CN201837728U - Rock stratum identification device based on array fiber sensor - Google Patents
Rock stratum identification device based on array fiber sensor Download PDFInfo
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- CN201837728U CN201837728U CN201020546859XU CN201020546859U CN201837728U CN 201837728 U CN201837728 U CN 201837728U CN 201020546859X U CN201020546859X U CN 201020546859XU CN 201020546859 U CN201020546859 U CN 201020546859U CN 201837728 U CN201837728 U CN 201837728U
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Abstract
The utility model relates to a rock stratum identification device based on an array fiber sensor, which comprises a master control machine; the output end of the master control machine is connected with a light source, and the light source is connected with an array fiber grating sensor after passing a shunt; the output end of the array fiber grating sensor is connected with the input end of a demodulator, the output end of the demodulator is connected with the input end of a filtering and amplifying module, the output end of the filtering and amplifying module is connected with the input end of an analog/digital (AD) converting module, the output end of the AD converting module is connected with the master control machine, and two-way communication is further performed between the master control machine and a peripheral data interface. The rock stratum identification device based on the array fiber sensor is applied to detecting the mine vibration of various mines, positioning a vibration source, and identifying the rock stratum information within the range of a sensor, thereby obtaining more mine information, and finding out the regularity of the movement of a mine on the condition with limited equipment.
Description
Technical field
The utility model relates to a kind of rock stratum recognition device based on the array fibre sensor.
Background technology
China is many ore deposits country, is accompanied by the exploitation of numerous mine resources, and the influence that the mining geology disaster causes also comes to cause more people's attention.It is many that China's mining geology disaster has kind, and it is wide to distribute, and influence is big, and potential disaster hidden danger is outstanding, and the form of disaster is varied, endangers very serious.Wherein, the geologic hazard of bringing out because of mining accounts for larger proportion, and aggravation trend is arranged in recent years.Regular meeting causes and to adopt that sky subsides, the pit gushing water in the recovery process, and the existence of these disasters is seriously restricting bargh's production and operation, is threatening vast mine worker's life security.How to predict being important problem in the current mine safety research effectively.
It is in close relations to adopt harm such as sky subsides, roof caving, pit gushing water and rock stratum physical behavior.In various mining activities, because digging activity meeting causes high stress concentrations, cause rock stratum around the digging space vibrations, break and release suddenly, and can follow a series of acoustic emission and microseism phenomenons, can think that above-mentioned dynamic phenomenon is the precursor signal of strata structure destruction and crack propagation or disastrous accident with dynamic characteristic.Before disaster took place, rock mass if can obtain rock stratum information effectively, and can monitor in real time rock stratum information, with the prevention and the control of the disaster that is highly advantageous to.
It is low, highly sensitive to adopt the fiber Bragg grating type vibration transducer to have a cost, and probe and transmission line are not charged, advantages such as essential safety, and be easy to arrange probe and carry out remote centralized control on a large scale.But the form of rock stratum is varied, and the condition on the face of land and underground geologic structure are ever-changing, and different classes of rock stratum soil is coupled to each other, not having obvious border distinguishes, and some place is easy to measure, and most positions are difficult to use apparatus measures, can only take certain way to infer, hidden Markov model (Hidden Markov Model, HMM) be exactly with local time's invariant feature of known substance estimate object integral body the time characteristic that becomes a kind of efficient ways, it is a kind of signal mode handling implement with stronger time series modeling ability, in speech processes, obtained widespread use, be particularly suitable for non-linear, the analysis of the signal that reproducibility is not good.
And the vibration signal that sensor receives can be thought by source wavelet through the result behind the channel filtering, therefore adopt continuous hidden Markov model CHMM (Continuous Hidden Markov Model) by to the effective modeling of acoustic signals, the formation characteristics that can utilize known topography and geomorphology analysis to obtain goes to predict, analysis integrated and the rock stratum information of discerning unknown topography and geomorphology.
Rock stratum recognition methods commonly used at present has 1 geological radar and Detection Techniques thereof, 2 radiowaves perspective and Detection Techniques thereof, 3 ultrasound waves, dynamic test for pile foundation and detection technique thereof, 4 high density DC electrical method measuring techniques.The advantage of above method is a technology maturation, but generally can not measure simultaneously by multiple spot, and can't long-continuedly measure.
