A ring network box with intelligent power supply data monitoring function

Abstract

The present invention relates to the field of ring network box monitoring technology, and more particularly to a ring network box with an intelligent power supply data monitoring function. The ring network box includes a first acquisition module for acquiring current power supply data of each power supply data type in a power supply data type set at the current monitoring moment, as well as the nearest neighbor power supply data and the nearest neighbor power supply data sequence corresponding to the current power supply data; a second acquisition module for acquiring an abnormality characterization value corresponding to each power supply data type at the current monitoring moment; a third acquisition module for acquiring an affected weight value corresponding to each power supply data type at the current monitoring moment, as well as an associated change characterization value at the current monitoring moment; and a status monitoring module for monitoring the status of the ring network box at the current monitoring moment based on the abnormality characterization value, the change associated characterization value, and the affected weight value. The present invention can improve the reliability and accuracy of monitoring the status of the ring network box.

Description

Technical Field

[0001] The present invention relates to the technical field of ring main box monitoring, and in particular to a ring main box with an intelligent power supply data monitoring function. Background Art

[0002] In the power system, the ring main box is a key distribution equipment. Its stability and reliability are crucial to ensuring the continuity and safety of power supply. Therefore, it is very important to monitor the status of the ring main box.

[0003] In the prior art, the status of a ring main box (RMB) is generally monitored solely through real-time power supply data collected from the RMG. If the power supply data collected by the collection device exceeds a threshold, the RMG is determined to be in an abnormal state. However, the reliability or accuracy of such existing methods for monitoring the RMG status is low. If the collection device is subject to external interference, such as electromagnetic interference, the power supply data collected by the corresponding collection device may also exceed the threshold. However, the power supply data exceeding the threshold caused by such external interference does not indicate an abnormal state of the RMG. However, existing methods for monitoring the RMG status may mistakenly determine that the RMG is in an abnormal state. If a fault such as poor contact occurs within the RMG, such a fault typically causes frequent changes in the collected power supply data, but does not necessarily cause the collected power supply data to exceed the threshold. Therefore, when a fault such as poor contact occurs within the RMG, existing methods for monitoring the RMG status may mistakenly determine that the RMG is in a normal state. Therefore, improving the reliability and accuracy of monitoring the RMG status has become an urgent issue that needs to be addressed. Summary of the Invention

[0004] In order to solve the above problems, the present invention provides a ring main box with intelligent power supply data monitoring function. The technical solutions adopted are as follows:

[0005] One embodiment of the present invention provides a ring mains box with an intelligent power supply data monitoring function, the ring mains box with an intelligent power supply data monitoring function includes:

[0006] A first acquisition module is used to obtain current power supply data of each power supply data type in the power supply data type set at the current monitoring moment, as well as the nearest neighbor power supply data and the neighbor power supply data sequence corresponding to the current power supply data, where the power supply data is the power supply data of the ring network box;

[0007] a second acquisition module, configured to obtain, based on a difference and a slope between the current power supply data and the nearest neighbor power supply data corresponding to the current power supply data, a difference between adjacent power supply data in the nearest neighbor power supply data sequence, and a variance of the nearest neighbor power supply data sequence, an abnormality characterization value corresponding to each power supply data type at the current monitoring moment;

[0008] The third acquisition module is used to obtain the transition sequence corresponding to each power supply data type at the current monitoring moment, and obtain the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment according to the transition sequence;

[0009] The status monitoring module is used to monitor the status of the ring network box at the current monitoring moment according to the abnormality characterization value, the change association characterization value and the affected weight value.

[0010] Beneficial effects: The present invention includes a first acquisition module for acquiring the current power supply data of each power supply data type in the power supply data type set at the current monitoring moment, as well as the nearest neighbor power supply data and the neighbor power supply data sequence corresponding to the current power supply data; a second acquisition module for obtaining the abnormal characterization value corresponding to each power supply data type at the current monitoring moment based on the difference and slope between the current power supply data and the nearest neighbor power supply data corresponding to the current power supply data, the difference between adjacent power supply data in the neighbor power supply data sequence, and the variance of the neighbor power supply data sequence; a third acquisition module for obtaining the turning sequence corresponding to each power supply data type at the current monitoring moment, and obtaining the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change characterization value at the current monitoring moment based on the turning sequence; a status monitoring module for monitoring the ring network box status at the current monitoring moment based on the abnormal characterization value, the change associated characterization value, and the affected weight value. Moreover, the present invention can improve the reliability and accuracy of monitoring the ring network box status based on the abnormal characterization value, the change associated characterization value, and the affected weight value. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 This is a structural block diagram of a ring network box with intelligent power supply data monitoring function of the present invention. DETAILED DESCRIPTION

[0013] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field fall within the scope of protection of the embodiments of the present invention.

[0014] 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 invention pertains.

[0015] This embodiment provides a ring network box with intelligent power supply data monitoring function, which is described in detail as follows:

[0016] like Figure 1 As shown, this embodiment provides a ring network box with an intelligent power supply data monitoring function, including:

[0017] The first acquisition module 01 is configured to acquire current power supply data of each power supply data type in a power supply data type set at a current monitoring moment, and the nearest neighbor power supply data and the nearest neighbor power supply data sequence corresponding to the current power supply data.

[0018] The purpose of this embodiment is to improve the reliability or accuracy of monitoring the status of the ring network box. The ring network box in this embodiment is mainly used in daily application places such as residential communities and high-rise buildings. For ease of understanding, this embodiment will subsequently analyze the status monitoring process of the ring network box in any operation process as an example.

[0019] First, all power supply data types of the ring main box are obtained, and the set constructed from all power supply data types of the ring main box is recorded as the power supply data type set. The power supply data types include but are not limited to voltage, current, grid frequency, and ambient temperature inside the box. Voltage refers to the potential difference between conductors in the main circuit of the ring main box and is a physical quantity that measures the electric field energy transmission capacity. Current refers to the directional flow of charge in the conductor of the ring main box and represents the amount of charge passing through the conductor cross-section per unit time. Grid frequency refers to the rate of periodic change of alternating current, measured in Hertz (Hz), and reflects the supply and demand balance of the power system. In a power system, if an abnormal state occurs in the ring main box, the power supply data of the ring main box will change. Therefore, the status of the ring main box is currently monitored by analyzing the power supply data of the ring main box. All subsequent power supply data belongs to the power supply data of the ring main box. In addition, an abnormal state of the ring main box mainly refers to an operational failure of the ring main box, such as poor contact inside the ring main box.

