IMPROVING THE ACCURACY OF VELOCITY WAVEFORM USING
TRANSFER FUNCTION OBTAINED BY GEOPHONE AND
ACCELEROMETER
TITTU BABU
Curtin University, Western Australian School of Mines
(WASM), Kalgoorlie WA, Australia
1. ABSTRACT: In order to break rocks at mines blasting operations are done. Along with rock
breakage blasting also produces unwanted by products such as air blast, seismic waves, noise and
fly rocks. Seismic waves result in ground vibrations .Noise and ground vibrations have a wider
impact on the environment and the people .When the vibration occurs each ground particle
possess a velocity and the maximum velocity is termed as Peak Particle Velocity (PPV).The
intensity of vibration is measured by PPV. If the ground vibration exceeds the PPV limit potential
damage will occur to the structure.So it is necessary to measure the ground vibrations precisely
inorder to avoid any kind of damages. In order to measure ground vibrations , measuring
instruments called Blast Seismographs ( geophone or accelerometer ) are used.Usually at mines,
blast vibrations are measured by geophones .But the measurement by a geophone is not precise as
that of an accelerometer and the usage of accelerometers at mines for vibration measurement is
limited due to its cost. The project objective is to improve the accuracy of velocity waveform
using transfer function obtained by geophone and accelerometer. For carrying out this research
project the blast vibrations produced by KCGM (Kalgoorlie Consolidated Gold Mine) will be
measured at WASM laboratory. Accelerometer selected for this research project is TEAC 708LF
and geophone selected for this project is PC-801 LPC.In order to acquire the same vibration both
geophone and accelerometer are attached together. Almost twenty six blast vibration readings are
taken. Only data with same units can be compared. So the acceleration data is integrated to
convert it into velocity data. Comparison of data in time domain has no meaning, so it is to be
converted to frequency domain. Then these values in time domain is converted to frequency
domain using FFT in OriginPro7J software. Then transfer function is obtained by dividing the
integrated acceleration data with geophone data. Finally in order to improve the accuracy of
velocity waveform, it is multiplied with the geophone data. Then this newly obtained waveform is
compared with the corresponding accelerometer and geophone data to obtain the desired result.
Finally suitable conclusions in support of the result are derived and it shows the degree of
accuracy of the final result.
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 2
2. INTRODUCTION: Blasting operations are done in mines for rock breakage. Along with rock breakage
blasting also produces unwanted by products such as air blast, seismic waves, noise and fly rocks.
Seismic waves result in ground vibrations. Ground vibrations can produce a huge impact on the
environment by creating discomfort to the people and potential damage to the nearby structures. The
factor responsible for damages induced by ground vibration is its Peak Particle Velocity (PPV).Each
structure has a particular level of peak particle velocity(PPV).If the ground vibration exceeds the PPV
limit, potential damages will occur to the structure.So it is necessary to measure the ground vibrations
precisely inorder to avoid any kind of damages. In order to measure ground vibrations, measuring
instruments called Blast Seismographs are used.
Geophone and accelerometer are the commonly used blast seismographs.The out put of a geophone is
velocity waveform and that of an accelerometer is acceleration waveform. A geophone is a kind of motion
transducer with moving coil and a magnet and it is highly sensitive in nature. It converts the movement or
displacement produced in the ground into voltage and that voltage may be recorded at a recording station.
Accelerometer works on the principle of simple harmonic motion of a damped mass.
Usually in mines geophones are used for vibration measurement.It is due to the fact that geophones are
cheap compared to accelerometers.Eventhough geophones are cheap, vibration measured by geophones
are not precise when compared to an accelerometer. There lies the relevance of this research project.As
already stated that the blast vibration measurements should be precisely done inorder to avoid damages
associated with it.In order to carryout precise vibration measurement with a geophone , its accuracy is to
be improved.The aim of this research project is how to improve the accuracy of velocity waveform of a
geophone so that so that blast vibrations can be accurately measured.
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 3
3. METHODOLOGY: This research project aims at
improving the accuracy of velocity waveform of
geophone using transfer function obtained by
geophone and accelerometer. For carrying out
this research project the blast vibrations
produced by KCGM will be measured at WASM
laboratory. The KCGM Super pit is one of the
largest open pit gold mines in Australia. It is
located in the south east edge of Kalgoorlie,
Western Australia.
