Conference Papers are technical papers that have been presented at sound and vibration conferences around the world.
Three methods for reproduction of sound using a maximum of eight loudspeakers were investigated in the context of testing telecommunication devices. They are the four-loudspeaker-based method as described in ETSI EG 202 396-1, Higher-Order ambisonics (HOA), and a matrix inversion method. HOA optimizes the reproduced sound at a sweet spot in the center of the array with radius determined by a spherical microphone array, which is used to derive the spherical harmonics decomposition of the reference sound. The four-loudspeaker-based method equalizes the magnitude response at the ears of a head and torso simulator (HATS) for sound reproduction, while the matrix inversion method optimizes the local sound field around a few target positions. The matrix inversion method had two conditions, i.e. with or without the extra processing steps described in ETSI TS 103 224; and three sets of optimization positions were defined, i.e. the ears of the HATS, positions close to a device under test, and standardized positions as described in ETSI TS 103 224. A listening experiment was performed to evaluate the perceived quality of the reproduced sounds at the microphones close to a device under test and at the ears of the HATS. The matrix inversion method performed best when listening to the reproduced sounds at target positions used for sound-field optimization and when listening to the microphones close to the device. HOA resulted in similar perceived quality as the matrix inversion method while a large degree of perceptual degradation was observed using the four-loudspeaker-based method.
Realistically experiencing the sound and vibration data through actually listening to and feeling the data in a full-vehicle NVH simulator remarkably aids the understanding of the NVH phenomena and speeds up the decision-making process. In the case of idle vibration, the sound and vibration of the idle condition are perceived simultaneously, and both need to be accurately reproduced simultaneously in a simulated environment in order to be properly evaluated and understood.
In this work, a case is examined in which a perceived idle quality of a vehicle is addressed. In this case, two very similar vehicles, with the same powertrain but somewhat different body structures, are compared. One has a lower subjective idle quality rating than the other, despite the vehicles being so similar. An NVH vehicle simulator was used to compare the sound and vibration characteristics of the two vehicles back-to-back in a realistic vehicle environment in order to understand the difference in the subjective rating. With the ability to control the various specific sound and vibration stimuli, the reason for the difference of subjective rating between the vehiclesbecame apparent rapidly.
Further, the interaction of sound and vibration and the resulting effect on human subjective perception is explored, which emphasizes the importance of having both sound and vibration accurately reproduced and controlled for such simulations.
City noise management involves a variety of disciplines such as planning, mapping, action plans, policing, complaint management, abatement and public awareness. With the wide availability of mobile broadband internet access coupled with low cost noise sensors, many authorities and researchers are eager to use sound sensor networks for these tasks. A sensor network can be defined as a group of specialized transducers and processing with a communications infrastructure and is intended to monitor and record conditions at diverse locations, connected to a central software. This definition covers a wide range of different possibilities, designs and components such as MEMS microphones, processing software, type approved instrumentation, smart phones, etc. However, are all networks suitable for all tasks? Many sensors trade off measurement precision to reduce cost and enable an increase in number of measurement points within a budget. This paper describes different sensor classes and implementation strategies. It discusses the relative merits of different sensors and describes what is important to take account of when implementing these networks for application to one or multiple noise management tasks, outlining what each can be used for and what they shouldn’t be used for. Aspects covered include architecture, and practical applicability. The paper concludes with recommendations for using different smart networks and for further research.
Near-field Acoustical Holography (NAH) is based on performing 2D spatial Discrete Fourier Transforms (DFT), and therefore the method requires a regular mesh of measure-ment positions. To avoid spatial aliasing problems, the mesh spacing must be somewhat less than half of the acoustic wavelength. In practice, this requirement sets a serious lim-itation on the upper frequency limit.
This paper provides practical information on using a multi-shaker MIMO vibration testing approach for MIL-STD-810 single axis transport testing of large, resonant, land based payloads (up to 6 ton in mass and 20ft in size).Such payloads can often exhibit significant dynamic behaviour within the test frequency range including transients > 50 times control level. The purpose of the paper is to provide guidance to organisations expanding from single shaker system testing to multi-shaker testing. It shares lessons learnt through hundreds of hours of real world sine and random testing using a 420kN (94,420 lbf) force quad electrodynamic vibration system and MIMO vibration controller in both horizontal and vertical configuration designed for MESA (multi exciter single axis) testing of both military and non-military type payloads. It targets the real world practical considerations of the test engineer/manager when defining and developing a MIMO vibration test facility for large payload testing.
