Offshore support and naval vessels operate in complex and hazardous environments facing the risk of impact from falling objects, collisions and projectiles. Accurate impact localization is essential to guarantee safety of the individuals, the environment and the asset.

This thesis explores the feasibility of impact localization on steel plates and stiffened panels by utilizing the information carried by the stress waves generated during impacts. These waves propagate along the surface of the structure as Guided Ultrasonic Waves (GUW). The inherent time reversibility and spatial reciprocity properties of the wave equations allow the use of Time Reversal (TR) process of the recorded wave signals to localize impacts.

The study combines experimental testing with an analytical framework. Small scale controlled impact experiments were performed in the Structures Laboratory at TU Delft while large scale tests were conducted onboard a Shoalbuster vessel at DAMEN Shipyards in Gorinchem, allowing the assessment of the scalability and robustness of the method. Acoustic Emissions (AE) were generated through Pencil Lead Breaks (PLBs) and instrumented hammer impacts. TR was implemented virtually in the frequency domain using an analytical propagation formulation that models dispersion and wave amplitude decay due to geometric spreading. The novelty of the present research lies in extending the analytical TR framework from plates to stiffened panels by removing the effect of stiffeners in back-propagation. This is achieved by introducing a scalar Transmission Coefficient (Tc) into the analytical model.

In the small scale experiments two configurations were tested, a plate and a stiffened plate with a stiffener located at the midspan, both measuring 400 x 400 mm². The average localization error for the plate ranged from 11 to 15 mm, while stiffened panel tests showed slightly higher errors in the order of 12 to 23 mm, depending on the impact type. Larger errors were observed for the instrumented hammer impacts. In the large scale tests, a 7500 x 2000 mm² area was monitored. Localization accuracy decreased due to increased structural complexity, including variable plate thickness, multiple stiffeners, and high acoustic noise from parallel steel work activity. A mean localization error of 662 mm was achieved, demonstrating the method’s scalability and potential for real world application.

These results confirm that TR of GUW is a feasible method for impact localization across different scales. The developed methodology shows potential for extension to composite materials and towards a complete impact identification framework that includes impact severity estimation, contributing to the development of integrated Structural Health Monitoring (SHM) systems capable of detecting, localizing, and quantifying structural impacts.

The use of fiber-reinforced composite materials in marine applications is limited by uncertainty surrounding their long-term fatigue behavior and micro-damage tolerance. This thesis aims to present and validate an experimental framework to detect and classify mechanical micro-damage in unidirectional carbon-fiber composites using acoustic emission (AE) monitoring and X-ray micro-computed tomography (micro-CT). AE monitoring provides real-time insight into the evolution of internal damage by capturing elastic waves emitted during micro-structural failure events, while micro-CT offers high-resolution visualization of internal damage states before and after mechanical loading. A comprehensive analysis was conducted involving signal processing, (normalized) frequency spectrum characterization, and unsupervised machine learning to classify AE events by damage type. This classification was subsequently validated against micro-CT scans. Results challenge the common assumption that AE signals with dominant low-frequency contributions are reliably indicative of matrix cracking. The proposed AE framework, when validated with micro-CT, shows promise for enabling accurate in-situ damage monitoring of composite structures in offshore environments. This approach supports the broader adoption of composites by improving confidence and knowledge about their structural integrity over time.

Underwater detection has garnered increasing attention in recent years due to its broad and impactful applications in marine ecological research, underwater structural inspection, archaeological exploration, and deep-sea resource extraction. However, despite the proliferation of research in this domain, a comprehensive methodology that addresses both object identification and localization in underwater scenarios remains absent. Existing studies tend to treat these two tasks separately, often omitting the practical implementation details necessary for real-world deployment. This fragmented approach limits the effectiveness and adaptability of underwater detection systems, particularly in dynamic or unpredictable marine conditions.
To bridge this gap, this report presents a detailed exploration of a camera-based framework for simultaneous object identification and localization in underwater environments. The proposed system leverages a Region-based Convolutional Neural Network (RCNN) for object identification, offering a favorable trade-off between precision and computational efficiency. RCNN's architecture enables it to effectively handle the complex visual features typically present in underwater imagery. For the localization task, two complementary strategies are employed: the Metric3D depth estimation algorithm, which utilizes learned monocular cues to infer depth maps with high accuracy, and a geometry-based method rooted in camera imaging principles, which estimates object distance based on intrinsic and extrinsic camera parameters. The former localization method (Metric 3D) is more computationally expensive, but it provides more robust results and easier applications.
Experimental evaluations demonstrate that the proposed integrated approach achieves robust performance in various underwater conditions. The RCNN consistently delivers accurate object classifications, while the localization strategies offer flexibility and reliability depending on the computational and environmental constraints.
Overall, this research contributes a novel and practical solution for real-time underwater object detection by unifying identification and localization. The proposed system enables safer navigation, more precise manipulation, and greater situational awareness. By addressing the methodological gaps in existing literature and emphasizing real-world applicability, this work contributes to the research of intelligent underwater operation and automation.

