A method, medium and system for dynamic detection of operation status of electric meter box

Abstract

The present application relates to the technical field of dynamic detection of electric meter boxes, and specifically to a method, medium and system for dynamic detection of the operating status of an electric meter box, which specifically includes: constructing a historical instability index of each electric meter at the latest moment based on the correlation between the voltage fluctuations at the input and output ends of each electric meter and the difference between the same-phase voltages at the input and output ends of the electric meter; constructing a severe pressure loss factor of each electric meter based on the continuity of pressure loss data in any phase voltage of the input and output ends of each electric meter and the distribution of the corresponding time of the pressure loss data in combination with the historical instability index; and determining and giving an alarm for pressure loss in the historical operating status of the electric meter by setting a pressure loss threshold, thereby improving the reliability of the assessment of the voltage loss situation in the electric meter box and the timeliness of the alarm, and improving the accuracy of the detection of the operating status of the electric meter box, thereby improving the stability of the power system, ensuring the accurate measurement of the electric energy meter, and avoiding further damage to the electrical equipment.

Description

Technical Field

[0001] The present application relates to the technical field of dynamic detection of electric meter boxes, and in particular to a method, medium and system for dynamic detection of the operating status of an electric meter box. Background Art

[0002] Dynamic detection of the operating status of the meter box is a key link in the intelligentization of the power system, and its development is closely linked to the construction of smart grids. By real-time monitoring of the meter box, the operating efficiency and safety of the power system are improved, and labor costs are reduced. With the advancement of sensors, the Internet of Things, big data, and artificial intelligence technologies, the meter box can analyze the status of the power system in real time, and promptly detect and handle anomalies such as faults and metering errors. The dynamic detection of the meter box is of great significance. Combined with big data and artificial intelligence, the online monitoring and automatic fault handling of the meter box will be more efficient, further improving the intelligent management level of the power system.

[0003] The loss of pressure of the meter in the meter box is usually caused by a power supply line failure or a problem with the meter itself. The loss of pressure will cause the meter to be unable to measure normally, thereby affecting the accuracy of the user's electricity consumption measurement and causing errors in the calculation of electricity bills. The existing technology of pressure loss measurement is usually to detect whether the voltage is continuously lower than the normal operating range of the meter. If the voltage is continuously lower than the normal operating range of the meter, it will be judged as the meter has lost pressure. However, if the meter is frequently lower than the normal operating range for a short time, it will also cause inaccurate measurement, and frequent fluctuations may affect the life of the meter and increase the risk of failure. Traditional pressure loss detection equipment is difficult to capture these instantaneous frequent changes, resulting in inaccurate assessment of the cause and impact of pressure loss, thereby affecting the accuracy of meter operation status detection. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a method, medium and system for dynamic detection of the operating status of an electric meter box. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for dynamically detecting the operating status of an electric meter box, the method comprising the following steps:

[0006] Collect the three-phase voltages at the input and output terminals of each meter in the meter box at each collection moment;

[0007] For each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree of the voltage fluctuation between the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the same-phase voltages at the input and output ends of the electric meter; and the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree;

[0008] The voltage loss data is obtained based on the size of the voltage data; based on the continuity of the voltage loss data in any phase voltage at the input and output ends of each meter, the voltage loss run entropy of any phase voltage is constructed; based on the distribution of the voltage loss data in any phase voltage corresponding to the time and the voltage loss run entropy, combined with the historical instability index of each meter at the latest moment, the serious voltage loss factor of each meter is constructed;

[0009] The operating status of each meter is determined based on the severe pressure loss factor of each meter.

[0010] In one embodiment, the process of obtaining the disorder consistency between the input terminal and the output terminal of the electric meter is:

[0011] For the three-phase voltage at each acquisition time of the meter input terminal, the average value and the range of the voltage of the three phases are calculated; the ratio of the range to the average value is calculated and recorded as the voltage imbalance; the voltage imbalance of the three-phase voltage at all acquisition times of the meter input terminal is arranged to obtain the voltage disorder sequence of the meter input terminal;

[0012] Based on the three-phase voltages at all acquisition moments at the output end of the electric meter, a voltage disorder sequence at the output end of the electric meter is obtained in the same manner as that of the voltage disorder sequence at the input end of the electric meter;

[0013] The correlation between the voltage disorder sequences at the input and output of the meter is calculated by a similarity algorithm and is recorded as disorder consistency.