[0020] Next, this embodiment uses the power supply data of the ring network box collected by the collection device at each monitoring moment. For example, the ambient temperature inside the box can be collected by a temperature sensor, and the power supply data of each power supply data type belonging to the power supply data type set can be obtained at each monitoring moment, that is, the collection method of all power supply data types of the ring network box is synchronous collection, and the collected data will be stored in the database; then the power supply data of each power supply data type belonging to the power supply data type set collected at the current monitoring moment is recorded as the current power supply data of each power supply data type in the power supply data type set at the current monitoring moment, that is, for any power supply data type, the ring network box power supply data belonging to the power supply data type collected at the current monitoring moment is the current power supply data of the power supply data type at the current monitoring moment. For example, for the ambient temperature data type inside the box, the current power supply data of the ambient temperature data type inside the box at the current monitoring moment is the ambient temperature data inside the box collected at the current monitoring moment.

[0021] In addition, it should be noted that the voltage, current, ambient temperature inside the box, etc. in this embodiment are collected by sensors, and the grid frequency can be obtained through the zero detection method, that is, by detecting the zero crossing point of the waveform of the AC voltage or current, the time interval between two adjacent zero crossing points can be calculated to obtain the grid frequency; and in this embodiment, the implementer also needs to set the data acquisition frequency according to actual conditions, that is, the time interval between adjacent monitoring moments. For example, in this embodiment, the time interval between adjacent monitoring moments can be set to 1 second.

[0022] After obtaining the current power supply data, the nearest neighbor power supply data and the nearest neighbor power supply data sequence corresponding to the current power supply data are obtained. The nearest neighbor power supply data and the nearest neighbor power supply data sequence are key data for subsequent accurate monitoring of the ring network box status. Therefore, the specific acquisition process of the nearest neighbor power supply data and the nearest neighbor power supply data sequence corresponding to the current power supply data of each power supply data type in the power supply data type set at the current monitoring moment is as follows:

[0023] For any power data type in the power data type set; first obtain the power data belonging to the power data type collected at the previous historical monitoring moment of the current monitoring moment, and record it as the nearest neighbor power data corresponding to the current power data of the power data type at the current monitoring moment, the previous historical monitoring moment of the current monitoring moment is the historical monitoring moment closest to the current monitoring moment; then obtain a set constructed by a preset number of consecutive historical monitoring moments adjacent to the current monitoring moment, and record it as the historical monitoring moment set, then obtain the power data belonging to the power data type collected at each historical monitoring moment in the historical monitoring moment set, and record the power data belonging to the power data type collected at each historical monitoring moment in the historical monitoring moment set as the historical power data of the power data type at the corresponding historical monitoring moment, then record the time series constructed by the current power data of the power data type obtained at the current monitoring moment and the historical power data of the power data type at all historical monitoring moments in the historical monitoring moment set as the nearest neighbor power data sequence corresponding to the current power data of the power data type at the current monitoring moment. In this embodiment, the implementer needs to set the value of the preset number according to the actual situation and experimental statistics, such as the value of the preset number can be set to 5.

[0024] Therefore, this embodiment can obtain the current power supply data of each power supply data type in the power supply data type set at the current monitoring moment and the nearest neighbor power supply data and the neighbor power supply data sequence corresponding to the current power supply data through the above process.

[0025] The second acquisition module 02 is used to obtain the abnormal characterization value corresponding to each power supply data type at the current monitoring moment based on the difference and slope between the current power supply data and the nearest neighbor power supply data corresponding to the current power supply data, the difference between adjacent power supply data in the neighbor power supply data sequence, and the variance of the neighbor power supply data sequence.

[0026] Currently, the status of the ring network box is generally monitored by whether the power supply data collected in real time exceeds the threshold. However, the interference of external factors on the collection equipment may also cause the collected power supply data to exceed the threshold. For example, when a certain collection equipment is subject to external interference such as electromagnetic interference, the power supply data collected by the corresponding collection equipment may exceed the threshold. However, the situation where the collected power supply data exceeds the threshold caused by such external interference does not mean that the ring network box is in an abnormal state. That is, although the collected power supply data exceeds the threshold at this time, the ring network box may still be in normal operation. Therefore, it can be seen that the interference of external factors on the collection equipment will cause the existing monitoring method to monitor the status of the ring network box. False monitoring phenomenon occurs, resulting in low monitoring reliability or accuracy. That is, the interference of external factors on the collection equipment will cause the ring network box in normal operation to be judged as an abnormal state. Since not all ring Any network box failure will cause the power supply data of the ring network box to exceed the specified range. For example, a poor contact failure inside the ring network box will usually cause the collected power supply data to change frequently, but it will not necessarily cause the collected power supply data to exceed the threshold. Therefore, when a poor contact failure or other failure occurs inside the ring network box, based on the existing monitoring method, the poor contact failure or other failure inside the ring network box will be mistakenly judged as the ring network box being in a normal state, which will also lead to low monitoring reliability or accuracy. In order to avoid the problem of low monitoring reliability or accuracy caused by the above situation, this embodiment will combine the change characteristics of the power supply data when it is interfered by external factors, the data change characteristics when the ring network box fails but the power supply data does not exceed the threshold, the change correlation between different power supply data types, and the situation where data of different power supply data types are affected by other types of data to achieve accurate monitoring of the ring network box status.

[0027] Therefore, this embodiment will first combine the change characteristics of the power supply data when it is interfered by external factors and the data change characteristics when the ring network box fails but the power supply data does not exceed the threshold to obtain the abnormal characterization value corresponding to each power supply data type at the previous monitoring moment, that is, this embodiment will then obtain the abnormal characterization value corresponding to each power supply data type at the current monitoring moment based on the difference and slope between the current power supply data of each power supply data type at the current monitoring moment and the nearest neighbor power supply data corresponding to the current power supply data, the difference between adjacent power supply data in the neighboring power supply data sequence corresponding to the current power supply data of each power supply data type at the current monitoring moment, and the variance of the neighboring power supply data sequence corresponding to the current power supply data of each power supply data type at the current monitoring moment. The abnormal characterization value is a key parameter reflecting whether the ring network box is in an abnormal state. Then the specific acquisition process of the abnormal characterization value corresponding to each power supply data type at the current monitoring moment is: for any power supply data type in the power supply data type set:

[0028] First, obtain the preset threshold range corresponding to the power supply data type. The preset threshold ranges corresponding to different power supply data types are usually determined by the grid demand, the parameters of the ring network box, and the requirements for ensuring the stability and safety of the ring network box operation. For example, if the power supply data type is a voltage data type and the rated voltage of the main circuit of the ring network box used is 12kV, then in order to ensure the stability and safety of the ring network box operation, it is usually required that the actual voltage of the ring network box be maintained within the range of ±10% of the rated voltage. Based on this, the preset threshold range corresponding to the voltage data type is [12kV×90%,12kV×110%].

