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The construction quality of the bolt is directly related to the safety of the project, and, as such, it must be tested. In this paper, the improved complete ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt detection signal analysis. The ICEEMD is used in order to decompose the anchor detection signal according to the approximate entropy of each intrinsic mode function (IMF). The noise of the IMFs is eliminated by the wavelet soft threshold denoising technique. Based on the approximate entropy and the wavelet denoising principle, the ICEEMD-De anchor signal analysis method is proposed. From the analysis of the vibration analog signal, as well as the bolt detection signal, the result shows that the ICEEMD-De method is capable of correctly separating the different IMFs under noisy conditions and also that the IMF can effectively identify the reflection signal of the end of the bolt.

The bolt anchoring system is subject to the geological conditions and the construction technology effect. If there are any hidden dangers that have not been detected, then it will cause engineering accidents and serious economic losses. Therefore, the construction quality of the bolt anchorage must be checked, so as to ensure the safety of the project. During the early stage, the detection of the anchor’s anchoring quality is mainly based on the drawing test [

The detection method for the quality of the anchor will be gradually replaced by the use of nondestructive testing methods, such as the acoustic wave method [

The low-end reflection signal of the bolt can be easily disturbed during the process of bolt detection; it is difficult to directly obtain the reflected wave arrival time. In order to obtain the effective signal, many data processing methods, such as the short-time Fourier transform, the Gabor transform, the Wigner-Ville transform, and the wavelet transform, are proposed. Wavelet transform is the most used signal analysis method among them [

The empirical mode decomposition (EMD) can adaptively select the substrate according to the characteristics of the signal for the multiresolution analysis of the signal, which will overcome the wavelet base selection problem [

Based on the mentioned research, the ICEEMD method is introduced into the bolt detection signal analysis in this paper. However, the actual signal of bolt detection is under noise interference. The processing signal under noise is critical problem with ICEEMD for bolt detection. By combining the approximate entropy and the wavelet denoising principle, the ICEEMD-De was established based on the ICEEMD. Then, the ICEEMD-de was used to process the simulation vibration signal and the actual bolt detection signal.

Based on the ICEEMD anchor detection signal analysis method, the ICEEMD-De integrates ICEEMD, the approximate entropy, and wavelet denoising. The three methods are introduced in the section.

The ICEEMD method is able to effectively prevent the occurrence of false IMF by adding the adaptive white noise to the signal and by redefining the local mean of each modal. Assuming the anchor detection signal

^{i}.^{i} can be expressed as

^{ i } is decomposed by using EMD. We obtain 1th residue

Go to step

All of the IMF approximate entropy can be expressed as

The wavelet denoise is achieved based on a critical threshold. The main steps of its denoise principle are as follows.

Based on ICEEMD, the approximate entropy, and wavelet denoising theory, we proposed ICEEMD-De method. The method is divided into five steps to implement processing vibrational signal. The ICEEMD-De analysis process is shown in Figure

Anchoring detection signal analysis flowchart using ICEEMD-De.

Focusing on the analysis of the anchor detection signal, one vibration simulation signal is considered, and the signal is decomposed by means of ICEEMD. The ICEEMD method is used in order to analyze the signal under the noise interference condition. The noise signal is directly decomposed by the ICEEMD, ICEEMD decomposition after the wavelet denoising, and ICEEMD-De for studying processing effect.

The supposed vibration simulation signal

Vibration simulation synthetic signal.

The simulation synthetic signal in Figure

IMF and spectrum after the decomposition of the vibration signal with ICEEMD: (a, c, e, and g) IMF1~IMF4; (b, d, f, and h) IMF4 spectrum.

According to Figure

The random signal is added to the source signal in Figure

Vibration signal under noise condition.

The IMF and spectrum with the vibration signal after the decomposition with ICEEMD: (a, c, e, and g) is IMF1~IMF4 and (b, d, f, and h) is IMF1~IMF4 spectrum.

The IMF and spectrum with the vibration signal after the decomposition with ICEEMD-De: (a, c, e, and g) is IMF1~IMF4 and (b, d, f, and h) is IMF1~IMF4 spectrum.

According to Figure

From Figure

In order to further study the effect of the proposed method on the denoising of the vibration signal, the denoising effect of the wavelet and the ICEEMD-De method on the

Denoising error line with wavelet and ICEEMD-De.

In Figure

In the signal denoising analysis, the signal-to-noise ratio (SNR) and the root-mean-square deviation (RMSE) are used in order to measure the denoising effect of the signal, which is defined as follows:

According to formulas (

ICEEMD denoising performance index.

Index | Original signal | ICEEMD | Wavelet |
---|---|---|---|

SNR (dB) | 5.000 | 13.741 | 11.179 |

RMSE | 0.411 | 0.151 | 0.201 |

From Table

Taking the high-slope anchor grouting test of Yunnan-highway as an example, the instrument is the LX-10 bolt, the sampling frequency is 10498 Hz, the sampling point is 980, and the sampling interval is 4.0

Bolt detection testing instrument and site.

Detection instrument

Testing site

Bolt detection signal in actual engineering.

The anchor detection signals in Figure

The IMF with the vibration signal after the decomposition with ICEEMD: (a)~(f) show IMF1 ~ 6 Signal decomposed with ICEEMD.

The IMF with the vibration signal after the decomposition with ICEEMD-De: (a)~(f) show t IMF1 ~ 6 which is the signal decomposed with ICEEMD-De.

According to Figure

According to Figure

ICEEMD IMF2 versus ICEEMD-De IMF2.

Based on the principle of the ICEEMD decomposition, the general approximation entropy, and wavelet denoising, the ICEEMD method is introduced into the bolt detection signal analysis. The anchor detection signal is decomposed by means of using the ICEEMD, while the approximate entropy is regarded as the condition for whether or not the IMF is denoising. Using the wavelet soft threshold denoising technique to eliminate the noise in the IMF, the ICEEMD-De anchor signal analysis method is proposed. Based on the usage of the ICEEMD-De to analyze the vibration’s analog signal and the anchor detection signal, the following conclusions have been drawn.

The authors declare that they have no conflicts of interest.

This research was funded by the Open Research Fund of Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education (Grant no. SLK2017A02) and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (Grant no. 3014-SYS1401). The authors wish to thank Su Jiankun from Yunnan Aerospace Engineering Geophysical Limited by Share Ltd. for providing the GPR practical detection data used in this study.