assessmentofblasting-inducedgroundvibrationinanopen-pit … · 2019. 6. 18. · the frequency band...

Research ArticleAssessment of Blasting-InducedGroundVibration in anOpen-PitMine under Different Rock Properties

Zhi-qiang Yin 12 Zu-xiang Hu 1 Ze-di Wei1 Guang-ming Zhao1 Ma Hai-feng1

Zhuo Zhang1 and Rui-min Feng3

1School of Mining and Safety Anhui University of Science and Technology Huainan 232001 Anhui China2School of Civil and Mechanical Engineering Curtin University Perth 6102 Western Australia Australia3Department of Chemical and Petroleum Engineering University of Calgary Calgary Canada T2N 1N4

Correspondence should be addressed to Zu-xiang Hu zxhuausteducn

Received 19 April 2018 Accepted 29 August 2018 Published 25 October 2018

Academic Editor Xiang Fan

Copyright copy 2018 Zhi-qiang Yin et al+is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In an open-pit mine slope rock mass has multiple joint structures and blasting operations have an obvious influence on itsstability +erefore accurately predicting the blasting vibration is necessary to ensure slope stability In this study the blastingvibration signals monitored at a blasting site with different rock masses were used to investigate the attenuation characteristics ofblasting vibration through the peak particle velocity (PPV) frequency characteristics and energy distribution of the blastingvibration signals analyzed with the time-frequency processing method +e results demonstrated that the main vibration fre-quency of the blasting vibration of dolomite was wider than that of shale and these main vibration frequencies occurred at 25 kHzand 14 kHz for dolomite and shale respectively at a distance of 50m from the blast area to the vibration monitoring point Withan increase in the distance from 50m to 200m the main vibration frequencies decreased to less than 5Hz With increasing jointdegree the attenuation rate of the vibration velocity and energy attenuation of the blasting vibration increase indicating that thestructural parameters of the rock mass (such as the number of joints) have a significant impact on the attenuation law of blastingvibration Furthermore a modified equation that can be used for predicting PPV was developed by considering the effect of thenumber of joints in the rock mass on the blasting vibration For the same ground vibration readings the correlation factorincreased from 08 to 085 for the Nicholls-USBM equation and the modified equation respectively +e PPV of blasting underdifferent rock masses of the Baideng open-pit phosphorite mine was used to verify the modified equation +e results show thata modified equation can be used for predicting the PPV of blasting engineering in the Baideng phosphorite mine and that theprediction accuracy is acceptable

1 Introduction

+e primary operation in open-pit mines is rock blasting Inblasting only 20ndash30 of the energy produced by theexplosives is converted into mechanical energy to fragmentand displace the rock mass +e remainder of the explosiveenergy is wasted in the form of blast disturbances such asrock vibrations noise and fly rock among others Rockmasses are typically characterized by discontinuous andanisotropic inhomogeneous structures +ese discontinuousstructures such as faults joints fissures and fracturedzones are randomly distributed in the rock mass and have

important implications for blasting engineering In blastingoperations natural cracks in the rock mass structure arechanged by additional stresses induced by the blasting andthe shear strength of the structural surface is significantlyreduced thereby decreasing the stability of the rock [1 2]Studies on blast vibration harm control are conducted basedon analysis of blast vibrations Peak particle velocity (PPV) isan evaluation criterion for the blasting vibration which hasbeen used for many years it is predicted by the distance andthe charge weight scaling law [3 4] In recent years manyresearchers have conducted studies on the mechanicalproperties and strength of structural planes [5 6] and their

HindawiAdvances in Civil EngineeringVolume 2018 Article ID 4603687 10 pageshttpsdoiorg10115520184603687

influence on the slope stability of the surface structure ofrock masses [7ndash11] However only a few studies have beencarried out regarding the vibration wave propagationcharacteristics of structural planes Studies on the vibrationeffects of blasting have described the transmission and re-flection of the stress wave on the surface of the structureusing theoretical analysis and have focused primarily on theamplitude attenuation effect of structures on the stress wave[12ndash14]+erefore research on the effect of rock mass mediaon the attenuation of blasting vibration and accurate analysisof the influence of rock structures on the propagation ofvibration attenuation in blasting engineering is worth fur-ther investigation

Over the last several decades additional sophisticatedapproaches such as the finite element method and artificialneural networks have been used to predict blast vibration[15ndash17] Many researchers have successfully attempted toprocess and analyze unstable random blast vibration signalsusing signal time-frequency analysis [18ndash20] Studies havealso explored the influence of the distance from the blastingcenter on the frequency band energy distribution of blastvibration signals and signal time-frequency analysis hasbecome an effective method for investigating the energydistribution characteristics of a blast vibration signal underrock mass joints Based on the results for the time-frequencycharacteristics of blasting signals research on factorsinfluencing blasting vibration establishment of a regressionformula describing blasting vibration and analysis of signaltime-frequency are effective and important methods for thestudy of blasting vibration hazards

In this study ground vibration monitoring data wereobtained from the Baideng open-pit phosphorite mine inChina +e energy spectrum of the blast vibration signalobtained from the measurement data collected duringblasting was then analyzed using a time-frequency analysismethod +e influence of the rock mass structure on theattenuation of blast seismic waves was explored from theperspective of the blast vibration energy Finally these vi-bration monitoring data were used to develop a new re-lationship in which the influence of discontinuousstructures is included in the number of joints in rock masses+e PPV for different rock masses was used to verify thisrelationship

2 Materials and Methods

21 General Project Site Information +is study was con-ducted at the Baideng open-pit phosphorite mine which isa subsidiary of the Guangming Chemical Co Ltd+is mineis located in Anning Yunnan China +e Baideng open-pitphosphorite mine lies at a latitude of 24deg52primeN and a longi-tude of 102deg22primeE +e dip of the strata is gently inclined andvaries from 8deg to 20deg +e strata overlying the ore body aredolomite shale and quaternary eluvial alluvium Deep-holebench blasting at a height of 10m is used in this mine asillustrated in Figures 1 and 2 In the mining area blastingexcavation has been used in dolomite and shale and theserock strata have developed fault joints Mechanical pa-rameters of the intact rock masses such as the uniaxial

compressive strength and tensile strength were testedaccording to the methods recommended by the In-ternational Society of Rock Mechanics (ISRM) [21ndash24] +erock mass wave velocity and the number of joints were alsomeasured [25] +e mechanical properties of the intact rockmasses are summarized in Table 1

