WO2006022568A1 - Procede permettant de determiner la defectuosite initiale et residuelle d'un article, la probabilite de detection de defauts et la qualite d'un article sur la base de composants de certitude et de probabilite d'une defectuosite residuelle - Google Patents

Procede permettant de determiner la defectuosite initiale et residuelle d'un article, la probabilite de detection de defauts et la qualite d'un article sur la base de composants de certitude et de probabilite d'une defectuosite residuelle Download PDF

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Publication number
WO2006022568A1
WO2006022568A1 PCT/RU2004/000317 RU2004000317W WO2006022568A1 WO 2006022568 A1 WO2006022568 A1 WO 2006022568A1 RU 2004000317 W RU2004000317 W RU 2004000317W WO 2006022568 A1 WO2006022568 A1 WO 2006022568A1
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Prior art keywords
defects
defect
product
dimensions
ucx
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PCT/RU2004/000317
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English (en)
Russian (ru)
Inventor
Alexandr Fedorovich Getmann
Nikolay Andreevich Mahutov
Alexander Alexeevich Tutunov
Vladimir Nikolaevich Lovchev
Dmitry Fedorovich Gucev
Yuri Grigorievich Dragunov
Yuri Alexandrovich Kurakov
Alexander Stepanovich Zubchenko
Mikhail Vladimirovich Grigoriev
Inna Vasilievna Kaliberda
Anatoly Vladimirovich Prosvirin
Yuri Viktorovich Konev
Gennady Samoylovich Vasilchenko
Vlada Alexandrovna Getman
Boris Ivanovich Lukasevich
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Zao 'koordinacionny Centr Po Nadeznosty, Bezopasnosty I Resursu Oborudovania I Truboprovodam Atomnyh Stancy'
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Priority to PCT/RU2004/000317 priority Critical patent/WO2006022568A1/fr
Publication of WO2006022568A1 publication Critical patent/WO2006022568A1/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
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4445—Classification of defects
    • 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
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4472—Mathematical theories or simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/26—Scanned objects
    • G01N2291/263—Surfaces
    • G01N2291/2634—Surfaces cylindrical from outside

Definitions

  • the invention relates to the field of non-destructive testing (hereinafter referred to as HK) of discontinuities, inhomogeneities and other defects in the material of a product or a group of products (parts, structural elements, etc.) including ultrasonic, eddy current, radiographic and other HK methods.
  • HK non-destructive testing
  • the invention can be used in assessing the quality, reliability and safety of a product based on HK results, evaluating the suitability of HK tools and methods, the adequacy of the qualifications of HK operators, and organizing product control during operation and / or manufacture.
  • HK responsible products are carried out after manufacture, before operation and during operation. It is assumed that as a result of HK, all defects that are available for detection by this control method are detected. All discontinuities, inhomogeneities, and the like anomalies of the metal, if they exceed the permissible sizes, are classified as defects and are eliminated by repair. It is believed that after HK and repair of the detected defects there are no other defects in the product (see, for example, “Equipment and pipelines of nuclear power plants. Welded joints and surfacing. Control rules)), PHAEG-7-010-89, Gosatomnadzor of Russia, Energoatomizdat , 1991). The same practice has developed in other countries.
  • the known methods do not provide complete identification of defects and does not allow the assessment of defects missed during inspection, which negatively affects the reliability and performance of the product.
  • a known method for determining the defectiveness of the product in which the initial defectiveness of the product is determined, and the parameters measured during the control are selected from the condition of ensuring the maximum possible reliability of control by reducing the likelihood of making an erroneous decision (USSR Author's Certificate N ° 1406888, 1995)
  • the technical result to which this invention is directed is that it allows one to evaluate the actual defectiveness of the product both before the inspection and after the inspection and repair of the detected defects, and to establish the boundary between the sizes of defects that reliably exist in the product (their probability existence is equal to 1), and the size of the defects that may or may not be in the product (the probability of their existence is less than 1).
