Evidence map›Paper›PMID 40218781›Full record

ArticleSensors (Basel, Switzerland)2025

Feasibility Study of Signal Processing Techniques for Vibration-Based Structural Health Monitoring in Residential Buildings.

Fedaa Ali, Leila Donyaparastlivari, Seyed Ghorshi, Abolghassem Zabihollah, Mohammad Alghamaz, Alwathiqbellah Ibrahim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fedaa AliDepartment of Electrical and Computer Engineering, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA.ORCID 0009-0004-2151-3881
Leila DonyaparastlivariDepartment of Mechanical Engineering, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA.
Seyed GhorshiDepartment of Electrical and Computer Engineering, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA.
Abolghassem ZabihollahDepartment of Mechanical, Environmental, and Civil Engineering, Tarleton State University, Stephenville, TX 76402, USA.ORCID 0000-0002-4996-9029
Mohammad AlghamazDepartment of Mechanical Engineering, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA.ORCID 0009-0004-1386-5692
Alwathiqbellah IbrahimDepartment of Mechanical Engineering, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX 75799, USA.ORCID 0000-0001-8093-840X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing vulnerability of residential buildings to seismic activity and dynamic loading underscores the need for robust, real-time Structural Health Monitoring (SHM) systems. This study investigates the feasibility of utilizing piezoelectric sensors integrated with advanced signal processing techniques, including Power Spectral Density (PSD) and Short-Time Fourier Transform (STFT), for vibration-based SHM in residential structures. A scaled three-story building prototype was fabricated and subjected to controlled base excitations at 25 Hz and 0.6 g acceleration to evaluate the response under three structural conditions: healthy, randomly damaged, and thickness-damaged. The experimental results revealed that structural degradation significantly altered sensor outputs, with random damage causing irregular signal dispersion and thickness damage introducing additional frequency harmonics. PSD analysis effectively identified shifts in energy distribution, signifying structural degradation, while STFT provided a detailed time-frequency representation, facilitating real-time damage detection. The findings confirm that piezoelectric sensors, when combined with PSD and STFT, can serve as a low-cost, scalable solution for early damage detection in residential buildings, offering a practical framework for enhancing structural resilience against earthquakes and other dynamic forces.

Indexed as

damage detectionpiezoelectric sensorsreliabilityresidential buildingssignal processingstructural health monitoring

Identifiers

PMID40218781
PMCPMC11991024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.