Static current detection method, device and equipment of electric energy meter and medium

Abstract

The invention discloses a quiescent current detection method, device and equipment of an electric energy meter and a medium, and relates to the technical field of electrical equipment quality detection. The detection method comprises the following steps: carrying out high-speed sampling on the quiescent current of the electric energy meter to obtain a quiescent current sampling signal; performing low-pass digital filtering processing on the quiescent current sampling signal to obtain a first signal; performing median average filtering processing on the first signal to obtain a second signal; comparing the arithmetic average value of the second signal with a quiescent current threshold value to obtain a first comparison result; comparing the proportion of the number of sampling points exceeding the quiescent current threshold value in the first signal with an over-limit rate threshold value to obtain a second comparison result; and judging whether the electric energy meter is qualified according to the first comparison result and the second comparison result. According to the invention, a plurality of digital filtering algorithms are used to process the sampling signal, and the quiescent current of the electric energy meter is comprehensively judged by multiple parameters, so that the accuracy of the detection result is improved, and misjudgment and missed judgment are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical equipment quality detection, and in particular to a static current detection method, device, equipment and medium for an electric energy meter. Background Art

[0002] With the country's vigorous promotion of smart grids, the smart electricity meters currently installed on site have gradually exposed various problems. Among them, battery failure is relatively serious, manifested as no battery power and low voltage, which leads to the disorder of the internal clock of the electricity meter, resulting in serious problems such as inability to recharge and disorder of frozen data time scale.

[0003] The static current of the energy meter has become an important indicator to measure the quality of the energy meter. When the energy meter is in sleep mode, excessive static current will consume battery power faster and shorten the service life of the energy meter. The current energy meter static current detection device mostly uses the extreme value or average value of multiple sampling as the basis for judging the detection result. However, due to the noise interference introduced by the sampling circuit and the periodic pulse signal generated by the internal chip of the energy meter, the actual sampling signal waveform is relatively complex. The judgment condition of this detection method is single, and problems such as misjudgment and missed judgment may occur in the actual detection process. Summary of the invention

[0004] The present invention provides a static current detection method, device, equipment and medium for an electric energy meter, so as to solve the problem that the existing method for detecting the static current of the electric energy meter is prone to misjudgment and missed judgment.

[0005] The present invention is achieved through the following technical solutions:

[0006] A first aspect of the present invention provides a static current detection method for an electric energy meter, comprising:

[0007] Perform high-speed sampling on the static current of the electric energy meter to obtain a static current sampling signal;

[0008] Performing low-pass digital filtering on the static current sampling signal to obtain a first signal;

[0009] Performing median average filtering on the first signal to obtain a second signal;

[0010] Comparing the arithmetic mean of the second signal with a static current threshold to obtain a first comparison result;

[0011] Compare the proportion of the number of sampling points exceeding the static current threshold in the first signal with the over-limit rate threshold to obtain a second comparison result;

[0012] If the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, it is judged to be qualified, otherwise it is unqualified.

[0013] The present invention aims at the problem that the existing extreme value or mean value detection of static current of an electric energy meter based on multiple sampling has a single judgment condition, and a lot of noise interference is introduced into the sampling signal, resulting in inaccurate judgment results, easy misjudgment and missed judgment. The present invention removes most of the noise interference introduced by the sampling circuit and the periodic pulse signal interference generated by the operation of the internal chip of the electric energy meter through ADC high-speed sampling, low-pass filtering and median filtering, improves the quality of the sampling signal, makes it more truly reflect the actual static current situation, thereby improving the accuracy of the judgment result, and makes a comprehensive judgment based on the static current threshold judgment combined with the over-limit rate, so as to avoid the problem of missed judgment caused by filtering out some abnormal values ​​by the median filtering.

[0014] In some implementations, the low-pass digital filtering process is:

[0015] Y n =a×X n +(1-a)×Y n-1

[0016] Among them, X n Indicates the static current sampling signal of the current detection time, Y n-1 Represents the first signal after low-pass filtering at the last detection time, Y n Indicates the first signal after low-pass filtering at the current detection time. a is the filter coefficient, and its value range is 0 to 1.

