Power distribution cabinet safety early warning method and device based on progressive early warning mode, computer equipment and storage medium

Abstract

The invention relates to the technical field of power distribution cabinet safety monitoring, in particular to a power distribution cabinet safety early warning method and device based on a progressive early warning mode, computer equipment and a storage medium. The operation cycle of the power distribution cabinet is divided into a starting stage, a normal operation stage and a shutdown stage, and sensors are deployed in each stage to collect specific parameters. Calculating initial risk indexes in the starting and stopping stages through a dynamic weighted summation algorithm, and calculating and fusing different load risk indexes in the normal operation stage by using nonlinear calculation and a risk matrix. And then calculating a progressive factor correction risk index, finally dividing into four risk levels of normal, attention, warning and emergency, and formulating an early warning strategy according to the levels. By collecting and analyzing various operation parameters of different operation stages of the power distribution cabinet, the risk index of each stage is accurately calculated, and the corresponding early warning strategy is formulated according to the risk level, so that comprehensive monitoring and effective early warning of the safety condition of the power distribution cabinet are realized, and the risk of power accidents is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution cabinet safety monitoring, and particularly to a power distribution cabinet safety warning method, device, computer device and storage medium based on a progressive warning method. Background Art

[0002] In modern power systems, as the core equipment for power distribution and control, the safety and stability of power distribution cabinets during operation are of crucial importance. With the continuous growth of power demand and the increasing degree of industrial automation, the tasks borne by power distribution cabinets are becoming more and more onerous, and the operating environment is also more complex and changeable.

[0003] During the actual operation process, a power distribution cabinet will go through different stages such as startup, normal operation, and shutdown, and each stage faces various potential risks. During the startup stage, due to the instantaneous changes in current and voltage, it may cause a large impact on the electrical components inside the power distribution cabinet, resulting in problems such as poor contact and insulation damage. During the normal operation stage, long-term load operation will cause the equipment to heat up, accelerating the aging of components; at the same time, interference factors such as harmonics and voltage fluctuations in the power grid will also affect the normal operation of the power distribution cabinet. The shutdown stage cannot be ignored either. If the current and voltage decay abnormally during the shutdown process, it may imply potential fault hazards inside the equipment.

[0004] Traditional power distribution cabinet safety monitoring methods have many limitations. Some simple monitoring methods only rely on the threshold judgment of a single parameter. For example, only the magnitude of the current is monitored, and an alarm is issued when the current exceeds the set threshold. However, this method cannot comprehensively consider the influence of other parameters such as voltage deviation and temperature change, and it is easy to misjudge or miss a judgment. Moreover, the operating state of the power distribution cabinet is a dynamic change process, and traditional methods are difficult to adapt to this change and cannot accurately evaluate its potential risks in a timely manner.

[0005] In addition, with the advancement of the intelligent development trend of power distribution cabinets, the requirements for the accuracy and real-time performance of their safety monitoring are also getting higher and higher. Existing monitoring technologies are difficult to meet this demand, resulting in some potential faults of power distribution cabinets not being discovered and processed in a timely manner during actual operation, which may then lead to serious power accidents, bringing huge economic losses and safety hazards to production and life. Therefore, it is extremely urgent to develop a more advanced and accurate power distribution cabinet safety warning method. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention proposes a power distribution cabinet safety warning method, device, computer device and storage medium based on a progressive warning method. By collecting and analyzing various operating parameters at different operating stages of the power distribution cabinet, accurately calculating the risk index of each stage, and formulating corresponding warning strategies according to the risk level, the comprehensive monitoring and effective warning of the safety status of the power distribution cabinet are realized, and the risk of power accidents is reduced.

[0007] The technical solution of the present invention is as follows:

[0008] One of the objectives of the present invention is to provide a power distribution cabinet safety warning method based on a progressive warning method, including:

[0009] The complete operation cycle of the power distribution cabinet is sequentially divided into a startup stage, a normal operation stage, and a shutdown stage; a variety of sensors are deployed in each stage to collect in real time the operating parameters affecting the power distribution cabinet;

[0010] According to the operating parameters, the preliminary startup stage risk index PSRI is calculated by the dynamic weighted summation algorithm;

[0011] The normal operation stage includes a light load operation stage and a full load operation stage. According to the operating parameters, the light load operation stage risk index NRI-L and the full load operation stage risk index NRI-H are calculated, and NRI-L and NRI-H are fused according to weights based on the dynamic fusion algorithm of the sliding time window to obtain the preliminary normal operation stage risk index PNRI;

[0012] Referring to the operating parameters at shutdown, the preliminary shutdown stage risk index PSHRI is calculated by the dynamic weighted summation algorithm;

[0013] Calculate the SHRI-SRI progression factor, the SRI-NRI progression factor, and the NRI-SHRI progression factor. Through the calculation of the progression factor and the corresponding preliminary risk factor, the startup stage risk index SRI, the normal operation stage risk index NRI, and the shutdown stage risk index SHRI are obtained;

[0014] The risk levels of each stage are divided into four levels: normal, attention, warning, and emergency, and a warning strategy based on the risk level is formulated. The risk thresholds of each level are set, and the warning strategy is obtained through the judgment of the risk index and the risk threshold.

