A stable voltage power switch safety monitoring system and method based on internet of things

Abstract

The application discloses a kind of based on Internet of Things's stable voltage power switch safety monitoring system and method, power switch management technical field, the electrical physical quantity of current in power supply circuit switch is detected, when warning occurs, record alarm time, obtain the running record of first detection time period before alarm time in first power supply phase, the difference of electrical physical quantity in two monitoring time periods is recorded as dispersion coefficient, obtain the load parameter of electric equipment in previous detection period and next detection period, calculate the data fluctuation change of the load parameter, when the dispersion degree of the data of load parameter increases, the moment of abnormality of electric equipment is judged, the accuracy of judgment is improved by twice judgment, the strategy of coping with power supply line problem is obtained, the connection mode of power supply switch to power line is adjusted.

Description

Technical Field

[0001] This invention relates to the field of power switch management technology, specifically to a safety monitoring system and method for a regulated power switch based on the Internet of Things. Background Technology

[0002] To ensure the stable operation of critical electrical equipment, backup power supplies are necessary. These backup power supplies switch over when equipment malfunctions, mitigating production risks caused by equipment downtime. Common backup power solutions are mainly divided into hot standby and cold standby. Hot standby power supplies are typically implemented as redundant power sources, operating while the equipment is running and ready to supply power at any time. Cold standby power supplies are usually shut down while the equipment is running, switching power when the equipment malfunctions.

[0003] While hot standby power supplies offer faster switching times, they require higher maintenance due to the need to keep them readily available, and they also consume additional grid resources. Cold standby power supplies, on the other hand, can save grid resources compared to hot standby power supplies, but require more time to switch between them. Current technologies struggle to achieve a balance between hot and cold standby power supplies. Summary of the Invention

[0004] The purpose of this invention is to provide a safety monitoring system and method for a regulated power supply switch based on the Internet of Things, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides a method for safety monitoring of a regulated power supply switch based on the Internet of Things.

[0006] Step S100: Set a first power supply phase and a second power supply phase for the power supply of the electrical equipment. Set a power supply circuit switch in the circuit between each power supply phase and the electrical equipment. Connect the circuit between the first power supply phase and the second power supply phase through a conversion circuit. Set a conversion circuit switch in the conversion circuit.

[0007] Step S200: Obtain historical data of the load power of the electrical equipment from the operation record of the electrical equipment;

[0008] Step S300: When power is supplied to the electrical equipment through the first power supply phase, the electrical physical quantity of the current in the power supply circuit switch is detected during the power supply process. When an alarm occurs, the alarm time is recorded. The operation record of the first power supply phase in the first detection time period before the alarm time is obtained. The unit monitoring time period is set. The difference of the electrical physical quantity in the two monitoring time periods is recorded as the discrete coefficient. The time when the discrete coefficient changes is recorded as time t1.

[0009] Step S400: Set the detection period, obtain the load parameters of the electrical equipment in the previous and next detection periods at time t1, calculate the data fluctuation of the load parameters, and when the dispersion of the load parameter data increases after time t1, determine whether the electrical equipment has an abnormality after time t1.

[0010] Step S500: Obtain sampling data of the electrical physical quantities of several first power supply phases, calculate the average value of the discrete coefficients, connect the circuit of the second power supply phase and the electrical equipment, and calculate the average value of the discrete coefficients after connecting the circuit of the second power supply phase and the electrical equipment.

[0011] Step S600: Compare the changes in the average value of the discrete coefficients, and adjust the power supply circuit of the electrical equipment based on the judgment result in step S400.

[0012] Furthermore, step S300 includes:

[0013] Step S301: Uniformly sample the electrical physical quantities in the first detection time period, set a unit monitoring time period, the first detection time period includes several unit monitoring time periods, the time length of the unit monitoring time period is T0, and collect the sampling data of the electrical physical quantities in each unit monitoring time period in the first detection time period.

