Remote electric energy meter fault analysis method based on acquisition terminal

Abstract

The invention relates to the technical field of electric energy meter fault analysis, and discloses a remote electric energy meter fault analysis method based on an acquisition terminal. According to the method, the operation data and the environment data of the electric energy meter are acquired in real time through the acquisition terminal and are transmitted to the data cloud platform in real time through the network, missing data are complemented in the data cloud platform through an interpolation method, the reliability of data processing is improved, and meanwhile, the calculation capability of the data cloud platform is utilized to improve the reliability of data processing. Fault characteristic parameters such as a voltage effective value, a current effective value, a power factor, instantaneous power and harmonic content of the electric energy meter are automatically calculated, then a fault diagnosis algorithm is used to rapidly identify fault types, a detailed fault analysis report is generated in real time, and the report is fed back to operation and maintenance personnel, so that a scientific decision basis is provided for the operation and maintenance personnel. The real-time performance and the accuracy are improved, so that the fault response time is shortened, the reliability of power supply is enhanced, and the power failure risk caused by the fault of the electric energy meter is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meter fault analysis, and in particular to a remote electric energy meter fault analysis method based on a data acquisition terminal. Background Art

[0002] The electric energy meter is an important device used to measure and record electricity consumption. It accurately calculates the user's electricity consumption by monitoring parameters such as current and voltage, and provides a billing basis for power companies. At the same time, the electric energy meter also plays an important role in data collection and monitoring in the power system, helping power management departments to conduct load analysis, fault detection and power dispatching, etc., to ensure the safe and stable operation of the power system.

[0003] Traditional methods of analyzing electric energy meter faults mostly rely on manual inspections and regular maintenance, and are unable to obtain the real-time operating data of electric energy meters in a timely manner. At the same time, the existing technologies have a low level of intelligence in data processing and fault diagnosis, and are unable to effectively handle data missing or abnormal situations, resulting in insufficient accuracy and real-time performance in fault identification. This means that when operation and maintenance personnel face sudden faults, they often lack a timely and effective basis for decision-making, which in turn reduces the reliability of power supply. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the deficiencies in the prior art, the present invention provides a remote electric energy meter fault analysis method based on an acquisition terminal, which acquires the operating data and environmental data of the electric energy meter in real time through the acquisition terminal, including information such as voltage, current, frequency, cumulative power consumption, operating temperature and humidity, and transmits the data to a data cloud platform in real time through the network. In the data cloud platform, the missing data is supplemented by the interpolation method, thereby ensuring the integrity of the data and improving the reliability of data processing. At the same time, the computing power of the data cloud platform is used to automatically calculate the fault characteristic parameters such as the effective value of the voltage, the effective value of the current, the power factor, the instantaneous power and the harmonic content of the electric energy meter, and then the fault diagnosis algorithm is used to quickly identify the fault type and generate a detailed fault analysis report in real time, and the report is fed back to the operation and maintenance personnel, thereby providing them with a scientific decision-making basis. The improvement of this real-time performance and accuracy not only reduces the fault response time, but also enhances the reliability of the power supply, reduces the risk of power outages caused by electric energy meter failures, ensures the stable operation of the power system, and solves the above-mentioned problems.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: a remote electric energy meter fault analysis method based on a data acquisition terminal, comprising the following steps:

[0008] S1. Collect the operation data and operation environment data of the electric energy meter through the collection terminal, including voltage data, current data, frequency, cumulative power consumption data, operation temperature data of the electric energy meter and operation humidity data of the electric energy meter, and transmit them to the data cloud platform in real time through the network for processing;

[0009] S2. If there are any missing data on the operation data and the operation environment data of the electric energy meter collected in the data cloud platform, the data is supplemented by interpolation method;

[0010] S3. The data cloud platform calculates the fault characteristic parameters of the electric energy meter based on the completed operation data of the electric energy meter and the operation environment data of the electric energy meter, including the effective value of the electric energy meter voltage, the effective value of the electric energy meter current, the power factor, the instantaneous power, the harmonic content of the voltage and current, the average operation temperature of the electric energy meter, and the frequency component of the electric energy meter;

[0011] S4. The data cloud platform uses the fault diagnosis algorithm based on the fault characteristic parameters of the electric energy meter to identify the fault type of the electric energy meter and generate a fault analysis report of the electric energy meter;

[0012] S5. The data cloud platform will provide real-time feedback of the electricity meter fault analysis report to the operation and maintenance personnel.