High energy demand of contemporary society increasingly relies on offshore production. Offshore floating energy production infrastructure, such as floating wind turbines, photovoltaics, and production storage and offloading units, is central to sustaining the energy supply. Mooring chains, which are crucial elements of these floating units, are particularly vulnerable to degradation mechanisms, such as corrosion, fatigue, and their combination. Their frequent inspection is critical to prevent structural failure, production shutdowns, and severe environmental consequences.

A Digital Twin (DT) is a virtual representation of a physical object that uses real-time data to simulate and predict its behaviour. Digital twins have emerged as promising tools, enhancing the monitoring and management of physical assets using real-time data and predictive models. The effectiveness and reliability of a DT for quantitative integrity assessment are contingent on the quality of the input data and the models employed. When paired with predictive models, DTs offer valuable insights for managing the integrity of offshore mooring systems.

The main contribution of this work is to lay the groundwork for enrichment of DTs for mooring chains with quantitative damage assessment. Assessing the structural integrity of submerged offshore mooring chains presents significant challenges due to their difficult accessibility and the complexities involved in subsea inspections. Additionally, the presence of marine growth on the chain links often requires cleaning before detailed inspections can be conducted. The cleaning process is often undesirable from technical, economic, and environmental perspectives. Currently, no in-water inspection techniques for mooring chains have been reported that do not require the removal of marine growth beforehand. Enabling this is another contribution area of this research.

This thesis proposes a novel non-contact acoustic emission (AE) monitoring approach in underwater environments, enhancing DTs of mooring chains without suffering from the limitations of conventional inspection methods. As a passive ultrasound method, AE is an established non-destructive testing (NDT) technique to detect and monitor corrosion and fatigue. Piezoelectric sensors, typically mounted in contact with the material surface, are often employed to capture high-frequency waves generated by damage initiation and propagation. Three key areas have been explored: (i) the feasibility of detecting and monitoring corrosion-fatigue in submerged conditions, both with and without marine growth, using non-contact AE, (ii) the construction of a DT representation based on AE data to identify the location of corrosion-fatigue damage in mooring chain links, and (iii) the integration of AE data with fatigue models to enhance the DT predictive capabilities for damage prognosis.

The feasibility of monitoring corrosion-fatigue damage in submerged conditions using non-contact AE monitoring has been explored using small-scale corrosion-fatigue experiments. The results demonstrated the effectiveness of the proposed approach, with corrosion-fatigue-induced ultrasound signals being detected with a satisfactory signal-to-noise ratio within the frequency range of 50–450 kHz. Cumulative and rate values of AE parameters provided a reliable representation of damage progression, successfully identifying four distinct stages of damage evolution. AE energy, in particular, proved to be the most promising indicator, especially for highlighting crack formation and rapid growth phases. Corrosion-fatigue-induced signals exhibited significantly higher energy levels, approximately an order of magnitude greater than those induced by corrosion alone. In addition, corrosion-induced damage resulted in fewer ultrasound signals than corrosion-fatigue damage. Further experiments demonstrated that simulated crack signals could be measured on steel plates both with and without marine growth, indicating that ultrasound waves in the frequency range of interest can penetrate marine growth and be detected by non-contact AE transducers in submerged conditions. While marine growth caused a noticeable drop in signal amplitude, the findings suggest that non-contact AE monitoring remains feasible in the presence of marine growth.

Large-scale experiments have been used to construct a DT representation based on AE data to identify the location of corrosion-fatigue damage in mooring chain links. Large-scale corrosion and fatigue tests were conducted to assess the feasibility of detecting, localising, and monitoring corrosion and fatigue damage in mooring chains. The results demonstrated the effectiveness of the proposed approach in monitoring growing damage over time. AE measurements were parameterised to track acoustic activity associated with the initiation and progression of corrosion-fatigue damage. A 3D source localisation algorithm was successfully implemented to localise damage-induced ultrasound signal sources, with the localisation results being mapped onto the surfaces of the mooring chain segment. In the fatigue test, the AE-based DT identified three distinct zones of acoustic activity, which aligned well with post-failure inspection results. The remote AE technique accurately detected and localised all damage indications found during post-failure mechanical testing, showcasing its potential for real-time damage detection and localisation in mooring chain links.

