CN111854920A - Preprocessing method and system based on DVS vibration monitoring signal - Google Patents
Preprocessing method and system based on DVS vibration monitoring signal Download PDFInfo
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Abstract
The invention discloses a preprocessing method and a system based on a DVS vibration monitoring signal, which comprises the steps of connecting a DVS and an optical cable to be monitored to monitor the vibration signal thereof, and establishing two-dimensional distribution data; respectively calculating the data of the vibration-free moment and the signal amplitude and phase of the kth space point by utilizing Fourier transform based on the two-dimensional distribution data to obtain a spectral subtraction result of the space points; carrying out inverse Fourier transform on the space points to obtain denoised signals; calculating the mean value of each point time domain of the denoised signal and smoothing the mean value; and respectively removing the trend of a space domain, the trend of a direct current quantity and the trend of a time domain by using the smoothed signals to finish the preprocessing. The invention solves the problem that the decision threshold of the event is difficult to determine when processing the signals generated at different positions on the circuit in the distributed vibration monitoring system by preprocessing the signals to be detected, and simultaneously effectively reduces the noise of the signals, especially the noise of the signals at the tail end of the monitoring system.
Description
Technical Field
The invention relates to the technical field of vibration signal monitoring, in particular to a method and a system for preprocessing a DVS vibration monitoring signal.
Background
A distributed optical fiber vibration monitoring system (DVS) is a sensing system which utilizes optical fibers as sensing sensitive elements and transmission signal media, can continuously sense the space distribution and time change information of vibration dynamic parameters in a transmission path, and has the advantages of high sensitivity, no source in the whole process, simultaneous multi-point positioning and the like. The interference effect between the backward Rayleigh scattering light in the optical pulse width is utilized, the method is a new technology for combining the interference effect and the backward Rayleigh scattering, and the advantages of high sensitivity and long-distance distributed measurement of the interference effect and the backward Rayleigh scattering are well combined.
Although DVS has been used in the fields of structural health, perimeter intrusion prevention, power monitoring, etc., it has problems to deal with since it is completely different from the conventional sensor principle.
Firstly, it can be known from the DVS principle that when there is disturbance on the optical fiber, the coherent waveform of the rayleigh backscatter signal at the corresponding position of the monitoring curve changes; conversely, when there is no disturbance on the fiber, the monitoring curve should remain unchanged. However, in actual measurement, due to the influence of various factors such as temperature and humidity, a small-range slow frequency drift exists in the wavelength and power of the laser, so that the DVS monitoring curve is continuously and slowly distorted even if no disturbance is added to the optical fiber, and the distortion is represented as a low-frequency trend value on a time domain signal. Distortion-induced low frequency noise may overwhelm the amplitude variations due to fiber disturbances, making the disturbance events difficult to detect, and therefore time domain trend values need to be removed in order to remove such low frequency disturbances.
Second, optical signals are no exception because any signal experiences attenuation during propagation, for example, the attenuation of 1550nm wavelength light in single mode fiber G652D is typically 0.18-0.25 dB/km. The strength of the end signal detected by the system is necessarily different from the strength of the front-end signal. This results in the inability to process signals at different locations in the fiber according to the same threshold, and therefore requires the removal of spatially trended values in order to remove the effects of attenuation.
Third, the noise amplitude of the system is substantially fixed, whether for the duration of the front-end signal or the back-end signal in the fiber, and the signal-to-noise ratio is relatively worse because the signal amplitude at the back-end of the fiber is smaller. The further the signal is from the device, the poorer the signal-to-noise ratio. In addition, due to the influence of the factor of "interference fading", the amplitude variation of the DVS in the space is not uniformly distributed — there are large fluctuations in the amplitude in the space, which also results in that the conventional data denoising method for the point sensor cannot be directly applied to the distributed sensing monitoring system.
In order to overcome the problems that the threshold value cannot be unified in the subsequent data processing and the reliability of the system operation is possibly influenced due to the change of the signal-to-noise ratio, the acquired initial signal needs to be preprocessed. Otherwise, when the same system processes signals occurring at different positions on the line to be measured, the decision threshold of the event is difficult to determine. Therefore, a preprocessing method for the DVS vibration monitoring signal is needed to be found, so that the influence caused by different noises on the spatial distribution of the system is reduced as much as possible, and the vibration signals to be measured at different positions on the line can be mapped into the same standard scale.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The invention is provided in view of the problem that the decision threshold of the event is difficult to determine when processing the signals generated at different positions on the line in the distributed vibration monitoring system.
