CN103616719A - Microseism acquisition device and method with noise identification and self-adaptive amplification functions - Google Patents
Microseism acquisition device and method with noise identification and self-adaptive amplification functions Download PDFInfo
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Abstract
The invention provides a microseism acquisition device and method with the noise identification and self-adaptive amplification functions. The device is composed of a microseism sensor, a signal conditioner, a power supply unit, a gain adjustment unit, a data acquisition unit, a noise identification unit, a storage unit, a communication unit and the like. The microseism is used for picking up microseism signals, the data acquisition unit converts the picked up microseism signals into digital signals, and the storage unit is used for storing the digital signals locally or uploading the digital signals through the communication control unit. For the acquired microseism signals, the gain of a front end amplifier can be changed in a self-adaptive mode through the gain adjustment unit, and thus the detected signals can be amplified selectively; noise signals can be identified through the noise identification unit and then suppressed. The device and method aim to improve the signal to noise ratio of the acquired microseism signals through an instrument itself, signals with a high signal to noise ratio are processed, and thus parameters relevant to microseism are extracted.
Description
Technical field
The present invention relates to a kind of microearthquake harvester, particularly a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function, just can improve certain signal to noise ratio (S/N ratio) in the time of for microearthquake signals collecting.
Background technology
Micro seismic monitoring is that current industrial circle is used for carrying out safety monitoring and prevents and reduces natural disasters and monitor effective method, so the quality of microseism data acquisition quality directly has influence on the effect of monitoring.In the occasion of carrying out micro seismic monitoring, microseismic signals is picked up by wave detector, and is converted to electric signal and sends into harvester.The signal collecting during micro seismic monitoring is all feeble signal, and amplitude is less, and harvester must amplify it, sometimes must amplify several thousand times and just can record.Gaining while amplifying owing to can not determining in advance that microseismic signals amplitude to be collected is big or small, thereby also just most suitable gain cannot be set.If take to arrange fixed gain, amplify, if microseismic signals is fainter, the microseismic signals after may amplifying also cannot be collected; If microseismic signals is more intense, the microseismic signals after may amplifying has exceeded the range of AD conversion in acquisition instrument, and microseismic signals just can not be collected completely.Therefore require the instrument that records microseismic signals not only to have very large enlargement factor, also must, according to the strong and weak enlargement factor that automatically changes in time of microseismic signals, the microseismic signals of various amplitude size all be recorded without distortion.
In microseismic signals gatherer process, because signal to be collected is fainter, and corresponding environmental interference is also larger, is inevitably mixed with various random interfering signals in the signal that acquisition instrument collects.If undesired signal is not identified, unified amplifies according to fixed gain, may occur noise signal to amplify, and useful signal does not have the extreme case amplifying.
Summary of the invention
The object of this invention is to provide a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function, use this device can automatically identify noise signal when gathering microseismic signals, noise signal is suppressed, can, according to the adjustment gain enlargement factor of the signal adaptive collecting, the dynamic range of acquisition instrument prime amplifier be matched all the time with the dynamic range of AD simultaneously.When gain is adjusted, adopt fast, slow two stages to adjust data gain.And adopt cross correlation algorithm to microseismic signals and interference noise is distinguished and suppress being judged as the signal of noise, reach the object that improves Signal-to-Noise.
The invention has the advantages that: due to when microseismic signals gathers, on instrument, just carry out noise identification and compacting, therefore can improve within the specific limits the signal to noise ratio (S/N ratio) of microearthquake data.
The present invention is mainly comprised of microseismic sensors (1), signal condition (2), gain adjusting unit (3), data acquisition unit (4), noise recognizing unit (5), storage unit (6), communication unit (7), power supply unit (8).Microseismic sensors (1) is sent into data acquisition unit (4) through signal condition (2) and gain adjusting unit (3) after picking up microseismic signals, by analog-signal transitions, it is digital signal, and carry out this locality storage or pass through communication unit (7) by storage unit (6), digital signal is uploaded to centralized control center, digital signal after gain adjusting unit (3) is changed data acquisition unit (4) judges, and then realize adaptive adjustment and gain, selectively microseismic sensors (1) being picked up to microseismic signals amplifies, digital signal after noise recognizing unit (5) is changed data acquisition unit (4) is carried out computing cross-correlation, according to the result after simple crosscorrelation, for the signal that is judged as noise, reduce gain multiple, play the object of compacting noise, for being judged as microseismic signals, improve gain enlargement factor, and in conjunction with gain adjusting unit (3), signal adaptive is amplified.
