Post on 26-Aug-2018
Audio System Evaluation with Music Signals, 1
Audio System Evaluation
with
Music Signals
Stefan Irrgang,
Wolfgang Klippel
KLIPPEL GmbH
Audio System Evaluation with Music Signals, 2
Motivation
• Field rejects are $$$
• Reproduce + analyse the problem before repair
Audio System Evaluation with Music Signals, 3
Audio System Evaluation
over the product life cycle
DefinitionTarget
Performance
Target Application Condition
DefinitionTarget
Performance
ProductSpecification
Standard Measurement Condition
Target Application Condition
DefinitionTarget
Performance
ProductSpecification
Development(components,
system)
Physical + PerceptualAssessment
PhysicalEvaluation
Standard Measurement Condition
Target Application Condition
DefinitionTarget
Performance
ProductSpecification
Development(components,
system)
Physical + PerceptualAssessment
PhysicalEvaluation
EOLTesting
Standard Measurement Condition
Target Application Condition
Production
DefinitionTarget
Performance
ProductSpecification
Development(components,
system)
Physical + PerceptualAssessment
PhysicalEvaluation
EOLTesting
FieldMonitoring
Service
Standard Measurement Condition
Target Application Condition
Production
Audio System Evaluation with Music Signals, 4
After Sales / Field Measurements
Acoustical measurements using (available) microphones reveal
- Frequency Response, SPL
- Overall transfer function
- Coherence
- Residual Distortion
Electrical measurements based on voltage and current monitoring
(control technology) reveal
- Voice coil and magnet temperature
- Peak displacement and offset in coil rest
position
- Change of suspension stiffness indicating
fatigue
- anticipation of a motor or suspension defect
DSP~audio
signal
amplifier
u, i
microfone
wooferparasitic vibration
u, i
amplifier
internal
sound
sourcesambient
noise
Challenges - audio signal used
- influence of other sound sources
- use of compromised test elements
- measurement shall be realized at low
cost
Objectives - evaluation of the performance as seen
by the end user
- long term testing under real condition
- Prevention of a total failure
- Service for customer complaint
Audio System Evaluation with Music Signals, 5
What is a critical defect?
• Related to customer complaints
• Observable in in-situ condition Impulsive distortion (panel buzzing, loose
particles, loose electrical connection) Significant air noise caused by a leakage of
the enclosure (Subwoofer) Excessive nonlinear distortion caused by
motor instability and severe asymmetries
Audio System Evaluation with Music Signals, 6
Input
Signal
Output
Signal
Linear Model
H(s)-1
Nonlinear
Model
Noise
u(t) p(t)
dn(t)
n(t)
dl(t)
Linear
Distortion
Nonlinear
Distortion Large Signal
Performance
(motor, suspension)
Undesired Defects • Rubbing coil, Buzzing parts
• Wire beat
• Loose particles, air leak noise
• Parasitic vibration of other components
Desired Small
Signal Performance
Reproduced Sound Quality Generation of Signal Distortion in an Audio System
Irregular
Distortion
Residual
Distortion
StimulusMeasured
Signal
Audio System Evaluation with Music Signals, 7
Properties of Music Stimulus
• Dense stimulus / Most complex
• Non persistant excitation
• Non stationary excitation
(Unknown time structure)
• Defects occur quasi randomly
How to separate defect from
accepted response?
Audio System Evaluation with Music Signals, 8
State of the art Correlation Technique
Stimulus
FFT
DUT
Y(f,n)
Syy(f,n)
),(ˆ nfSyy
FFT
MA MA
()*
H(f,n)IC(f,n)
Sxy(f,n)
Calculation
MA
Sxx(f,n)
X(f,n)
()*
)(ty
),(ˆ nfSxx ),(ˆ nfSxy
HWHW
Y*(f,n)
)(tx
Linear System Identification:
• Correlation Technique
• Requires Stationary Signals
),(ˆ
),(ˆ),(
,
,
nfS
nfSnfH
xx
yx
Incoherence:
• Power metric
• Good for Noise problems
• Moderate for regular non-linearities
• Poor for time varying TRF
• Poor for impulsive distortion
%100),(ˆ),(ˆ
),(ˆ
),(
,,
,
nfSnfS
nfSnf
yyxx
yx
dB%100
),(1log10),(
nfnfICdB
Audio System Evaluation with Music Signals, 9
State of the art Correlation Technique
Incoherence:
• Requires long (statistical!) time for accurate estimation (see paper) for low
energy symptoms.
