CN108961638A - Vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm - Google Patents
Vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm Download PDFInfo
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- CN108961638A CN108961638A CN201810501167.4A CN201810501167A CN108961638A CN 108961638 A CN108961638 A CN 108961638A CN 201810501167 A CN201810501167 A CN 201810501167A CN 108961638 A CN108961638 A CN 108961638A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/02—Mechanical actuation
- G08B13/12—Mechanical actuation by the breaking or disturbance of stretched cords or wires
- G08B13/122—Mechanical actuation by the breaking or disturbance of stretched cords or wires for a perimeter fence
- G08B13/124—Mechanical actuation by the breaking or disturbance of stretched cords or wires for a perimeter fence with the breaking or disturbance being optically detected, e.g. optical fibers in the perimeter fence
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Abstract
The vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm that the present invention provides a kind of, it include: that (1) acquisition does not have the background noise data of intrusion event and the vibration signal waveforms data of intrusion event occur, it is formed sample set [X, Y]；(2) sample set [X, Y] is normalized, forms normalization sample setIn the normalization sample setIn randomly select part sample as training sample to training parameter, remaining sample is as test sample to test performance；(3) adding window sub-frame processing is carried out to training sample and obtains the detection signal X of the i-th framei(n)；(4) using the start-stop endpoint of wavelet coefficient energy and algorithm detection vibration optical fiber invasion signal, judge whether it is really invasion signal；(5) examine constructed detection start-stop endpoint model whether effective using test sample.The present invention using wavelet coefficient energy and come distinguish silent signal and invasion signal, more can accurately detect vibration optical fiber intrusion event.
Description
Technical field
The present invention relates to vibration optical fiber security system technical fields, specially a kind of to be based on wavelet coefficient energy and algorithm
Vibration optical fiber intrusion event detection method.
Background technique
The distribution of the places such as petroleum industry oil recovery website, transmission pipeline, oil depot is scattered, only one pipe of multiple oil recovery websites
Reason station is managed, and multiple monitoring machines are usually arranged in an oil recovery website, and staff is difficult to 24 hours and makes an inspection tour and manage
Reason.
Currently, vibration optical fiber technology is by feat of than other with the implementation of natural gas line yard " unattended " theory
Security and guard technology rate of false alarm is low, install convenient, is suitable for various forms of fences, and the advantages such as prevention that can realize no dead angle,
Related fields plays a significant role, because of " unattended ", so that stolen, theft and destructive insident happen occasionally.Therefore, circumference
Prevention is just particularly important.
Correct detection intrusion event is a complicated process, is related to environmental factor and human factor, due to component environment
Factor and human factor cause to alarm caused by signal characteristic it is similar, make the rate of false alarm and leakage of its current security pre-warning system
Report rate is high, and detection method is greatly limited because its signal characteristic is similar.And as China is to oil gas field shale gas
Devoting Major Efforts To Developing, to security system device require continuous promotion.Therefore, a kind of inspection suitable for vibration optical fiber intrusion event
Survey method is very necessary.
Summary of the invention
For the defects in the prior art, the present invention provides a kind of vibration optical fiber based on wavelet coefficient energy and algorithm
Intrusion event detection method distinguishes invasion signal and silent signal using wavelet coefficient energy and algorithm, can be compared with subject to
True detection vibration optical fiber intrusion event.
Technical solution of the present invention is as follows:
A kind of vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm, it is critical that including
Following steps:
Step 1: acquiring the background noise data for not having intrusion event and the vibration signal wave of intrusion event occurs
Graphic data is formed sample set [X, Y]；
Step 2: sample set [X, Y] being normalized, normalization sample set is formedIn the normalization
Sample setIn randomly select part sample as training sample to training parameter, remaining sample is used as test sample
With test performance；
Step 3: adding window sub-frame processing being carried out to training sample and obtains the detection signal X of the i-th framei(n)；
Step 4: using the start-stop endpoint of wavelet coefficient energy and algorithm detection vibration optical fiber invasion signal, judging whether
Really to invade signal；
Step 5: will be in test sampleIt is input in the test side point model for having determined that threshold value, and obtains as a result, will
Reality output in the result and test sampleIt is compared, it is constructed if comparison result is less than preset error value
Test side point model is effective；Otherwise 1 is repeated the above steps to step 5, until the comparison result is less than the preset error value
Until.
