A method, system, and related device for monitoring the main cable of a flexible photovoltaic power station.

Abstract

This application discloses a method, system, and related devices for monitoring the main cable of a flexible photovoltaic power station, relating to the field of photovoltaic power generation. A sensing optical fiber is fixed along the main cable. The method includes: collecting the scattered echo signal from the sensing optical fiber over a period of time; the scattered echo signal is the optical signal scattered and transmitted back within the sensing optical fiber after an optical pulse signal is emitted; obtaining the vibration frequency data of the main cable based on the frequency change of the Rayleigh scattering signal in the scattered echo signal; obtaining the strain force data and temperature data of the main cable based on the frequency shift of the Brillouin scattering signal in the scattered echo signal; and inputting the vibration frequency data, strain force data, temperature data, inherent parameters of the main cable, and environmental parameters at the same time into a preset classification model for classification, obtaining the event category result of the main cable output by the preset classification model. This application uses a sensing optical fiber for main cable monitoring and introduces environmental parameters to cope with environmental interference, effectively improving the monitoring effect of the main cable.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power generation technology, and in particular to a method, system and related device for monitoring the main cable of a flexible photovoltaic power station. Background Technology

[0002] In flexible photovoltaic power plants, the main cable is the core load-bearing structure supporting the photovoltaic panels. Because the main cable is exposed to the outdoor environment for a long time, it is susceptible to wind load (a pressure or suction force generated on the surface of a building or engineering structure when wind encounters it), temperature changes, mechanical fatigue, etc., which can lead to damage or breakage of the main cable and thus affect the safety of the flexible photovoltaic power plant.

[0003] Therefore, staff need to monitor the main cable to detect potential hazards in advance and reduce risks. However, current main cable monitoring methods primarily rely on point sensors. Since point sensors can only monitor localized areas and cannot cover the entire length of the main cable, the monitoring effect is unsatisfactory. Summary of the Invention

[0004] In view of the above problems, this application provides a method, system, and related devices for monitoring the main cable of a flexible photovoltaic power station, so as to improve the monitoring effect of the main cable in complex environments. The specific solution is as follows:

[0005] The first aspect of this application provides a method for monitoring the main cable of a flexible photovoltaic power station, wherein a sensing optical fiber is fixed along the main cable, and the method for monitoring the main cable of the photovoltaic power station includes:

[0006] The scattered echo signal of the sensing fiber is collected over a period of time. The scattered echo signal is the signal transmitted back by the sensing fiber after an optical pulse signal is emitted to the sensing fiber.

[0007] The vibration frequency data of the main cable is obtained based on the frequency change of the Rayleigh scattered light signal in the scattered echo signal.

[0008] Based on the frequency shift of the Brillouin scattered light signal in the scattered echo signal, the strain and temperature data of the main cable are obtained. The frequency shift of the Brillouin scattering of the scattered echo signal has a linear relationship with both the temperature and the strain of the main cable.

[0009] The vibration frequency data, strain force data, temperature data, inherent parameters of the main cable, and environmental parameters at the same time are input into a preset classification model for classification, and the event category results of the main cable output by the preset classification model are obtained.

[0010] In one possible implementation, multiple measuring points are provided on the main cable, and the acquisition of the scattered echo signal of the sensing fiber over a period of time includes:

[0011] For each measuring point on the main cable, the scattered echo signal of the sensing fiber is collected over a period of time.

[0012] In one possible implementation, obtaining the vibration frequency data of the main cable based on the frequency variation of the Rayleigh scattered light signal in the scattered echo signal includes:

[0013] The polarization vibration energy difference of the Rayleigh scattered light signal in the scattered echo signal is demodulated to obtain the vibration frequency data of the main cable.

[0014] In one possible implementation, the process of obtaining the preset classification model includes:

[0015] The three-dimensional data of the main cable, the inherent parameters of the main cable, and the environmental parameters of the main cable are collected. The three-dimensional data of the main cable includes the vibration frequency data, strain data, and temperature data of the main cable.

[0016] Multiple sets of training data under different working conditions are acquired. Each set of training data under different working conditions consists of the three-dimensional data of the main cable with different values, the inherent parameters of the main cable, and environmental parameters.

[0017] Obtain labeled training data after event labeling of the training data, and use the labeled training data to train a convolutional neural network classification model to obtain the preset classification model. The types of labels for the labeled training data include: various normal events and various abnormal events.

