Drag force micro solid state silicon plate wind velocity sensor

Du, Lidong; Zhao, Zhan; Pang, Cheng; Fang, Zhen

doi:10.1016/j.sna.2009.02.003

Cited by 24 publications

(14 citation statements)

References 8 publications

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“…Recently, the development of multi-sensor integrated technology is a trend in MEMS followed by Du et al, among others, who integrated a previously designed drag force sensor [68] with a thermal one to realize a micro-wind sensor. Also in this case, the sensor utilizes the thermal part for low wind velocity (<2 m·s by measurement of the pressure difference between the stagnant fluid pressure in front of the sensor and static pressure of fluid around the sensor [70].…”

Section: Non-thermal Flow Sensorsmentioning

confidence: 99%

Micromachined Flow Sensors in Biomedical Applications

Silvestri

Schena

2012

Micromachines

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Application fields of micromachined devices are growing very rapidly due to the continuous improvement of three dimensional technologies of micro-fabrication. In particular, applications of micromachined sensors to monitor gas and liquid flows hold immense potential because of their valuable characteristics (e.g., low energy consumption, relatively good accuracy, the ability to measure very small flow, and small size). Moreover, the feedback provided by integrating microflow sensors to micro mass flow controllers is essential to deliver accurately set target small flows. This paper is a review of some application areas in the biomedical field of micromachined flow sensors, such as blood flow, respiratory monitoring, and drug delivery among others. Particular attention is dedicated to the description of the measurement principles utilized in early and current research. Finally, some observations about characteristics and issues of these devices are also reported.

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Section: Non-thermal Flow Sensorsmentioning

confidence: 99%

Micromachined Flow Sensors in Biomedical Applications

Silvestri

Schena

2012

Micromachines

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“…Wind direction and speed are the important parameters in meteorological observation, while the traditional wind sensor is not suitable to apply to the quadcopter for its large size and weight. Fortunately, MEMS technology pushed the development of the wind sensor, and made the devices with small size and low cost possible [3][4][5]. Even though that the thermal and mechanical sensitive elements of wind sensor must be direct contact with fluidic air, which easy be polluted and damaged in meteorological application [6].…”

Section: Introductionmentioning

confidence: 99%

Design of a Wind Sensor Based on Cylinder Diametrical Pressure Differences for Boundary Layer Meteorological Observation

et al. 2018

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Wind speed and direction are important parameters in meteorological observation. Solid wind sensor has needed with small Quadcopter for boundary layer meteorological observation. In this paper the principle of a cylindrical two-dimensional wind sensor is reported by analyzing the data from wind tunnel experiments. A model is proposed to describe the distribution of the pressure difference across a diameter of a cylinder and the wind sensor is fabricated with MEMS differential pressure sensors. In wind tunnel tests in range of 1~40 m/s, the relative speed measuring errors and the direction measuring errors of the prototype are no more than ±(0.2 + 0.03 V) m/s and 5° respectively.

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“…Most of the artificial cilium sensors for which some sort of correlation has been attempted have been fabricated by microelectromechanical (MEMS) processes in three general types: silicon cantilevers that are curled out‐of‐plane, silicon platens attached or fabricated perpendicular to silicon cantilevers, and cylindrical polymer hairs attached perpendicular to silicon cantilevers, polymeric slabs, or tilting plates . While the remainder of these devices have piezoresistive or piezoelectric transducers at the base of the cantilever or across the slab, much work has been done on a hair‐on‐tilting‐plate device with a capacitive transducer that seems to be well suited for detecting dynamic (“AC”) rather than steady airflows .…”

Section: Introductionmentioning

confidence: 99%

CNT‐Based Artificial Hair Sensors for Predictable Boundary Layer Air Flow Sensing

Slinker

Kondash

Dickinson

et al. 2016

Adv Materials Technologies

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While numerous flow sensor architectures mimic the natural cilia of crickets, locusts, bats, and fish, the prediction of sensor output for given flow conditions based on the sensor properties has not been achieved. Challenges include difficulty in determining the electromechanical properties of the sensors, limited working knowledge of the boundary layer, low sensitivity to small hair deflections, and lack of models for large deflections. Within this work, hair sensors are fabricated using piezoresistive arrays of carbon nanotubes (CNTs) without traditional microelectromechanical processing. While correlating the CNT array electromechanical properties to synthesis conditions remains a challenge, a consistent, proportional, and predictable response to steady, boundary-determined air flow is obtained using theory and measurement for various lengths of hairs. The moment sensitivity is shown to scale inversely with the CNT length and stiffness to a typical maximum of 1.3 ± 0.4% resistance change nN −1 m −1 . The normalized CNT piezoresistivity is constant (1.1 ± 0.2) for a majority of the more than two dozen sensors examined despite the orders-of-magnitude variability in both sensitivity and CNT compressive modulus. The sensor sensitivity and noise both distinctly change as the flow transitions from steady and laminar to turbulent, suggesting the sensor may be capable of detecting flow transitions.

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Drag force micro solid state silicon plate wind velocity sensor

Cited by 24 publications

References 8 publications

Micromachined Flow Sensors in Biomedical Applications

Micromachined Flow Sensors in Biomedical Applications

Design of a Wind Sensor Based on Cylinder Diametrical Pressure Differences for Boundary Layer Meteorological Observation

CNT‐Based Artificial Hair Sensors for Predictable Boundary Layer Air Flow Sensing

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