The main instruments used in this project are
accelerometer, geophone, amplifier, data logger
and a computer system. When the geophone is
subjected to blast vibrations an output voltage is
produced which is directly proportional to the
velocity of blast vibration. Similarly when the
accelerometer is subjected to blast vibrations the
output voltage produced is directly proportional
to the acceleration of blast vibration. After
measurement of blast vibrations the output
obtained from geophone is velocity waveform
and the output obtained from an accelerometer is
acceleration waveform. The output obtained
from a geophone is not precise when compared it
with an accelerometer. In order to compare the
output of geophone and accelerometer, both of
them will be attached together and will be
subjected to the same vibration.
The type of accelerometer used in this research
project is Touch 708LF.Geophone used in this
research project is PC-801 LPC, manufactured
by Oyo Corporation and it has a natural
frequency of 4.5Hz.The analog signal from the
geophone and accelerometer is collected by data
logger or data recorder. It acts an interface
between a personal computer and the vibration
measuring instrument. They have the ability to
collect data on a 24 hour basis. In the data logger
the analog to digital signal conversion takes
place.
Once the blasting took place corresponding
vibration is produced .Then these vibrational
waveforms are detected using a geophone and
accelerometer .Finally they are recorded using
the OPS software .The measured vibrational
waveforms are stored as CSV files in the
computer. The stored CSV files are then
subjected to various calculations in order to get
the desired result. In this chapter all the steps
related to research method and experimental
design are explained in detail under various sub
titles.
3.1 INSTRUMENTS USED
3.1.1 GEOPHONE
A geophone is a kind of motion transducer
which is highly sensitive in nature. It consists of
case (or housing), coil, magnet, a leaf spring and
a cylinder. The main part of a geophone is its
housing. The coil and the magnet assembly are
enclosed in the housing. The leaf spring supports
the coil mass and it helps in the axial movement
of the coil relative to the magnet. As a result of
ground vibrations the displacement produced in
the ground will be transmitted to the casing in
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 4
which the magnet is mounted .The magnet
moves while the coil remains stationary. Thus
the magnetic flux linked with the coil changes
.The relative motion between the coil and
magnet causes a voltage to be generated across
the coil windings. Thus the geophone operates
according to the Faradays law of electromagnetic
induction. Vα∂x
∂t .The output voltage produced is
directly proportional to the velocity .When the
frequency of a recorded waveform is higher than
the natural frequency of a geophone, the proof
mass displacement will be directly proportional
to the ground displacement .At higher
frequencies the output voltage produced by a
geophone is directly proportional to the ground
velocity. The geophone used in this research
project is PC-801 LPC. It is manufactured by
Oyo Corporation .Its natural frequency is 4.5 Hz.
The sensitivity of this geophone is 1 mV/m/s.
Figure 1-Geophone PC-801 LPC
3.1.2 ACCELEROMETER
Accelerometers are sensors that can detect
acceleration. It works on the principle of simple
harmonic motion. The vibration measurement by
an accelerometer is more precise than that of a
geophone. Accelerometers are of different types
such as capacitive, piezoelectric, piezoresistive,
strain gauge based, servo accelerometers etc. In
this project only piezoelectric accelerometer is
used. The main components of a piezoelectric
accelerometer are accelerometer base, center
post, seismic mass and piezoelectric element. A
piezoelectric accelerometer consists of base,
seismic mass, center post and piezoelectric
element. Out of this, the basic element is its
seismic mass and its active element is
piezoelectric material. One side of the
piezoelectric material is attached to the center
post at accelerometer base and the other side to
the seismic mass. The seismic mass is mounted
to the case of the accelerometer. When the body
of the accelerometer is subjected to vibration, the
seismic mass attached to the piezoelectric
crystals moves. But it actually wants to stay in
its original place due to inertia force. So the
compression and stretching of the piezoelectric
material will takes place .When a piezoelectric
material is subjected to a compression or shear
force correspondingly an output charge
proportional to the applied force will be
produced. Thus the force which causes the
movement of the seismic mass or piezoelectric
material is the product of acceleration and
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 5
seismic mass (As per Newton’s second law of
motion F = ma).Since the seismic mass is
constant the output produced will be
proportional to the acceleration of the mass. The
accelerometer used in this research project is
TEAC 708 LF manufactured by Teach
Instruments Corporation Japan. It has range of ±
150 G. Sensitivity of this accelerometer is 9.97
mV/G and the frequency response varies from
0.2 to 22000Hz.
