WO2022233153A1 - Procédé et appareil de détection de défauts d'arc, et appareil électrique à courant continu - Google Patents

Procédé et appareil de détection de défauts d'arc, et appareil électrique à courant continu Download PDF

Info

Publication number
WO2022233153A1
WO2022233153A1 PCT/CN2022/070255 CN2022070255W WO2022233153A1 WO 2022233153 A1 WO2022233153 A1 WO 2022233153A1 CN 2022070255 W CN2022070255 W CN 2022070255W WO 2022233153 A1 WO2022233153 A1 WO 2022233153A1
Authority
WO
WIPO (PCT)
Prior art keywords
arc fault
current
time
electrical appliance
waveform
Prior art date
Application number
PCT/CN2022/070255
Other languages
English (en)
Chinese (zh)
Inventor
袁金荣
赵志刚
李伟进
林宝伟
南树功
Original Assignee
珠海格力电器股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 珠海格力电器股份有限公司 filed Critical 珠海格力电器股份有限公司
Publication of WO2022233153A1 publication Critical patent/WO2022233153A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing

Definitions

  • the present disclosure relates to the technical field of electronic power, and in particular, to an arc fault detection method, a device, and a DC electrical appliance.
  • the DC electrical circuit has poor contact or a DC arc occurs at the fault, the continuous high-temperature ionized gas developed from it will release a lot of heat, which may cause fires and other accidents and affect the safe and reliable operation of electrical equipment. Since the DC current has no zero-crossing point, once the DC arc is generated, it is difficult to extinguish itself, which is more harmful than the AC arc.
  • the components in the DC power supply system are more diverse and complex, such as photovoltaics, wind power, energy storage, and DC appliances. Different DC appliances show different current time-frequency domain characteristics during arc faults.
  • an arc fault detection method comprising: judging whether an arc fault occurs according to a sampled current of a DC electrical appliance; after determining that an arc fault occurs, determining according to a waveform of the sampled current and a reference waveform Whether the judgment result is accurate; wherein, the reference waveform is the current waveform when the DC electrical appliance switches between the working states.
  • judging whether an arc fault occurs according to the sampled current of the DC electrical appliance includes: performing Fourier analysis on a preset frequency band of the sampled current to obtain a time-frequency domain feature; wherein the time-frequency domain feature Including time-domain fluctuations and frequency-domain harmonic components; determine whether the time-domain fluctuations are greater than or equal to a first preset threshold, and the frequency-domain harmonic components are greater than or equal to a second preset threshold; if so, then It is determined that an arc fault has occurred; if not, it is determined that an arc fault has not occurred.
  • At least one of the first preset threshold or the second preset threshold varies with the use time of the DC electrical appliance; wherein, the longer the use time, the first preset threshold At least one of the threshold or the second preset threshold is smaller.
  • the method before the Fourier analysis is performed on the sampled current, the method further includes: acquiring the operating current frequency of the DC electrical appliance; determining the preset frequency band according to the operating current frequency; wherein the The frequency of the working current of the DC electrical appliance is within the preset frequency band.
  • determining whether the determination result is accurate according to the waveform of the sampled current and the reference waveform includes: detecting whether the DC electrical appliance has switched operating states; Compare the current waveform with the reference waveform and determine whether the similarity is greater than or equal to a third preset threshold; if so, determine that the determination result is inaccurate; if not, determine that the determination result is accurate; if not , it is directly confirmed that the judgment result is accurate.
  • the method further includes: if the judgment result is accurate, outputting the judgment result; if the judgment result is inaccurate , then trigger to judge whether an arc fault occurs according to the sampling current of the DC electrical appliance.
  • the method further includes: storing the current time-frequency domain feature quantity, so that when the fault is judged next time, it can be directly judged according to the stored time-frequency domain feature quantity. An arc fault has occurred.
  • directly judging whether an arc fault occurs according to the stored time-frequency domain feature value includes: judging whether there is a time-frequency domain value consistent with the current time-frequency domain feature value in the stored time-frequency domain feature value The characteristic quantity; if so, it is determined that an arc fault has occurred.
  • judging whether an arc fault occurs according to the sampled current of the DC appliance further includes: sampling the current of the DC appliance for a preset number of times to obtain corresponding sampled currents; and judging whether the judgment result corresponding to each sampled current is An arc fault has occurred; if so, the final result is determined to be an arc fault.
