CN115479219B - Intelligent pipeline state monitoring method, monitoring device and intelligent pipeline system - Google Patents
Intelligent pipeline state monitoring method, monitoring device and intelligent pipeline system Download PDFInfo
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- 239000013307 optical fiber Substances 0.000 claims abstract description 93
- 230000005540 biological transmission Effects 0.000 claims abstract description 72
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/005—Protection or supervision of installations of gas pipelines, e.g. alarm
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H9/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
- G01H9/004—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means using fibre optic sensors
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- General Engineering & Computer Science (AREA)
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- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention relates to the technical field of gas pipeline security, and particularly discloses an intelligent pipeline state monitoring method, a monitoring device and an intelligent pipeline system, which comprise the following steps: acquiring an optical fiber transmission signal of a pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal; processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal; performing vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body; and determining the state of the pipeline body according to the vibration behavior analysis result. The intelligent pipeline state monitoring method provided by the invention can effectively monitor the pipeline state.
Description
Technical Field
The invention relates to the technical field of gas pipeline security, in particular to an intelligent pipeline state monitoring method, an intelligent pipeline state monitoring device and an intelligent pipeline system.
Background
The security means of the traditional pipeline is mainly based on civil air defense, has low efficiency and high cost, is mainly based on a mode of embedding optical fibers and additionally arranging the optical fibers even if the optical fibers are fused with various sensing systems, has physical intervals with the pipeline, is not really attached, is not really provided with the detected characteristics, and can not truly display the state of the pipeline, and the influence of a transmission medium on the pipeline under different conditions can lead to false alarm of the sensing system.
Therefore, how to effectively monitor the pipeline state to improve the security efficiency is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides an intelligent pipeline state monitoring method, an intelligent pipeline state monitoring device and an intelligent pipeline system, which solve the problem that the pipeline state in the related technology cannot be effectively monitored.
As a first aspect of the present invention, there is provided a smart pipe status monitoring method, wherein the smart pipe status monitoring method is applied to a smart pipe system including a pipe body and an optical fiber provided in the pipe body, the smart pipe status monitoring method including:
acquiring an optical fiber transmission signal of a pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal;
processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
performing vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body;
and determining the state of the pipeline body according to the vibration behavior analysis result.
Further, processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal includes:
demodulating the optical fiber transmission signal to obtain a demodulated signal;
determining an environmental noise signal corresponding to the current optical fiber transmission signal according to an environmental noise signal model library;
performing ambient noise signal removal processing on the demodulation signal to obtain an optical signal;
and extracting vibration characteristics of the optical signals to obtain vibration characteristic signals corresponding to the optical signals.
Further, determining, according to an environmental noise signal model library, an environmental noise signal corresponding to the optical fiber transmission signal at present, including:
respectively acquiring optical fiber transmission signals of the pipeline body under different environmental noise signals, wherein the different environmental noise signals can be determined according to an environmental noise acquisition device;
training optical fiber transmission signals under different environmental noise signals as a training data set to obtain an optical fiber transmission signal feature library, wherein the optical fiber transmission signal feature library comprises the mapping relation between the optical fiber transmission signals and the environmental noise signals;
and inputting the current optical fiber transmission signal into the environmental noise signal model library, and determining an environmental noise signal corresponding to the current optical fiber transmission signal.
Further, the vibration characteristic extraction of the optical signal to obtain a vibration characteristic signal corresponding to the optical signal includes:
performing characteristic decomposition on the optical signals to obtain corresponding vibration characteristic signals;
and decomposing the vibration characteristic signal to obtain an MFCC signal and a time domain signal.
Further, performing vibration behavior analysis according to the vibration characteristic signal to obtain a vibration behavior analysis result of the pipeline body, including:
calculating MFCC energy from the MFCC signal and calculating time domain energy from the time domain signal;
and comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values respectively, and determining a vibration behavior analysis result of the pipeline body according to the comparison result.
Further, comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values, and determining a vibration behavior analysis result of the pipe body according to the comparison result, including:
comparing the MFCC energy with a preset MFCC energy threshold, and comparing the time domain energy with a preset time domain energy threshold;
if the MFCC energy is greater than the preset MFCC energy threshold value and/or the time domain energy is greater than the preset time domain energy threshold value, determining a vibration behavior analysis result of the pipeline body according to an output result of the decision tree classifier;
if the MFCC energy is not greater than the preset MFCC energy threshold value, comparing the MFCC energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the MFCC energy is greater than the preset comprehensive threshold;
if the time domain energy is not greater than the preset time domain energy threshold value, comparing the time domain energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the time domain energy is greater than the preset comprehensive threshold;
the decision tree classifier comprises a mapping relation between time domain energy and vibration behavior and a mapping relation between MFCC energy and vibration behavior.