1. geological radar and Detection Techniques thereof
Geological radar and Detection Techniques application thereof: geological radar all is widely used in fields such as archaeology, urban construction, building, railway, highway, water conservancy, electric power, mining, aviations.Geological radar is used for the engineering place the earliest and reconnoitres: solve that cover thickness, soft layer thickness and distribution, basement rock waste mantle interface and distribution, basement rock joint and zone of fracture, underground water distribute, generaI investigation place underground karst cavity, cavity, subsidence area, underground grotto, down blow tunnel, underground blow-off line and underground utilities etc., on soft layers such as backfill, probing depth can reach more than the 20m, and probing depth can reach more than the 30m on densification or basement rock; Construction quality detects and disease screening: in recent years, subterranean tunnel, highway and urban road surfaces, airfield runway, height such as domestic and international Rail Highway are cut in the construction quality detection and disease screening of important engineering projects such as sloping barricade, extensively adopt Radar Technology.Main detect lining thickness, breakage, crack, come to nothing, cavity, percolation zone, backfill owe compact zone, country rock disturbance etc., each layer thickness of road surface and runway, damaged situation, cavity in the concrete component, crack and reinforcing bar distribution etc., accuracy of detection can reach the millimeter level; Underground installation and archaeology are sought and visited: archaeology is that geological radar is used field early, survey ancient building basis, underground chamber, metal etc., in urban renewal, use the detectable underground installation of radar, as electric power pipe network, aqueduct, blow-off line, steam transmitting pipe net, communication pipe network etc.; The tunnel is followed the tracks of in advance and is surveyed and forecast: tectonic structures such as the tomography in the 50m scope of the measurable the place ahead of geological radar, solution cavity, fissure zone, water-bearing zone; The detection application of geological radar in mine: China's coal-mine and metal mine are a lot, colliery and metal mine tectonic structure are quite complicated, geological radar has begun to be used for the down-hole, mine, can be used on heading end the place ahead forward probe and prediction, tunnel roof and floor and the detection of two nations at mine, be mainly used to survey tomography, karst collapse col umn, solution cavity, fissure zone, goaf, water-bearing zone, coal are thick, roof and floor, gas outburst danger band, metal bonanza etc.Technical characterstic: form by explosion-proof Industrial Control Computer, transmitter, receiver, serial antenna, collection and process software, high speed communication cable etc.But the tomography in 50 meters scopes of forward probe, karst collapse col umn, tectonic structures such as water-bearing zone.Method of work is flexible and varied, can comprehensively survey.Instrument is light and handy, easy to operate, shows in real time to measure section.The Data Processing software operation is simple, and intuitive measurement results is easy to explain.
2 radiowaves perspective and Detection Techniques thereof
Application: electromagnetic wave perspective technology began one's study and successively is applied to metal mine, colliery and engineering field from the seventies.Be mainly used in the colliery at present, it is mainly used to survey between two tunnels, between two borings, between boring and the tunnel, the tomography between dam body two footings, karst collapse col umn, fold, fold, wash away, soft broken band, water-bearing zone, cavity, gushing water structure, the thick variation band in coal seam, coal and gas outburst danger district, search blind orebody in the metallic ore and bonanza etc.Technical characterstic: in the coal seam interface of rift structure, and structure the coal seam shatter belt, the coal seam that cause are destroyed soft layering band and are rich in water low-resistivity band etc. and can both produce refraction, reflection and absorb electromagnetic wave, cause the loss of electromagnetic wave energy.If the electromagnetic wave of emissive source emission passes through in the approach of coal seam, have tomography, karst collapse col umn, rich water-bearing zone, top board collapses and the goaf of enrichment water, wash away, during geologic anomaly body such as the coal seam occurrence changes band, soft layering band is destroyed in Coal Seam Thickness Change and coal seam, the electromagnetic wave energy that receives will obviously weaken, and this will form perspective shadow (exceptions area).Mine electromagnetic wave perspective technology, electromagnetic instrument of a kind of sending and receiving and the data processing system of developing according to the propagation characteristic of electromagnetic wave in the coal seam exactly.It is by intelligent radio electric wave scenograph, compositions such as analysis software, computing machine and color inkjet printer.Instrument is light and handy, easy to operate, and the Data Processing software operation is simple, and visual result is easy to explain.
