Neurally Based Measurement and Evaluation of Environmental Noise

268 Pages·2015·16.15 MB·English

by  Yoshiharu Soeta

Mathematics for Industry 20
Yoshiharu Soeta
Yoichi Ando
Neurally Based
Measurement
and Evaluation
of Environmental
Noise
Mathematics for Industry
Volume 20
Editor-in-Chief
MasatoWakayama(KyushuUniversity,Japan)
ScientificBoardMembers
RobertS.Anderssen(CommonwealthScientificandIndustrialResearchOrganisation,Australia)
HeinzH.Bauschke(TheUniversityofBritishColumbia,Canada)
PhilipBroadbridge(LaTrobeUniversity,Australia)
JinCheng(FudanUniversity,China)
MoniqueChyba(UniversityofHawaiiatMānoa,USA)
Georges-HenriCottet(JosephFourierUniversity,France)
JoséAlbertoCuminato(UniversityofSãoPaulo,Brazil)
Shin-ichiroEi(HokkaidoUniversity,Japan)
YasuhideFukumoto(KyushuUniversity,Japan)
JonathanR.M.Hosking(IBMT.J.WatsonResearchCenter,USA)
AlejandroJofré(UniversityofChile,Chile)
KerryLandman(TheUniversityofMelbourne,Australia)
RobertMcKibbin(MasseyUniversity,NewZealand)
GeoffMercer(AustralianNationalUniversity,Australia)(Deceased,2014)
AndreaParmeggiani(UniversityofMontpellier2,France)
JillPipher(BrownUniversity,USA)
KonradPolthier(FreeUniversityofBerlin,Germany)
WilSchilders(EindhovenUniversityofTechnology,TheNetherlands)
ZuoweiShen(NationalUniversityofSingapore,Singapore)
Kim-ChuanToh(NationalUniversityofSingapore,Singapore)
EvgenyVerbitskiy(LeidenUniversity,TheNetherlands)
NakahiroYoshida(TheUniversityofTokyo,Japan)
Aims&Scope
The meaning of “Mathematics for Industry” (sometimes abbreviated as MI or MfI) is different
fromthatof“MathematicsinIndustry”(orof“IndustrialMathematics”).Thelatterisrestrictive:it
tendstobeidentifiedwiththeactualmathematicsthatspecificallyarisesinthedailymanagement
andoperationofmanufacturing.Theformer,however,denotesanewresearchfieldinmathematics
thatmayserveasafoundationforcreatingfuturetechnologies.Thisconceptwasbornfromthe
integrationandreorganizationofpureandappliedmathematicsinthepresentdayintoafluidand
versatileformcapableofstimulatingawarenessoftheimportanceofmathematicsinindustry,as
well as responding to the needs of industrial technologies. The history of this integration and
reorganizationindicatesthatthisbasicideawillsomedayfindincreasingutility.Mathematicscan
beakeytechnologyinmodernsociety.
Theseriesaimstopromotethistrendby(1)providingcomprehensivecontentonapplications
of mathematics, especially to industry technologies via various types of scientific research, (2)
introducingbasic,useful,necessaryandcrucialknowledgeforseveralapplicationsthroughcon-
crete subjects, and (3) introducing new research results and developments for applications of
mathematicsintherealworld.Thesepointsmayprovidethebasisforopeninganewmathematics-
orientedtechnologicalworldandevennewresearchfieldsofmathematics.
More information about this series at http://www.springer.com/series/13254
Yoshiharu Soeta Yoichi Ando
(cid:129)
Neurally Based
Measurement and Evaluation
of Environmental Noise
123
Yoshiharu Soeta YoichiAndo
National Institute ofAdvanced Industrial Kobe University
ScienceandTechnology Kobe
Osaka Japan
Japan
ISSN 2198-350X ISSN 2198-3518 (electronic)
Mathematics for Industry
ISBN978-4-431-55431-8 ISBN978-4-431-55432-5 (eBook)
DOI 10.1007/978-4-431-55432-5
LibraryofCongressControlNumber:2015937752
SpringerTokyoHeidelbergNewYorkDordrechtLondon
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Preface
Environmental noise is a big problem for human beings. Initially, noise level was
thebiggestproblem.Ithascausedmanybadeffects,suchasheadache,discomfort,
hearing loss, sleep disturbance. Long-term environmental noises also have deep
effects and are integrated in the brain and body without any conscious awareness
ofthem,asisdiscussedinChap.9.Particularly,theeffectsofthedevelopmentsof
unborn babies and the specialization of the cerebral hemispheres in growing chil-
dren are serious. Numerous new technologies, such as noise insulation and active
noise cancelling, have been developed and have contributed to the reduction of
noise levels. But people feel annoyed even when the noise level is quite low
because of the qualitative aspects of noises. In addition, the method of measuring
and evaluating noise is still premature because the model of the auditory-brain
system hasended attheperipheral level. Therefore,the development of measuring
and evaluating the quality of noise based on our brain function is becoming more
important for human beings.
