A monitoring method for cable pipeline collapse signal based on Φ-OTDR

Abstract

The present invention discloses a monitoring method for cable pipeline collapse signals based on Φ-OTDR, including: real-time monitoring and collecting distributed vibration data along the cable line; preprocessing the distributed vibration data; based on the preprocessed distributed vibration data, monitoring and identifying the cable pipeline collapse event signal through image processing and contour recognition, and realizing real-time full-line pipeline collapse event online monitoring and positioning. The present invention can monitor and analyze all vibration information of the entire cable pipeline in real time, can accurately parse out each pipeline collapse signal and locate the collapse section, provide real-time early warning services for the safe operation of optical cables, improve the reliability and safety of optical cable operation, and directly use redundant communication optical cables on both sides of the road to monitor the collapse situation, without the need for additional sensors, low cost, strong anti-interference ability, and low system maintenance costs.

Description

Technical Field

[0001] The invention relates to the technical field of optical cable monitoring, and in particular to a method for monitoring cable pipeline collapse signals based on Φ-OTDR. Background Art

[0002] In recent years, with the development of the economy, the traffic volume on the road has been increasing, and the phenomenon of overloading of trucks has become increasingly frequent. Due to long-term rain erosion, the roadbed may collapse due to insufficient bearing capacity, and at the same time, it will cause the collapse of cable pipelines on both sides of the road. In addition, when there are caves or burrows of animals such as rats under the pipeline, it may also cause the collapse of cable pipelines. The collapse of cable pipelines may cause major traffic accidents and cable breakage, greatly affecting the safety of traffic and pipelines. However, collapse events generally do not occur suddenly. The collapse events that can be seen on the surface are usually the result of long-term underground occurrence. If the collapse of cable pipelines can be monitored, the collapse point can be located in the early stage of the collapse accident before it causes major damage. The collapse position can be reinforced and repaired in time to avoid accidents and reduce economic losses. Therefore, it is very necessary to monitor the collapse of cable pipelines. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the roadbed may collapse due to insufficient bearing capacity, which may cause the cable pipelines on both sides of the road to collapse. When there are caves or burrows of animals such as mice under the pipelines, the cable pipelines may also collapse. The collapse of the cable pipelines may cause major traffic accidents and cable breakage, greatly affecting the safety of traffic and pipelines.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: real-time monitoring and collection of distributed vibration data along the cable; preprocessing the distributed vibration data; based on the preprocessed distributed vibration data, through image processing and contour recognition, monitoring and identifying the cable pipeline collapse event signal, to achieve real-time online monitoring and positioning of pipeline collapse events along the entire line.

[0007] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, the collected distributed vibration data along the cable is stored in a time length of 5 seconds, and each result file contains the vibration data of the entire line for 5 seconds.

[0008] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, wherein: a single monitoring result data is defined as time-space three-dimensional data, the time axis i represents a 5-second time range, the space axis j represents the entire cable length, H(i,j) is denoted as the corresponding array on the time-space coordinates, and its element H(i,j) refers to the vibration signal intensity of the spatial point i at the time j. After the H(i,j) is subjected to data normalization and de-meaning processing, high-pass filtering is performed to filter out noise signals.

[0009] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, the filtered result data is defined as I(i,j), and the time-space vibration signal heat map is drawn with the I(i,j) data. When a collapse event occurs, the cable vibration is driven, which indirectly stimulates the optical fiber vibration signal, causing the vibration signal in the collapse period to increase rapidly. The length of the highlighted area that appears locally represents the time and duration of the collapse event, and the width of the highlighted area represents the collapse event section.

[0010] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, the time-space vibration signal heat map is converted from RGB format to HSV format, and the hue channel data in the HSV image information is selected as single-channel image data.

[0011] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, the single-channel image array is defined as K(i,j), and K(i,j) is binarized. The threshold is initially set to 100, and then fine-tuned according to the long-term event recognition rate. The maximum value is set to 255, that is, if K(i,j) is greater than 100, K(i,j) is reassigned to 255, otherwise it is reassigned to 0. If the binary result array is all 255, no collapse event is monitored.

