DC arcing detection methods, devices, and photovoltaic inverters

Abstract

This application relates to the field of arc detection technology, providing a method, apparatus, and photovoltaic inverter for detecting DC arcing. The method includes: acquiring multiple current sampling data from the device under test; splitting the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands; determining the effective frequency band based on the amplitude of the spectrum of each frequency band; when the variance and rate of change of the multiple current sampling data exceed a preset threshold, increasing the amplitude of the spectrum of the effective frequency band by a preset negative gain to obtain the adjusted spectrum of the effective frequency band; determining the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band; and determining whether DC arcing has occurred in the device under test based on the arcing characteristic value. This application can accurately identify special scenarios of sudden current changes, thereby reducing the amplitude of the spectrum of the effective frequency band, and then accurately determining whether DC arcing has occurred based on the amplitude of the spectrum of the adjusted effective frequency band, reducing false arcing alarms and improving equipment safety.

Description

Technical Field

[0001] This application relates to the field of arc detection technology, specifically to a method, apparatus, and photovoltaic inverter for detecting DC arcing. Background Technology

[0002] DC arcing is a continuous spark generated when current breaks down the air at a circuit break. Sustained DC arcing can cause the contact materials to overheat, potentially leading to a fire. Therefore, timely inspection of relevant equipment, such as photovoltaic inverters, for DC arcing is crucial for equipment safety.

[0003] In related technologies, when detecting whether a photovoltaic inverter is generating DC arcing, in some special scenarios, such as sudden load increases or decreases, sudden large-area shading of photovoltaic panels, or small-power grid connection causing sudden current changes, it is not possible to accurately detect whether the photovoltaic inverter is generating DC arcing, thus leading to false arcing alarms and affecting equipment safety. Summary of the Invention

[0004] In view of this, the present application provides a method, apparatus and photovoltaic inverter for detecting DC arcing, in order to solve the technical problem in the related art that the photovoltaic inverter cannot accurately detect whether DC arcing occurs in some special scenarios that may cause sudden current changes, thus leading to false arcing alarms and affecting equipment safety.

[0005] In a first aspect, embodiments of this application provide a method for detecting DC arcing, including:

[0006] Acquire multiple current sampling data of the device under test, divide the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band;

[0007] When the variance and rate of change of the multiple current sampling data are greater than a preset threshold, the amplitude of the spectrum of the effective frequency band is increased by a preset negative gain to obtain the spectrum of the effective frequency band after adjustment.

[0008] The arcing characteristic value is determined based on the amplitude of the spectrum of the adjusted effective frequency band;

[0009] Based on the arcing characteristic value, it is determined whether the device under test has experienced DC arcing.

[0010] In one possible implementation of the first aspect, the step of splitting the spectrum corresponding to the plurality of current sampling data into frequency bands to obtain the spectrum of multiple frequency bands includes:

[0011] Perform a Fourier transform on the multiple current sampling data to obtain the corresponding spectrum;

[0012] Using the switching frequency of the device under test and its multiples as splitting nodes, the spectrum is divided into frequency bands to obtain a spectrum of multiple frequency bands.

[0013] In one possible implementation of the first aspect, performing a Fourier transform on the plurality of current sampling data to obtain the corresponding spectrum includes:

[0014] The multiple current sampling data are subjected to mean removal and Hanning window processing;

[0015] Perform a Fourier transform on the processed multiple current sampling data to obtain the corresponding spectrum.

[0016] In one possible implementation of the first aspect, determining the effective frequency band based on the amplitude of the spectrum of each frequency band includes:

[0017] For each frequency band, calculate the sum of the amplitudes of the spectrum in that frequency band;

[0018] The frequency band with the largest amplitude is taken as the effective frequency band.

[0019] In one possible implementation of the first aspect, determining the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band includes:

[0020] Calculate the magnitude of the amplitude at each frequency point in the spectrum of the adjusted effective frequency band, and filter the magnitude of the amplitude at each frequency point to obtain the magnitude of the amplitude at each frequency point after processing.