[0013] Preferably, the formula for identifying missing data is as follows:

[0014]

[0015] In the formula, M i Indicates a missing value identifier. When M i =1 indicates that data is missing. i =0 means the data is normal, x i Represents the i-th data point of the operating data of the electric energy meter or the operating environment data of the electric energy meter.

[0016] Preferably, the formula for data completion is as follows:

[0017] x b (i) = x i +[(x i+1 -x i )*(ki)]

[0018] In the formula, x b (i) represents the missing data value to be filled, x i Indicates the previous known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, x i+1 represents the next known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, and ki represents the missing value in x i and x i+1The relative position between them, k represents the index of the missing value data point.

[0019] Preferably, the calculation formula for the effective value of the electric energy meter voltage is as follows:

[0020]

[0021] In the formula, U yx Indicates the effective value of the electric energy meter voltage, U n 2 Represents the square of the voltage value of the electric energy meter at each moment, N represents the total number of voltage sampling points of the electric energy meter, and n represents the index subscript. Represents the voltage value U at each moment n After squaring, take the average and then take the square root to get the effective value of the electricity meter voltage.

[0022] Preferably, the calculation formula of the effective value of the electric energy meter current is as follows:

[0023]

[0024] In the formula, I yx Indicates the effective value of the electric energy meter current, I n 2 It represents the square of the current value of the electric energy meter at each moment, M represents the total number of current sampling points of the electric energy meter, and n represents the index subscript. Represents the current value I at each moment n After squaring, take the average and then take the square root to get the effective value of the electric energy meter current.

[0025] Preferably, the power factor calculation formula is as follows:

[0026]

[0027] In the formula, PF represents power factor, P represents active power, and Q represents apparent power. Indicates the actual power consumed in the energy meter. Indicates that the active power is normalized.

[0028] Preferably, the instantaneous power calculation formula is as follows:

[0029] P(t)=U(t)*I(t)

[0030] In the formula, P(t) represents the instantaneous power of the electric energy meter at time t, U(t) represents the voltage of the electric energy meter at time t, and I(t) represents the current of the electric energy meter at time t.

[0031] Preferably, the calculation formula for the harmonic content of the voltage and current is as follows:

[0032]

[0033] In the formula, H k Indicates the content of the kth harmonic, U n represents the voltage value of the nth sampling point, N represents the total number of sampling points, k represents the number of target harmonics, π represents the period, Represents the cosine component in the voltage and current signals, It represents the sinusoidal component in the voltage and current signals, cos represents the part with zero phase, and the waveform corresponding to k times the frequency is extracted. Xin represents the part related to 90 degrees of phase, and the relative component with k times the frequency is extracted. The square root of the overall formula means that the amplitudes of each frequency component calculated in the plane coordinate system are combined into a total amplitude value.

[0034] Preferably, the calculation formula for the average operating temperature of the electric energy meter is as follows:

[0035]

[0036] In the formula, Tp represents the average operating temperature of the energy meter, Q represents the total number of operating temperature samples of the energy meter, and tp j Indicates the temperature value of the jth electric energy meter temperature sample, j represents the index subscript, It means that all temperature data samples are accumulated and summed, and then divided by the total number of the meter operating temperature samples to obtain the average operating temperature of the meter.

