CN105973449B - A kind of optical fiber Recognition of Vibration Sources method, apparatus and system - Google Patents
A kind of optical fiber Recognition of Vibration Sources method, apparatus and system Download PDFInfo
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Abstract
The invention discloses a kind of optical fiber Recognition of Vibration Sources method, apparatus and systems.This method comprises: fiber-optic vibration signal is divided into J frame subsignal by identification terminal；Characteristic vector composition array T [J] of every frame subsignal is extracted, and obtains the array R [I] of the characteristic vector composition of preset signals model；According to distance g (R (0), T (0)), sequence calculate array T [J] each characteristic vector T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until the distance between characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)) is calculated；Calculate distance g (R (I-1), T (J-1)) and I and J's and between ratio, using the similarity distance as fiber-optic vibration signal and preset signals model；It imposes a condition if similarity distance meets, the vibration source type of fiber-optic vibration signal is determined as the corresponding vibration source type of preset signals model.By the above-mentioned means, can be realized the accuracy rate and speed for improving identification vibration source.
Description
Technical field
The present invention relates to fiber optic communication fields, more particularly to a kind of optical fiber Recognition of Vibration Sources method, apparatus and system.
Background technique
With optical fiber processing technology develop, using fiber-optic probe surrounding enviroment situation, for example whether have object pass through and
The object is specifically what.When detection fiber is influenced to vibrate by external interference, the part that light is transmitted in optical fiber is special
Property will change, identification terminal is acquired signal, and the feature of analysis acquisition signal is to judge the change of its light characteristic, in turn
It can detect that and the corresponding signal of vibration position occurs, and then its vibration source type is gone out according to the signal identification.
However, environment locating for optical fiber usually has more interference noise, biggish difficulty is brought to Recognition of Vibration Sources,
Moreover, operand needed for existing Recognition of Vibration Sources method is logical is big, recognition speed is lower.
Summary of the invention
The invention mainly solves the technical problem of providing consistent optical fiber Recognition of Vibration Sources method, apparatus and system, Neng Goushi
Now improve the accuracy rate and speed of identification vibration source.
In order to solve the above technical problems, one technical scheme adopted by the invention is that: a kind of optical fiber Recognition of Vibration Sources side is provided
Method, comprising: fiber-optic vibration signal is divided into J frame subsignal by identification terminal；Extract the characteristic vector composition number of every frame subsignal
Group T [J]={ T (0), T (j) ..., T (J-1) }, and obtain array R [I]={ R of the characteristic vector composition of preset signals model
(0), R (i) ..., R (I-1) }, wherein the Characteristic Vectors of the characteristic vector of the fiber-optic vibration signal and the preset signals model
The extracting mode of amount is consistent；Determine the distance between the characteristic vector T (0) and the characteristic vector R (0) g (R (0), T (0))
And parameter M, wherein the difference between the M and the I and J is positively correlated；According to the distance g (R (0), T (0)), sequence is counted
Calculate each characteristic vector T (j) of the array T [J] respectively between array R [I] at least partly characteristic vector R (i) away from
From g (R (i), T (j)), until the distance between the characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I- is calculated
1), T (J-1)), wherein, g (the R (i), T (j)) by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T
(j-1)) it is calculated, the corresponding Partial Feature vector R (i) of each characteristic vector T (j) includes in the array R [I]
Characteristic vector R (max (j-M, 0)) to characteristic vector R (min (j+M, I-1))；Calculate the distance g (R (I-1), T (J-1)) with
The I and it is described J's and between ratio, using the similarity distance as the fiber-optic vibration signal and the preset signals model；
It imposes a condition if the similarity distance meets, the vibration source type of the fiber-optic vibration signal is determined as the preset signals mould
The corresponding vibration source type of type.
Wherein, the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-
1) it) is calculated and specifically includes: the g (R (i), T (j)) is calculated using formula 1 and formula 2；
Wherein, the characteristic vector T (j) is expressed as (y1..., yn), the characteristic vector R (i) is expressed as (x1...,
xn)。
Wherein, the distance between the determination characteristic vector T (0) and the characteristic vector R (0) g (R (0), T (0))
The step of include: that the distance g (R (0), T (0)) is calculated using formula 3
G (R (0), T (0))=2d (T (0), R (0)) (3).
Wherein, described according to the distance g (R (0), T (0)), sequentially calculate each characteristic vector T of array T [J]
It (j) with the step of array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)) include: respectively root
According to the distance g (R (0), T (0)), sequentially calculate each characteristic vector T (j) of the array T [J] respectively with the characteristic vector
The distance between R (0) g (R (0), T (j))；Sequence calculate each characteristic vector T (j) of the array T [J] respectively with the array
R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), wherein as the j=0, the characteristic vector
The corresponding Partial Feature vector R (i) of T (0) includes all characteristic vectors in the array R [I], as the j ≠ 0,
The corresponding Partial Feature vector R (i) of the characteristic vector T (j) includes the characteristic vector R (max in the array R [I]
(j-M, 1)) to characteristic vector R (min (j+M, I-1)).
Wherein, the M=m+ | I-J |, m is a setting constant.
Wherein, the step of characteristic vector for extracting every frame signal includes: that every frame subsignal is passed through line respectively
Property predictive coding lpc analysis obtains corresponding cepstrum coefficient, using the cepstrum coefficient of every frame subsignal as its characteristic vector.