[0015] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, in the startup stage, the monitored and collected operating parameters include: the peak startup current, the voltage fluctuation amplitude, the cabinet internal temperature rise rate, the initial vibration peak value, and the environmental temperature and humidity gradient;

[0016] During the normal operation stage, the monitored and collected operation parameters include: current harmonic content, voltage deviation, average cabinet temperature, humidity value, and current transient characteristics;

[0017] During the shutdown stage, the monitored and collected operation parameters include: current decay rate, voltage fall curve, residual temperature inside the cabinet, shutdown vibration decay rate, and environmental particulate deposition rate.

[0018] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the steps of calculating the preliminary risk index PSRI of the startup stage by the dynamic weighted summation algorithm include:

[0019] Determine the weights of the operation parameters in the startup stage;

[0020] Based on the weights of the operation parameters in the startup stage, calculate the preliminary risk index PSRI of the startup stage. The calculation formula is:

[0021]

[0022] where PSRI is the preliminary risk index of the startup stage, x ni is the value after normalization of the i-th parameter in the startup stage, and ω i (t) is the weight corresponding to the i-th operation parameter.

[0023] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the calculation formula for the weights of the operation parameters in the startup stage is:

[0024]

[0025] where ω i (t) is the weight corresponding to the i-th operation parameter, is the real-time change rate of the i-th operation parameter, is the corresponding time interval, and β i is the empirical coefficient of the i-th operation parameter.

[0026] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the light load operation stage refers to the operation state when the load carried by the power distribution cabinet is equal to or lower than 60% of its rated load;

[0027] The full load operation stage is the operation state when the load carried by the power distribution cabinet is higher than 60% of its rated load;

[0028] The formula for calculating the risk index NRI-L of the light load operation stage is:

[0029]

[0030] Among them, x 1 represents the current harmonic content I h , x 2 represents the voltage deviation ΔV, x 3 represents the average temperature T inside the cabinet avg , x 4 represents the humidity value H, x 5 represents the current transient characteristic T tr , and represent the coefficients of single parameters, the coefficients of two-parameter interaction terms, and the coefficients of three-parameter interaction terms respectively;

[0031] The formula for calculating the risk index NRI-H in the full-load operation stage is:

[0032]

[0033] Among them, x 1 represents the current harmonic content I′ h , x 2 represents the voltage deviation ΔV′, x 3 represents the average temperature T′ inside the cabinet avg , x 4 represents the humidity value H′, x 5 represents the current transient characteristic T′ tr , s i is the grade score divided according to the severity of each parameter, r i is the evaluation coefficient of the possibility of risk occurrence.

[0034] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the steps for calculating the preliminary risk index PNRI in the normal operation stage include:

[0035] Set the sliding time window length T, and the time window slides on the operation time axis of the power distribution cabinet, and each time it slides by a fixed time interval Δt, where Δt < T;

[0036] Calculate the proportion P of the light-load operation time L and the proportion P of the full-load operation time H : and P L +P H = 1, where P L is the proportion of the light-load operation time, P H is the proportion of the full-load operation time, T L is the duration of the light-load operation, T H is the duration of the full-load operation,

[0037] By adopting the formula: PNRI = P L ×NRI - L + P H ×NRI - H, calculate the preliminary risk index PNRI in the normal operation stage.

[0038] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the steps of calculating the preliminary risk index PSHRI in the shutdown stage by the dynamic weighted summation algorithm include:

[0039] Determine the weights of the operating parameters in the shutdown stage;

[0040] Based on the weights of the operating parameters in the shutdown stage, calculate the preliminary risk index PSHRI, and the calculation formula is:

[0041]

[0042] Wherein, PSRRI is the preliminary risk index in the shutdown stage, x′ ni is the value after normalization of the i-th parameter in the shutdown stage, ω′ i (t) is the weight corresponding to the i-th operating parameter.

[0043] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the weight calculation formula of the operating parameters in the shutdown stage is:

[0044]

[0045] Wherein, ω′ i (t) is the weight corresponding to the i-th operating parameter, is the real-time change rate of the i-th operating parameter, is the corresponding time interval, β′ i is the experience coefficient of the i-th operating parameter.

