A method for detecting faults in electric energy metering equipment

Abstract

The present invention relates to the technical field of electric energy metering equipment detection, and discloses a method for detecting faults of electric energy metering equipment, comprising the following steps: obtaining the real-time primary side voltage and the real-time secondary side voltage of the electric energy metering equipment. The present invention obtains the real-time primary side voltage and the real-time secondary side voltage data of the electric energy metering equipment, calculates the theoretical secondary side voltage according to the voltage transformer ratio, obtains the secondary side voltage deviation value, analyzes the secondary voltage deviation value, calculates the secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient, and sums the calculated secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient to obtain a fault judgment value, and generates a fault signal or a no-fault signal by comparing the fault judgment value with the fault judgment threshold, so as to accurately judge whether the electric energy metering equipment has a fault.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy metering equipment detection, and in particular to a method for detecting faults of electric energy metering equipment. Background Art

[0002] With the rapid development of the power industry and the popularization of smart grids, power metering equipment plays a vital role in the power system. These devices are not only used to accurately measure the consumption of power, but also directly related to the fairness and accuracy of power transactions. In actual operation, power metering equipment may encounter various faults. If they are not detected and handled in time, it will seriously affect the stable operation of the power system and the normal order of the power market.

[0003] However, the traditional fault detection method of electric energy metering equipment mainly relies on manual inspection and regular inspection. This method has the following shortcomings. First, manual inspection requires a lot of manpower and material resources, and it is difficult to achieve real-time detection. Second, regular inspection often fails to detect hidden faults of equipment in time, which easily causes the accumulation and expansion of faults. Finally, traditional detection methods often rely on experience judgment, which is highly subjective and difficult to ensure the accuracy and reliability of detection.

[0004] In view of this, we propose a fault detection method for electric energy metering equipment. Summary of the invention

[0005] The purpose of the present invention is to provide a method for detecting faults in electric energy metering equipment, so as to solve the problem that the traditional method for detecting faults in electric energy metering equipment in the above background mainly relies on manual inspection and regular inspection.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for detecting faults of electric energy metering equipment comprises the following steps: step 1: obtaining the real-time primary side voltage and the real-time secondary side voltage of the electric energy metering equipment, processing them to obtain the theoretical secondary side voltage, and calculating the secondary side voltage deviation value; step 2: obtaining the secondary side voltage deviation value, and calculating to obtain the fault judgment value; wherein, the calculation process of the fault judgment value is: obtaining the secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient; summing the secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient to obtain the fault judgment value; step 3: obtaining the fault judgment value, if the fault judgment value is less than or equal to the fault judgment threshold, generating a no-fault signal, if the fault judgment value is greater than the fault judgment threshold, generating a fault signal; step 4: based on the above fault signal, obtaining the temperature value data of the electric energy metering equipment, and calculating the impact evaluation value of the temperature on the secondary side voltage deviation value; step 5: obtaining the impact evaluation value, if the impact evaluation value is less than or equal to the impact evaluation threshold, generating a no-impact signal, if the impact evaluation value is greater than the impact evaluation threshold, generating an impact signal; step 6: based on the above impact signal, obtaining the control coefficient, and adjusting the temperature of the electric energy metering equipment.

[0008] As a further solution of the present invention: the process of obtaining the secondary side voltage deviation value is:

[0009] Obtain the real-time primary side voltage and real-time secondary side voltage of the electric energy metering device, perform ratio processing on the real-time primary side voltage and the voltage transformer multiplier, and obtain the theoretical secondary side voltage;

[0010] The difference between the theoretical secondary side voltage and the real-time secondary side voltage is calculated to obtain the absolute value of the difference, which is recorded as the secondary side voltage deviation value.

[0011] As a further solution of the present invention: the process of obtaining the fluctuation coefficient of the secondary side voltage deviation value is as follows:

[0012] Obtain the secondary side voltage deviation value, take the detection time as the X-axis and the secondary side voltage deviation value as the Y-axis, build a secondary side voltage deviation value two-dimensional model, substitute the real-time secondary side voltage deviation value into the two-dimensional model, and draw a secondary side voltage deviation value curve;

[0013] Obtain the slope of the secondary side voltage deviation value curve in the rising section, and sum them to obtain the total value of the slope of the rising section; obtain the slope of the secondary side voltage deviation value curve in the falling section, and sum them to obtain the total value of the slope of the falling section;

