1000 resultados para Vibro-acoustic


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Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-colour images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

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Covertly tracking mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms requires both visual and acoustic stealth. Whilst the use of robots for stealthy surveillance is not new, the majority only consider navigation for visual covertness. However, most fielded robotic systems have a non-negligible acoustic footprint arising from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. This time-varying acoustic signature can jeopardise any visual covertness and needs to be addressed in any stealthy navigation strategy. In previous work, we addressed the initial concepts for acoustically masking a tracking robot’s movements as it travels between observation locations selected to minimise its detectability by a dynamic natural target and ensuring con- tinuous visual tracking of the target. This work extends the overall concept by examining the utility of real-time acoustic signature self-assessment and exploiting shadows as hiding locations for use in a combined visual and acoustic stealth framework.

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This work is motivated by the desire to covertly track mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms with a non-negligible acoustic signature. The use of robots for stealthy surveillance is not new. Many studies exist but only consider the navigation problem to maintain visual covertness. However, robotic systems also have a significant acoustic footprint from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. All these can jepordise any visual covertness. In this work, we experimentally explore the concepts of opportunistically utilizing naturally occurring sounds within outdoor environments to mask the motion of a robot, and being visually covert whilst maintaining constant observation of the target. Our experiments in a constrained outdoor built environment demonstrate the effectiveness of the concept by showing a reduced acoustic signature as perceived by a mobile target allowing the robot to covertly navigate to opportunistic vantage points for observation.

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Guitar technology underwent significant changes in the 20th century in the move from acoustic to electric instruments. In the first part of the 21st century, the guitar continues to develop through its interaction with digital technologies. Such changes in guitar technology are usually grounded in what we might call the "cultural identity" of the instrument: that is, the various ways that the guitar is used to enact, influence and challenge sociocultural and musical discourses. Often, these different uses of the guitar can be seen to reflect a conflict between the changing concepts of "noise" and "musical sound."

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This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

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The theory of ion-acoustic surface wave propagation on the interface between a dusty plasma and a dielectric is presented. Both the constant and variable dust-charge cases are considered. It is found that massive negatively charged dust grains can significantly affect the propagation and damping of the surface waves. Application of the results to surface-wave generated plasmas is discussed. © 1998 IEEE.

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A nonlinear theory for ion-acoustic surface waves propagating at the interface between a dusty plasma and a dielectric is presented. The nonlinear effects are associated with density modulations caused by surface-wave induced anomalous ionization. The negative charge of the massive dust grains is assumed to be constant. It is shown that the effect of the ionization nonlinearity arising from the ion-acoustic surface waves can result in the formation of surface envelope solitons. The wave phase shifts and the widths of the solitons are estimated for typical gas discharge plasmas.

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A self-consistent theory of ion-acoustic waves in dusty gas discharge plasmas is presented. The plasma is contaminated by fine dust particles with variable charge. The stationary state of the plasma and the dispersion and damping characteristics of the waves are investigated accounting for ionization, recombination, dust charge relaxation, and dissipation due to electron and ion elastic collisions with neutrals and dusts, as well as charging collisions with the dusts.

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A wave propagation in a complex dusty plasma with negative ions was considered. The relevant processes such as ionization, electron attachment, diffusion, positive-negative ion recombination, plasma particle collisions, as well as elastic Coulomb and inelastic dust-charging collisions were taken self-consistently. It was found that the equilibrium of the plasma as well as the propagation of ion waves were modified to various degrees by these effects.

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Negative ions and negatively charged micro- to nano-meter sized dust grains are ubiquitous in astrophysical as well as industrial processing plasmas. The negative ions can appear in electro-negative plasmas as a result of elementary processes such as dissociative or non-dissociative electron attachment to neutrals. They are usually rather small in number, and in general do not affect the overall plasma behavior. On the other hand, since the dust grains are almost always highly negative, even in small numbers they can take up a considerable proportion of the total negative charge in the system. The presence of dusts can affect the characteristics of most collective processes of the plasma since the charge balance in both the steady and dynamic states can be significantly altered. Another situation that often occurs is that the electron number density becomes small because of their absorption by the dust grains or the discharge walls. In this case the negative ions in the plasma can play a very important role. Here, a self-consistent theory of linear waves in complex laboratory plasmas containing dust grains and negative ions is presented. A comprehensive model for such plasmas including source and sink effects associated with the presence of dust grains and negative ions is introduced. The stationary state of the plasma as well as the dispersion and damping characteristics of the waves are investigated. All relevant processes, such as ionization, diffusion, electron attachment, negative-positive ion recombination, dust charge relaxation, and dissipation due to electron and ion elastic collisions with neutrals and dust particles, as well as charging collisions with the dusts, are taken into consideration.

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The current-driven dust ion-acoustic instability in a collisional dusty plasma is studied. The effects of dust-charge variation, electron and ion capture by the dust grains, as well as various dissipative mechanisms leading to the changes of the particles momenta, are taken into account. It is shown that the threshold for the excitation of the dust ion-acoustic waves can be high because of the large dissipation rate induced by the dusts. © 1999 American Institute of Physics.

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Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge addressed in this paper is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-color images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

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Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

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Background: Footwear remains a prime candidate for the prevention and rehabilitation of Achilles tendinopathy as it is thought to decrease tension in the tendon through elevation of the heel. However, evidence for this effect is equivocal. Purpose: This study used an acoustic transmission technique to investigate the effect of running shoes on Achilles tendon loading during barefoot and shod walking. Methods: Acoustic velocity was measured in the Achilles tendon of twelve recreationally–active males (age, 31±9 years; height, 1.78±0.06 m; weight, 81.0±16.9 kg) during barefoot and shod walking at matched self–selected speed (3.4±0.7 km/h). Standard running shoes incorporating a 10– mm heel offset were used. Vertical ground reaction force and spatiotemporal parameters were determined with an instrumented treadmill. Axial acoustic velocity in the Achilles tendon was measured using a custom built ultrasonic device. All data were acquired at a rate of 100 Hz during 10s of steady–state walking. Statistical comparisons between barefoot and shod conditions were made using paired t–tests and repeated measure ANOVAs. Results: Acoustic velocity in the Achilles tendon was highly reproducible and was typified by two maxima (P1, P2) and minima (M1, M2) during walking. Footwear resulted in a significant increase in step length, stance duration and peak vertical ground reaction force compared to barefoot walking. Peak acoustic velocity in the Achilles tendon (P1, P2) was significantly higher with running shoes. Conclusions: Peak acoustic velocity in the Achilles tendon was higher with footwear, suggesting that standard running shoes with a 10–mm heel offset increase tensile load in the Achilles tendon. Although further research is required, these findings question the therapeutic role of standard running shoes in Achilles tendinopathy.