Acoustic Monitoring Technique Research Articles

Toward identifying crack-length-related resonances in acoustic emission waveforms for structural health monitoring applications

In this study, we focus on analyzing the acoustic emission waveforms of the fatigue crack growth despite the conventional statistics-based analysis of acoustic emission. The acoustic emission monitoring technique is a well-known approach in the non-destructive evaluation/structural health monitoring research field. The growth of the fatigue crack causes the acoustic emission in the material that propagates in the structure. The acoustic emission happens not only from the crack growth but also from the interaction of the crack tips during the fatigue loading in the structure. The acoustic emission waveforms are generated from the acoustic emission events; they propagate and create local vibration modes along the crack faces (crack resonance). In-situ fatigue and acoustic emission experiments were conducted to monitor the acoustic emission waveforms from the fatigue cracks. Several test specimens were used in the fatigue experiments, and corresponding acoustic emission waveforms were captured. The acoustic emission waveforms were analyzed and distinguished into three types based on the similar nature in both time and frequency domains. Three-dimensional harmonic finite element analyses were performed to identify the local vibration modes. The local crack resonance phenomenon has been observed from the finite element simulation that could potentially give the geometric information of the crack. The laser Doppler vibrometry experiment was performed to identify the crack resonance phenomenon, and the experimental results were used to verify the simulated results.

Failure prediction and reliability analysis of ferrocement composite structures by incorporating machine learning into acoustic emission monitoring technique

This paper introduces suitable features and methods to define hazard rate function by acoustic emission (AE) parametric analysis to develop robust damage statement index and reliability analysis. AE signal energy was first examined to find out the relation between damage progress and AE signal energy so that a damage index based on AE signal energy could be proposed to quantify progressive damage imposed to ferrocement composite slabs. Moreover, by using AE signal strength, historic index could be computed and utilized to develop a modified hazard rate function through integration of bathtub curve and Weibull function. Furthermore, to provide a practical scheme for real condition monitoring, support vector regression was utilized to produce a robust tools for failure prediction considering uncertainties exist in real structures.

Compression after impact strength of repaired GFRP composite laminates under repeated impact loading

During their service life, composite materials are prone to damage, which compromises their structural performance significantly. In this study, glass/epoxy composite specimens fabricated using hand layup method and further cured in a compression molding machine were cut from the laminates and subjected to low velocity impact damage in order to investigate the effects of repair. The impacted laminates were repaired by removing the damage area with a circular cutout and filled with a chopped short Kevlar/epoxy: the efficiency of the repair procedure and toughness of the repaired laminates were examined by repeated impacts on the repaired site. The residual strength of the post impacted repaired laminates is investigated by the conduction of compression after impact (CAI) loading with acoustic emission monitoring (AE) technique. The structural performance of both repaired and unrepaired laminates are compared and discussed.

Wayside bearing fault diagnosis based on a data-driven Doppler effect eliminator and transient model analysis.

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects.

A low‐cost, yet simple and highly repeatable system for acoustically surveying cryptic species

AbstractAccurate determination of the population density of key focal species is necessary for monitoring the success of management programs and ecosystem health across a wide range of contexts. Unfortunately, many key taxa are visually cryptic and thus difficult to count using traditional observation‐based techniques. Bell miners (Manorina melanophrys), are just such a species. They are widespread throughout south‐eastern Australia, yet they are critical to monitor given their association and potential causal link to spreading vegetative dieback in this region. A new passive acoustic monitoring technique was trialled by testing its ability to determine population densities of bell miner colonies via counting the distinctive ‘tink’ vocalization of this species. This call was given at a constant rate per individual, and at a common amplitude across 10 colonies throughout the entire geographic range of the species. Theoretical sound transmission and playback trials through typical habitat determined that any bird within a 50‐m radius of the recorders used would be louder than 70 dB, enabling this threshold amplitude to be used to determine the number of birds in a 50 m radius of the recorder. Field trials of the acoustic protocol versus human observers using traditional visual surveys found that passive acoustic monitoring was able to detect more individuals, using a less expensive protocol that drastically reduced the need for observer training or expertise. Sound therefore offers a reliable method for determining the density of this vocal, but visually cryptic species. We present methods for calibrating recording devices and detecting calls louder than species‐specific thresholds using readily available freeware, enabling our methods to be easily adapted to census a variety of acoustically distinctive species, offering a more effective, yet lower cost and in our case more efficient census technique for surveying difficult species.