[0014] The total value of the slope of the ascending segment and the absolute value of the total value of the slope of the descending segment are summed to obtain the slope representation value;

[0015] Obtain the number of peaks and valleys of the secondary side voltage deviation curve, and sum them up to obtain a peak and valley number representation value;

[0016] Obtain the peak value and trough value of the secondary side voltage deviation curve, calculate the average value of the secondary side voltage deviation, calculate the difference between each peak value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all peak values ​​to obtain the total peak deviation; calculate the difference between each trough value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all trough values ​​to obtain the total trough deviation; sum the total peak deviation value and the total trough deviation value to obtain a discrete representation value;

[0017] The slope characterization value, the peak and valley number characterization value, and the discrete characterization value are summed to obtain the secondary side voltage deviation value fluctuation parameter;

[0018] The secondary side voltage fluctuation parameter is ratioed with the secondary side voltage fluctuation parameter standard value to obtain the secondary side voltage deviation value fluctuation coefficient.

[0019] As a further solution of the present invention: the process of obtaining the abnormal time characterization coefficient of the secondary side voltage deviation value is:

[0020] A line parallel to the X-axis is established with the secondary voltage deviation threshold as the baseline, and the portion of the secondary voltage deviation value curve located above the baseline is recorded as the abnormal area, and the portion of the secondary voltage deviation value curve located below the baseline is recorded as the normal area;

[0021] Obtain the time period of the abnormal area and sum them up to get the total abnormal time. Ratio the total abnormal time to the total duration to get the abnormal time ratio.

[0022] Get the number of abnormal area time period values ​​and the number of normal area time period values, sum them up to get the total number value, and perform ratio processing on the number of abnormal area time period values ​​and the total number value to get the number ratio value of the abnormal time period;

[0023] The abnormal time ratio is summed with the abnormal time period number ratio to obtain the abnormal time characterization coefficient of the secondary side voltage deviation value.

[0024] As a further solution of the present invention: the process of obtaining the impact assessment value is:

[0025] Obtain the overlap characterization value and the abnormal proportion deviation characterization value;

[0026] The overlap characterization value and the abnormal proportion deviation characterization value are processed as a ratio to obtain the impact assessment value.

[0027] As a further solution of the present invention: the process of obtaining the overlap characterization value and the abnormal proportion deviation characterization value is as follows:

[0028] Obtain the trend segment overlap time ratio and the anomaly overlap time ratio;

[0029] The overlap time ratio of the trend segment and the overlap time ratio of the abnormality are summed to obtain the overlap representation value;

[0030] Obtain the total value of the trend segment number deviation ratio and the value of the abnormal number deviation ratio;

[0031] The total value of the trend segment number deviation ratio and the value of the anomaly number deviation ratio are summed to obtain the anomaly ratio deviation representation value.

[0032] As a further solution of the present invention: the process of obtaining the trend segment overlap time ratio and the trend segment number deviation ratio is as follows:

[0033] Acquire fault judgment value data and fit it into a fault judgment value curve;

[0034] Obtain temperature value data of electric energy metering equipment and fit it into a temperature curve;

[0035] Obtain the overlapping time period of the temperature curve rising time period and the fault judgment value curve rising time period, and sum them up to record them as the total value of the rising overlapping time period;

[0036] Obtain the overlapping time period of the temperature curve falling time period and the fault judgment value curve falling time period, and sum them up to record them as the total value of the falling overlapping time period;

[0037] The total value of the rising overlap time period is summed with the total value of the falling overlap time period to obtain the total value of the overlap time period, and the total value of the overlap time period is ratioed with the total detection time to obtain the ratio of the overlap time of the trend segment;

[0038] Obtain the number of rising segments of the temperature curve and the number of rising segments of the fault judgment value curve, perform difference calculation, obtain the absolute value of the difference, and perform ratio processing with the number of rising segments of the fault judgment value curve to obtain the deviation ratio of the number of rising segments;

[0039] Obtain the number of values ​​of the temperature curve's descending section and the number of values ​​of the fault judgment value curve's descending section, perform difference calculation, obtain the absolute value of the difference, and perform ratio processing with the number of values ​​of the fault judgment value's descending section to obtain the deviation ratio of the number of descending sections;

[0040] Sum the deviation ratio of the number of rising segments and the deviation ratio of the number of falling segments to obtain the total value of the deviation ratio of the number of trend segments.