[0021] The mean of the amplitude at each frequency point after processing is calculated to obtain the arcing characteristic value.

[0022] In one possible implementation of the first aspect, filtering the magnitude of the amplitude at each frequency point to obtain the processed magnitude of the amplitude at each frequency point includes:

[0023] Calculate the average value and standard deviation of the amplitude at each frequency point;

[0024] The filtering operator is determined based on the sum of the average value and the standard deviation;

[0025] For the magnitude of the amplitude at each frequency point, if the magnitude of the amplitude at that frequency point is greater than the filtering operator, then the magnitude of the amplitude at that frequency point is set to zero; if the magnitude of the amplitude at that frequency point is less than or equal to the filtering operator, then the magnitude of the amplitude at that frequency point is set to remain unchanged.

[0026] The magnitude of the amplitude at each frequency point after processing is obtained.

[0027] In one possible implementation of the first aspect, determining whether the device under test has experienced DC arcing based on the arcing characteristic value includes:

[0028] Update the arc detection count, and update the threshold count when the arc feature value is greater than the preset arc threshold;

[0029] When the updated threshold count is equal to the first threshold and the updated arc detection count is less than or equal to the second threshold, it is determined that the device under test has experienced DC arcing, and the threshold count and the arc detection count are reset to zero; wherein, the first threshold is less than the second threshold;

[0030] When the updated threshold count is less than the first threshold and the updated arc detection count is equal to the second threshold, it is determined that the device under test has not experienced DC arcing, and the threshold count and the arc detection count are cleared to zero.

[0031] In one possible implementation of the first aspect, the preset threshold includes a preset variance threshold and a preset transformation rate threshold;

[0032] The method further includes:

[0033] Determine whether the variance of the plurality of current sampling data is greater than the preset variance threshold, and determine whether the rate of change of the plurality of current sampling data is greater than the preset conversion rate threshold.

[0034] Secondly, embodiments of this application provide a DC arc detection device, comprising:

[0035] The acquisition module is used to acquire multiple current sampling data of the device under test, split the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band.

[0036] The judgment module is used to increase the amplitude of the spectrum of the effective frequency band by a preset negative gain when the variance and rate of change of the multiple current sampling data are greater than a preset threshold, so as to obtain the spectrum of the effective frequency band after adjustment.

[0037] The calculation module is used to determine the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band;

[0038] The determination module is used to determine whether the device under test has experienced DC arcing based on the arcing characteristic value.

[0039] Thirdly, embodiments of this application provide a photovoltaic inverter, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the DC arcing detection method as described in any of the first aspects.

[0040] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the DC arc detection method as described in any of the first aspects.

[0041] Fifthly, embodiments of this application provide a computer program product that, when running on a photovoltaic inverter, causes the photovoltaic inverter to execute the DC arcing detection method described in any one of the first aspects.

[0042] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0043] The DC arcing detection method, apparatus, and photovoltaic inverter provided in this application split the spectrum of current sampling data into frequency bands. Based on the spectral amplitude of each frequency band, an effective frequency band that can effectively characterize arcing characteristics is determined. The variance and rate of change of the current sampling data are then judged to determine whether the current scenario is a special scenario causing a sudden current change. When the variance and rate of change of the current sampling data exceed the threshold, a preset negative gain is added to the spectral amplitude of the effective frequency band to reduce the increase in spectral amplitude caused by the sudden current change, thus reducing false alarms. Then, based on the adjusted spectral amplitude of the effective frequency band, an arcing characteristic value that can characterize the arcing characteristics is determined, and based on the aforementioned arcing characteristic value, it is determined whether the device under test has experienced DC arcing. This application can accurately determine special scenarios of sudden current changes, thereby reducing the spectral amplitude of the effective frequency band, and then accurately determining whether DC arcing has occurred based on the adjusted spectral amplitude of the effective frequency band, reducing false arcing alarms and improving equipment safety.