[0037] Preferably, the calculation formula of the frequency component of the electric energy meter is as follows:

[0038]

[0039] In the formula, F c represents the frequency component of the electric energy meter, N represents the total number of sampling points, c represents the index of the target frequency, which is the number of frequency components, and x n Indicates the nth voltage signal and current signal that need to be analyzed, represents the complex exponential term, which is used to describe the complex component of the signal at frequency c, e represents the base of the natural logarithm, j represents the imaginary unit, Indicates the phase information corresponding to the frequency, Represents the input signal x n Apply the complex exponential function and sum to each sampling point to get the frequency component F of the electric energy meter c .

[0040] Compared with the prior art, the present invention provides a remote electric energy meter fault analysis method based on a data acquisition terminal, which has the following beneficial effects:

[0041] The present invention acquires the operation data and environmental data of the electric energy meter in real time through the acquisition terminal, including information such as voltage, current, frequency, cumulative power consumption, operating temperature and humidity, and transmits it to the data cloud platform in real time through the network. In the data cloud platform, the missing data is supplemented by the interpolation method, so as to ensure the integrity of the data and improve the reliability of data processing. At the same time, the computing power of the data cloud platform is used to automatically calculate the fault characteristic parameters such as the effective value of voltage, effective value of current, power factor, instantaneous power and harmonic content of the electric energy meter, and then the fault diagnosis algorithm is used to quickly identify the fault type and generate a detailed fault analysis report in real time, and the report is fed back to the operation and maintenance personnel, so as to provide them with a scientific decision-making basis. The improvement of this real-time performance and accuracy not only reduces the fault response time, but also enhances the reliability of power supply, reduces the risk of power outages caused by electric energy meter failures, and ensures the stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The traditional electric energy meter fault analysis method has a low level of intelligence in data processing and fault diagnosis, and cannot effectively handle data loss or abnormal situations, resulting in insufficient accuracy and real-time performance in fault identification. This makes operation and maintenance personnel often lack timely and effective decision-making basis when facing sudden faults, thereby reducing the reliability of power supply. Therefore, a remote electric energy meter fault analysis method based on data acquisition terminal is proposed. Please refer to Figure 1 , the method comprises the following steps:

[0045] S1. Collect the operation data and operation environment data of the electric energy meter through the collection terminal, including voltage data, current data, frequency, cumulative power consumption data, operation temperature data of the electric energy meter and operation humidity data of the electric energy meter, and transmit them to the data cloud platform in real time through the network for processing;

[0046] By integrating advanced acquisition terminals, the system can efficiently and accurately collect the operating data and environmental data of the energy meter, including voltage data, current data, frequency, cumulative power consumption, operating temperature and humidity of the energy meter and other key parameters. The acquisition terminal adopts high-performance sensor technology, combined with embedded microprocessors, to achieve real-time monitoring and processing of data. These sensors have high sensitivity and wide measurement range, and can work continuously and stably in complex power environments. At the same time, the acquisition terminal uses wireless modules that support multiple communication protocols (including 4G, 5G, LoRa, etc.) to transmit the acquired data to the data cloud platform in real time through a secure network environment;

[0047] S2. If there are any missing data on the operation data and the operation environment data of the electric energy meter collected in the data cloud platform, the data is supplemented by interpolation method;

[0048] Among them, by setting up the missing value identifier M i , when M i =1 indicates that data is missing. i =0 means the data is normal, and M i =1 are completed by interpolation. The formula for data completion is as follows:

[0049] x b (i) = x i +[(x i+1 -x i )*(ki)]

[0050] The main benefit of using interpolation to complete data is to improve data integrity and analysis accuracy. During the operation of the electric energy meter, data loss or abnormal conditions may occur, which will directly affect the results of fault analysis. In the formula, x b (i) represents the missing data value to be filled, x i Indicates the previous known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, x i+1 represents the next known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, and ki represents the missing value in x i and x i+1 The relative position between them, k represents the index of the missing value data point. Through interpolation, the missing data can be effectively filled to ensure the continuity and consistency of the data set, which not only enhances the reliability of subsequent data analysis, but also avoids misdiagnosis caused by missing data, thereby reducing the risk of false positives and false negatives;

