KR101100675B1 - Method for sensing demage of composite material using Discrete Wavelet Transform - Google Patents

Abstract

The present invention relates to a damage detection method of a structure using a DWT, and more particularly, the numerical integral value of the envelope of a high frequency extraction component transformed by a discrete wavelet transform (DWT) of an acoustic emission signal generated when the structure is damaged. The present invention relates to a method of detecting damage of a used structure.
According to the present invention, the damage generated inside the structure can be detected using a wavelet as an acoustic emission signal according to the damage inside the structure.

Description

Damage detection method of composite material using DTV {{Method for sensing demage of composite material using Discrete Wavelet Transform}

The present invention relates to a damage detection method of a composite material using a DWT, and more particularly, the envelope of a high frequency extraction component transformed by a DWT (Discrete Wavelet Transform) of an acoustic emission signal generated when a composite material (ie, a structure) is damaged. The present invention relates to a method of detecting damage of a composite material using a numerical integral value of envelop.

A composite material is a material in which materials of different types are mated together and have characteristics that cannot be obtained with a single material. Of these, carbon nano-material (CNM) -reinforced polymer composites such as carbon nano-tube (CNT) and carbon nano-fiber (CNF) have recently been used because of their excellent mechanical and electrical properties. Attention is rapidly increasing.

By the way, when damage occurs in such a composite structure, there was conventionally an electro-micromechanical test method using an electrical resistance measurement as a method for checking the damage.

This electro-micromechanical test is a new economically non-destructive evaluation method for conducting reinforcing fibers themselves as conductive sensors, which can be applied to load / strain detection of reinforcing fibers and evaluation of interfacial properties of composites.

However, there is a disadvantage in that the specific failure mode (fracture mode or failure mode) of the composite structure cannot be determined when the electro-micromechanical test method is used. In other words, it is not possible to determine whether the damage is caused by interlaminar or damaged internal fibers.

The present invention is to provide a method for detecting damage by using the acoustic emission signal according to the damage inside the structure, in order to overcome the disadvantages according to the prior art.

Another object of the present invention is to provide a method for analyzing a cause of damage in a structure by using an acoustic emission signal according to damage in the structure.

The present invention provides a damage detection method of a structure using a discrete wavelet transform (DWT) to achieve the object raised above.

Damage detection method of the structure using the DWT, the detection step of detecting the acoustic emission signal generated according to the damage of the structure by the acoustic sensor as a source signal; A component decomposition step of decomposing the source signal into a plurality of approximation components and detail components using discrete wavelet transform; A selection step of selecting only an ultra high frequency region from the plurality of subdivisions; An envelope step of enveloping only the ultra-high frequency region; An envelope area calculation step of calculating the area of the envelope of the plurality of detail components by integrating an enveloped ultra-high frequency region; And comparing the areas of the plurality of subcomponents with each other to calculate a ratio of the area of the plurality of subcomponents to the total area to determine whether the composite material is damaged by an area ratio change of the envelope of the plurality of subcomponents. It includes a step of determining whether or not.

In addition, the component decomposition step is to decompose the plurality of approximate components and sub-components step by step according to the frequency band, the source component is characterized in that the sum of both the final approximation component and the plurality of sub-components of the plurality of approximate components do.

Here, the structure is characterized in that any one of a single material structure composed of a single material or a composite structure composed of laminated or bonded materials of different properties.

Here, the sound detection sensor is characterized in that it is installed outside or inside the structure.

Here, when the sound sensor is installed in the laminated structure of the composite structure may be laminated between the structures.

Here, the frequency band is characterized in that it is divided differently according to the sampling frequency.

In addition, the area amount is characterized in that the damage amount of the structure.

According to the present invention, the damage generated inside the structure can be detected using a wavelet as an acoustic emission signal according to the damage inside the structure.

In addition, another effect of the present invention is to cause the damage inside the structure by converting the acoustic emission signal according to the damage inside the structure using a wavelet, and from the transformed extracted value to obtain the change in the area ratio of the envelope for each component through several steps It is possible to analyze it.

