Microelectromechanical Systems Sensors Research Articles

Optimal sensor placement and model updating applied to the operational modal analysis of a nonuniform wind turbine tower

Abstract. Test planning is a crucial step in the operational modal analysis (OMA) of wind turbines (WT), and it is an essential part of choosing the best positions for installing the sensors of the structures. On the other hand, updating the finite element model (FEM) with the OMA results implies a better prediction of the real structure's dynamic and vibrational behavior. This paper aims to show how the OMA of a nonuniform and two-section wind turbine tower can be performed more effectively, using the required test planning and optimal sensor placement. Then, accordingly, the OMA is used in operating and parked conditions to find the objective bending mode characteristics. Moreover, the updating of the applicable FEM of the multi-sectional wind turbine tower will be described. The tailor-made genetic algorithm (GA) is used to find the MEMS (micro electro-mechanical system) sensors' optimal positions of the WT under study. The OMA was performed and the acquired data analyzed using the stochastic subspace identification (SSI) method. Based on the OMA results, the FEM is updated by applying the sensitivity method. The results show that a tailor-made GA is a practical and quick approach to finding the optimal position of the sensors to obtain the best results for the objective modes of the WT. The OMA results, under operating and parked conditions, prove some modal characteristics of WTs. Based on the sensitivity analysis and engineering judgment, the modulus of elasticity was selected as a parameter for updating. Finally, we found that the updated FEM had less than 1 % error compared to the obtained frequencies from the test.

A monolithic three-dimensional thermal convective acoustic vector sensor with acoustic-transparent heat sink.

An acoustic vector sensor can directly detect acoustic particle velocity based on the measured temperature difference between closely spaced heated wires. For the detection of velocity in three dimensions, an integrated three-dimensional (3 D) sensor is desired, but it remains challenging in MEMS (Micro-Electro-Mechanical System) manufacturing. Here, a novel monolithic 3 D acoustic vector sensor is proposed, which is constructed using in-plane distributed wires assembled with acoustically transparent heat sink. The planar MEMS structure of the proposed sensor makes it easy to be fabricated and packaged. This work offers a new method for the design of acoustic vector sensors and other thermal convection-based MEMS sensors.

Design of a Capacitive MEMS Accelerometer with Softened Beams

Lower stiffness can improve the performance of capacitive-based microelectromechanical systems sensors. In this paper, softened beams, achieved by the electrostatic assembly approach, are proposed to lower the stiffness of a capacitive MEMS accelerometer. The experiments show that the stiffness of the accelerometer is reduced by 43% with softened beams and the sensitivity is increased by 72.6%. As a result, the noise of the accelerometer is reduced to 26.2 μg/√Hz with an improvement of 44.5%, and bias instability is reduced to 5.05 μg with an enhancement of 38.7%. The electrostatic assembly-based stiffness softening technique is proven to be effective and can be used in many types of MEMS devices.

Enhanced H2S sensing performance of BiFeO3 based MEMS gas sensor with corona poling

In this work, BiFeO3 (BFO) nanoparticles of rhombohedral distorted perovskite structure with a particle about 50–100 nm are prepared by a facile sol-gel method. The as-prepared BFO nanoparticles are treated by the corona poling under different electric fields. The H2S gas sensing performances of as-obtained BFO based MEMS sensors are improved with the increase of corona poling fields. The BFO-P4 (corona poling at 4 kV) sensor exhibites a high response value of 4.8 to 1.2 ppm H2S at 220 °C, with a detection limit of 10 ppb and a short response/recovery time of only 3/7 s respectively. The corona poling treatment promotes the ion displacement, lattice expansion and dipole moments increase with the enhanced internal electric field in BFO nanoparticles, which are responsible for the reduced band gap and the increased adsorption oxygen, and thus improving H2S sensing performances of BFO based Micro-Electro-Mechanical System (MEMS) gas sensor.