[0044] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1This is a schematic flowchart of a DC arc detection method provided in an embodiment of this application;

[0047] Figure 2 This is a flowchart illustrating a DC arc detection method provided in another embodiment of this application;

[0048] Figure 3 This is a schematic diagram of the structure of a DC arc detection device provided in an embodiment of this application;

[0049] Figure 4 This is a schematic diagram of the structure of a photovoltaic inverter provided in one embodiment of this application. Detailed Implementation

[0050] The present application will be described more clearly below with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the function of the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0051] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0052] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0053] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0054] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0055] Furthermore, the term "multiple" mentioned in the embodiments of this application should be interpreted as two or more.

[0056] In related technologies, when detecting whether a photovoltaic inverter is generating DC arcing, in some special scenarios, such as sudden load increases or decreases, sudden large-area shading of photovoltaic panels, or small-power grid connection causing sudden current changes, it is not possible to accurately detect whether the photovoltaic inverter is generating DC arcing, thus leading to false arcing alarms and affecting equipment safety.

[0057] Based on the above problems, the inventors discovered that the variance and rate of change of the current sampling data can be used to determine whether the current scenario is a special scenario that causes sudden current changes. In the case of sudden current changes, the spectral amplitude of the effective frequency band can be reduced to reduce the increase in spectral amplitude caused by the sudden current changes. Subsequently, the amplitude of the adjusted effective frequency band can be used to accurately determine whether DC arcing has occurred, thereby reducing false arcing alarms and improving equipment safety.

[0058] Figure 1 This is a schematic flowchart of a DC arcing detection method provided in an embodiment of this application. Figure 1 As shown, the method in the embodiments of this application may include:

[0059] Step 101: Obtain multiple current sampling data of the device under test, split the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band.

[0060] For example, in this embodiment, the device to be tested can be a photovoltaic inverter or other photovoltaic power generation equipment to be tested, and a current sampling sensor can be used to collect N consecutive current sampling data at a time, where N is an integer greater than 1.

[0061] In one possible implementation, when this embodiment performs frequency band splitting on the spectrum corresponding to multiple current sampling data to obtain the spectrum of multiple frequency bands, it can perform Fourier transform on the multiple current sampling data to obtain the corresponding spectrum. Then, using the switching frequency and the multiples of the switching frequency of the device under test as the splitting nodes, the above spectrum is split into frequency bands to obtain the spectrum of multiple frequency bands.

[0062] Optionally, this embodiment performs mean removal and Hanning window processing on multiple current sampling data, and then performs Fourier transform on the processed multiple current sampling data to obtain the corresponding spectrum. In the mean removal process, the average value of multiple current sampling data is subtracted from each current sampling data, thereby standardizing the current sampling data and removing its offset. Hanning window processing is applied to the mean-filtered multiple current sampling data to reduce spectral leakage and sidelobe interference, facilitating subsequent Fourier transform and improving the accuracy of spectral analysis. Finally, a Fourier transform, such as a Fast Fourier Transform (FFT), is performed on the processed multiple current sampling data to obtain the corresponding spectrum.

[0063] The inventors discovered that DC arcing is similar to white noise, with its energy distributed almost evenly across the frequency spectrum. Specifically, this manifests as an increase in the spectral amplitude across different frequency bands, with some bands showing a more pronounced increase. Therefore, to improve the accuracy of subsequent DC arcing detection, it is necessary to determine effective frequency bands that can effectively characterize arcing features. Furthermore, since photovoltaic inverters and similar devices generate noise at their switching frequency and its harmonics, these frequencies must also be considered.

[0064] For example, in this embodiment, in order to reduce the impact of noise at the switching frequency and its harmonics on the spectrum, the spectrum is divided into frequency bands using the switching frequency fs of the device under test and the harmonics m*fs of the switching frequency as splitting nodes (where m is an integer greater than 1), to obtain the spectrum of the frequency bands 0~fs, fs~2*fs, ..., (m-1)*fs~m*fs.