Further, the vibration behavior includes calm behavior, pipe-blast behavior, pedestrian behavior, and mining behavior.
Further, the ambient noise signal includes temperature, flow and pressure.
As another aspect of the present invention, there is provided a smart pipe status monitoring device, wherein the smart pipe status monitoring device is applied to a smart pipe system including a pipe body and an optical fiber provided in the pipe body, the smart pipe status monitoring device comprising:
the acquisition module is used for acquiring an optical fiber transmission signal of the pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal;
the processing module is used for processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
the analysis module is used for carrying out vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body;
and the determining module is used for determining the state of the pipeline body according to the vibration behavior analysis result.
As another aspect of the present invention, there is provided a smart pipe system, including: the pipeline body is provided with an optical fiber in the pipeline body, an environmental noise acquisition device and the intelligent pipeline state monitoring device are arranged on the pipeline body, and the optical fiber and the environmental noise acquisition device are electrically connected with the intelligent pipeline state monitoring device;
the pipeline body comprises a medium transmission layer, a reinforcing layer, a coating layer, an optical cable adhesion layer and an optical cable protection layer which are sequentially arranged from inside to outside.
According to the intelligent pipeline state monitoring method, the optical fiber transmission signals are obtained, and the vibration characteristic signals are obtained after the optical fiber transmission signals are processed, so that the intelligent pipeline state is effectively monitored. Therefore, the intelligent pipeline state monitoring method provided by the invention realizes the real fusion of the optical fiber and the pipeline, demodulates the information such as the vibration intensity, the frequency and the like along the pipeline according to the change of the optical signal, combines the comprehensive application and analysis of the pressure, temperature and flow sensors, improves the accuracy of vibration signal behavior analysis, realizes the real-time monitoring of the pipeline application, performs key monitoring on the pipe explosion phenomenon under high pressure, gives out early warning in advance, accurately locates the pipe explosion position, and gains valuable time for rush repair of the pipeline.
Drawings
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate the invention and together with the description serve to explain, without limitation, the invention.
Fig. 1 is a flowchart of an intelligent pipeline state monitoring method provided by the invention.
Fig. 2 is a schematic structural diagram of a pipe body according to the present invention.
FIG. 3 is a schematic diagram of the vibration effect of pressure on pipeline monitoring provided by the present invention.
Fig. 4 is a system signal mapping chart under five-gear flow provided by the invention.
FIG. 5 is a schematic diagram showing the comparison of the energy of the MFCC in the same environment as the knocking and calm states.
Fig. 6 is a flowchart for determining the vibration behavior analysis result of the pipe body according to the present invention.
Fig. 7 is a block diagram of an intelligent pipeline state monitoring device provided by the invention.
Fig. 8 is a block diagram of the intelligent pipeline system provided by the invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this embodiment, an intelligent pipeline state monitoring method is provided and applied to an intelligent pipeline system, where the intelligent pipeline system includes a pipeline body and an optical fiber disposed in the pipeline body, and fig. 1 is a flowchart of the intelligent pipeline state monitoring method provided according to an embodiment of the present invention, as shown in fig. 1, and the intelligent pipeline state monitoring method includes:
s100, acquiring an optical fiber transmission signal of a pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal;
in the embodiment of the invention, the optical fiber transmission signal in the pipeline body can be specifically transmitted by the optical cable, and the optical fiber transmission signal transmitted by the optical cable in the pipeline body specifically comprises an optical signal and an environmental noise signal superposed on the optical signal because the pipeline body is influenced by environmental noise.
It should be understood that, in the embodiment of the present invention, as shown in fig. 2, specifically, a schematic structural diagram of the pipe body 10, specifically, the medium transmission layer 11, the reinforcing layer 12, the cladding layer 13, the optical cable 14 and the optical cable protection layer 15 may be sequentially disposed from inside to outside.
It should be understood that the cable 14 comprises in particular optical fibers, i.e. the cable is constituted by a certain number of optical fibers in a certain way as a cable core.
It should be noted that the pipe body 10 shown in fig. 2 is only an exemplary structure, and it should be understood that the pipe body 10 may also include other types of structures, such as, for example, providing an optical cable attachment layer on an outer layer of the optical cable 14, etc., and specifically, other types of structures may be provided as needed, which are not limited herein.