Local instantaneous heat flux measurements in an internal combustion engine using a MEMS sensor

• Local instantaneous heat flux was clearly measured using a resistance-type sensor. • Local instantaneous heat flux exhibited a strong cycle-to-cycle variation. • Influence of turbulent eddy on heat flux was detected experimentally. • Local heat transfer coefficient also exhibited a strong cycle-to-cycle variation. Wall heat transfer is one of the most important aspects of internal combustion engines. In this study, the local instantaneous heat transfer characteristics were investigated using an originally developed thin-film resistance-type sensor. The sensor, which was fabricated by micro-electro-mechanical systems (MEMS) technology, had advantages in the sensitivity, the spatial resolution, and the number of measurement points compared with conventional sensors. The MEMS sensor could clearly detect the cycle-by-cycle heat flux. Consequently, it was found that the local instantaneous heat flux had a strong cycle-to-cycle variability, the magnitude of which was in the order of 0.1–1 MW/m 2 , not only in fired operations but also a motored operation. The heat transfer coefficients also exhibited a strong cyclic variability with a magnitude of 0.1–1 kW/(m 2 ⋅K). These results indicated that the heat transfer characteristics could not be properly evaluated only by the conventional analysis based on the ensemble-averaged data. Additionally, it was found that the heat fluxes at the adjacent points exhibited similar but different values, indicating that there were turbulent eddies of sub-millimeter scale and they affected the local heat transfer. Since the local instantaneous heat transfer had quite different characteristics from the average, advanced design and control based on the understandings of the local instantaneous characteristics will be need for the further improvement of the engine’s thermal efficiency.

MEMS Sensor Network for Submarine Terrain and Strata Deformation Monitoring: Design and Field Experiment

The deformation monitoring of terrain and shallow strata is important to the gas hydrate mining environment and the early warning of seabed instabilities. Due to the complexity of the deep-sea environment and the difficulty of the seabed operation, in-situ and high-precision deformation monitoring of terrain and shallow strata simultaneously are big challenges for existing observation methods. This paper describes the design and experimental research of a terrain and strata deformation monitoring system based on MEMS (Micro-electro mechanical system) sensor network (SN). The SN consists of a horizontal array and a vertical array containing multiple cascaded MEMS accelerometers. The pitch angle and roll angle of the monitoring node can be calculated through the three-axis components of the accelerometer in the gravity field. Then, a reconstruction model of the terrain and strata deformation was proposed based on the rotation matrix and the arc model. To evaluate the monitoring system and validate the reconstruction model, a field experiment was conducted on a tidal flat in Changzhi Island for one week. The deformation of the terrain and strata and the pore water pressure were measured and obtained. The results demonstrate the feasibility of the proposed system.

Technique of TiNi-based shape memory alloy thin film coating on optical fibers

<sec>Intelligent, integrated and cost-effective micro-electro-mechanical system (MEMS) and micro sensors can be developed with TiNi-based memory alloy thin film and optical fibers. Such devices can work in harsh environment, like in deep sea, in space with flammable or explosive objects, or with strong electromagnetic interference; and examples of their possible applications include gas concentration detection in underground mines, dynamic detection of production parameters in oil or gas mining, etc. As TiNi-based memory alloy thin film possesses good biocompatibility, such devices can also be used in intracranial/endocardial pressure test, surgical resection, early cancer assessment, etc. The successful development of the above MEMS and micro sensors involve optical fibers coated with memory alloy films. However, unlike the common planar substrates, optical fiber is of a cylinder with a small diameter, and how to grow good-quality memory alloy film on its surface remains to be explored.</sec><sec>In this work, the silica fibers are coated with TiNi memory alloy films by magnetron sputtering. How to choose the proper operating parameters in the sputtering process, and also the effects of subsequent annealing treatment on the films, are discussed in detail. Uniform thin films are grown on the 125-μm-diameter cylindrical surfaces of optical fibers with our built coating mask device specially designed for fibers. The experiments show that when target-substrate distance, background vacuum degree, Ar gas flow and sputtering time are fixed in the sputtering process, the sputtering power can be optimized, while a higher sputtering pressure results in lower film deposition rate but better surface roughness. The thin film is well crystallized under annealing, and the major martensite B19′ phase and minor austenite B2 phase coexist in the Ti<sub>49.09</sub>Ni<sub>50.91</sub> film. In the experiments, with the optimal operating parameters (sputtering power of 150 W and sputtering pressure of 0.23 Pa), TiNi memory alloy film about 852.2 nm in thickness is grown on the fiber at a deposition rate of 0.118 nm/s, and surface root mean square roughness of the unannealed film is 15.1 nm. Annealing at temperatures of 500, 550 and 600 ℃ are respectively tried, and such a thermal treatment evidently refines the crystalline grains inside the film. Surface root mean square roughness of the film annealed at 600 ℃ is reduced to 6.32 nm.</sec><sec>This work indicates that a glass fiber can be coated with high-quality TiNi-based memory alloy film, and it thus forms a part of the bases of further development of relevant MEMS and micro sensors.</sec>