  • the present disclosure further provides an arc fault detection device, including: a first detection module for judging whether an arc fault occurs according to a sampled current of a DC electrical appliance; a second detection module for After judging that an arc fault occurs, it is determined whether the judgment result is accurate according to the waveform of the sampled current and the reference waveform; wherein, the reference waveform is the current waveform when the working state of the DC electrical appliance is switched.
  • the present disclosure provides a robot control device, comprising: a memory configured to store instructions; a processor coupled to the memory, the processor configured to execute the instructions stored in the memory to implement the above The method of any embodiment.
  • the present disclosure provides a DC electrical appliance, including the above-mentioned arc fault detection device.
  • the DC electrical appliances include at least one of the following: a rice cooker, a lighting lamp, an induction cooker, a DC refrigerator, a DC fan, a DC coffee machine, a DC dishwasher, and a DC air conditioner.
  • the present disclosure provides a computer-readable storage medium having a computer program stored thereon, the program implementing the above arc fault method when executed by a processor.
  • FIG. 1 is a flowchart of an arc fault detection method according to an embodiment of the present disclosure
  • FIG. 2 is a current waveform of an induction cooker when an arc fault occurs according to an embodiment of the present disclosure
  • FIG. 5 is a current waveform when an arc fault occurs in a DC fan according to an embodiment of the present disclosure
  • FIG. 6 is a flowchart of an arc fault detection method according to another embodiment of the present disclosure.
  • FIG. 7 is a flowchart of an exit setting according to an embodiment of the present disclosure.
  • FIG. 8 is a structural diagram of an arc fault detection device according to an embodiment of the present disclosure.
  • FIG. 9 is a structural diagram of an arc fault detection device according to another embodiment of the present disclosure.
  • FIG. 10 is a structural diagram of an arc fault detection device according to still another embodiment of the present disclosure.
  • FIG. 11 is a structural diagram of a DC electrical appliance according to an embodiment of the present disclosure.
  • first, second, etc. may be used to describe the preset thresholds in the embodiments of the present disclosure, these preset thresholds should not be limited to these terms. These terms are only used to distinguish between different preset thresholds.
  • the first preset threshold may also be referred to as the second preset threshold, and similarly, the second preset threshold may also be referred to as the first preset threshold.
  • the words “if”, “if” as used herein may be interpreted as “at” or “when” or “in response to determining” or “in response to detecting”.
  • the phrases “if determined” or “if detected (the stated condition or event)” can be interpreted as “when determined” or “in response to determining” or “when detected (the stated condition or event),” depending on the context )” or “in response to detection (a stated condition or event)”.
  • FIG. 1 is a flowchart of an arc fault detection method according to an embodiment of the present disclosure.
  • the method can be applied to DC electrical appliances, the DC electrical appliances refer to electrical appliances directly powered by DC, the power supply voltage level is such as 750VDC, 400VDC, etc., and has arc fault detection and protection functions.
  • the following arc fault detection methods are performed by an arc fault detection device.
  • S101 Determine whether an arc fault occurs according to the sampled current of the DC electrical appliance.
  • the arc fault is detected by analyzing the sampled current.
  • abnormal phenomena such as a decrease in current amplitude, an increase in high-frequency harmonic components, time-domain waveform distortion, and short-term jumps will occur.
  • the above changes can be used as the basis for judging arc faults.
  • Short Time Fourier Transform (STFT) is performed on the sampled current signal, and the relevant time-frequency domain feature quantities are constructed to realize the detection of arc faults.
  • the filtering of the original current signal is realized by the inner product of the time window function, and then the fast Fourier transform is performed to obtain the time-frequency distribution of the STFT analysis.
  • STFT analysis can reflect the time-frequency domain feature quantity when the arc fault occurs as a large pulse, which is beneficial to effectively locate the moment when the arc fault occurs.
  • the time-frequency domain feature quantity is compared There is a large change in the normal period, and the fault state and the normal state can be distinguished by the change of the value of the time-frequency domain feature quantity obtained before and after the occurrence of the arc fault.
  • FIG. 2 is a current waveform of the induction cooker when an arc fault occurs according to an embodiment of the present disclosure
  • FIG. 3 is a current waveform of the induction cooker according to an embodiment of the present disclosure when shifting gears. Shifting gears changes the working power of the induction cooker. From the comparison between Figure 2 and Figure 3, it can be seen that there are certain similarities between the current waveforms when an arc fault occurs and when the working state is switched (for example, when shifting gears). Therefore, it is necessary to design a corresponding arc fault detection algorithm. The two shift states are effectively distinguished to avoid wrongly judging the shift operation as an arc fault. Although the current waveform during arc fault is similar to the current waveform during gear shifting of the induction cooker, there are also differences. Therefore, after judging that an arc fault occurs, it can be determined whether the judgment result is accurate according to the waveform of the sampling current and the waveform when the working state is switched. , wherein, the working state switching refers to starting, stopping or shifting gears.
