Lotfollah Pahlavan
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38 records found
1
Acoustic emission (AE) monitoring is a method of structural health monitoring that relies on the detection of elastic waves generated by the release of concentrated strain energy when damage is created in a structural material. One of its strengths is that recorded waveforms can, in theory, be used to infer the source mechanisms, enabling estimation of damage type, location, and severity. One of the challenges, however, is how to automate the interpretation and reliably retain useful information from AE waveforms, which are often thousands of samples long. In this work, a method of waveform analysis in the frequency domain is presented that combines principal component analysis and an autoencoder to reduce the dimensionality of the problem to a pair of parameters, capturing the spectrum shape and the spectrum energy content. Tensile tests were carried out on composite coupon specimens while monitoring AE, and the progression of damage was assessed by X-ray scanning the specimens at two locations along their length, both before and after testing. Locations and types of damage in the scans are in good agreement with the results of the AE monitoring and analysis framework. The method is proposed as a tool for automated interpretation of AE signals with the potential to be generalized to other material, layup, and sensor setups.
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Acoustic emission (AE) monitoring is a method of structural health monitoring that relies on the detection of elastic waves generated by the release of concentrated strain energy when damage is created in a structural material. One of its strengths is that recorded waveforms can, in theory, be used to infer the source mechanisms, enabling estimation of damage type, location, and severity. One of the challenges, however, is how to automate the interpretation and reliably retain useful information from AE waveforms, which are often thousands of samples long. In this work, a method of waveform analysis in the frequency domain is presented that combines principal component analysis and an autoencoder to reduce the dimensionality of the problem to a pair of parameters, capturing the spectrum shape and the spectrum energy content. Tensile tests were carried out on composite coupon specimens while monitoring AE, and the progression of damage was assessed by X-ray scanning the specimens at two locations along their length, both before and after testing. Locations and types of damage in the scans are in good agreement with the results of the AE monitoring and analysis framework. The method is proposed as a tool for automated interpretation of AE signals with the potential to be generalized to other material, layup, and sensor setups.
Conference paper
(2026)
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Ali Mardanshahi, Lotfollah Pahlavan, Mohammad Fotouhi, Koen Van Den Abeele, Dimitrios Chronopoulos
Reliable guided-wave monitoring of pipelines requires models that are both computationally efficient and capable of capturing the main physical propagation mechanisms in cylindrical waveguides. In thin-walled large-diameter pipes, guided waves propagate locally in a plate-like manner while the cylindrical topology creates multiple deterministic surface-geodesic routes between actuator and sensor locations. Besides the direct route, spiral routes wrapping around the circumference can generate distinct received wave packets, and additional packets arise from reflections at pipe boundaries and local discontinuities. This paper presents a semi-analytical hybrid framework for pipeline guided waves that combines Wave Finite Element (WFE) dispersion extraction with a route-based long-range propagation engine. The model explicitly accounts for direct and spiral propagation routes as well as boundary-reflected contributions. Validation is performed in two steps. First, model predictions are compared to full 3D transient finite element simulations on a steel pipe, assessing arrival times, wave-packet structure, and route-dependent contributions. Second, experimental measurements on a steel pipe are used to identify and interpret the received wave packets. The results demonstrate that the proposed semi-analytical model captures the dominant wave packets observed in 3D FE and experiments, while requiring significantly lower computational effort than full transient simulation. The validated framework provides a foundation for subsequent model-assisted monitoring and data-driven localization studies in realistic pipeline environments.
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Reliable guided-wave monitoring of pipelines requires models that are both computationally efficient and capable of capturing the main physical propagation mechanisms in cylindrical waveguides. In thin-walled large-diameter pipes, guided waves propagate locally in a plate-like manner while the cylindrical topology creates multiple deterministic surface-geodesic routes between actuator and sensor locations. Besides the direct route, spiral routes wrapping around the circumference can generate distinct received wave packets, and additional packets arise from reflections at pipe boundaries and local discontinuities. This paper presents a semi-analytical hybrid framework for pipeline guided waves that combines Wave Finite Element (WFE) dispersion extraction with a route-based long-range propagation engine. The model explicitly accounts for direct and spiral propagation routes as well as boundary-reflected contributions. Validation is performed in two steps. First, model predictions are compared to full 3D transient finite element simulations on a steel pipe, assessing arrival times, wave-packet structure, and route-dependent contributions. Second, experimental measurements on a steel pipe are used to identify and interpret the received wave packets. The results demonstrate that the proposed semi-analytical model captures the dominant wave packets observed in 3D FE and experiments, while requiring significantly lower computational effort than full transient simulation. The validated framework provides a foundation for subsequent model-assisted monitoring and data-driven localization studies in realistic pipeline environments.
This paper aims to assess the influence of stiffeners and sensor transfer functions on the measurability of acoustic emission (AE) waves in ship structures travelling as ultrasonic-guided waves. A procedure for evaluating this influence by calculating sensor correction coefficients has been developed. After applying the obtained correction coefficients, the transmission of the ultrasonic-guided waves and their dependence on the angle of incidence and different frequency content are investigated using finite element simulations and experimental measurements. The experiments examine the propagation of 60 and 150 kHz AE signals in a 10-mm thick steel plate. By combining the results of the simulations and experimental results, the attenuation due to the presence of stiffeners turns out to be less than 5 dB and the transmission coefficient appears to have limited variation for different angles of incidence. The results of this study can be used to optimize the accuracy and coverage of AE monitoring systems.
