Academic literature on the topic 'Air noise detector'
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Journal articles on the topic "Air noise detector"
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Dong, Wei, Zi Wei Zhou, and Zheng Gan Zhou. "Application of Phase-Sensitivity Detector in Air-Coupled Ultrasonic Testing." Applied Mechanics and Materials 170-173 (May 2012): 3125–29. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.3125.
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The signal to noise ration of air-coupled ultrasonic testing is very poor and there is long time pulse residue, so it need adopt appropriate signal processing method to enhancing the SNR of received signal. Factors, which affect the received signal in ultrasonic testing process, is analyzed, phase sensitivity detection technology is presented to process the received signal, and ultrasonic testing information can be acquired by the calculation of phase signal. The principle of super-heterodyne receiver and phase sensitivity detector is introduced; some problem which should be pay attention in ultrasonic testing process is explained. Based on the research result, air-coupled ultrasonic testing system with phase sensitivity detector is constituted. Experiment results of image testing on carbon fiber reinforced plastic plate indicated that, phase sensitivity detection technology can improved signal to noise ratio of system and testing effect in evidence.
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Mehmet, Moritz, and Henning Vahlbruch. "The Squeezed Light Source for the Advanced Virgo Detector in the Observation Run O3." Galaxies 8, no. 4 (November 26, 2020): 79. http://dx.doi.org/10.3390/galaxies8040079.
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From 1 April 2019 to 27 March 2020, the Advanced Virgo detector, together with the two Advanced LIGO detectors, conducted the third joint scientific observation run O3, aiming for further detections of gravitational wave signals from astrophysical sources. One of the upgrades to the Virgo detector for O3 was the implementation of the squeezed light technology to improve the detector sensitivity beyond its classical quantum shot noise limit. In this paper, we present a detailed description of the optical setup and performance of the employed squeezed light source. The squeezer was constructed as an independent, stand-alone sub-system operated in air. The generated squeezed states are tailored to exhibit high purity at intermediate squeezing levels in order to significantly reduce the interferometer shot noise level while keeping the correlated enhancement of quantum radiation pressure noise just below the actual remaining technical noise in the Advanced Virgo detector.
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Schulze-Briese, Clemens. "Hybrid photon-counting detectors accelerating synchrotron and laboratory science." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C692. http://dx.doi.org/10.1107/s2053273314093073.
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Since their introduction in 2007, single-photon-counting PILATUS hybrid pixel detectors and MYTHEN micro-strip detectors have transformed synchrotron research by enabling new data acquisition modes and even novel experiments. At the same time data quality has improved due to the noise-free operation and the direct conversion of the X-rays, while millisecond readout time and high-frame rates allow for hitherto unknown data acquisition speed and efficiency. Instant retrigger technology, introduced in 2012 with the PILATUS3 further improves the count-rate capabilities to 107 photons/sec/pixel, allowing single photon counting at brightest synchrotron beamlines. On the other hand, the unique properties of these detectors have also been explored to improve and accelerate diffraction and scattering experiments in the laboratory. The noise-free operation is a key advantage in combination with the low-flux laboratory sources, allowing for high-throughput and optimal data quality. The modular architecture of the detectors and the vacuum-compatibility of the PILATUS detector modules are ideal prerequisites to design specific detector solutions. In-vacuum operation is ideally suited to eliminate all background arising from windows and air, resulting in optimal signal-to-noise ratio. Furthermore, the lowest accessible X-ray energy is no longer limited by windows and air absorption but rather by the beamline spectrum and the detector. The minimal X-ray energy compatible with noise-free counting for the PILATUS is below 2 keV. With EIGER, hybrid pixel detectors will enter into a new realm of spatial and temporal resolution. Continuous read-out with frame rates up to 3000 Hz and a pixel size of 75 µm are ideally suited for all scanning type of imaging experiments, time-resolved and high-throughput experiments as well as for outrunning radiation damage. A short overview of the novel aspects of the detector technology will be given. The main emphasize of the presentation will be on the science enabled by the combination of advanced source, optics and detector instrumentation.
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Dougakiuchi, Tatsuo, and Naota Akikusa. "Application of High-Speed Quantum Cascade Detectors for Mid-Infrared, Broadband, High-Resolution Spectroscopy." Sensors 21, no. 17 (August 24, 2021): 5706. http://dx.doi.org/10.3390/s21175706.
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Broadband, high-resolution, heterodyne, mid-infrared absorption spectroscopy was performed with a high-speed quantum cascade (QC) detector. By strictly reducing the device capacitance and inductance via air-bridge wiring and a small mesa structure, a 3-dB frequency response over 20 GHz was obtained for the QC detector, which had a 4.6-μm peak wavelength response. In addition to the high-speed, it exhibited low noise characteristics limited only by Johnson–Nyquist noise, bias-free operation without cooling, and photoresponse linearity over a wide dynamic range. In the detector characterization, the noise-equivalent power was 7.7 × 10−11 W/Hz1/2 at 4.6 μm, and it had good photoresponse linearity up to 250 mW, with respect to the input light power. Broadband and high-accuracy molecular spectroscopy based on heterodyne detection was demonstrated by means of two distributed-feedback 4.5-μm QC lasers. Specifically, several nitrous oxide absorption lines were acquired over a wavelength range of 0.8 cm−1 with the wide-band QC detector.