  • the arc fault detection method of this embodiment first, it is judged whether an arc fault has occurred through the sampling current of the DC electrical appliance, and after determining that the arc fault has occurred, the judgment result is determined according to the waveform of the sampling current and the reference waveform generated when the working state of the DC electrical appliance is switched. Accurate, can eliminate the interference caused by the switching of the working state of the DC electrical appliance itself, and improve the accuracy of arc fault detection.
  • the above step S101 may specifically include: performing Fourier analysis on the sampled current to obtain a time-frequency domain characteristic quantity; wherein the time-frequency domain characteristic quantity includes a time-domain fluctuation quantity and a frequency-domain characteristic quantity Harmonic component; time domain fluctuation amount is used to reflect the fluctuation of current with time within a certain sampling time.
  • the current value at each time point can be determined by taking multiple points in the sampling time. , calculate the average value, and then calculate the mean square error to reflect the fluctuation of the current during the sampling time, or calculate the absolute value of the difference between the current value corresponding to each time point and the above average value, and then calculate and , to reflect the fluctuation of the current during the sampling time.
  • the time domain fluctuation amount is greater than or equal to the first preset threshold, and the frequency domain harmonic component is greater than or equal to the first preset threshold. or equal to whether the second preset threshold is established. If established, it is determined that an arc fault has occurred. If not, it is determined that no arc fault has occurred, and the combination of current fluctuations and frequency-domain harmonic components can eliminate accidental factors and improve the accuracy of fault judgment.
  • the above-mentioned first preset threshold and second preset threshold may be determined through experiments before the DC electrical appliance leaves the factory. For example, through multiple experiments, the current fluctuation amount corresponding to the occurrence of an arc fault is obtained, the average value, the minimum value, the maximum value or the value with the most occurrences is obtained, and it is set as the first preset threshold value. Obtain the corresponding frequency domain harmonic components when an arc fault occurs, take the average value, the minimum value, the maximum value or the value with the most occurrences, and set it as the second preset threshold.
  • FIG. 4 is a current waveform when an arc fault occurs in a DC refrigerator according to an embodiment of the present disclosure
  • FIG. 5 is a current waveform when an arc fault occurs in a DC fan according to an embodiment of the present disclosure.
  • the first preset threshold or the second preset threshold At least one of the thresholds can be reduced to improve the detection sensitivity.
  • a threshold value that changes with the use time can be set. For example, when the DC appliance is initially put into use, the first preset threshold value is larger than the preset value by a preset amount (for example, larger than the set value). 10%), as the use time increases, the set value may gradually decrease until it is less than the preset amount relative to the set value (for example, 10% less than the set value).
  • At least one of the first preset threshold or the second preset threshold varies with the use time of the DC electrical appliance; wherein, the longer the use time, the first preset threshold or the second preset threshold At least one of them is smaller.
  • the detection feature is constructed in the form of a combination of multiple frequency bands to achieve anti-interference.
  • the method before performing Fourier analysis on the sampled current, the method further includes: acquiring the working current frequency of the DC appliance to be detected; determining the above-mentioned preset frequency band according to the working current frequency of the DC appliance to be detected to ensure the working current of the DC appliance The frequency is within the preset frequency band, so as to realize targeted detection and improve detection accuracy.
  • the above judgment result is output, so that the circuit in which the arc fault occurs can be controlled by the switch to shut down in time, so as to prevent the arc fault from causing local high temperature or even fire. If the above judgment result is inaccurate, retrigger to judge whether an arc fault occurs according to the sampling current of the DC electrical appliance.
  • the time-frequency domain characteristic quantities of the arc fault can be stored synchronously, the time-domain fluctuation amount and the frequency-domain harmonic component.