Stress Testing for Performance Analysis of Orientation Estimation Algorithms

Technological advancements have seen the spread of MEMS (Micro-electromechanical Systems) based sensors such as IMU (Inertial Measurement Unit) systems. The latter provide object orientation information in numerous applications such as smartphones, robotics, automotive, drones, and many others. In more detail, IMUs based on MEMS technology are characterized by small size, low power, and low cost. Technically, orientation information is provided by appropriate orientation estimation algorithms fed with quantities measured by MEMS sensors, such as acceleration, angular velocity, and magnetic field. A preliminary work pointed out that such MEMS sensors suffer significant drifts when they have to endure non-standard operating profiles in terms of thermal conditions. However, when considering very low-cost devices, the influence of temperature on the operation of orientation estimation algorithms still remains an important research gap in the literature. To deal with this important aspect, the paper proposes a specific test plan to analyze the performances of MEMS-based IMUs by considering a temperature stress test. Therefore, the effect of temperature was first analyzed on the individual sensors of the IMU (accelerometer, gyroscope, and magnetometer), then the effects of a very simple temperature compensation strategy were analyzed to highlight the importance of such step. Specifically, the effects of not compensating for temperature were studied considering a low-cost commercial IMU typically used in various fields of application. To better quantify such effects in practical applications, two well-known orientation estimation algorithms (i.e., Complementary Filter and AHRS) typically fed by IMUs output have been considered. The experimental results obtained using the custom devices under test show that temperature compensation is necessary for the best performance of the analyzed orientation estimation algorithms.

A Practical Implementation of a Low-Cost 6-DOF IMU by Kalman Algorithm

In this study, the implementation of a 6 Degree of Freedom (DOF) Inertial Measurement Unit (IMU) via the Kalman Filter is aimed. High accuracy IMU units have been in practical use since the first space navigation practices. Today, the need for IMU’s have been widespread among every aspect of life. The IMU sensors are mostly solid-state devices and are manufactured with Micro Electromechanical System (MEMS) technologies. The sensor noise has to be eliminated. The most popular method is the Kalman Filtering. The aim of this study is to better explain the IMU concept and make a practical implementation of the Kalman Filtering which is somehow complicated. In this study, a low cost IMU MEMS sensor has been selected and Kalman Filtering has been applied for both one and multi-dimensional outputs. The steps are explicitly explained to help the reader better understand the process. The study may be easily tailored to other sensor systems where noise is a concern.

