TWI459019B - On-site instant earthquake analysis system and method, and storage medium thereof - Google Patents

Description

Instant earthquake analysis system and method and storage medium thereof

The present invention relates to seismic prediction techniques, and more particularly to an in situ seismic analysis system and method thereof.

One of the theory of earthquake prediction technology is that the P wave (P-wave, primary wave or pressure wave) wave velocity is greater than the physical property of the S wave (secondary wave) (P wave is about 6-7 km/s; S wave is about 3- 4 km/s), in the event of an earthquake, measure the small vibrations caused by P waves to estimate the impact of subsequent S waves. The P wave is a kind of sparse wave or longitudinal wave. It is also one of the body waves transmitted through the interior of the Earth during an earthquake. The direction of vibration of the medium is parallel to the direction of transmission of the seismic energy. The P wave has the fastest propagation speed. But the destructive power is not as good as the S wave. The speed of another body wave S wave is second only to the P wave. The S wave belongs to the Shear Wave or the transverse wave. That is, the vibration direction of the medium is perpendicular to the transmission direction of the seismic energy, and the amplitude can reach the P wave. Several times. Therefore, the large earthquake amplitude of the S wave and the shearing effect on the transmission path during the transmission often bring about a major disaster.

Taiwan is at the junction of the Eurasia plate and the Philippine Sea plate and is also part of the Pacific Rim seismic zone, resulting in frequent earthquakes. The Central Meteorological Bureau has set up seismographs throughout the whole station. Through the joint calculation of several stations, high-precision seismic-related parameters can be obtained and each warning area can be informed. This mechanism can be regarded as a “wide-area” strong earthquake early warning system. . However, the wide-area strong earthquake early warning system is limited by the data collection and calculation time limit. Although it can reach high precision, it takes too long, and it can not provide effective warning in the near-shock area (within 50 km from the earthquake). For example, the seismic observation network built by the Central Meteorological Bureau of Taiwan takes 22 seconds to conduct the epicenter positioning and earthquake scale estimation. If only the speed difference between the P wave and the S wave is considered, and the geological and site effects are ignored, the system is for the epicenter. Early warning capabilities are available only in areas 70 km away from the station observation group. However, the earthquake shock wave near the epicenter area is higher than other areas, relying on such wide-area strong earthquake early warning system, and can not achieve the effect of pre-warning, escape and evacuation.

In addition, although existing studies can provide specific calculus theory for seismic wave prediction and simulation, these theories are applied in the field-type earthquake prediction, lacking a large number of experimental verification and correction, and can not achieve the expected accuracy. Furthermore, for accurate prediction of seismic parameters using short-term window data, there is currently no suitable hardware architecture suitable for signal processing and computing requirements of local earthquake prediction. The general computer system cannot properly process signals or provide immediate high-level computing performance. .

In view of the problems of the prior art, an embodiment of the present invention provides an on-the-spot seismic real-time analysis system for instantly analyzing an earthquake detected at a detection location to detect an earthquake at a detection location. A shear wave. The system includes a signal pre-processing module and an embedded computing host. The signal pre-processing module receives the acceleration signal of the initial wave received at the detection location and performs a hardware pre-processing on it. The embedded computing host receives the acceleration signal from the signal pre-processing module to calculate the peak surface acceleration of the shear wave. The hard-processed acceleration signal is converted into the surface velocity of the initial wave and the surface displacement to obtain a peak surface displacement in a first time window. The embedded computing host calculates the earthquake rupture time parameter by the surface velocity and the ground displacement in a second time window, and calculates the earthquake scale of the earthquake. The embedded computing host calculates a epicenter distance based on the peak surface displacement and the earthquake scale, and calculates the peak surface acceleration of the seismic shear wave at the detection location according to the earthquake scale and the epicenter distance.

In another embodiment of the present invention, an on-the-spot seismic real-time analysis method is provided for instantly analyzing an detected arrival wave of an earthquake at a detection location, the method comprising: accelerating the acceleration of the detection location The signal is subjected to hardware preprocessing; the converted acceleration signal is the surface velocity of the initial wave and the surface displacement; the peak surface displacement in the first time window is obtained; and the earthquake rupture time parameter is calculated by the surface velocity and the surface displacement in the second time window, And calculate the earthquake scale; calculate the epicenter distance according to the peak surface displacement and the earthquake scale; and calculate the peak surface acceleration of the shear wave of the earthquake at the detection location according to the earthquake scale and the epicenter distance.

