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As a kind of long-term favorable device, the microelectromechanical system (MEMS) sensor has become a powerful dominator in the detection applications of commercial and industrial areas. There have been a series of mature solutions to address the possible issues in device design, optimization, fabrication, and output processing. The recent involvement of neural networks (NNs) has provided a new paradigm for the development of MEMS sensors and greatly accelerated the research cycle of high-performance devices. In this paper, we present an overview of the progress, applications, and prospects of NN methods in the development of MEMS sensors. The superiority of leveraging NN methods in structural design, device fabrication, and output compensation/calibration is reviewed and discussed to illustrate how NNs have reformed the development of MEMS sensors. Relevant issues in the usage of NNs, such as available models, dataset construction, and parameter optimization, are presented. Many application scenarios have demonstrated that NN methods can enhance the speed of predicting device performance, rapidly generate device-on-demand solutions, and establish more accurate calibration and compensation models. Along with the improvement in research efficiency, there are also several critical challenges that need further exploration in this area. [ABSTRACT FROM AUTHOR]

Vacuum packaging is used extensively in MEMS sensors for improving performance. However, the vacuum in the MEMS chamber gradually degenerates over time, which adversely affects the long-term performance of the MEMS sensor. A mathematical model for vacuum degradation is presented in this article for evaluating the degradation of vacuum packaged MEMS sensors, and a temperature-accelerated test of MEMS gyroscope with different vacuums is performed. A mathematical degradation model is developed to fit the parameters of the degradation of Q-factor over time at three different temperatures. The results indicate that the outgassing rate at 85 °C is the highest, which is 0.0531 cm2/s; the outgassing rate at 105 °C is the lowest, which is 0.0109 cm2/s; and the outgassing rate at 125 °C is in the middle, which is 0.0373 cm2/s. Due to the different mechanisms by which gas was released, the rate of degradation did not follow this rule. It will also be possible to predict the long-term reliability of vacuum packaged MEMS sensors at room temperature based on this model. [ABSTRACT FROM AUTHOR]

Humidity sensors with comprehensive performance are of great interest for industrial and environmental applications. Most sensors, however, have to compromise on at least one characteristic such as sensitivity, response speed, and linearity. This paper reports a gravimetric humidity sensor based on a capacitive micromachined ultrasonic transducer (CMUT) with exceptional all-around performance, and presents a side-by-side comparative investigation of two types of gravimetric humidity sensors for a better understanding of their characteristics and sensing mechanisms. For these purposes, a circular CMUT and a quartz crystal microbalance (QCM) with a resonance frequency of 10 MHz were designed and fabricated. Poly(vinyl alcohol) (PVA) was employed as the humidity sensing layer for its hydrophilicity and ease of film formation. The electrical properties of the sensors, including the electrical input impedances and quality factors, were characterized by a vector network analyzer. The relative humidity (RH) sensing performance of the sensors was evaluated and compared from RH levels of 11% to 97%. Both sensors exhibited good repeatability and low hysteresis. The unique microscale resonant structure of the CMUT humidity sensor contributed to a high sensitivity of 2.01 kHz/%RH, short response and recovery times of 8 s and 3 s, respectively, and excellent linearity (R2 = 0.973), which were far superior to their QCM counterparts. The underlying mechanism was revealed and discussed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Random drift error is one of the important factors of MEMS (micro-electro-mechanical-system) sensor output error. Identifying and compensating sensor output error is an important means to improve sensor accuracy. In order to reduce the impact of white noise on neural network modeling, the ensemble empirical mode decomposition (EEMD) method was used to separate white noise from the original signal. The drift signal after noise removal is modeled by GRNN (general regression neural network). In order to achieve a better modeling effect, cross-validation and parameter optimization algorithms were designed to obtain the optimal GRNN model. The algorithm is used to model and compensate errors for the generated random drift signal. The results show that the mean value of original signal decreases from 0.1130 m/s2 to −1.2646 × 10−7 m/s2, while the variance decreases from 0.0133 m/s2 to 1.0975 × 10−5 m/s2. In addition, the displacement test was carried out by MEMS acceleration sensor. Experimental results show that the displacement measurement accuracy is improved from 95.64% to 98.00% by compensating the output error of MEMS sensor. By comparing the GA-BP (genetic algorithm-back propagation) neural network and the polynomial fitting method, the EEMD-GRNN method proposed in this paper can effectively identify and compensate for complex nonlinear drift signals. [ABSTRACT FROM AUTHOR]

