KR20230025192A - Nondestructive inspection method using acoustic emission signal - Google Patents

Abstract

As a step of measuring an acoustic emission signal generated from a diagnostic object using a sensor module, an embodiment of the present invention may provide a non-destructive inspection method using an acoustic emission signal, including: a measuring step of comprising a sensor module with a pair of main sensors disposed on the diagnostic object and a pair of auxiliary sensors spaced apart from the pair of main sensors; a selection step in which a data calculation unit selects only destruction signals generated from a defective part among the acoustic emission signals; a calculation step in which the data calculation unit calculates the measurement time, which is the time when the destruction signal reaches the main sensor and the auxiliary sensor; and an analysis step in which a data analysis unit analyzes the location of the defective part and the propagation speed of the destruction signal using the measurement time and location information of the sensor module. Accordingly, inspection can be performed using only one pair of main sensors and one pair of auxiliary sensors.

Description

Nondestructive inspection method using acoustic emission signal {Nondestructive inspection method using acoustic emission signal}

The present invention relates to a non-destructive testing method, and more particularly, to a non-destructive testing method for diagnosing a defect in a structure using an acoustic emission signal.

Non-destructive testing using acoustic emission signals is a technique for early diagnosis of structural defects by measuring elastic waves spontaneously generated from materials. In order to detect and respond to structural defects at an early stage, a high-accuracy analysis of the location and time of occurrence of the defect must be performed as well as a real-time inspection of whether the defect has occurred.

However, conventional non-destructive testing methods using acoustic emission signals have difficulties in accurately diagnosing whether a defect has occurred due to ambient noise and operating noise of the object to be diagnosed. In addition, even if the occurrence of a defect is detected, the accuracy of estimating the location of the defect and the occurrence time of the defect is somewhat low.

Accordingly, there is a need to develop a method for diagnosing whether or not a defect occurs in an operating diagnosis target and more accurately diagnosing a defect location and a defect occurrence time.

A technical problem to be achieved by the present invention is to provide a method for diagnosing whether or not a defect occurs in an operating diagnosis object in a non-destructive inspection method using an acoustic emission signal and more accurately diagnosing a defect location and a defect occurrence time.

The technical problem to be achieved by the present invention is not limited to the above-mentioned technical problem, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below. There will be.

In order to achieve the above technical problem, an embodiment of the present invention is a step of measuring a sound emission signal generated from a diagnosis object using a sensor module, wherein the sensor module is connected to a pair of main sensors disposed in the diagnosis object and the pair of A measuring step including a pair of auxiliary sensors spaced apart from a main sensor; a selection step of, by a data calculating unit, selecting only a disruptive signal generated from a defective part among the sound emission signals; A calculation step of calculating a measurement time, which is the time to reach the sensor, and an analysis step of analyzing the position of the defective part and the propagation speed of the destruction signal by a data analysis unit using the measurement time and the location information of the sensor module. It is possible to provide a non-destructive inspection method using a sound emission signal including.

In an embodiment of the present invention, before the screening step, the normal signal measuring step of measuring a normal signal in a diagnosis target object operating in a state in which no destruction occurs, and distinguishing the normal signal from the disrupted signal The method may further include selecting a criterion parameter for the diagnosis target and setting a criterion for determining whether or not destruction of the diagnosis object has occurred by using the selected criterion parameter.

In an embodiment of the present invention, the screening step compares the selected reference parameter with the criterion to determine whether or not destruction of the diagnosis target has occurred, and when it is determined that destruction has occurred in the diagnosis target, the Only the destruction signal classified according to the discrimination criterion may be selected.

In an embodiment of the present invention, the sensor module measures the sound emission signal by collecting voltage values input to the main sensor and the auxiliary sensor in real time, and in the calculating step, the voltage value is The moment in which the tendency to increase with time is the greatest can be calculated as the measurement time.

In an embodiment of the present invention, in the calculating step, a Kendall rank correlation coefficient may be used to analyze a tendency of the voltage value to change over time.

In an embodiment of the present invention, the analyzing step may include defining a first calculation formula based on the position of the sensor module and the measurement time, and using a second calculation formula defined based on the first calculation formula to detect the defect. and calculating a negative position and a propagation speed of the destruction signal, wherein the first calculation equation is defined by the following equations (1)-1, (1)-2, (1)-3, and (1)-4 becomes,

…(1)-1

… (1)-1

…(1)-2

… (1)-2

…(1)-3

… (1)-3

…(1)-4

… (1)-4

The second calculation formula is defined by the following determinants (2)-1, (2)-2, (2)-3 and (2)-4,

…(2)-1

… (2)-1

…(2)-2

… (2)-2

…(2)-3

… (2)-3

…(2)-4

… (2)-4

In Equation (1) and the determinant (2),

d: location of defects

v: propagation speed of the destruction signal

L: distance between the first main sensor and the second main sensor

E1: Distance between the first main sensor and the first auxiliary sensor

E2: Distance between the second main sensor and the second auxiliary sensor

: 제1 메인센서와 제2 메인센서의 측정 시간 차이

: Measurement time difference between the first main sensor and the second main sensor

: 제1 메인센서와 제2 보조센서의 측정 시간 차이

: Measurement time difference between the first main sensor and the second auxiliary sensor

: 제1 보조센서와 제2 메인센서의 측정 시간 차이

: Measurement time difference between the first auxiliary sensor and the second main sensor

: 제1 보조센서와 제2 보조센서의 측정 시간 차이

: Measurement time difference between the first auxiliary sensor and the second auxiliary sensor

: 행렬 X의 전치행렬로 정의될 수 있다.

: It can be defined as a transposed matrix of matrix X.

