Download Research on Intensity Quick Report and the Key Technology of

International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016) pp. 1-10
http://dx.doi.org/10.21742/ijitbd.2016.1.1.01
Research on Intensity Quick Report and the Key Technology of
Seismic Intensity Monitoring
Laibao Yu1, 2 and Tao Zhang1, 2
Institute of Geophysics and Geomatics,
China University of Geosciences Wuhan 430074
2
Wuhan City Vocational College, Wuhan 430064
Wuhan, China, 430074
[email protected]
1
Abstract
Combined with the status quo of intensity monitoring and intensity quick report system at
home and abroad, the present paper studies the key technologies of the intensity quick report
system, including the technical parameters required of seismic monitoring device and
hardware implementations, quick report system components and networking, intensity
calculation model, software of the system etc., and conducts a preliminary test. After testing,
the seismic monitoring device designed has good sensitivity and amplitude-frequency
characteristics. The system can send data, receive data and calculate intensity quickly,
meeting the requirements of intensity quick report.
Keywords: intensity quick report, seismic, network, design scheme
1. Introduction
Although China has a lot of earthquakes, China is one of the most vulnerable nations of
earthquake in the world, so far a real seismic intensity quick report system has not been
established in the mainland of China. Combined with the status quo at home and abroad, the
present paper studied the key technology of seismic intensity quick report system.
Seismic intensity quick report system get real-time data from seismic monitoring network
in advance layout. When the acceleration of monitoring nodes exceed the setting threshold
value, the data will be sent to the server through the network. The server analyzes the data
and calculates the intensity and judges the number of the node exceeding the setting threshold
value, so as to determine whether issue an emergency disposal instruction.
Seismic intensity quick report system contains seismic information acquisition,
information transmission, intensity calculation and other key parts.
2. The acquisition of seismic information
2.1. Device for obtaining seismic information
At present, there is no clear standard about instrument index of earthquake early warning
system in China, through the analysis of the technical parameters of instrument used in
existing earthquake early warning system, the present study summarizes the key indexes of
seismic pick-up device in earthquake early warning system [1].
IJITBD
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International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
Table 1. The table of the basic parameters of the seismic monitoring device
Countries
and
Regions
Type
Range
Frequency
Range
Dynamic
Range
Transverse
sensitivity
American
Japan
Taiwan
Turkey
3-axis
3-axis
3-axis
3-axis
±4g
±4g
±2g
±2g
DC~200HZ DC~100HZ DC~50HZ DC~50HZ
155dB
96dB
108dB
<0.03g/g
<0.03g/g
3dB
From the table, we can see the vibration pick-up device of early warning system generally
meet 3-axial measurement range , range≥2g, frequency response DC~50HZ, dynamic range
≥100db.
In recent years, the rapid development of MEMS offers an opportunity to the development
of earthquake prevention and disaster reduction constrained by seismic instruments cost. By
comprehensive comparison, HAAM-326B1 is selected as the acceleration measurement chip.
The basic parameters of HAAM-326B1 are as follows: the range of ± 2G, the frequency range
of DC~250HZ, the transverse sensitivity <5%, withstand the maximum impact of 5000g. Its
performance meets the requirements.
GND
HAAM326B
CPU
STANDBY +3V
Vcc +3V
xout VCH0 LTC1865
yout VCH1
zout
VCH2 LTC1865
C8051F
P2.0
020
P2.1
CONV_1 P2.2
SDO_2 P2.3
SCK_2
P2.4
CONV_2 P2.5
SDO_1
SCK_1
Figure 1. The hardware structure chart
As shown in fig.1, 16 bit double channel A\D chip LTC1865 is selected as data
acquisition chip. HAAM-326B1 integrates signal low pass filter circuit inside, the user only
need to provide the external capacitor to realize low-pass filter. Filter capacitance can be
calculated by the following equation.
F−3dB =
1
(2π × Rout (32k Ω) × Cx, y, z )
(1)
Considering the frequency range of natural earthquake, the setting of the cut-off
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International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
frequency is 50HZ. Low pass filter capacitor is 0.1uf through calculation. In order to
improve the precision of A\D, the device with an external precision voltage reference source
MAX873 is used.
2.2. Anti-interference Design
Seismic signal is weak and vulnerable to be interfered, so it is important to take measures
to reduce the interference. There are many factors causing interference, including the signal
channel interference and power supply interference etc. [2].
Anti-interference methods are mainly the following:
2.2.1 Ground connection
Grounding is the main method for interference suppression. Proper grounding can
eliminate the noise voltage generated when the circuit current flows through the common
ground resistance. The signal frequency of the system is below 1 kHz, belonging to the low
frequency circuit. The inductance between the wiring and components is not the main
problem, but when the grounding forms a loop, it will cause a great deal of interference on
the circuit, so take one point grounding.
