0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Human Health Effects Sign in to save

Mechanical structural health prognosis with nonlinear mixed frequency ultrasonic signal analysis

E3S Web of Conferences 2021 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Hanxin Chen, Mingming Liu, Zhenyu Hu, Menglong Li, Sen Li

Summary

Scientists developed an ultrasonic method to detect early fatigue cracks in aluminum alloy components by analyzing mixed-frequency signal responses. This engineering materials testing paper is unrelated to microplastic environmental research.

In order to detect the early fatigue crack of mechanical components simply, this paper puts forward the ultrasonic testing technology of different side collinear mixing. Firstly, based on the nonlinear ultrasonic theory, the method of calculating the difference frequency and sum frequency nonlinear coefficients of mixing ultrasonic is deduced. Then, the ram-5000 SINAP ultrasonic system is used to detect the aluminum alloy specimens with five different depth fatigue cracks, and the corresponding spectrum diagram is drawn. From the experimental results, we get that the crack depth is positively correlated with the nonlinear coefficients of difference frequency and sum frequency within a certain crack depth. Finally, by analyzing and fitting the experimental data, the prediction models of the difference frequency and sum frequency nonlinear coefficients on the crack depth are established. Through the analysis and combination of the above two prediction models, the prediction model of the mixing relative nonlinear coefficient is established, and the average error of the three prediction models is compared. The results show that the mixing relative nonlinear model has better results. The research work in this paper makes a useful exploration for crack detection and crack depth prediction.

Sign in to start a discussion.

More Papers Like This

Article Tier 2

Nonlinear ultrasonics for material state awareness

This paper reviews nonlinear ultrasonic techniques for detecting early-stage material damage in metal structures before visible cracks appear, by measuring changes in the material's internal microstructure. The study is focused on structural engineering and materials testing, with no direct relevance to microplastic pollution.

Article Tier 2

Influence of Defects on the Structural-phase State of Welded Joints and Parameters of Acous

This technical paper examines how iron impurities in aluminum affect the microstructure and ultrasonic properties of aluminum alloy welds. This is a metallurgy and welding engineering paper with no connection to microplastics or environmental health.

Article Tier 2

An Acoustic Emission Method for Assessing the Degree of Degradation of Mechanical Properties and Residual Life of Metal Structures under Complex Dynamic Deformation Stresses

This engineering paper presents an acoustic emission method for monitoring the structural health and remaining life of metal structures under complex stress conditions. It has no relevance to microplastic or environmental health research.

Article Tier 2

Development of an ultrasonic NDE&T tool for yield detection in steel structures

This engineering dissertation developed and tested ultrasonic non-destructive techniques for detecting when steel structural components have been stressed beyond their yield point. This is a structural engineering study with no relevance to microplastic pollution.

Article Tier 2

Study on Acoustic Emission Characteristics of Fatigue Damage of A7N01 Aluminum Alloy for High-Speed Trains

Not relevant to microplastics — this study uses acoustic emission monitoring to detect fatigue micro-cracks in aluminium alloy used in high-speed train manufacturing, with no connection to plastic pollution.

Share this paper