Modelling the Effect of Wheel Flat on Railway-Induced Ground Vibrations

2014 ◽  
Author(s):  
G. Alexandrou ◽  
G. Kouroussis ◽  
O. Verlinden
Keyword(s):  
Ground Vibrations ◽  
Wheel Flat

scholarly journals Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 144
Author(s):  
Yan Zhang ◽  
Jijian Lian ◽  
Songhui Li ◽  
Yanbing Zhao ◽  
Guoxin Zhang ◽  
...  
Keyword(s):  
Frequency Response ◽  
Frequency Distribution ◽  
Response Function ◽  
Frequency Response Function ◽  
Ground Vibration ◽  
Vibration Source ◽  
Ground Vibrations ◽  
High Energies ◽  
Flood Discharge ◽  
Opening Method

Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.

scholarly journals DYNAMIC LOADS OF TRAFFIC-INDUCED GROUND VIBRATIONS ON ROAD

2008 ◽  
Vol 73 (633) ◽  
pp. 1241-1247 ◽  
Author(s):  
Norio TAGUCHI ◽  
Toshikazu HANAZATO ◽  
Yoshio IKEDA ◽  
Riei ISHIDA
Keyword(s):  
Dynamic Loads ◽  
Ground Vibrations

scholarly journals Autocorrelation of the ground vibrations recorded by the SEIS-InSight seismometer on Mars

2020 ◽  
Author(s):  
Nicolas Compaire ◽  
Ludovic Margerin ◽  
Raphaël F. Garcia ◽  
Baptiste Pinot ◽  
Marie Calvet ◽  
...  
Keyword(s):  
Ground Vibrations

Wheel-flat diagnostic tool via wavelet transform

2006 ◽  
Vol 20 (8) ◽  
pp. 1953-1966 ◽  
Author(s):  
Vittorio Belotti ◽  
Francesco Crenna ◽  
Rinaldo C. Michelini ◽  
Giovanni B. Rossi
Keyword(s):  
Wavelet Transform ◽  
Diagnostic Tool ◽  
Wheel Flat
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