In an embodiment of the present invention, the analyzing step may include calculating the location of the defect by substituting the propagation speed value calculated by the second calculation equation into the first calculation equation, and the defect calculated by the second calculation equation. Further comprising the step of setting a weight by comparing the position value of the negative with the position value of the defective part calculated by the first calculation formula, wherein the weight is defined by Equations (3)-1 and (3)-2 below, ,

,

,

…(3)-1

,

,

… (3)-1

,

,

…(3)-2

,

,

… (3)-2

In the above equations (3)-1 and (3)-2,

: 수학식 (1)-1의 가중치

: Weight of Equation (1)-1

: 수학식 (1)-2의 가중치

: Weight of Equation (1)-2

: 수학식 (1)-3의 가중치

: Weight of Equation (1)-3

: 수학식 (1)-4의 가중치

: Weight of Equation (1)-4

: 제2 계산식으로 계산된 결함부의 위치

: Position of the defective part calculated by the second calculation formula

: 수학식 (1)-i로 계산된 결함부의 위치로 정의될 수 있다.

: It can be defined as the position of the defective part calculated by Equation (1)-i.

In an embodiment of the present invention, the analyzing step further includes defining a third calculation equation by reflecting the weight in the second calculation equation, and calculating the position of the defect part and the propagation speed by the third calculation equation. And, the third calculation formula can be defined as Equation (4) below.

…(4)

… (4)

In an embodiment of the present invention, the analyzing step may further include calculating the location of the defect part by substituting the propagation speed value calculated by the third calculation equation into the first calculation equation.

In an embodiment of the present invention, the analyzing step may include resetting the weight by comparing the position value of the defective part calculated by the third formula with the position value of the defective part calculated by the first formula, and The method may further include recalculating the location of the defective part by reflecting the reset weight in the third calculation formula.

In the non-destructive inspection method using acoustic emission signals according to an embodiment of the present invention, by simplifying and inspecting an object to be diagnosed in one dimension, the inspection can be performed using only a pair of main sensors and a pair of auxiliary sensors.

In addition, a pair of main sensors and a pair of auxiliary sensors can collect acoustic emission signals generated inside the area to be diagnosed and simultaneously remove noise generated outside the area to be diagnosed. Accordingly, more efficient inspection can be performed by excluding unnecessary data from the analysis target.

In addition, by calculating the measurement time using the change trend of the voltage with time, it is possible to prevent the occurrence of errors due to noise and provide a more accurate measurement time. Accordingly, a highly reliable non-destructive test can be performed even when the diagnosis target is in operation.

In addition, by comparing the values calculated in the first calculation equation, the second calculation equation, and the third calculation equation, and repeatedly resetting the weights, it is possible to provide a more accurate position of the defective part and propagation speed value of the destruction signal. Accordingly, the reliability of the non-destructive test result may be further increased.

1 is a diagram schematically illustrating a non-destructive testing apparatus for performing a non-destructive testing method using a sound emission signal according to an embodiment of the present invention.
2 is a view showing a defective part where destruction occurs in a diagnosis object in which a sensor module is installed.
3 is a graph showing parameters representing characteristics of a sound emission signal.
FIG. 4(a) is a graph showing the distribution of the first parameter when the object to be diagnosed is in a normal state, and (b) of FIG. 4 is a graph showing the distribution of the first parameter when the object to be diagnosed is destroyed.
FIG. 5(a) is a graph showing the distribution of the second parameter when the object to be diagnosed is in a normal state, and (b) of FIG. 5 is a graph showing the distribution of the second parameter when the object to be diagnosed is destroyed.
6 is a graph showing the time when the acoustic emission signal first exceeds the threshold value and the time when the maximum amplitude is reached.
7 is a graph showing a calculation period and a calculation window for calculating a measurement time of a sound emission signal.
FIG. 8(a) is a graph showing a calculation window in which a rank correlation coefficient value is maximized, and FIG. 8(b) is a graph showing a change in a rank correlation coefficient value within a calculation interval.
9 is a flowchart illustrating a process of a method for diagnosing a defect location using a sound emission signal according to an embodiment of the present invention.
10 is a flow chart showing the process of performing the analysis step in detail.

Hereinafter, the present invention will be described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms, and therefore is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is said to be "connected (connected, contacted, combined)" with another part, this is not only "directly connected", but also "indirectly connected" with another member in between. "Including cases where In addition, when a part "includes" a certain component, it means that it may further include other components without excluding other components unless otherwise stated.

Terms used in this specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "include" or "have" are intended to indicate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

In this specification, a “module” includes a unit composed of hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module can be an integral part or a minimal unit or part thereof that performs one or more functions. For example, the module may be composed of an application-specific integrated circuit (ASIC).

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram schematically illustrating a non-destructive testing apparatus for performing a non-destructive testing method using a sound emission signal according to an embodiment of the present invention. 2 is a view showing a defective part where destruction occurs in a diagnosis object in which a sensor module is installed.

Referring to FIGS. 1 and 2 , a non-destructive testing method using a sound emission signal according to an embodiment of the present invention may be performed by a non-destructive testing apparatus 1 . The non-destructive testing device 1 may be a device that inspects the state of the object to be diagnosed 10 in real time using an Acoustic Emission (AE) signal.

Specifically, the non-destructive testing apparatus 1 may diagnose whether the object to be diagnosed 10 is destroyed by measuring the acoustic emission signal of the object 10 to be diagnosed. In addition, when destruction occurs in the object to be diagnosed 10, the position of the defective part 11 and the occurrence time of the defective part 11 can be analyzed. Here, the defective part 11 may be a point where material destruction occurs within the object to be diagnosed 10 .

