ZA200306520B - Method for controlling and driving a technical process. - Google Patents

Method for controlling and driving a technical process. Download PDF

Info

Publication number
ZA200306520B
ZA200306520B ZA200306520A ZA200306520A ZA200306520B ZA 200306520 B ZA200306520 B ZA 200306520B ZA 200306520 A ZA200306520 A ZA 200306520A ZA 200306520 A ZA200306520 A ZA 200306520A ZA 200306520 B ZA200306520 B ZA 200306520B
Authority
ZA
South Africa
Prior art keywords
model
welding
base
result
parameters
Prior art date
Application number
ZA200306520A
Other languages
English (en)
Inventor
Gaetan Monari
Original Assignee
Usinor
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Usinor filed Critical Usinor
Publication of ZA200306520B publication Critical patent/ZA200306520B/en

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/048Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor

Landscapes

  • Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)
  • Diaphragms For Electromechanical Transducers (AREA)
  • General Factory Administration (AREA)
  • Electrical Discharge Machining, Electrochemical Machining, And Combined Machining (AREA)
  • Crystals, And After-Treatments Of Crystals (AREA)
  • Display Devices Of Pinball Game Machines (AREA)
  • Resistance Welding (AREA)
  • Vehicle Body Suspensions (AREA)
  • Pressure Welding/Diffusion-Bonding (AREA)
ZA200306520A 2001-03-01 2003-08-21 Method for controlling and driving a technical process. ZA200306520B (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
FR0102788A FR2821682B1 (fr) 2001-03-01 2001-03-01 Procede de controle et de commande d'un processus technique

Publications (1)

Publication Number Publication Date
ZA200306520B true ZA200306520B (en) 2004-04-29

Family

ID=8860599

Family Applications (1)

Application Number Title Priority Date Filing Date
ZA200306520A ZA200306520B (en) 2001-03-01 2003-08-21 Method for controlling and driving a technical process.

Country Status (18)

Country Link
US (1) US7127438B2 (de)
EP (1) EP1364258B1 (de)
JP (1) JP2004529416A (de)
KR (1) KR100851932B1 (de)
CN (1) CN1299173C (de)
AT (1) ATE295557T1 (de)
BR (1) BR0207870A (de)
CA (1) CA2438821A1 (de)
DE (1) DE60204122T2 (de)
ES (1) ES2240702T3 (de)
FR (1) FR2821682B1 (de)
MX (1) MXPA03007696A (de)
PL (1) PL364460A1 (de)
PT (1) PT1364258E (de)
RU (1) RU2289837C2 (de)
UA (1) UA74631C2 (de)
WO (1) WO2002071162A1 (de)
ZA (1) ZA200306520B (de)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4150383B2 (ja) 2004-04-13 2008-09-17 新日本製鐵株式会社 スポット溶接部の破断予測装置、方法、コンピュータプログラム、及びコンピュータ読み取り可能な記録媒体
US6961626B1 (en) * 2004-05-28 2005-11-01 Applied Materials, Inc Dynamic offset and feedback threshold
US7096085B2 (en) 2004-05-28 2006-08-22 Applied Materials Process control by distinguishing a white noise component of a process variance
FR2872074B1 (fr) * 2004-06-28 2006-09-29 Peugeot Citroen Automobiles Sa Procede de supervision d'un procede de soudage par resistance et dispositif pour la mise en oeuvre de ce procede
US7244905B2 (en) * 2005-06-09 2007-07-17 Daimlerchrysler Corporation Method for estimating nugget diameter and weld parameters
US8046086B2 (en) * 2007-05-15 2011-10-25 Fisher-Rosemount Systems, Inc. Methods and systems for batch processing and execution in a process system
DE102007045705B4 (de) 2007-09-24 2023-10-19 Volkswagen Ag Verfahren zur Durchführung eines Fügeprozesses in einer Fügevorrichtung
US8706282B2 (en) * 2010-01-12 2014-04-22 Ford Global Technologies, Llc Weldability prediction and recommendation systems and methods
DE102011087958A1 (de) * 2011-12-08 2013-06-13 Kuka Roboter Gmbh Schweißroboter
CN111570973A (zh) * 2013-03-14 2020-08-25 林肯环球股份有限公司 导出或者使用针对外部系统的焊接定序器数据的系统和方法
WO2017010072A1 (ja) * 2015-07-10 2017-01-19 Jfeスチール株式会社 抵抗スポット溶接方法
RU2653286C2 (ru) * 2016-06-10 2018-05-07 ФЕДЕРАЛЬНОЕ ГОСУДАРСТВЕННОЕ КАЗЕННОЕ ВОЕННОЕ ОБРАЗОВАТЕЛЬНОЕ УЧРЕЖДЕНИЕ ВЫСШЕГО ОБРАЗОВАНИЯ "Военная академия Ракетных войск стратегического назначения имени Петра Великого" МИНИСТЕРСТВА ОБОРОНЫ РОССИЙСКОЙ ФЕДЕРАЦИИ Способ прогнозирования кризисных ситуаций при контроле многопараметрических процессов
JP6815764B2 (ja) * 2016-06-28 2021-01-20 株式会社日立製作所 溶接監視システム
JP6572281B2 (ja) * 2017-10-06 2019-09-04 ファナック株式会社 スポット溶接システム
US10926346B2 (en) * 2018-06-20 2021-02-23 Antaya Technologies Corporation Resistance soldering system
DE102019207059A1 (de) * 2019-05-15 2020-11-19 Siemens Aktiengesellschaft Verfahren zur Validierung von Systemparametern eines Energiesystems, Verfahren zum Betrieb eines Energiesystems sowie Energiemanagementsystem für ein Energiesystem
CN110866910B (zh) * 2019-11-13 2022-04-12 上海电气集团股份有限公司 一种焊缝质量预测方法及系统、装置、计算机可存储介质
CN112985318B (zh) * 2019-12-17 2022-11-22 财团法人金属工业研究发展中心 扣件尺寸的线上预测方法与扣件尺寸的线上预测系统
CN114160944B (zh) * 2020-09-11 2023-03-31 宝山钢铁股份有限公司 用于窄搭接电阻焊机的焊缝厚度预测方法
DE102021104540B4 (de) * 2021-02-25 2024-02-29 Audi Aktiengesellschaft Schweißsystem und Verfahren zum Betreiben des Schweißsystems