Ammonium nitrate-fuel oil (ANFO) and nonelectricdetonators were used for the blasting excavation +e typicaldepth and diameter of the blast holes were 11m and130mm respectively resulting in a blasting pattern witha burden of 4m and spacing of 5m In-hole delay detonatorsoperated at 400ms An initiation pattern was produced onthe surface using NONEL with a delay of 25ms An exampleof the initiation network and pattern of drilling holes isshown in Figure 3

22 PPV Monitoring and Prediction Methods +e vibrationmonitoring points and blasting area were located at the sameelevation +e distances between the monitoring points andblasting area were 50 100 150 and 200m as shown inFigure 4 A blasting vibration recorder (EXP 3850) anda sensor (CDJ-1) were used to monitor blasting vibrationsEach monitoring point was equipped with a vibrationsensor +e sensor must be bonded to the surface of theintact rock with plaster and the location of the monitoringpoints must be adjusted appropriately to ensure the accuracyof the measurements +us the distance and azimuth weredetermined using GPS as shown in Figure 5

Over the last half century researchers have proposedseveral empirical equations to describe the attenuationcharacteristics of blast vibrations and predict the attenuationof the PPV [26ndash28] +e PPV equations that have beenproposed by different researchers are summarized in Table 2In most of these equations the distance from the free faceand the maximum charge weight per delay are consideredthe main parameters influencing PPV prediction Howeveris well known that PPV is influenced by other factors such asthe rock strength rock mass discontinuity conditions andblast geometry which have not been explicitly incorporatedin these empirical equations In this study the Nicholls-United States Bureau of Mines (USBM) empirical equationis used as the prediction equation

23 Wavelet Packet Analysis Method Wavelet packet anal-ysis is a time-frequency processing method for a non-stationary random signal +is signal is decomposed intotwo parts ie the low and high frequencies using low- andhigh-pass filters respectively +e two decomposed signalsare then further divided into two parts corresponding to thelow and high frequencies +us the signal is continuouslydecomposed thereby exhibiting a high-frequency resolution[29] Analysis of the signal continued to the eighth de-composition level +e signal decomposition process is il-lustrated in Figure 6 +e number of frequency bands in theblasting vibration signals at approximately 2n can be ob-tained such that n is the decomposition level of the waveletpacket analysis If the lowest frequency of the blast vibrationsignal s(t) is 0 and the highest frequency isW the width of

2 Advances in Civil Engineering

the frequency band at the nth decomposition level will beW2n

Based on the decomposition and reconstruction of thewavelet packet analysis method the blast vibration signals(t) can be expressed as follows

Shale

Dolomite

Quaternary eluvial

alluvium

Figure 2 Bench of Baideng phosphorite

Table 1 Mechanical parameters of rock masses

Rock type UCS (MPa) TS (MPa) ρ (gcm3) E (GPa) JF Vr (ms) Vrm (ms)Dolomite 9573 1648 353 8762 21 5247 2471Shale 5821 584 269 5585 09 3813 2895NoteUCS uniaxial compression strength TS tensile strength ρ dry density E Youngrsquos modulusVr wave velocity of rockVrm wave velocity of rock massJF number of joints per 10m

Quaternary eluvialalluvium

Shale

Dolomite

Ore body

Final slope

Figure 1 Geological prole of Baideng phosphorite

200 225 375350 475 500

450400325

25 0 125 275150 300 425

250175100

75

50

Figure 3 Initiation network and drilling holes pattern

1 (50m)

2 (100m)

3 (150m)

4 (200m)

Blasting area Monitoring point

Bench face

Figure 4 Diagram for location of blasting vibration monitoring

Vibrationsensor

GPS

Figure 5 Vibration sensor and GPS

Advances in Civil Engineering 3

s(t) 11139442iminus1

j

sij (1)

where sij is the reconstructed signal after wavelet packetdecomposition i is the decomposition level and j is theorder number of the frequency bands after decompositionj 0 1 2 3 2i minus 1

+e energy of each reconstructed signal Eij afterwavelet packet decomposition is defined as

Eij 1113946 sij(t)11138681113868111386811138681113868

111386811138681113868111386811138682dt 1113944

m

k1xjk

11138681113868111386811138681113868

111386811138681113868111386811138682 (2)

where xij is the amplitude of the discrete points of thereconstructed signal m is the number of discrete samplingpoints and k is the number of discrete pointsk 1 2 3 m

+e total energy of the analyzed signal E0 is expressed asfollows

E0 11139442iminus1

j0Eij (3)

+e ratio of the energy in each frequency band to thetotal energy can be derived as follows

Pj Eij

E0times 100 (4)

3 Results and Discussion

Approximately 24 events from 6 blasts were recorded at theBaideng phosphorite open-pit mine as summarized inTable 3 +e blasting areas were grouped into two locations

the dolomite bench and the shale bench Figure 7 shows thevelocity histories of the blasting vibration monitoring

31 Attenuation Law for the PPV of Blasting Vibration+e relationship between PPV and scaled distance revealedby the blasting vibration test data is shown in Figure 8 +ePPV of the dolomite and shale decreases steadily with in-creasing scaled distance +e PPV is larger in the dolomitethan in the shale for a constant scaled distance Lu et al [30]reported that the total energy of a blast-induced seismicactivity is directly proportional to the square of the PPVduring the same blasting +erefore more explosive energywas converted to rock mass vibration in the dolomite benchthan that in the shale bench +e field data were analyzed byregression using the least squares fitting method +e at-tenuation equations for dolomite (PPVd) and shale (PPVs)are presented as follows

PPVd 3852Q

radic

R1113888 1113889

257

PPVs 1367Q

radic

R1113888 1113889

194

(5)

+ese relationships indicate that the PPV decays pro-portionally to 1R257 for the dolomite and 1R194 for theshale with increasing distance for a constant explosivecharge weight +e relationships also indicate that PPVdecreases more rapidly in dolomite than shale

32 Attenuation Law of Energy for Blasting Vibration+e sampling rate of the monitoring equipment during theblasting vibration monitoring is 0ndash4 kHz Following the