[0051] S3. The data cloud platform calculates the fault characteristic parameters of the electric energy meter based on the completed operation data of the electric energy meter and the operation environment data of the electric energy meter, including the effective value of the electric energy meter voltage, the effective value of the electric energy meter current, the power factor, the instantaneous power, the harmonic content of the voltage and current, the average operation temperature of the electric energy meter, and the frequency component of the electric energy meter;

[0052] The formula for calculating the effective value of the voltage of the electric energy meter is as follows:

[0053]

[0054] The effective value of voltage is an important indicator of the power supply quality of the electric energy meter. It can accurately represent the actual impact of voltage on the load. By calculating the effective value of voltage, the stability and reliability of the electric energy meter under different load conditions can be evaluated, and voltage fluctuations, overvoltage or undervoltage problems can be discovered in time. In the formula, U yx Indicates the effective value of the electric energy meter voltage, U n 2 Represents the square of the voltage value of the electric energy meter at each moment, N represents the total number of voltage sampling points of the electric energy meter, and n represents the index subscript. Represents the voltage value U at each moment n After squaring, take the average and then square root to get the effective value of the voltage of the electric energy meter. The monitoring of the effective value of the voltage can also help optimize the operation of the power system, improve the transmission efficiency of electric energy and the service life of equipment;

[0055] The calculation formula of the effective value of the electric energy meter current is as follows:

[0056]

[0057] The effective value of current is also an important parameter for the operation of the energy meter. It can reflect the actual impact of current on the power load. By calculating the effective value of current in real time, the change of current can be monitored and potential overload or short circuit faults can be identified. In the formula, I yx Indicates the effective value of the electric energy meter current, I n 2 It represents the square of the current value of the electric energy meter at each moment, M represents the total number of current sampling points of the electric energy meter, and n represents the index subscript. Represents the current value I at each moment n After squaring, take the average and then square root to get the effective value of the electric energy meter current. Accurate calculation of the effective value of the current helps to implement load management and protection measures, ensure the safe operation of power equipment, and reduce the risk of equipment damage;

[0058] The power factor calculation formula is as follows:

[0059]

[0060] Power factor is an important indicator for evaluating the efficiency of electric energy utilization. Its value directly reflects the load characteristics of the power system. By calculating the power factor, it can be determined whether there is an invalid load in the operation of the electric energy meter, thereby helping the power company to optimize power dispatch and load distribution. Improving the power factor can not only reduce power loss, but also reduce electricity bills, and promote the economy and environmental protection of the power system. In the formula, PF represents power factor, P represents active power, and Q represents apparent power. Indicates the actual power consumed in the energy meter. Indicates that the active power is normalized;

[0061] The instantaneous power calculation formula is as follows:

[0062] P(t)=U(t)*I(t)

[0063] Instantaneous power is a parameter that reflects the power change of the electric energy meter at a specific moment. By real-time monitoring of instantaneous power, the dynamic characteristics of load changes can be captured, and power fluctuations and abnormal conditions in a short period of time can be discovered in time. The analysis of instantaneous power is helpful for load forecasting and optimization of power grid operation strategies. At the same time, it provides an important basis for power dispatching and ensures the stability of power supply. In the formula, P(t) represents the instantaneous power of the electric energy meter at time t, U(t) represents the voltage of the electric energy meter at time t, and I(t) represents the current of the electric energy meter at time t.