Wherein, before described the step of fiber-optic vibration signal is divided into J frame subsignal, the method also includes: it is right
The fiber-optic vibration signal carries out preemphasis processing；After described the step of fiber-optic vibration signal is divided into J frame subsignal,
The method also includes: windowing process is carried out to every frame subsignal；To every frame subsignal after the windowing process into
Row autocorrelation analysis.
In order to solve the above technical problems, another technical solution used in the present invention is: providing a kind of optical fiber Recognition of Vibration Sources
Device, comprising: division module, for fiber-optic vibration signal to be divided into J frame subsignal；Extraction module, for extracting every frame
The characteristic vector of signal forms array T [J]={ T (0), T (j) ..., T (J-1) }, and obtains the Characteristic Vectors of preset signals model
Measure composition array R [I]={ R (0), R (i) ..., R (I-1) }, wherein the characteristic vector of the fiber-optic vibration signal with it is described
The extracting mode of the characteristic vector of preset signals model is consistent；First determining module, for determine the characteristic vector T (0) with
The distance between the characteristic vector R (0) g (R (0), T (0)) and parameter M, wherein the difference between the M and the I and J
It is positively correlated；First computing module, for sequentially calculating each feature of the array T [J] according to the distance g (R (0), T (0))
Vector T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until calculate
Obtain the distance between the characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)), wherein the g (R
(i), T (j)) by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-1)) it is calculated, each feature
The corresponding Partial Feature vector R (i) of vector T (j) include characteristic vector R (max (j-M, 0)) in the array R [I] extremely
Characteristic vector R (min (j+M, I-1))；Second computing module, for calculating the distance g (R (I-1), T (J-1)) and the I
And it is described J's and between ratio, using the similarity distance as the fiber-optic vibration signal and the preset signals model；Second really
Cover half block, for when the similarity distance meets and imposes a condition, the vibration source type of the fiber-optic vibration signal to be determined as institute
State the corresponding vibration source type of preset signals model.
Wherein, the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-
1) it) is calculated and specifically includes: the g (R (i), T (j)) is calculated using formula 1 and formula 2；
Wherein, the characteristic vector T (j) is expressed as (y1..., yn), the characteristic vector R (i) is expressed as (x1...,
xn)。
In order to solve the above technical problems, another technical solution that the present invention uses is: a kind of fiber identification system is provided,
Including optical fiber, fibre optical sensor and identification terminal；The fibre optical sensor is used to issue the first optical signal to described optical fiber one end,
And receive the second optical signal for being reflected by first optical signal from described optical fiber one end, and to second optical signal into
Row sampling obtains multiple Sampled optical signals, and the multiple Sampled optical signals are converted to multiple sampling electric signals；The identification
When terminal is for determining that the first sampling electric signal is fiber-optic vibration signal, Recognition of Vibration Sources is carried out to the fiber-optic vibration signal,
In, the identification terminal includes above-mentioned optical fiber Recognition of Vibration Sources device, to carry out Recognition of Vibration Sources to the fiber-optic vibration signal.
Above scheme, processing terminal are sampled by the fiber-optic signal detected to fibre optical sensor using sliding window, and right
Sampled signal is identified, when recognizing sampled signal and preset signals Model Matching, by the environment shape of corresponding fiber position
Condition is determined as the corresponding default environmental aspect of the preset signals model.The sliding window sample mode is i.e. every less than setting time length
Sampling time difference fiber-optic signal is sampled to obtain the sampled signal of the setting time length so that sampled signal includes
Data it is more abundant, improve a possibility that sampled signal include enough valid data, when fiber-optic signal in the presence of and default letter
When the valid data of number Model Matching, above-mentioned sample mode there may be sampled signal includes greatly complete valid data,
So that by identifying that the sampled signal can accurately determine corresponding environmental aspect, therefore the identification for improving optic fibre environment situation is accurate
Degree.
Detailed description of the invention
Fig. 1 is the flow chart of one embodiment of optical fiber Recognition of Vibration Sources method of the present invention；
Fig. 2 is the structural schematic diagram of one embodiment of optical fiber Recognition of Vibration Sources system of the present invention；
Fig. 3 is the partial process view of another embodiment of optical fiber Recognition of Vibration Sources method of the present invention；
Fig. 4 is the partial process view of optical fiber Recognition of Vibration Sources method a further embodiment of the present invention；
Fig. 5 is the structural schematic diagram of one embodiment of optical fiber Recognition of Vibration Sources device of the present invention；
Fig. 6 is the structural schematic diagram of another embodiment of optical fiber Recognition of Vibration Sources device of the present invention.
Specific embodiment
In being described below, for illustration and not for limitation, propose such as specific system structure, interface, technology it
The detail of class, so as to provide a thorough understanding of the present application.However, it will be clear to one skilled in the art that there is no these specific
The application also may be implemented in the other embodiment of details.In other situations, omit to well-known device, circuit with
And the detailed description of method, so as not to obscure the description of the present application with unnecessary details.
Referring to Fig. 1, the flow chart of one embodiment of optical fiber Recognition of Vibration Sources method of the present invention, this method comprises:
S12: fiber-optic vibration signal is divided into J frame subsignal by identification terminal.
