1

Challenge

Real-time modeling of sounds and noise is increasingly

needed in product development.

Solution

AMP- Audible Model Platform, built on SIMULINK.

Advanced parameterized ”noise player”, may utilize

measured or modeled parameters

Results

Working AMP concept

Usage of AMP in several application areas

Utilization of AMP in evaluation of sound quality

VTT Technical Research Centre of Finland | Marko AntilaDesign of a Real-time Audible Noise Modeling Platform using Simulink

2

Motivation and challenge

Real-time modeling become more and more important

Including sounds and noise!

Not only for training and visualization-auralization but

True virtual model-based product development

Systems needed for quick what-if analysis

Should operate stand-alone and also with a Virtual Reality (VR),

in Virtual Environment (VE)

Need for a tool to create sounds to be evaluated for quality (Psychoacoustics)

Several commercial sw applications to model noise exist

Still wanted something modular, easy-to-use and re-usable

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3

Requirements

1. Lightweight processing needs

Should run on a laptop

2. Should produce audible noise in full audio bandwidth

No glitches, dropouts or distortion allowed

3. Parameter-based

Everything driven by parameters

4. Strictly real-time

Immediate response to parameter changes

5. Modular

High re-usability

Suitability for different applications

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4

A solution: AMP - Audible Model Platform

Built on SIMULINK

Advanced parameterized ”noise player”

not a replacement for audible modeling software tools based on physics

Measured or modeled parameters

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Requirement Solution

Lightweight processing need Multi-rate data processing, optimised blocks

Audible noise in full audio bandwidth Frame-based data processing and optimized audio

buffering

Parameter-based All audio is synthesized from a scratch, based on

parameters

Strictly real-time Discrete time solver

Modular Hierarchical design, usage of functional subsystems

Visual and self-documenting Extensive usage of GUI-style blocks

5

Why real-time audible modeling is needed?Why not recorded sounds? Why not off-line?

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Issue Real-time audible modeling Recorded or off-line generated sounds

Possibility to react to ”what-

if” questions

Available, quick evaluation of different

scenarios

Limited, all possible variations must be

available beforehand

Evaluation of non-existent

product

Possible No recordings available, off-line modeling

software may create audio files

Input data complexity and

file size

Low-complexity and lightweight, only

parameters are needed

Well-known audio formats, but may be

large especially in uncompressed formats

Real-time connectivity to

visualization and virtual

reality tools

Excellent, only parameters are sent to control

AMP via UDP

May be used as sample players, but

limited level of controllability

Suitability for different

product sounds

After initial effort to develop the platform easy

to apply to different products due to the

modular, Simulink-based design

All products must be treated separately

and

Accuracy of the audible

sound

Accuracy varies but may be tailored to be

close enough the product sound

Very accurate if recorded form the

product; if off-line generated depends on

the off-line modeling quality

6

A sidestep: AMP background

Spin-off on our work on Active Noise Profiling (ANP) system

– 4 mics, 4 + 1 loudspeakers, 6 engine orders profiled

– tested in lab and road conditions

– Jari Kataja (2012) Development of a robust and computationally efficient active

sound profiling algorithm in a passenger car. Degree of Lic. Tech., Tampere

University of Technology: Tampere, Finland.

Fully featured Simulink model used in the system development was evolved

into AMP

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Tone

synthesis

Output to

loud-

speakers

Error signals

from microphones

Control

law

Parallel

adaptive

filters

Noise target

profile

STacho

Advanced

plant model

CONTROL

ELECTRONICS

AMPLIFIERS

ENGINE SYSTEMS:

- RPM

- Load

- Others

AMPLIFIER

7

AMP application areas

AMP may be used and has been used to reproduce sounds/ noise

in a mine loader cabin (moving machinery)

in a car cabin (vehicles)

around large diesel engines (factories and installations)

wind power noise (environmental noise)

noise in workshops (noise at a workplace)

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8

Case example

Sandvik LH410 (Toro 7) Underground Loading and Hauling Device, LHD

Usually known as a loader

Used in mines to load and transport rocks

9

INDEPENDENT

AUTOMATIC

CONTROL

MANUAL

CONTROL

Hydraulics

(high orders)

RA

TIO

LHD (Loading and Hauling Device) sound sources

Engine

(low orders)

Ventilation/

Air Conditioning

(Blade Passing

Frequency - BPF,

broadband)