The medium conveying layer 11 can be specifically polyethylene pe, the reinforcing layer 12 can be specifically steel wires, steel belts, polyester filaments and the like, pressure resistance can be achieved, the coating layer 13 can be specifically polyethylene protection structure for preventing liquid corrosion, stainless steel protection is added on the coating layer 13 by adhering optical fibers, the optical cable adhesion layer is used for fixing the optical fibers, vibration conduction is enhanced, meanwhile, the thermal insulation effect is achieved, the influence of temperature change on vibration detection of the optical fibers is isolated, the outermost layer is an optical cable protection layer 15, the effect of optical cable hiding and covering is achieved, and targeted damage or shielding due to artificial intention is prevented.
In addition, the optical cable part considers the tension and pressure influence when the pipeline equipment is used, adopts the armored optical cable to add stainless steel layer protection to solve the gravity compression influence of coiled pipeline, and the optical cable 14 is selectively attached to the position of the point 40 or the point 20 of the pipeline 10, and the position of the optical cable 14 at the point 40 or the point 20 of the pipeline 10 is considered when the section of the pipeline shown in fig. 2 is a clock face, so that the problem of pressure bearing point is solved, and the gravity compression influence of the coiled pipeline can be effectively solved by arranging the optical cable at the two points.
It should be appreciated that the ambient noise signal may include temperature, flow and pressure, in particular. In order to eliminate the influence of the environmental noise signals, a flow sensor, a pressure sensor and a temperature sensor can be arranged on the pipeline body to detect the corresponding signals.
Because the pipeline is buried underground, the pipeline has a certain isolation effect on external noise, the design on the structure of the pipeline body shields the influence of temperature, and the vibration signals do not have obvious change at different temperatures in the actually-operated test data. Through a large number of lifting and lowering experiment data verification, it can be concluded that vibration influence of pressure on pipeline detection mainly concentrates on vibration signal jumping (as shown in fig. 3, pressure change) caused by abrupt change moment of pressure difference, and influence of liquid flow directly acts on a pipeline and an optical fiber, so that clients can realize the process of recording noise signal levels and calibrated vibration signal values of a pipeline body under different conditions through data acquisition of different flow rates if external noise is required to be shielded.
In addition, the influence factors of the changes of the pipeline pressure and the flow on the vibration change feature library are recorded into a system database, and fig. 4 is a corresponding diagram of the system signals under a five-gear flow experiment. FIG. 5 is a schematic diagram showing the energy comparison of the MFCC in the same environment with the knocking and calm state.
S200, processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
when the optical fiber transmission signal is obtained, the optical fiber transmission signal is firstly demodulated, and the optical fiber transmission signal received by the optical fiber transmission signal comprises an environmental noise signal, so that the influence of the environmental noise signal is eliminated in a calibration mode, and the vibration characteristic signal corresponding to the optical signal is obtained after the vibration characteristic extraction processing.
In some embodiments, step S200 may specifically include:
s210, carrying out signal demodulation on the optical fiber transmission signal to obtain a demodulated signal;
after the optical fiber transmission signal is obtained, the optical fiber transmission signal is subjected to signal demodulation, that is, the signal carried by the carrier light is converted into the intensity change of the light, and then the intensity change is detected by the photoelectric detector, and the demodulation process is well known to those skilled in the art and is not described herein.
S220, determining an environmental noise signal corresponding to the current optical fiber transmission signal according to an environmental noise signal model library;
in some embodiments, an optical fiber transmission signal feature library is first constructed, and then an environmental noise signal corresponding to the optical fiber transmission signal is determined according to the environmental noise signal model library.
Specifically, the method comprises the following steps:
s221, respectively acquiring optical fiber transmission signals of the pipeline body under different environmental noise signals, wherein the different environmental noise signals can be determined according to an environmental noise acquisition device;
in the embodiment of the invention, the environmental noise collection device specifically can comprise a temperature sensor, a pressure sensor and a flow sensor.
S222, training optical fiber transmission signals under different environmental noise signals as a training data set to obtain an optical fiber transmission signal feature library, wherein the optical fiber transmission signal feature library comprises a mapping relation between the optical fiber transmission signals and the environmental noise signals;
s223, inputting the current optical fiber transmission signal into the environmental noise signal model library, and determining an environmental noise signal corresponding to the current optical fiber transmission signal.