A MEMS IMU Gyroscope Calibration Method Based on Deep Learning

The errors of microelectromechanical system (MEMS) inertial measurement units (IMUs) are huge, complex, nonlinear, and time varying. The traditional calibration method based on a linear model for calibration and compensation is obviously not applicable. In this article, a calibration method based on deep learning is proposed for MEMS IMU gyroscopes. In this method, the output model of MEMS IMU gyroscope is constructed by using the temporal convolutional network. Based on the powerful data processing capability of deep learning, the error features are obtained from the gyroscope data in the past, and the gyroscope data after the error compensation can be regressed. The method in this article is validated on public dataset. The experimental results show that compared with the existing MEMS sensor error compensation method based on deep learning, the attitude and position accuracy obtained by the inertial navigation solution using the compensated gyroscope data are improved, which proves that the proposed method can effectively and accurately calibrate the gyroscope error.

Upper Body Posture Recognition Using Inertial Sensors and Recurrent Neural Networks

Inadequate sitting posture can cause imbalanced loading on the spine and result in abnormal spinal pressure, which serves as the main risk factor contributing to irreversible and chronic spinal deformity. Therefore, sitting posture recognition is important for understanding people’s sitting behaviors and for correcting inadequate postures. Recently, wearable devices embedded with microelectromechanical systems (MEMs) sensors, such as inertial measurement units (IMUs), have received increased attention in human activity recognition. In this study, a wearable device embedded with IMUs and a machine learning algorithm were developed to classify seven static sitting postures: upright, slump, lean, right and left bending, and right and left twisting. Four 9-axis IMUs were uniformly distributed between thoracic and lumbar regions (T1-L5) and aligned on a sagittal plane to acquire kinematic information about subjects’ backs during static-dynamic alternating motions. Time-domain features served as inputs to a signal-based classification model that was developed using long short-term memory-based recurrent neural network (LSTM-RNN) architecture, and the model’s classification performance was used to evaluate the relevance between sensor signals and sitting postures. Overall results from performance evaluation tests indicate that this IMU-based measurement and LSTM-RNN structural scheme was appropriate for sitting posture recognition.

AZO-Based ZnO Nanosheet MEMS Sensor with Different Al Concentrations for Enhanced H2S Gas Sensing.

The properties of H2S gas sensing were investigated using a ZnO nanostructure prepared with AZO (zinc oxide with aluminium) and Al surfaces which were developed on a MEMS (Micro Electromechanical System) device. Hydrothermal synthesis was implemented for the deposition of the ZnO nanostructure. To find the optimal conditions for H2S gas sensing, different ZnO growth times and different temperatures were considered and tested, and the results were analysed. At 250 °C and 90 min growth time, a ZnO sensor prepared with AZO and 40 nm Al recorded an 8.5% H2S gas-sensing response at a 200 ppb gas concentration and a 14% sensing response at a gas concentration of 1000 ppb. The dominant sensing response provided the optimal conditions for the ZnO sensor, which were 250 °C temperature and 90 min growth time. Gas sensor selectivity was tested with five different gases (CO, SO2, NO2, NH3 and H2S) and the sensor showed great selectivity towards H2S gas.

Photon force microelectromechanical system cantilever combined with a fibre optic system as a measurement technique for optomechanical studies

In this paper we present a metrological measurement technique that is a combination of fibre optic interferometry and a microelectromechanical system (MEMS) sensor for photon force (PF) measurement with traceability via an electromagnetic method. The main advantage of the presented method is the reference to the current balance, which is the primary mass/force metrological standard. The MEMS cantilever transduces the PF to a deflection that can be compensated with the use of the Lorentz force. This movement is measured with the use of the interferometer and does not require any mechanical calibration. Combining the MEMS current balance system with interferometry is a unique and fully metrological solution. The resolution of the proposed measurement technique is calculated to be 4 pN Hz–0.5 (2% uncertainty). The PF–MEMS used for the investigation is a cantilever with a resolution of 46 fN Hz–0.5, which was calculated from the thermomechanical noise and is far below the resolution limit of the whole system. Because the whole construction is based on a fibre optic system, it does not require any complex adjustment procedure and may work as an optomechanical reference in any metrological laboratory.

