阅读说明：本技术 基于光纤振动及温度测试的沙漠埋地管道监测系统与方法 (Desert buried pipeline monitoring system and method based on optical fiber vibration and temperature test ) 是由 葛亮 蒋炎 胡泽 肖小汀 汪敏 牟强 陈昊 靳涛 于 2021-11-17 设计创作，主要内容包括：本发明公开了基于光纤振动及温度测试的沙漠埋地管道监测系统与方法,方法包括设置沙漠埋地管道监测系统,并通过沙漠埋地管道监测系统采集埋地管道的振动信号和温度信号；对振动信号中的原始散射曲线进行差分处理得到最初的光强变化幅度结果,并运用滤波算法对差值曲线进行平滑处理,得到振动源位置数值；利用温度信号中的斯托克斯光和反斯托克斯光的光强进行温度解调,得到温度数值；获取振动信号的振动波形和温度信号的温度波形,提取振动波形和温度波形的频域的信号特征并计算管道移位变形大小,根据预设的判定条件判断故障事件类型。本发明能有效监测沙漠地带埋地管道由于沙丘移动而产生异常状况,可实时监测管道沿线情况,故障定位监测准确性高。(The invention discloses a desert buried pipeline monitoring system and a method based on optical fiber vibration and temperature test, wherein the method comprises the steps of arranging the desert buried pipeline monitoring system, and collecting vibration signals and temperature signals of buried pipelines through the desert buried pipeline monitoring system; carrying out differential processing on an original scattering curve in the vibration signal to obtain an initial light intensity variation amplitude result, and carrying out smoothing processing on the difference curve by using a filtering algorithm to obtain a vibration source position value; carrying out temperature demodulation by utilizing the light intensity of Stokes light and anti-Stokes light in the temperature signal to obtain a temperature value; the method comprises the steps of obtaining a vibration waveform of a vibration signal and a temperature waveform of a temperature signal, extracting signal characteristics of frequency domains of the vibration waveform and the temperature waveform, calculating the displacement deformation size of a pipeline, and judging the type of a fault event according to preset judgment conditions. The method can effectively monitor the abnormal condition of the buried pipeline in the desert area caused by the movement of the sand dune, can monitor the condition along the pipeline in real time, and has high fault positioning and monitoring accuracy.)

1. The desert buried pipeline monitoring method based on optical fiber vibration and temperature test comprises the following steps:

s1, setting a desert buried pipeline monitoring system, and collecting vibration signals and temperature signals of buried pipelines through the desert buried pipeline monitoring system;

s2, carrying out difference processing on the original scattering curve in the vibration signal by using a difference algorithm to obtain an initial light intensity change amplitude result, and carrying out smoothing processing on the difference curve by using a filtering algorithm to remove redundant noise in the vibration signal to obtain a vibration source position value;

s3, according to the spontaneous Raman scattering effect technology and the optical time domain reflection technology, the light intensity of Stokes light and anti-Stokes light in the temperature signal is utilized to demodulate the temperature to obtain a temperature value;

and S4, acquiring the vibration waveform of the vibration signal and the temperature waveform of the temperature signal, extracting the signal characteristics of the vibration waveform and the temperature waveform frequency domain, calculating the displacement deformation of the pipeline, and judging the type of the fault event according to preset judgment conditions.

2. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 1, wherein the step S2 specifically comprises the following sub-steps:

s21, assuming that N sets of backward rayleigh scattering signals are collected by the system, let t be t₁，t₂，t₃，...t_NWherein t is a scattering signal set and is the ith backward Rayleigh scattering signal; let M be the number of moving averages, the averaged set of backward rayleigh scattered signals can be represented as T ═ T₁，T₂，T₃...T_PWhere P ═ N-M +1, this treatment can be represented by the following formula:

wherein, T_iThe ith Rayleigh scattering curve after moving average;

s22, setting the difference interval of the difference processing as m, m is a natural number more than 1, and forming Rayleigh scattering curve T by adjacent pulse light emission_iAnd T_i-mThe difference is made, and the difference processing process is shown as the following formula:

ΔT(i)＝abs[T(i)-T(i-m)]

wherein Δ T (i) represents the i-th difference curve, T_iRepresenting the ith Rayleigh scattering curve of the system after moving average, and m represents the difference interval, then the signal set after moving difference is:

ΔT＝{ΔT₁,ΔT₂,...,ΔT_N-M+1}

s23, the amplitude value of the same sampling point of each curve in the signal set after moving difference is successively drawn in the same graph according to the time sequence of difference processing to form a difference curve image, the position of the buried pipeline where vibration occurs is found out in the difference curve image, the sampling point with obvious vibration is selected, the section diagram of the point at the same position is drawn, and the time domain image corresponding to the position of the sampling point can be extracted.

3. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 1, wherein the step S3 specifically comprises the following sub-steps:

s31, using Stokes light as reference light, obtaining the ratio I (T) of anti-Stokes light and Stokes light as expression:

s32, setting the temperature T at the reference fiber by arranging a reference fiber at the initial position of the fiber₀If the ratio of the anti-stokes light intensity to the stokes light intensity at the reference fiber is as follows:

further, according to I (T) and I (T)₀) The temperature expression of each section of the obtained optical fiber is as follows:

wherein, K_s，K_asCoefficient, S, representing the dependence of anti-Stokes light on the cross-section of the fiber_bRepresenting the backscattering factor, v, of the fibre_asRepresenting the frequency, alpha, of the anti-Stokes light₀，α_asRespectively representing the transmission loss coefficients of incident light and anti-Stokes light, h is Planck constant, h is 6.626 multiplied by 10^-34J.s, respectively; k is Boltzmann constant, h is 1.380 × 10^-23J.K^-1L represents the position from the source, T is the thermodynamic temperature of the environment in which the fiber is located, and Δ T is 1.359 × 10 for a silica fiber value¹³Hz。

4. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 1, wherein the step S4 of obtaining the vibration waveform of the vibration signal and the temperature waveform of the temperature signal, and the process of extracting the signal characteristics of the vibration waveform and the frequency domain of the temperature waveform specifically comprises the following sub-steps:

s41, using wavelet base to decompose N layers of wavelet packets for optical fiber signal S, recording the decomposition coefficient of jth node of Nth layer as

