Fault detection method and device for submarine cable and computer program product

Abstract

The invention discloses a submarine cable fault detection method and device and a computer program product, and relates to the technical field of offshore engineering, and the method comprises the steps: collecting a disturbance signal of a submarine cable, and obtaining the disturbance signal data of the submarine cable; performing feature extraction on the disturbance signal data to obtain a feature extraction result; performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable; and determining the fault type of the submarine cable based on the fault recording of the submarine cable by using a fault diagnosis model under the condition that the fault detection result is that the fault exists. By adopting the technical scheme, the problem of how to improve the fault detection efficiency of the submarine cable is solved.

Description

Technical Field

[0001] The present application relates to the field of offshore engineering technology, and in particular to a method, device and computer program product for detecting faults of submarine cables. Background Art

[0002] Submarine cables play a vital role in the power transmission system of offshore wind farms. They are not only responsible for transmitting the electricity generated by offshore wind turbines to the land power grid, but also undertake the task of data communication. However, submarine cables face a variety of potential threats in the marine environment, including mechanical fatigue, ocean current impact, and external interference (such as ship anchoring, fishing activities, etc.). These factors may cause abnormal vibration of the cable, which in turn leads to cable damage or insulation failure.

[0003] At present, submarine cable monitoring technology mainly relies on the vibration detection method of the phase change of backscattered Rayleigh light. This technology can provide high-resolution vibration data, but the transmission of massive amounts of raw vibration data has become a problem for remote monitoring and data analysis. The traditional data transmission method requires all collected vibration data to be transmitted to the land-based control center for processing, which not only consumes precious network bandwidth resources, but may also cause production data transmission to be blocked, affecting the normal operation of offshore wind farms.

[0004] Therefore, in the related art, there is a problem of how to improve the fault detection efficiency of submarine cables.

[0005] Regarding the problem of how to improve the fault detection efficiency of submarine cables in related technologies, no effective solution has been proposed so far.

[0006] Therefore, it is necessary to improve the related technology to overcome the above-mentioned defects in the related technology. Summary of the invention

[0007] The embodiments of the present application provide a submarine cable fault detection method, device and computer program product to at least solve the problem of how to improve the efficiency of submarine cable fault detection in the related art.

[0008] According to one aspect of an embodiment of the present application, a method for detecting a fault of a submarine cable is provided, comprising: collecting a disturbance signal of a submarine cable to obtain disturbance signal data of the submarine cable; performing feature extraction on the disturbance signal data to obtain a feature extraction result; performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable; and, when it is determined that the fault detection result indicates that a fault exists, determining the fault type of the submarine cable based on a fault recording of the submarine cable using a fault diagnosis model.

[0009] In an exemplary embodiment, the submarine cable includes an optical fiber, and the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable, including: determining signal collection parameters for collecting the disturbance signal, wherein the signal collection parameters at least include a sampling frequency; injecting pulse light into the optical fiber, and collecting signals at the measuring points of the submarine cable according to the sampling frequency to obtain the disturbance signal data.

[0010] In an exemplary embodiment, feature extraction is performed on the disturbance signal data to obtain a feature extraction result, including: extracting time domain features of the disturbance signal data, wherein the time domain features include disturbance amplitude, kurtosis and skewness; extracting frequency domain features of the disturbance signal data, wherein the frequency domain features include vibration frequency distribution; extracting time-frequency domain features of the disturbance signal data, wherein the time-frequency domain features include energy distribution; and determining the time domain features, the frequency domain features and the time-frequency domain features as the feature extraction result.

[0011] In an exemplary embodiment, fault detection is performed on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable, including: for multiple feature values ​​in the feature extraction result, determining whether the multiple feature values ​​all belong to a preset feature value range; if it is determined that the multiple feature values ​​all belong to the preset feature value range, determining that there is no fault in the submarine cable; if it is determined that there is a feature value in the multiple feature values ​​that does not belong to the preset feature value range, determining that there is a fault in the submarine cable.