[0018] A second aspect of this application provides a main cable monitoring system for a flexible photovoltaic power station, wherein a sensing optical fiber is fixed along the main cable, and the main cable monitoring system for the photovoltaic power station includes:

[0019] The acquisition unit is used to acquire the scattered echo signal of the sensing optical fiber over a period of time. The scattered echo signal is the signal transmitted back by the sensing optical fiber after an optical pulse signal is emitted to the sensing optical fiber.

[0020] The first acquisition unit is used to acquire the vibration frequency data of the main cable based on the frequency change of the Rayleigh scattered light signal in the scattered echo signal.

[0021] The second acquisition unit is used to acquire strain and temperature data of the main cable based on the frequency shift of the Brillouin scattering light signal in the scattered echo signal. The frequency shift of the Brillouin scattering of the scattered echo signal has a linear relationship with the temperature and strain of the main cable.

[0022] The classification unit is used to input the vibration frequency data, strain force data, temperature data, inherent parameters of the main cable and environmental parameters at the same time into a preset classification model for classification, and obtain the event category result of the main cable output by the preset classification model.

[0023] In one possible implementation, multiple measuring points are set on the main cable, and the acquisition unit is specifically configured as follows:

[0024] For each measuring point on the main cable, the scattered echo signal of the sensing fiber is collected over a period of time.

[0025] In one possible implementation, the first acquisition unit is specifically configured as follows:

[0026] The polarization vibration energy difference of the Rayleigh scattered light signal in the scattered echo signal is demodulated to obtain the vibration frequency data of the main cable.

[0027] In one possible implementation, the main cable monitoring system of the photovoltaic power station further includes a construction unit for the preset classification model, wherein the construction unit is specifically configured as follows:

[0028] The three-dimensional data of the main cable, the inherent parameters of the main cable, and the environmental parameters of the main cable are collected. The three-dimensional data of the main cable includes the vibration frequency data, strain data, and temperature data of the main cable.

[0029] Multiple sets of training data under different working conditions are acquired. Each set of training data under different working conditions consists of the three-dimensional data of the main cable with different values, the inherent parameters of the main cable, and environmental parameters.

[0030] Obtain labeled training data after event labeling of the training data, and use the labeled training data to train a convolutional neural network classification model to obtain the preset classification model. The types of labels for the labeled training data include: various normal events and various abnormal events.

[0031] A third aspect of this application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0032] The memory is used to store computer programs;

[0033] The processor is used to execute the computer program so that the electronic device can implement the main cable monitoring method of the flexible photovoltaic power station described in the first aspect or any implementation thereof.

[0034] The fourth aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the main cable monitoring method for a photovoltaic power station as described in the first aspect or any implementation thereof.

[0035] Based on the above technical solution, this application provides a method, system, and related device for monitoring the main cable of a flexible photovoltaic power station. This method uses optical fiber sensing to monitor the main cable. By collecting the scattered echo signal transmitted back from the optical pulse signal through the optical fiber, the vibration frequency data, strain force data, and temperature data of the main cable can be analyzed. The vibration frequency data, strain force data, temperature data, inherent parameters, and environmental parameters at the same time are input into a preset classification model for classification, obtaining the event category results of the main cable output by the preset classification model. This method uses optical fiber sensing for main cable monitoring, which can easily cover the entire length of the main cable. Furthermore, during analysis, this method incorporates not only the internal and inherent parameters of the main cable but also environmental parameters, enabling the preset classification model to cope with abnormal main cable parameters under environmental interference and to identify environmental interference events that are not inherent to the main cable itself. This effectively reduces the interference of the outdoor environment on the main cable monitoring. Therefore, this method can effectively improve the monitoring effect of the main cable. Attached Figure Description

[0036] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0037] Figure 1 A schematic diagram illustrating the composition of a distributed optical fiber sensing host provided in an embodiment of this application;

[0038] Figure 2 A flowchart illustrating a main cable monitoring method for a flexible photovoltaic power station provided in this application embodiment;

[0039] Figure 3 A schematic diagram of the main cable monitoring system for a flexible photovoltaic power station provided in this application embodiment;

[0040] Figure 4 This application provides a hardware structure block diagram of an electronic device. Detailed Implementation

[0041] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0042] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0043] The terms "first," "second," etc., used in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of units is not necessarily limited to those units, but may include other units not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0044] With the large-scale construction of flexible photovoltaic power plants, the main cable, as the core load-bearing structure supporting the photovoltaic panels, is exposed to the outdoor environment for extended periods. It is susceptible to factors such as wind loads, temperature changes, and mechanical fatigue, which can lead to abnormal stress, localized damage, or even breakage. Therefore, long-distance, real-time, and high-precision health monitoring of the main cable is necessary to prevent breakage accidents and reduce operation and maintenance costs.