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An acoustic quench detection method utilizing MEMS (Micro Electro-Mechanical System) acoustic sensors is proposed. To investigate this method, a commercially available MEMS piezoelectric microphone, the Vesper VM1000, and two types of second stage amplifiers, using either an OPA344 or a LMH6629 based amplifier circuit, were characterized at cryogenic temperatures in helium gas. The MEMS microphones were in their original package with an integrated preamplifier. The tests were performed inside a two-stage Gifford-McMahon cryocooler from room temperature down to 60 K, at static pressures between 1.2 and 1.4 bar in gaseous helium, over the frequency band from 100 Hz to 10 kHz. Second stage amplifiers were needed to achieve signal to noise ratios approaching the manufacturer specified operating levels. The OPA344 based amplifier reduced in gain by >55 dB below 230 K, while the LMH6629 based amplifier performed well down to 60 K. The MEMS microphones appear to perform acoustic measurements down to 165 K but with some reduction in sensitivity down to 60 K. An acoustic model of the cryocooler plane wave tube calibration setup is developed and used to calibrate the microphone despite the presence of a significant thermal gradients down the plane wave tube. [ABSTRACT FROM AUTHOR]

Tilt sensors are mainly used to measure the collapse of structures such as buildings, bridges and tunnels. Recently, due to the ease of use and low price, many tilt sensors using MEMS sensors have been used, but the measurement angle range is limited, and thus, they do not have high precision for 360 degree. This is due to the inherent offset and scale errors of MEMS sensors. In this paper, we proposed an algorithm for the calculation of precision angles to reduce the mechanical error of MEMS sensors, and produced a MEMS sensor module and a transmission module to compare the angle accuracy of sensor modules before calibration and the angle measurement accuracy after calibration. Experimental results show that the proposed technique has a precision of ± 0.015 degrees for all 360-degree. [ABSTRACT FROM AUTHOR]

This present research paper proposes the earthquake warning alarm system sense the initial shaking of a main earthquake, trigger alarm system in advance of the mainly aggressive shaking. The caution framework that need been recommended for everywhere the universe might use a organize about advanced seismometers deployed around those state with provide for populated ranges up to each moment about development cautioning. The alerts might permit businesses, inhabitants Also state funded organizations run through with get primed. The reason for the investigation keeps tabs on the identification algorithm utilizing those gathered information choose on a quake is happening. That calculation will be versatile for nature Also will be dependent upon a probabilistic approach through a sliding window on boost the identification for occasions toward changing the likelihood for false alarms under an altered rate. At long last test outcomes would Gave demonstrating that that system will backing the needed execution with both simulated and genuine seismic jolts. A could be allowed development of the approach Might a chance to be actualizing geological remote sensor networks utilizing contemporary Smartphone for information procurement. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this research paper is to develop and analyze micro-electro-mechanical systems sensor for vibration monitoring of pumping aggregate.Design/methodology/approach The system is based on smart sensor and smart mobile phone.Findings The numerous measurements on a wide range of turbo aggregates were performed to establish the operating condition of pumping aggregates.Originality/value Afterwards, the influence of vibration at different positions on the output vibration of the pumping aggregate was analyzed by adaptive neuro fuzzy inference system method. [ABSTRACT FROM AUTHOR]