Therefore, the technical problem solved by the invention is as follows: the method can map the vibration signals to be detected at different positions on a circuit into the same standard scale by preprocessing the signals to be detected, and is convenient for subsequent signal analysis.
In order to solve the technical problems, the invention provides the following technical scheme: connecting the DVS with an optical cable to be monitored to monitor a distributed vibration signal, and establishing two-dimensional distribution data of time and space based on the vibration signal; selecting data at a non-vibration moment and a signal of a k-th space point based on the two-dimensional distribution data, and respectively calculating the amplitude and the phase of the data and the signal of the k-th space point in the vibration signal by utilizing Fourier transform to obtain a spectral subtraction result of the k-th space point; performing inverse Fourier transform on the kth space point to obtain a denoised signal; calculating the time domain mean value of each point of the denoised signal and smoothing the time domain mean value of each space point; and respectively removing the trend of a space domain, the trend of a direct current quantity and the trend of a time domain by using the signals after the smoothing treatment to finish the pretreatment.
As a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: establishing two-dimensional distribution data of time and space based on the vibration signal, wherein the two-dimensional distribution data comprises the steps of defining the length of the optical fiber to be measured as L, the time length of each acquisition as T, the event sampling rate of the system as Fs, collecting M points by the system on the length (namely space) of the optical fiber, and collecting N points by the system on the time; the measured vibration data are arranged into a two-dimensional array X with the size of M multiplied by N according to space-time, and an element X (k, j) of the two-dimensional array X is defined as the vibration signal intensity of a space point k at a time j; the vibration signals of the k-th space point in X at all time are expressed by X (k,: then X (k,: is) is expressed as a row vector with the size of X.
As a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: calculating the amplitude and phase of the signal at the k-th space point in the vibration signal by using Fourier transform, wherein the amplitude and phase of the signal at the k-th space point in X0 are respectively calculated by performing fast Fourier transform on a signal sequence X0 (k): which is represented by F0 ═ A0+ B0:, wherein A0 represents a real part sequence of the fast Fourier transformed signal, B0:representsan imaginary part sequence of the fast Fourier transformed signal, and i is a unit imaginary number; using Amp0 to represent the amplitude sequence of the transformed signal, and Angle0 to represent the phase Angle sequence of the transformed signal, then:
performing fast Fourier transform on a signal X (k,: in a k-th space point in the vibration data X, wherein the transformed signal is represented as F ═ A + B:, A represents a real part sequence of the fast Fourier transformed signal, B:representsan imaginary part sequence of the fast Fourier transformed signal, and i is a unit imaginary number; using Amp to represent the amplitude sequence of the transformed signal, and Angle to represent the phase Angle sequence of the transformed signal, then:
as a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: the k-th spaceThe result of the spectral subtraction of the inter-point comprises the steps of calculating the amplitude difference value of the original signal and the noise signal, and defining the amplitude and the phase angle after denoising as Ampnew、Anglenew(ii) a The phase AnglenewCan be maintained unchanged as follows:
Anglenew＝Angle
the frequency spectrum Y after the spectral subtractionnewNamely:
Ynew＝Ampnew·sin(Anglenew)+Ampnew·cos(Anglenew)·i
as a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: performing inverse Fourier transform on the k-th space point to obtain a denoised signal, including for YnewInverse Fourier transform is performed, the real part is taken, and the obtained sequence is recorded as xkThen xkX (k) represents a row vector with the size of 1 multiplied by N after the signal is denoised by the spectral subtraction; k sequentially taking 1,2,3, … and M, and processing according to the steps to obtain a denoised signal x of each space point1,x2,x3，...,xMAnd then the two-dimensional array X denoises the signal XfiltedI.e. can be represented as:
as a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: calculating the mean value of each point in time domain of the denoised signal, including, based on the denoised signal XfiltedCalculating the long-time statistical average value of the signals of each space point, and recording the sequence points formed by the average values of all the space points as
It is expressed as 1 inA column vector of M; each point in space fluctuates around a central point, so a long-term statistical average is approximately equivalent to the central point of the signal fluctuation.
As a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: removing trend and direct current quantity of space domain includes defining the signal after removing trend on space as XnormCompleting the spatial detrending and direct current quantity processing of each spatial point signal; the process of detrending and dc-flow of the signal at time j for space point k is:
wherein, Xfilted(k, j) is the denoised vibration signal intensity of the space point k at the time j,
the signal mean intensity after the spatial point k smoothing is obtained.