[0014] In one embodiment, the process of obtaining the phase deviation degree between the input terminal voltage and the output terminal voltage of the electric meter at the latest moment is:

[0015] The difference between the in-phase voltages at the input and output ends of the electric meter at the latest moment is calculated and recorded as the first difference; the average value of all the first differences between the input voltage and the output voltage of the electric meter at the latest moment is calculated and recorded as the phase deviation degree.

[0016] In one embodiment, the expression of the historical instability index of the electric meter at the latest moment is: , where is the historical instability index of the ith meter at the latest moment, is the normalization function, is the phase deviation between the input voltage and output voltage of the ith meter at the latest moment, is the disorder consistency between the input and output of the i-th meter.

[0017] In one embodiment, the voltage loss data is voltage data whose voltage value is outside the normal working range of the electric meter.

[0018] In one embodiment, the process of obtaining the voltage drop run entropy of any phase voltage is as follows:

[0019] Record the sequence of continuous voltage loss data as voltage loss run, obtain the voltage loss runs of any phase voltage at the input and output ends of each electric meter, and take the number of voltage loss data in each voltage loss run as the length of each voltage loss run;

[0020] The frequency of each voltage drop run length of each meter in all voltage drop run lengths of each meter is counted, and the information entropy of any phase voltage is calculated based on the frequency of all voltage drop run lengths of any phase voltage, which is recorded as voltage drop run entropy.

[0021] In one embodiment, the process of obtaining the severe voltage loss factor of each electric meter is as follows:

[0022] The standard deviation of all the voltage loss data at any phase of the input and output terminals of each meter at the time of collection is recorded as the first standard deviation; the severe voltage loss factor of the ith meter is recorded as , The expression is: , where is the historical instability index of the ith meter at the latest moment; N is the sum of the phase numbers of the input voltage and the output voltage; is the first standard deviation of all voltage loss data in the j-th phase voltage of the i-th meter; is the voltage drop run entropy of the j-th phase voltage of the ith meter.

[0023] In one embodiment, the operation state of each electric meter is determined according to the severe voltage loss factor of each electric meter, specifically:

[0024] If the severe pressure loss factor of each meter is greater than the preset pressure loss threshold, each meter has experienced severe pressure loss and issues an alarm; otherwise, each meter has not experienced severe pressure loss and is in a normal state.

[0025] In a second aspect, the embodiment of the present application further provides a dynamic detection medium for the operation status of an electric meter box, including:

[0026] Data acquisition module: collects the three-phase voltages at the input and output ends of each meter in the meter box at each acquisition moment;

[0027] Electric meter stability analysis module: for each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree of the voltage fluctuation between the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the same-phase voltages of the input and output ends of the electric meter; the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree;

[0028] Electric meter voltage loss degree analysis module: obtain voltage loss data based on the size of voltage data; construct the voltage loss run entropy of any phase voltage based on the continuity of voltage loss data in any phase voltage at the input and output ends of each electric meter; construct the serious voltage loss factor of each electric meter based on the distribution of voltage loss data corresponding to time in any phase voltage and voltage loss run entropy, combined with the historical instability index of each electric meter at the latest moment;

[0029] Electricity meter operation status detection module: determines the operation status of the electricity meter according to the severe pressure loss factor of each electricity meter.

