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Journal articles on the topic 'Acoustic detector'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Gazivoda, Marko, Dinko Oletić, and Vedran Bilas. "Features and Always-On Wake-Up Detectors for Sparse Acoustic Event Detection." Electronics 11, no. 3 (February 6, 2022): 478. http://dx.doi.org/10.3390/electronics11030478.

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The need to understand and manage our surroundings has led to increased interest in sensor networks for the continuous monitoring of events and processes of interest. To reduce the power consumption required for continuous monitoring, dedicated always-on wake-up detectors have been designed, with an emphasis on their low power consumption, simple and robust design, and reliable and accurate detection. An especially interesting application of these wake-up detectors is in detecting acoustic signals. In this paper, we present a study on the features and detectors applicable for the detection of sporadic acoustic events. We perform a state-of-the-art acoustic detector analysis, grouping the detectors based on the features they utilize and their implementations. This analysis shows that acoustic wake-up detectors predominantly utilize spectro-temporal (56%) and temporal features (36%). Following the state-of-the-art analysis, we select two detector architecture candidates for a case study on passing motor vehicle detection. We utilize our previously developed spectro-temporal decomposition detector and develop a novel level-crossing rate detector. The results of the case study shows that the proposed level-crossing rate detector has lower component count (44 compared to 70) and power consumption (9.1 µW compared to 34.6 µW) and is an optimal solution for SNRs over 0 dB.

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2

Fertig, Glenn H. "Photo‐acoustic detector." Journal of the Acoustical Society of America 87, no. 5 (May 1990): 2281. http://dx.doi.org/10.1121/1.399123.

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3

Fertig, Glenn H. "Photo-acoustic detector." Journal of the Acoustical Society of America 89, no. 6 (June 1991): 3034. http://dx.doi.org/10.1121/1.400816.

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4

Riccobene, Giorgio. "The Positioning system for KM3NeT." EPJ Web of Conferences 207 (2019): 07005. http://dx.doi.org/10.1051/epjconf/201920707005.

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The paper describes the implementation of a hybrid positioning system based on tilt and compass sensors, integrated into an electronic board, and an acoustic positioning system to be installed aboard KM3NeT. The acoustic system will be capable to fulfil detector relative and absolute positioning, to provide data for cross-fertilisation with Earth and Sea science (bio-acoustics and environmental monitoring) and to allow studies for neutrino acoustic detection. Tilt and Compass boards installed in each optical module provide information about the DOM orientation.

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5

KARG, T., G. ANTON, K. GRAF, J. HÖSSL, A. KAPPES, U. KATZ, R. LAHMANN, C. NAUMANN, and K. SALOMON. "DESIGN CONSIDERATIONS AND SENSITIVITY ESTIMATES FOR AN ACOUSTIC NEUTRINO DETECTOR." International Journal of Modern Physics A 21, supp01 (July 2006): 212–16. http://dx.doi.org/10.1142/s0217751x06033647.

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We present a Monte Carlo study of an underwater neutrino telescope based on the detection of acoustic signals generated by neutrino induced cascades. This provides a promising approach to instrument large detector volumes needed to detect the small flux of cosmic neutrinos at ultra-high energies (E ≳ 1 EeV ). Acoustic signals are calculated based on the thermo-acoustic model. The signal is propagated to the sensors taking frequency dependent attenuation into account, and detected using a threshold trigger, where acoustic background is included as an effective detection threshold. A simple reconstruction algorithm allows for the determination of the cascade direction and energy. Various detector setups are compared regarding their effective volumes. Sensitivity estimates for the diffuse neutrino flux are presented.

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6

Zhou, Xiaoteng, Shihao Yuan, Changli Yu, Hongyuan Li, and Xin Yuan. "Performance Comparison of Feature Detectors on Various Layers of Underwater Acoustic Imagery." Journal of Marine Science and Engineering 10, no. 11 (October 31, 2022): 1601. http://dx.doi.org/10.3390/jmse10111601.

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Image feature matching is essential in many computer vision applications, and the foundation of matching is feature detection, which is a crucial feature quantification process. This manuscript focused on detecting more features from underwater acoustic imageries for further ocean engineering applications of autonomous underwater vehicles (AUVs). Currently, the mainstream feature detection operators are developed for optical images, and there is not yet a feature detector oriented to underwater acoustic imagery. To better analyze the suitability of existing feature detectors for acoustic imagery and develop an operator that can robustly detect feature points in underwater imageries in the future, this manuscript compared the performance of well-established handcrafted feature detectors and that of the increasingly popular deep-learning-based detectors to fill the gap in the literature. The datasets tested are from the most commonly used side-scan sonars (SSSs) and forward-looking sonars (FLSs). Additionally, the detection idea of these detectors on the acoustic imagery phase congruency (PC) layer was innovatively proposed with the aim of finding a solution that balances detection accuracy and speed. The experimental results show that the ORB (Oriented FAST and Rotated BRIEF) and BRISK (Binary Robust Invariant Scalable Keypoints) detectors achieve the best overall performance, the FAST detector is the fastest, and the PC and Sobel layers are the most favorable for implementing feature detection.

