A switchgear intelligent monitoring and control system

Abstract

This invention relates to the field of switch control cabinet monitoring and discloses an intelligent monitoring and control system for switch cabinets, comprising a parameter acquisition module, a variable establishment module, a change comparison module, and a second reference module. Building upon existing methods for overall switch cabinet temperature detection and individual device monitoring, this invention improves upon the monitoring of conductors. Specifically, it utilizes the principle of conductor thermal expansion to monitor the change in conductor diameter during thermal expansion. This diameter is then compared to a theoretical diameter value obtained under experimental conditions. Since each theoretical diameter value is calculated using a corresponding temperature, the theoretical diameter value and corresponding temperature form a reference table. By comparing the actual measured diameter with this reference table, the theoretically predicted temperature can be obtained. This allows for the determination of whether the conductor temperature is abnormal, enabling the issuance of an early warning.

Description

Technical Field

[0001] This invention belongs to the field of switch control cabinet monitoring, specifically an intelligent monitoring and control system for switch cabinets. Background Technology

[0002] Switchgear monitoring primarily relies on the installation of temperature sensors to achieve real-time monitoring of its operating status, enabling early fault detection and ensuring equipment safety. Specifically, this temperature detection method typically alerts maintenance personnel through threshold alarms. Once an abnormal temperature is detected (e.g., exceeding a set threshold), the system automatically alarms, indicating a potential overheating problem and prompting timely inspection by maintenance personnel to prevent accidents. For example, Chinese patent CN116345340B, based on this approach, further utilizes predicted temperatures compared to set thresholds for early warning monitoring, enabling faster detection and alerts.

[0003] However, for switchgear temperature, temperature sensors primarily detect the overall temperature of the cabinet, while monitoring internal components and wiring individually. Component temperature can be directly monitored using sensors. Wiring temperature monitoring methods mainly include thermocouple monitoring and infrared thermometers. However, a thermocouple is a temperature sensor primarily composed of two wires of different metals. These wires are connected at one end to form a junction, called the measuring junction or thermal junction. When the temperature at this junction changes, a thermoelectric potential (voltage) is generated in the wire. By measuring this voltage, the junction temperature can be calculated. Therefore, a thermocouple primarily detects the temperature at its measuring junction. This junction temperature does not represent the internal temperature of the wire. Infrared thermometers, on the other hand, primarily check for temperature rises by periodically scanning the wire surface. The wire surface and the inside of the wire are separated by an insulating material such as rubber, resulting in different internal and external temperatures. Judging whether the wire temperature is normal based on the surface temperature is inaccurate. Summary of the Invention

[0004] (a) Technical problem to be solved: How to introduce wire monitoring to make early warnings when monitoring switch cabinets.

[0005] (II) Technical Solution: This invention provides an intelligent monitoring and control system for switchgear, comprising:

[0006] Parameter acquisition module: acquires the initial diameter value of the wires connected to the devices in the switch cabinet at room temperature, and uses it as a monitoring benchmark;

[0007] Variable establishment module: Based on the material properties of the conductor, the coefficient of thermal expansion, and the initial diameter of the conductor at room temperature, a mathematical model of conductor diameter and temperature is established. The initial temperature to the maximum temperature is set to form multiple step temperature steps, namely the first step temperature to the Nth step temperature. The multiple step temperatures are substituted into the mathematical model to obtain the theoretical diameter reference range.

[0008] Change Comparison Module: Obtains the actual diameter value of the wires connected to the devices in the switch cabinet, compares the actual diameter value with the theoretical diameter value to obtain the theoretical temperature, sets a threshold temperature, and issues an abnormal warning when the theoretical temperature exceeds the threshold temperature.

[0009] Furthermore, it also includes a second reference module, which is used to capture the mechanical vibration generated by the conductor during thermal expansion and uses the mechanical vibration as an auxiliary parameter for judging temperature changes. The specific steps for its implementation are as follows:

[0010] First, install high-precision micro-vibration sensors or accelerometers at key points on the conductor to capture the vibrations caused by temperature changes.

[0011] Second, under controlled environmental conditions, the conductor is heated in sequence from the first step temperature to the Nth step temperature to obtain the vibration amplitude and vibration frequency of the conductor at different step temperatures, which are used as vibration data and corresponded one-to-one with the temperature to form a vibration characteristic change table.