Incorporated by reference to Fig. 2 for example, Fig. 2 shows an optical fiber Recognition of Vibration Sources system, which uses light
Impulse modulation system, by detect backscatter signals phase change caused by reflecting interference Strength Changes, can be simultaneously
Multiple concurrent vibration sources are detected, to realize early warning and position to vibration source.In the optical fiber Recognition of Vibration Sources system, fibre optical sensor 21
It is connect with identification terminal 22.Optical fiber 23 is set in the environment that need to be monitored such as underground, to monitor the environmental aspect.Fibre optical sensor
21 timings issue the first optical signal from one end of optical fiber 23, which can be a pulse signal, for example pulse width
For the laser of 10ns, the second optical signal that Rayleigh scattering is formed is passed through in first optical signal each position in optical fiber 23, and
Second optical signal is reflected back one end of the optical fiber 23.Fibre optical sensor 21 obtains second light letter from one end of the optical fiber 23
Number.Fibre optical sensor 21 samples the second optical signal, obtains multiple Sampled optical signals.Wherein, which can acquire
The optical signal that optical fiber emits every set distance, for example, first Sampled optical signals correspond to it is anti-apart from 1 meter of optical fiber one end position
The optical signal penetrated, second Sampled optical signals correspond to the optical signal reflected apart from the 2 meters of positions in optical fiber one end, and so on.
Due to the optical signal of backscattering and its faint, and its noise is smaller, difficult during to optical signal prosessing
Spend that larger, precision is smaller, therefore above-mentioned multiple Sampled optical signals are converted to corresponding sampling electric signal just by fibre optical sensor 33
In the processing of signal.Here analog signal can be converted to by general photoelectric converter such as APD, then passes through analog-to-digital conversion
Device converts analog signals into digital signal.
Multiple sampling electric signals after conversion are sent to identification terminal 22 by fibre optical sensor 21.Certainly, in other implementations
In example, which can be executed by identification terminal 22, i.e., 22 reception optical fiber sensor 21 of identification terminal believes the second light
Number obtained multiple Sampled optical signals of sampling, and convert thereof into multiple sampling electric signals.
Whether the sampling electric signal that identification terminal 22 detects in multiple sampling electric signal is fiber-optic vibration signal, if
The step of being, then executing this method embodiment.The fiber-optic vibration signal is expressed as adopting for the fiber position reflection of vibration source occur
The fiber optic telecommunications number that sample optical signal is converted, which carry the vibration performances of the vibration source.
S12: identification terminal extracts characteristic vector composition array T [J]={ T (0), T (j) ..., T (J- of every frame subsignal
1) }, and array R [I]={ R (0), the R (i) ..., R (I-1) } that the characteristic vector of preset signals model forms is obtained.
Wherein, the extracting mode of the characteristic vector of the characteristic vector of the fiber-optic vibration signal and the preset signals model
Unanimously.
For example, identification terminal is stored at least one preset signals model, corresponding each preset signals model includes one
Multiple characteristic vector R (0) of the fiber-optic vibration signal of kind vibration source, R (i) ..., R (I-1), wherein i is the preset signals model
Signal frame timing label, i=0 be the preset signals model rise pip signal frame, i=I-1 be the preset signals model
Terminal subsignal frame, therefore I is the frame sum of the preset signals model subsignal that includes, and R (i) is the preset signals mould
The characteristic vector of the subsignal of the i-th frame of type.Identification terminal extract the 1st frame subsignal to J frame subsignal characteristic vector one by one
It sequentially corresponds to T (0), T (j) ..., T (J-1), wherein j is the timing label of the signal frame of the fiber-optic vibration signal, and j=0 is
The fiber-optic vibration signal plays pip signal frame, and j=J-1 is the terminal subsignal frame of the fiber-optic vibration signal, therefore J is the light
The frame sum for the subsignal that fine vibration signal is included, T (i) are the Characteristic Vectors of the subsignal of a fiber-optic vibration signal jth frame
Amount.Above-mentioned I and J is all larger than 1, and the two can be equal or unequal, is not limited thereto.
It is worth noting that, the mode of the characteristic vector of identification terminal extraction subsignal and the spy in preset signals model
The extracting mode of sign vector is consistent, to guarantee both following accurate comparisons.That is, preset signals model and fiber-optic vibration
Signal uses the characteristic vector of same type.
Wherein, extracting mode can be a variety of, for example, linear predictive coding (linear predictive
Coding, LPC) what is obtained can represent the parameter of the subsignal feature, such as LPC coefficient or cepstrum coefficient.In another embodiment
In, the step of characteristic vector for extracting every frame signal includes: that every frame subsignal is passed through lpc analysis respectively to obtain pair
The cepstrum coefficient answered, using the cepstrum coefficient of every frame subsignal as its characteristic vector.
S13: identification terminal determines the distance between the characteristic vector T (0) and the characteristic vector R (0) g (R (0), T
And parameter M (0)).
Wherein, the difference between the M and the I and J is positively correlated.For example, the M=m+ | I-J |, m is a setting constant.
The m can be correspondingly arranged according to requirements such as operations, to reduce the operand of following step S14, optimize the fortune of following step S14
Scanning frequency degree.Such as when m is set as smaller, the operand of following step S14 is fewer.In a concrete application, which may be configured as I
Or 1 to a thirtieth/10th of J, and less than 10.
In the present embodiment, identification terminal using formula 11 be calculated characteristic vector T (0) and the characteristic vector R (0) it
Between distance g (R (0), T (0)).
G (R (0), T (0))=2d (T (0), R (0)) (11)
Wherein, the definition of the d please refers to the formula 13 and its associated description of step S14.
