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Статті в журналах з теми "Acoustic source location":
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Holford, Karen M., and D. C. Carter. "Acoustic Emission Source Location." Key Engineering Materials 167-168 (June 1999): 162–71. http://dx.doi.org/10.4028/www.scientific.net/kem.167-168.162.
This article describes a method to determine locations of noise sources that minimize modal coupling in complex acoustic volumes. Using the acoustic source scattering capabilities of the boundary element method, predictions are made of mode shape and pressure levels due to various source locations. Combining knowledge of the pressure field with a multivariable function minimization technique, the source location generating minimum pressure levels can be determined. The analysis also allows for an objective comparison of “best/worst” locations. The technique was implemented on a personal computer for the U.S. Space Station, predicting 5–10 dB noise reduction using optimum source locations.
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Coulter, John E., Robert S. Evans, and Michael O. Robertson. "Acoustic emission leak source location." Journal of the Acoustical Society of America 92, no. 6 (December 1992): 3453–54. http://dx.doi.org/10.1121/1.404160.
We have developed a novel acoustic-wave-equation-based full-waveform source location method to locate microseismic events. With the acoustic-wave equation and source signature independent inversion strategy, source location parameters (hypocenter locations) can be isolated from others and can then be retrieved independently and accurately, even when the origin time and source signature are not correct. Based on the acoustic-wave equation, new Fréchet derivatives of seismic waveforms with respect to the location parameters are derived to better accelerate the inversion process. To ease the cycle-skipping problem, a correlation is applied to select the best starting source positions. Some 2D and 3D numerical examples are presented to demonstrate the validity of our method. Compared with the waveform-based grid-search method, our method is effective in isolating the hypocenter locations from the source signature and origin time. The computational cost is nearly negligible compared with the waveform-based grid-search method. The robustness of our method is also tested for cases with inaccurate velocity models or using microseismic data with a signal-to-noise ratio of ≥[Formula: see text]. Finally, field data are used to indicate the practical applicability of our method.
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Chernov, Dmitriy V., Igor E. Vasil′ev, Artem Yu Marchenkov, Tatyana Yu Kovaleva, Ekaterina A. Kulikova, Ivan V. Mishchenko, and Mariya V. Goryachkina. "The Influence of Acoustic Signal Amplitude on the Acoustic Emission Source Detection Probability." Vestnik MEI, no. 1 (2022): 130–36. http://dx.doi.org/10.24160/1993-6982-2022-1-130-136.
The article discusses the results of using a standard algorithm for linearly locating the sources of acoustic emission signals generated by a broadband acoustic emission (AE) transducer mounted on the surface of a steel plate with sizes 1000×650×7 mm. To generate AE impulses with an amplitude of um = 55–100 dB, the electronic simulator’s difference of potentials was varied in the range of 10–300 V. As a result of laboratory experiments, the reduced error γ of the standard linear location algorithm was calculated. The maximum error equal to γ = 16.3% was recorded at the coordinate X = 100 mm in locating the source of acoustic signals with an amplitude of less than 60 dB and the antenna array basic size B = 800 mm. The minimum error equal to γ = 2.69% was recorded with the electronic simulator installed at the coordinate X = 400 mm. It is shown that the maximum error of the standard algorithm is observed in locating the sources of low-amplitude AE signals situated near the antenna array receiving transducers. The AE source detection probability as a function of recorded impulse amplitude is quantified. For determining the AE source detection probability p, the flow of recorded signals was divided into three amplitude ranges: 40–60 dB, 60–75 dB, and 75–100 dB. For the sources of acoustic signals with an amplitude of less than 60 dB and located at the coordinates X = 100, 200, 600, and 700 mm, the parameter p value tends to zero. It has been revealed in processing the experimental study results that the AE source detection probability increases with a growth in the maximum amplitude of the recorded signals. For AE impulses with an amplitude above 75 dB, the parameter p value approaches unity regardless of the source location. It has been determined that the error of the standard linear location algorithm depends on the distance between the AE source and the antenna array receiving transducers. The dependence p(X, um) has been demonstrated as a numerical assessment of the way in which the above-mentioned factors influence the obtained location picture results.
