Environmental Noise Measurement (Br0139)
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Laser Linewidth, Frequency Noise and Measurement
Laser Linewidth, Frequency Noise and Measurement WHITEPAPER | MARCH 2021 OPTICAL SENSING Yihong Chen, Hank Blauvelt EMCORE Corporation, Alhambra, CA, USA LASER LINEWIDTH AND FREQUENCY NOISE Frequency Noise Power Spectrum Density SPECTRUM DENSITY Frequency noise power spectrum density reveals detailed information about phase noise of a laser, which is the root Single Frequency Laser and Frequency (phase) cause of laser spectral broadening. In principle, laser line Noise shape can be constructed from frequency noise power Ideally, a single frequency laser operates at single spectrum density although in most cases it can only be frequency with zero linewidth. In a real world, however, a done numerically. Laser linewidth can be extracted. laser has a finite linewidth because of phase fluctuation, Correlation between laser line shape and which causes instantaneous frequency shifted away from frequency noise power spectrum density (ref the central frequency: δν(t) = (1/2π) dφ/dt. [1]) Linewidth Laser linewidth is an important parameter for characterizing the purity of wavelength (frequency) and coherence of a Graphic (Heading 4-Subhead Black) light source. Typically, laser linewidth is defined as Full Width at Half-Maximum (FWHM), or 3 dB bandwidth (SEE FIGURE 1) Direct optical spectrum measurements using a grating Equation (1) is difficult to calculate, but a based optical spectrum analyzer can only measure the simpler expression gives a good approximation laser line shape with resolution down to ~pm range, which (ref [2]) corresponds to GHz level. Indirect linewidth measurement An effective integrated linewidth ∆_ can be found by can be done through self-heterodyne/homodyne technique solving the equation: or measuring frequency noise using frequency discriminator. -
Design of Digital Filters for Frequency Weightings (A and C) Required for Risk Assessments of Workers Exposed to Noise
Industrial Health 2015, 53, 21–27 Original Article Design of digital filters for frequency weightings (A and C) required for risk assessments of workers exposed to noise Andrew N. RIMELL1, Neil J. MANSFIELD2* and Gurmail S. PADDAN3 1Aero Engine Controls, Rolls-Royce, UK 2Loughborough Design School, Loughborough University, UK 3Institute of Naval Medicine, UK Received January 4, 2013 and accepted August 18, 2014 Published online in J-STAGE September 13, 2014 Abstract: Many workers are exposed to noise in their industrial environment. Excessive noise ex- posure can cause health problems and therefore it is important that the worker’s noise exposure is assessed. This may require measurement by an equipment manufacturer or the employer. Human exposure to noise may be measured using microphones; however, weighting filters are required to correlate the physical noise sound pressure level measurements to the human’s response to an audi- tory stimulus. IEC 61672-1 and ANSI S1.43 describe suitable weighting filters, but do not explain how to implement them for digitally recorded sound pressure level data. By using the bilinear transform, it is possible to transform the analogue equations given in the standards into digital fil- ters. This paper describes the implementation of the weighting filters as digital IIR (Infinite Impulse Response) filters and provides all the necessary formulae to directly calculate the filter coefficients for any sampling frequency. Thus, the filters in the standards can be implemented in any numeri- cal processing software (such as a spreadsheet or programming language running on a PC, mobile device or embedded system). Key words: Hearing loss, IEC 61672-1, ANSI S1.43, Occupational health and safety, Noise measurement, Frequency weighting, Digital filter loss if the correct protective measures are not in place. -
NOISE-CON 2004 the Impact of A-Weighting Sound Pressure Level
Baltimore, Maryland NOISE-CON 2004 2004 July 12-14 The Impact of A-weighting Sound Pressure Level Measurements during the Evaluation of Noise Exposure Richard L. St. Pierre, Jr. RSP Acoustics Westminster, CO 80021 Daniel J. Maguire Cooper Standard Automotive Auburn, IN 46701 ABSTRACT Over the past 50 years, the A-weighted sound pressure level (dBA) has become the predominant measurement used in noise analysis. This is in spite of the fact that many studies have shown that the use of the A-weighting curve underestimates the role low frequency noise plays in loudness, annoyance, and speech intelligibility. The intentional de-emphasizing of low frequency noise content by A-weighting in studies can also lead to a misjudgment of the exposure risk of some physical and psychological effects that have been associated with low frequency noise. As a result of this reliance on dBA measurements, there is a lack of importance placed on minimizing low frequency noise. A review of the history of weighting curves as well as research into the problems associated with dBA measurements will be presented. Also, research relating to the effects of low frequency noise, including increased fatigue, reduced memory efficiency and increased risk of high blood pressure and heart ailments, will be analyzed. The result will show a need to develop and utilize other measures of sound that more accurately represent the potential risk to humans. 1. INTRODUCTION Since the 1930’s, there have been large advances in the ability to measure sound and understand its effects on humans. Despite this, a vast majority of acoustical measurements done today still use the methods originally developed 70 years ago. -