A method for reproduction of sound, based on crosstalk cancellation using inverse filters,
was implemented in the context of testing telecommunications devices.
The effect of the regularization parameter, number of loudspeakers,
type of background noise, and a technique to attenuate audible artefacts,
The quality of the reproduced sound was evaluated both objectively and subjectively
with respect to the reference sounds, at points where telecommunications devices
would be potentially placed around the head.
The highest regularization value gave the best results,
the performance was equally good when using eight or four loudspeakers,
and the reproduction method was shown to be robust for different program materials.
The proposed technique to reduce audible artefacts increased the perceived similarity.
Today, design of wind turbines is extensively done by the implementation of numerical models. These models simulate the dynamic behaviour of full-scale wind turbines which helps to ensure the structural integrity of prototypes. However, these numerical models need validation from experimental results, and in turn, numerical and analytical modelling help improve and validate new experimental techniques. Wind turbines are complex dynamic systems that consist of mutually moving substructures under high dynamic loads. At a standstill, the system can be modelled as linear time-invariant (LTI), and modal analysis requirements are thus fulfilled for the dynamic characterization. Under operation, the system cannot be considered as LTI and must be modelled as a linear periodic time-variant (LPTV) system, which allows for the application of the related theory for such systems. One of these methods is the Coleman transformation, which transforms the vibrations expressed in the blade rotating coordinates to the fixed-ground frame of reference. The application of this transformation, originally from helicopter theory, allows for the conversion of a LPTV system to a LTI system under certain assumptions, among which is the assumption of isotropic rotors. Since rotors are never completely isotropic in real life, this paper presents the application of operational modal analysis together with the Coleman transformation on both experimental data from a full-scale Vestas wind turbine with instrumented blades and nacelle, and its representative numerical model with a fully isotropic rotor. The results show that the first tower and rotor edgewise modes are well identified, and that the rotor edgewise modes can be identified from the nacelle signals. The results also uncover the challenge the excitation forces imply for the identification of flapwise modes.
The study addresses experimental identification of linear periodic time variant systems. The recently introduced Harmonic-OMA-Time Domain (H-OMA-TD) method is in focus. It is shown how this method can aid engineers and what additional information it can bring, compared to other methods. The method is demonstrated in application to experimental data obtained on operating wind turbine.
BHP Billiton Worsley Alumina Pty Ltd (BWAPL) consists of mining operations located near the town of Boddington, a 51km conveyor linking to an alumina refinery located in Worsley and a port load out facility located in Bunbury. BWAPL mining operations expanded in 2012, resulting in mining operations taking place much closer to a number of residential properties in the community and closer to the township of Boddington. Given the proximity of the mining operation to these sensitive receptors, noise was identified early on as a high risk to the operations that needed to be proactively managed to ensure that BWAPL’s environmental and social licences to operate were maintained. BWAPL adapted Brüel & Kjær’s Noise Sentinel monitoring system to monitor noise generated by mining operations and ensure that the impact on near neighbours was minimised. This was achieved by incorporating alert systems that allowed for proactive management. This paper will cover the compliance parameters required to be measured; the adaptations applied to the software and the key project challenges that were overcome. On the basis of the experiences gained and the positive outcomes achieved through implementing the Noise Sentinel system, BWAPL received a Highly Commended award at the 2013 BHP Billiton Health, Safety, Environment and Community Awards in the Environment category.