Large-scale fatigue test data were subsequently used to assess the feasibility of fatigue crack growth prognosis in submerged mooring chains using remote AE monitoring. A prognosis model, based on the Paris relation and AE energy, was proposed, and its predictive capabilities were evaluated. The results demonstrated the potential of remote AE monitoring to predict fatigue crack growth in submerged mooring chains. AE energy analysis at various test stages revealed distinct phases of crack growth, including initiation, stable propagation, and acceleration toward failure. The prognosis model effectively reflected these stages, as indicated by changes in AE energy rate. A sensitivity analysis on the model parameters showed that reducing the scaling coefficient B led to overestimated crack growth and shorter predicted fatigue life, while increasing it resulted in underestimated crack growth and longer predicted fatigue life. The power-law exponent p further amplified these effects. The fatigue life predictions underscored the importance of accurately determining the initial crack size and selecting the appropriate crack growth models to improve prognosis accuracy.

This research provides a foundation for enhancing DTs of offshore mooring chains through real-time monitoring and predictive analysis. The proposed system shows potential for autonomous inspections of subsea structures, with possible benefits including reduced inspection costs, condition-based maintenance, and improved safety. Its non-intrusive nature may also lessen disturbance to marine ecosystems. Demonstration under offshore conditions will be an important next step to assess and strengthen its practical value for supporting the safety, efficiency, and sustainability of floating energy infrastructure.

Society increasingly demands that ships become more sustainable and quieter, given their significant share of global fuel consumption and green-house gas emissions. Fiber-reinforced composite marine propellers can contribute meaningfully to these goals. As a promising alternative to the conventional rigid metallic propellers, flexible composite propellers can offer improved underwater radiated noise (URN) and propulsion efficiency. Furthermore, manufacturing propellers from fibre-reinforced composite materials makes them lighter and reduces their electromagnetic signature.

Despite the significant potential of composite propellers for marine propulsion systems, uncertainties in their fatigue behaviour have so far hindered their wide-spread adoption. These uncertainties can arise from imperfections during the manufacturing process, operational conditions different than the ones considered in the design, coating deterioration leading to water ingress, impact events, and more. Such factors can have significant impact on the lifetime of the propeller, which is typically expected to endure billions of cycles. Structural health monitoring (SHM) has the potential to mitigate this issue by real-time recording and assessing the structural response and integrity of the propeller. Such an SHM system should neither affect the propeller performance nor its load-bearing capacity. In addition to providing insights into the current structural integrity of the propeller, an SHM system may also enable enhanced estimation of the remaining lifetime, thereby minimizing the risk of unexpected failures and downtime.

This thesis investigates the feasibility of developing composite marine propellers with an embedded SHM system based on piezoelectric sensors. These sensors are capable of performing strain monitoring (with application in load/response estimation) and acoustic emission monitoring (with application in damage identification). Three main topics have been studied; (i) the feasibility of measuring dynamic strains in the propeller blade using the embedded sensors, (ii) the effect of embedding piezoelectric sensors on the structural integrity, and (iii) the feasibility of measuring and assessing damage-induced acoustic emissions using the embedded sensors. An analysis framework has been proposed for the identification, classification, and localisation of acoustic emissions in thick composite structures…

This thesis investigates the feasibility and effectiveness of Acoustic Emission (AE) methods for monitoring fatigue crack growth in metallic materials, with the aim of enhancing predictive capabilities and understanding of crack propagation under cyclic loading. The research specifically examines the correlation between various AE parameters—such as amplitude, count rate, energy rate, and entropy—and fatigue crack growth rates, using a multi-parametric approach.

Experiments were conducted on multiple specimens under different loading conditions, and both time-domain and frequency-domain AE parameters were analyzed. The study found that parameters like energy rate and rise angle were particularly effective in detecting specific stages of fatigue crack growth, while count rate and amplitude provided consistent indicators of crack initiation and progression. However, the study also highlighted limitations in the use of filtering techniques, such as SNR and amplitude filters, which can inadvertently remove crucial AE signals.

The findings suggest that while AE methods have potential for accurately monitoring fatigue crack growth, their effectiveness is influenced by the choice of AE parameters and the management of noise. To improve accuracy, the study recommends further research that includes a broader range of specimens, explores additional AE parameters, integrates complementary techniques such as Digital Image Correlation (DIC), and applies advanced analytical methods like machine learning. Future research should also consider the impact of environmental factors, such as corrosion fatigue, particularly in marine environments where realistic AE data is critical.

Overall, this study contributes to the broader understanding of AE monitoring for fatigue damage, laying a foundation for future research and practical applications, while acknowledging the need for further refinement and validation of AE techniques across diverse materials and conditions.

This thesis presents the design and experimental evaluation of an in-line, active ultrasound, condition monitoring setup for the detection of contamination in offshore bearing grease. This process is divided into three distinct research steps. First of all, the influences that affect ultrasound propagation through a bearing grease sample have been investigated through various laboratory experiments. Next, a practical, real-world experiment using a linear bearing has been designed and conducted with the aim of determining the applicability of such an in-line condition monitoring setup. Lastly, the performance of the in-line active ultrasound setup has been evaluated, improvements have been proposed and an overall condition monitoring strategy has been devised.