[0014] Uniform sampling means sampling data at equal time intervals. The uniform sampling method ensures that the number of sampled data is roughly the same in each unit monitoring time period.

[0015] Step S302: Obtain the data set M consisting of the sampled data of the electrical physical quantity in the j-th unit monitoring time period of the first detection time period. j , for M j The detached data in the dataset is removed to obtain dataset M. j * ;

[0016] Because the sampling or sensor is interfered with during data transmission, some discrete sampling data will appear during the sampling of electrical physical quantities. These discrete sampling data cannot accurately reflect the operating status of the electrical equipment. These discrete data are regarded as free data relative to the operating status data of the electrical equipment. These free data are removed so that the sampling data can better reflect the operating status of the equipment.

[0017] Step S303: Calculate the data set M j * The average value α jObtain a data set M consisting of sampled data of the electrical physical quantity in the (j+1)th unit monitoring time period of the first detection time period. j+1 Calculate M j With M j+1 The coefficients of variation dsc f , , where k i This represents the sampling data of the i-th electrical physical quantity in the (j+1)-th unit monitoring time period of the first detection time period, and N represents the number of sampling data in the (j+1)-th unit monitoring time period of the first detection time period.

[0018] The average value of the physical quantity in the previous monitoring period is calculated, and then the difference between the average value and the sampled data in the next monitoring period is calculated. All the differences are accumulated to show the difference between the sampled data of the physical quantity in the next monitoring period and the data of the physical quantity in the previous monitoring period.

[0019] Step S304: Obtain three consecutive discrete coefficients (dsc) between any four consecutive monitoring time periods. w dsc w+1 and dsc w+2 When dsc w+2 -dsc w+1 >dsc w+1 -dsc w When it is determined that the power supply of the first power supply phase is abnormal, the end time of the second unit monitoring time period in any four consecutive unit monitoring time periods is obtained and recorded as time t1 when the first power supply phase is abnormal.

[0020] The coefficient of variation represents the difference between the data in the later unit of monitoring time and the data in the previous unit of monitoring time. When the discrete data increases, it indicates that the stability of the physical quantity sampling data decreases and the fluctuation range becomes more drastic, thus indicating that the possibility of risk in the first power supply phase increases.

[0021] Furthermore, step S400 includes:

[0022] Step S401: Set a detection period with a time length of T1 to uniformly sample the load power of the electrical equipment. Set two adjacent detection periods TC1 and TC2. Calculate the variance σ1 of the load power sampling data of the electrical equipment in period TC1 and the variance σ2 of the load power sampling data of the electrical equipment in period TC2. When σ2 > σ1, it is determined that the electrical equipment has an abnormality after time t1.

[0023] Step S402: When σ2≤σ1, calculate the output power Q1 of the electrical equipment in period TC1 and the output power Q2 of the electrical equipment in period TC2. When Q2<Q1, determine that the electrical equipment has an abnormality after time t1.

[0024] Step S403: When Q2≥Q1, obtain the average power P2 of the electrical equipment in the TC2 time range, and collect the historical data of load power. The variance values ​​of the load power sampling data of the electrical equipment when the load power is P2 form a variance reference set R. The range of all variance values ​​in the variance reference set R is the variance reference range.

[0025] To measure the operational stability of electrical equipment, firstly, the variance of the output power of the electrical equipment is calculated to obtain the stability of the output of the electrical equipment. Then, the total output power before and after time t1 is compared to determine whether the output power of the electrical equipment starts to decrease at time t1. By comparing the above two points, it is determined whether the output of the electrical equipment is affected after time t1 when the data of the first power supply phase is abnormal.

[0026] Furthermore, by obtaining the moment t1 when the first power supply abnormality occurs, the state of the electrical equipment before and after time t1 is compared to determine whether the abnormality of the electrical equipment is caused by a power supply problem or by an abnormality in the power supply line itself.