Acoustic characterization of new species of bats for the State of Oaxaca, Mexico

Biodiversity inventories are sometimes biased by the various collection methods applied. In the case of the bats, the acoustic monitoring technique has proven to be complementary to conventional sampling. From July 2007 to June 2008, we studied the composition of a bat community in the southern region of the Isthmus of Tehuantepec, Oaxaca, Mexico. We registered 32 species of bats belonging to six families. Thirteen species of the family Phyllostomidae were captured in mist nets, while three species of the family of Emballonuridae, one species of family Noctilionidae and six of the family Molossidae were recorded by acoustic monitoring. Four species of the family Mormoopidae and five of the Vespertilionidae were registered with both methods. Through acoustic monitoring two new species are added to the 93 already known to the state of Oaxaca: Molossus molossus and M. sinaloae were registered in areas with tropical deciduous forest and gallery vegetation in two areas protected by native communities. These sites protected by local initiatives, turns out to be a good strategy of conservation for bats and other taxonomic groups. Key words: acousting monitoring, conservation, insectivorous bat, inventory, Tehuantepec Isthmus.

Laboratory investigations on cracking in reinforced concrete beams using on-line acoustic emission monitoring technique

This article presents an experimental study on variation in acoustic emission (AE) parameters during cracking in reinforced concrete (RC) beams subjected to incremental cyclic loading in laboratory conditions. Nine RC beams with three different span-to-depth ratios ranging from 2.0 to 6.0 with a reinforcement ratio roughly kept the same (1.4–1.5 %) were tested under bending till failure and simultaneously the released AE was recorded. The criteria used to characterize the cracking in RC beams are based on the AE parameters. The AE parameters such as frequency, duration, amplitude, count, rise time, parameters depending on AE signatures such as b-value, and damage parameter D follow the fracture process during the entire loading. The results are useful to distinguish different cracks in RC beams and extend them for field applications.

Drive level acoustic defectoscopy for head disc interface (HDI) integration and manufacturing

A short product development cycle for modern hard disc drive (HDD) depends entirely on early defect characterization. However, deviations from desired HDI mechanical performance are not always manifested in electromagnetic read back or servo control signals. The best non-destructive tool to monitor HDI dynamics at the HDD level is a passive acoustic technique that tracks equilibrium of the head gimbal assembly and air bearing (AB) modes. This technique is capable of active head protrusion detection as well as detection of embedded particles. The drawback of the passive acoustic monitoring technique at drive level is that a noisy HDD environment makes the detectability of a useful signal challenging. The proposed HDD level in situ passive HDI acoustic monitoring technique consists of external AE sensors driven by adequate electronics. These are enhanced by advanced signal processing routines that include adaptive discrete wavelet transforms. The system is tuned to monitor acoustic HDI signatures during drive spin-up/spin-down cycles as well as during passive and active height across the data zones. In addition, integrated acoustic energy metrics can be used in AB design evaluation stages. In this work examples of HDD level passive acoustic monitoring applications for HDI development, and manufacturing defect tracking, are presented and supported by failure analysis results.

Three different approaches for damage domain characterization in disordered materials: Fractal energy density, b-value statistics, renormalization group theory

Material characterization is usually based on the stress–strain constitutive laws directly derived from the load–displacement relations of uniaxial compression tests. This approach, which implies a uniform distribution of deformation along the specimen axis and an energy dissipation within a volume, does not permit to correctly describe the mechanical behavior and the damage evolution by varying the structural size and slenderness.In this paper, three different approaches are used to evaluate the physical dimension of the damage domain in disordered materials subjected to uniaxial compression. The energetic and the statistical methods are based on the acoustic emission monitoring technique, whereas the renormalization group procedure is based on the assumption of anomalous physical dimensions for the material properties. The three approaches agree very well in the determination of the damage domain fractal dimension.

Taking NIRS-BCIs Outside the Lab: Towards Achieving Robustness Against Environment Noise

This paper reported initial findings on the effects of environmental noise and auditory distractions on the performance of mental state classification based on near-infrared spectroscopy (NIRS) signals recorded from the prefrontal cortex. Characterization of the performance losses due to environmental factors could provide useful information for the future development of NIRS-based brain-computer interfaces that can be taken beyond controlled laboratory settings and into everyday environments. Experiments with a hidden Markov model-based classifier showed that while significant performance could be attained in silent conditions, only chance levels of sensitivity and specificity were obtained in noisy environments. In order to achieve robustness against environment noise, two strategies were proposed and evaluated. First, physiological responses harnessed from the autonomic nervous system were used as complementary information to NIRS signals. More specifically, four physiological signals (electrodermal activity, skin temperature, blood volume pulse, and respiration effort) were collected in synchrony with the NIRS signals as the user sat at rest and/or performed music imagery tasks. Second, an acoustic monitoring technique was proposed and used to detect startle noise events, as both the prefrontal cortex and ANS are known to involuntarily respond to auditory startle stimuli. Experiments with eight participants showed that with a startle noise compensation strategy in place, performance comparable to that observed in silent conditions could be recovered with the hybrid ANS-NIRS system.