  • a direct comparison method can be introduced, and the same time-frequency domain exists. Domain feature quantity, directly determine the arc fault, thereby shortening the detection time. For example, after it is determined that the judgment result is accurate, the current time-frequency domain feature quantity is stored in the storage unit of the DC electrical appliance, so that the next time a fault is judged, the arc fault can be directly judged according to the stored time-frequency domain feature quantity.
  • the consistent time-frequency domain characteristic quantity means that there is a set of time-frequency domain characteristic quantities in the above-mentioned storage unit, and the time-domain fluctuation quantity in it is the same as the time-domain fluctuation quantity of the current sampling current, and the frequency-domain harmonic quantity in it is the same as that of the current sampling current.
  • the wave component is the same as the frequency domain harmonic component of the previous sampled current.
  • the current of the DC electrical appliance may also be sampled for a preset number of times to obtain the corresponding sampling current; it is judged whether the judgment result corresponding to each sampling current is both An arc fault has occurred; if yes, the final result is determined to be an arc fault, if not, the final result is determined to be no arc fault.
  • arc faults must be detected within a specified safe time period (for example, 2s), so the number of multiple detections cannot be increased indefinitely, and the time between adjacent two detections cannot be infinitely extended. It is necessary to ensure that the final total detection time is less than the specified safety time.
  • FIG. 6 is a flowchart of an arc fault detection method according to another embodiment of the present disclosure. As shown in FIG. 6 , the method includes:
  • the time domain fluctuation amount is used to reflect the fluctuation of the current over time within a certain sampling time.
  • the average value can be calculated by taking multiple points in the sampling time and determining the current value at each time point. , and then by calculating the mean square error to reflect the fluctuation of the current during the sampling time, or by calculating the absolute value of the difference between the current value corresponding to each time point and the above average value, and then summing to reflect Fluctuation of the current during the sampling time.
  • S4 Obtain a comparison result between the standard deviation of the time-domain wave and the first preset threshold, and a comparison result between the frequency-domain harmonic component and the second preset threshold.
  • the time domain fluctuation amount is greater than or equal to the first preset threshold, and the frequency domain harmonic component is greater than or equal to the first preset threshold. or equal to whether the second preset threshold is established; if it is, it is determined that an arc fault has occurred; if not, it is determined that an arc fault has not occurred, and the combination of the current fluctuation and the frequency domain harmonic component can eliminate accidental factors and improve fault judgment. accuracy.
  • step S5 determines whether an arc fault occurs, if yes, go to step S6; if not, go back to step S1.
  • step S8 determine whether the DC electrical appliance has performed the operation of starting, stopping and shifting; if yes, go to step S9, if not, go to step S11.
  • step S9 judging whether the similarity between the current current waveform and the current waveform in the startup, shutdown and gear shifting states is greater than the third preset threshold; if so, after performing step S10, return to step S1; if not, perform step S11 .
  • step S9 it is necessary to call the current waveform in the starting, stopping and shifting states, that is, the reference waveform.
  • the reference waveform is stored in the control chip of the DC device at the factory setting.
  • the flow chart of the appearance setting includes:
  • the working state includes starting, stopping and shifting.
  • FIG. 8 is a structural diagram of an arc fault detection device according to an embodiment of the present disclosure. As shown in FIG. 8 , the device includes:
  • the first detection module 10 is used for judging whether an arc fault occurs according to the sampling current of the DC electrical appliance.
  • the detection of the arc fault adopts the method of analyzing the sampled current.
  • abnormal phenomena such as the reduction of the current amplitude, the increase of the high-frequency harmonic component, the distortion of the time domain waveform and the short-term jump will occur.
  • the above changes can be used as the basis for judging the arc fault.
  • Short-time Fourier analysis (STFT) is performed on the sampled current signal, and the relevant time-frequency domain feature quantities are constructed to realize the detection of arc faults.
  • the filtering of the original current signal is realized by the inner product of the time window function, and then the fast Fourier transform is performed to obtain the time-frequency distribution of the STFT analysis.
  • STFT analysis can reflect the time-frequency domain feature quantity when the arc fault occurs as a large pulse, which is beneficial to effectively locate the moment when the arc fault occurs.
  • the time-frequency domain feature quantity is compared There is a large change in the normal period, and the fault state and the normal state can be distinguished by the change of the value of the time-frequency domain feature quantity obtained before and after the occurrence of the arc fault.
