Acoustic methods for detection of specific failure modes in capacitive MEMS microphones

Hantos, Gergely; Desmulliez, Marc Phillipe Yves

doi:10.1109/estc48849.2020.9229745

Cited by 3 publications

(5 citation statements)

References 22 publications

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“…The shift in the -3dB point is not significant enough to affect the sensitivity of the mobile phone. Electrostatic stiction can be simulated by changing the bias voltage, Vbias, as described in [6], and by recording the frequency response of the microphone at each change of the bias voltage. Stiction occurs when Vbias reaches Vpi, which depends on the transducer geometry and its physical properties [5].…”

Section: B Failure Mode Simulationmentioning

confidence: 99%

“…The steps of the measurement procedure are shown in Fig. 3 in [6]. The measurements were recorded on two different experimental setups.…”

Section: Failure Mode Induction and Measurementmentioning

confidence: 99%

“…Experimental setup 2 was designed to extract the device response and background noise in a real-life environment. Detailed descriptions of the two setups are given in [6].…”

Section: Failure Mode Induction and Measurementmentioning

confidence: 99%

“…2 was developed, with each layer building on the previous one and includes: Lumped element modelling (Black layer), Failure mode simulation (Red layer), Failure mode discrimination (Blue layer) and Recovery (Yellow layer). The feasibility of the framework is supported by experimental data acquired through failure mode induction as presented in ESTC2020 [6]. The failure mode recognition involves four discrimination methods that allow the precise characterization of failure behavior and the detection of electrostatic capture without additional circuitry.…”

Section: Introductionmentioning

confidence: 99%

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On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

Hantos

Simon

Desmulliez

2022

IEEE Trans. Compon., Packag. Manufact. Technol.

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Most mobile phones today have capacitive microelectromechanical systems (MEMS) microphones that use either single or dual diaphragm. Methods to detect failures easily and non-invasively have become of critical importance for microphones mobile phone manufacturers as a basis for built-in self-test (BIST) and self-repair (BISR) strategies. In that regard, a four-layer framework is presented that includes lumped element modelling (LEM), failure mode simulation, failure mode discrimination and recovery. The frequency response of the microphone is taken as the main output to analyse. To experimentally validate this framework, this article provides a failure mode induction method based on bias voltage sweeping and four new techniques, based solely on acoustic measurements to discriminate the states of electrostatic capture for single diaphragm capacitive MEMS microphones. These include a) analysis of an acoustic signature that is unique to electrostatic capture based on cosine similarity analysis, b) -3 dB point measurement, C) +3 dB point measurement, and d) cluster analysis. Measurement of pull-in voltage and snapback voltage ranges is further demonstrated based on sensitivity measurements in laboratory conditions and response magnitude and noise power measurements in non-laboratory conditions. Up to 100% success rate in detecting electrostatic capture of diaphragm is reported for this type of device.

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Section: B Failure Mode Simulationmentioning

confidence: 99%

“…The steps of the measurement procedure are shown in Fig. 3 in [6]. The measurements were recorded on two different experimental setups.…”

Section: Failure Mode Induction and Measurementmentioning

confidence: 99%

“…Experimental setup 2 was designed to extract the device response and background noise in a real-life environment. Detailed descriptions of the two setups are given in [6].…”

Section: Failure Mode Induction and Measurementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

Hantos

Simon

Desmulliez

2022

IEEE Trans. Compon., Packag. Manufact. Technol.

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“…Digital temperature and voltage sensors were used and the experimental results showed a significant increase in the circuit delay. Moreover, the failure modes of capacitive MEMS microphone were detected by using a technique which is based on acoustic measurements for the pull-in and snapback voltage ranges [24]. The results showed a significant rate in detecting membrane capture events for this type of device.…”

Section: Introductionmentioning

confidence: 99%

Self-diagnostic approach for cell counting biosensor

Al-Gayem

Jaafar

Hreshee

2021

IJEECS

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<span id="docs-internal-guid-66699b2e-7fff-5c7e-3931-5de920908f42"><span>In this research, a test monitoring strategy for an array of biosensors is proposed. The principle idea of this diagnostic technique is to measure and compare the impedance of each sensor in the array to achieve fully controlled online health monitoring technique at the system level. The work includes implementation of the diagnostic system, system architecture for analogue part, and SNR analysis. The technique has been applied on a cell coulter counting biochip where the design and fabrication of this sensing chip with electrodes make the coulter counter be an effective mean to count and analyses the cells in a blood sample. The experimental results show that the indication factor of the sensing electrodes has increased from 1 to 1.8 gradually depending on the fault level.</span></span>

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Investigation Into Low Frequency Response of Acoustic MEMS for Determination of Failure Modes

Hantos

Desmulliez

2021

IEEE Trans. Semicond. Manufact.

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Acoustic methods for detection of specific failure modes in capacitive MEMS microphones

Cited by 3 publications

References 22 publications

On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

Self-diagnostic approach for cell counting biosensor

Investigation Into Low Frequency Response of Acoustic MEMS for Determination of Failure Modes

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