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Trozzo, Lucia, and Francesca Badaracco. "Seismic and Newtonian Noise in the GW Detectors." Galaxies 10, no. 1 (January 22, 2022): 20. http://dx.doi.org/10.3390/galaxies10010020.
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Gravitational wave detectors aim to measure relative length variations of the order of ΔL/L≃10−21, or less. Thus, any mechanism that is able to reproduce such a tiny variation can, in principle, threaten the sensitivity of these instruments, representing a source of noise. There are many examples of such noise, and seismic and Newtonian noise are among these and will be the subject of this review. Seismic noise is generated by the incessant ground vibration that characterizes Earth. Newtonian noise is instead produced by the tiny fluctuations of the Earth’s gravitational field. These fluctuations are generated by variations of air and soil density near the detector test masses. Soil density variations are produced by the same seismic waves comprising seismic noise. Thus, it makes sense to address these two sources of noise in the same review. An overview of seismic and Newtonian noise is presented, together with a review of the strategies adopted to mitigate them.
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Frajuca, Carlos, Fabio da Silva Bortoli, and Nadja Simao Magalhaes. "The Analysis of a Proposed Experiment to Measure the Speed of Gravity in Short Distances." Advances in High Energy Physics 2022 (May 25, 2022): 1–8. http://dx.doi.org/10.1155/2022/1991119.
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In order to investigate the speed of gravitational signals travelling in air or through a different medium two experiments were designed. One of the experiments contains 2 masses rotating at very high speed and in the other experiment a sapphire bar will vibrate, in both cases they will emit a periodic tidal gravitational signal and one sapphire device that behaves as a detector, which are suspended in vacuum and cooled down to 4.2 K will act as a detector. The vibrational amplitude of the sapphire detector device is measured by an microwave signal with ultralow phase-noise that uses resonance in the whispering gallery modes inside the detector device. Sapphire has a quite high mechanical Q and electrical Q which implies a very narrow detection band thus reducing the detection sensitivity. A new detector shape for the detector device is presented in this work, yielding a detection band of about half of the device vibrational frequency. With the aid of a Finite Element Program the normal mode frequencies of the detector can be calculated with high precision. The results show a similar expected sensitivity between the two experimental setup, but the experiment with the vibration masses is more stable in frequency then it is chosen for the experimental setup to measure the speed of gravity in short distances. Then a more precise analysis is made with this experiment reaching a signal-noise ratio of 10 at a frequency of 5000 Hz.
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Leisos, Antonios, Stavros Nonis, Apostolos Tsirigotis, George Bourlis, Kostas Papageorgiou, Ioannis Gkialas, Ioannis Manthos, and Spyros Tzamarias. "Hybrid Detection of High Energy Showers in Urban Environments." Universe 5, no. 1 (December 22, 2018): 3. http://dx.doi.org/10.3390/universe5010003.
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The Astroneu array comprises 9 large charged particle detectors and 3 RF antennas arranged in three autonomous stations operating at the University Campus of the Hellenic Open University in the city of Patras. Each station of the array detects extensive air showers with primary energy threshold of about 10 TeV, while double station coincidence events select showers with energies higher than 10 3 TeV. In such an environment, the radio detection of air showers is challenging. The RF signals besides being extremely weak they also suffer from strong human made electromagnetic noise. In this work, we present the analysis of double station coincidence events and we study the correlation of the RF data with the particle detectors data. We use the experimental information from the particle detectors and the antennas to select very high energy showers and we compare the timing of the RF signals with the timing of the particle detector signals as well as the strength of the RF signals with the simulation predictions.
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Fiscante, Nicomino, Pia Addabbo, Carmine Clemente, Filippo Biondi, Gaetano Giunta, and Danilo Orlando. "A Track-Before-Detect Strategy Based on Sparse Data Processing for Air Surveillance Radar Applications." Remote Sensing 13, no. 4 (February 12, 2021): 662. http://dx.doi.org/10.3390/rs13040662.
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In this paper we consider the tracking problem of a moving target competing against noise and clutter in a surveillance radar scenario. For a single array-antenna multiple-target tracking system and according to the Track-Before-Detect paradigm, we present a novel approach based on a three-stage processing chain that involves the Sparse Learning via Iterative Minimization algorithm, the k-means clustering method and the ad hoc detector by exploiting the sparse nature of the operating scenario. Under the latter assumption, the detection strategy declares the presence of targets subsequently to the retrieval of their corresponding tracks performed by jointly processing the received echoes of multiple consecutive radar scans. Simulation results show that the proposed approach is able to provide good tracking and detection capabilities for different multiple target trajectories with low Signal-to-Interference-plus-Noise ratio and results in providing advantages when compared to a number of other reference Track-Before-Detect strategies based on sparse data processing techniques.
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SUGAI, H., K. FUJIKI, K. ISHII, S. MATSUYAMA, A. TERAKAWA, Y. KIKUCHI, M. FUJIWARA, et al. "IMPROVEMENT OF THE DETECTION EFFICIENCY OF THE IN-AIR SUBMILLI-PIXE CAMERA FOR BIOLOGICAL APPLICATIONS." International Journal of PIXE 22, no. 01n02 (January 2012): 37–43. http://dx.doi.org/10.1142/s0129083512400050.
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The detection efficiency of the submilli-PIXE camera was improved by installing a new X-ray detector with a smaller distance from specimens. The distortion of elemental images caused by position dependent detection efficiency was corrected by estimating the detection efficiency based on the geometrical configuration of the detection system. The detection efficiency of characteristic X-rays from heavy elements such as iron and bromine became from 11 to 23 times higher than the previous system. The signal to noise ratios was improved from 1.8 to 2.5 times higher and detection limit was also decreased from 1/8 to 1/6 compared to the previous system. The in-air submilli-PIXE camera with improved detection system can be useful to biological applications.