The diagnosis target 10 may be, for example, a structure constituting a large facility such as a power plant. Specifically, the diagnosis target 10 may be a long structure such as a pipe or a beam. In this case, as shown in FIGS. 1 and 2 , non-destructive testing may be performed by simplifying the diagnosis object 10 in one dimension.

The acoustic emission signal may be an electrical signal obtained from an elastic wave generated from the object to be diagnosed 10 . In this case, the acoustic emission signal may include both a disruptive signal and a normal signal.

The destruction signal may be a sound emission signal uniquely generated only when destruction occurs in the diagnosis object 10 . The destruction signal may be continuously generated when very fine destruction occurs in the object to be diagnosed 10, that is, from the stage where destruction starts. In this case, the user installs the sensor module 100 on a test piece (not shown) having a material and shape similar to that of the diagnosis object 10 in advance, and collects data on the destruction signal by destroying the test piece. .

The normal signal may be a sound emission signal generated when the object to be diagnosed 10 without destruction is normally operated. A normal signal can be classified as noise from the point of view of diagnosing a breakdown. In this case, the user may operate the diagnosis object 10 to collect normal signals in a state where the sensor module 100 is previously installed on the diagnosis object 10 in a normal state.

The non-destructive testing device 1 may include a sensor module 100 , a data calculation unit 200 and a data analysis unit 300 .

The sensor module 100 may measure a sound emission signal generated from the diagnosis object 10 . Specifically, the sensor module 100 may convert an elastic wave generated from the object to be diagnosed 10 into an electrical signal and collect the voltage value in real time.

The sensor module 100 may include a plurality of sensors. Specifically, the sensor module 100 may include a pair of main sensors and a pair of auxiliary sensors.

A pair of main sensors and a pair of auxiliary sensors may be connected to the diagnosis object 10 . For example, the main sensor and the auxiliary sensor may be attached to the surface of the diagnosis object 10 .

A pair of main sensors and a pair of auxiliary sensors may be disposed apart from each other. Specifically, a pair of auxiliary sensors may be disposed apart from each other, and a pair of main sensors may be disposed spaced apart from each other between the pair of auxiliary sensors.

In this case, the distance between the first main sensor S1 and the second main sensor S2 is L, the distance between the first main sensor S1 and the first auxiliary sensor G1 is E1, and the second A distance between the main sensor S2 and the second auxiliary sensor G2 is defined as E2.

A pair of auxiliary sensors may partition a diagnosis target area. Specifically, a section between the first auxiliary sensor G1 and the second auxiliary sensor G2 may be defined as a region to be diagnosed.

In this case, the non-destructive testing apparatus 1 may consider an acoustic emission signal generated outside the area to be diagnosed as noise and may exclude it. In addition, only acoustic emission signals generated inside the area to be diagnosed may be collected and analyzed.

Specifically, the acoustic emission signal that first reaches the first main sensor S1 and then reaches the first auxiliary sensor G1 is determined to have occurred inside the area to be diagnosed and can be used for destruction diagnosis. Conversely, an acoustic emission signal that first reaches the first auxiliary sensor G1 and then reaches the first main sensor S1 is determined to be generated outside the area to be diagnosed and can be removed.

In the same way, the acoustic emission signal that first reaches the second main sensor S2 and then reaches the second auxiliary sensor G2 is determined to have occurred inside the area to be diagnosed and can be used for destruction diagnosis. Conversely, the acoustic emission signal that first reaches the second auxiliary sensor G2 and then reaches the second main sensor S2 is determined to be generated outside the area to be diagnosed and can be removed.

That is, the sensor module 100 may collect only signals necessary for diagnosis of destruction of the object to be diagnosed 10 generated inside the area to be diagnosed.

3 is a graph showing parameters representing characteristics of a sound emission signal. FIG. 4(a) is a graph showing the distribution of the first parameter when the object to be diagnosed is in a normal state, and (b) of FIG. 4 is a graph showing the distribution of the first parameter when the object to be diagnosed is destroyed. FIG. 5(a) is a graph showing the distribution of the second parameter when the object to be diagnosed is in a normal state, and (b) of FIG. 5 is a graph showing the distribution of the second parameter when the object to be diagnosed is destroyed.

Referring to FIGS. 1 and 3 to 5 , the data calculator 200 may select a disruptive signal from the acoustic emission signals measured by the sensor module 100 . The data calculation unit 200 may be, for example, a data acquisition (DAQ) device.

In order to select the destruction signal, the data calculator 200 may extract a parameter from the measured acoustic emission signal. In this case, the parameter may be a factor representing characteristics of a waveform of a single sound emission signal.

The parameters are Hit, Threshold (TH), Peak Amplitude (PA), Count (CT), Rising Time (RT), Duration (D), Energy ( Energy), strength, average signal level (ASL), and root mean square (RMS). However, the types of parameters are not limited thereto, and may further include other factors representing characteristics of the acoustic emission signal waveform.

A hit may refer to each single acoustic emission signal having an independent waveform. Specifically, the sound emission signal is composed of a plurality of burst-type signals that are continuously generated, and each of the signals having independent waveforms that are distinct from each other can be defined as one hit. The number of such hits may be one factor indicative of failure occurrence or progression of failure stages. More specifically, the cumulative number of hits occurring from a certain point in time or the number of hits occurring during a certain period of time may be defined as one parameter.

The threshold value TH may be a reference value for determining whether a sound emission signal is generated. The threshold value TH may be set by the user according to the characteristics of the waveform.

The maximum amplitude (PA) may mean a maximum amplitude value of a waveform of each hit.