  • the technical result also consists in the fact that due to the knowledge of the initial (before inspection) and residual (after inspection and repair of identified defects) defects in the product, the accuracy of the assessment of the real state of the product increases, it becomes possible to operate it reliably and safely, and it is possible to more accurately judge the acceptability or other HK methods, product manufacturing process quality.
  • the problem is solved in that in the method for determining the defectiveness of the product, including the manufacture of a test sample designed to determine the characteristics of non-destructive testing of discontinuities in the material of the product, control of this test sample by the method of non-destructive testing, which is used to judge the reliability of the control, and control products that are produced by the same method as the control of the test sample, the test sample is made in the form of the product or its most critical part from the same material and for that the same technology as the product, with defects located at random with different characteristic sizes ⁇ , the reliability of the control is defined as the probability of detecting defects P water ( ⁇ ):
  • N Hall is the number of defects inherent in the manufacture of the sample; when testing the product, the control results are presented in the form of a histogram in the coordinates ( ⁇ , N o in n U30 ), where N o in n uzo is the number of defects of a given size detected during the control of the product; the curve is determined initial defectiveness N ucx :
  • N ucx ( ⁇ ) N obd ( ⁇ ) IP water ( ⁇ ), repair the detected defects and determine the residual defectiveness N ocm as the difference between N ucx and N obn uzd , and the test sample contains three groups of defects: defects whose dimensions lie in the range from the dimensions of defects admissible during operation to the dimensions critical for the product in operation; defects, the sizes of which lie in the range from the sizes allowed during the manufacture of the product to the sizes of defects allowed during operation; defects, sizes of them lie in the range from the sizes minimally available for detecting defects to the sizes of defects acceptable during manufacture, the first two types of defects mimic defects of an operational nature, and the third type mimic technological defects, residual defects
  • N b, f i c ⁇ in the field of defects important to safety is determined as the number of defects in the product whose dimensions are equal to or greater than the critical dimensions ⁇ ⁇ in the product's operating mode: litis / L _ f detoxu ( ⁇ '
  • Xcr residual defectiveness N £ mLe in the region of defects important for reliability is determined as the number of defects whose dimensions exceed the dimensions of the defects [ xx. E. maximum permissible in the operation of the product: ;
  • the linear size of the defect is chosen as the characteristic size ⁇ of the defect.
  • Xo is the minimum defect size available for detection
  • the initial defect N ucx is determined by the formula:
  • residual defectiveness N 0 ⁇ 100 in the area of defects important for reliability is determined as the number of defects whose dimensions exceed the dimensions of the defects [ ⁇ ] ⁇ .e , the maximum allowable in operation of the product: residual imperfection N ⁇ 11 113 , in the region of defects determining the workmanship, in the form of the number of defects whose dimensions exceed the dimensions [ ⁇ ⁇ uzg of the discontinuities allowed in the manufacture: where ⁇ front - the maximum possible characteristic size of the defect, t - the number of similar products.
  • the linear size of the defect is chosen as the characteristic size ⁇ of the defect.
  • the minimum defect size Xo available for detection is determined when setting up the flaw detector used to inspect the product, or as the minimum defect size that was detected during inspection.
  • the constant ⁇ is taken equal to 0.
  • n-sLt.besop 5 residual defectiveness N ⁇ m d :) in the region of defects important for reliability is determined as the number of defects whose dimensions exceed the dimensions of the defects [ ⁇ ] ⁇ b .
  • maximum permissible in the operation of the product residual imperfection N ⁇ m u ⁇ in the region of defects determining the quality of manufacture, in the form of the number of defects whose dimensions exceed the dimensions [ ⁇ ] u ⁇ of the discontinuities allowed in the manufacture:
  • Ni er - ⁇ N oc ⁇ z) d ⁇
  • ⁇ rep. is the maximum possible characteristic size of the defect
  • t is the number of products of the same type
  • the residual defect is divided into the reliable part ⁇ ⁇ ⁇
  • the probabilistic part ⁇ > f ⁇ where ⁇ is the characteristic size of the defect, f ⁇ is the size of the defects at the boundary between the reliable and probabilistic parts, determined from: ⁇ max
  • the linear size of the defect is chosen as the characteristic size ⁇ of the defect.
