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Examines the use of acoustic emission techniques for monitoring part mating during the assembly process. The frequency recorded during a peg insertion is compared with known frequencies of successful peg insertion by a microcomputer. This allows unsuccessful alignment to be readjusted which being monitored by a digital sound analyzer. Outlines the concept of part mating which is based on the peg‐in‐hole theory developed by Simunovic and describes an acoustic emission monitoring system. Concludes that acoustic monitoring provides a relatively low cost, low complexity system for part mating monitoring but may have limitation in manufacturing environments where there is excessive background noise or machine part vibration.

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/

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.

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.

Outlines the need for the development of a top‐face sensor system to ensure consistent penetration during mechanized arc and laser welding. Lists the characteristics such a system should incorporate and describes current sensor systems which might be adapted. These include ultrasonic techniques, acoustic emission techniques, weld pool sag sensing techniques, weld pool oscillation sensing, weld pool viewing techniques, and thermal sensing techniques. Gives the range of application and accuracy of control of the reported systems and concludes that there is currently no one system, commercially available, which satisfies all the requirements of the ideal system.

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 acousto-ultrasonic approach is used for propagating stress waves through different configurations of CORTEN steel specimens. The propagated waves are recorded and analysed by piezoelectric sensors. The purpose of the study is to study the characteristics of the CORTEN steel by analysing the propagated waves.

To investigate the attenuation in acoustic wave propagation due to the corrosion formation in CORTEN steel specimens and to train a neural network model to classify the attenuated acoustic waves automatically.

Due to the corrosion formation in CORTEN steel specimens, attenuation is observed in amplitude, energy, counts and duration of the propagated waves. When the waves are analysed in their time-frequency characteristics, attenuation is observed in their frequency and spectral energy.

The corrosion formation in CORTEN steel can automatically be analysed by using the acousto-ultrasonic approach and the trained deep learning neural network.

In civil engineering construction, the reinforced concrete (RC) structure is generally used and exposed to fatigue loading as it is in service. The assessment of the RC structure is required to maintain the service life of the structure.

This paper presents the behaviour of RC beam specimens under increasing maximum fatigue loading until failure. Simultaneously the acoustic emission (AE) was recorded. Twelve phases of maximum fatigue loading at Stage 1 and Stage 2 were applied to the beam with the frequency of 1 Hz and 5,000 load cycles were applied for each load phase. Two AE parameters were analysed and discussed, namely average frequency and rise angle value at CH4 and CH5.

The results found that the load and crack are closely related to the AE activities in the RC beam specimen when subjected to increasing fatigue loading.

To investigate the AE characteristics of RC beam specimens subjected to 12 phases of maximum fatigue loading using the average frequency and rise angle value.

The purpose of this paper is to examine the effect of reciprocating compressor speeds and valve conditions on the roor-mean-square (RMS) value of burst acoustic emission (AE) signals associated with the physical motion of valves. The study attempts to explore the potential of AE signal in the estimation of valve damage under varying compressor speeds.

This study involves the acquisition of AE signal, valve flow rate, pressure and temperature at the suction valve of an air compressor with speed varrying from 450 to 800 rpm. The AE signals correspond to one compressor cycle obtained from two simulated valve damage conditions, namely, the single leak and double leak conditions are compared to those of the normal valve plate. To examine the effects of valve conditions and speeds on AE RMS values, two-way analysis of variance (ANOVA) is conducted. Finally, regression analysis is performed to investigate the relationship of AE RMS with the speed and valve flow rate for different valve conditions.

The results showed that AE RMS values computed from suction valve opening (SVO), suction valve closing (SVC) and discharge valve opening (DVO) events are significantly affected by both valve conditions and speeds. The AE RMS value computed from SVO event showed high linear correlation with speed compared to SVC and DVO events for all valve damage conditions. As this study is conducted at a compressor running at freeload, increasing speed of compressor also results in the increment of flow rate. Thus, the valve flow rate can also be empirically derived from the AE RMS value through the regression method, enabling a better estimation of valve damages.

The experimental test rig of this study is confined to a small pressure ratio range of 1.38–2.03 (free-loading condition). Besides, the air compressor is assumed to be operated at a constant speed.

This study employed the statistical methods namely the ANOVA and regression analysis for valve damage estimation at varying compressor speeds. It can enable a plant personnel to make a better prediction on the loss of compressor efficiency and help them to justify the time for valve replacement in future.

There has been a sustained interest over the past couple of decades in developing sophisticated leak detection techniques (LDTs) that are economical and reliable. Majority of current commercial LDTs are acoustics based and they are not equally suitable to all pipe materials and sizes. There is also limited knowledge on the comparative merits of such acoustics-based leak detection techniques (ALDTs). The purpose of this paper is to review six commercial ALDTs based on four decisive criteria and subsequently develop guidance for the optimal selection of an ALDT.

Numerous publications and field demonstration reports are reviewed for evaluating the performance of various ALDTs in this study to inform their optimal selection using an integrated multi-criteria decision analysis (MCDA) framework. The findings are validated using interviews of water utility experts.

The study approach and the findings will have a broad impact on the water utility industry by identifying a suite of suitable ALDTs for a range of typical application scenarios. The evaluated ALDTs include listening devices, noise loggers, leak-noise correlators, free-swimming acoustic, tethered acoustic, and acoustic emissions. The evaluation criteria include cost, reliability, access requirements, and the ability to quantify leakage severity. The guidance presented in this paper will support efficient decision making in water utility management to minimize pipeline leakage.

This study attempts to address the problem of severe dearth of performance data for pipeline inspection techniques. Performance data reported in the published literature on various ALDTs are appropriately aggregated and compared using a MCDA, while the uncertainty in performance data is addressed using the Monte Carlo simulation approach.