The invention has the following beneficial effects:
The vibration letter that the present invention acquires the background noise data for not having intrusion event first and intrusion event occurs
Number Wave data is formed sample set [X, Y], is normalized, and forms normalization sample setNormalize sample setIn randomly select part sample as training sample, remaining sample is as test sample；Pass through wavelet coefficient energy again
Silent signal and invasion signal are distinguished with algorithm, really invasion signal are judged whether it is, if there is continuous two spaces node
Invasion signal is shown, then determines that there is intrusion behavior in the position, and then judges whether that intrusion event occurs；Finally by
Whether the original inspection result of test specimens is accurate.The present invention can accurately judge whether vibration optical fiber occurs intrusion event,
Reduce the rate of false alarm and rate of failing to report of vibration optical fiber security system.
Detailed description of the invention
It, below will be to tool in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Body embodiment or attached drawing needed to be used in the description of the prior art are briefly described.In all the appended drawings, similar member
Part or part are generally identified by similar appended drawing reference.In attached drawing, each element or part might not be drawn according to actual ratio
System.
Fig. 1 is that vibration optical fiber invades signal detection flow chart；
Fig. 2 is that (a is to lose stone to the corresponding vibration optical fiber signal original waveform figure of different invasion modes, and b is climbing, and c is
It taps)；
Fig. 3 is the original waveform figure for losing stone invasion sample, in short-term wavelet coefficient energy and distribution map；
Fig. 4 is the original waveform figure for climbing invasion sample, in short-term wavelet coefficient energy and distribution map；
Fig. 5 is the original waveform figure for tapping invasion sample, in short-term wavelet coefficient energy and distribution map；
Fig. 6 is vibration optical fiber part invasion signal detecting result figure (a is to lose stone, and b is climbing, and c is to tap).
Specific embodiment
The embodiment of the present invention is described in further detail with reference to the accompanying drawing.
A kind of vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm as shown in Figure 1, by with
Lower step carries out:
Step 1: acquiring the background noise data for not having intrusion event and the vibration signal wave of intrusion event occurs
Graphic data is formed sample set [X, Y].
Step 2: being normalized and go mean value to sample set [X, Y], form normalization sample setInstitute
State normalization sample setIn randomly select 60% sample as training sample to training parameter, remaining 40% sample
This is as test sample to test performance.
Step 3: adding window sub-frame processing being carried out to training sample and obtains the detection signal X of the i-th framei(n), wherein the selected Chinese
Bright window function is as follows:
In above formula, M is window size, and n is discrete detection signal time sequence；
Sub-frame processing is as follows:
In above formula, wlen is the length of each frame, lap of the Overlap between adjacent two frame, and Overlap
=wlen-inc moves for inc frame, is displacement of a later frame relative to former frame, each frame is denoted as n=1, and 2 ..., N, n are
Discrete detection signal time sequence, N are detection signal total length, and i indicates frame number.
Step 4: the start-stop endpoint of the invasion signal of vibration optical fiber, judgement are detected using wavelet coefficient energy and algorithm
It whether is true card invasion signal, specifically, step 4 includes:
Step 4.1: calculate wavelet coefficient energy and, by the signal x after framingn[m] and low-pass filter and high-pass filtering
Device does convolution, does wavelet decomposition to signal, obtains two groups of wavelet coefficients, respectively every layer of wavelet coefficient and every layer of wavelet systems
Several numbers；
Function based on wavelet transform:
ψ(x)I, k=2-j/2ψ(2-jx-k) (3)
In above formula, j is wavelet transformation contraction-expansion factor, and k is wavelet transformation shift factor.
Scalar function is used in decomposable process, formula is as follows:
φ(x)I, k=2-j/2Φ(2-jx-k) (4)
M layers of wavelet coefficient energy:
In above formula, NmIt is the number of m layers of wavelet coefficient；It is m b-th of wavelet coefficient of layer；
In short-term wavelet coefficient energy and:
Here is that one group of knocking is tested, and the energy of wavelet coefficient in short-term and data of each frame are as shown in the table:
Table 1
Step 4.2: finding optimum threshold, the starting thresholding th of setting invasion thingin, terminate thresholding thout, it is maximum silent
Length maxsilence and minimum signal length minsignal is held, wherein starting thresholding thinWith termination thresholding thoutSet
Surely be concentrate the wavelet coefficient energy and E of all background signals by calculating training sample, meanwhile, training sample concentration is entered
It invades the wavelet coefficient energy of signal and is accordingly calculated, obtain the approximate extents of characteristic value first, secondly in the close of characteristic value
Like one group of starting thresholding th given in rangeinWith termination thresholding thout, search out maximum silence end length maxsilence and most
Small signal length minsignal, after determining maximum silence end length maxsilence and minimum signal length minsignal,
Using grid data service, by the start-stop endpoint parameter th with optimum detection performanceinAnd thoutIt is arranged as optimized parameter.