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Richarz, Werner G. "Jet noise source location via acoustic intensity." Journal of the Acoustical Society of America 78, S1 (November 1985): S26. http://dx.doi.org/10.1121/1.2022720.
Bhatt, Tarun, Esther T. Ososanya, and Corinne M. Darvennes. "Acoustic source location using a neural network." Journal of the Acoustical Society of America 101, no. 5 (May 1997): 3057. http://dx.doi.org/10.1121/1.418656.
Lympertos, Efstratios M., and Evangelos S. Dermatas. "Acoustic emission source location in dispersive media." Signal Processing 87, no. 12 (December 2007): 3218–25. http://dx.doi.org/10.1016/j.sigpro.2007.05.010.
Baxter, Matthew Geoffrey, Rhys Pullin, Karen M. Holford, and Sam L. Evans. "Delta T source location for acoustic emission." Mechanical Systems and Signal Processing 21, no. 3 (April 2007): 1512–20. http://dx.doi.org/10.1016/j.ymssp.2006.05.003.
Chang, Pi Sheng. "Acoustic source location using a microphone array." Journal of the Acoustical Society of America 113, no. 6 (2003): 2957. http://dx.doi.org/10.1121/1.1588801.
Aljets, Dirk. "Acoustic emission source location in composite aircraft structures using modal analysis." Thesis, University of South Wales, 2011. https://pure.southwales.ac.uk/en/studentthesis/acoustic-emission-source-location-in-composite-aircraft-structures-using-modal-analysis(6871e94b-6e94-4efd-b563-41b254ee27b4).html.
The aim of this research work was to develop an Acoustic Emission (AE) source location method suitable for Structural Health Monitoring (SHM) of composite aircraft structures. Therefore useful key signal features and sensor configurations were identified and the proposed method was validated using both artificially generated AE as well as actual AE resulting from damage. Acoustic Emission is a phenomenon where waves are generated in stressed materials. These waves travel through the material and can be detected with suitable sensors on the surface of the structure. These stress waves are attributed to propagating damage inside the material and can be monitored while the structure is in service. This makes AE very suitable for SHM, in particular for aircraft structures. In recent years composite materials such as carbon fibre reinforced epoxy (CFRP) are increasingly being used for primary and secondary structures in aircraft. The anisotropic layup of CFRP can lead to different failure mechanisms such as delamination, matrix cracking or fibre breakage which affects the remaining life time of the structure to different extents. Accurate damage location is important for SHM systems to avoid further inspections and allows for a maintenance scheme which considers the severity of the damage, due to damage type, extent and location. This thesis presents a novel source location method which uses a small triangular AE sensor array. The method determines the origin of an AE wave by a combination of time of arrival and modal analysis. The small footprint of the array allows for a fast and easy installation in hard-to-reach areas. The possibility to locate damage outside and at a relatively far distance from the array could potentially reduce the overall number of sensors needed to monitor a structure. Important wave characteristics and wave propagation in particular in CFRP were investigated using AE simulated by an artificial source and actual damage in composite specimens.
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Liu, Horng-Twu. "The use of high frequency stress waves for detecting shaft seal rubbing and source location." Thesis, Cranfield University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309839.
Heaney, Kevin Donn. "Inverting for source location and internal wave strength using long range ocean acoustic signals /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1997. http://wwwlib.umi.com/cr/ucsd/fullcit?p9737384.
Spriggs, M. P. "Quantification of acoustic emission from soils for predicting landslide failure." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/10903.