In another embodiment of the present invention, a computer readable storage medium is provided, in which a plurality of computer executable instructions are stored; when the computer executable instructions are read and executed by a local earthquake analysis system, The local-type seismic real-time analysis method described in the foregoing embodiments is performed. The in-situ earthquake real-time analysis system includes a signal pre-processing module and an embedded computing module. The method comprises: performing hardware pre-processing on the acceleration signal captured at the detection location; converting the acceleration signal to the surface velocity of the initial wave and the surface displacement; obtaining the peak surface displacement in the first time window; Calculate the earthquake rupture time parameter by the surface velocity and surface displacement, and calculate the earthquake scale; calculate the epicenter distance according to the peak surface displacement and the earthquake scale; and calculate the peak surface of the shear wave of the earthquake at the detection location according to the earthquake scale and the epicenter distance Acceleration.

Based on the characteristics of the seismic signal and the obstacles encountered in the past analysis process, the following embodiments of the present invention provide several optimized hardware architectures and optimized operational procedures required for the local seismic analysis, so as to capture at a short time The D-wave (P-wave) data accurately predicts the peak surface acceleration of the shear wave (S-wave) at the detection location, achieving the immediate warning effect on the spot. In the present invention, the integrated design of the software hardware system, the selection of the hardware components, and the matching of different algorithms are essential, and a large amount of experimental data verification is required to obtain the local seismic real-time analysis system and method optimized by the present invention. According to the system and method of the present invention, if the earthquake-related parameters are calculated by using the 3 seconds data of the first wavefront detected by the station and an early warning is made, the warning range can be greatly increased from 70 km away from the epicenter, for example, It is 10-50 km away from the epicenter; however, the actual data is still limited by the actual hardware/software/firmness, the formation characteristics of the seismic wave transmission path, and other possible variables.

Please refer to FIG. 1 , which is a block diagram of a system architecture of a local earthquake real-time analysis system according to an embodiment of the present invention. The existing earthquake-based real-time analysis system 10 includes an embedded computing host 100 and a signal pre-processing module 200; wherein the signal pre-processing module 200 performs pre-processing of the original initial wave acceleration signal, and the embedded computing host 100 performs multiple algorithm calculation programs.

Since one of the objectives of the system design is to shorten the operation time of the seismic parameters for early warning, the hardware configuration must effectively reduce the computational burden of the arithmetic operation end. Depending on the actual hardware component configuration, in one embodiment, the embedded computing host 100 and the signal preprocessing module 200 can be connected in series with all necessary hardware components by a special motherboard, supplemented by appropriate bus and signal interfaces. (Connector) is implemented. In another embodiment, the embedded computing host 100 and the signal pre-processing module 200 can be implemented by separate hardware components, and then connected to the signal interface by a suitable signal cable.

In an embodiment, the acceleration signal of the earthquake arrival wave is a surface strong vibration instrument (not shown) disposed at a detection location. The location of the detection site can be densely populated or near important buildings; for example, the Kinemetrics EpiSensor Force Balance Accelerometer (model FBA ES-T) can be used to measure small vibrations on the surface. And output X, Y, Z three axial acceleration signals. The time interval at which the strong shock meter extracts the output acceleration signal can usually be set by itself, but in one embodiment, the appropriate extraction or output frequency is 200 times per second.

In FIG. 1 , the signal pre-processing module 200 has a filter circuit 210 and an offset value removal circuit 220 . The filter circuit 210 performs a hardware filtering process on the initial wave acceleration signal outputted by the strong shock meter provided at the detection location, that is, filtering the unnecessary environmental noise in the initial wave acceleration signal through the filter circuit 210, and reducing the back end requirement Analyze the amount of data and increase the accuracy of the analysis. The offset value removing circuit 220 performs a hardware removal offset value program on the initial wave acceleration signal, that is, the offset value removing circuit 220 performs offset adjustment on the initial wave acceleration signal to make the initial wave acceleration signal The base value returns to zero; an example is to take the average value of the initial wave acceleration signal of the long time window (for example, 9~11 seconds) as the signal offset correction parameter, that is, the offset signal or data can be offset corrected. .

