Direct current series arc fault detection method and device based on magnetoelectric coupling sensing

Abstract

The invention discloses a direct current series arc fault detection method and device based on magnetoelectric coupling sensing. The method comprises the steps that a pre-designed magnetoelectric coupling sensor is perpendicular to a current wire of a direct current system to be detected in a non-contact mode to collect current signals, sensor output signals coupled through a coupling sensor are output, and the sensor output signals are high-frequency component waveforms of the current signals; performing spectrum analysis on the sensor output signal to obtain a spectrum of the sensor output signal; calculating an amplitude spectrum change rate of the predetermined characteristic frequency band based on the frequency spectrum; and comparing the amplitude spectrum change rate with a preset threshold value, and judging a DC series arc fault detection result according to a comparison result.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic measurement technology, and more specifically, to a method and apparatus for detecting DC series arc faults based on magnetoelectric coupling sensing. Background Technology

[0002] When a conductor-to-ground arc fault occurs in medium- and low-voltage DC systems such as electric vehicles, DC microgrids, and photovoltaic systems, the DC arc current lacks a zero-crossing point, resulting in a lack of short-circuit characteristic quantities, and the DC arc can be sustained at several amperes. Therefore, in the complex broadband background noise of the DC system, most impedance-based grounding faults are difficult to detect and locate effectively. Prolonged burning of the DC arc can lead to accidents such as fires, seriously threatening the safety of equipment and personnel. However, during the grounding transient process of medium- and low-voltage DC systems, the DC arc fault can generate a large number of abrupt high-frequency current components. These abrupt high-frequency magnetic field components can be detected using sensors such as electromagnetic induction coils, enabling grounding fault detection in the circuit.

[0003] Current methods for detecting DC arc faults include using DC shunts and Hall effect sensors. However, extracting arc pulse current signals from the background of switching current and high-order harmonic currents in DC systems presents challenges. This is partly because these sensors have better low-frequency responses than high-frequency responses, and partly because they are not specifically optimized for arc current detection and identification. Consequently, the detection performance of DC arc faults is often poor. Detection capabilities are typically only achieved when the DC arc fault has persisted for some time or has progressed to a severe stage, often resulting in irreversible damage to the arc.

[0004] When conductor-to-ground arcing faults occur in low- and medium-voltage DC systems such as electric vehicles, DC microgrids, and photovoltaic systems, the DC arc current lacks a zero-crossing point, resulting in a lack of short-circuit characteristic quantities, and the DC arc can be sustained at several amperes. Therefore, in the complex broadband background noise of DC systems, most impedance-based grounding faults are difficult to detect and locate effectively. Prolonged burning of a DC arc can lead to accidents such as fires, seriously threatening the safety of equipment and personnel. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and apparatus for detecting DC series arc faults based on magnetoelectric coupling sensing.

[0006] According to one aspect of the present invention, a method for detecting DC series arc faults based on magnetoelectric coupling sensing is provided, comprising:

[0007] The pre-designed magnetoelectric coupling sensor collects the current signal in a non-contact manner with the current wire perpendicular to the DC system under test, and outputs the sensor output signal after coupling by the coupling sensor, wherein the sensor output signal is the high-frequency component waveform of the current signal;

[0008] Perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal;

[0009] Based on the spectrum, calculate the rate of change of amplitude spectrum in a predetermined characteristic frequency band;

[0010] The amplitude spectrum change rate is compared with a preset threshold, and the DC series arc fault detection result is determined based on the comparison result.

[0011] Optionally, based on the spectrum, the rate of change of the amplitude spectrum of a predetermined characteristic frequency band is calculated, including:

[0012] Based on the spectrum, calculate the first root mean square value of the characteristic frequency band under normal conditions, and the second root mean square value of the characteristic frequency band under the condition to be judged;

[0013] The rate of change of the amplitude spectrum is calculated based on the first root mean square value and the second root mean square value.

[0014] Optionally, the formula for calculating the rate of change of the amplitude spectrum CR is:

[0015]

[0016] In the formula, RMS f and RMS n These are the second root mean square error and the first root mean square error, respectively.

