Detection of physical signal and time-frequency analysis owing to the impact on rubber material using a piezoelectric sensor
- Authors
- Hiremath, Shivashankar; Kim, Tae-Won
- Issue Date
- May-2024
- Publisher
- 대한기계학회
- Keywords
- CWT; Impact force; Impact signal; PVDF sensor; STFT; Time-frequency
- Citation
- Journal of Mechanical Science and Technology, v.38, no.5, pp 2455 - 2463
- Pages
- 9
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- Journal of Mechanical Science and Technology
- Volume
- 38
- Number
- 5
- Start Page
- 2455
- End Page
- 2463
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/204802
- DOI
- 10.1007/s12206-024-0424-2
- ISSN
- 1738-494X
1976-3824
- Abstract
- A signal is primarily generated when two objects collide, with one falling from a specific height and the other disrupting its balance. This signal contains an important component that aids in the diagnosis of material damage. In this work, a piezoelectric thin film sensor made of polyvinylidene fluoride (PVDF) was employed to monitor the impact signal and process the recorded signal. By stacking a left and right piezoelectric film sensor, drop impact experiments were performed on rubber sheet material. The data-acquisition system captured the impact signal, and a signal processing tool was used to assess its performance. To determine the time-frequency domain visibility of the impact signal, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used. The detection of the elastic signal and impact force on the material is suitable for piezoelectric film. A steel impactor strikes a silicon rubber sheet at a speed of 3.43 m/s and exerts an average impact force of 72.6 kN. To make the impact signal more visible, the noise signal can be denoised using a bandpass filter. The continuous wavelet transform has a high time-frequency resolution compared to the short-time Fourier transform. Additionally, the analysis of non-stationary signals is improved by using STFT and CWT approaches. Thus, the elastic signal detection in the material may be recognized using the average total of the signals identified by the sensor.
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