[0012] In an exemplary embodiment, when it is determined that the fault detection result is a fault, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable, including: obtaining the fault recording of the submarine cable, wherein the fault recording is used to record the waveform data of the disturbance signal within a target time period, and the target time period represents the period from a preset time before a fault occurrence time node to the preset time after the fault occurrence time node; inputting the fault recording into the fault diagnosis model to obtain the fault type output by the fault diagnosis model; and sending the fault type and the position of the measurement point where the fault recording is collected to the target object.

[0013] In an exemplary embodiment, the fault diagnosis model is trained in the following manner, including: obtaining historical fault records of the submarine cable, wherein the historical fault records include historical fault recordings and historical fault types; training an initial model with the historical fault recordings as input samples and the historical fault types as output samples to obtain a trained model; testing the trained model, and when it is determined that the test accuracy of the trained model is greater than a preset accuracy, determining the trained model as the fault diagnosis model.

[0014] According to another aspect of an embodiment of the present application, a fault detection device for a submarine cable is further provided, comprising: a signal acquisition module, used to acquire a disturbance signal of a submarine cable to obtain disturbance signal data of the submarine cable; a feature extraction module, used to perform feature extraction on the disturbance signal data to obtain a feature extraction result; a fault detection module, used to perform fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable; and a fault diagnosis module, used to determine the fault type of the submarine cable based on the fault recording of the submarine cable using a fault diagnosis model when it is determined that the fault detection result indicates that a fault exists.

[0015] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned submarine cable fault detection method when running.

[0016] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the submarine cable fault detection method through the computer program.

[0017] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps of the method described in each embodiment of the present application are implemented.

[0018] Through this application, the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable; the feature extraction of the disturbance signal data is performed to obtain the feature extraction result; the submarine cable is fault detected according to the feature extraction result to obtain the fault detection result of the submarine cable; when it is determined that the fault detection result is a fault, the fault type of the submarine cable is determined based on the fault recording of the submarine cable using the fault diagnosis model. The disturbance signal of the submarine cable can be collected in real time at the edge end, and the key features can be quickly extracted, so that potential fault conditions can be identified at the first time, avoiding the delay of data processing in traditional monitoring methods, and making fault detection more timely and effective. Thereby solving the problem of how to improve the fault detection efficiency of the submarine cable in the related technology, and achieving the effect of improving the fault detection efficiency of the submarine cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0021] Figure 1 It is a hardware structure block diagram of a computer terminal of a submarine cable fault detection method according to an embodiment of the present application;

[0022] Figure 2 is a flow chart of a method for detecting a fault of a submarine cable according to an embodiment of the present application;

[0023] Figure 3 It is a structural block diagram of a submarine cable fault detection device according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] The method embodiments provided in the embodiments of the present application can be executed in a computer terminal or a similar computing device. Taking running on a computer terminal as an example, Figure 1 1 is a hardware structure block diagram of a computer terminal of a submarine cable fault detection method according to an embodiment of the present application. Figure 1 As shown, the computer terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor (Central Processing Unit, MCU) or a programmable logic device (Field Programmable Gate Array, FPGA)) and a memory 104 for storing data, wherein the above-mentioned computer terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0027] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the fault detection method of the submarine cable in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0028] A wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0029] In this embodiment, a method for detecting faults in a submarine cable is provided. Figure 2 is a flow chart of a submarine cable fault detection method according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0030] Step S202, collecting disturbance signals of the submarine cable to obtain disturbance signal data of the submarine cable;

[0031] Optionally, in the above step S202, the disturbance signal refers to abnormal vibration of the submarine cable caused by mechanical fatigue, ocean current impact or external interference, etc. These abnormal vibrations can be detected and analyzed by specific monitoring technology to identify and warn potential failures or damages.

[0032] Step S204, performing feature extraction on the disturbance signal data to obtain a feature extraction result;

[0033] Step S206, performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable;

[0034] Step S208: When it is determined that the fault detection result indicates that a fault exists, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable.

[0035] Optionally, the above steps can be implemented by an edge computing device installed at the submarine cable measurement point, which can perform signal acquisition, data calculation and processing, perform fault diagnosis through a built-in trained fault diagnosis model, and transmit data to a centralized control center.