[0029] After obtaining the preset threshold interval corresponding to the power supply data type, the nearest neighbor power supply data corresponding to the current power supply data of the power supply data type is recorded as the first data, and the neighbor power supply data sequence corresponding to the current power supply data of the power supply data type is recorded as the first sequence; then, it is determined whether the current power supply data of the power supply data type exceeds the preset threshold interval corresponding to the power supply data type. If it is determined that the current power supply data of the power supply data type is not within the preset threshold interval corresponding to the power supply data type, then according to the difference and slope between the current power supply data of the power supply data type and the first data and the difference between the adjacent power supply data in the first sequence, the power supply data corresponding to the power supply data type at the current monitoring moment is obtained. The abnormal characterization value of the power supply data type is obtained, and if it is determined that the current power supply data of the power supply data type is within the preset threshold interval corresponding to the power supply data type, then according to the slope between the current power supply data of the power supply data type and the first data and the variance of the first sequence, the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is obtained; in addition, it should be noted that when the current power supply data of the power supply data type is not within the preset threshold interval corresponding to the power supply data type, it indicates that the current power supply data of the power supply data type is suspected abnormal data, but the suspected abnormal data may also be caused by external interference to the data acquisition device, that is, the suspected abnormal data may also be normal data, and the suspected abnormal data caused by external interference may be normal data. Abnormal data has the characteristics of randomness and suddenness, and in this embodiment, the difference and slope between the current power supply data of the power supply data type and the first data and the difference between the adjacent power supply data in the first sequence are analyzed to reflect the degree of obviousness of the randomness and suddenness of the current power supply data of the power supply data type, and the degree of obviousness of the randomness and suddenness of the current power supply data of the power supply data type can characterize the possibility that the current power supply data of the power supply data type is abnormal data, and the abnormal data is caused by the abnormal operation state of the ring network box; when the current power supply data of the power supply data type is within the preset threshold interval corresponding to the power supply data type When , it indicates that the current power supply data of the power supply data type is suspected normal data, but the suspected normal data may also be caused by abnormal conditions such as poor contact inside the ring network box, that is, the suspected normal data may also be abnormal data. The abnormal conditions such as poor contact inside the ring network box will cause the collected data to have mutations and frequent changes. Moreover, the slope between the current power supply data of the power supply data type and the first data and the variance of the first sequence can reflect the obvious degree of mutation and frequent changes of the current power supply data of the power supply data type. The obvious degree of mutation and frequent changes can characterize the possibility that the current power supply data of the power supply data type is abnormal data.

[0030] In this embodiment, the specific process of obtaining the abnormal characterization value corresponding to the power supply data type at the current monitoring moment based on the difference and slope between the current power supply data and the first data of the power supply data type and the difference between adjacent power supply data in the first sequence is: first, construct a coordinate system corresponding to the power supply data type, the vertical axis of the coordinate system corresponding to the power supply data type represents the value of the power supply data belonging to the power supply data type, and the horizontal axis represents the time; then, the current power supply data of the power supply data type, the acquisition time of the current power supply data of the power supply data type, the first data, and the acquisition time of the first data are all mapped to the coordinate system corresponding to the power supply data type, and the data point corresponding to the current power supply data of the power supply data type and the data point corresponding to the first data are obtained, and are recorded as the first data point and the second data point respectively, and the horizontal coordinate of the first data point is the power supply data type. The acquisition time of the current power supply data, the vertical axis is the current power supply data of the power supply data type, the horizontal axis of the second data point is the acquisition time of the first data, and the vertical axis is the first data; then the absolute value of the slope between the first data point and the second data point is obtained, and recorded as the slope characterization value of the power supply data type at the current monitoring moment, the slope between the two data points is the slope of the straight line formed by the two data points, the slope characterization value of the power supply data type at the current monitoring moment is normalized, and the normalized value obtained by the normalization process is recorded as the first characterization value, and the result of subtracting the first to-be-processed value from the preset constant is the normalized value obtained by normalizing the slope characterization value of the power supply data type at the current monitoring moment, the first to-be-processed value is the inverse obtained by adding the slope characterization value of the power supply data type at the current monitoring moment to the preset constant, and the first characterization value is ,in, is a preset constant, K is the slope between the first data point and the second data point, The larger the value, the more obvious the mutation degree of the current power supply data of the power supply data type; and in specific applications, the implementer needs to set a preset constant according to the actual situation. For example, in this embodiment, the preset constant is set to 1. The role of the preset constant in this embodiment includes realizing parameter normalization and preventing the denominator from being 0. Then, the absolute value of the difference between the current power supply data of the power supply data type and the first data is obtained, and recorded as the first difference value of the power supply data type at the current monitoring moment. The first difference is normalized, and the normalized value obtained by the normalization is recorded as the second characterization value, and the result of subtracting the second value to be processed from the preset constant is the normalized value obtained by normalizing the first difference. The second value to be processed is the inverse of the result obtained by adding the first difference and the preset constant. The second characterization value is , d is the difference between the current power supply data and the first data of the power supply data type, The larger the value, the greater the change. This indicates that the current power supply data of the power supply data type has undergone a significant change, and also indicates that the degree of mutation of the current power supply data of the power supply data type is more obvious. Then, a difference sequence of the first sequence is obtained, and the ath difference in the difference sequence is the absolute value of the difference between the ath power supply data and the a+1th power supply data in the first sequence; then, the absolute value of the difference between the first difference and the mean of the difference sequence is obtained, and the absolute value of the difference between the first difference and the mean of the difference sequence is normalized, and the result obtained by the normalization is recorded as the third characterization value, and the result of the preset constant minus the third value to be processed is the normalized value obtained by normalizing the first difference, and the second value to be processed is the reciprocal of the result obtained by adding the absolute value of the difference between the first difference and the mean of the difference sequence to the preset constant, and the third characterization value is the result of the normalization of the first difference. , is the difference between the first difference and the mean of the difference sequence, when When the value is larger, it indicates that the first difference is not universal, then the probability that the current power supply data of the power supply data type is extreme data or accidental data is greater, that is, the accidental characteristics of the current power supply data of the power supply data type are more obvious. Finally, the weighted sum of the first characterization value, the second characterization value, and the third characterization value is obtained, and recorded as the first weighted fusion characterization value. The result of subtracting the weighted fusion characterization value from the preset constant is recorded as the abnormal characterization value corresponding to the power supply data type at the current monitoring moment. The larger the abnormal characterization value, the greater the probability that the ring network box has an abnormal operating state at the current monitoring moment. The first weighted fusion characterization value is , F1 is the first characterization value, F2 is the second characterization value, F3 is the third characterization value, w1 is the first weight, and w2 is the second weight; and when the first characterization value, the second characterization value and the third characterization value are larger, it indicates that the possibility of the device collecting the power supply data type at the current monitoring moment being interfered with by the outside world is greater, and it also indicates that the possibility of the current power supply data of the power supply data type being abnormal data is smaller, that is, when the first weighted fusion characterization value is larger, it indicates that the possibility of the current power supply data of the power supply data type being abnormal data is smaller, then the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is smaller; on the contrary, when the first weighted fusion characterization value is smaller, that is, the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is larger, it indicates that the probability of being interfered with by the outside world when collecting the current power supply data of the power supply data type is smaller, indicating that the probability of the current power supply data of the power supply data type being abnormal data is greater, and also indicating that the probability of the ring network box being in an abnormal operating state at the current monitoring moment is greater.