The count CT may be the number of wave heights crossing the threshold in the waveform of each hit.

The rise time (RT) may be a time from when each hit exceeds a threshold value to when each hit reaches the maximum amplitude.

The duration D may be a time from a time point when the waveform of each hit exceeds a threshold value to a time point when the waveform of each hit falls below the threshold value again.

The energy may mean a value obtained by integrating the waveform of each hit.

The intensity may be a value obtained by performing an inner product of an absolute value of an amplitude with time.

The average signal level may be a value obtained by dividing an absolute value of an amplitude with time and then dividing the value by time.

The RMS may be a value obtained by averaging the squares of instantaneous voltages generated within the duration of each hit and obtaining the square root thereof.

A plurality of these parameters may be consecutively extracted to correspond to each of a plurality of successively measured acoustic emission signals. In addition, when a plurality of parameter values are displayed on a graph, different distributions may be displayed for each parameter.

The data calculation unit 200 may analyze the distribution of the extracted parameters. Specifically, the data calculation unit 200 may compare the distribution of parameters extracted from the normal signal (hereinafter referred to as normal distribution) and the distribution of parameters extracted from the destructive signal (hereinafter referred to as destructive distribution).

Based on the analysis result, the data calculation unit 200 may select a parameter that is easy to distinguish because the characteristics of the normal distribution and the destructive distribution are different from each other as the reference parameter. In addition, a criterion for distinguishing between a normal distribution and a destructive distribution may be set.

As an example, as shown exemplarily in FIG. 4 , the first parameter may be selected as the reference parameter. The normal distribution of the first parameter may represent a distribution such as an exponential function. Specifically, the normal distribution of the first parameter may represent a distribution in which the number of measured acoustic emission signals decreases as the value of the first parameter increases.

And, the destruction distribution of the first parameter may represent a distribution clustered in a specific section. Specifically, the destruction distribution of the first parameter may represent a distribution concentrated in a section with little or no normal distribution.

In this case, the data calculation unit 200 may set a section in which the destructive distribution of the first parameter is clustered as a criterion for determination. In addition, when the first parameter value extracted from the acoustic emission signal meets the criterion, the corresponding acoustic emission signal may be selected as a destruction signal.

In another embodiment, as exemplarily shown in FIG. 5 , the second parameter may be selected as the reference parameter. The normal distribution of the second parameter may represent a distribution such as a Gaussian function. Specifically, the normal distribution of the second parameter may represent a bell-shaped distribution that rapidly increases and then rapidly decreases in one section.

And, the destruction distribution of the second parameter may represent a distribution clustered in a specific section. Specifically, a distribution concentrated in one section in which a normal distribution appears and another section different from that of a normal distribution may be indicated.

In this case, the data calculation unit 200 may set a section in which the destructive distribution of the second parameter is clustered as a criterion for determination. In addition, when the second parameter value extracted from the acoustic emission signal meets the criterion, the corresponding acoustic emission signal may be selected as a destruction signal.

In addition to the above-described first parameter and second parameter, other parameters easily distinguishable between normal distribution and destructive distribution may be used as reference parameters.

The data calculation unit 200 may determine that the object to be diagnosed 10 is in a normal state when there is no disruptive signal determined from the measured acoustic emission signal. Conversely, when at least a part of the measured acoustic emission signals is determined to be a destruction signal, it can be determined that destruction has occurred in the object to be diagnosed 10 .

)이라고 지칭하기로 한다.When destruction occurs in the object to be diagnosed 10 , the data calculation unit 200 may calculate the time at which the selected destruction signal reaches the sensor module 100 . Here, the time the destruction signal reaches the sensor module 100 is the measurement time (

) will be referred to as

6 is a graph showing the time when the acoustic emission signal first exceeds the threshold value and the time when the maximum amplitude is reached.

) 또는 최대진폭(PA)에 이르는 시점(

)을 측정 시간으로 산출한다. 그러나, 이러한 산출 방법은 잡음에 의해 오차가 발생할 가능성이 크다는 문제점이 있다. 그리고, 산출된 측정 시간의 오차가 커질수록, 결함부(11)의 위치 및 결함부(11) 발생 시간을 정확하게 추정하기가 어려워진다.Referring to FIG. 6, in the conventional non-destructive testing method using a sound emission signal, the time point at which the waveform of the destructive signal first exceeds the threshold value TH (

) or the point at which the maximum amplitude (PA) is reached (

) is calculated as the measurement time. However, this calculation method has a problem in that errors are highly likely to occur due to noise. In addition, as the error of the calculated measurement time increases, it becomes difficult to accurately estimate the location of the defective portion 11 and the occurrence time of the defective portion 11 .

7 is a graph showing a calculation period and a calculation window for calculating a measurement time of a sound emission signal. FIG. 8(a) is a graph showing a calculation window in which a rank correlation coefficient value is maximized, and FIG. 8(b) is a graph showing a change in a rank correlation coefficient value within a calculation interval.

Referring to FIGS. 6 to 8 , the voltage measured by the main sensor and the auxiliary sensor shows a small and constant amplitude value before the breakdown signal arrives. On the other hand, after the destruction signal arrives, the magnitude of the amplitude rapidly increases and then gradually decreases.

)을 산출할 수 있다. 구체적으로, 데이터 연산부(200)는, 측정된 전압 값이 가장 급격하게 증가하는 시점을, 측정 시간(

)으로 산출할 수 있다. 보다 구체적으로, 데이터 연산부(200)는, 측정된 전압 값이 시간에 따라 증가하는 경향이 가장 큰 순간을, 측정 시간(

)으로 산출할 수 있다.The data calculation unit 200, based on the characteristics of the destruction signal as described above, the measurement time of the main sensor and the auxiliary sensor (

) can be calculated. Specifically, the data calculation unit 200 determines the point at which the measured voltage value most rapidly increases during the measurement time (

) can be calculated. More specifically, the data calculation unit 200 determines the moment when the measured voltage value has the greatest tendency to increase with time, the measurement time (

) can be calculated.