[0017] Optionally, the characteristic frequency band is the frequency band surrounding the resonant frequency of the magnetoelectric coupling sensor.

[0018] Optionally, the characteristic frequency band is 20kHz to 30kHz.

[0019] Optionally, the magnetoelectric coupling sensor includes a type 2-1 magnetoelectric composite material, a bias magnet, a conditioning circuit, and a battery; by adjusting the bias magnet, the external magnetic field applied to the type 2-1 magnetoelectric composite material is changed, and the resonant frequency of the magnetoelectric coupling sensor is fixed at a specific frequency band; the type 2-1 magnetoelectric composite material and the conditioning circuit are connected by wires.

[0020] Optionally, the 2-1 type magnetoelectric composite material consists of two layers of piezoelectric material and one layer of magnetic material. The magnetic material is a Terfenol-D alloy with a length of 80 mm, a width of 20 mm, and a thickness of 0.25 mm, and the piezoelectric material is lead zirconate titanate.

[0021] Optionally, the conditioning circuit includes a charge preamplifier and a high-pass filter; the charge preamplifier is used to amplify the signal obtained by the coupling of the 2-1 type magnetoelectric composite material, and the high-pass filter is used to filter out the DC component in the sensor output signal.

[0022] According to another aspect of the present invention, a DC series arc fault detection device based on magnetoelectric coupling sensing is provided, comprising:

[0023] The output module is used to collect current signals from a pre-designed magnetoelectric coupling sensor through a non-contact current wire perpendicular to the DC system under test, and output the sensor output signal after coupling by the coupling sensor, wherein the sensor output signal is the high-frequency component waveform of the current signal;

[0024] The acquisition module is used to perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal;

[0025] The calculation module is used to calculate the rate of change of amplitude spectrum in a predetermined characteristic frequency band based on the spectrum.

[0026] The comparison module is used to compare the amplitude spectrum change rate with a preset threshold and determine the DC series arc fault detection result based on the comparison result.

[0027] Optionally, the computing module includes:

[0028] The first calculation submodule is used to calculate the first root mean square value of the characteristic frequency band under normal conditions and the second root mean square value of the characteristic frequency band under the condition to be judged, based on the spectrum.

[0029] The second calculation submodule is used to calculate the rate of change of the amplitude spectrum based on the first root mean square value and the second root mean square value.

[0030] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0031] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0032] Therefore, this invention utilizes the resonant characteristics of a magnetoelectric coupling sensor. It amplifies high-frequency components in the fault signal through hardware magnetic sensing units such as a "magnetic-force-electric" composite multilayer material for sensitization and a cantilever beam sensing element. By calculating the amplitude spectrum change rate of the output electrical signal, it quantifies the fault characteristics in the characteristic frequency band, thereby achieving accurate and reliable detection of arc faults in DC systems. Simultaneously, the resonant operating frequency band of this sensor is adjustable and can be flexibly selected according to the inherent background noise of the DC system, enabling hardware-based non-fault characteristic filtering. This invention solves the problem of arc fault detection in medium and low voltage DC systems and avoids false alarms during switching or load transitions. Attached Figure Description

[0033] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0034] Figure 1 This is a flowchart illustrating a DC series arc fault detection method based on magnetoelectric coupling sensing provided in an exemplary embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the device structure of a magnetoelectric coupling sensor provided in an exemplary embodiment of the present invention;

[0036] Figure 3 This is a structural diagram of a type 2-1 magnetoelectric composite material provided in an exemplary embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of the amplitude-frequency curve of a sensor provided in an exemplary embodiment of the present invention;

[0038] Figure 5a This is a schematic diagram of the current waveform and the output waveform of the magnetoelectric coupling sensor for an arc fault, provided in an exemplary embodiment of the present invention.