[0027] Step S404: When σ2 is not within the variance reference range, it is determined that the electrical equipment has an abnormality after time t1.

[0028] Furthermore, step S500 includes:

[0029] Step S501: Starting from time t1, obtain sampling data of the electrical physical quantity of the first power supply phase for a continuous k1 unit monitoring time period, calculate the k1-1 discrete coefficients of the sampling data for a continuous u1 unit monitoring time period, and calculate the average value D1 of the k1-1 discrete coefficients.

[0030] Step S502: Connect the circuit switch between the second power supply phase and the electrical equipment, and record the time t2 when the circuit between the second power supply phase and the electrical equipment is connected;

[0031] Step S503: Starting from time t2, obtain sampling data of the electrical physical quantity of the first power supply phase for a continuous u1 unit monitoring time period, calculate u1-1 discrete coefficients of the sampling data for the continuous u1 unit monitoring time period, and calculate the average value D2 of the u1-1 discrete coefficients.

[0032] Furthermore, step S600 includes:

[0033] Step S601: When D2≥D1, and the electrical equipment malfunctions after time t1, disconnect the circuit switch between the first power supply phase and the electrical equipment.

[0034] Step S602: When D2 < D1, and the electrical equipment does not experience an abnormality after time t1, turn on the switching circuit switch and disconnect the circuit switch between the first power supply phase and the electrical equipment.

[0035] After connecting the backup power supply, test the first power supply phase again. If the operating data of the first power supply phase tends to be stable, it indicates that the abnormal grid data may be caused by a problem with the electrical equipment. If the operating data of the first power supply phase is still unstable, it indicates that there is a problem with the first power supply phase itself, and the first power supply phase will not be able to be used normally.

[0036] Step S603: When D2≥D1, and the electrical equipment does not experience an abnormality after time t1, or when D2<D1, and the electrical equipment experiences an abnormality after time t1, keep reminding the relevant equipment management personnel to check the relevant equipment.

[0037] To better implement the above methods, an IoT-based safety monitoring system for regulated power supply switches is also proposed. The system includes:

[0038] The system includes a circuit management module, a historical data management module, a discrete difference calculation module, an electrical equipment management module, a discrete coefficient averager module, and a switch management module. The circuit management module stores and manages the circuit structure, the historical data management module manages the historical data of the load power of the electrical equipment, the discrete difference calculation module calculates the time when the first power supply phase exhibits discrete difference, the electrical equipment management module manages the electrical equipment, the discrete coefficient averager module calculates the average value of the discrete coefficients, and the switch management module controls the circuit switches.

[0039] Furthermore, the discrete difference calculation module includes: a first sampling unit, a data cleaning unit, a discrete coefficient calculation unit, and an abnormal moment acquisition unit. The first sampling unit is used to sample the electrical physical quantities of the first power supply phase, the data cleaning unit is used to remove free data from the sampled data, the discrete coefficient calculation unit is used to calculate the discrete coefficient, and the abnormal moment management unit is used to calculate the time when the first power supply phase is abnormal.

[0040] Furthermore, the electrical equipment management module includes: a second sampling unit, a variance calculation unit, a power acquisition unit, and a first judgment unit. The second sampling unit is used to sample the load power of the electrical equipment, the variance calculation unit is used to calculate the variance of the sampled load power data of the electrical equipment, the power acquisition unit is used to acquire the output power of the electrical equipment, and the first judgment unit is used to determine whether the electrical equipment has an abnormality after time t1.

[0041] Furthermore, the discrete coefficient averager module includes: an abnormal moment acquisition unit, a first average calculation unit, and a second average calculation unit. The abnormal moment acquisition unit is used to acquire the moment when the first power supply phase is abnormal. The first average calculation unit is used to calculate the discrete coefficient average of the sampled data of the first power supply phase before the second power supply phase is connected to the circuit of the electrical equipment. The second average calculation unit is used to calculate the discrete coefficient average of the sampled data of the first power supply phase after the second power supply phase is connected to the circuit of the electrical equipment.

