Non-Destructive Testing and Condition Monitoring Techniques for Renewable Energy Industrial Assets

207 Pages·2019·22.931 MB·English

by  Mayorkinos Papaelias, Alexander Karyotakis

NON-DESTRUCTIVE
TESTING AND
CONDITION
MONITORING
TECHNIQUES
FOR RENEWABLE
ENERGY INDUSTRIAL
ASSETS
NON-DESTRUCTIVE
TESTING AND
CONDITION
MONITORING
TECHNIQUES
FOR RENEWABLE
ENERGY INDUSTRIAL
ASSETS
Edited by
MAYORKINOS PAPAELIAS
FAUSTO PEDRO GARCÍA MÁRQUEZ
ALEXANDER KARYOTAKIS
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Contributors
Nikolaos Angelopoulos
School of Metallurgy and Materials, The University of Birmingham, Birmingham,
United Kingdom
Fausto Pedro García Márquez
Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
Carlos Quiterio Gómez Muñoz
School of Architecture, Engineering and Design, Universidad Europea, Madrid, Spain
Farzad Hayati
School of Engineering, The University of Birmingham, Birmingham, United Kingdom
Álvaro Huerta Herraiz
Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
Valter Luiz Jantara, Jr.
School of Metallurgy and Materials, The University of Birmingham, Birmingham,
United Kingdom
Alfredo Arcos Jimenez
Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
Alexander Karyotakis
TERNA ENERGY, Athens, Greece
Jesús José Llandres
NATURGY Group; School of Architecture, Engineering and Design, Universidad
Europea, Madrid, Spain
Alberto Pliego Marugán
Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
Jose Carlos Montoya
School of Architecture, Engineering and Design, Universidad Europea, Madrid, Spain
Mayorkinos Papaelias
School of Metallurgy and Materials, The University of Birmingham, Birmingham,
United Kingdom; Ingenium Research Group, University of Castilla-La Mancha, Ciudad
Real, Spain
Jesús María Pinar Pérez
CUNEF-Ingenium, University College of Financial Studies, Madrid, Spain
Isaac Segovia Ramirez
Ingenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
Sanaz Roshanmanesh
School of Metallurgy and Materials, The University of Birmingham, Birmingham,
United Kingdom
ix
Introduction to non-destructive testing
and condition monitoring techniques for
renewable energy industrial assets
Fausto Pedro García Márqueza, Mayorkinos Papaeliasb,
Alexander Karyotakisc
aIngenium Research Group, University of Castilla-La Mancha, Ciudad Real, Spain
bSchool of Metallurgy and Materials, The University of Birmingham, Birmingham, United Kingdom
cTERNA ENERGY, Athens, Greece
The economic significance of renewable energy sources has increased
profoundly over the last two decades. Renewable energy assets, in the form
of wind turbines, photovoltaic installations, tidal turbines, wave energy de-
vices, concentrated solar power plants, biofuel and biomass installations have
become important part of the global economy with their net worth value
exceeding several hundreds of billions of Euros. Investments in renewable
energy are expected to continue to grow until at least 2030, before begin-
ning to stabilise. Renewable energy assets are complex systems with several
critical components. Therefore, it is of paramount importance that they are
inspected and maintained adequately in order to ensure their high availabil-
ity and uninterrupted operation. Unexpected failures and faults can result
in the underperformance of a particular renewable energy project which
may compromise its financial success and endanger future investment. Non-
destructive testing (NDT) and condition monitoring should be considered
as an integral part of the overall operation of any renewable energy project
ensuring its reliable and safe operation and enabling maintenance actions
to be carried out effectively and efficiently resulting in significant financial
savings for both manufacturers and operators. This book is the first of its
kind and will provide a useful insight to industrial engineers and scientists,
academics and students in the possibilities that NDT and condition moni-
toring technologies can offer. It also provides a useful reference to research-
ers working in the field.
The book has been created for a target audience of engineers and sci-
entists working in renewable energy production, renewable energy asset
manufacturing, maintenance and inspection, students and academics in en-
gineering and renewable energy, NDT inspection engineers and researchers
across the disciplines of renewable energy, NDT and condition monitoring
xi
xii Introduction to non-destructive testing and condition monitoring techniques
technologies, offshore engineers and scientists. But it is also open to other
readers.
The content of the book is particularly beneficial to its readers who are
expected to have a broad and interdisciplinary background, ranging from
physicists to mechanical, electrical and civil engineers, metallurgists, materials
scientists, computer scientists and IT engineers, mathematicians, and chemists.
At the moment, the information available on NDT and condition mon-
itoring research and applications in renewable energy is very fragmented.
This book integrates the state-of-the-art information and discusses the fu-
ture developments and their significance to the improvement of renewable
energy as an industry. The contents of the book are also useful to under-
graduate students as well as researchers providing relevant illustrations and
other visual paradigms wherever appropriate to enable better absorption of
the information contained by the reader.
The literature available on NDT and Condition Monitoring for
Renewable Energy sources is very fragmented. Most of the relevant litera-
ture sources on the subject can be found in the form of conference and jour-
nal papers. This book synthetizes in a single source of literature solely NDT
and Condition Monitoring applications and techniques in renewable energy.
