Advancing a Non-Contact Structural and Prognostic Health Assessment of Large Critical Structures.

This paper presents an overview of integrating new research outcomes into the development of a structural health monitoring strategy for the floating cover at the Western Treatment Plant (WTP) in Melbourne, Australia. The size of this floating cover, which covers an area of approximately 470 m × 200 m, combined with the hazardous environment and its exposure to extreme weather conditions, only allows for monitoring techniques based on remote sensing. The floating cover is deformed by the accumulation of sewage matter beneath it. Our research has shown that the only reliable data for constructing a predictive model to support the structural health monitoring of this critical asset is obtained directly from the actual floating cover at the sewage treatment plant. Our recent research outcomes lead us towards conceptualising an advanced engineering analysis tool designed to support the future creation of a digital twin for the floating cover at the WTP. Foundational work demonstrates the effectiveness of an unmanned aerial vehicle (UAV)-based photogrammetry methodology in generating a digital elevation model of the large floating cover. A substantial set of data has been acquired through regular UAV flights, presenting opportunities to leverage this information for a deeper understanding of the interactions between operational conditions and the structural response of the floating cover. This paper discusses the current findings and their implications, clarifying how these outcomes contribute to the ongoing development of an advanced digital twin for the floating cover.

Optimisation and Calibration of Bayesian Neural Network for Probabilistic Prediction of Biogas Performance in an Anaerobic Lagoon.

This study aims to enhance diagnostic capabilities for optimising the performance of the anaerobic sewage treatment lagoon at Melbourne Water's Western Treatment Plant (WTP) through a novel machine learning (ML)-based monitoring strategy. This strategy employs ML to make accurate probabilistic predictions of biogas performance by leveraging diverse real-life operational and inspection sensor and other measurement data for asset management, decision making, and structural health monitoring (SHM). The paper commences with data analysis and preprocessing of complex irregular datasets to facilitate efficient learning in an artificial neural network. Subsequently, a Bayesian mixture density neural network model incorporating an attention-based mechanism in bidirectional long short-term memory (BiLSTM) was developed. This probabilistic approach uses a distribution output layer based on the Gaussian mixture model and Monte Carlo (MC) dropout technique in estimating data and model uncertainties, respectively. Furthermore, systematic hyperparameter optimisation revealed that the optimised model achieved a negative log-likelihood (NLL) of 0.074, significantly outperforming other configurations. It achieved an accuracy approximately 9 times greater than the average model performance (NLL = 0.753) and 22 times greater than the worst performing model (NLL = 1.677). Key factors influencing the model's accuracy, such as the input window size and the number of hidden units in the BiLSTM layer, were identified, while the number of neurons in the fully connected layer was found to have no significant impact on accuracy. Moreover, model calibration using the expected calibration error was performed to correct the model's predictive uncertainty. The findings suggest that the inherent data significantly contribute to the overall uncertainty of the model, highlighting the need for more high-quality data to enhance learning. This study lays the groundwork for applying ML in transforming high-value assets into intelligent structures and has broader implications for ML in asset management, SHM applications, and renewable energy sectors.

Modal Decomposition of Acoustic Emissions from Pencil-Lead Breaks in an Isotropic Thin Plate.

Acoustic emission (AE) testing and Lamb wave inspection techniques have been widely used in non-destructive testing and structural health monitoring. For thin plates, the AEs arising from structural defect development (e.g., fatigue crack propagation) propagate as Lamb waves, and Lamb wave modes can be used to provide important information about the growth and localisation of defects. However, few sensors can be used to achieve the in situ wavenumber-frequency modal decomposition of AEs. This study explores the ability of a new multi-element piezoelectric sensor array to decompose AEs excited by pencil lead breaks (PLBs) on a thin isotropic plate. In this study, AEs were generated by out-of-plane (transverse) and in-plane (longitudinal) PLBs applied at the edge of the plate, and waveforms were recorded by both the new sensor array and a commercial AE sensor. Finite element analysis (FEA) simulations of PLBs were also conducted and the results were compared with the experimental results. To identify the wave modes present, the longitudinal and transverse PLB test results recorded by the new sensor array at five different plate locations were compared with FEA simulations using the same arrangement. Two-dimensional fast Fourier Transforms were then applied to the AE wavefields. It was found that the AE modal composition was dependent on the orientation of the PLB direction. The results suggest that this new sensor array can be used to identify the AE wave modes excited by PLBs in both in-plane and out-of-plane directions.

Acoustic Emission Source Characterisation during Fatigue Crack Growth in Al 2024-T3 Specimens.

