CN103616719B - 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 microseism harvester, particularly to one kind, there is Noise Identification and self adaptation enlarging function
Microseism harvester and method, for certain signal to noise ratio just can be improved when microseism signals collecting.
Background technology
Micro seismic monitoring be current industrial circle for carrying out safety monitoring and monitoring most efficient method of preventing and reducing natural disasters, therefore
The quality of microseism data acquisition quality directly influences the effect of monitoring.In the occasion carrying out micro seismic monitoring, microseismic signals are passed through
Cymoscope picks up, and is converted to signal of telecommunication feeding harvester.The signal collecting during micro seismic monitoring is all small-signal, amplitude
Less, harvester must amplify to it, sometimes must put and several thousand times larger just can record.Carry out gain amplify when due to
Cannot be determined beforehand microseismic signals amplitude size to be collected, thus most suitable gain also just cannot be arranged.If taking setting
Fixed gain is amplified, if microseismic signals are fainter, the microseismic signals after may amplifying also cannot be collected；If microseism is believed
Number stronger, then beyond the range of AD conversion in acquisition instrument, microseismic signals cannot be by for microseismic signals after may amplifying
Collect completely.Therefore it is required that the instrument of record microseismic signals does not only have very big amplification it is necessary to can believe according to microseism
Number power changes amplification automatically in time, and the microseismic signals of various amplitude size are all recorded without distortion.
In microseismic signals gatherer process, because signal to be collected is fainter, and corresponding environmental disturbances are also larger,
Inevitably it is mixed with various random interfering signals in the signal that acquisition instrument collects.If do not known to interference signal
, ununified amplify according to fixed gain, it is possible that noise signal is amplified, and that useful signal does not amplify is extreme
Situation.
Content of the invention
It is an object of the invention to provide a kind of microseism harvester with Noise Identification and self adaptation enlarging function and
Method, using this device gather microseismic signals when can automatic identification noise signal, noise signal is suppressed, with
When can be according to the adjust gain amplification of the signal adaptive collecting so that the dynamic model of acquisition instrument preamplifier
Enclose and match with the dynamic range of AD all the time.In Gain tuning, adjust data gain using fast, slow two stages.And adopt
Cross correlation algorithm makes a distinction to microseismic signals and interference noise and the signal being judged as noise is suppressed, and reaches raising letter
The purpose of number signal to noise ratio.
It is an advantage of the current invention that：Due to, when microseismic signals gather, Noise Identification and pressure just being carried out on instrument
System, therefore can improve the signal to noise ratio of microseism data within the specific limits.
The present invention is mainly by microseismic sensors（1）, signal condition（2）, gain adjusting unit（3）, data acquisition unit
（4）, noise recognizing unit（5）, memory element（6）, communication unit（7）, power subsystem（8）Composition.Microseismic sensors（1）Pickup
To after microseismic signals through signal condition（2）And gain adjusting unit（3）Send into data acquisition unit（4）, analogue signal is turned
It is changed into digital signal, and pass through memory element（6）Carry out locally stored or pass through communication unit（7）, digital signal is uploaded
To centralized control center, gain adjusting unit（3）To data acquisition unit（4）Digital signal after conversion is judged, and then realizes
Adaptive adjust gain, selectively to microseismic sensors（1）Pick up microseismic signals to be amplified, noise recognizing unit
（5）To data acquisition unit（4）Digital signal after conversion carries out computing cross-correlation, according to the result after cross-correlation, for sentencing
The signal for noise that breaks then reduces gain factor, plays the purpose of compacting noise, for being judged as microseismic signals, then improves gain
Amplification, and combine gain adjusting unit（3）Signal adaptive is amplified.
It is a feature of the present invention that described microseismic sensors（1）It is MEMS acceleration transducer.
It is a feature of the present invention that it is characterized in that, described gain adjusting unit（3）Including variable gain amplifier
（301）, fast adjustment unit（302）With slow adjustment unit（303）, wherein variable gain amplifier（301）Model AD8231,
8 stage gains can be realized amplify, be 1,2,4,8,16,32,64 and 128 times respectively.
It is a feature of the present invention that described data acquisition unit（3）The middle ADC adopting 24, its model
ADS1274, it is possible to achieve the sampling of 0.1ms, 0.2ms, 0.5ms, 1.0ms and 2.0ms.
It is a feature of the present invention that it is characterized in that, described noise recognizing unit（4）Realized using software, software is realized
Carrier be DSP, using TMS320VC5416DSP.
It is a feature of the present invention that Noise Identification can be carried out to the microseismic signals picked up, and noise signal is suppressed.