[0041] As a further solution of the present invention: the process of obtaining the abnormal overlap time ratio and the abnormal number deviation ratio:

[0042] Acquire temperature value data of the electric energy metering device, and compare the temperature value data of the electric energy metering device with a temperature threshold range;

[0043] If the temperature data is within the temperature threshold range, it is marked as normal temperature;

[0044] If the temperature data is not within the temperature threshold range, it is marked as abnormal temperature;

[0045] Obtain the time period marked as abnormal temperature and the time period for generating fault signals, calculate the abnormal coincidence time period, sum them up, obtain the total value of the abnormal coincidence time period, sum the abnormal temperature time periods, and obtain the total value of the abnormal temperature time periods;

[0046] The total value of the abnormal overlap time period is processed by ratio with the total value of the abnormal temperature time period to obtain the abnormal overlap time ratio;

[0047] The number of values ​​of the time period marked as abnormal temperature and the number of values ​​of the time period generating fault signals are obtained, and the difference is calculated to obtain the absolute value of the difference and the number of values ​​of the time period generating fault signals for ratio processing to obtain the abnormal number deviation ratio value.

[0048] As a further solution of the present invention: the process of obtaining the control coefficient is:

[0049] Obtain the fault judgment value curve and the time period for generating the fault signal, and sum them up to obtain the total value of the time for generating the fault signal, and perform ratio processing on the total value of the time for generating the fault signal and the total detection time to obtain the control coefficient;

[0050] As a further solution of the present invention: the process of adjusting the temperature of the electric energy metering device is:

[0051] Obtain the real-time temperature of the electric energy metering equipment, calculate the difference between the real-time temperature and the temperature standard value, and obtain the temperature deviation value;

[0052] When the temperature deviation value is greater than zero, the current fan speed is obtained, the temperature deviation value is multiplied by the control coefficient and the speed adjustment coefficient to obtain the speed adjustment value, and the speed adjustment value is summed with the current speed to obtain the final fan speed;

[0053] When the temperature deviation value is less than zero, the current electric heater power value is obtained, the absolute value of the temperature deviation value is multiplied by the control coefficient and the power adjustment coefficient to obtain the power adjustment value, and the difference between the power adjustment value and the current power value is calculated to obtain the final power value;

[0054] When the temperature deviation value is equal to zero, the cooling equipment and heating equipment are turned off.

[0055] Beneficial effects of the present invention:

[0056] The present invention obtains real-time primary-side voltage and real-time secondary-side voltage data of an electric energy metering device, calculates a theoretical secondary-side voltage according to a voltage transformer ratio, obtains a secondary-side voltage deviation value, analyzes the secondary voltage deviation value, calculates a secondary-side voltage deviation value fluctuation coefficient and a secondary-side voltage deviation value abnormal time characterization coefficient, and sums the calculated secondary-side voltage deviation value fluctuation coefficient and secondary-side voltage deviation value abnormal time characterization coefficient to obtain a fault judgment value, and generates a fault signal or a no-fault signal by comparing the fault judgment value with a fault judgment threshold, thereby accurately judging whether the electric energy metering device has a fault;

[0057] The present invention generates a fault signal, collects temperature data of the electric energy metering device, analyzes the fault judgment value curve and the temperature curve, calculates the coincidence characterization value and the abnormal proportion deviation characterization value, and calculates the impact assessment value based on the coincidence characterization value and the abnormal proportion deviation characterization value, and compares the impact assessment value with the impact assessment threshold, so as to determine whether the temperature is the influencing cause of the fault of the electric energy metering device;

[0058] The present invention generates an influence signal, calculates a control coefficient, and a temperature deviation value, and then takes specific adjustment measures according to a comparison between the temperature deviation value and zero. By adjusting the temperature, the influence of the temperature on the electric energy metering device is reduced, so that when a fault in the electric energy metering device is detected, timely adjustment can be performed to reduce the accumulation and expansion of faults caused by the failure to timely check. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The present invention will be further described below in conjunction with the accompanying drawings.