  • the second detection module 20 is configured to determine whether the judgment result is accurate according to the waveform of the sampled current and the reference waveform after judging that an arc fault occurs; wherein the reference waveform is the current waveform of the DC electrical appliance when the working state is switched.
  • the first detection module determines whether an arc fault occurs according to the sampling current of the DC electrical appliance.
  • the second detection module switches according to the waveform of the sampled current and the working state of the DC electrical appliance.
  • the reference waveform generated at the time of detection determines whether the judgment result is accurate, which can eliminate the interference caused by the switching of the working state of the DC electrical appliance itself, and improve the accuracy of arc fault detection.
  • FIG. 9 is a structural diagram of an arc fault detection apparatus according to another embodiment of the present disclosure.
  • the first detection module 10 includes:
  • the first obtaining unit 101 is configured to perform Fourier analysis on the sampled current of the DC electrical appliance to obtain the time-frequency domain feature quantity; wherein, the time-frequency domain feature quantity includes a time-domain fluctuation quantity and a frequency-domain harmonic component;
  • the fluctuation amount is used to reflect the fluctuation of the current with time within a certain sampling time.
  • the current value at each time point can be determined by taking multiple points in the sampling time, and then calculating the average value, and then using Calculate the mean square error to reflect the fluctuation of the current during the sampling time. You can also calculate the absolute value of the difference between the current value corresponding to each time point and the above average value, and then sum it up to reflect the current in the sampling time. fluctuations over time.
  • the first detection module 10 also includes a judging unit 102, since it may be contingent to judge whether an arc fault occurs only through the current fluctuation amount or only through the frequency domain harmonic component, therefore, the judging unit 102 needs to judge that the time domain fluctuation amount is greater than or equal to the first preset threshold value, and the frequency domain harmonic component is greater than or equal to the second preset threshold value. Whether the fluctuation amount in the time domain is greater than or equal to the first preset threshold value, and the frequency domain harmonic component is greater than or equal to the second preset threshold value.
  • the preset threshold When the preset threshold is established, it is determined that an arc fault has occurred; when the time domain fluctuation is greater than or equal to the first preset threshold, and the frequency domain harmonic component is greater than or equal to the second preset threshold, it is determined that no arc fault has occurred.
  • the combination of current fluctuation and frequency domain harmonic components can eliminate accidental factors and improve the accuracy of fault judgment.
  • the first preset threshold value and the second preset threshold value At least one can be adjusted down to improve the detection sensitivity.
  • a threshold value that changes with the use time can be set. For example, when the DC appliance is initially put into use, the first preset threshold value is larger than the preset value by a preset amount (for example, 10 larger than the preset value). %), as the use time increases, the set value can be gradually reduced until it is less than the preset amount relative to the set value (for example, 10% less than the set value).
  • the above-mentioned first detection module 10 further includes: a correction unit 103, configured to correct at least one of the above-mentioned first preset threshold value and the second preset threshold value according to the use time; wherein, the longer the use time, the first preset threshold value At least one of the two preset thresholds is smaller.
  • a correction unit 103 configured to correct at least one of the above-mentioned first preset threshold value and the second preset threshold value according to the use time; wherein, the longer the use time, the first preset threshold value At least one of the two preset thresholds is smaller.
  • the detection feature is constructed in the form of a combination of multiple frequency bands to achieve anti-interference.
  • the above-mentioned first detection module 10 further includes: a second acquisition unit 104 for acquiring the operating current frequency of the DC electrical appliance to be detected; and a frequency band determination unit 105 for acquiring the operating current of the DC electrical appliance to be detected The frequency determines the frequency band targeted for Fourier analysis, so as to achieve targeted detection and improve detection accuracy.
  • the above-mentioned second detection module 20 includes: a detection unit 201, which is used to detect whether the DC electrical appliance has been switched between working states after it is determined that an arc fault occurs; the first determination unit 202, which uses When it is detected that the DC electrical appliance has switched its working state, the waveform of the sampled current is compared with the reference waveform and it is judged whether the similarity is greater than or equal to the third preset threshold; if so, it indicates that the above judgment result is indeed due to the direct current Therefore, it is determined that the judgment result is inaccurate; if not, it means that although the working state of the DC appliance is switched, the above judgment result is not caused by the switching of the working state of the DC appliance.