[0012] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, wherein: a square convolution kernel with 3 rows and 3 columns is used to corrode and expand the binarized image data, and the processed single-channel image data is defined as J(i, j), the elements in the J(i, j) two-dimensional array represent the relative vibration intensity of the spatial point i at the time j, and the values ​​in the J(i, j) are pixel-inverted, that is, J(i, j) = 255-J(i, j); contour recognition is performed on the above-mentioned result image data, the minimum circumscribed rectangle is taken according to each contour result, and then the angle correction is performed on the rectangle with the deflection angle; the rectangular contours are merged and detected, and the intersecting or close rectangular contours are fused, and the margin threshold of two adjacent rectangular contours is initially set to 5, and the number of fragmented events is reduced by fusion processing.

[0013] As a preferred solution of the cable pipeline collapse signal monitoring method based on Φ-OTDR described in the present invention, the time and space segment of the collapse event are determined based on the coordinates of the vertices of the rectangular outline: an event outline is defined and identified as a rectangle ABCD, and the coordinates of each point are recorded as A(ia, ja), B(ib, jb), and C(ic, jc). At the same time, the time axis series is recorded as I(i), which refers to the moment at the time axis index i, and the space axis series is recorded as J(j), which refers to the cable distance at the space axis index j, that is, the distance from the Φ-OTDR device. The start time of the event is I(ia), the end time is I(ib), the duration is I(ib)-I(ia), and the occurrence position is the segment from the device J(ia) to the device J(ic).

[0014] The beneficial effects of the present invention are as follows: the present invention can monitor and analyze all vibration information of the entire cable pipeline in real time, can accurately analyze each pipeline collapse signal and locate the collapse section, provide real-time early warning services for the safe operation of the optical cable, and improve the reliability and safety of the optical cable operation. In addition, the redundant communication optical cables on both sides of the road are directly used to monitor the collapse situation, without the need for additional sensors, with low cost, strong anti-interference ability, and low system maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0016] Figure 1 A basic flow chart of a method for monitoring cable pipeline collapse signals based on Φ-OTDR provided by an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of a data monitoring process of a method for monitoring cable pipeline collapse signals based on Φ-OTDR provided by an embodiment of the present invention;

[0018] Figure 3 A typical pipeline collapse time domain signal time-space distribution heat map of a cable pipeline collapse signal monitoring method based on Φ-OTDR provided by an embodiment of the present invention;

[0019] Figure 4 A heat map of the time-space distribution of a time-domain signal after image format conversion in a method for monitoring a cable pipeline collapse signal based on Φ-OTDR provided by an embodiment of the present invention;

[0020] Figure 5 A time-space distribution heat map of a time domain signal after binarization, corrosion and expansion processing of a cable pipeline collapse signal monitoring method based on Φ-OTDR provided by an embodiment of the present invention;

[0021] Figure 6 A schematic diagram of a collapse event contour recognition result of a method for monitoring collapse signals of a cable pipeline based on Φ-OTDR provided by an embodiment of the present invention;

[0022] Figure 7 A schematic diagram of a fault location curve of an actual test of a method for monitoring a cable pipeline collapse signal based on Φ-OTDR provided by an embodiment of the present invention;

[0023] Figure 8 A schematic diagram of a denoised curve of a method for monitoring cable pipeline collapse signals based on Φ-OTDR provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0027] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0028] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0029] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0030] Example 1

[0031] Reference Figures 1 to 6 , as an embodiment of the present invention, provides a method for monitoring cable pipeline collapse signals based on Φ-OTDR, comprising:

[0032] S1: Real-time monitoring and collection of distributed vibration data along the cable.

[0033] It should be noted that the Φ-OTDR is connected to a redundant optical fiber of the cable to be monitored to realize distributed monitoring of vibration signals along the cable; the monitoring data results are stored in 5-second time lengths, and each result file contains 5-second vibration data of the entire line.

[0034] S2: Preprocess the distributed vibration data.

[0035] It should be noted that the data of a single monitoring result is three-dimensional data in time and space. The time axis i represents the 5-second time range, and the space axis j represents the entire length of the cable. H(i,j) is the corresponding array in the time and space coordinates, and its element H(i,j) refers to the vibration signal intensity of the spatial point i at time j. After data normalization and de-averaging processing are performed on H(i,j), high-pass filtering is performed to filter out noise signals.

[0036] S3: Based on the pre-processed distributed vibration data, the cable pipeline collapse event signal is monitored and identified through image processing and contour recognition, realizing real-time online monitoring and positioning of pipeline collapse events along the entire line.

