Assessment of measurement-based methods for separating wheel and track contributions to railway rolling noiseApplied Acoustics, https://doi.org/10. 1016/j.apacoust.2018.05.012 Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. AbstractThe noise produced during a train pass-by originates from several different sources such as propulsion noise, noise from auxiliary equipment, aerodynamic noise and rolling noise. The rolling noise is radiated by the wheels and the track and is excited by the wheel and rail unevenness, usually referred to as roughness. The current TSI Noise certification method, which must be satisfied by all new mainline trains in Europe, relies on the use of a reference track to quantify the noise from new vehicles. The reference track is defined by an upper limit of the rail roughness and a lower limit of the track decay rate (TDR). However, since neither the rail roughness nor the track radiation can be completely neglected, the result cannot be taken as representing only the vehicle noise and the measurement does not allow separate identification of the noise radiated by wheel and track. It is even likely that further reductions in the limit values for new rolling stock cannot be achieved on current tracks.There is therefore a need for a method to separate the noise into these two components reliably and cheaply. The purpose of the current study is to assess existing and new methods for rolling noise separation. Field tests have been carried out under controlled conditions, allowing the different methods to be compared. The TWINS model is used with measured vibration data to give reference estimates of the wheel and track noise components. Six different methods are then considered that can be used to estimate the track component. It is found that most of these methods can obtain the track component of noise with acceptable accuracy. However, apart from the TWINS model, the wheel noise component could only be estimated directly using three methods and unfortunately these did not give satisfactory results in the current tests.

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This study investigated how speech recognition in noise is affected by language proficiency for individual non-native speakers. The recognition of English and Chinese sentences was measured as a function of the signal-to-noise ratio (SNR) in sixty native Chinese speakers who never lived in an English-speaking environment. The recognition score for speech in quiet (which varied from 15%–92%) was found to be uncorrelated with speech recognition threshold (SRTQ /2), i.e. the SNR at which the recognition score drops to 50% of the recognition score in quiet. This result demonstrates separable contributions of language proficiency and auditory processing to speech recognition in noise.

This paper investigates the effect of the directivity of railway noise sources on the results of an identification procedure based on beamforming using a microphone array. Usually when performing pass-by noise tests, a single-microphone noise spectrum is obtained for a time window corresponding to the length of the whole train, or of a single vehicle. In this context, a source quantification algorithm should be able to evaluate the contribution of each noise source over this time window. However, different railway noise sources have different directivities, and it is shown that these need to be taken into account to achieve accurate source quantification. By making use of monopoles, dipoles and quadrupoles, it is shown that a different compensation is needed according to the directivity. For the particular case of the noise radiated by the rail, this has a complex directivity pattern that is only partially captured by a microphone array. It is demonstrated that the overestimation of the wheel contribution found in previous research may be attributed to a misinterpretation of part of the rail contribution from the beamforming map.

Ball valve is the core control component for flow in HVAC (Heating, Ventilation and Air Conditioning) system. And valve's flow noise is one of the key parameters to evaluate its performance. Ball valve's flow field is modeled by finite element method based on Lighthill acoustic theory. And turbulent kinetic energy of the flow field is obtained. The noise generation mechanism of ball valve's flow is obtained by analyzing the contours of pressure, velocity and sound pressure level. In order to reduce sound pressure level of ball valve, noise reduction scheme was proposed. And ball valve was reformed. Flow field characteristics of the modified ball valve are analyzed by numerical simulation method. The feasibility of noise reduction scheme is verified by experiments. The results show that refitted ball valve has good noise reduction effect while guaranteeing small change of flow. INDEX TERMS Ball valve, flow noise, noise reduction.