[0036] Through the above steps, the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable; the feature extraction is performed on the disturbance signal data to obtain the feature extraction result; the submarine cable is fault detected according to the feature extraction result to obtain the fault detection result of the submarine cable; when it is determined that the fault detection result is a fault, the fault type of the submarine cable is determined based on the fault recording of the submarine cable using the fault diagnosis model. The disturbance signal of the submarine cable can be collected in real time at the edge end, and the key features can be quickly extracted, so that potential fault conditions can be identified at the first time, avoiding the delay of data processing in traditional monitoring methods, and making fault detection more timely and effective. Thereby solving the problem of how to improve the fault detection efficiency of the submarine cable in the related technology, and achieving the effect of improving the fault detection efficiency of the submarine cable.

[0037] In an exemplary embodiment, the submarine cable includes an optical fiber, and the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable, including: determining signal collection parameters for collecting the disturbance signal, wherein the signal collection parameters at least include a sampling frequency; injecting pulse light into the optical fiber, and collecting signals at the measuring points of the submarine cable according to the sampling frequency to obtain the disturbance signal data.

[0038] Optionally, in the above embodiment, the sampling frequency refers to the number of times a continuous signal is sampled per unit time. The sampling frequency is expressed in Hertz (Hz), and the sampling frequency determines the degree of digitization of the signal and the highest frequency that can be accurately represented. The signal acquisition parameters may also include spatial resolution, which refers to the ability of the measurement system to distinguish the minimum distance between two adjacent points or objects. For example, the spatial resolution can be set to 10m and the sampling frequency to 2000Hz. A spatial resolution of 10m means that submarine cable disturbances at different locations at least 10 meters apart can be identified. A sampling frequency of 2000Hz means that the system collects 2000 data points per second. High spatial resolution and high sampling frequency help to more accurately locate the location of the disturbance and capture rapid changes in the disturbance.

[0039] In an optional embodiment, the process of collecting the disturbance signal of the submarine cable is as follows: first, the signal acquisition parameters are determined. In this embodiment, 2000 Hz is selected as the sampling frequency, which means that 2000 data points will be collected per second. This frequency is high enough to capture the subtle disturbances of the submarine cable, and at the same time, it will not generate too much data, which will affect the efficiency of data transmission. The spatial resolution can be selected as 10m, which means that the submarine cable disturbances at different locations at least 10 meters apart can be identified. Then a pulse light source is used, which can generate short pulses of light and inject them into the optical fiber according to the set sampling frequency. Each pulse of light will propagate in the optical fiber and generate Brillouin scattering when encountering the disturbance of the submarine cable. When the light pulse interacts with the sound wave (Brillouin wave) in the optical fiber, Brillouin scattering will occur. By measuring the frequency change of the scattered light, the Brillouin frequency can be calculated, and then the disturbance signal data can be obtained.

[0040] In an exemplary embodiment, feature extraction is performed on the disturbance signal data to obtain a feature extraction result, including: extracting time domain features of the disturbance signal data, wherein the time domain features include disturbance amplitude, kurtosis and skewness; extracting frequency domain features of the disturbance signal data, wherein the frequency domain features include vibration frequency distribution; extracting time-frequency domain features of the disturbance signal data, wherein the time-frequency domain features include energy distribution; and determining the time domain features, the frequency domain features and the time-frequency domain features as the feature extraction result.

[0041] Optionally, in the above embodiment, the disturbance amplitude is realized by calculating the maximum amplitude of the signal, which reflects the intensity of the disturbance to the submarine cable. Kurtosis is a statistic that measures the sharpness of the signal waveform. The kurtosis value is obtained by calculating the fourth-order normalized moment of the signal, which is used to identify abnormal peaks in the signal. Skewness is a statistic that measures the degree of skewness of the signal waveform. The skewness value is obtained by calculating the third-order normalized moment of the signal, which is used to identify the asymmetry of the signal. The disturbance signal is Fourier transformed, the time domain signal is converted into a frequency domain signal, and then the distribution of different frequency components is analyzed, so that the main frequency components causing the disturbance can be identified. Use time-frequency analysis methods, such as short-time Fourier transform or wavelet transform to analyze the distribution of the signal energy at different times and frequencies. Then, the energy concentration area of ​​the disturbance signal at different times and frequencies can be identified.