[0017] In some implementations, the filter coefficient is:

[0018]

[0019] Among them, f H is the cut-off frequency of the low-pass filter, and f is the sampling frequency.

[0020] In some implementations, the median average filtering process is:

[0021] Step 1, in the first signal, selecting a window of fixed length starting from the first sampling point;

[0022] Step 2, remove the maximum and minimum values ​​in the current window, calculate the arithmetic mean of the remaining sampling points, and obtain the filtered value of the current window;

[0023] Step 3: gradually move the window backward in the first signal, and repeat steps 2 to 3 until all sampling points are processed.

[0024] In some implementations, the exceeding rate threshold is between 0.1 and 0.2.

[0025] A second aspect of the present invention provides a static current detection device for an electric energy meter, comprising:

[0026] A high-speed sampling module is used to perform high-speed sampling on the static current of the electric energy meter to obtain a static current sampling signal;

[0027] A low-pass digital filtering module, used for performing low-pass digital filtering on the static current sampling signal to obtain a first signal;

[0028] A median average filtering module, used for performing median average filtering on the first signal to obtain a second signal;

[0029] A first comparison module, configured to compare the arithmetic mean of the second signal with a static current threshold to obtain a first comparison result;

[0030] A second comparison module is used to compare the proportion of the number of sampling points exceeding the static current threshold in the first signal with the over-limit rate threshold to obtain a second comparison result;

[0031] A determination module is used to determine that the signal is qualified if the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, otherwise it is determined to be unqualified.

[0032] In some implementations, the high-speed sampling module is an ADC high-speed sampling chip.

[0033] In some embodiments, the over-limit threshold is 0.1 to 0.2.

[0034] A third aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the static current detection method of the electric energy meter as described in any one of the first aspects of the present invention when executing the computer program.

[0035] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the static current detection method of an electric energy meter as described in any one of the first aspects of the present invention.

[0036] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0037] Compared with the single parameter electric energy meter static current detection method using sampling extreme value or mean value, the present invention uses a variety of digital filtering algorithms to process the sampling signal, reduces the influence of noise interference on the determination of the detection result, and improves the accuracy of the detection.

[0038] The static current sampling signal is comprehensively judged with multiple parameters, which reduces the influence of the periodic pulse signal generated by the internal chip of the meter on the judgment of the detection result, greatly reduces the possibility of misjudgment and missed judgment, and improves the scientificity and rationality of the detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0040] Figure 1 is a flow chart of a static current detection method of an electric energy meter according to an embodiment of the present invention;

[0041] Figure 2 is a diagram of simulation results of low-pass filtering waveforms with different cut-off frequencies according to an embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of a median average filtering process according to an embodiment of the present invention;

[0043] Figure 4 This is a simulation result diagram of a median average filtering waveform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0045] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to or inherent to other steps or units of the device.

[0046] The terms used in the various embodiments of the application are only used to describe the purpose of specific embodiments and are not intended to limit the various embodiments of the application. As used herein, the singular form is intended to also include the plural form, unless the context clearly indicates otherwise. Unless otherwise limited, all terms used here (including technical terms and scientific terms) have the same meaning as the meanings commonly understood by ordinary technicians in the field of the various embodiments of the application. The terms (such as the terms defined in the dictionary generally used) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning, unless clearly defined in the various embodiments of the application.

[0047] The embodiments of the present invention provide a static current detection method, device, equipment and medium for an electric energy meter, which are suitable for quality detection of an electric energy meter. By using a variety of digital filtering algorithms to process the sampling signals and making a comprehensive judgment on the static current of the electric energy meter with multiple parameters, the entire detection process is made more scientific and accurate, and more in line with actual working conditions, which is beneficial to improving the accuracy of the detection results and reducing missed judgments.

[0048] like Figure 1 As shown, Figure 1 It is a flow chart of a static current detection method of an electric energy meter provided by an embodiment of the present invention, which includes the following steps.

[0049] S1, performs high-speed sampling on the static current of the electric energy meter to obtain a static current sampling signal.

[0050] S2, performing low-pass digital filtering on the static current sampling signal to obtain a first signal.

[0051] S3, performing median average filtering processing on the first signal to obtain a second signal.

[0052] S4, comparing the arithmetic mean of the second signal with the static current threshold to obtain a first comparison result.