  • the histogram (N Obn , ⁇ ) is approximated by the equation
  • Xo is the minimum defect size that can be detected
  • Co., 1 "0" P) exp [ -or ( ⁇ - Z 0 )] ⁇ ⁇ .
  • the semi-axis of the ellipse which schematize the defect, is taken as the characteristic size, and the ratio a / c is taken constant for all a, determined from the condition of the maximum rate of development of the defect under operational conditions.
  • t ⁇ mfd determined for a particular product or group of products of similar m, wherein m in controlling all of one type of control results are summed and are in the form of a histogram.
  • the minimum defect size ⁇ 0 that is available for detection is determined when setting up the flaw detector used to control the product, or as the minimum defect size that was detected during inspection.
  • a test sample is manufactured to determine the characteristics of non-destructive testing of discontinuities in the product material, this test sample is controlled by the non-destructive testing method, and the product is controlled using the same method as the test sample, and the test the sample is made in the form of the product or its most critical part from the same material and according to the same technology as the product, with defects located at random with different characteristic p ⁇ , determine the probability of detecting defects P water ( ⁇ ):
  • N ucx f (a, c), where a, c are the linear dimensions of the defects, and when determining the residual defectiveness N ocm use the expression
  • the test sample contains three groups of defects: defects whose sizes lie in the range from the sizes of defects admissible during operation to sizes critical for the product in operation; defects, the sizes of which lie in the range from the sizes allowed during the manufacture of the product to the sizes of defects allowed during operation; defects, the sizes of which lie in the range from the sizes minimally available for detecting defects, to the sizes of defects acceptable in the manufacture while the first two types of defects mimic defects of an operational nature, and the third type - technological ones, residual defects N ⁇ m without defects in the region of defects that are important for safety, determined in the form of the number of defects in the product, the dimensions of which are equal to or greater than the critical dimensions%, p in the operation mode of the product:
  • Figure 1 schematically depicts a defect in the pipeline
  • figure 2 shows the distribution of defects of critical dimensions, allowable dimensions and allowable discontinuities in the manufacturing process (the corresponding manufacturing standards are shown in table NTD PHAEG-7 010-89)
  • Fig. 3 is a characteristic of the reliability of HK in the form of a dependence of the probability of detection of defects .P 00 ⁇ on its size (in this case, width a)
  • FIG. 4 is a histogram of defects detected in the product;
  • FIG. 5 initial defectiveness of the product, in FIG. 6 - residual defectiveness of the product, in FIG. 7 shows the results product control in example 2, in FIG. 8 - initial defective functions
  • FIG. 9 shows the probabilistic part of the residual defect.
  • the method is used for a specific product or group of similar products, the workmanship, the reliability and safety of which must be ensured using the well-known HK method when monitoring by an operator of known skill.
  • the methods of fracture mechanics determine the critical sizes of defects in the operating mode for this product ⁇ ⁇ , the maximum allowable defects in operation [ ⁇ ⁇ d e, permissible in the manufacture of defect size [ ⁇ ] ⁇ (standards product defects), defined by the applicable regulations and / or specifications for the production of ( ⁇ the Features -terrorism defect size, for example, a linear defect size is selected, or a combination of linear dimensions of the defect or defect area, or volume of the defect).
  • defects that determine quality are defects whose sizes are in the range from the minimum dimensions available for detecting defects (search) to the sizes of defects acceptable during manufacture and above; defects determining reliability are those defects whose sizes are in the range from defective during manufacture to acceptable during operation and higher; defects defining safety - from acceptable during operation to critical sizes and above.
  • the method involves the use of a test sample, in this case, the determination of the size of the defects is carried out before the manufacture of the test sample. Taking into account the real operational loads and conditions, the defects (discontinuities) are determined for the product (for example, pipeline, Fig. L) using the methods of fracture mechanics (taking into account safety factors):
  • curve 3 The distribution of defects of critical dimensions (curve 3), allowable sizes in use (curve 2), as well as allowable sizes of discontinuities in the manufacture (curve 1) are shown in FIG.