[0060] Figure 1 It is a process schematic diagram of a method for detecting a fault of an electric energy metering device according to the present invention;

[0061] Figure 2 It is a schematic diagram of the process of judging whether a fault occurs in a method for detecting a fault of an electric energy metering device according to the present invention;

[0062] Figure 3 It is a schematic diagram of a process for obtaining an impact assessment value in a method for detecting faults in electric energy metering equipment according to the present invention. DETAILED DESCRIPTION

[0063] 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. Embodiment 1

[0064] See also Figure 1-3 As shown, the present invention is a method for detecting faults in electric energy metering equipment, comprising the following steps:

[0065] Step 1: Obtain the real-time primary side voltage and the real-time secondary side voltage of the electric energy metering device, process them to obtain the theoretical secondary side voltage, and calculate the secondary side voltage deviation value;

[0066] In some embodiments, the real-time primary side voltage and the real-time secondary side voltage of the electric energy metering device are obtained, and the real-time primary side voltage is processed by ratio with the voltage transformer multiplier to obtain the theoretical secondary side voltage;

[0067] The voltage transformer ratio is the ratio of the primary voltage to the secondary voltage. The voltage transformer ratio can be obtained by checking the model manual.

[0068] The difference between the theoretical secondary side voltage and the real-time secondary side voltage is calculated to obtain the absolute value of the difference, which is recorded as the secondary side voltage deviation value;

[0069] Step 2: Obtain the secondary side voltage deviation value and calculate the fault judgment value;

[0070] In some embodiments, a secondary side voltage deviation value is obtained, with the detection time as the X-axis and the secondary side voltage deviation value as the Y-axis, a secondary side voltage deviation value two-dimensional model is constructed, the real-time secondary side voltage deviation value is substituted into the two-dimensional model, and a secondary side voltage deviation value curve is drawn;

[0071] Obtain the slope of the secondary side voltage deviation value curve in the rising section, and sum them to obtain the total value of the slope of the rising section; obtain the slope of the secondary side voltage deviation value curve in the falling section, and sum them to obtain the total value of the slope of the falling section;

[0072] The total value of the slope of the ascending segment and the absolute value of the total value of the slope of the descending segment are summed to obtain the slope representation value;

[0073] Obtain the number of peaks and valleys of the secondary side voltage deviation curve, and sum them up to obtain a peak and valley number representation value;

[0074] Obtain the peak value and trough value of the secondary side voltage deviation curve, calculate the average value of the secondary side voltage deviation, calculate the difference between each peak value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all peak values ​​to obtain the total peak deviation; calculate the difference between each trough value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all trough values ​​to obtain the total trough deviation; sum the total peak deviation value and the total trough deviation value to obtain a discrete representation value;

[0075] The slope characterization value, the peak and valley number characterization value, and the discrete characterization value are summed to obtain the secondary side voltage deviation value fluctuation parameter;

[0076] The secondary side voltage fluctuation parameter is processed by ratio with the secondary side voltage fluctuation parameter standard value (the secondary side voltage fluctuation parameter standard value is obtained by those skilled in the art based on the summary of historical work experiments) to obtain the secondary side voltage deviation value fluctuation coefficient;

[0077] It should be noted that when the fluctuation coefficient of the secondary side voltage deviation value is larger, the deviation degree between the secondary side voltage deviation value fluctuation parameter and the secondary side voltage fluctuation parameter standard value is larger, that is, the fluctuation degree of the secondary side voltage deviation value data is more drastic, indicating that the electric energy metering device is in an abnormal state;

[0078] A line parallel to the X-axis is established with the secondary voltage deviation threshold as the baseline, and the portion of the secondary voltage deviation value curve located above the baseline is recorded as the abnormal area, and the portion of the secondary voltage deviation value curve located below the baseline is recorded as the normal area;

[0079] Among them, the secondary side voltage deviation threshold is set by technicians in this field based on their work experience;

[0080] Obtain the time period of the abnormal area and sum them up to get the total abnormal time. Ratio the total abnormal time to the total duration to get the abnormal time ratio.