[0037] It should be noted that the filtered result data is recorded as I(i,j), and the time-space vibration signal heat map is drawn with I(i,j) data, as shown in Figure 3 As shown, Figure 3 The spatiotemporal thermal map of vibration signals of typical landslide events is shown. When a landslide event occurs, it will drive the cable to vibrate, which will indirectly stimulate the optical fiber vibration signal, causing the vibration signal in the area where the landslide occurs to increase rapidly. Figure 3 It is manifested as a local highlighted area. The length of the highlighted area (time span) represents the time and duration of the landslide event, and the width of the highlighted area (spatial span) represents the section where the landslide event occurred.

[0038] Further, Figure 3 Convert from RGB format to HSV format, select the hue channel data in the HSV image information as the single-channel image data, and the image result is as follows Figure 4 shown.

[0039] remember Figure 4 The single-channel image array is K(i,j), and K(i,j) is binarized. The threshold is initially set to 100, and can be fine-tuned later according to the long-term event recognition rate. The maximum value is set to 255, that is, if K(i,j) is greater than 100, K(i,j) is reassigned to 255, otherwise it is reassigned to 0. If the binary result array is all 255, no landslide event is detected.

[0040] Furthermore, a square convolution kernel with 3 rows and 3 columns is used to corrode and dilate the binarized image data. The processed image result is as follows: Figure 5 shown.

[0041] remember Figure 5 The single-channel image data is J(i,j). The elements in the two-dimensional array J(i,j) represent the relative vibration intensity of spatial point i at time j. The values ​​in J(i,j) are inverted pixel by pixel, that is, J(i,j)=255-J(i,j).

[0042] The contour recognition is performed on the above result image data, the minimum circumscribed rectangle is obtained according to each contour result, and then the angle correction is performed on the rectangle with the deflection angle.

[0043] The rectangular contours are merged and detected, and the intersecting or close rectangular contours are fused. The margin threshold of two adjacent rectangular contours is initially set to 5. The number of fragmented events is reduced through fusion processing. The final contour recognition result is as follows: Figure 6 As shown;

[0044] The time and space section of the landslide event can be determined by the coordinates of the vertices of each rectangular outline in the above steps; Figure 6 Take contour recognition as an example. Figure 6 An event outline is identified as a rectangle ABCD, and the coordinates of each point are recorded as A(ia,ja), B(ib,jb), and C(ic,jc). At the same time, the time axis series is recorded as I(i), which refers to the moment at the time axis index i, and the space axis series is recorded as J(j), which refers to the cable distance at the space axis index j (the distance from the Φ-OTDR device). Then the start time of the event is I(ia), the end time is I(ib), the duration is I(ib)-I(ia), and the occurrence location is the section from the device J(ia) to the device J(ic).

[0045] The present invention can monitor and analyze all vibration information of the entire cable pipeline in real time, accurately analyze each pipeline collapse signal and locate the collapse section, provide real-time early warning services for the safe operation of the optical cable, and improve the reliability and safety of the optical cable operation.

[0046] Example 2

[0047] Reference Figures 7-8 This is another embodiment of the present invention. Different from the first embodiment, this embodiment provides a verification test of a cable pipeline collapse signal monitoring method based on Φ-OTDR. In order to verify and illustrate the technical effect adopted in this method, this embodiment adopts a traditional technical solution and the method of the present invention for comparative testing, and compares the test results by means of scientific demonstration to verify the real effect of this method.

[0048] In this embodiment, a cable pipeline system is built in the SUMULIK environment in the MATLB software programming. Based on different forms of landslides and adding noise interference signals during the landslide process, the signal is tested using the method of the present invention. The test results are as follows: Figures 7-8 As shown, Figure 7 The figure shows the strong noise simulation signal of Φ-OTDR. Figure 8This is the original Φ-OTDR signal diagram extracted by the method of the present invention. The horizontal axis in the figure represents the number of sampling points of the curve, and the vertical axis represents the optical power value (dB) of the sampling point. Through simulation verification results, it can be seen that the effectiveness of the method of the present invention in suppressing Φ-OTDR noise interference not only improves the smoothness of the curve within the dynamic range, but also maintains the basic characteristics of the Φ-OTDR signal after eliminating the noise, which is conducive to real-time processing of the signal.