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Bastian-Querner, Benjamin, Lucas S. Binn, Sebastian Böser, Jannes Brostean-Kaiser, Dustin Hebecker, Klaus Helbing, Timo Karg, et al. "The Wavelength-Shifting Optical Module." Sensors 22, no. 4 (February 11, 2022): 1385. http://dx.doi.org/10.3390/s22041385.
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The Wavelength-shifting Optical Module (WOM) is a novel photosensor concept for the instrumentation of large detector volumes with single-photon sensitivity. The key objective is to improve the signal-to-noise ratio, which is achieved by decoupling the photosensitive area of a sensor from the cathode area of its photomultiplier tube (PMT). The WOM consists of a transparent tube with two PMTs attached to its ends. The tube is coated with wavelength-shifting paint that absorbs ultraviolet photons with nearly 100% efficiency. Depending on the environment, e.g., air (ice), up to 73% (41%) of the subsequently emitted optical photons can be captured by total internal reflection and propagate towards the PMTs, where they are recorded. The optical properties of the paint, the geometry of the tube, and the coupling of the tube to the PMTs have been optimized for maximal sensitivity based on theoretical derivations and experimental evaluations. Prototypes were built to demonstrate the technique and to develop a reproducible construction process. Important measurable characteristics of the WOM are the wavelength-dependent effective area, the transit time spread of detected photons, and the signal-to-noise ratio. The WOM outperforms bare PMTs, especially with respect to the low signal-to-noise ratio with an increase of a factor up to 8.9 in air (5.2 in ice). Since the gain in sensitivity is mostly in the UV regime, the WOM is an ideal sensor for Cherenkov and scintillation detectors.
Dissertations / Theses on the topic "Air noise detector"
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Ларін, Пилип Миколайович. "Пристрій пеленгування повітряних об’єктів." Master's thesis, Київ, 2018. https://ela.kpi.ua/handle/123456789/25601.
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Метою наукового дослідження є створення тракту вимірювання кута напрямку на повітряний об’єкт з шумоподібним сигналом за допомогою пакету програм Lab View. Об’єктом дослідження є процес вимірювання кута напрямку на ціль відносно акустичної вісі за допомогою прийомників тиску і коливальної швидкості. Предметом дослідження є алгоритм визначення значення кута напрямку
на ціль з використанням середовища та інструментальних можливостей пакету Lab View.
Результатом роботи є: дослідження принципу дії трактів пеленгування; дослідження умови вірного вимірювання пеленгу на ціль акустичними методами у повітрі; розроблення алгоритму вимірювання кута напрямку на ціль в середовищі програмного продукту LabView. Галузь застосування: акустичні вимірювання.The purpose of scientific research is to create a path for measuring the angle of the direction of the air object with a noisy signal using the Lab View program package. The object of the study is the process of measuring the direction of the target towards the target relative to the acoustic axis with the help of receivers of pressure and vibrational speed. The subject of the study is the algorithm for determining the value of the direction of the target on the target using the medium and the instrumental capabilities of the Lab View package. The result of the work is: research on the principle of the operation of the directional paths; esearch the conditions for the correct measurement of the bearings to the target by acoustic methods in the air; develop an algorithm for measuring the direction of the target on the target in the environment of the software LabView. Field of application: acoustic measurements
Целью научного исследования является создание тракта измерения угла направления на воздушный объект с шумоподобных сигналов с помощью пакета программ Lab View. Объектом исследования является процесс измерения угла направления на цель относительно акустической оси с помощью приемников давления и колебательной скорости. Предметом исследования является алгоритм определения значения угла направления на цель с использованием среды и инструментальных возможностей пакета Lab View. Результатом работы являются: исследование принципа действия трактов пеленгования; исследования условии верного измерения пеленга на цель акустическими методами в воздухе; разработка алгоритма измерения угла направления на цель в среде программного продукта LabView. Область применения: акустические измерения.
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Marintseva, Iryna Kozeletska, Маринцева, and Ірина Степанівна Козелецька. "The University Role in Mitigating and Overcoming Global Air Transport Sector Challenges." Thesis, Національний авіаційний університет, 2018. http://er.nau.edu.ua/handle/NAU/39359.
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The overall air transport sustainability provides for meeting the global demand for regular, efficient and economical air transport. A sustainable air transport system “should be affordable, should operate safely, securely, fairly and efficiently, and should offer choices of air services while supporting a competitive economy and balanced regional development». Training at the undergraduate, postgraduate, and doctoral students are encouraged to interact with their supervisors and professionals within the academic context and in a particular sectionЗагальна сталість повітряного транспорту забезпечує задоволення глобального попиту на регулярні, ефективні та економічні повітряні перевезення. Стала система повітряного транспорту «повинна бути доступною, безпечною, справедливою, ефективною з великим вибором повітряних перевезень за підтримки конкурентної економіки та збалансованого розвитку. Студенти бакалавріату, аспірантури та докторантури тісно співпрацюють з викладачами і професіоналами в теоретичній і практичній підготовці.