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This paper aims to assess the influence of stiffeners and sensor transfer functions on the measurability of acoustic emission (AE) waves in ship structures travelling as ultrasonic-guided waves. A procedure for evaluating this influence by calculating sensor correction coefficients has been developed. After applying the obtained correction coefficients, the transmission of the ultrasonic-guided waves and their dependence on the angle of incidence and different frequency content are investigated using finite element simulations and experimental measurements. The experiments examine the propagation of 60 and 150 kHz AE signals in a 10-mm thick steel plate. By combining the results of the simulations and experimental results, the attenuation due to the presence of stiffeners turns out to be less than 5 dB and the transmission coefficient appears to have limited variation for different angles of incidence. The results of this study can be used to optimize the accuracy and coverage of AE monitoring systems.
This paper presents a framework for impact source localization and force reconstruction in stiffened thin-walled steel structures using Guided Waves. Impact localization is performed using passive Time Reversal in the frequency domain, enabling the source signal reconstruction for subsequent force estimation. Force reconstruction is achieved using a parametric half-sine model combined with a transfer function obtained from a single calibration impact. The approach is experimentally validated on a steel plate subjected to controlled impacts while monitoring its structural response using piezoelectric sensors. The results show that impact localization can be achieved with mean errors of 14.7 mm and 23.7 mm for the plate and stiffened configurations, respectively. More than 80% of the impacts are localized within 10% of the sensor spacing. The reconstructed forces using the parametric model provide an estimate of the applied impact force, with a mean relative error of approximately 31%. The results demonstrate that the proposed approach can enable combined impact localization and force estimation in thin-walled structures, with and without the presence of structural stiffeners.
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This paper presents a framework for impact source localization and force reconstruction in stiffened thin-walled steel structures using Guided Waves. Impact localization is performed using passive Time Reversal in the frequency domain, enabling the source signal reconstruction for subsequent force estimation. Force reconstruction is achieved using a parametric half-sine model combined with a transfer function obtained from a single calibration impact. The approach is experimentally validated on a steel plate subjected to controlled impacts while monitoring its structural response using piezoelectric sensors. The results show that impact localization can be achieved with mean errors of 14.7 mm and 23.7 mm for the plate and stiffened configurations, respectively. More than 80% of the impacts are localized within 10% of the sensor spacing. The reconstructed forces using the parametric model provide an estimate of the applied impact force, with a mean relative error of approximately 31%. The results demonstrate that the proposed approach can enable combined impact localization and force estimation in thin-walled structures, with and without the presence of structural stiffeners.
Committee V.7
Structural Assessment During Operations
Conference paper
(2026)
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James Underwood, Alfonso Barbato, Anriëtte Bekker, Moritz Braun, Martin Alexander Eder, Paul Hess, Ian Thompson, Christian Jochum, Pooria Pahlavan, More Authors
Concern for the structural assessment of ship and offshore structures during operations, including unmanned operations. The focus shall be on methodologies translating monitoring and inspection data into operational and life-cycle management advice, with associated criteria for decision making. This shall include diagnosis and prognosis of structural health, prevention of structural degradation and failures, and structural renewal and reuse. The research and development in passive, latent and active systems including their sensors and actuators shall be addressed. Special attention is to be given to structural digital twin technology and methods including reduced order analysis, inverse modelling, and AI technology application, combined with the use of monitoring systems and inspection data, to provide real-time advice for safe operation during the structural life-cycle.
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Concern for the structural assessment of ship and offshore structures during operations, including unmanned operations. The focus shall be on methodologies translating monitoring and inspection data into operational and life-cycle management advice, with associated criteria for decision making. This shall include diagnosis and prognosis of structural health, prevention of structural degradation and failures, and structural renewal and reuse. The research and development in passive, latent and active systems including their sensors and actuators shall be addressed. Special attention is to be given to structural digital twin technology and methods including reduced order analysis, inverse modelling, and AI technology application, combined with the use of monitoring systems and inspection data, to provide real-time advice for safe operation during the structural life-cycle.
Journal article
(2026)
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Romain Habiyaremye, Cecilia Saccone, Arjan Mol, Harleigh Seyffert, Lotfollah Pahlavan
Seagoing vessels operate in harsh environments which make them especially prone to progressive degradation mechanisms such as fatigue and corrosion. Acoustic emission (AE) monitoring is gaining interest from ship operators and inspectors for its potential as an early-warning structural health monitoring technique for these types of damage. A major challenge facing the implementation of AE is dealing with the background noise. This article presents an experimental study of ultrasonic noise levels in representative environments and conditions AE monitoring. The probability of detection (PoD) is proposed as a quantitative metric for the detection of damage in the presence of operational noise. Measurements were carried out in multiple locations on board of a vessel under different operational conditions. Measurements at cruising speed on hull plates inside the engine room suggest that the ultrasonic background noise level exceeded 90 dB under 100 kHz but rapidly reduced in the higher frequencies associated with the failure mode-related AE signals. The PoD was estimated to be 94% for damage signals above 100 kHz. These results suggest that acoustic emission monitoring has the potential to perform reliably under noisy conditions. This perspective is promising to the future of a structural health monitoring system based on AE measurement.