)을 산출하는 방법을 보다 상세하게 설명하기로 한다.Hereinafter, the data calculation unit 200 measures the time (

) will be described in more detail.

First, the data calculation unit 200 may set a calculation period. Here, the calculation period may mean a period in which the destruction signal may have reached the sensor module 100 .

)을 기준으로 대칭되도록 설정될 수 있다. 구체적으로, 산출 구간은, 문턱값(TH)을 최초로 초과한 시점(

)보다 일정시간 빠른 시점으로부터, 일정시간 이후 시점까지의 구간일 수 있다. 이때, 산출 구간의 폭은, 진단대상물(10)의 특성에 따라, 사용자에 의해 설정될 수 있다.The calculation period is, for example, the time when the threshold value (TH) is first exceeded (

) can be set to be symmetrical based on. Specifically, the calculation interval is the time point when the threshold value TH is first exceeded (

) may be a section from a time point earlier than a certain time to a time point after a certain time. In this case, the width of the calculation section may be set by the user according to the characteristics of the object to be diagnosed 10 .

Also, the data calculation unit 200 may create a calculation window. The calculation window, as shown in FIG. 7 , may be a means for grouping some of the data within the calculation interval.

The data operator 200 may analyze a trend in which the voltage value changes with time within the calculation window. Specifically, the data operator 200 calculates data within the calculation window (eg, (first time, first voltage), (second time, second voltage), (third time, third voltage)... By comparison, the tendency of the voltage to change over time can be quantified.

In order to quantify the tendency of the voltage to change over time, the data calculator 200 may use a Kendall rank correlation coefficient as an example. Here, since a method for obtaining the Kendall rank correlation coefficient is widely known, a detailed description thereof will be omitted.

At this time, of course, an embodiment in which the data calculation unit 200 uses another digitization method other than the Kendall correlation coefficient is also possible.

) 과 최대진폭(PA)에 이르는 시점(

)의 차이와 같을 수 있다. 그러나, 산출 윈도우의 폭은 이에 한정되지는 않으며, 진단대상물(10)의 특성에 따라 다르게 설정될 수도 있다.The width of the calculation window may be smaller than the width of the calculation interval. The width of the calculation window, in one embodiment, first exceeds the threshold value (TH) (

) and the point at which the maximum amplitude (PA) is reached (

) may be equal to the difference in However, the width of the calculation window is not limited thereto and may be set differently according to the characteristics of the diagnosis object 10 .

At least one calculation window may be created. As an example, a plurality of calculation windows may be generated, and the plurality of calculation windows may be arranged at equal intervals within a calculation section.

In this case, the data calculation unit 200 may obtain Kendall correlation coefficients for each of a plurality of calculation windows and compare them. In addition, the measurement time can be calculated in the calculation window in which the value of the Kendall correlation coefficient is the largest. As an example, based on the width of the calculation window, the time value of the center point may be calculated as the measurement time.

)으로 산출함으로써, 파괴 신호가 메인센서 및 보조센서에 도달한 시간을 보다 정확하게 제공할 수 있다.In this way, the data calculation unit 200 determines the point at which the voltage value increases most rapidly within the calculation period as the measurement time (

), it is possible to more accurately provide the time at which the destruction signal reaches the main sensor and the auxiliary sensor.

In addition, by calculating the measurement time using the tendency of the voltage value to change, not the voltage value at a specific point in time, it is possible to prevent the occurrence of errors due to noise. Accordingly, it is possible to provide accurate test results even in the case of inspecting the diagnostic object 10 in operation.

Hereinafter, with reference to FIG. 2 again, the data analyzer 300 will be described.

)과, 센서 모듈(100)의 위치 정보를 이용하여, 결함부(11)의 위치 및 파괴 신호의 전파 속도를 분석할 수 있다.The data analysis unit 300, the measurement time (calculated by the data operation unit 200)

) and the location information of the sensor module 100, it is possible to analyze the location of the defective part 11 and the propagation speed of the destruction signal.

Here, the location information of the sensor module 100 is the distance L between the first main sensor S1 and the second main sensor S2 and the distance between the first main sensor S1 and the first auxiliary sensor G1. (E1) and the distance E2 between the second main sensor S2 and the second auxiliary sensor G2.

The position of the defective part 11 may be defined as a distance d at which the defective part 11 is separated from the first main sensor S1, as an example. At this time, the defective part 11 may be spaced apart from the first main sensor S1 , the second main sensor S2 , the first auxiliary sensor G1 and the second auxiliary sensor G2 at different distances.

)은 각각 상이할 수 있다.In this case, the destruction signal generated from the defective part 11 moves toward the first main sensor S1, the second main sensor S2, the first auxiliary sensor G1 and the second auxiliary sensor G2 at the same speed. It propagates, but the arrival time may be different. That is, the measurement time of the first main sensor S1, the second main sensor S2, the first auxiliary sensor G1 and the second auxiliary sensor G2 (

) may be different from each other.

)과 센서 모듈(100)의 위치 정보에 기반하여, 제1 계산식을 정의할 수 있다. 일 실시 예로, 제1 계산식은 하기 수학식 (1)-1, (1)-2, (1)-3 및 (1)-4와 같이 정의될 수 있다.The data analysis unit 300, the measurement time (

) and the location information of the sensor module 100, a first calculation formula may be defined. As an example, the first calculation formula may be defined as Equations (1)-1, (1)-2, (1)-3, and (1)-4 below.