It is a feature of the present invention that when carrying out microseismic signals collection, harvester itself can be according to sampled signal
Size determines the size of gain.
It is a feature of the present invention that the microseismic signals identification that pickup can be arrived by the microseismic signals detecting, device.
Noise signal is then suppressed, microseismic signals are just amplified.
It is a feature of the present invention that described adaptive gain amplifies and Noise Identification is all by Digital Realization.
Compared with prior art, it is an advantage of the current invention that：
For microseismic sensors input signal can adaptive amplify, rather than and in the past the same, using fixation
Yield value, be identified to noise simultaneously, it is to avoid the extreme phenomenon that noise amplifies.
The microseism harvester of the present invention adopts digital adaptation gain algorithm.Algorithm is by the input letter to acquisition instrument
Number carry out adaptive gain adjustment so that the dynamic range dynamic range phase with AD all the time of acquisition instrument preamplifier
Join.In Gain tuning, adjust data gain using fast, slow two stages.And using related algorithm to microseismic signals and interference
Noise makes a distinction, and according to the result distinguished, suppresses noise signal, improves the data SNR collecting.
Brief description：
Fig. 1 is the general function structured flowchart of the present invention.
Fig. 2 is Noise Identification and the adaptive gain flowchart of the present invention.
Fig. 3 is the adaptive gain figure with Noise Identification of the present invention.
Fig. 4 is the adaptive gain figure of the present invention.
Output waveform after the adjustment of Fig. 5 adaptive gain.
Fig. 6 microseismic signals become noise the output waveform after Noise Identification.
Fig. 7 noise become microseismic signals and after Noise Identification output waveform.
Specific embodiment
With reference to the accompanying drawings and detailed description the present invention is described in further detail：
As depicted in figs. 1 and 2, when in use, microseismic sensors（1）It is embedded in region to be monitored, do not have in system
Before life's work, using this device, background noise is acquired, gather N number of cycle and by data preserve for y (N)=
Y (1), y (2) ..., and y (N) } sequence.
During micro seismic monitoring, 1 cycle data collecting is x={ x (1), x (2) ..., x (n) } sequence.
When monitoring system formally uses, work as microseismic sensors（1）After picking up microseismic signals, through gain adjusting unit
（2）Data collecting unit（3）Be converted to digital signal, the background noise that the signal collecting collects first and above is carried out
Computing cross-correlation, the absolute value of cross-correlation coefficient, as the parameter value of the Noise Identification in next cycle, is carried out when next cycle
When sampling, the signal collecting and noise threshold are compared, if greater than threshold value then it is assumed that being noise signal,
Reducing the reference value that adaptive gain amplifies, stopping slow stage gain adjustment, if less than threshold value then it is assumed that being microseism simultaneously
Signal, recovers the reference value of adaptive gain amplification or is set to a new reference value, then runs slow stage gain and adjusts
Whole so as to gradually meet the requirement of AD gain.
As shown in figure 3, in microseismic signals gatherer process, because signal to be collected is fainter, and corresponding environment
Interference is also larger, is inevitably mixed with various random interfering signals in the signal that acquisition instrument collects.If not to interference
Signal is identified, and unified carries out gain amplification according to above-mentioned gain algorithm, it is possible that noise signal is amplified, and
The extreme case that useful signal does not amplify.
Cross-correlation describes degree of correlation between any two not value in the same time for two different stochastic signals, because
This utilizes the feature of microseismic signals and random noise, reaches identification random noise by computing cross-correlation, extracts microseismic signals
Detection method.
During device normal work, the background noise y that periodic signal x (n) sequence that collects collects first and above
(N) sequence carries out computing cross-correlation respectively, asks for meansigma methodss Rav of the absolute value of cross-correlation coefficient, with given noise gate
Value is compared, and if greater than threshold value then it is assumed that being noise signal, at this moment reduces the level reference value that adaptive gain amplifies
Eref, control gain adjusting system to reduce gain, noise signal suppressed；If less than threshold value, show to detect
Microseismic signals, reference voltage ErefOriginal value must be reverted to, or change into other values.Adjustment terminate after value all under
One cycle used.Because noise signal has randomness, for the signal being all judged as noise within continuously several cycles, at this moment
Using these cycles signal update as noise background signal.