This book deals with the methods of measurement and evaluation of environ-
mental noise based on an auditory neural and brain-oriented model. The model
consists of the autocorrelation function (ACF) and the interaural cross-correlation
function (IACF) mechanisms for signals arriving at the two ear entrances. This
model was based on neural evidence. First, we focused on the human auditory
system,whichwasinvestigatedmainlythroughthehumanbrainandpsychological
response, such as by electroencephalography (EEG), magnetoencephalography
(MEG), loudness, and annoyance, because the features of the human auditory
systemhavetobetakenintoaccountinevaluatingthequalityofnoises.Theresults
suggest that the human auditory system has ACF and IACF mechanisms and the
factorsextractedfromthosemechanismsareusefulascuesfortemporalandspatial
sensation of sounds.
It is hoped that the survey presented here will encourage researchers, students,
and engineers in a wide range of fields, such as the automotive industry, the
aerospace industry, mechanical engineering, railways, electronics industries,
soundscape, architecture, and acoustics.
v
vi Preface
This book largely serves as a record of the research carried out at the Ando
Laboratory, Graduate School of Science and Technology, Kobe University,
between1969and2009,evenaftertheauthors’graduationorretirement;aswellas
the studies conducted at the Living Informatics Research Group, National Institute
of Advanced Industrial Science and Technology (AIST) between 2002 and 2015.
The authors thank Dr. Shin-ichi Sato, Dr. Hiroyuki Sakai, Dr. Ryota Shimokura,
Dr.KenjiFujii,Dr.SeijiNakagawa,andDr.MitsuoTonoikefortheircollaboration
and help.
March 2015 Yoshiharu Soeta
Yoichi Ando
Contents
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2 Signal Processing Model of Human Auditory System . . . . . . . . . . 5
2.1 Human Hearing System. . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Neural Evidences of the Autocorrelation Model
in the Auditory Pathways. . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 Neural Evidences of the Interaural Cross-Correlation Model
in the Auditory Pathways. . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.4 Signal Processing Model of Human Auditory System . . . . . . . 29
2.5 Brain Response in Relation to Loudness . . . . . . . . . . . . . . . . 32
2.6 Brain Response Corresponding to Annoyance. . . . . . . . . . . . . 38
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3 Noise Measurement Method Based on the Model. . . . . . . . . . . . . 51
3.1 Correlation Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 Temporal Factors Extracted from the ACF. . . . . . . . . . . . . . . 53
3.3 Temporal Window of the ACF Processing. . . . . . . . . . . . . . . 59
3.4 Spatial Factors Extracted from the IACF . . . . . . . . . . . . . . . . 61
3.5 Auditory Temporal Window for the IACF Processing . . . . . . . 62
3.6 System of Noise Measurement . . . . . . . . . . . . . . . . . . . . . . . 63
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4 Temporal Primary Sensations of Noise . . . . . . . . . . . . . . . . . . . . 69
4.1 Formulation of Temporal and Spatial Sensations. . . . . . . . . . . 69
4.2 Loudness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.2.1 Loudness of Sharply Filtered Noise. . . . . . . . . . . . . . 71
4.2.2 Loudness of Complex Noise . . . . . . . . . . . . . . . . . . 74
4.2.3 Loudness of Iterated Rippled Noise. . . . . . . . . . . . . . 79
vii
viii Contents
4.3 Pitch. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
4.3.1 Pitches of Complex Tones and “Complex Noise” . . . . 88
4.3.2 Pitch of “Complex Noise” . . . . . . . . . . . . . . . . . . . . 93
4.3.3 Frequency Limits of the ACF Model. . . . . . . . . . . . . 95
4.4 Timbre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.5 Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5 Spatial Primary Sensations of Noise. . . . . . . . . . . . . . . . . . . . . . . 105
5.1 Localization of Noise Source . . . . . . . . . . . . . . . . . . . . . . . . 105