[0081] Get the number of abnormal area time period values ​​and the number of normal area time period values, sum them up to get the total number value, and perform ratio processing on the number of abnormal area time period values ​​and the total number value to get the number ratio value of the abnormal time period;

[0082] The abnormal time ratio value and the abnormal time period number ratio value are summed to obtain the abnormal time characterization coefficient of the secondary side voltage deviation value;

[0083] It should be noted that, when the abnormal time characterization coefficient of the secondary side voltage deviation value is larger, the corresponding abnormal time proportion value and abnormal time period proportion value are larger, that is, the larger the duration and frequency of the abnormal secondary side voltage deviation value are, it means that the electric energy metering device is in an abnormal state;

[0084] The secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient are summed to obtain a fault judgment value;

[0085] Step 3: Compare the fault judgment value with the threshold value to determine whether the electric energy metering device has a fault, and generate a fault signal or a no-fault signal;

[0086] In some embodiments, a fault judgment value is obtained, and the fault judgment value is compared with a fault judgment threshold;

[0087] Among them, the fault judgment threshold is set by those skilled in the art based on historical experimental data;

[0088] If the fault judgment value is less than or equal to the fault judgment threshold, it means that the secondary side voltage deviation value is within the normal fluctuation range, the electric energy metering device is in a normal state, and a no-fault signal is generated;

[0089] If the fault judgment value is greater than the fault judgment threshold, it means that the secondary side voltage deviation value fluctuates violently and the abnormal time characterization coefficient is large, the electric energy metering device is in an abnormal state, and a fault signal is generated;

[0090] The core idea of ​​this embodiment is: first, by acquiring the real-time primary voltage and real-time secondary voltage data of the electric energy metering device, and calculating the theoretical secondary voltage according to the voltage transformer ratio, the secondary voltage deviation value is obtained, the secondary voltage deviation value is analyzed, the secondary voltage deviation value fluctuation coefficient and the secondary voltage deviation value abnormal time characterization coefficient are calculated, and the calculated secondary voltage deviation value fluctuation coefficient and the secondary voltage deviation value abnormal time characterization coefficient are summed to obtain a fault judgment value, and by comparing the fault judgment value with the fault judgment threshold, a fault signal or a no-fault signal is generated, so that it is possible to accurately judge whether the electric energy metering device has a fault. Embodiment 2

[0091] Based on the above embodiments, the present invention is a method for detecting faults in electric energy metering equipment, further comprising the following steps:

[0092] Step 4: Based on the above fault signal, obtain the temperature value data of the electric energy metering equipment, and calculate the impact evaluation value of the temperature on the secondary side voltage deviation value;

[0093] In some embodiments, fault judgment value data is acquired and fitted into a fault judgment value curve;

[0094] Obtain temperature value data of electric energy metering equipment and fit it into a temperature curve;

[0095] Obtain the overlapping time period of the temperature curve rising time period and the fault judgment value curve rising time period, and sum them up to record them as the total value of the rising overlapping time period;

[0096] Obtain the overlapping time period of the temperature curve falling time period and the fault judgment value curve falling time period, and sum them up to record them as the total value of the falling overlapping time period;

[0097] The total value of the rising overlap time period is summed with the total value of the falling overlap time period to obtain the total value of the overlap time period, and the total value of the overlap time period is ratioed with the total detection time to obtain the ratio of the overlap time of the trend segment;

[0098] Obtain the number of rising segments of the temperature curve and the number of rising segments of the fault judgment value curve, perform difference calculation, obtain the absolute value of the difference, and perform ratio processing with the number of rising segments of the fault judgment value curve to obtain the deviation ratio of the number of rising segments;

[0099] Obtain the number of values ​​of the temperature curve's descending section and the number of values ​​of the fault judgment value curve's descending section, perform difference calculation, obtain the absolute value of the difference, and perform ratio processing with the number of values ​​of the fault judgment value's descending section to obtain the deviation ratio of the number of descending sections;

[0100] Sum the deviation ratio of the number of rising segments and the deviation ratio of the number of falling segments to obtain the total deviation ratio of the number of trend segments;

[0101] Compare the temperature value data of the electric energy metering device with the temperature threshold range (the temperature threshold range is set by technicians in this field based on their work experience);

[0102] If the temperature data is within the temperature threshold range, it means that the temperature of the energy meter is normal and is marked as normal temperature;

[0103] If the temperature data is not within the temperature threshold range, it means that the temperature of the electric energy meter is abnormal and is marked as abnormal temperature;

[0104] Obtain the time period marked as abnormal temperature and the time period for generating fault signals, calculate the abnormal coincidence time period, sum them up, obtain the total value of the abnormal coincidence time period, sum the abnormal temperature time periods, and obtain the total value of the abnormal temperature time periods;

[0105] The total value of the abnormal overlap time period is processed by ratio with the total value of the abnormal temperature time period to obtain the abnormal overlap time ratio;