A/D can neither be made to overflow, again as shown in figure 4, the gain being input between A/D conversion of microseismic signals should meet
Meet this two requirements of conversion accuracy.In order to meet the requirement during work of microseism acquisition system, the extension microseism of maximum magnitude is adopted
The dynamic range of acquisition means, the present invention proposes a kind of gain algorithm, and Gain tuning process is divided into fast adjustment and adjusts slowly by this algorithm
Whole two stages.In the fast metamorphosis stage, using large gain values, the microseismic signals detecting quickly are adjusted to rational amplitude model
Enclose, thus significantly shortening the time of Gain tuning；For some temporary impact signals occur in gatherer process, cause large gain
After adjustment, A/D overflows, and at this moment adopts the slow metamorphosis stage, is fine-tuned using little yield value, make the input data amplitude of A/D
It is locked in a less fluctuation range.Formula (1) gives the gain algorithm in two stages：
For formula（1）In Eref, it is used when the average amplitude of top n signal is as standard.Therefore, fast Gain tuning rank
Section, average amplitude and reference value herein according to the data of sampling compare, as the foundation of fast Gain tuning.Fast Gain tuning rank
Section, using each period modulation once.I.e. with the sampled value in previous cycle, ask for average amplitude by cumulative, execute formula（1）?
To fast adjust gain value.
Concretely comprise the following steps：
1）Collection microseism signal, obtaining a cycle sequence is x (k), and wherein k=1,2,3 ... n, n are a cycle
Sampled point quantity；
2）Calculate the average amplitude of microseism signal
3）Calculate gain, and the microseism signal after being amplified according to formula (1)
Due to the G drawing according to formula (1)1Value is not necessarily 2 series, simultaneously the 3 of AD8231 controlling switch A2A1A0Must
Corresponding level, therefore, G must be given1Value and the level of controlling switch and gain press following principle and choose：
If 0≤G1≤ 1, then A2A1A0=000, that is, actual gain is 1；
If 2≤G1≤3, A2A1A0=001, that is, actual gain is 2；
If 4≤G1≤6, A2A1A0=010, that is, actual gain is 4；
If 7≤G1≤12, A2A1A0=011, that is, actual gain is 8；
If 13≤G1≤24, A2A1A0=100, that is, actual gain is 16；
If 25≤G1≤48, A2A1A0=101, that is, actual gain is 32；
If 49≤G1≤96, A2A1A0=110, that is, actual gain is 64；
If 97≤G1≤128, A2A1A0=111, that is, actual gain is 128
Note：1 represent output high level above, 0 represents output low level.
The fast metamorphosis stage, each period modulation is once.I.e. with the sampled value in previous cycle, by asking for signal averaging width
Value, executes formula（1）Obtain fast adjust gain；
Slow gain stage, using the data after too fast Gain tuning as slow Gain tuning foundation, by the number after adjustment
Judge according to comparing with reference value again to be formed, slow yield value is automatically changed in real time by LMS iterative algorithm, thus reach regulation amplifying
The purpose of device input signal amplitude.By formula（1）The y (k) drawing substitutes into formula（2）Draw the error signal of Gain tuning, further according to
Formula（3）To G2K () is adjusted so that y (k) tends to V (k)；
E (k)=V (k)-G2(k)y(k) （2）
G2(k+1)=G2(k)+kge(k) （3）
In formula：0<Kg<1 is iteration step length, using LMS iteration Method gain Kg with error e consecutive variations, constantly
Adaptive updates.The method can follow the tracks of the minor variations of signal, adaptive gain regulating Kg in real time, ensures output signal
Amplitude meets requirement.
Through the accumulation adjustment of LMS adaptive gain algorithm, finally input signal amplitude peak peak value is adjusted to benchmark
Near level, thus ensureing that A/D input signal amplitude is constant.
Above-mentioned gain algorithm ensure that when input signal amplitude and standard value deviate larger, can rapidly pass through gain
Its amplitude is adjusted to suitable scope by adjustment；When signal amplitude value and standard value relatively when, then gain is finely adjusted
Or do not carry out Gain tuning.So can fluctuate in the case of faster in the convergence rate of system as far as possible little.
The effect that the Noise Identification self adaptation of the present invention increases function refers to Fig. 5, Fig. 6 and Fig. 7.Fig. 5 a is the microseism of simulation
Signal, Fig. 5 b is the output waveform after individually adopting fast Gain tuning, as can be seen from the figure in a cycle, due to system
Bring into operation, its Gain tuning is carried out according to fixed value, according to the meansigma methodss calculating the previous cycle after 1.2s, and bring fast gain into
Adjust into row operation, generate new gain, in 9.6s, due to input signal mutation, in the presence of fast Gain tuning, 9.6～
Desired value has been exceeded after input signal adjustment between 10.8s；After 19.2s, input signal is mutated again, 19.2～20.4s it
Between input signal adjustment after have also exceeded desired value.Input signal peak swing after 20.4s is adjusted to desired value again.