[0064] The formula for calculating the harmonic content of voltage and current is as follows:

[0065]

[0066] Harmonics are one of the main factors that cause interference to the power system. By calculating the harmonic content of voltage and current, the operating quality of power equipment and the purity of electric energy can be evaluated. Harmonic analysis can help identify the nonlinear load of the equipment and take timely measures to reduce the impact of harmonics, avoid equipment failure and power loss, and thus improve the overall performance and reliability of the power system. In the formula, H k Indicates the content of the kth harmonic, U n represents the voltage value of the nth sampling point, N represents the total number of sampling points, k represents the number of target harmonics, π represents the period, Represents the cosine component in the voltage and current signals, Represents the sinusoidal component in the voltage and current signals, cos represents the part with zero phase, and the waveform corresponding to k times the frequency is extracted, sin represents the part related to 90 degrees of phase, and the relative component with k times the frequency is extracted. The square root of the overall formula represents the merging of the amplitudes of the various frequency components calculated in the plane coordinate system into a total amplitude value;

[0067] The calculation formula for the average operating temperature of the electric energy meter is as follows:

[0068]

[0069] The operating temperature of the energy meter has a direct impact on its performance and life. By monitoring the average operating temperature of the energy meter, the problem of equipment overheating can be discovered in time to avoid failures or accidents caused by excessive temperature. In the formula, Tp represents the average operating temperature of the energy meter, Q represents the total number of operating temperature samples of the energy meter, and tp j Indicates the temperature value of the jth electric energy meter temperature sample, j represents the index subscript, It means that all temperature data samples are accumulated and then divided by the total number of temperature samples to get the average operating temperature of the meter. Temperature monitoring can also provide a basis for equipment maintenance and upgrades, ensuring that the meter operates under optimal working conditions and extending its service life.

[0070] The calculation formula of the frequency component of the electric energy meter is as follows:

[0071]

[0072] Frequency is an important indicator of power system stability. By monitoring the frequency component of the energy meter, the operating status of the power grid can be evaluated and power supply problems caused by frequency anomalies can be discovered in time. In the formula, F c represents the frequency component of the electric energy meter, N represents the total number of sampling points, c represents the index of the target frequency, which is the number of frequency components, and x n Indicates the nth voltage signal and current signal that need to be analyzed, represents the complex exponential term, which is used to describe the complex component of the signal at frequency c, e represents the base of the natural logarithm, j represents the imaginary unit, Indicates the phase information corresponding to the frequency, Represents the input signal x n Apply the complex exponential function and sum to each sampling point to get the frequency component F of the electric energy meter c ,Frequency monitoring and analysis helps maintain the balance of the power system, ensures that equipment operates within a safe frequency range, and avoids equipment damage and power quality degradation caused by frequency fluctuations;

[0073] S4. The data cloud platform uses the fault diagnosis algorithm based on the fault characteristic parameters of the electric energy meter to identify the fault type of the electric energy meter and generate a fault analysis report of the electric energy meter;

[0074] In the process of fault type identification, the fault characteristic parameters of the electric energy meter are first obtained from the data cloud platform, including the effective value of voltage, effective value of current, power factor, instantaneous power, harmonic content of voltage and current, average operating temperature and frequency component. According to the technical specifications and historical fault data of the electric energy meter, the normal range and threshold of each fault characteristic parameter are set. The normal range of the effective value of voltage is 220V±10%, the effective value of current is in the range of 9A-12A, the power factor should be greater than 0.9, and the upper limit of the harmonic content is set to the total harmonic distortion rate THD≤5%. Then, the threshold judgment is performed on each fault characteristic parameter, and the actual measured value is compared with the set threshold. If If the voltage effective value exceeds the upper and lower limits, there may be an overvoltage or undervoltage fault. If the current effective value exceeds the normal range, it indicates that the load is overloaded or abnormal. If the power factor is lower than the set value, it may indicate an invalid load or phase imbalance. A sharp fluctuation in instantaneous power may indicate a transient fault or short circuit. Exceeding the harmonic content indicates a nonlinear load problem or harmonic interference in the equipment. If the operating temperature exceeds the threshold, it indicates that the equipment is overheated and the heat dissipation or load situation needs to be checked. If the frequency component exceeds the normal range, it may indicate that the power system is unstable. By comprehensively analyzing the results of the above threshold judgments and combining the abnormal conditions of each parameter, the system can accurately identify the fault type and provide an important basis for subsequent fault analysis reports.

