KR930020299A - 검사 데이터를 평가하기 위한 신호 처리 장치 - Google Patents

검사 데이터를 평가하기 위한 신호 처리 장치 Download PDF

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KR930020299A
KR930020299A KR1019930004406A KR930004406A KR930020299A KR 930020299 A KR930020299 A KR 930020299A KR 1019930004406 A KR1019930004406 A KR 1019930004406A KR 930004406 A KR930004406 A KR 930004406A KR 930020299 A KR930020299 A KR 930020299A
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evaluating
neural network
signal
inspection
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요시히로 마쓰모도
히데노부 고마쓰
가즈히꼬 아오끼
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마노 아쓰시
겐시 넨료오 고오교오 가부시기가이샤
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Publication of KR930020299A publication Critical patent/KR930020299A/ko

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/72—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
    • G01N27/82—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
    • G01N27/90—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws using eddy currents
    • G01N27/9046—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws using eddy currents by analysing electrical signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/72—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
    • G01N27/82—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws
    • G01N27/90—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws using eddy currents
    • G01N27/9046—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables for investigating the presence of flaws using eddy currents by analysing electrical signals
    • G01N27/9053—Compensating for probe to workpiece spacing
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin
    • Y02E30/30—Nuclear fission reactors

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Abstract

탐사장치등에 의하여 얻은 검사 데이터를 자동적으로 고속으로 해석 평가하기 위한 신경회로망 구조의 신호 프로세서를 구비한 신호처리장치.
탐상장치로 부터의 측정신호는 입력 연산장치에서 수치화된 파라미터로 변환 되었고, 이 파라미터는 제1신경회로망에 의하여 결함, 타흔상, 부착물에 대하여 판정된다. 결함이라고 판정된 신호에 대하여는 제2신경회로망으로 결함의 정량평가(원주방향/축방향, 안면/바깥면의 분류, 크기, 깊이 등)을 할 수 있다.
S/N비가 작아서 판정이 곤란한 신호에 대하여는 잡음 분리의 학습을 실시한 제3신경회로망으로 정량평가하게 된다. 제3경 회로망으로 하더라도 판정이 곤란한 경우에는 그레이 신호가 출력된다.

Description

검사 데이터를 평가하기 위한 신호 처리 장치
본 내용은 요부공개 건이므로 전문내용을 수록하지 않았음
제1도는 본 발명의 한 실시예에 의한 신호처리장치의 구성을 나타낸 블럭도.
제2a도는 전진형 신경회로망의 구성을 나타낸 개념도.
제2b도는 마디안의 신호처리의 한 예를 나타낸 모식도.
제3도는 상호 결합형 신경회로망의 구성을 나타낸 개념도.

Claims (3)

  1. 검사 데이터를 평가하기 위한 신호 처리장치에 있어서, 검사장치로 피검사물을 검사하여 얻은 측정시호를 검사장치로부터 수용하는 입력수단과, 이 입력수단에 의하여 수용된 측정신호를 분석하여 피검사물의 결함 및/또는 부착물의 발생상태를 평가하는 평가수단등을 구비한 사실과, 평가수단은 각기 미리 하나 하나에 정하여진 입출력 응답함수를 갖는 여러개의 처리장치와, 이것들 처리 장치에 의하여 여러개의 마디가 형성되도록 처리장치 사이를 미리 정하여진 무게 계수의 전달 특성으로 결합하는 여러개의 접속수단등으로 된 신경회로망 구조의 신호 프로세서 수단을 포함한 사실과, 신호 프로세서 수단은 무게 계수를 접속 수단에 접속된 각 처리장치가 각각의 입력 데이터에 의하여 가장 적합한 출력을 각기 발생하도록 수정하기 위한 학습기능을 구비한 것을 특징으로 하는 감사 데이터를 평가하기 위한 신호 처리장치.
  2. 제1항에 있어서, 신경회로망 구조의 신호 프로세서 수단은 적어도 입력층과 출력층을 구비한 층 구조를 지니고, 입력층내의 각 처리장치와 출력층내의 각 처리장치등의 접속수단으로 결합된 전진형 신경회로망을 구성하고 있음을 특징으로 하는 감사 데이터를 평가하기 위한 신호 처리장치.
  3. 제1항에 있어서, 입력 수단은 검사장치로부터 수용한 측정신호에서 피검사물의 결함 및/ 또는 부착물에 관계하는 인자를 추출하여 신호 프로세서 수단에의 입력 데이터로서 수치화하는 연산 수단을 포함하고 있음을 특징으로 하는 감사 데이터를 평가하기 위한 신호 처리장치.
    ※ 참고사항 : 최초출원 내용에 의하여 공개하는 것임.
KR1019930004406A 1992-03-31 1993-03-22 검사 데이터를 평가하기 위한 신호 처리 장치 KR930020299A (ko)