DA2AA2

AAA3 DAA3

A1

S

DDA3ADA3 DAD3ADD3

D1

ADD3 DDD3

DD2AD2

Figure 6 Diagram for signal decomposition process A stands for low frequency D stands for high frequency and the numbers 1 2 and 3stands for decomposition levels

Table 2 Empirical PPV predictor presented by different researches

Name EquationNicholls-USBM PPV k[Q12R]n

General Prediction by Davies PPV kRminusnQa

Langefors and Kihlstrom PPV k[Q12R13]n

Bureau of Indian Standard PPV k[QR23]n

AmbressysndashHendron PPV k[Q13R]n

GhoshndashDaemen predictor PPV k[RQ12]minusneminusαR

Note R distance from the blast area to the vibration monitoring point Q maximum charge weight per delay k n a α site constants


Nyquist sampling theory the highest frequency of the signalsbeing analyzed is 2 kHz +e Daubechies wavelet seriesexhibits smoothness compact support and symmetrycompared to a conventional wavelet +is wavelet series hasbeen widely used in the analysis of blasting vibration signalsIn this study the blasting vibration signal was decomposedinto nine layers using wavelet packet analysis and 29

frequency bands were generated in which each frequencyband is 200029 390625Hz

+e blast vibration signals underwent decompositionand reconstruction using db5ndashdb10 in the wavelet packetaccording to Equations (2) and (4) respectively +e errorsin the reconstructed signals are listed in Table 4 +e sta-tistics in Table 4 indicate that the db8 wavelet packet has the

ndash70

0

70

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash15

0

15

(D) 202m

(C) 151m

ndash4

0

4

ndash1

0

1

t (s)

(B) 97m

(A) 46m

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

t (s)

t (s)

t (s)

(a)

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash25

0

25

(H) 201m

(G) 152m

(F) 97m

(E) 55m

ndash10

0

10

ndash5

0

5

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3ndash3

0

3

t (s)

t (s)

t (s)

t (s)

(b)

Figure 7 +e velocity histories of blasting vibration monitoring (a) D1 (b) S3

Table 3 Summary of the blasting-induced vibration data at Baideng phosphorite

NoDolomite

NoShale

JF Q (kg) R (m) PPV (mms) JF Q (kg) R (m) PPV (mms)

D1 24 100

46 69799

S1 08 75

57 3946197 14713 112 15026151 3771 168 7815202 0963 215 2231

D2 27 96

55 65726

S2 12 87

73 27564105 6285 133 13566147 2168 185 6258198 0884 223 1083

D3 18 98

48 45739

S3 10 80

55 23216111 12218 97 9843172 5375 152 4761237 1832 201 2926


smallest reconstruction error thus db8 is used to analyze thetime-frequency energy of the signal in Figure 6 e energydistribution of the wavelet packet frequency band for theblasting vibration signals was obtained for the dolomite andshale e results are listed in Table 5

e results presented in Table 5 indicate that the energyof the blast vibration signal is widely distributed in thefrequency band however most of the energy is concentratedat 0ndash5078125Hz e energy ratios for the eight signals at0ndash5078125Hz that comprise the total energy are 935379724 99867 9991 9788 9894 9852 and9988 In Figure 9 the time-frequency spectrum distri-bution is considered in the range of 0ndash50Hz to compare theincentuence of rock properties and propagation distance on thedistribution of blasting vibration energy e main vibrationfrequencies of the blasting vibration in dolomite and shale ata distance of 50m from the blast area are 25 and 14Hzrespectively e main vibration frequency decreasesgradually with increasing distance from the blast area to thevibration monitoring point e main vibration frequenciesof dolomite and shale are less than 5Hz at a distance fromthe blast area of 200m

e upper limit of the natural vibration frequency ofa ground building is 10Hz e energy of the blasting vi-bration waves is in the range of 0ndash20Hz and has an obviousepoundect on buildings erefore the blasting vibration wave inthis study is divided into primary (0ndash20Hz) and secondary(20ndash50Hz) incentuence frequency bands and the energy at-tenuation law for the dipounderent frequency bands is analyzede energy of each frequency band is subject to a normalizedanalysis e energy attenuation laws for the blasting vi-bration in dipounderent rock masses and frequency bands areshown in Figure 10 In Figure 10 at distances of 50ndash200mfrom the blast area to the vibration monitoring point theattenuation rate for the dolomite and shale blasting is lowerin the primary incentuence frequency band than in the sec-ondary incentuence frequency bande attenuation is lower in

the shale blasting than in the dolomite blasting for the samefrequency band Figures 9 and 10 show that in the near-blasting eld (less than 50m) the blasting vibration velocityand vibration energy of dolomite are higher than that ofshale and more vibration energy is distributed in the higherfrequency range In the far-blasting eld (more than 50m)the decay rate of the vibration velocity and energy attenu-ation of the blasting vibration of dolomite is higher than thatof shale e rock mechanics parameters in Table 1 indicatethat the uniaxial compression strength tensile strength andelastic modulus of dolomite are higher than that of shale butthe dolomite also had more developed joints than the shaleese results demonstrate that in the near-blasting eld thevibration attenuation of blasting is mainly apoundected by themechanical properties of the rock with increasing rockstrength and elastic modulus the blasting vibration velocityand vibration energy also increased which is consistent withthe testing results reported by Xu et al [31] However in thefar-blasting eld the vibration attenuation of blasting ismainly apoundected by the structural characteristics of the rockmass with increasing number of joints in the rock mass theattenuation rate of the vibration velocity and energy at-tenuation of blasting vibration increased erefore undergeological conditions leading to joint development thefunction of the joint should be considered in blasting vi-bration predictions

33 Development of a New Relationship For simplicity thedistance from the blast area to the vibration monitoringpoint (R) and then to the square root of the maximumexplosive charge per delay (Q) is called the scaled distance(SD) and their relationship can be expressed as follows

SD RQminus12 (6)

e PPV prediction with the Nicholls-USBM equation iswritten as follows

PPV k(SD)minusn kQ

radic

R( )

n

(7)

where k is the attenuation constant and n is the attenuationindex

e results shown in Figure 10 indicate that the atten-uation law of the blasting vibration was apoundected by thenumber of joints in the rock mass e incentuence of rockmass joints on the attenuation law of the blasting vibrationshould be considered comprehensively to predict the exactPPV of blasting and thus the attenuation equation needs tobe modied According to the studies conducted bySimangunsong and Wahyudi [32] the incentuence of thenumber of coal seams should be considered in the predictionof blasting vibration e proposed modied equation forPPV and SD can be expressed as follows

