Acoustic Emission Signal Characteristics Research Articles

Acoustic emission sources localization of laser cladding metallic panels using improved fruit fly optimization algorithm-based independent variational mode decomposition

Laser cladding technology has recently become an essential issue in engineering research and application. Specifically, acoustic emission (AE)-based structural health monitoring (SHM) of metallic panel laser cladding process is a hot research direction in the field of mechanical intelligent fault diagnosis. However, owing to the strong non-stationary characteristics of laser cladding AE signal, it is generally composed of multiple components (e.g. environmental noise, aperiodic pulses and other external signal), traditional AE source localization methods are generally difficult to localize and characterize AE sources in plate-like structure that has complex geometric features, such as laser cladding operations. To address this issue, a new method for the localization of laser cladding AE sources known as improved fruit fly optimization algorithm-based independent variational mode decomposition (IFOA-IVMD) is proposed in this paper, which can optimize effectively the inside parameters (i.e. mode number K and penalty parameter α) of IVMD and decompose adaptively the original AE signal into a number of intrinsic mode function (IMF) components. To validate the performance of the proposed approach, a 316L stainless steel is utilized to collect AE signals during the laser cladding experiments. Moreover, comparisons with three conventional AE source location methods (i.e. PAC AE acquisition system, Newton’s method and multiple cross-correlation based on Geiger algorithm) and two representative approaches (i.e. deep learning and Bayesian methodology) for localizing AE sources generated by complex metallic structures are conducted, and the comparison results verify the effectiveness and advantage of the proposed approach in the localization of laser cladding AE sources. Finally, the generalization of the proposed approach is evaluated for typical scenarios in which laser cladding AE sources are generated by different processing parameters. The results demonstrate the effectiveness of the proposed approach for AE-based SHM of plate-like structures.

Experimental characterisation of laser surface remelting via acoustic emission wavelet decomposition

This paper presents a novel technique of monitoring laser surface remelting (LSR) via measurements of process generated acoustic emission (AE). The LSR conditions include a variable laser power level and an ambient air or argon 5.0 inert gas atmosphere. The microstructure and microhardness of the remelted surface layer are evaluated. The recorded AE signal datasets are analysed via the wavelet decomposition technique. The resulting energy and energy proportions of approximation and detail coefficients are calculated. The decomposed AE signal features are evaluated in correlation with the LSR process conditions. A supervised machine learning cubic support vector machine classifier type is used for the classification of laser pulses. The experimental results show an overall 98% classification accuracy into the corresponding LSR laser power level and atmosphere conditions, confirming the utility of monitoring the LSR process and the resulting material surface layer characteristics via the AE wavelet decomposition technique.

Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

Acoustic emission signal characteristics and its critical slowing down phenomenon during the loading process of water-bearing sandstone

In deep underground engineering, the rock mass is often in a water-bearing state. Understanding the acoustic emission (AE) signal characteristics of water-bearing rock during loading process plays a crucial role in the monitoring and prediction of dynamic disasters in deep underground engineering. Therefore, sandstone samples with varying water contents were subjected to a series of uniaxial compression experiments, and AE signals were simultaneously collected. The mechanical properties and AE signal features of water-bearing sandstone were studied, and the influence mechanism of water on AE signals was expounded. Then, with reference to the critical slowing down theory, both the autocorrelation coefficient and the variance of the AE energy sequence were calculated, and the precursor characteristics of sandstone failure with varying water contents were discussed. It was pointed out that there was a critical slowing down phenomenon in AE signal. Compared with autocorrelation coefficient, variance is more sensitive to large-scale fracture of rock and has less false signal. Therefore, the sudden increase of variance can serve as an effective precursor that indicates rock failure. Moreover, for a sandstone sample with a higher the water content, the precursor point occurs earlier and appears to be more notable.

Analytical model and spectral characteristics of acoustic emission signal produced by localized fault of rolling element bearing

The accurate description of acoustic emission signals produced by the localized fault of a rolling element bearing plays an important role in its feature extraction and analysis. This paper analyzes the excitation mechanisms and develops the analytical model of acoustic emission signals produced when the rolling element bearing passes across the localized fault on the inner or outer race. Based on the analytical model, the spectral characteristics are discussed substantially. Simulations and experiments are carried out to validate the efficacy of the model developed in the paper. The experimental results show that the response signal thus produced has two parts. The first one is produced by the entry of the rolling element bearing, while the other is produced by the departure of the rolling element bearing. The energy of both parts is concentrated around the resonance frequency of the acoustic emission transducer. Generally, the interval of adjacent acoustic emission events is not equivalent to each other and the corresponding spectrum is continuous in the high frequency band.

Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

Evaluation of alkali–silica reaction damage in concrete by using acoustic emission signal features and damage rating index: damage monitoring on concrete prisms

Evaluation of alkali–silica reaction damage in concrete by using acoustic emission signal features and damage rating index: damage monitoring on concrete prisms

Cracking mechanism and strength criteria evaluation of granite affected by intermediate principal stresses subjected to unloading stress state

Extensive true-triaxial unloading tests are conducted on rectangular Miluo granite specimens to investigate their crack propagation behavior and peak unloading strength properties. Experimental results demonstrate that their failure mode transforms from shear to slabbing with the increase in intermediate principal stresses σ2. Under a lower value of σ2, the dominant failure mode represented by the macro shear band is composed of several meso-extensional cracks parallel to the maximum principal stress σ1, and the fracturing process indicates intensive dislocation and slide owing to the normal force acting on extensional cracks. However, the increase in σ2 exacerbates the extensional cracks and further propagates them toward the end of the specimen along the direction of σ1, if σ3 is unloaded to 0. This is primarily due to the enhanced ability to resist mutual slide and squeeze among extensional cracks in the shear band, and the promotion of crack initiation and propagation in the unloading direction (σ3) owing to the provided free surface. The transformation of the cracking mode is revealed via three-dimensional combined finite/discrete element modeling, scanning electron microscope observations, and acoustic emission signal feature (average frequency, rise angle, Acoustic emission (AE) counts, and accumulated AE energy) analysis. The peak unloading strength exhibits an initial increase followed by a decrease as a function of σ2. Four rock-strength criteria are employed to evaluate the true-triaxial data with emphasis on predictability in practical applications and accuracy between best-fitting functions (experimental data) and theoretical (predicted) solutions. It is demonstrated that modified the Wiebols–Cook criterion and modified Lade criterion cannot accurately estimate the unloading strength throughout the true-triaxial data. Although the Mogi 1971 criterion fits the experimental data (higher correlation coefficients) well, it cannot be correlated to strength parameters (cohesion and internal frictional angle). Hence, it fails to predict the real strength values if complex true-triaxial unloading tests are not performed. The linear Mogi criterion is recommended for predicting the true-triaxial unloading strength of granite.

A MICROSTRUCTURE-BASED MECHANISTIC MODEL FOR BONE SAWING: PART 2 - ACOUSTIC ENERGY RATE PREDICTIONS

Abstract Part-2 of this paper is focused on modeling the acoustic emission (AE) energy rate as a function of the specific cortical bone microstructures (viz., osteon, interstitial matrix, lamellar bone, and woven bone) and the depth-of-cut encountered by the bone sawtooth. First, the AE signal characteristics from the sawing experiments (in Part-1) are related to the pure haversian and pure plexiform regions of the cut. Using the cutting force predictions from Part-1 as input, the AE energy rate is then modeled in terms of the energies dissipated in the shearing and ploughing zones encountered by the rounded cutting edge. For this calculation, the rounded edge geometry of the sawtooth is modeled as a combination of (i) shear-based cutting from a negative rake cutting tool; and (ii) ploughing deformation from a round-nose indenter. The spread seen in the AE energy rate is captured by modeling the variations in sawed surface height profile, tool cutting edge geometry, and porosity of the bone. The model calibration and validation protocols are similar to those used in Part-1. The validated AE model is useful for process planning both in terms of its ability to predict AE energy rate trends and cutting force variations, based on the differences in the underlying bone microstructures.

Structural damage monitoring for metallic panels based on acoustic emission and adaptive improvement variational mode decomposition–wavelet packet transform

The metallic panel acoustic emission signal with strong non-stationary properties is normally composed of multiple components (e.g. impulses, background noise, and other external signal), where impulses relevant to metallic panel are easily contaminated by background noise and other external signal, making it difficult to excavate the inherent acoustic emission signal features. To address this issue and achieve the damage monitoring of metallic panels based on acoustic emission technology, a new scheme based on adaptive improvement variational mode decomposition–wavelet packet transform is developed for extracting acoustic emission signal features of metallic panels. Specifically, three different dimensions of Q235B steel plates are utilized to collect acoustic emission signal during three-point bending experiments, to evaluate the effectiveness of the proposed approach and to investigate the influence of size effect on the acoustic emission signal characteristics. In addition, the transient process and centroid frequency distribution of each damage stage are investigated, and the internal structure variations in the bending damage process are detected by scanning electron microscopy inspection. Moreover, the generalization of the proposed damage monitoring method is evaluated for plate-like structures that have complex geometric features, such as welds. The results demonstrate the effectiveness of the proposed method for acoustic emission–based structural health monitoring of metallic plate-like structures.

