Signal Sampling criteria and application of structural monitoring based on amplitude analysis

The research explores the influence of sampling frequency on the amplitude analysis error for signals with diverse functional forms, and delineates the approach for ascertaining the optimal sampling frequency for amplitude analysis of signals under dynamic monitoring. A method for determining the sampling frequency of amplitude analysis based on the maximum error criterion is proposed through theoretical derivation of sine function and its composite forms. The correctness of the proposed method is further verified through numerical simulation analysis using MATLAB software. The results indicate that the Nyquist sampling criterion does not meet the precision requirements for amplitude analysis; the impact of odd multiples and even multiples `sampling frequencies on the accuracy of signal amplitude analysis is different; the maximum amplitude error is closely related to the order of the signal; and the even multiples sampling frequency is more reasonable for amplitude analysis. The proposed sampling frequency determination method was applied to the construction of dust removal impact testing system and the fatigue damage analysis of a four-section boom pump truck structure, demonstrating the feasibility of this method in engineering applications. The research in this paper provides theoretical and methodological support for the economic collection and efficient processing of massive condition monitoring signals in engineering practice.

Authors

Publication Details

Journal
Journal of Vibroengineering
Published
2025-03-11
DOI
https://doi.org/10.21595/jve.2025.24531
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Signal Sampling criteria and application of structural monitoring based on amplitude analysis

Guangjun Hua, Chengji Mi, Wenping Tang, Yong Shi
Journal of Vibroengineering
Structural Health Monitoring Techniques
article

Signal Sampling criteria and application of structural monitoring based on amplitude analysis

Guangjun Hua, Chengji Mi, Wenping Tang, Yong Shi
article en

Abstract

The research explores the influence of sampling frequency on the amplitude analysis error for signals with diverse functional forms, and delineates the approach for ascertaining the optimal sampling frequency for amplitude analysis of signals under dynamic monitoring. A method for determining the sampling frequency of amplitude analysis based on the maximum error criterion is proposed through theoretical derivation of sine function and its composite forms. The correctness of the proposed method is further verified through numerical simulation analysis using MATLAB software. The results indicate that the Nyquist sampling criterion does not meet the precision requirements for amplitude analysis; the impact of odd multiples and even multiples `sampling frequencies on the accuracy of signal amplitude analysis is different; the maximum amplitude error is closely related to the order of the signal; and the even multiples sampling frequency is more reasonable for amplitude analysis. The proposed sampling frequency determination method was applied to the construction of dust removal impact testing system and the fatigue damage analysis of a four-section boom pump truck structure, demonstrating the feasibility of this method in engineering applications. The research in this paper provides theoretical and methodological support for the economic collection and efficient processing of massive condition monitoring signals in engineering practice.

Journal of VibroengineeringVol. 27(3)
Openalex Percentile: Top 95%
Structural Health Monitoring Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.