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The purpose of this paper is to provide a method to predict the situation of a loaded element in the compressive stress curve to prevent failure of crucial elements in load-bearing masonry walls and to propose a material model to simulate a compressive element successfully in Abaqus software to study the structural safety by using non-linear finite element analysis.

A Weibull distribution function was rewritten to relate between failure probability function and axial strain during uniaxial compressive loading. Weibull distribution parameters (shape and scale parameters) were defined by detected acoustic emission (AE) events with a linear regression. It was shown that the shape parameter of Weibull distribution was able to illustrate the effects of the added fibers on increasing or decreasing the specimens’ brittleness. Since both Weibull function and compressive stress are functions of compressive strain, a relation between compressive stress and normalized cumulative AE hits was calculated when the compressive strain was available. By suggested procedures, it was possible to monitor pretested plain or random distributed short fibers reinforced adobe elements (with AE sensor and strain detector) in a masonry building under uniaxial compression loading to predict the situation of element in the compressive stress‒strain curve, hence predicting the time to element collapse by an AE sensor and a strain detector. In the predicted compressive stress‒strain curve, the peak stress and its corresponding strain, the stress and strain point with maximum elastic modulus and the maximum elastic modulus were predicted successfully. With a proposed material model, it was illustrated that the needed parameters for simulating a specimen in Abaqus software with concrete damage plasticity were peak stress and its corresponding strain, the stress and strain point with maximum elastic modulus and the maximum elastic modulus.

The AE cumulative hits versus strain plots corresponding to the stress‒strain curves can be divided into four stages: inactivity period, discontinuous growth period, continuous growth period and constant period, which can predict the densifying, linear, non-linear and residual stress part of the stress‒strain relationship. By supposing that the relation between cumulative AE hits and compressive strain complies with a Weibull distribution function, a linear analysis was conducted to calibrate the parameters of Weibull distribution by AE cumulative hits for predicting the failure probability as a function of compressive strain. Parameters of m and θ were able to predict the brittleness of the plain and tire fibers reinforced adobe elements successfully. The calibrated failure probability function showed sufficient representation of the cumulative AE hit curve. A mathematical model for the stress–strain relationship prediction of the specimens after detecting the first AE hit was developed by the relationship between compressive stress versus the Weibull failure probability function, which was validated against the experimental data and gave good predictions for both plain and short fibers reinforced adobe specimens. Then, the authors were able to monitor and predict the situation of an element in the compressive stress‒strain curve, hence predicting the time to its collapse for pretested plain or random distributed short fibers reinforced adobe (with AE sensor and strain detector) in a masonry building under uniaxial compression loading by an AE sensor and a strain detector. The proposed model was successfully able to predict the main mechanical properties of different adobe specimens which are necessary for material modeling with concrete damage plasticity in Abaqus. These properties include peak compressive strength and its corresponding axial strain, the compressive strength and its corresponding axial strain at the point with maximum compressive Young’s modulus and the maximum compressive Young’s modulus.

The authors were not able to decide about the effects of the specimens’ shape, as only cubic specimens were chosen; by testing different shape and different size specimens, the authors would be able to generalize the results.

The paper includes implications for monitoring techniques and predicting the time to the collapse of pretested elements (with AE sensor and strain detector) in a masonry structure.

This paper proposes a new method to monitor and predict the situation of a loaded element in the compressive stress‒strain curve, hence predicting the time to its collapse for pretested plain or random distributed short fibers reinforced adobe (with AE sensor and strain detector) in a masonry building under uniaxial compression load by an AE sensor and a strain detector.

The smaller sizes of current electronic devices suggest the feasibility of creating a smart composite structure using piezoelectric implant to monitor in-situ and in-service conditions the life of civil and aerospace structures. Piezoelectric (lead zirconate-titanate (PZT)) sensors embedded within laminates composites represent a new branch of engineering with the potential to greatly enhance the confidence and use of these materials. The paper aims to discuss these issues.

This study presents a health monitoring of laminates composites materials incorporating by piezoelectric (PZT) implant using acoustic emission (AE) technique. A series of specimens of laminate composite with and without embedded piezoelectric were tested in three-point bending tests in static and creep loading while continuously monitoring the response by the AE technique. The AE signals were analysed using the classification k-means method in order to identify the different damages and to follow the evolution of these various mechanisms for both types of materials (with and without embedded sensors).