A time–frequency acoustic emission-based monitoring technique to identify workpiece surface malfunctions in milling with multiple teeth cutting simultaneously

In the view of implementing automated solutions for monitoring complex machining processes such as milling, the usage of acoustic emission (AE) in machining is regarded as a promising way for assessing machine tool condition and for in-process detection of workpiece malfunctions. Correlating AE signal events with the occurrence of workpiece surface anomalies (e.g. laps, material drag) can be a powerful method for scrap reduction of expensive components such as those employed in aerospace industry. This paper proposes new methods for supervising cutting processes with multiple teeth cutting simultaneously, i.e. milling, by use of AE signals backed-up by force data. This is done by taking into account signals patterns when one, two or three teeth are cutting simultaneously, situation that often occurs in real milling applications. The research shows for the first time that identification of milling conditions (i.e. cutting with one/two/three teeth) is possible using only AE signal in time–frequency ( T– F) domain. Moreover, detection of surface anomalies, such as folded laps that are generated by damaged cutting edges can be successfully identified in various milling conditions. The paper demonstrates that time–frequency analysis of AE signals empowered with advanced processing techniques has great potential to be used in flexible and easily to implement monitoring solutions to enable milling of anomaly-free workpiece surfaces in difficult-to-cut aerospace materials.

Use of an on-press acoustic sensor to monitor coldset offset printing of newspaper

A newly developed acoustic emission on-line monitoring technique (Voltaire J. et al. 2004) provides insight into the dynamic interactions occurring between paper, ink-fount emulsion, and rubber b ...

Avoidance behaviour of Alosa fallax fallax to pulsed ultrasound and its potential as a technique for monitoring clupeid spawning migration in a shallow river

A hydroacoustic monitoring technique to quantify and assess the ecological requirements for migration of the anadromous clupeid, Alosa fallax fallax (twaite shad) was developed, and its effectiveness studied, on the River Wye in Wales. The acoustic monitoring technique was a side aspect application, with two transducers fixed permanently to the riverbank and the acoustic beam from each aimed horizontally across the river towards the opposite bank, perpendicular to flow. Two split-beam echo sounders and transducers were deployed, each operating at different frequencies (200 and 420 kHz). Using a combination of these two frequencies it was possible to demonstrate that shad show strong avoidance behaviour to sound transmitted at 200 kHz and would not pass the monitoring site when sound was transmitted at this frequency. They remained unaffected by sound transmitted at 420 kHz and were observed migrating upstream in large, loosely aggregated shoals. From visual observations above and below the water, shoals were estimated to comprise of many hundreds of individuals, covering a size range of between 30 and 45 cm. Only a few individuals could be resolved by the acoustic system operating at 420 kHz, and it was therefore, not possible to obtain a count of fish by “target tracking” single shad. However, by transmitting 200 kHz sound pulses on a 50% duty cycle the seasonal and daily patterns of shad migration were derived from the analysis of data gathered by the acoustic system operating at 420 kHz.

Acoustic sensor: a novel technique for low pressure membrane integrity monitoring

Control of membrane integrity is critical to assuring process efficacy in terms of microbial removal. Various monitoring techniques such as turbidity, particle counting, and air testing are commonly used in membrane operation. However, membrane integrity is not necessarily reflected by a changing of the permeate quality, i.e., turbidity as well as particle count. Therefore, acoustic integrity monitoring (AIM) was developed to monitor the integrity of the membrane, especially when other techniques such as particle counting are not applicable. Based on hydrophonic sensor technology, the acoustic monitoring technique consists of measuring the noise due to a compromised fiber. The advantage of a hydrophonic sensor is that integrity of the membranes is monitored continuously during filtration. Moreover, AIM enables detection of a non-cut compromised fiber with a hole of 0.5 mm which therefore guarantees more than 6 log removal of viruses.

Fracture Mechanisms of FRPC by Acoustic Emission Monitoring. Effects of Nozzle Diameter and Screw Design.

In order to investigate the effects of nozzle diameter and screw design on the fracture mechanism when FRPC is molded with an injection molding machine, the acoustic emission monitoring technique is used during tensile testing of the molded specimens. The optimal nozzle diameter and screw design can be derived by the maximum load Pmax and the loads at the change in damage mechanism Rb and Pc which are determined by the AE energy gradient method. The damage at the loads Pb and Pc is discussed by the peak frequencies in using the AE frequency analysis.

In situ investigation of loosened zone around deep under ground openings, by acoustic emission monitoring technique : Aoki, K; Toida, M; Koshizuka, K Proc International Symposium on Rock at Great Depth, Pau, 28–31 August 1989 VI, P313–319. Publ Rotterdam: A A Balkema, 1989

In situ investigation of loosened zone around deep under ground openings, by acoustic emission monitoring technique : Aoki, K; Toida, M; Koshizuka, K Proc International Symposium on Rock at Great Depth, Pau, 28–31 August 1989 VI, P313–319. Publ Rotterdam: A A Balkema, 1989

Acceptance testing of graphite /epoxy composite parts using an acoustic emission monitoring technique

A graphite/epoxy composite dome was proof-tested by pressurization. Acoustic emission (AE) data was obtained during the proof test. A low-frequency bandpass was used to minimize AE signal propagation losses. The AE system and test part were calibrated in situ by an instrumented pencil-lead break. Large energy AE signals provide a clear indication of a flawed composite part.