[0106] Obtain the number of values ​​of the time period marked as abnormal temperature and the number of values ​​of the time period in which the fault signal is generated, and perform difference calculation to obtain the absolute value of the difference and the number of values ​​of the time period in which the fault signal is generated, and perform ratio processing to obtain the abnormal number deviation ratio value;

[0107] The overlap time ratio of the trend segment and the overlap time ratio of the abnormality are summed to obtain the overlap representation value;

[0108] The total value of the deviation ratio of the number of trend segments and the value of the deviation ratio of the number of anomalies are summed to obtain the deviation representation value of the anomaly ratio;

[0109] The overlap characterization value and the abnormal proportion deviation characterization value are processed as ratios to obtain the impact assessment value;

[0110] Step 5: Compare the impact assessment value with the threshold value to generate an impact signal or a no-impact signal;

[0111] In some embodiments, obtaining an impact assessment value, comparing the impact assessment value to an impact assessment threshold;

[0112] Among them, the impact assessment threshold is set by those skilled in the art based on experience;

[0113] If the impact assessment value is less than or equal to the impact assessment threshold, it means that the overlap between the temperature curve and the fault judgment value curve is small, and the deviation of the abnormal proportion is large, that is, the temperature has no effect on the fault of the electric energy metering equipment, and a no-effect signal is generated;

[0114] If the impact assessment value is greater than the impact assessment threshold, it means that the overlap between the temperature curve and the fault judgment value curve is large, and the deviation of the abnormal proportion is small, that is, the temperature has an impact on the fault of the electric energy metering equipment, and an impact signal is generated;

[0115] The core idea of ​​this embodiment is: based on the fault signal generated by the above embodiment, the temperature data of the electric energy metering equipment is collected, the fault judgment value curve and the temperature curve are analyzed, the coincidence characterization value and the abnormal proportion deviation characterization value are calculated, and the impact assessment value is calculated based on the coincidence characterization value and the abnormal proportion deviation characterization value, and the impact assessment value is compared with the impact assessment threshold, so as to determine whether the temperature is the influencing cause of the fault of the electric energy metering equipment. Embodiment 3

[0116] Based on the above embodiments, by adjusting the temperature, the influence of temperature on the failure of the electric energy metering device is reduced, so that the electric energy metering device can be optimized. The present invention is a method for detecting a failure of an electric energy metering device, which also includes the following steps:

[0117] Step 6: Based on the above-mentioned influencing signal, obtain the control coefficient and adjust the temperature of the electric energy metering device;

[0118] In some embodiments, a fault judgment value curve and a time period for generating a fault signal are obtained and summed to obtain a total value of the time for generating a fault signal, and the total value of the time for generating a fault signal is ratioed to the total time to obtain a control coefficient;

[0119] Obtain the real-time temperature of the electric energy metering device, calculate the difference between the real-time temperature and the temperature standard value (the temperature standard value is the maximum value of the temperature threshold range), and obtain the temperature deviation value;

[0120] When the temperature deviation value is greater than zero, it means that the real-time temperature is greater than the temperature standard value, and the current temperature needs to be lowered. The way to lower the current temperature includes but is not limited to adjusting the fan speed;

[0121] Specifically, the current speed is obtained, the temperature deviation value is multiplied by the control coefficient and the speed adjustment coefficient to obtain the speed adjustment value, the speed adjustment value is summed with the current speed to obtain the final speed of the fan, and the fan speed is adjusted to the final speed of the fan;

[0122] The speed adjustment coefficient is a constant set according to the system characteristics, which is set by the staff in this field through precise calculation and is used to adjust the speed increase rate;

[0123] When the temperature deviation value is less than zero, it means that the real-time temperature is less than the temperature standard value, and the current temperature needs to be increased. The way to increase the current temperature includes but is not limited to adjusting the power of the electric heater;

[0124] Specifically, the current power value is obtained, the absolute value of the temperature deviation value is multiplied by the control coefficient and the power adjustment coefficient to obtain the power adjustment value, the difference between the power adjustment value and the current power value is calculated to obtain the final power value, and the current power value is adjusted to the final power value;

[0125] The power adjustment coefficient is a constant set according to system characteristics, which is set by personnel in this field after precise calculation and is used to adjust the rate of power increase;

[0126] When the temperature deviation value is equal to zero, it means that the real-time temperature is equal to the temperature standard value, and the cooling equipment (such as fans) and heating equipment (such as electric heaters) are turned off to reduce energy loss;

[0127] The core solution of this embodiment is: based on the influence signal generated by the above embodiment, the control coefficient and the temperature deviation value are calculated, and then specific adjustment measures are taken according to the comparison between the temperature deviation value and zero. By adjusting the temperature, the influence of temperature on the electric energy metering device is reduced, so that timely adjustment can be made when a fault in the electric energy metering device is detected.