Laser scanning and accelerometer measurements are often used for analysing vibrations of for instance motors under operation. However, the methods have certain disadvantages: Laser techniques typically scan one point at a time, which limits the methods to be applied only for stationary conditions. Accelerometers can be used for non-stationary conditions, but their physical mounting will to some extend influence the vibration of the source surface and due to cabling they are not practical for rotating objects. Near-field Acoustical Holography (NAH) is a non-contact experimental technique for mapping sound and vibration, and since the sound field is measured at multiple points around the source simultaneously, it can also be applied for non-stationary conditions. In particular, the Equivalent Source Method (ESM) is an attractive holography method, because it does not require neither the source nor the array geometry to be given in separable coordinates (planar, spherical, cylindrical etc.). This paper describes a non-stationary ESM approach for reconstruction of quantities like surface velocity and displacement. A set of measurements has been made with a 60 channel microphone array on a small electrical motor. Vibrations were also measured with a laser vibrometer in order to validate the accuracy of the array calculations.
Continuous, unattended noise monitoring systems can immediately alert you should noise levels exceed defined criteria. Once alerted to an exceedance, operators can act to return levels to compliance. This approach has two significant limitations. Firstly the operator can only take action after the breach has occurred and therefore systems are only able to inform owners about problems that have occurred in the past, rather than allowing them to maintain compliance. Secondly the noise limit exceedances might not be due to specific noise from the operator but from unrelated, residual noise in the often complex noise climates around the site. Compliance breaches are frequently triggered by aircraft overflights, road traffic or community sources. Modern monitoring systems enable users to view noise characteristics and listen to the noise breach to determine the source and take action if it is relevant. However, this approach can create significant false positives each taking up operator time to address. This paper describes how airport noise management systems have addressed this problem by combining data from other systems. It also shows how different techniques are required in urban & industrial noise management, giving examples of techniques that allow operators to take action before a compliance breach occurs.
There is an increasing interest for automatic classification of sounds in various applications. The processing consists in extracting some selected features from the raw data and applying a classifier algorithm to automatically estimate the class of source the input data belongs to. In order to perform this task, the system is first trained on a set of input data (in case of supervised learning), then applied on new data. The performances of classification depend on many factors: the selected features, the classifier, but also the data. For some practical applications, this approach is of interest to estimate the sound pressure level or others acoustic quantities attached to a specific class of sources in a complex environment. For example, there is a benefit to quantify the only contributions of airplanes, in the sound acquired by a noise monitoring system located nearby an airport. One practical difficulty is the presence of other sources. In the present study, we are looking at this type of scenario, when multiple sources may act at the same time or in presence of background noise. We consider here different environmental sound sources: aircrafts, car traffic among others. In a first step, different features in connection with a classifier are evaluated on ‘clean’ data, meaning with no mixture. In a second step, we mix artificially data from different sound sources at different rates of mixtures and calculate the sound pressure level contribution from each source based on the proposed classification algorithm. We consider as well mixtures with sounds sources that are not among the predefined classes. Finally the most robust classification configuration is evaluated in the case of real outdoor measurements.
This paper deals with the source separation task related to indoor pass-by noise tests. Several different approaches are discussed. The classical transfer path modelling concept making use of operational data together with acoustic transfer functions is explained and a time-domain implementation is verified for a real operating vehicle. Pass-by noise contribution from components such as engine, intake and tyres are estimated and ranked as a result of such processing. Another and completely different source separation methodology is introduced in terms of a blind source separation method for clear separation of tyre noise from engine related noise. Features of the two methods are discussed and results for the same indoor pass-by dataset presented.
The indoor vehicle pass-by test is a simulation of a field pass-by noise measurement in a controlled environment allowing repeatable measurements independent of weather conditions. During vehicle development modifications can be tested out in a fast manner to see the immediate influence on the overall vehicle noise levels produced during a pass-by acceleration test. Besides performing the standard pass-by noise test, vehicle improvement work requires knowledge about the noise contribution from the different vehicle sources during the pass-by test. A source path contribution (SPC) concept involving modelling the main vehicle noise sources contributing to the pass-by noise will be presented. A special feature of this approach is that it processes entirely in the time-domain to produce source strength estimates for theconsidered noise sources followed by a synthesis to produce pass-by noise estimates for the vehicle and for individual noise sources based on indicator microphone near-field data and acoustic transfer functions. As a result major pass-by noise contributors are identified at a given vehicle position during the pass-by test. Results produced by this method will be compared to a blind source separation (BSS) methodology applied to the operational dataset only for extracting source signals related to the different noise processes during vehicle operation. Extracted source signals are correlated with far-field measurements to estimate pass-by noise contributions. The BSS methodology is verified using a speaker setup showing excellent separation of tyre and engine noise contributions. Data from indoor pass-by noise measurements with a vehicle on a chassis-dynamometer is finally used to test and evaluate the two methods.