[0045] Traditional main cable monitoring primarily relies on point sensors. However, point sensors have limited monitoring range, requiring a large number of sensors to cover the entire length of the main cable, leading to high monitoring costs. Furthermore, point sensors require polling and protocol conversion before data flows to the platform for diagnostic analysis, resulting in poor real-time performance. Additionally, deploying point sensors alongside the main cable in outdoor environments with complex conditions can negatively impact monitoring effectiveness, potentially causing false alarms.

[0046] To address the aforementioned issues, this application provides a method for monitoring the main cable of a flexible photovoltaic power station. A single sensing optical fiber can easily cover the entire length of the main cable. Furthermore, this method can diagnose the main cable by directly analyzing the optical signal transmitted back from the sensing optical fiber. The pre-defined classification model of this method also considers environmental factors, effectively reducing the impact of environmental factors on the main cable diagnosis. The main cable monitoring method for a photovoltaic power station according to this application will be described in detail below with reference to the accompanying drawings.

[0047] In this embodiment, a sensing fiber is fixed along the main cable. The sensing fiber can refer to a sensing technology carrier that utilizes the physical properties of optical fibers to sense and transmit external signals. When light propagates in the fiber, due to the interaction between the light and the external environment, physical quantities in the environment (such as temperature and pressure) can change the parameters of the light through various optical reactions (such as thermo-optical reactions and elasto-optical reactions). Therefore, by detecting changes in the parameters of light in the sensing fiber, physical quantities such as temperature and pressure can be measured. In this embodiment, the sensing fiber can be a product with a long service life (e.g., more than 25 years), ensuring that the service life of the sensing fiber is consistent with that of the flexible photovoltaic power station. Furthermore, the sensing fiber is generally longer than the main cable; a single distributed optical fiber sensing host can connect to more than 50 kilometers of sensing fiber, allowing one sensing fiber to cover multiple main cables. Regarding the installation of the sensing fiber, this embodiment can tightly fix the sensing fiber to the main cable (e.g., using wide clamps at 1-3 meter intervals or using tape fixation), achieving full-length sensing fiber deployment along the main cable. This ensures the sensing fiber is parallel to the main cable and that its deformation is synchronized with the main cable (the deformation of the main cable and the sensing fiber is consistent or follows a certain pattern), and that their relative displacement is consistent when the main cable swings. Alternatively, in another optional embodiment, the sensing fiber can be wound around the main cable, ensuring it remains stable relative to the cable. Wrapping can refer to winding the sensing fiber around the main cable in a spiral, loop, or specific trajectory.

[0048] Specifically, in order to realize the fiber optic monitoring of the main cable, this embodiment mainly uses a distributed fiber optic sensor, which may include a distributed fiber optic sensor host and a sensing fiber. This embodiment can realize the real-time acquisition and monitoring of signals such as temperature and vibration around the fiber optic cable by using the distributed fiber optic sensor host and sensing fiber, as well as various light scattering principles.

[0049] The distributed fiber optic sensing host can integrate optical components such as: ultra-narrow linewidth light sources, pulsed EDFA (Erbium-Doped Fiber Amplifier), Raman amplifiers, modulators, WDM (Wavelength Division Multiplexing), isolators, DWDM (Dense Wavelength Division Multiplexing), Raman amplifiers, analyzers, and photodetectors. Specifically, for example... Figure 1The schematic diagram of the distributed fiber optic sensing host shown illustrates the following components: an ultra-narrow light source (laser source) can be used to output continuous optical signals; a driver can be used to generate optical pulse signals and drive the modulator; the modulator can be used to modulate the continuous optical signal output by the ultra-narrow light source into an optical pulse signal; a pulsed EDFA (Pulsed Erbium-Doped Fiber Amplifier) ​​can be used to amplify the optical pulse signal; a circulator (3-port optical circulator) can be used for directional transmission of the optical pulse signal; WDM (Wavelength Division Multiplexing) can be used to improve channel capacity when transmitting or receiving optical signals; an isolator can be used for unidirectional transmission of optical signals and to block back-reflected light; DWDM (Dense Wavelength Division Multiplexing) can be used to simultaneously transmit multiple optical signals of different wavelengths in a single sensing fiber; a Raman amplifier can be used to amplify the optical signal; a polarizer can be used to detect the polarization state of the optical signal and convert the polarization state into a quantifiable signal; and a photodetector can be used to convert the weak scattered light signal in the sensing fiber into a quantifiable signal.