During the laboratory experiments, various influences on ultrasound wave propagation have been investigated. First of all, design-specific parameters, such as the distance between the sensors, the test-setup material, and the scalability of the measured output voltage have been investigated. Next, the effects of temperature fluctuations, air bubble fluctuations, water contamination and iron particle contamination on the attenuation and velocity of waves for active ultrasound spectroscopy were investigated. It has been shown that air bubble concentration and temperature fluctuations influence the attenuation of the ultrasound in the grease sample. Therefore, the temperature should be kept constant throughout the other experiments. Additionally, the air bubble concentration should be managed through a constant resting time throughout the other experiments. Moreover, it has been shown that a condition monitoring setup employing active ultrasound spectroscopy is able to determine water contamination and iron particle contamination. The highest sensitivity of this contamination detection is located in the first percentage of contamination concentration, showing an amplitude drop of about 0.5dB/mm to 1dB/mm and a change in speed of sound of about 5\% to 15\%. It is however, difficult to differentiate between the different types of contamination using only the attenuation and velocity spectroscopy methods.

The practical, real-world experiment using an operational Huisman linear bearing has illustrated the applicability of using an in-line grease condition monitoring setup in such an environment, by evaluating obstacles such as spatial constraints, location constraints, flowability of the grease and surrounding noise. It has been shown that these obstacles pose minimal challenges for the successful implementation of an in-line grease monitoring setup for effective condition monitoring of offshore bearing grease.

The evaluation of the improved in-line active ultrasound condition monitoring setup has highlighted the strengths and weaknesses of implementing such a setup for offshore applications. A possible combination of the proposed grease condition monitoring method with Acoustic Emission monitoring offers

Governments are looking more and more to invest in renewable energy sources due to the energy transition that is currently taking place. One of the many renewable energy sources is wind energy which is increasingly positioned at sea. Wind turbines in deep parts of the ocean can be placed on floating structures which are often moored to the sea bottom by mooring ropes. For deep sea, the only viable option is a synthetic mooring line due to its almost neutral buoyancy.
Mooring ropes have a vital role in the offshore floating structure as it is keeping the structure in place. When a mooring line breaks, the consequences may be big, leading to serious damage or dangerous situations. Therefore, the structural integrity of mooring ropes should be evaluated regularly. For synthetic mooring ropes, the only method at this point in time is visual inspection. This can be done by divers or by Remotely Operated Vehicles (ROVs). This method is expensive, time consuming and in case it is done by divers, it is potentially dangerous. Furthermore, synthetic mooring ropes are susceptible to external damage which means inspection would have to be executed without direct contact with the mooring ropes. Therefore, it is necessary to assess the feasibility of a non-contact, non-destructive testing method in order to assess the structural integrity of a synthetic mooring line. The combination of non-destructive material property assessment and tension assessment is believed to produce a structural health monitoring instrument for synthetic mooring ropes.
In this thesis, a methodology is proposed which uses two independent non-contact, non-destructive measurements to assess the structural integrity of a high modulus polyethylene (HMPE) rope specimen. The measurements involved are ultrasonic guided wave (UGW) measurements and vibration measurements. The UGW measurements are performed to assess the stiffness of the test specimen according to the principle of attenuation of ultrasonic waves propagating through a specimen. The vibration measurements are performed to assess the natural frequencies of a manually excited test specimen. The assessed natural frequencies and the determined stiffness of the test specimen can be used to calculate the load acting on the test specimen.
The methodology is tested by conducting experiments in a laboratory environment where in-situ conditions are recreated by performing the tests underwater. It was concluded that the loads can be recalculated with varying accuracy of approximately 10% with respect to the actual values, with increasing accuracy for higher load values. It is concluded that the proposed methodology has the potential to determine load on a synthetic mooring line in a non-contact, non-destructive manner.

Highly-loaded low-speed roller bearings are commonly used in the offshore machinery, for example in turret moorings systems of Floating Production Storage and Offloading (FPSO) units and in slew bearings in heavy-lifting cranes. Safe and reliable operation and structural integrity can be ensured by monitoring the condition of the bearing. Condition monitoring based on acoustic emission (AE) has shown good potential for monitoring the health of highly-loaded low-speed bearings. With the increase in potential and proven condition monitoring methods, the need for lifetime predicting methods is increasing.
In this thesis, the feasibility of a digital twin (DT) concept is tested to make lifetime predictions of a highly-loaded low-speed roller bearing. The developed DT uses a combination of the Paris model and an AE-based model presenting the current state of the bearing. In the remaining useful life (RUL) prediction, the final crack size and total number of load cycles are determined based on an integrated form of the Paris model. Three different forms were tested for the RUL prediction.
The Paris model and the AE-based model showed good agreement in a benchmark case, based on which the two models were combined. The AE-based prediction was tested for hits and counts, with the counts yielding into better results due to a better fitting of the model constants. The linear RUL based on the number of load cycles resulted in the best prediction. The developed DT showed good potential in making lifetime predictions of highly-loaded low-speed roller bearings and enrichment of future DTs with prognostic information.