Общая устойчивость воздушного транспорта обеспечивает удовлетворение глобального спроса на регулярные, эффективные и экономичные воздушные перевозки. Устойчивая система воздушного транспорта "должна быть доступной, безопасной, эффективной, справедливой, предлагать широкий выбор воздушных перевозок при поддержке конкурентоспособной экономики и сбалансированного развития". Студенты бакалавриата, аспирантуры и докторантури тесно взаимодействуют с преподавателями и профессионалами в теоретической и практической подготовке
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Lin, Yu-Wen, and 林禹文. "FFT Based Noise Reduction and Feedback Cancellation with Pitch Based Voice Activity Detector for Digital Hearing Aid System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/62925680823023498970.
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碩士國立交通大學
電子工程學系 電子研究所
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With the advanced technology and signal processing, digital hearing aids have been the main trend of hearing aids. However, it is difficult to implement a complicated algorithm due to the limitation of battery size and capacity. The effective way of solving this problem is to design an efficient low power algorithm, architecture and circuit. And there are two main problems in nowadays hearing aids system. The first problem is that the intelligibility may be degraded due to the background noise. The second problem is the echo from the speaker. In order to solve these two problems, we propose an FFT based noise reduction and feedback cancellation. The proposed pitch based noise reduction includes the pitch based voice activity detection and noise reduction algorithm. The pitch based VAD utilizes the pitch and its harmonics and onset characteristics of speech to detect speech activity. In order to improve the VAD accuracy, two kinds of methods are combined for pitch and harmonic detection. Besides, in order to improve the performance of NR, we modify the original pitch based NR algorithm applicable to Quasi-ANSI filter bank [1] to be more effective for noise reduction and it is applicable to FFT based decomposition. We add some mechanisms, like two curves eight levels gain assignment, to improve the PESQ. The accuracy rate of proposed pitch based VAD can achieve 79.99% and 80.31% in stationary and non-stationary noise environment respectively. And the average improvement of segmental signal-noise-ratio (SNRseg) and signal-noise-ratio (SNR) of the proposed noise reduction is 6.09dB and 8.86dB in stationary noise environment and 6.49dB and 9.28dB in non-stationary noise environment. Moreover, the average improvement of sound quality (PESQ) is 0.31 and 0.46 in stationary and non-stationary noise environments respectively. The design of feedback cancellation is based on FFT decomposition and a decorrelation filter coefficient update mechanism is proposed. The decorrelation filter coefficient update utilizes the pitch information to estimate speech formant to enhance the robustness and the sound quality of adaptive feedback cancellation (AFC). The proposed AFC design can achieve similar added stable gain (ASG) and PESQ but with four orders complexity reduction compared to PEM-AFC design.
Books on the topic "Air noise detector"
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Huffaker, Ray, Marco Bittelli, and Rodolfo Rosa. Entropy and Surrogate Testing. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198782933.003.0005.
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Reconstructing real-world system dynamics from time series data on a single variable is challenging because real-world data often exhibit a highly volatile and irregular appearance potentially driven by several diverse factors. NLTS methods help eliminate less likely drivers of dynamic irregularity. We set a benchmark for regular behavior by investigating how linear systems of ODEs are restricted to exponential and periodic dynamics, and illustrating how irregular behavior can arise if regular linear dynamics are corrupted with noise or shift over time (i.e., nonstationarity). We investigate how data can be pre-processed to control for the noise and nonstationarity potentially camouflaging nonlinear deterministic drivers of observed complexity. We can apply signal-detection methods, such as Singular Spectrum Analysis (SSA), to separate signal from noise in the data, and test the signal for nonstationarity potentially corrected with SSA. SSA measures signal strength which provides a useful initial indicator of whether we should continue searching for endogenous nonlinear drivers of complexity. We begin diagnosing deterministic structure in an isolated signal by attempting to reconstructed a shadow attractor. Finally, we use the classic Lorenz equations to illustrate how a deterministic nonlinear system of ODEs with at least three equations can generate observed irregular dynamics endogenously without aid of exogenous shocks or nonstationary dynamics.
Book chapters on the topic "Air noise detector"
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Setayesh, Mahdi, Mengjie Zhang, and Mark Johnston. "Investigating Particle Swarm Optimisation Topologies for Edge Detection in Noisy Images." In AI 2011: Advances in Artificial Intelligence, 609–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25832-9_62.
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Saxena, Priyank, and R. Sukesh Kumar. "Restoration of CT Images Corrupted With Fixed Valued Impulse Noise Using an Optimum Decision-Based Filter." In Advances in Multimedia and Interactive Technologies, 220–39. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5246-8.ch008.
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The main aim of this chapter is to perform the restoration of computed tomography (CT) images acquired at the reduced level of radiation dose. Reduction in radiation dose affects the image quality as it increases noise and decreases low contrast resolution. In this chapter, an optimum decision-based filter (ODBF) is proposed as an image-space denoising technique, to detect and restore the low dose CT (LDCT) images corrupted with fixed valued impulse noise (salt and pepper) of unequal density. The detection stage employs k-means clustering to discriminate the noise-free pixels from the noisy-pixels by splitting the image data into three clusters of different intensities. The restoration stage employs mask else trimmed median (METM) estimation followed by an optional adaptive mask sizing for restoration of noisy pixels. The proposed method demonstrates noticeable improvement over other existing methods in restoration of LDCT images while maintaining the image contrast and edge details.
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Suhanek, Mia, and Sanja Grubesa. "Innovative Approaches to Noise Reduction." In Noise and Environment [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93056.