[0012] Third, the mathematical relationship between temperature and vibration characteristics is obtained by fitting a table of vibration characteristic changes;

[0013] Fourth, use the fitted mathematical relationship to set an abnormal early warning threshold between temperature and vibration characteristics.

[0014] Furthermore, by utilizing the fitting model, setting an abnormal early warning threshold between temperature and vibration characteristics specifically includes two aspects:

[0015] First, the vibration amplitude threshold: find the amplitude change at different temperatures in the experimental data, take the rate of change of vibration amplitude as the temperature gradually increases as the normal reference value, and the vibration amplitude exceeding the normal reference value is abnormal.

[0016] Second, vibration frequency threshold: set the normal range of vibration frequency variation. If the frequency variation exceeds the normal range, it indicates that the temperature rise rate is too fast and an abnormal warning is required.

[0017] Furthermore, for different rates of temperature rise, the amplitude and frequency thresholds are adjusted to set first, second, and third warning levels. The first warning level corresponds to a slight increase in vibration frequency and amplitude beyond the set value, the second warning level corresponds to a significant increase in vibration frequency and amplitude beyond the set value, and the third warning level corresponds to a sharp increase in vibration amplitude and a sharp increase in frequency change amplitude.

[0018] Furthermore, vibration data and diameter data are used for joint anomaly early warning, specifically including:

[0019] Firstly, if the vibration frequency and vibration amplitude in the vibration data both exceed the normal range, and the wire temperature estimated by the wire diameter is also abnormal, then a Level 1 abnormality warning is set. The Level 1 abnormality warning automatic control system stops and notifies maintenance personnel to carry out maintenance.

[0020] Secondly, if the vibration frequency and vibration amplitude in the vibration data both exceed the normal range, but the wire temperature estimated by the wire diameter is normal at this time, then a level two abnormality warning is set, and the level two abnormality warning will notify the maintenance personnel to carry out maintenance.

[0021] Third, if either the vibration frequency or the vibration amplitude in the vibration data exceeds the normal range, but the wire temperature estimated by the wire diameter is normal at this time, then a level three abnormality warning is set. Level three abnormality warnings require additional inspection by maintenance personnel.

[0022] Furthermore, during the mechanical vibration of the conductor, the echo delay of the sound waves generated by the mechanical vibration of the conductor and the echo produced by the collision between the sound waves and the inner wall of the switch cabinet is measured and recorded simultaneously. At the same time, the relationship between temperature and echo delay is determined experimentally. The echo delay obtained from this relationship is compared with the measured echo delay to obtain the estimated conductor temperature. A threshold is set according to the safe temperature range of the conductor to determine whether the conductor is abnormal.

[0023] Furthermore, the specific steps for determining the relationship between temperature and echo delay are as follows:

[0024] The internal temperature of the switch cabinet was gradually increased in the experimental environment, and the echo delay was measured at each temperature. The delay value corresponding to each temperature was recorded, and the temperature and corresponding echo delay data were compiled into a table.

[0025] Based on the compiled table, a scatter plot is drawn with temperature as the horizontal axis and echo delay as the vertical axis to obtain the data distribution trend. Based on the data distribution trend, a fitting model is obtained.

[0026] Furthermore, the location of the vibration sensor is configured with a corresponding location identifier based on the location and type of the wire. A corresponding wire list is constructed based on the location identifier. The wire list includes the wire identifier and the location identifier under that wire identifier. In addition, the wire list also includes the connected wire identifiers of the target wire identifier that establish a mapping relationship. The wires corresponding to the connected wire identifiers are used to guide maintenance personnel to identify the location of abnormal wires.

[0027] Furthermore, the amount of vibration frequency data and vibration amplitude data in the vibration characteristic data needs to be kept the same during recording. If the two are unbalanced, the SMOTE algorithm is used to sample them to increase the number of samples. The SMOTE algorithm includes: identifying minority class data in different types of data, randomly selecting one data from the K neighbor data of the minority class data, generating a new data on the connection line between the randomly selected data and the original minority class data as the new data of the corresponding minority class data, and further putting the new data into the original minority class data to expand the corresponding minority class data.

