De-Dopplerisation in Vehicle External Noise Measurements

Transcription

1 VSB-Technical University of Ostrava Faculty of Mechanical Engineering Department of ontrol Systems and Instrumentation De-Dopplerisation in Vehicle Eternal Noise Measurements Jiri Tuma 7. listopadu 5, Ostrava Poruba zech Republic 3 July 24 ISV

2 Outline Pass-by vehicle noise measurements Doppler phenomenon Vehicle velocity and position Vehicle tonal noise sources Vehicle pass-by noise analysis Multispectrum decomposition Vold-Kalman Order Filter, the second generation onclusion 3 July 24 ISV 2

3 Pass-by Vehicle Noise Measurements ISO standard R : Peak noise level at time constant FAST, measured in db(a) scale Etended frequency analysis: Recording Signals Pass-by Noise (Mic Left, Mic Right) Vehicle Engine RPM (Tacho probe) 3 July 24 ISV 3

4 Doppler Phenomenon - Vehicle v R v V Test track 7.5 α Microphone Vehicle velocity relative to the microphone sin v R v V where ( α ) 2 2 ( α ) 7.5 sin + Vehicle position t v V dt Doppler frequency shift c f where c is the sound velocity f c + vr De-Dopplerisation process avoids Doppler effect in frequency analysis 3 July 24 ISV 4

5 Vehicle Velocity and Position It is assumed that the wheels circumferential speed v K is proportional to the engine angular speed ω F T F Z v K v V - Longitudinal force coefficient vs. tire slip vk vv s p v F F T Z f M s M k s P Longitudinal force for proportionality range FT vk vv FT FZ F Z vk s Ma M Equation of Motion dvv FT m dt Euler s method for numeric solution dvv vt vv [ vv ] t+ t [ vv ] t+ t [ vv ] t+ K t dt v T 3 July 24 ISV 5

6 Vehicle Pass-By Noise Analysis Fourier transform (implemented in 994) Etraction of the multispectrum components with a frequency that is a multiple of the engine rotational speed Vold-Kalman order tracking filter (24) Etraction of the envelope of a modulated harmonic component 3 July 24 ISV 6

7 Vehicle Tonal Noise Sources Engine timing gears rankshaft Fan amshaft E3 E2 E4 Air ompressor Fuel injection pump Oil pump Input shaft Secondary shaft Output shaft N Gearbo R REV E5 Drop gearbo 3 July 24 ISV 7

8 Multispectrum decomposition 3 July 24 ISV 8

9 Truck Pass-by Noise Multispectrum 3 July 24 ISV 9

10 Truck Noise Sources ontribution to Overall Pass-by Noise Level 3 July 24 ISV

11 Second generation of the Vold-Kalman order tracking filter 3 July 24 ISV

12 Data Equations (eq. measurement equation) ( n) ( n) ep ( jθ( n) ) + η( n), n N y,, where Θ n ( n) ω( i) i t Matri form of equations y η η η where is a diagonal matri { ep( jθ() ),, ( jθ( N ))} diag ep Square of error-vector Euclidean norm ( T y )( y ) y(n) measured signal η(n) error term Θ(n) phase ω(n) angular frequency (n) comple envelope t sampling interval 3 July 24 ISV 2

13 Structural Equations (eq. process equation) Two-order difference equation Im double root n 2 n + n 2 Let to be (n) filtered signal, ε(n) error term Added constrains to force smoothness of an envelope ( ) ( ) ( ) Solution in the form a linear function of n n n ( n) az + bnz a + cn t ( c t b) ( n) ( n ) ε ( n) ( n) 2( n ) + ( n 2) ε ( n) ( n) 3( n ) + 3( n 2) ( n 3) ε ( n) z Re one-pole filter two-pole filter three-pole filter 3 July 24 ISV 3

14 Matri Form of Structural Equations Structural equation emulating the two-pole filter ( n) 2 ( n ) + ( n 2) ε( n), n N 2 () 2 ( 2),, 2 ( N ) ε ε ε () 3 ( 4) ( N ) Banded sparse matri A N-2 rows N columns Matri form of equations A ε Square of error-vector Euclidean norm ε T ε A T A 3 July 24 ISV 4

15 Global Solution Equations y η and A ε forms a system of underdetermined linear equations. Loss function: 2 T T J r ε ε + η η min r weighting coefficient A T A * A T A Solution: r J 2 ( T ) A A + E y ( 2 T A A E) r + y r 2 A T A+E SPD Symmetric Positive Definite matri 3 July 24 ISV 5

16 Software for Vold-Kalman Order Filtration LabShop PULSE, Software Type 773 IDEAS VSB Technical University of Ostrava M-functions in MATLAB, including crossing orders Signal Analyser (Visual Basic), without crossing orders 3 July 24 ISV 6

17 Effect of Weighting oefficient on Filter Selectivity Low-Pass Filter Roll-Off per Decade -2 db * Pole Number Narrow Band Signal -2 f f Frequency shift y(t)* ep(-jω t) Abs bandwidth in rel freq r Abs bandwidth in rel freq - -2 f f *f/fs Weighting coefficient 3 July 24 ISV 7

18 3 July 24 ISV 8 Multi-component filtration Data and structural equations for etraction of P components ( ) ( ) ( ) ( ) ( ) N n n n j n n y P ï i i,,, ep + η Θ,,,, P i J i P i k k k k i i i i + y B Global solution P matri blocks P matri blocks y y y B B B P P P P P P P * PP block matri E A A B + i T i i r 2

19 Pass By Noise Measurements [Pa],5,,5, -,5 -, -,5 Time istory : 3r : Left Time [s] RPM c/(c-v) RPM r : Inst Speed Vold-Kalman : 3r : Left,2,,,99,98,97 - Time [s] Position [m] 3 July 24 ISV 9 c/(c-v)

20 Pass By Noise Multispectrum Autospectrum : 3r : Left RPM RMS db(a)/ref 2E-5 Pa Frequency [z] 3 July 24 ISV 2

21 Toothmeshing omponent Envelope RMS db(a)/ref 2E-5 [Pa] Vold-Kalman : 3r : Left Position [m] 27 ord 54 ord 8 ord 3 July 24 ISV 2

22 onclusion The paper describes dedopplerisation of the noise signal filtered using Vold-Kalman order tracking filter. The resulting noise level of the signal component as a function of the vehicle position in relation to the microphones gives clear information about the significance of the noise source of interest. 3 July 24 ISV 22