S14: identification terminal sequentially calculates each characteristic vector of the array T [J] according to the distance g (R (0), T (0))
T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until be calculated
The distance between the characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)).
Wherein, the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-
1) it) is calculated.For example, the g (R (i), T (j)) is calculated using formula 12 and formula 13 in identification terminal；
Wherein, the characteristic vector T (j) is expressed as (y1..., yn), the characteristic vector R (i) is expressed as (x1..., xn).When
So, in other embodiments, Euclidean distance can also be used in distance function d, is
Wherein, the corresponding Partial Feature vector R (i) of each characteristic vector T (j) includes the spy in the array R [I]
It levies vector R (max (j-M, 0)) to characteristic vector R (min (j+M, I-1)).
Said sequence, which calculates, may be expressed as: order of elements according to array T [J], calculate each characteristic vector T (j) and same
The distance of one characteristic vector R (i), and according to the order of elements of array R [I], calculate its characteristic vector R (i) and same Characteristic Vectors
Measure the distance of T (j).Such as above-mentioned formula 12, each characteristic vector T (j) need to be previous special by it at a distance from characteristic vector R (i)
The distance between vector is levied, therefore needs to calculate according to array sequence.
Referring to Fig. 3, in another embodiment, which specifically includes following sub-step:
S141: identification terminal sequentially calculates each Characteristic Vectors of the array T [J] according to the distance g (R (0), T (0))
Measure T (j) respectively with the distance between the characteristic vector R (0) g (R (0), T (j)).
S142: identification terminal sequence calculate each characteristic vector T (j) of the array T [J] respectively with the array R [I] extremely
The distance between small part characteristic vector R (i) g (R (i), T (j)).
Wherein, as the j=0, the corresponding Partial Feature vector R (i) of the characteristic vector T (0) includes described
All characteristic vectors in array R [I], as the j ≠ 0, the corresponding Partial Feature vector R of the characteristic vector T (j)
(i) include characteristic vector R (max (j-M, 1)) to characteristic vector R (min (j+M, I-1)) in the array R [I].
For improve operation accuracy, identification terminal first calculate each characteristic vector T (j) of the array T [J] respectively with institute
State the distance between characteristic vector R (0) g (R (0), T (j)) and characteristic vector T (0) respectively with each spy of the array R [I]
Levy the distance between vector R (i) g (R (i), T (0)).Then, identification terminal is sequentially calculated in the array T [J] again except T (0)
Outer each characteristic vector T (j) respectively with the array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T
(j)), the corresponding Partial Feature vector R (i) of the characteristic vector T (j) includes the characteristic vector R in the array R [I]
(max (j-M, 1)) to characteristic vector R (min (j+M, I-1)).Though the embodiment has been slightly increased characteristic vector R (0), Characteristic Vectors
The distance operation amount of T (0) is measured, but operation accuracy can be further increased.
Above-mentioned calculation is explained below, in the present invention, in order to compare fiber-optic vibration signal and default letter
Similarity between number model is higher apart from smaller then similarity using calculating the distance between they.In order to calculate optical fiber vibration
Dynamic the distance between signal and preset signals model, need to from fiber-optic vibration signal and preset signals model each corresponding subsignal
The distance between frame is counted.
For example, Dynamic Programming (DP) can be used in the calculating of the similarity distance between fiber-optic vibration signal and preset signals model
Method.Specifically such as, two-dimensional Cartesian coordinate system is established, if each frame number j=0~(J-1) of fiber-optic vibration signal in horizontal axis
On mark, each frame number i=0~(I-1) of preset signals model is marked on longitudinal axis, respectively to indicate frame number on transverse and longitudinal axis
Each coordinate makes the straight line perpendicular to axis where the coordinate as initial point, so that a network can be formed, in the network
Each crosspoint (i, j) indicates the joint of a certain frame of correspondence of fiber-optic vibration signal and preset signals model.DP algorithm can
A path by several lattice points in this network is found to be attributed to, the lattice point that path passes through is fiber-optic vibration signal and pre-
If the frame number calculated in signal model.Path be not it is elective, the speed of signal any first is likely to
Variation, but the precedence of its each section can not change, therefore selected path must be gone out from the lower left corner (i, j=0)
Hair terminates at the upper right corner (i=I-1, j=J-1).
Because fiber-optic vibration signal is different with preset signals model length, so there are many kinds of its corresponding matching relationships,
Therefore need to find out apart from that shortest coupling path, when from above-mentioned network one grid (i-1, j-1), (i-1, j) or
(i, j-1) is moved to next grid (i, j), and if transversely or longitudinally moving, distance is d (i, j), if it is
That sideling diagonal line comes is then 2d (i, j), so, two characteristic vector times of fiber-optic vibration signal and preset signals model
Distance such as above-mentioned formula 13.The g (R (i), T (j)) indicates that fiber-optic vibration signal and preset signals model are all sweared from initiation feature
Amount is gradually matched to characteristic vector R (i) and characteristic vector T (j).When being matched to characteristic vector R (I-1) and characteristic vector T (J-1)
Distance g (R (I-1), T (J-1)), that is, being matched to this step is the distance between fiber-optic vibration signal and preset signals model.
S15: identification terminal calculate the distance g (R (I-1), T (J-1)) and the I and it is described J's and between ratio, with
Similarity distance as the fiber-optic vibration signal and the preset signals model.