In the embodiment of the invention, the environmental noise signal model library collects calibration data according to the changes of flow, pressure and temperature, a training set is generated, the model library is trained into different model libraries through a pattern recognition algorithm, the calibration data contains environmental noise information, in practice, a matching addition algorithm of basic feature factors is carried out based on training results, and the time domain energy threshold is judged to be changed under different conditions.
S230, performing ambient noise signal removal processing on the demodulation signal to obtain an optical signal;
it should be understood that, after the above-mentioned demodulation signal is obtained and the environmental noise signal is determined by combining the environmental noise signal model library with the environmental noise signal, the result that the demodulation signal does not contain the environmental noise signal can be determined, that is, the optical signal can be determined.
S240, extracting vibration characteristics of the optical signals to obtain vibration characteristic signals corresponding to the optical signals.
Specifically, the method comprises the following steps:
performing characteristic decomposition on the optical signals to obtain corresponding vibration characteristic signals;
and decomposing the vibration characteristic signal to obtain an MFCC (Mel Frequency Cepstrum Coefficient, mel frequency cepstral coefficient) signal and a time domain signal.
And performing characteristic decomposition on the optical signal to obtain a vibration characteristic signal therein, and further decomposing to obtain an MFCC signal and a time domain signal.
S300, performing vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body;
specifically, the method comprises the following steps:
calculating MFCC energy from the MFCC signal and calculating time domain energy from the time domain signal;
and comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values respectively, and determining a vibration behavior analysis result of the pipeline body according to the comparison result.
It should be understood that the vibration monitored in the pipeline is especially the most focused pipe explosion behavior, which is an instantaneous behavior, belongs to a short-time feature, the performance characteristic of which is very suitable for an MFCC feature analysis mode sensitive to the short-time mutation feature, while the behaviors such as third party mining and the like usually show time persistence, so as to consider the detection performance of the two behaviors, and the vibration behavior is analyzed by adopting the detection mode of combining MFCC energy and time domain energy features according to different embodiments of the pipeline vibration signal and the voice signal.
Specifically, comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values, and determining a vibration behavior analysis result of the pipe body according to the comparison result, as shown in fig. 6, including:
comparing the MFCC energy with a preset MFCC energy threshold, and comparing the time domain energy with a preset time domain energy threshold;
if the MFCC energy is greater than the preset MFCC energy threshold value and/or the time domain energy is greater than the preset time domain energy threshold value, determining a vibration behavior analysis result of the pipeline body according to an output result of the decision tree classifier;
if the MFCC energy is not greater than the preset MFCC energy threshold value, comparing the MFCC energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the MFCC energy is greater than the preset comprehensive threshold;
if the time domain energy is not greater than the preset time domain energy threshold value, comparing the time domain energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the time domain energy is greater than the preset comprehensive threshold;
the decision tree classifier comprises a mapping relation between time domain energy and vibration behavior and a mapping relation between MFCC energy and vibration behavior.
The vibration behavior includes calm behavior, pipe-frying behavior, pedestrian behavior, and mining behavior.
According to the conduction characteristics of the built-in optical fibers of the pipeline, the changed Mel frequency cepstrum coefficient (MFCC energy value) and the time domain energy value are adopted as basic signal characteristic values, threshold judgment is adopted as pre-alarm judgment logic, wherein any value exceeds a set threshold, a behavior analysis result is given through a decision tree classifier, the judgment flow is as follows, the comprehensive threshold is used for further preventing missing report, the situation that the single threshold in special time does not meet the threshold judgment, but the two meet the set value in the comprehensive threshold still gives pre-alarm and enters the decision tree classifier for behavior analysis, the basic MFCC energy value is 20, the time domain energy threshold is divided into five steps according to the system detection flow rate, the units of (0-0.5), (0.5-1), (1.5-2) and (2-2.5) and (more than 3) are respectively m/s, the time domain energy thresholds are respectively 80, 100, 120, 140 and 160, the MFCC energy value in the comprehensive threshold is 15, and the time domain energy threshold is 70, 90, 100, 120 and 140.
And if the absolute value of the pressure gauge change is larger than 3MPA, the frame signal does not participate in all vibration judgment so as to reduce misjudgment caused by pressure change.
In the embodiment of the invention, the calculation process of the MFCC energy is as follows:
the method comprises the steps of collecting a group of signals with a format of a [ X, Y ] and Y representing the geographic position, calculating the energy characteristics of the MFCC, splitting the signals into Y frames of b [ X ] signals, carrying out fast FFT operation on the b [ X ] signals, and obtaining a frame of signals to be detected, wherein X points of discrete Fourier transform is used as DFT, and the calculation formula is as follows:
where k represents the index number, i.e. from 0 to the last in the signal array.
