“…Scenario 3 is to demonstrate the effectiveness of the proposed method using the response measured with a single sensor installed at different location of the beam. Here it should be noted that, in the previous studies [12][13][14][15][16][17][18][19], authors only used the response of midspan of the beam in damage identification but did not try to use the responses of others positions. Scenario 4 is to evaluate the effectiveness of mass velocities, and scenario 5 is to evaluate the effectiveness of the proposed method for the multicracked beam.…”
Section: Numerical Modelmentioning
confidence: 99%
“…Later, Khorram et al [16] proposed another method of multiple cracks detection in a simply supported beam subjected to a moving load based on CWT combined with factorial design. The similar wavelet based methods can be found in [17,18].…”
This paper presents a novel damage detection method based on the reconstructed phase space of vibration signals using a single sensor. In this approach, a moving mass is applied as excitation source, and the structure vibration responses at different positions are measured using a single sensor. A Moving Filter Function (MFF) is also presented to be used to separate and filter the responses before phase space reconstruction. Using the determined time delay and embedding dimensions, the responses are translated from time domain into the spatial domain. The index CPST (changes of phase space topology) values are calculated from the reconstructed phase space and used to identify structural damage. To demonstrate the method, six analysis scenarios for a beam-like structure considering the moving mass magnitude, damage location, the single sensor location, moving mass velocity, multiple types of damage, and the responses contaminated with noise are calculated. The acceleration and displacement responses are both used to identify the damage. The results indicate that the proposed method using displacement response is more sensitive to damage than that of acceleration responses. The results also proved that the proposed method can use a single sensor installed at different location of the beam to locate the damage/much damage reliably, even though the responses are contaminated with noise.
“…Scenario 3 is to demonstrate the effectiveness of the proposed method using the response measured with a single sensor installed at different location of the beam. Here it should be noted that, in the previous studies [12][13][14][15][16][17][18][19], authors only used the response of midspan of the beam in damage identification but did not try to use the responses of others positions. Scenario 4 is to evaluate the effectiveness of mass velocities, and scenario 5 is to evaluate the effectiveness of the proposed method for the multicracked beam.…”
Section: Numerical Modelmentioning
confidence: 99%
“…Later, Khorram et al [16] proposed another method of multiple cracks detection in a simply supported beam subjected to a moving load based on CWT combined with factorial design. The similar wavelet based methods can be found in [17,18].…”
This paper presents a novel damage detection method based on the reconstructed phase space of vibration signals using a single sensor. In this approach, a moving mass is applied as excitation source, and the structure vibration responses at different positions are measured using a single sensor. A Moving Filter Function (MFF) is also presented to be used to separate and filter the responses before phase space reconstruction. Using the determined time delay and embedding dimensions, the responses are translated from time domain into the spatial domain. The index CPST (changes of phase space topology) values are calculated from the reconstructed phase space and used to identify structural damage. To demonstrate the method, six analysis scenarios for a beam-like structure considering the moving mass magnitude, damage location, the single sensor location, moving mass velocity, multiple types of damage, and the responses contaminated with noise are calculated. The acceleration and displacement responses are both used to identify the damage. The results indicate that the proposed method using displacement response is more sensitive to damage than that of acceleration responses. The results also proved that the proposed method can use a single sensor installed at different location of the beam to locate the damage/much damage reliably, even though the responses are contaminated with noise.
“…11 Later, this idea was improved and another type of response, namely, acceleration, was used to locate the damage with CWT. 12–14 Nguyen and Tran 15 used the dynamic response measured directly from the moving vehicle of the bridge-vehicle system along with wavelet transform method to locate the damage. Khorram et al 16 proposed a method for multiple cracks detection in beam bridges subjected to a moving load based on CWT combined with factorial design.…”
Section: Introductionmentioning
confidence: 99%
“…Most of the above-mentioned studies 11–21 detect the structural damage using only a few sensor measurements. This article proposes another approach utilizing limited measurements from only two sensors to locate damage in bridge structures subjected to moving loads.…”
A novel damage detection approach using only two sensors to detect the damage in beam bridges subjected to a moving vehicle is proposed in this article. In this approach, a moving mass is considered representing a vehicle moving across the bridge, and structural vibration responses at two locations are measured from a pair of sensors. A moving window is defined with a certain length determined by the sampling frequency and the fundamental frequency of the measured responses. The windowed pair time series extracted from these two measured responses are used to calculate the cross-correlation, which is used to define the local damage index. A simply supported beam bridge subjected to a moving mass is simulated to demonstrate the effectiveness and accuracy of the proposed approach. Numerical results indicate that the proposed approach can accurately identify the single and multiple damages using both displacement and acceleration responses, even when the responses are smeared with a significant noise. This indicates a good robustness to the noise effect. Experimental verifications on a laboratory beam bridge model demonstrate that the proposed approach can successfully identify the damage location using different selections of sensor pairs. Both the numerical and experimental results demonstrate that the new damage index is a good candidate for structural damage detection with very limited measurement information.
“…Many time- and frequency-domain methods are used to correct the Doppler distortion. 12–15 However, very few algorithms have been developed for the multiple source separation in the TADS. Figure 1.Basic model of TADS: (a) solid model view, and (b) schematic block diagram.…”
The extraction of single train signal is necessary in wayside fault diagnosis because the acoustic signal acquired by a microphone is composed of multiple train bearing signals and noises. However, the Doppler distortion in the signal acquired by a microphone effectively hinders the signal separation and fault diagnosis. To address this issue, we propose a novel method based on the generalized S-transform, morphological filtering, and time–frequency amplitude matching-based resampling time series for multiple-Doppler-acoustic-source signal separation and correction. First, the original time–frequency distribution is constructed by applying generalized S-transform to the raw signal acquired by a microphone. Based on a morphological filter, several time–frequency distributions corresponding to different single source Doppler fault signals are extracted from the original time–frequency distribution. Subsequently, the time–frequency distributions are reverted to time signals by inverse generalized S-transform. Then, a resampling time series is built by time–frequency amplitude matching to obtain the correct signals without Doppler distortion. Finally, the bearing fault is diagnosed by the envelope spectrum of the correction signal. The effectiveness of this method is verified by simulated and practical signals.
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