In general, the signal pre-processing module 200 receives the plurality of initial wave acceleration signals captured at the detection location, and performs a hardware pre-processing on the hardware circuit. The wave acceleration signal is pre-processed with the signal. The hardware pre-processing may include a hardware filtering program and a hardware removal offset value program, or other hardware circuit executable signal processing program. However, since in the method of the present invention, the initial wave acceleration signal needs to be converted into Ground Velocity and Ground Displacement data of the initial wave, and the process requires an initial wave acceleration signal or data. The "integration" process is performed. Therefore, in order to further reduce the computational burden of the back-end embedded computing host 100, in one embodiment, the hardware pre-processing of the signal pre-processing module includes a hard volume subroutine. As shown in FIG. 2, the signal pre-processing module 200 in another embodiment may further include an integration circuit 230 for performing the foregoing hard volume division procedure on the initial wave acceleration signal, that is, for the initial wave. The acceleration signal performs hard volume division, and converts the initial wave acceleration signal into the surface velocity of the initial wave and the surface displacement; the subsequent embodiments and the fourth figure also have related descriptions.

In the first figure, the embedded computing host 100 has an arithmetic processor 110, a system memory 120, a storage unit 130, a signal interface 140, and a bus bar 150. The initial wave acceleration signal after the hardware pre-processing module 200 performs the hardware pre-processing is transmitted to the operation processor 110 through the signal interface 140 and the bus bar 150 for calculation. In this embodiment, the storage unit 130 can store any seismic data or data, and a plurality of necessary algorithm programs. The arithmetic processor 110 of the embedded computing host 100 can load the necessary algorithm program into the system memory 120 for performing. The operation of various seismic parameters. The plurality of algorithm programs to be executed by the foregoing operational processor 110 are part of the local seismic real-time analysis method of the present invention.

In an embodiment, the embedded computing host 100 can be implemented by a computer system based on a Disk Operating System (DOS); the disk operating system used can be Microsoft MS-DOS or other suitable version. An example used in an experiment is: "Micro-Box x86 Based Instant Control Platform" (Micro-Box) developed by (1) TeraSoft Inc., with (2) Math Works (The Math Works, Inc.) Simulink tool software as an algorithm program development tool.

Among them, the Micro-Box system of the Titanium Technology Model Micro-Box 3000 (PCI Interface (Peripheral Component Interconnect interface)) has the following main hardware specifications: Processor Celeron M 1GHz; system memory is 256MB DDR DRAM; storage unit can be 64MB Compact Flash card; standard PCI expansion bus. In other words, in one embodiment, the hardware portion of the embedded computing host 100 can be implemented by the Titanium Corporation model Micro-Box 3000.

The aforementioned Simulink tool software is a multi-domain simulation and model-based design tool developed by MathWorks for dynamic systems and embedded systems. In one embodiment, the algorithm program of the embedded computing host 100 is written in the Simulink tool software and executed in the DOS environment on the aforementioned Micro-Box system of Titans Technology Co., Ltd. to realize the local earthquake of the present invention. At least part of the analytical method. In other words, one or more of the algorithm programs of this embodiment must be executable in a DOS environment; that is, the arithmetic processor 110 of such an embedded computing host 100 must perform a DOS-based algorithm. program.

In another embodiment, the computing processor of the embedded computing host can have built-in memory, and each algorithm program required by the present invention can be written to the computing processor through a specific firmware editing platform. In the firmware, high-speed operations can be performed in the firmware execution mode. In other words, one or more of the algorithm programs of this embodiment must be executable in the firmware environment of the computing processor; that is, the computing processor 110 of such an embedded computing host 100 must execute in its own firmware. The required algorithm program. One example is the DS1103 PPC controller board of Germany dSPACE company. The various algorithm programs of the present invention can still be written by Simulink tool software, and finally converted into mechanical language to implant its arithmetic processor (1 GHz). In the firmware of the PPC 750GX, high-speed operation can be performed in the firmware execution mode.

For the algorithm program executed by the embedded computing host 100 and the local seismic real-time analysis method performed by the entire in-situ seismic real-time analysis system 10, please refer to the subsequent flowchart and related description.

Please refer to FIG. 3, which is a flow chart of a method for real-time analysis of a local earthquake in another embodiment of the present invention. Although the following is a sequence of steps and a flow chart for explaining the components of the present-day seismic analysis method; unless otherwise defined, there is no absolute procedural relationship between the components of the method of the present invention.