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Nowadays, each individual is exposed to noise on a daily basis, and noise is often referred as in literature as a plague of modern society. Noise pollution is often overlooked when compared to other environmental pollutions (e.g. air, water, soil pollution). However, same as the all aforementioned pollutions, noise exposure has an accumulating character, meaning that the harmful effect of noise is detected only after a long period of time. Long exposure to noise pollution can be displayed as a bad mood, fatigue, insomnia, headache and loss of concentration, which causes reduced work ability and ultimately permanent hearing impairment. The goal of this chapter is to present two different approaches (traditional and contemporary) in noise reductions. The aim of both approaches is to link objective and subjective acoustic parameters, in order to plan future urban infrastructures while keeping in mind the existing acoustic environments, and to create and implement new solutions that will design, preserve and improve acoustic environments. Thus, we can conclude this chapter will be oriented towards human health and overall quality of life in terms of noise reduction.
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Wongchoosuk, Chatchawal, Panida Lorwongtragool, and Teerakiat Kerdcharoe. "Malodor Detection Based on Electronic Nose." In Air Quality Monitoring, Assessment and Management. InTech, 2011. http://dx.doi.org/10.5772/16582.
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Bolse, Nico, Anne Habermehl, Carsten Eschenbaum, and Uli Lemmer. "Fluorescence Quenching Sensor Arrays for the Discrimination of Nitroaromatic Vapors." In Electronic Nose Technologies and Advances in Machine Olfaction, 58–93. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3862-2.ch004.
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Fluorescence quenching is a promising technique for chemical sensing applications such as the detection of explosive trace vapors. Nitroaromatic explosives are one of the primary targets for this approach enabling ultra-low detection limits down to sub parts-per-billion in air. Many studies, however, focus on enhanced sensor sensitivity, whereas practical applications often require the identification and quantification of detected species. Electronic noses and efficient sensor systems are a promising solution to address this challenge. The authors review recent approaches and trends for explosive trace vapor detection and discuss theoretical concepts for fluorescence quenching as well as target analytes, sensor materials, and fabrication techniques. Statistical learning techniques such as principal component analysis and linear discriminant analysis, sensor systems, and camera-based read-out strategies are in the focus of the chapter. The authors conclude with recommendations and solutions for the elaborated challenges and with visions on future research directions.
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Singh, Dharmpal, Gopal Purkait, Abhishek Banerjee, and Parag Chatterjee. "Innovative Approaches for Pre-Screening and Sensing of Diseases." In Pre-Screening Systems for Early Disease Prediction, Detection, and Prevention, 88–107. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7131-5.ch004.
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Prescreening and sensing of diseases offers a number of benefits that can help in prevention of major diseases. The aim of disease pre-screening is to detect possible disorders or diseases in people who do not have any symptoms. Earlier screening methods for the detection of diseases was invasive, complicated, and would require extensive tests. Some conventional methods used in clinical diagnoses include many invasive and potentially hazardous biopsy procedures, endoscopy, computed tomography; numerous innovative approaches have evolved to overcome the limitations of traditional techniques. Non-invasive biomedical sensor, genomics, electronic nose, nano-material, plasmonicsensor devices, microfabrication-based technologies, flat-panel detectors, digital breast object models, endomicroscopy, breath biopsy, and wavelet-based enhancement methods are some of the emerging frontiers in prescreening and sensing of diseases. This chapter will provide an in-depth discussion of the abovementioned innovative techniques related to prescreening and sensing of diseases.
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Yıldız, Erkan. "Non-Allergic Rhinitis." In Inflammation [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94544.
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Non-allergic rhinitis is a term used for situations where no allergen can be detected as the cause of rhinitis. In non-allergic rhinitis; Skin test positivity or specific Ig E response cannot be detected. The pathophysiology of nonallergic rhinitis (NAR) is heterogeneous. The most common type is vasomotor rhinitis, also called idiopathic. In addition, there are many types such as hormonal, gustatory, occupational, atrophic, cold air-induced and systemic diseases. Patients; They present with symptoms such as nasal congestion, runny nose, sneezing, and itching in the nose, the symptoms of the patients do not show a seasonal pattern. There are family stories, but they are not as common as allergic rhinitis (AR). An underlying factor such as infection, sinusitis or polyps cannot be detected in patients. It was determined that the patients showed more neurogenic abnormalities in the pathophysiology. These patients have been shown to be hypersensitive to substances with ingredients such as cold air or capsaicin. The diagnosis is made clinically, the onset of the disease is in adolescence. Oral/nasal antihistamines, steroids, leukotriene antagonists are used in the treatment.
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Sidi Ahmed, Taouli. "Mathematical Morphology and the Heart Signals." In Biomedical Engineering. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.104113.
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Nowadays, signal processing is integrated into most systems for analyzing and interpreting ECG and PCG signals. Its objectives are multiple and mainly include compensating for the addition of artifacts to the signals of interest, and extracting information that is not visible by direct visual analysis. Considering that useful clinical information is found in the characteristic waves of the ECG, in particular, the P wave, the QRS complex, the T wave and the heart sounds of the PCG signal. These signals provide important indicators for the diagnosis of heart disease because they reflect physiological processes. These are non-stationary signals that are very sensitive to noise, hence the need to have optimal conditions to record them. It is necessary to use appropriate signal processing tools for noise suppression and wave detection of the ECG signal. Our method uses Morphological filtering, multi-scale morphological and the other by top-hat transform, which are based on mathematical morphology. The latter is based on mathematical operators called opening and closing morphology operators. These methods are also tested, with the aim of removing the noise and detection of the waves of the ECG signal and of the pathological sounds of the PCG signal.