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Seagoing vessels operate in harsh environments which make them especially prone to progressive degradation mechanisms such as fatigue and corrosion. Acoustic emission (AE) monitoring is gaining interest from ship operators and inspectors for its potential as an early-warning structural health monitoring technique for these types of damage. A major challenge facing the implementation of AE is dealing with the background noise. This article presents an experimental study of ultrasonic noise levels in representative environments and conditions AE monitoring. The probability of detection (PoD) is proposed as a quantitative metric for the detection of damage in the presence of operational noise. Measurements were carried out in multiple locations on board of a vessel under different operational conditions. Measurements at cruising speed on hull plates inside the engine room suggest that the ultrasonic background noise level exceeded 90 dB under 100 kHz but rapidly reduced in the higher frequencies associated with the failure mode-related AE signals. The PoD was estimated to be 94% for damage signals above 100 kHz. These results suggest that acoustic emission monitoring has the potential to perform reliably under noisy conditions. This perspective is promising to the future of a structural health monitoring system based on AE measurement.
Conference paper
(2026)
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Romain Habiyaremye, Yelitza Delgado-González, Axel Homborg, Harleigh Seyffert, Arjan MOL, Lotfollah Pahlavan
Corrosion is a leading damage mechanism in the degradation of marine assets. Organic barrier coatings are widely used as a corrosion mitigation measure, because their application suppresses the interaction between the metallic structure and the corrosive environment. Electrochemical impedance spectroscopy (EIS) is a well-established technique for the evaluation of coating performance. Acoustic emission (AE) monitoring has gained increasing interest as a technique for continuous monitoring of corrosion damage. In this experimental study, EIS measurements are combined with AE monitoring to investigate the degradation of different organic barrier coatings. Laboratory experiments were performed on 7 aluminum specimens covered with different types of coatings. Water uptake was achieved by immersing the samples in a salt solution for 24 hours prior to each test. Each sample was equipped with an electrochemical cell (Ag/AgCl reference electrode, platinum mesh counter electrode, acidic NaCl solution; pH=2) and an AE sensor (85-180kHz). The acidic salt solution was used to accelerate the degradation of the coatings for a period of 24 hours during which periodic EIS measurements were performed as well as continuous AE monitoring. AE signals detected during the test could be associated with a measured reduction in coating resistance and, in some cases, visible signs of surface degradation. The preliminary results from the study indicate that coating degradation generates AE signals in the same frequency range as that of typical AE from corrosion degradation. This is a promising perspective towards expanding the capabilities of AE based structural health monitoring systems.
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Corrosion is a leading damage mechanism in the degradation of marine assets. Organic barrier coatings are widely used as a corrosion mitigation measure, because their application suppresses the interaction between the metallic structure and the corrosive environment. Electrochemical impedance spectroscopy (EIS) is a well-established technique for the evaluation of coating performance. Acoustic emission (AE) monitoring has gained increasing interest as a technique for continuous monitoring of corrosion damage. In this experimental study, EIS measurements are combined with AE monitoring to investigate the degradation of different organic barrier coatings. Laboratory experiments were performed on 7 aluminum specimens covered with different types of coatings. Water uptake was achieved by immersing the samples in a salt solution for 24 hours prior to each test. Each sample was equipped with an electrochemical cell (Ag/AgCl reference electrode, platinum mesh counter electrode, acidic NaCl solution; pH=2) and an AE sensor (85-180kHz). The acidic salt solution was used to accelerate the degradation of the coatings for a period of 24 hours during which periodic EIS measurements were performed as well as continuous AE monitoring. AE signals detected during the test could be associated with a measured reduction in coating resistance and, in some cases, visible signs of surface degradation. The preliminary results from the study indicate that coating degradation generates AE signals in the same frequency range as that of typical AE from corrosion degradation. This is a promising perspective towards expanding the capabilities of AE based structural health monitoring systems.
Flexible composite marine propeller blades can offer the potential for reduced greenhouse gas emissions as well as a reduction in underwater radiated noise. Nevertheless, their application in the real world is hindered, among others, by unknowns in the fatigue behaviour of these blades. This research assesses the structural health measurements of an experimental campaign wherein a glass-fibre reinforced plastic marine propeller blade was tested under 1½ times the design operational load for 16 million cycles. Acoustic emissions were investigated that were recorded underwater by hydrophones that were placed close by the blade. Approximately 40Gb of AE feature data was obtained, alongside 200+Gb of waveform data. The feature data was filtered to only assess the data pertaining to the hydrophones, with a focus on hit-rate over time and cumulative energy. The results give an insight into the fatigue behaviour of the blade, alongside considerations regarding placement of hydrophones and comparison to other relevant data such as load-displacement histories and visual observations.
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Flexible composite marine propeller blades can offer the potential for reduced greenhouse gas emissions as well as a reduction in underwater radiated noise. Nevertheless, their application in the real world is hindered, among others, by unknowns in the fatigue behaviour of these blades. This research assesses the structural health measurements of an experimental campaign wherein a glass-fibre reinforced plastic marine propeller blade was tested under 1½ times the design operational load for 16 million cycles. Acoustic emissions were investigated that were recorded underwater by hydrophones that were placed close by the blade. Approximately 40Gb of AE feature data was obtained, alongside 200+Gb of waveform data. The feature data was filtered to only assess the data pertaining to the hydrophones, with a focus on hit-rate over time and cumulative energy. The results give an insight into the fatigue behaviour of the blade, alongside considerations regarding placement of hydrophones and comparison to other relevant data such as load-displacement histories and visual observations.