S42, reconstructing the decomposition coefficient of each nodeTo representA reconstructed signal of

S43, calculating the energy of each sub-band signal,the energy of (A) is:

wherein x is_j(k) For reconstructing sub-band signalsA discrete value of (d); calculating the total energy E of the signal, by each sub-unitThe wavelet packet energy characteristics are obtained after the percentage normalization of the frequency band energy in the total energy,to representSignal energy at j nodes, E denotesSum of energy of (c):

wherein the content of the first and second substances,

s44, calculating the entropy of each sub-band signal,the corresponding entropy values are:

wherein p is_j(k)＝|x_j(k)|²/||x_j(k)²L; the wavelet packet entropy characteristics obtained by further processing are as follows:

wherein, γ₁Is the energy of the small wave packet and is,to representEntropy at the jth node, p_jIs x_jHas a probability of_ip_j＝1，γ₂Is the entropy characteristic of the wavelet packet.

5. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 1, wherein the process of calculating the displacement deformation of the pipeline in the step S4 specifically includes: according to the deformation curves of the vibration waveform and the temperature waveform, the deformation curve is divided into N small sections by adopting a corner cut recursion method, the coordinates of all division points in the deformation curve are respectively deduced, and the difference values between the division points are respectively calculated to obtain the displacement deformation size of the pipeline.

6. A monitoring system for the desert buried pipeline monitoring method based on optical fiber vibration and temperature tests, which is characterized by comprising a data acquisition module, a signal amplification module, a signal acquisition module, a signal analysis module, an upper computer, a reference optical fiber and a mode identification module. The signal acquisition module is respectively connected with the reference optical fiber and the signal amplification module; the signal amplification module is connected with the data acquisition module; the upper computer is respectively connected with the data acquisition module and the reference optical fiber; the signal analysis module is connected with the upper computer; the pattern recognition module is connected with the signal analysis module.

7. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 6, wherein the signal collection module comprises a wavelength division multiplexer, an isolator, a light source module and two photoelectric detection modules, the two photoelectric detection modules are respectively connected with the wavelength division multiplexer, the light source module is connected with the wavelength division multiplexer through the isolator, and the wavelength division multiplexer is connected with the reference optical fiber.

8. The method for monitoring the buried pipeline in the desert based on the optical fiber vibration and temperature test as claimed in claim 7, wherein the light source module is a distributed optical fiber vibration sensor, the photoelectric detection module is a distributed optical fiber temperature sensor, the distributed optical fiber vibration sensor collects vibration signals of the buried pipeline, and the distributed optical fiber temperature sensor collects temperature signals of the buried pipeline; the distributed optical fiber vibration sensor and the distributed optical fiber temperature sensor are both connected to a buried pipeline in a binding mode through rolling tape pasting.

Technical Field

The invention relates to the technical field of pipeline monitoring, in particular to a desert buried pipeline monitoring system and method based on distributed optical fiber vibration and temperature testing.

Background

With the reform of energy structure and the increase of energy demand in China, petroleum and natural gas will increase year by year in the energy demand in China. Petroleum and natural gas need to pass through links from exploitation to consumption, and are influenced by energy distribution in China, and producing areas and consumption-intensive areas may span thousands of kilometers away. The transportation of oil gas generally adopts the pipeline transportation mode, and the pipeline transportation has become the main transportation mode of dangerous material and fluid material such as oil, natural gas at present, especially after the adjustment of national energy strategy and the successful operation of west gas east transport engineering, the pipeline transportation mode has obtained large-scale use. However, due to the fact that the transportation geographical position span is large, particularly in a desert area containing quicksand areas, the working environment is severe, the pipeline loss is severe, the service life is generally lower than a normal value, the problems of exposure, displacement, arching, distortion, shearing, leakage and even pipeline fracture of the pipeline occur, the pipeline events are frequent day by day, not only can enterprises bear heavy economic loss, but also great threats can be caused to lives and properties of people and the environment. It is obviously impractical to avoid the abnormal problem in the pipeline transportation process, so for researchers, the abnormal phenomenon can be timely and efficiently monitored only from the point of preventing the abnormity, and the loss is reduced to the minimum. And analyzing the abnormal pipeline section to obtain key information, judging the fault mode and the fault grade, and taking corresponding measures as early as possible to remedy the fault.

For example, patent application No. CN201410332580.4 discloses a pipeline monitoring method based on a distributed optical fiber sensor and sound waves, which includes the steps of laying the distributed optical fiber sensor in a pipeline monitoring area, installing sound wave sensing units at two ends of the pipeline or on the pipeline in segments, and simultaneously monitoring the pipeline in real time by using the distributed optical fiber sensor and the sound wave sensing units; configuring a light power detection module for the distributed optical fiber sensor and configuring a sound wave signal receiving and processing device for the sound wave sensing unit; and when the pipeline leaks, the steps of judging the leakage signal detected by the distributed optical fiber sensor and the leakage signal detected by the sound wave sensing unit are integrated. Although the optical fiber sensor and the acoustic wave sensing unit are adopted to simultaneously monitor the pipeline in real time, the signals extracted by the sensor are not subjected to feature processing, and the accuracy of the monitoring signals is not high.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides a system and a method for monitoring desert buried pipeline information based on distributed optical fiber vibration and temperature test, wherein the displacement is calculated by an upper computer and the displacement deformation condition of the buried pipeline is analyzed; then extracting vibration event and temperature event signal characteristics through the displacement deformation condition of the buried pipeline; and finally, carrying out pattern recognition and making corresponding early warning processing measures according to the signal characteristic type.

The purpose of the invention is realized by the following technical scheme:

a desert buried pipeline monitoring method based on optical fiber vibration and temperature testing comprises the following steps:

s1, setting a desert buried pipeline monitoring system, and collecting vibration signals and temperature signals of buried pipelines through the desert buried pipeline monitoring system;

s2, carrying out difference processing on the original scattering curve in the vibration signal by using a difference algorithm to obtain an initial light intensity change amplitude result, and carrying out smoothing processing on the difference curve by using a filtering algorithm to remove redundant noise in the vibration signal to obtain a vibration source position value;

s3, according to the spontaneous Raman scattering effect technology and the optical time domain reflection technology, the light intensity of Stokes light and anti-Stokes light in the temperature signal is utilized to demodulate the temperature to obtain a temperature value;

and S4, acquiring the vibration waveform of the vibration signal and the temperature waveform of the temperature signal, extracting the signal characteristics of the frequency domains of the vibration waveform and the temperature waveform, calculating the displacement deformation of the pipeline, and judging the type of the fault event according to preset judgment conditions.