Acoustic emission (AE) is a natural phenomenon that occurs when a solid is subjected to stress. These emissions are produced by all materials during pre failure. In soil, AE results from the release of energy as particles undergo small strains. If these emissions can be detected, then it becomes possible to develop an early warning system to predict slope failure. International research has shown that AE can be used to detect ground deformations earlier than traditional techniques, and thus it has a role to play in reducing risk to humans, property and in mitigating such risks. This thesis researches the design of a system to quantify the AE and calculate the distance to the deformation zone, and hence information on the mechanism of movement. The quantification of AE is derived from measuring the AE event rate, the output of which takes the form of a displacement rate. This is accurate to an order of magnitude, in line with current standards for classifying slope movements The system also demonstrates great sensitivity to changes within the displacement rate by an order of magnitude, making the technique suitable to remediation monitoring. Knowledge of the position of the shear surface is critical to the planning of cost effective stabllisation measures. This thesis details the development of a single sensor source location technique used to obtain the depth of a developing or existing shear surface within a slope. The active waveguide is used to reduce attenuation by taking advantage of the relatively low attenuation of metals such as steel. A method of source location based on the analysis of Lamb wave mode arrival times at a smgle sensor is summansed. An automatic approach to source location is demonstrated to locate a regular AE source to within one metre. Overall consideration is also given to field trials and towards the production of monitoring protocols for data analysis, and the implementation of necessary emergency/remediation plans.
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Muhamad, Bunnori Norazura. "Acoustic emission techniques for the damage assessment of reinforced concrete structures." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54633/.
Reinwald, Michael. "Wave propagation in mammalian skulls and its contribution to acoustic source localization." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS244.
La précision avec laquelle le dauphin localise les sources sonores est excellente, que les sources soient situées dans le plan médial ou dans le plan transverse. Cette faculté est contre-intuitive étant donné que les dauphins n’ont pas d’oreille externe (pavillon), qui joue un rôle important chez les autres mammifères pour la localisation de sources en élévation. Dans cette thèse, des simulations tridimensionnelles ont été réalisées pour déterminer l’influence de la conduction osseuse du son dans le crâne d’un dauphin commun à bec court sur la pression acoustique au voisinage de l’oreille. La modalisation n’a pas permis de mettre en évidence d’encoches spectrales telles que celles créées par le pavillon de l’oreille externe des humains et qui codent chez celui-ci l’élévation de la source sonore. Une série d’expériences sur un crâne de dauphin, immergé dans une piscine, a permis de mesurer directement la conduction osseuse dans la mandibule. Les formes d’ondes complètes des sons reçus aux récepteurs fixés sur la mandibule, et particulièrement la coda du signal, a pu être utilisée avec succès pour obtenir la position de sources en utilisant un algorithme de corrélation. Ce résultat, qui devra être conforté par la réalisation d’autres expériences, suggère que le système auditif du dauphin pourrait utiliser la coda des signaux reçus lors de l’écholocation. Enfin, des simulations 2D ont permis de mettre en évidence le potentiel bénéfice du couplage de la conduction osseuse du son avec la propagation dans des structures graisseuses de la tête du dauphin The spatial accuracy of source localization by dolphins has been observed to be equally accurate independent of source azimuth and elevation. This ability is counter-intuitive if one considers that humans and other species have presumably evolved pinnae to help determine the elevation of sound sources, while cetaceans have actually lost them. In this work, 3D numerical simulations are carried out to determine the influence of bone-conducted waves in the skull of a short-beaked common dolphin on sound pressure in the vicinity of the ears. The skull is not found to induce any salient spectral notches, as pinnae do in humans, that the animal could use to differentiate source elevations in the median plane. Experiments are conducted in a water tank by deploying sound sources on the horizontal and median plane around a skull of a dolphin and measuring bone-conducted waves in the mandible. Their full waveforms, and especially the coda, can be used to determine source elevation via a correlation-based source localization algorithm. While further experimental work is needed to substantiate this speculation, the results suggest that the auditory system of dolphins might be able to localize sound sources by analyzing the coda of biosonar echoes. 2D numerical simulations show that this algorithm benefits from the interaction of bone-conducted sound in a dolphin's mandible with the surrounding fats
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Latham, Michael. "Noise source location in the built environment, using a simple microphone array." Thesis, University of Plymouth, 1994. http://hdl.handle.net/10026.1/2876.