While acoustic emission (AE) testing can be used as a valuable technique in structural health monitoring and non-destructive testing, little research has been conducted to establish its sources, particularly in 2024-T3 aluminium alloys. The major contribution of this work is that it provides a method to obtain a better linear relationship of count rate with crack growth rate based on waveform. This paper aims to characterise AE sources by synchronising the AE waveforms with load levels and then to propose possible dominant frequency ranges. The AE waveforms during fatigue crack growth in edge-notched 2024-T3 aluminium specimens, from an initial crack length of 10 mm to 70 mm, were collected at two different load ratios R = 0.125 and 0.5. At the same time, the crack growth rate was determined using thermal imaging and associated control software. The AE waveforms obtained were processed using the fast Fourier transform. It was shown that a significantly higher AE count rate was recorded at R = 0.125 compared to R = 0.5 when the maximum load was kept the same. This means that the R-ratio would affect the total amount of AE activities collected. It was also found that the dominant frequency range of the AE waveforms directly related to crack growth was 152-487 kHz, and the ranges due to crack closure were likely to be 310 kHz-316 kHz and 500-700 kHz. Based on the proposed frequency ranges, waveform selection was conducted and a better linear relationship between count rate and crack growth rate was observed. This study provides a better understanding of the AE sources and waveforms for future structural health monitoring applications.

Monitoring Osseointegration Process Using Vibration Analysis.

Osseointegration implant has attracted significant attention as an alternative treatment for transfemoral amputees. It has been shown to improve patients' sitting and walking comfort and control of the artificial limb, compared to the conventional socket device. However, the patients treated with osseointegration implants require a long rehabilitation period to establish sufficient femur-implant connection, allowing the full body weight on the prosthesis stem. Hence, a robust assessment method on the osseointegration process is essential to shorten the rehabilitation period and identify the degree of osseointegration prior to the connection of an artificial limb. This paper investigates the capability of a vibration-related index (E-index) on detecting the degree of simulated osseointegration process with three lengths of the residual femur (152, 190 and 228 mm). The adhesive epoxy with a setting time of 5 min was applied at the femur-implant interface to represent the stiffness change during the osseointegration process. The cross-spectrum and colormap of the normalised magnitude demonstrated significant changes during the cure time, showing that application of these plots could improve the accuracy of the currently available diagnostic techniques. Furthermore, the E-index exhibited a clear trend with a noticeable average increase of 53% against the cure time for all three residual length conditions. These findings highlight that the E-index can be employed as a quantitative justification to assess the degree of osseointegration process without selecting and tracing the resonant frequency based on the geometry of the residual femur.

Experimental Investigation of Vibration Analysis on Implant Stability for a Novel Implant Design.

Osseointegrated prostheses are widely used following transfemoral amputation. However, this technique requires sufficient implant stability before and during the rehabilitation period to mitigate the risk of implant breakage and loosening. Hence, reliable assessment methods for the osseointegration process are essential to ensure initial and long-term implant stability. This paper researches the feasibility of a vibration analysis technique for the osseointegration (OI) process by investigating the change in the dynamic response of the residual femur with a novel implant design during a simulated OI process. The paper also proposes a concept of an energy index (the E-index), which is formulated based on the normalized magnitude. To illustrate the potential of the E-index, this paper reports on changes in the vibrational behaviors of a 133 mm long amputated artificial femur model and implant system, with epoxy adhesives applied at the interface to simulate the OI process. The results show a significant variation in the magnitude of the colormap against curing time. The study also shows that the E-index was sensitive to the interface stiffness change, especially during the early curing process. These findings highlight the feasibility of using the vibration analysis technique and the E-index to quantitatively monitor the osseointegration process for future improvement on the efficiency of human health monitoring and patient rehabilitation.

Modal Frequencies Associations with Musculoskeletal Components of Human Legs for Extracorporeal Bone Healing Assessment Based on a Vibration Analysis Approach.

Reliable and quantitative assessments of bone quality and fracture healing prompt well-optimised patient healthcare management and earlier surgical intervention prior to complications of nonunion and malunion. This study presents a clinical investigation on modal frequencies associations with musculoskeletal components of human legs by using a prototype device based on a vibration analysis method. The findings indicated that the first out-of-plane and coupled modes in the frequency range from 60 to 110 Hz are associated with the femur length, suggesting these modes are suitable quantitative measures for bone evaluation. Furthermore, higher-order modes are shown to be associated with the muscle and fat mass of the leg. In addition, mathematical models are formulated via a stepwise regression approach to determine the modal frequencies using the measured leg components as variables. The optimal models of the first modes consist of only femur length as the independent variable and explain approximately 43% of the variation of the modal frequencies. The subsequent findings provide insights for further development on utilising vibration-based methods for practical bone and fracture healing monitoring.

Detection of Defects in Geomembranes Using Quasi-Active Infrared Thermography.