As a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: time domain de-trending process, including, for XnormAnd carrying out high-pass filtering on the signals by space points to filter the trend of the signals in time.
As a preferable aspect of the DVS vibration monitoring signal-based preprocessing method according to the present invention, wherein: smoothing the time domain mean value of each space point, including
Smoothing the large-scale window to remove burrs in the signal, and recording the smoothed signal as
As a preferable aspect of the DVS vibration monitor signal-based preprocessing system according to the present invention, wherein: the monitoring module comprises a DVS and an optical cable to be monitored, and is used for monitoring a distributed vibration signal; the statistical module is connected with the monitoring module and used for obtaining a spectral subtraction result of the kth space point; the denoising module is connected with the statistical module and used for obtaining denoised signals, calculating the time domain mean value of each point of the denoised signals and smoothing the time domain mean value of each space point; the de-trending module is connected with the statistical module and comprises a spatial domain de-trending module and a time domain de-trending module, and is used for removing the trending of the spatial domain and the trending of the direct current and the time domain and finishing the preprocessing.
The invention has the beneficial effects that: the invention can map the vibration signals to be detected at different positions on the line into the same standard scale by preprocessing the signals to be detected, solves the problem that the judgment threshold of an event is difficult to determine when processing the signals occurring at different positions on the line in the distributed vibration monitoring system, and effectively reduces the noise of the signals, especially the noise of the signals at the tail end of the monitoring system.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
FIG. 1 is a flowchart illustrating the operation of a DVS vibration monitor signal-based preprocessing method according to the present invention;
FIG. 2 is a schematic diagram of a data monitoring process for providing a DVS vibration monitoring signal based preprocessing method of the present invention;
FIG. 3 is a signal at each spatial point at a time of a pre-processing method for providing a vibration monitor signal based on DVS according to the present invention;
fig. 4 shows a denoised signal of each spatial point at a certain time and a signal smoothed by a window of 201 size using a statistical mean signal according to a preprocessing method for DVS vibration monitoring signals provided by the present invention;
FIG. 5 is a diagram illustrating a signal after removing spatial trends at spatial points at different times according to a DVS vibration monitoring signal preprocessing method of the present invention;
FIG. 6 is a set of tap signal comparisons before and after removing temporal trends for a pre-processing method based on DVS vibration monitor signals according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1, a basic flowchart of a DVS vibration monitoring signal-based preprocessing method is provided for a first embodiment of the present invention, a DVS is connected to an optical cable to be monitored to monitor a distributed vibration signal, and time and space two-dimensional distribution data based on the vibration signal is established; selecting data at a non-vibration moment and a signal of a k-th space point based on the two-dimensional distribution data, and respectively calculating the amplitude and the phase of the data and the signal of the k-th space point in the vibration signal by utilizing Fourier transform to obtain a spectral subtraction result of the k-th space point; performing inverse Fourier transform on the kth space point to obtain a denoised signal; calculating the time domain mean value of each point of the denoised signal and smoothing the time domain mean value of each space point; and respectively removing the trend of a space domain, the trend of a direct current quantity and the trend of a time domain by using the signals after the smoothing treatment to finish the pretreatment.
S1: creating two-dimensional distribution data of time and space based on the vibration signal, wherein the step of creating two-dimensional distribution data includes,
connecting the DVS with a core redundant fiber of the optical cable to be monitored to realize the monitoring of the distributed vibration signal in the optical cable;
defining the length of an optical fiber to be measured as L, the time length of each acquisition as T, the event sampling rate of the system as Fs, and acquiring M points by the system on the length (namely space) of the optical fiber and acquiring N points in time;
the measured vibration data are arranged into a two-dimensional array X with the size of M multiplied by N according to space-time, and an element X (k, j) of the two-dimensional array X is defined as the vibration signal intensity of a space point k at a time j;
the vibration signals of the k-th space point in X at all time are expressed by X (k,: then X (k,: is) is expressed as a row vector with the size of X.