Floating Offshore Wind Turbines (FOWTs) have emerged as a promising technology for generating clean energy in deep water locations. Bluewater Energy Services proposes a Tension Leg Platform (TLP) as the floating support structure. An effective Structural Health Monitoring (SHM) system (of which there are various types) can facilitate timely interventions and optimize inspection and maintenance activities by providing continuous insights into their structural condition. Fatigue damage is especially critical for the support structures of FOWTs, as they are subject to cyclic loads that can cause structural damage.

This research proposes a fatigue monitoring system for a TLP supporting FOWTs. The methodology used is Modal Decomposition and Expansion (MDE). Due to the complexity of the studied structure in terms of structural dynamics, MDE is selected for its ability to capture dynamic behaviour. The main objective of the fatigue monitoring system is to perform the full-field strain estimation based on a limited number of sensors. This could also allow for the verification of the design considerations. With the presented response reconstruction approach, the stress in the locations prone to fatigue of the platform can be monitored and therefore, enabling estimation of the remaining lifetime of the structure and optimize maintenance planning.

Different analytical and numerical models are used in this investigation. The application of MDE in a simple structure (i.e. a cantilever beam) is first assessed to verify the performance and to gain insights of the methodology. Later, MDE is applied to a simplified TLP model to validate the response reconstruction approach and demonstrate its applicability for TLP-like structures.

Finally, a FOWT numerical model is used to design the fatigue monitoring system. The proposed system consists of two layouts of two strain gauges in the upper column of the TLP, and two layouts of two strain gauges on each pontoon. This system can provide full-field strain estimations with over 88.9% accuracy and predict fatigue damage accumulation with errors of less than 0.01%. Also, the system presented in this thesis only predicts global responses. However, the fatigue of the structure is also influenced by local structural responses due to sea pressures. Therefore, future research to include local effects in the predictions is recommended.

Fiber reinforced composites have been increasingly used in the aerospace and automotive industry, due to their potential advantages for designing flexible, strong and lightweight structures. More recently they are also being considered for the manufacturing of marine propellers. Since they have the potential to lower the weight, lower the maintenance costs, increase the efficiency at off-design conditions, improve cavitation inception speed and minimize acoustic signatures. Exploiting the full potential of composite propellers however requires that they need to be cost-effective and to do so it is required that the lifetime of the blade is sufficient. To determine the lifetime of the blade it is
crucial to determine how the composite blade will respond to a wide variety of environmental and loading conditions that it will experience over its life. Basically one needs to determine what effects fatigue will have on the material properties of the blade. The main objective of this thesis is to estimate the fatigue lifetime of composite marine propellers subjected to a pressure distribution determined by a Fluid-Structure Interaction
(FSI)model with the use of a progressive damage model integrated into a Finite
Element Model (FEM). The fluid structure interaction model to determine the pressure distribution has already been created Maljaars (2019). Currently the mostly used and most reliable approach is to use an experimental approach in order to estimate the fatigue life. However, for custom designs such as marine propellers this is a long and costly process. Modelling fatigue the fatigue performance in an earlier stage of the design cycle will result in significant cost and time savings.

The expected fatigue lifetime of the composite marine propeller is concluded to be at least 1012 cycles under the considered loading condition. If the propeller would rotate at 600 rpm for 24 hours per day this would translate to over 3000 years. The reason behind this large number is that the combination of the applied pressure load and the strength of the carbon fiber propeller is such that the stresses in each ply are very low. These low stresses create almost no damage throughout the propeller blade even for ultra high cycles.

One of the key challenges for offshore pipeline installation are free spans, which are sections not supported by the seabed. Within these sections the stress in the pipeline is increased due to local buckling which is caused by high bending moments at free span shoulders and midspan. Additionally, hydrodynamic loading due to currents and waves, and vortex induced vibrations increase fatigue damage.

There are many solutions to mitigate free spans and their negative effects, like building supports underneath the pipeline, or reducing the span length by burying a section of the pipeline in the seabed at the shoulder. From a deficiency analysis it is concluded that there is a need for a new system concept especially for steep slopes. This new free span mitigation shall be suitable to be performed by Allseas, an offshore construction company, during pipeline installation with the S-lay method, without the need for subcontractors like dredging companies.

Oil and Gas pipelines which are installed onshore do not create free spans as they follow the topography by being bent. This makes route intervention less extensive as it is done offshore.

