Distributed fiber abrupt vibration detection method and device based on adaptive fitting

Abstract

The application discloses a kind of based on adaptive fitting distributed optical fiber abrupt vibration detection method and device, wherein method includes: original data is collected, the original data is preprocessed, and original data chain is obtained;The original data chain is operated with polynomial fitting, and fitting data chain is obtained;The fitting data chain is adapted with adaptive program, and the fitting data chain after adaptation is obtained;Difference operation is carried out based on the fitting data chain after adaptation and the original data, and target data chain is obtained;Target data block is obtained based on the target data chain, and the type of sudden event is judged based on the target data block.The application has good adaptability to complex environment and dynamic environment of various engineering sites based on adaptive polynomial fitting analysis, and can accurately and quickly identify sudden disastrous vibration.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of signal processing, and particularly relates to a distributed optical fiber abrupt vibration detection method and device based on adaptive fitting. BACKGROUND

[0002] Optical fiber measurement of vibration has good development prospects in engineering applications, especially in the application of abnormal vibration monitoring of some large-scale projects, such as abnormal vibration of rails, sudden rupture of oil and gas pipelines, unstable fluctuations of bridges, and detection of a series of sudden events such as landslides. Improving the perception of sudden vibration can improve the application of distributed optical fiber sensing systems in abnormal vibration detection.

[0003] However, the existing technology has a large amount of data collection, resulting in slow processing speed and poor detection effect in dynamic environment. SUMMARY

[0004] The present application provides a distributed optical fiber abrupt vibration detection method and device based on adaptive fitting to detect and prevent various sudden disaster events commonly seen in life.

[0005] To achieve the above purpose, the present application provides the following scheme: a distributed optical fiber abrupt vibration detection method based on adaptive fitting, comprising:

[0006] Collecting original data, preprocessing the original data to obtain an original data chain;

[0007] Performing a polynomial fitting operation on the original data chain to obtain a fitted data chain;

[0008] Adapting the fitted data chain to obtain an adapted fitted data chain;

[0009] Based on the adapted fitted data chain and the original data, a difference operation is performed to obtain a target data chain;

[0010] Based on the target data chain, a target data block is obtained, and based on the target data block, the type of sudden event is determined.

[0011] Preferably, the method for obtaining the original data chain comprises:

[0012] The original data is divided into blocks to obtain data blocks;

[0013] The data blocks are indexed by single spatial points, and the original data chain is extracted.

[0014] Preferably, the polynomial fitting operation comprises:

[0015]

[0016] wherein, represents a fitted data chain; polyfit represents a polynomial fitting analysis; I(n) represents an original data chain.

[0017] Preferably, the method for obtaining the fitted data chain comprises:

[0018] Based on the fitted data chain, a fitting curve is obtained.

[0019] Based on the fitting curve, a goodness-of-fit judgment is made, and the fitting factor is updated.

[0020] Based on the fitted data chain after updating the fitting factor, fitting is performed again, and the above operations are repeated until the environmental characteristics are adapted, and the fitted data chain is output.

[0021] Preferably, the method for judging the type of the emergency event comprises:

[0022] Based on the target data block, the target data block is observed from a spatial perspective, and the occurrence position of the emergency event is obtained.

[0023] Based on the time perspective of the occurrence position, the envelope of the event occurrence is extracted, and the frequency domain and amplitude information are obtained.

[0024] Based on the frequency domain and amplitude information, the type of the emergency event is judged.

[0025] The application also provides a distributed optical fiber sudden change vibration detection device based on adaptive fitting, comprising: a real-time processing device;

[0026] The real-time processing device is used to execute the above-mentioned detection method, so as to judge the type of the emergency event.

[0027] The detection device further comprises an optical-electric conversion device, a high-speed acquisition device, a display device and a historical record query device.

[0028] The optical-electric conversion device is used to convert the optical signal into an electrical signal.

[0029] The high-speed acquisition device is used to obtain the original data based on the electrical signal.

[0030] The display device is used to trigger an alarm light based on the emergency event.

[0031] The historical record query device is used to provide a historical query interface.

[0032] Preferably, the method for obtaining the original data by the high-speed acquisition device comprises:

[0033] The electric signal is collected at high speed, the electric signal collected at high speed is saved as an lvm format data packet, and the original data is obtained based on the data packet.

[0034] Preferably, the real-time processing device comprises:

[0035] a first processing unit, a second processing unit, an adaptive unit, a third processing unit, and a judging unit.

