National Academies Press: OpenBook

Acoustic Beamforming: Mapping Sources of Truck Noise (2009)

Chapter: Chapter 1 - Background

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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2009. Acoustic Beamforming: Mapping Sources of Truck Noise. Washington, DC: The National Academies Press. doi: 10.17226/14311.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2009. Acoustic Beamforming: Mapping Sources of Truck Noise. Washington, DC: The National Academies Press. doi: 10.17226/14311.
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2009. Acoustic Beamforming: Mapping Sources of Truck Noise. Washington, DC: The National Academies Press. doi: 10.17226/14311.
×
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Suggested Citation:"Chapter 1 - Background." National Academies of Sciences, Engineering, and Medicine. 2009. Acoustic Beamforming: Mapping Sources of Truck Noise. Washington, DC: The National Academies Press. doi: 10.17226/14311.
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Page 9

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61.1 Introduction Heavy trucks are significant contributors to overall traffic noise levels. At highway speeds, the noise level produced by heavy trucks is about 10 dB greater than that of light vehicles (1). As a result, every heavy truck in the traffic flow contributes the same amount to the average noise levels as 10 light vehi- cles. Because of their contribution, a thorough understanding of trucks as a noise source is crucial to the prediction and mit- igation of traffic noise. In addition to the overall noise level of truck passbys, the location and relative strength of the princi- pal noise sources (e.g., exhaust, powertrain, tire–pavement, and aerodynamic) on individual trucks is important. For mod- eling and abatement of traffic noise, the barrier performance of sound walls depends on the assumed distribution of source heights. In some states, highway sound walls are designed so the top of the exhaust stack is obscured from sight under the assumption that exhaust noise is a major source. For abating truck noise through quieter pavements, the amount of expected noise reduction depends on the contribution of tire–pavement noise relative to other sources such as powertrain, exhaust, and possibly aerodynamic noise. The current treatment of truck noise for highway conditions is simplistic, placing about 50% of the source strength at a height of 12 ft (3.7 m) and the other half at ground level. Recently, a number of observations have challenged the current treatment of trucks and led to the need for new research. First, truck noise levels are one of the very few noise sources regulated at the federal level in the United States. Over the past few decades, the regulated noise level has been incre- mentally lowered to the point where trucks are expected to meet the same level requirement as light vehicles under engine noise–dominated test procedures. In achieving this lower level of noise performance, engine and exhaust noise have been addressed. As older trucks are replaced, these sources are expected to play less of a role in total truck noise emissions under highway conditions than tire–pavement noise. In the United States, source height distributions were last measured in the mid-1990s using the technology available at that time (2, 3). Those measurements were made when the current reg- ulated level had been in place for 8 years. They do not reflect changes in the fleet that may have occurred in the subsequent decade. A second factor challenging the current treatment of truck noise is recent research that has been performed in Europe. From these studies (4, 5), tire–pavement noise has been found to make a much larger contribution, 63% to 84%, to total truck noise at highway speeds. From the European work (6) and some research in the United States, a strong dependence on truck tire type has also been determined. The more aggres- sive tread tires often used on the drive axles are found to be as much as 10 dB louder than those used on the steering or trailer axles. With such large differences between tire types, it is expected that tire–pavement noise could be quite pro- nounced for some trucks, depending on tire selection. The third set of observations comes from research work conducted in conjunction with the application of quieter pavements. In a number of recent projects, reductions in traf- fic noise have been measured consistent with the reduction of tire–pavement source levels when pavement modifications have been made (7–9). Even statistical passby measurements for trucks have shown reductions with pavement modifica- tions almost as great as indicated by tire–pavement noise source level reductions (10). The reduction in truck noise source levels goes beyond that which would be predicted based on the current 50-50 split between tire–pavement and other, elevated noise sources on trucks. 1.2 Heavy Truck Noise Sources Noise from heavy trucks originates from a variety of sources: • Exhaust stack outlet • Muffler shell C H A P T E R 1 Background

