L1, be mainly used for the local operation of equipment with
Parameter management.
Host computer stove group management system L2 passes through Ethernet and electrical control system using wincc v7.4 softwares as programming platform
The L1 that unites carries out data exchange, as the production management system of equipment group, is mainly used for carrying out data exchange with MES system, and
There is provided device operating system friendly man-machine interface, picture management based on dendrogram, including：Custom system management, equipment
Number management, self diagnosis inquire three parts.Custom system manages the management that content is user's operation permission, mainly there is user to log in,
The operations such as user exits, software exits, shuts down；Device number management refers to all operation contents of equipment under the corresponding device number,
Including equipment state, technological parameter, history curve, history table, production operation, attended operation, device parameter, alarm in detail,
And operation air tightness test, fan condition test, burner efficiency test, the furnace wall temperature rising state of intelligent self-diagnosing part
Deng；Self diagnosis inquiry is the map-integrated OA report generated for the result of intelligent self-diagnosing part operation, and user pair can set
Standby inspection result is checked in a manner of reporting, reports result based on three bulks, i.e. air tightness test, fan condition
Test, burner efficiency test, homepage picture are as shown in Figure 1.
Shop floor production control MES system L3 carries out data exchange by Ethernet and host computer stove group management system L2, uses
In being carried out to stove group equipment, the production schedule, process management, product material information tracks and the intelligent autodiagnosis of inquiry and equipment
Disconnected report queries, shop floor production control MES system L3 are searched and are called by specified intelligent self-diagnosing report generation catalogue
Intelligent self-diagnosing is reported, and is exported in the form of web pages in customer side, and user's far-end operation is facilitated.
L1, L2, L3 equipment at different levels are connected to by interchanger D-Link on network.
Periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system is actually to important equipment monomer segment intelligence
Self diagnosis can be changed, include mainly：Air tightness test, fan condition test, burner efficiency test, furnace wall temperature rising state.Rely on PLC
Based on control, the network information turns to platform, and the hand inspection flow of each single devices standard is converted into being examined by program
It looks into, can be periodic test, can also be casual inspection, to reduce the cumbersome of engineer's operation, make maintenance and inspection
It is more convenient to repair.Single devices intelligent self-diagnosing content：
One, air tightness test
Furnace body air tightness test is the self diagnosis carried out to the furnace sealing performance of n 2 annealing stove, by detection device identical
Operating mode and under the conditions of, the variation of furnace pressure, understand furnace sealing behavior pattern.It first has to set the big flow into stove to fill
Furnace pressure desired value when nitrogen（Furnace pressure, which reaches this value, can stop nitrogen charging, while open small flow valve pressurize）, small flow nitrogen
Minimum furnace pressure value when gas pressurize（If there is pressure value is less than this value during small flow valve opens pressurize, then illustrate stove
Body sealing performance is unqualified）, test temperature limitation（This value is the restrictive condition of furnace body air tightness test, just can be with less than this value
Carry out air tightness test）." test starts " button, button virescence are clicked, test starting is tested and run as follows：
" manual confirmation sky oven-like state " --- blocking material temperature thermocouple jack --- " closing fire door " manual system examines automatically
Look into that --- " valve state " ensures that the pipe valve of air blowing is the state --- " open nitrogen large-capacity valve " --- closed
Furnace pressure reaches desired value when big flow inflated with nitrogen --- and " closing large-capacity valve, open small flow valve ", it is small by what is be charged into
Flow nitrogen, to carrying out pressurize in burner hearth --- " record nitrogen flow and furnace pressure state " passes through PLC journeys in small flow pressure maintaining
Sequence captures out the maximum value and minimum value of furnace pressure --- and test terminates, and generates test report.
Minimum furnace pressure when the flow nitrogen pressurize small if there is furnace pressure record value ＜ during the test of furnace body air-tightness
As test failure when setting value, needs to overhaul, and investigates furnace body leakage situation and the measurement situation of furnace pressure sensor.Test
Picture is as shown in Figure 2.