[0042] Furthermore, the switch management module includes: a second determination unit, a circuit switch control unit, and an information feedback unit. The second determination unit is used to determine the de-control mode of the switch in the circuit, the circuit switch control unit is used to control the switch in the circuit, and the information feedback unit is used to send message reminders to relevant management personnel.

[0043] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: The present invention measures the operating status of the power supply line and the electrical equipment separately, compares the order in which the power supply line and the electrical equipment become abnormal, improves the accuracy of the judgment through two judgments, obtains a strategy to deal with the power supply line problem, and adjusts the connection method of the power supply line by using a power switch to deal with different line abnormality problems. Attached Figure Description

[0044] 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:

[0045] Figure 1 This is a schematic diagram of the structure of a voltage regulator switch safety monitoring system based on the Internet of Things, as per this invention patent.

[0046] Figure 2 This is a schematic diagram of the first part of the process of a safety monitoring method for a regulated power supply switch based on the Internet of Things in this invention patent;

[0047] Figure 3 This is a schematic diagram of the second part of the process of a safety monitoring method for a regulated power supply switch based on the Internet of Things in this invention patent;

[0048] Figure 4 This is a schematic diagram of the switching circuit of a voltage regulator switch safety monitoring method based on the Internet of Things according to this invention patent. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Please see Figure 1 , Figure 2 , Figure 3 and Figure 4 The present invention provides the following technical solution:

[0051] Step S100: Set a first power supply phase and a second power supply phase for the power supply of the electrical equipment. Set a power supply circuit switch in the circuit between each power supply phase and the electrical equipment. Connect the circuit between the first power supply phase and the second power supply phase through a conversion circuit. Set a conversion circuit switch in the conversion circuit.

[0052] Figure 4 This indicates a power switch connection method, where EA represents the electrical equipment, Power1 represents the first power supply phase, and Power2 represents the second power supply phase. The power supply phase includes the power supply or the power supply line.

[0053] SW1 represents the circuit switch between the first power supply phase and the electrical equipment, SW2 represents the circuit switch between the second power supply phase and the electrical equipment, and SW3 represents the transfer circuit switch. The circuit switches are connected to the system through the Internet of Things, such as Bluetooth, Wi-Fi, LoRa, or wired connection.

[0054] h1, h2, h3 and h4 represent the connection nodes in the circuit, the power supply direction of the first power supply phase is h1→h2, and the power supply direction of the second power supply phase is h4→h3.

[0055] Step S200: Obtain historical data of the load power of the electrical equipment from the operation record of the electrical equipment;

[0056] Step S300: When power is supplied to the electrical equipment through the first power supply phase, the electrical physical quantity of the current in the power supply circuit switch is detected during the power supply process. When an alarm occurs, the alarm time is recorded. The operation record of the first power supply phase in the first detection time period before the alarm time is obtained. The unit monitoring time period is set. The difference of the electrical physical quantity in the two monitoring time periods is recorded as the discrete coefficient. The time when the discrete coefficient changes is recorded as time t1.

[0057] Step S300 includes:

[0058] Step S301: Uniformly sample the electrical physical quantities in the first detection time period, set a unit monitoring time period, the first detection time period includes several unit monitoring time periods, the time length of the unit monitoring time period is T0, and collect the sampling data of the electrical physical quantities in each unit monitoring time period in the first detection time period.