[0036] The first processing unit is configured to obtain an original data chain based on the original data.

[0037] The second processing unit is configured to perform a polynomial fitting operation on the original data chain to obtain a fitting data chain.

[0038] The adaptive unit is configured to perform adaptive program adaptation on the fitting data chain to obtain an adapted fitting data chain.

[0039] The third processing unit is configured to perform a difference operation on the adapted fitting data chain and the original data chain to obtain a target data chain.

[0040] The judging unit is configured to obtain a target data block based on the target data chain and determine a burst event type based on the target data block.

[0041] The present application has the following advantages:

[0042] 1. The distributed optical fiber system based on adaptive polynomial fitting analysis has good adaptability to complex environments, even dynamic environments, of various engineering sites, and can accurately and quickly identify sudden disastrous vibrations.

[0043] 2. The present application solves the contradiction between large amount of collected data and processing speed, and the real-time processing and display device can realize real-time processing and display. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the present application, the following briefly introduces the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 The flowchart of the distributed optical fiber burst vibration detection method based on adaptive fitting of the present application embodiment one;

[0046] Figure 2 The method flowchart of the adaptive polynomial fitting of the present application embodiment one;

[0047] Figure 3 Figure 2 is a structural schematic diagram of a distributed optical fiber abrupt vibration detection device based on adaptive fitting according to an embodiment of the present application. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0049] In order to make the above objectives, characteristics and advantages of the present application more apparent, further detailed description will be made to the present application with reference to the drawings and specific embodiments.

[0050] Embodiment one

[0051] As shown in Figure 1 ,Figure 1 is a flow schematic diagram of a distributed optical fiber abrupt vibration detection method based on adaptive fitting according to an embodiment of the present application, which comprises the following steps. Figure 2

[0052] S1, collecting original data, pre-processing the original data to obtain an original data chain.

[0053] The method for collecting original data comprises: converting the scattered light signal into an electrical signal, converting the coherent intensity value of light into an electrical amplitude value; collecting the converted electrical signal at high speed and discretely, saving it as an lvm format data packet to obtain the original data. In this embodiment, the original data is a one-dimensional long array with a length of L, and the spatial information and time information are intertwined. The collection rate is much greater than the maximum frequency of the electrical signal to ensure that no mixing occurs, thereby extracting accurate external event information.

[0054] The method for obtaining the original data chain comprises:

[0055] 1, block processing the original data to obtain a data block.

[0056] The one-dimensional long array with a length of L is divided into q data blocks, each data block is m rows and n columns, the rows are unified as the spatial information of the optical fiber, and the columns are unified as the time information of the event.

[0057] 2, taking a single spatial point as an index to extract the original data chain.

[0058] The above data block is processed in a chain, taking a spatial point as an axis, each axis point corresponds to a data chain, and then each data block region can be divided into m original data chains.

[0059] S2, performing a polynomial fitting operation on the original data chain to obtain a fitted data chain;

[0060] The fitting operation includes:

[0061]

[0062] In the formula, The fitted data chain is represented by polyfit, and the original data chain is represented by I(n).

[0063] The polynomial fitting analysis includes: performing a first fitting on the original data chain to obtain a fitted curve; and performing a goodness-of-fit judgment based on the fitted curve.

[0064] S3, performing adaptive program adaptation on the fitted data chain to obtain an adapted fitted data chain;

[0065] Specifically, it includes:

[0066] Based on the fitted data chain, a fitted curve is obtained;

[0067] Based on the fitted curve, a goodness-of-fit judgment is performed, and the fitting factor is updated;

[0068] Based on the fitted data chain after updating the fitting factor, fitting is performed again, and the above operations are repeated until the environment characteristics are adapted, and the adapted fitted data chain is output.

[0069] The method of determining whether the environment characteristics are adapted includes:

[0070] The regression sum of squares RSS and the total sum of squares TSS of the fitted data chain are calculated;

[0071] RSS and TSS are determined to determine whether a threshold stable stage is reached, wherein the threshold interval is set according to environmental changes. If the threshold stable stage is reached, the next step is entered; otherwise, fitting is continued, and the next environmental adaptation is performed until the environment characteristics are adapted, and the adapted fitted data chain is output.

[0072] S4, performing a difference operation on the fitted data chain and the original data based on the adapted fitted data chain to obtain a target data chain;

[0073] The method of the difference operation includes:

[0074]

[0075] In the formula, T(n) represents the target data chain, I(n) represents the original data chain, The fitted data chain is represented by polyfit.