Here we present a holistic wafer-level approach for the fabrication of highly sensitive electromechanical transducers, using the intrinsic piezoresistive effect of enriched semiconducting single-walled carbon nanotubes (SWCNTs). Therefore membrane based demonstrators were fabricated on 150 mm wafers using MEMS compatible micromachining. Carbon nanotube field-effect transistors were positioned at membrane sites with the highest strain upon pressure driven actuation. The giant piezoresistive effect of SWCNTs was proved and quantified. We derived the gauge factor to be more than 600, which is significantly higher than for common silicon strain gauges. [ABSTRACT FROM AUTHOR]

Low-cost inertial and motion sensors embedded on smartphones have provided a new platform for dynamic activity pattern inference. In this research, a comparison has been conducted on different sensor data, feature spaces and feature selection methods to increase the efficiency and reduce the computation cost of activity recognition on the smartphones. We evaluated a variety of feature spaces and a number of classification algorithms from the area of Machine Learning, including Naive Bayes, Decision Trees, Artificial Neural Networks and Support Vector Machine classifiers. A smartphone app that performs activity recognition is being developed to collect data and send them to a server for activity recognition. Using extensive experiments, the performance of various feature spaces has been evaluated. The results showed that the Bayesian Network classifier yields recognition accuracy of 96.21% using four features while requiring fewer computations. [ABSTRACT FROM AUTHOR]

Abstract: Microcantilevers are very effective tools in detecting of small amount of bio-species and chemicals. Recent advances in metal-oxide-semiconductor field effect transistor (MOSFET) as a transducer to detect the molecule binding-induced cantilever deflection has gained extensive attention due to its high sensitivity and direct compatibility with micro-electro-mechanical system (MEMS) sensors. In this paper, six different piezoresistive nMOSFET-embedded microcantilevers are designed and characterized to systematically study the impacts of different cantilever and transistor channel geometries on the device sensitivity. It is found that the amount of change in the drain current is the same range as reported in the literature. For point-loading applications, transistors with lower channel width are optimal for relative drain current change even though their absolute current output is less. In particular, the embedded nMOSFET Exhibits 63.6% higher sensitivity by decreasing transistor channel width from 300 to 60μm. Furthermore, theoretical results are compared with experimental data to optimize cantilever and transistor geometrical factors to achieve higher stress or force sensitivity. The low frequency noise characteristics of the devices show better resolution for higher aspect-ratio transistors, with drain current noise in the nanoampere range. Results reveal useful design guidelines to enhance the MOSFET-embedded microcantilever sensitivity for various applications. [Copyright &y& Elsevier]

A new method was proposed to measure the thermal conductivity of liquids with infinitesimal samples, which are much smaller than those required in conventional methods. The method utilizes a micro-beam-type MEMS sensor fabricated across a trench on a silicon substrate. Numerical analysis of heat conduction within and around a uniformly heated sensor showed that the temperature of a 10 μm long sensor reached a steady state within approximately 0.1ms, after the start of heating. It was also revealed that the average temperature of the sensor at the steady state was higher in liquids with lower thermal conductivity. These results demonstrate a new idea of measuring the thermal conductivity of liquids within an extremely short time at a steady state before the onset of natural convection. [ABSTRACT FROM AUTHOR]

Abstract: Micro-electro-mechanical system (MEMS) technology offers sensors with lower cost, smaller size, and lower power consumption. In this paper, a kind of low cost motion-sensing system based on MEMS sensors is developed. The objective of the design is: small volume, light weight and low cost, in order to be used in many fields. The constituting principle of the system is described and the algorithms and hardware of the system are researched. The definition of coordinates, calculation of pose angles, transform of acceleration and calculation of the velocities and displacement of the moving object are presented with the corresponding mathematics model and the associated algorithms. The experiments are carried out in principle and the results are given. It is proved that the low cost motion-sensing system is effective and accurate. [Copyright &y& Elsevier]

