A residual current detection method, device and medium

Abstract

This application discloses a residual current detection method, device, and medium, relating to the field of current detection. Since the magnetic core of a residual current transformer is significantly affected by temperature, resulting in low detection accuracy, this application applies a square wave excitation signal to the residual current transformer; acquires effective voltage data at the rising and falling edges, and generates an effective data sequence according to the corresponding time order; obtains a residual current characteristic value sequence and a residual current characteristic value curve based on the effective data sequence; and obtains a residual current compensation characteristic value curve based on the residual current characteristic value curve and temperature linearity data. When detecting DC residual current, the residual current characteristic curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linearity data of the residual current transformer to obtain the residual current compensation characteristic value curve. Based on the residual current compensation characteristic value curve, the characteristic value of the temperature-compensated residual current can be obtained, improving the detection accuracy.

Description

Technical Field

[0001] This application relates to the field of current detection, and in particular to a method, apparatus and medium for detecting residual current. Background Technology

[0002] With economic development and the rapid growth of the power industry, the variety of household appliances has also increased significantly, making the safety of residents' electricity use paramount. In the current electrical environment, residual current includes low-frequency AC, high-frequency AC, and DC signals. Among these, residual AC current poses a significant health hazard; 50mA / s can cause ventricular fibrillation. With the increasing variety of electricity usage, DC current is now widely used, including in DC charging stations, variable frequency motors, and household appliances such as certain types of laptops, microwave ovens, and washing machines. Therefore, the detection of residual DC current is also becoming increasingly important.

[0003] Currently, most residual current detection products on the market use electromagnetic current transformers, Hall effect current sensors, and magnetically modulated current transformers for DC residual current detection. However, the detection accuracy is low because the leakage electromagnetic core is greatly affected by temperature.

[0004] Therefore, providing a residual current detection method with core temperature compensation is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide a residual current detection method with core temperature compensation.

[0006] To address the aforementioned technical problems, this application provides a residual current detection method, comprising:

[0007] Apply a square wave excitation signal to the residual current transformer;

[0008] Acquire the effective voltage data at the rising and falling edges, and generate an effective data sequence according to the corresponding time order;

[0009] The residual current characteristic value sequence is obtained based on the effective data sequence;

[0010] The residual current characteristic value sequence at different temperatures is fitted to obtain the residual current characteristic value curve;

[0011] Obtain linear temperature data of the current residual current transformer as a function of time;

[0012] The residual current compensation characteristic curve is obtained based on the residual current characteristic curve and the temperature linearity data.

[0013] Preferably, in the above residual current detection method, the step of acquiring the effective voltage data at the rising and falling edges and generating an effective data sequence according to the corresponding time order includes:

[0014] The voltage data of the rising and falling edges of each cycle are obtained according to the preset sampling time interval;

[0015] The average voltage at the rising edge and the average voltage at the falling edge of each cycle are obtained based on the voltage data.

[0016] The average voltage at the rising edge and the average voltage at the falling edge are arranged in chronological order to generate a valid data sequence.

[0017] Preferably, in the above residual current detection method, obtaining the average voltage at the rising edge and the average voltage at the falling edge for each cycle based on the voltage data includes:

[0018] The average voltage at the rising edge and the average voltage at the falling edge of each cycle are obtained according to the first formula and the voltage data.

[0019] The first formula is:

[0020] in, This represents the voltage data at the rising or falling edge of one cycle; N is the number of samples.

[0021] Preferably, in the above residual current detection method, obtaining the residual current feature value sequence based on the valid data sequence includes:

[0022] The effective data difference sequence is obtained based on the effective data sequence;

[0023] The residual current characteristic value sequence is obtained by inverting the odd-numbered terms of the effective data difference sequence.

[0024] Preferably, in the above residual current detection method, applying a square wave excitation signal to the residual current transformer includes:

[0025] The square wave excitation signal is applied to the residual current transformer through the H-bridge drive circuit.

[0026] Preferably, in the above residual current detection method, after obtaining the residual current compensation characteristic curve based on the residual current characteristic curve and the temperature linearity data, the method further includes:

[0027] Based on the base temperature and time, and combined with the residual current compensation characteristic value curve, the current compensation characteristic value is obtained.