• T is defined by required resolution (Woofer 1 Hz / Midrange 5 Hz)
• K (number of processed blocks) = f(error)
• Example: df = 1Hz, total time =5s
error: 30%, Incoherence too low by 1.5dB
• Assumption: stationary excitation
• When using non-stationary signals: Symptoms may be not stable!
• No Auralization of separated distortion (power measure!)
KfIC
fICfeIC
%100
)(
)()(
T
KTtot
2
Audio System Evaluation with Music Signals, 10
State of the art Correlation Technique / Measurement Results
KLIPPEL
10
10 2 10 3 10 4
Incoherence
Frequency [Hz]
Defect SetupNormal
Setup
1
Frequency [Hz]Frequency [Hz]
IC [%
]
100
Distortion from regular nonlinearities mask symptoms from rattling
Incoherence measurement is not sensitive for impulsive distortion
Audio System Evaluation with Music Signals, 11
Acoustical In-Situ Measurement
Linear Distortion
Audio Source
DUT
p
Audio Source
DUT
-
Physical Characteristics
AdaptiveLinear
Modelling plin
p
Linear Distortion
Adaptive Identification of Linear System
Properties:
• Adaptive identification
• Fast initial learning
• Copes with non
stationary input
• Follows changes of
linear system
Improved separation
• Typical ANC method
Audio System Evaluation with Music Signals, 12
Short Term Response (1 s)
Compression of SPL Output
Long term response
measured after
applying the
sinusoidal stimulus
for 1 min
Sound Pressure Response
20 50 200 500 2k
Frequency [Hz]
80
85
90
95
100
105
110
115
120
125
130
dB
Long Term Response (1 min)
Short term response
measured within 1 s
(without voice coil
heating)
Audio System Evaluation with Music Signals, 13
KLIPPEL
50
60
70
80
90
100
110
120
130
140
150
160
170
0 500 1000 1500 2000 2500 3000 3500
resonance frequency fs (t) at rest position X=0
Kms [N
/mm]
t [sec]
fs (X=0)
Hz
Influence of Ambient Conditions
More than one octave shift
KLIPPEL
0
25
50
75
100
125
150
0
1
2
3
4
5
6
7
8
9
10
11
12
0 500 1000 1500 2000 2500 3000 3500
Delta
Tv [K
]
P [W]
t [sec]
Delta Tv Tambient P real P Re Pnom
Winter
Sommer
Ambient temperature
-30° C
80° C
Influence to the Loudspeaker System Alignment
Properties of the mechanical suspension depend on humidity, temperature
voice coil displacement cannot be predicted by time-invariant parameters
adaptive learning process required
Audio System Evaluation with Music Signals, 14
Acoustical In-Situ Measurement Residual Distortion
Audio Source
DUT
-
dr
Physical Characteristics
Adaptive
Linear
Modelling
Residual
Distortion
plin
p
Linear
Distortion
Properties:
• Model identifies linear
system only Separation
of residual from linear
distortion
• Exploit Residual:
• Non-linear Distortion
• Defect Distortion
• Noise
Audio System Evaluation with Music Signals, 15
Assessing Regular Nonlinear and Irregular
Distortion
Impact on sound quality:
• Parasitic resonances are excited by
sufficient (kinetic) energy
• Defect occurs rarely
• Depends on
• Level (not highest!)
• Phase relationship
• Distortion require high state (e.g. Bl(x))
KLIPPEL
0.00
0.25
0.50
0.75
1.00
1.25
-3 -2 -1 0 1 2 3
PD
F [
1/m
m]
Displacement [mm]
Proabilitiy densitiy function (pdf)
sine tone
music
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
-5 -4 -3 -2 -1 -0 1 2 3 4 5
Bl [N
/A]
<< Coil in X [mm] coil out >>
Nonlinear Force Factor
More comprehensive
then sine sweep!