  • test sample When implementing a method for determining the initial and residual defects of a product using a test sample, it is manufactured according to the shape of the product and on a scale of about 1: 1 to the product or its most critical part.
  • the most critical part of the product is that part of the product in which the most likely occurrence of defects (welds, places of maximum operational influences, etc.) or the destruction of which is dangerous.
  • the test sample is made of the same material and using the same technology as the product. Three types of artificial defects are laid in test samples:
  • the first two types of defects should imitate defects of an operational nature
  • the third type - of technological defects Operational defects - defects that can develop from technological defects or originate and develop under the action of operational loads (fatigue cracks, stress corrosion cracking cracks, etc.)
  • technological defects are defects whose occurrence is associated with the features of manufacturing or installation technology (lack of fusion, non-fusion, pores, etc.).
  • it is possible to lay a different combination of types of defects one, any two, three), if necessary, it is also possible to produce a different number of samples, in each of which one type of effects or their various combination.
  • All embedded defects must be hidden from HK operators, i.e. be internal (subsurface) or, if the defect is superficial, be located in a place inaccessible to visual detection (or have dimensions that cannot be visually fixed).
  • defects are randomly placed in the sample, for example, using random number tables.
  • the minimum allowable distance between defects is determined on the basis of the condition for the existence of single defects (if single defects are laid) or less for group cracks (the conditions of mutual influence are known, for example, Guidelines MP 108.7-86, M., TSNIITMASH, 1986).
  • the number of defects of each type should be sufficient for statistical processing of the results, for example, at least 9 pieces. (With less results are less reliable).
  • Any defect can be conservatively modeled by a crack, and any crack can be described by an ellipse with semi-axes: short a and long c.
  • Defects in the form of ellipses are laid in the test sample, while the ratio of the axes of the ellipse is arbitrary, and the area of the plane defect or the projection area of the volume defect on the plane of the probable development of the defect is taken as characterizing the size of the defect;
  • Defects in the form of ellipses are placed in the test sample, while the number of defects and the ratio of the axes of the ellipse are selected using mathematical methods for planning the experiment, based on the condition of minimizing the number of defects to be laid (K. Daniel, Using statistics in an industrial experiment, because of Mir M. 1979);
  • the defects to be inserted into the test sample do not have the shape of an ellipse, then they are schematized by ellipses.
  • test sample After the manufacture of the test sample, it is controlled using the same means and methods of control and by operators of the same qualifications, which will then be used to control the product, the results of the monitoring are compared with real defects embedded in the test sample.
  • N total b ⁇ lN hall mo (%) N total b ⁇ lN hall mo (%), where N total m0 is the number of defects detected during the control of the test sample, N Hall is the number of defects incorporated in the manufacture of the sample,
  • a probability curve for detecting defects for a given part is constructed using this HK method depending on the characteristic size of the defects.
  • Defect probability curve from the dimensions of the defects " ⁇ " and "c” any defect in the material can be conservatively described by an ellipse with axes a and c), it is possible to approximate the equation that most closely describes the experimental results of control, for example, p w - c 0 )] - ⁇ , or
  • QL NK - confidence coefficient HK characterizes the increase in the detection of defects depending on its size
  • ⁇ is a constant characterizing the ultimate detectability of the control by this method for an arbitrarily large defect size; if the dimensions of the part are small, then this value can be neglected by introducing an appropriate adjustment of the value
  • ⁇ ⁇ is the characteristic size of the defect, for example, its area
  • ⁇ 0 is the minimum characteristic size of the defect
  • the product is inspected, and the inspection results are presented in the form of a histogram in the coordinates “characteristic x size of the defect ⁇ - the number of detected defects of this size TV 0 ⁇ uzd ”.
  • the initial defectiveness N ucx is defined as the ratio of N o in n ISC / P in
  • the residual N ⁇ mfiepp in the field of defects important to safety is determined as the number of defects in the product whose dimensions are equal to or greater than the critical dimensions ⁇ * p in the operating mode of the product:
  • the initial and residual defects of the product using the results of non-destructive testing, as well as determining the quality of the product by the reliable and probable parts of the residual defect, the non-destructive testing of the product (HK) is carried out by the selected method (ultrasonic, eddy current, radiographic and other HK methods) and technical control equipment by operators of certain qualifications.