[0059] Step S302: Obtain the data set M consisting of the sampled data of the electrical physical quantity in the j-th unit monitoring time period of the first detection time period. j , for M j The detached data in the dataset is removed to obtain dataset M. j * ;

[0060] Methods for removing detached data include:

[0061] Standard deviation method (Z-score), box plot, DBSCAN clustering, isolated forest algorithm, statistical methods or local outlier identification method (LOF);

[0062] Step S303: Calculate the data set M j * The average value α j Obtain a data set M consisting of sampled data of the electrical physical quantity in the (j+1)th unit monitoring time period of the first detection time period. j+1 Calculate M j With M j+1 The coefficients of variation dsc f , , where k i This represents the sampling data of the i-th electrical physical quantity in the (j+1)-th unit monitoring time period of the first detection time period, and N represents the number of sampling data in the (j+1)-th unit monitoring time period of the first detection time period.

[0063] Step S304: Obtain three consecutive discrete coefficients (dsc) between any four consecutive monitoring time periods. w dsc w+1 and dsc w+2 When dsc w+2 -dsc w+1 >dsc w+1 -dsc w When it is determined that the power supply of the first power supply phase is abnormal, the end time of the second unit monitoring time period in any four consecutive unit monitoring time periods is obtained and recorded as time t1 when the first power supply phase is abnormal.

[0064] Step S400: Set the detection period, obtain the load parameters of the electrical equipment in the previous and next detection periods at time t1, calculate the data fluctuation of the load parameters, and when the dispersion of the load parameter data increases after time t1, determine whether the electrical equipment has an abnormality after time t1.

[0065] Step S400 includes:

[0066] Step S401: Set a detection period with a time length of T1 to uniformly sample the load power of the electrical equipment. Set two adjacent detection periods TC1 and TC2. Calculate the variance σ1 of the load power sampling data of the electrical equipment in period TC1 and the variance σ2 of the load power sampling data of the electrical equipment in period TC2. When σ2 > σ1, it is determined that the electrical equipment has an abnormality after time t1.

[0067] Step S402: When σ2≤σ1, calculate the output power Q1 of the electrical equipment in period TC1 and the output power Q2 of the electrical equipment in period TC2. When Q2<Q1, determine that the electrical equipment has an abnormality after time t1.

[0068] Step S403: When Q2≥Q1, obtain the average power P2 of the electrical equipment in the TC2 time range, and collect the historical data of load power. The variance values ​​of the load power sampling data of the electrical equipment when the load power is P2 form a variance reference set R. The range of all variance values ​​in the variance reference set R is the variance reference range.

[0069] Step S404: When σ2 is not within the variance reference range, it is determined that the electrical equipment has an abnormality after time t1;

[0070] Step S500: Obtain sampling data of the electrical physical quantities of several first power supply phases, calculate the average value of the discrete coefficients, connect the circuit of the second power supply phase and the electrical equipment, and calculate the average value of the discrete coefficients after connecting the circuit of the second power supply phase and the electrical equipment.

[0071] Step S500 includes:

[0072] Step S501: Starting from time t1, obtain sampling data of the electrical physical quantity of the first power supply phase for a continuous k1 unit monitoring time period, calculate the k1-1 discrete coefficients of the sampling data for a continuous u1 unit monitoring time period, and calculate the average value D1 of the k1-1 discrete coefficients.

[0073] Step S502: Connect the circuit switch between the second power supply phase and the electrical equipment, and record the time t2 when the circuit between the second power supply phase and the electrical equipment is connected;

[0074] Step S503: Starting from time t2, obtain sampling data of the electrical physical quantity of the first power supply phase for a continuous u1 unit monitoring time period, calculate u1-1 discrete coefficients of the sampling data for the continuous u1 unit monitoring time period, and calculate the average value D2 of the u1-1 discrete coefficients.

[0075] Step S600: Compare the changes in the average value of the discrete coefficients, and adjust the power supply circuit of the electrical equipment based on the judgment result in step S400;

[0076] Step S600 includes:

[0077] Step S601: When D2≥D1, and the electrical equipment malfunctions after time t1, disconnect the circuit switch between the first power supply phase and the electrical equipment.