[0028] Preferably, in the above residual current detection method, after obtaining the current compensation characteristic value based on the base temperature and time, combined with the residual current compensation characteristic value curve, the method further includes:

[0029] Determine whether the current compensation feature value exceeds the feature value threshold;

[0030] If so, issue an alarm indicating that the current residual current is too high.

[0031] To address the aforementioned technical problems, this application also provides a residual current detection device, comprising:

[0032] The excitation module is used to apply a square wave excitation signal to the residual current transformer;

[0033] The data acquisition module is used to acquire the effective voltage data at the rising and falling edges and generate an effective data sequence according to the corresponding time order.

[0034] A feature value sequence generation module is used to obtain a residual current feature value sequence based on the effective data sequence;

[0035] The fitting module is used to fit the residual current characteristic value sequence at different temperatures to obtain the residual current characteristic value curve;

[0036] The temperature data acquisition module is used to acquire linear temperature data of the current residual current transformer as a function of time.

[0037] The compensation module is used to obtain the residual current compensation characteristic curve based on the residual current characteristic curve and the temperature linear data.

[0038] To address the aforementioned technical problems, this application also provides a residual current detection device, comprising:

[0039] Memory, used to store computer programs;

[0040] A processor is used to implement the steps of the above-described residual current detection method when executing the computer program.

[0041] To address the aforementioned technical problems, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned residual current detection method.

[0042] The residual current detection method provided in this application applies a square wave excitation signal to a residual current transformer; acquires effective voltage data at the rising and falling edges, and generates an effective data sequence according to the corresponding time sequence; obtains a residual current characteristic value sequence based on the effective data sequence; fits the residual current characteristic value sequences at different temperatures to obtain a residual current characteristic value curve; acquires temperature linearity data of the current residual current transformer's temperature changing over time; and obtains a residual current compensation characteristic value curve based on the residual current characteristic value curve and the temperature linearity data. In this embodiment, when detecting DC residual current, the residual current characteristic curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linearity data of the residual current transformer to obtain the residual current compensation characteristic value curve. Based on the residual current compensation characteristic value curve, the characteristic value of the temperature-compensated residual current can be obtained. This application considers the influence of temperature on detection, thus improving the accuracy of detection.

[0043] In addition, this application also provides an apparatus and medium, including the above-mentioned residual current detection method, with the same effect. Attached Figure Description

[0044] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments 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.

[0045] Figure 1 A flowchart of a residual current detection method provided in an embodiment of this application;

[0046] Figure 2 A detection device based on a residual current transformer is provided in this application embodiment;

[0047] Figure 3 A voltage sampling waveform diagram provided in an embodiment of this application;

[0048] Figure 4 A waveform diagram showing the variation of sampling with temperature is provided as an embodiment of this application;

[0049] Figure 5 A schematic diagram of residual current compensation characteristic value curves at different temperatures provided for embodiments of this application;

[0050] Figure 6 This is a schematic diagram of a residual current detection device provided in an embodiment of this application;

[0051] Figure 7 This is a structural diagram of another residual current detection device provided in an embodiment of this application. Detailed Implementation

[0052] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0053] The core of this application is to provide a residual current detection method, device, and medium.

[0054] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] In electrical fire monitoring systems, residual current transformers, based on Kirchhoff's current law, are used to detect the residual current value of protected power lines. They are used in conjunction with electrical measurement and control devices and motor protection devices to protect power lines. Residual current refers to the current in a low-voltage distribution line where the vector sum of the currents in each phase (including the neutral line) is not zero. Simply put, when an accident occurs on the electricity consumption side, current flows from a live conductor through the human body to the ground, causing the current in the main circuit's incoming and outgoing lines to be unequal in magnitude between phase I and phase I. The instantaneous vector sum of the currents at this time is called the residual current, commonly known as leakage current. The function of a residual current transformer is to detect residual current (leakage current) and determine whether there is leakage current and fire risk in the circuit. Residual current transformers are specifically designed for detecting residual current and are a core component of residual current circuit breakers (RCCBs). With the increasing demand for RCCBs in the power distribution market, the number of RCCBs to be produced and tested is also increasing. Traditional manual testing methods have significantly limited the production capacity of RCCBs. Therefore, it is necessary to study intelligent detection technology to achieve automated testing of residual current transformers, reduce human intervention, and improve detection efficiency.