Acoustic emission signal clustering in CFRP laminates using a new feature set based on waveform analysis and information entropy analysis

Acoustic emission (AE) for structural health monitoring of fiber-reinforced polymers (FRP) has been under extensive study in past decades. Many of the available methods rely on using the conventional features of AE signals for clustering. These clusters are then related to a specific failure mechanism based on their behaviors. The conventional AE features are derived from a portion of the signal waveform that passes through a pre-determined threshold and is heavily affected by attenuation. Therefore, recent studies on AE are more focused on waveform analysis. A key parameter when analyzing the waveform distribution is the selection of appropriate bin width. This study discusses the choice of an optimum bin width for waveform analysis. This parameter is then shown to be well correlated to the conventional threshold-dependent features of AE signals. The bin width is then used as a time-domain representation of the waveform and is used with the peak frequency for signal clustering. A series of tensile tests are performed on cross-ply and quasi-isotropic open-hole carbon FRP (CFRP) specimens. The results show that AE signal clustering using these features outperform clustering performance using conventional AE features. This approach is shown to divide signals into two clusters; a cluster with matrix dominated signals and a cluster with fiber dominated signals. The information entropy of signals in each cluster is evaluated and compared to the information entropy of noise signals.

Acoustic emission signal characteristics of maraging steel 250 pressure vessel during a hydraulic qualification test

ABSTRACT High-strength aero-space grade maraging steels finding an increased use in industry for manufacturing of pressure vessels. Structural integrity assessment of such pressure vessels is an important and yet challenging task. Several researchers have attempted to quantify failure or structural integrity of similar pressure vessels using acoustic emission (AE) but a one stop criterion to assess quality of pressure vessels has not been evolved. In this study, an integrated approach in evaluating behaviour of maraging steel specimens has been carried out. AE Behaviour during tensile deformation of maraging steel specimens studied with respect to AE parameters. Two types of specimens viz. type A and type B data are presented in this manuscript. In type A, failure was due to rupture caused by inherent defects and in type B, failure was predominantly due to yielding. Further, an effort was put forth to compare such AE Parameters acquired during qualification burst test of a maraging steel pressure vessel. The pressure vessel that was burst also exhibited type A and type B behaviour at two different zones on the vessel. A reasonable match in the AE behaviour of specimens to that of a pressure vessel has been observed. The promulgated AE criteria have the potential to identify a real-time defect growth during a pressure test.

RETRACTED: Elastic wave methods for non-destructive damage diagnosis in the axisymmetric viscoelastic cylindrical waveguide

The popular technique for damage detection in a cylindrical waveguide is the ultrasonic guided wave propagation based acoustic emission (AE) monitoring method. It comes under the dynamic non-destructive evaluation (NDE) category, primarily established on the fluctuations in AE signal features to detect the structural damage in real-time. In this paper, the numerical modeling of wave scattering by a structural discontinuity in axisymmetric high strength steel wire - viscoelastic waveguide medium for analyzing the wave interaction by inhomogeneity is presented. The hybrid standard three-dimensional finite element (3D FE) method and semi-analytical finite element (SAFE) method for numerical analysis of guided ultrasonic wave propagation are employed. For the simulation of waveguide media with arbitrary defect shapes, the hybrid 3D FE-SAFE method can be used. The basic idea is to express the frequency response of the cross-section at the two ends of the 3D FE part as a modal superposition calculated by the semi-analytical method. A case study on a steel wire is conducted to calculate the displacement response under a narrow-band external force excitation. The AE signal characteristics are used to understand the wave interaction of the pitting corrosion and tapered section in steel wire. The investigation of the amplitude of elastic waves passing through the discontinuity for the both undamped and damped cylindrical waveguide is proposed to understand the distribution of energy at points of reflections or refraction and the ratio between the amplitudes arriving at that point. Another contribution of the research work includes the robust algorithm for wave reflection and scattering based on the hybrid element method, which can effectively improve the calculation competence using an internal degree of freedom condensation and modal acceleration. It is suitable for models with multiple damages in the 3D FE area, and the accuracy of the results on wave-damage interactions can be achieved. The recommended method can be used to distinguish damages present in a viscoelastic cylindrical waveguide.