[0075] S5. The data cloud platform feeds back the electric energy meter fault analysis report to the operation and maintenance personnel in real time;

[0076] The report is transmitted via the secure network communication protocol HTTPS to ensure that the data is not tampered with or leaked during transmission. The report not only includes a comparison of the actual value of the fault characteristic parameters with the normal value and the identification results of the fault type, but also provides possible fault causes and targeted maintenance suggestions. In addition, the cloud platform uses visual data processing technology to present complex fault information in the form of charts and dashboards, which is convenient for operation and maintenance personnel to quickly understand and analyze. It also has an intelligent reminder function. When a critical fault is detected, the operation and maintenance personnel can be notified via SMS, email or mobile application push notifications to ensure that they are aware of the equipment status in a timely manner and take corresponding measures. This process not only improves the efficiency of fault response, but also greatly enhances the reliability and safety of the power system.

[0077] Embodiment 1:

[0078] In this experiment, this method was used to conduct a preliminary fault analysis on the voltage and current effective values ​​of the electric energy meter, and the following data were collected using the acquisition terminal, including:

[0079] Voltage value U n : [220,225,215,230,218,222,219,221,223,224];

[0080] Current value I n : [10,10,5,9.5,11,10.2,10.8,10,9.8,10.5,11.2];

[0081] According to the formula for calculating the effective value of the voltage of the electric energy meter

[0083] According to the formula for calculating the effective value of the electric energy meter current

[0084] According to the above calculation results, the voltage effective value range is 220V±10%, that is, between 198V-242V. The calculated voltage effective value of 220.3V falls within this range, which means that the voltage of the energy meter is normal, and the normal current range is 9A-12A. The calculated current effective value of 10.25A is also within the normal range, that is, the voltage of the energy meter is normal, and there is no overvoltage, undervoltage or load abnormality.

[0085] Embodiment 2:

[0086] In this experiment, this method was used to conduct a preliminary fault analysis on the voltage and current effective values ​​of the electric energy meter, and the following data were collected using the acquisition terminal, including:

[0087] Voltage value U n : [200,190,185,250,240,195,210,185,260,270];

[0088] Current value I n : [5,4.5,3,1,6,5.5,4,4.2,3.5,2];

[0089] According to the formula for calculating the effective value of the voltage of the electric energy meter

[0090] According to the formula for calculating the effective value of the electric energy meter current

[0091] According to the above calculation results, the voltage effective value range is 220V±10%, that is, between 198V-242V. The calculated voltage effective value of 206.44V falls within this range, which means that the voltage of the electric energy meter is normal, and the normal current range is 9A-12A. The calculated current effective value of 3.95A is in the abnormal range, that is, the electric energy meter may have serious overload or underload problems. At this time, the electric energy meter current abnormality detection report is generated and sent to the operation and maintenance personnel for troubleshooting.

[0092] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote electric energy meter fault analysis method based on a data acquisition terminal, characterized in that: The following steps are involved: S1. Collect the operation data and operation environment data of the electric energy meter through the collection terminal, including voltage data, current data, frequency, cumulative power consumption data, operation temperature data of the electric energy meter and operation humidity data of the electric energy meter, and transmit them to the data cloud platform in real time through the network for processing; S2. If there are any missing data on the operation data and the operation environment data of the electric energy meter collected in the data cloud platform, the data is supplemented by interpolation method; S3. The data cloud platform calculates the fault characteristic parameters of the electric energy meter based on the completed operation data of the electric energy meter and the operation environment data of the electric energy meter, including the effective value of the electric energy meter voltage, the effective value of the electric energy meter current, the power factor, the instantaneous power, the harmonic content of the voltage and current, the average operation temperature of the electric energy meter, and the frequency component of the electric energy meter; S4. The data cloud platform uses the fault diagnosis algorithm based on the fault characteristic parameters of the electric energy meter to identify the fault type of the electric energy meter and generate a fault analysis report of the electric energy meter; S5. The data cloud platform will provide real-time feedback of the electricity meter fault analysis report to the operation and maintenance personnel.

2. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 1, characterized in that: The formula for identifying missing data is as follows: In the formula, M i Indicates a missing value identifier. When M i =1 indicates that data is missing. i =0 means the data is normal, x i Represents the i-th data point of the operating data of the electric energy meter or the operating environment data of the electric energy meter.

3. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 2, characterized in that: The formula for data completion is as follows: x b (i)=x i +[(x i+1 -x i )*(k-i)] In the formula, x b (i) represents the missing data value to be filled, x i Indicates the previous known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, x i+1 represents the next known operating data point of the electric energy meter or the operating environment data point of the electric energy meter, and ki represents the missing value in x i and x i+1 The relative position between them, k represents the index of the missing value data point.

4. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 3, characterized in that: The calculation formula of the effective value of the electric energy meter voltage is as follows: In the formula, U yx Indicates the effective value of the electric energy meter voltage, U n 2 Represents the square of the voltage value of the electric energy meter at each moment, N represents the total number of voltage sampling points of the electric energy meter, and n represents the index subscript. Represents the voltage value U at each moment n After squaring, take the average and then take the square root to get the effective value of the electricity meter voltage.

5. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 4, characterized in that: The calculation formula of the effective value of the electric energy meter current is as follows: In the formula, I yx Indicates the effective value of the electric energy meter current, I n 2 It represents the square of the current value of the electric energy meter at each moment, M represents the total number of current sampling points of the electric energy meter, and n represents the index subscript. Represents the current value I at each moment n After squaring, take the average and then take the square root to get the effective value of the electric energy meter current.

6. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 5, characterized in that: The power factor calculation formula is as follows: In the formula, PF represents power factor, P represents active power, and Q represents apparent power. Indicates the actual power consumed in the energy meter. Indicates that the active power is normalized.

7. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 6, characterized in that: The instantaneous power calculation formula is as follows: P(t)=U(t)*I(t) In the formula, P(t) represents the instantaneous power of the electric energy meter at time t, U(t) represents the voltage of the electric energy meter at time t, and I(t) represents the current of the electric energy meter at time t.

8. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 7, characterized in that: The calculation formulas for the harmonic content of the voltage and current are as follows: In the formula, H k Indicates the content of the kth harmonic, U n represents the voltage value of the nth sampling point, N represents the total number of sampling points, k represents the number of target harmonics, π represents the period, Represents the cosine component in the voltage and current signals, It represents the sinusoidal component in the voltage and current signals, cos represents the part with zero phase, and the waveform corresponding to k times the frequency is extracted. Sin represents the part related to 90 degrees of phase, and the relative component with k times the frequency is extracted. The square root of the overall formula means that the amplitudes of each frequency component calculated in the plane coordinate system are combined into a total amplitude value.

9. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 8, characterized in that: The calculation formula for the average operating temperature of the electric energy meter is as follows: In the formula, Tp represents the average operating temperature of the energy meter, Q represents the total number of operating temperature samples of the energy meter, and tp j Indicates the temperature value of the jth electric energy meter temperature sample, j represents the index subscript, It means that all temperature data samples are accumulated and summed, and then divided by the total number of the meter operating temperature samples to obtain the average operating temperature of the meter.

10. A remote electric energy meter fault analysis method based on a data acquisition terminal according to claim 9, characterized in that: The calculation formula of the frequency component of the electric energy meter is as follows: In the formula, F c represents the frequency component of the electric energy meter, N represents the total number of sampling points, c represents the index of the target frequency, which is the number of frequency components, and x n Indicates the nth voltage signal and current signal that need to be analyzed, represents the complex exponential term, which is used to describe the complex component of the signal at frequency c, e represents the base of the natural logarithm, j represents the imaginary unit, Indicates the phase information corresponding to the frequency, Represents the input signal x n Apply the complex exponential function and sum to each sampling point to get the frequency component F of the electric energy meter c .

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