[0053] S5, comparing the proportion of the number of sampling points exceeding the static current threshold in the first signal with the exceeding rate threshold to obtain a second comparison result.

[0054] S6, judging whether the quality of the electric energy meter is qualified according to the first comparison result and the second comparison result.

[0055] Specifically, if the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, it is determined to be qualified, otherwise it is unqualified.

[0056] In the above scheme, step S1 can sample the electric energy meter to be detected through the ADC high-speed sampling chip to obtain a high-quality sampling signal, so as to improve the accuracy of subsequent processing. Step S2 can connect the ADC high-speed sampling chip through a low-pass digital filter to perform low-pass filtering on the static current sampling signal to filter out high-frequency noise interference. Step S3 can connect the low-pass digital filter to the low-pass digital filter through the median average filter, and then perform median average filtering on the signal to eliminate the sampling value deviation caused by pulse interference. Thus, the two main interferences in the static current sampling signal, the noise signal introduced by the sampling circuit and the periodic pulse signal generated by the internal chip of the electric energy meter, are filtered out. Finally, the result of the static current threshold determination in step S4 is made more accurate. Combined with the over-limit rate determination of the signal before the median average filtering, it is determined whether the proportion of the sampling points exceeding the current threshold after the low-pass digital filtering algorithm exceeds the threshold in the total sampling points, so as to avoid the arithmetic mean value of the second signal decreasing due to the filtering of some abnormal values ​​with higher values ​​due to the median average filtering, and there is a situation of missed judgment. When the over-limit rate is high, it is very likely to cause missed judgment in step S4. Therefore, through comprehensive judgment, if both parameters do not exceed the threshold, it is judged as qualified; if any parameter exceeds the threshold or both parameters exceed the threshold, it is judged as unqualified, further reducing misjudgment and missed judgment.

[0057] In some embodiments of the present invention, the static current detection of the electric energy meter is a continuous detection within a period of time. During the detection time, multiple detections are performed based on the real-time collected data, and whether the electric energy meter is qualified is judged based on the continuously output detection results. If the detection time is T and the number of detections is t, then a static current sampling signal of T / t duration is collected each time, and a detection is performed based on the static current sampling signal collected this time, and the qualified / unqualified results of t detections are obtained. The quality of the electric energy meter is judged based on the t detection results. If all t detections are qualified, the quality of the electric energy meter is qualified and can be put into use.

[0058] The detection method of the present invention can be used for pre-shipment detection and can also be used for online detection of electric energy meters in use. During the detection, the electric energy meter can be placed in a dormant state.

[0059] The static current of the electric energy meter is the working current generated by the internal battery of the meter to power the clock chip and some important modules when the electric energy meter is in a dormant state. This current is a small current, and the value is usually only a few microamperes to tens of microamperes. In hardware, an amplifier circuit is required to amplify the signal before sampling, and noise interference will be introduced during the period. In addition, the battery of the meter is powered by direct current, and its current changes relatively slowly. Therefore, a low-pass digital filtering algorithm is used in this embodiment to filter out high-frequency noise interference in the sampled signal. The low-pass digital filtering method is a method of simulating the hardware filtering function through a software algorithm. It allows the low-frequency components in the input signal to pass through, while removing the high-frequency components. The algorithm can conveniently realize the storage of data through a ring queue structure, and can simulate the differential equation of the hardware RC low-pass filter through a differential equation, so as to process the digital signal with a software algorithm.

[0060] In some implementations of the present invention, the following low-pass digital filtering algorithm is used to filter out high-frequency noise interference in the sampled signal.

[0061] Y n =a×X n +(1-a)×Y n-1

[0062] Among them, X n Indicates the static current sampling signal of the current detection time, Y n-1 Represents the first signal after low-pass filtering at the last detection time, Y n Indicates the first signal after low-pass filtering at the current detection time. a is the filter coefficient, and its value range is 0 to 1.

[0063] The smaller the value of the filter coefficient a is, the smaller the current input weight is, the smoother the output waveform is, but the response sensitivity is reduced. Preferably, in order to balance the smoothness and response sensitivity, the filter coefficient a is determined according to the following formula.

