Identification of rail contribution to pass-by noise by a modified wave signature extraction (WSE) method

• The present paper explores a modified version the wave signature extraction (WSE) method [1], whose aim is to separate the rail contribution to the pass-by noise of railway vehicles. The method requires a line microphone array parallel to the rail, and two accelerometers on the rail in the ver- tical and lateral direction. The motivation for this work is the need to separate the rail contribution to the pass-by noise of railway vehicles. The WSE method [1] is based on the wavenumber domain filtering of pass-by data measured with a microphone array located in the near-field of the rail. The filter design does not require a priori information of the structural properties of the rail, since the required information is obtained from array pressure data and rail vibration data before and after the train passes in front of the array. The filter is such that it extracts the dispersion plot branches of the first family of horizontal and vertical bending waves (moving band-pass filter). Although the comparison with TWINS simulation data provides very promising results, there are discrepancies at the higher frequencies, possibly due to the onset of new bending wave families. Therefore in the present paper we propose a modified filtering procedure, where a bank of band-pass and low-pass filters are used instead, and the results are compared to the original WSE implementation and the TWINS simulation data. We show that the results in the higher frequency range are improved with respect to the original WSE implementation.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Strömningsmekanik och akustik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Fluid Mechanics and Acoustics (hsv//eng)

Keyword

Vehicle and Maritime Engineering

Farkostteknik

Engineering Mechanics

Teknisk mekanik

Electrical Engineering

Elektro- och systemteknik

Publication and Content Type

vet (subject category)

kon (subject category)