  • the second determining unit 203 is used to exclude the possibility of misjudgment caused by the switching of the working state when the DC electrical appliance does not switch the working state, and directly determine that the judgment result is accurate.
  • the first determining unit 202 and The second determining unit 203 is further configured to output the above-mentioned determination result after determining that the determination result is accurate, so that the circuit in which the arc fault occurs can be controlled by the switch to shut down in time, so as to prevent the arc fault from causing local high temperature or even fire. If the above judgment result is inaccurate, the first detection module 10 judges whether an arc fault occurs again according to the sampled current of the DC electrical appliance.
  • the time-frequency domain feature quantity of the arc fault is stored synchronously.
  • a direct comparison method can be introduced. If the same time-frequency domain feature quantity exists, it is directly determined as an arc fault, thereby reducing the size of the arc fault. detection time.
  • the above-mentioned second detection module 20 further includes: a storage unit 204 for storing the current time-frequency domain feature quantity while determining that the judgment result is accurate and outputting the judgment result, so as to facilitate the next fault judgment , directly according to the stored time-frequency domain feature quantity to determine whether an arc fault occurs.
  • the above-mentioned first detection module 10 also includes a second judgment unit 106 for judging whether there is a time-frequency domain characteristic quantity consistent with the time-frequency domain characteristic quantity of the current sampling current in the stored time-frequency domain characteristic quantity; In this case, it is directly determined that an arc fault occurs.
  • the obtaining unit 101 can also sample the current of the DC electrical appliance for a preset number of times to obtain the corresponding sampling current; the judging unit 102 is also used for judging the judgment corresponding to each sampling current Whether the result is an arc fault; if so, determine the final result as an arc fault.
  • arc faults must be detected within a specified safe time period (for example, 2s), so the number of multiple detections cannot be increased indefinitely, and the time between adjacent two detections cannot be infinitely extended. It is necessary to ensure that the final total detection time is less than the specified safety time.
  • FIG. 10 is a structural diagram of an arc fault detection apparatus according to yet another embodiment of the present disclosure. As shown in FIG. 10 , the arc fault detection apparatus includes a memory 1001 and a processor 1002 .
  • the memory 1001 is used to store instructions, and a processor 1002 is coupled to the memory 1001, and the processor 1002 is configured to implement the method according to any of the embodiments of FIGS. 1 , 6 and 7 based on the execution of the instructions stored in the memory.
  • the arc fault detection apparatus further includes a communication interface 1003 for exchanging information with other devices.
  • the arc fault detection device further includes a bus 1004 , the processor 1002 , the communication interface 1003 , and the memory 1001 communicate with each other through the bus 1004 .
  • the memory 1001 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.
  • the memory 1001 may also be a memory array.
  • the storage 1001 may also be divided into blocks, and the blocks may be combined into virtual volumes according to certain rules.
  • the processor 1002 may be a central processing unit (CPU), or may be an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present disclosure.
  • CPU central processing unit
  • ASIC application specific integrated circuit
  • the present disclosure also relates to a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, any one of the embodiments in FIGS. Methods.
  • FIG. 11 is a structural diagram of a DC electrical appliance according to an embodiment of the present disclosure.
  • the DC appliance 1101 includes the arc fault detection device 1102 in the above-mentioned embodiment, and the arc fault detection device can be arranged in the DC plug or DC adapter of the DC appliance to improve the accuracy of arc fault detection, and further Ensure the reliability of the operation of the entire DC electrical appliance.
  • the above-mentioned DC electrical appliances include at least one of the following: a rice cooker, a lighting lamp, an induction cooker, a DC refrigerator, a DC fan, a DC coffee machine, a DC dishwasher, and a DC air conditioner.
  • the device embodiments described above are only illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed over multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each embodiment can be implemented by means of software plus a necessary general hardware platform, and certainly can also be implemented by hardware.
  • the above-mentioned technical solutions can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic A disc, an optical disc, etc., includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments or some parts of the embodiments.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)
  • Emergency Protection Circuit Devices (AREA)