Figure 2-Accelerometer TEAC 708 LF
3.1.3 AMPLIFIER
The output voltage produced by an
accelerometer is not quite good enough for
measurement .So it has to be amplified or
boosted up to the required level. So an amplifier
is used to perform this job. The amplifier used in
this research project is TEAC SA- 611 Charge
Amplifier. SA- 611 is mainly used for
piezoelectric accelerometers (for both charge and
pre-amplifier type of accelerometers).Its
sensitivity can be set by a three digit digital
switches and it is easy to set up for different
accelerometer sensors. This amplifier is compact
and light weight .It can be operated with three
types of power supplies such as built in batteries
(4 AA batteries), external dc and ac adaptor. It
has two types of inputs .The first one is
‘CHARGE’ for charge type sensors and second
is ‘FET’ for IEPE type sensors.
Figure 3- TEAC SA- 611 Charge Amplifier
SA-611 main specifications
Input Switched Charge Type or
IEPE Type
Sensitivity Setting Three Digits Digital Switch
Input Ranges 1, 10, 100
Output Filter Low Pass Filter(LPF) : 1kHz,
10kHz
High Pass Filter(HPF) :5Hz
Calibration Voltage
(CAL)
Rectangular Wave
200Hz±20Hz,
Current Sources 0.5mA, 4mA,24V DC
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 6
3.1.4 DATA LOGGER AND COMPUTER
Geophone and accelerometer transmit
continuous analog signal A computer cannot
detect analog signal, so a data logger is used to
convert the anlog signal to digital signal. It is
impossible and inefficient to record every bit of
transmitted data. So the data collection
instrument (data logger or data recorder) is to be
manipulated in order to get the readings at
specific intervals. Three important parameters
are to be controlled in data logger in order to
obtain accurate measurement. They are sampling
frequency, sampling time and number of samples.
A data logger is an instrument which can record
the measured data over time .they can be used in
interface with a personal computer. Thus it can
act as a local interface device with a computer.
Data loggers are generally used for wide range
of applications. The main components of a data
logger are input channel, analog to digital
convertor, microprocessor, memory, power
supply, data output port, weatherproof enclosure
and software. The output from the geophone and
accelerometer are connected to the input channel
of data logger. The channel composed of
circuitry design which is specially designed to
guide a sensor signal (output voltage of
geophone and accelerometer) to data logger
processor .Usually a data logger has four to eight
channels. The next main component is analog to
digital convertor. It converts the analog signal
obtained from the sensors (geophone and
accelerometer) to digital signal. Microprocessor
is a basically a logical circuit which has the
ability to process the necessary basic instructions
to run a computer or a data logger. Then the
measured data are recorded in the memory of
data logger. Data logger uses two types of
memory such as RAM (Random access Memory)
and EEPROM (Electronically Erasable and
Programmable Read Only Memory).Another
unique feature of a data logger is its low power
requirement. Most data logger requires a 12 V dc
power. But the one used in this research project
utilizes ac power for its working. A data logger
communicates with a computer through a serial
port. It allows the data to get transfer in a series
to the computer. Some kinds of data loggers are
embedded with special software in order to get
synchronized with the computer. Finally using
the OPS software the measured data are recorded
and stored in the computer as CSV files.
Figure 4-TEAC Data logger
3.2 EXPERIMENTAL SET UP
As already stated that in order to obtain the
project objective transfer function is required. So
the transfer function between a geophone and
accelerometer is to be obtained. Thus for the
sake of this purpose both the instruments are
attached together so that they can acquire the
same blast vibration. The site selected to carry
out this research project was a small area located
close to the geology building
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 7
Figure 5-geophone and accelerometer attached together
After attaching the geophone and accelerometer
together, output of the accelerometer is
connected to the amplifier .From the amplifier
connection goes to the data logger. On the mean
while the output of the geophone is connected
directly to the data logger. Finally the output of
the data logger is connected to the computer.