176 Assessment of Noise Impact: a Case Study
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by UMP Institutional Repository National Conference in Mechanical Engineering Research and Postgraduate Studies (2nd NCMER 2010) 3-4 December 2010, Faculty of Mechanical Engineering, UMP Pekan, Kuantan, Pahang, Malaysia; pp. 176-182 ISBN: 978-967-0120-04-1; Editors: M.M. Rahman, M.Y. Taib, A.R. Ismail, A.R. Yusoff, and M.A.M. Romlay ©Universiti Malaysia Pahang ASSESSMENT OF NOISE IMPACT: A CASE STUDY DUE TO AIRCRAFT ACTIVITIES A.R. Ismail1, M.F.M.Tahir2, M.J.M. Nor2, M.H.M. Haniff2 and R.Zulkifli2 1Faculty of Mechanical Engineering, Universiti Malaysia Pahang 26600 UMP, Pekan, Pahang, Malaysia Phone: +6013-3942463, Fax: +609-4242202 E-mail: [email protected] 2Department of Mechanical and Material Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia. Tel.: +603-89216511. Fax: +603-89259659 E-mail: [email protected] ABSTRACT This paper presents the results obtained from an environmental noise measurement at a selected location in Malaysia in order to establish the impact of noise to human at residential area. The measurement site was situated less than three kilometers from the nearest airport and any major activities can be expected to be heard. The noise measurement was carried out for 24 hours monitoring for 30 days by using integrated B&K SLM equipments to obtain the equivalent sound level (Leq), L10 and L90 so that the exposure of noise to community can be assessed. Maximum sound level (Lmax) and sound exposure level have been measured as specified by the Federal Aviation Administration (FAA) for aviation noise assessment. -
Time-Series Prediction of Environmental Noise for Urban Iot Based on Long Short-Term Memory Recurrent Neural Network
applied sciences Article Time-Series Prediction of Environmental Noise for Urban IoT Based on Long Short-Term Memory Recurrent Neural Network Xueqi Zhang 1,2 , Meng Zhao 1,2 and Rencai Dong 1,* 1 State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; [email protected] (X.Z.); [email protected] (M.Z.) 2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: [email protected]; Tel.: +86-010-62849112 Received: 12 January 2020; Accepted: 6 February 2020; Published: 8 February 2020 Abstract: Noise pollution is one of the major urban environmental pollutions, and it is increasingly becoming a matter of crucial public concern. Monitoring and predicting environmental noise are of great significance for the prevention and control of noise pollution. With the advent of the Internet of Things (IoT) technology, urban noise monitoring is emerging in the direction of a small interval, long time, and large data amount, which is difficult to model and predict with traditional methods. In this study, an IoT-based noise monitoring system was deployed to acquire the environmental noise data, and a two-layer long short-term memory (LSTM) network was proposed for the prediction of environmental noise under the condition of large data volume. The optimal hyperparameters were selected through testing, and the raw data sets were processed. The urban environmental noise was predicted at time intervals of 1 s, 1 min, 10 min, and 30 min, and their performances were compared with three classic predictive models: random walk (RW), stacked autoencoder (SAE), and support vector machine (SVM). -
Noise Element Introduction General Plan Elements Plan General Noise
HISTORIC OVERVIEW NOISE ELEMENT INTRODUCTION GENERAL PLAN ELEMENTS NOISE “Nature and silence go together better” —Astrid Alauda APPENDICES Introduction ...................................................................................................................................228 Changes Since 1988 ...................................................................................................................228 Definitions .......................................................................................................................................228 Measurement and Effects of Noise ......................................................................................229 Sound Levels and Human Response ...................................................................................230 Standards for Maximum Noise Levels ................................................................................231 Noise Sources ................................................................................................................................232 AREA PLANS Goal N1, Policies, and Strategies ..........................................................................................236 TOWN OF WOODSIDE GENERAL PLAN 2012 227 IntrodUction CHanGes Since 1988 This Element has been prepared in accordance with The greatest increase in noise levels in Town over the last Section 65302(f) of the California Government Code, two decades has been from residential construction and which outlines requirements for the Noise Element -
