research on health risk due to impulsive noise and vibrations

University of CincinnatiApplied Acoustics/Mechanics Lab

Research on Health Risk due to Impulsive Noise and Vibrations

Research Results Conducted in Collaboration with NIOSHProfessor Jay KimStudents:

Xiangdong Zhu, Wonjoon SongUniversity of CincinnatiMarch 2006


Presentation Overview

Background Analytic Wavelet Transform as the Basic Signal Analysis

Tool for Impulsive Events Hearing Loss Due to Impulsive Sound

Current work Long-term approach

Hand Arm Vibration Syndrome (HAVS) Some preliminary results Planned approach

Other Applications of AWT Gunshot data/ear protector analysis AWT based rotating systems analysis


Background: Conducting NIOSH-UC power tool research consortium, lack of method for assessment of exposure risk to impulsive noise and vibrations

Impulsive Noise Induced Hearing Loss (INIHL) Complex noise environment in

workplaces Military noises

Hand-Arm Vibration Syndrome (HAVS) due to impulsive vibrations

Current codes are based on steady-state metrics ignoring temporal variation of spectral characteristics

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1-30

-20

-10

0

10

20

30

Time (s)

Pre

ssur

e (P

a)

Impact Wrench

Measured noise from power wrench


Issues in Risk Assessment of Impulsive Noise and Vibrations Inherent difficulties of transient events

More parameters are necessary to characterize the event Difficult to formulate metric and relate it to experimental or

demographic study results Characterization technique: time-frequency analysis is

necessary Wavelet analysis should be a choice, but nearly entire existing

practices and data are based on Fourier quantities Analytic Wavelet Transform (AWT): a hybrid of wavelet and FFT

that works like a superb transient FFT analysis. All Fourier definitions, SPL, frequency spectra, can be defined in transient sense.


Current Status (1/2): Impulsive Noise

Impulsive Noise: Current standards (OSHA, NIOSH, European standards) are

based on equal energy hypothesis (85 dB, 6 dB exchange rule) Use of dBA is considering spectral information Temporal information is considered in very limited sense through

allowable maximum peak SPL Temporal variation of frequency spectrum is not considered

Research efforts to reflect temporal variations: AHAAH model by Price and Kalb: time domain simulation of human

ear Chinchilla based study on INIHL by Hamernik et. al.

Expose chinchillas to steady-state and impulsive/complex noise Used Kurtosis as the metric to represent temporal variations


Current Status (2/2): Impulsive Vibrations

Impulsive Vibrations: Similar to INIHL cases because of the transient nature, but

dissimilar because hand and arm do not have spatial frequency sensor as the hearing organ

Group of researchers at NIOSH Morgantown Established frequency weightings for hand-arm vibrations and finger

vibrations Developed standard test procedures, numerical models,

demographic study and theoretical background Collaboration with UC is embarked in applying AWT and transient

analysis technique to HAVS


Analytic Wavelet Transform (AWT): brief background (1/2)

Use variable time-frequency atom: source of the main advantage of wavelet analysis for transient signals

tu

s

os

ou

,u s ,o ou s

,ˆ ( )o ou s

,ˆ ( )u s

os

s

/ os

/ s

picks up fast, high-frequency components

picks up slow, low-frequency components

Problems

Works in un-familiar terms to engineers and scientists: scale, wavelet intensity, etc. instead of frequency and amplitude


Analytic Wavelet Transform (AWT): brief background (2/2)

Hybrid of wavelet transform and Fourier transform Work in terms of traditional Fourier variables: frequency, amplitude

and phase, however all as functions of time A perfect replacement of Short-time Fourier transform (STFT) for

transient analysis

*, ,( ) ( ), ( )s t s t sW t f u f u dt

,

1( )u s

u tu

s s

2

222 1/ 4

1( ) ( )

( )

tj t j tt g t e e e

Our version of AWT is set up so that each AWT provides a time history of 1/3 octave component of center frequency of

s


AWT: application example(1/2)

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1-30

-20

-10

0

10

20

30

Time (s)

Pre

ssur

e (P

a)

Impact Wrench

Impulsive sound, time domain

T-F representation by AWT with cochlea mapping T-F representation by STFT

Inst. 1/3 octave spectrum

1/3 octave time history

Superiority of AWT compare to STFT is clear

AWT

STFT


AWT: application example(2/2)