S2: the amplitude and phase of the signal with the k-th spatial point in the vibration signal are calculated separately using fourier transform, specifically,
selecting a group of signals X0 without obvious vibration at each position on the optical fiber to be tested based on the measured data, wherein X0 only contains the information of system noise;
performing fast fourier transform on a signal sequence X0(k,: in a k-th space point in X0, wherein the transformed signal sequence is represented as F0 ═ a0+ B0 ×, where a0 represents a real part sequence of the fast fourier transformed signal, B0 × i represents an imaginary part sequence of the fast fourier transformed signal, and i is a unit imaginary number;
using Amp0 to represent the amplitude sequence of the transformed signal, and Angle0 to represent the phase Angle sequence of the transformed signal, then:
performing fast Fourier transform on a signal X (k,: in a k-th space point in the vibration data X, wherein the transformed signal is represented as F ═ A + B:, A represents a real part sequence of the fast Fourier transformed signal, B:representsan imaginary part sequence of the fast Fourier transformed signal, and i is a unit imaginary number;
using Amp to represent the amplitude sequence of the transformed signal, and Angle to represent the phase Angle sequence of the transformed signal, then:
it should be noted that the result of the spectral subtraction for the k-th spatial point obtained by calculation is as follows,
calculating the amplitude difference value of the original signal and the noise signal, and defining the amplitude and the phase angle after denoising as Ampnew、Anglenew；
Considering that the phase of the vibration signal is not generally concerned in practical applications, the phase AnglenewCan be maintained unchanged as follows:
Anglenew＝Angle
the frequency spectrum Y after the spectral subtractionnewNamely:
Ynew＝Ampnew·sin(Anglenew)+Ampnew·cos(Anglenew)·i
the vibration signal monitored by the DVS is denoised based on spectral subtraction, and system noise, particularly noise of a signal at the rear end of the optical fiber to be detected, is reduced.
S3: performing inverse Fourier transform on the k-th space point to obtain a denoised signal, wherein the inverse Fourier transform is performed by the following steps,
for YnewInverse Fourier transform is performed, the real part is taken, and the obtained sequence is recorded as xkThen xkThe signal is X (k): denoised by spectral subtraction, and a row vector with the size of 1 multiplied by N is represented.
Taking 1,2 and 3 … M in sequence for k, and processing according to the steps to obtain a denoised signal x of each space point1,x2,x3，...,xMAnd then the two-dimensional array X denoises the signal XfiltedI.e. can be represented as:
s4: calculating the time domain mean value of each point of the denoised signal, wherein the calculation steps are as follows,
based on denoised signal XfiltedCalculating the long-time statistical average value of the signals of each space point, and recording the sequence points formed by the average values of all the space points as
It is represented as a column vector of size 1 × M;
since each point in space fluctuates around a central point, a statistical average over a long period of time is approximately equivalent to the central point of the signal fluctuation.
Wherein the step of smoothing the time domain mean value of each spatial point is as follows,
to pair
Smoothing the large-scale window to remove burrs in the signal, and recording the smoothed signal as
The denoised signal of each spatial point at a certain time and the signal smoothed by a window with the size of 201 as a statistical average signal monitored by the system are shown in fig. 4.
S5: and respectively removing the trend of a space domain, the trend of direct current and the trend of a time domain by using the smoothed signals, so that the vibration signals to be detected at different positions on the line can be mapped into the same standard scale to finish the pretreatment.
It should be noted that, the specific steps of removing trend and dc flow in the spatial domain include,
defining the signal after removing the spatial trend as XnormGo to finishAnd performing spatial detrending and direct current amount processing on the signals of each spatial point.
The process of detrending and dc-flow of the signal at time j for space point k is:
wherein, Xfilted(k, j) is the denoised vibration signal intensity of the space point k at the time j,
the signal mean intensity after the spatial point k smoothing is obtained.
The second time domain de-trending process step includes,
considering the variation of the signal at low frequency, the time-detrending process is actually equivalent to a high-pass filter to filter the slowly distorted trend values;
based on pair XnormAnd carrying out high-pass filtering on the signals by space points to filter the trend of the signals in time.
The above steps are the DVS vibration monitoring signal preprocessing process.
The technical effects adopted in the method are verified and explained, the embodiment selects the traditional technical scheme normalized signal processing method and adopts the method to carry out comparison test, and the test results are compared by means of scientific demonstration to verify the real effect of the method.
The traditional technical scheme eliminates the problem that the judgment threshold is difficult to determine due to the fact that the signals to be identified have range difference and the difference generated by different events is too large through normalization processing, and concretely normalizes the range of all the signal values to the range of [ -1,1]Within the interval, if x (t) is the signal to be identified, the normalized signal can be obtained according to the following formula
Based on the detection result, the problem that the event decision gate is difficult to determine is not effectively solved in the conventional technical scheme, and low-frequency noise affects the reliability of system operation.