Acoustic Emission Monitoring of S.A. Agulhas II
Parametric Analysis and Correlation with Global Strain
Conference paper
(2026)
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Cecilia Saccone, Gerhard Durandt, Nicole Catherine Taylor, Anriëtte Bekker, Lotfollah Pahlavan
Ensuring the structural reliability of ships in demanding sea states requires monitoring approaches capable of detecting fatigue damage during operational conditions. This study investigates the application of Acoustic Emission through a full-scale monitoring campaign on board the Polar Supply and Research Vessel S. A. Agulhas II. Two sensor nodes were installed: one on the port side near an active fatigue crack and one on the starboard side in a previously repaired region, enabling a direct comparison under similar loading conditions. More than four million AE signals were recorded, with roughly 80% originating from the active-crack region. The analysis focuses on AE parametric features—amplitude, hit rate and cumulative counts—and their qualitative correlation with local strain gauge measurements. Differences between the two sensor locations are assessed to evaluate the sensitivity of AE parameters to local structural condition. The results offer practical insights on sensor placement, data handling and the integration of AE with complementary onboard measurements, contributing to the assessment of AE for in-service monitoring of ship structures.
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Ensuring the structural reliability of ships in demanding sea states requires monitoring approaches capable of detecting fatigue damage during operational conditions. This study investigates the application of Acoustic Emission through a full-scale monitoring campaign on board the Polar Supply and Research Vessel S. A. Agulhas II. Two sensor nodes were installed: one on the port side near an active fatigue crack and one on the starboard side in a previously repaired region, enabling a direct comparison under similar loading conditions. More than four million AE signals were recorded, with roughly 80% originating from the active-crack region. The analysis focuses on AE parametric features—amplitude, hit rate and cumulative counts—and their qualitative correlation with local strain gauge measurements. Differences between the two sensor locations are assessed to evaluate the sensitivity of AE parameters to local structural condition. The results offer practical insights on sensor placement, data handling and the integration of AE with complementary onboard measurements, contributing to the assessment of AE for in-service monitoring of ship structures.
Corrosion is a leading damage mechanisms in the degradation of marine assets. Acoustic emission (AE) monitoring has gained increasing interest as a technique for continuous monitoring of corrosion damage. This study numerically and experimentally investigates the feasibility of wall thickness loss estimation from the AE signals due to localized corrosion. The interaction of the elastic waves emitted due to the evolution of corrosion damage are influenced by the local thickness and material properties of the structure. A steel plate of (500 mm x 500 mm x 10 mm) with a localized wall thickness loss between 0 and 80% in the center of the plate was considered. The numerical investigation was conducted using a higher-order finite element model. Laboratory experiments were performed on a carbon steel specimen instrumented with 7 AE transducers (40 - 250 kHz). Corrosion damage was artificially introduced in the steel plate by progressively milling a pit in the center. At different stages of wall thickness loss, simulated AE sources were generated. The response of the structure was evaluated based on signal characteristics such as amplitude, rise-time, frequency content, and waveform. A correlation between the signal amplitudes and the wall thickness loss was observed in both experimental and numerical results. This perspective is promising for the feasibility of corrosion-induced wall thickness loss estimation based on AE measurements.
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Corrosion is a leading damage mechanisms in the degradation of marine assets. Acoustic emission (AE) monitoring has gained increasing interest as a technique for continuous monitoring of corrosion damage. This study numerically and experimentally investigates the feasibility of wall thickness loss estimation from the AE signals due to localized corrosion. The interaction of the elastic waves emitted due to the evolution of corrosion damage are influenced by the local thickness and material properties of the structure. A steel plate of (500 mm x 500 mm x 10 mm) with a localized wall thickness loss between 0 and 80% in the center of the plate was considered. The numerical investigation was conducted using a higher-order finite element model. Laboratory experiments were performed on a carbon steel specimen instrumented with 7 AE transducers (40 - 250 kHz). Corrosion damage was artificially introduced in the steel plate by progressively milling a pit in the center. At different stages of wall thickness loss, simulated AE sources were generated. The response of the structure was evaluated based on signal characteristics such as amplitude, rise-time, frequency content, and waveform. A correlation between the signal amplitudes and the wall thickness loss was observed in both experimental and numerical results. This perspective is promising for the feasibility of corrosion-induced wall thickness loss estimation based on AE measurements.
In this paper, an investigation of the characterization of fatigue damage-induced signals by means of Acoustic Emission (AE) monitoring is presented. The objective is to establish a correlation between AE signals and fatigue crack growth data. To achieve this, small-scale fatigue experiments have been performed. The test consists of cyclic loading of standardized compact test (CT) specimens at room temperature. Damage-induced ultrasound signals were continuously measured using four AE transducers. The results suggest that AE signals emitted by fatigue crack growth from the initiation moment can be detected with a satisfactory signal-to-noise ratio. A multi-parameter analysis including amplitude, counts and hit rate of AE data in correlation with crack growth data was performed. Three stages of fatigue crack growth were identified, offering a basis for further damage characterisation using AE monitoring.
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In this paper, an investigation of the characterization of fatigue damage-induced signals by means of Acoustic Emission (AE) monitoring is presented. The objective is to establish a correlation between AE signals and fatigue crack growth data. To achieve this, small-scale fatigue experiments have been performed. The test consists of cyclic loading of standardized compact test (CT) specimens at room temperature. Damage-induced ultrasound signals were continuously measured using four AE transducers. The results suggest that AE signals emitted by fatigue crack growth from the initiation moment can be detected with a satisfactory signal-to-noise ratio. A multi-parameter analysis including amplitude, counts and hit rate of AE data in correlation with crack growth data was performed. Three stages of fatigue crack growth were identified, offering a basis for further damage characterisation using AE monitoring.