[0046] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the calculation formulas of the SHRI - SRI progressive factor, SRI - NRI progressive factor and SRI - NRI progressive factor are:

[0047]

[0048] Wherein, K SHRI-SRI is the SHRI - SRI progressive factor, K SRI-NRI is the SRI - NRI progressive factor, λ 1 and σ 1 、λ 2 and σ 2 、and λ 3 and σ3 They are the adjustment coefficients corresponding to the SHRI-SRI progression factor, the SRI-NRI progression factor, and the NRI-SHRI progression factor respectively.

[0049] According to the power distribution cabinet safety warning method based on the progressive warning method of the present application, in a possible implementation manner, the risk indices in the startup stage SRI, the risk index in the normal operation stage NRI, and the risk index in the shutdown stage SHRI are calculated by the following formulas:

[0050] SRI = PSRI × (1 + K SHRI-SRI );

[0051] NRI = PNRI × (1 + K SRI-NRI );

[0052] SHRI = PSHRI × (1 + K NRI-SHRI ).

[0053] The second object of the present invention is to provide a device for implementing the power distribution cabinet safety warning method based on the progressive warning method. The device includes:

[0054] Operation stage division and parameter acquisition module: used to sequentially divide the complete operation cycle of the power distribution cabinet into a startup stage, a normal operation stage, and a shutdown stage; deploy a variety of sensors in each stage to collect the operation parameters affecting the power distribution cabinet in real time;

[0055] PSRI calculation module: used to calculate the preliminary risk index PSRI in the startup stage according to the operation parameters through the dynamic weighted summation algorithm;

[0056] PNRI calculation module: The normal operation stage includes a light load operation stage and a full load operation stage. According to the operation parameters, calculate the risk index NRI-L in the light load operation stage and the risk index NRI-H in the full load operation stage, and fuse NRI-L and NRI-H according to the weight based on the dynamic fusion algorithm of the sliding time window to obtain the preliminary risk index PNRI in the normal operation stage;

[0057] PSHRI calculation module: used to calculate the preliminary risk index PSHRI in the shutdown stage by referring to the operation parameters at shutdown through the dynamic weighted summation algorithm;

[0058] Progression factor calculation module: used to calculate the SHRI-SRI progression factor, the SRI-NRI progression factor, and the NRI-SHRI progression factor, and obtain the risk index SRI in the startup stage, the risk index NRI in the normal operation stage, and the risk index SHRI in the shutdown stage through the calculation of the progression factor and the corresponding preliminary risk factor;

[0059] Risk level classification and early warning strategy execution module: used to classify the risk levels in each stage into four levels: normal, attention, warning, and emergency, formulate an early warning strategy based on the risk level, set the risk thresholds for each level, and obtain the early warning strategy by judging the risk index and the risk threshold.

[0060] A third object of the present invention is to provide a computer device, the computer device includes: a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement a power distribution cabinet safety early warning method based on a progressive early warning method.

[0061] A fourth object of the present invention is to provide a computer-readable storage medium, and at least one instruction, at least one program, a code set or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a power distribution cabinet safety early warning method based on a progressive early warning method.

[0062] The beneficial effects brought by the technical solutions provided in the embodiments of the present application at least include the following beneficial effects:

[0063] Traditional monitoring methods often ignore the differences in different operation stages of the power distribution cabinet. This method divides its complete operation cycle into start-up, normal operation, and shutdown stages, and deploys multiple sensors to collect specific parameters in each stage. In the start-up stage, parameters such as the peak value of the start-up current are monitored. In the normal operation stage, the light load and full load conditions are subdivided to monitor the harmonic content of the current, etc. In the shutdown stage, the current decay rate is monitored, etc. Through multi-stage fine monitoring, the operation state of the power distribution cabinet is comprehensively grasped, the risk is more accurately evaluated, and the one-sidedness of the traditional method is overcome.

[0064] The dynamic weighted summation algorithm is used to calculate the preliminary risk index in the start-up and shutdown stages, and the weights are adjusted according to the real-time change rate of the parameters. The parameters with a large change rate have a high weight, which can more accurately reflect the influence of the parameters on the risk. In the normal operation stage, the non-linear calculation method and the risk matrix are combined with the parameter correction coefficient to calculate the light load and full load risk indexes respectively, and then the sliding time window dynamic fusion algorithm is used to comprehensively consider the proportion of the light load and full load operation time, so that the preliminary risk index in the normal operation stage is more in line with the actual situation. These advanced algorithms effectively improve the accuracy of risk assessment.

[0065] Calculate the progressive factors of SHRI-SRI, SRI-NRI, and NRI-SHRI, comprehensively consider the differences in operation parameters in different stages, and reflect the progressive relationship of risks in each stage. Use the progressive factor to correct the preliminary risk index, so that the final risk index can reflect the dynamic changes of the operation risk of the power distribution cabinet, optimize the risk assessment system, and provide a basis for more accurately judging the risk trend.