[0056] Existing residual current circuit breakers are typically only suitable for detecting residual current in AC power, not DC power. With the development of DC power distribution in China, the number of DC power consumption scenarios and DC loads will increase significantly. To ensure electrical safety, corresponding DC residual current protection circuit breakers are needed. Currently, the market for residual current detection products of type B and higher specifications mostly uses electromagnetic current transformers, Hall effect current sensors, and magnetically modulated current transformers for residual current detection. These methods are significantly affected by temperature, resulting in lower detection accuracy.

[0057] To address the aforementioned problems, embodiments of this application provide a residual current detection method, such as... Figure 1 As shown, it includes:

[0058] S11: Apply a square wave excitation signal to the residual current transformer;

[0059] S12: Obtain the effective voltage data at the rising and falling edges, and generate an effective data sequence according to the corresponding time order;

[0060] S13: Obtain the residual current characteristic value sequence based on the valid data sequence;

[0061] S14: Fit the residual current characteristic value sequence at different temperatures to obtain the residual current characteristic value curve;

[0062] S15: Obtain the linear temperature data of the current residual current transformer as a function of time;

[0063] S16: Obtain the residual current compensation characteristic curve based on the residual current characteristic curve and temperature linearity data.

[0064] It should be noted that in this application, to improve detection accuracy, ferrite is used as the core material of the residual current transformer. Utilizing the hysteresis loop characteristic of ferrite, DC signals are insensitive in the linear region, and the same principle applies to the saturation region. However, there is a DC induced value in the nonlinear region. It is through the change in this region that the DC residual current can be detected. By applying a bipolar square wave to the coil, the magnetic core is magnetized and demagnetized in both directions, ensuring that the core reaches the saturation region. Different DC leakage current values ​​will result in different times to reach the saturation ampere-turns, corresponding to different currents. The differences in different DC residual currents can be extracted from sampling resistors, and the corresponding DC leakage current value can be obtained through algorithm analysis. Ferrite is affected by temperature, causing changes in its initial permeability, which in turn affects the time it takes for the core to reach saturation excitation, affecting the DC characteristic data and thus the accuracy of leakage current detection. However, its characteristics can be used to estimate the current temperature of the ferrite, thereby compensating for the influence on the DC characteristic and improving the accuracy of leakage current detection.

[0065] Figure 2 This application provides a detection device based on a residual current transformer. Step S11 involves applying a square wave excitation signal to the residual current transformer to induce it into the saturation region for detection. Utilizing the characteristics of the ferrite hysteresis loop, positive and negative voltages are applied to the magnetic core to ensure bidirectional magnetic penetration into the saturation region, generating a reverse magnetic field of equal magnitude. This causes the winding to shift from one saturation region to another. Different DC leakage current values ​​will result in different times to reach the saturation ampere-turns, corresponding to different currents. The differences in DC residual current can be extracted from sampling by the sampling resistor, and the corresponding DC leakage current value can be obtained through algorithm analysis. Figure 2As shown, the sampling resistor mentioned in this embodiment is connected in parallel with the residual current transformer. The voltage value of the sampling resistor is used as the sampling signal. The collected voltage value is amplified and the analog-to-digital converter outputs a digital signal as the detection signal, which is then used for data analysis in the algorithm module.

[0066] Step S12 acquires the effective voltage data at the rising and falling edges, and generates an effective data sequence according to the corresponding time order. In DC detection, the timing of the rising and falling edges of the excitation square wave is required to distinguish the response signal during positive excitation and the response signal during negative excitation of the magnetic core. The effective data sequence at a fixed position after the rising or falling edge is extracted for data localization. Figure 7 A voltage sampling waveform diagram provided for an embodiment of this application, such as Figure 3 As shown, the valid data corresponding to the rising edge has a data length of N1, and the area within the black arrow represents the valid data corresponding to the falling edge, with a data length of N2. The average value of segment N1 can be selected as the valid voltage data, or the median value can be selected, depending on the actual needs. Each excitation square wave cycle outputs two valid voltage data points: the valid voltage at the rising edge and the valid voltage at the falling edge. A valid data sequence is generated based on the corresponding time order.

[0067] Step S13 obtains the residual current feature value sequence based on the valid data sequence. Step S14 fits the residual current feature value sequence at different temperatures to obtain the residual current feature value curve. The residual current feature value curve is the feature value curve of the residual current at different temperatures.