[0050] Reference Figure 2 , Figure 2 A flowchart illustrating a main cable monitoring method for a flexible photovoltaic power station provided in this application embodiment is shown below. Figure 2 As shown in the embodiment of this application, a main cable monitoring method for a flexible photovoltaic power station is provided. The method may include steps S10 to S13, which are described in detail below.

[0051] S10. Collect the scattered echo signal of the sensing fiber over a period of time. The scattered echo signal is the signal transmitted back by the sensing fiber after an optical pulse signal is emitted to the sensing fiber.

[0052] The scattered echo signal of the sensing fiber can be: the optical signal that is scattered back by each optical pulse signal after the optical pulse signal is emitted into the sensing fiber.

[0053] The process of a distributed optical fiber sensing host transmitting an optical pulse signal to a sensing optical fiber can be described as follows: an ultra-narrow light source transmits a continuous optical signal, a modulator modulates the continuous optical signal output by the ultra-narrow light source into an optical pulse signal, a pulse EDFA amplifies the optical pulse signal, the optical pulse signal enters from port 1 of the circulator and is output from port 2 to the WDM, and the optical pulse signal is incident on the sensing optical fiber through the WDM.

[0054] The process of transmitting optical pulse signals in the sensing optical fiber and collecting the scattered echo signals transmitted back from the sensing optical fiber by the distributed optical fiber sensing host can be described as follows: the scattered echo signal from the sensing optical fiber enters the WDM, the scattered echo signal enters through port 2 of the circulator through the WDM, the scattered echo signal is output from port 3 of the circulator, the analyzer detects the polarization state of the scattered echo signal after passing through the DWDM, and the photodetector converts the scattered echo signal into an electrical signal to realize digital signal acquisition, which is convenient for subsequent signal processing.

[0055] S11. Obtain the vibration frequency data of the main cable based on the frequency change of the Rayleigh scattered light signal in the scattered echo signal;

[0056] S12. Based on the frequency shift of the Brillouin scattered light signal in the scattered echo signal, obtain the strain and temperature data of the main cable. The frequency shift of the Brillouin scattering of the scattered echo signal has a linear relationship with the temperature and strain of the main cable.

[0057] Steps S11 and S12 may not have a specific execution order. In one optional embodiment, step S11 may be executed first, followed by step S12. In another optional embodiment, step S12 may be executed first, followed by step S11.

[0058] The vibration frequency of the main cable can refer to the vibration frequency generated by the main cable under the influence of external excitation or its own dynamic characteristics. The strain force of the main cable can refer to the interaction force generated by the action of external force on adjacent parts of the main cable. The temperature of the main cable can refer to the temperature value of the main cable under specific environmental or working conditions.

[0059] Rayleigh scattering is an optical phenomenon where light waves are scattered by tiny particles (such as gas molecules or nanoparticles) much smaller than their wavelength. Therefore, when an external vibration wave (such as a sound wave) acts on a sensing optical fiber, the glass lattice inside the fiber can vibrate at the same frequency. This vibration causes Rayleigh scattering of the light pulse signal propagating in the sensing fiber, forming a backward Rayleigh echo carrying vibrational information. Furthermore, the polarization state of this backward Rayleigh echo can vibrate with the vibrational frequency of the glass lattice.

[0060] Because the sensing fiber is tightly fixed to the main cable, this embodiment can demodulate the vibration information of the glass lattice in the sensing fiber by detecting the polarization state or phase change of the Rayleigh scattered light signal in the scattered echo signal transmitted back by the sensing fiber, thereby determining the vibration status of the main cable. Specifically, this embodiment can demodulate the polarization vibration energy difference of the Rayleigh scattered light signal in the scattered echo signal to obtain the vibration frequency data of the main cable. The polarization vibration energy difference refers to the uneven energy distribution caused by the difference in the vibration direction and the interaction with the medium when the light wave is in a specific polarization state.

[0061] Brillouin scattering is an optical phenomenon where light waves, propagating through a medium, interact with acoustic phonons (elastic waves generated by thermal vibration or external excitation), causing a frequency shift in the scattered light. Therefore, when an optical pulse signal propagates in a sensing fiber, photons collide inelasticly with acoustic phonons generated by the thermal motion of fiber material molecules, resulting in a frequency shift in the scattered light. Furthermore, in this embodiment, the frequency shift of the Brillouin scattering of the scattered echo signal is approximately linearly related to the temperature and strain of the main cable within a normal range. For example, as the temperature increases, the thermal expansion of the sensing fiber leads to a decrease in density, a decrease in sound velocity, and a smaller frequency shift; conversely, as the strain increases, material compression leads to an increase in sound velocity and a larger frequency shift.