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A. Stumpo, Katherine. "Mass Spectrometry Imaging of Neurotransmitters." In Mass Spectrometry [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93835.
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Mass spectrometry imaging (MSI) is a powerful analytical method for the simultaneous analysis of hundreds of compounds within a biological sample. Despite the broad applicability of this technique, there is a critical need for advancements in methods for small molecule detection. Some molecular classes of small molecules are more difficult than others to ionize, e.g., neurotransmitters (NTs). The chemical structure of NTs (i.e., primary, secondary, and tertiary amines) affects ionization and has been a noted difficulty in the literature. In order to achieve detection of NTs using MSI, strategies must focus on either changing the chemistry of target molecules to aid in detection or focus on new methods of ionization. Additionally, even with new strategies, the issues of delocalization, chemical background noise, and ability to achieve high throughput (HTP) must be considered. This chapter will explore previous and up-and-coming techniques for maximizing the detection of NTs.
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Stevens, Martin. "Stars of the Tactile World." In Secret Worlds, 107–35. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198813675.003.0005.
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This chapter addresses the supreme level of refinement found in many animals for analysing tactile and pressure information. It begins by looking at the sensory organ of the star-nosed mole. The mole’s star-shaped organ is used purely for collecting tactile information. The chapter then considers the Eimer’s organs which cover every appendage that comprises the nose, some of which are used for initial prey detection, while others are for identification. Owing to the number of Eimer’s organs, their tiny size, and the way that the sensory cells respond to patterns of stimulation across parts of each individual Eimer’s organ, the mole obtains exquisite detail on texture, almost to a microscopic level. The chapter also discusses the highly refined tactile sense of spiders, looking at how they rely on vibrations transmitted through the ground, the silk web strands, or the surface waves and air for prey detection and capture. Spiders are equipped with a variety of sensors to detect mechanical information, including fine hairs sensitive to wind movement and touch, and special organs called slit sensilla around the joints of legs that measure physical forces acting on the exoskeleton. Finally, the chapter studies the nature and function of integumentary sense organs or ISOs in both crocodiles and alligators. The heavily built bodies of crocodiles and alligators belie a high sensitivity, being able to detect the slightest changes in touch and pressure.
Conference papers on the topic "Air noise detector"
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Lu, Pong-Jeu, Ming-Chuan Zhang, Tzu-Cheng Hsu, and Jin Zhang. "An Evaluation of Engine Faults Diagnostics Using Artificial Neural Networks." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0029.
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Application of artificial neural network (ANN)-based method to perform engine condition monitoring and fault diagnosis is evaluated. Back-propagation, feedforward neural nets are employed for constructing engine diagnostic networks. Noise-contained training and testing data are generated using an influence coefficient matrix and the data scatters. The results indicate that under high-level noise conditions ANN fault diagnosis can only achieve a 50–60% success rate. For situations where sensor scatters are comparable to those of the normal engine operation, the success rates for both 4-input and 8-input ANN diagnoses achieve high scores which satisfy the minimum 90% requirement. It is surprising to find that the success rate of the 4-input diagnosis is almost as good as that of the 8-input. Although the ANN-based method possesses certain capability in resisting the influence of input noise, it is found that a preprocessor that can perform sensor data validation is of paramount importance. Auto-associative neural network (AANN) is introduced to reduce the noise level contained. It is shown that the noise can be greatly filtered to result in a higher success rate of diagnosis. This AANN data validation preprocessor can also serve as an instant trend detector which greatly improves the current smoothing methods in trend detection. It is concluded that ANN-based fault diagnostic method is of great potential for future use. However, further investigations using actual engine data have to be done to validate the present findings.
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Prakash, Shashvat, Yedidia Neumeier, and Ben T. Zinn. "Blowout Margin Estimation Based on Two Precursor Types." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27874.
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Lean, premixed combustion has been aggressively pursued in recent years because it offers a practical approach for reducing emissions of nitrogen oxides (NOx) from gas turbines. However, lean premixed flames pose a greater risk of blowout. Studies on swirl and dump stabilized flames have shown that as a flame approaches blowout, distinctive precursors occur, such as pockets of localized extinctions and brief flame shape transitions to a thin ‘tornado’ configuration. For this study, both precursor types are detected using separate, dedicated optical sensors. Observations indicate that the tornado mode is part of the blowout process in a 127 mm long combustor and that a localized extinction precursor immediately precedes the tornado mode transition. Despite the causality, the statistics of tornado bursts and localized extinctions suggest a ‘memoryless’ Poisson process, where the occurrence of one event type does not influence the time until the next event of the same type. Localized extinctions have been used previously for blowout margin estimation, and are well suited for the purpose because the occurrence frequency increases with diminishing margin. However, the signals commonly used to detect localized extinction events are noisy due to the nature of the flame; thus, detection is prone to false alarms. Detecting tornado bursts, by comparison, is less ambiguous but such events occur too rarely for blowout mitigation applications. The shortcomings of both precursor detection methods can be addressed by combining observations of both precursor types in a meaningful manner. The presence of tornado bursts indicates that the flame is near blowout; this fact can be used to calibrate margin estimation routines based upon localized extinction. However, this approach would require two sensors since any one optical sensor cannot directly differentiate both precursor types. A single sensor approach can be developed whereby the causal relationship between the two precursor types is exploited. Local extinctions with longer duration times can potentially perturb the flame into an alternate flow configuration. The presence of these tornado ‘triggers’ manifest as an increase in the low frequency content of the chemiluminescence signal. A low pass filter with the appropriate cutoff frequency can differentiate between the tornado-triggering and benign, inconsequential localized extinctions. Therefore, the same signal that detects localized extinctions can be filtered to capably predict tornado mode shifts. This scheme will enable robust margin detection and minimize sensitivity to noise.