Two, fan condition is tested
Fan condition test is the self diagnosis carried out to wind turbine single devices, by detection device under identical operating mode, wind turbine fortune
Row parameter（Electric current）Variation, understand the operating condition and loading condition of wind turbine.First wind is set before wind turbine starts test
Machine low speed（20Hz）Current reference value and wind turbine high speed（40Hz）Current reference value, offset 10% are clicked " test starts " and are pressed
Button, button virescence, test starting, test are run as follows：
" manual confirmation sky oven-like state " --- " closing fire door " manual system checks automatically --- combustion system starts burner hearth
Be warming up to 200 degree --- confirm furnace temperature be maintained at 200 degree or more, wind turbine low speed 20Hz operate 5 minutes, and it is bent to record wind turbine electric current
Line captures the maximum value and minimum value of blowing machine running current by PLC program --- and wind turbine high speed 40Hz is operated 5 minutes, and
Wind turbine current curve is recorded, the maximum value and minimum value of blowing machine running current are captured by PLC program --- test terminates,
Generate test report.
When wind turbine is during the test if there is then wind of the test current value beyond test current reference value offset ranges
Machine is test failure, needs to overhaul.Test pictures are as shown in Figure 3.
Three, burner efficiency test
Burner efficiency test is the inspection to burner combustion operating mode.Respectively by the orifice plate differential pressure transmitter of combustion-supporting air pipe line and naturally
Combustion air instantaneous flow when the orifice plate differential pressure transmitter of air pipe calculates burner combustion and natural gas instantaneous flow, pass through burning
Mouth efficiency test will be seen that the air of single burner and the ratio of natural gas（And air-fuel ratio）Whether burn in rational range,
To judge whether the stability of burner combustion is good, whether fuel burns fully, whether best, discharge of combustion products is scaling loss
No qualification etc..Being chosen before burner efficiency test needs burner number to be tested, and the burning of two sections of valve positions is detected in burner test process
Mouth operating mode（There is the reference value of corresponding combustion air amount and natural gas tolerance in every section of valve position）, there is correspondence in every section of valve position
The setting of natural gas and combustion air flow reference value and deviation set, these parameters are also required to set before burner test,
" test starts " button, button virescence are clicked, test starting is tested and run as follows：
" manual confirmation sky oven-like state " --- " closing fire door " manual system checks --- combustion system startup --- automatically
Burner is tested in 1 stage of valve position, and combustion-supporting wind flow and gas discharge are shown with block diagram in real time in test process, and record stream
Measure curve（Only shown in report）, capture out combustion air and natural gas respectively by PLC program and flowed in burner test process
The maximum value and minimum value of amount, the state of burner test point are not carried out, are carrying out, success and failure four by text importing
Kind state, test terminates test process 3 minutes --- 2 stage of valve position tests, and logic is tested with 1 stage of valve position ---, generates survey
Examination report.
When tested burner catches fire because failure can not be put（Automatic ignition is three times）, system quotes burner failure, automatically
Next burner is jumped to be tested（Burner test process is number being surveyed one by one by ascending sequence by alternative burner
Examination）, and burner test crash is shown in report, it needs to overhaul.It, can be according to the burner in report when alternative burner is successfully tested
Air-fuel flow when burning, was compared with the combustion air of the corresponding valve setting and gas discharge reference value, if there is wink
Shi Liuliang exceeds the deviation of flow reference value, and test report can then show that combustion air is excessive or insufficient, natural gas is excessive or not
Foot, burner need to optimize.Test pictures are as shown in Figure 4.
Four, furnace wall radiating state
Radiate Diagnosis of Work Conditions for furnace wall, radiates and measures to regions such as furnace wall, fire door, furnace roofs, passes through the thermoelectricity of each region installation of furnace body
Even measuring device measures the furnace wall temperature in each region, and generates temperature curve, records in real time, understands and judge the heat preservation of stove
Performance, thermal losses point position, in time insulating layer of furnace body repair it is kind, to reach extend stove service life and improve stove
The purpose of energy.It is as shown in Figure 5 to diagnose picture.
Claims (7)
1. a kind of periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system, it is characterised in that including：
Electric control system（L1）, with PLC cores in order to control, using the distributed scenes I/O substation collection site sensor signal,
The logic control and operation of processing equipment carry out operation and parametron using touch screen as man-machine interface operate interface to equipment
Reason；
Host computer stove group management system（L2）, pass through Ethernet and electric control system（L1）Carry out data exchange, monitoring and behaviour
Make each single devices, production management system and shop floor production control MES system as equipment group（L3）Data exchange is carried out,
And provide the man-machine interface of device operating system；
Shop floor production control MES system（L3）, pass through Ethernet and host computer stove group management system（L2）Data exchange is carried out, is used
In being carried out to stove group equipment, the production schedule, process management, product material information tracks and the intelligent autodiagnosis of inquiry and equipment
Disconnected report queries, and self diagnosis report is exported in the form of web pages, facilitate user's far-end operation.
2. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as described in claim 1, which is characterized in that factory
Production management MES system（L3）By specified intelligent self-diagnosing report generation catalogue, intelligent self-diagnosing is searched and called
Report.
3. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as described in claim 1, it is characterised in that include
Single devices intelligent self-diagnosing includes mainly：Furnace body air-tightness diagnosis, fan condition diagnosis, burner combustion Diagnosis of Work Conditions and
Radiate Diagnosis of Work Conditions for furnace wall.
4. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as described in claim 1, it is characterised in that with song
The forms such as line, table, block diagram and explanatory note automatically generate the self diagnosis report of equipment.
5. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as described in claim 1, it is characterised in that scene
The spot sensor signal of substation acquisition is uploaded to PLC by profibus DP buses.
6. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as described in claim 1, it is characterised in that upper
Machine stove group management system（L2）The man-machine interface of the device operating system of offer, picture management is based on dendrogram, including using
Family system administration, device number management, self diagnosis inquire three parts.
7. periodic aluminium coiled material n 2 annealing stove intelligent self-diagnosing system as claimed in claim 6, which is characterized in that user
System administration refers to the management of user's operation permission, mainly have user log in, user exits, software exits, power-off operation；Equipment
Number management refers to all operation contents of equipment under the corresponding device number, including equipment state, technological parameter, history curve, is gone through
History table, production operation, attended operation, device parameter, the operation air-tightness of alarm and intelligent self-diagnosing part in detail are surveyed
Examination, fan condition test, burner efficiency test, furnace wall temperature rising state；Self diagnosis inquiry is grasped for intelligent self-diagnosing part
The map-integrated OA report that the result of work generates, user can check the inspection result of equipment in a manner of reporting.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810685232.3A CN108594782B (en) | 2018-06-28 | 2018-06-28 | Intelligent self-diagnosis system of periodic aluminum coiled material nitrogen annealing furnace |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810685232.3A CN108594782B (en) | 2018-06-28 | 2018-06-28 | Intelligent self-diagnosis system of periodic aluminum coiled material nitrogen annealing furnace |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110735029A (en) * | 2019-10-23 | 2020-01-31 | 宁波萨科森工业科技有限公司 | intelligent aluminum foil heat treatment system |
| CN110794737A (en) * | 2019-11-13 | 2020-02-14 | 蚌埠凯盛工程技术有限公司 | Communication control system and control method for photovoltaic rolled glass annealing fan |
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| CN105546572A (en) * | 2016-01-06 | 2016-05-04 | 北京首钢自动化信息技术有限公司 | Automatic control system and method for temperature of combustion section of vertical type annealing furnace |
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| CN107219833A (en) * | 2017-06-20 | 2017-09-29 | 上海第二工业大学 | A kind of cold rolling grinding roller intelligent plant manufacturing monitoring system |
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2018
- 2018-06-28 CN CN201810685232.3A patent/CN108594782B/en active Active
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| JPS6289820A (en) * | 1985-10-14 | 1987-04-24 | Kawasaki Steel Corp | Method for diagnosing apparatus in continuous annealing furnace |
| CN102721288A (en) * | 2012-07-05 | 2012-10-10 | 河北新烨工程技术有限公司 | High-efficiency intelligentized heating furnace control method |
| CN202928762U (en) * | 2012-11-30 | 2013-05-08 | 天津市中环电子计算机有限公司 | Portable tester for automatic quantification measurement of airtightness |
| CN105546572A (en) * | 2016-01-06 | 2016-05-04 | 北京首钢自动化信息技术有限公司 | Automatic control system and method for temperature of combustion section of vertical type annealing furnace |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110735029A (en) * | 2019-10-23 | 2020-01-31 | 宁波萨科森工业科技有限公司 | intelligent aluminum foil heat treatment system |
| CN110794737A (en) * | 2019-11-13 | 2020-02-14 | 蚌埠凯盛工程技术有限公司 | Communication control system and control method for photovoltaic rolled glass annealing fan |
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| Publication number | Publication date |
|---|---|
| CN108594782B (en) | 2023-11-28 |
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