Amplifier is very essential to boost the output
signal of an accelerometer. Figure 6 shows the
schematic diagram of experimental set up
Figure 6-Experimental set up
3.4 OBTAINING THE AMPLIFICATION FACTOR
The next step, after the experimental set up, is
obtaining the amplification factor. The type of
amplifier used in this research project is TEAC
SA-611 charge amplifier. An amplifier is used to
increase or amplify the power of a signal. It
performs this job by acquiring energy from the
power supply and it controls the output to match
with the shape of the input signal but with
greater amplitude. An accelerometer output is
not quite strong enough to detect and measure
.So it has to be amplified up to a certain level to
make it easy to detect and measure. In order to
obtain the amplification factor some connection
rearrangements are done in the experimental set
up. It is shown clearly in figure 7.
Figure 7-Experimental set up to obtain amplification
factor
Figure 7 shows the experimental set up to obtain
the amplification factor. In order to obtain this
some rearrangements are done in the previous
experimental set up connections. Accelerometer
is detached from the geophone. Geophone output
has two connection leads. One connection wire
goes directly to the data logger and the other
connection wire is connected to the data logger
via an amplifier. Then the geophone is subjected
to vibrational input and corresponding output is
obtained and recorded. Thus two output
waveforms are obtained. The first one is the
native one and the second one is the magnified
or amplified one. The amplification factor is
obtained by dividing the amplified output
waveform with the normal output waveform. So
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 8
after careful calculations and considerations the
amplification factor is obtained as 10.Thus it can
be concluded that the accelerometer data
(acceleration waveform) is amplified ten times
by the amplifier.
3.5 MEASURING THE BLAST VIBRATIONS
The blast vibrations from KCGM are recorded
using the OPS software. It is one of the best
professional and functional blast wave recording
software. Before taking measurements all the
necessary settings in the software should be
done. The first step is to set up the range. It is
essential to define the range of blast waves. At
first the range was set as 500 mV for the first
channel and 200 mv for the second channel
.Later on it was identified as 500 mV was too
large for the blast vibration waves which would
make the recorded wavelet too much steady .So
it would be too difficult to analyse. Finally the
range for the first and second channel was set as
200 mv and 100 mV respectively. This newly
selected range was absolutely perfect to offer the
exact wavelet for the analysis. The trigger level
was set as 1% (1 % of 200 mV = 2 mV).The
filter type selected was low pass filter. Then the
filter frequency was set up. It is the filter
frequency which decides up to what range of
frequency an instrument can detect and record.
Filter frequency was set as 500 Hz, so that blast
vibrations with frequency above 500 Hz will not
be recorded. Next step was to determine the
sampling frequency. Sampling frequency is
defined as the number of samples per unit time
(in seconds) taken from a continuous analog
signal in order to make it discrete.
In this research project the sampling frequency
was set as 10000 Hz. Finally the memory was set
as 100µs/10 KHz and the block size was
32KW*32.So all the above said settings were
done and proceeded to the experiment. Before
recording the blast vibrations, all the electrical
connections were rechecked in order to avoid
any kind of loose contacts. Then the OPS
software was selected in the simulation mode.
After obtaining a steady waveform from
geophone and accelerometer, the record button
in OPS software was clicked. Then waited for
the blasting from KCGM. Once the blasting had
occurred corresponding waveforms were
recorded using the OPS software and they were
stored as CSV files in the computer. Almost 26
different blast vibration data were collected and
measured.
Figure 8-recorded blast vibration waveform
Figure 8 shows an example of recorded blast
vibration waveform. The waveform is in time
domain. The waveform shown in red colour is
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 9
the accelerometer data and the waveform shown
in blue colour is the geophone data. Here the X
axis is time in µs and Y axis is voltage in mV.
From this two waveforms it can observe that the
output waveforms of both the instruments are in
the same trend. There is some difference is in
amplitude due to the difference in sensitivity of
both the instruments.
3.6 SUMMARY OF RESEARCH METHOD &
EXPERIMENTAL
The method and procedure of carrying out this
research project is clearly summarised in this
chapter. This chapter is mainly categorised under
five titles including the introduction. The main
titles are instruments used, experimental set up,
obtaining amplification factor and measuring
blast vibrations. The title, instruments used is
again categorised into geophone, accelerometer,
amplifier, data logger and computer. All the
essential features and requirements of these
instruments are described in detail under each
title (geophone, accelerometer, amplifier, data
logger and computer).It also includes the
specifications of each instrument. Under the title
experimental set up the method of conducting
the research project is explained. It also reveals
the strategy adopted to obtain the desired result.