Naval vessels are valuable assets that are expensive to build and maintain. Predictive maintenance is crucial to enhance efficiency and operability and to extend the service life of these structures. Fatigue is regarded as one of the main damage modes affecting the structural integrity of ship structures. Fatigue cracks can develop at the intersections of stiffeners and other structural elements, without being detected until they substantially grow, introducing a degree of uncertainty in the estimation of the fatigue damage. Acoustic emission (AE) is a passive ultrasound method for the detection and localization of different types of damage. AE is sensitive to crack propagation and can cover large areas, making it suitable for structural health monitoring of ship hulls. However, for accurate fatigue crack detection via AE it is crucial to understand how ultrasound waves interact with structural members i.e. stiffeners and longitudinal frames. Dispersion, scattering, reflection, and multimodality have so far hindered the application of AE in this context. This study aims to assess ultrasound wave behavior in ship structures in the presence of structural elements such as stiffeners and longitudinal/transversal frames. It investigates the ultrasound wave transmission dependence on source frequency and angle of incidence using spectral finite element (SEM) simulations and experimental measurements. The experimental setup includes a 10mm thick steel plate with a stiffener and a longitudinal beam (Figure 1). Pairs of sensors are placed on each side of the stiffener to record the incoming and transmitted waves, and to determine the transmission coefficient. By combining the results of both simulation and experiments, an expression for the transmission coefficient as a function of different frequencies and angles is presented. The results of this study can be used to maximize the coverage of AE monitoring systems and enhance their sensitivity for detection of fatigue cracks on ship structures.
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Naval vessels are valuable assets that are expensive to build and maintain. Predictive maintenance is crucial to enhance efficiency and operability and to extend the service life of these structures. Fatigue is regarded as one of the main damage modes affecting the structural integrity of ship structures. Fatigue cracks can develop at the intersections of stiffeners and other structural elements, without being detected until they substantially grow, introducing a degree of uncertainty in the estimation of the fatigue damage. Acoustic emission (AE) is a passive ultrasound method for the detection and localization of different types of damage. AE is sensitive to crack propagation and can cover large areas, making it suitable for structural health monitoring of ship hulls. However, for accurate fatigue crack detection via AE it is crucial to understand how ultrasound waves interact with structural members i.e. stiffeners and longitudinal frames. Dispersion, scattering, reflection, and multimodality have so far hindered the application of AE in this context. This study aims to assess ultrasound wave behavior in ship structures in the presence of structural elements such as stiffeners and longitudinal/transversal frames. It investigates the ultrasound wave transmission dependence on source frequency and angle of incidence using spectral finite element (SEM) simulations and experimental measurements. The experimental setup includes a 10mm thick steel plate with a stiffener and a longitudinal beam (Figure 1). Pairs of sensors are placed on each side of the stiffener to record the incoming and transmitted waves, and to determine the transmission coefficient. By combining the results of both simulation and experiments, an expression for the transmission coefficient as a function of different frequencies and angles is presented. The results of this study can be used to maximize the coverage of AE monitoring systems and enhance their sensitivity for detection of fatigue cracks on ship structures.
The marine industry is increasingly considering the use of flexible composite marine propellers for their potential to reduce carbon emissions and underwater radiated noise. Given the early stage of development of flexible composite propellers, there are unknowns on their structural degradation. Structural health monitoring (SHM) can provide additional insight into the occurrence and propagation of degradation in these structures. A passive and lightweight method of SHM is the measurement and processing of acoustic emissions (AE) that are induced by different degradation mechanisms. The current research investigates the measurement of AE signals in composite marine propeller blades using embedded piezoelectric sensors. A full-scale glass-fibre polymer composite propeller blade is suspended in a tank filled with artificial seawater. The propeller blade contains 24 embedded piezoelectric sensors that were installed between laminas during manufacturing. Additionally, the tank includes an array of hydrophones for validation of the results. AE signals are simulated on the blade using underwater pencil lead breaks. The measured AE signals are assessed for their amplitude and frequency content. The results demonstrate the feasibility of measuring AE signals in composite marine propeller blades using embedded piezoelectric sensors and hydrophones.
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The marine industry is increasingly considering the use of flexible composite marine propellers for their potential to reduce carbon emissions and underwater radiated noise. Given the early stage of development of flexible composite propellers, there are unknowns on their structural degradation. Structural health monitoring (SHM) can provide additional insight into the occurrence and propagation of degradation in these structures. A passive and lightweight method of SHM is the measurement and processing of acoustic emissions (AE) that are induced by different degradation mechanisms. The current research investigates the measurement of AE signals in composite marine propeller blades using embedded piezoelectric sensors. A full-scale glass-fibre polymer composite propeller blade is suspended in a tank filled with artificial seawater. The propeller blade contains 24 embedded piezoelectric sensors that were installed between laminas during manufacturing. Additionally, the tank includes an array of hydrophones for validation of the results. AE signals are simulated on the blade using underwater pencil lead breaks. The measured AE signals are assessed for their amplitude and frequency content. The results demonstrate the feasibility of measuring AE signals in composite marine propeller blades using embedded piezoelectric sensors and hydrophones.