Flexural ductility and crack-controlling capacity of polypropylene fiber reinforced ECC thin sheet with waste superfine river sand based on acoustic emission analysis

Engineered cementitious composite (ECC) with waste superfine river sand (WSRS) and polypropylene (PP) fiber is an economical and sustainable cement-based composite material (WSRSPP-ECC), which has the deformation hardening and multi-cracking characteristics, and affinity for engineering promotion. In this study, acoustic emission (AE) technology was used to monitor the flexural damage process of WSRSPP-ECC thin sheets with different deformability. Based on AE signal features, the damage development and accumulation of WSRSPP-ECC thin sheet under flexural load were analyzed. The results showed that AE signal parameters can capture and describe the transition of different damage stages of WSRSPP-ECC thin sheets. The b-value analysis further showed that the internal micro-cracks characteristics of WSRSPP-ECC thin sheets with various deformability were different in the flexural damage process, which was mainly related to the ability of fibers controlling stable cracking. In view of the smaller fluctuation of AE signals in the first two stages of flexural damage process, three modified indirect AE signal feature parameters including average energy, average waveform coefficient and average frequency were proposed. Then the quantitative relationship models between these three indirect AE signal parameters and flexural ductility as well as crack-controlling capacity of WSRSPP-ECC thin sheet were established. Moreover, through the economic analysis, it is corroborated that WSRSPP-ECC has the higher comprehensive cost performance, and it is a new economical cement-based material suitable for practical engineering application. The production of WSRSPP-ECC by replacing PVA fiber and silica sand with PP fiber and WSRS can not only save cost, and also keep the physical performances, which effectively solves the problems of river channel sedimentation and blocking.

Acoustic emission characteristics of used 70 MPa type IV hydrogen storage tanks during hydrostatic burst tests

Currently, the periodic inspection of composite tanks is typically achieved via hydrostatic test combined with internal and external visual inspections. Acoustic emission (AE) technology demonstrates a promising nondestructive testing method for damage mode identification and damage assessment. This study focuses on AE signals characteristics and evolution behaviors for used 70 MPa Type IV hydrogen storage tanks during hydrostatic burst tests. AE-based tensile tests for epoxy resin specimen and carbon fiber tow were implemented to obtain characteristics of matrix cracking and fiber breakage. Then, broad-band AE sensors were used to capture AE signals during multi-step loading tests and hydrostatic burst tests. K-means ++ algorithm and wavelet packet transform are performed to cluster AE signals and verify the validity. Combining with tensile tests, three clusters are manifested via matrix cracking, fiber/matrix debonding and fiber breakage according to amplitude, duration, counts and absolute energy. The number of three clustering signals increases with the increase of pressure, showing accumulated and aggravated damage. The sudden appearance of a large number of fiber breakage signals during hydrostatic burst tests suggests that the composite tank structure is becoming mechanically unstable, namely the impending burst failure of the tank.

Identification of crack development in granite under triaxial compression based on the acoustic emission signal

To explore the development mechanism of cracks in the process of rock failure, triaxial compression tests with simultaneous acoustic emission monitoring were performed on granite specimens using the MTS rock mechanics test system. The frequency-domain information of the acoustic emission signal was obtained by the fast Fourier transform. The Gutenberg–Richter law was used to calculate the acoustic emission signals and obtain the b-value dynamic curve in the loading process. Combined with the stiffness curve of granite specimens and acoustic emission signal in the time domain and frequency domain, the crack development characteristics in different stages were analyzed. The results showed that the acoustic emission signals of granite samples under triaxial compression can be divided into four stages: quiet period 1, active stage 1, quiet period 2, and active stage 2. b-value attained its maximum value in the active phase 2 when it is close to the sample loss, and then drops rapidly, which means the propagation of cracks and the formation of large cracks. The acoustic emission signal’s dominant frequency was not more than 500 kHz, mostly concentrated in the medium-frequency band (100–200 kHz), which accounted for more than 80%. The proportion of signals in each frequency band can reflect the distribution of the three kinds of cracks, while the change in low-frequency signals can reflect the breakthrough of microcracks and the formation time of macrocracks in granite samples. By fully analyzing the characteristics of acoustic emission signals in the time domain and frequency domain, the time and conditions of producing large cracks can be determined accurately and efficiently.