[0066] The risk level is divided into four levels: normal, concerned, warning, and emergency. Thresholds are set based on the historical operation data of the power distribution cabinet and industry standards. Corresponding early warning strategies are formulated for different levels. For the normal level, continuous monitoring is carried out; for the concerned level, reminders are given and the inspection frequency is increased; for the warning level, an alarm is issued and a comprehensive inspection is carried out in preparation for maintenance; for the emergency level, an emergency early warning is issued and the emergency response plan is activated. This scientific classification and targeted strategy can respond to risks in a timely manner and ensure the safe operation of the power distribution cabinet. Description of the Drawings

[0067] Figure 1 It is a schematic diagram of the overall process of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0068] Figure 2 It is a flowchart of step S100 of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0069] Figure 3 It is a flowchart of step S200 of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0070] Figure 4 It is a flowchart of step S300 of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0071] Figure 5 It is a flowchart of step S400 of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0072] Figure 6 It is a flowchart of step S500 of the safety early warning method for the power distribution cabinet based on the progressive early warning method;

[0073] Figure 7 It is a flowchart of step S600 of the safety early warning method for the power distribution cabinet based on the progressive early warning method. Detailed Implementation Manner

[0074] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0075] Example 1

[0076] Traditional safety monitoring methods for distribution cabinets often use single indicators or simple threshold judgment methods, making it difficult to comprehensively and accurately evaluate the risk status of distribution cabinets at different operating stages. This monitoring method is prone to false positives or false negatives, unable to detect potential safety hazards in a timely manner, resulting in the distribution cabinet possibly continuing to operate in an undetected faulty state, thereby triggering serious power accidents and causing huge economic losses and social impacts.

[0077] To solve the above problems, please refer to Figure 1 , which shows a safety warning method for distribution cabinets based on a progressive warning method provided by an embodiment of the present invention. The method includes:

[0078] S100: Sequentially divide the complete operating cycle of the distribution cabinet into a startup stage, a normal operating stage, and a shutdown stage; deploy multiple sensors in each stage to collect operation parameters affecting the distribution cabinet in real time.

[0079] S200: Calculate the preliminary startup risk index PSRI in the startup stage according to the operation parameters through a dynamic weighted summation algorithm.

[0080] The normal operating stage includes a light load operating stage and a full load operating stage. Calculate the light load operating stage risk index NRI-L and the full load operating stage risk index NRI-H according to the operation parameters, and fuse NRI-L and NRI-H according to weights based on a dynamic fusion algorithm with a sliding time window to obtain the preliminary normal operating stage risk index PNRI.

[0081] S400: Calculate the preliminary shutdown stage risk index PSHRI in the shutdown stage by referring to the operation parameters at shutdown through a dynamic weighted summation algorithm.

[0082] S500: Calculate the SHRI-SRI progression factor, the SRI-NRI progression factor, and the NRI-SHRI progression factor. Obtain the startup stage risk index SRI, the normal operating stage risk index NRI, and the shutdown stage risk index SHRI through the calculation of the progression factor and the corresponding preliminary risk factor.

[0083] S600: Divide the risk levels of each stage into four levels: normal, attention, warning, and emergency, and formulate a warning strategy based on the risk level. Set the risk thresholds for each level, and obtain the warning strategy through the judgment of the risk index and the risk threshold.

[0084] S100 divides the operating stage of the distribution cabinet into three stages: startup, normal operation, and shutdown. The startup stage starts from the moment the power is turned on until the internal electrical components are initialized and the equipment runs stably. The normal operating stage includes light load and full load operating conditions. The shutdown stage starts from the moment the shutdown command is issued until the internal equipment completely stops working and the parameters return to zero. Sensors are deployed in the distribution cabinet to collect various operation parameters in the three stages respectively.

[0085] Please refer to Figure 2 , which shows the flowchart of S100 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application. The content includes:

[0086] S110: Divide the operation stage of the power distribution cabinet into a startup stage, a normal operation stage, and a shutdown stage.

[0087] The definition of the startup stage starts from the moment when the power distribution cabinet is powered on and ends at the time when all internal electrical components complete initialization and the equipment operation state reaches stability, which is defined as the startup stage. At the moment of startup, due to the transient response of components such as inductors and capacitors in the circuit, parameters such as current and voltage will fluctuate greatly.

[0088] The normal operation stage covers two working conditions: a light load operation stage and a full load operation stage. The light load operation stage refers to the operation state when the load carried by the power distribution cabinet is less than 60% of its rated load; the full load operation stage is the operation state when the load reaches or approaches the rated load. Under different load conditions, the variation laws of the operation parameters of the power distribution cabinet are different, and monitoring and evaluation need to be carried out separately.