[0068] Step S15 obtains the temperature linearity data of the current residual current transformer as a function of time, that is, the temperature linearity data based on the characteristics of the magnetic core of the current residual current transformer itself. In this embodiment, ferrite is used as the magnetic core. When the signal passes through the nonlinear region, the permeability changes. When the excitation amplitude changes with time, the permeability can be regarded as a time-varying parameter μ(t). At this time, the induced signal of the coil can be expressed as:

[0069]

[0070] The above formula is the formula for the induction of a coil in the nonlinear region at room temperature. E is the induced electromotive force, which is the induced electromotive force generated by the change of magnetic flux. Since the permeability is affected by temperature, a temperature coefficient is introduced.

[0071] The temperature coefficient is defined based on the assumption that permeability has a linear relationship with temperature. Between two given temperatures, the relative change in permeability divided by the temperature difference that caused this change is the temperature coefficient of permeability, denoted by α. μi express:

[0072]

[0073] μ t1 The initial permeability of T1 at the reference temperature; μ i2 : Initial permeability of T2 at the reference temperature.

[0074] The permeability is affected by temperature:

[0075] μ i2 =α μi *(T2-T1)*μ i1 +μ i1

[0076] μ i2 At the reference temperature T2, the change in permeability with varying excitation over time is:

[0077] μ i (t)=a μi *(T2-T1)*μ(t)+μ(t)=(α μi *(T2-T1)+1)*μ(t)

[0078] The permeability increases with increasing temperature, which speeds up the time it takes for the excitation to reach saturation. Therefore, the relationship between permeability and the initial permeability μ is evident. (t) It does indeed show a linear relationship.

[0079] Temperature measurement method: Based on the linear change in the time it takes for the excitation to reach the saturation region due to the influence of temperature on magnetic permeability, a base temperature T is first established. i The time to reach saturation is measured as follows: Figure 4 As shown, the time interval from t1 to t2 is t i Therefore, the temperature measurement equation, i.e., the above linear temperature data, is:

[0080]

[0081] T is the measured temperature value, and t is the time it takes for the temperature at temperature T to reach the saturation region from the lowest point.

[0082] Step S16: Obtain the residual current compensation characteristic curve based on the residual current characteristic curve and the temperature linear data. Assume that the residual current characteristic curve at temperature T is X(T), and compensate the characteristic value based on the estimated temperature.

[0083]

[0084] At this time Y T It is the residual current compensation characteristic curve at temperature T.

[0085] Figure 5This is a schematic diagram of residual current compensation characteristic value curves at different temperatures, provided for an embodiment of this application.

[0086] The residual current detection method provided in this embodiment applies a square wave excitation signal to the residual current transformer; acquires the effective voltage data at the rising and falling edges, and generates an effective data sequence according to the corresponding time sequence; obtains a residual current characteristic value sequence based on the effective data sequence; fits the residual current characteristic value sequences at different temperatures to obtain a residual current characteristic value curve; acquires the temperature linearity data of the current residual current transformer as a function of time; and obtains a residual current compensation characteristic value curve based on the residual current characteristic value curve and the temperature linearity data. In this embodiment, when detecting DC residual current, the residual current characteristic curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linearity data of the residual current transformer to obtain the residual current compensation characteristic value curve. Based on the residual current compensation characteristic value curve, the characteristic value of the temperature-compensated residual current can be obtained. This application considers the influence of temperature on detection, thus improving the accuracy of detection.

[0087] According to the above embodiments, this embodiment provides a preferred solution, wherein obtaining the effective voltage data of the rising and falling edges and generating an effective data sequence according to the corresponding time order includes:

[0088] The voltage data of the rising and falling edges of each cycle are obtained according to the preset sampling time interval;

[0089] The average voltage at the rising edge and the average voltage at the falling edge of each cycle are obtained based on the voltage data.

[0090] The average voltage at the rising edge and the average voltage at the falling edge are arranged in chronological order to generate a valid data sequence.

[0091] like Figure 7 As shown, the effective voltage data corresponding to the rising edge has a data length of N1, and the effective voltage data corresponding to the falling edge has a data length of N2.

[0092]

[0093] That is, N1 data points are obtained from the effective voltage data corresponding to the rising edge, which are used as the rising edge voltage data of the current cycle, and N2 data points are obtained from the effective voltage data corresponding to the falling edge, which are used as the falling edge voltage data of the current cycle.