Research on the Attenuation Characteristics of AE Signals of Marble and Granite Stone

When an underground rock is deformed or fractured by an external or internal force, the energy will be released in the form of an elastic wave, which is known as the acoustic emission (AE) phenomenon. Extracting useful information from complex AE signals for the early warning of fracture characteristics and the damage monitoring of rock materials is of great significance for the prevention and control of dynamic disasters in coal mines. In this work, by taking rod-shaped rocks and plate-shaped rocks with different lithologies as the research objects, the elastic wave propagation characteristics of the rod-shaped rocks and plate-shaped rocks were studied by a self-constructed experimental platform. The results demonstrate that the elastic wave attenuation of the rod-shaped marble was the fastest, and the elastic wave attenuation characteristics of the three groups of rod-shaped granite were similar. The attenuation of the P-wave preceded that of the S-wave. With the increase in the propagation distance, the amplitude of the large-scale plate-shaped rock showed an approximate exponential attenuation characteristic. The elastic wave attenuation of the plate-shaped granite in the 0° direction was stronger than that of the plate-shaped marble, and it was weaker than that of the plate-shaped marble in the 45° and 90° directions. The energy changes in marble were more severe than those in granite. The main dominant energy of the AE signals of experimental rock was concentrated in the range of 0–176.78 kHz, and part of the residual energy was located in the high-frequency band of 282.25–352.56 kHz.

Quantitative damage, fracture mechanism and velocity structure tomography of sandstone under uniaxial load based on acoustic emission monitoring technology

Rock is an opaque medium body, and it is impossible to visually see its internal damage, which brings difficulties to the investigation of rock damage. In the light of the problems of rock damage, fracture mechanism and velocity structure evolution under load, the acoustic emission (AE) technology is adopted in this paper to monitor and analyze AE events in sandstone specimens during uniaxial loading. To investigate the damage law and fracture mechanism of sandstone under uniaxial load, a mechanical model that can quantitatively describe rock damage is constructed. Finally, the time-lapse double-difference tomography (tomo-TDD) is used to invert the velocity structure in the loaded rock. The results show that the fracture mode of the sandstone under uniaxial load is mainly shear fracture accompanied by a small amount of tensile fracture. The fracture modes of the three stages divided by the characteristics of AE signals, during loading process of the sandstone, is shear fracture, tensile fracture and shear fracture respectively. The damage mechanics model including the whole process of stress-strain curve in the post peak stress stage and the stage of primary micro-pores’ compaction and closure can quantitatively describe the damage degree and accurately predict the failure of rock under different stress levels, which is consistent with the velocity structure inverted by tomo-TDD. The velocity structure inversion based on tomo-TDD can reflect the damage degree, damage distribution and velocity structure evolution of any section under any stress level. The research results can be used for rock stability analysis and risk prediction, and at the same time, it provides a more intuitive reference for the non-destructive testing of rock masses in engineering.

Wire breaking localization of parallel steel wire bundle using acoustic emission tests and finite element analysis

The precise localization of cable damage is a major issue in bridge engineering. The acoustic emission (AE) method has been applied to detect defects for cable structures in bridges. In this paper, an AE localization method is proposed to localize both lateral and longitudinal positions of defects in a parallel steel wire bundle composed of seven steel wires. The proposed method is verified numerically and experimentally. Tension failure test of the parallel steel wire bundle composed of seven wires was carried out, and the precise localization of defects was realized by through modal AE techniques and the analysis of the characteristics of AE signal. A Multiphysics model based on COMSOL was established to facilitate the visualization of stimulated AE propagated in the parallel wire bundle. The propagation mechanism of AE signal was studied, and the feasibility of localization method was verified.

Predicting rock failure with the critical slowing down theory

Early warning signals of critical transitions in rock before its sudden failure are key for forecasting geological disasters in rock engineering. Here we examined the critical slowing down characteristics of acoustic emission (AE) and precursory signals preceding catastrophic rock failure. We conducted laboratory experiments on different types of rock specimens subjected to tension and compression, instrumented by real-time AE monitoring. Based on the critical slowing down theory, AE signals monitored over the deformation and failure of the rock specimens were parametrized statistically. The results show that the critical slowing down characteristics of AE signals exist for rocks under various experimental conditions. The sudden and significant increase in the variance and the autocorrelation coefficient of AE can be used as precursors for rock failure. The time intervals between the precursory signals and rock rupture for brittle rocks under tension are smaller than those under compression. These early warning time intervals are longer and the ratios of the early warning to peak states are lower during Brazilian tests than during direct tensile tests. Furthermore, relationships between multiple influencing factors and precursory signals were discussed. We found that the precursory signals are strongly related to the intrinsic properties of rock and the external experimental conditions. Finally, the applicability and reliability of precursory signals through the critical slowing down theory were verified for rock failure by statistically analysing the laboratory data from a wide range of rocks.