After the Fourier variation value is obtained, performing frequency spectrum modular squaring to obtain a signal power spectrum, performing filtering operation on the obtained signal power spectrum through a triangular filter bank with a Mel scale, defining a filter bank with 25 filters, wherein the frequency response of the triangular filter is defined as follows:
wherein,
m represents the sequence numbers from 0 to 25, k represents the index number, and f (m) represents the frequency bin of the triangular filter.
To sum up, the MFCC energy value for that channel is accumulated by taking the logarithm from the filter bank calculation.
In the embodiment of the invention, the time domain energy is calculated by splitting a [ x, y ] into y a [ x ] signals, calculating the slope of the connecting line between each point and the subsequent point of the signal between each signal, calculating the absolute value of each slope to obtain x-1 values, summing all the values to obtain N, and accumulating the first M values N of the continuous characteristic of the time domain to obtain the time domain energy (M can be set according to the verification of the test experiments such as actual tube explosion, excavation and the like, and M is generally set to be 4).
Because the decision tree classifier is trained by using the scikit-learn tool, sample data comprise four data of pipe explosion, pedestrian, excavation and calm under different environments, the number of samples is 15600, the number of positive samples is 8000, the number of negative samples is 7600, the learning depth is set to be 6, data annotation is carried out according to the actual behaviors of the samples, 0 represents calm, 1 represents pipe explosion, 2 represents pedestrian and 3 represents excavation, model training and data verification are carried out, a classification model library is obtained, and the accuracy can reach 96.7%.
S400, determining the state of the pipeline body according to the vibration behavior analysis result.
Since the vibration behavior analysis result may include calm, pipe explosion, pedestrian and excavation in particular, the state of the current pipe body may be determined according to the vibration behavior analysis result, that is, whether the state of the current pipe body is safe or not may be determined.
In summary, according to the intelligent pipeline state monitoring method provided by the invention, the vibration characteristic signal is obtained by acquiring the optical fiber transmission signal and processing the optical fiber transmission signal, so that the intelligent pipeline state is effectively monitored. Therefore, the intelligent pipeline state monitoring method provided by the invention realizes the real fusion of the optical fiber and the pipeline, demodulates the information such as the vibration intensity, the frequency and the like along the pipeline according to the change of the optical signal, combines the comprehensive application and analysis of the pressure, temperature and flow sensors, improves the accuracy of vibration signal behavior analysis, realizes the real-time monitoring of the pipeline application, performs key monitoring on the pipe explosion phenomenon under high pressure, gives out early warning in advance, accurately locates the pipe explosion position, and gains valuable time for rush repair of the pipeline.
As another embodiment of the present invention, there is provided a smart pipe status monitoring apparatus, wherein the smart pipe status monitoring apparatus is applied to a smart pipe system including a pipe body and an optical fiber disposed within the pipe body, as shown in fig. 7, the smart pipe status monitoring apparatus 100 includes:
an acquisition module 110, configured to acquire an optical fiber transmission signal of a pipe body, where the optical fiber transmission signal includes an optical signal and an environmental noise signal superimposed on the optical signal;
a processing module 120, configured to process the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
the analysis module 130 is configured to perform vibration behavior analysis according to the vibration characteristic signal, so as to obtain a vibration behavior analysis result of the pipeline body;
and the determining module 140 is used for determining the state of the pipeline body according to the vibration behavior analysis result.
According to the intelligent pipeline state monitoring device, the optical fiber transmission signals are obtained and processed to obtain the vibration characteristic signals, so that the intelligent pipeline state is effectively monitored. Therefore, the intelligent pipeline state monitoring device provided by the invention realizes the real fusion of the optical fiber and the pipeline, demodulates the information such as the vibration intensity, the frequency and the like along the pipeline according to the change of the optical signal, combines the comprehensive application and analysis of the pressure, temperature and flow sensors, improves the accuracy of vibration signal behavior analysis, realizes the real-time monitoring of pipeline application, performs key monitoring on the pipe explosion phenomenon under high pressure, gives out early warning in advance, accurately positions the pipe explosion position, and gains valuable time for rush repair of the pipeline.
The specific working process of the intelligent pipeline state monitoring device provided by the invention can refer to the description of the intelligent pipeline state monitoring method, and the description is omitted here.