For example, identification terminal obtains the distance g (R (I-1), T that are matched to characteristic vector R (I-1) and characteristic vector T (J-1)
(J-1)) after, the similarity distance s of the fiber-optic vibration signal Yu the preset signals model is calculated according to formula 14；
S16: imposing a condition if the similarity distance meets, and identification terminal is by the vibration source type of the fiber-optic vibration signal
It is determined as the corresponding vibration source type of the preset signals model.
The setting condition is for example less than setting similarity distance, or for the minimum in all preset signals models it is similar away from
From.For example, identification terminal stores multiple preset signals models, identification terminal is performed a plurality of times above-mentioned steps S13-S15, obtains each
The similarity distance of preset signals model and the fiber-optic vibration model, by identification terminal by the vibration source classification of type of fiber-optic vibration model
For the corresponding vibration source type of the smallest preset signals model of similarity distance.Certainly, for the different demands of concrete application, the setting
Condition can be not specifically limited herein with other conditions.
In the present embodiment, identification terminal is by calculating the characteristic vector of every frame subsignal of fiber-optic vibration signal and presetting letter
The distance of the characteristic vector of number model, to obtain the similarity between the fiber-optic vibration signal speech preset signals model, in turn
The vibration source type that fiber-optic vibration signal is determined by similarity realizes the vibration source classification to fiber-optic vibration signal, and the classification side
Formula can carry out Accurate classification to vibration source, improve the accuracy rate of Recognition of Vibration Sources, and identification terminal is only calculated according to setting rule
The distance between array T [J] each characteristic vector T (j) and array R [I] Partial Feature vector R (i), reduce operand, mention
High recognition speed and efficiency, save the process resource of identification terminal.
Referring to Fig. 4, Fig. 4 is the partial process view of optical fiber Recognition of Vibration Sources method a further embodiment of the present invention, this method
Including above-mentioned S12-S16, and further comprising the steps of before step S12:
S41: identification terminal carries out preemphasis processing to the fiber-optic vibration signal.
For example, the preemphasis network used is a fixed single order digital display circuit, the signal equation are as follows:
S (n)=s (n) -0.94s (n-1)；
Wherein, s (n) is the fiber-optic vibration signal before processing, and S (n) is the fiber-optic vibration signal before processing.
S42: fiber-optic vibration signal is divided into J frame subsignal by identification terminal.
S43: identification terminal carries out windowing process to every frame subsignal.
For example, the sharp change of the signal edge as caused by framing is eliminated using Hamming (Hamming) window, in one embodiment,
The Hamming window is defined as:
S44: identification terminal carries out autocorrelation analysis to every frame subsignal after the windowing process.
For example, identification terminal carries out autocorrelation calculation to every frame subsignal after the windowing process are as follows:
Wherein, S indicates the subsignal after windowing process.
S45: every frame subsignal is passed through lpc analysis respectively and obtains the LPC coefficient of p rank by identification terminal, by described every
The LPC coefficient of the p rank of frame subsignal is converted to the cepstrum coefficient of corresponding q rank.
The cepstrum coefficient of the q rank of every frame subsignal is the characteristic vector of the subsignal, and above-mentioned p, q are not equal to 0.On
It states and LPC coefficient i.e. cepstrum coefficient is obtained by lpc analysis sees existing correlation analysis, be not specifically described herein.In this reality
It applies in example, the characteristic vector of above-mentioned preset signals model is also the cepstrum coefficient of same type, and the preset signals model is using same
The forms of sample carry out windowing process.
Referring to Fig. 5, Fig. 5 is the structural schematic diagram of one embodiment of Recognition of Vibration Sources device of the present invention, which includes:
Framing module 51, for fiber-optic vibration signal to be divided into J frame subsignal.
Extraction module 52, the characteristic vector for extracting every frame subsignal form array T [J]={ T (0), T (j) ..., T
(J-1) }, and obtain preset signals model characteristic vector composition array R [I]={ R (0), R (i) ..., R (I-1) },
In, the characteristic vector of the fiber-optic vibration signal is consistent with the extracting mode of characteristic vector of the preset signals model.
First determining module 53, for determining the distance between the characteristic vector T (0) and the characteristic vector R (0) g
(R (0), T (0)) and parameter M, wherein the difference between the M and the I and J is positively correlated.
First computing module 54, for it is each sequentially to calculate the array T [J] according to the distance g (R (0), T (0))
Characteristic vector T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until
The distance between the characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)) is calculated, wherein institute
State g (R (i), T (j)) by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-1)) it is calculated, each
The corresponding Partial Feature vector R (i) of characteristic vector T (j) include in the array R [I] characteristic vector R (max (j-M,
0)) to characteristic vector R (min (j+M, I-1)).
Second computing module 55, for calculate the distance g (R (I-1), T (J-1)) and the I and it is described J's and between
Ratio, using the similarity distance as the fiber-optic vibration signal and the preset signals model.
Second determining module 56 is used for when the similarity distance meets and imposes a condition, by the fiber-optic vibration signal
Vibration source type is determined as the corresponding vibration source type of the preset signals model.
Optionally, the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T
(j-1)) be calculated and specifically include: the g (R is calculated using above-mentioned formula 12 and formula 13 in the first computing module 54
(i),T(j))。
Optionally, the distance between the determination characteristic vector T (0) and the characteristic vector R (0) g (R (0), T
(0)) the step of includes: that using above-mentioned formula 11 the distance g (R (0), T (0)) is calculated in the first determining module 53.