[0030] In a third aspect, an embodiment of the present application further provides a system for dynamically detecting the operating status of an electric meter box, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0031] The embodiments of the present application have at least the following beneficial effects:

[0032] The present application proposes a method, medium and system for dynamically detecting the operating status of an electric meter box. By collecting the three-phase voltages of the input and output terminals of each electric meter in the electric meter box at each collection time, based on the correlation degree of the voltage fluctuations between the input and output terminals of each electric meter and the difference between the same-phase voltages of the input and output terminals of the electric meter, a historical instability index of each electric meter at the latest time is constructed, the imbalance problem of the voltage at both ends of the electric meter is analyzed, and the problem of stability analysis of the electric meter undervoltage is solved; based on the continuity of the undervoltage data in any phase voltage of the input and output terminals of each electric meter and the corresponding time of the undervoltage data, the undervoltage data is analyzed. The distribution of voltage loss is analyzed, and the serious voltage loss factor of each meter is constructed in combination with the historical instability index. The severity of voltage loss and the uncertainty of time distribution are evaluated to eliminate the impact of short-term voltage loss and further improve the accuracy of voltage loss analysis of the meter. By setting the voltage loss threshold, the voltage loss judgment and alarm are made based on the historical operating status of the meter, which improves the reliability of the voltage loss assessment in the meter box and the timeliness of the alarm, and improves the accuracy of the meter box operating status detection, thereby improving the stability of the power system, ensuring the accurate measurement of the energy meter, and avoiding further damage to electrical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 A flowchart of a method for dynamically detecting the operating status of an electric meter box provided in one embodiment of the present application;

[0035] Figure 2 It is a schematic diagram of the process of obtaining the decompression run entropy;

[0036] Figure 3 The present invention is a structural schematic diagram of a dynamic detection medium for the operation status of an electric meter box. DETAILED DESCRIPTION

[0037] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the method, medium and system for dynamic detection of the operating status of an electric meter box proposed in the present application, its specific implementation method, structure, features and effects in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0039] The following is a detailed description of a method, medium and system for dynamically detecting the operating status of an electric meter box provided by the present application in conjunction with the accompanying drawings.

[0040] See also Figure 1 , which shows a flowchart of a method for dynamically detecting the operating status of an electric meter box provided by an embodiment of the present application, the method comprising the following steps:

[0041] Step S1, collecting the three-phase voltages of the input and output terminals of each meter in the meter box at each collection time.

[0042] For each meter in the meter box, connect a three-phase voltmeter to the input and output ends of the meter to measure the three-phase voltage at both ends of the meter; set the normal working range of the meter voltage to ,in is the rated voltage of the meter.

[0043] Preferably, in one embodiment of the present application, the acquisition frequency of the three-phase voltage data is set to 100 Hz, and the voltage data within the nearest hour to the current time is collected. As other embodiments of the present application, the implementer can set the acquisition frequency and data acquisition time period of the three-phase voltage data by himself. It should be noted that the implementer can set the normal working range of the voltage of the electric meter according to the actual situation, and this application does not make specific restrictions.

[0044] Step S2: for each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree between the voltage fluctuations at the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the in-phase voltages at the input and output ends of the electric meter; and the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree.

[0045] In the circuit system, the three-phase voltage may be unbalanced due to the asymmetric load in the system, the asymmetry of the line or transformer, the ground fault or resonance, etc. This imbalance may cause the voltage of some phases to decrease. When the voltage decreases to a certain level, it will cause voltage loss. In the three-phase system, once voltage loss occurs, especially in the electric energy meter connected through the voltage transformer (PT), the primary or secondary side fuse of the voltage transformer may blow, which may cause the electric energy meter to lose the voltage reference of one or more phases, thereby affecting the accurate measurement of the electric energy meter.

[0046] Voltage loss is exacerbated by the long-term presence of three-phase voltage imbalance, as unbalanced voltage distribution may cause certain parts of the system to bear greater loads, thereby increasing the risk of failure.

[0047] (1) For the three-phase voltage at each meter input end at each sampling moment, the average value and the range of the voltages of the three phases in the three-phase voltage are calculated; and the ratio of the range of the three-phase voltage to the average value is used as the voltage unbalance degree of the three-phase voltage;

[0048] The voltage unbalance degrees of the three-phase voltages at all acquisition moments of the input terminals of the electric meters are arranged in ascending time order to obtain a voltage disorder sequence at the input terminals of the electric meters.