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Ganguli, Ranjan. "Data Rectification and Detection of Trend Shifts in Jet Engine Gas Path Measurements Using Median Filters and Fuzzy Logic." In ASME Turbo Expo 2001: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/2001-gt-0014.
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Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.
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Romessis, C., and K. Mathioudakis. "Setting Up of a Probabilistic Neural Network for Sensor Fault Detection Including Operation With Component Faults." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30030.
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The diagnostic ability of Probabilistic Neural Networks (PNN) for detecting sensor faults on gas turbines is examined. The structure and the features of a PNN, for sensor fault detection, are presented. It is shown that with the proposed formulation, a powerful tool for sensor fault identification is produced. A particular feature of the PNN produced is the ability to detect sensor faults even in the presence of engine component malfunction, as well as on deteriorated engines. In such situations, the size of bias that can be identified increases. The way to establish the limits of sensor bias that can be detected is presented along with results from application to test cases with realistic noise magnitudes. The diagnostic procedure proposed here is also supported by an engine performance model. The data used for setting up and testing the PNN are generated by such a model.
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Palmer, Carl A., Nicholos A. Mackos, and Michael J. Roemer. "Approach to Monitor and Assess the Quality of Sensor Data in Support of Calibration and Condition Based Maintenance for Turbine Powered Navy Vessels." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-28251.
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This paper describes a flexible, widely applicable sensor health monitoring system, as developed in partnership with Northrop Grumman Ship Systems (NGSS) under a small business innovative research contract for the US Navy. Traditional signal processing techniques were employed in conjunction with data driven models and fault identification and classification techniques to provide a robust analysis of sensor health. Key aspects of the system include: • Analysis of both high and low bandwidth data; • Modules that assess a sensor’s performance on an individual basis. These are designed to detect noise, incipient faults, spiking and signal dropout; • Modules that assess a sensor’s performance from an overall system perspective, enabling early identification of sensor drift and calibration issues; • Algorithms for high bandwidth signals designed to detect clipping, abnormal signal mean and range, and signal shape anomalies that enable identification of certain mechanical and electrical failures; • Mode detection algorithms that enable dynamic weighting of calculated health parameters in order to mitigate false alarms and missed detects; • Fusion algorithms that combine and interpret the output from the aforementioned modules, to provide estimates of overall sensor health and failure mode. The system’s capabilities were exercised on 1) laboratory datasets generated in-house with implanted faults, 2) data from tests conducted on the power distribution system driven by a Rolls-Royce MT30 gas turbine slated to power the Navy’s DDG1000 destroyer, and 3) from a low pressure air compressor (LPAC) found on legacy Navy weapons systems. The ability to detect and classify various electrical faults, issues related to calibration, and certain mechanical failures was validated. The system is suitable for offline mining of historical data, embedded on-line monitoring, and for application in distributed computing networks.
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Morgan, M. D., S. A. (Raj) Mehta, T. J. Al-Himyary, and R. G. (Gord) Moore. "Automatic, Non-Intrusive, Flame Detection in Pipelines." In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0274.
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Many methods of flame detection are available. Unfortunately, few offer remote, non-line-of-sight, detection. In cases where flammable mixtures are transported within tubing (such as flare lines, storage tank vents, air drilling, and improperly designed purging operations) there is often no means by which combustion can be detected. This is a significant deficiency in some applications. If the mixture were to ignite, the results could be catastrophic. To address this problem, combustion noise is being investigated at the University of Calgary as a possible means of detecting flames within tubing. An experimental study has been completed that shows that combustion noise can be distinguished from other sources of noise by its inverse power law relationship with frequency. A robust algorithm has been developed that, when combined with high-speed pressure measurements, provides early detection of flames. When combined with other filters, the algorithm can automatically separate combustion noise from other sources of noise. In this paper, a stop band filter was used to remove the noise created by a fluttering check valve.
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DePold, Hans R., Ravi Rajamani, William H. Morrison, and Krishna R. Pattipati. "A Unified Metric for Fault Detection and Isolation in Engines." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-91095.
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In this paper we make two key contributions. First, we formalize the effectiveness of fault detection and isolation (FDI) with a metric that globally considers the following: variance in engine parameter estimate residuals under normal conditions, costs of missed detections and false alarms, costs associated with misclassification of faults, fault frequencies and fault severities. Reducing the error variance increases the signal-to-noise ratio, thereby increasing the reliability and speed of fault-detection algorithms. Minimizing missed detections has enormous implications on operational safety, while minimizing false alarms and fault misclassifications has implications on downtime, asset management, cannot duplicates, and operational costs. This metric measures the trade off between reducing data error variances, between false and missed detects, and misclassification of faults. As a second contribution, we embed this metric in a systematic data-driven diagnostic optimization process for normative decisions on input parameter selection for residual generation, FDI methods and prediction/classification fusion techniques.