[0031] In this embodiment, according to the slope between the current power supply data and the first data of the power supply data type and the variance of the first sequence, the specific process of obtaining the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is as follows: first, obtain the inverse of the slope characterization value of the power supply data type at the current monitoring moment and add the preset constant, and record it as the slope characteristic value; then obtain the variance of the first sequence, record the inverse of the sum of the preset constant and the variance of the first sequence as the variance characteristic value, and record the weighted sum of the variance characteristic value and the slope characteristic value as the second weighted fusion characterization value, and the second weighted fusion characterization value is , is the slope eigenvalue, The larger the value is, the more obvious the mutation degree of the current power supply data of the power supply data type is. is the variance of the first series, When the value is larger, it indicates that the data belonging to the power supply data type has the characteristics of frequent changes or the changes are more unstable. w3 is the third weight value, and w4 is the fourth weight value. Finally, the result of subtracting the second weighted fusion characterization value from the preset constant is recorded as the abnormal characterization value corresponding to the power supply data type at the current monitoring moment. The bigger and When the value is larger, it indicates that the probability that the current power supply data of the power supply data type is abnormal data is greater. On the contrary, when The smaller and The smaller the value, the greater the probability that the current power supply data of the power supply data type is normal data. The bigger and The larger the value is, the smaller the second weighted fusion characterization value is and the larger the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is. Therefore, when the second weighted fusion characterization value is smaller or the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is larger, it indicates that the probability that the current power supply number of the power supply data type is abnormal data is greater, and it also indicates that the probability that there is an operating fault in the ring network box is greater or the probability that the ring network box is in an abnormal operating state at the current monitoring moment is greater.

[0032] In specific applications, implementers need to set the values ​​of w1, w2, w3, and w4 based on actual conditions or differences in the importance of abnormal characterization values. For example, when excluding data affected by external interference from suspected abnormal data, mutation characteristics are more important, so the value of w1 can be set to 0.6 and the value of w2 can be set to 0.4. When screening abnormal data from suspected normal data, the feature of frequent data changes is more important, so the value of w3 can be set to 0.4 and the value of w4 can be set to 0.6.

[0033] Therefore, this embodiment can obtain the abnormal characterization value corresponding to each power supply data type at the current monitoring moment through the above process.

[0034] The third acquisition module 03 is used to obtain the transition sequence corresponding to each power supply data type at the current monitoring moment, and obtain the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment according to the transition sequence.

[0035] In order to further improve the reliability and accuracy of the ring network box status monitoring, this embodiment, after obtaining the abnormal characterization value corresponding to each power supply data type at the current monitoring moment, continues to obtain the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change characterization value at the current monitoring moment; and the reason for obtaining the affected weight value corresponding to each power supply data type at the current monitoring moment is because the affected weight value can reflect the influence of different power supply data types on the data of other power supply data types or the influence of different power supply data types on the data of other power supply data types. When the influence of the data of other power supply data types is greater, that is, the affected weight value corresponding to the corresponding power supply data type is greater, it indicates that the corresponding power supply data type can better reflect the operating status of the ring network box, and also indicates that the corresponding power supply data type is more sensitive to the status change of the ring network box. If the affected weight value corresponding to a certain power supply data type is greater, And at this time, there is an operational fault that causes the data belonging to this power supply data type to become abnormal. Then, at this time, the data abnormality belonging to this power supply data type will cause the data of other power supply data types to become abnormal. Therefore, in order to improve the monitoring accuracy, when subsequently determining the status of the ring network box, the participation of the abnormal characterization value corresponding to the power supply data type at the current monitoring moment should be higher; and the reason for obtaining the associated change characterization value at the current monitoring moment is because the associated change characterization value can reflect that the various power supply data of the ring network box at the current monitoring moment have changed compared with the historical power supply data, but the change at this time is not caused by the influence of different power supply data on each other. When the various power supply data of the ring network box have changed compared with the historical power supply data, and these changes are not caused by the influence of different power supply data on each other, it indicates that the probability of abnormal operation of the ring network box at the current monitoring moment will be relatively large, so it is necessary to increase the attention to the ring network box at this time.

