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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 4947

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Special Issue Editors

Prof. Dr. Pavel Fiala

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Guest Editor

Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, 616 00 Brno, Czech Republic
Interests: numerical modeling; measurement; metrology; low-level measurements; pulsed power generators; harvesters; microwave technology; MEMS / NEMS; electromagnetic field; sensing technology; sensors; coupled modeling; plasma, nanoengineering
Special Issues, Collections and Topics in MDPI journals

Dr. Petr Drexler

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Guest Editor

Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, 616 00 Brno, Czech Republic
Interests: optical measurement; pulse technology; RF and UHF sensors; harvesting; electrical circuits; theoretical electrical engineering; sensors

Dr. Miloslav Steinbauer

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Guest Editor

Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, 616 00 Brno, Czech Republic
Interests: HF magnetic field; NMR; NQR; measurement; pulse power technology; RF and UHF sensors; harvesting; electrical circuits; theoretical electrical engineering; numerical modeling; electronics; sensors

Special Issue Information

Dear Colleagues,

This Special Issue of the magazine aims to highlight:

(a) The theoretical foundations of harvesting (electromagnetic field) as a form of energy conversion to electrical energy with broader applications, to focus on some applications (technological and implementation issues) in MEMS and NEMS sensors, to address the issue of choice of principles and processing of harvesting technical solution (efficiency, yield, limiting factors of operation) for the chosen shape and size of the sensor.

(b) The sensor as a non-trivial device has very different energy requirements for specific purposes, and therefore it is important to address in a targeted manner the possibilities of energy generation, conversion, utilization and storage for both energy and data/information purposes.

Prof. Dr. Pavel Fiala
Dr. Petr Drexler
Dr. Miloslav Steinbauer
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

transformation
MEMS
NEMS
sensors
harvesting

Published Papers (4 papers)

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Research

21 pages, 4912 KiB

Open AccessArticle

Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition

by Fernanda Irrera, Alessandro Gumiero, Alessandro Zampogna, Federico Boscari, Angelo Avogaro, Michele Antonio Gazzanti Pugliese di Cotrone, Martina Patera, Luigi Della Torre, Nicola Picozzi and Antonio Suppa

Sensors 2024, 24(5), 1554; https://doi.org/10.3390/s24051554 - 28 Feb 2024

Viewed by 558

Abstract

We propose a new methodology for long-term biopotential recording based on an MEMS multisensor integrated platform featuring a commercial electrostatic charge-transfer sensor. This family of sensors was originally intended for presence tracking in the automotive industry, so the existing setup was engineered for the acquisition of electrocardiograms, electroencephalograms, electrooculograms, and electromyography, designing a dedicated front-end and writing proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in a domestic environment will be discussed in detail. The excellent results indicate that this technology can provide a low-power, unexplored solution to biopotential acquisition. The technological breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, it opens up additional possibilities for wearable sensors and strengthens the role of MEMS technology in medical wearables for the long-term synchronous acquisition of a wide range of signals. Full article

(This article belongs to the Special Issue Application of MEMS/NEMS-Based Sensing Technology)

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11 pages, 2637 KiB

Open AccessCommunication

A Reliability Analysis of a MEMS Flow Sensor with an Accelerated Degradation Test

by Qiaoqiao Kang, Yuzhe Lin and Jifang Tao

Sensors 2023, 23(21), 8733; https://doi.org/10.3390/s23218733 - 26 Oct 2023

Cited by 1 | Viewed by 1155

Abstract

With the wide application of flow sensors, their reliability under extreme conditions has become a concern in recent years. The reliability of a Micro Electro Mechanical Systems (MEMS) flow sensor under temperature

{(T}_{s})

is researched in this paper. This flow [...] Read more.