[0062] Because the sensing fiber is in close contact with the main cable, the temperature and strain of the sensing fiber are highly correlated with those of the main cable. Therefore, in this embodiment, the temperature and strain of the main cable can be determined by detecting the frequency shift of the Brillouin scattered light signal in the scattered echo signal transmitted back from the sensing fiber and the approximately linear relationship between the frequency shift and temperature and strain. Alternatively, in another optional embodiment, the temperature and strain of the main cable can also be determined by the power change of the Brillouin scattered light signal in the scattered echo signal. In both spontaneous and stimulated Brillouin scattering, the power change of the Brillouin scattered light signal also exhibits a linear relationship with the temperature and strain of the main cable. For example, increased temperature enhances molecular vibration, leading to increased scattering efficiency; conversely, increased strain disrupts molecular order, resulting in decreased scattering efficiency.

[0063] When this embodiment obtains the vibration frequency data, strain force data, and temperature data of the main cable at each moment, a multi-dimensional information change trend diagram of the main cable over a period of time can be obtained during visualization, making it easier to observe the change trend of various information of the main cable and provide early warning.

[0064] S13. Input the vibration frequency data, strain data, temperature data, inherent parameters of the main cable and environmental parameters at the same time into the preset classification model for classification, and obtain the event category results of the main cable output by the preset classification model.

[0065] The inherent parameters of the main cable can refer to physical parameters related to the main cable itself, such as length and load-bearing capacity. Environmental parameters can refer to parameters related to the current environment in which the main cable is located, such as weather, latitude and longitude, season, wind speed, and wind direction. The preset classification model is a classification model obtained in this embodiment through training using the vibration frequency data, strain force data, temperature data, inherent parameters of the main cable, and environmental parameters. Alternatively, in another optional embodiment, the inherent parameters of the main cable can be preset as fixed parameters within the preset classification model.

[0066] The event category results output by the preset classification model can refer to the predicted event type and level of the main cable. Event types include strong winds, heavy rain, fatigue, and short wires, while event levels include Level 1, Level 2, and Level 3. Therefore, the event category results output by the preset classification model could be, for example, rain event / Level 4, wind-induced vibration / Level 3, etc. During visualization, a 3D health heat map of the main cable can be generated based on the output of the preset classification model, marking the location of potential hazards, the corresponding identifier for the event type, and the event level (different event levels can correspond to different marker colors). When potential hazards are detected in the main cable, an alarm can be sent to maintenance personnel via PC or mobile terminal.

[0067] This embodiment converts abstract main cable monitoring data into event types and event levels, solving the problems of difficulty in quantifying data related to potential main cable hazards and difficulty in unifying evaluation standards. Furthermore, it displays relevant main cable data in an intuitive visualization manner, making it easier for maintenance personnel to quickly determine the current status of the main cable and the location of potential hazards.

[0068] Furthermore, in this embodiment, multiple measuring points can be set on the main cable. For each measuring point on the main cable, the scattered echo signal of the sensing fiber at that measuring point can be collected over a period of time, and the vibration frequency data, strain data, and temperature data of the main cable at each measuring point can be obtained through the above processing.

[0069] This embodiment uses Optical Time Domain Reflectometry (OTDR) to locate multiple measurement points on the main cable. The principle is as follows: an optical pulse signal is emitted into the sensing fiber of the main cable under test. Scattering occurs within the sensing fiber, resulting in backscattered and forward scattered light. The backscattered light propagates backward to the starting end of the sensing fiber (the injection end of the optical pulse signal). Since each backscattered beam corresponds to a scattering point on the sensing fiber, the distance between the scattering point and the starting end of the sensing fiber can be calculated based on the travel time of the backscattered light. This allows the determination of the location of the scattering point on the sensing fiber, which in turn corresponds to a measurement point on the main cable. The formula for calculating the distance between the scattering point and the starting end of the sensing fiber is as follows:

[0070] ;

[0071] in, It can represent the distance between the location of the scattering point and the starting end of the sensing fiber; It can represent the speed of light in a vacuum; It can represent the total time from the transmission of an optical signal to the receipt of the optical signal (two-way); It can represent the refractive index of the sensing fiber.

[0072] The accuracy of determining the measuring points on the main cable can be related to the frequency at which the host optical switch and detector capture the optical signal to generate the optical pulse signal. In this embodiment, the positioning accuracy of the measuring points is set to 1~2 meters, that is, a measuring point is set every 1~2 meters on the main cable. When deploying the sensing fiber, the sensing fiber range corresponding to the length range of each main cable has been determined, so the continuous measuring points on each main cable can be determined.