The number of wind turbines and their complexity have both increased
in recent years. Maintaining a high level of reliability for wind turbines as sys-
tems has become gradually significantly more challenging. At the same time,
maintenance costs have risen due to the size and complexity of wind turbines
even at subcomponent level. The most important faults in wind turbines are
those that result in the highest downtime and loss of p roductivity. There are
some studies that have considered specific faults affecting wind turbine op-
eration. However, they depend on the wind turbine model considered, the
geographic and environmental changes, etc. Chapter 1 presents a research
overview of the main faults commonly affecting industrial wind turbines
based on the state-of-the-art together with a systematic analysis. A fault tree
has been developed to synthesize all faults of interest and evaluate qualitatively
the condition of the wind turbine system. The fault tree has been studied
quantitatively via binary decision diagrams. The approach presented in this
chapter is a useful study to be implemented in any condition monitoring
system in order to support the maintenance management of wind turbines.
Chapter 2 describes the main wind turbine inspection and condition
monitoring issues. A general introduction about the importance of the
wind turbine industry is done from different market point of view. It is
remarked that there is a need for the Operational and Maintenance in this
Introduction to non-destructive testing and condition monitoring techniques xiii
industry and the Levelised Cost of Electricity. It is employed as a remote
Condition Monitoring Systems to continuously evaluate the condition of
critical wind turbine components. The main objective is to avoid the cat-
astrophic failures. Certain component faults can be particularly dangerous
leading even to a complete loss of the wind turbine. A detailed analysis of
the main catastrophic failures is introduced in this chapter. In order to avoid
them, the main inspections of wind turbine components are described.
Wind energy is also one of the most important renewable energy
sources exploited at a global scale with approximately 0.5T W of installed
capacity as of 2019. There is a need to optimise the operational and main-
tenance costs of wind turbines in order to increase the competitiveness of
this power generation industry. An efficient way of reducing costs is through
an evolution from corrective to predictive maintenance procedures, for
example based on condition monitoring of critical turbine components.
Condition monitoring systems allow early detection of health degradation
of the main components, for example gearbox, brake system, blade, tower,
facilitating a proactive response, minimising downtime, and maximising the
overall annual capacity production of wind farms. A large number of recent
research studies have focused on the field of wind turbine remote condi-
tion monitoring due to the importance of operational reliability. Chapter 3
summarises the state-of-the-art in wind turbine maintenance management,
describing different maintenance models, condition monitoring techniques,
and approaches. A qualitative evaluation, using fault tree analysis, has also
been carried out to identify future research opportunities for fault detection
and diagnostics.
The weather conditions determine the wind farm energy productivity
with time. Ice formation on blades is the environmental phenomenon that
generates more downtime in the wind energy industry. Wind turbine op-
eration must stop production when ice is detected on the blades for safety
reasons. People, animals, devices, etc., close to the wind farm can be put at
risk due to the possibility of ice detaching from the blades as they rotate at
high speed. Moreover, abnormal vibration of the wind turbine arising from
the ice accumulation can cause failures. The resulting downtime can lead
to significant financial costs due to the lost production. NDT techniques
are therefore required in order to detect ice accumulation on the blades.
Chapter 4 presents the main NDT approaches for blade icing monitoring.
The main method for eliminating the ice is also discussed.
Approximately 75% of all wind turbines are based on geared designs.
Wind turbine gear designs often follow the ISO 6336-5 standard. Gears
xiv Introduction to non-destructive testing and condition monitoring techniques
are typically made from high Cr steel grades such as 4320, 4820, 9310, and
18CrNiMo7-6. These steel grades have low carbon and high chromium and
molybdenum content, to increase the maximum toughness of the material.
Wind turbine gearbox designs have been improving over the years resulting
in the continuous revision of the IEC-61400 international standard, which
outlines the minimum requirements for specification, design, and verifica-
tion of gearboxes in wind turbines. Despite these continuous improvements,
several technical challenges remain that have yet to be overcome, especially
in the case of offshore wind farms. Chapter 5 covers the most common
wind turbine gearbox failures, while also providing examples on how to de-
tect and prevent unexpected failures by using appropriate condition mon-
itoring systems and surface engineering treatment techniques, respectively.
Turbulence influences the amount of wind energy harvested using wind
turbine blades reducing the efficiency of the overall electric power pro-
duction of wind turbines. This results to a lower level of competitiveness
of this industry in comparison with other energy sources such as fossil
fuel-based power generation. Turbulence effects can be further enhanced
by the characteristics of the wind turbine blade surface itself, for example
ice accumulation, impacting insects, dirt, mud. NDT techniques can be
applied in order to monitor the blade surface characteristics or condition.
However, NDT is yet to be widely employed for this particular purpose in
the industry yet. Chapter 6 looks into the application of ultrasonic waves for
monitoring the presence of dirt, mud, and other potential surface artefacts
potentially accumulating with time. Several scenarios have been considered
in order to validate this particular approach, considering various levels of
mud. Pattern recognition employing neural networks has been considered
for the detection and quantification of accumulation of mud on the blade
surface.
