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Carbon fibre composites have a promising application future of the vehicle, due to its excellent physical properties. Debonding is a major defect of the material. Analyses of wave packets are critical for identification of the defect on ultrasonic nondestructive evaluation and testing. In order to isolate different components of ultrasonic guided waves (GWs), a signal decomposition algorithm combining Smoothed Pseudo Wigner-Ville distribution and Vold–Kalman filter order tracking is presented. In the algorithm, the time-frequency distribution of GW is first obtained by using Smoothed Pseudo Wigner-Ville distribution. The frequencies of different modes are computed based on summation of the time-frequency coefficients in the frequency direction. On the basis of these frequencies, isolation of different modes is done by Vold–Kalman filter order tracking. The results of the simulation signal and the experimental signal reveal that the presented algorithm succeeds in decomposing the multicomponent signal into monocomponents. Even though components overlap in corresponding Fourier spectrum, they can be isolated by using the presented algorithm. So the frequency resolution of the presented method is promising. Based on this, we can do research about defect identification, calculation of the defect size, and locating the position of the defect.

Carbon fibre composite is widely used in modern industry, such as aerospace domain and military products, because of its high strength and light weight. At present, such a material has been generalized to automotive industry, obviously reducing the weight of automobile. Debonding defect is a major defect of the carbon fibre composites. A great number of investigations of the nondestructive evaluation and testing (NDE/NDT) have done research for this type of defect [

Currently, ultrasonic guided wave (GW) testing has emerged as a popular NDE/NDT technique. The method can estimate the location, severity, and type of defects. Successful applications of defect identification of carbon fibre composites have been done [

A number of scholars have done investigations about signal processing methods of GWs. Kercel et al. [

EMD, which can isolate adaptively different components, was proposed by Huang in 1998 [

In 1993, Vold and Leuridan [

The rest of this paper is organized as follows. Section

Wigner-Ville distribution has a fine time-frequency resolution and can reach the low boundary of Heisenberg uncertainty principle. It is defined as [

Isolation of different modes is important for defect identification by ultrasonic guided waves. On this basic, we can locate the defect and evaluate the defect size. Therefore, VKF_OT is employed to separate wave packages.

In this paper, the angular-displacement VKF_OT techniques are adapted. The method is used to obtain the tracked components by minimizing the energy of errors for both the structural and data equations by mean of one of the least squares approaches [

The

As the tracked component

A measured signal

Let

The terms with negative indexes in (

As mentioned above, SPWVD has a promising time-frequency resolution. Therefore, we obtain frequencies and durations of modes from SPWVD distributions of testing guided waves. Furthermore, VKF_OT is adapted to realize isolation of different wave packages with obtained mode frequencies. Finally, the final mode waveforms are cut out from the wave packages of modes by durations of modes. The processing steps of the extension algorithm are shown in Figure

The different steps of the algorithm presented in the paper.

In Section

We construct a sample signal to illustrate the presented algorithm,

The curve of the sample signal in time domain.

Firstly, we employ SPWVD for the sample signal to obtain the corresponding time-frequency panel, which is shown in Figure

The representation of the sample signal by using SPWVD.

The Fourier spectrum of the sample signal.

After that, (

The different frequency-group summations of the time-frequency panel of the sample signal.

And then, the primary IAs of different modes are obtained by the peak-track algorithm. The filters in time domain of different modes are obtained by employing (

The filters in time domain of different modes: (a) mode at 300 kHz, (b) mode at 55 kHz, and (c) mode at 50 kHz.

Finally, we conduct time-domain filter for the result of VKF_OT, and the results are shown in Figure

The decomposition result and the original modes of the sample signal

The errors of decomposition result of the sample signal

To compare with EEMD, the sample signal is also processed by this decomposition method. Figure

Correlation coefficients between IMFs and the original signal.

The IMFs 1–4 in the EEMD of the sample signal and the corresponding Fourier spectrums: (a) the IMFs and (b) the corresponding Fourier spectrums.

The material of the specimen is a specific composite material. The size is 400 mm × 300 mm × 3 mm and contains 15 layers. The corresponding size diagram is presented in Figure

The size diagram of the specimen.

Figure

The diagram of the testing principle.

The GWs collected in the experiment: (a) no defect, (b) 20 mm, and (c) 30 mm.

Figure

The SPWVD representations of the GWs in the experiment: (a) no defect, (b) 20 mm, and (c) 30 mm.

The different frequency-group summations of the time-frequency panel of the experimental signals: (a) no defect, (b) 20 mm, and (c) 30 mm.

The decomposition result of experimental signals by using the presented algorithm: (a) no defect, (b) 20 mm, and (c) 30 mm.

This paper presents a decomposition algorithm aiming to analyze the characteristics of ultrasonic GWs generated in a NDT for the debonding in a type of composite material by combining SPWVD and VKF_OT. The presented method succeeds in isolating different GW modes. On the basis of the presented algorithm, the characteristics of the experimental signals were investigated. Some conclusions, which are valuable for identification of defect, calculation of defect size, and locating defect, are obtained. The technique also can be applied in analogue NDTs and NDEs on the basic of the ultrasonic GWs. Further research will be done to validate the feasibility for locating defects by the algorithm.

The authors declare that they have no conflicts of interest.