1 is a system conceptual diagram for implementing a damage detection method of a structure using a discrete wavelet transform (DWT) according to an embodiment of the present invention.
2 is a flow chart showing a damage detection process of a structure using a DWT according to an embodiment of the present invention.
3 is a view showing a wavelet decomposition structure according to an embodiment of the present invention.
Figure 4 is an exploded view of the approximate and sub-components of the source signal generated from damage of the structure according to an embodiment of the present invention step by step according to the frequency band.
FIG. 5 is a diagram illustrating only ultra-high frequency ranges from detail components according to an embodiment of the present invention.
FIG. 6 is a view showing the area of sub-components integrating only the enveloped microwave region according to an embodiment of the present invention.
7 is a graph of an acoustic emission (AE) signal showing a steady state of a structure in accordance with one embodiment of the present invention.
8 is a graph of an acoustic emission signal showing a damaged state of a structure according to an embodiment of the present invention.

Hereinafter, a damage detection method of a structure using a discrete wavelet transform (DWT) according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a system conceptual diagram for implementing a damage detection method of a structure using a discrete wavelet transform (DWT) according to an embodiment of the present invention. Referring to FIG. 1, the system includes a structure 100, an acoustic sensor 110 that detects an acoustic emission (AE) signal resulting from damage to the structure 100, and from the acoustic sensor 110. The data storage device 120 receives the detected signal and stores the data, and the signal processing device 130 receives the signal from the storage device 120 and processes the signal to analyze the cause of damage to the structure 100.

Here, an example of the acoustic emission signal is shown in FIGS. 7 to 8. This will be described later. Briefly, FIG. 7 illustrates an acoustic emission signal when the structure 100 is in a normal state, and FIG. 8 illustrates an acoustic emission signal when the structure 100 is damaged.

A composite material, which is one of the materials constituting the structure 100, is a material that usually expresses a more effective function while combining two or more materials to form different phases physically and chemically. Composite structures are classified into fibre-reinforced composites and particle-reinforced composites according to the structure of the reinforcement, and polymer matrix composites and metal composites according to the matrix to reinforce. It can be divided into metal matrix composite and ceramic matrix composite.

In addition, the present invention is not limited thereto, and may be applied to general load-bearing structures such as metal structures, reinforced concrete structures, and polymer plastic structures.

The sound detection sensor 110 is a vibration detection sound detection sensor that detects a sound emission signal generated when the structure 100 is damaged. The sound detection sensor 110 is attached to the surface of the structure 100 or inserted into the structure 100.

The acoustic sensor 110 includes a PZT (Piezoelectric) sensor, a PolyVinyliDene Fuoride (PVDF) film sensor as well as an optical fiber sensor system that can be easily inserted into the structure. Sensors, Mahgender interference sensors, Michelson interference sensors and the like can be used.

The acoustic sensor 110 is inserted into the outer surface or the inside of the structure 100 to detect a sound emission signal generated from the structure 100 to generate a source signal. A diagram showing such a source signal is shown in FIG. This will be described later.

The data storage device 120 stores a source signal generated from the acoustic sensor 110. Of course, the data storage device 120 may include a nonvolatile memory such as a hard disk drive, a flash memory, a ferro-electric RAM (FRAM), a phase-change RAM (PRAM), a magnetic RAM (MRAM), or the like to store a source signal. Volatile memory such as Random Access Memory) may be used.

The signal processing device 130 has a source signal stored in the data storage device 120 and compares the discrete wavelet component decomposition process, the envelope process for the decomposition component, the integration process for the enveloped region, and the integrated envelope area. And analyzing the cause of damage to the structure 100 through the change in the area ratio of the envelope.

Of course, the signal processing device 130 is provided with a microprocessor (not shown), a storage device (not shown), a program, software, a display (not shown), etc. to process such a series of processes. Therefore, the signal processing device 130 analyzes the cause of damage to the structure 100 through various steps such as a discrete wavelet transform (DWT) from a source signal stored in the data storage device 120.

In addition, the signal processing device 130 may display the cause of damage to the structure 100 on the display.

Then, the concept of the discrete wavelet transform (DWT) will be briefly described before explaining the damage detection process of the structure using the DWT according to the system conceptual diagram illustrated in FIG. 1.

The wavelet transform is to decompose the source signal x (t) by transforming the magnitude and the horizontal position of the circular wavelet function. Continuous wavelet (CWT) is defined as follows.

