Portable direct current arc detection method for distributed photovoltaic power station and related device

Abstract

The invention discloses a portable direct current arc detection method for a distributed photovoltaic power station and a related device, and the method comprises the steps: obtaining the state information of the distributed photovoltaic power station, and the state information of the distributed photovoltaic power station comprises current information, voltage information, temperature information and electromagnetic induction information; preprocessing the state information of the distributed photovoltaic power station; performing feature extraction on the preprocessed state information of the distributed photovoltaic power station to obtain a multi-dimensional feature vector; according to the method and the related device, the direct current arc of the distributed photovoltaic power station can be accurately detected, the detection cost is low, and the detection efficiency is high.

Description

Technical Field

[0001] This invention belongs to the field of distributed photovoltaic power station technology, and relates to a portable DC arc detection method and related device for distributed photovoltaic power stations. Background Technology

[0002] Against the backdrop of the booming development of distributed photovoltaic power station technology, existing technologies for DC arc detection are becoming increasingly diverse. On the one hand, some traditional detection methods rely on large monitoring equipment fixedly installed at key nodes of the power station. These devices are usually based on complex electrical principles, such as the principle of current surge detection. They use high-precision current sensors to continuously monitor the line current, and once the current fluctuates dramatically and meets the preset arc current change model, an arc is determined to have occurred.

[0003] However, these existing technologies have many drawbacks. First, they are not portable. Fixed monitoring equipment is bulky and heavy, making it difficult to move flexibly in the complex and dispersed layout of distributed photovoltaic power stations to conduct comprehensive inspections. This is especially true for some small photovoltaic arrays located in remote areas with scattered equipment, where maintenance personnel find it inconvenient to carry them and cannot conduct accurate inspections of suspected arc fault points anytime and anywhere.

[0004] Secondly, the detection efficiency is low. Distributed photovoltaic power stations are significantly affected by environmental factors such as changes in sunlight, temperature, and load, as well as internal conditions such as component aging and loose wiring. Traditional detection methods, which rely on single electrical parameter thresholds, are prone to misjudgments or missed detections. For example, when a sudden change in sunlight intensity causes fluctuations in component output power, the current will also change accordingly. Simply relying on this current surge could easily lead to a misjudgment of a DC arc, when there is actually no arc hazard. Conversely, when the initial characteristics of an arc are not obvious and the current change is subtle, it is easy to miss detection, missing the optimal treatment window, increasing safety risks, and failing to meet the needs of efficient operation and maintenance of distributed photovoltaic power stations.

[0005] Furthermore, the installation and maintenance costs of existing technologies are high. Complex fixed monitoring equipment not only incurs substantial upfront purchase costs, but subsequent professional installation, commissioning, and regular calibration and maintenance require significant manpower and resources from specialized technicians. For numerous distributed photovoltaic power stations of varying sizes, especially small private power stations, this represents a heavy economic burden, limiting the widespread application of advanced monitoring technologies and hindering the healthy development of the entire distributed photovoltaic industry. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a portable DC arc detection method and related device for distributed photovoltaic power stations. This method and related device can accurately detect DC arcs in distributed photovoltaic power stations, with low detection cost and high detection efficiency.

[0007] To achieve the above objectives, this invention discloses a portable DC arc detection method for distributed photovoltaic power stations, comprising:

[0008] The status information of the distributed photovoltaic power station is obtained, including current information, voltage information, temperature information, and electromagnetic induction information.

[0009] The status information of the distributed photovoltaic power station is preprocessed;

[0010] Feature extraction is performed on the preprocessed state information of the distributed photovoltaic power station to obtain a multi-dimensional feature vector;

[0011] The operating conditions and electric arc determination of the distributed photovoltaic power station are performed based on the multi-dimensional feature vector.

[0012] A further improvement of the portable DC arc detection method for distributed photovoltaic power stations described in this invention is as follows:

[0013] Furthermore, the process of preprocessing the state information of the distributed photovoltaic power station is as follows:

[0014] The status information of the distributed photovoltaic power station is denoised and compensated.

[0015] Furthermore, the process of preprocessing the state information of the distributed photovoltaic power station is as follows:

[0016] The state information of the distributed photovoltaic power station is processed by removing random noise using the mean filtering method, and then a data calibration algorithm is used for compensation and calibration.

[0017] Furthermore, the multi-dimensional feature vector is Where ΔI / Δt is the rate of change of current, V peak This is the peak voltage. For the temperature gradient, P peak This represents the peak value of the electromagnetic radiation spectrum.

[0018] This invention discloses a portable DC arc detection system for distributed photovoltaic power stations, comprising:

[0019] The acquisition module is used to acquire the status information of the distributed photovoltaic power station, which includes current information, voltage information, temperature information and electromagnetic induction information.