This section incorporates the entire vital
schematic diagram necessary for the better
understanding of the research project from a
wider perspective. It shows the connection
between various instruments used for the
research project. It is then followed by the title
obtaining the amplification factor. This section
explains how to obtain the amplification factor.
Accelerometer output waveform is not strong
enough for recording and measurement. So it has
to be boosted up .Amplification factor is
obtained by doing some rearrangements in the
connections made for experimental set up.
Finally the amplification factor is obtained as
10.Therefore it can be concluded that output
waveform of an accelerometer is amplified by
ten times. After that the obtained blast vibrations
from KCGM are recorded. They are measured
and recorded using the OPS software. It is one
most functional and professional blast wave
recording software. Before taking measurements
all the necessary settings in the software should
be done. First among this was setting up of the
range. So the range for the first and second
channel was set as 200 mv and 100 mV
respectively. Then the filter frequency was as
500 Hz. It is the filter frequency which decides
up to what range of frequency an instrument can
detect and record. Next the sampling frequency
was set as 10000 Hz. The trigger level was set as
1%. At the end memory and block size was set
as 100µs/10 KHz and 32KW*32 respectively.
The vibrational waveforms detected and
recorded by the OPS software are stored in
computer as CSV files. Almost 26 different blast
vibration data were collected and measured.
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 10
4. RESULT AND ANALYSIS
4.1 BLAST VIBRATIONAL WAVEFORM
Almost twenty six blast vibration data were
obtained .Among them the best twenty data are
collected and compared. Using OPS software the
velocity waveform and acceleration waveform
for the corresponding blast vibrations are
recorded. A sample of the recorded blasting
wavelet is shown in figure 9.
Figure 9- recorded blasting wavelet
Figure 9 shows an example of recorded blasting
wavelet. Here the wave form is in the time
domain. The blue waveform indicates the
geophone data and the red waveform indicates
the accelerometer data. Both the output
waveform will be in mV and the time interval is
0.0001 s. Both the velocity and acceleration
waveform shows the same trend and there are
some differences in amplitude for both these
waveforms due to the difference in sensitivity of
geophone and accelerometer.
4.2 TIME DOMAIN SPECTRA
The recorded blasting wavelets are stored as
CSV files. Then all the manipulations are done
in these files. Suitable time interval of 0.0001
second is provided. For each recorded blasting
wavelet there are 32000 data. So the time
interval is defined up to 32000 data. The next
step is to divide the accelerometer data by 10. It
is because the amplification factor has to be
taken to consideration. In this case the
amplification factor is 10.It is obtained by
dividing the amplified geophone data with the
original geophone data subjected to same input
vibration. The output of geophone and
accelerometer is in mV. But for this research
project the data from the geophone is to be
obtained in m/s and the data from the
accelerometer is to be obtained in m/s2. The
sensitivity of geophone is 1 mV/m/s. and that of
accelerometer is 9.97mv/G or 9.97mV/9.98m/s2
which is equivalent to 1 mV/m/s2 .From this it
can concluded that for an output of 1 mv from
the geophone the corresponding velocity will be
1 m/s. Similarly for an output of 1 mV from the
accelerometer the corresponding acceleration
will be 1 m/s2.In order to obtain the transfer
function, both the geophone data and
accelerometer data has to be compared. But only
data with same units can be compared. Here
geophone and accelerometer detect the same
wave but the output will be in different unit, one
is m/s and the other in m/s2.So the obtained
acceleration data is integrated to convert it into
velocity data.
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 11
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-10
-5
0
5
10
15
Volta
ge (m
V)
Time (s)
Figure 10-velocity waveform from geophone (case 1)
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-25
-20
-15
-10
-5
0
5
10
15
20
Vol
tage
(mV
)
Time (s)
Figure 11- velocity waveform from geophone (case 2)
Case 1 and case 2 shown in figure 10 and 11 are
two examples of velocity waveform obtained
from geophone during the experiment (blast
vibration measurement). The graphs show the
variation of voltage with time (with a time
interval of 0.0001s).As it is mentioned before
that 1 mV is equal to 1 m/s .So the above shown
graphs can be considered as velocity waveforms.