The standard DNV-ST-F101 which contains requirements, principles and acceptance criteria for submarine pipeline systems, allows for cold field bends for submarine pipelines as long as certain requirements are met. There are many ideas published to bend the submarine pipeline such that it follows the seabed topography like it is the case for onshore pipelines. These approaches have been either patented or presented as case studies but have not been used in projects, so far.

It has been estimated in some of these previous case studies that the bending moments at the shoulders are reduced and stresses in the bend are within an acceptable range. From the presented opportunities and the described need, it is concluded that it is reasonable to develop a feasible new system concept which satisfies the operational and functional requirements defined in this thesis.

From combining different solutions of common subfunctions a number of concepts have been found which have been analysed and narrowed down to one possible most promising design. Using this new tool which is used in combination with an AUXROV it is possible to bend one 12m joint of the size of 32’’ by 18.5°. With the given parameters of this design the free span length and height are narrowed down and the pipeline follows the topography when bent. It is verified that the bending moment at the free span shoulder is indeed reduced as presented in the literature.

The concept design, presented in this thesis, is at an early development stage but can serve as basis for detailed engineering, the next step in concept development. With a tool like this a new opportunity as standard solution for free span mitigation at steep slopes is introduced.

Highly-loaded low-speed roller bearings form crucial connections in offshore structures, such as heavy-lifting vessels, single-point mooring systems, and wind turbines. In order to safeguard the integrity and reliability of these assets and their operations, a quantitative methodology for condition monitoring of the bearings can be of substantial value. To date, a number of assessment methods have been proposed to for this purpose, e.g. based on strain, vibration, lubrication, and acoustic emission (AE) monitoring. Despite their demonstrated potential for medium- and high-speed bearings (>600 rpm), no notable success has yet been reported in the assessment of low-speed bearings subjected to naturally-developing degradation. In this dissertation, a novel methodology for the analysis of damage-induced AE and inferring the bearing condition has been proposed. Acoustic emissions in this context are ultrasonic signals generated by the release of elastic energy in a material. In solid media, these signals propagate as stress waves and can be recorded by dedicated transducers.

A mathematical framework to describe the generation, propagation, transmission, and detection of transient ultrasonic waves in complex geometries has been presented. An assessment of inter-component stress-wave transmission has been performed utilising this framework. For a representative sheave bearing, results indicate that a transmission loss in the order of 15 dB is to be expected in the amplitude of the AE waves for a single rolling contact arrangement. In conjunction with a preliminary field trial regarding the ultrasonic background noise in representative operational conditions, this evaluation has shown that it is feasible to detect damage initiated AE signals from each of the rolling elements upon field implementations.

A waveform-similarity based clustering algorithm has been proposed for the
identification of damage-induced AE source mechanisms. Consistency in the source mechanism is theorised to indicate gradual progressive failure, such as crack growth. Through the descriptive framework, it has been shown that high similarity of the recorded signal must be the result of high similarity in the emitted source. Additional numerical verification of this assumptions on transfer path similarity has been performed, confirming the equivalence derived from the descriptive framework.

A low-speed run-to-failure test was performed with a purpose-built linear bearing segment, representative of the main bearing of a mooring turret, to assess the performance of the clustering algorithm. Intermediate and final visual inspections report the development of wear comprising erosion, surface roughening, pitting and surface initiated fatigue. In independent analysis of the recorded AE signals, several highly-consistent structures of clusters were identified over multiple measurement channels. The nose raceway could be identified as the source of these structures of clusters, which matched the observed evolution of localised damage during the inspections.

Based on the source-identified AE activity, a novel quantitative indicator has been proposed to infer bearing condition. The bearing condition index (BCI) adopts a value of 1 when the bearing is in good condition. The BCI drops in value as the bearing degrades, as represented by a more significant detection of clusters of similar AE signals within the normalised period of a load cycle over a multitude of measurement frequencies.

Run-to-failure experiments have been conducted to assess the proposed BCI. Intermediate and final inspections report the progressive erosion and surface roughening. Additional lubrication samples collected during these inspections contained high levels of particle contamination. A direct correlation between the AE hit-rate and the particle contamination of the lubricant was observed. Utilising progressive scaling based on cluster size, the excessive influence of lubrication contamination-induced AE signals on the BCI could be reduced, while still providing a timely warning.

In review, it is concluded that the proposed methodology can effectively describe the complex generation and propagation of AE due to damage evolution in highlyloaded low-speed roller bearings. The developed clustering method has shown to effectively identify patterns and trends in the AE signals at different stages of degradation, and provide the basis for filtering out noise-related signals. The formulated BCI can subsequently provide an intuitive indication of the condition of a low-speed roller bearing in an in-situ non-intrusive manner. As such, the methodology is believed to offer promising potential to contribute to the safe and continued operation of the offshore energy infrastructure.