[0028] (III) Technical Effects:

[0029] 1. This invention, building upon existing methods for overall temperature monitoring of switchgear and individual device monitoring, improves upon the monitoring of conductors. Specifically, it utilizes the principle of conductor thermal expansion to monitor the change in conductor diameter during thermal expansion. This change is then compared to the theoretical diameter value obtained under experimental conditions. Since each theoretical diameter value is calculated based on a corresponding temperature, the theoretical diameter value and its corresponding temperature form a reference table. By comparing the actual measured diameter with this reference table, the theoretically predicted temperature can be obtained. This allows for the determination of whether the conductor temperature is abnormal, enabling the issuance of an early warning.

[0030] 2. In this invention, when the conductor expands thermally, not only will the conductor diameter change, but the conductor will also vibrate. By monitoring the vibration of the conductor, vibration data at different temperatures are fitted under a controllable environment. The vibration data and temperature correspond to form a characteristic change table. This characteristic change table can be fitted to set an abnormal warning threshold between temperature and vibration characteristics. That is, it can be determined whether the conductor temperature is abnormal and whether a warning is needed based on whether the vibration frequency and vibration amplitude are within the normal range.

[0031] 3. In this invention, the vibration of the conductor and the enclosed environment of the switchgear can be used to establish specific criteria for determining whether the conductor temperature is abnormal. Because conductor vibration generates sound waves, and these sound waves impacting the inner wall of the switchgear produce echoes, by monitoring the echo delay and establishing a relationship between temperature and echo delay under controlled conditions, the echo delay corresponding to the temperature-echo delay relationship can be compared with the actual echo delay to estimate the conductor temperature and determine whether it is abnormal. Attached Figure Description

[0032] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0033] Figure 1 This is a schematic diagram of the module structure of the monitoring system of the present invention;

[0034] Figure 2 This is a schematic diagram of the structure of the second reference module of the present invention. Detailed Implementation

[0035] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0036] The intelligent monitoring and control system for switchgear provided in this specific embodiment, such as Figure 1 and Figure 2 Shown, including:

[0037] Parameter acquisition module: This module acquires the initial diameter of the wires connected to the devices in the switch cabinet at room temperature, using this as a monitoring reference. For example, a laser rangefinder can be used to accurately measure the cross-sectional diameter of the wires using laser reflection. Because the wires inside the switch cabinet are densely arranged, the laser rangefinder can obtain high-precision measurement data without contacting the wires.

[0038] Variable Establishment Module: Based on the material properties of the conductor, its coefficient of thermal expansion, and its initial diameter at room temperature, a mathematical model of the conductor's diameter versus temperature is established. The formula for the change in conductor diameter with temperature is typically: .in: It is the diameter of the wire at temperature T; This is the reference temperature, i.e., room temperature; It is the coefficient of linear expansion of the conductor material; It is the change in temperature, that is For example, the conductor material is copper, the initial diameter is 10mm, and the coefficient of thermal expansion is... If the temperature increases by 50°C, the change in the diameter of the wire can be calculated as follows: By setting an initial temperature to a maximum temperature gradient, multiple temperature steps are created, ranging from the first to the Nth step. These step temperatures are then substituted into a mathematical model to obtain a reference range for the theoretical diameter value. This allows us to obtain the theoretical diameter values ​​at different temperatures and establish a table showing the relationship between diameter and temperature. For example:

[0039]

[0040] This is the relationship table between the two.

[0041] The change comparison module obtains the actual diameter of the wires connected to devices in the switchgear, compares the actual diameter with the theoretical diameter to derive the theoretical temperature, sets a threshold temperature, and issues an early warning when the theoretical temperature exceeds the threshold temperature. In summary, based on existing overall switchgear temperature monitoring and individual device monitoring, this module utilizes the principle of wire thermal expansion to monitor the change in wire diameter during thermal expansion. This diameter is compared with the theoretical diameter value obtained under experimental conditions. Since each theoretical diameter value is calculated using a corresponding temperature, the theoretical diameter value and corresponding temperature form a reference table. The actual measured diameter, compared with this reference table, yields the theoretically predicted temperature, thus determining whether the wire temperature is abnormal and initiating an early warning process.