[0020] The preprocessing module is used to preprocess the status information of the distributed photovoltaic power station;

[0021] The feature extraction module is used to extract features from the preprocessed state information of the distributed photovoltaic power station to obtain multi-dimensional feature vectors.

[0022] The identification module is used to identify the operating conditions and determine the electric arc of the distributed photovoltaic power station based on the multi-dimensional feature vector.

[0023] A further improvement of the portable DC arc detection system for distributed photovoltaic power stations described in this invention is as follows:

[0024] Furthermore, the acquisition module includes a current sensor, a voltage probe, a temperature sensor, and an electromagnetic induction antenna. The current sensor is installed at the inverter output terminal and the combiner box input line, and the temperature sensor is installed at the connection terminal inside the combiner box and on the inverter power module.

[0025] Furthermore, the voltage probe is connected to the circuit under test using alligator clips or piercing probes.

[0026] The current sensor is clipped onto the wire.

[0027] Furthermore, the preprocessing module, feature extraction module, and recognition module are integrated into the handheld terminal.

[0028] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the portable DC arc detection method for distributed photovoltaic power stations.

[0029] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the portable DC arc detection method for distributed photovoltaic power stations.

[0030] The present invention has the following beneficial effects:

[0031] The portable DC arc detection method and related device for distributed photovoltaic power stations described in this invention acquires the status information of the distributed photovoltaic power station, including current information, voltage information, temperature information, and electromagnetic induction information. A dimensional feature vector is extracted from this information, and then the operating condition and arc determination of the distributed photovoltaic power station are performed based on the dimensional feature vector. A multi-parameter comprehensive diagnostic approach is adopted to improve the accuracy of the detection. Furthermore, the detection equipment is relatively conventional, has low cost, and high detection efficiency. Attached Figure Description

[0032] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0033] Figure 1 This is a system diagram of the present invention;

[0034] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0037] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0038] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0039] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0040] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0042] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0043] Example 1

[0044] refer to Figure 1 The portable DC arc detection system for distributed photovoltaic power stations described in this invention includes a current sensor, a voltage probe, a temperature sensor, an electromagnetic induction antenna, and a handheld terminal.

[0045] The current sensor selected is a Hall effect miniature current sensor, model LTS25-NP, with a measurement range of 0-25A and an accuracy of ±0.5%, sufficient to cover the common DC current range of distributed photovoltaic power stations. This sensor is based on the Hall effect principle, and its output voltage V... out It has a linear relationship with the measured current I: V out=K×I, where K is the sensitivity coefficient of the sensor. For the LTS25-NP model, K = 0.1V / A. At key current monitoring points such as the inverter output and combiner box input, a non-intrusive installation method is used. The sensor is clipped onto the conductor and connected to the subsequent signal conditioning circuit through a shielded conductor, ensuring that signal transmission is not subject to external electromagnetic interference, with a shielding effectiveness of no less than 60dB.

[0046] The voltage probe selected is the P6015A high-voltage probe, which has a maximum input voltage of 15kV and a bandwidth of 75MHz, enabling accurate measurement of voltage values ​​at different voltage levels within a photovoltaic power station. Based on the voltage divider principle, its output voltage V′ out With the input measured voltage V in The relationship is R1 and R2 are the high-voltage arm and low-voltage arm resistors of the voltage divider, respectively. For the P6015A type, R1 = 900MΩ and R2 = 10MΩ. The voltage probe is connected to the circuit under test using alligator clips or piercing probes, which is convenient and quick and can adapt to different wiring scenarios. After signal conditioning, it is connected to the data acquisition system.

[0047] The temperature sensor selected is the DS18B20 digital temperature sensor, with a measurement accuracy of ±0.5℃ and a temperature range of -55℃ to +125℃. Thermally conductive silicone is used to tightly attach the temperature sensors to heat-prone components such as the connection terminals and inverter power modules within the combiner box. The thermal conductivity of the silicone (k = 3 W / (m·K)) ensures efficient heat transfer. Multiple temperature sensors communicate with the main control chip via a one-wire bus protocol, allowing up to 128 sensors to be connected to a single bus for simultaneous multi-point temperature acquisition and comprehensive monitoring of temperature changes in critical components.

[0048] Based on the frequency characteristics of electromagnetic radiation generated by an electric arc, a loop electromagnetic induction antenna was customized. Through theoretical analysis and experimental optimization, the inductance L and capacitance C parameters of the electromagnetic induction antenna were determined so that its resonant frequency f0 falls within the main frequency band of electric arc electromagnetic radiation, ranging from 10MHz to 100MHz. This was achieved according to the formula... Adjustments were made. The electromagnetic induction antenna uses a high-permeability ferrite core to improve induction sensitivity. It is installed near locations where electric arcs may occur, such as cable joints and connections of aging photovoltaic modules, to capture weak electromagnetic signals. After amplification, filtering, and other preprocessing, the signals are sent to the data acquisition system. The amplification factor is set to 100 times, and a bandpass filter with a center frequency of 50MHz and a bandwidth of 20MHz is used to remove interference from irrelevant frequency bands.

