WO2020250583A1 - Système d'inspection - Google Patents

Système d'inspection Download PDF

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Publication number
WO2020250583A1
WO2020250583A1 PCT/JP2020/017835 JP2020017835W WO2020250583A1 WO 2020250583 A1 WO2020250583 A1 WO 2020250583A1 JP 2020017835 W JP2020017835 W JP 2020017835W WO 2020250583 A1 WO2020250583 A1 WO 2020250583A1
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WO
WIPO (PCT)
Prior art keywords
inspection system
defect
arithmetic unit
threshold value
flaw detection
Prior art date
Application number
PCT/JP2020/017835
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English (en)
Japanese (ja)
Inventor
周平 橋本
Original Assignee
株式会社Ihi
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 株式会社Ihi filed Critical 株式会社Ihi
Publication of WO2020250583A1 publication Critical patent/WO2020250583A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/11—Analysing solids by measuring attenuation of acoustic waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/22—Details, e.g. general constructional or apparatus details
    • G01N29/30—Arrangements for calibrating or comparing, e.g. with standard objects

Definitions

  • the present disclosure relates to an inspection system.
  • the present application claims priority based on Japanese Patent Application No. 2019-108543 filed in Japan on June 11, 2019, the contents of which are incorporated herein by reference.
  • the present disclosure has been made in view of the above-mentioned problems, and an object of the present disclosure is to carry out a non-destructive inspection on a honeycomb structure according to a uniform standard.
  • the inspection system of one aspect of the present disclosure includes a flaw detector for detecting the surface of the honeycomb structure and an arithmetic unit for calculating based on the signal of the flaw detector, and the arithmetic unit is a defect in the honeycomb structure.
  • the presence or absence of a defect is determined based on the defect determination threshold value for determining the presence or absence of a defect.
  • the arithmetic unit plots the signal on a two-dimensional map in which the signal is stored in advance, and the defect discrimination threshold value is represented as a linear or two-dimensional shape on the two-dimensional map. You may.
  • the arithmetic unit may create the two-dimensional map by machine learning a plurality of data acquired by detecting a test piece in advance.
  • the two-dimensional map may be created based on the phase and amplitude of the signal.
  • the flaw detector may generate vibration having a frequency of 1 to 50 kHz.
  • the arithmetic unit may determine the defect position based on the position determination threshold value for determining the defect position in the honeycomb structure.
  • the honeycomb structure is detected by the flaw detector, and the signal of the flaw detector is discriminated by the arithmetic unit based on the defect discrimination threshold value. This makes it possible to perform a homogeneous non-destructive inspection on the honeycomb structure according to a uniform standard.
  • the inspection system S performs non-destructive inspection of the object W.
  • the object W is a honeycomb structure, and a plurality of regular hexagonal cells are formed.
  • the object W is a substantially plate-shaped member in which a carbon fiber reinforced plastic plate is attached to one surface (outer surface W2) and a glass fiber reinforced plastic plate is attached to the other surface (inner surface W1). It is said that. Further, in the object W, the outer surface W2 is close to or joined to another structure, and the object W can be detected only on the inner surface W1.
  • the inspection system S includes a flaw detection device 1, a flaw detection probe 2, an A / D converter 3, and an arithmetic unit 4.
  • the inspection system S detects a defect inside the object W by using the flaw detection device 1 and the flaw detection probe 2.
  • the flaw detection device 1 is a control device that controls the frequency and the like of ultrasonic waves transmitted from the flaw detection probe 2.
  • the flaw detection device 1 sets, for example, the frequency of ultrasonic waves generated from the flaw detection probe 2 to 1 to 50 kHz.
  • the flaw detection probe 2 is a pitch catch probe that integrally includes an oscillator and a receiver.
  • the flaw detection probe 2 generates ultrasonic waves in one direction and receives the reflected ultrasonic waves.
  • the A / D converter 3 converts the analog signal transmitted from the flaw detector 1 into a digital signal and transmits it to the arithmetic unit 4.
  • the arithmetic unit 4 performs arithmetic processing based on the signal acquired from the flaw detector 1 via the A / D converter 3.
  • the arithmetic unit 4 is a computer including, for example, a CPU, a memory, a hard disk, and the like.
  • the arithmetic unit 4 averages the amplitude and phase of the signal acquired from the flaw detection device 1 and records it in a two-dimensional map stored in advance. This two-dimensional map records the average values of the amplitude and phase of the signal obtained by detecting a test piece whose presence or absence of defects is known in advance.
  • the arithmetic unit 4 determines the defect discrimination threshold value by machine learning the average value of the amplitude and phase of the signal acquired at the defective portion by a neural network or the like. As shown in FIG. 2, the average value of the amplitude of the acquired signal differs depending on the position of the inner surface W1 or the outer surface W2 on the two-dimensional map. Specifically, when there is a defect on the outer surface, the amplitude tends to be small, and when there is a defect on the inner surface, the amplitude tends to be large. Based on this, the arithmetic unit 4 determines the position determination threshold value for determining the defect position.
  • the arithmetic unit 4 sets a linear defect discrimination threshold value (linear expression) for discriminating the presence or absence of a defect by machine learning, a defect on the outer surface W2, and a defect on the inner surface W1.
  • the linear position discrimination threshold value (linear expression) for discrimination is stored in advance.
  • the inspection system S performs ultrasonic flaw detection on the inner surface W1 of the object W by the flaw detection device 1 and the flaw detection probe 2 (step S1). At this time, the flaw detection probe 2 generates ultrasonic waves of 1 to 50 kHz and receives the ultrasonic waves reflected by the object W.
  • the inspection system S acquires the signal of the flaw detection device 1 via the A / D converter 3 by the arithmetic unit 4 (step S2). Then, the inspection system S calculates the average value of the amplitude and phase of all the acquired signals by the arithmetic unit 4 (step S3).
  • the inspection system S plots the average value of the acquired signals on the two-dimensional map by the arithmetic unit 4 (step S4). Subsequently, the inspection system S determines the defect based on the position where the average value of the signal is plotted on the two-dimensional map shown in FIG. 2 by the arithmetic unit 4 (step S5). That is, by determining at which position the average value of the above signals is plotted among the three areas divided by the defect discrimination threshold value and the position discrimination threshold value, the presence or absence of a defect, and if there is a defect, the inner surface W1 It is determined which of the outer surface W2 is present.
  • the arithmetic unit 4 can discriminate a defect of the object W of the honeycomb structure from the signal of the flaw detection device 1 based on the defect discrimination threshold value. Therefore, it is possible to perform a homogeneous non-destructive inspection on the object W according to a uniform standard.
  • the arithmetic unit 4 determines and stores the defect discrimination threshold value and the position discrimination threshold value by machine learning. Therefore, it is possible to easily set the defect discrimination threshold value and the position discrimination threshold value for each characteristic of the flaw detection device 1 and the shape and characteristics of the object W.
  • the arithmetic unit 4 plots the signal acquired from the flaw detection device 1 on a two-dimensional two-dimensional map centered on the amplitude and phase. This makes it possible to use both the amplitude data and the phase data as the reference for discrimination.
  • the arithmetic unit 4 can determine the defect position of the honeycomb structure from the signal of the flaw detection device 1 based on the position determination threshold value. Therefore, even when flaw detection is performed from the inner surface W1 of the object W, it is possible to discriminate defects on both the inner surface W1 and the outer surface W2.
  • the pitch catch probe is used as the flaw detection probe 2, but the present disclosure is not limited to this.
  • the flaw detection probe 2 it is possible to use those having various structures according to the shape of the object W.
  • the frequency band of the flaw detection probe 2 is set to 1 to 50 kHz, but the present disclosure is not limited to this. It is also possible to appropriately change the frequency band depending on the shape and material of the object W.
  • This disclosure can be applied to inspection systems.