[0073] This embodiment can acquire data from multiple measuring points on the main cable using a single sensing fiber, achieving full-length coverage and detection of the main cable. Compared to the deployment cost of a large number of point sensors, the deployment cost of sensing fiber is significantly lower.

[0074] Specifically, the process of obtaining the preset classification model includes steps one through three:

[0075] Step 1: Collect the three-dimensional data, inherent parameters and environmental parameters of the main cable. The three-dimensional data of the main cable includes the vibration frequency data, strain data and temperature data of the main cable.

[0076] Step 2: Obtain multiple sets of training data under different working conditions. Each set of training data consists of the three-dimensional data of the main cable with different values, the inherent parameters of the main cable, and environmental parameters.

[0077] Step 3: Obtain labeled training data after event labeling of the training data, and use the labeled training data to train the convolutional neural network classification model to obtain the preset classification model. The types of labels for the labeled training data include: various normal events and various abnormal events.

[0078] In this context, a normal event refers to a situation where the main cable is in a normal state under the given circumstances. For example, during a strong wind or heavy rain event, the vibration frequency of the main cable may be abnormal compared to normal. However, since the event involves strong winds or heavy rain, the vibration frequency is considered a normal change under the influence of this event and does not indicate a problem with the main cable itself. An abnormal event, on the other hand, refers to a situation where the main cable is in an abnormal state under the given circumstances. For example, in the absence of wind, the vibration frequency of the main cable may be abnormal compared to normal. However, since the event involves no wind, the abnormal vibration frequency is not due to the event itself, but rather to a problem with the cable itself. Therefore, this embodiment considers environmental factors in the annotation of training data, enabling the training model to determine whether the abnormal parameters of the main cable are caused by the environment or by a problem with the main cable itself, effectively reducing the interference of environmental factors on the monitoring of the main cable.

[0079] Since the training data for each set of working conditions consists of the three-dimensional data of the main cable with different values, the inherent parameters of the main cable, and environmental parameters, when annotating the data, we can comprehensively consider the actual situation and experience to determine whether each set of working conditions belongs to a normal event or an abnormal event, and then label the event type. Of course, we can also label the event level. In addition to obtaining sample data of abnormal events by labeling abnormal events for training data, we can also obtain more sample data of abnormal events through simulated abnormal physical injection, simulated abnormal generation, fault library migration labeling, etc.

[0080] This embodiment labels the training data for each working condition based on actual conditions, dividing them into normal events and abnormal events. By converting the abstract main cable monitoring data into events, the adaptability of the training model to actual application scenarios can be effectively improved, its classification accuracy can be increased, and the sample data of abnormal events can be expanded in various ways, which can effectively improve the training model's ability to respond to and identify abnormal events.

[0081] In this embodiment, when collecting training data, vibration frequency data, strain force data, temperature data, inherent parameters of the main cable, and environmental parameters of each measuring point on the main cable can be collected over a period of time. The time-series data of each measuring point can be formed by combining the sampling time interval, and subsequent data annotation can be performed. The vibration frequency data, strain force data, and temperature data of the main cable can be segmented according to the positioning of the main cable.

[0082] During data preprocessing, not only can noise filtering and signal reconstruction be performed on the collected data, but data augmentation can also be applied. For example, noise filtering can separate the vibration signal of the main cable from the mechanical noise of the photovoltaic panel based on envelope analysis, or it can suppress false alarms by comparing and learning noise feature templates such as wind vibration and rain impact. Data augmentation, on the other hand, can generate synthetic data on the fracture and fatigue of the main cable based on the wave equation, or it can synchronize the strain and vibration data of the main cable with the wind speed in the external environment through time-series correlation.

[0083] The training model selected in this embodiment can be a deep learning model, optionally a convolutional neural network classification model, or a Long Short-Term Memory (LSTM) network and its variants. Specifically, the model structure in this embodiment may include: an input layer, a multimodal data fusion layer, an output layer, constraints, etc. During model training, cross-validation can be performed, and fine-tuning of the model can be automatically triggered after labeling false positives and false negatives.