[0064]

[0065] Among them, f H is the cut-off frequency of the low-pass filter, and f is the sampling frequency.

[0066] When the sampling frequency f is fixed, the cutoff frequency f H The larger the value of the filter coefficient a is, the greater the weight of the current input static current sampling signal is, and the better the tracking effect between the calculated output and the actual output is, that is, the better the dynamic response is, and the smaller the impact of amplitude attenuation is. HThe smaller it is, the smaller the value of the filter coefficient a is, and the smaller the weight of the current input static current sampling signal is, so the calculated output signal is smoother, and the filtering effect of noise interference and harmonics is better, but the dynamic response becomes worse, and a certain degree of amplitude attenuation will occur. It can be understood that the above calculation formula is intended to represent the value of the filter coefficient a. In actual application, a may not use the actual value of the calculation result. In order to facilitate data processing, a is taken as a value approximately equal to the calculation result, which can also be expressed as

[0067] like Figure 2 The low-pass filter waveform simulation results of different cutoff frequencies (1Hz, 5Hz, 50Hz, 500Hz) are shown in the figure. In the figure, the green curve is the static current sampling signal containing noise, the blue curve is the standard sine signal, and the red curve is the calculated output of the sampling signal after passing through the first-order low-pass filter. It can be found that when the cutoff frequency is small, the output signal amplitude attenuates significantly and there is a certain lag; as the cutoff frequency increases, the tracking effect of the standard sine signal is better; when the cutoff frequency is too large, the sampling signal can be almost completely reproduced, but the filtering effect of the noise becomes worse.

[0068] The static current sampling signal of the electric energy meter presents obvious periodic characteristics due to the operation of the internal chip of the meter. In a single-phase meter, the amplitude fluctuation of this periodic signal is small, and the impact on the detection and judgment is small. In a three-phase meter, the amplitude fluctuation of this periodic signal is large, showing obvious low-frequency pulse characteristics, and its amplitude can even reach hundreds of times the normal static working current. However, due to its low frequency of occurrence and narrow pulse width, it will not have much impact on the battery life and belongs to a normal working state. Therefore, the present invention adopts the median average filtering algorithm to eliminate the interference of the pulse signal on the sampling value.

[0069] The median average filtering method, also known as the anti-pulse interference average filtering method, is a commonly used digital signal processing technology. It combines the advantages of median filtering and arithmetic mean filtering. It has both the robustness of median filtering and the smoothness of average filtering. It can effectively filter out accidental pulse interference while maintaining data stability.

[0070] In some embodiments of the present invention, see Figure 3 The schematic diagram of the median average filtering process shown is a schematic diagram of the median average filtering process, and the median average filtering process includes the following steps.

[0071] S3-1, in the original signal (ie, the first signal), a window of fixed length is selected starting from the first sampling point.

[0072] If the first signal Y nThere are a total of N sampling points, where n = 1, 2, …… N. The window length is P, and P < N. Then the selected window includes the first P sampling points of the signal Y. n The 1st to Pth sampling points in it, and P is generally taken as an odd number.

[0073] S3-2. Remove the maximum and minimum values in the current window, and calculate the arithmetic mean of the remaining sampling points to obtain the filtered value of the current window.

[0074] In this step, one maximum value and one minimum value are removed from the P sampling points in the window. Then there are P - 2 remaining sampling points. The average value of the remaining sampling points is used as the filtered value of the current window. The main purpose is to remove pulse interference and maintain the stability of the data through arithmetic mean filtering.

[0075] S3-3. Move the window step by step backward in the original signal, and repeat steps S3-2 to S3-3 until all sampling points are processed.

[0076] In this step, the window is moved in the first signal Y n according to a predetermined step size. The length of the window remains fixed. The step size can be set as an integer from 1 to P, that is, each time the window moves backward by 1 to P sampling points. The more overlapping sampling points there are between two adjacent windows, the better the robustness of the filtered data. Finally, according to the filtering order of each window, the filtered values are sequentially combined to obtain the signal after median mean filtering, that is, the second signal.

[0077] In some embodiments of the present invention, multiple maximum and minimum values can be removed in step S3-2 to deal with the situation of multiple pulse signals in one window.