[0039] Figure 5b This is a schematic diagram comparing the output waveform spectrum of a magnetoelectric coupling sensor provided in an exemplary embodiment of the present invention;

[0040] Figure 6a This is a schematic diagram of the current waveform and the output waveform of the magnetoelectric coupling sensor under load switching conditions provided in an exemplary embodiment of the present invention;

[0041] Figure 6b This is a schematic diagram comparing the output waveform spectrum of a magnetoelectric coupling sensor provided in an exemplary embodiment of the present invention;

[0042] Figure 7 This is a schematic diagram illustrating the change in the amplitude spectrum rate of change during an arc fault, provided by an exemplary embodiment of the present invention.

[0043] Figure 8 This is a schematic diagram of the structure of a DC series arc fault detection device based on magnetoelectric coupling sensing provided in an exemplary embodiment of the present invention;

[0044] Figure 9 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0045] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It is obvious that the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0046] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0047] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0048] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0049] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0050] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0051] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0052] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0053] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0054] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0055] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0056] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0057] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0058] Exemplary methods

[0059] Figure 1 This is a schematic flowchart of a DC series arc fault detection method based on magnetoelectric coupling sensing provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as... Figure 1 As shown, the DC series arc fault detection method 100 based on magnetoelectric coupling sensing includes the following steps:

[0060] Step 101: The pre-designed magnetoelectric coupling sensor is used to collect the current signal in a non-contact manner with the current wire perpendicular to the DC system under test, and the sensor output signal after coupling by the coupling sensor is output, wherein the sensor output signal is the high-frequency component waveform of the current signal.

[0061] Step 102: Perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal;

[0062] Step 103: Calculate the amplitude spectrum change rate of the predetermined characteristic frequency band based on the spectrum;

[0063] Step 104: Compare the amplitude spectrum change rate with a preset threshold, and determine the DC series arc fault detection result based on the comparison result.

[0064] Specifically, in order to improve the detection effect of DC arc and achieve non-contact high-sensitivity detection, this invention proposes a magnetoelectric coupled DC grounding fault detection sensor and its application method, aiming to solve the problem of grounding arc detection in medium and low voltage DC systems such as electric vehicles, DC microgrids, and photovoltaics.

[0065] Unlike traditional electromagnetic induction methods for detecting current signals, magnetoelectric coupling materials utilize a layered composite of magnetostrictive and piezoelectric materials. This multilayered "magnetic-force-electric" composite sensitive material converts magnetic field signals into voltage signals. Furthermore, the core component of the magnetoelectric coupling material is fabricated into a specific cantilever beam structure, further enhancing sensitivity through structural resonance. This effectively amplifies the magnetic field characteristics generated by fault arc currents, achieving ultra-high sensitivity sensing of extremely weak magnetic fields at different frequencies.

[0066] I. The key technical problem of this invention is:

[0067] a) The aim is to invent a DC series arc fault detection method based on magnetoelectric coupling sensing suitable for DC systems, which can accurately detect arc faults;

[0068] b) The present invention designs an electromagnetic coupling sensor with adjustable resonant frequency. The sensor is perpendicular to the current loop and is placed in a non-contact manner, which can sensitively capture the high-frequency components in the current signal of the circuit under test.

[0069] c) This invention proposes that the measurement signal of the magnetoelectric coupling sensor be used as a key indicator for arc fault detection;

[0070] d) This invention relies on the resonant characteristics of the magnetoelectric coupling sensor to amplify the high-frequency components of the fault that occur after the arc fault is generated, and uses the amplitude spectrum change rate of the frequency band near the resonant frequency point to quantify the fault information, which solves the problem of difficult DC arc fault detection. Moreover, this method will not produce false alarms when the load is switched.

[0071] II. The specific technical solution is as follows:

[0072] 1. The magnetoelectric coupling sensor consists of a type 2-1 magnetoelectric composite material, a bias magnet, a conditioning circuit, and a battery. A cross-sectional view of the sensor is shown below. Figure 2 As shown, the magnetic material and conditioning circuit are connected by wires. The structure of this type 2-1 magnetoelectric composite material is as follows. Figure 3 As shown, it consists of two layers of piezoelectric material and one layer of magnetic material. The magnetic material is a Terfenol-D alloy with a length of 80 mm, a width of 20 mm, and a thickness of 0.25 mm, and the piezoelectric material is lead zirconate titanate (PZT).