Specifically, step S2 specifically includes the following sub-steps:

s21, assuming that N sets of backward rayleigh scattering signals are collected by the system, let t be t₁，t₂，t₃，...t_NWherein t is a scattering signal set and is the ith backward Rayleigh scattering signal; let M be the number of moving averages, the averaged set of backward rayleigh scattered signals can be represented as T ═ T₁，T₂，T₃...T_PWhere P ═ N-M +1, this treatment can be represented by the following formula:

wherein, T_iThe ith Rayleigh scattering curve after moving average;

s22, setting the difference interval of the difference processing as m, m is a natural number more than 1, and forming Rayleigh scattering curve T by adjacent pulse light emission_iAnd T_i-mThe difference is made, and the difference processing process is shown as the following formula:

ΔT＝abs[T(i)-T(i-m)]

wherein Δ T (i) represents the i-th difference curve, T_iRepresenting the ith Rayleigh scattering curve of the system after moving average, and m represents the difference interval, then the signal set after moving difference is:

ΔT＝{ΔT₁，ΔT₂，...，ΔT_N-M+1}

s23, the amplitude value of the same sampling point of each curve in the signal set after moving difference is successively drawn in the same graph according to the time sequence of difference processing to form a difference curve image, the position of the buried pipeline where vibration occurs is found out in the difference curve image, the sampling point with obvious vibration is selected, the section diagram of the point at the same position is drawn, and the time domain image corresponding to the position of the sampling point can be extracted.

Specifically, step S3 specifically includes the following sub-steps:

s31, using Stokes light as reference light, obtaining the ratio I (T) of anti-Stokes light and Stokes light as expression:

s32, setting the temperature T at the reference fiber by arranging a reference fiber at the initial position of the fiber₀If the ratio of the anti-stokes light intensity to the stokes light intensity at the reference fiber is as follows:

further, according to I (T) and I (T)₀) The temperature expression of each section of the obtained optical fiber is as follows:

wherein, K_s，K_asCoefficient, S, representing the dependence of anti-Stokes light on the cross-section of the fiber_bRepresenting the backscattering factor, v, of the fibre_asRepresenting the frequency, alpha, of the anti-Stokes light₀，α_asRespectively representing the transmission loss coefficients of incident light and anti-Stokes light, h is Planck constant, h is 6.626 multiplied by 10^-34J.s, respectively; k is Boltzmann constant, h is 1.380 × 10^-23J.K^-1L represents the position from the source, T is the thermodynamic temperature of the environment in which the fiber is located, and Δ T is 1.359 × 10 for a silica fiber value¹³Hz。

Specifically, the step S4 of obtaining the vibration waveform of the vibration signal and the temperature waveform of the temperature signal, and the process of extracting the signal characteristics of the frequency domain of the vibration waveform and the temperature waveform specifically includes the following sub-steps:

s41, using wavelet base to decompose N layers of wavelet packets for optical fiber signal S, recording the decomposition coefficient of jth node of Nth layer as

S42, reconstructing the decomposition coefficient of each nodeTo representA reconstructed signal of

S43, calculating the energy of each sub-band signal,the energy of (A) is:

wherein x is_j(k) For reconstructing sub-band signalsA discrete value of (d); calculating the total energy E of the signals, and normalizing according to the percentage of the energy of each sub-band in the total energy to obtain the wavelet packet energy characteristics:

wherein the content of the first and second substances,

s44, meterThe entropy of each sub-band signal is calculated,the corresponding entropy values are:

wherein p is_j(k)＝|x_j(k)|²/||x_j(k)²L; the wavelet packet entropy characteristics obtained by further processing are as follows:

wherein gamma is₁Is the energy of the small wave packet and is,to representEntropy at the jth node, p_jIs x_jHas a probability of_ip_j＝1，γ₂Is the entropy characteristic of the wavelet packet.

Specifically, the step S4 of calculating the displacement deformation size of the pipeline specifically includes: according to the deformation curves of the vibration waveform and the temperature waveform, the deformation curve is divided into N small sections by adopting a corner cut recursion method, the coordinates of all division points in the deformation curve are respectively deduced, and the difference values between the division points are respectively calculated to obtain the displacement deformation size of the pipeline.

A desert buried pipeline monitoring system based on optical fiber vibration and temperature testing comprises a data acquisition module, a signal amplification module, a signal acquisition module, a signal analysis module, an upper computer, a reference optical fiber and a mode identification module. The signal acquisition module is respectively connected with the reference optical fiber and the signal amplification module; the signal amplification module is connected with the data acquisition module; the upper computer is respectively connected with the data acquisition module and the reference optical fiber; the signal analysis module is connected with the upper computer; the pattern recognition module is connected with the signal analysis module.

Specifically, the signal acquisition module includes wavelength division multiplexer, isolator, light source module and two photoelectric detection modules, and two photoelectric detection modules are connected with wavelength division multiplexer respectively, and the light source module passes through the isolator to be connected with wavelength division multiplexer, and wavelength division multiplexer is connected with reference optical fiber.

Specifically, the light source module is a distributed optical fiber vibration sensor, the photoelectric detection module is a distributed optical fiber temperature sensor, the distributed optical fiber vibration sensor collects vibration signals of the buried pipeline, and the distributed optical fiber temperature sensor collects temperature signals of the buried pipeline; the distributed optical fiber vibration sensor and the distributed optical fiber temperature sensor are both connected to a buried pipeline in a binding mode through rolling tape pasting.

The invention has the beneficial effects that:

1. the method can effectively monitor the abnormal condition of the buried pipeline in the desert area caused by the movement of the sand dune, and visually monitor the displacement deformation condition, the invasion condition, the exposure condition, the arching condition and the leakage condition of the pipeline along the line in real time; the distributed optical fiber vibration sensor and the distributed temperature sensor are used for co-positioning and monitoring, so that the method has the characteristics of higher accuracy and higher efficiency; the distributed optical fiber is not limited by pipeline materials, and can detect pipelines of all materials.