…(1)-1

… (1)-1

…(1)-2

… (1)-2

…(1)-3

… (1)-3

…(1)-4

… (1)-4

At this time, the symbols used in Equations (1)-1, (1)-2, (1)-3 and (1)-4 are defined as follows.

d: location of defects

v: propagation speed of the destruction signal

L: distance between the first main sensor and the second main sensor

E1: Distance between the first main sensor and the first auxiliary sensor

E2: Distance between the second main sensor and the second auxiliary sensor

: 제1 메인센서와 제2 메인센서의 측정 시간 차이

: Measurement time difference between the first main sensor and the second main sensor

: 제1 메인센서와 제2 보조센서의 측정 시간 차이

: Measurement time difference between the first main sensor and the second auxiliary sensor

: 제1 보조센서와 제2 메인센서의 측정 시간 차이

: Measurement time difference between the first auxiliary sensor and the second main sensor

: 제1 보조센서와 제2 보조센서의 측정 시간 차이

: Measurement time difference between the first auxiliary sensor and the second auxiliary sensor

Also, the first calculation equation may be expressed as a matrix equation as shown in Equation (a) below.

…(a)

… (a)

Based on the first calculation formula, the data analyzer 300 may define a second calculation formula. As an example, the second calculation equation may be defined as the following determinants (2)-1, (2)-2, (2)-3, and (2)-4.

…(2)-1

… (2)-1

…(2)-2

… (2)-2

…(2)-3

… (2)-3

…(2)-4

… (2)-4

At this time, the symbols used in the determinants (2)-1, (2)-2, (2)-3 and (2)-4 are defined as follows.

: 행렬 X의 전치행렬

: transpose matrix of matrix X

) 값과, 센서 모듈(100)의 위치 정보(L, E1, E2의 값)을 대입하여, 결함부(11)의 위치와 파괴 신호의 전파 속도를 계산할 수 있다.The data analysis unit 300 calculates the measurement time calculated by the data operation unit in the second calculation formula (

) value and the location information (values of L, E1, and E2) of the sensor module 100, the position of the defective part 11 and the propagation speed of the destruction signal can be calculated.

In addition, the position values of the four different defective parts 11 may be obtained by substituting the propagation speed values calculated in the second calculation formula into the first calculation formula. In this case, the position values of the four defective parts 11 may be different from the position values of the defective parts 11 calculated by the second calculation formula.

In this case, the data analyzer 300 may set a weight by comparing the position value of the defective part calculated by the first calculation formula with the position value of the defective part calculated by the second formula. As an example, the weight may be defined as in Equations (3)-1 and (3)-2 below.

,

,

…(3)-1

,

,

… (3)-1

,

,

…(3)-2

,

,

… (3)-2

At this time, the symbols used in Equations (3)-1 and (3)-2 are defined as follows.

: 수학식 (1)-1의 가중치

: Weight of Equation (1)-1

: 수학식 (1)-2의 가중치

: Weight of Equation (1)-2

: 수학식 (1)-3의 가중치

: Weight of Equation (1)-3

: 수학식 (1)-4의 가중치

: Weight of Equation (1)-4

: 제2 계산식으로 계산된 결함부의 위치

: Position of the defective part calculated by the second calculation formula

: 수학식 (1)-i로 계산된 결함부의 위치

: Position of the defective part calculated by Equation (1)-i

Table (1) below shows an example of applying weights in this way.

[Table (1)]

Referring to Table (1), as the calculated position value of the defective part 11 is closer to the position value of the defective part 11 calculated in the second calculation formula, a higher weight can be assigned to the corresponding formula. That is, among Equations (1)-1 to (1)-4, an equation that calculates a result value similar to the second calculation equation may be regarded as a more accurate equation. In addition, a weight value may be set high so that a value calculated from an expression with high accuracy is more greatly reflected in a final result value.

Based on the set weight, the data analysis unit 300 may define a third calculation formula. Specifically, the data analysis unit 300 may define a third calculation equation by reflecting a weight set in the second calculation equation. As an example, the third calculation formula may be defined as Equation (4) below.

…(4)

… (4)

) 값과, 센서 모듈(100)의 위치 정보(L, E1, E2의 값)을 대입하여, 결함부(11)의 위치와 파괴 신호의 전파 속도를 계산할 수 있다. The data analysis unit 300 calculates the measurement time calculated by the data operation unit in the third calculation formula (

) value and the location information (values of L, E1, and E2) of the sensor module 100, the position of the defective part 11 and the propagation speed of the destruction signal can be calculated.

In addition, the position values of the four defective parts 11 may be obtained by substituting the propagation velocity values calculated in the third calculation equation into the first calculation equation described above. At this time, the position values of the four defective parts 11 may be different from the position values of the defective parts 11 calculated by the third calculation formula.

In this case, the data analyzer 300 may reset the weight by comparing the position value of the defective part calculated by the first calculation formula with the position value of the defective part calculated by the third formula. At this time, since the method of resetting the weight is the same as or similar to the method of setting the weight, a detailed description thereof will be omitted.

The data analysis unit 300 may recalculate the position of the defective part 11 and the propagation speed of the destruction signal using the third calculation formula to which the reset weight is applied. Then, as described above, the process of resetting the weights and applying the reset weights to the third calculation equation to recalculate may be repeated.

As this process is repeated, the position and propagation speed value of the defect part 11 calculated by the third formula may converge to a specific value. Also, the data analysis unit 300 may calculate the converged position and propagation speed value of the defective part 11 as a final result value.