[0049] The handheld terminal uses an STM32F407 microcontroller as its core control and data processing unit, boasting a high clock speed of 168MHz and powerful computing capabilities. It connects to various sensors and signal processing circuits, and includes a built-in 16GB eMMC storage chip for storing historical data, algorithm models, and preset threshold parameters for different operating conditions. Equipped with a Wi-Fi module (ESP8266) and a Bluetooth module (HC-05), the Wi-Fi module supports 802.11b / g / n protocols, and the Bluetooth module conforms to the Bluetooth 4.0 standard, facilitating data transmission with a host computer or cloud platform for remote monitoring and data analysis backup. The handheld terminal's casing is made of high-strength, insulating polycarbonate material, measuring 200mm × 100mm × 50mm and weighing approximately 1kg, combining portability and protection. It features a 5-inch LCD touchscreen with a resolution of 800 × 480 for intuitive display of real-time data, detection results, and historical trends.

[0050] Example 2

[0051] refer to Figure 2 The portable DC arc detection method for distributed photovoltaic power stations described in this invention includes the following steps:

[0052] Temperature, current, voltage, and electromagnetic radiation information are collected using temperature sensors, current sensors, voltage sensors, and electromagnetic radiation sensors.

[0053] The data acquisition program running on the STM32F407 microcontroller utilizes its built-in timer to set the sampling frequency of each sensor. The sampling frequency for the current, voltage, and electromagnetic radiation sensors is set to 10kHz, while the temperature sensor's sampling frequency is set to 1Hz. This ensures that rapidly changing electrical parameters can be captured promptly, while also monitoring slow temperature changes appropriately. Interrupt service routines read data from each sensor in real time and store it in a predefined buffer of 1024 bytes. A circular overwrite method is used; when the buffer is full, new data overwrites old data, ensuring real-time data transmission.

[0054] 2) Preprocess the collected data;

[0055] A denoising algorithm is applied to the collected data. Mean filtering is used to remove random noise introduced by environmental electromagnetic interference, line jitter, etc. Taking current data as an example, the average of five consecutive sampling points is used as the filtered current value at the current moment. Then, a data calibration algorithm is applied to compensate and correct the data collected by each sensor according to preset sensor calibration parameters. For example, for a voltage probe, given its measurement error under different input voltages, linear interpolation is performed by looking up the error table to obtain an accurate voltage value, ensuring data accuracy.

[0056] 3) Perform feature extraction on the processed data to obtain multi-dimensional feature vectors.

[0057] Based on the typical characteristics exhibited by electric arcs across multiple parameters, key features are extracted from the preprocessed data. For example, the rate of change of current ΔI / Δt is calculated using the difference method, i.e., the difference between the current value at the current sampling point and the current value at the previous sampling point is divided by the sampling interval. ΔI / Δt > 10 A / s is used as one of the current abrupt change features. The peak voltage V is also extracted. peak By iterating through the voltage sampling values ​​within a certain time window, the maximum value is found as V. peak ; Calculate the temperature gradient For adjacent temperature sensors, if the temperature difference is greater than 10℃, record the temperature gradient; analyze the peak value P of the electromagnetic radiation spectrum. peak The electromagnetic radiation signal is transformed from the time domain to the frequency domain using the Fast Fourier Transform (FFT), and the maximum value P in the frequency domain is found. peak Construct multi-dimensional feature vectors

[0058] 4) Based on the multi-dimensional feature vector Perform operating condition identification.

[0059] Combining real-time data collected from distributed photovoltaic power plants, such as irradiance (acquired via a BH1750 irradiance sensor, measurement range 0-65535 lx) and module output power (using a power sensor, accuracy ±1%), a condition identification subsystem based on the K-means clustering algorithm is used to determine the current operating condition of the power plant. Historical data is clustered into several operating condition categories according to different irradiance and power ranges, such as high power on sunny days and low power on cloudy days. Each operating condition category corresponds to a set of preset normal parameter variation ranges. When the real-time collected data falls into a certain operating condition category, the current operating condition is determined, providing a basis for subsequent threshold judgments.

[0060] 5) Based on the multi-dimensional feature vector Perform arc detection.

[0061] The extracted feature vectors are compared with pre-stored arc feature threshold models for the corresponding operating conditions. For example, under high-power conditions in sunny weather, the preset current change rate threshold is 15A / s, the peak voltage threshold is 200V, the temperature gradient threshold is 15℃, and the peak electromagnetic radiation spectrum threshold is 5dBm. When the feature vectors simultaneously exceed the thresholds in multiple dimensions and conform to the dynamic evolution law of the arc, a DC arc is determined to have occurred, and an audible and visual alarm is immediately triggered. Detailed fault information is displayed on the handheld terminal screen, including the location of the arc (based on the sensor installation location), abnormal parameter values, etc. At the same time, alarm notifications are pushed to the mobile phones of maintenance personnel or the monitoring center via Wi-Fi or Bluetooth modules. The notification messages are in JSON format and contain key information such as fault type, occurrence time, and location, ensuring accurate and efficient information transmission.