[0042] Optionally, in the above embodiment, the feature extraction results can be used for fault diagnosis. For example, if the disturbance amplitude is abnormally high, it may indicate that the submarine cable is subjected to strong external impact; if the kurtosis and skewness values ​​are abnormal, it may indicate that there are abnormal spikes or asymmetry in the signal; if the frequency domain and time-frequency domain features show that a specific frequency component is abnormal, it may indicate a specific disturbance source. Through these features, the health of the submarine cable can be diagnosed more accurately, and timely measures can be taken to prevent potential failures.

[0043] In an exemplary embodiment, fault detection is performed on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable, including: for multiple feature values ​​in the feature extraction result, determining whether the multiple feature values ​​all belong to a preset feature value range; if it is determined that the multiple feature values ​​all belong to the preset feature value range, determining that there is no fault in the submarine cable; if it is determined that there is a feature value in the multiple feature values ​​that does not belong to the preset feature value range, determining that there is a fault in the submarine cable.

[0044] Optionally, in the above embodiment, for example, the characteristic values ​​in the feature extraction result include disturbance amplitude, kurtosis, skewness index in the time domain, spectrum analysis results in the frequency domain, and energy spectrum in the time-frequency domain. After analyzing the historical data, a preset characteristic value range is set for each characteristic value. This range is based on the characteristic value statistics of the submarine cable under normal operating conditions and is used to determine whether the cable is normal. The extracted characteristic values ​​are compared with the preset characteristic value range. If all the extracted characteristic values ​​are within the preset characteristic value range, the system will determine that there is no fault in the submarine cable. If any characteristic value exceeds the preset characteristic value range, the system will determine that there is a fault in the submarine cable.

[0045] In an exemplary embodiment, when it is determined that the fault detection result is a fault, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable, including: obtaining the fault recording of the submarine cable, wherein the fault recording is used to record the waveform data of the disturbance signal within a target time period, and the target time period represents the period from a preset time before a fault occurrence time node to the preset time after the fault occurrence time node; inputting the fault recording into the fault diagnosis model to obtain the fault type output by the fault diagnosis model; and sending the fault type and the position of the measurement point where the fault recording is collected to the target object.

[0046] Optionally, in the above embodiment, during the monitoring of the submarine cable, once a fault is detected, the edge computing device will immediately start the fault recording function. Fault recording refers to recording the waveform data of the disturbance signal within a preset time period before and after the fault occurs. For example, if the preset time is 5 seconds before and after the fault occurs, the fault recording will cover the time period from 5 seconds before the fault occurs to 5 seconds after the fault occurs. After obtaining the fault recording, these waveform data are input into a pre-trained fault diagnosis model. The fault diagnosis model is a machine learning model that can identify the fault type based on the input waveform data. This model is trained on a large amount of historical fault data based on deep learning. After analyzing the fault recording data, the fault diagnosis model will output a fault type, such as "anchor damage", "fishing damage", "mechanical fatigue", etc. This output is based on the feature extraction and learning results of the waveform data by the model, and can more accurately determine the nature of the fault. Once the fault type is determined, the edge computing device will send the fault type and the location information of the measurement point where the fault recording is collected to the target object, such as to a remote centralized control center.

[0047] In an exemplary embodiment, the fault diagnosis model is trained in the following manner, including: obtaining historical fault records of the submarine cable, wherein the historical fault records include historical fault recordings and historical fault types; training an initial model with the historical fault recordings as input samples and the historical fault types as output samples to obtain a trained model; testing the trained model, and when it is determined that the test accuracy of the trained model is greater than a preset accuracy, determining the trained model as the fault diagnosis model.

[0048] Through the above embodiments, submarine cable disturbance monitoring and fault diagnosis based on edge computing architecture can be realized, which effectively reduces the data transmission volume and improves data security. At the same time, it has signal data acquisition, time-frequency domain signal feature calculation, fault recording and fault type diagnosis functions, thereby improving the fault detection efficiency of submarine cables.

