Dielectric based sensing of atmospheric ice

Mughal, Umair Najeeb; Virk, Muhammad Shakeel; Mustafa, Mohamad Y.

doi:10.1063/1.4854758

Cited by 10 publications

(6 citation statements)

References 2 publications

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“…These types of instruments are more expensive and not entirely reliable. Direct ice detection methods, on the other hand, measure the change in a property such as mass, conductivity, inductance, and dielectric constant to measure ice formation on the surface [84]. A direct ice detection method is based on ultrasonic damping [85].…”

Section: Traditional Ice Sensors Used In Ice Protection Systemsmentioning

confidence: 99%

Recent Developments on Dielectric Barrier Discharge (DBD) Plasma Actuators for Icing Mitigation

et al. 2022

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Ice accretion is a common issue on aircraft flying in cold climate conditions. The ice accumulation on aircraft surfaces disturbs the adjacent airflow field, increases the drag, and significantly reduces the aircraft’s aerodynamic performance. It also increases the weight of the aircraft and causes the failure of critical components in some situations, leading to premature aerodynamic stall and loss of control and lift. With this in mind, several authors have begun to study the thermal effects of plasma actuators for icing control and mitigation, considering both aeronautical and wind energy applications. Although this is a recent topic, several studies have already been performed, and it is clear this topic has attracted the attention of several research groups. Considering the importance and potential of using dielectric barrier discharge (DBD) plasma actuators for ice mitigation, we aim to present in this paper the first review on this topic, summarizing all the information reported in the literature about three major subtopics: thermal effects induced by DBD plasma actuators, plasma actuators’ ability in deicing and ice formation prevention, and ice detection capability of DBD plasma actuators. An overview of the characteristics of these devices is performed and conclusions are drawn regarding recent developments in the application of plasma actuators for icing mitigation purposes.

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Section: Traditional Ice Sensors Used In Ice Protection Systemsmentioning

confidence: 99%

Recent Developments on Dielectric Barrier Discharge (DBD) Plasma Actuators for Icing Mitigation

et al. 2022

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“…Atmospheric icing is a complex mixture of ice crystal and air, and the material proportion can be reflected in its relative dielectric constant [ 4 , 12 , 13 ]. According to the Wiener relation [ 20 ], the relative dielectric constant of a mixed material can be calculated as follows:

where

denotes the relative dielectric constant of pure ice (

and

denote the volume proportion of pure ice and air, which can be reflected in the parameters of icing density,

.…”

Section: The Background Of the Capacitive Sensing Techniquementioning

confidence: 99%

“…Bhattu et al studied the transient response of the dielectric constant of atmospheric icing, under different operating atmospheric conditions, and found that the icing-detection sensor is feasible, based on the capacitance effect [ 13 , 19 ]. Mughal et al studied the variations of dielectric property in snow and pure ice, and presented the characteristics of the electrical properties that are affected by density, ambient temperature, conductivity, test frequency, and relaxation time [ 20 , 21 , 22 ]. These research studies have provided some important theoretical reference for the design of capacitive icing sensors.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Icing Dielectric Constant for the Capacitive Icing Sensor

Zhu

Huang

Tian

et al. 2018

Sensors

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The capacitive method is considered to be a suitable icing-detection technology, but the lack of fundamental parameters restricts the development of icing-detection sensors. In this paper, an artificial icing laboratory, a capacitive sensor, and some simulation conductors have been designed for obtaining the artificial icing samples. Subsequently, the same characteristic values of artificial icing have been measured by an LCR device, under a selected frequency. This research found that the value of the icing dielectric constant closely correlated with its density, internal sublayer, and the test temperature. Finally, a fitting formula has been presented for calculating the relative dielectric constant, which may provide some important reference value for the design of icing-detection sensors.

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“…Meteorological observing systems collect the meteorological data, then predict the blade icing condition through analyzing the effect of atmosphere changes on WT . For external icing condition monitoring systems, specialized sensors are installed on the WT besides the standard configuration to measure the physical property changes in blades due to ice accretion, such as mass, conductivities, and dielectric constants . However, this method not only increases the WT mechanical complexity, but also induces extra maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Intelligent wind turbine blade icing detection using supervisory control and data acquisition data and ensemble deep learning

Liu

Cheng

Kong

et al. 2019

Energy Science & Engineering

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Ice accretion on wind turbine blades is one of the major faults affecting the operational safety and power generation efficiency of wind turbines. Current icing detection methods are based on either meteorological observing system or extra condition monitoring system. Compared with current methods, icing detection using the intrinsic supervisory control and data acquisition (SCADA) data of wind turbines has plenty of potential advantages, such as low cost, high stability, and early icing detection ability. However, there have not been deep investigations in this field at present. In this paper, a novel intelligent wind turbine blade icing detection method based on the wind turbine SCADA data is proposed. This method consists of three processes: SCADA data preprocessing, automatic feature extraction, and ensemble icing detection model construction. Specifically, deep autoencoders network is employed to learn multilevel fault features from the complex SCADA data adaptively. And the ensemble technique is utilized to make full use of all the extracted features from different hidden layers of the deep autoencoders network to build the ensemble icing detection model. The effectiveness of the proposed method is validated using the data collected from actual wind farms. The experimental results reveal that the proposed method is able to not only adaptively extract valuable fault features from the complex SCADA data, but also obtains higher detection accuracy and generalization capability compared with conventional machine learning models and individual deep learning model.

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Dielectric based sensing of atmospheric ice

Cited by 10 publications

References 2 publications

Recent Developments on Dielectric Barrier Discharge (DBD) Plasma Actuators for Icing Mitigation

Recent Developments on Dielectric Barrier Discharge (DBD) Plasma Actuators for Icing Mitigation

Experimental Study on the Icing Dielectric Constant for the Capacitive Icing Sensor

Intelligent wind turbine blade icing detection using supervisory control and data acquisition data and ensemble deep learning

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