Fault Location in Power Distribution Systems Via Deep Graph
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks Kunjin Chen, Jun Hu, Member, IEEE, Yu Zhang, Member, IEEE, Zhanqing Yu, Member, IEEE, and Jinliang He, Fellow, IEEE Abstract—This paper develops a novel graph convolutional solving a set of nonlinear equations. To solve the multiple network (GCN) framework for fault location in power distri- estimation problem, it is proposed to use estimated fault bution networks. The proposed approach integrates multiple currents in all phases including the healthy phase to find the measurements at different buses while taking system topology into account. The effectiveness of the GCN model is corroborated faulty feeder and the location of the fault [2]. It is pointed by the IEEE 123 bus benchmark system. Simulation results show out in [15] that the accuracy of impedance-based methods can that the GCN model significantly outperforms other widely-used be affected by factors including fault type, unbalanced loads, machine learning schemes with very high fault location accuracy. heterogeneity of overhead lines, measurement errors, etc. In addition, the proposed approach is robust to measurement When a fault occurs in a distribution system, voltage drops noise and data loss errors. Data visualization results of two com- peting neural networks are presented to explore the mechanism can occur at all buses. The voltage drop characteristics for of GCNs superior performance. A data augmentation procedure the whole system vary with different fault locations. Thus, the is proposed to increase the robustness of the model under various voltage measurements on certain buses can be used to identify levels of noise and data loss errors. -
Monitoring of Sound Pressure Level
1. INTRODUCTION Noise is one of the main environmental problems of modern life and it is inseparable from human activities, urban and technological growth. National and international standards provide for a minimum of acoustic comfort for coexistence between man and industrial development. That's why a study of noise emission and environmental noise at the PALAGUA - CAIPAL Field was carried out; samples of measurements were taken in specific (punctual) manner to meet the sound pressure level (SPL) with a duration of five minutes per sample/measurement for noise measurements and 15 minutes for ambient or environmental noise in each direction: (north, east, south, west and vertical). The result of these measurements was compared with the maximum permissible noise emission and environmental noise standards stated in Resolution 627 of 2006 Ministry of Environment, Housing, and Territorial Development (MAVDT) and thus it was verified that they comply with environmental regulations in the PALAGUA - CAIPAL Field. 1 INFORME DE LABORATORIO 0860-09-ECO. NIVELES DE PRESIÓN SONORA EN EL AREA DE PRODUCCION CAMPO PALAGUA - CAIPAL PUERTO BOYACA, BOYACA. NOVIEMBRE DE 2009. 2. OBJECTIVES • To evaluate the emission of noise and environmental noise encountered in the PALAGUA - CAIPAL Gas Field area, located in the municipality of Puerto Boyacá, Boyacá. • To compare the obtained sound pressure levels at points monitored, with the permissible limits of resolution 627 of the Ministry of Environment, SECTOR C: RESTRICTED INTERMEDIATE NOISE, which allows a maximum of 75 dB in the daytime (7:01 to 21:00) and 70 dB in the night shift (21:01 to 7: 00 hours) 2 INFORME DE LABORATORIO 0860-09-ECO. -
The Psychophysiological Implications of Soundscape: a Systematic Review of Empirical Literature and a Research Agenda
International Journal of Environmental Research and Public Health Review The Psychophysiological Implications of Soundscape: A Systematic Review of Empirical Literature and a Research Agenda Mercede Erfanian * , Andrew J. Mitchell , Jian Kang * and Francesco Aletta UCL Institute for Environmental Design and Engineering, The Bartlett, University College London (UCL), Central House, 14 Upper Woburn Place, London WC1H 0NN, UK; [email protected] (A.J.M.); [email protected] (F.A.) * Correspondence: [email protected] (M.E.); [email protected] (J.K.); Tel.: +44-(0)20-3108-7338 (J.K.) Received: 16 September 2019; Accepted: 19 September 2019; Published: 21 September 2019 Abstract: The soundscape is defined by the International Standard Organization (ISO) 12913-1 as the human’s perception of the acoustic environment, in context, accompanying physiological and psychological responses. Previous research is synthesized with studies designed to investigate soundscape at the ‘unconscious’ level in an effort to more specifically conceptualize biomarkers of the soundscape. This review aims firstly, to investigate the consistency of methodologies applied for the investigation of physiological aspects of soundscape; secondly, to underline the feasibility of physiological markers as biomarkers of soundscape; and finally, to explore the association between the physiological responses and the well-founded psychological components of the soundscape which are continually advancing. For this review, Web of Science, PubMed, Scopus, and -