[0036] Based on the above analysis, it can be seen that this embodiment further needs to obtain the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment. However, in this embodiment, before obtaining the affected weight value and the associated change representation value, it is necessary to first obtain the turning sequence corresponding to each power supply data type at the current monitoring moment. That is, the turning sequence is the key to the subsequent analysis of obtaining the affected weight value and the associated change representation value. Then, the specific process of obtaining the turning sequence corresponding to each power supply data type at the current monitoring moment is as follows:

[0037] For any power supply data type: first, obtain the slope characterization value of the power supply data type at the historical monitoring moment, and the method for obtaining the slope characterization value of the power supply data type at the historical monitoring moment is the same as the method for obtaining the slope characterization value of the power supply data type at the current monitoring moment, so it will not be described in detail; then, the slope characterization value of the power supply data type at the historical monitoring moment is normalized, and the normalization result is recorded as the turning characterization value of the power supply data type at the corresponding historical monitoring moment, and the method for normalizing the slope characterization value of the power supply data type at the historical monitoring moment here is consistent with the above-mentioned method for normalizing the slope characterization value of the power supply data type at the current monitoring moment; then, obtain the historical monitoring moment closest to the current monitoring moment and whose turning characterization value is greater than the preset turning threshold, and record it as the nearest neighbor turning monitoring moment corresponding to the power supply data type at the current monitoring moment, and finally obtain the nearest neighbor turning monitoring moment corresponding to the power supply data type at the current monitoring moment. The time series consisting of all power supply data belonging to the power supply data type collected between the historical monitoring moment and the current monitoring moment is recorded as the turning sequence corresponding to the power supply data type at the current monitoring moment; if the turning characterization values ​​of the power supply data type at all historical monitoring moments from the next historical monitoring moment of the historical monitoring moment t to the current monitoring moment are not greater than the preset turning threshold, and the turning characterization values ​​of the power supply data type at the historical monitoring moment t are all greater than the preset turning threshold, then the historical monitoring moment t is recorded as the nearest neighbor turning monitoring moment corresponding to the power supply data type at the current monitoring moment, and the time series consisting of all power supply data belonging to the power supply data type collected between the historical monitoring moment t and the current monitoring moment is the turning sequence corresponding to the power supply data type at the current monitoring moment; in addition, in specific applications, the implementer needs to determine the preset turning threshold based on actual conditions and experimental statistics. For example, after experimental statistics, the preset turning threshold in this embodiment is 0.3.

[0038] After obtaining the transition sequence corresponding to the power supply data type at the current monitoring moment, the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment are obtained according to the transition sequence corresponding to each power supply data type at the current monitoring moment.

[0039] In this embodiment, the specific process of obtaining the affected weight value corresponding to each power supply data type at the current monitoring time is as follows: first, all power supply data types in the power supply data type set are permuted and combined without repetition to obtain all power supply data type combinations. The permutation and combination process is a well-known technique and is therefore not described in detail in this embodiment. Then, based on the nearest neighbor turning monitoring time and turning sequence corresponding to each power supply data type in each power supply data type combination at the current monitoring time, the impact index value corresponding to each power supply data type combination at the current monitoring time is obtained. Then, the impact index value corresponding to each power supply data type combination at the historical monitoring time is obtained. The method for obtaining the impact index value corresponding to each power supply data type combination at the historical monitoring time is the same as the method for obtaining the impact index value corresponding to each power supply data type combination at the current monitoring time and is therefore not described in detail. Then, based on the impact index value corresponding to each power supply data type combination at the historical monitoring time and the impact index value corresponding to each power supply data type combination at the current monitoring time, the affected weight value corresponding to each power supply data type at the current monitoring time is obtained. If the affected weight value corresponding to each power supply data type at the current monitoring time is larger, it indicates that the participation degree of the abnormal characterization value corresponding to the corresponding power supply data type at the current monitoring time should be higher when determining the status of the ring network box.

[0040] In this embodiment, according to the nearest neighbor turning monitoring moment and turning sequence corresponding to each power supply data type in each power supply data type combination at the current monitoring moment, the specific process of obtaining the impact index value corresponding to each power supply data type combination at the current monitoring moment is as follows: first, obtain the time interval between the nearest neighbor turning monitoring moment of each power supply data type at the current monitoring moment and the current monitoring moment, and record it as the time distance of the corresponding power supply data type at the current monitoring moment; then obtain the number of extreme values ​​in the turning sequence corresponding to each power supply data type at the current monitoring moment, and use it as the trend change characterization value corresponding to the corresponding power supply data type at the current monitoring moment, and the extreme values ​​include minimum values ​​and maximum values; then take the acquisition process of the impact index value corresponding to any power supply data type combination A at the current monitoring moment as an example to describe, that is, the acquisition process of the impact index value corresponding to the power supply data type combination A at the current monitoring moment is: record the two power supply data types in the power supply data type combination A as power supply data type A1 and power supply data type A2 respectively, record the absolute value of the difference between the time distance of the power supply data type A1 at the current monitoring moment and the time distance of the power supply data type A2 at the current monitoring moment as the first change index value corresponding to the power supply data type combination A, and when the power supply data type combination A corresponds to The smaller the first change index value is, the closer the time when the data changes of the two types of data, power supply data type A1 and power supply data type A2, are. It also indicates that the data belonging to power supply data type A1 at the current monitoring moment may have a greater impact on the data belonging to power supply data type A2, or the data belonging to power supply data type A2 at the current monitoring moment may have a greater impact on the data belonging to power supply data type A1, and the impact index value corresponding to the power supply data type combination A at the current monitoring moment is also greater; the absolute value of the difference between the trend change characterization value corresponding to the power supply data type A1 at the current monitoring moment and the trend change characterization value corresponding to the power supply data type A2 at the current monitoring moment is recorded as the second change index value corresponding to the power supply data type combination A, and when the second change index value corresponding to the power supply data type combination A is smaller, it indicates that the probability that the trends of the two types of data, power supply data type A1 and power supply data type A2, are synchronously changing is greater, and it also indicates that the data belonging to power supply data type A1 at the current monitoring moment may have a greater impact on the data belonging to power supply data type A2, or the data belonging to power supply data type A2 at the current monitoring moment may have a greater impact on the data belonging to power supply data type A1, and the impact index value corresponding to the power supply data type combination A at the current monitoring moment is greater;Finally, the reciprocal of the sum of the first change index value and the preset constant and the reciprocal of the sum of the second change index value and the preset constant are obtained, and are recorded as the first reciprocal value and the second reciprocal value respectively. The average of the first reciprocal value and the second reciprocal value is used as the impact index value corresponding to the power supply data type combination A at the current monitoring moment. The specific expression of the impact index value corresponding to the power supply data type combination A at the current monitoring moment is: , where t1 is the time distance of the power supply data type A1 at the current monitoring moment, t2 is the time distance of the power supply data type A2 at the current monitoring moment, g1 is the trend change representation value corresponding to the power supply data type A1 at the current monitoring moment, and g2 is the trend change representation value corresponding to the power supply data type A2 at the current monitoring moment.