2. In order to inhibit the influence of environmental factors on the optical fiber and carry out temperature calibration on the optical fiber sensor, the invention arranges a section of reference optical fiber at the initial position of the optical fiber sensor, and improves the accuracy of fault identification analysis by comparing a reference signal with a signal after actual processing, thereby overcoming the limitation that wavelet analysis only decomposes a low-frequency space but not a high-frequency space. In addition, the invention also uses the mobile difference to realize the positioning of the disturbance signal, thereby improving the positioning precision of the pipeline fault point.

Drawings

FIG. 1 is a schematic block diagram of a monitoring system of the present invention.

Fig. 2 is a differential principle positioning diagram of the present invention.

Figure 3 is a displacement deformation diagram of the buried pipeline of the present invention.

Fig. 4 is a schematic diagram of curve reconstruction based on corner cut recursion according to the present invention.

Detailed Description

The following describes in detail a specific embodiment of the monitoring method with reference to the technical solution and the accompanying drawings, in which only some embodiments, but not all embodiments, are described in detail, and other embodiments obtained by innovative modifications by other persons skilled in the art are within the scope of the present invention.

The first embodiment is as follows:

in this embodiment, as shown in fig. 1, a system for monitoring desert buried pipeline information based on distributed optical fiber vibration and temperature test includes a data acquisition module, a signal amplification module, a signal acquisition module, a signal analysis module, an upper computer, a reference optical fiber, and a mode identification module. The signal acquisition module is respectively connected with the reference optical fiber and the signal amplification module; the signal amplification module is connected with the data acquisition module; the upper computer is respectively connected with the data acquisition module and the reference optical fiber; the signal analysis module is connected with the upper computer; the pattern recognition module is connected with the signal analysis module.

In this embodiment, the signal acquisition module includes a wavelength division multiplexer, an isolator, a light source module, and two photoelectric detection modules, the two photoelectric detection modules are respectively connected with the wavelength division multiplexer, the light source module is connected with the wavelength division multiplexer through the isolator, and the wavelength division multiplexer is connected with the reference optical fiber. Meanwhile, the light source module and the photoelectric detection module are respectively connected with the signal amplification module.

The light source module is a distributed optical fiber vibration sensor, and the photoelectric detection module is a distributed optical fiber temperature sensor. The distributed optical fiber vibration sensor collects vibration signals of the buried pipeline, and the distributed optical fiber temperature sensor collects temperature signals of the buried pipeline.

In an actual application scenario, the distributed optical fiber vibration sensor and the distributed optical fiber temperature sensor are arranged in the embodiment and buried underground together with a buried pipeline, and the distributed optical fiber vibration sensor and the distributed optical fiber temperature sensor are both connected to the buried pipeline in a rolling band pasting and binding mode.

In this embodiment, the signal amplification module is a signal amplification circuit, and is used for amplifying the voltage signals output by the light source module and the photoelectric detection module, that is, the vibration signals and the temperature signals output by the distributed optical fiber vibration sensor and the distributed optical fiber temperature sensor, respectively.

In this embodiment, the data acquisition module is an analog-to-digital converter (ADC) configured to perform analog-to-digital conversion on the amplified vibration signal and the amplified temperature signal. In this embodiment, two analog-to-digital converters are provided to perform analog-to-digital conversion on the amplified vibration signal and temperature signal, respectively, and upload the converted vibration signal and temperature signal to an upper computer for analysis and processing.

Preferably, the data acquisition module in this embodiment is a data acquisition card, and can acquire multiple paths of vibration signals and temperature signals at the same time to perform analog-to-digital conversion, and upload the signals to an upper computer for processing.

In this embodiment, the upper computer is mainly configured to perform signal filtering and temperature demodulation processing on the vibration signal and the temperature signal after the analog-to-digital conversion through the PCI system bus, send the processed data to the computer, and perform specific analysis processing by using a signal analysis module and a pattern recognition module that are arranged in the computer.

In the embodiment, the upper computer firstly obtains a vibration signal and a temperature signal of the buried pipeline according to the reference optical fiber, controls the data acquisition module to amplify a voltage signal output by the distributed optical fiber vibration and temperature sensor through the signal amplification module, then performs analog-to-digital conversion, signal filtering and temperature demodulation, and finally sends the processed data to the computer through the PCI system bus.

In this embodiment, the upper computer performs difference processing on the acquired original scattering curve by using a difference algorithm to obtain an initial light intensity variation amplitude result, and performs smoothing on the difference curve by using a filtering algorithm to remove redundant noise in the signal, so as to obtain a position value of the vibration source. And simultaneously, the upper computer demodulates the temperature by utilizing the light intensity of Stokes light and anti-Stokes light in the optical fiber according to a spontaneous Raman scattering effect technology and an optical time domain reflection technology to obtain a temperature value.

In this embodiment, the signal analysis module is configured to extract signal characteristics of frequency domains of the vibration waveform and the temperature waveform, calculate a displacement deformation size of the pipeline according to the extracted signal characteristics, determine a type of a fault event of the buried pipeline according to a preset determination condition, and finally input a determination result into the pattern recognition module.

The signal analysis module comprises a vibration waveform module and a temperature module, wherein the vibration waveform module is used for displaying the frequency spectrum waveform (vibration waveform) of the vibration signal, and the temperature module is used for displaying the temperature signal waveform (temperature waveform).

In this embodiment, the pattern recognition module is configured to perform maintenance processing on a corresponding event according to a determination result of the type of the fault event. The pattern recognition module comprises an intrusion module, an exposure module, an arching module, a leakage module and an early warning module.

The exposed module, the arched module and the leakage module are mostly under the influence of non-human factors, and due to the particularity of the geographical environment of the desert, the pipeline is bent, deformed and displaced along with the fact that a sand dune moves in no direction under the action of strong wind, and the conditions of exposure, arching, leakage and the like are generated under severe conditions;

the invasion module is under the influence of undesirable human factors, such as sand excavation and oil theft events in desert areas, so that the pipelines are damaged at multiple points and oil and gas cannot be normally transported and supplied; in order to monitor whether the pipeline is invaded, exposed, arched or leaked, the early warning module judges the type of the event by analyzing the frequency characteristics of the vibration and temperature signals of the pipeline.