3 ultrasound waves, dynamic test for pile foundation and detection technique thereof
Application: construction quality detects, and the ultrasonic transmission beam method of architecture foundation piles such as house that detects pile construction integrity, pre-buried Ultrasonic Detection pipe as the ultrasonic transmission beam method of the abutment foundation pile of pre-buried Ultrasonic Detection pipe detects that pile construction integrity, various strength of reinforced concrete detect, the foundation pile reflective wave method of placing concrete packing and defects detection, various buildings detects pile construction integrity etc. in reinforced concrete crackle and the steel pipes such as Crack Detection, bridge.
Technical characterstic: supercritical ultrasonics technology is to launch high frequency elasticity pulsating wave by the ultrasonic pulse emissive source in concrete, when existing discontinuous in the concrete or during damaged interface, the defective face forms the wave impedance interface, produces the transmission and the reflection of ripple, and the transmitted wave energy that receives is obviously reduced; During major defects such as, honeycomb loose, hole, will produce the scattering and the diffraction of ripple when existing in the concrete; According to the first arrival time of arrival of ripple and the features such as energy attenuation characteristic, frequency change and wave form distortion degree of ripple, can obtain the packing parameter of coverage of survey area inner concrete.Test record is the ultrasonic fluctuation characteristic on ipsilateral, the differing heights not, just can differentiate survey through Treatment Analysis and distinguish inner concrete and have defects property, size and locus and referenced strength.Dynamic test for pile foundation be reflective wave method be to carry out vertical exciting at the pile body top, elastic wave is propagated downwards along pile body, when pile body exists interface (at the bottom of as stake, positions such as fracture and serious segregation) or pile body sectional area variation (as hole enlargement or undergauge) position of obvious wave impedance difference, will produce reflection wave.Through receiving amplification, filtering and data processing, can discern reflective information from different parts, calculate pile body speed in view of the above, to judge pile body integrity and to estimate strength grade of concrete.Also can be checked the physical length of stake time of arrival according to velocity of wave and pile bottom reflection ripple.Ultrasound wave, light, the execute-in-place convenience of dynamic test for pile foundation instrument, the Data Processing software operation is simple, visual result.
4 high density DC electrical method measuring techniques
Application: can be widely used in aspects such as energy exploration and city physical prospecting, road and bridge exploration, metal and nonmetal mineral resource exploration; Also be used for engineering geologic investigation (detections such as ground basement rock interface, karst, basement rock rift structure, cover thickness, sliding mass glide plane); Hydrological engineering is as water detection, detection place underground moisture cloth etc.; Dam hidden danger and percolating water are surveyed; The hole body is surveyed, archaeological work; Mine, tunnel water-bearing structure and small coal mine ponding are surveyed.Technical characterstic: the high-density resistivity measuring system is with reference on the basis of external advanced electrical method instrument, and in conjunction with the electric method meter measuring system of new generation of China's national situation development, this system has characteristics such as memory space is big, measurement is accurately quick, easy to operate.High density direct current resistivity is dc resistivity in fact sheerly, and ultimate principle is identical with traditional conventional DC resistivity method, and different is, and its device is a kind of combined type section device.They all are a kind of geophysical prospecting method based on the conductivity difference of underground medium (rock stratum): underground various media are applying under the electric field action, because the electrical property difference of medium causes the distribution of current of underground conduction also to there are differences, and reflects this electrical property difference distribution with apparent resistivity.Under certain power supply and potential electrode arrangement mode, power by transmitting electrode, potential electrode is measured the potential difference (PD) between the potential electrode, calculates apparent resistivity by mathematical formulae again, then by the regularity of distribution analysis of apparent resistivity is sought the geologic objective body.
The utility model content
The purpose of this utility model is to address the above problem, a kind of rock stratum recognition device and method based on the array fibre sensor is provided, it can be suitable for various mines and detect the ore deposit shake, carries out the focus location and in ranges of sensors rock stratum information is discerned, so that under limited appointed condition, the more information that obtains the mine is excavated the mine laws of motion.
For achieving the above object, the utility model adopts following technical scheme:
A kind of rock stratum recognition device based on the array fibre sensor, it comprises main control computer, and the main control computer output terminal is connected with light source, and light source is connected with the array fibre sensor behind shunt; Array fibre sensor output terminal is connected with the detuner input end, the detuner output terminal is connected with filtering amplification module input end, filtering amplification module output terminal is connected with AD modular converter input end, AD modular converter output terminal is connected with main control computer, main control computer and the two-way communication of peripheral data interface, the main control computer output terminal also is connected with warning device.