[0065] In one possible implementation, when determining the effective frequency band, this embodiment can calculate the sum of the amplitudes of the spectrum of each frequency band and take the frequency band with the largest sum of amplitudes as the effective frequency band.

[0066] As mentioned above, the amplitude of DC arcing increases significantly in some frequency bands. Therefore, in this embodiment, the amplitude of the spectrum in each frequency band is calculated, and the frequency band with the largest amplitude sum is taken as the effective frequency band. The determined effective frequency band can effectively characterize the arcing characteristics.

[0067] Step 102: When the variance and rate of change of multiple current sampling data exceed a preset threshold, increase the amplitude of the effective frequency band spectrum by a preset negative gain to obtain the adjusted effective frequency band spectrum.

[0068] For example, in this embodiment, the preset thresholds include a preset variance threshold and a preset conversion rate threshold. The variance and conversion rate of N current sampling data are calculated. It is determined whether the variance of the N current sampling data is greater than the preset variance threshold, and whether the conversion rate of the N current sampling data is greater than the preset conversion rate threshold. When the variance is greater than the preset variance threshold and the conversion rate is greater than the preset conversion rate threshold, the current scenario is considered a special scenario causing a sudden current change. To reduce the interference of the increased spectral amplitude caused by the sudden current change on DC arc detection and reduce false alarms, a preset negative gain is added to the spectral amplitude of the effective frequency band, i.e., the spectral amplitude of the effective frequency band is reduced, thereby obtaining the adjusted spectrum of the effective frequency band for subsequent DC arc detection. The preset negative gain can be set based on a large number of experiments.

[0069] Optionally, the expression for the rate of change is:

[0070]

[0071] In the formula, R is the rate of change, N is the number of current sampling data, and x max x is the maximum value among N current sampling data. min It is the minimum value among N current sampling data.

[0072] Step 103: Determine the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band.

[0073] Step 104: Based on the arcing characteristic value, determine whether the device under test has experienced DC arcing.

[0074] For example, in this embodiment, the average amplitude of the spectrum of the adjusted effective frequency band, or the sum of the amplitudes of the spectrum of the adjusted effective frequency band, can be used as the arcing characteristic value. Subsequently, the arcing characteristic value can be used to determine whether the device under test has experienced DC arcing. For instance, if the arcing characteristic value is greater than a preset arcing characteristic value, it is determined that the device under test has experienced DC arcing. The preset arcing characteristic value can be set based on the arcing characteristic value when the device experiences DC arcing.

[0075] The DC arcing detection method provided in this application involves splitting the spectrum of current sampling data into frequency bands. Based on the spectral amplitude of each frequency band, an effective frequency band that can effectively characterize arcing characteristics is determined. The variance and rate of change of the current sampling data are used to determine whether the current scenario is a special scenario causing a sudden current change. In scenarios with sudden current changes, a preset negative gain is added to the spectral amplitude of the effective frequency band to reduce the increase in spectral amplitude caused by the sudden current change, thereby reducing false alarms. Then, based on the adjusted spectral amplitude of the effective frequency band, an arcing characteristic value that can characterize arcing characteristics is determined, and based on the aforementioned arcing characteristic value, it is determined whether the device under test has experienced DC arcing. This application can accurately identify special scenarios of sudden current changes, thereby reducing the spectral amplitude of the effective frequency band, and then accurately determining whether DC arcing has occurred based on the adjusted spectral amplitude of the effective frequency band, reducing false arcing alarms and improving device safety.

[0076] In this embodiment, in order to further determine the arcing feature value that can effectively characterize the arcing feature and improve the accuracy of DC arcing detection, the amplitude of the spectrum of the effective frequency band can also be filtered to determine the arcing feature value, and the number of times the arcing feature value is greater than the preset arcing threshold can be used to determine whether DC arcing has occurred.