[0041] In this embodiment, according to the impact index values ​​corresponding to each power supply data type combination at the historical monitoring moment and the impact index values ​​corresponding to each power supply data type combination at the current monitoring moment, the specific process of obtaining the affected weight values ​​corresponding to each power supply data type at the current monitoring moment is as follows: for any power supply data type: first, among all power supply data type combinations, all power supply data type combinations containing the power supply data type are recorded as feature combinations, and the impact index value set corresponding to each feature combination at the current monitoring moment is obtained, and the impact index value set corresponding to any feature combination at the current monitoring moment is composed of the impact index value corresponding to the feature combination at the current monitoring moment and the impact index values ​​corresponding to the feature combination at the consecutive preset number of historical monitoring moments closest to the current monitoring moment. If the preset number in this embodiment is 5 and the current monitoring moment is the jth monitoring moment, then from the j-5th monitoring moment, the impact index value set corresponding to each feature combination at the current monitoring moment is composed of the impact index value corresponding to the feature combination at the current monitoring moment and the impact index value ..., The combination of the impact index values ​​corresponding to the feature combination obtained between the monitoring moment and the jth monitoring moment is the impact index value set corresponding to the feature combination at the current monitoring moment, and the impact index value set includes the impact index values ​​corresponding to the feature combination at the j-5th monitoring moment and the jth monitoring moment; then the mean of the impact index value set corresponding to each feature combination at the current monitoring moment is obtained, and recorded as the comprehensive index value corresponding to the corresponding feature combination at the current monitoring moment; then the mean of the comprehensive index values ​​corresponding to all feature combinations at the current monitoring moment is obtained, and the mean of the comprehensive index values ​​corresponding to all feature combinations at the current monitoring moment is normalized, and the result of the normalization is used as the affected weight value corresponding to the power supply data type at the current monitoring moment. Here, the normalization function Norm() is used to normalize the mean of the comprehensive index values ​​corresponding to all feature combinations at the current monitoring moment.

[0042] In this embodiment, the specific process of obtaining the associated change characterization value at the current monitoring moment is: first, obtain the change impact characterization value corresponding to all power supply data type combinations at the current monitoring moment, and record the average of the change impact characterization values ​​corresponding to all power supply data type combinations at the current monitoring moment as the associated change characterization value at the current monitoring moment. The larger the change impact characterization value corresponding to all power supply data type combinations at the current monitoring moment or the larger the associated change characterization value at the current monitoring moment, the greater the probability of data changes occurring in multiple power supply data types at the current monitoring moment, and the smaller the probability that the data changes occurring at this time are caused by the influence between different power supply data types, then the probability of abnormal operation of the ring network box at the current monitoring moment will also be relatively large.

[0043] And the specific acquisition process of the change impact characterization value corresponding to the power supply data type combination at the current monitoring moment is: for the power supply data type combination A: first, the absolute value of the difference between the inverse of the first difference of the power supply data type A1 at the current monitoring moment and the inverse of the first difference of the power supply data type A2 at the current monitoring moment is recorded as the first characteristic difference. The first characteristic difference can reflect the change similarity between the power supply data type A1 and the power supply data type A2 at the current moment, and the smaller the more similar, that is, the first characteristic difference is the absolute value of the inverse difference between the first difference of the power supply data type A1 at the current monitoring moment and the first difference of the power supply data type A2 at the current monitoring moment; then the inverse of the result obtained by adding the preset constant and the first characteristic difference is obtained, and recorded as the change similarity characteristic value corresponding to the power supply data type combination A, and the result of subtracting the influence index value corresponding to the power supply data type combination A from the preset constant is obtained, and recorded as the second characteristic difference; then the result obtained by multiplying the second characteristic difference and the change similarity characteristic value corresponding to the power supply data type combination A is obtained, and recorded as the change impact characterization value corresponding to the power supply data type combination A at the current monitoring moment.

[0044] Therefore, this embodiment obtains the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment through the above process.

[0045] The state monitoring module 04 is configured to monitor the state of the ring network box at the current monitoring moment according to the abnormality characterization value, the change association characterization value and the affected weight value.

[0046] After obtaining the abnormal characterization value corresponding to each power supply data type at the current monitoring moment, the affected weight value corresponding to each power supply data type at the current monitoring moment, and the associated change characterization value at the current monitoring moment, this embodiment obtains the ring network box state determination index value at the current monitoring moment based on the abnormal characterization value corresponding to each power supply data type at the current monitoring moment, the affected weight value corresponding to each power supply data type at the current monitoring moment, and the associated change characterization value at the current monitoring moment. The specific process of obtaining the ring network box state determination index value at the current monitoring moment is as follows:

[0047] The weighted abnormal characterization value corresponding to each power supply data type at the current monitoring moment is obtained, and the weighted abnormal characterization value corresponding to any power supply data type at the current monitoring moment is the product of the abnormal characterization value corresponding to the power supply data type at the current monitoring moment and the affected weight value corresponding to the power supply data type at the current monitoring moment; then the cumulative sum of the weighted abnormal characterization values ​​corresponding to all power supply data types at the current monitoring moment is obtained, and the average value of the result obtained by adding the cumulative sum of the weighted abnormal characterization values ​​corresponding to all power supply data types at the current monitoring moment and the associated change characterization value at the current monitoring moment is recorded as the ring network box status judgment index value at the current monitoring moment, that is, the expression of the ring network box status judgment index value at the current monitoring moment is , H is the cumulative sum of the weighted abnormal characterization values ​​corresponding to all power supply data types at the current monitoring moment, and Z is the ring network box state determination index value at the current monitoring moment; then, it is determined whether the ring network box state determination index value at the current monitoring moment is greater than a preset determination threshold value. If so, it is determined that the ring network box at the current monitoring moment has an abnormal operating state; otherwise, it is determined that the ring network box at the current monitoring moment is in a normal operating state; and in specific applications, the implementer needs to set the preset determination threshold value based on actual conditions, experimental statistics, and the value range of the ring network box state determination index value. For example, in this embodiment, the preset determination threshold value is set to 0.4.