Comparing embedded sensor to sensor mounted on the surface, the embedded sensor showed a much higher sensitivity. It was thus verified that the embedded AE sensor had great potential for AE monitoring in fibre reinforced composites structures.

Piezoelectric implant to monitor in-situ and in-service conditions the life of civil and aerospace structures.

The purpose of this paper is to present the results of acoustic emission (AE) and ultrasonic inspection of two H₂S storage tanks carried out in a heavy water plant, in order to characterize point type defects observed during earlier ultrasonic inspection and to ensure that these defects are not growing during hydrotesting of the tanks.

Using multiple AE sensors and AE source location methodology, the entire tank could be covered to detect and locate any dynamic sources of AE associated with local plastic deformation and/or growing discontinuities from any part of the tank during the hydrotest. For confirmation of the results obtained by AE, ultrasonic inspection on the tanks and on virgin plates from which the tanks were manufactured, were carried out.

The AE signals generated during first pressurisation are attributed to the micro yielding of the material of the tanks. A few scattered AE events were observed at a few locations during the hydrotesting of the tanks and these are due to structural and rubbing noise. During hold periods and repressurising cycle of the hydrotesting, no detectable AE events were observed and this confirmed the absence of any growing discontinuity in the tanks during the hydrotesting. Ultrasonic inspection on the tanks and on virgin plates confirmed that the point type defects detected are manufacturing defects and not formed during service life.

The combined results from AE and ultrasonic techniques confirmed the structural integrity of the tanks and ensured their healthiness for continued operation.

The paper brings out the use of AE and ultrasonic techniques for monitoring hydrotesting of storage tanks of a heavy water plant. The storage tanks where point type defect indications were reported during previous ultrasonic inspection and whether these defects are growing during hydrotesting of the tanks or not, were required to be known before the tanks are put in to further service. AE signals collected during pressurising and repressurising cycles of the hydrotest and subsequent inspection by ultrasonic confirmed the vessels to be free from growing defects during the hydrotest and provided baseline data for future inspection.

This paper aims to focus on investigating the failure mode of fused deposition modeling (FDM) fabricated parts by using acoustic emission (AE) technique.

Considering the special prototyping way of FDM, the failure modes of FDM-fabricated parts were investigated experimentally. One test was carried out and the other two describe what has been observed on this basis. Acoustic emissions are obtained during the tensile process. AE features of peak frequency, energy and amplitude are extracted and preliminarily analyzed. Then, the unsupervised clustering method of k-means is applied to explore the relationship between the failure modes and the AE signals.

Failure modes of filament debonding and breakage can be successfully recognized by the pattern recognition technique of k-means.

The results obtained can help us understand the failure process of FDM printed parts. This will provide an available monitoring method in the application of FDM-fabricated parts.

This paper has investigated and characterized the failure modes of FDM fabricated parts for the first time.

This paper aims to study acoustic emission (AE) propagation characteristics by a crack under a moving heat source, which mainly provides theoretical basis and method for the actual crack detection during welding process.

The paper studied the AE characteristics in welding using thermoelastic theory, which investigates the dynamical displacement field caused by a crack and the welding heating effect. In the calculation model, the crack initiation and extension are represented by moment tensor as the AE source, and the welding heat source is the Gauss heat flux distribution. The extended finite element method (XFEM) is implemented to calculate and solve the AE response of a thermoelastic plate with a crack during the welding heating effect. The wavelet transform is applied to the time–frequency analysis of the AE signals.

The paper provides insights about the changing rule of the acoustic radiation patterns influenced by the heating effect of the moving heat source and the AE signal characteristics in thermoelastic plate by different crack lengths and depths. It reveals that the time–frequency characteristics of the AE signals from the simulation are in good agreement with the theoretical ones. The energy ratio of the antisymmetric mode A0 to symmetric mode S0 is a valuable quantitative inductor to estimate the crack depth with a certain regularity.

This paper mainly discusses the application of XFEM to calculate and analyze thermoelastic problems, and has presented few cases based on a specified configuration. Further work will focus on the calculation and analysis under different plate configurations and conditions, which is to obtain more interesting and general conclusions for guiding practice.