[0084] This application provides a method for monitoring the main cable of a flexible photovoltaic power station. This method uses optical fiber sensing to monitor the main cable. By collecting the scattered echo signal transmitted back from the optical pulse signal through the optical fiber, the vibration frequency, strain, and temperature data of the main cable can be analyzed. The vibration frequency, strain, and temperature data, along with the inherent parameters and environmental parameters at the same time, are input into a preset classification model for classification, obtaining the event category results of the main cable output by the preset classification model. This method uses optical fiber sensing for main cable monitoring, which can easily cover the entire length of the main cable. Furthermore, during analysis, this method incorporates not only the internal and inherent parameters of the main cable but also environmental parameters, enabling the preset classification model to handle abnormal main cable parameters under environmental interference and to identify environmental interference events that are not inherent to the main cable itself. This effectively reduces the interference of the outdoor environment on main cable monitoring, thus significantly improving the monitoring effect of the main cable.

[0085] The above describes a main cable monitoring method for a flexible photovoltaic power station provided by the embodiments of this application. The following will describe a system that applies the above-described main cable monitoring method for a flexible photovoltaic power station.

[0086] Please see Figure 3 , Figure 3 This is a schematic diagram of the main cable monitoring system for a flexible photovoltaic power station, provided as an embodiment of this application. Figure 3 As shown, the main cable monitoring system of this photovoltaic power station has sensing optical fibers fixed along the main cable. The system may include:

[0087] The acquisition unit 100 is used to acquire the scattered echo signal of the sensing fiber over a period of time. The scattered echo signal is the signal transmitted back by the sensing fiber after an optical pulse signal is emitted to the sensing fiber.

[0088] The first acquisition unit 110 is used to acquire the vibration frequency data of the main cable based on the frequency change of the Rayleigh scattered light signal in the scattered echo signal.

[0089] The second acquisition unit 120 is used to acquire strain and temperature data of the main cable based on the frequency shift of the Brillouin scattered light signal in the scattered echo signal. The frequency shift of the Brillouin scattering of the scattered echo signal has a linear relationship with the temperature and strain of the main cable.

[0090] The classification unit 130 is used to input the vibration frequency data, strain data, temperature data, inherent parameters of the main cable and environmental parameters at the same time into the preset classification model for classification, and obtain the event category result of the main cable output by the preset classification model.

[0091] In one possible implementation, multiple measuring points are set on the main cable, and the acquisition unit can be specifically configured as follows:

[0092] For each measuring point on the main cable, the scattered echo signal of the sensing fiber is collected over a period of time.

[0093] In one possible implementation, the first acquisition unit can be specifically configured as follows:

[0094] The polarization vibration energy difference of the Rayleigh scattered light signal in the demodulated scattered echo signal is used to obtain the vibration frequency data of the main cable.

[0095] In one possible implementation, the main cable monitoring system of the photovoltaic power station may also include a construction unit for a pre-defined classification model, the construction unit being specifically configured as follows:

[0096] The process involves collecting three-dimensional data of the main cable, its inherent parameters, and environmental parameters. The three-dimensional data includes vibration frequency data, strain data, and temperature data. Multiple sets of training data under different operating conditions are acquired. Each set of training data consists of three-dimensional data of the main cable, its inherent parameters, and environmental parameters with different values. Annotated training data is obtained after event labeling. This labeled training data is then used to train a convolutional neural network classification model to obtain a preset classification model. The labeled training data includes various types of normal events and various types of abnormal events. This embodiment annotates the training data under each operating condition based on actual conditions, classifying them into normal time and abnormal events. The training model's ability to classify events effectively improves its adaptability to real-world application scenarios and enhances its classification accuracy.

[0097] This application also provides an electronic device in its embodiments. (See reference...) Figure 4 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0098] like Figure 4 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. When the electronic device is powered on, the RAM 403 also stores various programs and data required for the operation of the electronic device. The processing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0099] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, memory cards, hard drives, etc.; and communication devices 409. Communication device 409 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0100] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the main cable monitoring methods for flexible photovoltaic power stations provided in this application.

[0101] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the main cable monitoring methods for flexible photovoltaic power stations provided in this application.