Referring to FIG. 1 and FIG. 3 together, in an embodiment of the present invention, the local seismic analysis method includes the following parts:

Step S310: Perform hardware pre-processing on the initial wave acceleration signal of one earthquake taken from a detection location. In this embodiment, the hardware pre-processing includes a hardware filtering process and a hardware removal offset value program, and the filter circuit 210 and the offset value removing circuit 220 of the signal pre-processing module 200 respectively capture the detected locations locally. The initial wave acceleration signal of the earthquake is processed; in one embodiment, the initial wave acceleration signal is captured at a frequency of 200 times per second.

The foregoing part is executed by the signal preprocessing module 200 of the local earthquake real-time analysis system, and the following part is executed by the arithmetic processor 110 of the embedded computing host 100.

Step S320: Converting the hard-preconditioned pre-acquisition wave acceleration signal into the surface velocity and the ground displacement of the initial wave. In this embodiment, an arithmetic operation program is executed by the arithmetic processor 110 of the embedded computing host 100 to convert the initial wave acceleration signal into the surface velocity and the ground displacement of the initial wave; if the processing is 200 initials per second The wave acceleration signal is used to calculate that the data output of the ground wave velocity and the surface displacement of the first wave is also about 200 values per second.

Step S330: Obtaining a Peak Ground Displacement (PGD) in the first time window. Since it is important to find the peak surface displacement PGD with the least amount of time, the first time window is defined as the time required to include at least one peak surface displacement; and the velocity of the initial wave P wave is 6-7 km/s (ie, the initial time) The wave period is about 6-7 seconds. Here, the first time window can be defined to be about 3-3.5 seconds. In other words, the first time window can be defined as 1/2 period of the first wave. Of course, the longer the time, the more complete the data, the first time window can be defined as the complete period of the initial wave to find a more accurate peak surface displacement PGD.

Step S340: Calculate an earthquake rupture time parameter τc by the surface velocity and the ground displacement in the second time window. Before the local earthquake real-time analysis system has sufficient computing power, steps S330 and S340 do not need to be distinguished, but can be processed in parallel. The calculation method of the earthquake rupture time parameter τc is:

Where v is the surface velocity and u is the surface displacement, both of which are functions of time t; t1 and t2 are the start and end times of the calculation, respectively. This formula refers to the 2008 Sensors Journal, titled "Development of an Earthquake Early Warning System Using Real-Time Strong Motion Signals" by Yih-Min Wu and Hiroo Kanamori. In an embodiment, the local earthquake real-time analysis system and method are set to continuously calculate the earthquake rupture time parameter τc, and can wait for the judgment of any earthquake event, save analysis and early warning time. Basically, the longer the second time window (ie, the time interval between t1 and t2), the more accurate the value is calculated across the border, but it also delays the earthquake warning time and reduces the evacuation time of the people. One of the trade-offs is t2-t1=6-7 seconds, and the second time window, that is, the difference between t2 and t1 is equal to one complete cycle of the initial wave. The meaning of the above formula 1 is to take the time interval of t1-t2, calculate the squared value of the surface velocity and the square value of the ground displacement, and then divide the two and open the square root as the denominator. Multiply by 2π to obtain the earthquake rupture time parameter τc.

Step S350: Calculating a seismic magnitude (Magnitude) of the earthquake. An example is the earthquake rupture time parameter τc, which is:

M=3.088*log(τc)+5.300 (Formula 2)

By substituting the earthquake rupture time parameter τc calculated in step S340 into the formula 2, the earthquake scale M can be obtained. The source of Formula 2 is also referred to the "Development of an Earthquake Early Warning System Using Real-Time Strong Motion Signals" published by Yih-Min Wu and Hiroo Kanamori in the 2008 issue of Sensors, but the following original formulas have been revised after long-term and extensive experiments. Formula II.