[0042] The table here is a static table listing the wire diameter values ​​corresponding to different temperatures. This table was collected from experimental data and can be easily and quickly looked up. However, if the wire diameter changes irregularly, i.e., under the premise of a non-linear relationship, the current wire temperature can be estimated as follows to determine whether an abnormality warning is needed: the current wire temperature T equals the actual measured diameter value D minus the reference diameter value. Then divide by the influence coefficient k of temperature on diameter change and add the reference temperature. According to The influence coefficient k of temperature on diameter change is calculated using linear regression analysis to determine the slope k. This method can be considered the first reference module for judging whether the conductor temperature is abnormal. In addition, because the conductor's diameter changes and vibrations are also caused by thermal expansion, vibration can be used as a second reference module. The specific steps are as follows:

[0043] First, high-precision micro-vibration sensors or accelerometers are installed at key points on the conductor to capture minute vibrations caused by temperature changes. Depending on the specific situation, vibration sensors can be installed at both ends or the middle of the conductor. It is crucial to ensure that the sensors can stably capture the amplitude and frequency of the conductor's vibrations. Notably, the locations of the vibration sensors are configured with corresponding location markers based on the conductor's location and type. A corresponding conductor list is then constructed based on these location markers. The conductor list includes the conductor identifier and the location markers under that identifier. Furthermore, the list includes connected conductor identifiers that establish a mapping relationship with the target conductor identifier. The conductors corresponding to these connected conductor identifiers guide maintenance personnel to identify the location of abnormal conductors.

[0044] Secondly, in a controlled environment, the vibration frequency and amplitude of the conductor at the initial temperature are recorded. As the temperature gradually increases, the vibration frequency and amplitude are recorded again at fixed temperature intervals. The collected vibration frequencies, amplitudes, and temperatures are mapped one-to-one to form a vibration characteristic change table. Here, the data from both sources need to be identical. If the data are different, the data will be biased towards the larger sample size during fitting. However, in actual recording, the data may become unbalanced due to omissions. In this case, the SMOTE algorithm can be used to sample both sources to increase the sample size. The SMOTE algorithm includes: identifying the minority class data in different data types; randomly selecting one data point from the K nearest neighbors of the minority class data; generating a new data point on the connection line between the randomly selected data point and the original minority class data as the new data point for the corresponding minority class; and further adding the new data point to the original minority class data to expand the corresponding minority class data. Assuming the initial temperature is 20℃ and the recording is repeated every 10℃, the resulting vibration characteristic change table can be as follows:

[0045]

[0046] Based on the data in the table above, fit a mathematical relationship between temperature and vibration characteristics. If the relationship is linear, it can be expressed as... If it is non-linear, it can be represented as The above The vibration frequencies, a, b, and c, are obtained by fitting experimental data through quadratic regression analysis. For example, if the data indicates that the vibration frequency increases by approximately 2 Hz / 10℃, the formula can be used. It indicates the trend of frequency change.

[0047] Finally, a fitting model is used to set warning thresholds between temperature and vibration characteristics, including vibration amplitude and vibration frequency. For the vibration amplitude threshold: the amplitude variation at different temperatures is identified from experimental data, and the rate of change of vibration amplitude with gradually increasing temperature is used as a normal reference value. For example, if the vibration amplitude increases by 0.2 micrometers for every 10°C increase, an increase exceeding 0.2 micrometers every 10 minutes can be set as abnormal during on-site monitoring. For the vibration frequency threshold: a normal range for vibration frequency variation is set, for example, the frequency change should not exceed 2 Hz every 10 minutes. If the frequency change exceeds 2 Hz, the surface temperature rise rate is too fast, requiring an abnormal warning. Based on this, different warning levels can be set by adjusting the amplitude and frequency thresholds to address different rates of temperature rise. For example, warning levels can be divided into Level 1, Level 2, and Level 3. For Level 1 warning: the changes in vibration frequency and amplitude slightly exceed the set values, for example, an amplitude change of 0.15 micrometers and a frequency change approaching 2 Hz within 10 minutes, prompting monitoring. For Level 2 warnings: Changes in vibration frequency and amplitude significantly exceed set values, such as an increase in vibration amplitude of 0.25 micrometers or a frequency change of 3 Hz within 10 minutes, with a rapid rise in surface temperature; inspection is recommended. For Level 3 warnings: A sharp increase in vibration amplitude, such as exceeding 0.4 micrometers, or a frequency change reaching or exceeding 4 Hz, indicates that the temperature may be too high; the system will automatically alarm and shut down. In addition, vibration data and diameter data can be combined for joint anomaly warnings. If both vibration frequency and amplitude in the vibration data exceed the normal range, and the wire temperature estimated using the wire diameter is also abnormal, a Level 1 anomaly warning is issued, automatically stopping the control system and notifying maintenance personnel for repair. If both vibration frequency and amplitude in the vibration data exceed the normal range, but the wire temperature estimated using the wire diameter is normal, a Level 2 anomaly warning is issued, notifying maintenance personnel for repair. If either vibration frequency or amplitude in the vibration data exceeds the normal range, but the wire temperature estimated using the wire diameter is normal, a Level 3 anomaly warning is issued, requiring additional inspection by maintenance personnel.