  • results of the control are presented in the form of a histogram in the coordinates "characteristic x size of the defect ⁇ - the number of detected defects of this size N UN UJ () ".
  • the horizontal axis ⁇ must include the critical size of the defect, even if as a result of the inspection all the detected defects did not reach critical sizes.
  • N obn ( ⁇ ) N ucx ( ⁇ ) P water ( ⁇ )
  • N Obn is the number of defects detected during inspection per unit of characteristic size. If the semimajor axis of the ellipse with which the defect is schematized is selected as the characteristic size, then the dimension N 00 - ,, - mm "1 ;
  • N ucx is the function of the initial (up to HK) defectiveness with the same dimension as N o6terrorism ;
  • P water is the probability of detecting a defect of a given size ⁇ .
  • N 0611 (Z) ⁇ - 1 ⁇ 1 - (1 - ⁇ ) exp [-a ( ⁇ - ⁇ o )] - ⁇ ], where A, n, a, ⁇ , ⁇ 0 are constants.
  • ⁇ 0 - the minimum defect size that is available for detection - is determined when setting up the flaw detector used to control the product, or as the minimum defect size that was detected during the inspection; As a first approximation, ⁇ can be taken equal to 0. As a result, three unknowns remain, which greatly simplifies the task of determining them.
  • the constants A, n, and a can be determined either by solving a system of three equations with respect to A, n, and a, which are obtained if we take three points on the histogram, or they are determined using the least squares method.
  • the number of remaining defects in the product is determined, as in the method using test samples, in three ranges: residual defectiveness N ⁇ 1n hp in the area of defects important for safety, is determined as the number of defects in the product whose dimensions are equal or more critical dimensions ⁇ ⁇ in product operation mode:
  • the HK results are presented as analytical expressions.
  • K bn ( ⁇ ) N ucx ( ⁇ ) P water ( ⁇ ) where N obn is the number of defects detected during inspection per unit of characteristic size. If the semimajor axis of the ellipse with which the defect is schematized is selected as the characteristic size, then the dimension is N OH - mm "1 ;
  • N ucx is the function of the initial (up to HK) defectiveness with the same dimension as N obn ;
  • P water is the probability of detecting a defect of a given size ⁇ .
  • N ucx and P water are determined based on the condition of the greatest simplicity of expression, the minimum number of constants and the correspondence of the physically determined dependence of N ucx and P water on ⁇ .
  • the numerical values of the constants A, n, a, ⁇ are determined from the condition that the equation N obn ( ⁇ ) is as close as possible to the HK results presented in the form of a histogram.
  • ⁇ 0 - the minimum defect size that is available for detection - is determined when setting up the flaw detector used to control the product, or as the minimum defect size that was detected during the inspection; As a first approximation, ⁇ can be taken equal to 0. As a result, three unknowns remain, which greatly simplifies the task of determining them.
  • the constants A, n and can be determined either by solving a system of three equations with respect to A, n, and ⁇ , which are obtained if we take three points on the histogram, or they are determined using the least squares method.
  • N ocm N ucx ( ⁇ ) - N obn ( ⁇ ).
  • the number of remaining defects in the product is determined in three ranges as described above: residual defectiveness N ⁇ 1n cr in the area of defects important for safety, residual defectiveness N 1 ⁇ 103 in the region of defects important for reliability, residual defectiveness N ⁇ m u ⁇ r in the field of defects that determine the quality of workmanship.
  • the horizontal axis ⁇ must include the critical size of the defect, even if, as a result of the control, all detected defects did not reach critical sizes.
  • test sample After the manufacture of the test sample, it is controlled using the same means and methods of control and by operators of the same qualifications, which will then be used to control the product, the results of the monitoring are compared with real defects embedded in the test sample.