Abstract

La présente invention concerne un système d'inspection (S) qui comprend : un dispositif de détection de défaut (1) qui détecte un défaut sur une surface d'une structure en nid d'abeilles ; et un dispositif d'opération arithmétique (4) qui effectue une opération arithmétique sur la base d'un signal provenant du dispositif de détection de défaut. Le dispositif d'opération arithmétique détermine la présence/l'absence d'un défaut sur la base d'une valeur de seuil de discrimination de défaut pour discriminer la présence/l'absence du défaut dans la structure en nid d'abeilles.
PCT/JP2020/017835 2019-06-11 2020-04-24 Système d'inspection WO2020250583A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2019-108543 2019-06-11
JP2019108543 2019-06-11

Publications (1)

Publication Number Publication Date
WO2020250583A1 true WO2020250583A1 (fr) 2020-12-17

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ID=73781603

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2020/017835 WO2020250583A1 (fr) 2019-06-11 2020-04-24 Système d'inspection

Country Status (1)

Country Link
WO (1) WO2020250583A1 (fr)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003043016A (ja) * 2001-05-22 2003-02-13 Central Res Inst Of Electric Power Ind 非破壊き裂深さ判定法
JP2013088239A (ja) * 2011-10-17 2013-05-13 Ihi Corp 合成構造体の欠陥面積率算出装置及び欠陥面積率算出方法
JP2017129444A (ja) * 2016-01-20 2017-07-27 株式会社日立パワーソリューションズ 超音波検査方法及び装置
US20170248549A1 (en) * 2016-02-29 2017-08-31 The Boeing Company Method and system for non-destructive testing of composites
JP2018091685A (ja) * 2016-12-01 2018-06-14 国立研究開発法人産業技術総合研究所 検査装置および検査方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003043016A (ja) * 2001-05-22 2003-02-13 Central Res Inst Of Electric Power Ind 非破壊き裂深さ判定法
JP2013088239A (ja) * 2011-10-17 2013-05-13 Ihi Corp 合成構造体の欠陥面積率算出装置及び欠陥面積率算出方法
JP2017129444A (ja) * 2016-01-20 2017-07-27 株式会社日立パワーソリューションズ 超音波検査方法及び装置
US20170248549A1 (en) * 2016-02-29 2017-08-31 The Boeing Company Method and system for non-destructive testing of composites
JP2018091685A (ja) * 2016-12-01 2018-06-14 国立研究開発法人産業技術総合研究所 検査装置および検査方法

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