[0076] S5, obtaining a target data block based on the target data chain, and judging a burst event type based on the target data block.

[0077] The method for determining the type of the emergency event comprises:

[0078] Based on the target data block, the target data block is observed from a spatial perspective to obtain a position of occurrence of the emergency event;

[0079] Based on a time perspective of the position of occurrence, an envelope of the occurrence of the event is extracted to obtain frequency domain and amplitude information;

[0080] Based on the frequency domain and amplitude information, the type of the emergency event is determined.

[0081] Embodiment two

[0082] As shown in Figure 3 Embodiments of the present application also provide a distributed optical fiber abrupt vibration detection device based on adaptive fitting, comprising: a real-time processing device, an optical-electric conversion device, a high-speed acquisition device, a display device and a historical record query device.

[0083] The optical-electric conversion device is configured to convert the optical signal into an electrical signal.

[0084] Specifically, the scattered light signal is converted into an electrical signal, and the coherent intensity value of the light is converted into an electrical amplitude value, so as to facilitate subsequent processing.

[0085] The high-speed acquisition device is configured to obtain original data based on the electrical signal.

[0086] The specific working process of the high-speed acquisition device for obtaining the original data comprises:

[0087] The converted electrical signal is high-speed discretely collected and saved as an lvm format data packet to obtain the original data. In this embodiment, the original data is a one-dimensional long array with a length of L, and the spatial information and the time information are intertwined. The acquisition rate is much greater than the maximum frequency of the electrical signal to ensure that no mixing occurs, so that accurate external event information can be extracted.

[0088] The real-time processing device is configured to execute the detection method described in Embodiment One to determine the type of the emergency event. Specifically, the real-time processing device comprises:

[0089] a first processing unit, a second processing unit, an adaptive unit, a third processing unit and a determination unit.

[0090] The first processing unit is configured to obtain an original data chain based on the original data.

[0091] The working process of the first processing unit comprises:

[0092] The original data is processed in blocks to obtain data blocks.

[0093] Divide a one-dimensional array of length L into q data blocks, each data block having m rows and n columns. Unify the rows to represent the spatial information of optical fibers and the columns to represent the temporal information of events.

[0094] The original data chain is extracted by using a single spatial point as an index for each data block.

[0095] The data blocks are split into chains, with each spatial point as an axis and each axis point corresponding to a data chain. Thus, each data block region can be divided into m original data chains.

[0096] The second processing unit is used to perform a polynomial fitting operation on the original data chain to obtain the fitted data chain.

[0097] The specific working process of the second processing unit includes:

[0098] The fitting operation includes:

[0099]

[0100] In the formula, I(n) represents the fitted data chain; polyfit represents the polynomial fitting analysis; I(n) represents the original data chain.

[0101] The polynomial fitting analysis includes: performing an initial fitting on the original data chain to obtain a fitting curve; and judging the goodness of fit based on the fitting curve.

[0102] The adaptation unit is used to adaptively adapt the fitted data chain to obtain the adapted fitted data chain.

[0103] The specific working process of the adapter unit includes:

[0104] Based on the fitted data chain, the fitted curve is obtained;

[0105] Based on the fitted curve, the goodness of fit is judged, and the fitting factors are updated.

[0106] The fitted data chain with the updated fitting factors is fitted again, and the above operation is repeated until it adapts to the environmental characteristics, and the adapted fitted data chain is output.

[0107] Methods for determining whether an individual is adapted to environmental characteristics include:

[0108] Calculate the regression sum of squares (RSS) and the total sum of squares (TSS) of the fitted data chain;

[0109] The RSS and TSS are assessed to determine whether a threshold stabilization stage has been reached. The threshold range is set according to environmental changes. If the threshold stabilization stage is reached, the process proceeds to the next step; otherwise, the fitting process continues, performing the next environmental adaptation, until the data adapts to the environmental characteristics, and the adapted fitted data chain is output.

[0110] The third processing unit is configured to perform a difference operation on the fitted data chain and the original data chain to obtain a target data chain;

[0111] The specific working process of the third processing unit includes:

[0112] The method of the difference operation includes:

[0113]

[0114] In the formula, T(n) represents the target data chain, I(n) represents the original data chain, represents the fitted data chain.

[0115] The judging unit is configured to obtain a target data block based on the target data chain, and determine a type of the burst event based on the target data block.