An inadequate level of noise attenuation provided by a building element is frequently the result of a lack of completeness in the construction. This often invisible fault acts as a noise source in a room, so in order to undertake remedial work the source position must be found. Recently, near field noise intensity measurement has been the popular method for noise source location in buildings. This method of using intensity studies requires a grid of readings to be taken. An alternative method, the one used in this work, employs a different strategy. Here, the source location is identified by direction scanning of time delays at a number of microphones arranged in a regular three-dimensional array. A novel arrangement of seven microphones, in the shape of a wheel-brace, is used to measure the differences in time taken for the sound waves to travel from a source to the various microphones. The magnitudes of these time differences are combined and converted into the coordinates of the source, relative to an origin which is placed at the centre of the wheel-brace array. The mathematics for this conversion is derived and the errors in the experimental arrangement discussed. The use of this airay for the identification of faults in built structures is explored. A significant contribution is made to the knowledge of noise source location in buildings, since the microphone array is used to demonstrate the location of a noise source irrespective of the direction of the incoming noise. The use of computerised data collection is described for a budget system, where time was cheap, but equipment expensive. The accuracy of the technique would be improved considerably if state-of-the-art electronics were used to measure the lime differences. The feasibility, advantages and potential performance of a modem system, that could be assembled today, is described and discussed.
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Jerauld, Joseph G. "Acoustical emission source location in thin rods through wavelet detail crosscorrelation." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA345954.
Thesis (Degree of Aeronautical and Astronautical Engineer) Naval Postgraduate School, March 1998. "March 1998." Thesis advisor(s): Edward M. Wu. Includes bibliographical references (p. 135-136). Also available online.
Jerauld, Joseph G. Acoustical emission source location in thin rods through wavelet detail crosscorrelation. Monterey, Calif: Naval Postgraduate School, 1998.
G, Fischer F., and Geological Survey (U.S.), eds. Location of acoustic sources using seismological techniques and software. Menlo Park, Calif: U.S. Dept. of the Interior, U.S. Geological Survey, 1993.
S, Preisser John, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Location of noise sources using a phase-slope method. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.
A, Watkins William, and Woods Hole Oceanographic Institution, eds. Whale call data for the North Pacific: November 1995 through July 1999 occurrence of calling whales and source locations from SOSUS and other acoustic systems. Woods Hole, Mass: Woods Hole Oceanographic Institution, 2000.
Kraus, D., and J. F. Böhme. "EM Algorithm for Wideband Source Location Estimation." In Acoustic Signal Processing for Ocean Exploration, 315–20. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1604-6_31.
Huang, Gaoming, Luxi Yang, and Zhenya He. "Multiple Acoustic Sources Location Based on Blind Source Separation." In Lecture Notes in Computer Science, 683–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539087_88.
Blahacek, Michal, M. Chlada, and Z. Prevorovský. "Acoustic Emission Source Location Based on Signal Features." In Advanced Materials Research, 77–82. Stafa: Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-420-0.77.
Rendas, M. João, and José M. F. Moura. "Source Location Observability in the Underwater Multipath Acoustic Channel." In Acoustic Signal Processing for Ocean Exploration, 115–30. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1604-6_9.
Aggelis, Dimitrios G., Markus G. R. Sause, Pawel Packo, Rhys Pullin, Steve Grigg, Tomaž Kek, and Yu-Kun Lai. "Acoustic Emission." In Structural Health Monitoring Damage Detection Systems for Aerospace, 175–217. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72192-3_7.
AbstractAcoustic emission (AE) is one of the most promising methods for structural health monitoring (SHM) of materials and structures. Because of its passive and non-invasive nature, it can be used during the operation of a structure and supply information that cannot be collected in real time through other techniques. It is based on the recording and study of the elastic waves that are excited by irreversible processes, such as crack nucleation and propagation. These signals are sensed by transducers and are transformed into electric waveforms that offer information on the location and the type of the source. This chapter intends to present the basic principles, the equipment, and the recent trends and applications in aeronautics, highlighting the role of AE in modern non-destructive testing and SHM. The literature in the field is vast; therefore, although the included references provide an idea of the basics and the contemporary interest and level of research and practice, they are just a fraction of the total possible list of worthy studies published in the recent years.