Fig. 5 c is that fast, slow gain is common adjust after output signal it can be seen that due to the effect of slow Gain tuning, in sign mutation
When, the part that fast Gain tuning can not respond rapidly to, after slow Gain tuning, substantially also close to desired value.
Fig. 6 is to be changing into pure noise during the microseismic signals input of simulation, and through identification post-simulation output waveform.From Fig. 6 a
In as can be seen that microseism input signal become pure noise after 9.6s；If as can be seen that simple adopt soon, slowly from Fig. 6 b
Gain tuning input signal, not only microseismic signals amplified, noise signal is similarly amplified；Fig. 6 c is through making an uproar
After sound identification again using the waveform after speed, Gain tuning it can be seen that when after 9.6s, microseismic signals become noise, pass through
2.4s, that is, to after 12s, due to the execution of Noise Identification algorithm, noise is identified, changes reference value, so that yield value is obtained
Arrive adjustment, reduce the amplification to pure noise.
Fig. 7 is to turn to microseism input signal and emulated to becoming from pure noise.Turning with pure noise to microseismic signals
Become, the result of cross-correlation correlation computations has exceeded the threshold value of the detection of noise and input signal.Illustrate to detect microseism letter
Number, reference value ErefIt is adjusted.Adaptive gain system is by being calculated suitable gain so that microseismic signals are put
Greatly.If from Fig. 6 and 7 as can be seen that indiscriminate amplification, noise also will be by unconfined amplification.Known using band noise
After other adaptive gain algorithm, the amplitude peak of microseismic signals is adjusted to expected value substantially although noise is also exaggerated,
But the amplitude amplified is well below microseismic signals.This illustrates this adaptive gain scheme, can be completed quickly and effectively certainly
Adapt to gain-adjusted.
Claims (9)
1. a kind of microseism harvester with Noise Identification and self adaptation enlarging function is it is characterised in that this device includes
Microseismic sensors (1), signal condition (2), gain adjusting unit (3), data acquisition unit (4), noise recognizing unit (5), deposit
Storage unit (6), communication control unit (7), power subsystem (8)；Microseismic sensors (1) are adjusted through signal after picking up microseismic signals
Reason (2) and gain adjusting unit (3) send into data acquisition unit (4), and analog-signal transitions are digital signal, and by storage
Unit (6) carries out locally stored or by communication control unit (7), digital signal is uploaded to centralized control center, Gain tuning list
First (3) are used for the digital signal after data acquisition unit (4) conversion is judged, and then realize next periodic sampling data
Adaptive gain adjusts, and selectively picks up microseismic signals to microseismic sensors (1) and is amplified, noise recognizing unit (5)
Carry out computing cross-correlation for the digital signal after data acquisition unit (4) conversion with using the background signal gathering before,
Meansigma methodss according to cross-correlation coefficient absolute value and noise threshold result of the comparison, judge the analogue signal that collects as noise
Signal or microseismic signals, for being judged as that noise signal then reduces gain factor, play the purpose of compacting noise, for being judged as
Microseismic signals, then improve gain amplification, and combines gain adjusting unit (3) to signal adaptive amplification, for continuously N number of
It is judged as noise signal within cycle, then background signal is updated to using the noise signal in N number of cycle.
2. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, described microseism harvester adopts analog- and digital- hybrid circuit to constitute.
3. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, described microseismic sensors (1) are MEMS acceleration transducers.
4. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, described gain adjusting unit (3) includes variable gain amplifier (301), fast adjustment unit (302) and slow adjustment unit
(303), model AD8231 of wherein variable gain amplifier (301), it is possible to achieve 8 stage gains are amplified is 1 respectively, 2,4,
8th, 16,32,64 and 128 times.
5. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, described data acquisition unit (4) includes AD conversion (401) data collection (402), wherein AD conversion (401) adopts
The ADC of 24, its model ADS1274, it is possible to achieve the sampling of 0.1ms, 0.2ms, 0.5ms, 1.0ms, 2.0ms, 4.0ms,
Data acquisition (402) adopts digital method to realize.
6. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, described noise recognizing unit (5) adopts digital method, realized using software, the carrier that software is realized is DSP, adopts
TMS320VC5416DSP.
7. the microseism harvester with Noise Identification and self adaptation enlarging function according to claim 1, its feature
It is, adaptive gain amplifies and Noise Identification can be with on-line tuning, fast response time, using the adjustment of previous cycle sampled data
The gain in next cycle and Noise Identification threshold value.
