Condition assessment of steel truss bridge using time frequency domain analysis

Walia, Suresh Kumar; Patel, Raj Kumar; Vinayak, Hemant Kumar; Parti, Raman

doi:10.2298/fuace1602141w

Cited by 1 publication

(1 citation statement)

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“…The direction of the measured sensor data is accounted during its analysis. The detailed description of the types of sensors, data accusation system and cross section of the bridge can be obtained from previous studies (Walia et al , 2016).…”

Section: Description Of Bridgementioning

confidence: 99%

Steel truss bridge vibration-based condition monitoring using Savitzky-Golay filter, Hilbert transform, MUSIC and ESPRIT

Sharma

Kumar

Vinayak

et al. 2021

JEDT

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Purpose This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure. Design/methodology/approach The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques. Findings The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge. Originality/value The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

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Section: Description Of Bridgementioning

confidence: 99%