[0049] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0050] In this embodiment, a submarine cable fault detection device is also provided, which is used to implement the above embodiments and preferred implementations, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0051] Figure 3 : is a structural block diagram of a submarine cable fault detection device according to an embodiment of the present application, the device comprising:

[0052] A signal acquisition module 32, used to collect disturbance signals of the submarine cable to obtain disturbance signal data of the submarine cable;

[0053] A feature extraction module 34 is used to extract features from the disturbance signal data to obtain feature extraction results;

[0054] A fault detection module 36, configured to perform fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable;

[0055] The fault diagnosis module 38 is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable using a fault diagnosis model when it is determined that the fault detection result indicates that a fault exists.

[0056] Through the above-mentioned device, the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable; the feature extraction of the disturbance signal data is performed to obtain the feature extraction result; the submarine cable is fault detected according to the feature extraction result to obtain the fault detection result of the submarine cable; when it is determined that the fault detection result is a fault, the fault type of the submarine cable is determined based on the fault recording of the submarine cable using the fault diagnosis model. The disturbance signal of the submarine cable can be collected in real time at the edge end, and the key features can be quickly extracted, so that potential fault conditions can be identified at the first time, avoiding the delay of data processing in traditional monitoring methods, and making fault detection more timely and effective. Thereby solving the problem of how to improve the fault detection efficiency of the submarine cable in the related technology, and achieving the effect of improving the fault detection efficiency of the submarine cable.

[0057] In an exemplary embodiment, the signal acquisition module 32 is also used to determine signal acquisition parameters for collecting the disturbance signal, wherein the signal acquisition parameters at least include a sampling frequency; inject pulse light into the optical fiber, and collect signals from the measuring points of the submarine cable according to the sampling frequency to obtain the disturbance signal data.

[0058] In an exemplary embodiment, the feature extraction module 34 is further used to extract time domain features of the disturbance signal data, wherein the time domain features include disturbance amplitude, kurtosis and skewness; extract frequency domain features of the disturbance signal data, wherein the frequency domain features include vibration frequency distribution; extract time-frequency domain features of the disturbance signal data, wherein the time-frequency domain features include energy distribution; and determine the time domain features, the frequency domain features and the time-frequency domain features as the feature extraction results.

[0059] In an exemplary embodiment, the fault detection module 36 is further used to determine, for a plurality of feature values ​​in the feature extraction result, whether the plurality of feature values ​​all belong to a preset feature value range; if it is determined that the plurality of feature values ​​all belong to the preset feature value range, it is determined that there is no fault in the submarine cable; if it is determined that there is a feature value in the plurality of feature values ​​that does not belong to the preset feature value range, it is determined that there is a fault in the submarine cable.

[0060] In an exemplary embodiment, the above-mentioned fault diagnosis module 38 is also used to obtain the fault recording of the submarine cable, wherein the fault recording is used to record the waveform data of the disturbance signal within a target time period, and the target time period represents the period from a preset time before a fault occurrence time node to the preset time after the fault occurrence time node; the fault recording is input into the fault diagnosis model to obtain the fault type output by the fault diagnosis model; the fault type and the position of the measurement point where the fault recording is collected are sent to the target object.

[0061] In an exemplary embodiment, the above-mentioned device is also used to train the fault diagnosis model in the following manner, including: obtaining historical fault records of the submarine cable, wherein the historical fault records include historical fault recordings and historical fault types; training the initial model with the historical fault recordings as input samples and the historical fault types as output samples to obtain a trained model; testing the trained model, and when it is determined that the test accuracy of the trained model is greater than a preset accuracy, determining the trained model as the fault diagnosis model.

[0062] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0063] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0064] S1, collecting disturbance signals of submarine cables to obtain disturbance signal data of the submarine cables;

[0065] S2, performing feature extraction on the disturbance signal data to obtain a feature extraction result;

[0066] S3, performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable;

[0067] S4: When it is determined that the fault detection result indicates that a fault exists, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable.

[0068] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0069] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0070] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0071] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0072] S1, collecting disturbance signals of submarine cables to obtain disturbance signal data of the submarine cables;

[0073] S2, performing feature extraction on the disturbance signal data to obtain a feature extraction result;

[0074] S3, performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable;

[0075] S4: When it is determined that the fault detection result indicates that a fault exists, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable.