Judge that the condition of intrusion event starting point is greater than th for signal f in step 4.2in, judge the condition of intrusion event terminal
It is less than th for signal foutAnd the event silence end length silence_len is greater than maximum silence end length maxsilence；
Minimum signal length minsignal whether is had reached by the invasion signal length that the judgement of start-stop endpoint detects, if reached
Minimum signal length, then be judged as invasion signal, is otherwise considered as interfering and abandon.
Step 4.3: the signal frame of each space nodes is successively traversed, detecting the node, whether there is or not invasions, until the last one
Processing terminate for the signal frame of space nodes, if there is continuous two spaces node to show invasion signal, determine the position have into
Invade behavior.
Step 4.4, entered in vibration signal using wavelet coefficient energy in short-term and differentiation invasion signal and silent signal
Invading signal and silent signal has different wavelet coefficient energy and feature, and the wavelet coefficient energy and feature are invasion letter
Number energy value it is larger, the energy value of silent signal is smaller, therefore can use wavelet coefficient energy and distinguish invasion signal
And silent signal, calculate the space nodes signal frame the energy of wavelet coefficient in short-term and, if wavelet coefficient energy and being greater than in short-term
The energy of wavelet coefficient in short-term and threshold value of the point, then be judged to invading signal；Otherwise determine to return to step there is no invasion signal
Rapid 4.3.
Step 5: will be in 40% test sampleIt is input in the test side point model for having determined that threshold value, works as survey
After the completion of this input of sample, will be obtained in the form of marking whole story endpoint on original signal waveform figure as a result, being obtained described
As a result with the reality output in the test sampleIt is compared, it is constructed if comparison result is less than preset error value
Test side point model is effective；Otherwise 1 is repeated the above steps to step 5, until the comparison result is less than the preset error value
Until.
As shown in Figures 2 to 6 using method of the invention to lose the intrusion events such as stone, climbing, percussion test to obtain as
Lower technical effect:
Fig. 2 is that (a is to lose stone to the corresponding vibration optical fiber signal original waveform figure of different invasion modes, and b is climbing, and c is
It taps)；Fig. 3 is the original waveform for losing stone invasion sample, in short-term wavelet coefficient energy and distribution map；Fig. 4 is climbing invasion sample
This original waveform, in short-term wavelet coefficient energy and distribution map；Fig. 5 is the original waveform for tapping invasion sample, in short-term wavelet systems
Number energy and distribution map；Fig. 6 is that (a is to lose stone to vibration optical fiber part invasion signal detecting result figure, and b is climbing, and c is to strike
It hits)；
Invading signal using the part of wavelet coefficient energy in short-term and algorithm detection vibration optical fiber, (a is to lose stone, and b is to climb
Climb, c be tap) start-stop endpoint, laboratory test results as shown in fig. 6, wherein dotted line indicate invasion signal starting point, strokes and dots
Line indicates the terminal of invasion signal, the experimental results showed that a loses stone, b climbing, c percussion is invasion signal, and then judging should
Whether position occurs intrusion behavior.
By carrying out invasion signal detection analysis to 300 groups of test samples.Wavelet coefficient energy is utilized by statistics
Correctly detect that invasion signal start-stop endpoint reaches about 96.23% with algorithm, omission factor about 3.77% meets and determines invasion thing
The error requirements of part endpoint.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, those skilled in the art should understand that；It is still
It can modify to technical solution documented by previous embodiment, or some or all of the technical features are carried out
Equivalent replacement；And these are modified or replaceed, technical solution of the embodiment of the present invention that it does not separate the essence of the corresponding technical solution
Range, should all cover within the scope of the claims and the description of the invention.