Piezoresistive pressure sensors are being widely used for various industrial applications, such as in automobiles and process control. But conventional MEMS piezoresistive pressure sensors possess low sensitivity in the lower pressure range for biomedical applications. Alternative structures of MEMS pressure sensors include the use of bossed diaphragms and nanocrystalline piezoresistors. In this paper, four different diaphragm structures—flat diaphragm, standard bossed diaphragm, complementary bossed diaphragm, and nanocrystalline porous silicon-silicon composite diaphragm—have been analyzed in terms of sensitivity and nonlinearity. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel two-dimensional MEMS shear stress sensor is designed for ocean turbulence. • The fabricated sensor has a higher signal-to-noise ratio than PNS shear probe. • Triangular structures are designed at the root of the sensor beam to make it stable. • The sensor could bear pressure of 40 MPa, and has potential to work at 4000 m depth. Ocean turbulence observation is essentially important to the study of microscopic structure and macroscopic motion. The shear probe sensor is one of the effective ways for turbulence measurement. However, most of the shear probe sensors sensitive in a single direction and the observation of turbulence is short of directivity characteristics. In this work, a ciliated two-dimensional MEMS shear stress sensor with high signal to noise ratio is designed for ocean turbulence measurement. The MEMS sensor is composed of four silicon beams with varistors and a bionic cilium. To evaluate the performance of the sensor, comparisons with a PNS shear probe (PNS06) are made in a calibration water tank. The results reveal that the MEMS sensor performs similarly to the PNS shear probe in the same experimental condition and has high signal to noise ratio. Additionally, the MEMS sensor is highly sensitive to flow direction. The MEMS sensor is found to work well under the hydrostatic pressure of 40 MPa, which make it suitable for deep ocean turbulence measurements. [ABSTRACT FROM AUTHOR]

• Miniaturized and highly sensitive CMUT based humidity sensors were developed. • An inkjet printing process was developed to functionalize the CMUTs with uniform graphene oxide films. • The CMUT sensors exhibited high sensitivity, fast response, and low hysteresis. • The hysteresis reduction mechanism was discussed. Capacitive micromachined ultrasonic transducer (CMUT) is a proven MEMS based gravimetric sensor featuring high mass sensitivity. It can be highly sensitive for relative humidity (RH) measurement when drop-casted with moisture-sensitive graphene oxide (GO) film. However, high hysteresis appears to be a critical problem for the sensor partially due to the non-uniformity of the sensing film. Here, we present miniaturized CMUTs that are functionalized by the inkjet-printed GO film and exhibit high sensitivity and meanwhile low hysteresis. Hexagon CMUTs with a side length of 500 μm were designed and fabricated by the nitride-to-oxide wafer bonding process. GO inks were prepared using a mixture of DI water and ethanol as the solvent. A square pattern formed by a 2D array of ink droplets was inkjet printed on the CMUT membranes. GO films with different thicknesses were deposited on three CMUTs. The humidity sensing performance of the sensors was evaluated by measuring the resonance frequency shifts induced by the added mass of adsorbed water molecules. The sensors delivered high RH sensitivity of up to 3.35 kHz/%RH, short response/recovery time down to 8 s/2 s, and hysteresis as low as 2.6 %RH. This work demonstrates that the inkjet printing technique is an excellent tool to functionalize CMUT with the advantages of minimized material consumption, batch-production capability, and exceptional control over the film thickness and quality. The CMUT printed with GO film has also shown to be a promising candidate as a miniaturized humidity sensing platform. [ABSTRACT FROM AUTHOR]