Further, the power supply line and the signal line should be separated in the PCB
wiring .In addition, in order to remove the coupled simulation of the integrated circuit and
reduce the noise, when design the analog circuit connect the spare pins of analog chip to
high level or GND through resistor.
2.2.2 Filtering
Filtering is divided into power supply filtering and signal filtering. A simple power supply
filter circuit and the EMI flake filter with magnetic beads are adopted .After filtering, the
noise of the circuit is significantly reduced; Signal filtering is mainly to reduce the use of
capacitive and inductive energy storage element to decrease the mean square values of
thermal noise.
3. Network and signal transmission
The
seismic
intensity quick
report system, including
an
information
processing server, special
transmission
network, monitoring
node,
network
interconnection equipment, and emergency disposal device etc., is a complex system. The
architecture frame of urban intensity quick report system is shown in the Fig.2.
When the earthquake occurs, the seismic data monitored by the monitoring node is sent to
the server through a dedicated network; The server quickly analyzes the data, estimates the
seismic parameters, evaluates the effects of range, and finally makes the integrated decision
by integrating the engineering condition, seismic vulnerability and other information.
3.1. Monitoring node
The main function of the monitoring node includes collection of strong motion data, trigger
judgment, storage and upload of the vibration data before and after the trigger, fault
self-checking, and periodically sending node running status etc.
3.2. Transmission Network
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International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
Transmission network consists of the backbone nodes which are arranged in the place
having better installation environment with higher reliability than other monitoring nodes.
Transmission network transmits the strong motion data got from backbone nodes and other
nodes to data processing server, and transmits the instructions of data center to each backbone
node.
Lay special network as the backbone network and use the IPv4 protocol as internet address
allocation Special network is connected into the public network through the firewall.
Figure 2. The architecture frame of network and signal transmission
3.3. The server and client
The server is the central module of the whole city intensity reporting system. It’s a set of
software system installed on the computer system, and it can realize remote control, data
processing, human-computer interaction and so on, so as to analyze and publish the data
obtained, so as to achieve the ultimate goal of intensity quick report system design.
4. Intensity calculation
The current Chinese seismic intensity scale gives the reference relationship between two
physical parameters which are the horizontal peak ground motion acceleration and peak
velocity and seismic intensity above V degree. When calculate the intensity using PGA and
PGV respectively, the coincidence rate of the result of calculation and field survey intensity is
very low. The intensity calculation methods of Japan Meteorological Agency use almost all
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International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
parameters of ground motions, and have high coincidence rate.
After comprehensive consideration, the system adopts the main idea of the Japanese
intensity calculation, combined with Chinese geological and structural characteristics,
properly modified the parameters of the algorithms 'duration', and finally it achieves good
results. The specific steps of the algorithm are described in detail as follows [3].
Earthquake acceleration time history of three directions
gi (t ) gets by Fourier transform
respectively.
The results
Gi (ω ) , multiplied by three kinds of filter function，gets the function G 'i (ω )
G 'i (ω ) = Gi (ω ).F1 (ω ).F2 (ω ).F3 (ω )
(2)
Formula parameters are defined as follows:
F1 (ω ) = (1/ ω )1/2
F2 (ω ) =
1
(1 + 0.694 x + 0.24 x + 0.0557 x 6 + 0.009664 x8
2
4
+0.00134 x10 + 0.000155 x12 )
F3 (ω ) = (1 − exp(−ω / ω0 )3 )
=
=
x ω=
Hz , ω0 0.5 Hz
/ ωc , ωc 10
ω is the frequency of seismic wave
'
'
Third, the gi (t ) is obtained by the inverse Fourier transform of G i (ω ) .
Fourth, the three time history components are synthesized into vector acceleration
A=
g1' (t ) 2 + g 2 ' (t ) 2 + g3' (t ) 2
Fifth, guarantee
(3)
τ ( Am ) ≥ 0.3s
=
I JMA 2.log Am + 0.94 , then get the
Sixth, put equivalent acceleration A into the formula
intensity.
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START
i=1,3
FFT Gi (ω ) ← gi (t )
G 'i (ω ) = Gi (ω ).F1 (ω ).F2 (ω ).F3 (ω )
FFT −1 gi ' (t ) ← G 'i (ω )
Vector acceleration v (t )(t = 1, n)
k =1
Select data set v(k ), v(k + 1),...v(k + j )
k= k + l
Sort s (1), s (2),...s ( j + 1)
Dert min e
vector amplitude a0 (k ) = s (m)
Calculate IISI IISI (k )
END
Figure 3. The flow chart of intensity calculation
5. Software Design
5.1. Processing of the monitoring node [4]
(1) If the personal device used as a seismograph detects the acceleration exceeding a fixed
threshold value, a client program installed in the personal device will be in a transmission
standby state.