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JP92-103914 1992-03-31
JP4103914A JPH05281199A (ja) 1992-03-31 1992-03-31 探傷データ評価装置及び方法

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DE (1) DE4310279A1 (ko)
FR (1) FR2689273A1 (ko)

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JPH1021211A (ja) * 1996-06-28 1998-01-23 Taisei Corp ニューラルネットワークおよびコンクリート構造物中の鉄筋腐食の評価方法および予測方法
DE19649563A1 (de) * 1996-11-29 1998-06-04 Alsthom Cge Alcatel Vorrichtung und Verfahren zur automatischen Klassifikation von Objekten
DE19747510A1 (de) * 1997-10-28 1999-05-06 Sican F & E Gmbh Sibet Meßsystem und Verfahren zur Auswertung von Sensorsignalen
US8387444B2 (en) * 2009-11-12 2013-03-05 Westinghouse Electric Company Llc Method of modeling steam generator and processing steam generator tube data of nuclear power plant
JP5562629B2 (ja) 2009-12-22 2014-07-30 三菱重工業株式会社 探傷装置及び探傷方法
FR3015757B1 (fr) * 2013-12-23 2019-05-31 Electricite De France Procede d'estimation quantitative du colmatage des plaques d'un generateur de vapeur
US11615297B2 (en) 2017-04-04 2023-03-28 Hailo Technologies Ltd. Structured weight based sparsity in an artificial neural network compiler
US11551028B2 (en) 2017-04-04 2023-01-10 Hailo Technologies Ltd. Structured weight based sparsity in an artificial neural network
US11544545B2 (en) 2017-04-04 2023-01-03 Hailo Technologies Ltd. Structured activation based sparsity in an artificial neural network
US11238334B2 (en) 2017-04-04 2022-02-01 Hailo Technologies Ltd. System and method of input alignment for efficient vector operations in an artificial neural network
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JP7318402B2 (ja) * 2018-08-02 2023-08-01 東レ株式会社 欠点検査方法および欠点検査装置
JP6950664B2 (ja) * 2018-10-31 2021-10-13 Ｊｆｅスチール株式会社 欠陥判定方法、欠陥判定装置、鋼板の製造方法、欠陥判定モデルの学習方法、及び欠陥判定モデル
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US11237894B1 (en) 2020-09-29 2022-02-01 Hailo Technologies Ltd. Layer control unit instruction addressing safety mechanism in an artificial neural network processor
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JPH0752439B2 (ja) * 1987-10-30 1995-06-05 日本電気株式会社 ダイナミックプログラミング機能を有するニューラルネットワーク
JP2637760B2 (ja) * 1988-03-24 1997-08-06 富士通株式会社 パターン学習・生成方式
JPH0410986A (ja) * 1990-04-27 1992-01-16 Toppan Printing Co Ltd 凹版オフセット印刷用印刷版およびそれを用いた印刷方法

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JPH05281199A (ja) 1993-10-29
FR2689273A1 (fr) 1993-10-01
DE4310279A1 (de) 1993-10-07

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