5.2 Subjective Diffuseness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.3 Apparent Source Width (ASW) . . . . . . . . . . . . . . . . . . . . . . 112
5.3.1 ASW of the Band-Pass-Filtered Noise. . . . . . . . . . . . 112
5.3.2 ASW of “Complex Noise”. . . . . . . . . . . . . . . . . . . . 116
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
6 Noise Measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
6.1 Aircraft Noise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
6.2 Road Traffic Noise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
6.3 Flushing Toilet Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
6.4 Railway Noise in a Train Station . . . . . . . . . . . . . . . . . . . . . 137
6.5 Railway Noise in a Train Car. . . . . . . . . . . . . . . . . . . . . . . . 144
6.5.1 Effect of Train Type and Noise Caused
by Wheel–Rail Interaction . . . . . . . . . . . . . . . . . . . . 144
6.5.2 Effects of External Environments . . . . . . . . . . . . . . . 151
6.6 Floor Impact Sound . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
6.7 Heating, Ventilating, and Air Conditioning (HVAC) Noise . . . 162
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
7 Annoyance of Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
7.1 Annoyance of Noise with a Pure Tone Component. . . . . . . . . 167
7.2 Annoyance of Band-Pass-Filtered Noise. . . . . . . . . . . . . . . . . 173
7.3 Annoyance of Noise in Relation to the Spatial Factors . . . . . . 179
7.3.1 Effect of IACC Fluctuation . . . . . . . . . . . . . . . . . . . 179
7.3.2 Effect of τ Fluctuation. . . . . . . . . . . . . . . . . . . . 181
IACC
7.4 Annoyance of Road Traffic Noise. . . . . . . . . . . . . . . . . . . . . 185
7.5 Annoyance of Noise in a Train Station . . . . . . . . . . . . . . . . . 188
7.6 Annoyance of Noise in a Train Car. . . . . . . . . . . . . . . . . . . . 191
7.7 Annoyance of Floor Impact Sound . . . . . . . . . . . . . . . . . . . . 194
7.8 Annoyance of Heating, Ventilation,
and Air Conditioning (HVAC) Noise . . . . . . . . . . . . . . . . . . 196
7.9 A General Equation for Annoyance. . . . . . . . . . . . . . . . . . . . 198
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
Contents ix
8 Short-Term Effects of Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
8.1 Speech Disturbance by Different Directional Noise. . . . . . . . . 203
8.2 Sleep Disturbance by Upstairs Toilet Noise Changing
Spatial Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
8.3 Model of Duration Experience Due to Noise . . . . . . . . . . . . . 210
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
9 Long-Term Effects of Noise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
9.1 Human Placental Lactogen (HPL) in Maternal Plasma. . . . . . . 216
9.2 Birthweight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
9.3 Reactions in Sleeping Babies . . . . . . . . . . . . . . . . . . . . . . . . 220
9.3.1 Reaction of Babies on PLG and EEG . . . . . . . . . . . . 220
9.3.2 Remarks of ACF Factors of the Noise and Music. . . . 222
9.4 Development of Specialization of Cerebral Hemispheres . . . . . 224
9.5 Development of Height . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
10 Application to Sound Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
10.1 Subjective Diffuseness of Music Signals Convolved
with Binaural Impulse Responses . . . . . . . . . . . . . . . . . . . . . 233
10.1.1 Relationship Between IACC and IACC . . . . . . . . 235
IR SR
10.1.2 PsychoAcoustic Experiment. . . . . . . . . . . . . . . . . . . 239
10.2 Listening Level of Music Through Headphones
in Train Car Noise Environments . . . . . . . . . . . . . . . . . . . . . 243
10.2.1 Experimental Methods. . . . . . . . . . . . . . . . . . . . . . . 244
10.2.2 Effects of Noise Source. . . . . . . . . . . . . . . . . . . . . . 248
10.2.3 Effects of Music Source . . . . . . . . . . . . . . . . . . . . . 250
10.3 Subject Preference for Birdsongs . . . . . . . . . . . . . . . . . . . . . 253
10.4 Urban Soundscape Design . . . . . . . . . . . . . . . . . . . . . . . . . . 256
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261