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-0.10
-0.05
0.00
0.05
0.10
0.15
Acc
eler
atio
n (m
/s2 )
Time (s)
Figure 12-acceleration waveform from accelerometer
(case 1)
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-0.2
-0.1
0.0
0.1
0.2
0.3
Acc
eler
atio
n (m
/s2 )
Time (s)
Figure 13- acceleration waveform from accelerometer
(case 2)
Case 1 and case 2 shown in figure 12 and 13 are
two examples of acceleration waveform obtained
from an accelerometer during the experiment
(blast vibration measurement).The graphs show
the variation of acceleration with time in seconds
(time interval is 0.0001s).As already stated that
the output data of both accelerometer and
geophone must be compared to get the transfer
function. But in order to compare, both the data
should be in the same unit. So the acceleration
data is integrated to obtain the velocity data.
Thus it can be easily compared with geophone
data. Integration of acceleration data shown in
figure 12 (case 1) and figure 13 (case 2) gives
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 12
the velocity data shown in figure 14(case 1) and
figure 15 (case 2).
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
0.000
0.005
0.010
0.015
0.020
0.025
0.030
Velo
city
(m/s)
Time (s)
Figure 14-Integrated accelerometer data (case 1)
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
Velo
city (
m/s)
Time (s)
Figure 15- Integrated accelerometer data (case 2)
4.3 FILTERING OFF LOW FREQUENCY SIGNALS
The values obtained after the integration of
accelerometer data has some drift components
.These drift components are unnecessary low
frequency signals. It is shown in red coloured
lines in figure 14 and 15. So it has to be
eliminated before doing all the calculations. It is
done in OriginPro 7J software. Thus the low
frequency signals are removed from the
integrated accelerometer data. The required
filtered data from figure 14(case 1) and figure 15
(case 2) is shown below in figure 16 (case 1) and
17 (case 2).
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-0.0006
-0.0004
-0.0002
0.0000
0.0002
0.0004
Vel
ocity
(m
/s)
Time (s)
Figure 16-Low frequency filtered data (case 1)
-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
-0.0008
-0.0006
-0.0004
-0.0002
0.0000
0.0002
0.0004
0.0006
0.0008
0.0010
Vel
ocity
(m
/s)
Time (s)
Figure 17- Low frequency filtered data (case 2)
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 13
4.4 FREQUENCY DOMAIN SPECTRA
Comparison of data in time domain has no
meaning, it has no real life applications .It is not
a better method to describe the relationship
between geophone and accelerometer in time
domain. So the measured velocity data from the
geophone and integrated accelerometer data has
to be converted from time domain to frequency
domain. This is done through the Fourier
Transform. Using FFT function (Fast Fourier
Transform) in OriginPro7J software
accelerometer data and geophone data from time
domain is converted to frequency domain. It is
shown in figures below
Figure 18 –Acceleration waveform after FFT (case 1)
Figure 19- Acceleration waveform after FFT (case 2)
Figure 18 and 19 shows the acceleration
waveform after Fast Fourier Transformation for
both case 1 and case 2.
Figure 20-Velocity waveform after FFT (case 1)
Figure 21- Velocity waveform after FFT (case 2)
Similarly FFT is done for geophone data in the
OriginPro7J software and is shown in above
figures. Figure 20 and 21 shows the velocity
waveform after Fast Fourier Transformation for
both case 1 and case 2.
4.5 OBTAIN TRANSFER FUNCTION
Next step was to obtain the transfer function
between the geophone and accelerometer .Thus
in order to obtain the transfer function almost
twenty vibration measurements are collected for
both geophone and accelerometer. The transfer
function is obtained by dividing the integrated
accelerometer data in frequency domain with the
geophone data in frequency domain.