The invention is characterized in, described microseismic sensors (1) is MEMS acceleration transducer.
The invention is characterized in and it is characterized in that, described gain adjusting unit (3) comprises variable gain amplifier (301), fast adjustment unit (302) and slow adjustment unit (303), wherein the model of variable gain amplifier (301) is AD8231, can realize 8 gain per stages and amplify, be respectively 1,2,4,8,16,32,64 and 128 times.
The invention is characterized in, in described data acquisition unit (3), adopt the ADC of 24, its model is ADS1274, can realize the sampling of 0.1ms, 0.2ms, 0.5ms, 1.0ms and 2.0ms.
The invention is characterized in and it is characterized in that, described noise recognizing unit (4) adopts software to realize, and the carrier that software is realized is DSP, adopts TMS320VC5416DSP.
The invention is characterized in, can carry out noise identification to the microseismic signals of picking up, and noise signal is suppressed.
The invention is characterized in when carrying out microseismic signals collection, harvester self can determine according to the size of sampled signal the size of gain.
The invention is characterized in the microseismic signals by detecting, device can be to the microseismic signals identification of picking up.For noise signal, suppress, for microseismic signals, just amplify.
The invention is characterized in that described adaptive gain amplifies and noise identification is all to pass through Digital Realization.
Compared with prior art, the invention has the advantages that:
Signal for microseismic sensors input can adaptively amplify, rather than with in the past the same, adopts fixing yield value, noise is identified simultaneously, the extreme phenomenon of having avoided noise to amplify.
Microseism harvester of the present invention adopts digital adaptation gain algorithm.Algorithm, by the input signal of acquisition instrument is carried out to adaptive gain adjustment, matches the dynamic range of acquisition instrument prime amplifier all the time with the dynamic range of AD.When gain is adjusted, adopt fast, slow two stages to adjust data gain.And adopt related algorithm to distinguish microseismic signals and interference noise, according to the result of distinguishing, compacting noise signal, has improved the data signal to noise ratio (S/N ratio) collecting.
Accompanying drawing explanation:
Fig. 1 is general function structured flowchart of the present invention.
Fig. 2 is noise identification of the present invention and adaptive gain realization flow figure.
Fig. 3 is the adaptive gain figure with noise identification of the present invention.
Fig. 4 is adaptive gain figure of the present invention.
Output waveform after the adjustment of Fig. 5 adaptive gain.
Fig. 6 microseismic signals becomes noise the output waveform after noise identification.
Fig. 7 noise becomes microseismic signals and output waveform after noise identification.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail:
As depicted in figs. 1 and 2, when in use, microseismic sensors (1) is embedded in region to be monitored, before system does not have life's work, utilize this device to gather ground unrest, gather N cycle and data are preserved as y (N)={ y (1), y (2),, y (N) } and sequence.
During micro seismic monitoring, 1 cycle data collecting is x={x (1), x (2) ..., x (n) } and sequence.
When monitoring system is formally used, when microseismic sensors (1) is picked up after microseismic signals, through gain adjusting unit (2) and data acquisition unit (3), be converted to digital signal, the signal collecting first and the ground unrest collecting above carry out computing cross-correlation, by the absolute value of cross-correlation coefficient, parameter value as the noise identification in next cycle, when next cycle samples, the signal collecting and Noise gate limit value compare, if be greater than threshold value, think noise signal, reduce the reference value that adaptive gain amplifies, stop slow stage gain adjusts simultaneously, if be less than threshold value, think microseismic signals, recover the reference value of adaptive gain amplification or be set to a new reference value, then moving slow stage gain adjusts, make it meet gradually the requirement of AD gain.