[0078] Step S602: When D2 < D1, and the electrical equipment does not experience an abnormality after time t1, turn on the switching circuit switch and disconnect the circuit switch between the first power supply phase and the electrical equipment.

[0079] Step S603: When D2≥D1, and the electrical equipment does not experience an abnormality after time t1, or when D2<D1, and the electrical equipment experiences an abnormality after time t1, keep reminding the relevant equipment management personnel to check the relevant equipment.

[0080] When D2≥D1, and the electrical equipment experiences an abnormality after time t1, it indicates that the electrical equipment is affected by the abnormality of the first power supply phase. At this time, the first power supply phase is unavailable, and the second power supply phase supplies power to the electrical equipment. At this time, the IoT system controls SW1 and SW2 to disconnect and SW2 to close.

[0081] When D2 < D1, and the electrical equipment does not experience an abnormality after time t1, after the second power supply phase is connected, the data of the first power supply phase becomes stable, indicating that the load of the electrical equipment itself has increased beyond the design specifications. At this time, the first power supply phase and the second power supply phase need to work together to supply power to the electrical equipment. In order to solve the circuit operation problem, the two currents are combined. At this time, SW2 and SW3 are closed and SW1 is opened by controlling the Internet of Things system.

[0082] The system includes:

[0083] The system includes a circuit management module, a historical data management module, a discrete difference calculation module, an electrical equipment management module, a discrete coefficient average meter module, and a switch management module.

[0084] The circuit management module is used to store and manage the circuit structure.

[0085] The historical data management module is used to manage historical data on the load power of electrical equipment.

[0086] The discrete difference calculation module is used to calculate the time when discrete differences occur in the first power supply phase. The discrete difference calculation module includes: a first sampling unit, a data cleaning unit, a discrete coefficient calculation unit, and an abnormal time acquisition unit. The first sampling unit is used to sample the electrical physical quantities of the first power supply phase, the data cleaning unit is used to remove free data from the sampled data, the discrete coefficient calculation unit is used to calculate the discrete coefficient, and the abnormal time management unit is used to calculate the time when an abnormality occurs in the first power supply phase.

[0087] The electrical equipment management module is used to manage electrical equipment. The electrical equipment management module includes: a second sampling unit, a variance calculation unit, a power acquisition unit, and a first judgment unit. The second sampling unit is used to sample the load power of the electrical equipment. The variance calculation unit is used to calculate the variance of the sampled load power data of the electrical equipment. The power acquisition unit is used to acquire the output power of the electrical equipment. The first judgment unit is used to determine whether the electrical equipment has an abnormality after time t1.

[0088] The discrete coefficient averager module is used to calculate the average of the discrete coefficients. The discrete coefficient averager module includes an abnormal time acquisition unit, a first average calculation unit, and a second average calculation unit. The abnormal time acquisition unit is used to acquire the time when the first power supply phase is abnormal. The first average calculation unit is used to calculate the average of the discrete coefficients of the sampled data of the first power supply phase before the second power supply phase is connected to the circuit of the electrical equipment. The second average calculation unit is used to calculate the average of the discrete coefficients of the sampled data of the first power supply phase after the second power supply phase is connected to the circuit of the electrical equipment.