Because the energy peak values of different distributed optical fiber vibration signals and temperature signals are different, the energy distribution is obviously different, the entropy distribution is also very different, and different event types are judged by analyzing the energy distribution and the entropy distribution of different frequency bands. The specific event type identification process of the pattern identification module is as follows:

bare module identification: when the pipeline is exposed, the optical fiber attached to the surface of the pipeline is in a sandstorm erosion state at any time, irregular vibration occurs around the pipeline, and the difference between the exposed pipeline surface temperature signal and the pipeline surface temperature in the desert soil is large. The distributed optical fiber temperature sensor can detect large temperature signal change of the exposed part of the pipeline; the distributed optical fiber vibration sensor can detect irregular vibration signals of the exposed part of the pipeline. And judging the exposed condition of the pipeline according to the vibration frequency spectrum waveform distributed at 0-300Hz and the temperature signal change.

Identification by an arching module: when the pipeline is arched upwards and exposed out of the ground, fluid in the pipeline generates fluid-solid coupling phenomenon at the arched part to generate vibration, and the vibration frequency at the arched part tends to increase compared with that at the straight pipe. Judging the arching condition on the pipeline according to the frequency spectrum waveform and the positive temperature difference of the vibration signals distributed at 0-500 Hz; when the pipeline is arched downwards, fluid in the pipeline generates fluid-solid coupling phenomenon at the arched position so as to generate vibration, and the vibration frequency at the arched position tends to increase compared with that at the straight pipeline. And judging the arching condition on the pipeline according to the acquired vibration signal frequency spectrum waveform of the arching section distributed at 0-500Hz and the negative temperature difference.

And (3) leakage module identification: when the pipeline leaks, fluid at the leakage point generates turbulence and cavitation, and the distributed optical fiber sensor can detect continuous and regular high-frequency vibration signals and irregular high-frequency random vibration signals. The distributed optical fiber temperature sensor can detect the temperature sharp change at the leakage point. And positioning the leakage position according to the frequency spectrum waveform and the temperature signal change of the regular high-frequency vibration signal and the irregular high-frequency random vibration signal.

And (3) identifying an intrusion module: when people walk around the pipeline or sand digging and oil stealing occur, the monitoring system and the monitoring method judge the pipeline invasion condition according to the frequency spectrum waveform of the vibration signal which is distributed at 0-600Hz and regularly changes from small to large or from large to small and the change of the temperature signal.

The specific maintenance processing operation of the pattern recognition module comprises; if the pipeline invasion event is the pipeline invasion event, the indicating lamp displays the invasion red lamp indicating state, red invasion mark points are marked on a map, and an audible and visual alarm is sent to inform workers to check; if the pipeline leakage event is the pipeline leakage event, displaying the leakage grade, displaying the leakage red light indicating state by the indicating lamp, marking a red leakage mark on a map, and informing a worker of fixed-point maintenance and overhaul; if the pipeline is in the arching event, the indicator lamp displays the arching red light indicating state, marks a red arching mark on the map and informs workers; if the pipeline is exposed, the indicating lamp displays the exposed red light indicating state, a red exposed mark is marked on the map, and workers are informed.

The embodiment has the following technical effects:

the monitoring system provided by the embodiment can effectively monitor abnormal conditions of the buried pipeline in the desert area caused by the movement of the sand dune, and visually monitor the displacement deformation condition, the invasion condition, the exposure condition, the arching condition and the leakage condition of the pipeline along the line in real time; the distributed optical fiber vibration sensor and the distributed temperature sensor are used for co-positioning and monitoring, so that the method has the characteristics of higher accuracy and higher efficiency; the distributed optical fiber is not limited by pipeline materials, and can detect pipelines of all materials.

Example two:

in this embodiment, a method for monitoring desert buried pipeline information based on distributed optical fiber vibration and temperature is performed based on the monitoring system provided in the first embodiment, and specifically includes the following steps:

s1, when the system enters a working state, the upper computer respectively obtains a vibration signal detected by the distributed optical fiber vibration sensor and a temperature signal detected by the distributed optical fiber temperature sensor;

s2, the upper computer performs difference processing on the original scattering curve in the vibration signal by using a difference algorithm to obtain an initial light intensity change amplitude result, and performs smoothing processing on the difference curve by using a filtering algorithm to remove redundant noise in the vibration signal to obtain a vibration source position value;

s3, the upper computer demodulates the temperature by using the light intensity of Stokes light and anti-Stokes light in the temperature signal according to the spontaneous Raman scattering effect technology and the optical time domain reflection technology to obtain a temperature value;

and S4, extracting the signal characteristics of the frequency domains of the vibration waveform and the temperature waveform according to the vibration signal frequency spectrum waveform and the temperature signal waveform, calculating the displacement deformation of the pipeline, and judging the type of the fault event. If the pipeline invasion event is the pipeline invasion event, the indicating lamp displays the invasion red lamp indicating state, red invasion mark points are marked on a map, and an audible and visual alarm is sent to inform workers to check; if the pipeline leakage event is the pipeline leakage event, displaying the leakage grade, displaying the leakage red light indicating state by the indicating lamp, marking a red leakage mark on a map, and informing a worker of fixed-point maintenance and overhaul; if the pipeline is in the arching event, the indicator lamp displays the arching red light indicating state, marks a red arching mark on the map and informs workers; if the pipeline is exposed, the indicating lamp displays the exposed red light indicating state, a red exposed mark is marked on the map, and workers are informed.

In this embodiment, in step S1, as shown in fig. 3, the distributed optical fiber 1 and the buried pipeline 2 are bound and buried in the dune 4 by the application of the rolling tape 3. Under the action of wind force, the sand dune 4 moves along the arrow direction, the buried pipeline 2 inside the sand dune 4 is subjected to displacement deformation along the arrow direction, and the distributed optical fiber vibration and temperature sensor detects vibration signals and temperature signals of a pipe section subjected to displacement deformation.