As shown in Figure 3, in microseismic signals gatherer process, because signal to be collected is fainter, and corresponding environmental interference is also larger, is inevitably mixed with various random interfering signals in the signal that acquisition instrument collects.If undesired signal is not identified, amplifications that gain of the unified gain algorithm according to above-mentioned, may occur noise signal amplification, and useful signal does not have the extreme case of amplification.
Simple crosscorrelation is described two different random signals in any two degrees of correlation between value in the same time not, therefore utilizes the feature of microseismic signals and random noise, by computing cross-correlation, reaches identification random noise, extracts the detection method of microseismic signals.
During device normal operation, periodic signal x (n) sequence collecting first and ground unrest y (N) sequence collecting above carry out respectively computing cross-correlation, ask for the mean value Rav of the absolute value of cross-correlation coefficient, compare with given Noise gate limit value, if be greater than threshold value, think noise signal, at this moment reduce the level reference value E that adaptive gain amplifies
ref, ride gain regulating system reduces gain, noise signal is suppressed; If be less than threshold value, show to have detected microseismic signals, reference voltage E
refmust revert to original value, or change into other value.Value after adjustment finishes is all used in next cycle.Because noise signal has randomness, for being all judged as the signal of noise within continuous several cycles, at this moment adopt the signal update in these cycles as the background signal of noise.
As shown in Figure 4, being input to gain between A/D conversion and should meeting and can not make A/D overflow of microseismic signals, meets these two requirements of conversion accuracy again.Requirement while working in order to meet microseism acquisition system, the dynamic range of the expansion microseism harvester of maximum magnitude, the present invention proposes a kind of gain algorithm, and this algorithm is divided into fast adjustment and two stages of slow adjustment by gain adjustment process.In the fast adjusting stage, adopt large yield value that the microseismic signals rapid adjustment detecting is arrived to rational amplitude range, thereby significantly shorten the time that gain is adjusted; For there will be some temporary impact signals in gatherer process, cause large gain adjustment after A/D overflow, at this moment adopt the slow adjusting stage, adopt little yield value to carry out meticulous adjusting, the input data amplitudes of A/D is locked in a less fluctuation range.Formula (1) has provided the gain algorithm in two stages:
For the E in formula (1)
ref, use the average amplitude of working as top n signal as standard.Therefore, gain the adjusting stage soon, herein according to average amplitude and the reference value comparison of the data of sampling, the foundation of adjusting as fast gain.The fast gain adjusting stage, adopt each cycle to adjust once.Use the sampled value in last cycle, by cumulative, ask for average amplitude, execution formula (1) obtains adjusting soon yield value.
Concrete steps are:
1) gather microearthquake signal, obtaining one-period sequence is x (k), wherein k=1,2,3 ... n, the sampled point quantity that n is one-period;
2) calculate the average amplitude of microearthquake signal
3) according to formula (1) calculated gains, and the microearthquake signal after being amplified
Due to the G drawing according to formula (1)
1value is 2 progression not necessarily, controls pin A for 3 of AD8231 simultaneously
2a
1a
0must provide corresponding level, therefore, G
1value and level and the gain of controlling pin by following principle, choose:
If 0≤G
1≤ 1, A
2a
1a
0=000, actual gain is 1;
If 2≤G1≤3, A
2a
1a
0=001, actual gain is 2;
If 4≤G1≤6, A
2a
1a
0=010, actual gain is 4;
If 7≤G1≤12, A
2a
1a
0=011, actual gain is 8;
If 13≤G1≤24, A
2a
1a
0=100, actual gain is 16;
If 25≤G1≤48, A
2a
1a
0=101, actual gain is 32;
If 49≤G1≤96, A
2a
1a
0=110, actual gain is 64;
If 97≤G1≤128, A
2a
1a
0=111, actual gain is 128
Note: high level is exported in 1 representative above, and 0 represents output low level.