[0062] It should be noted that this invention can reliably detect DC arcs in a highly portable and efficient manner in the actual operating environment of distributed photovoltaic power stations, effectively ensuring the safe and stable operation of the power station and providing strong technical support for the development of the distributed photovoltaic industry.

[0063] Example 3

[0064] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a portable DC arc detection method for a distributed photovoltaic power station. For example, the portable DC arc detection method for a distributed photovoltaic power station includes: acquiring state information of the distributed photovoltaic power station, the state information including current information, voltage information, temperature information, and electromagnetic induction information; preprocessing the state information of the distributed photovoltaic power station; extracting features from the preprocessed state information of the distributed photovoltaic power station to obtain a multi-dimensional feature vector; and identifying the operating condition and determining the arc of the distributed photovoltaic power station based on the multi-dimensional feature vector. The memory may include main memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which may be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store the program; specifically, the program may include program code, and the program code includes computer operation instructions. Memory can include main memory and non-volatile memory, and provides instructions and data to the processor.

[0065] Example 4

[0066] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a portable DC arc detection method for a distributed photovoltaic power station, including: acquiring state information of the distributed photovoltaic power station, the state information including current information, voltage information, temperature information, and electromagnetic induction information; preprocessing the state information of the distributed photovoltaic power station; extracting features from the preprocessed state information of the distributed photovoltaic power station to obtain a multi-dimensional feature vector; and identifying the operating condition and determining the arc of the distributed photovoltaic power station based on the multi-dimensional feature vector. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0067] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0068] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0069] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0070] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0071] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0072] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0073] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A portable DC arc detection method for distributed photovoltaic power stations, characterized in that, include: The status information of the distributed photovoltaic power station is obtained, including current information, voltage information, temperature information, and electromagnetic induction information. The status information of the distributed photovoltaic power station is preprocessed; Feature extraction is performed on the preprocessed state information of the distributed photovoltaic power station to obtain a multi-dimensional feature vector; The operating conditions and electric arc determination of the distributed photovoltaic power station are performed based on the multi-dimensional feature vector.

2. The portable DC arc detection method for distributed photovoltaic power stations according to claim 1, characterized in that, The process of preprocessing the state information of the distributed photovoltaic power station is as follows: The status information of the distributed photovoltaic power station is denoised and compensated.

3. The portable DC arc detection method for distributed photovoltaic power stations according to claim 1, characterized in that, The process of preprocessing the state information of the distributed photovoltaic power station is as follows: The state information of the distributed photovoltaic power station is processed by removing random noise using the mean filtering method, and then a data calibration algorithm is used for compensation and calibration.

4. The portable DC arc detection method for distributed photovoltaic power stations according to claim 1, characterized in that, Multidimensional feature vectors are Where ΔI / Δt is the rate of change of current, V peak Peak voltage For the temperature gradient, P peak This represents the peak value of the electromagnetic radiation spectrum.

5. A portable DC arc detection system for distributed photovoltaic power stations, characterized in that, include: The acquisition module is used to acquire the status information of the distributed photovoltaic power station, which includes current information, voltage information, temperature information and electromagnetic induction information. The preprocessing module is used to preprocess the status information of the distributed photovoltaic power station; The feature extraction module is used to extract features from the preprocessed state information of the distributed photovoltaic power station to obtain multi-dimensional feature vectors. The identification module is used to identify the operating conditions and determine the electric arc of the distributed photovoltaic power station based on the multi-dimensional feature vector.

6. The portable DC arc detection system for distributed photovoltaic power stations according to claim 5, characterized in that, The acquisition module includes a current sensor, a voltage probe, a temperature sensor, and an electromagnetic induction antenna. The current sensor is installed at the inverter output terminal and the combiner box input line, and the temperature sensor is installed at the connection terminal inside the combiner box and on the inverter power module.

7. The portable DC arc detection system for distributed photovoltaic power stations according to claim 5, characterized in that, The voltage probe is connected to the circuit under test using alligator clips or piercing probes. The current sensor is clipped onto the wire.

8. The portable DC arc detection system for distributed photovoltaic power stations according to claim 5, characterized in that, The preprocessing module, feature extraction module, and recognition module are integrated into the handheld terminal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the portable DC arc detection method for distributed photovoltaic power stations as described in any one of claims 1-4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the portable DC arc detection method for distributed photovoltaic power stations as described in any one of claims 1-4.

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