Claims (4)
1. a kind of vibration optical fiber intrusion event detection method based on wavelet coefficient energy and algorithm, which is characterized in that including with
Lower step:
Step 1: acquiring the background noise data for not having intrusion event and the vibration signal waveforms number of intrusion event occurs
According to formation sample set [X, Y]；
Step 2: sample set [X, Y] being normalized, normalization sample set is formedIn the normalization sample
CollectionIn randomly select part sample as training sample to training parameter, remaining sample is as test sample to survey
Try performance；
Step 3: adding window sub-frame processing being carried out to training sample and obtains the detection signal X of the i-th framei(n)；
Step 4: using the start-stop endpoint of wavelet coefficient energy and algorithm detection vibration optical fiber invasion signal, judging whether it is real
Invade signal；
Step 5: will be in test sampleIt is input in the test side point model for having determined that threshold value, and obtains as a result, will be described
As a result with the reality output in test sampleIt is compared, if comparison result is less than preset error value, constructed detection
Endpoint model is effective；Otherwise 1 is repeated the above steps to step 5, until the comparison result is less than the preset error value.
2. the vibration optical fiber intrusion event detection method according to claim 1 based on wavelet coefficient energy and algorithm,
It is characterized in that, adding window sub-frame processing is carried out to training sample in step 3 and obtains the detection signal X of the i-th framei(n), wherein the selected Chinese
Bright window function is as follows:
In above formula, M is window size, and n is discrete detection signal time sequence；
Sub-frame processing is as follows:
In above formula, wlen is the length of each frame, lap of the Overlap between adjacent two frame, and Overlap=
Wlen-inc moves for inc frame, is displacement of a later frame relative to former frame, and each frame is denoted as n=1,2 ..., N, n be from
Detection signal time sequence is dissipated, N is detection signal total length, and i indicates frame number.
3. the vibration optical fiber intrusion event detection method according to claim 1 based on wavelet coefficient energy and algorithm,
It is characterized in that, step 4 includes:
Step 4.1: calculate wavelet coefficient energy and, by the signal x after framingn[m] is rolled up with low-pass filter and high-pass filter
Product, does wavelet decomposition to signal, obtains two groups of wavelet coefficients, of respectively every layer of wavelet coefficient and every layer of wavelet coefficient
Number；
Function based on wavelet transform:
ψ(x)I, k=2-j/2ψ(2-jx-k) (3)
In above formula, j is wavelet transformation contraction-expansion factor, and k is wavelet transformation shift factor.
Scalar function is used in decomposable process, formula is as follows:
φ(x)I, k=2-j/2Φ(2-jx-k) (4)
M layers of wavelet coefficient energy:
In above formula, NmIt is the number of m layers of wavelet coefficient；It is m b-th of wavelet coefficient of layer；
In short-term wavelet coefficient energy and:
Step 4.2: finding optimum threshold, the starting thresholding th of setting invasion thingin, terminate thresholding thout, maximum silent end it is long
Maxsilence and minimum signal length minsignal is spent, wherein starting thresholding thinWith termination thresholding thoutSetting be logical
It crosses and calculates wavelet coefficient energy and E that training sample concentrates all background signals, meanwhile, the invasion signal that training sample is concentrated
Wavelet coefficient energy and accordingly calculated, obtain the approximate extents of characteristic value first, next characteristic value approximate extents
It is interior to give one group of starting thresholding thinWith termination thresholding thout, search out maximum silence end length maxsilence and minimum signal
Length minsignal uses net after determining maximum silence end length maxsilence and minimum signal length minsignal
Lattice search, by the start-stop endpoint parameter th with optimum detection performanceinAnd thoutIt is arranged as optimized parameter；
Step 4.3: successively traversing the signal frame of each space nodes, detecting the node, whether there is or not invasions, until the last one space
Processing terminate for the signal frame of node, if there is continuous two spaces node to show invasion signal, determines that the position has invasion to go
To occur；
Step 4.4: using wavelet coefficient energy and distinguishing invasion signal and silent signal, calculate the small of the space nodes signal frame
Wave system number energy and, if wavelet coefficient energy and wavelet coefficient energy and threshold value greater than the point, are judged to invading signal；If
It is not greater than the wavelet coefficient energy and threshold value of the point, then is judged to returning to step 4.3 there is no invasion signal.
4. the vibration optical fiber intrusion event detection method according to claim 3 based on wavelet coefficient energy and algorithm,
It is characterized in that, judges that the condition of intrusion event starting point is greater than th for signal f in step 4.2in, judge the condition of intrusion event terminal
It is less than th for signal foutAnd the event silence end length silence_len is greater than maximum silence end length maxsilence；It is logical
Cross whether the invasion signal length that the judgement of start-stop endpoint detects has reached minimum signal length minsignal, if reached most
Small signal length, then be judged as invasion signal, is otherwise considered as interfering and abandon.
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