Optionally, the first computing module 54 executes described according to the distance g (R (0), T (0)), sequentially calculates the number
Group T [J] each characteristic vector T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i),
T (j)) the step of include: that each characteristic vector T (j) of the array T [J] is sequentially calculated according to the distance g (R (0), T (0))
Respectively with the distance between the characteristic vector R (0) g (R (0), T (j))；Sequence calculates each characteristic vector of the array T [J]
T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), wherein as the j
When=0, the corresponding Partial Feature vector R (i) of the characteristic vector T (0) includes all features in the array R [I]
Vector, as the j ≠ 0, the corresponding Partial Feature vector R (i) of the characteristic vector T (j) includes the array R [I]
In characteristic vector R (max (j-M, 1)) to characteristic vector R (min (j+M, I-1)).
Optionally, the M=m+ | I-J |, m is a setting constant.
Optionally, it includes: by every frame that extraction module 52, which executes the step of characteristic vector for extracting every frame signal,
Subsignal passes through linear predictive coding lpc analysis respectively and obtains corresponding cepstrum coefficient, by the cepstrum system of every frame subsignal
Number is used as its characteristic vector.
Optionally, the device further include:
Pre-emphasis module, for carrying out preemphasis processing to the fiber-optic vibration signal, by preemphasis treated optical fiber
Vibration signal is sent to framing module 51.
Adding window module carries out windowing process to every frame subsignal for what framing module 51 exported；
Auto-correlation module, for carrying out autocorrelation analysis to every frame subsignal after the windowing process.
Wherein, the above-mentioned module of the identification device is respectively used to execute the corresponding steps in above method embodiment, specifically
Implementation procedure embodiment of the method explanation as above, therefore not to repeat here.
It is the structural schematic diagram of another embodiment of Recognition of Vibration Sources device of the present invention refering to Fig. 6, Fig. 6, which includes
Processor 61, memory 62, receiver 63 and bus 64.Wherein, processor 61, memory 62, receiver 63 may each be one
It is a or multiple, in Fig. 6 only for one.
Receiver 63 is used to receive the information of external equipment transmission.For example, reception optical fiber sensor detect by more
A sampling electric signal.
Memory 62 provides the computer program to processor 61, and can store place for storing computer program
Manage the data that device 61 is handled, such as multiple sampling electric signals that receiver 63 receives.Wherein, memory 62 may include read-only
At least one of memory, random access memory and nonvolatile RAM (NVRAM).
In embodiments of the present invention, the computer program that processor 61 is stored by executing memory 62, is used for:
Fiber-optic vibration signal is divided into J frame subsignal；For example, the fiber-optic vibration signal be receiver 63 receive it is more
One of sampling electric signal in a sampling electric signal.Processor can carry out vibration detection to multiple sampling electric signal,
When determining that one of sampling electric signal is fiber-optic vibration signal, above-mentioned framing is carried out to the fiber-optic vibration signal.
Characteristic vector composition array T [J]={ T (0), the T (j) ..., T (J-1) } of every frame subsignal is extracted, and is obtained pre-
If the array R [I] that the characteristic vector of signal model forms={ R (0), R (i) ..., R (I-1) }, wherein the fiber-optic vibration letter
Number characteristic vector it is consistent with the extracting mode of characteristic vector of the preset signals model；
Determine the distance between the characteristic vector T (0) and the characteristic vector R (0) g (R (0), T (0)) and parameter
M, wherein the difference between the M and the I and J is positively correlated；
According to the distance g (R (0), T (0)), sequentially calculate each characteristic vector T (j) of the array T [J] respectively with institute
Array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)) is stated, until the characteristic vector is calculated
The distance between T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)), wherein the g (R (i), T (j)) is by g (R
(i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-1)) be calculated, each characteristic vector T (j) is corresponding
The Partial Feature vector R (i) includes the characteristic vector R (max (j-M, 0)) to characteristic vector R (min in the array R [I]
(j+M,I-1))；
Calculate the distance g (R (I-1), T (J-1)) and the I and it is described J's and between ratio, using as the optical fiber
The similarity distance of vibration signal and the preset signals model；
It imposes a condition, the vibration source type of the fiber-optic vibration signal is determined as described pre- if the similarity distance meets
If the corresponding vibration source type of signal model.
Optionally, processor 61 execute the g (R (i), T (j)) by g (R (i-1), T (j)), g (R (i-1), T (j-1)),
Or g (R (i), T (j-1)) is calculated and specifically includes: g (R (i), the T is calculated using above-mentioned formula 12 and formula 13
(j))。
Optionally, processor 61 execute between the determination characteristic vector T (0) and the characteristic vector R (0) away from
It include: that the distance g (R (0), T (0)) is calculated using above-mentioned formula 11 from the step of g (R (0), T (0)).
Optionally, processor 61 executes described according to the distance g (R (0), T (0)), sequentially calculates the array T [J]
Each characteristic vector T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j))
The step of include: that each characteristic vector T (j) of the array T [J] is sequentially calculated respectively according to the distance g (R (0), T (0))
The distance between described characteristic vector R (0) g (R (0), T (j))；Sequence calculates each characteristic vector T (j) of the array T [J]
Respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), wherein as the j=0
When, the corresponding Partial Feature vector R (i) of the characteristic vector T (0) includes all Characteristic Vectors in the array R [I]
Amount, as the j ≠ 0, the corresponding Partial Feature vector R (i) of the characteristic vector T (j) includes in the array R [I]
Characteristic vector R (max (j-M, 1)) to characteristic vector R (min (j+M, I-1)).