[0049] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in an assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed ASIC for this purpose.

[0050] Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. The computer program includes a plurality of instructions that may be executed by one or more processors.

[0051] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor, the invention described herein includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques described in the present invention, the present invention also includes the computer itself. The computer program can be applied to input data to perform the functions described herein, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on a display.

[0052] As used in this application, the terms "component", "module", "system", etc. are intended to refer to a computer-related entity, which can be hardware, firmware, a combination of hardware and software, software, or software in operation. For example, a component can be, but is not limited to: a process running on a processor, a processor, an object, an executable file, a thread in execution, a program, and / or a computer. As an example, an application running on a computing device and the computing device can both be components. One or more components can exist in a process and / or thread in execution, and a component can be located in a computer and / or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures thereon. These components can communicate in a local and / or remote process manner, such as according to a signal having one or more data packets (e.g., data from a component that interacts with another component in a local system, a distributed system, and / or interacts with other systems in a signal manner through a network such as the Internet).

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring cable pipeline collapse signals based on Φ-OTDR, characterized in that: include: Real-time monitoring and collection of distributed vibration data along the cable line; Preprocessing the distributed vibration data; Based on the pre-processed distributed vibration data, the cable pipeline collapse event signal is monitored and identified through image processing and contour recognition, realizing real-time online monitoring and positioning of pipeline collapse events along the entire line; The collected distributed vibration data along the cable are stored in a time length of 5 seconds, and each result file contains 5 seconds of vibration data of the entire line; Define a single monitoring result data as spatiotemporal three-dimensional data, where the time axis i represents a 5-second time range, and the space axis j represents the full length of the cable. H(i,j) is the corresponding array on the spatiotemporal coordinates, and its element H(i,j) refers to the vibration signal intensity of the spatial point i at time j. After data normalization and de-averaging processing are performed on H(i,j), high-pass filtering is performed to filter out noise signals; The result data after filtering is defined as I(i,j), and the time-space vibration signal heat map is drawn with the I(i,j) data. When a landslide occurs, it will drive the cable to vibrate, indirectly stimulate the optical fiber vibration signal, and rapidly enhance the vibration signal in the area where the landslide occurs. The length of the highlighted area that appears locally represents the time and duration of the landslide, and the width of the highlighted area represents the section where the landslide occurs. Convert the time-space vibration signal heat map from RGB format to HSV format, and select the hue channel data in the HSV image information as single-channel image data; The single-channel image data is defined as K(i,j), and K(i,j) is binarized. The threshold is initially set to 100, and then fine-tuned according to the long-term event recognition rate. The maximum value is set to 255, that is, if K(i,j) is greater than 100, K(i,j) is reassigned to 255, otherwise it is reassigned to 0. If the binarization result array is all 255, no landslide event is detected; The time and space segment of the landslide event are determined based on the coordinates of the vertices of the rectangular contour obtained based on the contour recognition: an event contour is defined as a rectangle ABCD, and the coordinates of each point are recorded as A(ia, ja), B(ib, jb), and C(ic, jc). At the same time, the time axis series is recorded as I(i), which refers to the moment at the time axis index i, and the space axis series is recorded as J(j), which refers to the cable distance at the space axis index j, that is, the distance from the Φ-OTDR device. The start time of the event is I(ia), the end time is I(ib), the duration is I(ib)-I(ia), and the occurrence position is the segment from the device J(ia) to the device J(ic).

2. The cable pipeline collapse signal monitoring method based on Φ-OTDR as claimed in claim 1, characterized in that: A square convolution kernel with 3 rows and 3 columns is used to corrode and expand the binarized image data, and the processed single-channel image data is defined as J(i, j). The elements in the two-dimensional array J(i, j) represent the relative vibration intensity of the spatial point i at the time j. The pixel value in J(i, j) is inverted, that is, J(i, j) = 255-J(i, j); Perform contour recognition on the processed single-channel image data after pixel inversion, take the minimum circumscribed rectangle based on each contour result, and then perform angle correction on the rectangle with deflection angle; The rectangular contours are merged and detected, and the intersecting or close rectangular contours are fused. The margin threshold of two adjacent rectangular contours is initially set to 5, and the number of fragmented events is reduced through fusion processing.

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