[0078] Such as Figure 4 the simulation result graph of the median mean filtering waveform shown. In the figure, the blue curve is the data before median mean filtering, and the red curve is the data after median mean filtering. It can be seen from the figure that there are two outliers in the original data, and the median mean filtering algorithm can effectively filter out the pulse interference caused by such outliers.

[0079] In some embodiments of the present invention, the average limit value of the static current of the electric energy meter is used as the static current threshold.

[0080] The relevant specifications of the electric energy meter clearly require the capacity and minimum service life of the internal battery of the meter. From this, the average limit value of the static current of the electric energy meter can be calculated and used as the current threshold for static current detection. The sampling points processed by the digital filtering algorithm are applied with the median mean filtering algorithm again. All sampling points are selected as the calculation window. After removing multiple maximum and minimum values, the arithmetic mean is obtained as parameter 1 and compared with the current threshold.

[0081] Due to factors such as welding processing and differences in components, some meters consume a lot of power. There may be multiple large abnormal values ​​in the sampling signal, which seriously affects the battery life and should be judged as static overcurrent. However, since the use of the median average filtering algorithm will filter out some abnormal values, it may cause the problem meter to miss the judgment. Therefore, this embodiment introduces the over-limit rate as parameter 2 for auxiliary judgment. The over-limit rate is defined as the proportion of sampling points that exceed the current threshold after the low-pass digital filtering algorithm in the total sampling points, which is used as parameter 2 for comparison with the over-limit rate threshold.

[0082] In some implementations of the present invention, the threshold value of the over-limit rate is set at 0.1 to 0.2. The threshold value of the over-limit rate is set according to the actual sampling frequency and the number of sampling points, and generally ranges from 0.1 to 0.2.

[0083] In response to the need to quickly, accurately and effectively screen out defective meters with excessive static power consumption in the quality inspection of smart electric energy meters, the present invention processes the sampled signals using a variety of digital filtering algorithms, and completes the detection of the static current of the smart electric energy meter with a comprehensive judgment of multiple parameters. The final detection result uses the sampling average value after median average filtering as parameter 1 and the over-limit rate after low-pass digital filtering as parameter 2, which are compared with their respective corresponding thresholds for comprehensive judgment. If both parameters do not exceed the threshold, it is judged as qualified; if any parameter exceeds the threshold or both parameters exceed the threshold, it is judged as unqualified.

[0084] An embodiment of the present invention further provides a static current detection device for an electric energy meter, comprising:

[0085] ADC high-speed sampling module, used for high-speed sampling of the static current of the electric energy meter to obtain a static current sampling signal;

[0086] A low-pass digital filtering module, used for performing low-pass digital filtering on the static current sampling signal to obtain a first signal;

[0087] A median average filtering module is used to perform median average filtering on the first signal to obtain a second signal

[0088] A first comparison module, configured to compare the arithmetic mean of the second signal with a static current threshold to obtain a first comparison result;

[0089] A second comparison module is used to compare the proportion of the number of sampling points exceeding the static current threshold in the first signal with the over-limit rate threshold to obtain a second comparison result;

[0090] A determination module is used to determine that the signal is qualified if the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, otherwise it is determined to be unqualified.

[0091] In some implementations of the present invention, the high-speed sampling module is an ADC high-speed sampling chip.

[0092] In some embodiments of the present invention, the processing algorithm of the low-pass digital filtering module is:

[0093] Y n =a×X n +(1-a)×Y n-1

[0094] Among them, X n Indicates the static current sampling signal of the current detection time, Y n-1 Represents the first signal after low-pass filtering at the last detection time, Y n Indicates the first signal after low-pass filtering at the current detection time. a is the filter coefficient, and its value range is 0 to 1.

[0095] In some implementations of the present invention, the filter coefficient is:

[0096]

[0097] Among them, f H is the cut-off frequency of the low-pass filter, and f is the sampling frequency.

[0098] In some embodiments of the present invention, the specific processing performed in the median average filtering module is:

[0099] Step 1, in the first signal, selecting a window of fixed length starting from the first sampling point;

[0100] Step 2, remove the maximum and minimum values ​​in the current window, calculate the arithmetic mean of the remaining sampling points, and obtain the filtered value of the current window;

[0101] Step 3: gradually move the window backward in the first signal, and repeat step 2 until all sampling points are processed.

