Generalized Resonance Sensor Based on Fiber Bragg Grating

Chen, Xinxin; Wang, Enbo; Jiang, Yali; Zhan, Hui; Li, Hongwei; Lyu, Guohui; Sun, Songlin

doi:10.3390/photonics8050156

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…Due to the characteristics of filter bank distribution, I-MFCCs can greatly enhance the feature description resolution of the high-frequency part of fault information and obtain the I-MFCCs features with high identification. The frequency response formula of the filter bank constructed by the traditional MFCC can be seen in equation (6), and the specific distribution can be seen in figure 2. In this paper, the Mel filter bank distribution is reconstructed.…”

Section: Bearing Fault Diagnosis Based On I-mfccs and Dcnsmentioning

confidence: 99%

See 1 more Smart Citation

Bearing fault diagnosis based on inverted Mel-scale frequency cepstral coefficients and deformable convolution networks

Zhao¹,

baofu²,

yuhang³

et al. 2023

Meas. Sci. Technol.

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In the online test of bearing fault diagnosis algorithm based on data-driven, it is difficult to guarantee that the training and testing data come from the same time series distribution. Inconsistent distribution will lead to a decline in diagnostic performance. In addition, the convolutional neural network is limited by the fixed shape of its convolution kernel, which makes it difficult to fully extract the spatial constraint features between fault data. To solve the above problems, this paper proposes a bearing fault diagnosis method based on inverted Mel-scale frequency cepstrum coefficients and deformable convolution networks. The core of traditional Mel-scale frequency cepstrum coefficients is to construct a non-uniformly distributed frequency domain filter bank. It is characterized by the dense distribution of low-frequency regions and the sparse distribution of high-frequency regions. Considering that the features that can well characterize the fault information are concentrated in the high-frequency part, we reconstruct the traditional Mel-scale frequency cepstrum coefficients filter bank and propose a feature extraction method of inverted Mel-scale frequency cepstrum coefficients. This method can obtain the frequency domain characteristics of bearing vibration signals, highlight the fault information contained in the high-frequency region, and reduce the influence of time series distribution inconsistency between training samples and testing samples on the diagnosis accuracy. In order to further improve the spatial discrimination between different fault categories, the deformable convolution networks model is introduced to extract the spatial distribution information of fault features and improve the accuracy of fault diagnosis. Finally, two public datasets and an experimental platform data verify that the method can achieve high-precision fault diagnosis, and inverted Mel-scale Frequency cepstrum coefficients are effective in solving the problem of inconsistent distribution.

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Section: Bearing Fault Diagnosis Based On I-mfccs and Dcnsmentioning

confidence: 99%

“…When the bearing fails, the fault information is not evenly distributed in different frequency bands. The content containing effective information on fault features will be concentrated in the high-frequency region [6,7]. The high-frequency region of fault information is a key content to improve the accuracy of fault diagnosis [8].…”

Section: Introductionmentioning

confidence: 99%

Bearing fault diagnosis based on inverted Mel-scale frequency cepstral coefficients and deformable convolution networks

Zhao¹,

baofu²,

yuhang³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…With the development of optical fiber technology, vibration sensors based on optical fibers have attracted more and more interest due to their unique properties [9], such as strong immunity to electromagnetic interference, corrosion resistance, high temperature resistance, small size and easy networking. There are many new types of optical fiber accelerometers that have been proposed, which consist of Michelson interferometers [10], Fabry-Perot interferometers [11], fiber lasers [12] and fiber Bragg gratings [13][14][15][16][17][18][19][20][21][22][23][24]. Vibration sensors based on interference and fiber laser vibration sensors can achieve highsensitivity detection, but the output signal stability is easily affected by the fluctuation of the light source, the demodulation is complicated, which has high requirements for the sensor packaging and the monitoring environment, and a single sensor has a high cost in the interrogation system.…”

Section: Introductionmentioning

confidence: 99%

“…Vibration sensors based on interference and fiber laser vibration sensors can achieve highsensitivity detection, but the output signal stability is easily affected by the fluctuation of the light source, the demodulation is complicated, which has high requirements for the sensor packaging and the monitoring environment, and a single sensor has a high cost in the interrogation system. In contrast, FBG-based accelerometers with wavelength demodulation have obvious advantages [13], which makes them suitable for a variety of vibration measurements including structural health monitoring [14] of civil engineering [15] and mechanical equipment [16].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity-Tunable Oscillator-Accelerometer Based on Optical Fiber Bragg Grating

et al. 2021

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We demonstrate a fiber Bragg grating (FBG)-based oscillator-accelerometer in which the acceleration sensitivity can be tuned by controlling the location of the mass oscillator. We theoretically and experimentally investigated the performance of the proposed accelerometer. Theoretical analysis showed that both the mass and location of the oscillator affect the sensitivity and resonant frequency of the accelerometer. To simplify the analysis, a nondimensional parameter, P, was introduced to tune the sensitivity of the FBG-based oscillator-accelerometer, which is related to the location of the mass oscillator. Numerical analysis showed that the accelerometer sensitivity is linearly proportional to the P parameter. In the experiment, six FBG-based oscillator-accelerometers with different P parameters (0.125, 0.25, 0.375, 0.5, 0.625, 0.75) were fabricated and tested. The experimental results agree very well with the numerical analysis, in which the sensitivity of the proposed accelerometer linearly increased with the increase in parameter P (7.6 pm/g, 15.8 pm/g, 19.3 pm/g, 25.4 pm/g, 30.6 pm/g, 35.7 pm/g). The resonance frequency is quadratically proportional to parameter P, and the resonance frequency reaches the minimum of 440 Hz when P is equal to 0.5. The proposed oscillator-accelerometer showed very good orthogonal vibration isolation.

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Resonance Detection Method and Realization of Bearing Fault Signal Based on Kalman Filter and Spectrum Analysis

Chen

Sun

2023

Applied Sciences

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The rolling bearing is an important part of mechanical equipment, and its performance significantly affects the quality and life of the mechanical equipment. This article uses the integrated fiber Bragg grating resonant structure sensor excited by periodic micro-shocks caused by micro faults to realize the extraction of information relating to potential faults. Because the fault signal is weak and can easily be interfered with by ambient noise, in order to extract the effective signal, this article determines the autoregressive model of bearing vibration by the final prediction error criterion and the recursive least squares estimation algorithm. The augmented state space model is established based on the autoregressive model. A Kalman filter is used to reduce the noise interference, and then the reduction noisy signal is analyzed by power spectrum and improved autocorrelation envelope spectrum to realize the detection of bearing faults. Through data analysis and method comparison, the proposed improved autocorrelation envelope spectrum analysis can directly extract the bearing fault frequency, which is superior to other methods such as cepstral analysis.

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Generalized Resonance Sensor Based on Fiber Bragg Grating

Cited by 3 publications

References 15 publications

Bearing fault diagnosis based on inverted Mel-scale frequency cepstral coefficients and deformable convolution networks

Bearing fault diagnosis based on inverted Mel-scale frequency cepstral coefficients and deformable convolution networks

Sensitivity-Tunable Oscillator-Accelerometer Based on Optical Fiber Bragg Grating

Resonance Detection Method and Realization of Bearing Fault Signal Based on Kalman Filter and Spectrum Analysis

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