[0077] Figure 2 This is a flowchart illustrating a DC arcing detection method according to another embodiment of this application. Figure 2 As shown, the method in the embodiments of this application may include:

[0078] Step 201: Obtain multiple current sampling data of the device under test, split the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band.

[0079] Step 202: When the variance and rate of change of multiple current sampling data are greater than a preset threshold, the amplitude of the effective frequency band spectrum is increased by a preset negative gain to obtain the adjusted effective frequency band spectrum.

[0080] The specific implementation process and principle of steps 201 to 202 in this embodiment can be referred to the relevant description in the foregoing embodiments, and will not be repeated here.

[0081] Step 203: Calculate the magnitude of the amplitude at each frequency point in the spectrum of the adjusted effective frequency band, and filter the magnitude of the amplitude at each frequency point to obtain the processed magnitude of the amplitude at each frequency point.

[0082] Step 204: Calculate the mean of the amplitude at each frequency point after processing to obtain the arcing characteristic value.

[0083] Steps 203 to 204 above define the process for determining the arc characteristic value.

[0084] In some embodiments, when filtering the magnitude of the amplitude at each frequency point to obtain the processed magnitude of the amplitude at each frequency point, the average value and standard deviation of the magnitude of the amplitude at each frequency point can be calculated, and the filtering operator can be determined based on the sum of the average value and the standard deviation. For the magnitude of the amplitude at each frequency point, if the magnitude of the amplitude at that frequency point is greater than the filtering operator, the magnitude of the amplitude at that frequency point is set to zero; if the magnitude of the amplitude at that frequency point is less than or equal to the filtering operator, the magnitude of the amplitude at that frequency point is set to remain unchanged, thus obtaining the processed magnitude of the amplitude at each frequency point.

[0085] For example, in this embodiment, the spectrum of the adjusted effective frequency band includes multiple frequency points. The magnitude of the amplitude corresponding to each frequency point is calculated, and the filtering operator is determined based on the average value and standard deviation of the magnitudes of the amplitudes corresponding to each frequency point. The expression for the filtering operator W is: W = average value + 3 * standard deviation.

[0086] Subsequently, the magnitude of the amplitude at multiple frequency points of the adjusted effective frequency band is filtered according to the filtering operator and the following filtering formula to filter out the deviation values ​​in the magnitude of the amplitude at each frequency point, that is, to filter out the interference signals in the spectrum of the adjusted effective frequency band and retain only the effective signals, so as to avoid the deviation values ​​from affecting the accuracy of the arcing characteristic values.

[0087] The filtering formula is:

[0088]

[0089] In the formula, Z i Let |[Y]| be the magnitude of the amplitude at the i-th frequency point after processing, where i = 1, 2, ..., k, and k is determined according to the number of frequency points. Amp | i Let W be the magnitude of the amplitude at the i-th frequency point, and W be the filtering operator.

[0090] Optionally, in this embodiment, the average value of the magnitude of the amplitude at each frequency point after processing is calculated as the arcing characteristic value.

[0091] Step 205: Update the number of arc detections, and update the threshold count when the arc feature value is greater than the preset arc threshold.

[0092] Step 206: When the updated threshold count is equal to the first threshold and the updated arc detection count is less than or equal to the second threshold, determine that the device under test has experienced DC arcing, and clear the threshold count and the arc detection count to zero.

[0093] Step 207: When the updated threshold count is less than the first threshold and the updated arc detection count is equal to the second threshold, it is determined that the device under test has not experienced DC arcing, and the threshold count and arc detection count are cleared to zero.

[0094] The first threshold is less than the second threshold. Steps 205 to 207 define the process of determining whether the device under test has experienced DC arcing.

