Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades

In areas where there is high humidity and freezing rain, there is a tendency of blade icing on wind turbines. It results in energy dissipation and mechanical abrasion and also creates a safety concern due to the risk of having falling ice. Real-time online detection of icing is crucial in the enhanc...

Full description

Saved in:
Bibliographic Details
Main Authors: Min Meng, Xiangyuan Zheng, Zhonghui Wu, Hanyu Hong, Lei Zhang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/3/613
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850199955717750784
author Min Meng
Xiangyuan Zheng
Zhonghui Wu
Hanyu Hong
Lei Zhang
author_facet Min Meng
Xiangyuan Zheng
Zhonghui Wu
Hanyu Hong
Lei Zhang
author_sort Min Meng
collection DOAJ
description In areas where there is high humidity and freezing rain, there is a tendency of blade icing on wind turbines. It results in energy dissipation and mechanical abrasion and also creates a safety concern due to the risk of having falling ice. Real-time online detection of icing is crucial in the enhancement of power generation efficiency and in the safety of wind turbines. The current methods of icing detection that use ultrasound, optics, vibration, and electromagnetics are already studied. But these methods have their drawbacks, including small detection ranges, low accuracy, large size, and challenges in distributed installation, making it hard to capture the real-time dynamics of the icing and de-icing processes on the wind turbine blades. To this end, this paper presents a new blade surface icing detection technique using microstrip lines. This approach uses the impact of icing state and thickness on the effective dielectric constant of the microstrip line surface. This paper presents the analysis of time-domain features of microwave signals, which facilitates the identification of both the icing state and the corresponding thickness. Simulation and experimental measurement of linear and S-shaped microstrip sensors are used in this research in order to compare the response of the sensors to the variation in the thickness of the icing layer. It is seen that for icing thickness ranging from 0 mm to 6 mm, the imaginary part of the S21 parameter of the S-shaped microstrip line has a more significant change than that of the linear microstrip line. The above experiments also confirm that the phase shift value of the S-shaped microstrip line is always higher than that of the linear microstrip line for the same variation of icing thickness, which proves that the S-shaped microstrip line is more sensitive than the linear one. Also, it was possible to establish the relationship between the phase shift values and icing thickness, which makes it possible to predict the icing thickness. The developed microwave microstrip detection technology is intended for usage in the wind turbine blade icing and similar surface detection areas. This method saves the size and thickness of icing sensors, which makes it possible to conduct measurements at various points. This is especially beneficial for usage in wind turbine blades and can be further applied in aerospace, automotive, and construction, especially the bridges.
format Article
id doaj-art-2432e548bc5146d7aef48395b824cde0
institution OA Journals
issn 1424-8220
language English
publishDate 2025-01-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-2432e548bc5146d7aef48395b824cde02025-08-20T02:12:29ZengMDPI AGSensors1424-82202025-01-0125361310.3390/s25030613Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine BladesMin Meng0Xiangyuan Zheng1Zhonghui Wu2Hanyu Hong3Lei Zhang4Institute for Ocean Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, ChinaInstitute for Ocean Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, ChinaSchool of Electrical and Information, Engineering Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Electrical and Information, Engineering Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Electrical and Information, Engineering Wuhan Institute of Technology, Wuhan 430205, ChinaIn areas where there is high humidity and freezing rain, there is a tendency of blade icing on wind turbines. It results in energy dissipation and mechanical abrasion and also creates a safety concern due to the risk of having falling ice. Real-time online detection of icing is crucial in the enhancement of power generation efficiency and in the safety of wind turbines. The current methods of icing detection that use ultrasound, optics, vibration, and electromagnetics are already studied. But these methods have their drawbacks, including small detection ranges, low accuracy, large size, and challenges in distributed installation, making it hard to capture the real-time dynamics of the icing and de-icing processes on the wind turbine blades. To this end, this paper presents a new blade surface icing detection technique using microstrip lines. This approach uses the impact of icing state and thickness on the effective dielectric constant of the microstrip line surface. This paper presents the analysis of time-domain features of microwave signals, which facilitates the identification of both the icing state and the corresponding thickness. Simulation and experimental measurement of linear and S-shaped microstrip sensors are used in this research in order to compare the response of the sensors to the variation in the thickness of the icing layer. It is seen that for icing thickness ranging from 0 mm to 6 mm, the imaginary part of the S21 parameter of the S-shaped microstrip line has a more significant change than that of the linear microstrip line. The above experiments also confirm that the phase shift value of the S-shaped microstrip line is always higher than that of the linear microstrip line for the same variation of icing thickness, which proves that the S-shaped microstrip line is more sensitive than the linear one. Also, it was possible to establish the relationship between the phase shift values and icing thickness, which makes it possible to predict the icing thickness. The developed microwave microstrip detection technology is intended for usage in the wind turbine blade icing and similar surface detection areas. This method saves the size and thickness of icing sensors, which makes it possible to conduct measurements at various points. This is especially beneficial for usage in wind turbine blades and can be further applied in aerospace, automotive, and construction, especially the bridges.https://www.mdpi.com/1424-8220/25/3/613microwavemicrostrip lineicing thicknesswind turbine
spellingShingle Min Meng
Xiangyuan Zheng
Zhonghui Wu
Hanyu Hong
Lei Zhang
Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
Sensors
microwave
microstrip line
icing thickness
wind turbine
title Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
title_full Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
title_fullStr Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
title_full_unstemmed Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
title_short Research and Application of Microwave Microstrip Transmission Line-Based Icing Detection Methods for Wind Turbine Blades
title_sort research and application of microwave microstrip transmission line based icing detection methods for wind turbine blades
topic microwave
microstrip line
icing thickness
wind turbine
url https://www.mdpi.com/1424-8220/25/3/613
work_keys_str_mv AT minmeng researchandapplicationofmicrowavemicrostriptransmissionlinebasedicingdetectionmethodsforwindturbineblades
AT xiangyuanzheng researchandapplicationofmicrowavemicrostriptransmissionlinebasedicingdetectionmethodsforwindturbineblades
AT zhonghuiwu researchandapplicationofmicrowavemicrostriptransmissionlinebasedicingdetectionmethodsforwindturbineblades
AT hanyuhong researchandapplicationofmicrowavemicrostriptransmissionlinebasedicingdetectionmethodsforwindturbineblades
AT leizhang researchandapplicationofmicrowavemicrostriptransmissionlinebasedicingdetectionmethodsforwindturbineblades