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Asaue, H., T. Shiotani, and K. Hashimoto. "Two-Dimensional Source Location of Acoustic Emission by Means of AI." In Springer Proceedings in Physics, 131–38. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12111-2_12.
Jiang, Yu, FeiYun Xu, Antolino Gallego, Francisco Sagata, and Oswaldo Gonçalves dos Santos Filho. "Acoustic Emission Tomography to Improve Source Location in Concrete Material Using SART." In Springer Proceedings in Physics, 323–35. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1239-1_30.
Mizutani, Y., N. Inagaki, K. R. Kholish, Q. Zhu, and A. Todoroki. "Source Location of Acoustic Emission for Anisotropic Material Utilizing Artificial Intelligence (WCCM2019)." In Lecture Notes in Mechanical Engineering, 573–78. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9199-0_54.
Тези доповідей конференцій з теми "Acoustic source location":
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Lima, S. E. U., O. Frazão, R. G. Farias, F. M. Araújo, L. A. Ferreira, V. Miranda, and J. L. Santos. "Acoustic source location of partial discharges in transformers." In (EWOFS'10) Fourth European Workshop on Optical Fibre Sensors, edited by José Luís Santos, Brian Culshaw, José Miguel López-Higuera, and William N. MacPherson. SPIE, 2010. http://dx.doi.org/10.1117/12.866489.
Pollack, Martin L. "Flow Noise Source: Resonator Coupling." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-1066.
Abstract This paper investigates the coupling mechanism between flow noise sources and acoustic resonators. Analytical solutions are developed for the classical cases of monopole and dipole types of flow noise sources. The effectiveness of the coupling between the acoustic resonator and the noise source is shown to be dependent on the type of noise source as well as its location on the acoustic pressure mode shape. For a monopole source, the maximum coupling occurs when the noise source is most intense near an acoustic pressure antinode (i.e., location of maximum acoustic pressure). A numerical study with the impedance method demonstrates this effect. A dipole source couples most effectively when located near an acoustic pressure node.
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Forero, Pedro A., and Paul A. Baxley. "Reweighted sparse source-location acoustic mapping in shallow water." In ICA 2013 Montreal. ASA, 2013. http://dx.doi.org/10.1121/1.4800580.
Jin Yang, Yumei Wen, and Ping Li. "Application of blind system identification in acoustic source location." In 2008 10th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2008. http://dx.doi.org/10.1109/icarcv.2008.4795794.
Zhu, Yueqing, Chuanyi Tao, Xiaofeng Gao, Jingke Li, Wei Wang, Hao Wang, Jingnan Zhang, and Yubing Liu. "Acoustic emission source location based on artificial neural network." In Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVI, edited by Peter J. Shull, Tzuyang Yu, Andrew L. Gyekenyesi, and H. Felix Wu. SPIE, 2022. http://dx.doi.org/10.1117/12.2612284.
Golliard, Joachim, Devis Tonon, and Stefan Belfroid. "Experimental Investigation of the Source Locations for Whistling Short Corrugated Pipes." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30732.
The goal of this study is to investigate the issue of the aeroacoustic source location within corrugated pipes. A configuration with a short pipe and well defined boundary conditions has been chosen, in order to have a precise knowledge of the distribution of the acoustic velocity and pressure within the pipe. The source locations have been investigated methodologically by using straight pipe segments to replace the corrugated section near the acoustic velocity nodes or near the acoustic velocity antinodes. The main locations of the sound sources have been identified to be the sections of the corrugated pipe near the acoustic velocity antinodes.
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Breen, Nick P., and Krishan K. Ahuja. "Limitations of Acoustic Beamforming for Accurate Jet Noise Source Location." In AIAA AVIATION 2020 FORUM. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-2603.