Flexible composite marine propellers can aid the marine industry in reducing carbon emissions and underwater radiated noise pollution. The structural integrity of the blades can be assessed using structural health monitoring. One of these methods is the measurement and analysis of damage-induced acoustic emission signals. This paper experimentally investigates the feasibility of using embedded piezoelectric sensors for the measurement of acoustic emissions throughout a submerged flexible composite marine propeller blade. A full-scale glass-fibre reinforced polymer blade has been manufactured with 24 embedded sensors. While suspended in artificial seawater, acoustic emissions were simulated on the blade. The measurements show that the embedded piezoelectric sensors can measure acoustic emissions while the blade is submerged. Further, the distance from source to sensor over which the acoustic emission is measurable was investigated. For a noise level of 40 dB and a source amplitude of 70 dB between 100 and 250 kHz, an average maximum measurable distance of 124 mm was obtained. For higher frequencies, the distance drops and for lower noise levels the distance increases.
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Flexible composite marine propellers can aid the marine industry in reducing carbon emissions and underwater radiated noise pollution. The structural integrity of the blades can be assessed using structural health monitoring. One of these methods is the measurement and analysis of damage-induced acoustic emission signals. This paper experimentally investigates the feasibility of using embedded piezoelectric sensors for the measurement of acoustic emissions throughout a submerged flexible composite marine propeller blade. A full-scale glass-fibre reinforced polymer blade has been manufactured with 24 embedded sensors. While suspended in artificial seawater, acoustic emissions were simulated on the blade. The measurements show that the embedded piezoelectric sensors can measure acoustic emissions while the blade is submerged. Further, the distance from source to sensor over which the acoustic emission is measurable was investigated. For a noise level of 40 dB and a source amplitude of 70 dB between 100 and 250 kHz, an average maximum measurable distance of 124 mm was obtained. For higher frequencies, the distance drops and for lower noise levels the distance increases.
Large-scale low-speed rolling element bearings form crucial connections in offshore installations such as heavy-lifting cranes, single point mooring systems, and wind turbines. Due to the stochastic nature of wind and waves, the applied loads on these bearings are hardly predictable. Furthermore, the remote nature of the offshore environment requires a high standard of operational safety and reliability, reinforcing the need for advanced inspection and monitoring methods. Acoustic emission (AE) is a continuous monitoring technique for condition assessment of low-speed bearings, as it may detect the stress waves associated with developing degradation within the rolling elements. This paper presents an investigation on the influence of grease contamination on acoustic emission (AE) monitoring of low-speed bearings. It discusses several experiments that have been conducted in various regimes of particle contaminated lubrication, and proposes a strategy for condition monitoring. The presented experiments have been conducted with differing bearing geometries in multiple testing environments. The contamination particles have been both naturally developed and artificially introduced. The results total of 9 experimental cases are discussed and compared. All experiments follow the same data-acquisition principles, utilising arrays of three AE transducers sensitive in a range between 40-580 kHz. Data is recorded while operating the bearing at low speed under load. Abrasive wear of the rolling elements and crushing of the particles are concluded to be the main sources of AE due to particle contamination. Processing consists of waveform cross-correlation clustering and feature analysis. The results suggest that hard abrasive particles make significant contribution to the AE signals, which is associated with abrasive wear of the rollers and raceways. Comparisons with the contribution of softer and finer particles are presented as well.
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Large-scale low-speed rolling element bearings form crucial connections in offshore installations such as heavy-lifting cranes, single point mooring systems, and wind turbines. Due to the stochastic nature of wind and waves, the applied loads on these bearings are hardly predictable. Furthermore, the remote nature of the offshore environment requires a high standard of operational safety and reliability, reinforcing the need for advanced inspection and monitoring methods. Acoustic emission (AE) is a continuous monitoring technique for condition assessment of low-speed bearings, as it may detect the stress waves associated with developing degradation within the rolling elements. This paper presents an investigation on the influence of grease contamination on acoustic emission (AE) monitoring of low-speed bearings. It discusses several experiments that have been conducted in various regimes of particle contaminated lubrication, and proposes a strategy for condition monitoring. The presented experiments have been conducted with differing bearing geometries in multiple testing environments. The contamination particles have been both naturally developed and artificially introduced. The results total of 9 experimental cases are discussed and compared. All experiments follow the same data-acquisition principles, utilising arrays of three AE transducers sensitive in a range between 40-580 kHz. Data is recorded while operating the bearing at low speed under load. Abrasive wear of the rolling elements and crushing of the particles are concluded to be the main sources of AE due to particle contamination. Processing consists of waveform cross-correlation clustering and feature analysis. The results suggest that hard abrasive particles make significant contribution to the AE signals, which is associated with abrasive wear of the rollers and raceways. Comparisons with the contribution of softer and finer particles are presented as well.
Mooring chains are key parts of floating energy production units, such as floating wind turbines, photovoltaic islands, and floating production-storage-offloading units (FPSOs). These structures are predominantly subject to corrosion and fatigue. Detailed integrity assessment of mooring chains can be challenging due to difficult access, complex geometry, surface conditions (often with the presence of corrosion pits), and weather conditions. Additionally, the presence of marine growth on the surface of the chain links often requires the need of surface cleaning to obtain a detailed assessment of the structural integrity. This paper highlights an experimental investigation of monitoring of corrosion-induced damage in mooring chain links by means of non-contact Acoustic Emission (AE) technique. Accelerated corrosion experiments were performed on a large-scale mooring chain sample recovered from the field. A dedicated experimental set-up was designed to apply accelerated corrosion on two chain links submerged in natural sea-water. An immersion tank, i.e. an instrumented 1000x1000x1200mm3 water tank, was used to submerge the chain links in natural sea-water. The corrosion process was accelerated by means of anodic polarization. Ultrasound signals were continuously measured using two arrays of underwater AE transducers (in the frequency range between 50-450 kHz) placed on two perpendicular planes at a fixed distance from the chain links. Corrosion-induced AE sources were localized on the 3D geometry of the tested links. The variation and evolution of AE parameters extracted from the measured signals were analyzed as a function of testing time. The results of the accelerated corrosion experiment suggest that corrosion-induced ultrasound signals can be detected and monitored by means of non-contact AE. The results of this study may be used for characterization of corrosion-induced AE signals in mooring chain links.