[0048] Furthermore, the vibration of the conductors and the enclosed environment of the switchgear can provide specific evidence for determining whether the conductor temperature is abnormal. This is because conductor vibration generates sound waves, which, when they strike the inner wall of the switchgear, produce echoes. By monitoring the echo delay and, under controlled conditions, establishing a relationship between temperature and echo delay, comparing the corresponding echo delay in the temperature-echo-delay relationship with the actual echo delay, the conductor temperature can be estimated to determine if there is an anomaly. The specific steps are as follows:

[0049] First, select a suitable location inside the switch cabinet near the wires to install acoustic sensors to capture the echoes generated by the wire vibrations.

[0050] Secondly, an initial temperature is set for the conductor, and the echo delay at this temperature is recorded as a baseline value. By heating the conductor, the echo delay at different set temperatures is recorded to obtain the relationship between temperature and echo delay. Assuming the initial temperature is 20℃, and the temperature increases by 10℃ each time, the relationship between temperature and echo delay can be recorded as follows:

[0051]

[0052] By comparing the measured echo delay with this change, the conductor temperature can be estimated to determine if there is an anomaly. However, if the table density is insufficient or the amount of experimental data is inadequate, the accuracy of the table-based lookup cannot be guaranteed. Therefore, when the table density is insufficient, a formula fitting can be used to calculate the estimated conductor temperature. First, plot a scatter plot with temperature on the horizontal axis and echo delay on the vertical axis, observe the data distribution, and perform linear or nonlinear fitting based on the data trend. If the data shows a straight line, use linear regression; if there is a curvilinear trend, use a nonlinear model. This is the same as the fitting in the conductor vibration example above. Therefore, based on this example, the formula for calculating the estimated conductor temperature can be: or Here, t is the actual measured echo delay, and a, b, and c are obtained by fitting experimental data. The specific fitting method can be software-based or the least squares method, etc.