Abstract

L'invention concerne un procédé et un appareil de détection de défauts d'arc (1102), ainsi qu'un appareil électrique à courant continu (1101). Le procédé de détection de défauts d'arc selon l'invention consiste : à déterminer, en fonction d'un courant échantillonné d'un appareil électrique à courant continu (1101), si un défaut d'arc se produit (S101) ; et, lorsqu'il est déterminé qu'un défaut d'arc se produit, à déterminer, en fonction d'une forme d'onde du courant échantillonné et d'une forme d'onde de référence, si le résultat de détermination est précis, la forme d'onde de référence étant une forme d'onde de courant lorsqu'une commutation d'état de fonctionnement se produit dans l'appareil électrique à courant continu (1101) (S102). Le procédé selon l'invention permet d'éliminer les interférences générées par une commutation d'état de fonctionnement de l'appareil électrique à courant continu (1101) lui-même, ce qui améliore la précision de détection de défauts d'arc.
PCT/CN2022/070255 2021-05-07 2022-01-05 Procédé et appareil de détection de défauts d'arc, et appareil électrique à courant continu WO2022233153A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202110496825.7 2021-05-07
CN202110496825.7A CN113125913B (zh) 2021-05-07 2021-05-07 一种电弧故障检测方法、装置及直流电器

Publications (1)

Publication Number Publication Date
WO2022233153A1 true WO2022233153A1 (fr) 2022-11-10

Family

ID=76781322

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2022/070255 WO2022233153A1 (fr) 2021-05-07 2022-01-05 Procédé et appareil de détection de défauts d'arc, et appareil électrique à courant continu

Country Status (2)

Country Link
CN (1) CN113125913B (fr)
WO (1) WO2022233153A1 (fr)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113125913B (zh) * 2021-05-07 2022-12-27 国创能源互联网创新中心(广东)有限公司 一种电弧故障检测方法、装置及直流电器
JP7270945B2 (ja) * 2021-10-08 2023-05-11 Ｉｇｒ技研株式会社 漏洩電流遮断装置

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103245897A (zh) * 2013-05-02 2013-08-14 复旦大学 一种使用多重判据的光伏系统直流故障电弧检测方法
CN105223476A (zh) * 2015-09-16 2016-01-06 北京芯同汇科技有限公司 一种基于高频特征的故障电弧检测方法与装置
CN107064752A (zh) * 2017-03-22 2017-08-18 北京航空航天大学 一种航空故障电弧检测的判别算法
CN109581160A (zh) * 2018-12-05 2019-04-05 公安部沈阳消防研究所 故障电弧检测方法
US20190324075A1 (en) * 2013-09-26 2019-10-24 James J. Kinsella Monitoring service current for arc fault detection in electrical branch circuits
CN111474451A (zh) * 2020-04-26 2020-07-31 威胜集团有限公司 提高故障电弧准确率的检测方法、装置和可读存储介质
CN113125913A (zh) * 2021-05-07 2021-07-16 珠海格力电器股份有限公司 一种电弧故障检测方法、装置及直流电器