Shale gas has transformed the energy market in the United States where drilling is underway in 17 states, with more than 80,000 wells drilled or permitted since 2005. Deposits elsewhere in the world are under varying degrees of exploration.
The main environmental impacts of the process are water usage, waste water management, methane emissions, groundwater and soil contamination. These are generally addressed as part of national environmental regulations and strong stakeholder engagement is critical in addressing concerns.
close to residential areas there is a significant risk of disturbance triggering complaints.
This study reports structural dynamic characteristics obtained experimentally from an extensive testing campaign on a 34m long wind turbine blade mounted on a test-rig under laboratory conditions. Further, these experimental results have been compared with analog numerical results obtained from a very detailed FE model of the same blade using 3D solid elements. Both an undamaged and a damaged blade are investigated, and it is observed that the natural frequencies of the first few modes of the blade change very little due to a significant artificial damage imposed in trailing edge, whereas the mode shapes - especially if decomposed into the flapwise, edgewise and torsional components - contain information which might be helpful for detecting and localizing wind turbine blade damages.
Creating the perfect vehicle sound is a critical challenge that needs the buy-in of diverse decision-makers to establish targets, and greater inter-departmental collaboration to realize them. Free-driving sound simulation captures subjective sound preferences with real-time modification. It helps to cascade that target sound down to subsystem or component level, and provides a focal point where all relevant and available data (CAE or test-based) can be assessed for its impact on sound style. In this way, NVH simulators can reduce uncertainty throughout the vehicle development programme: from target setting to delivery. This reduces the need for prototypes by more completely marrying the virtual-world design process with the real-world results, and enabling assessment of NVH predictions from CAE models.
The unified matrix polynomial approach (UMPA) was developed in order to understand and derive various experimental modal analysis algorithms (which have been developed in isolation) using a common mathematical formulation. Various commercially available algorithms – such as the polyreference time domain, least squares complex exponential, and eigensystem realization algorithm etc. – can be explained using UMPA methodology, which makes it easier to understand both the advantages and limitations of such algorithms. In view of this fundamental characteristic of the UMPA, this paper aims at using the approach to understand, explain and develop the stochastic subspace identification (SSI) algorithm - a popular time domain operational modal analysis (OMA) algorithm. The roots of SSI algorithm lie in the identification of linear dynamic systems, traditionally a communications and controls engineering area. By means of the UMPA, the SSI algorithm’s similarity to a high order time domain OMA algorithm can be shown. It can also be shown that state transition matrices identified using the SSI algorithm and UMPA formulation are related to each other through a similarity transformation, thus characterizing the same system.
It was recently shown that blind source separation (BSS), as originally developed in the signal processing community, can be used in operational modal analysis to separate the responses of a structure into its individual modal contributions. This, in turn, allows the application of simple single-of-degree-freedom techniques to identify the modal parameters of interest. Several publications have recently attempted to give a posteriori physical interpretations to BSS – as initially developed in telecommunication signal processing -- when applied to the field of structural dynamics. This paper proposes to follow the route the other way round. It shows that several separation criteria purposely dedicated to operational modal analysis can be deduced from general physical considerations. Three such examples are introduced, based on very different properties that uniquely characterise a structural mode. The first criterion, coined the “principle of shortest envelope”, conjectures that the envelope of a modal response has, among all possible envelopes, the shortest length. That such a principle leads to the governing differential equation of a single-degree-of-freedom oscillator is proved from calculus of variation. The second criterion, coined the “principle of minimum spectral variance”, conjectures that the frequency spectrum of a structural mode is maximally concentrated around its central frequency. Finally, the third criterion, coined the “principle of least spectral complexity”, states that a structural mode has the lowest possible entropy in the frequency domain. All three criteria can be expressed in terms of a mixing matrix whose columns contain the unknown mode shapes. The recovery of the latter is then trivially achieved by minimising the criteria. Extensive simulations show that the proposed criteria lead to figures of merit very similar to those of the state-of-the-art, while at the same time providing physical insight that other algorithms issued form the signal processing community may dramatically lack.