Turkoglu, Cagin, Serhat Cagdas, Anil Celebi, and Sarp Erturk. "Hardware Design of Anembedded Real-Time Acoustic Source Location Detector." In 2014 6th International Conference on New Technologies, Mobility and Security (NTMS). IEEE, 2014. http://dx.doi.org/10.1109/ntms.2014.6814022.
Nong, Songqin, Chao Huang, and Liangguo Dong. "Acoustic wave-equation based traveltime inversion for microseismic source location." In SEG Technical Program Expanded Abstracts 2017. Society of Exploration Geophysicists, 2017. http://dx.doi.org/10.1190/segam2017-17751662.1.
Miskovic, Milan, Miljko Fric Milan Stanojevic, Marija Milosavljevic, and Zoran Mihailovic. "Experimental results of the outdoor near-field acoustic source location." In 2011 19th Telecommunications Forum Telfor (TELFOR). IEEE, 2011. http://dx.doi.org/10.1109/telfor.2011.6143730.
Звіти організацій з теми "Acoustic source location":
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Kim, K. Bayesian Seismoacoustic Source Location: Acoustic Approach. Office of Scientific and Technical Information (OSTI), September 2022. http://dx.doi.org/10.2172/1885650.
Beattie, Alan. Acoustic emission non-destructive testing of structures using source location techniques. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1096442.
In 2015, the Natural Sounds and Night Skies Division (NSNSD) received a request to collect baseline acoustical data at Mesa Verde National Park (MEVE). Between July and August 2015, as well as February and March 2016, three acoustical monitoring systems were deployed throughout the park, however one site (MEVE002) stopped recording after a couple days during the summer due to wildlife interference. The goal of the study was to establish a baseline soundscape inventory of backcountry and frontcountry sites within the park. This inventory will be used to establish indicators and thresholds of soundscape quality that will support the park and NSNSD in developing a comprehensive approach to protecting the acoustic environment through soundscape management planning. Additionally, results of this study will help the park identify major sources of noise within the park, as well as provide a baseline understanding of the acoustical environment as a whole for use in potential future comparative studies. In this deployment, sound pressure level (SPL) was measured continuously every second by a calibrated sound level meter. Other equipment included an anemometer to collect wind speed and a digital audio recorder collecting continuous recordings to document sound sources. In this document, “sound pressure level” refers to broadband (12.5 Hz–20 kHz), A-weighted, 1-second time averaged sound level (LAeq, 1s), and hereafter referred to as “sound level.” Sound levels are measured on a logarithmic scale relative to the reference sound pressure for atmospheric sources, 20 μPa. The logarithmic scale is a useful way to express the wide range of sound pressures perceived by the human ear. Sound levels are reported in decibels (dB). A-weighting is applied to sound levels in order to account for the response of the human ear (Harris, 1998). To approximate human hearing sensitivity, A-weighting discounts sounds below 1 kHz and above 6 kHz. Trained technicians calculated time audible metrics after monitoring was complete. See Methods section for protocol details, equipment specifications, and metric calculations. Median existing (LA50) and natural ambient (LAnat) metrics are also reported for daytime (7:00–19:00) and nighttime (19:00–7:00). Prominent noise sources at the two backcountry sites (MEVE001 and MEVE002) included vehicles and aircraft, while building and vehicle predominated at the frontcountry site (MEVE003). Table 1 displays time audible values for each of these noise sources during the monitoring period, as well as ambient sound levels. In determining the current conditions of an acoustical environment, it is informative to examine how often sound levels exceed certain values. Table 2 reports the percent of time that measured levels at the three monitoring locations were above four key values.
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Watkins, William A., Joseph E. George, Mary Ann Daher, Kristina Mullin, and Darel L. Martin. Whale Call Data for the North Pacific November 1995 through July 1999 Occurrence of Calling Whales and Source Locations from SOSUS and Other Acoustic Systems. Fort Belvoir, VA: Defense Technical Information Center, February 2000. http://dx.doi.org/10.21236/ada375142.
