JP7438382B2 - 電気化学電池、特に燃料電池のバイポーラプレートを検査するための方法および検査装置 - Google Patents
電気化学電池、特に燃料電池のバイポーラプレートを検査するための方法および検査装置 Download PDFInfo
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Description
12 マッピング
14 バイポーラプレート
16 一方のカテゴリ
18 他方のカテゴリ
20 ニューラルネットワーク
22 詳細検査
24 検査装置
26 カメラ
28 起こり得る欠陥
Claims (10)
- 電気化学電池のバイポーラプレートを検査するための方法であって、バイポーラプレート(14)の表面のマッピング(12)が作成され、
前記マッピング(12)は、起こり得る欠陥(28)について自動画像処理支援評価システムによって試験され、
前記評価システムが、試験されたバイポーラプレート(14)を潜在的欠陥を含む可能性があるプレートとして識別した場合、前記潜在的欠陥を含む可能性があるプレートの、潜在的欠陥として識別された領域の詳細検査(22)が実施され、
前記評価システムは、潜在的欠陥を含む可能性があるプレートを識別するために、非欠陥バイポーラプレート(14)および欠陥バイポーラプレート(14)から作成されるバイポーラプレート(14)の複数のマッピング(12)に基づいて訓練されるニューラルネットワーク(20)を有し、
前記ニューラルネットワーク(20)は、前記詳細検査(22)の結果を用いて継続的に訓練され、前記ニューラルネットワーク(20)は、強化学習を実施する、方法。 - 前記詳細検査(22)において、少なくとも1つの非破壊検査は、前記潜在的欠陥を含む可能性があるプレートについて、前記潜在的欠陥として識別された領域で実施される、請求項1に記載の方法。
- 非破壊検査として、浸透探傷試験および/または磁粉探傷試験および/または超音波検査および/または放射線透過検査および/または渦電流試験は、前記潜在的欠陥を含む可能性があるプレートについて、前記潜在的欠陥として識別された領域で実施される、請求項2に記載の方法。
- 前記バイポーラプレート(14)を製造するために、2枚以上のシートメタルの溶接が行われ、前記溶接中、前記溶接時に発生する溶接シームの複数のマッピング(12)が作成され、評価される、請求項1から3のいずれか一項に記載の方法。
- 前記バイポーラプレート(14)を製造するために、前記溶接後、前記溶接シーム全体のマッピング(12)が作成され、評価される、請求項4に記載の方法。
- 前記評価システムによる前記評価の結果を用いて、前記溶接のプロセス制御の適合が行われる、請求項4または5に記載の方法。
- 請求項1から6のいずれか一項に記載の方法を実施するための検査装置であって、
前記バイポーラプレート(14)の表面の少なくとも1つのマッピング(12)を作成するためのカメラ(26)と、
起こり得る欠陥(28)について前記マッピング(12)を試験するための自動画像処理支援評価システムと、
前記評価システムによって潜在的欠陥を含む可能性があるプレートとして識別されたバイポーラプレートを詳細検査ステーションに誘導するための、前記評価システムによって操作可能な切替器と、を備え、
前記評価システムは、潜在的欠陥を含む可能性があるプレートを識別するために、非欠陥バイポーラプレート(14)および欠陥バイポーラプレート(14)から作成されるバイポーラプレート(14)の複数のマッピング(12)に基づいて訓練されるニューラルネットワーク(20)を有し、前記評価システムは、前記詳細検査(22)の結果を保存するための、前記ニューラルネットワーク(20)と連結された、前記詳細検査ステーションと通信するインターフェースを、前記詳細検査(22)の前記結果を用いる前記ニューラルネットワーク(20)の継続訓練の目的で有する、検査装置。 - 評価ユニットは、前記バイポーラプレート(14)を製造するための少なくとも1つの生産ユニットと連結可能な少なくとも1つの出力ポートを、前記評価システムによる評価の結果に応じて、前記生産ユニットのプロセス制御を適合するために有することを特徴とする、請求項7に記載の検査装置。
- 前記少なくとも1つの生産ユニットは、溶接装置および/または打ち抜き装置および/または成形装置であることを特徴とする、請求項8に記載の検査装置。
- 前記詳細検査ステーションは、前記潜在的欠陥を含む可能性があるプレートの非破壊検査のための、少なくとも1つの検査機器を有することを特徴とする、請求項7から9のいずれか一項に記載の検査装置。
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DE102020107779.3A DE102020107779A1 (de) | 2020-03-20 | 2020-03-20 | Verfahren und Prüfanlage zum Prüfen einer Bipolarplatte einer Brennstoffzelle |
DE102020107779.3 | 2020-03-20 | ||