A local solve method will be presented for extracting modal parameters from inconsistent data. By definition global parameter estimation methods cannot handle inconsistent Frequency Response Function (FRF) data (frequency shifts, non-linearity’s, etc.) and in practice it is very difficult to select appropriate poles from the stability or consistency diagrams presented in commercially available modal parameter estimation methods. The typical way to resolve this issue is to employ measurement techniques that acquire all FRF’s simultaneously, requiring shakers, numerous accelerometers and a large channel count acquisition system; or performing a Roving hammer, Multiple Reference Impact Test (MRIT). The reality is that sometimes FRF data is not acquired in a consistent manner. This paper presents a “local solve” method that performs a global solve on individual or groups of consistent FRF’s and combines the end result into a set of global modal parameters.
Second Order Blind Source Separation (SO-BSS) techniques possess several mathematical characteristics making them a viable option for Operational Modal Analysis (OMA). However, on closer scrutiny it is revealed that there are certain subtleties that limit their direct application to OMA applications. This paper continues from past work of the authors, which focussed on understanding SO-BSS techniques from a perspective of OMA applicability and developing SO-BSS based algorithm for OMA. In this paper, a new algorithm is proposed that overcomes the inherent limitations of SO-BSS algorithms with regards to their applicability to OMA. These limitations include applicability to heavily damped systems, identification of complex modes, and applicability to scenarios where number of available sensors is lesser than the number of modes to be estimated, etc. The algorithm’s advantage over original form of SO-BSS is demonstrated by means of an analytical example.
Modal parameters (natural frequency, damping and mode shapes) play an important role in dynamic characterization of a structure. These parameters are estimated using advance parameter estimation algorithms. However, the estimated modal parameters are often quoted without much statistical evaluation of the estimation procedure. Since, modal parameters are estimated from measured data and the estimation procedure itself is often an error minimization procedure (like Least Squares approach), it is necessary to quantify the uncertainty associated with the parameter estimation procedure. One way to achieve this goal is by providing confidence intervals for the estimated modal parameters.
This paper addresses the issue of uncertainty quantification for modal parameters estimated using high order time domain algorithms. A methodology for estimating confidence intervals for the estimated modal parameters is presented and its usage is illustrated by means of simulated and experimental examples.
A method for sound recognition of coexisting environmental noise sources by applying pattern recognition techniques is developed. The investigated technique could benefit several areas of application, such as noise impact assessment, acoustic pollution mitigation and soundscape characterization. This study distinguishes from other investigations by focusing on cases where the noise sources appear mixed (i.e., several noise sources might be present at the same time in one location), which is a more realistic and frequent situation in cities than a single sound source without other interfering noises. The identification and, furthermore, the estimation of the contribution of each source to the overall level is one important goal in the current investigation, which would improve environmental noise assessment in complex situations. The method for recognizing the noise sources in adverse conditions is based on the Fisher’s Linear Discriminant classifier, and estimates noise source contributions based on a distance measure of vector projections. The method is able to identify mixed sources in 96% of the 27 tested signals and to correlate the contribution of the individual sources with their sound pressure level. The results obtained from tests in real city environments show an accurate performance in the description of the sound scenarios.
The presented study continues the work on application of Output Only Modal Analysis (OMA) to operating wind turbines. It is known from previous studies that issues like the time-varying nature of the equations of motion of an operating wind turbine (in particular the significant harmonic components due to the rotor rotation) as well as the considerable aerodynamic damping make OMA of operating wind turbines a difficult task. While in the previous works OMA was based on data provided by sensors mounted on the wind turbine tower and nacelle, we here attempt to improve the results by instrumenting the blades as well. It is believed that the availability of vibration data from the blades will improve the observability of the main global vibration modes (especially the heavily damped out-of-plane modes), and thus will assure a better estimation of modal parameters, especially the damping.