[0094] Calculate the mean of the rising edge voltage data and the mean of the falling edge voltage data respectively. Based on the first formula and the voltage data, obtain the mean rising edge voltage and the mean falling edge voltage for each cycle respectively.

[0095] The first formula is:

[0096] in, This represents the voltage data at the rising or falling edge of one cycle; N is the number of samples.

[0097] Through formula Calculate the average voltage over the rising edge using the formula. Calculate the average voltage over the falling edge.

[0098] In this embodiment, the mean of the valid data within the interval of rising or falling edges is used as the valid data sequence to improve the accuracy of the sampled data.

[0099] In addition, this embodiment provides a preferred solution, wherein step S13, obtaining the residual current characteristic value sequence based on the effective data sequence, includes:

[0100] The effective data difference sequence is obtained based on the effective data sequence;

[0101] The residual current characteristic value sequence is obtained by inverting the odd-numbered terms of the effective data difference sequence.

[0102] Based on the effective data sequence, an effective data difference sequence is obtained, and the effective data sequence is then subjected to difference processing. Difference, also known as a difference function or difference operation, reflects a change between discrete quantities. The odd-numbered terms of the effective data difference sequence are inverted to obtain the residual current characteristic value sequence, and the values ​​of the sequence are modulated to positive numbers for ease of calculation.

[0103] Preferably, applying a square wave excitation signal to the residual current transformer includes:

[0104] The square wave excitation signal is applied to the residual current transformer through the H-bridge drive circuit.

[0105] An H-bridge is a relatively simple circuit, typically containing four independently controlled switching components (such as MOSFETs). These are commonly used to drive high-current loads, such as motors. An H-bridge can reverse the voltage / current across its connected load or output terminals. H-bridge control is mainly divided into approximate square wave control, pulse width modulation (PWM), and cascaded multilevel control. Approximate square wave control, or quasi-square-wave control, adds a zero-level to the output waveform compared to an alternating positive and negative square wave, significantly reducing harmonics and approximating a square wave excitation signal.

[0106] When the residual current compensation characteristic curve of the current residual current transformer is obtained, the residual current can be detected. After obtaining the residual current compensation characteristic curve based on the residual current characteristic curve and the temperature linearity data, the process further includes:

[0107] Based on the base temperature and time, and combined with the residual current compensation characteristic value curve, the current compensation characteristic value is obtained.

[0108] The current temperature can be obtained based on the current time and the base temperature. Then, the corresponding residual current compensation characteristic value curve is selected based on the current temperature to obtain the current compensation characteristic value. The compensation characteristic value obtained at this time takes into account the influence of temperature changes, which improves the accuracy of detection.

[0109] The process of obtaining the current compensation characteristic value based on the base temperature and time, combined with the residual current compensation characteristic value curve, further includes:

[0110] Determine whether the current compensation feature value exceeds the feature value threshold;

[0111] If so, issue an alarm indicating that the current residual current is too high.

[0112] By determining whether the current compensation characteristic value exceeds the characteristic value threshold, an alarm indicating that the current residual current is too high is issued. If this residual current transformer is a component of a residual current protection circuit breaker, it can control the electronic equipment to disconnect to protect the equipment.

[0113] In the above embodiments, the residual current detection method has been described in detail. This application also provides embodiments corresponding to the residual current detection device. It should be noted that this application describes the embodiments of the device part from two perspectives: one is based on the functional module, and the other is based on the hardware.

[0114] Figure 6 This is a schematic diagram of a residual current detection device provided in an embodiment of this application, as shown below. Figure 6 As shown, it includes:

[0115] Excitation module 21 is used to apply a square wave excitation signal to the residual current transformer;

[0116] The data acquisition module 22 is used to acquire the effective voltage data of the rising and falling edges and generate an effective data sequence according to the corresponding time order.

[0117] The feature value sequence generation module 23 is used to obtain the residual current feature value sequence based on the effective data sequence;

[0118] The fitting module 24 is used to fit the residual current characteristic value sequence at different temperatures to obtain the residual current characteristic value curve;

[0119] Temperature data acquisition module 25 is used to acquire linear temperature data of the current residual current transformer as the temperature changes over time.

[0120] Compensation module 26 is used to obtain the residual current compensation characteristic curve based on the residual current characteristic curve and the temperature linear data.

