Damage assessment of shear connectors with vibration measurements and power spectral density transmissibility

2015 ◽  
Vol 54 (2) ◽  
pp. 257-289 ◽  
Author(s):  
Jun Li ◽  
Hong Hao ◽  
Yong Xia ◽  
Hong-Ping Zhu
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Damage Assessment ◽  
Vibration Measurements ◽  
Shear Connectors ◽  
Power Spectral

Damage Detection of Shear Connectors Based on Power Spectral Density Transmissibility

2013 ◽  
Vol 569-570 ◽  
pp. 1241-1248 ◽  
Author(s):  
Jun Li ◽  
Hong Hao
Keyword(s):  
Spectral Density ◽  
Damage Detection ◽  
Frequency Response ◽  
Power Spectral Density ◽  
Experimental Studies ◽  
Measurement Data ◽  
Response Functions ◽  
Frequency Response Functions ◽  
Shear Connectors ◽  
Power Spectral

Damage of shear connectors in slab-on-girder structures will result in shear slippage between slab and girder, which significantly reduces the load-carrying capacity of the bridge. This paper proposes a dynamic damage detection approach to identify the damage of shear connectors in slab-on-girder bridges with power spectral density transmissibility (PSDT). PSDT formulates the relationship between the auto-spectral density functions of two responses. Measured impact force and acceleration responses from hammer tests are analyzed to obtain the frequency response functions at the slab and girder sensor locations by experimental modal analysis. When measurement data from the undamaged structure are available, PSDT from the slab response to the girder response is derived with the obtained frequency response functions. PSDT matrices in the undamaged and damaged states are directly compared to identify the damage of shear connectors. When the measurement data from the undamaged structure are not available, PSDT matrices from measured response at a reference sensor response to those of the slab and girder in the damaged state can also be used to detect the damage of shear connectors. Experimental studies with a concrete slab supported by two steel girders are conducted to investigate the accuracy and efficiency of the proposed approach. Identification results demonstrated that damage of shear connectors can be identified accurately and efficiently with and without measurement data from the undamaged structure.

Fuzzy Modeling of Multi-Degree-of-Freedom Power Spectral Density Systems

2009 ◽  
Vol 2 (1) ◽  
pp. 40-47
Author(s):  
Montasser Tahat ◽  
Hussien Al-Wedyan ◽  
Kudret Demirli ◽  
Saad Mutasher
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Fuzzy Modeling ◽  
Degree Of Freedom ◽  
Power Spectral

scholarly journals Noise power spectral density scaled SNR response estimation with restricted range search for sound source localisation using unmanned aerial vehicles

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Benjamin Yen ◽  
Yusuke Hioka
Keyword(s):  
Spectral Density ◽  
Noise Reduction ◽  
Power Spectral Density ◽  
Sound Source ◽  
Processing Algorithm ◽  
Post Processing ◽  
Time Frequency ◽  
Distance Error ◽  
Rotor Noise ◽  
Power Spectral

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

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