Output‐Only Damage Detection of Steel Beam Using Moving Average Filter

Abstract

This paper provides a simple and direct output-only baseline-free method to detect damage from the noisy acceleration data by using Moving Average Filter (MAF). MAF is a convolution approach based on a simple filter kernel (rectangular shape) that works as an averaging method to smooth signal and remove incorporated noise. In this paper, a method is proposed to employ MAF to smooth acceleration signals obtained from a series of accelerometers and determine the damage location along a steel beam. To verify the proposed method, a simply supported beam was modelled through a 3D numerical simulation and an experimental model under a moving vehicle load. The response acceleration data was then recorded at a sampling frequency of 500 Hz. Finally, damage location was identified by applying the proposed method. The results showed that the proposed method can accurately estimate the damage location from the acceleration signal without applying any frequency filtering or baseline correction.

Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky–Golay Filter

“…The damage detection of a simply supported beam under different moving loads has received great attention over the past few decades [1,3,20,21,23,37,38]. Truckloads are generally modeled by three different methods: (1) Moving force, (2) moving mass, and (3) moving sprung mass.…”

“…However, in some cases, such as heavy traffic load on bridges, the input excitations can hardly be measured. In such cases, where the operational loads exerted on the structure are not available, the output-only-based methods can be used as a proper workaround, which have received great attention in structural health monitoring (SHM) [1,2]. It has been proved that vibration data (e.g., acceleration data) have some damage signatures that cannot be observed by the naked eye [1].…”

“…Therefore, signal processing is necessary to provide a visible form of these signatures. Some of these signal processing-based methods are transformers [3][4][5][6][7][8], time-domain methods (e.g., random decrement technique (RDT)) [1,2,[9][10][11][12][13][14], and source separation methods (e.g., blind source separation (BSS)) [15][16][17][18][19]. To implement a systematic damage detection procedure, a nested loop of RDT and a Savitzky-Golay filter (SGF) is employed in the present paper.…”

“…Since the moving average filter (MAF) has the ability of noise reduction, some researchers only highlighted the use of MAF to enhance the accuracy of the BHM system [20][21][22]. Direct use of MAF in BHM was also addressed in a few studies in which the damage was numerically and experimentally located along the bridge type structures [1,23]. It should be noted that the MAF is the zero-order SGF and the SGF is a time-domain smoothing filter that finds a trend line for a curve using an nth-order polynomial function in its kernel [24,25].…”

Output-Only Damage Detection of Shear Building Structures Using an Autoregressive Model-Enhanced Optimal Subpattern Assignment Metric

“…In turn, the inaccurate measurement of structural input information will cause the spurious damage detection results. In this case, using the output-only damage detection method without complete prior excitation knowledge becomes an effective and alternative way [57][58][59][60].…”