[0121] In this embodiment, the excitation module 21 applies a square wave excitation signal to the residual current transformer; the data acquisition module 22 acquires the effective voltage data at the rising and falling edges and generates an effective data sequence according to the corresponding time sequence; the feature value sequence generation module 23 obtains the residual current feature value sequence based on the effective data sequence; the fitting module 24 fits the residual current feature value sequence at different temperatures to obtain the residual current feature value curve; the temperature data acquisition module 25 acquires the temperature linear data of the current residual current transformer as a function of time; and the compensation module 26 obtains the residual current compensation feature value curve based on the residual current feature value curve and the temperature linear data. In this embodiment, when detecting DC residual current, the residual current feature curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linear data of the residual current transformer to obtain the residual current compensation feature value curve. Based on the residual current compensation feature value curve, the feature value of the temperature-compensated residual current can be obtained. This application considers the influence of temperature on detection and improves the accuracy of detection.

[0122] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0123] Figure 7 A structural diagram of another residual current detection device provided in the embodiments of this application is shown below. Figure 7 As shown, the residual current detection device includes: a memory 30 for storing computer programs;

[0124] The processor 31 is used to execute a computer program to implement the steps of the method for obtaining user operation habit information as described in the above embodiment (residual current detection method).

[0125] The residual current detection device provided in this embodiment may include, but is not limited to, smartphones, tablets, laptops, or desktop computers.

[0126] The processor 31 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 31 may be implemented using at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 31 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 31 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 31 may also include an Artificial Intelligence (AI) processor, which handles computational operations related to machine learning.

[0127] The memory 30 may include one or more computer-readable storage media, which may be non-transitory. The memory 30 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 30 is used to store at least the following computer program 301, which, after being loaded and executed by the processor 31, is capable of implementing the relevant steps of the residual current detection method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 30 may also include an operating system 302 and data 303, and the storage method may be temporary or permanent storage. The operating system 302 may include Windows, Unix, Linux, etc. The data 303 may include, but is not limited to, data involved in implementing the residual current detection method.

[0128] In some embodiments, the residual current detection device may further include a display screen 32, an input / output interface 33, a communication interface 34, a power supply 35, and a communication bus 36.

[0129] Those skilled in the art will understand that Figure 7 The structure shown does not constitute a limitation on the residual current detection device and may include more or fewer components than shown.

[0130] The residual current detection device provided in this application includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the following method: a residual current detection method, which involves applying a square wave excitation signal to a residual current transformer; acquiring effective voltage data at the rising and falling edges, and generating an effective data sequence according to the corresponding time sequence; obtaining a residual current characteristic value sequence based on the effective data sequence; fitting the residual current characteristic value sequence at different temperatures to obtain a residual current characteristic value curve; acquiring temperature linearity data of the current residual current transformer's temperature changing over time; and obtaining a residual current compensation characteristic value curve based on the residual current characteristic value curve and the temperature linearity data. In this embodiment, when detecting DC residual current, the residual current characteristic curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linearity data of the residual current transformer to obtain the residual current compensation characteristic value curve. Based on the residual current compensation characteristic value curve, the characteristic value of the temperature-compensated residual current can be obtained. This application considers the influence of temperature on detection, thus improving the accuracy of detection.

[0131] Finally, this application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above-described residual current detection method embodiment (which may be a method corresponding to the server side, a method corresponding to the diagnostic device side, or a method corresponding to both the server side and the diagnostic device side).

[0132] It is understood that if the methods in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0133] The computer-readable storage medium provided in this embodiment stores a computer program. When the processor executes the program, it can implement the following method: a residual current detection method, which involves applying a square wave excitation signal to a residual current transformer; acquiring effective voltage data at the rising and falling edges, and generating an effective data sequence according to the corresponding time sequence; obtaining a residual current characteristic value sequence based on the effective data sequence; fitting the residual current characteristic value sequence at different temperatures to obtain a residual current characteristic value curve; acquiring temperature linearity data of the current residual current transformer's temperature change over time; and obtaining a residual current compensation characteristic value curve based on the residual current characteristic value curve and the temperature linearity data. In this embodiment, when detecting DC residual current, the residual current characteristic curves of the residual current transformer at different temperatures are obtained in advance, and then combined with the temperature linearity data of the residual current transformer to obtain the residual current compensation characteristic value curve. Based on the residual current compensation characteristic value curve, the characteristic value of the temperature-compensated residual current can be obtained. This application considers the influence of temperature on detection, thus improving the accuracy of detection.