Described light source adopts the amplified spontaneous emission wideband light source.
Described main control computer is PC or flush bonding processor or dsp processor.
Described array fibre sensor is made up of several same fiber Bragg grating type vibration transducer, and their frequency ranges separately are 10～5kHz.
Described peripheral data interface is a kind of among RS232, RS485, USB, the CAN.
Described rock stratum recognition methods based on the array fibre sensor, the performing step of this recognition methods is:
(1) system initialization;
(2) utilize the array fibre sensor to carry out vibration detection;
(3), return step (2) if do not detect vibration signal; If detect vibration signal, change step (4) over to;
(4) main control computer shows in real time and writes down vibration signal;
(5) main control computer judges that whether the vibration signal amplitude surpasses specialized range, if exceed then report to the police, incorporates changing step (6) over to into; If there is not the overshoot scope, then directly change step (6) over to;
(6) main control computer utilizes the time of arrival difference of each vibration wave between different sensors to calculate the source location;
(7) extract the spectrum signature parameter of vibration signal, with vibration wave spectrum signature between fiber Bragg grating type vibration transducer probe as rock characteristic;
(8) carry out continuous Hidden Markov Model (HMM) identification computing;
(9) record recognition result;
(10) need to judge whether to report to the police, if desired, then report to the police, and the output result; If need not report to the police, then directly export the result.
In the described step (6), the source location determines that method is, after the mistiming between a plurality of sensors is determined, adopts the Newton iteration method to determine the source location; Waveform was calculated by cross-correlation method in the mistiming that each sensor arrives.
In the described step (7), the method for extracting the spectrum signature parameter of vibration signal is: at first determine sample frequency, carry out normalized according to the root mean square method for normalizing then, as shown in the formula:
Wherein X (k) is the vibration signal sample value, X (k)
NormBe the vibration signal sample value after the normalization, RMS (X) is a sequence X root mean square function, and it is calculated as follows:
Obtain the frequency spectrum with focus fiber Bragg grating type vibration transducer point-blank at last, calculate the rock stratum spectrum signature of adjacent fiber raster pattern vibration transducer by deconvolution.
In the described step (8), identifying is that the corresponding continuous Hidden Markov Model (HMM) of each sensor also constitutes fully-connected network; Feature to be identified is connected in series this fully-connected network of input, calculates optimal path and best score, each node on this optimal path is recognition result.
The utility model is a kind of method that relies on array fibre raster pattern sensor and carry out pattern-recognition by means of continuous Hidden Markov Model (HMM) technology.This method takes to install a plurality of fiber Bragg grating type vibration transducers in to be monitored and identified region, by these sensors the mine oscillation phenomenon is monitored in real time, and adopt the multisensor location technology to obtain the source location, obtain the spectral characteristic of the rock stratum between transducer arrangements scope inner sensor and the sensor by Deconvolution Technique, and extract the feature that effectively characterizes the rock stratum proterties, to each rock frame Hidden Markov Model (HMM), the two carries out recognition training and identification more than utilizing, recognition result can show or upload in real time, or dynamically shows by the three-dimensional information treatment technology.
The utility model is arranged a plurality of fiber Bragg grating type vibration transducers in formation area to be identified, its receptible source location of institute can be outside this zone, and the sensitivity of this energy that vibrates with focus, sensor is relevant.The monitoring record vibration signal obtains the vibration signal data stream that contains noise in real time, and adopts bandpass filter that signal is carried out filtering.The multichannel vibration signal that obtains is analyzed, is comprised 1) time-delay analysis, time-delay analysis is mainly used in vibration source is positioned, and after the time delay between a plurality of sensors is determined, has many methods can find out the source location, does not repeat them here; 2) the rock characteristic information between the extraction sensor.