PCT/DE2021/100195 WO2021185404A1 (de) | 2020-03-20 | 2021-02-26 | Verfahren und prüfanlage zum prüfen einer bipolarplatte einer elektrochemischen zelle, insbesondere einer brennstoffzelle |
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CN114267844B (zh) * | 2021-11-09 | 2024-02-27 | 深圳市氢瑞燃料电池科技有限公司 | 一种燃料电池极板生产的系统与方法 |
KR20230110189A (ko) * | 2022-01-14 | 2023-07-21 | 주식회사 엘지에너지솔루션 | 모니터링 장치 및 그것의 동작 방법 |
CN114577816A (zh) * | 2022-01-18 | 2022-06-03 | 广州超音速自动化科技股份有限公司 | 一种氢燃料双极板检测方法 |
DE102022109188B3 (de) | 2022-04-14 | 2023-08-03 | Schaeffler Technologies AG & Co. KG | Brennstoffzellenstapel und Verfahren zur Montage eines Brennstoffzellenstapels |
WO2024049194A1 (ko) * | 2022-08-31 | 2024-03-07 | 주식회사 엘지에너지솔루션 | 인공지능 모델 기반의 이상 진단 방법, 이를 이용한 이상 진단 장치 및 공장 모니터링 시스템 |
CN118130487B (zh) * | 2024-05-06 | 2024-07-26 | 同创兴业(天津)模架有限公司 | 一种基于脚手架的焊接检测方法及系统 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2000285934A (ja) | 1999-03-31 | 2000-10-13 | Toshiba Corp | 燃料電池、その製造方法およびその検査方法 |
JP2007018176A (ja) | 2005-07-06 | 2007-01-25 | Sharp Corp | 学習装置、学習方法、学習プログラム、記録媒体、パターン認識装置およびパターン認識方法 |
JP2007178384A (ja) | 2005-12-28 | 2007-07-12 | Aichi Mach Ind Co Ltd | 検査装置および検査方法 |
JP2013167596A (ja) | 2012-02-17 | 2013-08-29 | Honda Motor Co Ltd | 欠陥検査装置、欠陥検査方法及びプログラム |
JP2015138745A (ja) | 2014-01-24 | 2015-07-30 | 日産自動車株式会社 | 燃料電池の製造方法 |
JP2018192524A (ja) | 2017-05-12 | 2018-12-06 | 株式会社神戸製鋼所 | 自動溶接システム、溶接制御方法、及び機械学習モデル |
Family Cites Families (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE3809221A1 (de) | 1988-03-18 | 1989-09-28 | Roth Electric Gmbh | Verfahren zum detektieren von fehlstellen an pressteilen oder anderen werkstuecken und vorrichtung zur durchfuehrung des verfahrens |
JP2968442B2 (ja) * | 1994-09-26 | 1999-10-25 | 川崎重工業株式会社 | 溶接欠陥の評価システム |
US7179553B2 (en) | 2002-09-06 | 2007-02-20 | General Motors Corporation | Method for detecting electrical defects in membrane electrode assemblies |
DE102009059765A1 (de) | 2009-12-21 | 2011-06-22 | Daimler AG, 70327 | Verfahren zur Herstellung einer Bipolarplatte |
US9784625B2 (en) | 2010-11-30 | 2017-10-10 | Bloom Energy Corporation | Flaw detection method and apparatus for fuel cell components |
CN104833925A (zh) * | 2015-05-07 | 2015-08-12 | 昆山弗尔赛能源有限公司 | 一种基于机器视觉的燃料电池双极板检测方法及系统 |
DE102015221697B3 (de) | 2015-11-05 | 2017-02-23 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Anordnung zur Bestimmung der Oberflächenbeschaffenheit von Bauteiloberflächen |