[0089] The determination of the shutdown stage is the process from the operator issuing a shutdown command, the power distribution cabinet starts to cut off the load current until all internal electrical equipment stops working completely and the relevant parameters return to zero, which is the shutdown stage. During the shutdown process, the decay of current and voltage, and the decrease of equipment temperature.

[0090] S120: Deploy sensors in the power distribution cabinet to monitor and collect various operation parameters that affect the operation of the power distribution cabinet in the startup stage, normal operation stage, and shutdown stage.

[0091] In the startup stage, the monitored and collected operation parameters include: peak startup current, voltage fluctuation amplitude, cabinet internal temperature rise rate, initial vibration peak value, and environmental temperature and humidity gradient.

[0092] In the normal operation stage, the monitored and collected operation parameters include: current harmonic content, voltage deviation, average cabinet internal temperature, humidity value, and current transient characteristics.

[0093] In the shutdown stage, the monitored and collected operation parameters include: current decay rate, voltage fall curve, remaining temperature in the cabinet, shutdown vibration decay rate, and environmental particulate deposition rate.

[0094] S200 preprocesses the operation parameters collected in the startup stage. Adjust the weight according to the real-time change rate of the parameter. The greater the real-time change rate, the higher the weight, and vice versa. Finally, use the dynamic weighted summation algorithm to calculate the preliminary risk index PSRI in the startup stage.

[0095] Please refer toFigure 3 , which shows the flowchart of S200 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application, and its content includes:

[0096] S210: Preprocess the operating parameters in the startup phase.

[0097] The preprocessing methods include outlier detection processing and data normalization processing.

[0098] Perform outlier detection on the collected startup current peak value, voltage fluctuation amplitude, cabinet internal temperature rise rate, vibration initial peak value, and ambient temperature and humidity gradient data.

[0099] In an optional embodiment, the 3σ principle based on statistics is adopted, that is, if the deviation of a data point from the mean exceeds 3 times the standard deviation, it is determined as an outlier.

[0100] For outliers, in an optional embodiment, interpolation methods such as linear interpolation or Lagrange interpolation are used for processing to ensure the continuity and accuracy of the data.

[0101] To eliminate the influence of different parameter dimensions and magnitudes, normalize the processed operating parameters.

[0102] In an optional embodiment, the min-max normalization method is adopted to map the data to the [0,1] interval. For the parameter x in the startup phase, its normalization formula is:

[0103]

[0104] where, x n is the value of the parameter x in the startup phase after normalization processing, x max and x min are respectively the minimum and maximum values of this parameter in the acquisition time period in the startup phase.

[0105] S220: Calculate the preliminary risk index PSRI in the startup phase through the dynamic weighted summation algorithm.

[0106] Determine the weights of the operating parameters in the startup phase.

[0107] In an optional embodiment, adjust the weights of the operating parameters according to the real-time change rate of the parameters. The weight calculation formula of each operating parameter is:

[0108]

[0109] where, ω i (t) is the weight corresponding to the i-th operating parameter, is the real-time change rate of the i-th operating parameter, is the corresponding time interval, β i is the empirical coefficient of the i-th operating parameter

[0110] The parameter with a larger real-time change rate means that it has a more significant impact on the operating state of the power distribution cabinet during the current startup phase, and a higher weight should be assigned; conversely, for the parameter with a smaller real-time change rate, the weight is correspondingly reduced.

[0111] Based on the weights of the operating parameters during the startup phase, calculate the preliminary risk index PSRI during the startup phase. The calculation formula is as follows

[0112]

[0113] where PSRI is the preliminary risk index during the startup phase, and x ni is the value after normalization of the i-th parameter during the startup phase.

[0114] S300 divides the normal operation phase into light load and full load operation phases. During the light load operation phase, calculate the risk index NRI-L through a non-linear formula considering the interactive effects between parameters. During the full load operation phase, calculate the risk index NRI-H based on the risk matrix and parameter correction coefficients. Use the sliding time window dynamic fusion algorithm to determine the fusion weight according to the proportion of light load and full load operation time, and fuse NRI-L and NRI-H to obtain the preliminary risk index PNRI during the normal operation phase to reflect the real-time risk status.

[0115] Please refer to Figure 4 , which shows the flowchart of S300 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application. Its content includes

[0116] S310: Divide the normal operation phase into a light load operation phase and a full load operation phase.

[0117] In the power system, the size of the load carried by the power distribution cabinet will significantly affect its operating characteristics. The light load operation phase refers to the operating state when the load carried by the power distribution cabinet is equal to or lower than 60% of its rated load. The full load operation phase is the operating state when the load reaches or approaches the rated load, that is, the operating state when the load carried by the power distribution cabinet is higher than 60% of its rated load. At this time, the pressure on each component of the power distribution cabinet is greater, the operating parameters change more complexly, and the potential risks are also higher.

