Embedded Sensitivity Functions for Improving the Effectiveness of Vibro-Acoustic Modulation and Damage Detection on Wind Turbine Blades

2014 ◽  
Author(s):  
Janette J. Meyer ◽  
Douglas E. Adams ◽  
Janene Silvers
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Wind Turbine ◽  
Frequency Response ◽  
Health Monitoring ◽  
Sensitivity Function ◽  
Structural Health ◽  
Sensitivity Functions ◽  
Acoustic Modulation ◽  
Sensor Locations

In structural health monitoring, it is desirable to select sensor locations in order to minimize the number of sensors required for and the cost associated with an on-board monitoring system. When using a frequency response-based structural health monitoring technique, data measured at sensor locations which exhibit the greatest change in frequency response function (FRF) due to damage are expected to maximize the effectiveness of the chosen technique. In this work, an embedded sensitivity function is presented which identifies the sensor locations at which the maximum differences in FRFs due to damage at a known location will be observed. The formulation of the embedded sensitivity function is based on FRFs measured on a healthy structure in the frequency range in which the damage detection technique will be applied. The effectiveness of the embedded sensitivity functions in predicting the most effective sensor locations is demonstrated by applying a vibro-acoustic modulation (VAM) damage detection method to a residential-scale wind turbine blade. First, data from the healthy blade is acquired and the embedded sensitivity functions are calculated. Then, the blade is damaged and the VAM method is applied using several sensor locations. The data acquired using sensor locations identified by the embedded sensitivity functions as being most effective are shown to most clearly identify the damage on the blade.

Radar-based structural health monitoring of wind turbine blades: The case of damage detection

2017 ◽  
Vol 17 (4) ◽  
pp. 815-822 ◽  
Author(s):  
Jochen Moll ◽  
Philip Arnold ◽  
Moritz Mälzer ◽  
Viktor Krozer ◽  
Dimitry Pozdniakov ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Wind Turbine ◽  
Health Monitoring ◽  
Turbine Blades ◽  
Heterogeneous Material ◽  
Material System ◽  
Wind Turbine Blades ◽  
Millimetre Wave ◽  
Structural Health

Structural health monitoring of wind turbine blades is challenging due to its large dimensions, as well as the complex and heterogeneous material system. In this article, we will introduce a radically new structural health monitoring approach that uses permanently installed radar sensors in the microwave and millimetre-wave frequency range for remote and in-service inspection of wind turbine blades. The radar sensor is placed at the tower of the wind turbine and irradiates the electromagnetic waves in the direction of the rotating blades. Experimental results for damage detection of complex structures will be presented in a laboratory environment for the case of a 10-mm-thick glass-fibre-reinforced plastic plate, as well as a real blade-tip sample.

Structural Health Monitoring of Composite Material Typical of Wind Turbine Blades by Novelty Detection on Vibration Response

2012 ◽  
Vol 518 ◽  
pp. 319-327
Author(s):  
Nikolaos Dervilis ◽  
R. Barthorpe ◽  
Wieslaw Jerzy Staszewski ◽  
Keith Worden
Keyword(s):  
Composite Material ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Health Monitoring ◽  
Novelty Detection ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Structural Health

New generations of offshore wind turbines are playing a leading role in the energy arena. One of the target challenges is to achieve reliable Structural Health Monitoring (SHM) of the blades. Fault detection at the early stage is a vital issue for the structural and economical success of the large wind turbines. In this study, experimental measurements of Frequency Response Functions (FRFs) are used and identification of mode shapes and natural frequencies is accomplished via an LMS system. Novelty detection is introduced as a robust statistical method for low-level damage detection which has not yet been widely used in SHM of composite blades. Fault diagnosis of wind turbine blades is a challenge due to their composite material, dimensions, aerodynamic nature and environmental conditions. The novelty approach combined with vibration measurements introduces an online condition monitoring method. This paper presents the outcomes of a scheme for damage detection of carbon fibre material in which novelty detection approaches are applied to FRF measurements. The approach is demonstrated for a stiffened composite plate subject to incremental levels of impact damage.

scholarly journals Structural Health Monitoring in Composite Structures: A Comprehensive Review

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 153
Author(s):  
Sahar Hassani ◽  
Mohsen Mousavi ◽  
Amir H. Gandomi
Keyword(s):  
Composite Materials ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Composite Structures ◽  
Impact Damage ◽  
Detection Methods ◽  
Comprehensive Review ◽  
Structural Health ◽  
Acoustic Modulation