In step S2, the difference calculation mainly uses a method of subtracting the rayleigh scattering curve when there is vibration from the rayleigh scattering curve when there is no vibration, and the obtained difference curve generates a distinct peak only at the position where there is vibration.

Assuming N groups of backward Rayleigh scattering signals acquired by the system, and making t equal to t₁，t₂，t₃，...t_NWhere t is the set of scattered signals, t_iThe i-th backward Rayleigh scattering signal is generated by the light pulse, is not processed, and is directly collected by a data acquisition card. Let M be the number of moving averages, the set of averaged backward Rayleigh scattering signals can be expressed as { T }₁，T₂，T₃...T_PWhere P ═ N-M +1, this treatment can be represented by the following formula:

the above formula shows that the curves T after moving average are arbitrarily adjacent_iAnd T_i+1The amplitudes are very similar, if the difference is made by using adjacent curves, an external disturbance signal is difficult to demodulate, and in view of the interval time of incident light pulses, the positioning of the disturbance signal is realized by using a mobile difference, wherein the difference interval can be 1, namely the difference is made on Rayleigh scattering curves formed by adjacent emitted pulse light; or a number greater than 1, i.e. the difference is made between rayleigh scattering curves corresponding to periods separated by several repeated transmission frequencies. The differential processing procedure can be expressed by the following formula:

ΔT(i)＝abs[T(i)-T(i-m)]

wherein Δ T (i) represents the i-th difference curve, T_iThe ith curve after the system has undergone moving averaging is shown, and m represents the difference interval. Then the shifted differentiated signal set is:

ΔT＝{ΔT₁，ΔT₂，...，ΔT_N-M+1}

in practical tests, the scattering curves of adjacent pulse periods are acquired at short time intervals, the difference between the two curves is small, and it is difficult to generate obvious peak values by directly making adjacent differences, so the difference interval is usually set to be a number greater than 1. The number needs to be specifically set according to the specific conditions of conditions such as sensing distance, sampling frequency and the like, the amplitude of a non-vibration point is obvious due to excessively large differential interval, and the positioning error is large; setting the differential interval too small causes the amplitude difference between the overall noise and the vibration point to be too small, and the signal-to-noise ratio is low.

Furthermore, a certain time interval exists between each difference curve, the amplitude value of the same sampling point of each curve is jointly drawn in the same graph according to the time sequence of difference processing, so that the time domain change condition of the scattered light signal of a certain position point on the optical fiber can be represented, wherein the repetition frequency of the injected light pulse is equivalent to the sampling frequency of the point. And finding out the position where the vibration occurs through the difference curve image after the difference processing, selecting a sampling point with obvious vibration, drawing a sectional view of the same position point, and extracting a time domain image corresponding to the position of the sampling point. The time can be obtained by the correlation calculation conversion of the light pulse repetition frequency and the average times, and the calculation formula is as follows:

it can be seen from the above formula that the average frequency and the repetition frequency directly affect the time interval of adjacent time sampling points in the scattered light time domain image of the same position point, if the time interval is long, and the vibration frequency of external disturbance is high, then a part of the sampling points may be missed according to the sampling theorem, so that effective retention of signal information cannot be accurately realized, and the frequency response range of the system is limited. In general, the pulse repetition frequency of a conventional experimental system is fixed, and too many averaging times are a large factor to hinder the performance of the system.

Assuming that every 100 sets of rayleigh scattering signals continuously collected by the moving average and difference processing system, let the 100 sets of rayleigh scattering signals be t ═ t₁，t₂，t₃，...t₁₀₀If the moving average time M is 5, the rayleigh signal set T after moving average is T { T }₁，T₂，T₃...，T₉₆}. Because adjacent rayleigh scattering signals are relatively similar, backward rayleigh scattering signals with intervals of 4 pulse periods are adopted for moving difference, and the obtained difference signals are as follows:

ΔT＝{ΔT₁，ΔT₂，...，ΔT₉₂}＝{T₅-T₁，T₆-T₂，...，T_i+4-T_i，T₉₆-T₉₂}

the moving average algorithm is a filtering algorithm, and is a simple smooth prediction technology, and can eliminate the influence of periodic variation and random variation on data. The method comprises the following specific steps:

firstly, according to whether the weight of the used data is the same during prediction, a simple moving average method or a weighted moving average method is correspondingly selected, wherein the simple moving average method and the weighted moving average method both belong to a moving average algorithm, the weight of the data acquired at each time point is the same in the simple moving average, and the weighted moving average is to endow the data acquired recently with higher weight;

further, intercepting the measured values obtained within a period of time and sequentially taking a certain number of subdata sets;

further, the obtained subdata sets are subjected to arithmetic mean one by one to obtain a moving average value;

further, the obtained moving average values are arranged in sequence and are put into a pre-defined array;

furthermore, the data in the array is taken out and drawn into a waveform diagram.

In general, the background noise of the scattering signal image without any preprocessing is extremely large, and the specific amplitude change condition cannot be clearly judged; after the processing of the initial simple moving average algorithm, the smooth effect of the curve changes obviously, sharp peak points containing abrupt change basically do not appear, background noise is relatively reduced, but the overall amplitude is reduced to some extent.

In step S3, in the two-way demodulation method for raman temperature measurement, a temperature demodulation algorithm is used in which the stokes light is used as the reference light and the demodulation is performed using the ratio of the anti-stokes light to the stokes light. The method comprises the following specific steps:

first, the ratio i (t) of the anti-stokes light to the stokes light is expressed as:

further, in order to suppress the influence of environmental factors on the optical fiber and perform temperature calibration on the optical fiber sensor, a section of reference optical fiber is usually disposed at the initial position of the optical fiber;

further, the temperature at the reference fiber is set to T₀If the ratio of the anti-stokes light intensity to the stokes light intensity at the reference fiber is as follows:

further, according to I (T) and I (T)₀) The temperature expression of each section of the obtained optical fiber is as follows:

wherein K_s，K_asCoefficient, S, representing the dependence of anti-Stokes light on the cross-section of the fiber_bRepresenting the backscattering factor, v, of the fibre_asRepresenting the frequency, alpha, of the anti-Stokes light₀，α_asRespectively representing the transmission loss coefficients of incident light and anti-Stokes light, h is Planck constant, h is 6.626 multiplied by 10^-34J.s, respectively; k is Boltzmann constant, h is 1.380 × 10^-23J.K-1, L denotes the position from the light source, T is the thermodynamic temperature of the environment in which the fiber is located, Δ T is 1.359 × 10 for a silica fiber¹³Hz。

During the actual measurement, the reference temperature T is known₀The ratio I (T) of the anti-Stokes light to the Stokes light corresponding to the temperature to be measured and the ratio I (T) of the anti-Stokes light to the Stokes light corresponding to the reference temperature₀) Temperature demodulation can be realized to obtain the actual temperature T.