Solar plants require sophisticated condition monitoring systems and
methods to manage the new large power production due to the increasing
number of photovoltaics modules installed. Chapter 7 focuses on thermo-
graphic techniques for the evaluation of solar panels. Thermography can
be used to evaluate the condition of the photovoltaic system very fast, and
economically providing reliable inspection results. The most important
thermographic techniques for solar plants are discussed herewith together
with the governing principles. Active and passive techniques are analysed
in order to determine the method that provides the best results. The main
advantages and disadvantages of using thermographic technologies are an-
alysed. In addition, the main variables that should be considered during
Introduction to non-destructive testing and condition monitoring techniques xv
thermographic inspection are considered. Finally, certain types of failures
that can be detected using thermography are evaluated through the differ-
ent thermographic patterns in obtained thermal images.
The constant increasing of renewable energy demand is leading wind tur-
bines to become very complex and sophisticated devices. These technolog-
ical developments imply new methods and tools to ensure the reliability of
the systems. For this purpose, non-destructive testing techniques are widely
employed in the field of wind turbine maintenance. Chapter 8 presents the
implementation of a walking robot-based system that allows non-destructive
testing to be carried out in difficult access areas of wind turbines. The chap-
ter is divided as a brief literature overview that is done to identify those lim-
itations of current procedures that could be overcome by using the proposed
tool; a detailed explanation of the novel system is given, where the different
components and features of the robot are described; several applications of
the proposed systems are also shown. These applications can be classified
according to the type of sensor and the area to inspect: Acoustic emission, vi-
sual inspection, guided wave testing, noise analysis, or thermographic inspec-
tions are some of the non-destructive testing techniques that can be aided.
Moreover, external and internal surfaces of blades, tower, nacelle, and other
difficult access areas can be reached by the robot. Finally, some advantages of
this system are enhanced with respect to the conventional methodologies.
The usefulness of the proposed system is demonstrated in terms of safety and
efficiency with respect to other procedures.
The development of newer and more ecofriendly energies is now
more important in the world. Solar energy has been growing considerably
over the last years, and, for example, photovoltaic solar farms size has in-
creased, where the problems in operation and maintenance also has raised.
Automated inspection is being applied with emerging hardware and soft-
ware technologies such as computer vision, unmanned aerial vehicles, and
thermal cameras. Chapter 9 illustrates an integration of all these technolo-
gies, coming up with an effective solution for the detection of malfunction-
ing solar panels in large solar parks.
Tidal energy is still a developing renewable energy source with only a
few commercial projects having been commissioned to date. Although there
are several different device designs that have been proposed and investigated
for harvesting tidal energy, most of them have only been tested either at
model or small scale. A handful of designs have managed to gather sufficient
financial support to be tested at sea at full scale. There are currently plans
for significant utility-sized tidal energy plants in the short-to-medium term.
xvi Introduction to non-destructive testing and condition monitoring techniques
Nonetheless, these still face uncertainty regarding their eventual implemen-
tation due to financing issues that have not been entirely resolved yet. Types
of damage that can affect the drive-train of a tidal turbine include misalign-
ment, imbalance, looseness, broken gear teeth, bearing defects, lubrication
variability resulting in dry contact of the rotating surfaces, and excessive
wear. It is very important to be able to detect accidental impacts on the
rotor and damage evolution in the drive-train. Certain commercial tidal
turbines make use of vibration condition monitoring systems in the same
way as most multi-MW wind turbines. Chapter 10 presents the main tidal
power generator components: rotor blades, drive train, power convertors,
low-voltage consumable power, control and management systems, support
structure, and power transmission. The main condition monitoring system
for each component are discussed.
Acoustic emission testing is a structural health monitoring technique
with a wide range of applications. Several structural components in vari-
ous renewable energy systems, for example wind turbine blades made of
fibre reinforced plastics, towers, foundation, tidal turbine blades, wave energy
harvesting systems, pressure vessels in concentrated solar power plants and
many others, can be monitored using acoustic emission. Acoustic emission
measurements can produce datasets which contain thousands to hundreds
of thousands of logged signals. Particularly for large components, such as
a wind turbine blade, where several piezoelectric acoustic emission sen-
sors are required to monitor the load bearing parts of the structure over
a prolonged time period, the size of the dataset generated may be exceed-
ingly large. Although manual analysis of large acoustic emission datasets is
possible, it is not trivial, particularly when complex damage mechanics are
involved. Therefore, it is desirable to use methods to automatically analyse
complex acoustic emission datasets without the need for manual interven-
tion. Effective automatic analysis can also help establish appropriate filtering
methodologies which can help improve data acquisition parameters, so as to
minimise the logging of unwanted signals from noise sources such as friction
and echoes of primary damage events. The automatic processing of large
acoustic emission datasets can be based on statistical analysis using different
algorithms. Chapter 11 summarises the various algorithms that can be used
for the unsupervised clustering of complex acoustic emission datasets.
Integrating the use of plastic dielectric components in the insulation
is attempted to reduce the maintenance costs compared with the fluid in-
sulation technology cables (mainly paper-fluid oil). It could prevent not-
expected problems such as the appearance of defects in the manufacturing