This study presents a comprehensive review of the history of research and development of different damage-detection methods in the realm of composite structures. Different fields of engineering, such as mechanical, architectural, civil, and aerospace engineering, benefit excellent mechanical properties of composite materials. Due to their heterogeneous nature, composite materials can suffer from several complex nonlinear damage modes, including impact damage, delamination, matrix crack, fiber breakage, and voids. Therefore, early damage detection of composite structures can help avoid catastrophic events and tragic consequences, such as airplane crashes, further demanding the development of robust structural health monitoring (SHM) algorithms. This study first reviews different non-destructive damage testing techniques, then investigates vibration-based damage-detection methods along with their respective pros and cons, and concludes with a thorough discussion of a nonlinear hybrid method termed the Vibro-Acoustic Modulation technique. Advanced signal processing, machine learning, and deep learning have been widely employed for solving damage-detection problems of composite structures. Therefore, all of these methods have been fully studied. Considering the wide use of a new generation of smart composites in different applications, a section is dedicated to these materials. At the end of this paper, some final remarks and suggestions for future work are presented.

scholarly journals The influence of frequency content on the performance of artificial neural network–based damage detection systems tested on numerical and experimental bridge data

2020 ◽  
pp. 147592172092432
Author(s):  
Ana C Neves ◽  
Ignacio González ◽  
Raid Karoumi ◽  
John Leander
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Frequency Response ◽  
Health Monitoring ◽  
High Frequency ◽  
Novelty Detection ◽  
Future Research ◽  
Engineering Structures ◽  
Structural Health ◽  
Artificial Neural

The method herein proposed provides a novel perspective about data processing within structural health monitoring, which is essential for automated real-time monitoring and assessment of civil engineering structures. The low- and high-frequency contents of the forced vibration response of a structure are used to train and test artificial neural networks for the purpose of damage detection. In the context of several damage scenarios, the different versions of the networks are compared with each other with the aim of verifying which are the most efficient regarding novelty detection (one-class classification). The data related with the high-frequency response showed to contain more useful information for the proposed damage detection algorithm, when compared with the low-frequency response data (typically modal). In view of that, high frequencies should be given more attention in future research about their application in connection with structural health monitoring systems.

scholarly journals Magnetostrictive Sensors for Composite Damage Detection and Wireless Structural Health Monitoring

2019 ◽  
Vol 55 (7) ◽  
pp. 1-6
Author(s):  
Zhaoyuan Leong ◽  
William Holmes ◽  
James Clarke ◽  
Akshay Padki ◽  
Simon Hayes ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Health ◽  
Composite Damage

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Structural Health Monitoring of Research-Scale Wind Turbine Blades

2013 ◽  
Vol 558 ◽  
pp. 364-373 ◽  
Author(s):  
Stuart G. Taylor ◽  
Kevin M. Farinholt ◽  
Gyu Hae Park ◽  
Charles R. Farrar ◽  
Michael D. Todd ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Embedded Systems ◽  
Wind Turbine ◽  
Health Monitoring ◽  
Turbine Blades ◽  
Field Tests ◽  
Ultrasonic Waves ◽  
Wind Turbine Blades ◽  
Structural Health ◽  
Sensing System

This paper presents ongoing work by the authors to implement real-time structural health monitoring (SHM) systems for operational research-scale wind turbine blades. The authors have been investigating and assessing the performance of several techniques for SHM of wind turbine blades using piezoelectric active sensors. Following a series of laboratory vibration and fatigue tests, these techniques are being implemented using embedded systems developed by the authors. These embedded systems are being deployed on operating wind turbine platforms, including a 20-meter rotor diameter turbine, located in Bushland, TX, and a 4.5-meter rotor diameter turbine, located in Los Alamos, NM. The SHM approach includes measurements over multiple frequency ranges, in which diffuse ultrasonic waves are excited and recorded using an active sensing system, and the blades global ambient vibration response is recorded using a passive sensing system. These dual measurement types provide a means of correlating the effect of potential damage to changes in the global structural behavior of the blade. In order to provide a backdrop for the sensors and systems currently installed in the field, recent damage detection results for laboratory-based wind turbine blade experiments are reviewed. Our recent and ongoing experimental platforms for field tests are described, and experimental results from these field tests are presented. LA-UR-12-24691.

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