[0118] S320: Calculate the risk index NRI-L during the light load operation phase.

[0119] The operating parameters affecting the light load operation phase include: current harmonic content I h , voltage deviation ΔV, average cabinet temperature T avg , humidity value H, and current transient characteristic T trCalculate the risk index NRI-L of the light load operation stage through the operation parameters in the light load operation stage.

[0120] In an alternative embodiment, a non-linear calculation of the risk index NRI-L of the light load operation stage considering the interaction effects between parameters is introduced, and the calculation formula is as follows:

[0121]

[0122] where x 1 represents the current harmonic content I h ; x 2 represents the voltage deviation ΔV; x 3 represents the average temperature T inside the cabinet avg ; x 4 represents the humidity value H; x 5 represents the current transient characteristic T tr , and represent the coefficients of single parameters, the coefficients of two-parameter interaction terms, and the coefficients of three-parameter interaction terms respectively.

[0123] S330: Calculate the risk index NRI-H of the full load operation stage.

[0124] During the full load operation stage of the power distribution cabinet, the operation parameters affecting the full load operation stage are the same as those affecting the light load operation stage, including: current harmonic content I′ h , voltage deviation ΔV′, average temperature T′ inside the cabinet avg , humidity value H′, and current transient characteristic T′ tr . Calculate the risk index NRI-H of the load operation stage through the operation parameters of the load operation stage.

[0125] In an alternative embodiment, calculate the risk index NRI-H of the full load operation stage based on the calculation method of the risk matrix and the parameter correction coefficient, and the calculation formula is as follows:

[0126]

[0127] where x 1 represents the current harmonic content I′ h , x 2 represents the voltage deviation ΔV′; x 3 represents the average temperature T′ inside the cabinet avg , x 4 represents the humidity value H′; x 5 represents the current transient characteristic T′ tr , s i is the grade score divided according to the severity of each parameter, and r i is the evaluation coefficient of the possibility of risk occurrence.

[0128] S340: Fuse NRI-L and NRI-H using the dynamic fusion algorithm based on a sliding time window, and calculate the preliminary risk index PNRI during the normal operation stage.

[0129] According to the operating characteristics of the power distribution cabinet and the data analysis requirements, set a suitable length T of the sliding time window. The time window slides on the time axis of the power distribution cabinet operation, and each time it slides by a fixed time interval Δt, where Δt < T.

[0130] Within each sliding time window, determine the fusion weights of NRI-L and NRI-H according to the proportion P L of the light load operation time and the proportion P H of the full load operation time.

[0131] The proportion P L of the light load operation time and the proportion P H of the full load operation time are calculated as follows: within the sliding time window, count the duration T L of the light load operation and the duration T H of the full load operation, then: and P L +P H = 1.

[0132] Utilize the calculated proportion P L of the light load operation time and the proportion P H of the full load operation time to fuse NRI-L and NRI-H through the following formula to obtain the preliminary risk index PNRI during the normal operation stage:

[0133] PNRI = P L × NRI-L + P H × NRI-H.

[0134] As the time window slides, continuously update the proportion P L of the light load operation time and the proportion P H of the full load operation time, thereby dynamically fusing the risk indices of the light load and full load operation stages, enabling PNRI to more accurately reflect the real-time risk status during the normal operation stage of the power distribution cabinet.

[0135] S400 adjusts the weights of each operating parameter according to the real-time change rate of the operating parameters collected during the shutdown stage. The greater the real-time change rate, the higher the weight. Use the dynamic weighted summation algorithm to calculate the preliminary risk index PSHRI during the shutdown stage.

[0136] Please refer to Figure 5 , which shows the flowchart of S400 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application, and its content includes:

[0137] S410: Preprocess the operating parameters during the shutdown phase.

[0138] During the shutdown phase of the power distribution cabinet, the obtained operating parameters include: current decay rate, voltage drop curve, residual temperature inside the cabinet, shutdown vibration decay rate, and environmental particulate deposition rate.

[0139] Preprocess the operating parameters during the shutdown phase.

[0140] The preprocessing methods include outlier detection processing and data normalization processing.

[0141] Perform outlier detection on the collected current decay rate, voltage drop curve, residual temperature inside the cabinet, shutdown vibration decay rate, and environmental particulate deposition rate.

[0142] In an optional embodiment, the 3σ principle based on statistics is adopted, that is, if the deviation of a data point from the mean exceeds 3 times the standard deviation, it is determined as an outlier.

[0143] For outliers, in an optional embodiment, interpolation methods such as linear interpolation or Lagrange interpolation are used to ensure the continuity and accuracy of the data.