  • N 0 ⁇ H mo is the number of defects detected during the control of the test sample
  • N 3 (U i that - the number of inherent in the manufacture of sample defects, the results of control building curve probability detectable TM defects to the part data by HK depending on the characteristic size of defects curve of the probability of detecting defects on the defect size "a" and "c". (any defect in the material can be conservatively described by an ellipse with semiaxes a and c) can be approximated by the equation that most closely describes the experimental results of control, for example
  • a NK - confidence coefficient HK characterizes the increase in detected TM defects depending on its size; ⁇ is a constant characterizing the ultimate detectability of the control by this method for an arbitrarily large defect size; if the dimensions of the part are small, then this value can be neglected by introducing an appropriate adjustment of a H k .
  • ⁇ is the characteristic size of the defect, for example, its area; ⁇ 0 is the minimum characteristic size of the defect; a 0 , C 0 - minimum defect sizes available for detecting HK.
  • the product is inspected, and the inspection results are presented in the form of a histogram in the coordinates “characteristic x size of the defect ⁇ - the number of detected defects of this size N U JJ ”.
  • the initial defectiveness N ucx is defined as the ratio of N obn w ⁇ P water
  • F is the defect area
  • n, A, D, and c are the coefficients selected from the condition that the analytical curve is as close as possible to the experimental data, with c being the average value of c, and D the variance.
  • N obn is determined from the analytical expression N ucx • P water ( ⁇ ), i.e. residual imperfection N ocm can be represented as the equation
  • N ⁇ m ⁇ ezop in the field of defects important for safety is determined as the number of defects in the product whose dimensions are equal to or greater than the critical dimensions ⁇ ⁇ in the operating mode of the product:
  • residual defects are divided into a reliable part ⁇ ⁇ X a , in which defects with dimensions ⁇ ⁇ d exist reliably, and the probabilistic part ⁇ > ⁇ schreib, in which defects with sizes ⁇ > ⁇ , may or may not exist.
  • Fektnosti is determined from the condition:
  • the reliability of the HK is determined using the method (ultrasonic, eddy current, radiographic and other HK methods), a technical tool and an HK operator of a certain qualification, which will also be used to control the product.
  • the results of determining P water from a are presented in FIG.
  • the initial defect N ucx is determined .
  • the results of determining N ucx are presented in the form of a graph in FIG. 5 in coordinates N ucx — the characteristic size of the defect (in this case, the width of the defect a, the defect is schematically shown in FIG. L).
  • N ocm The residual imperfection graph N ocm is presented in the same coordinates as for N ucx , in FIG. 6. To obtain N ocm , for each fixed value, a subtraction from the number N ucx of the number of detected defects was subtracted.
  • the number of defects remaining in the product after HK and repair of the detected defects was determined, and it was obtained that: the total number of defects whose dimensions are equal to or exceed the critical dimensions of the defects in operation was:
  • the manufacturing technology of the product and / or HK technology need to be improved, because in the case of transferring the product into operation, as a result of the operational HK, up to 23 defects of unacceptable dimensions will be detected, which will lead to additional repair of the product under operating conditions (which is a more expensive measure than factory repair), and in case of missing defects according to the results of operational control, an accident may occur with partial or complete destruction of the product (in this case, the pressure pipeline).
  • the product after manufacturing, HK and repair of the identified defects can be allowed to operate.
  • the determination of the characteristics of the initial (before HK) and residual (after HK and repair of detected defects) defects indicates a low level of reliability of the product and the need for its improvement.
  • the critical size of the defect corresponds to 1.15mm (FIG. 2).
  • N obn Aa ⁇ n [l-exp [-a (aa 0 )].
  • N obn 0.66 was obtained as averaging the number of detected defects in the range from 1 1 to 13 mm, which was 2/3, where 2 is the number of detected defects, 3 is the number of intervals.
  • N ucx l000cG 2 '56 ; defect detection probability equation:
  • N ocm ( ⁇ ) N ucx ( ⁇ ) - N obn ( ⁇ ).