In step S4, before feature extraction of the signal, the frequency band is divided into multiple levels by wavelet packet decomposition, which overcomes the limitation that wavelet analysis only decomposes low frequency space and not high frequency space. Since different types of signals have different spectral structures, it is common to have the energy of the different types of signals distributed over different frequency bands. Therefore, after wavelet packet decomposition, a signal is divided into a plurality of levels of characteristic band spaces, and energy distribution of the signal in each sub-band space is used as a characteristic value, which is a widely used characteristic extraction method for distributed optical fiber measurement signals. The weighted integral of the square of the amplitude of the wavelet packet transform coefficients over the scale-displacement plane is equal to the time-domain total energy of the signal, so the energy of the signal in the subband space can be calculated using the wavelet packet coefficients.

For a random signal X, if it takes X_jHas a probability of p_jAnd is provided withThe Shannon entropy of X is defined as:

entropy is defined as the average amount of information and is a measure of the information that is transmitted. In a broad sense, entropy refers to the state of the average diffusion of energy and substance, and is closely related to energy. According to entropy theory and meaning, the energy distribution of different types of optical fiber signals in each characteristic frequency band space is different, and the entropy value obtained by the energy distribution is different accordingly. The characteristic that the entropy value is sensitive to the time variation of the signal makes the entropy value be used for representing the change situation of the optical fiber signal in the time domain, and the entropy value is calculated by the energy distribution of the optical fiber signal in each frequency band, and is bound to have rich frequency domain information, so the wavelet packet entropy of the optical fiber signal can be used as the classification characteristic.

Taking 2 of the last layer in the wavelet packet decomposition tree^NThe sub-band energy distribution and its entropy are used as the wavelet packet characteristics of the fiber signal. The wavelet packet energy and entropy feature extraction steps of the optical fiber signal are as follows:

firstly, using wavelet basis to make N-layer wavelet packet decomposition on optical fiber signal S, recording the decomposition coefficient of nth node of Nth layer as

Further, the decomposition coefficient of each node is reconstructed byTo representA reconstructed signal of

Further, calculating the energy of each sub-band signal,the energy of (A) is:

wherein x_j(k) For reconstructing sub-band signalsA discrete value of (d). Calculating the total energy E of the signals, and normalizing according to the percentage of the energy of each sub-band in the total energy to obtain the wavelet packet energy characteristics:

wherein

Further, calculating the entropy of each sub-band signal,the corresponding entropy values are:

wherein p is_j(k)＝|x_j(k)|²/||x_j(k)²||

And obtaining wavelet packet entropy characteristics:

through the steps, wavelet packet energy and wavelet packet entropy processing of the signals are completed, and frequency domain features are extracted.

In this embodiment, the pipeline displacement deformation calculation process includes: firstly, according to the deformation curves of the vibration waveform and the temperature waveform, dividing the deformation curve into N small sections by adopting a corner cut recursion method, respectively deducing the coordinates of all division points in the deformation curve, and respectively calculating the difference values between the division points to obtain the displacement deformation size of the pipeline.

The displacement deformation calculation method is based on tangential angle recursion deformation curve reconstruction, and the basic idea is as follows: the deformation curve is divided into N small segments, and when N is large enough, the length of the arc segment of the divided curve is small enough, so that the arc segment can be regarded as a section of infinitesimal arc. The coordinate of the starting point of the curve is set as (0, 0, 0), according to the principle of differential geometry, the curvature and the tangential angle of the micro-arc segment are utilized to deduce the coordinate increment of the first point of the deformation curve relative to the starting point, and then the coordinate increment of the second point relative to the first point, and so on, the coordinates of all points of the curve can be deduced. As shown in fig. 4.

And establishing a rectangular coordinate system x-y by taking the starting point of the curve as an origin and taking the tangent of the curve at the origin as an x axis. O is₁And O₂Respectively, the starting point and the end point of a section of differential arc on the curve, the arc O₁O₂The length is s. With O₁Point is the origin, and the direction parallel to the x-axis is x₁Rectangular coordinate system x is established to axle₁-y₁With O₁Point as origin, curve at O₁Tangent to the point x₁Rectangular coordinate system x is established to axle₁-y₁. Alpha is O₁Angle between point tangent and x-axis, O₁The coordinate in the x-y coordinate system is (x)_O1，y_O1)，O₂The coordinate in the x-y coordinate system is (x)_O2，y_O2) Curve at O₁And O₂Curvature of point is k₁And k₂，O₂Relative to O₁The coordinate increments for the points are Δ x and Δ y.

If the arc selected on the curve is small enough, the tangent angle α of the corresponding point can be found by integration:

integration yields:

at x₁-y₁And x₂-y₂In the coordinate system, there are:

suppose a circular arc O₁O₂Corresponding to a central angle of beta and a radius of curvature of r₁Then, using the relationship between arc length and curvature radius, there are:

due to the point O₁O₂Sufficiently close that the arc between these two points can be viewed approximately as a segment of a circular arc having a radius of curvature r₁Can use O₁O₂The mean of the radii of curvature of the points is expressed as:

wherein k is₁、k₂Is O₁And O₂The curvature of (d) is adjusted to obtain:

at x₂-y₂In the coordinate system, there are:

after finishing, obtaining:

and finally obtaining:

o can be obtained by the above formula₂Relative to O₁The coordinate increment of the point is delta x and delta y, when the whole curve is reconstructed, the curve starting point can be set as the origin, the curve is divided into N arc segments, and the coordinate increment delta x of the first point relative to the second origin can be obtained by derivation according to the formula₁And Δ y₁Then the coordinates of the first point are (Δ x)₁，Δy₁) Then, the coordinate increment (Deltax) of the second point relative to the first point is determined₂，Δy₂) Then the coordinates of the second point (Δ x)₁+Δx₂，Δy₂+Δy₁) And so on, the nth point coordinate can be found as:

(Δx₁+Δx₂+...Δx_n，Δy₁+Δy₂+...Δy_n)

at this point, the coordinates of any point on the curve are obtained, and then the discrete points are connected to complete the curve reconstruction.