[0089] The switch management module is used to control the circuit switches. The switch management module includes a second determination unit, a circuit switch control unit, and an information feedback unit. The second determination unit is used to determine the de-control mode of the switches in the circuit, the circuit switch control unit is used to control the switches in the circuit, and the information feedback unit is used to send message reminders to relevant management personnel.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0091] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An Internet of Things-based stable voltage power switch safety monitoring method, characterized in that, The method comprises the following steps: Step S100: setting a first power supply phase and a second power supply phase for a power consumption device, each power supply phase being provided with a power supply circuit switch in the circuit of the power consumption device, connecting the circuits between the first power supply phase and the second power supply phase through a conversion circuit, and setting a conversion circuit switch in the conversion circuit; Step S200: obtaining historical data of the load power of the power consumption device from the operation record of the power consumption device; Step S300: when the power consumption device is powered by the first power supply phase, detecting the electrical physical quantity of the current in the power supply circuit switch during the power supply process, recording the alarm time when an alarm occurs, obtaining the operation record of the first power supply phase in the first detection time period before the alarm time, setting a unit monitoring time period, recording the difference of the electrical physical quantity in the two monitoring time periods as a dispersion coefficient, and recording the moment when the dispersion coefficient changes as the t1 moment; Step S300 comprises: acquire three consecutive discrete coefficients between any four consecutive monitoring time periods, dsc w , dsc w+1 and dsc w+2 , when dsc w+2 -dsc w+1 > dsc w+1 -dsc w , it is judged that the first power supply phase power supply is abnormal, and the end time of the second unit monitoring time period in the four consecutive monitoring time periods is obtained, which is recorded as the t1 time when the first power supply phase is abnormal. Step S400: setting a detection period, obtaining the load parameters of the power consumption device in the previous detection period and the next detection period of the t1 moment, calculating the data fluctuation change of the load parameters, and determining whether the power consumption device is abnormal after the t1 moment when the dispersion degree of the data of the load parameters increases; Step S500: obtaining the sampling data of the electrical physical quantity of a plurality of first power supply phases, calculating the average value of the dispersion coefficient, connecting the circuit of the second power supply phase and the power consumption device, and calculating the average value of the dispersion coefficient after the circuit of the second power supply phase and the power consumption device is connected; Step S600: comparing the change of the average value of the dispersion coefficient, and adjusting the power supply circuit of the power consumption device in combination with the determination result in step S400. 2.The stable voltage power switch safety monitoring method based on the Internet of Things according to claim 1, characterized in that: Step S300 comprises: Step S301: uniformly sampling the electrical physical quantity in the first detection time period, setting a unit monitoring time period, the first detection time period comprising a plurality of unit monitoring time periods, the time length of the unit monitoring time period being T0, and collecting the sampling data of the electrical physical quantity in each unit monitoring time period in the first detection time period; Step S302: obtaining a data set M composed of the sampled data of the electrical physical quantity in the jth unit monitoring time period in the first detection time period j , removing the free data in M j , to obtain a data set M j * ; Step S303: calculating the data set M j * the average value a j , obtaining a data set M composed of sampling data of the electrical physical quantity in the j+1th unit monitoring time period in the first detection time period j+1 , calculating M j and the discrete coefficient dsc j+1 of M f , , wherein k i represents the i th sampling data of the electrical physical quantity in the j+1th unit monitoring time period in the first detection time period, and N represents the number of sampling data in the j+1th unit monitoring time period in the first detection time period. 3.The IoT-based stable voltage power switch safety monitoring method according to claim 2, characterized in that: Step S400 comprises: Step S401: uniformly sampling the load power of the power consumption device by setting a detection period with a time length of T1, setting two adjacent detection periods TC1 and TC2, calculating the variance σ1 of the load power sampling data of the power consumption device in the period TC1, the variance σ2 of the load power sampling data of the power consumption device in the period TC2, and determining that the power consumption device is abnormal after the t1 moment when σ2> σ1; Step S402: when σ2≤ σ1, calculating the output power Q1 of the power consumption device in the period TC1 and the output power Q2 of the power consumption device in the period TC2, and determining that the power consumption device is abnormal after the t1 moment when Q2< Q1; Step S403: When Q2≥Q1, the average power P2 of the electrical equipment in the time range of TC2 is obtained, and the variance values of the load power sampling data of the electrical equipment when the load power is P2 form a variance reference set R, and the range of all the variance values in the variance reference set R is a variance value reference range; Step S404: When σ2 is not in the variance value reference range, it is determined that the electrical equipment is abnormal after t1.