Here, a> 0 and b∈R are parameters representing scale and translation, respectively. Ψ (t) is a wavelet solver and Ψ * represents a complex conjugate. The result of Equation 1 is the wavelet coefficient for the scale and the horizontal shift parameter.

Substituting a = 2 ^j and b = k2 ^j in Equation 1 results in a discrete wavelet transform. The constants j and k are scale and translation variables, respectively.

In one-dimensional signal decomposition using wavelets, wavelet function (Ψ) and scale function (Φ) are used. The wavelet function (Ψ) is used to obtain the detail component (D _j ) from the source signal. It is used to resolve the approximate component A _j from the signal. In DWT, the wavelet expansion and wavelet coefficient of the source signal x (t) can be expressed as follows.

Here, α _{j, k} is a wavelet coefficient of x (t), and Ψ _{j, k} is a discrete basic function made by the scale and horizontal movement of the analysis wavelet function Ψ (t). Discrete wavelet and scale functions can be written as

In the discrete wavelet function above, assuming that the horizontal shift parameter is k = 0, the wavelet function and the scale function are Ψ _{j, 0} (j = 1,2,3), Φ _{j, 0} (j = 0,1,2,3 ) And may be divided step by step according to the step of j as shown in FIG. 3 is a view showing a wavelet decomposition structure according to an embodiment of the present invention. Referring to FIG. 3, the source signal S is decomposed step by step as follows.

S = A1 + D1

  = A2 + D2 + D1

  = A3 + D3 + D2 + D1

  = A4 + D4 + D3 + D2 + D1

3 shows an example in which j = 4, and it should be understood that the present invention is not limited thereto.

The detail component and the approximate component of each step of the source signal S may be obtained through Equation 2, wherein the detail component D _j in the j stage may be expressed as follows.

Here, the source signal may be re-synthesized by performing an inverse transform process that adds all the sub-components (D _j ) to _j again.

The approximate component A _j based on the arbitrary value J can be defined as the sum of the subcomponents j> J as shown in Equation 8, from which the approximate component is A _{J -1} = A _J + D _J It can be seen that it has a property of.

Thus, wavelet transform can decompose a signal into several low resolution components by selecting different binary scales, which is called a wavelet decomposition tree. 3 is a diagram illustrating this.

3 illustrates an example in which the source signal S is decomposed in four steps using a Daubechy 4 (db4) wavelet function.

Next, a damage detection process of the structure 100 using the DWT according to an embodiment of the present invention will be described based on the concept of a discrete wavelet transform (DWT). A diagram showing this is shown in FIG. 2. Referring to FIG. 2, when damage occurs in the structure (100 of FIG. 1), sound is emitted, and the acoustic sensor 110 detects the emitted sound and detects a source signal S therefrom ( Step S200).

Using DWT, the source signal S is decomposed into approximate components A _j and sub-components D _j step by step according to the frequency band (step S210). A screen example showing this is shown in FIG. 4. That is, FIG. 4 is an exploded view of an approximate component (A _j ) and a detailed component (D _j ) obtained by dividing a source signal resulting from damage of a structure according to an embodiment of the present invention step by step according to a frequency band.

Referring to FIG. 4, the first approximation component 411 and the first subcomponent 410 are decomposed from the source signal 400, and the second approximation component 421 and the second approximation component 411 are decomposed from the first approximation component 411. The detail component 420 is decomposed, and the third approximation component 431 and the third detail component 430 are decomposed from the second approximation component 421. Finally, the fourth approximation component 441 and the fourth subcomponent 440 are decomposed from the third approximation component 431.

Of course, these approximate components 411 to 441 and sub-components 420 to 440 are decomposed in stages according to frequency bands.

Frequency band Approximation Ingredient 200-300 kHz A ₁ D ₁ 100-250 kHz A ₂ D ₂ 50-150 kHz A ₃ D ₃ 0-100 kHz A ₄ D ₄

Of course, Table 1 is illustrated for understanding, the frequency band can be configured differently according to the properties of the structure (100). For example, it is possible to divide frequency bands such as D ₁ for 200-500 kHz, D ₂ for 100-300 kHz, D ₃ for 40-160 kHz, and D ₄ for 0-80 kHz. That is, the division of the frequency band is different depending on the superscript M (sampling frequency) shown in D ₁ ^1M , D ₂ ^1M , D ₃ ^1M , D ₄ ^1M , as shown in FIGS. 7 to 8.