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7

Pudov, A. O., S. A. Sokolov, A. S. Abyzov, A. V. Rybka, and V. E. Kutny. "Digital FPGA-based processing of pulses of gas-filled gamma-radiation detector for acoustic noise suppression." Технология и конструирование в электронной аппаратуре, no. 1-3 (2022): 44–49. http://dx.doi.org/10.15222/tkea2022.1-3.44.

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Gas-filled proportional detectors of ionizing radiation often contain such elements as thin anode wire, which make them sensitive to external acoustic or vibrational impact. This study investigates such sensitivity for the case of the proportional -radiation detectors filled with high-purity xenon gas. The detector demonstrates a dependence of its signal noise on the external acoustic wave frequency, the character of which most likely depends on the design of the detector, i.e. on such parameters as diameter and tension strength of the anode wire, etc. To suppress the negative impact of acoustic noise on the characteristics of the detector, the detector digital signal is processed in a Field-Programmable Gate Array board. The authors investigate the algorithm of «time windows», which allows separating (filtering) low-frequency noise in the output signal of a gas-filled detector, which arises due to the influence of external sound, from the useful signal, i.e. the ionization pulses. This approach allows performing spectral measurements of -radiation with a significant acoustic noise background, when detectors with a conventional analog spectrometric channel cannot handle the task.

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8

Kuczera, H., H. Iglseder, U. Weishaupt, and E. Igenbergs. "Acoustic Penetration and Impact Detector for Micrometeoroid and Space Debris Application." International Astronomical Union Colloquium 85 (1985): 129. http://dx.doi.org/10.1017/s0252921100084487.

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AbstractAn active detector is described which recently has been developed for laboratory impact measurements and which already has been proposed for cosmic dust flight experiments. The detector consists of a very thin penetration foil and an impact plate. By means of piezo detectors the elastic-wave propagation times between the impact location and the piezo detectors can be measured in the foil and in the target. The evaluation of these signals gives the time of the event, the impact location, the projectile velocity, the flight path direction and at least the order of magnitude of mass of the impacting particle. This type of sensor will meet all requirements for particle detection in the diameter range from a few microns (dust particles) up to approx. a few millimeters (space debris) at all velocities. Small-sized projectiles can be detected by sensitive amplifiers. Low-energy electronics including data storage can be used for triangulation and impact time calculation. First experimental results which have been achieved in the Munich Accelerator Facilities will be presented.

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9

Rowan, Sheila. "Current and future status of gravitational wave astronomy - gravitational wave facilities." Proceedings of the International Astronomical Union 2, no. 14 (August 2006): 526–27. http://dx.doi.org/10.1017/s1743921307011684.

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AbstractCurrently a network of interferometric gravitational wave detectors is in operation around the globe, in parallel with existing acoustic bar-type detectors. Searches are underway aimed at the first direct detection of gravitational radiation from astrophysical sources. This paper briefly summarizes the current status of operating gravitational wave facilities, plans for future detector upgrades, and the status of the planned space-based gravitational wave detector LISA.

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10

Baule, Heinrich, and Manfred Borgers. "Acoustic ground vibration detector." Journal of the Acoustical Society of America 87, no. 2 (February 1990): 923. http://dx.doi.org/10.1121/1.398879.

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11

Cook, Bill D., J. Ted Miller, and D. Kent Lewis. "Acoustic microscope with an acousto‐optic array detector." Journal of the Acoustical Society of America 84, S1 (November 1988): S72. http://dx.doi.org/10.1121/1.2026451.

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12

MANTHEI, GERD, JÜRGEN EISENBLÄTTER, and THOMAS SPIES. "EXPERIENCE ON ACOUSTIC WAVE PROPAGATION IN ROCK SALT IN THE FREQUENCY RANGE 1-100 kHz AND CONCLUSIONS WITH RESPECT TO THE FEASIBILITY OF A ROCK SALT DOME AS NEUTRINO DETECTOR." International Journal of Modern Physics A 21, supp01 (July 2006): 30–34. http://dx.doi.org/10.1142/s0217751x06033313.