[0073] 2. By adjusting the bias magnet, the external magnetic field applied to the sensor is adjusted, thereby changing the magnetic properties of the material and fixing the resonant frequency of the magnetoelectric coupling sensor. Figure 4 (26.7kHz is one embodiment). The conditioning circuit includes a charge preamplifier to amplify the signal coupled from the magnetoelectric composite material, and a high-pass filter to filter out the DC component to avoid affecting the acquisition of high-frequency signals. The battery powers the internal conditioning circuit of the sensor.

[0074] 3. When using this sensor, install it perpendicular to the wire of the current being measured.

[0075] 4. During normal operation of a DC line, the magnetoelectric coupling sensor can couple the high-frequency component waveform of the current, and the amplitude spectrum change rate is close to 0. When a series arc fault occurs in the system, the high-frequency signal coupled by the sensor will change, and the frequency band change near the resonance point is particularly obvious. The amplitude spectrum change rate increases significantly, which can provide a basis for the occurrence of arc faults and detect arc faults.

[0076] like Figure 5a The figure shows the current waveform and the output waveform of the magnetoelectric coupling sensor when a DC arc fault occurs at a current level of 20A. After the fault occurs, the current decreases, and the sensor induces high-frequency noise. A Fast Fourier Transform (FFT) analysis is performed on the output signal of the magnetoelectric coupling sensor, and the spectrum is shown below. Figure 5b As shown, after the electric arc occurs, the high-frequency components of the output signal of the magnetoelectric coupling sensor increase significantly, and the increase in components at the resonant frequency point of 26.7kHz and its vicinity is particularly significant.

[0077] To avoid false alarms during load switching, the measurement signals of the magnetoelectric coupling sensor under load switching experimental conditions were analyzed. For example... Figure 6a The figure shows the current waveform and the output waveform of the magneto-electric coupling sensor during load switching at a current rating of 20A. After load switching, the current decreases, and the sensor detects a high-frequency pulse at the instant of current change. Subsequently, the signal is almost the same as before load switching. FFT analysis of the output signal of the magneto-electric coupling sensor is performed, and the spectrum is shown below. Figure 6b As shown, the high-frequency components of the output signal of the magnetoelectric coupling sensor after load switching almost overlap with those before load switching, which is significantly different from arc faults.

[0078] The amplitude spectrum change rate of the output signal of the magnetoelectric coupling sensor in the 20-30kHz frequency band was selected as a feature to quantify the change characteristics of the high-frequency component of the resonant frequency after the occurrence of an arc fault. First, the root mean square value (RMS) of the characteristic frequency band was calculated, as shown in Equation (1). Then, the amplitude spectrum change rate CR was calculated, as shown in Equation (2).

[0079]

[0080] Where X(f) iThe spectrum is the current spectrum obtained by FFT, where n is the FFT result number corresponding to the 20kHz frequency point, m is the FFT result number corresponding to the 30kHz frequency point, and RMS is... f and RMS n The results show the root mean square values ​​calculated using FFT on the faulty and normal sensor output waveforms within the selected characteristic frequency bands. When no fault occurs, the amplitude spectrum change rate is close to 0. When an arc fault occurs, the amplitude spectrum change rate increases significantly. By setting threshold conditions, it is possible to determine whether a fault has occurred.

[0081] like Figure 7 The figure shows the amplitude spectrum change rate curve of the magnetoelectric coupling sensor output signal when an electric arc occurs. The calculation time window is 10ms, and the first time window of the waveform data is selected as the normal time window for comparison calculation. When no electric arc fault occurs, the amplitude spectrum change rate is close to 0. After the fault occurs, the amplitude spectrum change rate increases significantly, which indicates that a DC series electric arc fault has occurred.