[0144] To eliminate the influence of different parameter dimensions and magnitudes, normalize the processed operating parameters.

[0145] In an optional embodiment, the min-max normalization method is adopted to map the data to the [0,1] interval. For parameter x′, its normalization formula is:

[0146]

[0147] where x′ is the value of the shutdown phase parameter x′ after normalization processing, and x′ max and x′ min are respectively the minimum and maximum values of this parameter during the collection time period in the shutdown phase.

[0148] S420: Calculate the preliminary shutdown phase risk index PSHRI through the dynamic weighted summation algorithm.

[0149] Determine the weights of the operating parameters during the shutdown phase.

[0150] In an optional embodiment, adjust the weights of the operating parameters according to the real-time change rate of the parameters. The weight calculation formula for each operating parameter is:

[0151]

[0152] where ω′ i (t) is the weight corresponding to the i-th operating parameter, is the real-time change rate of the i-th operating parameter, is the corresponding time interval, β′ i is the empirical coefficient of the i operating parameters.

[0153] Based on the weights of the operating parameters in the shutdown stage, calculate the preliminary risk index PSHRI in the shutdown stage. The calculation formula is:

[0154]

[0155] where PSRRI is the preliminary risk index in the shutdown stage, x′ ni is the value of the i-th parameter in the shutdown stage after normalization.

[0156] S500 calculates three progressive factors, SHRI - SRI, SRI - NRI, and NRI - SHRI, which respectively measure the risk change degrees from the previous shutdown to the current startup, from startup to normal operation, and from normal operation to the shutdown stage. These factors comprehensively consider the differences in operating parameters in the corresponding stages, and set adjustment coefficients according to the historical operating data of the power distribution cabinet and expert experience. Using the progressive factors, combined with the preliminary risk indexes in the startup, normal operation, and shutdown stages, calculate the final risk indexes SRI, NRI, and SHRI in each stage respectively

[0157] Please refer to Figure 6 , which shows the flowchart of S500 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application. Its content includes:

[0158] S510: Calculate the SHRI - SRI progressive factor, the SRI - NRI progressive factor, and the SRI - NRI progressive factor.

[0159] The SHRI - SRI progressive factor is used to measure the degree of risk change from the previous shutdown stage to the current startup stage. The SHRI - SRI progressive factor comprehensively considers the differences in various operating parameters from the previous shutdown stage to the current startup stage to reflect the progressive relationship of risks between these two key stages in the entire operation cycle of the power distribution cabinet. The SRI - NRI progressive factor is used to reflect the risk change from the startup stage to the normal operation stage. The SRI - NRI progressive factor compares the relevant operating parameters in the startup stage and the normal operation stage, analyzes the progressive trend of risks between these two stages, and provides a basis for accurately evaluating the operation risk of the power distribution cabinet. The NRI - SHRI progressive factor reflects the progressive relationship of risks from the normal operation stage to the shutdown stage. By analyzing the differences in operating parameters between these two stages, the changing trend of risks in the later stage of the power distribution cabinet operation can be grasped more accurately, thereby providing more accurate information for risk assessment and warning. The calculation formulas are:

[0160]

[0161] Among them, K SHRI-SRI is the SHRI-SRI progression factor, and K SRI-NRI is the SRI-NRI progression factor. λ 1 and σ 1 , λ 2 and σ 2 , and λ 3 and σ 3 are the adjustment coefficients corresponding to the SHRI-SRI progression factor, the SRI-NRI progression factor, and the NRI-SHRI progression factor respectively, which are set according to the historical operation data of the power distribution cabinet and expert experience, and the value range is [0, 1]. The change amount of the comprehensive parameter in the shutdown stage is obtained by weighted summation of the change amplitudes of the operation parameters in the shutdown stage (current decay rate, voltage drop curve, residual temperature in the cabinet, shutdown vibration decay rate, environmental particulate deposition rate); the change amount of the comprehensive parameter in the startup stage is obtained by weighted summation of the change amplitudes of the operation parameters in the startup stage (peak startup current, voltage fluctuation amplitude, cabinet temperature rise rate, initial vibration peak, environmental temperature and humidity gradient); the change amount of the comprehensive parameter in the normal operation stage is the weighted summation of the change amplitudes of the operation parameters in the normal operation stage (current harmonic content, voltage deviation, average cabinet temperature, humidity value, current transient characteristics).

[0162] S520: Calculate the startup stage risk index SRI, the normal operation stage risk index NRI, and the shutdown stage risk index SHRI.