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6362628B2 (en) * 1998-12-21 2002-03-26 Pass & Seymour, Inc. Arc fault circuit detector device detecting pulse width modulation of arc noise
US6388849B1 (en) * 2000-02-14 2002-05-14 Eaton Corporation ARC fault detector responsive to average instantaneous current and step increases in current and circuit breaker incorporating same
US20040100274A1 (en) * 2002-11-22 2004-05-27 Siemens Energy & Automation, Inc. Arc fault tester
CN102253293A (zh) * 2011-05-30 2011-11-23 南京航空航天大学 一种直流电弧故障检测方法及装置
CN102375107B (zh) * 2011-09-20 2013-07-10 上海交通大学 基于时频综合分析的故障电弧检测方法及其装置
US9431816B2 (en) * 2012-09-28 2016-08-30 Eaton Corporation Direct current arc fault detector and circuit interrupter, and method of detecting an arc in a direct current power circuit
EP3823121A1 (fr) * 2013-05-24 2021-05-19 Delta Electronics (Thailand) Public Co., Ltd. Détection d'arc de serie sur la base des harmoniques dans le spectre du signal d'un courant cc, en particulier par la sommation d'harmoniques et par la comparaison du nombre d'harmonique et une amplitude importante
CN103592550B (zh) * 2013-11-26 2018-11-23 华侨大学 一种电弧故障检测方法及保护装置
CN103913663B (zh) * 2014-04-21 2017-01-25 南京航空航天大学 一种直流系统电弧故障在线检测方法和保护装置
CN104866632B (zh) * 2015-04-30 2018-03-06 广东美的制冷设备有限公司 家电设备的故障数据获取方法、装置及终端
CN105633903A (zh) * 2016-01-18 2016-06-01 京东方科技集团股份有限公司 具有故障监控功能的电气设备、电气系统以及终端设备
CN106199131B (zh) * 2016-06-22 2019-08-20 华为技术有限公司 一种直流电流中电弧的检测电路及微处理器
CN106054009B (zh) * 2016-08-19 2019-01-29 广东美的制冷设备有限公司 家电设备及用于其的故障电弧检测装置和方法
CN107340459B (zh) * 2016-11-24 2019-06-04 安徽江淮汽车集团股份有限公司 一种直流故障电弧检测方法及系统
CN109655678B (zh) * 2017-10-11 2021-11-16 湖南中车时代电动汽车股份有限公司 一种用于用电器件的散热性能评估方法及系统
CN109061415A (zh) * 2018-08-21 2018-12-21 珠海格力电器股份有限公司 一种故障电弧检测方法及装置、计算机装置、计算机可读存储介质
CN112269110A (zh) * 2020-10-19 2021-01-26 合肥阳光新能源科技有限公司 一种电弧故障判定方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103245897A (zh) * 2013-05-02 2013-08-14 复旦大学 一种使用多重判据的光伏系统直流故障电弧检测方法
US20190324075A1 (en) * 2013-09-26 2019-10-24 James J. Kinsella Monitoring service current for arc fault detection in electrical branch circuits
CN105223476A (zh) * 2015-09-16 2016-01-06 北京芯同汇科技有限公司 一种基于高频特征的故障电弧检测方法与装置
CN107064752A (zh) * 2017-03-22 2017-08-18 北京航空航天大学 一种航空故障电弧检测的判别算法
CN109581160A (zh) * 2018-12-05 2019-04-05 公安部沈阳消防研究所 故障电弧检测方法
CN111474451A (zh) * 2020-04-26 2020-07-31 威胜集团有限公司 提高故障电弧准确率的检测方法、装置和可读存储介质
CN113125913A (zh) * 2021-05-07 2021-07-16 珠海格力电器股份有限公司 一种电弧故障检测方法、装置及直流电器

Also Published As

Publication number Publication date
CN113125913B (zh) 2022-12-27
CN113125913A (zh) 2021-07-16

Similar Documents

Publication Publication Date Title
WO2022233153A1 (fr) Procédé et appareil de détection de défauts d'arc, et appareil électrique à courant continu
Artale et al. Arc fault detection method based on CZT low-frequency harmonic current analysis
US20220294204A1 (en) Processor-based circuit interrupting devices
US8654487B2 (en) Methods, systems, and apparatus and for detecting parallel electrical arc faults
Lezama et al. An embedded system for AC series arc detection by inter-period correlations of current
CN104678265A (zh) 一种串联故障电弧检测装置及检测方法
US10121622B2 (en) Systems and methods for controlling relay activation timing
CN102955098A (zh) 中性点非有效接地系统单相接地故障识别方法
CA2641836C (fr) Coupe-circuit, et methode de synchronisation de phase de processeur
TW556382B (en) Power protection
Luan et al. Arc fault detection and identification via non-intrusive current disaggregation
Marhoon et al. Design and implementation of intelligent circuit breaker for electrical current sensing and monitoring
Gong et al. Series arc fault identification method based on wavelet transform and feature values decomposition fusion DNN
JP5150927B2 (ja) トラッキング電流検出装置
JP4856391B2 (ja) トラッキング電流検出装置
WO2021227128A1 (fr) Procédé de test et circuit de test de caractéristique d'action pour dispositif d'action de protection contre les fuites électriques
CN111025102B (zh) 基于电压波形分析的低压电弧故障检测方法及装置
JP2022529872A (ja) 配電および／または送電ネットワークを短絡から保護する方法
WO2022118901A1 (fr) Dispositif de détection de décharge
JP2013054853A (ja) ヒータ断線検知装置、電力調整装置及びヒータ断線検知方法
CN104793166A (zh) 一种用于电弧故障检测装置afdd测试装置及其方法
CN112327151B (zh) 一种有载分接开关切换状态的监测方法、装置及终端设备
CN110568331B (zh) 一种电弧故障检测方法及保护装置
US20210048462A1 (en) Electricity meter with fault tolerant power supply
CN205015445U (zh) 一种局部放电自动测试装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22798495

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 22798495

Country of ref document: EP

Kind code of ref document: A1