Model 426B02 In-Line ICP™ A-Weight Filter Installation
Model 426B02 In-line ICP™ A-weight Filter Installation and Operating Manual For assistance with the operation of this product, contact PCB Piezotronics, Inc. Toll-free: 800-828-8840 24-hour SensorLine: 716-684-0001 Fax: 716-684-0987 E-mail: [email protected] Web: www.pcb.com Repair and Maintenance Returning Equipment If factory repair is required, our representatives will PCB guarantees Total Customer Satisfaction through its provide you with a Return Material Authorization (RMA) “Lifetime Warranty Plus” on all Platinum Stock Products number, which we use to reference any information you sold by PCB and through its limited warranties on all other have already provided and expedite the repair process. PCB Stock, Standard and Special products. Due to the This number should be clearly marked on the outside of sophisticated nature of our sensors and associated all returned package(s) and on any packing list(s) instrumentation, field servicing and repair is not accompanying the shipment. recommended and, if attempted, will void the factory warranty. Contact Information Beyond routine calibration and battery replacements PCB Piezotronics, Inc. where applicable, our products require no user 3425 Walden Ave. maintenance. Clean electrical connectors, housings, and Depew, NY14043 USA mounting surfaces with solutions and techniques that will Toll-free: (800) 828-8840 not harm the material of construction. Observe caution 24-hour SensorLine: (716) 684-0001 when using liquids near devices that are not hermetically General inquiries: [email protected] sealed. Such devices should only be wiped with a Repair inquiries: [email protected] dampened cloth—never saturated or submerged. For a complete list of distributors, global offices and sales In the event that equipment becomes damaged or ceases representatives, visit our website, www.pcb.com. -
AN279: Estimating Period Jitter from Phase Noise
AN279 ESTIMATING PERIOD JITTER FROM PHASE NOISE 1. Introduction This application note reviews how RMS period jitter may be estimated from phase noise data. This approach is useful for estimating period jitter when sufficiently accurate time domain instruments, such as jitter measuring oscilloscopes or Time Interval Analyzers (TIAs), are unavailable. 2. Terminology In this application note, the following definitions apply: Cycle-to-cycle jitter—The short-term variation in clock period between adjacent clock cycles. This jitter measure, abbreviated here as JCC, may be specified as either an RMS or peak-to-peak quantity. Jitter—Short-term variations of the significant instants of a digital signal from their ideal positions in time (Ref: Telcordia GR-499-CORE). In this application note, the digital signal is a clock source or oscillator. Short- term here means phase noise contributions are restricted to frequencies greater than or equal to 10 Hz (Ref: Telcordia GR-1244-CORE). Period jitter—The short-term variation in clock period over all measured clock cycles, compared to the average clock period. This jitter measure, abbreviated here as JPER, may be specified as either an RMS or peak-to-peak quantity. This application note will concentrate on estimating the RMS value of this jitter parameter. The illustration in Figure 1 suggests how one might measure the RMS period jitter in the time domain. The first edge is the reference edge or trigger edge as if we were using an oscilloscope. Clock Period Distribution J PER(RMS) = T = 0 T = TPER Figure 1. RMS Period Jitter Example Phase jitter—The integrated jitter (area under the curve) of a phase noise plot over a particular jitter bandwidth. -
Soundscape Mapping in Environmental Noise Management and Urban Planning
This is a repository copy of Soundscape mapping in environmental noise management and urban planning. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/128385/ Version: Published Version Article: Margaritis, E. and Kang, J. orcid.org/0000-0001-8995-5636 (2017) Soundscape mapping in environmental noise management and urban planning. Noise Mapping (4). 1. pp. 87-103. ISSN 2084-879X https://doi.org/10.1515/noise-2017-0007 Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can’t change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Noise Mapp. 2017; 4:87ś103 Research Article Efstathios Margaritis* and Jian Kang Soundscape mapping in environmental noise management and urban planning: case studies in two UK cities https://doi.org/10.1515/noise-2017-0007 tentional design process comparable to landscape and to Received Dec 22, 2017; accepted Dec 28, 2017 introduce the theories of soundscape into the design pro- cess of urban public spaces”. Lately, suggestions of ap- plied soundscape practises were introduced in the Master plan level thanks to the initiative of the local authorities.