2, only the ultrahigh frequency region is selected from the decomposed detail component D _j (step S220). That is, referring to FIG. 4, there are places where waveforms appear intensively in detail components 410 to 440, which is an ultra-high frequency region. A diagram showing such an ultra high frequency region is shown in FIG. 5. That is, FIG. 5 is a diagram illustrating only ultra-high frequency ranges from detail components according to an embodiment of the present invention.

Referring to FIG. 5, FIG. 5A illustrates a first ultra-high frequency region 500 selected from the sub-components 410 shown in FIG. 4. FIG. 5B illustrates a second ultra-high frequency region 510 selected from the subcomponent 420 shown in FIG. 4.

FIG. 5C shows a third ultra-high frequency region 520 selected from the subcomponent 430 shown in FIG. 4. FIG. 5D illustrates a fourth ultra-high frequency region 530 selected from the subcomponent 440 shown in FIG. 4.

2, only the selected ultra-high frequency regions 500 to 530 are enveloped (step S230). Envelope is also defined as an imaginary line connecting the amplitude of a signal.

There are various types of enveloping techniques, some of which are explained for understanding the present invention include natural envelopes, pre-envelopes, and complex envelopes.

Natural envelopes are envelopes that have only positive magnitudes obtained by putting an absolute value on an analytical signal. The pre-envelope is used to describe the interpretation signal itself before taking absolute values in the natural envelope.

Complex envelopes represent complex-type envelopes in which the analysis signal itself has magnitude and phase. Since these envelope types are well known techniques, further description will be omitted for a clear understanding of the present invention.

2, in the exemplary embodiment of the present invention, both the positive and negative portions of the ultra-high frequency regions 500 to 530 selected in FIG. 5 are enveloped. That is, the entire ultra-high frequency region 500 to 530 selected in FIG. 5 is enveloped.

If only this enclosed ultra-high frequency region is integrated, it is possible to calculate the area of the detail component Dj (step S240). A diagram showing this is shown in FIG. 6. That is, FIG. 6 is a view showing the area of the detail component (D _j ) integrating only the enclosed ultra-high frequency region according to an embodiment of the present invention.

Referring to FIG. 6, FIG. 6A illustrates the area 600 of the envelope of the first subcomponent calculated by integrating the first ultra-high frequency region 500 illustrated in FIG. 5 using an envelope technique. FIG. 6B shows the area 610 of the envelope of the second subcomponent calculated by integrating the second ultra-high frequency region 510 shown in FIG. 5 by using the envelope technique.

FIG. 6C shows the area 620 of the envelope of the third subcomponent calculated by integrating the third ultra-high frequency region 520 shown in FIG. 5 using an envelope technique. FIG. 6C shows the area 630 of the envelope of the fourth subcomponent calculated by integrating the fourth ultra-high frequency region 530 shown in FIG. 5 using an envelope technique.

2, the area of the detail component (D _j ) is compared with each other, and as a result of the comparison, the amount of change in the area ratio of the envelope for each detail component (D _j ) determines whether the composite material (100 in FIG. 1) is damaged or not. (Steps S250, S260).

In other words, when the area of the subcomponent D _j is calculated, it is possible to obtain the area occupied by the subcomponents D _j . That is, referring to FIG. 6, the sum of the detailed components D1 to D4 results in a total area of 100%. Thus, the area 600 of the envelope of the first subcomponent, the area 610 of the envelope of the second subcomponent, the area 620 of the envelope of the third subcomponent, and the area 630 of the envelope of the fourth subcomponent. In comparison, the area ratio of the area of each subcomponent to the total area is calculated.

Therefore, whether or not the damage of the structure 100 has occurred can be determined through the ratio of D ₁ , D ₂ , D ₃ , D ₄ . For example, if the area ratio is D ₁ > D ₂ > D ₃ > D ₄ before the damage, the magnitude of the rate change occurs as D ₄ > D ₃ > D ₁ > D ₂ It can be determined whether the damage occurs in the structure (100).