Signal is equivalent to pass through a plurality of passages through multiple strata structure, and as shown in Figure 3: total rock stratum sound channel frequency characteristic is equivalent to the product of each frequency domain characteristic.Channel frequence response between fiber Bragg grating type vibration transducer probe 2 and the fiber Bragg grating type vibration transducer probe 3 like this, can be calculated by fiber Bragg grating type vibration transducer probe 2 and 3 frequency responses that obtain of fiber Bragg grating type vibration transducer probe, preliminary plan adopts FFT to calculate spectrum information.Specific practice: at first utilize cepstrum uncoiling technology to remove the pumping signal feature, only extract the sound channel feature, utilize the deconvolution technology to isolate spectral characteristic between each sensor then.Velocity of wave can be used as the additional parameter participation identification of feature in addition.
Adopt the feature of continuous Hidden Markov Model (HMM) and said extracted that modeling is carried out in various rock stratum, the driving source of modeling (focus) can adopt manually blows out, and utilize the deconvolution technology to remove the influence of driving source to feature, and model is carried out the multipass adjustment, the model of adjusting is used for identification.
For guaranteeing the stability of model, the utility model also can be provided with training process, promptly for the continuous Hidden Markov Model (HMM) of Training Company, need lay sensor in the position of known rock stratum information, and can adopt the mode of blowing out manually to make focus.Spectrum signature between the employing Deconvolution Algorithm Based on Frequency obtains to pop one's head in and pop one's head in is as the identification vector, and model adopts 3 state models, two edge transition states and a center situation of corresponding actual rock stratum, and each model output vector distribution is by single Gauss model processing.Each eigenvector derives from a certain state of rock stratum, and the state of the current vector correspondence of state redirect is to the transfer process of the state of next vector correspondence.
In the identifying, the model of eigenvector and rock stratum to be identified is known, will and focus probe point-blank between vector bring prototype network figure into, calculate optimum score, the rock stratum of model correspondence is recognition result on the path of score optimum.
The beneficial effects of the utility model are: the utility model utilizes the array fibre sensor to carry out the focus location and in ranges of sensors rock stratum information is discerned, under limited appointed condition, obtain more mine information, excavate the mine laws of motion, be suitable for various mines and detect the ore deposit shake.When detecting microseism and acoustic emission signal, utilize CHMM technology acquisition formation information and dynamic-change information in a big way, successful recognition result will provide effective information for hazard forecasting.
Description of drawings
Fig. 1 is a system construction drawing of the present utility model;
Fig. 2 forms the arrangenent diagram of array for fiber Bragg grating type vibration transducer probe;
Fig. 3 is many rock stratum sound channel synoptic diagram;
Fig. 4 is the Hidden Markov Model (HMM) figure that every kind of rock stratum is set up;
Fig. 5 is a workflow diagram of the present utility model;
Fig. 6 is distorted for the rock stratum or ruptures the broken synoptic diagram that produces vibrational excitation;
Wherein, 1. main control computer, 2. light source, 3. shunt, 4. fiber Bragg grating type vibration transducer, 5. detuner, 6. filtering amplification module, 7.AD modular converter, 8. warning device, 9. peripheral data interface.
Embodiment
Below in conjunction with accompanying drawing and embodiment the utility model is described further.
Among Fig. 1, based on the rock stratum recognition device of array fibre sensor, it comprises main control computer 1, and main control computer 1 output terminal is connected with light source 2, and light source 2 is connected with some fiber Bragg grating type vibration transducers 4 behind shunt 3; Some optical fiber raster vibration sensor 4 output terminals all are connected with detuner 5 input ends, detuner 5 output terminals are connected with filtering amplification module 6 input ends, filtering amplification module 6 output terminals are connected with AD modular converter 7 input ends, AD modular converter 7 output terminals are connected with main control computer 1, main control computer 1 also with 9 two-way communications of peripheral data interface, main control computer 1 output terminal is connected with warning device 8.Warning device 8 mainly be the intensity when seismic wave transfinite or the same area in the rock stratum when obviously difference takes place the recognition result of different time, can externally export the sound and light alarm signal or externally export control signal in order to control some key equipment.
Among Fig. 2, the array fibre sensor is by several same and be divided into a plurality of groups fiber Bragg grating type vibration transducer 4 and form, and their frequency ranges separately are 10～5kHz; Array fibre raster pattern sensor sensing extraneous vibration signal is converted to corresponding optical information with time dependent oscillation intensity, sends into detuner.