Where k(s) is the curvature on the curve, k₁、k₂Is O₁And O₂Curvature of r₁Is O₁Radius of curvature at a point, r₀Is OO₂Radius of the arc segment, alpha being O₁The included angle between the tangent line at the point and the x axis, beta is an arc O₁O₂The corresponding central angles Deltax and Deltay are O₂Relative to O₁Coordinate increment of point, s-arc O₁O₂The length, the above parameters are all indicated in fig. 4.

In the embodiment, the signal characteristics of the frequency domains of the vibration waveform and the temperature waveform are extracted, the displacement and deformation size of the pipeline is calculated, the displacement and deformation size of the pipeline is judged according to the preset judgment condition, the fault event type of the displacement and deformation sent by the buried pipeline is obtained, and corresponding early warning and alarm processing are performed according to the fault event type.

The embodiment can achieve the following technical effects:

in order to suppress the influence of environmental factors on the optical fiber and perform temperature calibration on the optical fiber sensor, a section of reference optical fiber is arranged at the initial position of the optical fiber sensor, and the reference signal is compared with the actually processed signal, so that the accuracy of signal analysis and processing is improved, and the limitation that wavelet analysis is only performed on a low-frequency space and is not performed on a high-frequency space is overcome. In addition, the embodiment also realizes the positioning of the disturbance signal by using the mobile difference, and improves the positioning precision of the pipeline fault point.

Example three:

the embodiment is realized based on the first embodiment and the second embodiment, and the displacement deformation in the desert of the pipeline can be positioned by adopting the distributed optical fiber vibration and temperature sensor in the embodiment.

The pipeline is displaced and deformed due to the movement of the sand dune, so that the transverse and longitudinal buckling deformation of the pipeline is mainly caused, fluid-solid coupling vibration is generated inside the pipeline at the moment, and further, the refractive index of the optical fiber is changed due to the vibration, and the returned light intensity is changed. Since the light intensity of the vibration region changes more strongly than that of the non-vibration region, the light intensity changes more strongly, so that the vibration location is determined according to the light intensity changes. The monitoring system and the monitoring method utilize a difference algorithm to carry out difference processing on an acquired original scattering curve to obtain an initial light intensity change amplitude result, further, a filtering algorithm is used to carry out smoothing on the difference curve to remove redundant noise in a signal, and further, a curve graph with a high peak value is obtained, wherein the position corresponding to the peak value is the position of a vibration source. When fluid in the pipe passes through the displacement deformation section, the temperature on the surface of the pipe is greatly changed, and according to a double-path demodulation method of Raman temperature measurement, a spontaneous Raman scattering effect technology and an optical time domain reflection technology are adopted, and the temperature demodulation is carried out by utilizing the light intensity of Stokes light and anti-Stokes light in the optical fiber, so that the temperature monitoring of the displacement deformation part of the pipe is realized. The monitoring system and the monitoring method calculate the displacement deformation size and analyze the displacement deformation distribution condition through the vibration frequency spectrum waveform and the temperature change.

In this embodiment, the distributed optical fiber vibration and temperature sensor can determine the exposure distribution of the pipeline in the desert. The pipeline is exposed to the ground due to the movement of the sand dune. When the pipeline is exposed, the optical fiber attached to the surface of the pipeline is in a sandstorm erosion state at any time, irregular vibration occurs around the pipeline, and the difference between the exposed pipeline surface temperature signal and the pipeline surface temperature in the desert soil is large. The distributed optical fiber temperature sensor can detect large temperature signal change of the exposed part of the pipeline; the distributed optical fiber vibration sensor can detect irregular vibration signals of the exposed part of the pipeline. The monitoring system and the monitoring method judge the pipeline exposure condition according to the vibration frequency spectrum waveform and the temperature signal change distributed at 0-300 Hz.

In this embodiment, the distributed optical fiber vibration and temperature sensor can determine the pipeline arching condition of the pipeline in the desert. The pipeline can be arched due to the movement of the sand dune, and hard soil can not be arched.

1) When the pipeline is arched upwards and exposed out of the ground, fluid in the pipeline generates fluid-solid coupling phenomenon at the arched part to generate vibration, and the vibration frequency at the arched part tends to increase compared with that at the straight pipe. The monitoring system and the monitoring method judge the arching condition on the pipeline according to the frequency spectrum waveform and the positive temperature difference of the vibration signals of the arching section distributed in 0-500 Hz.

2) When the pipeline is arched downwards, fluid in the pipeline generates fluid-solid coupling phenomenon at the arched position so as to generate vibration, and the vibration frequency at the arched position tends to increase compared with that at the straight pipeline. The monitoring system and the monitoring method judge the arching condition on the pipeline according to the acquired vibration signal frequency spectrum waveform of the arching section distributed at 0-500Hz and the negative temperature difference.

In this embodiment, the distributed optical fiber vibration and temperature sensor can determine the pipe intrusion condition. When people walk around the pipeline or sand digging and oil stealing occur, the monitoring system and the monitoring method judge the pipeline invasion condition according to the frequency spectrum waveform of the vibration signal which is distributed at 0-600Hz and regularly changes from small to large or from large to small and the change of the temperature signal.

In this embodiment, the distributed fiber vibration and temperature sensor can locate the location of the pipeline leak. When the pipeline leaks, fluid at the leakage point generates turbulence and cavitation, and the distributed optical fiber sensor can detect continuous and regular high-frequency vibration signals and irregular high-frequency random vibration signals. The distributed optical fiber temperature sensor can detect the temperature sharp change at the leakage point. The monitoring system and the monitoring method locate the leakage position according to the frequency spectrum waveform and the temperature signal change of the high-frequency vibration signal

The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.