Piezoelectric MEMS—evolution from sensing technology to diversified applications in the 5G/Internet of Things (IoT) era

The rapid development of the fifth-generation mobile networks (5G) and Internet of Things (IoT) is inseparable from a large number of miniature, low-cost, and low-power sensors and actuators. Piezoelectric microelectromechanical system (MEMS) devices, fabricated by micromachining technologies, provide a versatile platform for various high-performance sensors, actuators, energy harvesters, filters and oscillators (main building blocks in radio frequency front-ends for wireless communication). In this paper, we provide a comprehensive review of the working mechanism, structural design, and diversified applications of piezoelectric MEMS devices. Firstly, various piezoelectric MEMS sensors are introduced, including contact and non-contact types, aiming for the applications in physical, chemical and biological sensing. This is followed by a presentation of the advances in piezoelectric MEMS actuators for different application scenarios. Meanwhile, piezoelectric MEMS energy harvesters, with the ability to power other MEMS devices, are orderly enumerated. Furthermore, as a representative of piezoelectric resonators, Lamb wave resonators are exhibited with manifold performance improvements. Finally, the development trends of wearable and implantable piezoelectric MEMS devices are discussed.

Characterization and Benchmark of a Novel Capacitive and Fluidic Inclination Sensor.

In this paper, a fluidic capacitive inclination sensor is presented and compared to three types of silicon-based microelectromechanical system (MEMS) accelerometers. MEMS accelerometers are commonly used for tilt measurement. They can only be manufactured by large companies with clean-room technology due to the high requirements during assembly. In contrast, the fluidic sensor can be produced by small- and medium-sized enterprises (SMEs) as well, since only surface mount technologies (SMT) are required. Three different variants of the fluidic sensor were investigated. Two variants using stacked printed circuit boards (PCBs) and one variant with 3D-molded interconnect devices (MIDs) to form the sensor element are presented. Allan deviation, non-repeatability, hysteresis, and offset temperature stability were measured to compare the sensors. Within the fluidic sensors, the PCB variant with two sensor cavities performed best regarding all the measurement results except non-repeatability. Regarding bias stability, white noise, which was determined from the Allan deviation, and hysteresis, the fluidic sensors outperformed the MEMS-based sensors. The accelerometer Analog Devices ADXL355 offers slightly better results regarding offset temperature stability and non-repeatability. The MEMS sensors Bosch BMA280 and TDK InvenSense MPU6500 do not match the performance of fluidic sensors in any category. Their advantages are the favorable price and the smaller package. From the investigations, it can be concluded that the fluidic sensor is competitive in the targeted price range, especially for applications with extended requirements regarding bias stability, noise, and hysteresis.

Effect of -ray irradiation on performance of LiNbO3-based piezoelectric vibration sensors

LiNbO3 (LN)-based micro-electro-mechanical systems (MEMS) vibration sensors exhibit giant perspectives in extreme environments, where a great amount of irradiation exists. However, to the best of our knowledge, it is still unknown whether the irradiation affects the performance of LN-based piezoelectric MEMS sensors. Based on this consideration, it is necessary to model the irradiation environment to investigate the effect of high-dosage irradiation on LN-based vibration sensors. Firstly, the theoretical work is done to study the Compton effect on the gamma-ray irradiation with a 60Co source. After irradiation, X-ray diffraction (XRD) characterization is performed to verify the effect of irradiation on the crystalline of LN thin film. Meanwhile, the performances of output voltages on the five MEMS devices under various dosage of irradiation are compared. As a result, a neglected shift of 0.02 degrees is observed from the XRD image only under maximum irradiation dosage of 100 Mrad(Si). Moreover, the output voltages of cantilever beam vibration sensors decrease by 3.1%. Therefore, it is verified that the γ-ray irradiation has very little influence on the LN-based MEMS vibration sensors, which have great attraction on the materials and sensors under high-dose irradiation.