[0049] (2) Based on the three-phase voltages at all acquisition moments of the output end of each meter, the voltage disorder sequence at the output end of each meter is obtained in the same manner as the voltage disorder sequence at the input end of each meter.

[0050] (3) Calculate the Pearson correlation coefficient between the voltage disorder sequences at the input and output of each meter, which is recorded as disorder consistency. It should be noted that for calculating the correlation between the voltage disorder sequences at the input and output of each meter, this application only provides a correlation calculation method. There are many existing methods for calculating correlation. The implementer may also use other similarity algorithms to calculate the correlation between the voltage disorder sequences at the input and output of each meter. This application does not make any specific restrictions.

[0051] The more correlated the voltage fluctuations at the input and output ends of the meter are, the greater the disorder consistency is, that is, when the voltage imbalance at the input end increases, the voltage imbalance at the output end also tends to increase.

[0052] (4) Calculate the difference between the in-phase voltages at the input and output of each meter at the latest moment, and record it as the first difference; calculate the average value of all the first differences between the input voltage and the output voltage of each meter at the latest moment, and record it as the phase deviation degree.

[0053] Preferably, in one embodiment of the present application, the first difference may be an absolute value of a difference between the in-phase voltages at the input and output ends of each electric meter at the latest moment;

[0054] In other embodiments of the present application, the first difference may also be the square of the difference between the in-phase voltages at the input and output ends of each electric meter at the latest moment.

[0055] Ideally, if the input and output of the meter are completely synchronized, the difference between the in-phase voltages should be close to zero. The closer the phase deviation is to zero, the greater the phase deviation is. The greater the phase deviation is, the greater the phase deviation between the input and output of the meter is.

[0056] (5) Based on the disorder consistency and phase deviation degree, the historical instability index of each meter at the latest moment is calculated, and the expression is: , where is the historical instability index of the ith meter at the latest moment, is the normalization function, is the phase deviation between the input voltage and output voltage of the ith meter at the latest moment, is the disorder consistency between the input and output of the i-th meter.

[0057] The greater the phase deviation, the more unstable the meter is. The larger the absolute value of the disorder consistency is, the more the voltages at the input and output are correlated in time, that is, the stronger the stability of the input and output is, and the higher the historical instability index is. The smaller.

[0058] The historical instability index reflects the phase deviation and time consistency of the voltage at both ends of the meter. The larger the historical instability index, the greater the phase deviation of the voltage at both ends of the meter, and the more inconsistent the voltage change trend between the input and output ends. At this time, the phase deviation of the voltage leads to inaccurate energy measurement and the stability of the meter is worse.

[0059] Step S3, obtaining the voltage loss data based on the size of the voltage data; constructing the voltage loss run entropy of any phase voltage based on the continuity of the voltage loss data in any phase voltage at the input and output ends of each electric meter; constructing the severe voltage loss factor of each electric meter based on the distribution of the voltage loss data in any phase voltage corresponding to the time and the voltage loss run entropy, combined with the historical instability index of each electric meter at the latest moment.

[0060] During the operation of the meter box, if only one phase voltage decreases while the other two phase voltages are normal, this situation is called single-phase voltage loss, which will cause some parts of the three-phase equipment to not work properly, but the equipment may still be able to operate; if two-phase voltage decreases while the other phase voltage is normal, this situation is called two-phase voltage loss, which will cause the equipment to not work properly, because most three-phase equipment requires three-phase voltage balance to operate normally. If the three-phase voltages are all reduced to a state where they cannot meet the equipment requirements, this situation is called three-phase full voltage loss, which will cause the equipment to stop working completely.

[0061] (1) The voltage data whose voltage value is outside the normal working range of the electric meter is recorded as the voltage loss data; for any phase voltage at the input and output ends of each electric meter, the standard deviation of the collection time corresponding to all the voltage loss data in the any phase voltage is calculated and recorded as the first standard deviation.