The method of the invention is optimized and tested by experiments to obtain the optimized result, the optimized process and the optimized effect are as follows,
as shown in fig. 2, the monitoring principle and the vibration data source of the invention are that the DVS is connected with a core redundant fiber of the optical cable to be monitored to realize the monitoring of the distributed vibration signal in the optical cable, and fig. 3 shows that the monitoring data really has signal attenuation and uneven distribution in space; establishing two-dimensional distribution data according to the monitored signals, selecting data at a vibration-free moment and a signal at a k-th space point, performing Fourier transform and inverse transform of Fourier transform on the data to obtain denoised signals, calculating time domain mean values of all points of the denoised signals, and performing smoothing processing on the time domain mean values of all the space points, wherein the denoised signals of all the space points at a certain moment monitored by a system and the signals of which statistical mean values are smoothed through a window with the size of 201 are shown in figure 4, which shows that the signals are actually fluctuated around the statistical mean values; the smoothed signal is used to remove the trend of the spatial domain, the trend of the direct current and the trend of the time domain respectively, as shown in fig. 5, the signal obtained by removing the spatial trend at each spatial point at different time in the invention shows that the method can effectively extract the trend in the space and pull the signal to the same level; fig. 6 shows a set of comparison of the tapping signals before and after removing the trend in time in the present invention, which illustrates that the method can effectively filter the trend in time in the original signal, so that the vibration signal is more clearly shown.
The beneficial effects of the invention are more clearly shown by the comparison of the figure data, the vibration signals to be detected at different positions on the line can be mapped into the same standard scale by preprocessing the signals to be detected, and the problem that the judgment threshold of an event is difficult to determine when the signals occurring at different positions on the line in the distributed vibration monitoring system are processed is solved; meanwhile, the noise of the signal, especially the noise of the signal at the tail end of the monitoring system, is effectively reduced.
Example 2
The foregoing embodiment is implemented based on a DVS vibration monitoring signal preprocessing method, depending on the system of the present embodiment. The system comprises a monitoring module, a statistical module, a denoising module and a trend removing module.
More specifically, the monitoring module is used for connecting the DVS with an optical cable to be monitored to monitor a distributed vibration signal and establishing two-dimensional distribution data of time and space based on the vibration signal;
the statistical module is connected with the monitoring module, based on the two-dimensional distribution data, the data at the vibration-free moment and the signal of the kth space point are selected, the amplitude and the phase of the signal of the kth space point in the vibration signal are respectively calculated by utilizing Fourier transform, and the amplitude and the phase are used for obtaining a spectral subtraction result of the kth space point;
the denoising module is connected with the statistical module and used for obtaining denoised signals by performing inverse Fourier transform on the kth space point; calculating the time domain mean value of each point of the denoised signal and smoothing the time domain mean value of each space point;
and the de-trend module is connected with the statistical module and is used for respectively removing the trend of a space domain, the trend of a direct current quantity and the trend of a time domain by utilizing the signals after the smoothing processing so as to finish the preprocessing.
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein. A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
As used in this application, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (10)
1. A preprocessing method based on DVS vibration monitoring signals is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
connecting the DVS with an optical cable to be monitored to monitor a distributed vibration signal, and establishing two-dimensional distribution data of time and space based on the vibration signal;
selecting data at a non-vibration moment and a signal of a k-th space point based on the two-dimensional distribution data, and respectively calculating the amplitude and the phase of the data and the signal of the k-th space point in the vibration signal by utilizing Fourier transform to obtain a spectral subtraction result of the k-th space point;
performing inverse Fourier transform on the kth space point to obtain a denoised signal;
calculating the time domain mean value of each point of the denoised signal and smoothing the time domain mean value of each space point;
and respectively removing the trend of a space domain, the trend of a direct current quantity and the trend of a time domain by using the signals after the smoothing treatment to finish the pretreatment.
2. A method of pre-processing based on DVS vibration monitor signals as recited in claim 1, wherein: establishing two-dimensional distribution data based on time and space of the vibration signal, including,
defining the length of an optical fiber to be measured as L, the time length of each acquisition as T, the event sampling rate of the system as Fs, and acquiring M points by the system on the length (namely space) of the optical fiber and acquiring N points in time;
the measured vibration data are arranged into a two-dimensional array X with the size of M multiplied by N according to space-time, and an element X (k, j) of the two-dimensional array X is defined as the vibration signal intensity of a space point k at a time j;
the vibration signals of the k-th space point in X at all time are expressed by X (k,: then X (k,: is) is expressed as a row vector with the size of X.