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Abstract

La présente invention relève du domaine du contrôle non destructif (CND) de défauts tels que la discontinuité, l'hétérogénéité et autres de matériaux d'un article ou d'un groupe d'articles et peut être utilisée pour évaluer la fiabilité de moyens et de procédés de CND, la qualification d'opérateurs de CND, le contrôle d'articles au moment de leur fonctionnement et/ou de leur production. Dans une variante, le procédé de cette invention consiste à produire et à tester un échantillon test, puis à déterminer la fiabilité du test en définissant la probabilité de détection de défauts sur la base de défauts détectés pendant le test de l'échantillon test et d'un certain nombre de défauts imités lors de la production de l'échantillon test, à tester l'article de la même manière, à déterminer une défectuosité initiale compte tenu de la probabilité de détection de défauts, à réparer les défauts révélés et à déterminer une défectuosité résiduelle. Dans une autre variante, appliquée pour un article précis ou un groupe m d'articles du même type, le procédé consiste à déterminer les dimensions critiques ψcr des défauts en mode fonctionnement, les dimensions admissibles des défauts en mode fonctionnement [ψ]af, ainsi que les dimensions admissibles des défauts en mode fabrication [ψ]fab; à déterminer une défectuosité initiale Ni et la probabilité de détection des défauts Pdd; à réparer les défauts et à déterminer une défectuosité résiduelle Nr représentant la différence entre Ni et Nr, Nr étant déterminée dans trois gammes de défauts, à savoir: des défauts importants en termes de sécurité, des défauts importants en terme de fiabilité et des défauts importants en terme de qualité de production. Dans une troisième variante, le procédé de cette invention consiste à déterminer la probabilité de détection de défauts Pdd, la défectuosité initiale Ni=f(ψ), la défectuosité résiduelle Nr =f(ψ) (après test et réparation des défauts révélés) représentant la différence entre Ni et Nr, à diviser la défectuosité résiduelle en un composant de certitude ψ≤ψδ et un composant de probabilité ψ>ψδ, ψ désignant une dimension caractéristique du défaut, tandis que ψδ désigne la dimension des défauts sur la limite entre les composants de certitude et de probabilité.
PCT/RU2004/000317 2004-08-13 2004-08-13 Procede permettant de determiner la defectuosite initiale et residuelle d'un article, la probabilite de detection de defauts et la qualite d'un article sur la base de composants de certitude et de probabilite d'une defectuosite residuelle WO2006022568A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114549448A (zh) * 2022-02-17 2022-05-27 中国空气动力研究与发展中心超高速空气动力研究所 一种基于红外热成像数据分析的复杂多类型缺陷检测评估方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4183139A (en) * 1978-01-19 1980-01-15 Asami Tanaka Method of marking dental contact points
SU1748052A1 (ru) * 1989-12-11 1992-07-15 Ростовский-На-Дону Институт Сельскохозяйственного Машиностроения Тест-образец дл ультразвукового контрол
RU2191376C2 (ru) * 2000-02-25 2002-10-20 Открытое акционерное общество "Новосибирский завод химконцентратов" Способ измерения размеров дефектов при ультразвуковом контроле изделий
RU2214589C2 (ru) * 2001-12-25 2003-10-20 Дубов Анатолий Александрович Способ контроля качества изделий

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4183139A (en) * 1978-01-19 1980-01-15 Asami Tanaka Method of marking dental contact points
SU1748052A1 (ru) * 1989-12-11 1992-07-15 Ростовский-На-Дону Институт Сельскохозяйственного Машиностроения Тест-образец дл ультразвукового контрол
RU2191376C2 (ru) * 2000-02-25 2002-10-20 Открытое акционерное общество "Новосибирский завод химконцентратов" Способ измерения размеров дефектов при ультразвуковом контроле изделий
RU2214589C2 (ru) * 2001-12-25 2003-10-20 Дубов Анатолий Александрович Способ контроля качества изделий

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114549448A (zh) * 2022-02-17 2022-05-27 中国空气动力研究与发展中心超高速空气动力研究所 一种基于红外热成像数据分析的复杂多类型缺陷检测评估方法
CN114549448B (zh) * 2022-02-17 2023-08-11 中国空气动力研究与发展中心超高速空气动力研究所 一种基于红外热成像数据分析的复杂多类型缺陷检测评估方法

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