Cooling

(BPF,

broadband)

VARIABLE

RATIO

Transmission

after moment

converter

(low orders)

Work

Cycle

sounds

10

Step 1: Binaural recordings

The time domain data captured

In LHD cabin

Also simultaneously rpm and load information, and rpm after

moment converter

Used for the analysis and base for the engine sound model

Also data from modeled audio field might be used

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

x 105

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

11

Step 2: Parameter extraction for periodic noise components

Matlab scripts extract

automatically :

Engine and auxiliary devices

orders level and relative

phase information

By RPM and load

multidimensional table

Automatic data acquisition

from incomplete – partial data

Also visualisation in frequency

and order domains

LOAD

0 20 40 60 80 100

RPM 1000 68,3957 46,70894 58,29323 47,97325 48,01132 40,2533

1250 68,3957 46,70894 58,29323 47,97325 48,01132 40,2533

1500 68,3957 46,70894 58,29323 47,97325 48,01132 40,2533

1750 63,98383 48,27006 50,22502 40,21068 43,9224 39,18387

2000 61,36211 49,72515 50,37796 36,26558 36,61513 42,31848

2250 58,32018 50,11174 46,44691 34,77836 39,67247 45,19108

2500 60,2929 48,71836 48,75093 41,49328 41,58613 44,54498

2750 61,23419 52,47007 49,38902 40,46355 37,90863 35,82102

3000 67,23477 43,25078 49,90166 34,75546 35,94381 37,68533

3250 63,24308 41,11168 47,14768 40,63964 36,89333 45,48749

3500 63,29586 43,97126 47,69728 36,58711 39,92282 36,0829

3750 62,38304 41,30848 44,30967 38,44657 43,163 36,09735

4000 62,38304 41,30848 44,30967 38,44657 43,163 36,09735

4250 59,87534 39,4939 46,8668 45,48802 37,26114 41,48915

4500 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

4750 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

5000 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

5250 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

5500 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

5750 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

6000 69,23209 46,85214 48,23304 40,52334 40,14557 36,57247

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

x 105

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

12

Step 3: Ventilation noise parameter extraction with modeling

Goal: to be able to produce audible ventilation

noise based on the parameters

– Geometry, flow rate, pressure drop,…

Modelling: CFD, parameters to AMP and also to

VE

Result: Audible noise model based on CFD

calculations

Unique: full chain from CFD - > Simulation model -

> real-time audible noise

0 0.5 1 1.5 2 2.5

x 104

-10

0

10

20

30

40

50

60Ventilation noise contributions

Frequency (Hz)

Mag

nitu

de (

dB)

Diff max-min

Diff max-off

Diff min-off

13

Final step: Putting it all together and running the modelParameter

source

selection

Individual

control

of orders Engine

model

Hydraulics/

cooling model

Ventilation

model

Constant

RPM 1200

Run-up/

Run-down

14

Video:

Example run

15

Bonus video:

big diesel

engine

16

Conclusions

Audible Model Platform (AMP) is able to

– reproduce product noise efficiently in SIMULINK

– mimic different products (cars, trucks, moving machinery, diesel engines, wind turbines…)

Some references: Antila M., Kataja J. and Kokkonen E. (2013) Virtual engine and ventilation noise generation for an underground loader cabin. Aachen

Acoustic Colloquium 2013, Aachen, Germany: 167-174.

Antila M., Kataja J., Isomoisio H. and Nykänen H. (2014) Recording, evaluation and artificial real-time creation of metal workshop noise.

Proceedings of Baltic-Nordic Acoustic Meeting 2014 (BNAM 2014). 2 - 4 June 2014 (to be published). Tallinn, Estonia.

Aromaa S, Antila M, Kokkonen E, Krassi B, Leino S, Nykänen H, et al. (2013) Designing user experience for the machine cabin of the

future. In: Belloni K and Ventä O (eds) eEngineering 2009 - 2012 - Digitising the product process. Espoo, Finland: VTT, 45 - 56.

Antila M. and Kataja J. (2013) Tuulivoimamelun kuunneltava malli (Audible model of wind turbine noise, in Finnish). Akustiikkapäivät

2013: 166 - 170. 22. - 23.5.2013. Turku, Finland

Marko Antila

VTT Technical Research Centre of Finland

marko.antila@vtt.fi

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