[0095] For example, in this embodiment, after calculating the arcing feature value, the arcing detection count is updated, for example, by incrementing the arcing detection count by 1. The arcing feature value is then compared with a preset arcing threshold. If the arcing feature value is greater than the preset arcing threshold, the threshold count is updated, for example, by incrementing the threshold count by 1. Afterwards, based on the updated threshold count and the updated arcing detection count, it is determined whether a DC arcing has occurred.

[0096] For example, the first threshold can be set to 6, and the second threshold can be set to 10. When the updated threshold count is less than 6 and the updated arc detection count is less than 10, steps 201 to 205 are re-executed. When the updated threshold count is equal to 6 and the updated arc detection count is less than or equal to 10, it indicates that the arc characteristic value is greater than the preset arc threshold in a relatively small number of arc detections. In this case, it can be determined that the device under test has experienced DC arcing, and the threshold count and arc detection count are reset to zero. When the updated threshold count is less than 6 and the updated arc detection count is equal to 10, it indicates that the arc characteristic value is greater than the preset arc threshold in a relatively small number of arc detections. It can be determined that the device under test has not experienced DC arcing, i.e., the device under test is normal. The threshold count and arc detection count are reset to zero, and steps 201 to 205 are re-executed. The determination of whether a DC arcing has occurred is based on the number of times the arcing characteristic value exceeds the preset arcing threshold and the number of arcing detections. This avoids the randomness of judging based solely on a single instance of the arcing characteristic value exceeding the preset arcing threshold, thereby improving the accuracy of DC arcing detection and reducing false alarms.

[0097] In this embodiment, the amplitude of the spectrum of the effective frequency band is filtered to remove deviations in the magnitude of the amplitude at each frequency point, so as to avoid the deviations affecting the accuracy of the arcing characteristic value. Furthermore, the accuracy of DC arcing detection can be improved and false alarms can be reduced by judging whether DC arcing has occurred based on the number of times the arcing characteristic value is greater than the preset arcing threshold and the number of arcing detections.

[0098] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0099] Figure 3 This is a schematic diagram of the structure of a DC arcing detection device provided in one embodiment of this application. Figure 3As shown, the DC arc detection device provided in this embodiment may include: an acquisition module 301, a judgment module 302, a calculation module 303, and a determination module 304.

[0100] The acquisition module 301 is used to acquire multiple current sampling data of the device under test, split the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band.

[0101] The judgment module 302 is used to increase the amplitude of the spectrum of the effective frequency band by a preset negative gain when the variance and rate of change of multiple current sampling data are greater than a preset threshold, so as to obtain the spectrum of the effective frequency band after adjustment.

[0102] The calculation module 303 is used to determine the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band.

[0103] The determination module 304 is used to determine whether the device under test has experienced DC arcing based on the arcing characteristic value.

[0104] Optionally, module 301 is specifically used for:

[0105] Perform a Fourier transform on the multiple current sampling data to obtain the corresponding spectrum;

[0106] Using the switching frequency of the device under test and its multiples as splitting nodes, the spectrum is divided into frequency bands to obtain a spectrum of multiple frequency bands.

[0107] Optionally, module 301 is specifically used for:

[0108] The multiple current sampling data are subjected to mean removal and Hanning window processing;

[0109] Perform a Fourier transform on the processed multiple current sampling data to obtain the corresponding spectrum.

[0110] Optionally, module 301 is specifically used for:

[0111] For each frequency band, calculate the sum of the amplitudes of the spectrum in that frequency band;

[0112] The frequency band with the largest amplitude is taken as the effective frequency band.

[0113] Optionally, the calculation module 303 is specifically used for:

[0114] Calculate the magnitude of the amplitude at each frequency point in the spectrum of the adjusted effective frequency band, and filter the magnitude of the amplitude at each frequency point to obtain the magnitude of the amplitude at each frequency point after processing.

[0115] The mean of the amplitude at each frequency point after processing is calculated to obtain the arcing characteristic value.