[0102] In some implementations of the present invention, the exceeding rate threshold is set at 0.1-0.2.

[0103] An embodiment of the present invention also provides an electronic device, which includes a processor, a memory, an input device, an output device and a communication device; the number of processors in the computer device can be one or more; the processor, memory, input device and output device in the electronic device can be connected via a bus or other means.

[0104] The memory is a computer-readable storage medium that can be used to store software programs, computer executable programs, and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory to implement the static current detection method of the electric energy meter of any of the above embodiments of the present invention.

[0105] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0106] The input device may be a barcode scanner for scanning the meter barcode to input meter number information, and the output device may be an LED display for displaying the output test results.

[0107] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the static current detection method of the electric energy meter of any embodiment of the present invention is implemented. The storage medium can be ROM / RAM, a magnetic disk, an optical disk, etc.

[0108] An embodiment of the present invention further provides a computer program product. When the computer program product is run on a computer, the computer executes the static current detection method of the electric energy meter according to any one of the above embodiments of the present invention.

[0109] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A static current detection method for an electric energy meter, characterized in that: include: Perform high-speed sampling on the static current of the electric energy meter to obtain a static current sampling signal; Performing low-pass digital filtering on the static current sampling signal to obtain a first signal; Performing median average filtering on the first signal to obtain a second signal; Comparing the arithmetic mean of the second signal with a static current threshold to obtain a first comparison result; Compare the proportion of the number of sampling points in the first signal that exceed the static current threshold with the over-limit rate threshold to obtain a second comparison result; If the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, it is judged to be qualified, otherwise it is unqualified.

2. The static current detection method of the electric energy meter according to claim 1, characterized in that: The low-pass digital filtering process is: AND n =a×X n +(1-a)×Y n-1 ; Among them, X n Indicates the static current sampling signal of the current detection time, Y n-1 Represents the first signal after low-pass filtering at the last detection time, Y n Indicates the first signal after low-pass filtering at the current detection time. a is the filter coefficient, and its value range is 0 to 1.

3. The static current detection method of the electric energy meter according to claim 2, characterized in that: The filter coefficient is: Among them, f H is the cut-off frequency of the low-pass filter, and f is the sampling frequency.

4. The static current detection method of the electric energy meter according to claim 1, characterized in that: The median average filtering process is as follows: Step 1, in the first signal, selecting a window of fixed length starting from the first sampling point; Step 2, remove the maximum and minimum values ​​in the current window, calculate the arithmetic mean of the remaining sampling points, and obtain the filtered value of the current window; Step 3: gradually move the window backward in the first signal, and repeat steps 2 to 3 until all sampling points are processed.

5. The static current detection method of the electric energy meter according to claim 1, characterized in that: The exceeding rate threshold is between 0.1 and 0.

2.

6. A static current detection device for an electric energy meter, characterized in that: include: A high-speed sampling module is used to perform high-speed sampling on the static current of the electric energy meter to obtain a static current sampling signal; A low-pass digital filtering module, used for performing low-pass digital filtering on the static current sampling signal to obtain a first signal; A median average filtering module, used for performing median average filtering on the first signal to obtain a second signal; A first comparison module, configured to compare the arithmetic mean of the second signal with a static current threshold to obtain a first comparison result; A second comparison module is used to compare the proportion of the number of sampling points exceeding the static current threshold in the first signal with the over-limit rate threshold to obtain a second comparison result; A determination module is used to determine that the signal is qualified if the first comparison result is that the arithmetic mean of the second signal is less than the static current threshold, and the second comparison result is that the proportion of the number of sampling points in the first signal that exceed the static current threshold is less than the excess rate threshold, otherwise it is determined to be unqualified.

7. The static current detection device of the electric energy meter according to claim 6, characterized in that: The high-speed sampling module is an ADC high-speed sampling chip.

8. The static current detection device of the electric energy meter according to claim 6, characterized in that: The over-limit threshold is 0.1 to 0.

2.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the static current detection method of the electric energy meter described in any one of claims 1-5 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the static current detection method of the electric energy meter described in any one of claims 1 to 5 is implemented.

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