[0048] In addition, as another embodiment, the state of the ring network box and the processing method can also be determined according to multiple preset judgment intervals. If the ring network box state judgment index value at the current monitoring moment belongs to the preset first judgment interval, the ring network box at the current monitoring moment is determined to be in normal operating state and no warning is issued. If the ring network box state judgment index value at the current monitoring moment belongs to the preset second judgment interval, a first-level warning is issued to remind the staff to pay attention to the subsequent state of the ring network box. If the ring network box state judgment index value at the current monitoring moment belongs to the preset third judgment interval, a second-level warning is issued to inform the staff of the possibility of a fault in the ring network box. The ring network box status determination index value at the current monitoring moment is relatively high and requires immediate inspection. If the ring network box status determination index value at the current monitoring moment falls within the preset fourth determination interval, a level 3 warning is issued to notify the staff that the ring network box is operating abnormally and to immediately shut down the ring network box for inspection and maintenance. In this embodiment, the implementer also needs to set the determination interval based on actual conditions, experimental statistics, and the value range of the ring network box status determination index value. For example, in this embodiment, the preset first determination interval can be set to [0, 0.2], the preset second determination interval can be set to (0.2, 0.4], the preset third determination interval can be set to (0.4, 0.6], and the preset fourth determination interval can be set to (0.6, 1].

[0049] So far, this embodiment has completed the monitoring of the ring network box status.

[0050] In summary, this embodiment includes a first acquisition module for acquiring the current power supply data of each power supply data type in the power supply data type set at the current monitoring moment, as well as the nearest neighbor power supply data and the neighbor power supply data sequence corresponding to the current power supply data; a second acquisition module for obtaining the abnormal characterization value corresponding to each power supply data type at the current monitoring moment based on the difference and slope between the current power supply data and the nearest neighbor power supply data corresponding to the current power supply data, the difference between adjacent power supply data in the neighbor power supply data sequence, and the variance of the neighbor power supply data sequence; a third acquisition module for obtaining the turning sequence corresponding to each power supply data type at the current monitoring moment, and obtaining the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change characterization value at the current monitoring moment based on the turning sequence; a status monitoring module for monitoring the ring network box status at the current monitoring moment based on the abnormal characterization value, the change associated characterization value, and the affected weight value. Moreover, this embodiment can improve the reliability and accuracy of monitoring the ring network box status based on the abnormal characterization value, the change associated characterization value, and the affected weight value.

[0051] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A ring main box with intelligent power supply data monitoring function, characterized in that: The ring network box with intelligent power supply data monitoring function includes: A first acquisition module is used to obtain current power supply data of each power supply data type in the power supply data type set at the current monitoring moment, as well as the nearest neighbor power supply data and the neighbor power supply data sequence corresponding to the current power supply data, where the power supply data is the power supply data of the ring network box; a second acquisition module, configured to obtain, based on the difference and slope between the current power supply data and the nearest neighbor power supply data corresponding to the current power supply data, the difference between adjacent power supply data in the nearest neighbor power supply data sequence, and the variance of the nearest neighbor power supply data sequence, the abnormality characterization value corresponding to each power supply data type at the current monitoring moment; The third acquisition module is used to obtain the transition sequence corresponding to each power supply data type at the current monitoring moment, and obtain the affected weight value corresponding to each power supply data type at the current monitoring moment and the associated change representation value at the current monitoring moment according to the transition sequence; A status monitoring module is used to monitor the status of the ring network box at the current monitoring moment according to the abnormal characterization value, the change association characterization value and the affected weight value; The method for obtaining the turning sequence includes: for any power supply data type, obtaining the slope characterization value of the power supply data type at the historical monitoring moment, and using the normalized value of the slope characterization value of the power supply data type at the historical monitoring moment as the turning characterization value of the power supply data type at the corresponding historical monitoring moment; obtaining the historical monitoring moment closest to the current monitoring moment and with a turning characterization value greater than a preset turning threshold, and recording it as the nearest neighbor turning monitoring moment corresponding to the power supply data type at the current monitoring moment; recording the time series consisting of all power supply data belonging to the power supply data type collected between the nearest neighbor turning monitoring moment and the current monitoring moment as the turning sequence corresponding to the power supply data type at the current monitoring moment; The method for obtaining the affected weight value corresponding to each power supply data type at the current monitoring moment includes: Perform pairwise non-repeating permutations and combinations on all power supply data types in the power supply data type set to obtain all power supply data type combinations; obtain the impact index value corresponding to the power supply data type combination at the current monitoring time based on the nearest neighbor turning monitoring time and turning sequence corresponding to each power supply data type in the power supply data type combination at the current monitoring time; For any power supply data type: among all power supply data type combinations, all power supply data type combinations containing the power supply data type are recorded as feature combinations, and the impact index value corresponding to each feature combination at the historical monitoring moment and the impact index value set corresponding to each feature combination at the current monitoring moment are obtained. The impact index value set corresponding to any feature combination at the current monitoring moment is composed of the impact index value corresponding to the corresponding feature combination at the current monitoring moment and the impact index values ​​corresponding to the corresponding feature combinations at a preset number of historical monitoring moments. The mean of the impact index value set corresponding to each feature combination at the current monitoring moment is recorded as the comprehensive index value corresponding to the corresponding feature combination at the current monitoring moment; the normalized value of the mean of the comprehensive index values ​​corresponding to all feature combinations at the current monitoring moment is used as the affected weight value corresponding to the power supply data type at the current monitoring moment; The method for obtaining the impact index value corresponding to the power supply data type combination at the current monitoring moment includes: The time interval between the nearest turning monitoring moment of each power supply data type at the current monitoring moment and the current monitoring moment is recorded as the time distance of the corresponding power supply data type at the current monitoring moment, and the number of extreme values ​​in the turning sequence corresponding to each power supply data type at the current monitoring moment is used as the trend change representation value corresponding to the corresponding power supply data type at the current monitoring moment; For any power supply data type combination A: the two power supply data types in the power supply data type combination A are respectively recorded as power supply data type A1 and power supply data type A2, the absolute value of the difference between the time distance of the power supply data type A1 at the current monitoring moment and the time distance of the power supply data type A2 at the current monitoring moment is recorded as the first change index value corresponding to the power supply data type combination A, the absolute value of the difference between the trend change characterization value corresponding to the power supply data type A1 at the current monitoring moment and the trend change characterization value corresponding to the power supply data type A2 at the current monitoring moment is recorded as the second change index value corresponding to the power supply data type combination A, the reciprocal of the first change index value added to the preset constant and the reciprocal of the second change index value added to the preset constant are respectively recorded as the first reciprocal value and the second reciprocal value, and the average of the first reciprocal value and the second reciprocal value is used as the impact index value corresponding to the power supply data type combination A at the current monitoring moment; The method for obtaining the correlation change representation value at the current monitoring moment includes: For the power supply data type combination A, the absolute value of the difference between the reciprocal of the first difference of the power supply data type A1 at the current monitoring moment and the reciprocal of the first difference of the power supply data type A2 at the current monitoring moment is recorded as the first characteristic difference, the reciprocal of the result obtained by adding the preset constant to the first characteristic difference is recorded as the change similarity characteristic value corresponding to the power supply data type combination A, and the result obtained by subtracting the influence index value corresponding to the power supply data type combination A from the preset constant and multiplying the change similarity characteristic value corresponding to the power supply data type combination A is recorded as the change influence characterization value corresponding to the power supply data type combination A at the current monitoring moment; the first difference value of any power supply data type is the absolute value of the difference between the current power supply data of the power supply data type and the nearest neighbor power supply data corresponding to the current power supply data of the power supply data type; The average of the change impact characterization values ​​corresponding to all power supply data type combinations at the current monitoring moment is recorded as the associated change characterization value at the current monitoring moment.