As another embodiment of the present invention, there is provided a smart pipe system 1, wherein, as shown in fig. 8, comprising: the pipeline body 10, the optical fiber arranged in the pipeline body 10, the environmental noise acquisition device 20 arranged on the pipeline body 10 and the intelligent pipeline state monitoring device 100, wherein the optical fiber and the environmental noise acquisition device 20 are electrically connected with the intelligent pipeline state monitoring device 100;
the pipe body 10 comprises a medium transmission layer, a reinforcing layer, a coating layer, an optical cable and an optical cable protection layer which are sequentially arranged from inside to outside.
It should be understood that the environmental noise collection device 20 is specifically disposed on the outer side of the optical cable protection layer of the pipe body 10, and the specific location of the disposition is not limited to the embodiment of the present invention, and may be set as required. In addition, the ambient noise collection device 20 may include temperature sensors, pressure sensors, and flow sensors, as well as other types of sensors as desired.
The specific structure of the pipe body 10 may be shown in fig. 2, and the description of the specific structure may be referred to the description of the pipe body structure in the foregoing intelligent pipe state monitoring method, which is not repeated herein.
The intelligent pipeline system provided by the invention realizes the real fusion of the optical fiber and the pipeline, demodulates the information such as the vibration intensity, the frequency and the like along the pipeline according to the change of the optical signal, combines the comprehensive application and analysis of the pressure, the temperature and the flow sensor, improves the accuracy of the vibration signal behavior analysis, realizes the real-time monitoring of the pipeline application, performs important monitoring on the pipe explosion phenomenon under high pressure, sends out early warning in advance, accurately locates the pipe explosion position, and gains precious time for repairing the pipeline.
The specific working principle of the intelligent pipeline system provided by the invention can be described by referring to the pipeline body structure in the intelligent pipeline state monitoring method, and the description is omitted here.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (5)
1. An intelligent pipeline state monitoring method is characterized by being applied to an intelligent pipeline system, wherein the intelligent pipeline system comprises a pipeline body and an optical fiber arranged in the pipeline body, and the intelligent pipeline state monitoring method comprises the following steps:
acquiring an optical fiber transmission signal of a pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal;
processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
performing vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body;
determining the state of the pipeline body according to the vibration behavior analysis result;
processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal, including:
demodulating the optical fiber transmission signal to obtain a demodulated signal;
determining an environmental noise signal corresponding to the current optical fiber transmission signal according to an environmental noise signal model library;
performing ambient noise signal removal processing on the demodulation signal to obtain an optical signal;
extracting vibration characteristics of the optical signals to obtain vibration characteristic signals corresponding to the optical signals;
extracting vibration characteristics of the optical signal to obtain a vibration characteristic signal corresponding to the optical signal, including:
performing characteristic decomposition on the optical signals to obtain corresponding vibration characteristic signals;
decomposing the vibration characteristic signal to obtain an MFCC signal and a time domain signal;
and performing vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body, wherein the vibration behavior analysis result comprises:
calculating MFCC energy from the MFCC signal and calculating time domain energy from the time domain signal;
comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values respectively, and determining a vibration behavior analysis result of the pipeline body according to the comparison result;
comparing the MFCC energy and the time domain energy with respective corresponding energy threshold values, and determining a vibration behavior analysis result of the pipe body according to the comparison result, including:
comparing the MFCC energy with a preset MFCC energy threshold, and comparing the time domain energy with a preset time domain energy threshold;
if the MFCC energy is greater than the preset MFCC energy threshold value and/or the time domain energy is greater than the preset time domain energy threshold value, determining a vibration behavior analysis result of the pipeline body according to an output result of the decision tree classifier;
if the MFCC energy is not greater than the preset MFCC energy threshold value, comparing the MFCC energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the MFCC energy is greater than the preset comprehensive threshold;
if the time domain energy is not greater than the preset time domain energy threshold value, comparing the time domain energy with a preset comprehensive threshold, and determining a vibration behavior analysis result of the pipeline body according to an output result of a decision tree classifier when the time domain energy is greater than the preset comprehensive threshold;
the decision tree classifier comprises a mapping relation corresponding to time domain energy and vibration behaviors and a mapping relation corresponding to MFCC energy and vibration behaviors;
determining an environmental noise signal corresponding to the current optical fiber transmission signal according to an environmental noise signal model library, wherein the determining comprises the following steps:
respectively acquiring optical fiber transmission signals of the pipeline body under different environmental noise signals, wherein the different environmental noise signals can be determined according to an environmental noise acquisition device;
training optical fiber transmission signals under different environmental noise signals as a training data set to obtain an optical fiber transmission signal feature library, wherein the optical fiber transmission signal feature library comprises the mapping relation between the optical fiber transmission signals and the environmental noise signals;
and inputting the current optical fiber transmission signal into the environmental noise signal model library, and determining an environmental noise signal corresponding to the current optical fiber transmission signal.
