Design of a Characterisation Environment for a MEMS Ultrasound Sensor under Guided Ultrasonic Wave Excitation

2021 ◽  
Vol 10 (1) ◽  
pp. 58
Author(s):  
Liv Rittmeier ◽  
Thomas Roloff ◽  
Jan Niklas Haus ◽  
Andreas Dietzel ◽  
Michael Sinapius

Microelectromechanical Systems (MEMS) are a current subject of research in the field of structural health monitoring (SHM) for the detection of guided ultrasonic waves (GUW). The dispersive behaviour of GUW, reflections and other kinds of wave interactions might result in a complex wave field that requires a specific analysis and interpretation of the recorded signals. This makes it difficult or impossible to interpret the sensor signal regarding the distinguishability between the sensor transfer behaviour and the specific behaviour of the test structure. Therefore, a proper application-suited design of the tested structure is crucial for reliable sensor characterisation. The aim of this contribution is the design and evaluation of a setup that allows a representative situation for a GUW application and provides a defined vibration energy for a MEMS sensor characterisation. Parameters such as the specimen’s geometry, material properties and the sensor specifications are taken into account as well as the experimental settings of the GUW excitation. Furthermore, the requirements for the test application case are discussed.

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 353
Author(s):  
Bin Zhang ◽  
Hongsheng Liu ◽  
Dezhi Li ◽  
Jinhui Liang ◽  
Jun Gao

Energy harvesting using piezoceramic has drawn a lot of attention in recent years. Its potential usage in microelectromechanical systems is starting to become a reality thanks to the development of an integrated circuit. An accurate equivalent circuit of piezoceramic is important in energy harvesting and the sensing system. A piezoceramic is always considered to be a current source according to empirical testing, instead of the derivation from its piezoelectric characteristics, which lacks accuracy under complicated mechanical excitation situations. In this study, a new current output model is developed to accurately estimate its value under various kinds of stimulation. Considering the frequency, amplitude and preload variation imposed on a piezoceramic, the multivariate model parameters are obtained in relation to piezo coefficients. Using this model, the current output could be easily calculated without experimental testing in order to quickly estimate the output power in energy harvesting whatever its geometric shape and the various excitations.


2001 ◽  
Author(s):  
Emily J. Pryputniewicz ◽  
John P. Angelosanto ◽  
Gordon C. Brown ◽  
Cosme Furlong ◽  
Ryszard J. Pryputniewicz

Abstract Using recent advances in microelectromechanical systems (MEMS) technology, a new multivariable sensor was developed. This MEMS sensor, capable of measuring temperature, absolute pressure, and differential pressure on a single chip, is particularly suitable for applications in process control industry. However, functional operation of the sensor depends on validation of its performance under specific test conditions. We have developed a hybrid methodology, based on analysis and measurements, that allows such validation. In this paper, the MEMS multivariable sensor is described, the hybrid methodology is outlined, and its use is illustrated with representative results.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Clara Sanz Morère ◽  
Łukasz Surażyński ◽  
Ana Rodrigo Pérez-Tabernero ◽  
Erkki Vihriälä ◽  
Teemu Myllylä

Locomotor activities are part and parcel of daily human life. During walking or running, feet are subjected to high plantar pressure, leading sometimes to limb problems, pain, or foot ulceration. A current objective in foot plantar pressure measurements is developing sensors that are small in size, lightweight, and energy efficient, while enabling high mobility, particularly for wearable applications. Moreover, improvements in spatial resolution, accuracy, and sensitivity are of interest. Sensors with improved sensing techniques can be applied to a variety of research problems: diagnosing limb problems, footwear design, or injury prevention. This paper reviews commercially available sensors used in foot plantar pressure measurements and proposes the utilization of pressure sensors based on the MEMS (microelectromechanical systems) technique. Pressure sensors based on this technique have the capacity to measure pressure with high accuracy and linearity up to high pressure levels. Moreover, being small in size, they are highly suitable for this type of measurement. We present two MEMS sensor models and study their suitability for the intended purpose by performing several experiments. Preliminary results indicate that the sensors are indeed suitable for measuring foot plantar pressure. Importantly, by measuring pressure continuously, they can also be utilized for body balance measurements.


Author(s):  
S. Sathyanarayanan ◽  
A. Vimala Juliet

Micromachining technology has greatly benefited from the success of developments in implantable biomedical microdevices. In this paper, microelectromechanical systems (MEMS) capacitive pressure sensor operating for biomedical applications in the range of 20–400 mm Hg was designed. Employing the microelectromechanical systems technology, high sensor sensitivities and resolutions have been achieved. Capacitive sensing uses the diaphragm deformation-induced capacitance change. The sensor composed of a rectangular polysilicon diaphragm that deflects due to pressure applied over it. Applied pressure deflects the 2 µm diaphragm changing the capacitance between the polysilicon diaphragm and gold flat electrode deposited on a glass Pyrex substrate. The MEMS capacitive pressure sensor achieves good linearity and large operating pressure range. The static and thermo electromechanical analysis were performed. The finite element analysis data results were generated. The capacitive response of the sensor performed as expected according to the relationship of the spacing of the plates.