Table 4 Reconstruction errors of wavelet packet analysis

dbN db5 db6 db7 db8 db9 db10Error value (10minus10) 9896 7708 4141 2537 1481 1529

100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)

Figure 8 Scaled distance versus PPV of dipounderent positions atBaideng phosphorite


Table 5 +e wavelet packet frequency band energy distribution for blasting vibration signals

Frequency band (Hz)D1 S3

46 (m) 97 (m) 151 (m) 202 (m) 55 (m) 97 (m) 152 (m) 201 (m)0sim390625 282Eminus 02 242Eminus 04 335Eminus 03 809Eminus 03 237E+ 00 428E+ 00 684E+ 00 401E+ 01390625sim78125 307Eminus 02 203Eminus 02 152Eminus 02 387Eminus 03 739E+ 00 140E+ 01 305E+ 01 976E+ 0078125sim1171875 549Eminus 01 438Eminus 02 287Eminus 03 238Eminus 03 162E+ 01 311E+ 01 172E+ 01 129E+ 011171875sim15625 495Eminus 01 396Eminus 02 855Eminus 03 175Eminus 03 457E+ 01 251E+ 01 178E+ 01 335E+ 0115625sim1953125 543Eminus 01 283Eminus 03 562Eminus 05 660Eminus 06 181E+ 00 206E+ 00 140E+ 00 108Eminus 011953125sim234375 184Eminus 01 683Eminus 03 106Eminus 04 167Eminus 05 305E+ 00 290E+ 00 321E+ 00 902Eminus 02234375sim2734375 162E+ 00 994Eminus 03 261Eminus 03 283Eminus 04 168E+ 01 155E+ 01 132E+ 01 201E+ 002734375sim3125 372Eminus 01 932Eminus 03 576Eminus 04 140Eminus 04 337E+ 00 299E+ 00 784E+ 00 127E+ 003125sim3515625 201Eminus 02 751Eminus 05 151Eminus 06 180Eminus 08 121Eminus 02 140Eminus 02 785Eminus 04 870Eminus 033515625sim390625 128Eminus 02 138Eminus 04 243Eminus 06 644Eminus 08 299Eminus 02 105Eminus 02 257Eminus 03 113Eminus 02390625sim4296875 150Eminus 02 132Eminus 03 752Eminus 06 391Eminus 07 161Eminus 01 184Eminus 02 310Eminus 02 879Eminus 024296875sim46875 158Eminus 02 264Eminus 04 395Eminus 06 270Eminus 07 280Eminus 02 202Eminus 02 173Eminus 02 113Eminus 0246875sim5078125 317Eminus 01 109Eminus 03 187Eminus 05 213Eminus 06 940Eminus 01 883Eminus 01 479Eminus 01 245Eminus 025078125sim1015625 212Eminus 01 370Eminus 03 383Eminus 05 106Eminus 05 186Eminus 02 144Eminus 03 298Eminus 04 297Eminus 061015625sim203125 574Eminus 02 148Eminus 04 267Eminus 06 164Eminus 07 179Eminus 03 670Eminus 05 479Eminus 06 177Eminus 06203125sim30078125 387Eminus 03 982Eminus 07 822Eminus 07 679Eminus 08 190Eminus 04 750Eminus 06 689Eminus 07 177Eminus 0730078125sim500 103Eminus 02 678Eminus 07 165Eminus 06 193Eminus 07 914Eminus 06 671Eminus 07 306Eminus 08 187Eminus 07500sim1000 386Eminus 03 474Eminus 06 307Eminus 06 162Eminus 06 967Eminus 08 161Eminus 07 108Eminus 09 122Eminus 071000sim2000 242Eminus 03 353Eminus 07 321Eminus 07 159Eminus 06 418Eminus 09 160Eminus 07 430Eminus 10 113Eminus 07

0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)

Figure 9 Time-frequency energy spectrum distributions for blast vibration signals (a) D1 (b) S3


PPV k SDJF( )minusn k [1 + log(1 + JF times R)]

RQ

radic minusn

(8)

If JR is 0 then the new SDJF will become the original SD(Equation (6)) in which no incentuence of the joint plane isconsidered in the prediction of PPV

A total of 24 ground vibration readings at the Baidengopen-pit phosphorite mine are listed in Table 2 and wereused to examine the relationship between PPV SD andSDJF e results are plotted in Figure 11 e modiedequation PPVJF exhibits a better correlation factor (R2) thanthe original Nicholls-USBM relationship PPV the correla-tion factors are 085 and 080 respectively e newlymodied equation which considers the epoundect of jointsdemonstrates superior accuracy and applicability for pre-dicting blasting vibration at the Baideng open-pit phos-phorite mine

In an open-pit mineeld dipounderent rock properties areobserved between the blasting area and the monitoringpoint thereby corresponding to dipounderent joint degrees asshown in Figure 12 JF in the dipounderent rock masses areexpressed by JF1 JF2 JFi and the distances are expressedby R1R2 Ri respectively erefore Equation (8) can beexpressed as follows

PPV k 1 + log 1 +sum JFi middot Ri( )[ ]RQ

radic minusn

(9)

A total of 15 vibration readings were obtained from theBaideng open-pit phosphorite mine in which the blastingareas and monitoring points are located in the dipounderent rockmasses ie shale and dolomite as summarized in Table 6

e modied equation and Nicholls-USBM empiricalequation were then used to predict the PPV of the remainingreadings e results are shown in Figure 13 in which the

monitored PPV is compared with the predicted results InFigure 13 the PPV predicted by the modied equation isvisually a better t for the monitoring data than that predictedby the Nicholls-USBM equation In particular the predictionresults are greater than the monitored data for predictingstrong vibrations which will benet the analysis of slopestability during blasting e results demonstrate that themodied equation can be used for predicting the PPV ofblasting engineering in the Baideng open-pit phosphoritemine and that the accuracy of the predictions is acceptable