Let G (ω) is the velocity waveform obtained by
geophone after Fourier transformation. V(ω) is
the velocity waveform obtained by
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 14
accelerometer after integration. Therefore
transfer function will be
T (ω) = V(ω)
G(ω)
-6000 -4000 -2000 0 2000 4000 6000
0.0000
0.0002
0.0004
0.0006
0.0008
0.0010
0.0012
0.0014
0.0016
0.0018
0.0020
Four
ier
Am
plitud
e
Frequency (Hz)
Figure 22-Graphical representation of transfer
function
The transfer function obtained in this research
project is graphically represented in figure 43
with transfer function in the Y axis and
frequency in the X axis .It is obtained from
OriginPro 7J software. There are 32770 different
frequency points. The frequency ranges from -
5000 Hz to 5000 Hz .from the graph it is clear
that the maximum Fourier amplitude is 0.00021
and the average Fourier amplitude is
0.0001.Using this transfer function the accuracy
of velocity waveform of a geophone can be
improved.
4.6 IMPROVING THE ACCURACY OF VELOCITY WAVEFORM
The project objective is improving the accuracy
of velocity waveform using transfer function
obtained by geophone and accelerometer. So the
next step is to utilize this transfer function to
improve the accuracy of velocity waveform.
Besides twenty vibration measurements three
additional readings are taken. Then these three
readings were subjected to Fourier
transformation using fft function in OriginPro7J
software .After that the transfer function is
multiplied with the three geophone data ( case 1,
2 and 3).Then newly obtained improved velocity
waveform is compared with the corresponding
geophone and accelerometer data.
Case 1
0 50 100 150 200
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Four
ier
Am
plitu
de
Frequency Hz
Figure 23-Velocity waveform obtained by multiplying
transfer function with geophone data
0 50 100 150 200
0.0
0.1
0.2
0.3
0.4
Four
ier A
mpl
itude
Frequency Hz
Figure 24-Integrtaed Acceleration waveform (
acceleration data)
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 15
0 20 40 60 80 100 120 140 160 180 200
0
2000
4000
6000
8000
Fou
rier
Am
plitud
e
Frequency Hz
Figure 25-Velocity waveform (geophone data)
Case 2
0 50 100 150 200
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Four
ier
Am
plitu
de
Frequency (Hz)
Figure 26- Velocity waveform obtained by multiplying
transfer function with geophone data
0 50 100 150 200
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Four
ier
Am
plitu
de
Frequency (Hz)
Figure 27-Integrated Acceleration waveform
(acceleration data)
0 50 100 150 200
0
2000
4000
6000
8000
10000
Four
ier
Ampl
itude
Frequency (Hz)
Figure 28- Velocity waveform (geophone data)
Case 3
0 50 100 150 200
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Four
ier
Am
plitu
de
Frequency (Hz)
Figure 29- Velocity waveform obtained by multiplying
transfer function with geophone data
0 50 100 150 200
0.0
0.1
0.2
0.3
0.4
0.5
Four
ier A
mpl
itude
Frequency
Figure 30- Integrated Acceleration waveform
(acceleration data)
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 16
0 50 100 150 200
0
1000
2000
3000
4000
5000
Four
ier
Am
plitud
e
Frequency (Hz)
Figure 31 -Velocity waveform (geophone data)
In order to obtain the result, three graphs
[Velocity waveform obtained by multiplying
transfer function with geophone data, Integrated
acceleration waveform (acceleration data) and
Velocity waveform (geophone data)] are
compared. After comparison of first two graphs
for all the three cases (improved velocity
waveform and integrated acceleration
waveform), it can concluded that the peaks and
valleys of both the graphs almost look alike.
Noticeable waveform occurs between the
frequency ranges 0 to 200 Hz for all the cases
.Thus while generating graphs waveform
generated between 0 to 200 Hz is only
considered for the final analysis. When the three
waveforms in all the three cases are closely
studied, the main thing which can be noticed is
that the occurrence of peak amplitude .In all the
cases the peak amplitude occurs between the
range of 0 to 50 Hz. For the first case the value
of the highest peak in integrated acceleration
waveform is 1.7 times the value of highest peak
in accuracy improved velocity waveform and for
the second case the value of the highest peak in
integrated acceleration waveform is 1.5 times the
value of highest peak in accuracy improved
velocity waveform. Finally for the third case the
value of the highest peak in integrated
acceleration waveform is 1.25 times the value of
highest peak in accuracy improved velocity
waveform. Thus from three cases it can be
concluded that the average range will be 1.48
times. This value will change if more results are
considered. Thus the project objective of
improving the accuracy of velocity waveform
using transfer function, obtained by geophone
and accelerometer, is achieved.