Method of the present utility model is, it adopts array fibre raster pattern vibration transducer that the mine oscillation phenomenon is monitored, obtain multichannel vibration signal data simultaneously, and adopt the multisensor location technology that vibration source is positioned, simultaneously to the spectral characteristic of the rock stratum between transducer arrangements scope inner sensor and the sensor, and extract the feature that effectively characterizes the rock stratum proterties, to each rock frame Hidden Markov Model (HMM), the two carries out recognition training and identification more than utilizing, and recognition result is shown with data transmit at last; Its step is:
(1) system initialization;
(2) utilize array fibre raster pattern sensor to carry out vibration detection;
(3), return step (2) if do not detect vibration signal; If detect vibration signal, change step (4) over to;
(4) main control computer shows in real time and writes down vibration signal;
(5) main control computer judges that whether the vibration signal amplitude surpasses specialized range, if exceed then report to the police, incorporates changing step (6) over to into; If there is not the overshoot scope, then directly change step (6) over to;
(6) main control computer utilizes each vibration wave in the difference calculating source location time of arrival of different sensors;
(7) extract the spectrum signature parameter of vibration signal, with shock wave spectrum signature between sensor probe as rock characteristic; Be that vibration wave obtains digital signal after high speed acquisition, this digital signal carried out spectrum analysis obtain its frequency spectrum designation; Signal spectrum is to have the impulse response convolution of pumping signal and passage to obtain, and is multiplication relationship on frequency domain; By de-convolution operation, obtain the passage frequency domain characteristic between adjacent sensors;
(8) carry out CHMM identification computing;
(9) record recognition result;
(10) need to judge whether to report to the police, if desired, then report to the police, and the output result; If need not report to the police, then directly export the result.
In the described step (6), the source location determines that method is, adopts Delay Analysis, after the time delay between a plurality of sensors is determined, adopts conventional method to determine the source location; Waveform was calculated by cross-correlation method in the mistiming that each sensor arrives.
In the described step (7), the method of extracting the spectrum signature parameter of vibration signal is, its detailed process is: determine sample frequency, usually select the 10kHZ sampling for use, carry out normalized according to root-mean-square value RMS method for normalizing then, be the root mean square of each fiber Bragg grating type vibration transducer 4 sampling point, select 1024 at this sequence length divided by sequence, as shown in the formula:
X (k) vibration signal sample value wherein, k is a natural number, gets k=1,2 ..., N, X (k)
NormBe the vibration signal sample value after the normalization, RMS (X) is a sequence X root mean square function, and it is calculated as follows:
Carry out digital band pass filtering then, filter range is selected 10～4kHz, obtains the signal of this position.To sensor group, per 4 is one group, carries out the focus location Calculation then.The algorithm of the existing many maturations of location algorithm is such as Newton iteration method.Spectrum analysis is carried out to the waveform with focus probe series point-blank in location back, calculate rock stratum spectrum signature between adjacent probe by deconvolution, and feature is carried out rock stratum identification as eigenvector thus.
In the described step (8), identifying is that the corresponding CHMM model of each sensor also constitutes fully-connected network; Feature to be identified is connected in series this fully-connected network of input, calculates optimal path and best score, each node on this optimal path is recognition result.
In the preferred embodiment of the present utility model, fiber Bragg grating type vibration transducer 4 is embedded in the ore body, and the quantity of sensor installation decide according to the situation of change of the area in zone to be measured and rock stratum to be identified, and installation is not less than 32 probes in common one square kilometre.
The recognition methods of the utility model preferred embodiment is that at first fiber Bragg grating type vibration transducer 4 detects vibration wave: vibration wave obtains digital signal after 16 high speed acquisition.Microseism and acoustic emission signal belong to vibration signal together, and it produces mainly is because the rock stratum is distorted or the fragmentation of rupturing etc. produces vibrational excitation, form vibration wave after the resonance of rock stratum and filtering, as shown in Figure 6; Suppose that vibration wave is x (t), vibration wave x (t) is carried out spectrum analysis can obtain its frequency spectrum designation, because signal spectrum is to have the impulse response convolution of pumping signal and passage to obtain.The time-domain representation of supposing pumping signal is s (t), and the impulse response of rock stratum passage is v (t), and then vibration wave can be expressed as x (t)=s (t) * v (t), and * represents convolution algorithm; And be multiplication relationship on frequency domain, suppose that the sound wave transmission experienced the individual rock stratum of k (k gets natural number) sound channel, the frequency response of each rock stratum sound channel is respectively V
1(ω), V
2(ω) ... V
K(ω), so the frequency spectrum of vibration wave can be expressed as X
K(ω)=S (ω) V
1(ω) V
2(ω) ... V
K(ω), then have
V
K(ω)＝V
K(ω)/[S(ω)V
1(ω)...V
k-1(ω)]＝X
K(ω)/X
K-1(ω)
X
K(ω), X
K-1(ω) can be undertaken obtaining after the FFT conversion, so, can calculate the passage frequency domain characteristic between adjacent sensors by above-mentioned de-convolution operation by the signal that fiber Bragg grating type vibration transducer 4 probes detect.