M _w =3.373logτ _c +5.787±0.412 (former formula)

Step S360: Calculate a epicenter distance according to the peak surface displacement and the earthquake scale. The epicenter distance (R) is defined as the distance between the aforementioned detection location (ie, the location of the above-mentioned strong seismograph) and the epicenter. In an implementation, the regression formula for the calculation of the epicenter distance R is as follows, with reference to the formula published by Yih-Min Wu. Substituting the peak surface displacement PGD obtained in step S330 and the earthquake scale M obtained in the second formula of step S350, the epicenter distance R can be obtained:

Log(PGD)=-3.801+0.722M-1.444*log(R) (Formula 3)

Step S370: Calculate a peak ground acceleration PGA (Peak Ground Acceleration) of the shear wave of the earthquake at the detection location according to the earthquake scale M and the epicenter distance R. Referring to the attenuation curve method of Jianwen Yu, the present embodiment uses the following formula 4 to calculate the peak surface acceleration PGA, as long as the seismic scale M obtained in the second step of step S350 and the epicenter distance R obtained in step S360 are substituted.

PGA=0.00284exp(1.73306M)[R+0.09994exp(0.77185M)] ^(-2.06392) (Formula 4)

According to the calculated peak surface acceleration PGA value, it can be directly judged whether the earthquake alarm of the local location of the detection location is issued, and the seismicity of the detection location can also be obtained. For example, according to China's earthquake grading, if the value of the peak surface acceleration PGA falls within the range of 80-250 gal, it means that when the shear wave of the earthquake reaches the detection location, the earthquake at the detection location will have a magnitude 5 earthquake; 250~400 gal is the sixth degree of earthquake.

Please refer to FIG. 4, which is a flow chart of a method for real-time analysis of a local earthquake in another embodiment of the present invention. In this embodiment, steps S430, S440, S450, S460, and S470 are the same as steps S330, S340, S350, S460, and S370 in FIG. 3, and the difference is that the integral operation program belongs to a high computational amount, time-consuming, and most The process of consuming the computing resource is removed, so that the integral computing program calculated by the original embedded computing module 100 is removed, and in step 410, the signal preprocessing module 200 performs a hard volume partitioning process, and the signal is preprocessed by the second image. The integration circuit 230 of the module 200 executes. In this way, the overall signal and data processing speed can be further accelerated.

Please refer to FIG. 5, which is a flow chart of a method for real-time analysis of a local earthquake in another embodiment of the present invention. In this embodiment, steps S510, S520, S530, S540, S550, S560, and S570 are the same as steps S310, S320, S330, S340, S350, S460, and S370 in FIG. 3, and the difference is that the fifth figure is more. Step S580 and step S590; step S570 performs a seismic prediction logic to initially determine whether the earthquake is a seismic event, and step S520 performs a preset early action. In various embodiments, step S580 can be set to be performed earlier or parallel to all other steps of embedded computing module 100. That is, other steps may be determined depending on the result of step S580, or whether the steps are still performed in parallel with the result of step S580. After all, with the prior art, step S580 is not 100% accurate. However, step S580 still has the effect of its early warning, and its implementation can still receive certain benefits.

The earthquake prediction logic in step S580 may be an Optimized Short Term Averaging over Long Term Averaging Method (Optimized STA/LTA Method; Optimized Short Term Averaging over Long Term Averaging Method).

The optimized long-term window average ratio method is described below. First, the three-axis seismic digital signal sequence is UD _n (vertical acceleration signal), NS _n (north-south acceleration signal) and EW _n (east-west acceleration signal), and the data sampling time is dT , which is short-term. The window mean STA (Short Term Averaging) is defined as shown in Equation 5:

among them

α=[( UD _n - UD _{n -1} ) ² +( NS _n - NS _{n -1} ) ² +( EW _n - EW _{n -1} ) ² ] ^1/2

m is the amount of data contained in the short-time window; k is the data amount ( n 1) after averaging the UD _n , NS _n and EW _n triaxial acceleration signals; the data sampling time length T _m of the short-time window is m * dT .

The long term Averaging (LTA) is defined as shown in Equation 6:

among them

β=[( UD _n - UD _{n -1} ) ² +( NS _n - NS _{n -1} ) ² +( EW _n - EW _{n -1} ) ² ] ^1/2

l is the amount of data contained in the long window

k is the amount of data ( n 1) after averaging the UD _n , NS _n and EW _n triaxial acceleration signals; the length of time T _l of the long window is l * dT .