The fast adjusting stage, each cycle is adjusted once.Use the sampled value in last cycle, by asking for signal averaging amplitude, execution formula (1) obtains the fast gain of adjusting;
Slow gain stage, the foundation that data after too fast gain is adjusted are adjusted as slow gain, data after adjusting are relatively formed to judgement with reference value again, by LMS iterative algorithm, automatically change in real time slow yield value, thereby reach the object of resonance-amplifier input signal amplitude.Y (k) the substitution formula (2) that formula (1) is drawn draws the error signal that gain is adjusted, then according to formula (3) to G
2(k) adjust, make y (k) be tending towards V (k);
e(k)＝V(k)-G
2(k)y(k) （2）
G
2(k+1)＝G
2(k)+k
ge(k) （3）
In formula: 0<Kg<1 is iteration step length, use the gain Kg of LMS process of iteration calculating along with error e changes continuously, constantly adaptive updates.The method is the subtle change of tracking signal in real time, and adaptive gain regulating Kg guarantees that the amplitude of output signal meets the demands.
Accumulation adjustment through LMS adaptive gain algorithm, is finally adjusted to input signal amplitude peak peak value near reference level, thereby guarantees that A/D input signal amplitude is constant.
Above-mentioned gain algorithm has guaranteed to depart from when larger when input signal amplitude and standard value, can by gain, be adjusted its amplitude is adjusted to suitable scope rapidly; When signal amplitude value and standard value relatively approach, gain is finely tuned or the adjustment that do not gain.Like this can the speed of convergence of system faster in situation fluctuation as far as possible little.
The effect that noise identification self-adaptation of the present invention increases function refers to Fig. 5, Fig. 6 and Fig. 7.Fig. 5 a is the microseismic signals of simulation, Fig. 5 b is the output waveform adopting separately after fast gain is adjusted, as can be seen from the figure in first cycle, because system brings into operation, its gain adjustment is carried out according to fixed value, after 1.2s, according to the mean value that calculates the last cycle, and bring fast gain adjustment into and carry out computing, generate new gain, at 9.6s, due to input signal sudden change, under the effect of adjusting in fast gain, after the input signal adjustment between 9.6～10.8s, surpassed desired value; After 19.2s, input signal suddenlys change again, after the input signal adjustment between 19.2～20.4s, has also surpassed desired value.Input signal peak swing after 20.4s is adjusted to desired value again.Fig. 5 c is the output signal after common adjustment of fast, slow gain, can find out, due to the effect that slow gain is adjusted, in sign mutation, the part that fast gain adjustment can not respond rapidly, after slow gain is adjusted, also approaches desired value substantially.
Fig. 6 is varied to pure noise while being the microseismic signals input of simulating, and through identification post-simulation output waveform.From Fig. 6 a, can find out, microseism input signal becomes pure noise after 9.6s; From Fig. 6 b, can find out, if simple, adopt fast, slow gain to adjust input signal, not only microseismic signals has obtained amplification, and noise signal has obtained amplification too; Fig. 6 c is the waveform adopting again after noise identification after speed, gain are adjusted, can see when microseismic signals becomes noise after 9.6s, through 2.4s, after 12s, due to the execution of noise identification algorithm, noise is identified, has changed reference value, make yield value obtain adjustment, reduced the amplification to pure noise.
Fig. 7 has carried out emulation to being changed to microseism input signal from pure noise.Along with the transformation of pure noise to microseismic signals, the result of simple crosscorrelation correlation computations has surpassed the threshold value of the detection of noise and input signal.Illustrate and microseismic signals detected, reference value E
refbe adjusted.Adaptive gain system, by calculating suitable gain, is amplified microseismic signals.From Fig. 6 and 7, can find out, if indiscriminate amplification, noise also will be by unconfined amplification.After the adaptive gain algorithm of employing with noise identification, the amplitude peak of microseismic signals is adjusted to expectation value substantially, although noise is also exaggerated, the amplitude of amplifying is well below microseismic signals.This illustrates this adaptive gain scheme, can fast and effeciently complete adaptive gain and regulate.