Floating offshore production units are typically anchored to the seabed with mooring chains. Structural degradation of mooring chain steel can lead to premature failure with large environmental and financial consequences. In the oceanic environment, corrosion and fatigue are the dominant failure modes for mooring chains. These damage mechanisms are hard to predict and even harder to identify at early stages of damage evolution. Continuous research to develop improved monitoring techniques is performed to increase the safety and reliability of these structures. However, inspection techniques that can accurately and quantitatively diagnose these damage mechanisms in the submerged steel parts are yet insufficient.

Acoustic emission (AE) monitoring is a non-destructive evaluation technique that can identify structural degradation in solid materials. The technique consists of recording and processing the ultrasonic waves generated by irreversible changes in the material matrix due to damage growth. This research is focused on the global parametric analysis of the primary features of AE signals recorded during corrosion-fatigue experiments performed with submerged steel and non-contact sensors. Three experiments have been analysed to assess which of the AE primary features can most accurately correlate to the fatigue damage evolution.

Signal characterization based on their energy and duration was performed to distinguish three levels of severity. Based on a global parametric analysis the hit-rate and energy-rate have the highest potential and show good correlation to the corrosion-fatigue damage evolution. However, the global features seem to differ notably between different samples and several moments with absence of recorded activity precede final failure. Performing assessment only based on the global features is not considered sufficient. Thus, local analysis methods for AE signals is suggested to extract further information on the source of the emitting damage mechanisms.

Fiber Reinforced Composite (FRC) materials are gaining great popularity in marine structures because of their excellent strength-to-weight ratio, low density, and provided freedom in the design process. However, the use of FRC materials comes along with relatively large uncertainties in material properties and structural integrity after manufacturing and during its use. In this research a new in-situ non-destructive stiffness assessment methodology is proposed. This methodology is based on a coupling principle between the laminate structural stiffness properties and the ultrasonic guided wave characteristics of FRC materials. In the methodology, a range of possible stiffness properties is defined based on the structural information available for a structure of interest. The average relation between this stiffness range of interest and corresponding wave characteristics is described using a set of coupling coefficients which are determined using numerical simulations. For this, a batch of reference laminates is constructed that covers the entire stiffness range of interest. Input for the system are the group velocities of the zeroth-order symmetric and antisymmetric guided wave modes, measured on the structure of interest. The potential of the proposed methodology is evaluated using a numerical feasibility study based on numerical simulations. Good results were obtained for different test scenarios, varying in the amount of structural information available on the structure of interest. Thereafter, the in-situ application of the methodology has been examined in an experimental setup. Good measurement and analysis times were achieved by using a compact measuring device that is capable of recording the wave signal in five directions simultaneously. A reliable accuracy assessment of the in-situ application of the methodology was, however, difficult to obtain due to the lack of reliable reference studies. Therefore, in future research reliable reference information should be gathered. Additionally, a next step for future research should focus on decreasing the amount of information available on the structure of interest.

Fiber-reinforced composite (FRC) marine propellers potentially outperform metallic propellers in terms of efficiency and underwater radiated noise (URN) by hydro-elastic tailoring of the blades. Several methods can assess the extent of these potentials. Research shows that embedded sensing methods can be used in dynamic measurements of composites. This thesis studies a full-scale application of a network of embedded piezoelectric sensors in an FRC marine propeller blade. The study prefers using piezoelectric sensors because of their ability to operate in a relatively wide frequency range. The focus of the thesis starts with designing the full-scale network of embedded piezoelectric sensors. Since no literature includes this application on FRC blades, this study holds a pioneering role in embedding piezoelectric sensors in an FRC marine propeller blade. Detailed analysis of material dimensions - including sensors, wiring, and fiber plies - leads to a successful sensor network design. Considerations regarding the location of 24 sensors included both the in-plane and the in-depth position within the FRC laminate. Fabrication of an FRC blade has been done using a resin transfer moulding (RTM) process. For the first time, an FRC marine propeller blade is embedded with piezoelectric sensors. Demoulding of the blade caused damage to some of the sensor wires. An amount of 54% of the embedded sensors survived the process with full connectivity. The performance of the intact sensors after fabrication is assessed. These sensors are exposed to free vibration tests of the FRC blade. An excitation is imposed on the blade with an impact hammer. A data acquisition (DAQ) system is used to capture the responses of the embedded piezo-sensors. The frequency response functions (FRFs) of multiple locations on the blade are computed. These FRFs provide more insight into the dynamic behavior of the blade. A frequency range of 1-1000Hz is used in the modal analysis. The first five natural frequencies are found between 240Hz and 840Hz. Natural frequencies measured by the embedded piezo-sensors and surface-mounted strain gauges differ up until 25% from natural frequencies computed by a finite element model (FEM) of the blade. The mode shape of the blade at the natural frequencies is computed for by the FEM and embedded piezo-sensors. Some difference in mode shapes is demonstrated between measurements computed by FEM and those measured by the embedded piezo-sensors and surface-mounted strain gauges. The piezo-sensors and strain gauges are in agreement regarding the measured natural frequencies. Therefore, it is expected that discrepancies exist between the physical blade and FEM. Several points for improvement of the results have been found. The study provides the first-time feasibility of dynamic measurements from embedded piezo-sensors in an FRC marine propeller blade. Additionally, a framework for reconstructing the full-field vibration response is provided, which can provide more accurate results when the agreement between piezo-sensor and FEM measurements has improved.