[0082] Therefore, this invention proposes a magnetoelectrically coupled DC grounding fault detection sensor and its application method, which can realize non-contact measurement of DC arc fault characteristic signals in DC systems. Compared with existing methods, its hardware frequency selection feature gives this patent great application potential. On the one hand, it can effectively reduce the deployment difficulty of the system without changing the wiring method of the original DC system; on the other hand, its high-sensitivity frequency selection characteristic has good immunity to non-fault characteristics, and can replace the original high-speed sampling and feature analysis system with a relatively simple hardware system, significantly reducing the cost of arc fault detection.

[0083] This invention utilizes the resonant characteristics of a magnetoelectric coupling sensor. It amplifies high-frequency components in fault signals through hardware magnetic sensing units such as a "magnetic-force-electric" composite multilayer material for sensitization and a cantilever beam sensing element. By calculating the rate of change of the amplitude spectrum of the output electrical signal, it quantifies fault characteristics in the characteristic frequency band, thereby achieving accurate and reliable detection of arc faults in DC systems. Simultaneously, the sensor's resonant operating frequency band is adjustable and can be flexibly selected based on the inherent background noise of the DC system, enabling hardware-based non-fault characteristic filtering. This invention solves the problem of arc fault detection in medium- and low-voltage DC systems and prevents false alarms during switching or load transitions.

[0084] Exemplary device

[0085] Figure 8 This is a schematic diagram of a DC series arc fault detection device based on magnetoelectric coupling sensing provided in an exemplary embodiment of the present invention. Figure 8 As shown, the device 800 includes:

[0086] The output module 810 is used to collect current signals from a pre-designed magnetoelectric coupling sensor through a non-contact current wire perpendicular to the DC system under test, and output the sensor output signal after coupling by the coupling sensor, wherein the sensor output signal is the high-frequency component waveform of the current signal.

[0087] The acquisition module 820 is used to perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal;

[0088] The calculation module 830 is used to calculate the rate of change of amplitude spectrum in a predetermined characteristic frequency band based on the spectrum.

[0089] The comparison module 840 is used to compare the amplitude spectrum change rate with a preset threshold and determine the DC series arc fault detection result based on the comparison result.

[0090] Optionally, the computing module 830 includes:

[0091] The first calculation submodule is used to calculate the first root mean square value of the characteristic frequency band under normal conditions and the second root mean square value of the characteristic frequency band under the condition to be judged, based on the spectrum.

[0092] The second calculation submodule is used to calculate the rate of change of the amplitude spectrum based on the first root mean square value and the second root mean square value.

[0093] Optionally, the formula for calculating the rate of change of the amplitude spectrum CR is:

[0094]

[0095] In the formula, RMS f and RMS n These are the second root mean square error and the first root mean square error, respectively.

[0096] Optionally, the characteristic frequency band is the frequency band surrounding the resonant frequency of the magnetoelectric coupling sensor.

[0097] Optionally, the characteristic frequency band is 20kHz to 30kHz.

[0098] Optionally, the magnetoelectric coupling sensor includes a type 2-1 magnetoelectric composite material, a bias magnet, a conditioning circuit, and a battery; by adjusting the bias magnet, the external magnetic field applied to the type 2-1 magnetoelectric composite material is changed, and the resonant frequency of the magnetoelectric coupling sensor is fixed at a specific frequency band; the type 2-1 magnetoelectric composite material and the conditioning circuit are connected by wires.

[0099] Optionally, the 2-1 type magnetoelectric composite material consists of two layers of piezoelectric material and one layer of magnetic material. The magnetic material is a Terfenol-D alloy with a length of 80 mm, a width of 20 mm, and a thickness of 0.25 mm, and the piezoelectric material is lead zirconate titanate.

[0100] Optionally, the conditioning circuit includes a charge preamplifier and a high-pass filter; the charge preamplifier is used to amplify the signal obtained by the coupling of the 2-1 type magnetoelectric composite material, and the high-pass filter is used to filter out the DC component in the sensor output signal.

[0101] Exemplary electronic devices

[0102] Figure 9 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. For example... Figure 9 As shown, the electronic device 90 includes one or more processors 91 and memory 92.

[0103] The processor 91 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0104] The memory 92 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 91 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above, and / or other desired functions. In one example, the electronic device may also include an input device 93 and an output device 94, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0105] In addition, the input device 93 may also include, for example, a keyboard, a mouse, etc.