[0128] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for detecting faults in electric energy metering equipment, characterized in that: The following steps are involved: Step 1: Obtain the real-time primary side voltage and the real-time secondary side voltage of the electric energy metering device, process them to obtain the theoretical secondary side voltage, and calculate the secondary side voltage deviation value; Step 2: Obtain the secondary side voltage deviation value and calculate the fault judgment value; Among them, the calculation process of the fault judgment value is: Obtain the secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient; The secondary side voltage deviation value fluctuation coefficient and the secondary side voltage deviation value abnormal time characterization coefficient are summed to obtain a fault judgment value; Step 3: Obtain a fault judgment value. If the fault judgment value is less than or equal to the fault judgment threshold, generate a no-fault signal. If the fault judgment value is greater than the fault judgment threshold, generate a fault signal. Step 4: Based on the above fault signal, obtain the temperature value data of the electric energy metering equipment, and calculate the impact evaluation value of the temperature on the secondary side voltage deviation value; Step 5: Obtain an impact assessment value. If the impact assessment value is less than or equal to the impact assessment threshold, generate a no-impact signal. If the impact assessment value is greater than the impact assessment threshold, generate an impact signal. Impact assessment value: obtain fault judgment value data and fit it into a fault judgment value curve; obtain temperature value data of electric energy metering equipment and fit it into a temperature curve; Obtain the overlapping time period of the temperature curve rising time period and the fault judgment value curve rising time period, and sum them up, which is recorded as the total value of the rising overlapping time period; obtain the overlapping time period of the temperature curve falling time period and the fault judgment value curve falling time period, and sum them up, which is recorded as the total value of the falling overlapping time period; The total value of the rising overlap time period is summed with the total value of the falling overlap time period to obtain the total value of the overlap time period, and the total value of the overlap time period is ratioed with the total detection time to obtain the ratio of the overlap time of the trend segment; The numerical values ​​of the rising section of the temperature curve and the numerical values ​​of the rising section of the fault judgment value curve are obtained, and the difference is calculated to obtain the absolute value of the difference, and the difference is processed with the numerical values ​​of the rising section of the fault judgment value curve to obtain the deviation ratio of the number of rising sections; the numerical values ​​of the falling section of the temperature curve and the numerical values ​​of the falling section of the fault judgment value curve are obtained, and the difference is calculated to obtain the absolute value of the difference, and the difference is processed with the numerical values ​​of the falling section of the fault judgment value to obtain the deviation ratio of the number of falling sections; Sum the deviation ratio of the number of rising segments and the deviation ratio of the number of falling segments to obtain the total deviation ratio of the number of trend segments; Acquire temperature value data of the electric energy metering device, and compare the temperature value data of the electric energy metering device with the temperature threshold range; if the temperature data is not within the temperature threshold range, mark it as abnormal temperature; Obtain the time period marked as abnormal temperature and the time period for generating fault signals, calculate the abnormal coincidence time period, sum them up, obtain the total value of the abnormal coincidence time period, sum the abnormal temperature time periods, and obtain the total value of the abnormal temperature time periods; The total value of the abnormal overlap time period is processed by ratio with the total value of the abnormal temperature time period to obtain the abnormal overlap time ratio; Obtain the number of values ​​of the time period marked as abnormal temperature and the number of values ​​of the time period in which the fault signal is generated, and perform difference calculation to obtain the absolute value of the difference and the number of values ​​of the time period in which the fault signal is generated, and perform ratio processing to obtain the abnormal number deviation ratio value; The trend segment overlap time ratio and the abnormal overlap time ratio are summed to obtain the overlap representation value; the trend segment number deviation ratio total value and the abnormal number deviation ratio value are summed to obtain the abnormal ratio deviation representation value; The overlap characterization value and the abnormal proportion deviation characterization value are processed as ratios to obtain the impact assessment value; Step 6: Based on the above-mentioned influencing signal, obtain the control coefficient and adjust the temperature of the electric energy metering device.