The practical approach is to take the three-axis seismic acceleration signal of the long-term window (assuming T _l is 10 seconds) and the short-time window (assuming T _m is 0.4 seconds), and then take the sampling points of each axial direction and its adjacent unit sampling points. The acceleration difference is summed and squared, and the short-time window signal average (STA) and long-term window signal average (LTA) are obtained according to the length of the long-term window and the short-time window. When the ratio of the two reaches a certain threshold and continues to exceed the monitoring time (assuming 0.05 seconds), the earthquake can be determined as an earthquake event; if the earthquake event occurs, the ratio is less than the set threshold and continues to exceed the monitoring time (assuming 0.05) ~10 seconds), that is, the end of the earthquake event.

Compared with the traditional long- and short-time window average value method, the optimized long- and short-time window average value method of this embodiment has been optimized according to the empirical data of seismic observation of Taiwan Island.

After the earthquake prediction logic is performed in step S580 to initially determine whether the earthquake is an earthquake event, step S520 performs a preset early action. This pre-set early action may include: performing subsequent calculation steps, displaying early warnings on the system, and the like.

Please refer to FIG. 6A-6B. FIG. 6A is a flowchart of a real-time seismic analysis method according to another embodiment of the present invention; FIG. 6B is a Fourier amplitude of a primary wave and a shear wave in the embodiment of FIG. 6A. Frequency graph. For convenience of explanation, the detail fluctuations of the respective curves in Fig. 6B are flattened. Since the estimated seismic frequency of the shear wave is helpful for the seismic analysis of buildings or structures, the local-type earthquake real-time analysis system and method in this embodiment can further output the estimated seismic frequency of the shear wave. As a seismic analysis of buildings or structures.

In Fig. 6A, steps S610-S680 are the same as steps S310-S380 of Fig. 3, and the main difference is that in this embodiment, regardless of the surface velocity and the surface displacement, it is a hardware (integration circuit) or a software (integration operation program). In a manner, the local seismic real-time analysis method may further comprise: supplementing the acceleration signal of the first time window with a data amount required for a complete initial wave period to perform Fourier Transform (step S690), and correcting the initial wave The Fourier amplitude-frequency curve is used to obtain the Estimated Seismic Main Frequency of the shear wave (step S695). This two steps are performed by the arithmetic processor 110 of the embedded computing host 100 in the local seismic analysis system.

The method of supplementing the acceleration signal of the first time window with the amount of data required for a complete initial wave period is as follows. If the initial wave acceleration signal capture frequency is 200 times per second, the first time window is 3-3.5 seconds, the accumulated data volume is only about 600-700; and the initial wave P wave cycle is 6-7 seconds. The amount of data required is 1200-1400. One method of complementing the amount of data is to mirror the acceleration signal of the first time window, that is, to obtain a complete initial wave waveform period; to facilitate Fourier transform, in another embodiment, the data amount is complemented by 1024 Can be carried out.

The method of correcting the Fourier amplitude-frequency curve of the initial wave to obtain the estimated main frequency of the shear wave is to correct the Fourier amplitude-frequency curve of the initial wave to the initial wave Fourier amplitude-frequency curve of the 1/2 frequency. And using the 1/2 frequency initial wave Fourier amplitude-frequency curve as the estimated Fourier amplitude-frequency curve of the shear wave S wave, the estimated earthquake frequency of the shear wave can be obtained. The reliable basis for this method comes from long-term and a large number of experimental verifications. Please refer to FIG. 6B for analysis of the signals or data obtained by the system and method described in the foregoing embodiments of the present invention, and the measured preliminary waves are indicated by broken lines. The Fourier amplitude-frequency curve has a similar trend to the measured shear wave Fourier amplitude-frequency curve after being corrected to the initial wave Fourier amplitude-frequency curve of the 1/2 frequency. Therefore, the estimated seismic dominant frequency of the shear wave can be obtained by using the initial wave Fourier amplitude-frequency curve of the 1/2 frequency as the estimated Fourier amplitude-frequency curve of the shear wave S wave.

In combination with the above embodiments, the present invention provides an on-the-spot seismic real-time analysis method for instantly analyzing a detected arrival wave of an earthquake at a detection location, the method comprising: performing hardware for the acceleration signal captured at the detection location Pre-processing; the conversion acceleration signal is the surface velocity and surface displacement of the first wave; the peak surface displacement in the first time window is obtained; the earthquake rupture time parameter is calculated by the surface velocity and the surface displacement in the second time window, and the earthquake is calculated Scale; calculate the epicentral distance according to the peak surface displacement and the earthquake scale; and calculate the peak surface acceleration of the shear wave of the earthquake at the detection location according to the earthquake scale and the epicenter distance.