0 0.05 0.1 0.15 0.20

100

dBA

, 12

5 H

z

time, s0 0.05 0.1 0.15 0.2

0

100

dBA

, 12

50 H

z

time, s

0 0.05 0.1 0.15 0.20

100

dBA

, 50

0 H

z

time, s0 0.05 0.1 0.15 0.2

0

100

dBA

, 10

00 H

z

time, s

0 0.05 0.1 0.15 0.20

100

dBA

, 20

00 H

z

time, s0 0.05 0.1 0.15 0.2

0

100

dBA

, 40

00 H

z

time, s

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

7000

Airbag sound

T-F plot

1/3 octave time histories


Hearing Loss due to Impulsive Sound (1/3): Current approach in pending NIH proposal

Chinchilla Test Data at SUNY-Plattsburgh

Digitized Noise data

Various, controlled noise set

About 400 Chinchillas

TTS, PTS, IHC and OHC loss data as functions of frequency

AWTT-F noise metrics

Statistical correlation study to choose the best metric

Chinchilla NIHL model

Human NIHL model

Existing data

Proposed research


Hearing Loss due to Impulsive Sound (2/3): long-term plan

Human NIHL model

Chinchilla ear model

Human ear model

Ear simulation model output (basilar membrane displacement)

Ear simulation model output

Inter-species scaling law

Environmental Noise AWT

NIHL risk

noise metric

Final form of implementation

Necessary development


Hearing Loss Due to Impulsive Sound: long-term plan (3/3): Develop inter-species scaling law

Chinchilla NIHL model

Simulation ear model for chinchillas

Test Noise Data

Cat NIHL model

Simulation ear model for cats

Model output (basilar membrane displacement)

Model output

Inter-species scaling law

Simulated cat NIHL dataRepeat NIHL model

development for cats using cat experiment data Confirm scaling law

development

use

Compare to validate


Example of Ear Model: AHAAH model developed by Price and Kalb

Outer EarInner Ear

Middle Ear

area

Ue

Pe Lh RhCb

LdsCds

Rds

Eardrum conductive part

Ldm Cdc Rdc 1:Nt

Cm

Diffraction sound field

Air Plug

ConchaEarcanal

Li Ls Cal Ral LvCochleaIncus Stapes

Annular ligament

Vestibular Volume

Uc

Lo

RoRcPc

HelicotremaRound window

Incudo- stapedal

joint

Malteo- Incudal

joint

Lever and area

ratio

Eardrum independent

partBulla

Rmi

Cmi Cis

Ris Crw

Rdf

Ldf

2P P

Lpl

Rpl L1 L2 L3

A1 A2 A3

length


Hand Arm Vibration Syndrome (1/3)

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

-200

-150

-100

-50

0

50

100

150

200

time [sec]

x-di

r ac

cele

ratio

n [m

/s2 ]

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

-3000

-2000

-1000

0

1000

2000

3000

time [sec]

x-di

r ac

cele

ratio

n [m

/s2 ]

Time series

T-F representation with ISO HA frequency weighting

T-F representation with one of frequency weightings proposed for fingers



0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.110

0

101

time [sec]

tota

l acc

eler

atio

n [m

/s2 ]

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.110

0

101

time [sec]

tota

l acc

eler

atio

n [m

/s2 ]

2

1

( ) ( , )fn

f f ii

a t A f t

Sum frequency components at each time point

Frequency weighted time history: reflects what hand arm feel



0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.110

0

101

time [sec]

tota

l acc

eler

atio

n [m

/s2 ]

HAVS threshold acceleration level

Metric based on frequency weighted time history

Hazard dose curve

2

11 1

( )1 1N Nf j th

jj j th

a t aI I

N N a

( )

21 1

1 1 1f j th

th

a t aN N

j aj j

eI I

N N e

Non-linear metric function

Threshold level


Gunshot sound analysis

Outside of ear protector

Inside of ear protector

Reduce SPL


Other Interesting Application: AWT based Campbell diagram

Fourier transform based Campbell Diagram

AWT based Campbell Diagram

Rotating system start-up analysis

In-situ FRF construction without excitation


Questions/Suggestions?

research on health risk due to impulsive noise and vibrations

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