DE102016211449A1 (de) | 2016-06-27 | 2017-12-28 | Bayerische Motoren Werke Aktiengesellschaft | Prüfsystem und Verfahren zum Prüfen von Bauteilen |
WO2018132321A1 (en) * | 2017-01-10 | 2018-07-19 | Kla-Tencor Corporation | Diagnostic methods for the classifiers and the defects captured by optical tools |
US10809635B2 (en) * | 2017-11-20 | 2020-10-20 | Taiwan Semiconductor Manufacturing Company, Ltd. | Defect inspection method and defect inspection system |
CN108320278A (zh) * | 2018-01-09 | 2018-07-24 | 北京百度网讯科技有限公司 | 产品缺陷检测定位方法、装置、设备及计算机可读介质 |
US11069030B2 (en) * | 2018-03-22 | 2021-07-20 | Adobe, Inc. | Aesthetics-guided image enhancement |
JP6990610B2 (ja) | 2018-03-23 | 2022-02-03 | 本田技研工業株式会社 | 燃料電池の電流リーク検査方法 |
CN108631727B (zh) * | 2018-03-26 | 2019-08-09 | 河北工业大学 | 一种基于卷积神经网络的太阳能电池板缺陷识别方法 |
US10769770B2 (en) * | 2018-05-07 | 2020-09-08 | Cummins Enterprise Llc | Quality monitoring system and quality monitoring method for fuel cell manufacturing line and quality monitoring system for manufacturing line |
DE102018214307A1 (de) * | 2018-08-23 | 2020-02-27 | Friedrich-Alexander-Universität Erlangen-Nürnberg | System und Verfahren zur Qualitätsprüfung bei der Herstellung von Einzelteilen |
CN109598721B (zh) * | 2018-12-10 | 2021-08-31 | 广州市易鸿智能装备有限公司 | 电池极片的缺陷检测方法、装置、检测设备和存储介质 |
CN110132237A (zh) * | 2019-05-05 | 2019-08-16 | 四川省地质工程勘察院 | 一种城市地面变形灾害早期识别的方法 |
CN110473806A (zh) * | 2019-07-13 | 2019-11-19 | 河北工业大学 | 光伏电池分拣的深度学习识别与控制方法及装置 |
-
2020
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-
2021
- 2021-02-26 JP JP2022550973A patent/JP7438382B2/ja active Active
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Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2000285934A (ja) | 1999-03-31 | 2000-10-13 | Toshiba Corp | 燃料電池、その製造方法およびその検査方法 |
JP2007018176A (ja) | 2005-07-06 | 2007-01-25 | Sharp Corp | 学習装置、学習方法、学習プログラム、記録媒体、パターン認識装置およびパターン認識方法 |
JP2007178384A (ja) | 2005-12-28 | 2007-07-12 | Aichi Mach Ind Co Ltd | 検査装置および検査方法 |
JP2013167596A (ja) | 2012-02-17 | 2013-08-29 | Honda Motor Co Ltd | 欠陥検査装置、欠陥検査方法及びプログラム |
JP2015138745A (ja) | 2014-01-24 | 2015-07-30 | 日産自動車株式会社 | 燃料電池の製造方法 |
JP2018192524A (ja) | 2017-05-12 | 2018-12-06 | 株式会社神戸製鋼所 | 自動溶接システム、溶接制御方法、及び機械学習モデル |
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