Utilize each vibration wave in the difference calculating source location time of arrival of different sensors: the propagation of vibration signal in the rock stratum needs the time, the time that arrives each sensor like this is different, by detecting the mistiming that vibration wave arrives each sensor, can calculate the position of focus.Waveform can be calculated by cross-correlation method in the mistiming that each sensor arrives.
Suppose that the detected vibration signal mistiming of two sensors is τ
0, establish the detected vibration signal of two sensors and be expressed as x respectively
1(t) and x
2(t), and both satisfy x
2(t)=x
1(t-τ), the simple crosscorrelation of two signals is:
As τ=τ
0The time, y (τ) obtains maximal value; Therefore simple crosscorrelation that can be by calculating two signals also finds the corresponding peaked moment to be the mistiming of two signals.
Select formation area to be identified as required, utilize in this zone and signal that sensor that adjacent locations distributes receives carries out the rock stratum information Recognition, and the output recognition result, recognition result is exactly the kind of rock stratum here.In the information Recognition of rock stratum, also can add training process, training process refers to oneself and knows the rock stratum kind, and be the blank that Hidden Markov Model (HMM) is set up in these oneself classification rock stratum, obtain the spectrum signature of these rock stratum correspondences by aforementioned content, be updated in the Hidden Markov Model (HMM) and train, till model parameter is stable.
Hidden Markov model is a dual random process, promptly includes the stochastic process of sightless (a hiding) subordinate stochastic process, and this sightless subordinate stochastic process can only be observed by the stochastic process of another set of generation observation sequence and be obtained.The spectrum signature sequence that obtains by deconvolution in the utility model is observation sequence, and rock stratum kind to be asked is implicit subordinate stochastic process.A Hidden Markov process is made up of a plurality of Hidden Markov Model (HMM), and each Hidden Markov Model (HMM) is by parameter A, and B, π represent that the purpose of training is exactly to find the parameter A of model, B, π.Therefore, at first on oneself knows the rock stratum of rock stratum kind, experimentize, obtain a large amount of vectors of observing, observe vectors by these then and just can obtain parameter A, B, π through forward direction algorithm or Viterbi Viterbi algorithm or Bao Mu-Wei Erqi Baum-Welch algorithm.
In order to train continuous Hidden Markov Model (HMM), need lay sensor in the position of known rock stratum information, and can adopt the mode of blowing out manually to make focus.Spectrum signature between the employing Deconvolution Algorithm Based on Frequency obtains to pop one's head in and pop one's head in is as the identification vector, because vibration has the branch of P ripple S ripple, and be the aliasing of two kinds of ripples in the actual detected, each vibration signal that vibrates early stage, mid-term and later stage often has than big-difference, may in order better to show these, adopt three condition Hidden Markov HMM model at this, note the characteristics of HMM model, three condition is not represented only correspondence section three basic times of each model, because under each state resident number of times can be arranged, this parameter can have the training stage to obtain.Signal all can a corresponding characteristic parameter (vector sequence) at the resident each time of each state, principle according to Probability Theory and Math Statistics, occurring in nature is maximum is distributed as Gaussian distribution, and any probability distribution all can be expressed as the weighted blend of multiple Gaussian distribution.According to our statistics, the probability distribution of vibration signal output spectrum characteristic parameter is approximately single Gaussian distribution.For simplifying computing, select single Gauss as its probability density function at this.Model adopts 3 state models, two edge transition states and a center situation of corresponding actual rock stratum, and as shown in Figure 4, each model output vector distributes and handles by single Gauss model.