In the case of damage size prediction, when the damage occurs, the ratio size occurs, for example, in the order of D ₄ > D ₃ > D ₁ > D ₂ , but even if more damage occurs, the ratio itself does not change significantly. do.

However, in the case of more damage, D ₄ '> D ₃ '> D ₁ '> D ₂ ', D ₄ '> D ₄ , D ₃ '> D ₃ , D ₁ '> D ₁ , D ₂ '> D _2, so the damage size can be determined by comparing the data with the standardized data. Of course, for this purpose, the standardized data is stored in the signal processing device 130 shown in FIG.

Therefore, as described above, it is possible to analyze the cause of damage to the structure 100 by the amount of change in this area ratio. This is because the area amounts of D ₁ , D ₂ , D ₃ , and D ₄ are damage amounts of the structure 100. For example, referring to FIG. 6, since the area 600 of the envelope of the first subcomponent is larger than the areas 610 to 630 of the envelope of the other subcomponent, it may be determined that there is a major damage on the D ₁ side. .

In this case, it can be seen, for example, as damage to the fibers inside the structure 100 according to comparison of the standardized data. On the contrary, when D ₃ and D ₄ are large, it may be determined as an interlayer damage of the structure 100.

7 is a graph of an acoustic emission signal showing a steady state of a structure in accordance with one embodiment of the present invention. Referring to FIG. 7, the x axis represents time, the y axis represents amplitudes of D ₁ , D ₂ , D ₃ , D _4, and S (source signal), and the superscript 1M represents a sampling frequency. When there is no damage to the structure (100 of FIG. 1), as shown in Figure 7, D ₁ , D ₂ , D ₃ , D ₄ does not appear a damage signal.

8 is a graph of an acoustic emission signal showing a damaged state of a structure according to an embodiment of the present invention. Referring to FIG. 8, when damage occurs to the structure 100, damage signals 800 and 810 appear. In other words, D _3, the damage signal (810), D ₄ is shown the damage signal (800).

Although one preferred embodiment of the present invention has been described above with reference to the accompanying drawings, the scope of the present invention is not limited to this embodiment, it will be understood by those skilled in the art that numerous modifications are possible. Accordingly, the scope of the invention should be defined by the appended claims and equivalents thereof.

100: structure 110: acoustic detection sensor
120: data storage device 130: signal processing device
400: source signal
410, 420, 430, 440: detail component (A _i )
411, 421, 431, 441: approximate component (D _i )
500, 510, 520, 530: Ultra-high frequency range of detail component (D _i )
600, 610, 620, 630: area of the envelope per detail component (D _i )

Claims (7)

Detecting a sound emission signal generated according to damage of the structure by the sound detection sensor as a source signal;
A discrete wavelet transform is used to decompose the source signal into a plurality of approximation components belonging to the frequency band and a plurality of detail components according to the frequency band of the source signal, and the sum of the plurality of detail components is one of the plurality of approximation components. Component decomposition step defined by any one;
A screening step of selecting only an ultra-high frequency region from the plurality of detail components;
An envelope step of enveloping only the ultra-high frequency region;
An envelope area calculation step of calculating the area of the envelope of the plurality of detail components by integrating an enveloped ultra-high frequency region; And
Comparing the area of the plurality of detail components to calculate the ratio occupied by the area of the plurality of detail components to the total area to determine whether the damage of the structure by the change in the area ratio of the envelope of the plurality of detail components step
Damage detection method of the structure using a DWT (Discrete Wavelet Transform) comprising a. The method of claim 1,
The component decomposition step decomposes the plurality of approximate components and detail components step by step according to the frequency band,
And the source component is a sum of a final approximation component and the plurality of detail components among the plurality of approximation components. The method of claim 2,
The structure is a damage detection method of a structure using a DWT is any one of a single structure or a composite structure consisting of laminated or bonded material of different properties. The method of claim 3, wherein
Damage detection method of the structure using the DWT is the acoustic sensor installed outside or inside the structure. The method of claim 4, wherein
Damage detection method of a structure using a DWT stacked between the structure when the acoustic sensor is installed inside the structure. The method of claim 2,
The frequency band is damaged detection method of the structure using a DWT divided differently according to the sampling frequency. The method of claim 2,
The area amount of the plurality of detail components is damage detection method of the structure using a DWT of the damage amount of the structure.

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