4 Conclusions

In this study blasting vibration signals were monitored fordolomite and shale blasting areas in the Baideng open-pitphosphorite mine Moreover the epoundect of attenuation lawson the blasting vibration signals in rock masses havingdipounderent properties was analyzed using the wavelet packettime-frequency analysis method Based on the results thefollowing conclusions can be made

(1) e blasting vibration attenuation coecopycient exhibitsa clear relationship with the rockmasse attenuationlaw coecopycient k and n for the blasting vibration waveswere (3852 257) and (1367 194) at the dolomite andshale blasting areas in the Baideng open-pit minerespectively e attenuation rates of the PPV andenergy are higher in the dolomite than in the shale

(2) e blasting vibration signal spectra based on thewavelet packet time-frequency analysis are mainlycomposed of low frequencies whereas the spectra ofthe blasting vibration signals are mainly composed oflow frequencies with the main vibration frequencyin the range of 0ndash50Hz e main vibration fre-quency decreases with increasing distance to themonitoring points

(3) e degree of development that the rock mass jointshave undergone incentuences the attenuation rate of thePPV and the PPV attenuation rate is high when thenumber of joints in the rock mass is high A new

1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085

PPV = 2046 SDndash2202

R2 = 08

SD (mkg05) SDJF (mkg05)

ndash1943

Figure 11 Relationships between PPV and SD and SDJF

50 100 150

00

02

04

06

08

10

200Epicentral distance (m)

Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz

Figure 10 e energy attenuation law of dipounderent frequencybands


relationship was developed to improve the pre-diction of PPV in the dipounderent rock masses of theopen-pit mine by accounting for the degree of de-velopment and number of joints in the rock mass

Data Availability

e data used to support the ndings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no concenticts of interestregarding the publication of this paper

Acknowledgments

is work was supported by the Anhui Provincial NaturalScience Foundation (1808085ME159 and 1808085QE149)National Natural Science Foundation of China (51774014)Science and Technology Planning Project of Anhui Province(1604a0802107) Program for Innovative Research Team inthe University of Anhui Province (Prevention and Controlof Coal Rock Dynamic Disasters in Deep Coal Mine) andNatural Science Foundation of the Anhui Higher EducationInstitutions (KJ2017A093)

References

[1] D J Armaghani M Hajihassani E T Mohamad A Martoand S A Noorani ldquoBlasting-induced centyrock and groundvibration prediction through an expert articial neural net-work based on particle swarm optimizationrdquo Arabian Journalof Geosciences vol 7 no 12 pp 5383ndash5396 2014

[2] P K Singh M P Roy R K Paswan R K Dubey andC Drebenstedt ldquoBlast vibration epoundects in an undergroundmine caused by open-pit miningrdquo International Journal ofRock Mechanics and Mining Sciences vol 80 pp 79ndash88 2015

[3] G R Tripathy and I D Gupta ldquoPrediction of ground vi-brations due to construction blasts in dipounderent types of rockrdquoRock Mechanics and Rock Engineering vol 35 no 3pp 195ndash204 2002

Table 6 e blasting vibration data at bench of dipounderent rock properties

No Q (kg) Rlowasts (m) RD (m) JFS JFD PPV (mms) PPV1 (mms) PPVJF (mms)Dipounderence ()PPV1 PPVJF

1 1900 57 144 05 20 8579 8551 6765 0 212 660 76 177 13 27 0346 1676 1231 385 2563 660 76 122 13 27 1554 2837 2203 83 424 660 76 71 13 27 8087 5379 4530 33 445 500 49 147 12 23 0757 2152 1747 184 1316 500 49 203 12 23 0467 1254 0969 169 1087 95 5 98 09 12 5748 1440 1819 75 688 3515 102 15 05 15 61029 52937 62651 13 39 3515 136 39 05 15 18631 22293 22777 20 2210 1770 150 713 10 26 0158 0346 0201 120 2711 830 87 3 03 24 33838 19737 34558 42 212 126 216 114 08 14 0149 0160 0166 7 1213 81 134 206 05 13 0105 0093 0101 11 414 81 134 66 05 13 1538 0292 0381 81 7515 81 60 10 05 13 7521 2782 5061 63 33RSD distances of shale or dolomite JFSD number of joints in shale or dolomite per 10m PPV1 predicted PPV by Nicholls-USBM PPVJF predicted PPV bymodied relationship

0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10

Nicholls-USBMModified relationship

Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit

Figure 13 Comparison between predicted and monitored PPV

JF1 JF2 JFi

R1 R2 RiBlasting areaMonitoring point

Ground

Figure 12 Schematic diagram of lithology changes between blasting area and monitoring point


[4] W M Yan L G +am and K V Yuen ldquoReliability ofempirical relation on the attenuation of blast-induced vi-brationsrdquo International Journal of Rock Mechanics andMining Sciences vol 59 pp 160ndash165 2013

[5] X Fan K Li H Lai Y Xie R Cao and J Zheng ldquoInternalstress distribution and cracking around flaws and openings ofrock block under uniaxial compression a particle mechanicsapproachrdquo Computers and Geotechnics vol 102 pp 28ndash382018

[6] X Fan R Chen H Lin H Lai C Zhang and Q ZhaoldquoCracking and failure in rock specimen containing combinedflaw and hole under uniaxial compressionrdquo Advances in CivilEngineering vol 2018 Article ID 9818250 15 pages 2018

[7] X Li J Zhou S Wang and B Liu ldquoReview and practice ofdeep mining for solid mineral resourcesrdquo China JournalNonferrous Metals vol 27 no 6 pp 1236ndash1262 2017 inChinese

[8] M Tao H Zhao X Li J Ma K Du and X Xie ldquoDe-termination of spalling strength of rock by incident waveformrdquoGeomechanics and Engineering vol 12 no 1 pp 1ndash8 2017

[9] Y X Wang P P Guo W X Ren et al ldquoLaboratory in-vestigation on strength characteristics of expansive soiltreated with jute fiber reinforcementrdquo International Journal ofGeomechanics vol 17 no 11 article 04017101 2017

[10] Y Zhao Y WangWWangWWan and J Tang ldquoModelingof non-linear rheological behavior of hard rock using triaxialrheological experimentrdquo International Journal of Rock Me-chanics and Mining Sciences vol 93 pp 66ndash75 2017