2. The intelligent duct status monitoring method of claim 1, wherein the vibration behavior comprises calm behavior, pipe-blast behavior, pedestrian behavior, and mining behavior.
3. The intelligent duct status monitoring method of claim 1, wherein the ambient noise signals include temperature, flow and pressure.
4. An intelligent pipeline state monitoring device for implementing the intelligent pipeline state monitoring method of any one of claims 1 to 3, wherein the intelligent pipeline system is applied to an intelligent pipeline system, the intelligent pipeline system comprises a pipeline body and an optical fiber arranged in the pipeline body, and the intelligent pipeline state monitoring device comprises:
the acquisition module is used for acquiring an optical fiber transmission signal of the pipeline body, wherein the optical fiber transmission signal comprises an optical signal and an environmental noise signal superposed on the optical signal;
the processing module is used for processing the optical fiber transmission signal to obtain a vibration characteristic signal corresponding to the optical signal;
the analysis module is used for carrying out vibration behavior analysis according to the vibration characteristic signals to obtain a vibration behavior analysis result of the pipeline body;
and the determining module is used for determining the state of the pipeline body according to the vibration behavior analysis result.
5. An intelligent plumbing system, comprising: the intelligent pipeline state monitoring device comprises a pipeline body, an optical fiber arranged in the pipeline body, an environmental noise acquisition device arranged on the pipeline body and the intelligent pipeline state monitoring device according to claim 4, wherein the optical fiber and the environmental noise acquisition device are electrically connected with the intelligent pipeline state monitoring device;
the pipeline body comprises a medium transmission layer, a reinforcing layer, a coating layer, an optical cable and an optical cable protection layer which are sequentially arranged from inside to outside.
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| CN116295788B (en) * | 2023-04-07 | 2024-01-09 | 长扬科技(北京)股份有限公司 | Multi-mode natural gas leakage detection system and method |
| CN118294283B (en) * | 2024-04-11 | 2024-08-16 | 中国人民解放军陆军装甲兵学院 | Dynamic pressure testing method under high-temperature high-pressure high-speed transient condition |
| CN119860836B (en) * | 2025-03-24 | 2025-07-25 | 上海济辰水数字科技有限公司 | Monitoring method and system of underground intelligent pipe network based on optical fiber transmission detection |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102997062A (en) * | 2011-09-14 | 2013-03-27 | 中国石油天然气集团公司 | Optical fiber sensor-based natural gas pipeline leakage monitoring method and system and installation method for system |
| CN203147289U (en) * | 2012-11-12 | 2013-08-21 | 北京工业大学 | Double-Sagnac pipeline safety monitoring system |
| CN104565826A (en) * | 2013-10-29 | 2015-04-29 | 中国石油天然气股份有限公司 | Pipeline optical fiber safety monitoring and early warning method and system |
| CN204629114U (en) * | 2015-03-23 | 2015-09-09 | 中国石油天然气集团公司 | A kind of adaptive noise cancelling arrangement be applied in predispersed fiber alarm system |
| CN205746047U (en) * | 2016-06-20 | 2016-11-30 | 李林 | A kind of long-distance oil & gas pipeline safety monitoring system |
| CN106225907A (en) * | 2016-06-28 | 2016-12-14 | 浙江大学 | A kind of fiber-optic vibration identification system and method based on Φ OTDR technique |
| WO2017036363A1 (en) * | 2015-09-02 | 2017-03-09 | 同方威视技术股份有限公司 | Optical fiber perimeter intrusion signal identification method and device, and perimeter intrusion alarm system |
| CN107478319A (en) * | 2017-08-31 | 2017-12-15 | 电子科技大学 | A kind of optical fiber sensing system for oil-gas pipeline safety monitoring |
| CN110131486A (en) * | 2019-04-17 | 2019-08-16 | 北京百世通管道科技有限公司 | Optical fiber compound pipeline complex pipeline and its monitoring system and method for early warning |