[0116] The method of determining the type of the burst event by the judging unit includes:

[0117] Based on the target data block, a spatial perspective of the target data block is observed to obtain a position of the burst event;

[0118] Based on a time perspective of the position, an envelope of the event is extracted to obtain frequency domain and amplitude information;

[0119] Based on the frequency domain and amplitude information, the type of the burst event is determined.

[0120] The display device is configured to trigger an alarm light based on the burst event;

[0121] Specifically, the display device is further configured to display a three-dimensional mode of the target data block, a vibration position, amplitude and frequency information of the event, and trigger the alarm light to alarm when the burst event is detected to prevent the occurrence of disasters.

[0122] The historical record query device is configured to store the target data block and provide a historical query interface.

[0123] The above-described embodiments are only descriptions of the preferred modes of the present application, and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those skilled in the art shall fall within the protection scope of the present application as defined by the claims.

Claims

1. A method for distributed fiber abrupt vibration detection based on adaptive fitting, characterized in that, The method comprises the following steps: Collecting original data, preprocessing the original data, and obtaining an original data chain; Performing a polynomial fitting operation on the original data chain to obtain a fitted data chain; Adapting the fitted data chain to obtain an adapted fitted data chain; The method for obtaining the adapted fitted data chain comprises the following steps: Based on the fitted data chain, a fitting curve is obtained; Based on the fitting curve, a goodness-of-fit judgment is performed, and a fitting factor is updated; Based on the fitted data chain after updating the fitting factor, fitting is performed again, and the above operations are repeated until the environmental characteristics are adapted, and the adapted fitted data chain is output; The method for judging whether the environmental characteristics are adapted comprises the following steps: Calculate the regression sum of squares RSS and the total sum of squares TSS of the fitted data chain; Determine whether the RSS and the TSS reach a threshold stable stage; if yes, proceed to the next step; otherwise, continue fitting and perform the next environmental adaptation; Based on the difference between the adapted fitted data chain and the original data, a target data chain is obtained; Based on the target data chain, a target data block is obtained, and the type of the burst event is determined based on the target data block.

2. The method of claim 1, wherein, The method for obtaining the original data chain comprises the following steps: The original data is divided into blocks to obtain data blocks; The original data chain is extracted by taking a single spatial point as an index.

3. The method of claim 1, wherein, The polynomial fitting operation comprises the following steps: wherein represents the fitted data chain; polyfit represents the polynomial fit analysis; I(n) represents the original data chain.

4. The method of claim 1, wherein, The method for determining the type of the burst event comprises the following steps: Based on the target data block, the target data block is observed from a spatial perspective to obtain the occurrence position of the burst event; Based on the time perspective of the occurrence position, the envelope of the event occurrence is extracted to obtain frequency domain and amplitude information; Based on the frequency domain and amplitude information, the type of the burst event is determined.

5. A distributed fiber optic sudden change vibration detection apparatus based on adaptive fitting, comprising: The method comprises the following steps: Real-time processing device; The real-time processing device is used to execute the detection method of any one of claims 1-4, so as to determine the type of the burst event; The detection device further comprises a photoelectric conversion device, a high-speed acquisition device, a display device, and a historical record query device; The photoelectric conversion device is used to convert an optical signal into an electrical signal; The high-speed acquisition device is used to obtain original data based on the electrical signal; The display device is used to trigger an alarm light based on the burst event; The historical record query device is used to provide a historical query interface.

6. The distributed fiber optic sudden change vibration detection apparatus based on adaptive fitting of claim 5, wherein, The method for obtaining the original data by the high-speed acquisition device comprises the following steps: The electrical signal is high-speed discretely collected, the electrical signal subjected to high-speed discretization collection is saved as an lvm format data packet, and the original data is obtained based on the data packet.

7. The distributed fiber optic sudden change vibration detection apparatus based on adaptive fitting of claim 5, wherein, The real-time processing device comprises the following units: A first processing unit, a second processing unit, an adaptation unit, a third processing unit, and a judgment unit; The first processing unit is used to obtain an original data chain based on the original data; The second processing unit is used to perform a polynomial fitting operation on the original data chain to obtain a fitted data chain; The adaptation unit is used to adapt the fitted data chain to obtain an adapted fitted data chain; The third processing unit is used to perform a difference operation on the adapted fitted data chain and the original data chain to obtain a target data chain; The judging unit is configured to obtain a target data block based on the target data link, and judge the type of the emergency event based on the target data block.

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