4. The stable voltage power supply switch safety monitoring method based on the Internet of Things according to claim 3, characterized in that: Step S500 includes: Step S501: From t1, the sampling data of the electrical physical quantity of the first power supply phase in the continuous k1 unit monitoring time period is obtained, the k1-1 dispersion coefficients of the sampling data in the continuous u1 unit monitoring time period are calculated, and the average value D1 of the k1-1 dispersion coefficients is calculated; Step S502: The circuit switch between the second power supply phase and the electrical equipment is turned on, and the time t2 when the second power supply phase and the electrical equipment circuit are connected is recorded; Step S503: From time t2, the sampling data of the electrical physical quantity of the first power supply phase in the continuous u1 unit monitoring time period is obtained, the u1-1 dispersion coefficients of the sampling data in the continuous u1 unit monitoring time period are calculated, and the average value D2 of the u1-1 dispersion coefficients is calculated.

5. The method according to claim 4, wherein the method is characterized by: Step S600 includes: Step S601: When D2≥D1, and the electrical equipment is abnormal after t1, the circuit switch between the first power supply phase and the electrical equipment is turned off; Step S602: When D2 Step S603: When D2≥D1, and the electrical equipment is not abnormal after t1, or D2 6. A switching safety monitoring system for a regulated power supply based on the switching safety monitoring method according to any one of claims 1 to 5, characterized in that The system includes the following modules: circuit management module, historical data management module, dispersion difference calculation module, electrical equipment management module, dispersion coefficient average value calculation module, and switch management module, wherein the circuit management module is used to store and manage the circuit structure, the historical data management module is used to manage the historical data of the load power of the electrical equipment, the dispersion difference calculation module is used to calculate the time when the first power supply phase appears dispersion difference, the electrical equipment management module is used to manage the electrical equipment, the dispersion coefficient average value calculation module is used to calculate the average value of the dispersion coefficient, and the switch management module is used to control the circuit switch.

7. The regulated power supply switch safety monitoring system of claim 6, wherein: The dispersion difference calculation module includes a first sampling unit, a data cleaning unit, a dispersion coefficient calculation unit, and an abnormal time acquisition unit, wherein the first sampling unit is used to sample the electrical physical quantity of the first power supply phase, the data cleaning unit is used to remove the free data in the sampling data, the dispersion coefficient calculation unit is used to calculate the dispersion coefficient, and the abnormal time acquisition unit is used to calculate the time when the first power supply phase appears abnormal.

8. The regulated power supply switch safety monitoring system of claim 7, wherein: The power utilization equipment management module comprises a second sampling unit, a variance calculation unit, a work acquisition unit and a first judging unit, wherein the second sampling unit is configured to sample the load power of the power utilization equipment, the variance calculation unit is configured to calculate the variance of the load power sampling data of the power utilization equipment, the work acquisition unit is configured to acquire the output work of the power utilization equipment, and the first judging unit is configured to judge whether the power utilization equipment is abnormal after t1.

9. The regulated power supply switch safety monitoring system of claim 8, wherein: The discrete coefficient average value calculation module comprises an abnormal time acquisition unit, a first average value calculation unit and a second average value calculation unit, wherein the abnormal time acquisition unit is configured to acquire the time when the first power supply phase is abnormal, the first average value calculation unit is configured to calculate the average value of the discrete coefficient of the first power supply phase sampling data before the second power supply phase is connected to the power utilization equipment circuit, and the second average value calculation unit is configured to calculate the average value of the discrete coefficient of the first power supply phase sampling data after the second power supply phase is connected to the power utilization equipment circuit.

10. The regulated power supply switch safety monitoring system of claim 9, wherein: The switch management module comprises a second judging unit, a circuit switch control unit and an information feedback unit, wherein the second judging unit is configured to judge the control mode of the switch in the circuit, the circuit switch control unit is configured to control the switch in the circuit, and the information feedback unit is configured to remind the relevant management personnel of the message.

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