{(T}_{s})

is researched in this paper. This flow sensor consists of two parts, a sensor chip and a signal-processing system (SPS). Firstly, the step-stress accelerated degradation test (SSADT) is implemented. The sensor chip and the flow sensor system are tested. The results show that the biggest drift is 3.15% for sensor chips under 150 °C testing conditions, while 32.91% is recorded for the flowmeters. So, the attenuation of the SPS is significant to the degeneration of this flowmeter. The minimum drift of the SPS accounts for 82.01% of this flowmeter. Secondly, using the Coffin–Manson model, the relationship between the cycle index and

T_{s}

is established. The lifetime with a different

T_{s}

is estimated using the Arrhenius model. In addition, Weibull distribution (WD) is applied to evaluate the lifetime distribution. Finally, the reliability function of the WD is demonstrated, and the survival rate within one year is 87.69% under 85 °C conditions. With the application of accelerated degradation testing (ADT), the acquired results are innovative and original. This research illustrates the reliability research, which provides a relational database for the application of this flow sensor. Full article

(This article belongs to the Special Issue Application of MEMS/NEMS-Based Sensing Technology)

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27 pages, 10559 KiB

Open AccessArticle

Buildings’ Biaxial Tilt Assessment Using Inertial Wireless Sensors and a Parallel Training Model

by Luis Pastor Sánchez-Fernández, Luis Alejandro Sánchez-Pérez, José Juan Carbajal-Hernández, Mario Alberto Hernández-Guerrero and Lucrecia Pérez-Echazabal

Sensors 2023, 23(11), 5352; https://doi.org/10.3390/s23115352 - 05 Jun 2023

Cited by 1 | Viewed by 948

Abstract

Applications of MEMS-based sensing technology are beneficial and versatile. If these electronic sensors integrate efficient processing methods, and if supervisory control and data acquisition (SCADA) software is also required, then mass networked real-time monitoring will be limited by cost, revealing a research gap related to the specific processing of signals. Static and dynamic accelerations are very noisy, and small variations of correctly processed static accelerations can be used as measurements and patterns of the biaxial inclination of many structures. This paper presents a biaxial tilt assessment for buildings based on a parallel training model and real-time measurements using inertial sensors, Wi-Fi Xbee, and Internet connectivity. The specific structural inclinations of the four exterior walls and their severity of rectangular buildings in urban areas with differential soil settlements can be supervised simultaneously in a control center. Two algorithms, combined with a new procedure using successive numeric repetitions designed especially for this work, process the gravitational acceleration signals, improving the final result remarkably. Subsequently, the inclination patterns based on biaxial angles are generated computationally, considering differential settlements and seismic events. The two neural models recognize 18 inclination patterns and their severity using an approach in cascade with a parallel training model for the severity classification. Lastly, the algorithms are integrated into monitoring software with 0.1° resolution, and their performance is verified on a small-scale physical model for laboratory tests. The classifiers had a precision, recall, F1-score, and accuracy greater than 95%. Full article

(This article belongs to the Special Issue Application of MEMS/NEMS-Based Sensing Technology)

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15 pages, 3437 KiB

Open AccessFeature PaperArticle

A Novel High-Sensitivity MEMS Pressure Sensor for Rock Mass Stress Sensing

by Honghui Wang, Dingkang Zou, Peng Peng, Guangle Yao and Jizhou Ren

Sensors 2022, 22(19), 7593; https://doi.org/10.3390/s22197593 - 07 Oct 2022

Cited by 8 | Viewed by 1755

Abstract

This paper proposes a novel high-sensitivity micro-electromechanical system (MEMS) piezoresistive pressure sensor that can be used for rock mass stress monitoring. The entire sensor consists of a cross, dual-cavity, and all-silicon bulk-type (CCSB) structure. Firstly, the theoretical analysis is carried out, and the relationship between the structural parameters of the sensor and the stress is analyzed by finite element simulation and curve-fitting prediction, and then the optimal structural parameters are also analyzed. The simulation results indicate that the sensor with the CCSB structure proposed in this article obtained a high sensitivity of 87.74 μV/V/MPA and a low nonlinearity error of 0.28% full-scale span (FSS) within the pressure range of 0–200 MPa. Compared with All-Si Bulk, grooved All-Si Bulk, Si-Glass Bulk, silicon diaphragm, resistance strain gauge, and Fiber Bragg grating structure pressure sensors, the designed sensor has a significant improvement in sensitivity and nonlinearity error. It can be used as a new sensor for rock disaster (such as collapse) monitoring and forecasting. Full article

(This article belongs to the Special Issue Application of MEMS/NEMS-Based Sensing Technology)

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