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Rock salt is a promising material for the detection of acoustic waves generated by interactions of high energy neutrinos. The economical feasibility of an acoustic neutrino detector strongly depends on the spacing between the acoustic sensors. In this paper we report on our experience on acoustic wave propagation and wave attenuation in rock salt in the frequency range of 1 to 100 kHz and some conclusions with respect to the usefulness of rock salt as a neutrino detector. The experience bases on long-term acoustic emission measurements in a salt mine.

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13

Lowes, Gavin James, Jeffrey Neasham, Richie Burnett, Benjamin Sherlock, and Charalampos Tsimenidis. "Passive Acoustic Detection of Vessel Activity by Low-Energy Wireless Sensors." Journal of Marine Science and Engineering 10, no. 2 (February 12, 2022): 248. http://dx.doi.org/10.3390/jmse10020248.

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This paper presents the development of a low-energy passive acoustic vessel detector to work as part of a wireless underwater monitoring network. The vessel detection method is based on a low-energy implementation of Detection of Envelope Modulation On Noise (DEMON). Vessels produce a broad spectrum modulated noise during propeller cavitation, which the DEMON method aims to extract for the purposes of automated detection. The vessel detector design has different approaches with mixtures of analogue and digital processing, as well as continuous and duty-cycled sampling/processing. The detector re-purposes an existing acoustic modem platform to achieve a low-cost and long-deployment wireless sensor network. This integrated communication platform enables the detector to switch between detection/communication mode seamlessly within software. The vessel detector was deployed at depth for a total of 84 days in the North Sea, providing a large data set, which the results are based on. Open sea field trial results have shown detection of single and multiple vessels with a 94% corroboration rate with local Automatic Identification System (AIS) data. Results showed that additional information about the detected vessel such as the number of propeller blades can be extracted solely based on the detection data. The attention to energy efficiency led to an average power consumption of 11.4 mW, enabling long term deployments of up to 6 months using only four alkaline C cells. Additional battery packs and a modified enclosure could enable a longer deployment duration. As the detector was still deployed during the first UK lockdown, the impact of COVID-19 on North Sea fishing activity was captured. Future work includes deploying this technology en masse to operate as part of a network. This could afford the possibility of adding vessel tracking to the abilities of the vessel detection technology when deployed as a network of sensor nodes.

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14

Yao, Shuai, and Yinjia Liu. "A Novel Feature-Based Detector for Underwater Acoustic Beacon Signals Using Superimposed Envelope Spectrum of Multi-Pulses." Journal of Marine Science and Engineering 9, no. 12 (November 28, 2021): 1337. http://dx.doi.org/10.3390/jmse9121337.

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For tackling the challenge of in-time searching a sea-crashed plane, it is critical to develop a convenient and reliable detector for the underwater beacon signal. In the application of signal detection, a conventional detector such as linear correlation (LC) is used based on the assumption of Gaussian white noise, but it has turned out to be a poor choice in a sophisticated underwater environment. To address this issue, a novel feature-based detector using superimposed envelope spectrum (SES) of multi-pulses is proposed in this paper. The proposed detector firstly extracts the envelopes of the received multi-pulse signals and superimposes the envelopes according to the known period. Then, the harmonic features of the SES are derived and utilized in the feature judgment to make the final decision. The proposed method is evaluated together with several existing state-of-the-art detectors, including the matched filter (MF), the generalized likelihood ratio test (GRLT) detector, and the periodogram of the directly dislocation superposition (PDDS) detectors with constant false alarm probability. Compared with the conventional detectors, it is found that the proposed SES detector is more robust against the colored noise, the random phase, and the channel distortions caused by the sophisticated underwater environment. Simulation results show that, given a detection probability value of 90% and a false alarm probability value of 1%, the proposed detector shows a gain of 3–12 dB compared with the best one of the MF, GRLT, and the PDDS detectors under distorted channels in terms of signal-to-noise ratio (SNR) requirements, respectively. Experimental results based on lake trial data have also verified the validity and feasibility of the proposed feature-based detector.

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15

Van Elewyck, Véronique. "The Antares And Km3Net Neutrino Telescopes: Status And Outlook For Acoustic Studies." EPJ Web of Conferences 216 (2019): 01004. http://dx.doi.org/10.1051/epjconf/201921601004.