• Exhaust pipes • Engine block • Intake • Fan • Tires • Aerodynamics The relative contributions of these sources vary with vehicle type and operating condition, and (for tire noise) the type of pavement. Most sources are fairly localized, although installa- tion details (i.e., engine compartment configuration) can affect the effective position and size of mechanical sources. Tire and aerodynamic noise are distributed, with tire noise near the ground along the length of the vehicle. Source distribution is important in several ways: • Source height is a major parameter in the design of roadside barriers. • Source height is an important parameter for calculation of the effect of the ground on sound propagation. • Truck dimensions are not small compared to standard ref- erence measurement distances of 50 ft (15 m)—typical U.S. practice—or 25 ft (7.5 m)—typical European practice. Measurements conducted by Wyle during development of roadside test procedures (11) showed that propagation of truck noise at distances less than 50 ft (15 m) does not nec- essarily follow the 6 dB per distance doubling rule expected for simple sources. The relative contribution and spatial distribution of truck noise sources can be quite complex and display significant variation from truck to truck, from site to site, and with truck speed due to the following factors: • Exhaust system sources including the outlet and sound radi- ation from the muffler and exhaust pipe shells depend not only on the location and orientation of the system (e.g., ver- tical or horizontal) but also on the amount of deterioration or modification. • Powertrain noise including radiation from the engine block, cooling fan, and intake will depend on powertrain configu- ration as well as its state of maintenance and loading. • Tire noise will depend strongly on tire type and on pave- ment type with either of these contributing differences of up to 10 dB or more. • The presence of exterior shrouds and air deflectors may also affect aerodynamically generated noise. Because of all these parameters, it is important to have more information about each specific truck being evaluated than that which can be observed in typical uncontrolled passby measurements along the side of a roadway. Vehicle speed, exhaust configuration, and pavement type can all be deter- mined by using typical statistical passby test methods. Other key parameters, such as tire type, engine configuration, vehicle loading/operating condition, and general state of mainte- nance and/or modification, cannot be obtained in uncon- trolled roadside testing. The state of compliance with the federally regulated noise emission levels also cannot be deter- mined. For these reasons, evaluation of truck noise sources must include a combination of controlled passby and random, statistical passby data. 1.3 Source Identification Methods During development of EPA’s heavy truck noise regulations (12), extensive studies were conducted on truck noise sources. Source identification was typically obtained by combinations of near-field measurements, component wrapping, removal of components, and substitution of components (13). Stationary tests (idle-max-idle and dynamometer) and moving tests at various power settings (including coastby) further mapped out the contributions of various sources. That type of testing pro- vided good results. For example, Wyle’s light vehicle source study (14) mapped source and subsource characteristics over a full range of power and revolutions per minute (rpm), and yielded designs that were demonstrated to work on the road (15). Such testing is, however, labor intensive, and source analy- sis was performed on a relatively small number of vehicles. Substantially higher productivity can be achieved with remote sensing methods, such as acoustic holography, beamforming, and acoustic intensity measurements. A number of studies reported in the current literature have addressed localizing noise sources on moving ground vehicles. Much of this work initially addressed high-speed trains. More recently, applications to motor vehicle passbys are appearing. A technique that has been proven successful in identifying and quantifying motor vehicle noise is the mapping of sound intensity. Typically, this technique is applied in a laboratory setting such as a chassis dynamometer where the sound inten- sity probe can be placed near different source regions of the vehicle. The resultant data can then be processed into sound intensity contour maps to assess source regions. Although this methodology is commonly used in a stationary laboratory setting, it has also been successfully used to map the source regions of moving tires (16). For controlled vehicle testing, this method could be extended to mapping the source regions of an entire vehicle. Such mapping would provide a direct linkage to the sound intensity method of tire–pavement noise measurements currently being applied in the California Department of Transportation (Caltrans) work and the Federal Highway Administration (FHWA) studies. The method could not be employed in uncontrolled situations, but was used in this study as a more sophisticated controlled test technique, 7