A novel MEMS sensor concept to improve signal-to-noise ratios

Dynamic measuring concepts of sensors use a variety of different metrics. Some monitor the amplitude and/or phase, while others track resonance frequency or stability thresholds. Based on the underlying physics we further distinguish between quasi-static and dynamic, linear and nonlinear, passive and active, as well as coupled and decoupled concepts. While linear, passive concepts of single and/or decoupled oscillators are the state of the art and therefore widely used in technological applications today, the properties of nonlinear, active and/or coupled oscillators are far less implemented. In this work we theoretically investigate the amplification properties of an active micro-electromechanical system (MEMS) subject to an external dynamic load. Previously derived governing equations describe a real composite MEMS cantilever with integrated self-sensing and self-actuating mechanisms. A comprehensive dynamic analysis is presented to investigate the amplification properties of the active system in contrast to its passive counterpart, including equilibria, modal analysis, stability maps and bifurcation diagrams. New insights reveal compressive nonlinear amplification properties for the operation of the active system — similar to what can be observed by bio-sensor properties in the human cochlea. We conclude the work with a brief discussion on significantly increased noise-filtering properties for future signal processing technologies and how current limits of signal-to-noise ratio can be overcome.

Combination of Ceramic Laser Micromachining and Printed Technology as a Way for Rapid Prototyping Semiconductor Gas Sensors.

The work describes a fast and flexible micro/nano fabrication and manufacturing method for ceramic Micro-electromechanical systems (MEMS)sensors. Rapid prototyping techniques are demonstrated for metal oxide sensor fabrication in the form of a complete MEMS device, which could be used as a compact miniaturized surface mount devices package. Ceramic MEMS were fabricated by the laser micromilling of already pre-sintered monolithic materials. It has been demonstrated that it is possible to deposit metallization and sensor films by thick-film and thin-film methods on the manufactured ceramic product. The results of functional tests of such manufactured sensors are presented, demonstrating their full suitability for gas sensing application and indicating that the obtained parameters are at a level comparable to those of industrial produced sensors. Results of design and optimization principles of applied methods for micro- and nanosystems are discussed with regard to future, wider application in semiconductor gas sensors prototyping.

Fault and calibration shift detection in a robust MEMS accelerometer array

The latest generation micro-electro-mechanical system(MEMS) accelerometers offer high bandwidth and low noisefloors previously limited to piezoelectric (PZT) based sensors.These relatively low cost MEMS sensors drastically expandthe financially practical applications for high frequency,vibration based, prognostics health management (PHM).This paper examines a robust array of MEMS accelerometersfor applications where sensor access after deploymentis difficult or infeasible. Three identical single axis MEMSaccelerometers were place in an array for testing. Insteadof a typical tri-axial configuration, the three sensors werealigned on a common axis. An auto-correlation algorithmwas used to detect gross system faults of individual sensorsin the array. A separate algorithm was developed to detectabnormal sensor sensitivity drift. The 3 sensor array wastested under a variety of conditions to test the developedalgorithms; power supply voltages were systematically variedaffecting the ratio-metric accelerometer sensitivity andindividual sensor mounts were purposely compromised tosimulate common fault symptoms. A decision logic treewas then implemented to respond to both types of faults.Results show the feasibility of implementing robust MEMSaccelerometer arrays using the latest generation of high bandwidthMEMS accelerometers. Planned future work includesdeploying the sensor array on tribology test equipment tovalidate MEMS sensor effectiveness compared to traditionalPZT based accelerometers.

The Application of Quaternions to Strap-Down MEMS Sensor Data.

We describe the mathematical transformations required to convert the data recorded using typical 6-axis microelectromechanical systems (MEMS) sensor packages (3-axis rate gyroscopes and 3-axis accelerometers) when attached to an object undergoing a short duration loading event, such as blast loading, where inertial data alone are sufficient to track the object motion. By using the quaternion description, the complex object rotations and displacements that typically occur are translated into the more convenient earth frame of reference. An illustrative example is presented where a large and heavy object was thrown by the action of a very strong air blast in a complex manner. The data conversion process yielded an accurate animation of the object’s subsequent motion.