3. A DVS vibration monitor signal based preprocessing method as claimed in claim 2 wherein: calculating the amplitude and phase of the signal with the k-th spatial point in the vibration signal by using Fourier transform, respectively, including,
performing fast fourier transform on a signal sequence X0(k,: in a k-th space point in X0, wherein the transformed signal sequence is represented as F0 ═ a0+ B0 ×, where a0 represents a real part sequence of the fast fourier transformed signal, B0 × i represents an imaginary part sequence of the fast fourier transformed signal, and i is a unit imaginary number;
using Amp0 to represent the amplitude sequence of the transformed signal, and Angle0 to represent the phase Angle sequence of the transformed signal, then:
performing fast Fourier transform on a signal X (k,: in a k-th space point in the vibration data X, wherein the transformed signal is represented as F ═ A + B:, A represents a real part sequence of the fast Fourier transformed signal, B:representsan imaginary part sequence of the fast Fourier transformed signal, and i is a unit imaginary number;
using Amp to represent the amplitude sequence of the transformed signal, and Angle to represent the phase Angle sequence of the transformed signal, then:
4. a method of pre-processing a DVS vibration monitor signal based on claim 1 or 3, wherein: the result of the spectral subtraction of the k-th spatial point, comprising,
calculating the amplitude difference value of the original signal and the noise signal, and defining the amplitude and the phase angle after denoising as Ampnew、Anglenew；
The phase AnglenewCan be maintained unchanged as follows:
Anglenew＝Angle
the frequency spectrum Y after the spectral subtractionnewNamely:
Ynew＝Ampnew·sin(Anglenew)+Ampnew·cos(Anglenew)·i
5. a method of pre-processing based on DVS vibration monitor signals according to claim 3, wherein: performing inverse Fourier transform on the k-th space point to obtain a denoised signal, including,
for YnewInverse Fourier transform is performed, the real part is taken, and the obtained sequence is recorded as xkThen xkX (k) represents a row vector with the size of 1 multiplied by N after the signal is denoised by the spectral subtraction;
k sequentially taking 1,2,3, … and M, and processing according to the steps to obtain a denoised signal x of each space point1,x2,x3，...,xMAnd then the two-dimensional array X denoises the signal XfiltedI.e. can be represented as:
6. a method of pre-processing based on DVS vibration monitor signals as recited in claim 5, wherein: calculating the time domain mean value of each point of the denoised signal, including,
based on denoised signal XfiltedCalculating the long-time statistical average value of the signals of each space point, and recording the sequence points formed by the average values of all the space points as
It is represented as a column vector of size 1 × M;
each point in space fluctuates around a central point, so a long-term statistical average is approximately equivalent to the central point of the signal fluctuation.
7. A method of pre-processing based on DVS vibration monitor signals according to claim 6, wherein: the trend of the removal of the spatial domain and the dc component, including,
defining the signal after removing the spatial trend as XnormCompleting the spatial detrending and direct current quantity processing of each spatial point signal;
the process of detrending and dc-flow of the signal at time j for space point k is:
wherein, Xfilted(k, j) is the denoised vibration signal intensity of the space point k at the time j,
the signal mean intensity after the spatial point k smoothing is obtained.
8. A method of pre-processing a DVS vibration monitor signal based on claim 6 or 7, wherein: a time domain de-trending process that includes,
to XnormAnd carrying out high-pass filtering on the signals by space points to filter the trend of the signals in time.
9. A method of pre-processing based on DVS vibration monitor signals according to claim 6, wherein: and the time domain mean value of each space point is processed by smoothing treatment, including,
to pair
Smoothing the large-scale window to remove burrs in the signal, and recording the smoothed signal as
10. A DVS vibration monitor signal based preprocessing system, comprising: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the monitoring module comprises a DVS and an optical cable to be monitored and is used for monitoring a distributed vibration signal;
the statistical module is connected with the monitoring module and used for obtaining a spectral subtraction result of the kth space point;
the denoising module is connected with the statistical module and used for obtaining denoised signals, calculating the time domain mean value of each point of the denoised signals and smoothing the time domain mean value of each space point;
the de-trending module is connected with the statistical module and comprises a spatial domain de-trending module and a time domain de-trending module, and is used for removing the trending of the spatial domain and the trending of the direct current and the time domain and finishing the preprocessing.
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