[0053] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0054] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A smart monitoring and control system for switchgear, characterized in that, include: Parameter acquisition module: acquires the initial diameter value of the wires connected to the devices in the switch cabinet at room temperature, and uses it as a monitoring benchmark; Variable establishment module: Based on the material properties of the conductor, the coefficient of thermal expansion, and the initial diameter of the conductor at room temperature, a mathematical model of conductor diameter and temperature is established. The initial temperature to the maximum temperature is set to form multiple step temperature steps, namely the first step temperature to the Nth step temperature. The multiple step temperatures are substituted into the mathematical model to obtain the theoretical diameter reference range. Change Comparison Module: Obtain the actual diameter value of the wires connected to the devices in the switch cabinet, compare the actual diameter value with the theoretical diameter value to obtain the theoretical temperature, set the threshold temperature, and issue an abnormal warning when the theoretical temperature exceeds the threshold temperature; It also includes a second reference module, which is used to capture the mechanical vibration generated by the conductor during thermal expansion and uses the mechanical vibration as an auxiliary parameter for judging temperature changes. The specific steps for its implementation are as follows: First, install high-precision micro-vibration sensors or accelerometers at key points on the conductor to capture the vibrations caused by temperature changes. Second, under controlled environmental conditions, the conductor is heated in sequence from the first step temperature to the Nth step temperature to obtain the vibration amplitude and vibration frequency of the conductor at different step temperatures, which are used as vibration data and corresponded one-to-one with the temperature to form a vibration characteristic change table. Third, the mathematical relationship between temperature and vibration characteristics is obtained by fitting a table of vibration characteristic changes; Fourth, set abnormal warning thresholds between temperature and vibration characteristics using the fitted mathematical relationship. The abnormal warning thresholds between temperature and vibration characteristics using the fitted model include two aspects: First, the vibration amplitude threshold: find the amplitude changes at different temperatures in the experimental data, take the rate of change of vibration amplitude as the temperature gradually increases as the normal reference value, and the vibration amplitude exceeding the normal reference value is abnormal; Second, the vibration frequency threshold: set the normal range of vibration frequency changes. If the frequency changes exceed the normal range, it indicates that the temperature rise rate is too fast and an abnormal warning is required. The echo delay of the sound waves generated by the mechanical vibration of the conductor and the echo produced by the collision between the sound waves and the inner wall of the switch cabinet is measured and recorded simultaneously during the mechanical vibration of the conductor. At the same time, the relationship between temperature and echo delay is determined experimentally. The echo delay obtained by this relationship is compared with the measured echo delay to obtain the estimated conductor temperature. A threshold is set according to the safe temperature range of the conductor to determine whether the conductor is abnormal.

2. The intelligent monitoring and control system for switchgear according to claim 1, characterized in that, For different rates of temperature rise, the amplitude and frequency thresholds are adjusted to set first, second and third warning levels. The first warning level corresponds to the vibration frequency and amplitude changes slightly exceeding the set values, the second warning level corresponds to the vibration frequency and amplitude changes significantly exceeding the set values, and the third warning level corresponds to the vibration amplitude and frequency change amplitude increasing sharply.

3. The intelligent monitoring and control system for switchgear according to claim 2, characterized in that, The warning system can also combine vibration data and diameter data for joint anomaly warnings. Specifically, if both the vibration frequency and amplitude in the vibration data exceed the normal range, and the wire temperature estimated from the wire diameter is also abnormal, it corresponds to a Level 1 anomaly warning. The automatic control system stops at Level 1 anomaly warning and notifies maintenance personnel for repair. If both the vibration frequency and amplitude in the vibration data exceed the normal range, but the wire temperature estimated from the wire diameter is normal, it corresponds to a Level 2 anomaly warning, which notifies maintenance personnel for repair. If either the vibration frequency or amplitude in the vibration data exceeds the normal range, but the wire temperature estimated from the wire diameter is normal, it corresponds to a Level 3 anomaly warning, which requires additional inspection by maintenance personnel.

4. The intelligent monitoring and control system for switchgear according to claim 1, characterized in that, The specific steps for determining the relationship between temperature and echo delay are as follows: gradually increase the internal temperature of the switch cabinet in the experimental environment, measure the echo delay at each temperature, record the delay value corresponding to each temperature, and organize the temperature and corresponding echo delay data into a table; based on the organized table, plot a scatter plot with temperature as the horizontal axis and echo delay as the vertical axis to obtain the data distribution trend, and obtain the fitting model based on the data distribution trend.

5. The intelligent monitoring and control system for switchgear according to claim 1, characterized in that, The location of the vibration sensor is configured with a corresponding location identifier based on the location and type of the wire. A corresponding wire list is constructed based on the location identifier. The wire list includes the wire identifier and the location identifier under that wire identifier. In addition, the wire list also includes the connected wire identifiers of the target wire identifier that establish a mapping relationship. The wires corresponding to the connected wire identifiers are used to guide maintenance personnel to identify the location of abnormal wires.

6. The intelligent monitoring and control system for switchgear according to claim 1, characterized in that, The vibration frequency data and vibration amplitude data in the vibration characteristic data need to be kept the same during recording. If the two are unbalanced, the SMOTE algorithm is used to sample them to increase the number of samples. The SMOTE algorithm includes: identifying the minority class data in different types of data, randomly selecting one data from the K neighbor data of the minority class data, generating a new data on the connection line between the randomly selected data and the original minority class data as the new data of the corresponding minority class data, and further putting the new data into the original minority class data to expand the corresponding minority class data.

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