[11] Y Zhao S Luo Y Wang W Wang L Zhang andW WanldquoNumerical analysis of karst water inrush and a criterion forestablishing the width of water-resistant rock pillarsrdquo MineWater and the Environment vol 36 no 4 pp 508ndash5192017

[12] D Blair and A Minchinton ldquoOn the damage zone sur-rounding a single blastholerdquo Fragblast vol 1 no 1 pp 59ndash721997

[13] X L Li D Y Li T Hu T F Gao and S T Zhang ldquoTestingmethod for the weak and broken rock mass blasting vibrationin theory and applicationrdquo Journal of Safety and Environmentvol 16 no 2 pp 148ndash153 2016 in Chinese

[14] H Lin P Cao and Y Wang ldquoNumerical simulation ofa layered rock under triaxial compressionrdquo InternationalJournal of Rock Mechanics and Mining Sciences vol 60pp 12ndash18 2013

[15] M Khandelwal and T N Singh ldquoPrediction of blast-inducedground vibration using artificial neural networkrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 46 no 7 pp 1214ndash1222 2009

[16] K W Liu H Hao and X B Li ldquoNumerical analysis of thestability of abandoned cavities in bench blastingrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 92 pp 30ndash39 2017

[17] M Hajihassani D J Armaghani A Marto andE T Mohamad ldquoGround vibration prediction in quarryblasting through an artificial neural network optimized byimperialist competitive algorithmrdquo Bulletin of EngineeringGeology and the Environment vol 74 no 3 pp 873ndash8862015

[18] W Sweldens ldquo+e lifting scheme a construction of secondgeneration waveletsrdquo SIAM Journal on Mathematical Anal-ysis vol 29 no 2 pp 511ndash546 1998

[19] G S Zhong L P Ao and K Zhao ldquoInfluence of explosionparameters on wavelet packet frequency band energy

distribution of blast vibrationrdquo Journal of Central SouthUniversity vol 19 no 9 pp 2674ndash2680 2012

[20] X L Li Z H Li and E Y Wang ldquoAnalysis of natural mineralearthquake and blast based on Hilbert-Huang transform(HHT)rdquo Journal of Applied Geophysics vol 128 pp 79ndash86 2016

[21] YWang P Guo F Dai X Li Y Zhao and Y Liu ldquoBehaviourand modelling of fiber reinforced clay under triaxial com-pression by using the combining superposition method withthe energy based homogenization techniquerdquo InternationalJournal of Geomechanics vol 18 no 12 article 040181722018

[22] Y Wang P Guo S Shan H Yuan and B Yuan ldquoStudy onstrength influence mechanism of fiber-reinforced expansivesoil using juterdquo Geotechnical and Geological Engineeringvol 34 no 4 pp 1079ndash1088 2016

[23] H Lin W Xiong and Q Yan ldquoModified formula for thetensile strength as obtained by the flattened brazilian disktestrdquo Rock Mechanics and Rock Engineering vol 49 no 4pp 1579ndash1586 2016

[24] H Lin W Xiong and Q Yan ldquo+ree-dimensional effect oftensile strength in the standard brazilian test consideringcontact lengthrdquo Geotechnical Testing Journal vol 39 no 1article 20140268 2015

[25] H Wang H Lin and P Cao ldquoCorrelation of UCS rating withschmidt hammer surface hardness for rock mass classifica-tionrdquo Rock Mechanics and Rock Engineering vol 50 no 1pp 195ndash203 2017

[26] R Kumar D Choudhury and K Bhargava ldquoDeterminationof blast-induced ground vibration equations for rocks usingmechanical and geological propertiesrdquo Journal of Rock Me-chanics and Geotechnical Engineering vol 8 no 3 pp 341ndash349 2016

[27] M Hajihassani D J Armaghani M MonjeziE T Mohamad and A Marto ldquoBlast-induced air and groundvibration prediction a particle swarm optimization-basedartificial neural network approachrdquo Environmental EarthSciences vol 74 no 4 pp 2799ndash2817 2015

[28] D J Armaghani M Hajihassani M MonjeziE T Mohamad A Marto and M R Moghaddam ldquoAppli-cation of two intelligent systems in predicting environmentalimpacts of quarry blastingrdquo Arabian Journal of Geosciencesvol 8 no 11 pp 9647ndash9665 2015

[29] X Z Shi X Y Qiu J Zhou X Chen Y-Q Fan and E-W LuldquoApplication of Hilbert-Huang transform based delay timeidentification in optimization of short millisecond blastingrdquoTransactions of Nonferrous Metals Society of China vol 26no 7 pp 1965ndash1974 2016

[30] W B Lu P Li M Chen C B Zhou and D Q ShuldquoComparison of vibrations induced by excavation of deep-buried cavern and open pit with method of bench blastingrdquoJournal of Central South University of Technology vol 18no 5 pp 1709ndash1718 2011

[31] Z Xu H Guo L Guo and X Liu ldquoEffects of rock propertieson the propagation of blasting vibrationrdquo Journal of NorthChina Institute of Science and Technology vol 12 no 4pp 25ndash30 2015

[32] G M Simangunsong and S Wahyudi ldquoEffect of beddingplane on prediction blast-induced ground vibration in openpit coal minesrdquo International Journal of Rock Mechanics andMining Sciences vol 79 pp 1ndash8 2015


International Journal of

AerospaceEngineeringHindawiwwwhindawicom Volume 2018

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Shock and Vibration


Civil EngineeringAdvances in

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Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

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Submit your manuscripts atwwwhindawicom

influence on the slope stability of the surface structure ofrock masses [7ndash11] However only a few studies have beencarried out regarding the vibration wave propagationcharacteristics of structural planes Studies on the vibrationeffects of blasting have described the transmission and re-flection of the stress wave on the surface of the structureusing theoretical analysis and have focused primarily on theamplitude attenuation effect of structures on the stress wave[12ndash14]+erefore research on the effect of rock mass mediaon the attenuation of blasting vibration and accurate analysisof the influence of rock structures on the propagation ofvibration attenuation in blasting engineering is worth fur-ther investigation