Claims (9)
1. microearthquake harvester and a method with noise identification and self-adaptation enlarging function, it is characterized in that, this device comprises microseismic sensors (1), signal condition (2), gain adjusting unit (3), data acquisition unit (4), noise recognizing unit (5), storage unit (6), communication control unit (7), power supply unit (8), microseismic sensors (1) is sent into data acquisition unit (4) through signal condition (2) and gain adjusting unit (3) after picking up microseismic signals, by analog-signal transitions, it is digital signal, and carry out this locality storage or pass through communication unit (7) by storage unit (6), digital signal is uploaded to centralized control center, digital signal after gain adjusting unit (3) is changed data acquisition unit (4) judges, and then realize the adaptive gain adjustment of next periodic sampling data, selectively microseismic sensors (1) being picked up to microseismic signals amplifies, the background signal gathering before digital signal after noise recognizing unit (5) is changed data acquisition unit (4) and use carries out computing cross-correlation, according to the result of the mean value of cross-correlation coefficient absolute value and the comparison of Noise gate limit value, for the signal that is judged as noise, reduce gain multiple, play the object of compacting noise, for being judged as microseismic signals, improve gain enlargement factor, and in conjunction with gain adjusting unit (3), signal adaptive is amplified.
2. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, is characterized in that, described microearthquake harvester adopts analog-and digital-hybrid circuit to form.
3. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, is characterized in that, described microseismic sensors (1) is MEMS acceleration transducer.
4. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, it is characterized in that, described gain adjusting unit (3) comprises variable gain amplifier (301), fast adjustment unit (302) and slow adjustment unit (303), wherein the model of variable gain amplifier (301) is AD8231, can realize 8 gain per stages and amplify, be respectively 1,2,4,8,16,32,64 and 128 times.
5. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, it is characterized in that, described data acquisition unit (4) comprises AD conversion (401) and data acquisition (402), wherein AD conversion (401) adopts the ADC of 24, its model is AD1274, can realize the sampling of 0.1ms, 0.2ms, 0.5ms, 1.0ms, 2.0ms, 4.0ms, data acquisition (402) adopts numerical approach to realize.
6. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, it is characterized in that, described noise recognizing unit (5) adopts numerical approach, utilizes software to realize, the carrier that software is realized is DSP, adopts TMS320VC5416DSP.
7. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, is characterized in that, the noise identifying can be pressed.
8. a kind of microearthquake harvester and method with noise identification and self-adaptation enlarging function according to claim 1, it is characterized in that, adaptive gain amplifies and noise identification can be adjusted online, fast response time is generally to utilize last cycle sampled data to adjust gain and the noise identification threshold value in next cycle.
9. adaptive gain method of adjustment according to claim 4, it is characterized in that, adaptive gain adjustment is divided into fast adjustment and two stages of slow adjustment, the fast adjusting stage, adopt large yield value that the microseismic signals rapid adjustment detecting is arrived to rational amplitude range, the temporary impact signal occurring in gatherer process, after causing fast gain adjustment, A/D overflows, adopt the slow adjusting stage, adopt little yield value to carry out meticulous adjusting, the input data amplitudes of A/D is locked in a less fluctuation range.Concrete steps:
1) gather microearthquake signal, obtaining one-period sequence is x (k), wherein k=1,2,3 ... n, the sampled point quantity that n is one-period;
2) calculate the average amplitude of microearthquake signal
3) according to formula (1) and formula (2) calculated gains, and the microearthquake signal after being amplified;
G
1＝int(V
ref/V) （1）
y(k)＝G
1×x(k) （2）
Due to the G drawing according to (1) formula
1value is 2 progression not necessarily, controls pin A for 3 of AD8231 simultaneously
2a
1a
0must provide corresponding level, therefore, G