Author(s):  
Hiro Yoshida ◽  
Takahiro Inoue ◽  
Yinsheng Li

A series of finite element analyses with elastic assumption were made to predict the plausible damage behavior of axial and radial type ceramic blades. Present analysis showed that the stress peaking process was strongly influenced by the interaction of various stress waves. Peaks of the maximum principal tensile (PMPT) stress are considered to lead to the structural damages. In the axial blade, locations of the PMPT stress qualitatively corresponded well with the damaged parts of the blade observed in the experiment. The maximum PMPT stress appeared on the suction (impact) surface and the averaged PMPT stress value on this surface was roughly twice as large as that in the pressure surface. On the radial blade, the maximum PMPT stress occurred in the pressure surface, contrary to the axial blade. Its value was remarkably larger than the initial impact stress due to the complex wave interactions. In spite of the elastic assumption, the present finite element analysis is useful in understanding structural fracture behavior.


2021 ◽  
Author(s):  
Phoebe Utting ◽  
Giles Hammond ◽  
Abhinav Prasad ◽  
Richard Middlemiss

<p>Gravimetry has many useful applications from volcanology to oil exploration; being a method able to infer density variations beneath the ground. Therefore, it can be used to provide insight into subsurface processes such as those related to the hydrothermal and magmatic systems of volcanoes. Existing gravimeters are costly and heavy, but this is changing with the utilisation of a technology most notably used in mobile phone accelerometers: MEMS –(Microelectromechanical-systems). Glasgow University has already developed a relative MEMS gravimeter and is currently collaborating with multiple European institutions to make a gravity sensor network around Mt Etna - NEWTON-g. A second generation of the MEMS sensor is now being designed and fabricated in the form of a semi-absolute pendulum gravimeter. Gravity data for geodetic and geophysical use were provided by pendulum measurements from the 18<sup>th</sup> to the 20<sup>th</sup> century. However, scientists and engineers reached the limit of fabrication tolerances and readout accuracy approximately 100 years ago. With nanofabrication and modern electronics techniques, it is now possible to create a competitive pendulum gravimeter again. The pendulum method is used to determine gravity values from the oscillation period of a pendulum with known length. The current design couples two pendulums together. Here, an optical shadow-sensor pendulum readout technique is presented. This employs an LED and split photodiode set-up. This optical readout can provide measurements to sub-nanometre precision, which could enable gravitational sensitivities for useful geophysical surveying. If semi-absolute values of gravity can be measured, then instrumental drift concerns are reduced. Additionally, the need for calibration against commercial absolute gravimeters may not be necessary. This promotes improved accessibility of gravity measurements at an affordable cost.</p>


Materials ◽  
2012 ◽  
Vol 5 (12) ◽  
pp. 2917-2926 ◽  
Author(s):  
Yunbo Shi ◽  
Hao Guo ◽  
Haiqiao Ni ◽  
Chenyang Xue ◽  
Zhichuan Niu ◽  
...  

2021 ◽  
pp. 875529302098196
Author(s):  
Alireza Taale ◽  
Carlos E Ventura ◽  
Jose Marti

The microelectromechanical systems (MEMS) accelerometer built into a smart meter (SM) has a nominal digital resolution of 16 bits. However, this resolution collapses to 7 bits of information per sample when used in an urban environment. This collapse in resolution limits the sensitivity required to effectively operate the earthquake early warning platform (EEWP). In this study, we evaluate the performance of the MEMS sensor in present SMs with respect to a reference sensor, with a special focus on its poor noise power spectral density (PSD, [Formula: see text]). We also explore the general capacity of the SM in an IoT-based EEWP and provide explicit information regarding the 16-bit digital MEMS accelerometer. Then, we investigate the functionality of the sensor in the context of event detection in the presence of background vibration. When the value of acceleration root mean square (RMS) exceeds 20 mg, the meter’s error decreases to <20%, whereas the peak ground acceleration error decreases to <20% for the peak value greater than ~70 mg. The MEMS sensor is unreliable for motions with a peak acceleration of less than 148 mg or those with an RMS value less than 46 mg. However, we note that SMs exhibit reasonable amplitude and phase coherence for frequencies above 1 Hz with respect to the reference accelerometer. To enhance the sensitivity, averaging 1000 coherent accelerometer observations enhances the digital resolution to 14 bits, which allows the efficient usage of the network bandwidth. Since the accelerometer is used as an anti-tampering mechanism, the SM is similar to a tiltmeter. Therefore, it is necessary to reconfigure SMs for early warning systems. Despite the challenges, the use of SM for an IoT-based EEWP is technically feasible.


2016 ◽  
Vol 23 (8) ◽  
pp. 1108-1120 ◽  
Author(s):  
Kajetan Dziedziech ◽  
Lukasz Pieczonka ◽  
Piotr Kijanka ◽  
Wieslaw J Staszewski

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 268
Author(s):  
Mohammad H Hasan ◽  
Amin Abbasalipour ◽  
Hamed Nikfarjam ◽  
Siavash Pourkamali ◽  
Muhammad Emad-Ud-Din ◽  
...  

The goal of this paper is to provide a novel computing approach that can be used to reduce the power consumption, size, and cost of wearable electronics. To achieve this goal, the use of microelectromechanical systems (MEMS) sensors for simultaneous sensing and computing is introduced. Specifically, by enabling sensing and computing locally at the MEMS sensor node and utilizing the usually unwanted pull in/out hysteresis, we may eliminate the need for cloud computing and reduce the use of analog-to-digital converters, sampling circuits, and digital processors. As a proof of concept, we show that a simulation model of a network of three commercially available MEMS accelerometers can classify a train of square and triangular acceleration signals inherently using pull-in and release hysteresis. Furthermore, we develop and fabricate a network with finger arrays of parallel plate actuators to facilitate coupling between MEMS devices in the network using actuating assemblies and biasing assemblies, thus bypassing the previously reported coupling challenge in MEMS neural networks.


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