Abstract
Available commercial piezoelectric pressure sensors are not able to accurately reproduce the ultra-fast transient pressure occurring during an air blast experiment. In this communication a new pressure sensor prototype based on a miniature silicon membrane and piezoresistive gauges is reported for significantly improving the performances in terms of time response. Simulation results demonstrate the feasibility of a pressure transducer having a fundamental resonant frequency almost ten times greater than the commercial piezoelectric sensors one. The sensor uses a 5μm-thick SOI membrane and four P-type silicon gauges (doping level ≅ 1019 at/cm3) in Wheatstone bridge configuration. To obtain a good trade-off between the fundamental mechanical resonant frequency and pressure sensitivity values, the typical dimension of the rectangular membrane is fixed to 30μm x 90μm with gauge dimension of 1μm x 5μm. The achieved simulated mechanical resonant frequency of these configuration is greater than 40MHz with a sensitivity of 0.04% per bar.
Highlights
The typical pressure over time during an explosion is shown in Figure 1 [1,2]
The pressure increases abruptly from atmospheric pressure to reach the overpressure peak Pmax
It can be observed that the time response is too long to provide an accurate estimation of the overpressure peak Pmax
Summary
The typical pressure over time during an explosion is shown in Figure 1 [1,2]. In order to validate the hydrocode, i.e. numerical simulations describing the shockwave discontinuity, an accurate measurement of the overpressure peak Pmax is required [3], involving the use of pressure sensors presenting a short time response ( 1000 °C) makes the real-time dynamic pressure measurement of the blast very challenging. It can be observed that the time response is too long to provide an accurate estimation of the overpressure peak Pmax. Typical piezoelectric sensors have a low cut-off frequency (> 0.5 Hz at -5 %) which is too high to follow the overpressure decrease. The piezoresitive detection has been chosen because it provides a better signal-to-noise ratio than their capacitive counterpart [4]
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