| CN110567571A (en) * | 2019-09-26 | 2019-12-13 | 华北水利水电大学 | A Vibration Detection Method of Oil Pipeline Based on Optical Fiber Distributed Monitoring |
| CN110953487A (en) * | 2019-12-23 | 2020-04-03 | 杭州绿洁环境科技股份有限公司 | A kind of pipeline leakage detection method and equipment |
| CN111024210A (en) * | 2019-12-15 | 2020-04-17 | 北京百世通管道科技有限公司 | PCCP pipeline broken wire monitoring and pipe explosion early warning method and system |
| CN111157099A (en) * | 2020-01-02 | 2020-05-15 | 河海大学常州校区 | Distributed optical fiber sensor vibration signal classification method and identification classification system |
| CN112504428A (en) * | 2020-10-19 | 2021-03-16 | 威海北洋光电信息技术股份公司 | Low-power-consumption embedded high-speed distributed optical fiber vibration sensing system and application thereof |
| CN113819401A (en) * | 2021-11-17 | 2021-12-21 | 西南石油大学 | Desert buried pipeline monitoring system and method based on optical fiber vibration and temperature test |
| CN114295195A (en) * | 2021-12-31 | 2022-04-08 | 河海大学常州校区 | Method and system for judging abnormity of optical fiber sensing vibration signal based on feature extraction |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116973043A (en) * | 2023-09-25 | 2023-10-31 | 中海油能源发展股份有限公司采油服务分公司 | Pipeline intelligent monitoring and early warning method and system based on distributed optical fiber |
-
2022
- 2022-09-20 CN CN202211142544.2A patent/CN115479219B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102997062A (en) * | 2011-09-14 | 2013-03-27 | 中国石油天然气集团公司 | Optical fiber sensor-based natural gas pipeline leakage monitoring method and system and installation method for system |
| CN203147289U (en) * | 2012-11-12 | 2013-08-21 | 北京工业大学 | Double-Sagnac pipeline safety monitoring system |
| CN104565826A (en) * | 2013-10-29 | 2015-04-29 | 中国石油天然气股份有限公司 | Pipeline optical fiber safety monitoring and early warning method and system |
| CN204629114U (en) * | 2015-03-23 | 2015-09-09 | 中国石油天然气集团公司 | A kind of adaptive noise cancelling arrangement be applied in predispersed fiber alarm system |
| WO2017036363A1 (en) * | 2015-09-02 | 2017-03-09 | 同方威视技术股份有限公司 | Optical fiber perimeter intrusion signal identification method and device, and perimeter intrusion alarm system |
| CN205746047U (en) * | 2016-06-20 | 2016-11-30 | 李林 | A kind of long-distance oil & gas pipeline safety monitoring system |
| CN106225907A (en) * | 2016-06-28 | 2016-12-14 | 浙江大学 | A kind of fiber-optic vibration identification system and method based on Φ OTDR technique |
| CN107478319A (en) * | 2017-08-31 | 2017-12-15 | 电子科技大学 | A kind of optical fiber sensing system for oil-gas pipeline safety monitoring |
| CN110131486A (en) * | 2019-04-17 | 2019-08-16 | 北京百世通管道科技有限公司 | Optical fiber compound pipeline complex pipeline and its monitoring system and method for early warning |
| CN110567571A (en) * | 2019-09-26 | 2019-12-13 | 华北水利水电大学 | A Vibration Detection Method of Oil Pipeline Based on Optical Fiber Distributed Monitoring |
| CN111024210A (en) * | 2019-12-15 | 2020-04-17 | 北京百世通管道科技有限公司 | PCCP pipeline broken wire monitoring and pipe explosion early warning method and system |
| CN110953487A (en) * | 2019-12-23 | 2020-04-03 | 杭州绿洁环境科技股份有限公司 | A kind of pipeline leakage detection method and equipment |
| CN111157099A (en) * | 2020-01-02 | 2020-05-15 | 河海大学常州校区 | Distributed optical fiber sensor vibration signal classification method and identification classification system |
| CN112504428A (en) * | 2020-10-19 | 2021-03-16 | 威海北洋光电信息技术股份公司 | Low-power-consumption embedded high-speed distributed optical fiber vibration sensing system and application thereof |
| CN113819401A (en) * | 2021-11-17 | 2021-12-21 | 西南石油大学 | Desert buried pipeline monitoring system and method based on optical fiber vibration and temperature test |
| CN114295195A (en) * | 2021-12-31 | 2022-04-08 | 河海大学常州校区 | Method and system for judging abnormity of optical fiber sensing vibration signal based on feature extraction |
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