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Mariani, Stefano, Thompson V. Nguyen, Francesco Lanza di Scalea, and Mahmood Fateh. "High Speed Non-Contact Ultrasonic Guided Wave Inspections of Rails." In 2014 Joint Rail Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/jrc2014-3745.
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This paper describes a new system for high-speed and non-contact rail defect detection being developed at the University of California at San Diego (UCSD). A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection has been tested at the UCSD Rail Defect Farm. This solution presents an improvement over the previously considered laser/air-coupled hybrid system because it replaces the costly and hard-to-maintain laser with a much cheaper, faster, and easier-to-maintain air-coupled transmitter. In addition to a real-time statistical analysis algorithm, the prototype uses a specialized filtering approach to mitigate the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. Many of the system operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. Extensions of the system capability are planned to add rail surface characterization to the internal rail defect detection to optimize rail grinding operations.
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Meskin, N., E. Naderi, and K. Khorasani. "Fault Diagnosis of Jet Engines by Using a Multiple Model-Based Approach." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23442.
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In this paper, a novel real-time fault detection and isolation (FDI) scheme that is based on the concept of multiple model approach is proposed for jet engines. A modular and a hierarchical architecture is proposed which enables the detection and isolation of both single as well as permanent concurrent faults in the engine. The nonlinear dynamics of the jet engine is linearized in which compressors and turbines maps are used for performance calculations and a set of linear models corresponding to various operating modes of the engine (namely healthy and different fault modes) at each operating point is obtained. Using the multiple model approach the probabilities corresponding to each operating point of the engine are generated and the current operating mode of the system is detected based on evaluating the maximum probability criteria. It is shown that the proposed methodology is also robust to the failure of pressure and temperature sensors and extensive levels of noise outliers in the sensor measurements. Simulation results presented demonstrate the effectiveness of our proposed multiple model FDI algorithm for both structural faults and actuator fault in the jet engine.
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Bake, Friedrich, Ulf Michel, and Ingo Roehle. "Investigation of Entropy Noise in Aero-Engine Combustors." In ASME Turbo Expo 2006: Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-90093.
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Strong evidence is presented that entropy noise is the major source of external noise in aero-engine combustion. Entropy noise is generated in the outlet nozzles of combustors. Low frequency entropy noise — which was predicted earlier in theory and numerical simulations — was successfully detected in a generic aero-engine combustion chamber. It is shown that entropy noise dominates even in the case of thermo-acoustic resonances. In addition to this, a different noise generating mechanism was discovered that is presumably of even higher relevance to jet engines: There is strong evidence of broad band entropy noise at higher frequencies (1 kHz to 3 kHz in the reported tests). This unexpected effect can be explained by the interaction of small scale entropy perturbations (hot spots) with the strong pressure gradient in the outlet nozzle. The direct combustion noise of the flame zone seems to be of minor importance for the noise emission to the ambiance. The combustion experiments were supplemented by experiments with electrical heating. Two different methods for generating entropy waves were used, a pulse excitation and a sinusoidal excitation. In addition, high-frequency entropy noise was generated by steady electrical heating.
Reports on the topic "Air noise detector"
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Zhang, Speng, Qinwei Fu, Xin Jin, Junwen Tan, Xinrong Li, and Qinxiu Zhang. Association Between Air Pollution and the Prevalence of Allergic Rhinitis in Chinese Children: Protocol for a Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2021. http://dx.doi.org/10.37766/inplasy2021.10.0094.
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Review question / Objective: For Chinese children, to explore whether air pollution increases the incidence of allergic rhinitis in children. Condition being studied: Allergic rhinitis (AR) is a common chronic inflammatory disease in the upper airways, causing nasal congestion, itching, runny nose, and sneezing. It has serious impacts on people's quality of lives, and affects economic growth indirectly. Epidemiological studies revealed that 10% to 40% of the population were suffering from AR worldwide. In addition, children are more likely to develop allergic rhinitis than adults. The prevalence of allergic rhinitis in children is 25% worldwide, and 4% ~ 31% in China. Eligibility criteria: (1) Trials in which children were AR, and the diagnosis of "AR" was in line with the international guidelines. (2) Children’s age was limited of 0-18 years, and they were born and lived in China and at least one year of exposure to air pollution.(3) Air pollutant concentration in the test was derived from the mean value of data provided by ambient air detectors. (Include NO2, SO2, O3, PM10, PM2.5) (4) Literatures only include cross-sectional studies, cohort and case-control studies. (5) All of these articles provide data that allows us to calculate 95% confidence interval (CI) of the influence of air pollutants on AR. (6) Trials published in English only.
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Blevins, Matthew, Gregory Lyons, Carl Hart, and Michael White. Optical and acoustical measurement of ballistic noise signatures. Engineer Research and Development Center (U.S.), January 2021. http://dx.doi.org/10.21079/11681/39501.
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Supersonic projectiles in air generate acoustical signatures that are fundamentally related to the projectile’s shape, size, and velocity. These characteristics influence various mechanisms involved in the generation, propagation, decay, and coalescence of acoustic waves. To understand the relationships between projectile shape, size, velocity, and the physical mechanisms involved, an experimental effort captured the acoustic field produced by a range of supersonic projectiles using both conventional pressure sensors and a schlieren imaging system. The results of this ongoing project will elucidate those fundamental mechanisms, enabling more sophisticated tools for detection, classification, localization, and tracking. This paper details the experimental setup, data collection, and preliminary analysis of a series of ballistic projectiles, both idealized and currently in use by the U.S. Military.