2. The method for detecting faults in electric energy metering equipment according to claim 1, characterized in that: The process of obtaining the secondary side voltage deviation value is as follows: Obtain the real-time primary side voltage and real-time secondary side voltage of the electric energy metering device, perform ratio processing on the real-time primary side voltage and the voltage transformer multiplier, and obtain the theoretical secondary side voltage; The difference between the theoretical secondary side voltage and the real-time secondary side voltage is calculated to obtain the absolute value of the difference, which is recorded as the secondary side voltage deviation value.

3. The method for detecting faults in electric energy metering equipment according to claim 1, characterized in that: The process of obtaining the fluctuation coefficient of the secondary side voltage deviation value is as follows: Obtain the secondary side voltage deviation value, take the detection time as the X-axis and the secondary side voltage deviation value as the Y-axis, build a secondary side voltage deviation value two-dimensional model, substitute the real-time secondary side voltage deviation value into the two-dimensional model, and draw a secondary side voltage deviation value curve; Obtain the slope of the secondary side voltage deviation value curve in the rising section, and sum them to obtain the total value of the slope of the rising section; obtain the slope of the secondary side voltage deviation value curve in the falling section, and sum them to obtain the total value of the slope of the falling section; The total value of the slope of the ascending segment and the absolute value of the total value of the slope of the descending segment are summed to obtain the slope representation value; Obtain the number of peaks and valleys of the secondary side voltage deviation curve, and sum them up to obtain a peak and valley number representation value; Obtain the peak value and trough value of the secondary side voltage deviation curve, calculate the average value of the secondary side voltage deviation, calculate the difference between each peak value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all peak values ​​to obtain the total peak deviation; calculate the difference between each trough value and the average value of the secondary side voltage deviation, and sum the absolute values ​​of the differences corresponding to all trough values ​​to obtain the total trough deviation; The total peak deviation value and the total trough deviation value are summed to obtain a discrete representation value; The slope characterization value, the peak and valley number characterization value, and the discrete characterization value are summed to obtain the secondary side voltage deviation value fluctuation parameter; The secondary side voltage fluctuation parameter is ratioed with the secondary side voltage fluctuation parameter standard value to obtain the secondary side voltage deviation value fluctuation coefficient.

4. The method for detecting faults in electric energy metering equipment according to claim 3, characterized in that: The process of obtaining the abnormal time characterization coefficient of the secondary side voltage deviation value is as follows: A line parallel to the X-axis is established with the secondary voltage deviation threshold as the baseline, and the portion of the secondary voltage deviation value curve located above the baseline is recorded as the abnormal area, and the portion of the secondary voltage deviation value curve located below the baseline is recorded as the normal area; Obtain the time period of the abnormal area and sum them up to get the total abnormal time. Ratio the total abnormal time to the total duration to get the abnormal time ratio. Get the number of abnormal area time period values ​​and the number of normal area time period values, sum them up to get the total number value, and perform ratio processing on the number of abnormal area time period values ​​and the total number value to get the number ratio value of the abnormal time period; The abnormal time ratio is summed with the abnormal time period number ratio to obtain the abnormal time characterization coefficient of the secondary side voltage deviation value.

5. The method for detecting faults in electric energy metering equipment according to claim 1, characterized in that: The process of obtaining the control coefficient is: Obtain the fault judgment value curve and the time period for generating the fault signal, sum the time period for generating the fault signal, obtain the total time value for generating the fault signal, perform ratio processing on the total time value for generating the fault signal and the total detection time, and obtain the control coefficient.

6. A method for detecting faults in electric energy metering equipment according to claim 5, characterized in that: The process of adjusting the temperature of the electric energy metering equipment is as follows: Obtain the real-time temperature of the electric energy metering equipment, calculate the difference between the real-time temperature and the temperature standard value, and obtain the temperature deviation value; When the temperature deviation value is greater than zero, the current fan speed is obtained, the temperature deviation value is multiplied by the control coefficient and the speed adjustment coefficient to obtain the speed adjustment value, and the speed adjustment value is summed with the current speed to obtain the final fan speed; When the temperature deviation value is less than zero, the current electric heater power value is obtained, the absolute value of the temperature deviation value is multiplied by the control coefficient and the power adjustment coefficient to obtain the power adjustment value, and the difference between the power adjustment value and the current power value is calculated to obtain the final power value; When the temperature deviation value is equal to zero, the cooling equipment and heating equipment are turned off.

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