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The ANTARES detector has been operating continuously since 2007 in the Mediterranean Sea, demonstrating the feasibility of an undersea neutrino telescope. Its superior angular resolution in the reconstruction of neutrino events of all flavors results in unprecedented sensitivity for neutrino source searches in the southern sky at TeV energies, so that valuable constraints can be set on the origin of the cosmic neutrino flux discovered by theIceCube detector. The next generation KM3NeT neutrino telescope is now under construction, featuring two detectors with the same technology but different granularity: ARCA designed to search for high energy (TeV-PeV) cosmic neutrinos and ORCA designed to study atmospheric neutrino oscillations at the GeV scale, focusing on the determination of the neutrino mass hierarchy. Both detectors use acoustic devices for positioning calibration, and provide testbeds for acoustic neutrino detection.

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16

Kieβling, Dominik, and Robert Lahmann. "Simulation studies for large scale acoustic neutrino detectors." EPJ Web of Conferences 216 (2019): 04002. http://dx.doi.org/10.1051/epjconf/201921604002.

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The AMADEUS system is a submarine acoustic array that was operated from 2008 until 2015 as a part of the ANTARES neutrino telescope in the Mediterranean Sea. Its design goal was to investigate the feasibility of acoustic neutrino detection in the deep sea. The data taken during its eight years of operation provide a wealth of information for setting up realistic simulations of future acoustic neutrino detectors. Using in addition simulations of neutrino interactions in water, various potential acoustic neutrino detector designs were investigated and methods for suppressing background and reconstructing energy and direction of incoming neutrinos were developed. In this article, some recent results will be presented.

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17

Thomas, Charles E. "Acoustic tool touch detector with minimized detection delay." Journal of the Acoustical Society of America 84, no. 2 (August 1988): 798. http://dx.doi.org/10.1121/1.396783.

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18

Vick, K. W. "Acoustic location fixing insect detector." Journal of the Acoustical Society of America 99, no. 6 (1996): 3277. http://dx.doi.org/10.1121/1.414906.

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19

Heavner, Matthew. "A new acoustic bat detector." Journal of the Acoustical Society of America 117, no. 4 (April 2005): 2552. http://dx.doi.org/10.1121/1.4788489.

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20

Philippe, François. "Differential detector of acoustic pressure." Journal of the Acoustical Society of America 88, no. 5 (November 1990): 2509. http://dx.doi.org/10.1121/1.400060.

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21

Soltie, Leland P. "Surface acoustic wave Doppler detector." Journal of the Acoustical Society of America 88, no. 4 (October 1990): 2051. http://dx.doi.org/10.1121/1.400122.

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22

Ueno, Hiroshi. "ACOUSTIC EMISSION DETECTOR AND CONTROLLER." Journal of the Acoustical Society of America 132, no. 6 (2012): 4092. http://dx.doi.org/10.1121/1.4770411.

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23

DuVall, Dale R. "Acoustic obstruction detector and method." Journal of the Acoustical Society of America 83, no. 6 (June 1988): 2469. http://dx.doi.org/10.1121/1.396340.

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24

Bostock, Peter. "Acoustic detector with noise cancellation." Journal of the Acoustical Society of America 122, no. 3 (2007): 1317. http://dx.doi.org/10.1121/1.2781442.

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25

Sun, Cheng-Liang, K. H. Lam, J. Wang, H. L. W. Chan, X. Z. Zhao, and C. L. Choy. "Precision piezoelectric acoustic position detector." Sensors and Actuators A: Physical 128, no. 2 (April 2006): 290–95. http://dx.doi.org/10.1016/j.sna.2006.01.043.

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26

Krasylnikov, Oleg, Viktor Beregun, and Tetiana Polobiuk. "Analysis of the characteristics of а cumulant system for liquid leakage detection in pipelines." Problems of General Energy 2022, no. 1-2 (May 22, 2022): 105–14. http://dx.doi.org/10.15407/pge2022.01-02.105.

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Acoustic noise signals that are generated by fluid leakage due to a leak in the pipeline have in general case non-Gaussian distribution, so for the further development of acoustic contact leak detection together with correlation-spectral methods it is advisable to use methods used for probabilistic analysis of non-Gaussian processes, in particular cumulant methods of noise diagnostics. The principle of cumulant method of liquid leakage detection in pipelines during operation is considered, which is based on the use of cumulants to distinguish acoustic noise signals registered at the control points of the pipeline section, namely on use of the distance between the cumulant vectors of signals and the mutual correlation function of signals. The block diagram of the cumulant system for liquid leakage detection is given. In order to use the cumulant leakage detection system for power plant diagnosis, a layout of the acoustic leak detection system has been developed, which is a hardware-software complex that performs the collection, registration and statistical processing of acoustic noise signals, as a result of which a decision is made on the presence or absence of leakage, the parameters of the hardware part of the system were given. To obtain estimates of the statistical characteristics of real leakage signals, an installation was used that allows to perform physical modeling of fluid leakage in a pipeline in standing water under sustainable conditions, with fixed leak dimensions and pressure level control. Acoustic noise generated by the flow of fluid moving in the heat pipeline is used as interference. Using the statistical characteristics of real signals, the characteristics of the cumulant leakage detection system were determined – leakage signal attenuation; the maximum distance between the transducers at which the leakage is detected; detector sensitivity; the influence of bandpass filtering on these characteristics is investigated. Keywords: acoustic contact leak detection, liquid leakage detector, acoustic noise signals, cumulant analysis