[0116] Optionally, the calculation module 303 is specifically used for:

[0117] Calculate the average value and standard deviation of the amplitude at each frequency point;

[0118] The filtering operator is determined based on the sum of the average value and the standard deviation;

[0119] For the magnitude of the amplitude at each frequency point, if the magnitude of the amplitude at that frequency point is greater than the filtering operator, then the magnitude of the amplitude at that frequency point is set to zero; if the magnitude of the amplitude at that frequency point is less than or equal to the filtering operator, then the magnitude of the amplitude at that frequency point is set to remain unchanged.

[0120] The magnitude of the amplitude at each frequency point after processing is obtained.

[0121] Optionally, module 304 is specifically used for:

[0122] Update the arc detection count, and update the threshold count when the arc feature value is greater than the preset arc threshold;

[0123] When the updated threshold count is equal to the first threshold and the updated arc detection count is less than or equal to the second threshold, it is determined that the device under test has experienced DC arcing, and the threshold count and the arc detection count are reset to zero; wherein, the first threshold is less than the second threshold;

[0124] When the updated threshold count is less than the first threshold and the updated arc detection count is equal to the second threshold, it is determined that the device under test has not experienced DC arcing, and the threshold count and the arc detection count are cleared to zero.

[0125] Optionally, the preset threshold includes a preset variance threshold and a preset transformation rate threshold; the judgment module 302 is further configured to:

[0126] Determine whether the variance of the plurality of current sampling data is greater than the preset variance threshold, and determine whether the rate of change of the plurality of current sampling data is greater than the preset conversion rate threshold.

[0127] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0128] Figure 4 This is a schematic diagram of the structure of a photovoltaic inverter provided in one embodiment of this application. Figure 4As shown, the photovoltaic inverter 400 of this embodiment includes a processor 410 and a memory 420, wherein the memory 420 stores a computer program 421 that can run on the processor 410. When the processor 410 executes the computer program 421, it implements the steps in any of the above method embodiments, for example... Figure 1 Steps 101 to 104 are shown. Alternatively, when processor 410 executes computer program 421, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of modules 301 to 304 are shown.

[0129] For example, computer program 421 may be divided into one or more modules / units, one or more of which are stored in memory 420 and executed by processor 410 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of computer program 421 in photovoltaic inverter 400.

[0130] Those skilled in the art will understand that Figure 4 This is merely an example of a photovoltaic inverter and does not constitute a limitation on photovoltaic inverters. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0131] The processor 410 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0132] The memory 420 can be an internal storage unit of the photovoltaic inverter, such as the hard drive or memory of the photovoltaic inverter, or an external storage device of the photovoltaic inverter, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc. The memory 420 can also include both internal and external storage units of the photovoltaic inverter. The memory 420 is used to store computer programs and other programs and data required by the photovoltaic inverter. The memory 420 can also be used to temporarily store data that has been output or will be output.

[0133] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0134] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0135] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0136] In the embodiments provided by this invention, it should be understood that the disclosed device / photovoltaic inverter and method can be implemented in other ways. For example, the device / photovoltaic inverter embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0137] The units described as separate components may or may not be physically separate. 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0138] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0140] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for detecting DC arcing, characterized in that, include: Acquire multiple current sampling data of the device under test, divide the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band; When the variance and rate of change of the multiple current sampling data are greater than a preset threshold, the amplitude of the spectrum of the effective frequency band is increased by a preset negative gain to obtain the spectrum of the effective frequency band after adjustment. The arcing characteristic value is determined based on the amplitude of the spectrum of the adjusted effective frequency band; Based on the arcing characteristic value, determine whether the device under test has experienced DC arcing; The step of determining the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band includes: Calculate the magnitude of the amplitude at each frequency point in the spectrum of the adjusted effective frequency band, and filter the magnitude of the amplitude at each frequency point to obtain the magnitude of the amplitude at each frequency point after processing. The mean of the amplitude at each frequency point after processing is calculated to obtain the arcing characteristic value.