[0062] The first standard deviation measures the degree of fluctuation of the voltage loss data over time. The larger the value, the greater the change in the degree of voltage loss at different times, which means the worse the voltage stability.

[0063] (3) Record the sequence of continuous voltage loss data as voltage loss run, obtain the voltage loss runs of any phase voltage at the input and output ends of each meter, and take the number of voltage loss data in each voltage loss run as the length of each voltage loss run.

[0064] (4) Count the frequencies of occurrence of each voltage drop run length of each meter in all voltage drop run lengths of each meter, and calculate the information entropy of any phase voltage based on the frequencies of occurrence of all voltage drop run lengths of any phase voltage, which is recorded as voltage drop run entropy. The information entropy is a well-known technology, and the specific calculation process is not repeated here.

[0065] The decompression run entropy is used to measure the uncertainty of the decompression run length distribution. The larger the decompression run entropy is, the more diverse and unpredictable the decompression run length distribution is, that is, there is no obvious pattern or regularity in the temporal distribution of the decompression phenomenon.

[0066] (5) Based on the first standard deviation and voltage loss run entropy of any phase voltage at the input and output ends of each meter, combined with the historical instability index of each meter at the latest moment, the severe voltage loss factor of each meter is calculated. The expression is: , where is the severe voltage loss factor of the ith meter, is the historical instability index of the ith meter at the latest moment; N is the sum of the phases of the input voltage and the output voltage. Here, there are three-phase voltages at the input and output ends, and the value is 6; is the first standard deviation of all voltage loss data in the j-th phase voltage of the i-th meter; is the voltage drop run entropy of the j-th phase voltage of the ith meter.

[0067] The larger the first standard deviation, the more discontinuous the voltage loss is. At this time, it means that there are more short-term voltage losses in the j-th phase voltage and fewer continuous voltage losses, so the serious voltage loss factor decreases accordingly; the larger the voltage loss run entropy, the more chaotic the temporal distribution of the voltage loss phenomenon is. Similarly, it indicates that there are fewer continuous voltage losses in the j-th phase voltage, so the serious voltage loss factor decreases accordingly.

[0068] The magnitude of the severe voltage loss factor directly reflects the severity of the voltage loss and the uncertainty of its time distribution. When the severe voltage loss factor is large, it indicates that the voltage loss is frequent and fluctuates greatly, the metering accuracy of the energy meter is affected, and the system stability is poor. On the contrary, a small severe voltage loss factor means that there are fewer voltage loss problems, the energy meter is reliable, and the system operation is stable.

[0069] Step S4, determining the operating status of each meter according to the severe pressure loss factor of each meter.

[0070] In the meter box, voltage loss is usually only judged when the voltage remains below the threshold for a period of time. However, short-term and frequent voltage fluctuations can also have a serious impact on the power system. Such frequent voltage fluctuations may cause inaccurate meter readings and affect the fairness of billing. At the same time, voltage instability may also cause damage to electrical equipment connected to the meter, such as difficulty in starting, performance degradation, and even equipment damage.

[0071] A pressure loss threshold is set. Preferably, in the embodiment of the present application, the pressure loss threshold is set to 0.7. As other embodiments of the present application, the implementer can set the pressure loss threshold according to the actual situation. For each meter in the meter box, if the severe pressure loss factor of the meter is greater than the pressure loss threshold, it means that the meter has experienced enough pressure loss during the historical time period of data collection, so that the meter is considered to have experienced severe pressure loss and an alarm is issued. The frequent voltage below the normal working threshold will affect the accuracy of the meter readings, resulting in inaccurate billing, and may also cause damage to the electrical equipment connected to the meter, such as difficulty in starting, performance degradation or equipment damage. If the severe pressure loss factor of the meter is less than or equal to the pressure loss threshold, it means that the meter has not experienced severe pressure loss and is in a normal state.

[0072] The schematic diagram of the process of obtaining the decompression travel entropy is as follows: Figure 2 shown.