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Mooring chains are key parts of floating energy production units, such as floating wind turbines, photovoltaic islands, and floating production-storage-offloading units (FPSOs). These structures are predominantly subject to corrosion and fatigue. Detailed integrity assessment of mooring chains can be challenging due to difficult access, complex geometry, surface conditions (often with the presence of corrosion pits), and weather conditions. Additionally, the presence of marine growth on the surface of the chain links often requires the need of surface cleaning to obtain a detailed assessment of the structural integrity. This paper highlights an experimental investigation of monitoring of corrosion-induced damage in mooring chain links by means of non-contact Acoustic Emission (AE) technique. Accelerated corrosion experiments were performed on a large-scale mooring chain sample recovered from the field. A dedicated experimental set-up was designed to apply accelerated corrosion on two chain links submerged in natural sea-water. An immersion tank, i.e. an instrumented 1000x1000x1200mm3 water tank, was used to submerge the chain links in natural sea-water. The corrosion process was accelerated by means of anodic polarization. Ultrasound signals were continuously measured using two arrays of underwater AE transducers (in the frequency range between 50-450 kHz) placed on two perpendicular planes at a fixed distance from the chain links. Corrosion-induced AE sources were localized on the 3D geometry of the tested links. The variation and evolution of AE parameters extracted from the measured signals were analyzed as a function of testing time. The results of the accelerated corrosion experiment suggest that corrosion-induced ultrasound signals can be detected and monitored by means of non-contact AE. The results of this study may be used for characterization of corrosion-induced AE signals in mooring chain links.
The acoustic emission (AE) technique allows monitoring damage in (reinforced) concrete in a non-destructive way by means of piezoelectric sensors attached to the material surface. This approach has disadvantages such as a decrease of the sensor coupling over time, high attenuation of AE waves in concrete, and difficulties in terms of sensor placement. Embedded AE sensors, so-called ‘smart aggregates’ (SA), can be a valuable addition or alternative to surface-mounted AE sensors. However, the embedment of sensors brings its own challenges. In this paper, the use of SA is investigated to monitor cracking of fiber reinforced concrete during a three-point bending test, and corrosion and related concrete cracking of reinforced concrete during an accelerated corrosion test. The novelty of the paper is the application of SA for passive AE monitoring during concrete degradation processes with a varying cracking behavior and crack orientation. Special emphasis is put on data filtering and localization of AE sources. The results show that, despite a higher level of wide-band noise for the SA sensors, they are able to detect and localize concrete cracking after dedicated filtering. Furthermore, the potential of SA sensors in early-stage detection of corrosion damage is demonstrated, offering enhanced possibilities for predictive maintenance of concrete structures.
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The acoustic emission (AE) technique allows monitoring damage in (reinforced) concrete in a non-destructive way by means of piezoelectric sensors attached to the material surface. This approach has disadvantages such as a decrease of the sensor coupling over time, high attenuation of AE waves in concrete, and difficulties in terms of sensor placement. Embedded AE sensors, so-called ‘smart aggregates’ (SA), can be a valuable addition or alternative to surface-mounted AE sensors. However, the embedment of sensors brings its own challenges. In this paper, the use of SA is investigated to monitor cracking of fiber reinforced concrete during a three-point bending test, and corrosion and related concrete cracking of reinforced concrete during an accelerated corrosion test. The novelty of the paper is the application of SA for passive AE monitoring during concrete degradation processes with a varying cracking behavior and crack orientation. Special emphasis is put on data filtering and localization of AE sources. The results show that, despite a higher level of wide-band noise for the SA sensors, they are able to detect and localize concrete cracking after dedicated filtering. Furthermore, the potential of SA sensors in early-stage detection of corrosion damage is demonstrated, offering enhanced possibilities for predictive maintenance of concrete structures.
Journal article
(2024)
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M.G.A. Adams, A.J. Huijer, C. Kassapoglou, Johannes A.A. Vaders, Lotfollah Pahlavan
The multimodal and dispersive character of ultrasonic guided waves (UGW) offers the potential for non-destructive evaluation of fiber-reinforced composite (FRC) materials. In this study, a methodology for in situ stiffness assessment of FRCs using UGWs is introduced. The proposed methodology involves a comparison between measured wave speeds of the fundamental symmetric and antisymmetric guided wave modes with a pre-established dataset of UGW speeds and translation of them to corresponding stiffness properties, i.e., 𝐴𝐵𝐷-components, in an inverse manner. The dispersion relations of guided waves have been calculated using the semi-analytical finite element method. First, the performance of the proposed methodology has been assessed numerically. It has been demonstrated that each of the independent 𝐴𝐵𝐷-components of the considered laminate can be approximated with an error lower than 10.4% compared to its actual value. The extensional and bending stiffness properties can be approximated within an average error of 3.6% and 9.0%, respectively. Secondly, the performance of the proposed methodology has been assessed experimentally. This experimental assessment has been performed on a glass fiber-reinforced composite plate and the results were compared to mechanical tensile and four-point bending tests on coupons cut from the plate. Larger differences between the estimated 𝐴𝐵𝐷-components according to UGW and mechanical testing were observed. These differences were partly attributed to the variation in material properties across the test plate and the averaging of properties over the measurement area.