2. The method for detecting DC arcing according to claim 1, characterized in that, The step of splitting the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands includes: Perform a Fourier transform on the multiple current sampling data to obtain the corresponding spectrum; Using the switching frequency of the device under test and its multiples as splitting nodes, the spectrum is divided into frequency bands to obtain a spectrum of multiple frequency bands.

3. The method for detecting DC arcing according to claim 2, characterized in that, The step of performing a Fourier transform on the multiple current sampling data to obtain the corresponding spectrum includes: The multiple current sampling data are subjected to mean removal and Hanning window processing; Perform a Fourier transform on the processed multiple current sampling data to obtain the corresponding spectrum.

4. The method for detecting DC arcing according to claim 1, characterized in that, The determination of effective frequency bands based on the amplitude of the spectrum of each frequency band includes: For each frequency band, calculate the sum of the amplitudes of the spectrum in that frequency band; The frequency band with the largest amplitude is taken as the effective frequency band.

5. The method for detecting DC arcing according to claim 1, characterized in that, The step of filtering the magnitude of the amplitude at each frequency point to obtain the processed magnitude of the amplitude at each frequency point includes: Calculate the average value and standard deviation of the amplitude at each frequency point; The filtering operator is determined based on the sum of the average value and the standard deviation; For the magnitude of the amplitude at each frequency point, if the magnitude of the amplitude at that frequency point is greater than the filtering operator, then the magnitude of the amplitude at that frequency point is set to zero; if the magnitude of the amplitude at that frequency point is less than or equal to the filtering operator, then the magnitude of the amplitude at that frequency point is set to remain unchanged. The magnitude of the amplitude at each frequency point after processing is obtained.

6. The method for detecting DC arcing according to claim 1, characterized in that, The step of determining whether the device under test has experienced DC arcing based on the arcing characteristic value includes: Update the arc detection count, and update the threshold count when the arc feature value is greater than the preset arc threshold; When the updated threshold count is equal to the first threshold and the updated arc detection count is less than or equal to the second threshold, it is determined that the device under test has experienced DC arcing, and the threshold count and the arc detection count are reset to zero; wherein, the first threshold is less than the second threshold; When the updated threshold count is less than the first threshold and the updated arc detection count is equal to the second threshold, it is determined that the device under test has not experienced DC arcing, and the threshold count and the arc detection count are cleared to zero.

7. The method for detecting DC arcing according to any one of claims 1 to 6, characterized in that, The preset thresholds include a preset variance threshold and a preset transformation rate threshold; The method further includes: Determine whether the variance of the plurality of current sampling data is greater than the preset variance threshold, and determine whether the rate of change of the plurality of current sampling data is greater than the preset conversion rate threshold.

8. A DC arc detection device, characterized in that, include: The acquisition module is used to acquire multiple current sampling data of the device under test, split the spectrum corresponding to the multiple current sampling data into frequency bands to obtain the spectrum of multiple frequency bands, and determine the effective frequency band based on the amplitude of the spectrum of each frequency band. The judgment module is used to increase the amplitude of the spectrum of the effective frequency band by a preset negative gain when the variance and rate of change of the multiple current sampling data are greater than a preset threshold, so as to obtain the spectrum of the effective frequency band after adjustment. The calculation module is used to determine the arcing characteristic value based on the amplitude of the spectrum of the adjusted effective frequency band; The determination module is used to determine whether the device under test has experienced DC arcing based on the arcing characteristic value; The calculation module is further used to calculate the magnitude of the amplitude at each frequency point in the spectrum of the adjusted effective frequency band, and to filter the magnitude of the amplitude at each frequency point to obtain the magnitude of the amplitude at each frequency point after processing. The mean of the amplitude at each frequency point after processing is calculated to obtain the arcing characteristic value.

9. A photovoltaic inverter, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the DC arc detection method as described in any one of claims 1 to 7.

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