Optionally, the M=m+ | I-J |, m is a setting constant.
Optionally, it includes: by every frame that processor 61, which executes the step of characteristic vector for extracting every frame signal,
Signal passes through linear predictive coding lpc analysis respectively and obtains corresponding cepstrum coefficient, by the cepstrum coefficient of every frame subsignal
As its characteristic vector.
Optionally, processor 61 is also used before executing described the step of fiber-optic vibration signal is divided into J frame subsignal
In to fiber-optic vibration signal progress preemphasis processing；
After executing described the step of fiber-optic vibration signal is divided into J frame subsignal, it is also used to: to every frame subsignal
Carry out windowing process；Autocorrelation analysis is carried out to every frame subsignal after the windowing process.
Above-mentioned processor 61 can also be known as CPU (Central Processing Unit, central processing unit).Specifically
Application in, the various components of terminal are coupled by bus 64, and wherein bus 64 may be used also in addition to including data/address bus
To include power bus, control bus and status signal bus in addition etc..But for the sake of clear explanation, by various buses in figure
All it is designated as bus 64.The method that aforementioned present invention embodiment discloses also can be applied in processor 61, or by processor
61 realize.
In above scheme, identification terminal is by calculating the characteristic vector of every frame subsignal of fiber-optic vibration signal and presetting letter
The distance of the characteristic vector of number model, to obtain the similarity between the fiber-optic vibration signal speech preset signals model, in turn
The vibration source type that fiber-optic vibration signal is determined by similarity realizes the vibration source classification to fiber-optic vibration signal, and the classification side
Formula can carry out Accurate classification to vibration source, improve the accuracy rate of Recognition of Vibration Sources, and identification terminal is only calculated according to setting rule
The distance between array T [J] each characteristic vector T (j) and array R [I] Partial Feature vector R (i), reduce operand, mention
High recognition speed and efficiency, save the process resource of identification terminal.
Mode the above is only the implementation of the present invention is not intended to limit the scope of the invention, all to utilize this
Equivalent structure or equivalent flow shift made by description of the invention and accompanying drawing content, it is relevant to be applied directly or indirectly in other
Technical field is included within the scope of the present invention.
Claims (10)
1. a kind of optical fiber Recognition of Vibration Sources method characterized by comprising
Fiber-optic vibration signal is divided into J frame subsignal by identification terminal；
Characteristic vector composition array T [J]={ T (0), the T (j) ..., T (J-1) } of every frame subsignal is extracted, and obtains default letter
Array R [I]={ R (0), the R (i) ..., R (I-1) } of the characteristic vector composition of number model, wherein the fiber-optic vibration signal
Characteristic vector is consistent with the extracting mode of characteristic vector of the preset signals model, and I is that the preset signals model includes
Subsignal frame sum；
Determine the distance between the characteristic vector T (0) and the characteristic vector R (0) g (R (0), T (0)) and parameter M,
In, the difference between the M and the I and J is positively correlated；
According to the distance g (R (0), T (0)), sequentially calculate each characteristic vector T (j) of the array T [J] respectively with the number
Group R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until the characteristic vector T (J- is calculated
1) with the distance between characteristic vector R (I-1) g (R (I-1), T (J-1)), wherein the g (R (i), T (j)) by g (R (i-1),
T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-1)) be calculated, the corresponding portion of each characteristic vector T (j)
Dividing characteristic vector R (i) includes the characteristic vector R (max (j-M, 0)) to characteristic vector R (min (j+M, I- in the array R [I]
1))；
Calculate the distance g (R (I-1), T (J-1)) and the I and it is described J's and between ratio, using as the fiber-optic vibration
The similarity distance of signal and the preset signals model；
It imposes a condition if the similarity distance meets, the vibration source type of the fiber-optic vibration signal is determined as the default letter
Number corresponding vibration source type of model.
2. the method as described in claim 1, which is characterized in that the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R
(i-1), T (j-1)) or g (R (i), T (j-1)) be calculated and specifically include:
The g (R (i), T (j)) is calculated using formula 1 and formula 2；
Wherein, the characteristic vector T (j) is expressed as (y1..., yn), the characteristic vector R (i) is expressed as (x1..., xn)。
3. method according to claim 2, which is characterized in that the determination characteristic vector T (0) and the characteristic vector
The step of the distance between R (0) g (R (0), T (0)) includes:
The distance g (R (0), T (0)) is calculated using formula 3；
G (R (0), T (0))=2d (T (0), R (0)) (3).
4. the method as described in claim 1, which is characterized in that described according to the distance g (R (0), T (0)), sequence calculates
The each characteristic vector T (j) of the array T [J] respectively with array R [I] at least partly the distance between characteristic vector R (i) g
The step of (R (i), T (j)) includes:
According to the distance g (R (0), T (0)), sequentially calculate each characteristic vector T (j) of the array T [J] respectively with the spy
Levy the distance between vector R (0) g (R (0), T (j))；
Sequence calculate each characteristic vector T (j) of the array T [J] respectively with array R [I] at least partly characteristic vector R
The distance between (i) g (R (i), T (j)), wherein as the j=0, the corresponding part of the characteristic vector T (0) is special
Sign vector R (i) includes all characteristic vectors in the array R [I], and as the j ≠ 0, the characteristic vector T (j) is corresponding
The Partial Feature vector R (i) include characteristic vector R (max (j-M, 1)) to characteristic vector R in the array R [I]
(min(j+M,I-1))。
5. the method as described in claim 1, which is characterized in that the M=m+ | I-J |, m is a setting constant.