Specifically, the data analysis unit 300, when the amount of change in the position and propagation speed value of the defective part 11 calculated in the third calculation formula is smaller than a preset criterion, the last calculated position of the defective part 11 and The propagation speed value can be calculated as the final result. That is, when the value calculated by the third calculation formula satisfies the following Equation (b), the analysis may be terminated.

…(b)

… (b)

At this time, the symbols used in Equation (b) may be defined as follows.

: 제3 계산식으로 계산된 값의 변화량

: The amount of change in the value calculated by the third formula

: 미리 설정된 기준값

: preset reference value

Using the finally calculated position and propagation speed values of the defective part 11 , the data analysis unit 300 may calculate the location coordinates of the defective part 11 and the occurrence time of the defective part 11 . And, it can be displayed on a separate display device (not shown). Accordingly, the user can easily check information on the defective part 11 .

In this way, the data analysis unit 300 compares the values calculated in the first calculation formula, the second calculation formula, and the third formula, and repeatedly resets the weight, thereby positioning and destroying the defective part 11 with higher accuracy. It can provide the value of the speed of propagation of the signal.

9 is a flowchart illustrating a process of a method for diagnosing a defect location using a sound emission signal according to an embodiment of the present invention.

Referring to FIG. 9 , a method for non-destructive testing of an acoustic emission signal according to embodiments of the present invention may be performed as follows.

First, in step S100, the sensor module 100 may measure a normal signal from the diagnostic target object 10 operating in a state where no destruction occurs, and may measure a destruction signal from the test piece.

Next, in step S200, it is possible to compare the measured characteristics of the normal signal and the disrupted signal, and set reference parameters and criterion for distinguishing the normal signal from the disrupted signal.

Next, in step S300, the sensor module 200 may measure an acoustic emission signal from the diagnostic object 10 in operation.

Next, in step S400, the data calculation unit 200 may select a disruptive signal from the measured acoustic emission signal.

Next, in step S500, the data calculation unit 300 may calculate the measurement time of the selected destruction signal.

Next, in step S600, an analysis step of analyzing the position of the defective part 11 and the propagation speed of the destruction signal using the calculated measurement time and the position information of the sensor module 100 by the data analyzer 300. can be done

10 is a flow chart showing the process of performing the analysis step in detail.

Referring to FIG. 10 , the analysis step (S600) according to an embodiment of the present invention may be performed as follows.

First, in step S610, the data analyzer 300 may define a first calculation formula based on the location information of the sensor module 100 and the calculated measurement time.

Next, in step S620, the data analysis unit 300 defines a second calculation formula based on the defined first calculation formula, and substitutes the location information of the sensor module 100 and the calculated measurement time into the second calculation formula, The position of the defective portion 11 and the propagation speed of the destruction signal can be calculated.

Next, in step S630, the position values of the four defective parts 11 may be obtained by substituting the propagation speed values calculated by the second calculation formula into the first calculation formula.

Next, in step S640, a weight may be set by comparing the position value of the defective part 11 calculated by the second calculation formula and the first formula.

Next, in step S650, a third calculation equation in which the weight set in the second calculation equation is reflected may be defined. In addition, the location of the defective portion 11 and the propagation speed of the destruction signal may be calculated by substituting the location information of the sensor module 100 and the calculated measurement time into the third calculation formula.

Next, in step S660 , the propagation speed calculated in the third calculation equation is substituted into the first calculation equation to obtain the position values of the four defective parts 11 .

Next, in step S670, it may be determined whether the resultant value of the third calculation formula has sufficiently converged.

If it is determined that the result of the third calculation formula has not sufficiently converged, the weights may be reset in step S680. Steps S650, S660, and S670 may be performed again.

If it is determined that the resultant value of the third calculation formula has sufficiently converged, in step S690, the position value and propagation speed value of the defective part 11 calculated in the third calculation formula can be calculated as the final result value.

In the non-destructive inspection method using acoustic emission signals according to an embodiment of the present invention, by simplifying the diagnosis object 10 in one dimension and inspecting it, the inspection can be performed using only a pair of main sensors and a pair of auxiliary sensors.

In addition, a pair of main sensors and a pair of auxiliary sensors can collect acoustic emission signals generated inside the area to be diagnosed and simultaneously remove noise generated outside the area to be diagnosed. Accordingly, more efficient inspection can be performed by excluding unnecessary data from the analysis target.

In addition, by calculating the measurement time using the change trend of the voltage with time, it is possible to prevent the occurrence of errors due to noise and provide a more accurate measurement time. Accordingly, a non-destructive test with high reliability can be performed even when the object to be diagnosed 10 is in operation.

In addition, by comparing the values calculated in the first calculation formula, the second calculation formula, and the third formula, and repeatedly resetting the weight, it is possible to provide a more accurate position of the defective part 11 and a propagation speed value of the destruction signal. there is. Accordingly, the reliability of the non-destructive test result may be increased.

The method according to the embodiment of the present invention described above may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. A computer-readable recording medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on a computer-readable recording medium may be specially designed and configured for the embodiment of the present invention, or may be known and usable to those skilled in the art in the field of computer software. Computer-readable recording media include magnetic recording media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, ROMs, RAMs, and flash memories. , includes hardware configured to store and execute program instructions. Program instructions include machine language codes generated by a compiler and high-level language codes that can be executed on a computer using an interpreter. The hardware may be configured to act as one or more software modules to process the method according to the present invention and vice versa.

A method according to an embodiment of the present invention may be executed in an electronic device in the form of program commands. Electronic devices include portable communication devices such as smart phones and smart pads, computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, and home appliances.