[0102] It should also be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the system embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0104] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0105] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0106] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0107] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0108] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method of monitoring a main cable of a flexible photovoltaic power plant, characterized in that, The sensing optical fiber is fixed along the main cable by wide piece hoop rings at intervals of 1-3 meters or by a rolling belt, the main cable is deformed synchronously with the sensing optical fiber, and the main cable monitoring method of the photovoltaic power station comprises the following steps: Collecting scattering echo signals of the sensing optical fiber within a period of time, the scattering echo signals being signals returned by the sensing optical fiber after the sensing optical fiber emits light pulse signals; Obtaining vibration frequency data of the main cable according to frequency changes of Rayleigh scattering light signals in the scattering echo signals; Obtaining strain force data and temperature data of the main cable according to frequency shifts of Brillouin scattering light signals in the scattering echo signals, the frequency shifts of Brillouin scattering of the scattering echo signals being linearly related to the temperature of the main cable and the strain force of the main cable; Inputting the vibration frequency data, the strain force data, the temperature data, inherent parameters and environmental parameters of the main cable at the same time into a preset classification model for classification to obtain an event type and an event level of the main cable currently located in the preset classification model; The obtaining process of the preset classification model comprises the following steps: Collecting three-dimensional data, inherent parameters and environmental parameters of the main cable, the three-dimensional data of the main cable comprising vibration frequency data, strain force data and temperature data of the main cable; Obtaining a plurality of groups of training data under different working conditions, each group of training data being composed of the three-dimensional data, the inherent parameters and the environmental parameters of the main cable with different values; Obtaining labeled training data after event labeling of the training data, training a convolutional neural network classification model with the labeled training data, and obtaining the preset classification model, the labeled types of the labeled training data comprising various normal events and various abnormal events.

2. The method for monitoring the main cable of a flexible photovoltaic power plant according to claim 1, characterized in that, The main cable is provided with a plurality of measuring points, and the collecting of the scattering echo signals of the sensing optical fiber within a period of time comprises the following steps: For each measuring point on the main cable, the scattering echo signals of the sensing optical fiber within a period of time are collected.

3. The method of monitoring the main cable of a flexible photovoltaic power plant according to claim 1, characterized in that, The obtaining of the vibration frequency data of the main cable according to the frequency changes of Rayleigh scattering light signals in the scattering echo signals comprises the following steps: Demodulating polarization vibration energy differences of Rayleigh scattering light signals in the scattering echo signals to obtain the vibration frequency data of the main cable.

4. A main cable monitoring system for a flexible photovoltaic power plant, characterized in that The sensing optical fiber is fixed along the main cable by wide piece hoop rings at intervals of 1-3 meters or by a rolling belt, the main cable is deformed synchronously with the sensing optical fiber, and the main cable monitoring system of the photovoltaic power station comprises the following steps: A collecting unit is configured to collect scattering echo signals of the sensing optical fiber within a period of time, the scattering echo signals being signals returned by the sensing optical fiber after the sensing optical fiber emits light pulse signals; A first obtaining unit is configured to obtain vibration frequency data of the main cable according to frequency changes of Rayleigh scattering light signals in the scattering echo signals; The second acquisition unit is configured to acquire strain force data and temperature data of the main cable according to a frequency shift of Brillouin scattering light signals in the scattered echo signals, the frequency shift of Brillouin scattering of the scattered echo signals being linearly related to the temperature of the main cable and the strain force of the main cable; The classification unit is configured to input the vibration frequency data, the strain force data, the temperature data, intrinsic parameters and environmental parameters of the main cable at the same time into a preset classification model for classification, to obtain an event type and an event level of the main cable currently in which the main cable is located, which are output by the preset classification model; The main cable monitoring system of the photovoltaic power station further comprises a construction unit of the preset classification model, and the construction unit is specifically configured to: acquire three-dimensional data of the main cable, intrinsic parameters and environmental parameters of the main cable, the three-dimensional data of the main cable comprising vibration frequency data, strain force data and temperature data of the main cable; acquire a plurality of groups of training data under different working conditions, each group of training data being composed of the three-dimensional data of the main cable, the intrinsic parameters and the environmental parameters of the main cable with different values; obtain labeled training data after event labeling of the training data, and train a convolutional neural network classification model by using the labeled training data, to obtain the preset classification model, the types of the labeled training data including various normal events and various abnormal events.

5. A main cable monitoring system for a flexible photovoltaic power plant according to claim 4, characterized in that, The main cable is provided with a plurality of measuring points, and the acquisition unit is specifically configured to: for each measuring point on the main cable, acquire scattered echo signals of the sensing optical fiber within a period of time.

6. The main cable monitoring system of a flexible photovoltaic power plant according to claim 4, characterized in that, The first acquisition unit is specifically configured to: demodulate a polarization vibration energy difference of Rayleigh scattering light signals in the scattered echo signals, to acquire vibration frequency data of the main cable.

7. An electronic device, comprising: The electronic device comprises at least one processor and a memory connected to the processor, wherein: the memory is configured to store a computer program; the processor is configured to execute the computer program, so that the electronic device can implement the main cable monitoring method of the flexible photovoltaic power station according to any one of claims 1 to 3.

8. A computer program product, characterised in that, The computer readable instructions, when executed on an electronic device, enable the electronic device to implement the main cable monitoring method of the flexible photovoltaic power station according to any one of claims 1 to 3.

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