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0128491B1 (de) * 1983-06-03 1989-12-13 Omron Tateisi Electronics Co. Zeitdiskret selbstanpassender Ein/Aus-Schaltregler
US4861960A (en) * 1988-04-25 1989-08-29 General Electric Company Real time adaptive control for resistance spot welding process
US5353207A (en) * 1992-06-10 1994-10-04 Pavilion Technologies, Inc. Residual activation neural network
JPH0756608A (ja) * 1993-08-17 1995-03-03 Kawasaki Steel Corp 信号処理方法
JP3221296B2 (ja) * 1995-09-29 2001-10-22 松下電器産業株式会社 抵抗溶接の制御装置および制御方法
JP3022488B2 (ja) * 1997-06-04 2000-03-21 社団法人高等技術研究院研究組合 抵抗スポット溶接品質制御装置
JP3588668B2 (ja) * 1997-08-27 2004-11-17 日産自動車株式会社 スポット溶接におけるナゲット径の推定方法
US6018729A (en) * 1997-09-17 2000-01-25 Lockheed Martin Energy Research Corporation Neural network control of spot welding
JP2000056805A (ja) * 1998-08-06 2000-02-25 Hitachi Ltd 予測制御装置
JP2001106703A (ja) * 1999-10-06 2001-04-17 Mitsubishi Rayon Co Ltd 品質予測反応制御システム
WO2002024392A1 (en) * 2000-09-21 2002-03-28 Massachusetts Institute Of Technology Spot welding system and method for sensing welding conditions in real time

Also Published As

Publication number Publication date
FR2821682B1 (fr) 2003-05-30
BR0207870A (pt) 2004-06-22
CN1494667A (zh) 2004-05-05
RU2003129160A (ru) 2005-04-10
EP1364258B1 (de) 2005-05-11
WO2002071162A1 (fr) 2002-09-12
PL364460A1 (en) 2004-12-13
CN1299173C (zh) 2007-02-07
ES2240702T3 (es) 2005-10-16
CA2438821A1 (fr) 2002-09-12
EP1364258A1 (de) 2003-11-26
JP2004529416A (ja) 2004-09-24
US20040073319A1 (en) 2004-04-15
DE60204122T2 (de) 2005-10-06
ATE295557T1 (de) 2005-05-15
PT1364258E (pt) 2005-09-30
MXPA03007696A (es) 2004-03-16
FR2821682A1 (fr) 2002-09-06
KR100851932B1 (ko) 2008-08-12
KR20030084955A (ko) 2003-11-01
UA74631C2 (en) 2006-01-16
US7127438B2 (en) 2006-10-24
DE60204122D1 (de) 2005-06-16
RU2289837C2 (ru) 2006-12-20

Similar Documents

Publication Publication Date Title
ZA200306520B (en) Method for controlling and driving a technical process.
Gundersen et al. The use of an integrated multiple neural network structure for simultaneous prediction of weld shape, mechanical properties, and distortion in 6063-T6 and 6082-T6 aluminium assemblies
Pashazadeh et al. Statistical modeling and optimization of resistance spot welding process parameters using neural networks and multi-objective genetic algorithm
Pal et al. Artificial neural network modeling of weld joint strength prediction of a pulsed metal inert gas welding process using arc signals
US8354608B2 (en) Methods for control of a fusion welding process by maintaining a controlled weld pool volume
CN109472358A (zh) 基于神经网络的焊接工艺参数推荐方法、装置及机器人
EP2423766B1 (de) Analyseverfahren für eine modellprädiktive Steuerungsanwendung
US6518536B2 (en) Joining equipment
Cao et al. Modeling of weld penetration control system in GMAW-P using NARMAX methods
Liu et al. A tutorial on learning human welder's behavior: Sensing, modeling, and control
CN120055614B (zh) 一种用于机床制造的智能化焊接方法
Brdyś et al. Optimal structures for steady-state adaptive optimizing control of large-scale industrial processes
WO2022233991A2 (de) Wärmequellenmodell für ein lichtbogenschmelzschweissverfahren
Di et al. Neural-network-based self-organized fuzzy logic control for arc welding
CN120575112A (zh) 镀锌钢板工艺参数的智能优化方法及系统
Wang et al. Real-time feedback control of penetration stability in al alloy laser welding based on a parallel self-learning fuzzy neural network controller
Casalino et al. Parameter selection by an artificial neural network for a laser bending process
Karsai et al. Neural network methods for the modeling and control of welding processes
JP2005078545A (ja) プロセスモデルの調整方法及び調整装置
JP2020093287A (ja) 抵抗溶接評価装置及び抵抗溶接評価方法
Liu et al. Weld penetration control in gas tungsten arc welding (GTAW) process
Liu et al. Adaptive modeling of the weld pool geometry in gas tungsten arc welding
CN120778032B (zh) 一种非球面光学元件修形的脉冲离子束控制系统及方法
Bestard et al. Automatic Control of the Weld Bead Geometry
Chen et al. Modeling and fuzzy control of the resistance spot welding process