[0076] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0077] An embodiment of the present application further provides a computer program product, comprising a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program product, and when the computer program is executed by a processor, the steps of the method described in each embodiment of the present application are implemented.

[0078] Optionally, in this embodiment, the above computer program may be configured to implement the following steps when executed by a processor:

[0079] S1, collecting disturbance signals of submarine cables to obtain disturbance signal data of the submarine cables;

[0080] S2, performing feature extraction on the disturbance signal data to obtain a feature extraction result;

[0081] S3, performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable;

[0082] S4: When it is determined that the fault detection result indicates that a fault exists, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable.

[0083] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0084] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0085] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for detecting faults in a submarine cable, characterized in that: include: Collecting disturbance signals of submarine cables to obtain disturbance signal data of the submarine cables; Performing feature extraction on the disturbance signal data to obtain a feature extraction result; Performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable; When it is determined that the fault detection result indicates that a fault exists, a fault diagnosis model is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable.

2. The method according to claim 1, characterized in that The submarine cable includes an optical fiber, and the disturbance signal of the submarine cable is collected to obtain the disturbance signal data of the submarine cable, including: Determining signal acquisition parameters for acquiring the disturbance signal, wherein the signal acquisition parameters at least include a sampling frequency; Pulse light is injected into the optical fiber, and signals are collected at the measuring points of the submarine cable according to the sampling frequency to obtain the disturbance signal data.

3. The method according to claim 1, characterized in that Performing feature extraction on the disturbance signal data to obtain feature extraction results includes: Extracting time domain features of the disturbance signal data, wherein the time domain features include disturbance amplitude, kurtosis and skewness; Extracting frequency domain features of the disturbance signal data, wherein the frequency domain features include vibration frequency distribution; Extracting time-frequency domain features of the disturbance signal data, wherein the time-frequency domain features include energy distribution; The time domain feature, the frequency domain feature and the time-frequency domain feature are determined as the feature extraction result.

4. The method according to claim 1, characterized in that: Performing fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable includes: For multiple feature values ​​in the feature extraction result, determining whether the multiple feature values ​​all belong to a preset feature value range; In the case where it is determined that the multiple characteristic values ​​all belong to the preset characteristic value range, determining that there is no fault in the submarine cable; When it is determined that there is a characteristic value that does not belong to the preset characteristic value range among the multiple characteristic values, it is determined that there is a fault in the submarine cable.

5. The method according to claim 1, characterized in that When it is determined that the fault detection result is that a fault exists, using a fault diagnosis model to determine the fault type of the submarine cable based on the fault recording of the submarine cable includes: Obtaining a fault recording of the submarine cable, wherein the fault recording is used to record waveform data of a disturbance signal within a target time period, and the target time period represents a preset time from a preset time before a fault occurrence time node to a preset time after the fault occurrence time node; Inputting the fault recording into the fault diagnosis model to obtain the fault type output by the fault diagnosis model; The fault type and the location of the measurement point where the fault recording is collected are sent to a target object.

6. The method according to claim 1, characterized in that The fault diagnosis model is obtained by training in the following manner, including: Acquire the historical fault records of the submarine cable, wherein the historical fault records include historical fault recordings and historical fault types; The historical fault recording is used as an input sample and the historical fault type is used as an output sample to train the initial model to obtain a trained model; The trained model is tested, and when it is determined that the test accuracy of the trained model is greater than a preset accuracy, the trained model is determined as the fault diagnosis model.

7. A submarine cable fault detection device, characterized in that: include: A signal acquisition module, used to collect disturbance signals of the submarine cable to obtain disturbance signal data of the submarine cable; A feature extraction module is used to extract features from the disturbance signal data to obtain feature extraction results; A fault detection module, used to perform fault detection on the submarine cable according to the feature extraction result to obtain a fault detection result of the submarine cable; The fault diagnosis module is used to determine the fault type of the submarine cable based on the fault recording of the submarine cable using a fault diagnosis model when it is determined that the fault detection result is a fault.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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