6. the method as described in claim 1, which is characterized in that the step of characteristic vector for extracting every frame subsignal wraps
It includes:
Every frame subsignal is passed through into linear predictive coding lpc analysis respectively and obtains corresponding cepstrum coefficient, by every frame
The cepstrum coefficient of subsignal is as its characteristic vector.
7. method as claimed in claim 6, which is characterized in that fiber-optic vibration signal is divided into J frame subsignal described
Before step, the method also includes:
Preemphasis processing is carried out to the fiber-optic vibration signal；
After described the step of fiber-optic vibration signal is divided into J frame subsignal, the method also includes:
Windowing process is carried out to every frame subsignal；
Autocorrelation analysis is carried out to every frame subsignal after the windowing process.
8. a kind of optical fiber Recognition of Vibration Sources device characterized by comprising
Framing module, for fiber-optic vibration signal to be divided into J frame subsignal；
Extraction module, the characteristic vector for extracting every frame subsignal form array T [J]={ T (0), T (j) ..., T (J-1) },
And obtain array R [I]={ R (0), the R (i) ..., R (I-1) } of the characteristic vector composition of preset signals model, wherein the light
The characteristic vector of fine vibration signal is consistent with the extracting mode of characteristic vector of the preset signals model, and I is the default letter
The frame sum for the subsignal that number model includes；
First determining module, for determining the distance between the characteristic vector T (0) and the characteristic vector R (0) g (R (0), T
(0)) and parameter M, wherein the difference between the M and the I and J is positively correlated；
First computing module, for sequentially calculating each Characteristic Vectors of the array T [J] according to the distance g (R (0), T (0))
Measure T (j) respectively with array R [I] at least partly the distance between characteristic vector R (i) g (R (i), T (j)), until calculate
To the distance between the characteristic vector T (J-1) and characteristic vector R (I-1) g (R (I-1), T (J-1)), wherein the g (R
(i), T (j)) by g (R (i-1), T (j)), g (R (i-1), T (j-1)) or g (R (i), T (j-1)) it is calculated, each feature
The corresponding Partial Feature vector R (i) of vector T (j) include characteristic vector R (max (j-M, 0)) in the array R [I] extremely
Characteristic vector R (min (j+M, I-1))；
Second computing module, for calculate the distance g (R (I-1), T (J-1)) and the I and it is described J's and between ratio,
Using the similarity distance as the fiber-optic vibration signal and the preset signals model；
Second determining module is used for when the similarity distance meets and imposes a condition, by the vibration source class of the fiber-optic vibration signal
Type is determined as the corresponding vibration source type of the preset signals model.
9. device as claimed in claim 8, which is characterized in that the g (R (i), T (j)) is by g (R (i-1), T (j)), g (R
(i-1), T (j-1)) or g (R (i), T (j-1)) be calculated and specifically include:
The g (R (i), T (j)) is calculated using formula 1 and formula 2；
Wherein, the characteristic vector T (j) is expressed as (y1..., yn), the characteristic vector R (i) is expressed as (x1..., xn)。
10. a kind of fiber identification system, which is characterized in that including optical fiber, fibre optical sensor and identification terminal；
The fibre optical sensor is used to issue the first optical signal to described optical fiber one end, and receives from described optical fiber one end by described
The second optical signal that first optical signal reflects, and second optical signal is sampled to obtain multiple Sampled optical signals,
The multiple Sampled optical signals are converted to multiple sampling electric signals；
When the identification terminal is for determining that the first sampling electric signal is fiber-optic vibration signal, the fiber-optic vibration signal is carried out
Recognition of Vibration Sources, wherein the identification terminal includes the described in any item optical fiber Recognition of Vibration Sources devices of claim 8-9, to institute
It states fiber-optic vibration signal and carries out Recognition of Vibration Sources.
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| CN108132092A (en) * | 2016-12-01 | 2018-06-08 | 光子瑞利科技（北京）有限公司 | Threshold value optical fiber vibration event recognition methods is gone based on adaptive mean value |
| CN108287016A (en) * | 2017-01-10 | 2018-07-17 | 光子瑞利科技（北京）有限公司 | A kind of ocean optical fiber Recognition of Vibration Sources method, apparatus and system based on decision Tree algorithms |
| CN108387925A (en) * | 2017-05-08 | 2018-08-10 | 武汉普惠海洋光电技术有限公司 | Based on optical fiber the localization method of acoustic detector intruder detection system |
| CN109612568B (en) * | 2018-11-22 | 2021-06-29 | 北京航天易联科技发展有限公司 | Vibration source moving interference source identification method |
| CN109974835B (en) * | 2018-12-29 | 2021-06-04 | 无锡联河光子技术有限公司 | Vibration detection identification and space-time positioning method and system based on optical fiber signal characteristics |
| JP7016013B2 (en) * | 2019-02-05 | 2022-02-04 | 日本電信電話株式会社 | Vibration detection method, signal processing device and program |
| CN110672196B (en) * | 2019-08-22 | 2021-09-24 | 北京航天易联科技发展有限公司 | Mobile interference vibration source filtering method based on image operator |
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