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27

Chin, W. C. "MWD surface signal detector having enhanced acoustic detection means." Journal of the Acoustical Society of America 104, no. 6 (December 1998): 3155. http://dx.doi.org/10.1121/1.424247.

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28

Madhusudhana, Shyam, Brian S. Miller, Meghan G. Aulich, and Nat Kelly. "Automated detection of blue whale D-calls using deep learning with a double-observer performance assessment." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A29. http://dx.doi.org/10.1121/10.0010552.

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An automated algorithm for passive acoustic detection of blue whale D-calls is developed based on established deep learning methods for image recognition via the DenseNet architecture. Koogu—an open-source Python package—was used for developing the detector. The detector was trained on annotated acoustic recordings from the Antarctic, and the performance of the detector was assessed by calculating precision and recall using a separate independent dataset also from the Antarctic. Detections from both the human analyst and automated detector were then inspected by a more experienced analyst to identify any calls missed by either approach and to adjudicate whether the apparent false-positive detections from the automated approach were actually true-positives. Lastly, an additional performance assessment was conducted using double-platform methods (via a closed-population Huggins mark recapture model) to assess the probability of detection of both the human analyst and automated detector, based on the assumption of false-positive-free and reconciled detections. According to our double-platform analysis, the automated detector performed very well with higher recall and fewer false-positives that the original human analyst.

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29

Sekhar, Laligam N. "Acoustic aneurysm detector and associated method." Journal of the Acoustical Society of America 90, no. 1 (July 1991): 629. http://dx.doi.org/10.1121/1.402321.

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30

Thurbide, Kevin B., Peter D. Wentzell, and Walter A. Aue. "Acoustic Flame Detector for Gas Chromatography." Analytical Chemistry 68, no. 17 (January 1996): 2758–65. http://dx.doi.org/10.1021/ac951243q.

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31

Kumar, Sumit, Aditya Vijaykumar, and Alexander H. Nitz. "Detecting Baryon Acoustic Oscillations with Third-generation Gravitational Wave Observatories." Astrophysical Journal 930, no. 2 (May 1, 2022): 113. http://dx.doi.org/10.3847/1538-4357/ac5e34.

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Abstract We explore the possibility of detecting baryon acoustic oscillations (BAO) solely from gravitational wave (GW) observations of binary neutron star mergers with third-generation (3G) GW detectors such as the Cosmic Explorer and the Einstein Telescope. These measurements would provide a new independent probe of cosmology. The detection of the BAO peak with current-generation GW detectors (solely from GW observations) is not possible because i) unlike galaxies, the GW mergers are poorly localized, and ii) there are not enough merger events to probe the BAO length scale. With the 3G GW detector network, it is possible to observe ∼  ( 1000 ) binary neutron star mergers per year that are localized well within one square degree in the sky for redshift z ≤ 0.3. We show that 3G observatories will enable precision measurements of the BAO feature in the large-scale two-point correlation function; the effect of BAO can be independently detected at different redshifts, with a log-evidence ratio of ∼23, 17, or 3, favoring a model with a BAO peak at redshift of 0.2, 0.25, or 0.3, respectively, using a redshift bin corresponding to a shell of thickness 150h −1 Mpc.

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32

Chen, Chin-Ning, Katy Ferguson, Anton Wiranata, Mark Shaw, Wan-Eih Huang, George Chiu, Patricia Davies, and Jan P. Allebach. "Using Acoustic Information to Diagnose the Health of A Printer." Electronic Imaging 2020, no. 15 (January 26, 2020): 353–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.15.color-352.

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We present a sound-based anomaly detection system to diagnose printer health. Also, we improve the model performance by using acoustic data augmentation. We first use the detector to extract the important acoustic information from the input printer sound. Second, we use principal component analysis to do feature extraction. Third, we feed the extracted features from the previous step into the two different anomaly detection models to evaluate the model performances. Finally, we go through the same system pipeline with different augmented training data to see whether or not acoustic data augmentation can improve the model performance.

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33

Shinonaga, Hideyuki. "Coherent surface acoustic wave unique word detector." Journal of the Acoustical Society of America 94, no. 6 (December 1993): 3536. http://dx.doi.org/10.1121/1.407150.