[0073] See also Figure 3 , Figure 3 1 is a schematic diagram of a structure of a dynamic detection medium for the operation status of an electric meter box provided in an embodiment of the present application. In this embodiment, each unit included in the terminal is used to execute each step in an embodiment corresponding to a method for dynamic detection of the operation status of an electric meter box. Figure 3 , the dynamic detection media of running status include:

[0074] Data acquisition module: collects the three-phase voltages at the input and output ends of each meter in the meter box at each acquisition moment;

[0075] Electric meter stability analysis module: for each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree of the voltage fluctuation between the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the same-phase voltages of the input and output ends of the electric meter; the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree;

[0076] Electric meter voltage loss degree analysis module: obtain voltage loss data based on the size of voltage data; construct the voltage loss run entropy of any phase voltage based on the continuity of voltage loss data in any phase voltage at the input and output ends of each electric meter; construct the serious voltage loss factor of each electric meter based on the distribution of voltage loss data corresponding to time in any phase voltage and voltage loss run entropy, combined with the historical instability index of each electric meter at the latest moment;

[0077] Electricity meter operation status detection module: determines the operation status of the electricity meter according to the severe pressure loss factor of each electricity meter.

[0078] Based on the same inventive concept as the above method, an embodiment of the present application also provides a system for dynamically detecting the operating status of an electric meter box, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above methods for dynamically detecting the operating status of an electric meter box when executing the computer program.

[0079] In summary, the embodiment of the present application provides a method for dynamically detecting the operating status of an electric meter box, by collecting the three-phase voltages of the input and output terminals of each electric meter in the electric meter box at each collection time, based on the correlation degree of the voltage fluctuations between the input and output terminals of each electric meter and the difference between the same-phase voltages of the input and output terminals of the electric meter, a historical instability index of each electric meter at the latest time is constructed, the imbalance problem of the voltage at both ends of the electric meter is analyzed, and the problem of stability analysis of the voltage loss of the electric meter is solved; based on the continuity of the voltage loss data in any one phase voltage of the input and output terminals of each electric meter and the corresponding time of the voltage loss data The distribution of voltage loss is combined with the historical instability index to construct the serious voltage loss factor of each meter, and the severity of voltage loss and the uncertainty of time distribution are evaluated to eliminate the impact of short-term voltage loss, so as to further improve the accuracy of voltage loss analysis of the meter; by setting the voltage loss threshold, the voltage loss judgment and alarm are made based on the historical operating status of the meter, which improves the reliability of the voltage loss assessment in the meter box and the timeliness of the alarm, and improves the accuracy of the meter box operating status detection, thereby improving the stability of the power system, ensuring the accurate measurement of the energy meter, and avoiding further damage to electrical equipment.