High-density polyethylene geomembranes are employed as covers for the sewage treatment lagoons at Melbourne Water Corporation's Western Treatment Plant, to harvest the biogas produced during anaerobic degradation, which is then used to generate electricity. Due to its size, inspecting the cover for defects, particularly subsurface defects, can be challenging, as well as the potential for the underside of the membrane to come into contact with different substrates, viz. liquid sewage, scum (consolidated solid matter), and biogas. This paper presents the application of a novel quasi-active thermography inspection method for subsurface defect detection in the geomembrane. The proposed approach utilises ambient sunlight as the input thermal energy and cloud shading as the trigger for thermal transients. Outdoor laboratory-scale experiments were conducted to study the proposed inspection technique. A pyranometer was used to measure the intensity of solar radiation, and an infrared thermal camera was used to measure the surface temperature of the geomembrane. The measured temperature profile was analysed using three different algorithms for thermal transient analysis, based on (i) the cooling constant from Newton's law of cooling, (ii) the peak value of the logarithmic second derivative, and (iii) a frame subtraction method. The outcomes from each algorithm were examined and compared. The results show that, while each algorithm has some limitations, when used in combination the three algorithms could be used to distinguish between different substrates and to determine the presence of subsurface defects.

Towards a Non-Invasive Technique for Healing Assessment of Internally Fixated Femur.

The lack of a quantitative method to adequately assess fractured bone healing that has undergone fixation limits prognostic capabilities on patients' optimal return to work. This paper addresses the use of vibrational analysis to monitor the state of healing of a plate-screw fixated femur and supplement the current clinical radiographic assessment. This experimental study involves an osteotomised composite femur specimen enclosed by modelling clay to simulate the damping effect of overlying soft tissues. Epoxy adhesives are applied to the fractured region and to simulate the healing process. With the instrumentation described, the cross-spectrum and coherence are obtained and analysed in the frequency domain over a period of time. The results suggest that it is crucial to analyse the cross-spectrum and proposed healing index to quantitatively assess the stages of healing. The results also show that the mass loading effect due to modelling clay did not influence the proposed healing assessment technique. The findings indicate a potential non-intrusive technique to evaluate the healing of fractured femur by utilising the vibrational responses.

A Quantitative Approach for the Bone-implant Osseointegration Assessment Based on Ultrasonic Elastic Guided Waves.

Quantitative and reliable monitoring of osseointegration will help further evaluate the integrity of the orthopaedic construct to promote novel prosthesis design and allow early mobilisation. Quantitative assessment of the degree or the lack of osseointegration is important for the clinical management with the introduction of prosthetic implants to amputees. Acousto-ultrasonic wave propagation has been used in structural health monitoring as well as human health monitoring but so far has not extended to osseointegrated implants or prostheses. This paper presents an ultrasonic guided wave approach to assess the osseointegration of a novel implant. This study explores the potential of integrating structural health monitoring concepts into a new osseointegrated implant. The aim is to demonstrate the extension of acousto-ultrasonic techniques, which have been widely reported for the structural health monitoring of engineering structures, to assess the state of osseointegration of a bone and implant. To illustrate this potential, this paper will report on the experimental findings which investigated the unification of an aluminium implant and bone-like geometry surrogate. The core of the test specimen is filled with silicone and wrapped with plasticine to simulate the highly damped cancellous bone and soft tissue, respectively. To simulate the osseointegration process, a 2-h adhesive epoxy is used to bond the surrogate implant and a bone-like structure. A series of piezoelectric elements are bonded onto the surrogate implant to serve as actuators and sensors. The actuating piezoelectric element on an extramedullary strut is excited with a 1 MHz pulse signal. The reception of the ultrasonic wave by the sensing elements located on the adjacent and furthest struts is used to assess the integration of this implant to the parent bone structure. The study shows an Osseointegration Index can be formulated by using engineering and acousto-ultrasonic methods to measure the unification of a bone and implant. This also highlights a potential quantitative evaluation technique regardless of bone-implant geometry and soft tissue damping.

Experimental and Computational Studies on the Scattering of an Edge-Guided Wave by a Hidden Crack on a Racecourse Shaped Hole.

Reliable and quantitative non-destructive evaluation for small fatigue cracks, in particular those in hard-to-inspect locations, is a challenging problem. Guided waves are advantageous for structural health monitoring due to their slow geometrical decay of amplitude with propagating distance, which is ideal for rapid wide-area inspection. This paper presents a 3D laser vibrometry experimental and finite element analysis of the interaction between an edge-guided wave and a small through-thickness hidden edge crack on a racecourse shaped hole that occurs, in practice, as a fuel vent hole. A piezoelectric transducer is bonded on the straight edge of the hole to generate the incident wave. The excitation signal consists of a 5.5 cycle Hann-windowed tone burst of centre frequency 220 kHz, which is below the cut-off frequency for the first order Lamb wave modes (SH1). Two-dimensional fast Fourier transformation (2D FFT) is applied to the incident and scattered wave field along radial lines emanating from the crack mouth, so as to identify the wave modes and determine their angular variation and amplitude. It is shown experimentally and computationally that mid-plane symmetric edge waves can travel around the hole's edge to detect a hidden crack. Furthermore, the scattered wave field due to a small crack length, a, (compared to the wavelength λ of the incident wave) is shown to be equivalent to a point source consisting of a particular combination of body-force doublets. It is found that the amplitude of the scattered field increases quadratically as a function of a/λ, whereas the scattered wave pattern is independent of crack length for small cracks a << λ. This study of the forward scattering problem from a known crack size provides a useful guide for the inverse problem of hidden crack detection and sizing.