The paper is a successful application of XFEM to solve the problem of AE response of a crack in the dynamic welding inhomogeneous heating effect. The paper provides an effective way to obtain the AE signal characteristics in monitoring the welding crack.

The purpose of this paper is to investigate the monitoring of the friction condition of mechanical seals.

Acoustic emission signals from the friction of the seal end face were obtained, and their bispectral characteristics were extracted. The variation of non-Gaussian information with the degree of friction was investigated, and by combining bispectral characteristics with information entropy, a bispectral entropy index was established to represent the friction level of the seal end face.

In the start-up stage, the characteristic frequency amplitude of the micro-convex body contact is obvious, the friction of the end face is abnormal, the complexity of the system increases in a short time and the bispectral entropy rises continuously in a short time. In the stable operation stage, the characteristic frequency amplitude of the micro-convex body contact varies with the intensity of the seal face friction, the seal face friction is stable and the bispectral entropy fluctuates up and down for a period of time.

The bispectral analysis method is applied to the seal friction monitoring, the seal frequency domain characteristics are extracted, the micro-convex body contact characteristic frequency is defined and the bispectral entropy characteristic index is proposed, which provides a certain theoretical basis for the mechanical seal friction monitoring.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0242/

The purpose of this paper is to determine the feasibility of identifying the creep rupture of reactor cladding tubes using acoustic emission technique (AET).

The creep rupture tests were carried out by pressuring stainless steel capsules upto 6 MPa at room temperature and then heating continuously in a furnace upto rupture. The acoustic emission (AE) signals generated during the creep rupture tests were recorded using a 150 kHz resonant sensor and analysed using AE Win software.

When rupture occurs in the pressurized capsule tube representing the cladding tube, AE sensor attached to a waveguide captures the mechanical disturbance from the capsule and these data can be advantageously used to identify the creep rupture event of the cladding tube.

The creep rupture data of fuel clad tube is very important in design and for smooth operation of nuclear reactors without fuel pin failure in reactors.

AE is an advanced non-destructive evaluation technique. This technique has been successfully applied for on-line monitoring of creep rupture of the reactor cladding tube which otherwise could be detected by thermocouple readings only.

Numerous studies have been conducted in the field of acoustic emission (AE) technology applied to rotating machine fault diagnosis. Principally, most of the work to date has been focused on correlating AE activity to the defect condition on rolling element bearings with limited investigations on hydrodynamic bearings. This paper aims to address this issue.

This paper presents experimental tests aimed at understanding the influence of speed and load on generation of AE in a hydrodynamic bearing.

The research presented shows that the power losses associated which hydrodynamic bearing has a direct influence on the generation of AE.

Further research should include the application of the proposed methodology on a broad range of operational machines employing hydrodynamic bearings.

In developing the AE technology for monitoring hydrodynamic bearings operated under variable speed and load conditions, it is essential that a relationship between the operational variables and the generation of AE is established, and this paper explores such a relationship.

The paper presents the first known correlation between AEs and the operating parameters of a hydrodynamic bearing.

This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement.

In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built.

The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains.

The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

The aim of the present study is to investigate the mechanical behaviour of cross‐ply laminates under static tensile and buckling loading. Different cross‐ply laminates constituting of carbon fibers (CFRP), hybrid fibers (HFRP) and glass fibers (GFRP) in an epoxy matrix were considered. This work is also interested in identifying and characterizing the local damage in the composites with the use of acoustic emission method (AE).

The cross‐ply laminates are differentiated by the stacking sequences, thickness of 90° oriented layers and reinforcement. They are subjected to the static tensile and buckling load. The damage investigation is reached by the analysis of acoustic emission signals collected from static buckling tests.

The results show the effects of reinforcement type, stacking sequences and thicknesses ratio of 90° and 0° layers on the stiffness, failure load and displacement. A cluster analysis of acoustic emission data is achieved and the results are correlated to the damage mechanism of specimens under buckling tests.

The analysis of acoustic emission signals collected from static buckling tests under loading levels of 40, 60 and 100 per cent of the static failure load allows the damage investigation in cross‐ply laminates.