During identification,, directly the spectrum signature data that obtain are updated in the Hidden Markov Model (HMM) that trains, calculate final score for rock stratum to be identified.In actual applications, constitute fully-connected network by each Hidden Markov Model (HMM), each model is arranged on the node of this network, and feature to be identified is connected in series this fully-connected network of input, calculate optimal path and best score, each node on this optimal path is recognition result.Optimal path is a paths of probability maximum, can obtain by the Viterbi algorithm computation.Best score on so-called each node promptly arrives the most probable value of this node.Last recognition result represent along this section sound wave the kind of rock stratum between each sensor of process.
Claims (5)
1. the rock stratum recognition device based on the array fibre sensor is characterized in that it comprises main control computer, and the main control computer output terminal is connected with light source, and light source is connected with the array fibre sensor behind shunt; Array fibre sensor output terminal is connected with the detuner input end, the detuner output terminal is connected with filtering amplification module input end, filtering amplification module output terminal is connected with AD modular converter input end, AD modular converter output terminal is connected with main control computer, main control computer and the two-way communication of peripheral data interface, the main control computer output terminal also is connected with warning device.
2. the rock stratum recognition device based on the array fibre sensor as claimed in claim 1 is characterized in that described light source adopts the amplified spontaneous emission wideband light source.
3. the rock stratum recognition device based on the array fibre sensor as claimed in claim 1 is characterized in that, described main control computer is PC or flush bonding processor or dsp processor.
4. the rock stratum recognition device based on the array fibre sensor as claimed in claim 1 is characterized in that described array fibre sensor is made up of several same fiber Bragg grating type vibration transducer, and their frequency ranges separately are 10～5kHz.
5. the rock stratum recognition device based on the array fibre sensor as claimed in claim 1 is characterized in that, described peripheral data interface is a kind of among RS232, RS485, USB, the CAN.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201020546859XU CN201837728U (en) | 2010-09-29 | 2010-09-29 | Rock stratum identification device based on array fiber sensor |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101968550A (en) * | 2010-09-29 | 2011-02-09 | 山东大学 | Rock stratum recognizing device and method based on array optical fiber sensor |
| CN102928889A (en) * | 2012-11-08 | 2013-02-13 | 中国矿业大学 | Integrative radio wave perspective exploration instrument |
| CN107356957A (en) * | 2017-07-11 | 2017-11-17 | 中国矿业大学 | A kind of Microseismic monitoring system and installation and monitoring method based on optical fibre grating acceleration sensor |
| CN108711265A (en) * | 2017-06-13 | 2018-10-26 | 南京康腾生物科技有限公司 | Mudstone flow monitoring is taken refuge alarm system and method |
| CN111766573A (en) * | 2020-06-02 | 2020-10-13 | 武汉烽理光电技术有限公司 | Method and system for improving array grating positioning spatial resolution of Kalman filtering |
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2010
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101968550A (en) * | 2010-09-29 | 2011-02-09 | 山东大学 | Rock stratum recognizing device and method based on array optical fiber sensor |
| CN101968550B (en) * | 2010-09-29 | 2013-03-06 | 山东大学 | Rock stratum recognizing device and method based on array optical fiber sensor |
| CN102928889A (en) * | 2012-11-08 | 2013-02-13 | 中国矿业大学 | Integrative radio wave perspective exploration instrument |
| CN102928889B (en) * | 2012-11-08 | 2016-01-20 | 中国矿业大学 | Integrative radio wave perspective exploration instrument |
| CN108711265A (en) * | 2017-06-13 | 2018-10-26 | 南京康腾生物科技有限公司 | Mudstone flow monitoring is taken refuge alarm system and method |
| CN108711265B (en) * | 2017-06-13 | 2020-02-18 | 南京康腾生物科技有限公司 | Debris flow monitoring refuge alarm system and method |
| CN107356957A (en) * | 2017-07-11 | 2017-11-17 | 中国矿业大学 | A kind of Microseismic monitoring system and installation and monitoring method based on optical fibre grating acceleration sensor |
| CN111766573A (en) * | 2020-06-02 | 2020-10-13 | 武汉烽理光电技术有限公司 | Method and system for improving array grating positioning spatial resolution of Kalman filtering |
| CN111766573B (en) * | 2020-06-02 | 2024-02-27 | 武汉烽理光电技术有限公司 | Method and system for improving array grating positioning spatial resolution through Kalman filtering |
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