In another embodiment of the present invention, a computer readable storage medium, such as a data disc, a hard disk, a flash memory, a memory card, etc., is stored therein, and a plurality of computer executable instructions are stored therein; When the executable instructions are read and executed by the present-presence seismic real-time analysis system, the local-type seismic real-time analysis method described in the foregoing embodiments is executed. The in-situ earthquake real-time analysis system includes a signal pre-processing module and an embedded computing module. The method comprises: performing hardware pre-processing on the acceleration signal captured at the detection location; converting the acceleration signal to the surface velocity of the initial wave and the surface displacement; obtaining the peak surface displacement in the first time window; Calculate the earthquake rupture time parameter by the surface velocity and surface displacement, and calculate the earthquake scale; calculate the epicenter distance according to the peak surface displacement and the earthquake scale; and calculate the peak surface of the shear wave of the earthquake at the detection location according to the earthquake scale and the epicenter distance Acceleration.

However, the above is only the preferred embodiment of the present invention, and the scope of the present invention is not limited thereto; therefore, the simple equivalent changes and modifications made in accordance with the scope of the present invention and the contents of the invention are modified. All should remain within the scope of the invention patent.

10. . . Local earthquake immediate analysis system

100. . . Embedded computing module

110. . . Arithmetic processor

120. . . System memory

130. . . Storage unit

140. . . Signal interface

150. . . Busbar

200. . . Signal preprocessing module

210. . . Filter circuit

220. . . Offset value removal circuit

230. . . Integral circuit

1 is a block diagram of a system architecture of an existing earthquake-type real-time analysis system according to an embodiment of the present invention;

2 is a block diagram of a system architecture of another local earthquake-type real-time analysis system in another embodiment of the present invention;

3 is a flow chart of a method for real-time analysis of a local earthquake in another embodiment of the present invention;

4 is a flow chart of another real-time seismic analysis method in another embodiment of the present invention;

Figure 5 is a flow chart showing another method for real-time analysis of earthquakes in another embodiment of the present invention;

6A is a flow chart of another real-time earthquake analysis method in another embodiment of the present invention; and

Figure 6B is a Fourier amplitude-frequency plot of the first wave and the shear wave in the embodiment of Figure 6A.

10. . . Local earthquake immediate analysis system

100. . . Embedded computing module

110. . . Arithmetic processor

120. . . System memory

130. . . Storage unit

140. . . Signal interface

150. . . Busbar

200. . . Signal preprocessing module

210. . . Filter circuit

220. . . Offset value removal circuit

230. . . Integral circuit

Claims (20)

