A Compact Acoustic Particle Velocity Gradient Sensor Based on MEMS Hot-Wire Sensor Chips

Yang, Lingmeng; Zhu, Zhezheng; Chang, Wen-Han; Meng, Fanning; Gao, Chengchen; Yang, Zhiqing

doi:10.1109/transducers50396.2021.9495574

Cited by 2 publications

(11 citation statements)

References 8 publications

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“…One ADS is shown in Figure 10 , which is a particle velocity type ADS based on MEMS TAPVS chips, similar to the one in our previous work [ 27 ]. The spacing

of the two TAPVS chips is 3.6 mm.…”

Section: Quantitative Analysis Methods Based On Directivity Beam Patternmentioning

confidence: 99%

“…In our previous work [ 27 ], we proposed a compact acoustic particle velocity gradient sensor based on MEMS thermal acoustic particle velocity sensor (TAPVS) [ 29 ] chips. The MEMS TAPVS is a kind of acoustic vector senor that can directly measure the particle velocity of the sound signals [ 13 ].…”

Section: Theoretical Model Of Mixed Mismatchesmentioning

confidence: 99%

“…The particle velocity gradient can be obtained by the difference between the outputs of two TAPVSs and its variation with the angle of sound incident direction

is shown in Figure 12 . The measurement setup used to obtain the measured beam pattern in Figure 12 is the same with the one in [ 27 ], which is also shown in Figure 13 . Pules sound signals generated via a waveform generator is played on a loudspeaker.…”

Section: Theoretical Model Of Mixed Mismatchesmentioning

confidence: 99%

“…Sound pressure type ADSs, composed of APSs, measure the second-order sound pressure gradient after twice finite-difference approximation of sound pressure [ 22 ]. Particle velocity type ADSs, composed of AVSs, measure the acoustic particle velocity gradient after once finite-difference approximation of acoustic particle velocity [ 23 , 24 , 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Analysis Method and Correction Algorithm Based on Directivity Beam Pattern for Mismatches between Sensitive Units of Acoustic Dyadic Sensors

Yang

Zhu

Chen

et al. 2023

Sensors

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Acoustic dyadic sensors (ADSs) are a new type of acoustic sensor with higher directivity than microphones and acoustic vector sensors, which has great application potential in the fields of sound source localization and noise cancellation. However, the high directivity of an ADS is seriously affected by the mismatches between its sensitive units. In this article, (1) a theoretical model of mixed mismatches was established based on the finite-difference approximation model of uniaxial acoustic particle velocity gradient and its ability to reflect the actual mismatches was proven by the comparison of theoretical and experimental directivity beam patterns of an actual ADS based on MEMS thermal particle velocity sensors. (2) Additionally, a quantitative analysis method based on directivity beam pattern was proposed to easily estimate the specific magnitude of the mismatches, which was proven to be useful for the design of ADSs to estimate the magnitudes of different mismatches of an actual ADS. (3) Moreover, a correction algorithm based on the theoretical model of mixed mismatches and quantitative analysis method was successfully demonstrated to correct several groups of simulated and measured beam patterns with mixed mismatches.

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“…One ADS is shown in Figure 10 , which is a particle velocity type ADS based on MEMS TAPVS chips, similar to the one in our previous work [ 27 ]. The spacing

of the two TAPVS chips is 3.6 mm.…”

Section: Quantitative Analysis Methods Based On Directivity Beam Patternmentioning

confidence: 99%

Section: Theoretical Model Of Mixed Mismatchesmentioning

confidence: 99%

“…The particle velocity gradient can be obtained by the difference between the outputs of two TAPVSs and its variation with the angle of sound incident direction

Section: Theoretical Model Of Mixed Mismatchesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quantitative Analysis Method and Correction Algorithm Based on Directivity Beam Pattern for Mismatches between Sensitive Units of Acoustic Dyadic Sensors

Yang

Zhu

Chen

et al. 2023

Sensors

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“…An alternative to microphone arrays is vector sensors. They can achieve accurate directional response relying on many different techniques and configurations and appropriate signal processing schemes [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. More recently, the reduced size, lightweight, and lower power requirements of MEMS-based directional acoustic sensors fostered interest in their development [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

Dual Band MEMS Directional Acoustic Sensor for Near Resonance Operation

Alves

Rabelo

Karunasiri

2022

Sensors

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In this paper, we report on the design and characterization of a microelectromechanical systems (MEMS) directional sensor inspired by the tympana configuration of the parasitic fly Ormia ochracea. The sensor is meant to be operated at resonance and act as a natural filter for the undesirable frequency bands. By means of breaking the symmetry of a pair of coupled bridged membranes, two independent bending vibrational modes can be excited. The electronic output, obtained by the transduction of the vibration to differential capacitance and then voltage through charge amplifiers, can be manipulated to tailor the frequency response of the sensor. Four different frequency characteristics were demonstrated. The sensor exhibits, at resonance, mechanical sensitivity around 6 μm/Pa and electrical sensitivity around 13 V/Pa. The noise was thoroughly characterized, and it was found that the sensor die, rather than the fundamental vibration, induces the predominant part of the noise. The computed average signal-to-noise (SNR) ratio in the pass band is about 91 dB. This result, in combination with an accurate dipole-like directional response, indicates that this type of directional sensor can be designed to exhibit high SNR and selectable frequency responses demanded by different applications.

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A Compact Acoustic Particle Velocity Gradient Sensor Based on MEMS Hot-Wire Sensor Chips

Cited by 2 publications

References 8 publications

Quantitative Analysis Method and Correction Algorithm Based on Directivity Beam Pattern for Mismatches between Sensitive Units of Acoustic Dyadic Sensors

Quantitative Analysis Method and Correction Algorithm Based on Directivity Beam Pattern for Mismatches between Sensitive Units of Acoustic Dyadic Sensors

Dual Band MEMS Directional Acoustic Sensor for Near Resonance Operation

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