The paper discusses the technical challenges regarding blade instrumentation and data acquisition, data processing applied to eliminate the time-varying nature of an operating wind turbine in the resulting eigenvalue problem and, finally, it presents and discusses the initial results.
Engineers designing wind turbines often use Campbell diagrams as a convenient tool for representing the dependence of wind turbine modal parameters on the rotor (and wind) speed. Experimentally obtained Campbell diagrams are used for tuning wind turbine numerical models, which are used heavily in the design of wind turbine structures and their control systems. Several previous studies showed that Operational Modal Analysis (OMA) can be successfully employed for plotting experimental Campbell diagrams. In this study, OMA is applied to a number of experimental sets of data measured under different wind conditions. However, because several OMA assumptions are partly violated, the resulting diagram is contaminated by computational and noise poles, which cannot be filtered out by conventional means provided by OMA algorithms.
The presented study compares three methods for segregating the physical poles from their computational and noise counterparts. Since the modal frequencies and damping of a wind turbine change with the rotor speed, these modal parameters cannot be utilized for grouping the poles, as is typically done in the case of stabilization diagrams. The mode shape vectors are utilized instead.
The first presented method uses hierarchical clustering to group the poles according to the similarity between the associated mode shape vectors. The second method is based on the Singular Value Decomposition (SVD) performed on an AutoMAC matrix. This method was originally suggested by other authors for cleaning up stabilization diagrams. Finally, the third method utilizes Self-organizing Maps (SOM) for the same purpose.
The methods are applied to the experimental data from the ALSTOM WIND ECO 100 3MW wind turbine; the results are compared and the advantages and disadvantages of the methods are discussed.
The presented study focuses on application of Output Only Modal Analysis to operational wind turbines. Issues like time varying nature of operational wind turbine, significant harmonic components due to rotor rotation and considerable aerodynamic damping make OMA of operational wind turbines a difficult task. The study presents the results of OMA applied to experimental data from ALSTOM Wind 3MW Eco-100 wind turbine. Issues like data handling, using clustering for modal identification and uncertainties analysis are presented and discussed.
The acceleration response of a wind turbine gearbox, tested on a back-to-back test stand of Winergy, is used as input data to a pre-processed operational modal analysis (OMA) or output-only modal analysis. The data is heavily influenced by harmonics and sidebands caused by rotating gear wheels, shafts and bearings. This violates an OMA assumption to have a flat spectrum as input. Therefore, cleaning methods are applied to remove harmonics in the time series. The methods – Time Synchronous Averaging, Periodogram-based and Cepstrum-based – are tested for the applicability to gearbox data concerning their userfriendliness, the quality of the results and possibility of automation.
Understanding and characterization of wind turbine dynamics, especially when operating, is an important though challenging task. The main problem is that an operating wind turbine cannot be truly modeled as a time invariant system, which limits the applicability of conventional well-established modal analysis methods. This paper compares two experimental techniques that characterize the dynamic behavior of an operating horizontal axis wind turbine (Vestas V27, 225kW, rotor diameter 27m, 12 accelerometers on each blade). The first method uses a multiblade coordinate transformation to convert the time periodic system into a time invariant one, assuming that the system is perfectly isotropic. Conventional operational modal analysis then can be applied to identify the modal parameters of the time invariant model. The second method processes the periodic response directly based on an extension of modal analysis to linear time periodic systems. It utilizes the harmonic power spectrum, which is analogous to the power spectrum for a time invariant system, to identify a periodic model for the turbine. This work demonstrates both of these methods on measurements from the operating turbine and discusses the challenges that are encountered. The procedure is demonstrated by using it to extract the time-periodic mode shapes of the first edge-wise modes, revealing that this turbine apparently has non-negligible blade-to-blade variations and hence the dynamics of these modes are considerably different than one would expect for an anisotropic turbine.