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34

Barkhatov, V. A., A. S. Semukhin, and R. Ya Valieva. "Ultrasonic Measuring Facility. Detector of Acoustic Signals." Russian Journal of Nondestructive Testing 39, no. 8 (August 2003): 596–98. http://dx.doi.org/10.1023/b:runt.0000016385.78544.1d.

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35

Fabian, Carl E., and Philip M. Anderson. "Surgical implement detector utilizing an acoustic marker." Journal of the Acoustical Society of America 97, no. 3 (March 1995): 2018. http://dx.doi.org/10.1121/1.411988.

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36

Felizardo, M., R. C. Martins, A. R. Ramos, T. Morlat, T. A. Girard, F. Giuliani, D. Limagne, G. Waysand, and J. G. Marques. "Improved acoustic instrumentation of the SIMPLE detector." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 585, no. 1-2 (January 2008): 61–68. http://dx.doi.org/10.1016/j.nima.2007.11.018.

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37

Mallekh, R., J. P. Lagardère, J. P. Eneau, and C. Cloutour. "An acoustic detector of turbot feeding activity." Aquaculture 221, no. 1-4 (May 2003): 481–89. http://dx.doi.org/10.1016/s0044-8486(03)00074-7.

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38

Vetelino, J. F., R. K. Lade, and R. S. Falconer. "Hydrogen Sulfide Surface Acoustic Wave Gas Detector." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 34, no. 2 (March 1987): 156–61. http://dx.doi.org/10.1109/t-uffc.1987.26927.

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39

Belikov, A. V., A. V. Erofeev, A. V. Skripnik, Yu A. Sinel’nik, and Yu V. Sudenkov. "A new fiber acoustic laser-energy detector." Technical Physics Letters 23, no. 2 (February 1997): 113–14. http://dx.doi.org/10.1134/1.1261582.

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40

Yousif Al-Aboosi, Yasin, Mustafa Sami Ahmed, and Ammar Ali Sahrab. "NEAR–OPTIMUM DETECTION OF SIGNALS IN UNDERWATER ACOUSTIC NOISE USING LOCALLY OPTIMAL DETECTOR IN TIGERS RIVER." Journal of Engineering and Sustainable Development 27, no. 1 (January 1, 2023): 19–27. http://dx.doi.org/10.31272/jeasd.27.1.2.

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Signal detection has been considered important in under-water signal processing and digital communications, and depending upon noise statistics’ knowledge, near-optimum signal detections in the under-water acoustic noises (UWANs) may be realized in a more effective manner. The theory of the normal (i.e. Gaussian) noise permits using matched filter (MF) detectors; for that reason, a locally optimal (LO) detector has been designed in the present work for improving the probability of the detection ( based on knowing the probability density function (PDF) of noise. Under-water noise that has been utilized for the validation represents the real data that had been gathered from the sea with the use of the broad-band hydrophones at Abo Dali district -Kazem Al Ali Village-Tigris Beaches-Baghdad-Iraq. The LO detector performance is compared after that to the conventional matched filter detector and those have been assessed based on their values. For time-varying signals, the probability of false alarms has been identified as 0.010, and of 90%, energy-to-noise ratios (ENRs) of LO are more efficient compared to the ones of Matched Filter by 4.1dB and for the signals with a fixed frequency, LO is more efficient compared to matched filter by 4.7dB.

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41

Svatos, Jakub, Jan Holub, and Jan Belak. "System for an acoustic detection, localisation and classification." ACTA IMEKO 10, no. 2 (June 29, 2021): 62. http://dx.doi.org/10.21014/acta_imeko.v10i2.1041.

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<p class="Abstract">Currently, acoustic detection techniques of gunshots (gunshot detection and its classification) are increasingly being used not only for military applications but also for civilian purposes. Detection, localisation, and classification of a dangerous event such as gunshots employing acoustic detection is a perspective alternative to visual detection, which is commonly used. In some situations, to detect and localise the source of a gunshot, an automatic acoustic detection system, which can classify the caliber, may be preferable. This paper presents a system for acoustic detection, which can detect, localise and classify acoustic events such as gunshots. The system has been tested in open and closed shooting ranges and tested firearms are 9 mm short gun, 6.35 mm short gun, .22 short gun, and .22 rifle gun with various subsonic and supersonic ammunition. As ‘false alarms’, sets of different impulse acoustic events like door slams, breaking glass, etc. have been used. Localisation and classification algorithms are also introduced. To successfully classify the tested acoustic signals, Continuous Wavelet and Mel Frequency Transformation methods have been used for the signal processing, and the fully two-layer connected neural network has been implemented. The results show that the acoustic detector can be used for reliable gunshot detection, localisation, and classification.</p>

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Karpinsky, Vladimir, and Vladimir Asming. "Results of the infrasonic array on the Valaam Island primary data processing." Российский сейсмологический журнал [Russian Journal of Seismology] 2, no. 1 (March 18, 2020): 85–91. http://dx.doi.org/10.35540/2686-7907.2020.1.08.