(2) When a measurement value exceeds a threshold value, the client program transmits the
data of the instantaneous acceleration, time, and latitude longitude to a regional server.
(3) After sending data to the server, the client records acquired acceleration and acceleration
for N seconds, and the recorded data is transmitted to the server. This operation is repeated a
few times at intervals of N seconds.
(4) When the server processes data from many clients and decides the detected oscillation as a
big earthquake, the earthquake information is sent to many clients in the area.
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International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
Start
Start
Initialization of the system
Wait state
Acceleration exceeding
the threshold value
Receive data
N
N
Y
Y
Transmitted the value to server
Data recording 2 seconds
Calculation of intensity values
Intensity exceeding the
threshold value
N
Transmitted the data array to server
Y
The number of
measuring points beyond
the intensity>N
N
Y
Start the emergency device
Figure 4. Software Flow Chart
5.2. Processing of the server
Each detailed operation is represented as follows:
(5) A regional server maintains a standby state until much of data is received. On this state,
the server program preserve data sent from clients to DB.
(6) When the number of data reception reaches gets over a threshold, the server program
starts a decision process of seismic intensity using received data in DB.
(7) When the server program judged that a big earthquake happened, an alarm is sent to many
clients.
(8) After the first alarm was dispatched, the server program continues to receive data at the
fixed interval from many clients, and sends alarms which raised accuracy gradually.
6. System verification
6.1. Monitoring node test
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International Journal of Internet of Things and Big Data
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Fixed the monitoring node and standard accelerometer on the vibration table at the same
time. Changed the frequency of the vibration table, recorded the acceleration of monitoring
nodes and standard accelerometer, then obtained the normalized amplitude-frequency
characteristics monitoring node [5] [6][7]. Test results are shown in Table 2.
As seen from the results, the data collected by calibrated intensity meter is accurate, and it
can be used as the basis data for calculating the intensity.
Table 2. Test results of amplitude-frequency characteristics
Frequency (Hz)
X-axis/Standard sensor
Y-axis/Standard sensor
Z-axis/Standard sensor
1.0
1.001
1.000
1.001
3.0
0.999
1.001
1.001
10.0
1.000
1.001
1.000
30.0
1.001
1.000
1.000
6.2. Data transmission test
Set the trigger threshold as 0.01g on the server, fix one monitoring node on the vibration
table and make the vibration table simulate seismic waves, and observe whether the server
receives and records vibration waveform.
Figure 5. Simulated earthquake wave
After testing, the system can be triggered, and it can record data.
6.3. Intensity quick report test
The vibration table is used for quick report test. Fix three monitoring nodes on the
vibration table at the same time, and make the vibration table simulate seismic waves, and
observe whether the system generates an alarm or not. After test, the software responds
quickly, and it can quickly give intensity values [8].
7. Summary
The research on the key technology of intensity quick report, including ground vibration
monitoring, data transmission, and intensity calculation and so on was carried out. The
present study completed the design work, including the design of ground motion detection
device, data transmission and the design of intensity calculation model, and finally conducted
the relevant analysis and experiment.
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Copyright ⓒ 2016 GV School Publication
International Journal of Internet of Things and Big Data
Vol. 1, No. 1 (2016)
References
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instrument for the lifeline engineering: low cost embedded system solution”, 2010 International
Conference on Intelligent Computation Technology and Automation.p242-245
[2] T. Uga, “An Emergency Earthquake Warning System Using Mobile Terminals with a Built-in
Accelerometer”, 2012 12th International Conference on ITS Telecommunications.p837-842.
[3] Y. Li, H. Fang, “Modeling and Analysis of Networked Control Systems with Network-Induced
Delay and Multiple-Packet Transmission”, ICARCV 2008, p 494-498, 2008.
[4] S. Hu, “Principles of Automatic Control”, Fourth edition. Beijing: National Defense Industry
Press.2001.2:20~21
[5] F. Yamazaki, Y. Shimizu, W. Nakayama, “New development of super-dense seismic monitoring
and damage assessment system for city gas networks,” Structural Safety and Reliability, p. 1-8,
2001.
[6] Shake Table II of ,
http://www.quanser.com/english/html/earthquake/fs_overview.htm
[7] P2P earthquake Information,
http://www11.plala.or.jp/taknet/p2pquake/
[8] Z. Wu, “Concurrent Product Design and Seismic Analysis for Fuel Handling Equipment”, 2010
IEEE.p200-204.
Author
Yu-Laibao, (1984- ), mainly engaged in instrumental research.
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