[0106] The output device 94 can output various information to the outside. The output device 94 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0107] Of course, for the sake of simplicity, Figure 9 Only some of the components of this electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0108] Exemplary computer program products and computer-readable storage media

[0109] In addition to the methods and apparatus described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0110] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0111] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0112] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0113] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0114] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0115] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0116] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0117] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0118] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for detecting DC series arc faults based on magnetoelectric coupling sensing, characterized in that, include: A pre-designed magnetoelectric coupling sensor is used to collect current signals in a non-contact manner with a current conductor perpendicular to the DC system under test, and outputs a sensor output signal after being coupled by the coupling sensor, wherein the sensor output signal is the high-frequency component waveform of the current signal; Perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal; Based on the spectrum, calculate the amplitude spectrum change rate of the predetermined characteristic frequency band; The amplitude spectrum change rate is compared with a preset threshold, and the DC series arc fault detection result is determined based on the comparison result.

2. The method according to claim 1, characterized in that, Based on the spectrum, the rate of change of amplitude spectrum in a predetermined characteristic frequency band is calculated, including: Based on the spectrum, calculate the first root mean square value of the characteristic frequency band under normal conditions, and the second root mean square value of the characteristic frequency band under the condition to be judged; The amplitude spectrum change rate is calculated based on the first root mean square value and the second root mean square value.

3. The method according to claim 1, characterized in that, The formula for calculating the amplitude spectrum change rate CR is: In the formula, RMS f and RMS n These are the second root mean square error and the first root mean square error, respectively.

4. The method according to claim 2, characterized in that, The characteristic frequency band is the frequency band surrounding the resonant frequency point of the magnetoelectric coupling sensor.

5. The method according to claim 4, characterized in that, The characteristic frequency band is 20kHz to 30kHz.

6. The method according to claim 1, characterized in that, The magnetoelectric coupling sensor includes a type 2-1 magnetoelectric composite material, a bias magnet, a conditioning circuit, and a battery. By adjusting the bias magnet, the external magnetic field applied to the type 2-1 magnetoelectric composite material is changed, and the resonant frequency of the magnetoelectric coupling sensor is fixed at a specific frequency band. The type 2-1 magnetoelectric composite material and the conditioning circuit are connected by wires.

7. The method according to claim 6, characterized in that, The 2-1 type magnetoelectric composite material consists of two layers of piezoelectric material and one layer of magnetic material. The magnetic material is a Terfenol-D alloy with a length of 80 mm, a width of 20 mm, and a thickness of 0.25 mm, and the piezoelectric material is lead zirconate titanate.

8. The method according to claim 6, characterized in that, The conditioning circuit includes a charge preamplifier and a high-pass filter; the charge preamplifier is used to amplify the signal coupled by the 2-1 type magnetoelectric composite material, and the high-pass filter is used to filter out the DC component in the sensor output signal.

9. A DC series arc fault detection device based on magnetoelectric coupling sensing, characterized in that, include: The output module is used to collect current signals from a pre-designed magnetoelectric coupling sensor through a non-contact current wire perpendicular to the DC system under test, and output the sensor output signal after coupling by the coupling sensor, wherein the sensor output signal is the high-frequency component waveform of the current signal. The acquisition module is used to perform spectrum analysis on the sensor output signal to obtain the spectrum of the sensor output signal; The calculation module is used to calculate the amplitude spectrum change rate of a predetermined characteristic frequency band based on the spectrum. The comparison module is used to compare the amplitude spectrum change rate with a preset threshold and determine the DC series arc fault detection result based on the comparison result.

10. The apparatus according to claim 9, characterized in that, The calculation module includes: The first calculation submodule is used to calculate, based on the spectrum, the first root mean square value of the characteristic frequency band under normal conditions and the second root mean square value of the characteristic frequency band under the condition to be judged. The second calculation submodule is used to calculate the amplitude spectrum change rate based on the first root mean square value and the second root mean square value.

11. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-8.

12. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-8.

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