1value and level and the actual gain of controlling pin by following principle, choose:
If 0≤G
1≤ 1, A
2a
1a
0=000, actual gain is 1;
If 2≤G1≤3, A
2a
1a
0=001, actual gain is 2;
If 4≤G1≤6, A
2a
1a
0=010, actual gain is 4;
If 7≤G1≤12, A
2a
1a
0=011, actual gain is 8;
If 13≤G1≤24, A
2a
1a
0=100, actual gain is 16;
If 25≤G1≤48, A
2a
1a
0=101, actual gain is 32;
If 49≤G1≤96, A
2a
1a
0=110, actual gain is 64;
If 97≤G1≤128, A
2a
1a
0=111, actual gain is 128;
Note: high level is exported in 1 representative above, and 0 represents output low level;
The fast adjusting stage, each cycle is adjusted once, uses the sampled value in last cycle, and by asking for signal averaging amplitude, execution formula (1) obtains the fast gain of adjusting;
4) slow gain stage, by the data after too fast adjustment and reference value comparison, by LMS adaptive algorithm, change in real time slow yield value, thereby reach resonance-amplifier input signal amplitude, y (k) substitution (3) that formula (2) is drawn draws the error signal that gain is adjusted, then according to formula (4) to G
2(k) adjust, make y (k) be tending towards V (k);
e(k)＝V(k)-G
2(k)y(k) （3）
G
2(k+1)＝G
2(k)+k
ge(k) （4）
Through the accumulation adjustment of LMS adaptive gain algorithm, input signal amplitude peak peak value is adjusted near reference level, guarantee that A/D input signal amplitude is constant, LMS adaptive algorithm is realized by software, and the carrier of realization is TMS320VC5416DSP.10. noise identification according to claim 6, it is characterized in that, the signal that adopts ground unrest and collect carries out computing cross-correlation, the increase of the reference level of amplifying according to the output control adaptive gain of cross-correlation coefficient absolute value and the comparison of Noise gate limit value or reduce, thereby noise is suppressed, and the method comprises the steps:
1) obtain the background noise data in N cycle and preserve, for y (N)=y (1), y (2) ... y (N) } sequence, during micro seismic monitoring, 1 cycle data collecting is x={x (1), x (2) ..., x (n) } and sequence;
2) calculate signal y(N) cross-correlation coefficient of sequence and x, ask for averaged R after absolute value
av;
3) compare cross-correlation coefficient absolute value mean value R
avif with Noise gate limit value R
av> threshold value, what show collection is noise signal, next cycle acquisition system must reduce gain, reduces the reference value E of adaptive gain system
refif, R
av< threshold value, shows to have detected microseismic signals, next cycle reference voltage E
refmust revert to original value, or change into other value;
4) after k periodic duty, be all judged as noise signal continuously, with the signal in this k cycle, replace ambient noise signal y (N) sequence above, reach the object of constantly noise being upgraded.
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| CN104570099A (en) * | 2015-01-29 | 2015-04-29 | 中国矿业大学 | Multi-point collected signal data recovery device and method of micro-seismic system |
| CN104749627A (en) * | 2015-03-23 | 2015-07-01 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Microseismic signal highlighting method based on similarity |
| CN105956526A (en) * | 2016-04-22 | 2016-09-21 | 山东科技大学 | Method for identifying a microearthquake event with low signal-to-noise ratio based on multi-scale permutation entropy |
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| CN108107472A (en) * | 2017-11-30 | 2018-06-01 | 中国石油天然气股份有限公司 | Seismic signal processing device and method |
| CN110703319A (en) * | 2019-09-26 | 2020-01-17 | 广东石油化工学院 | Microseismic event detection method and system based on Khichin-Einstein theorem |
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| CN108107472A (en) * | 2017-11-30 | 2018-06-01 | 中国石油天然气股份有限公司 | Seismic signal processing device and method |
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| CN110703319A (en) * | 2019-09-26 | 2020-01-17 | 广东石油化工学院 | Microseismic event detection method and system based on Khichin-Einstein theorem |
| CN110703319B (en) * | 2019-09-26 | 2021-06-11 | 广东石油化工学院 | Microseismic event detection method and system based on Khichin-Einstein theorem |
| CN113609971A (en) * | 2021-08-04 | 2021-11-05 | 广州威拓电子科技有限公司 | Method, device and equipment for inspecting microseism observation equipment and storage medium |
| CN113609971B (en) * | 2021-08-04 | 2024-07-05 | 广州威拓电子科技有限公司 | Method, device, equipment and storage medium for checking microseism observation equipment |
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