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The infrasound array VALS developed in Kola Branch GS RAS has been installed in June 2016 on the Valaam Island in addition to the continuously operating seismic station VALR. The array consists of 3 spaced low-frequency microphones. The data with a sampling rate of 100 Hz is stored continuously at the acquisition computer; the timing is carried out using GPS. In addition to the acquisition system, an infrasound signal detector is installed on the computer. It works in near real-time mode and enables us to find signals and compute their back azimuths. At the end of 2018, a new version of the detector was developed at the Kola Branch GS RAS. The detector began to work much faster, which enabled us to carry out data processing for 2.5 years in two frequency ranges in a short time. The main task of the array is acoustic monitoring, the detection of infrasound events, the determination of their parameters, and the selection of events of natural origin. The data are also used (in combination with the VALR seismic station data) to locate near seismic events, especially weak ones. The analysis of the obtained data revealed the prevailing directions to the signal sources. The change of directions to sources in time was investigated, seasonal features were revealed. Acoustic events were detected in the frequency bands 1–5 Hz and 10–20 Hz, and a significant difference was found in the azimuthal distribution of events for these ranges. A joint analysis of acoustic and seismic data showed that the part of events with both acoustic and seismic components is low – it is almost completely exhausted by career explosions. It was also noted that in addition to explosions in nearby quarries (Kuznechnoye, Pitkäranta) located at a distance of 50–60 km, according to acoustic data, events corresponding to explosions at quarries located at a distance of 100 km or more were repeatedly identified.

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Buhaiov, М. V., V. V. Branovytskyi, and Y. O. Khorenko. "ANALYSIS OF THE EFFICIENCY OF SPECTRAL ESTIMATION METHODS FOR DETECTION OF UAV ACOUSTIC SIGNALS." Проблеми створення, випробування, застосування та експлуатації складних інформаційних систем, no. 19 (January 15, 2021): 4–15. http://dx.doi.org/10.46972/2076-1546.2020.19.01.

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One of the most important components of counteracting small unmanned aerial vehicles is their reliable detection. You can use propeller noise to detect such objects at short distances. An energy or harmonic detector is used to receive unmanned aerial vehicles acoustic emission. At low signal-to-noise ratios , which is most common in practice, the harmonic detector provides a higher probability of detection compared to energy. The principle of the harmonic detector is based on spectral analysis of acoustic signals. A mathematical model of the acoustic signal of an aircraft-type unmanned aerial vehicles is proposed. It is shown that at short time intervals (tens of milliseconds) such signals can be considered as stationary and for its analysis can be used known methods of spectral estimation. Nonparametric, parametric and subspace methods of spectral estimation are considered for processing of acoustic emission of unmanned aerial vehicles. To conduct a comparative analysis of different methods of spectral estimation, a statistical quality index was used, which can be calculated as a variation of the estimation of power spectral density. This index characterizes the method of spectral estimation in terms of frequency resolution and the ability to detect harmonic components of the signal into noise and not create interference that exceeds the amplitude of the signal. As a result of researches it was established that at high signal-to-noise ratios parametric methods are more effective in comparison with nonparametric. However, such a statement will be valid only if the correct order of the model. It is shown that the use of spatial methods is impractical for the analysis of acoustic signals of unmanned aerial vehicles. The use of the value of the statistical quality indicator as a threshold for deciding on the presence or absence of the acoustic signal of the unmanned aerial vehicles in the adopted implementation and its further processing should be used at SNR values greater than 5 dB.

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Shockley, Richard C., Paul J. Gendron, and J. Mark Stevenson. "Detection of an undersea acoustic communications network by an energy detector." Journal of the Acoustical Society of America 141, no. 6 (June 2017): 4136–47. http://dx.doi.org/10.1121/1.4984102.

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Gao, Xin-Xia, Jin-Ming Cui, Ming-Zhong Ai, Yun-Feng Huang, Chuan-Feng Li, and Guang-Can Guo. "An Acoustic Sensor Based on Active Fiber Fabry–Pérot Microcavities." Sensors 20, no. 20 (October 11, 2020): 5760. http://dx.doi.org/10.3390/s20205760.

