Resumen
The versatility of piezoelectric sensors in measurement techniques and their performance in applications has given rise to an increased interest in their use for structural and manufacturing component monitoring. They enable wireless and sensor network solutions to be developed in order to directly integrate the sensors into machines, fixtures and tools. Piezoelectric sensors increasingly compete with strain-gauges due to their wide operational temperature range, load and strain sensing accuracy, low power consumption and low cost. This research sets out the use of piezoelectric sensors for real-time monitoring of mechanical strength in metallic structures in the ongoing operational control of machinery components. The behaviour of aluminium and steel structures under flexural strength was studied using piezoelectric sensors. Variations in structural behaviour and geometry were measured, and the load and μstrains during operational conditions were quantified in the time domain at a specific frequency. The lead zirconium titanate (PZT) sensors were able to distinguish between material types and thicknesses. Moreover, this work covers frequency selection and optimisation from 20 Hz to 300 kHz. Significant differences in terms of optimal operating frequencies and sensitivity were found in both structures. The influence of the PZT voltage applied was assessed to reduce power consumption without signal loss, and calibration to μstrains and loads was performed.
Idioma original | Inglés |
---|---|
Número de artículo | 1471 |
Páginas (desde-hasta) | 1471 |
Número de páginas | 1 |
Publicación | Sensors |
Volumen | 20 |
N.º | 5 |
DOI | |
Estado | Publicada - 1 mar 2020 |
Palabras clave
- Piezoelectric smart sensor
- Real-time
- Optimal frequency
- Low power
- Load monitoring
- Electromechanical impedance
- Sensing
- Smart structures
- Smart manufacturing
Project and Funding Information
- Project ID
- info:eu-repo/grantAgreement/EC/H2020/869884/EU/RE-manufaCturing and Refurbishment LArge Industrial equipMent/RECLAIM
- Funding Info
- This research was funded by Basque Government, grant number KK-2019/00051-SMARTRESNAK and_x000D_ by the European Commission, grant number 869884- RECLAIM.