2. The ring main box with intelligent power supply data monitoring function according to claim 1, characterized in that: The method for obtaining the nearest neighbor power supply data and the nearest neighbor power supply data sequence corresponding to the current power supply data includes: For any power supply data type, the power supply data belonging to the power supply data type collected at the previous historical monitoring moment before the current monitoring moment is recorded as the nearest neighbor power supply data corresponding to the current power supply data of the power supply data type, and the time series sequence composed of all power supply data belonging to the power supply data type collected at the current monitoring moment and a preset number of consecutive historical monitoring moments adjacent to the current monitoring moment is recorded as the nearest neighbor power supply data sequence corresponding to the current power supply data of the power supply data type.

3. The ring main box with intelligent power supply data monitoring function according to claim 1, characterized in that: The method for obtaining the abnormal characterization value corresponding to each power supply data type at the current monitoring moment includes: For any power supply data type: the nearest neighbor power supply data corresponding to the current power supply data of the power supply data type is recorded as the first data, and the neighbor power supply data sequence corresponding to the current power supply data of the power supply data type is recorded as the first sequence, and it is determined whether the current power supply data of the power supply data type exceeds the preset threshold interval corresponding to the power supply data type. If so, the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is obtained based on the difference and slope between the current power supply data of the power supply data type and the first data and the difference between adjacent power supply data in the first sequence. Otherwise, the abnormal characterization value corresponding to the power supply data type at the current monitoring moment is obtained based on the slope between the current power supply data of the power supply data type and the first data and the variance of the first sequence.

4. The ring main box with intelligent power supply data monitoring function according to claim 3, characterized in that: The method for obtaining, based on a difference and a slope between current power supply data of the power supply data type and the first data and a difference between adjacent power supply data in the first sequence, an abnormality characterization value corresponding to the power supply data type at a current monitoring moment, includes: Obtain the data points corresponding to the current power supply data of the power supply data type and the data points corresponding to the first data, which are respectively recorded as the first data point and the second data point, the horizontal coordinate of the first data point is the acquisition time of the current power supply data of the power supply data type, and the vertical coordinate is the current power supply data of the power supply data type, the horizontal coordinate of the second data point is the acquisition time of the first data, and the vertical coordinate is the first data; record the absolute value of the slope between the first data point and the second data point as the slope characterization value of the power supply data type at the current monitoring moment, and record the normalized value of the slope characterization value of the power supply data type at the current monitoring moment as the first characterization value; record the current power supply data of the power supply data type as the first characterization value. The absolute value of the difference between the ath power supply data and the first data is recorded as the first difference of the power supply data type at the current monitoring moment, and the normalized value of the first difference is recorded as the second characterization value; the difference sequence of the first sequence is obtained, and the ath difference in the difference sequence is the absolute value of the difference between the ath power supply data and the a+1th power supply data in the first sequence; the normalized value of the absolute value of the difference between the first difference and the mean of the difference sequence is recorded as the third characterization value; the weighted sum of the first characterization value, the second characterization value, and the third characterization value is recorded as the first weighted fusion characterization value; the result of subtracting the weighted fusion characterization value from the preset constant is recorded as the abnormal characterization value corresponding to the power supply data type at the current monitoring moment.

5. The ring main box with intelligent power supply data monitoring function according to claim 4, characterized in that: The method for obtaining, according to a slope between current power supply data of the power supply data type and the first data and a variance of the first sequence, an abnormality characterization value corresponding to the power supply data type at a current monitoring moment, includes: The inverse of the sum of the slope characterization value of the power supply data type at the current monitoring moment and the preset constant is recorded as the slope characteristic value, the inverse of the sum of the preset constant and the variance of the first sequence is recorded as the variance characteristic value, the weighted sum of the slope characteristic value and the variance characteristic value is recorded as the second weighted fusion characterization value, and the result of subtracting the second weighted fusion characterization value from the preset constant is recorded as the abnormal characterization value corresponding to the power supply data type at the current monitoring moment.

6. The ring main box with intelligent power supply data monitoring function according to claim 1, characterized in that: The method for monitoring the state of the ring network box at the current monitoring moment according to the abnormal characterization value, the change association characterization value and the affected weight value includes: For any power supply data type, the product of the abnormal characterization value corresponding to the power supply data type at the current monitoring moment and the affected weight value corresponding to the power supply data type at the current monitoring moment is recorded as the weighted abnormal characterization value corresponding to the power supply data type at the current monitoring moment; The average value of the result obtained by adding the cumulative sum of the weighted abnormal characterization values ​​corresponding to all power supply data types at the current monitoring moment and the associated change characterization value at the current monitoring moment is recorded as the ring network box status judgment index value at the current monitoring moment; if the ring network box status judgment index value is greater than the preset judgment threshold, the state of the ring network box is judged to be abnormal.

Images