Audio System Evaluation with Music Signals, 16
Audio system defect: Parasitic Vibration problem
Most defects behave as a nonlinear oscillator
• active above a critical amplitude
• new mode of vibration
• powered and synchronized by stimulus
Loose joint
(Nonlinearity)
parasitic resonator
Externally excited
spring
mass
Loose joint
(Nonlinearity)
parasitic resonator
Externally excited
spring
mass
time one period
vibration
distortion signal
Audio System Evaluation with Music Signals, 17
Residuum of the Linear Modeling (defect in car)
KLIPPEL
-0.10
-0.05
0.00
0.05
0.10
0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
Time [s]
Mic
. V
oltag
e
[V]
tambourine measured signal p(t)
modelled signal plin(t)
residuum e(t)
+10dB (!)
next
Audio System Evaluation with Music Signals, 18
Time Frequency Analysis of the Residuum
KLIPPEL
210
310
410
0.2 0.4 0.6 0.8 1.0 1.2 1.4
Fre
qu
en
cy
[Hz]
Time [s]
-74
-71
-68
-65
-62
-59
-56
-53
-50
-47
-44
-41
-38
-35
0 0.5 1.0 1.5Time [s]
Fre
q. [H
z]
100
1k
10k-35
-38
-41
-44
-47
-50
-53
-65
-68
<-68
-56
-59
-62
dBFS KLIPPEL
210
310
410
0.2 0.4 0.6 0.8 1.0 1.2 1.4
Fre
qu
en
cy
[Hz]
Time [s]
-74
-71
-68
-65
-62
-59
-56
-53
-50
-47
-44
-41
-38
-35
0 0.5 1.0 1.5Time [s]
Fre
q. [H
z]
100
1k
10k-35
-38
-41
-44
-47
-50
-53
-65
-68
<-68
-56
-59
-62
dBFS
Defect
defective car (with tambourine)
Normal car (without tamborine)
KLIPPEL
0.00
60 62 64 66 68 70
V
Time [ms]
Normal car
Defective car
-0.02
0.01
0.02
-0.01
residuum in time domain
next
Audio System Evaluation with Music Signals, 19
Standard EOL test of defect
KLIPPEL
210
310
410
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Fre
qu
en
cy
[Hz]
Time [s]
-95
-92
-89
-86
-83
-80
-77
-74
-71
-68
-65
-62
-59
-56
-53
-50
-47
-44
-41
-38
-35
0 0.5 1.0Time [s]
Fre
q. [H
z]
100
1k
10k
dBFS-35
-41
-47
-53
-65
-71
-59
-77
-83
-89
KLIPPEL
210
310
410
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Fre
qu
en
cy
[Hz]
Time [s]
-95
-92
-89
-86
-83
-80
-77
-74
-71
-68
-65
-62
-59
-56
-53
-50
-47
-44
-41
-38
-35
0 0.5 1.0Time [s]
Fre
q. [H
z]100
1k
10k-35
-41
-47
-53
-65
-71
-59
dBFS
-77
-83
-89
defective car (with tambourine)
Normal car (without tamborine)
So
und
Pre
ssure
[d
B]
Frequency [Hz]
KLIPPEL
30
40
50
60
70
80
90
100
110
101
102
103
104
Defect
Pass/Fail Limit
Fundamental
Rub&Buzz
Using log sweep
Audio System Evaluation with Music Signals, 20
Audio Source
DUT
-
Physical Characteristics
AdaptiveLinear
Modelling plin
p
Linear Distortion
Time-Variant
Distortion
Adaptive Identifcation of slowly changing
linear system
Acoustic In-Situ Measurements Auralization
pAAudio Source
DUT
- dr
Sdis
Physical Characteristics
Listening
Test
Perceptual Characteristics
Auralization
plin
p
Linear
Distortion
Perceptional
Modeling
Adaptive
Linear
Modelling
Residual
Distortion
Adaptive Identification
provides:
• Separated linear
response
• Purified from time variant
linear distortion
• Residual Distortion to be
scaled up and down
Benefit:
• Objective Criteria
• Rate importance
• Is this defect acceptable?
• Action required?
Audio System Evaluation with Music Signals, 21
Finding most critical section
KLIPPEL
-30
-25
-20
-15
-10
-5
0
5
50 75 10025 150
Distortion ratio
dB
re
l.
Time s
mean
distortion
peak
distortion
RMS
125
Challenge:
• Find highest distortion in a
long recording
• Non-Stationary excitation
Solution:
• Check Crest factor of
Residual:
High Peak and Low Mean
distortion indicate
impulsive distortion
(defect symptom)
Select Best Section
Audio System Evaluation with Music Signals, 22
Summary
• Simple Setup – Wave file / Web based solutions
• Comprehensive System Evaluation – Linear Response + Residual distortion
• Using any stimulus – Customer specific audio material
• Fast Identification of defects – Automatic selection of critical section
– Time Domain Analysis
– Auralization