supplementing the classic near-field, component wrapping, and component substitution methods. Another microphone array method used for source identi- fication is acoustic holography. This method is also typically used in stationary laboratory test conditions. However, it has been used to identify source regions of tire–pavement noise under on-road operating conditions. In this application, the acoustic array is suspended along side and moving with the test tire (17, 18). Using a combination of near-field acoustic holog- raphy and far-field calculations based on Helmholtz’s integral equation, it is possible to obtain a complete description of the sound field of the source, where both magnitude and phase of the sound pressure field are known at any point. The results of these works clearly indicated the source regions and compared well with similar localization studies performed using sound intensity. One of the features of acoustic holography is that the plane of the source distribution can be propagated very close to the source or farther away from the source, to typical passby measurement distances. However, unlike beamforming, the array used for acoustic holography must be physically as large as the source region of interest. In addition, acoustic hologra- phy is not suitable for passby applications when the array is sta- tionary and the source is moving. As with sound intensity, this method could not be employed for uncontrolled passby test- ing, although it may be useful for some aspects of source local- ization under controlled conditions. The more compelling method of localizing sources has been the application of acoustic beamforming, as detailed by Crewe et al. (19). Beamforming techniques in a horizontal direction have also been employed in French research specifically on truck sources (6). Acoustic beamforming uses an array of microphones to focus measurement on a specific point on an imaginary source plane near the actual source. This focus point is electronically swept across this plane, and the noise level is determined. In more advanced approaches, which should be used in the case of moving vehicles, the source plane moves with the vehicle and points are scanned over the time the vehicle goes by. Such an advanced approach requires that the algorithm accounts for both the moving source plane and Doppler shifting of the sound during the passby. In this man- ner, several slices in time can be evaluated near the position of interest, such as the time when the maximum passby noise level occurs. Unlike the more simple methods that consider only one instant during the passby, beamforming, by tracking the source and averaging over several instances, has a more accurate result. Because of tracking capability, this type of beamforming can also be exploited to evaluate source direc- tivity as the vehicle approaches and recedes from the measure- ment position. Beamforming algorithms can also be provided for either spherical or planar cases. For the planar case, the array is assumed to be far enough from the source plane so that there is no path length difference for different points on the source plane (acoustic plane wave assumption). For the more complex spherical case, path lengths are assumed to be different and are accounted for properly by including spheri- cal divergence. Because of the large physical size of the source plane for trucks, spherical beamforming which tracks the vehi- cle during the passby is likely the only appropriate approach to consider. Based on the analysis of existing literature, research, and current practices, as well as the study team’s experience in the preceding truck noise studies, beamforming is considered the most promising noise mapping method for trucks. It is capa- ble of mapping both vertical and horizontal noise source dis- tributions and implicitly carries with it spectral information about sources under actual operating conditions. Unlike the sound intensity and acoustic holography techniques, this method is also capable of identifying and tracking large mov- ing sources during uncontrolled vehicle passby testing. Although beamforming techniques are promising for local- izing truck noise sources under passby conditions, several issues needed to be resolved before this technique could be selected for the truck application, namely: • The spatial resolution of the technique for the frequencies of interest for truck noise. In the successful applications in the literature, the revealing “pictures” of sound are typically higher in frequency, above 1500 Hz. In part because of the longer wavelengths and the limitations of the array, at fre- quencies below 1000 Hz the source regions may appear quite large and source identification uncertain. • Source-to-array distance. For controlled tests, distance can be optimized to be relatively close to the vehicle. For road- side measurements, practical issues of safe access, ambient conditions, and not distracting drivers limit how close the array can be positioned to the lane of travel. • Practical concerns such as the effect of large vehicle wakes, random turbulence, and other background noise. A study (20) performed by Illingworth & Rodkin, Inc. (I&R) under contract to Caltrans in 2005 focused on the ability of beamforming technology to localize sources on different types of trucks under several modes of operation. The results of this work addressed many of the application issues mentioned pre- viously. The data from the Caltrans project was used to opti- mize the methodology with regard to the number of array microphones needed and the configuration of the array itself. The signal processing required for the beamforming algorithm was developed by Dr. William Blake for both the Caltrans study and this NCHRP study and includes spherical diver- gence, source tracking, and Doppler shift, as described in more detail in Section 3.2.1. A significant part of the demonstration of a relatively new technique such as beamforming is to demonstrate that it yields 8

correct results and agrees with measurements from established methods. The work of Crewe et al. (19) provides some of that demonstration. Their test vehicle was, however, rather simple—a minivan whose dominant noise source was tire– pavement noise. Two non-tire noise sources were identified: the vehicle’s horn and a speaker placed in the top near part of the engine compartment. The distribution of noise sources on heavy trucks is, in general, considerably more complex and requires additional technique verification. 1.4 Objective and Scope of Research The objective of this study was to use acoustic measure- ments and noise source mapping techniques to accurately identify, locate, and quantify the noise sources on typical com- mercial truck and tractor-semitrailer combinations operating in the U.S. roadway environment. The scope of work for this project was divided into nine tasks that generally define and demonstrate a technology for truck noise source localization, plan and execute mea- surements to better understand truck noise source distri- butions under actual operating conditions, and document the results throughout the project. These tasks are detailed in Chapter 2. The interim report for the project, submitted in July 2007 in accordance with Task 4, presented the results of the literature search, development of the experimental design, and proof-of- concept tests (Tasks 1 through 3). Upon an NCHRP review and approval of the interim report, the roadside test plan was developed and implemented in Tasks 5 and 6. This final report incorporates the interim report material revised per the NCHRP comments (Tasks 1 through 4), includes the results of the roadside truck testing (Tasks 5 and 6), summarizes the key findings of the study (Task 7), and identifies the future research and testing needs (Task 8). 9

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TRB’s National Cooperative Highway Research Program (NCHRP) Report 635: Acoustic Beamforming: Mapping Sources of Truck Noise explores the acoustic beamforming technique in an attempt to pinpoint and measure noise levels from heavy truck traffic. The beamforming technique uses an elliptical array of more than 70 microphones and data acquisition software to measure noise levels from a variety of noise sources on large trucks—including the engine, tires, mufflers, and exhaust pipes.

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