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We demonstrate an active acoustic sensor based on a high-finesse fiber Fabry–Pérot micro-cavity with a gain medium. The sensor is a compacted device lasing around 1535 nm by external optical pumping. The acoustic pressure acting on the sensor disturbs the emitted laser frequency, which is subsequently transformed to beat signals through a delay-arm interferometer, and directly detected by a photo-detector. In this configuration, the sensing device exhibits a high sensitivity of 2.6 V/Pa and a noise equivalent acoustic signal level of 230 μPa/Hz1/2 at a frequency of 4 kHz. Experimental results provide a wide frequency response from 100 Hz to 18 kHz. As the sensor works at communication wavelength and the output laser can be electrically tuned in the 10 nm range, a multi-sensor network can be easily constructed with the dense wavelength division multiplexing devices. Extra lasers or demodulators are unnecessary thus the proposed sensor is low cost and easy fabrication. The proposed sensor shows broad applications prospect in remote oil and gas leakage exploration, photo-acoustic spectrum detection, and sound source location.

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Karimanzira, Divas, Helge Renkewitz, David Shea, and Jan Albiez. "Object Detection in Sonar Images." Electronics 9, no. 7 (July 21, 2020): 1180. http://dx.doi.org/10.3390/electronics9071180.

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The scope of the project described in this paper is the development of a generalized underwater object detection solution based on Automated Machine Learning (AutoML) principles. Multiple scales, dual priorities, speed, limited data, and class imbalance make object detection a very challenging task. In underwater object detection, further complications come in to play due to acoustic image problems such as non-homogeneous resolution, non-uniform intensity, speckle noise, acoustic shadowing, acoustic reverberation, and multipath problems. Therefore, we focus on finding solutions to the problems along the underwater object detection pipeline. A pipeline for realizing a robust generic object detector will be described and demonstrated on a case study of detection of an underwater docking station in sonar images. The system shows an overall detection and classification performance average precision (AP) score of 0.98392 for a test set of 5000 underwater sonar frames.

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Oh, Yoo Rhee, Kiyoung Park, and Jeon Gyu Park. "Online Speech Recognition Using Multichannel Parallel Acoustic Score Computation and Deep Neural Network (DNN)- Based Voice-Activity Detector." Applied Sciences 10, no. 12 (June 14, 2020): 4091. http://dx.doi.org/10.3390/app10124091.

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This paper aims to design an online, low-latency, and high-performance speech recognition system using a bidirectional long short-term memory (BLSTM) acoustic model. To achieve this, we adopt a server-client model and a context-sensitive-chunk-based approach. The speech recognition server manages a main thread and a decoder thread for each client and one worker thread. The main thread communicates with the connected client, extracts speech features, and buffers the features. The decoder thread performs speech recognition, including the proposed multichannel parallel acoustic score computation of a BLSTM acoustic model, the proposed deep neural network-based voice activity detector, and Viterbi decoding. The proposed acoustic score computation method estimates the acoustic scores of a context-sensitive-chunk BLSTM acoustic model for the batched speech features from concurrent clients, using the worker thread. The proposed deep neural network-based voice activity detector detects short pauses in the utterance to reduce response latency, while the user utters long sentences. From the experiments of Korean speech recognition, the number of concurrent clients is increased from 22 to 44 using the proposed acoustic score computation. When combined with the frame skipping method, the number is further increased up to 59 clients with a small accuracy degradation. Moreover, the average user-perceived latency is reduced from 11.71 s to 3.09–5.41 s by using the proposed deep neural network-based voice activity detector.

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Bautista-Durán, Marta, Joaquín García-Gómez, Roberto Gil-Pita, Inma Mohíno-Herranz, and Manuel Rosa-Zurera. "Energy-Efficient Acoustic Violence Detector for Smart Cities." International Journal of Computational Intelligence Systems 10, no. 1 (2017): 1298. http://dx.doi.org/10.2991/ijcis.10.1.89.

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CHEN, JIANSHE, CATHRINE KARLSSON, and MALCOLM POVEY. "ACOUSTIC ENVELOPE DETECTOR FOR CRISPNESS ASSESSMENT OF BISCUITS." Journal of Texture Studies 36, no. 2 (April 2005): 139–56. http://dx.doi.org/10.1111/j.1745-4603.2005.00008.x.

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Anosov, A. A., A. A. Sharakshane, A. S. Kazanskii, A. D. Mansfel’d, A. G. Sanin, and A. S. Sharakshane. "Instrument function of a broadband acoustic thermometric detector." Acoustical Physics 62, no. 5 (September 2016): 626–32. http://dx.doi.org/10.1134/s1063771016050018.

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