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The multimodal and dispersive character of ultrasonic guided waves (UGW) offers the potential for non-destructive evaluation of fiber-reinforced composite (FRC) materials. In this study, a methodology for in situ stiffness assessment of FRCs using UGWs is introduced. The proposed methodology involves a comparison between measured wave speeds of the fundamental symmetric and antisymmetric guided wave modes with a pre-established dataset of UGW speeds and translation of them to corresponding stiffness properties, i.e., 𝐴𝐵𝐷-components, in an inverse manner. The dispersion relations of guided waves have been calculated using the semi-analytical finite element method. First, the performance of the proposed methodology has been assessed numerically. It has been demonstrated that each of the independent 𝐴𝐵𝐷-components of the considered laminate can be approximated with an error lower than 10.4% compared to its actual value. The extensional and bending stiffness properties can be approximated within an average error of 3.6% and 9.0%, respectively. Secondly, the performance of the proposed methodology has been assessed experimentally. This experimental assessment has been performed on a glass fiber-reinforced composite plate and the results were compared to mechanical tensile and four-point bending tests on coupons cut from the plate. Larger differences between the estimated 𝐴𝐵𝐷-components according to UGW and mechanical testing were observed. These differences were partly attributed to the variation in material properties across the test plate and the averaging of properties over the measurement area.
Corrosion-fatigue is considered to be one of the main degradation mechanisms affecting the structural integrity of offshore support structures. This paper presents a feasibility assessment for the detection and monitoring of corrosion-fatigue damage using non-contact acoustic emission (AE). An accelerated corrosion-fatigue experiment was conducted on a S420NL dog-bone specimen. A corrosion-fatigue cell was designed and fabricated to simultaneously apply accelerated corrosion and cyclic loads on the specimen submerged in artificial seawater. A three-electrode electrochemical configuration under potentiostatic control was used to accelerate corrosion. The ultrasound signals were continuously measured using underwater AE transducers (in the frequency range of 50–450 kHz) placed at a fixed distance from the tested coupon. The results of the accelerated corrosion-fatigue experiment suggest that corrosion-fatigue-induced ultrasound signals can be detected with a satisfactory signal-to-noise ratio using non-contact AE sensors. The mean energy of the corrosion-fatigue-induced ultrasound signals was one order of magnitude higher than that of the corrosion-induced signals. The trends of the AE parameters extracted from the AE signals were analysed as functions of the load cycles. The results revealed high potential for the identification and monitoring of corrosion-fatigue damage using the non-contact AE technique.
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Corrosion-fatigue is considered to be one of the main degradation mechanisms affecting the structural integrity of offshore support structures. This paper presents a feasibility assessment for the detection and monitoring of corrosion-fatigue damage using non-contact acoustic emission (AE). An accelerated corrosion-fatigue experiment was conducted on a S420NL dog-bone specimen. A corrosion-fatigue cell was designed and fabricated to simultaneously apply accelerated corrosion and cyclic loads on the specimen submerged in artificial seawater. A three-electrode electrochemical configuration under potentiostatic control was used to accelerate corrosion. The ultrasound signals were continuously measured using underwater AE transducers (in the frequency range of 50–450 kHz) placed at a fixed distance from the tested coupon. The results of the accelerated corrosion-fatigue experiment suggest that corrosion-fatigue-induced ultrasound signals can be detected with a satisfactory signal-to-noise ratio using non-contact AE sensors. The mean energy of the corrosion-fatigue-induced ultrasound signals was one order of magnitude higher than that of the corrosion-induced signals. The trends of the AE parameters extracted from the AE signals were analysed as functions of the load cycles. The results revealed high potential for the identification and monitoring of corrosion-fatigue damage using the non-contact AE technique.
Journal article
(2024)
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Filippo Riccioli, Øystein Gabrielsen, Ingrid Skutle Høgsæt, Pedro Silva Barros, Lotfollah Pahlavan
This paper investigates the feasibility of detection, localisation, and monitoring of corrosion-fatigue damage in mooring chain links using remote Acoustic Emission (AE) technique in submerged conditions. A large-scale experiment was conducted on a studless R4 chain retrieved after about two decades of operation offshore. Ultrasound signals were continuously measured using fixed and movable arrays of AE transducers placed on perpendicular planes in the water tank enclosing the chain. The AE parameters extracted from the measured signals have been analysed. AE sources were successfully localised on the 3D geometry of the chain links. The results suggest that damage growth can be detected and localised using non-contact underwater AE transducers.
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This paper investigates the feasibility of detection, localisation, and monitoring of corrosion-fatigue damage in mooring chain links using remote Acoustic Emission (AE) technique in submerged conditions. A large-scale experiment was conducted on a studless R4 chain retrieved after about two decades of operation offshore. Ultrasound signals were continuously measured using fixed and movable arrays of AE transducers placed on perpendicular planes in the water tank enclosing the chain. The AE parameters extracted from the measured signals have been analysed. AE sources were successfully localised on the 3D geometry of the chain links. The results suggest that damage growth can be detected and localised using non-contact underwater AE transducers.