Modal parameters (natural frequency, damping and mode shapes) play an important role in dynamic characterization of a structure. These parameters are estimated using advance parameter estimation algorithms. However, the estimated modal parameters are often quoted without much statistical evaluation of the estimation procedure. Since, modal parameters are estimated from measured data and the estimation procedure itself is often an error minimization procedure (like Least Squares approach), it is necessary to quantify the uncertainty associated with the parameter estimation procedure. One way to achieve this goal is by providing confidence intervals for the estimated modal parameters. This paper addresses the issue of uncertainty quantification for modal parameters estimated using high order time domain algorithms. A methodology for estimating confidence intervals for the estimated modal parameters is presented and its usage is illustrated by means of simulated and experimental examples.
The use of single layer and double layer microphone arrays, both hand-held as well as robot operated, has been greatly extended within the last decade. This paper summarizes how a small double layer array with typically 128 microphones can be used for interior cabin measurements for mapping various acoustical properties. There are four major applications. The first one is general patch holography (or conformal mapping) of basic acoustical quantities like sound pressure, particle velocity and sound intensity. Optionally sound quality (SQ) metrics for describing human annoyance like loudness, sharpness, fluctuation strength and roughness, etc. can also be mapped. Other applications are in-situ absorption measurement - for example inside a car cabin, intensity component analysis (e.g. incident, reflected, scattered, net intensity, etc. can be separated) and finally sound pressure contribution from various panels inside cabins to an operator/driver's position. Some measurements are done in operational condition and some are reference laboratory measurement of typical frequency response functions.
A measurement technique is described for the localization and visualization of noise sources on moving rail vehicles using beamforming. The Delay-And-Sum (DAS) beamforming is often used on stationary (fixed) sources. However, the method can also be applied to moving sources such as rail vehicles, road vehicles and aircraft fly-overs, as well as rotating blades on wind turbines. Recently, deconvolution techniques have been introduced as post-processing after DAS to improve spatial resolution and reduce the level of ghost sources in the calculated noise maps. This paper describes a commercially available system which includes DAS and deconvolution techniques, dedicated to the rail vehicle industry. Special consideration is paid to the configuration of the test site and its influence on the measurement results. The advantages of various microphone array designs for measurements on bogies, rails and pantographs are discussed. Guidelines are given for a selection of appropriate array (half-wheel, logarithmic wheel) for the source of interest and illustrated with practical results from noise emission measurements on regional trains.
The paper describes a commercially available fly-over beamforming system based on methodologies already published, but using an array that was designed for quick and precise deployment on a concrete runway rather than for minimum sidelobe level. Time domain tracking Delay And Sum (DAS) beamforming is the first processing step, followed by Deconvolution in the frequency domain to reduce sidelobes, enhance resolution, and get absolute scaling of the source maps. The system has been used for a series of fly-over measurements on a Business Jet type MU300 from Mitsubishi Heavy Industries. Results from a couple of these measurements are presented: Contribution spectra from selected areas on the aircraft to the sound pressure level at the array are compared against the total sound pressure spectrum measured by the array. One major aim of the paper is to verify that the system performs well although the array was designed with quick deployment as a main criterion. The results are very encouraging. A second aim is to elaborate on the handling of the array shading function in connection with the calculation of the Point Spread Function (PSF) used in deconvolution. Recent publications have used a simple formula to compensate for Doppler effects for the case of flat broadband spectra. A more correct formula is derived in the present paper, covering also a Doppler correction to be made in the shading function, when that function is used in the PSF calculation.
The number of noise source identification (NSI) techniques available to engineers working on noise, vibration and harshness problems has increased considerably in recent years. The choice of the most appropriate technique depends upon the application and the information required. This paper reviews techniques for noise source identification and quantification ranging from simple hand-held sound intensity systems, hand-held array systems to large ground based microphone arrays. The methods include Beamforming, Spherical Beamforming and Acoustic Holography. Guidelines are given to help the engineer choose a suitable technique based on the frequency range of interest, the distance from the measurement array to the test object and the resolution required. Practical application examples ranging from hearing aids to wind turbines are presented to illustrate the various NSI techniques.