8. a kind of microseism acquisition method with Noise Identification and self adaptation enlarging function, methods described is applied to claim
The microseism harvester with Noise Identification and self adaptation enlarging function described in 4 is it is characterised in that adaptive gain adjusts
It is divided into fast adjustment and two stages of slow adjustment, the fast metamorphosis stage, using large gain values, the microseismic signals detecting quickly are adjusted
To rational amplitude range, the temporary impact signal occurring in gatherer process, after causing to adjust soon, A/D overflows, then adjusted using slow
In the whole stage, fine-tuned using little yield value, make the input data amplitude of A/D be locked in a less fluctuation range
Interior；Concrete steps：
1) microseismic signals are gathered, obtaining a cycle sequence is x (k), and wherein k=1,2,3 ... n, n are the sampled point of a cycle
Quantity；
2) calculate the average amplitude of microseismic signals
3) calculate gain according to formula (1) and formula (2), and the microseismic signals after being amplified；
G1(k)=int (Vref/V(k)) (1)
Y (k)=G1(k)×x(k) (2)
Wherein, G1：The yield value of fast adjustment；V(k)：Reference voltage level；Vref：The reference voltage level of Gain tuning；y(k)：Amplify
Signal afterwards；
Due to the G drawing according to (1) formula1Value is not necessarily 2 series, simultaneously the 3 of AD8231 controlling switch A2A1A0Must give
Go out corresponding level, therefore, G1Value and the level of controlling switch and actual gain press following principle and choose：
If 0≤G1≤ 1, then A2A1A0=000, that is, actual gain is 1；
If 2≤G1≤3, A2A1A0=001, that is, actual gain is 2；
If 4≤G1≤6, A2A1A0=010, that is, actual gain is 4；
If 7≤G1≤12, A2A1A0=011, that is, actual gain is 8；
If 13≤G1≤24, A2A1A0=100, that is, actual gain is 16；
If 25≤G1≤48, A2A1A0=101, that is, actual gain is 32；
If 49≤G1≤96, A2A1A0=110, that is, actual gain is 64；
If 97≤G1≤128, A2A1A0=111, that is, actual gain is 128；
1 represent output high level above, 0 represents output low level；
The fast metamorphosis stage, each period modulation once, that is, with the sampled value in previous cycle, by asking for signal averaging amplitude, is held
Line (1) obtains fast adjust gain；
4) slow gain stage, the data after too fast adjustment is compared with reference value, is changed in real time by LMS adaptive gain algorithm
Slack-off yield value, thus reaching regulation amplifier input signal amplitude, the y (k) that formula (2) is drawn substitutes into (3) and show that gain is adjusted
Whole error signal, further according to formula (4) to G2K () is adjusted so that y (k) tends to V (k)；
E (k)=V (k)-G2(k)y(k) (3)
G2(k+1)=G2(k)+kge(k) (4)
Wherein, G2：The yield value of slow adjustment；V(k)：Reference voltage level；Kg：Slow adjust gain penalty coefficient；
Through the accumulation adjustment of least mean square algorithm LMS adaptive gain algorithm, input signal amplitude peak peak value is adjusted to
Reference level nearby it is ensured that A/D input signal amplitude is constant, realized by software, and the carrier of realization is by LMS adaptive gain algorithm
TMS320VC5416DSP.
9. a kind of microseism acquisition method with Noise Identification and self adaptation enlarging function, methods described is applied to claim
A kind of described in 6 has the microseism harvester of Noise Identification and self adaptation enlarging function it is characterised in that making an uproar using background
Sound and the signal collecting carry out computing cross-correlation, are controlled according to cross-correlation coefficient absolute value and noise threshold result of the comparison
The increase of reference level or reduction that adaptive gain amplifies, thus suppressing to noise, the method comprises the steps：
1) obtain the background noise data in N number of cycle and preserve, be y (N)={ y (1), y (2) ..., y (N) } sequence, microseism is supervised
During survey, 1 cycle data collecting is x={ x (1), x (2) ..., x (n) } sequence, and wherein, n is the sampled point of a cycle
Quantity；
2) cross-correlation coefficient of signal calculated y (N) sequence and x, asks for averaged R after absolute valueav；
3) cross-correlation coefficient absolute value meansigma methodss R are comparedavIf with noise threshold Rav>Threshold value, then show collection is to make an uproar
Acoustical signal, next cycle acquisition system must reduce gain, reduces reference value E of adaptive gain systemrefIf, Rav<Thresholding
Value, shows to detect microseismic signals, next cycle reference voltage ErefOriginal value must be reverted to, or change into more than former
The other values of the value come, or change into the other values less than original value；
4) all it is judged as noise signal after continuous k periodic duty, then replace background noise above with the signal in this k cycle
Signal y (N) sequence, reaches the purpose constantly noise being updated.
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