Over the last several decades additional sophisticatedapproaches such as the finite element method and artificialneural networks have been used to predict blast vibration[15ndash17] Many researchers have successfully attempted toprocess and analyze unstable random blast vibration signalsusing signal time-frequency analysis [18ndash20] Studies havealso explored the influence of the distance from the blastingcenter on the frequency band energy distribution of blastvibration signals and signal time-frequency analysis hasbecome an effective method for investigating the energydistribution characteristics of a blast vibration signal underrock mass joints Based on the results for the time-frequencycharacteristics of blasting signals research on factorsinfluencing blasting vibration establishment of a regressionformula describing blasting vibration and analysis of signaltime-frequency are effective and important methods for thestudy of blasting vibration hazards

In this study ground vibration monitoring data wereobtained from the Baideng open-pit phosphorite mine inChina +e energy spectrum of the blast vibration signalobtained from the measurement data collected duringblasting was then analyzed using a time-frequency analysismethod +e influence of the rock mass structure on theattenuation of blast seismic waves was explored from theperspective of the blast vibration energy Finally these vi-bration monitoring data were used to develop a new re-lationship in which the influence of discontinuousstructures is included in the number of joints in rock masses+e PPV for different rock masses was used to verify thisrelationship

2 Materials and Methods

21 General Project Site Information +is study was con-ducted at the Baideng open-pit phosphorite mine which isa subsidiary of the Guangming Chemical Co Ltd+is mineis located in Anning Yunnan China +e Baideng open-pitphosphorite mine lies at a latitude of 24deg52primeN and a longi-tude of 102deg22primeE +e dip of the strata is gently inclined andvaries from 8deg to 20deg +e strata overlying the ore body aredolomite shale and quaternary eluvial alluvium Deep-holebench blasting at a height of 10m is used in this mine asillustrated in Figures 1 and 2 In the mining area blastingexcavation has been used in dolomite and shale and theserock strata have developed fault joints Mechanical pa-rameters of the intact rock masses such as the uniaxial

compressive strength and tensile strength were testedaccording to the methods recommended by the In-ternational Society of Rock Mechanics (ISRM) [21ndash24] +erock mass wave velocity and the number of joints were alsomeasured [25] +e mechanical properties of the intact rockmasses are summarized in Table 1

Ammonium nitrate-fuel oil (ANFO) and nonelectricdetonators were used for the blasting excavation +e typicaldepth and diameter of the blast holes were 11m and130mm respectively resulting in a blasting pattern witha burden of 4m and spacing of 5m In-hole delay detonatorsoperated at 400ms An initiation pattern was produced onthe surface using NONEL with a delay of 25ms An exampleof the initiation network and pattern of drilling holes isshown in Figure 3

22 PPV Monitoring and Prediction Methods +e vibrationmonitoring points and blasting area were located at the sameelevation +e distances between the monitoring points andblasting area were 50 100 150 and 200m as shown inFigure 4 A blasting vibration recorder (EXP 3850) anda sensor (CDJ-1) were used to monitor blasting vibrationsEach monitoring point was equipped with a vibrationsensor +e sensor must be bonded to the surface of theintact rock with plaster and the location of the monitoringpoints must be adjusted appropriately to ensure the accuracyof the measurements +us the distance and azimuth weredetermined using GPS as shown in Figure 5

Over the last half century researchers have proposedseveral empirical equations to describe the attenuationcharacteristics of blast vibrations and predict the attenuationof the PPV [26ndash28] +e PPV equations that have beenproposed by different researchers are summarized in Table 2In most of these equations the distance from the free faceand the maximum charge weight per delay are consideredthe main parameters influencing PPV prediction Howeveris well known that PPV is influenced by other factors such asthe rock strength rock mass discontinuity conditions andblast geometry which have not been explicitly incorporatedin these empirical equations In this study the Nicholls-United States Bureau of Mines (USBM) empirical equationis used as the prediction equation

23 Wavelet Packet Analysis Method Wavelet packet anal-ysis is a time-frequency processing method for a non-stationary random signal +is signal is decomposed intotwo parts ie the low and high frequencies using low- andhigh-pass filters respectively +e two decomposed signalsare then further divided into two parts corresponding to thelow and high frequencies +us the signal is continuouslydecomposed thereby exhibiting a high-frequency resolution[29] Analysis of the signal continued to the eighth de-composition level +e signal decomposition process is il-lustrated in Figure 6 +e number of frequency bands in theblasting vibration signals at approximately 2n can be ob-tained such that n is the decomposition level of the waveletpacket analysis If the lowest frequency of the blast vibrationsignal s(t) is 0 and the highest frequency isW the width of




Shale

Dolomite

Quaternary eluvial

alluvium





Shale

Dolomite

Ore body

Final slope


200 225 375350 475 500

450400325

25 0 125 275150 300 425

250175100

75

50


1 (50m)

2 (100m)

3 (150m)

4 (200m)


Bench face


Vibrationsensor

GPS




j

sij (1)



Eij 1113946 sij(t)11138681113868111386811138681113868

111386811138681113868111386811138682dt 1113944

m

k1xjk

11138681113868111386811138681113868

111386811138681113868111386811138682 (2)



E0 11139442iminus1

j0Eij (3)


Pj Eij

E0times 100 (4)





PPVd 3852Q

radic

R1113888 1113889

257

PPVs 1367Q

radic

R1113888 1113889

194

(5)



DA2AA2

AAA3 DAA3

A1

S

DDA3ADA3 DAD3ADD3

D1

ADD3 DDD3

DD2AD2














ndash70

0

70

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash15

0

15

(D) 202m

(C) 151m

ndash4

0

4

ndash1

0

1

t (s)

(B) 97m

(A) 46m

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

t (s)

t (s)

t (s)

(a)

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash25

0

25

(H) 201m

(G) 152m

(F) 97m

(E) 55m

ndash10

0

10

ndash5

0

5

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3


0

3

t (s)

t (s)

t (s)

t (s)

(b)



NoDolomite

NoShale


D1 24 100

46 69799

S1 08 75

57 3946197 14713 112 15026151 3771 168 7815202 0963 215 2231

D2 27 96

55 65726

S2 12 87

73 27564105 6285 133 13566147 2168 185 6258198 0884 223 1083

D3 18 98

48 45739

S3 10 80

55 23216111 12218 97 9843172 5375 152 4761237 1832 201 2926







SD RQminus12 (6)