A method according to an embodiment of the present invention may be provided by being included in a computer program product. Computer program products may be traded between sellers and buyers as commodities. The computer program product may be distributed in the form of a machine-readable recording medium or online through an application store. In the case of online distribution, at least part of the computer program product may be temporarily stored or temporarily created in a storage medium such as a manufacturer's server, an application store server, or a relay server's memory.

Components according to embodiments of the present invention, for example, each module or program, may be composed of one or more sub-components, and some of these sub-components may be omitted, or other sub-components may be further added. can be included Some components (modules or programs) may be integrated into one entity and perform the same or similar functions performed by each corresponding component prior to integration. Operations performed by modules, programs, or other components according to embodiments of the present invention are sequentially, parallelly, repetitively, or heuristically executed, or at least some operations are executed in a different order, are omitted, or other operations are added. It can be.

The above description of the present invention is for illustrative purposes, and those skilled in the art can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts should be interpreted as being included in the scope of the present invention.

1: non-destructive testing device
10: diagnosis object
11: defective part
100: sensor module
200: data calculation unit
300: data analysis unit

Claims (10)

A step of measuring an acoustic emission signal generated from an object to be diagnosed using a sensor module, wherein the sensor module is provided with a pair of main sensors disposed on the object and a pair of auxiliary sensors spaced apart from the pair of main sensors. ;
a selection step of selecting, by a data operation unit, only a destruction signal generated from a defective unit among the sound emission signals;
A calculation step of calculating a measurement time, which is a time at which the destruction signal reaches the main sensor and the auxiliary sensor, by a data calculation unit; and
A non-destructive inspection method using a sound emission signal comprising: a data analysis unit analyzing the position of the defective part and the propagation speed of the destructive signal using the measurement time and the location information of the sensor module. According to claim 1,
Prior to the screening step,
A normal signal measuring step in which the sensor module measures a normal signal in a diagnosis target that operates in a state where no destruction has occurred; and
Selecting a reference parameter for distinguishing the normal signal from the destruction signal, and using the selected reference parameter, setting a criterion for determining whether or not destruction of the diagnosis object has occurred; further comprising a sound Non-destructive testing method using emission signals. According to claim 2,
In the selection step,
Comparing the selected reference parameter with the criterion to determine whether or not destruction of the diagnosis target has occurred;
When it is determined that destruction has occurred in the diagnosis target, a non-destructive testing method using an acoustic emission signal to select only the destruction signal classified according to the determination criterion. According to claim 1,
The sensor module measures the sound emission signal by collecting voltage values input to the main sensor and the auxiliary sensor in real time,
In the calculation step,
A non-destructive inspection method using an acoustic emission signal that calculates a moment in which the voltage value has the greatest tendency to increase with time as the measurement time. According to claim 4,
In the calculation step,
A non-destructive inspection method using an acoustic emission signal, which uses a Kendall rank correlation coefficient to analyze a trend in which the voltage value changes over time. According to claim 1,
The analysis step is
defining a first calculation formula based on the location of the sensor module and the measurement time; and
Calculating the location of the defect part and the propagation speed of the destruction signal using a second calculation equation defined based on the first calculation equation;
The first calculation formula is defined by the following equations (1)-1, (1)-2, (1)-3 and (1)-4,

… (1)-1

… (1)-2

… (1)-3

… (1)-4
The second calculation formula is defined by the following determinants (2)-1, (2)-2, (2)-3 and (2)-4,

… (2)-1

… (2)-2

… (2)-3

… (2)-4
In Equation (1) and the determinant (2),
d: location of defects
v: propagation speed of the destruction signal
L: distance between the first main sensor and the second main sensor
E1: Distance between the first main sensor and the first auxiliary sensor
E2: Distance between the second main sensor and the second auxiliary sensor

: Measurement time difference between the first main sensor and the second main sensor

: Measurement time difference between the first main sensor and the second auxiliary sensor

: Measurement time difference between the first auxiliary sensor and the second main sensor

: Measurement time difference between the first auxiliary sensor and the second auxiliary sensor

: A non-destructive inspection method using an acoustic emission signal, defined as a transposed matrix of matrix X. According to claim 6,
The analysis step is
calculating a position of the defect part by substituting the propagation speed value calculated by the second calculation formula into the first calculation formula; and
Further comprising setting a weight by comparing the position value of the defective part calculated by the second calculation formula with the position value of the defective part calculated by the first formula,
The weight is defined by the following equations (3)-1 and (3)-2,

,

,

… (3)-1

,

,

… (3)-2
In the above equations (3)-1 and (3)-2,

: Weight of Equation (1)-1

: Weight of Equation (1)-2

: Weight of Equation (1)-3

: Weight of Equation (1)-4

: Position of the defective part calculated by the second calculation formula

: A non-destructive inspection method using an acoustic emission signal, defined as the position of the defective part calculated by Equation (1)-i. According to claim 7,
The analysis step is
Defining a third calculation equation by reflecting the weight in the second calculation equation, and calculating the location of the defect part and the propagation speed by the third calculation equation; further comprising,
The third calculation formula is defined by Equation (4) below,

… (4)
Non-destructive testing method using acoustic emission signal. According to claim 8,
The analysis step is
The non-destructive inspection method using acoustic emission signals further comprising: calculating the position of the defective part by substituting the propagation speed value calculated by the third calculation formula into the first calculation formula. According to claim 9,
The analysis step is
resetting the weight by comparing the position value of the defective part calculated by the third formula with the position value of the defective part calculated by the first formula; and
Further comprising the step of recalculating the position of the defective part by reflecting the reset weight in the third calculation formula; non-destructive inspection method using an acoustic emission signal.

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