[0080] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. The above-mentioned specific embodiments of the present application are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0082] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for dynamically detecting the operating status of an electric meter box, characterized in that: The method comprises the following steps: Collect the three-phase voltages at the input and output terminals of each meter in the meter box at each collection moment; For each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree of the voltage fluctuation between the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the same-phase voltages at the input and output ends of the electric meter; and the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree; The voltage loss data is obtained based on the size of the voltage data; based on the continuity of the voltage loss data in any phase voltage at the input and output ends of each meter, the voltage loss run entropy of any phase voltage is constructed; based on the distribution of the voltage loss data in any phase voltage corresponding to the time and the voltage loss run entropy, combined with the historical instability index of each meter at the latest moment, the serious voltage loss factor of each meter is constructed; Determine the operating status of each meter based on its severe pressure loss factor; The process of obtaining the disorder consistency between the input and output ends of the electric meter is as follows: For the three-phase voltage at each acquisition time of the meter input terminal, the average value and the range of the voltage of the three phases are calculated; the ratio of the range to the average value is calculated and recorded as the voltage imbalance; the voltage imbalance of the three-phase voltage at all acquisition times of the meter input terminal is arranged to obtain the voltage disorder sequence of the meter input terminal; Based on the three-phase voltages at all acquisition moments at the output end of the electric meter, a voltage disorder sequence at the output end of the electric meter is obtained in the same manner as that of the voltage disorder sequence at the input end of the electric meter; The correlation between the voltage disorder sequences at the input and output ends of the meter is calculated by a similarity algorithm and recorded as disorder consistency; The expression of the historical instability index of the electric meter at the latest moment is: , where is the historical instability index of the ith meter at the latest moment, is the normalization function, is the phase deviation between the input voltage and output voltage of the ith meter at the latest moment, is the disorder consistency between the input and output terminals of the i-th meter; The process of obtaining the voltage drop run entropy of any phase voltage is as follows: Record the sequence of continuous voltage loss data as voltage loss run, obtain the voltage loss runs of any phase voltage at the input and output ends of each electric meter, and take the number of voltage loss data in each voltage loss run as the length of each voltage loss run; Counting the frequency of each voltage drop run length of each electric meter in all voltage drop run lengths of each electric meter, and calculating the information entropy of the arbitrary phase voltage based on the frequency of all voltage drop run lengths of the arbitrary phase voltage, which is recorded as voltage drop run entropy; The process of obtaining the severe voltage loss factor of each electric meter is as follows: The standard deviation of all the voltage loss data at any phase of the input and output terminals of each meter at the time of collection is recorded as the first standard deviation; the severe voltage loss factor of the ith meter is recorded as , The expression is: , where is the historical instability index of the ith meter at the latest moment; N is the sum of the phase numbers of the input voltage and the output voltage; is the first standard deviation of all voltage loss data in the j-th phase voltage of the i-th meter; is the voltage drop run entropy of the j-th phase voltage of the ith meter.

2. A method for dynamic detection of the operating status of an electric meter box as claimed in claim 1, characterized in that: The process of obtaining the phase deviation degree between the input terminal voltage and the output terminal voltage of the electric meter at the latest moment is as follows: The difference between the in-phase voltages at the input and output ends of the electric meter at the latest moment is calculated and recorded as the first difference; the average value of all the first differences between the input voltage and the output voltage of the electric meter at the latest moment is calculated and recorded as the phase deviation degree.

3. A method for dynamic detection of the operation status of an electric meter box as claimed in claim 1, characterized in that: The voltage loss data is voltage data whose voltage value is outside the normal working range of the electric meter.

4. A method for dynamically detecting the operating status of an electric meter box according to claim 1, characterized in that: The operation status of the electric meter is determined according to the severe pressure loss factor of each electric meter, specifically: If the severe pressure loss factor of each meter is greater than the preset pressure loss threshold, each meter has experienced severe pressure loss and issues an alarm; otherwise, each meter has not experienced severe pressure loss and is in a normal state.

5. A dynamic detection medium for the operation status of an electric meter box, which implements the method as claimed in claim 1, characterized in that: The medium includes: Data acquisition module: collects the three-phase voltages at the input and output ends of each meter in the meter box at each acquisition moment; Electric meter stability analysis module: for each electric meter, the disorder consistency between the input and output ends of the electric meter is constructed based on the correlation degree of the voltage fluctuation between the input and output ends of the electric meter; the phase deviation degree between the input voltage and the output voltage of the electric meter at the latest moment is constructed based on the difference between the same-phase voltages of the input and output ends of the electric meter; the historical instability index of the electric meter at the latest moment is constructed based on the disorder consistency and the phase deviation degree; Electric meter voltage loss degree analysis module: obtain voltage loss data based on the size of voltage data; construct the voltage loss run entropy of any phase voltage based on the continuity of voltage loss data in any phase voltage at the input and output ends of each electric meter; construct the serious voltage loss factor of each electric meter based on the distribution of voltage loss data corresponding to time in any phase voltage and voltage loss run entropy, combined with the historical instability index of each electric meter at the latest moment; Electricity meter operation status detection module: determines the operation status of the electricity meter according to the severe pressure loss factor of each electricity meter.

6. A dynamic detection system for the operation status of an electric meter box, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

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