PPV k(SD)minusn kQ

radic

R( )

n

(7)





100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)






0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




Shale

Dolomite

Quaternary eluvial

alluvium





Shale

Dolomite

Ore body

Final slope


200 225 375350 475 500

450400325

25 0 125 275150 300 425

250175100

75

50


1 (50m)

2 (100m)

3 (150m)

4 (200m)


Bench face


Vibrationsensor

GPS




j

sij (1)



Eij 1113946 sij(t)11138681113868111386811138681113868

111386811138681113868111386811138682dt 1113944

m

k1xjk

11138681113868111386811138681113868

111386811138681113868111386811138682 (2)



E0 11139442iminus1

j0Eij (3)


Pj Eij

E0times 100 (4)





PPVd 3852Q

radic

R1113888 1113889

257

PPVs 1367Q

radic

R1113888 1113889

194

(5)



DA2AA2

AAA3 DAA3

A1

S

DDA3ADA3 DAD3ADD3

D1

ADD3 DDD3

DD2AD2














ndash70

0

70

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash15

0

15

(D) 202m

(C) 151m

ndash4

0

4

ndash1

0

1

t (s)

(B) 97m

(A) 46m

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

t (s)

t (s)

t (s)

(a)

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash25

0

25

(H) 201m

(G) 152m

(F) 97m

(E) 55m

ndash10

0

10

ndash5

0

5

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3


0

3

t (s)

t (s)

t (s)

t (s)

(b)



NoDolomite

NoShale


D1 24 100

46 69799

S1 08 75

57 3946197 14713 112 15026151 3771 168 7815202 0963 215 2231

D2 27 96

55 65726

S2 12 87

73 27564105 6285 133 13566147 2168 185 6258198 0884 223 1083

D3 18 98

48 45739

S3 10 80

55 23216111 12218 97 9843172 5375 152 4761237 1832 201 2926







SD RQminus12 (6)


PPV k(SD)minusn kQ

radic

R( )

n

(7)





100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)






0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



j

sij (1)



Eij 1113946 sij(t)11138681113868111386811138681113868

111386811138681113868111386811138682dt 1113944

m

k1xjk

11138681113868111386811138681113868

111386811138681113868111386811138682 (2)



E0 11139442iminus1

j0Eij (3)


Pj Eij

E0times 100 (4)





PPVd 3852Q

radic

R1113888 1113889

257

PPVs 1367Q

radic

R1113888 1113889

194

(5)



DA2AA2

AAA3 DAA3

A1

S

DDA3ADA3 DAD3ADD3

D1

ADD3 DDD3

DD2AD2














ndash70

0

70

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash15

0

15

(D) 202m

(C) 151m

ndash4

0

4

ndash1

0

1

t (s)

(B) 97m

(A) 46m

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

t (s)

t (s)

t (s)

(a)

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash25

0

25

(H) 201m

(G) 152m

(F) 97m

(E) 55m

ndash10

0

10

ndash5

0

5

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3


0

3

t (s)

t (s)

t (s)

t (s)

(b)



NoDolomite

NoShale


D1 24 100

46 69799

S1 08 75

57 3946197 14713 112 15026151 3771 168 7815202 0963 215 2231

D2 27 96

55 65726

S2 12 87

73 27564105 6285 133 13566147 2168 185 6258198 0884 223 1083

D3 18 98

48 45739

S3 10 80

55 23216111 12218 97 9843172 5375 152 4761237 1832 201 2926







SD RQminus12 (6)


PPV k(SD)minusn kQ

radic

R( )

n

(7)





100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)






0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia





ndash70

0

70

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash15

0

15

(D) 202m

(C) 151m

ndash4

0

4

ndash1

0

1

t (s)

(B) 97m

(A) 46m

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3

t (s)

t (s)

t (s)

(a)

V (m

ms

)V

(mm

s)

V (m

ms

)V

(mm

s)

ndash25

0

25

(H) 201m

(G) 152m

(F) 97m

(E) 55m

ndash10

0

10

ndash5

0

5

ndash1 0 1 2 3

ndash1 0 1 2 3

ndash1 0 1 2 3


0

3

t (s)

t (s)

t (s)

t (s)

(b)



NoDolomite

NoShale


D1 24 100

46 69799

S1 08 75

57 3946197 14713 112 15026151 3771 168 7815202 0963 215 2231

D2 27 96

55 65726

S2 12 87

73 27564105 6285 133 13566147 2168 185 6258198 0884 223 1083

D3 18 98

48 45739

S3 10 80

55 23216111 12218 97 9843172 5375 152 4761237 1832 201 2926







SD RQminus12 (6)


PPV k(SD)minusn kQ

radic

R( )

n

(7)





100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)






0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia







SD RQminus12 (6)


PPV k(SD)minusn kQ

radic

R( )

n

(7)





100101

1

10

100

DolomiteShale

PPV

(mm

s)

SD (mkg05)






0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia





0

15

30

45 (A) 46m

P (

)P

()

P (

)

f (Hz)

P (

)

0

15

30

45

(D) 202m

(C) 151m

(B) 97m

0

15

30

45

0

15

30

45

f (Hz)

f (Hz)

f (Hz)0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

(a)

P (

)P

()

P (

)P

()

f (Hz)

f (Hz)

f (Hz)

f (Hz)

0

15

30

45

(H) 201m

(G) 152m

(F) 97m

(E) 55m

0

15

30

45

0

15

30

45

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 50

0 10 20 30 40 500

15

30

45

(b)




RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



RQ

radic minusn

(8)





radic minusn

(9)




4 Conclusions





1 10 100

1

10

100

PPV

(mm

s)

PPV = 5205 SDJF

R2 = 085


R2 = 08


ndash1943


50 100 150

00

02

04

06

08

10


Vib

ratio

n at

tenu

atio

n co

effici

ent

0~20 HzD1S1

D1S1

20~50 Hz




Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Data Availability




Acknowledgments


References







0 20 40 60

0

20

40

60

0 2 4 6 8 1002468

10


Monitored PPV (mms)

Pred

icte

d PP

V (m

ms

)

100 fit


JF1 JF2 JFi


Ground




































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


assessmentofblasting-inducedgroundvibrationinanopen-pit … · 2019. 6. 18. · the frequency band...

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