• Development of cantilever-type MEMS tactile sensors with fluoroelastomer. • Measurement in liquid by previous sensor with PDMS is difficult. • Fluoroelastomer has resistance to water, organic solvent, and chemical solutions. • Successful force detection in various solutions by fabricated sensor. In previous works, we have developed cantilever-type MEMS tactile sensors with the PDMS elastomer that are sensitive to force and light and demonstrated that it can detect complex tactile senses including normal and shear forces, proximity, and temperature. However, it is difficult for this sensor to detect correct response in liquid such as water or ethanol because of luck of resistances to these solutions. In this work, we have newly employed the fluoroelastomer as the elastomer material instead of the PDMS. It is demonstrated that fabricated tactile sensor using fluoropolymer can detect force and light successfully in water, ethanol, and NaClO aqueous solution exactly as detection in air. Therefore, this sensor becomes available for uses in various environment or with cleaning and disinfection processes. [ABSTRACT FROM AUTHOR]

With the fast development of the fifth-generation cellular network technology (5G), the future sensors and microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS) are presenting a more and more critical role to provide information in our daily life. This review paper introduces the development trends and perspectives of the future sensors and MEMS/NEMS. Starting from the issues of the MEMS fabrication, we introduced typical MEMS sensors for their applications in the Internet of Things (IoTs), such as MEMS physical sensor, MEMS acoustic sensor, and MEMS gas sensor. Toward the trends in intelligence and less power consumption, MEMS components including MEMS/NEMS switch, piezoelectric micromachined ultrasonic transducer (PMUT), and MEMS energy harvesting were investigated to assist the future sensors, such as event-based or almost zero-power. Furthermore, MEMS rigid substrate toward NEMS flexible-based for flexibility and interface was discussed as another important development trend for next-generation wearable or multi-functional sensors. Around the issues about the big data and human-machine realization for human beings' manipulation, artificial intelligence (AI) and virtual reality (VR) technologies were finally realized using sensor nodes and its wave identification as future trends for various scenarios. [ABSTRACT FROM AUTHOR]

• A novel MEMS sensor for the detection of ferrous particles in liquids is presented. • The sensor consists of a microcantilever and a planar coil to accumulate the particles. • The accumulation of particles leads to a linear shift of the cantilever resonance frequency. • The sensor was capable of detecting 250 nm iron oxide particles in deionized water. • A special class of roof tile-shaped modes offers a mass responsivity of 82.5 pg/Hz. We present a novel MEMS sensor which allows the detection of ferrous particles in liquid environments. The device is based on a resonantly excited silicon microcantilever with an integrated planar coil on its surface, which attracts and accumulates ferrous particles on the sensor via magnetophoresis. The additional mass leads to a shift in resonance frequency of the microcantilever, which in turn can be used to deduce the accumulated particle mass. A reference microcantilever of the same design, which does not actively accumulate particles, is operated in close vicinity to cancel out any parasitic environmental influences, such as fluid temperature fluctuations on the viscosity. The sensor performance is determined by measuring the sensor response to 250 nm iron oxide (Fe 3 O 4) particles, dispersed in deionized water. After a measurement duration of 100 min., a differential resonance frequency shift of 5916 Hz is found, which corresponds to a total accumulated mass of approximately 0.49 μg and a mass responsivity of 82.85 pg/Hz. Based on this result, the detection limit for the sensor in the current design is derived to about 4 ng. Besides its compact and robust architecture, these results promise the successful operation in a broad range of industrial applications, such as predictive maintenance in lubricated machinery. [ABSTRACT FROM AUTHOR]

Inertial navigation systems based on microelectromechanical systems (MEMS) sensors offer advantages that include small size, light weight, low power consumption, strong environmental adaptability, and low cost. These advantages make these sensors particularly suitable for application to precision-guided munitions, which commonly have poor launching environments, strict volume and power consumption requirements, and high cost sensitivity. In this article, the key technologies required for missile-borne integrated navigation systems and the solutions for the problems with each of these technologies are analyzed. An attitude angle estimation method for satellite-assisted MEMS measurement information is proposed that solves the in-flight alignment problem. A high-precision combination of satellite positioning and microinertial navigation is realized through design of a new integrated algorithm framework. The experimental results show that the proposed methods can effectively solve the current problems in guided ammunition navigation. [ABSTRACT FROM AUTHOR]