For floating photovoltaic systems, an uncommon type of offshore structure is considered, which is very flexible and deforms with the motion of the waves. In this research, the bending characteristics of a drop-stitch floater is analysed, which is an inflatable panel. By inflating the drop-stitch floater to a low air pressure, it obtains a flattened shape and the ability to support the flexible solar panels, while still retaining flexibility to deform with the motion of the waves. The bending characteristics of a drop-stitch floater are more complex than common offshore structures due to different non-linearities: wrinkling, hyperelastic material behaviour and internal pressure-volume work. Getting a better understanding in the bending response is important to eventually determine the response and limit states in offshore conditions. A finite element and experimental analysis has been performed of the response in a three point bending load case. Also, an experimental uniaxial tensile test has been performed to evaluate the hyperelastic anisotropic material behaviour. Different yarns spacings, internal air pressures and face sheet thicknesses are evaluated. This showed that there are two types of failure modes with distinct behaviour for an uniaxial pure bending load case: a global wrinkling and folding failure mode.

Highly-loaded low-speed roller bearings are frequently used in equipment offshore e.g. slew bearings in crane, sheave bearings and FPSO turret bearings. Reducing maintenance costs, increasing productivity, ensuring safety of people and structural integrity and longevity assurance of equipment can be achieved by the condition monitoring of highly-loaded low-speed roller bearings.

Currently, very limited research is performed in the field of condition monitoring with acoustic emission (AE) monitoring for highly-loaded low-speed (<10 rpm) bearings with naturally developed damage. Acoustic emission monitoring has shown promising results in early stage and real time identification of defects according to literature. Furthermore, contamination of wear particles in lubricant shows an increase in AE activity according to literature.

In this research, the applicability of AE monitoring for damage assessment of highly-loaded low-speed roller bearings is investigated in a full scale duration test. Furthermore, the influence of contaminated lubricant with steel particles is investigated in the contamination test to study the feasibility of real-time detection of contaminated lubricant during operations and as a supporting technique for wear debris analysis in lubricant.

From the results, an increase in AE activity expressed in hit-rates is observed for a wide frequency band of 40 - 580 kHz during the duration test where the basic rating lifetime (L10) is consumed from 40% to 50%. Wear development in the bearing is observed during visual inspection and has been quantified with lubrication analysis.
A safety limit and a limit if the bearing is at risk for the AE activity has been defined with the results of the baseline and duration test. This research suggests that AE monitoring can be applied on highly-loaded low-speed bearings to assess the damage for representative operational conditions.

From the results of the lubricant contamination test, an increased AE activity with respect to higher lubricant contamination levels were observed. Furthermore, with a proper choice of the SNR-level, there is no masking effect of acoustic emission signals due to contaminated lubricant. The results of the contamination tests, indicates the possibility of detecting contaminated lubricant with AE monitoring.

Currently, as the utilization of offshore wind energy continues to increase, floating wind turbines are expected to be widely used. As the fixed system of the turbine, the safety of the mooring chain has gradually attracted the attention of researchers. Mooring chains immersed in seawater are mainly subjected to various mechanical loads and corrosion. Therefore, premature failure and frequent replacement are the main problems of mooring chain systems. In order to avoid huge losses of safety caused by structural failure, it is urgent to establish mooring integrity management, accurately identify hazards, and evaluate the service life of the mooring system. Considering the requirements of sufficient mechanical properties and economic benefits, high-strength low-alloy steel has gradually replaced low-carbon steel as the main material for mooring chains. However, there are few studies on the detailed corrosion process of mooring chain steel.
This research aims to explore the corrosion process of mooring chain steel and the influence of marine environmental factors on the corrosion process. Traditional electrochemical techniques, morphology observation and new in-situ non-destructive technique acoustic emission are used to investigate the corrosion process. The experiment includes the exploration of the corrosion process of steel under natural and accelerated conditions. Experiments on the influence of flow velocity and temperature are also included. The corrosion process of mooring chain steel is successfully explored during the monitoring process. Acoustic emission signals related to corrosion are separated. Their sources are reasonably identified. The effects of water flow velocity and temperature of the corrosion process are summarized.