Noise from large construction projects can be a nuisance for nearby communities. Vibration from activities like pile driving, concrete crushing and tunneling can also create nuisance but may also risk structural damage. Increasingly, both noise and vibration are significant factors surrounding a construction project. If not managed properly they can lead to project delays, further prolonging the nuisance and significantly increasing project cost. To help mitigate these risks, contractors are now using continuous noise and vibration monitoring to ensure that the impact from construction activity is kept within guidelines.This paper looks at how continuous real time monitoring of noise and vibration can be used to help manage community impact and reduce the risk of structural damage. It will look at legislation and best practice both in Canada and in other parts of the world. Presenting the concept of environmental capacity it also shows how engaging communities, setting expectations and building trust can be effective way of mitigating impact.The paper goes on to highlight new technology that is in use in Canadian construction sites which uses the approaches discussed above to help manage compliance and reduce risk.
Since its first mention in 1999, Integrated Environment Noise Management has promised new possibilities for managing environment noise through the interaction between measurements and calculations. This has lead to the technique of Dynamic Noise Mapping, where measurements are used to update calculated noise maps, which was primarily intended to improve local noise maps and supplement noise monitoring results. However, with the ever-increasing availability of internet communication and the rise of managed services which enable the efficient exploitation of new technology, integrating measurements and calculations for more pro-active environment noise management, where noise issues can be avoided, is becoming potentially interesting and possible. So, the link between calculation software and real-time noise monitoring solutions enables the automated creation of noise maps based on real-life noise and weather monitoring, giving feedback to enable a more optimal planning of operations within the noise limits. This dynamic mapping can be done with updates as regularly as every hour enabling industry to schedule operational activity, quickly assess the noise impact and ensure that they are doing the utmost whilst complying with noise limits. This paper describes how Dynamic Noise Mapping for Pro-Active Environment Noise Management works and its possibilities, challenges and limitations based on current knowledge and technology. The paper will also identify areas of future research.
The construction of infrastructure and new buildings risks causing significant impact on the neighbourhood, particularly for major infrastructure projects. Due to local community concerns, construction activities are often subject to operational restrictions. To effectively operate within these restrictions, instrumentation is often deployed to monitor noise and / or vibration. An alternative approach to the purchasing and operating costly equipment to monitor compliance is available through Managed Services offering technology innovation enabling simultaneous noise and vibration monitoring and manpower and cost reductions in monitoring resulting in a more economically attractive approach to traditional noise monitoring.
Long term monitoring of noise from airports, industrial facilities and construction projects has been well established over many years. The systems monitor noise levels at various points around the facility, feed the data back to a central system where data can be summarized and any breaches in compliance criteria are reported. These systems are passive by nature; they simply report what happened giving little opportunity to do anything to prevent breaches in the first place. Should breaches occur, attendance at the site is typically necessary to investigate before advice on mitigation can be given to prevent future breaches of compliance.
Technology advances in how data is captured, what data is captured and how it is accessed now means that in a large number of cases investigation can be achieved remotely without the need for site visits. This makes the process more efficient, lower cost, and much more immediate. Technology can now deliver results in real time that can help to prevent breaches occurring in the first place.
This paper outlines the technology advances and suggests how they will help to change the way noise consultants can deliver more monitoring services over a wider geographical area with fewer staff whilst simultaneously providing a better quality result.
The two microphone acoustic impedance tube is used to measure the acoustic impedance and absorption coefficient properties for absorptive materials. A commonly followed test method for this is described by the standard ASTM E1050. This test standard is popular compared to alternative test methods due to its repeatability, speed of test and small sample size requirements. The two microphone broadband noise source based test method was introduced in 1985 and was an update to the single microphone sinusoidal excitation method given by ASTM C384. The ASTM E1050 standard was updated in 1998 to include changes in the required physical dimensions of the tube. Specifically, the tube length was said to be increased to be sufficiently long to meet the requirement that plane waves be fully developed before reaching the microphones and test specimen. Further, a minimum of three tube diameters was specified between the sound source and the nearest microphone to allow for sufficient distance for the subsiding of any non-plane waves propagating within the tube. Using two different tube lengths meeting the requirements of the two versions of the standard, this study investigated experimentally whether any differences resulted in the measured normal incidence absorption for multiple test samples as a result of the prescribed dimensional changes. The precision of the measured results are compared using the repeatability and reproducibility requirements defined in Table 2 of the E1050 standard.