An on-the-spot seismic real-time analysis system that instantly analyzes a primary wave detected by a seismic at a detection location to predict a Shear Wave of the earthquake at the detection location, The system includes: a signal pre-processing module, receiving the complex acceleration signal of the initial wave at the detection location, and performing a hardware pre-processing; and an embedded computing host Receiving the acceleration signals from the signal pre-processing module to calculate a peak ground acceleration (Peak Ground Acceleration); wherein the acceleration signals pre-processed by the hardware are converted into the initial a complex surface velocity of the wave and a plurality of surface displacements to obtain a Peak Ground Displacement in the first time window; the embedded computing host further uses the surface velocity in the second time window The ground surface displacement calculates a Seismic Fracture Time Parameter and calculates a Seismic Magnitude of the earthquake; the embedded computing host according to the peak Surface displacement with the scale of the earthquake epicenter calculate a distance (Epicentral Distance), and in accordance with the scale of the earthquake epicenter distance, calculate the shear wave of the earthquake of the peak ground acceleration in the detection of place. The real-time seismic real-time analysis system according to claim 1, wherein the embedded computing host determines whether the earthquake is an earthquake event according to a seismic prediction logic. The present invention provides a real-time seismic analysis system according to claim 1, wherein the signal pre-processing module includes a filter circuit and an offset value removing circuit, and the filter circuit performs the hardware filtering process on the acceleration signals. The offset value removing circuit executes the hardware removal offset value program for the acceleration signals. The present invention provides an on-site seismic real-time analysis system, wherein the signal pre-processing module includes an integration circuit, and the integration circuit performs a hard volume division procedure on the acceleration signals to transmit the acceleration signals. Converted to the ground speed of the first wave and the displacement of the surface. The real-time seismic real-time analysis system according to claim 1, wherein the embedded computing host executes an integral operation program to convert the acceleration signals into the surface velocity of the initial wave and the surface displacement. The present invention provides an on-the-spot seismic real-time analysis system, wherein the embedded computing host includes at least one arithmetic processor in one firmware itself or in a disk operating system ( At least one algorithmic program is executed in the Disk Operating System environment to analyze the earthquake. The present invention provides an on-site seismic real-time analysis system as described in claim 1, wherein the first time window is defined as a period of the initial wave or a period of 1/2. The present invention provides an on-site seismic real-time analysis system as described in claim 1, wherein the second time window is defined as a period of the initial wave. An on-the-spot seismic real-time analysis method for instantly analyzing a detected arrival wave of a seismic at a detection location, the method comprising: performing a hardware pre-processing on the complex acceleration signal captured at the detection location; The acceleration signals are the complex surface velocity and the complex surface displacement of the initial wave; a peak surface displacement in a first time window is obtained; and the surface velocity in the second time window is calculated from the surface displacements An earthquake rupture time parameter, and thereby calculating a seismic scale of the earthquake; calculating a epicenter distance according to the peak surface displacement and the earthquake scale; and calculating a shear wave of the earthquake according to the earthquake scale and the epicenter distance One of the measured locations is the peak surface acceleration. The method for real-time analysis of a local earthquake according to claim 9 of the patent application, further comprising determining whether the earthquake is an earthquake event according to an earthquake prediction logic. The method for real-time analysis of a local earthquake according to claim 10, wherein the earthquake prediction logic includes an optimized short term Averaging over Long Term Averaging Method (Optimized STA/LTA Method; Optimized Short Term Averaging over Long Term Averaging Method) . The method for real-time analysis of a local type earthquake according to claim 9, wherein the hardware preprocessing comprises a hardware filtering program and a hardware removal offset value program. The method for real-time analysis of a local type earthquake according to claim 9, wherein the hardware preprocessing comprises a hard volume subroutine for converting the acceleration signal to the surface velocity of the initial wave and the displacement of the surface . The method for real-time analysis of a local earthquake according to claim 9, wherein the method further comprises performing an integral operation program to convert the acceleration signals into the surface velocity of the initial wave and the displacement of the surface. The method for real-time analysis of a local earthquake according to claim 9, wherein the method further comprises: adding the acceleration signal of the first time window to the amount of data required for completing a complete period of the initial wave to correct the initial wave. One of the Fourier amplitude-frequency curves yields one of the shear waves to estimate the dominant frequency of the earthquake. The method for real-time analysis of a local type earthquake according to claim 15 , further comprising mirroring the acceleration signal of the first time window to complement the amount of data required for the complete period of the initial wave. The method for real-time analysis of a local earthquake according to claim 15, wherein the Fourier amplitude-frequency curve of the primary wave 1/2 frequency is used as one of the shear waves to predict the Fourier amplitude-frequency curve. To obtain the estimated seismic frequency of the shear wave. The method for real-time analysis of a local type earthquake according to claim 9, wherein the first time window is defined as a period of the initial wave or a period of 1/2. The method for real-time analysis of a local type earthquake according to claim 9, wherein the second time window is defined as a period of the initial wave. A computer readable storage medium storing a plurality of computer executable instructions for performing an instant seismic analysis method for real-time analysis when the computer executable instructions are read and executed by a local earthquake real-time analysis system An earthquake detected at a detection location is one of the primary waves; wherein the local seismic real-time analysis system includes a signal pre-processing module and an embedded computing module; wherein the method includes: Performing a hardware pre-processing on the complex acceleration signals captured at the measurement location, converting the acceleration signals to the complex surface velocity and the complex surface displacement of the initial wave, and obtaining a peak surface displacement in the first time window, Calculating an earthquake rupture time parameter from the surface velocities in the two-time window and the surface displacements, and calculating a seismic magnitude of the earthquake, calculating a epicenter distance from the peak surface displacement and the seismic scale, and according to the earthquake scale From the epicenter distance, calculate the peak surface acceleration of one of the shear waves at the detection location.