[0134] The residual current detection method, apparatus, and medium provided in this application have been described in detail above. The various embodiments in the 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 the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0135] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A residual current detection method characterized by, The method comprises the following steps: applying a square wave excitation signal to a residual current transformer; obtaining effective voltage data of rising and falling edges, and generating an effective data sequence according to a corresponding time sequence; obtaining a residual current characteristic value sequence according to the effective data sequence; fitting the residual current characteristic value sequences at different temperatures to obtain a residual current characteristic value curve; obtaining temperature linear data of a current residual current transformer temperature change over time; When the excitation signal varies with time, the change in magnetic permeability is calculated, and the expression for the change in magnetic permeability is μ i (t) = α μi *(T2-T1)*μ(t) + μ(t) = (α μi *(T2-T1) + 1)*μ(t); where α μi is the temperature coefficient of the magnetic permeability; α μi has the expression ; T2 > T1; μ i1 is the initial magnetic permeability at the reference temperature T1; μ i2 is the initial magnetic permeability at the reference temperature T2. According to the influence of the magnetic permeability on the temperature, the timeline of the excitation reaching the saturation region linearly changes, a basic temperature Ti is first set up, the time of reaching the saturation region is measured, and the time of t1~t2 is ti: the temperature linear data is expressed as: ; wherein T is the measured temperature value, t is the time of reaching the saturation region from the lowest point at T temperature; According to the residual current characteristic value curve and the temperature linear data, a residual current compensation characteristic value curve is obtained; the compensation method of the residual current compensation characteristic value curve includes: the residual current compensation characteristic value curve Y T is expressed as Y T =X(T)*T; wherein, X(T) is a residual current characteristic value curve at T temperature.

2. The residual current detection method according to claim 1, characterized in that, the step of obtaining effective voltage data of rising and falling edges, and generating an effective data sequence according to a corresponding time sequence, comprises the following steps: obtaining voltage data of rising and falling edges of each period according to a preset sampling time interval; obtaining rising edge voltage mean and falling edge voltage mean of each period according to the voltage data; arranging the rising edge voltage mean and the falling edge voltage mean according to a time sequence to generate an effective data sequence.

3. The residual current detection method according to claim 1, characterized in that, the step of obtaining a residual current characteristic value sequence according to the effective data sequence, comprises the following steps: obtaining an effective data difference sequence according to the effective data sequence; obtaining the residual current characteristic value sequence by taking the opposite of the odd items of the effective data difference sequence.

4. The residual current detection method according to claim 1, characterized in that, the step of applying a square wave excitation signal to a residual current transformer, comprises the following steps: applying the square wave excitation signal to the residual current transformer through an H-bridge driving circuit.

5. The residual current detection method according to claim 2, characterized in that, after obtaining a residual current compensation characteristic value curve according to the residual current characteristic value curve and the temperature linear data, the method further comprises the following steps: obtaining a current compensation characteristic value according to a base temperature and time in combination with the residual current compensation characteristic value curve.

6. The residual current detection method according to claim 5, characterized in that, after obtaining a current compensation characteristic value according to a base temperature and time in combination with the residual current compensation characteristic value curve, the method further comprises the following steps: determining whether the current compensation characteristic value exceeds a characteristic value threshold; if yes, issuing an alarm representing that the current residual current is too large.

7. A residual current detection apparatus adapted to the residual current detection method according to any one of claims 1 to 6, characterized in that, The method comprises the following steps: an excitation module for applying a square wave excitation signal to a residual current transformer; an acquisition data module for obtaining effective voltage data of rising and falling edges, and generating an effective data sequence according to a corresponding time sequence; a characteristic value sequence generation module for obtaining a residual current characteristic value sequence according to the effective data sequence; a fitting module for fitting the residual current characteristic value sequences at different temperatures to obtain a residual current characteristic value curve; a temperature data acquisition module for obtaining temperature linear data of a current residual current transformer temperature change over time; a compensation module for obtaining a residual current compensation characteristic value curve according to the residual current characteristic value curve and the temperature linear data.

8. A residual current detection device, characterized by The method comprises the following steps: a memory for storing a computer program; a processor for executing the computer program to implement the steps of the residual current detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the residual current detection method according to any one of claims 1 to 6.

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