5 CONCLUSIONS AND RECOMMENDATIONS
After obtaining the result suitable conclusions
should be derived. The research project as a
whole is dependent on geophone and
accelerometer .The primary aim of the research
project was to improve the accuracy of velocity
waveform using transfer function. So the transfer
function between geophone and accelerometer is
obtained .Obtaining the transfer function was the
secondary aim of the research project. Thus the
main conclusions obtained in the research
project are summarized below.
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 17
5.1 CONCLUSIONS
(1) As already stated that the objective of this
research project was to improve the accuracy of
velocity waveform using transfer function
obtained by geophone and accelerometer. This is
considered as the primary objective.
(2) In order to achieve this primary objective
transfer function has to be obtained. So obtaining
transfer function was set as the secondary
objective. In order to obtain transfer function
almost twenty blast vibration measurements
were taken and it was followed by subsequent
necessary calculations .Finally the transfer
function was obtained. Transfer function for
twenty results was obtained. Then the final
transfer function was obtained by taking the
average of all the twenty transfer functions.
(3) In order to apply these transfer function three
additional blast vibrational measurements were
taken. Then the transfer function is multiplied
with the corresponding geophone data for all the
three cases .This resulted in the improvement of
accuracy of velocity waveform. After that all the
three waveforms are compared.
(4) After comparison of first two graphs for all
the three cases (improved velocity waveform and
integrated acceleration waveform), it can be
stated that the peaks and valleys of both the
graphs almost look alike.
(5) From the comparison of three waveforms, it
can be concluded that noticeable waveform
always occurs between the frequency ranges 0 to
200 Hz for all the cases.
(6) By the careful study of all the three
waveforms a conclusion can derived that the
peak amplitude occurs between the ranges of 0
to 50 Hz.
(7) From the observation and analysis of three
graphs the variation of amplitude between the
accuracy improved velocity waveform and
integrated acceleration waveform is noticeable
.For the first case the amplitude of the highest
peak in integrated acceleration waveform is 1.7
times the value of highest peak in accuracy
improved velocity waveform. For the second and
third case it is 1.5 and 1.25 times respectively.
Thus from three cases it can be concluded that
the average range will be 1.48 times.
(8) For this research project almost twenty six
blast vibration measurements were taken. The
accuracy of the final result depends on the
transfer function. Transfer function was obtained
from average of twenty readings The degree of
accuracy depends upon the number of readings.
The accuracy of the final result would have been
improved if more readings were taken (such as
50 or 100 readings).
5.2 RECOMMENDATIONS FOR FURTHER WORK
This research project entirely depends on
transfer function .But the transfer function
between geophone and accelerometer depends
on the recorded blast vibration waves.
Sometimes the results will cause some ambiguity
Improving the accuracy of velocity waveform using transfer function obtained by geophone and accelerometer
Tittu Bbau 16320587 Curtin University, Western Australian School of Mines (WASM), Kalgoorlie WA, Australia 18
.It is due to the presence of some existing errors
in the instruments .So it is always recommended
to collect as many blast vibration data to
minimize the error. And it can maximize the
degree of accuracy of final result.
Through this research project it can be shown
that the obtained transfer function can improve
the accuracy of geophone. Thus the final result
will be a much more precise velocity waveform
from a geophone. Thus the application of
transfer function is not only limited to this
research project but also can be employed in
large scale blast vibration measurements so that
geophones can be used effectively and
economically. Thus this research project will
result in precise vibration measurement at low
cost in mines.
ACKNOWLEDGEMENTS
I would like to thank and extend my sincere
gratitude to all the academic staff of Mining
Engineering Department, Western Australian
School of Mines (WASM) Curtin University
Western Australia.I am deeply thankful to my
supervisor Dr. Youhei Kawamura without whom
this project would never happen. His instructive
advice and valuable suggestions helped me a lot
for the completion of this thesis. Support from
the supervisor for the completion of this research
project was outstanding.
I would also like to thank Prof .Erkan Topal ,
Head of Mining Engineering Department , for
his full support for me as an international student
during the last one and half year. I am deeply
grateful to Mr .Mahroof for granting me
permission to use the Geology department lab.
Finally I would like to thank the almighty god,
my parents and my brother for their
unconditional love and support. Once again I
would like to thank each and every one who has
helped me in my entire work.
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