[0163] Using the obtained SHRI-SRI progression factor, SRI-NRI progression factor, and SRI-NRI progression factor, corresponding to the preliminary risk index PSRI in the startup stage, the preliminary risk index PNRI in the normal operation stage, and the preliminary risk index PSHRI in the shutdown stage respectively, calculate the startup stage risk index SRI, the normal operation stage risk index NRI, and the shutdown stage risk index SHRI. The calculation formulas are as follows:[[]]

[0164] SRI = PSRI × (1 + K SHRI-SRI );

[0165] NRI = PNRI × (1 + K SRI-NRI );

[0166] SHRI = PSHRI × (1 + K NRI-SHRI ).

[0167] The S600 classifies the risk levels of each stage of the power distribution cabinet into four levels: normal, attention, warning, and emergency. The risk thresholds for each level are set based on the historical operation data of the power distribution cabinet and industry standards. Corresponding warning strategies are formulated for different risk levels. The risk level is determined by comparing the risk index of each stage with the risk threshold, and the corresponding warning strategy is automatically triggered and executed.

[0168] Please refer to Figure 7 , which shows the flowchart of S600 of an exemplary power distribution cabinet safety warning method based on a progressive warning method in this application. The content includes:

[0169] S610: Classify the risk levels of each stage into four levels: normal, attention, warning, and emergency, and set the risk threshold.

[0170] Normal level: The risk index is at an extremely low level, indicating that the operation status of the power distribution cabinet is stable, all parameters are within the safe range, and there are almost no potential risks. The lower limit of the risk threshold is set to 0, and the upper limit is determined according to the historical operation data of the power distribution cabinet and industry standards. Within this range, the equipment performance of the power distribution cabinet is good, and no additional attention or special measures are required.

[0171] Attention level: The risk index begins to rise but has not reached a dangerous level. There may be some minor abnormalities at this stage, but they will not immediately affect the normal operation of the power distribution cabinet. The lower limit of the risk threshold is the upper limit of the normal level, and the upper limit is set according to the historical operation data of the power distribution cabinet and industry standards. The attention level means that some notable changes have occurred in the power distribution cabinet, and it is necessary to start paying attention to the fluctuations of relevant operation parameters.

[0172] Warning level: The risk index rises further, and the operation of the power distribution cabinet shows obvious abnormalities. If no measures are taken, it may cause a failure and affect the power supply stability. The lower limit of the risk threshold is the upper limit of the attention level, and the upper limit is set according to the historical operation data of the power distribution cabinet and industry standards. At this time, the operation and maintenance personnel need to attach great importance, check the power distribution cabinet in time, analyze the cause of the abnormality, and formulate and prepare to implement corresponding treatment measures.

[0173] Emergency level: The risk index reaches an extremely high level, and the power distribution cabinet is in a serious dangerous state, and a failure may occur at any time. Immediate emergency measures must be taken. The lower limit of the risk threshold is the upper limit of the warning level, and there is no upper limit setting. Once entering this level, the operation of the power distribution cabinet should be stopped immediately, and professional personnel should be organized for emergency repair to avoid greater losses caused by the expansion of the failure.

[0174] S620: Formulate a warning strategy based on the risk level.

[0175] Normal level warning strategy: No dedicated warning messages are sent, but the operation data of the power distribution cabinet is continuously recorded and monitored. Operation reports are generated regularly to simply summarize and analyze the operation data, ensuring that the power distribution cabinet always remains in a normal operation state.

[0176] Attention level warning strategy: Remind the operation and maintenance personnel to pay attention to the operation status of the power distribution cabinet through text messages or in-system messages. At the same time, highlight the relevant data of the power distribution cabinet in the monitoring system and mark it with a yellow identifier (or other distinct color). It is recommended that the operation and maintenance personnel increase the inspection frequency of the power distribution cabinet and focus on checking the equipment components corresponding to the abnormal parameters.

[0177] Warning level warning strategy: In addition to text message and in-system message notifications, a sound alarm is also required to attract the high attention of the operation and maintenance personnel. Mark the power distribution cabinet in red in the monitoring system and list the abnormal parameters and possible risk warnings in detail. Require the operation and maintenance personnel to immediately conduct a comprehensive inspection of the power distribution cabinet, including the equipment appearance, connection lines, internal components, etc. At the same time, organize technical personnel to conduct fault analysis, formulate a maintenance plan, and prepare the necessary maintenance tools and spare parts.

[0178] Emergency level warning strategy: Immediately send emergency warning messages to all relevant personnel through multiple channels. Automatically start the emergency plan, such as cutting off the power supply of the power distribution cabinet to prevent the further deterioration of the fault. Organize a professional repair team to quickly rush to the scene for repair, requiring the normal operation of the power distribution cabinet to be restored within the shortest time and reducing the impact of power outages on production and life.

[0179] S630: Implement warning judgment and strategy execution.

[0180] Compare the calculated start-up stage risk index SRI, normal operation stage risk index NRI, and shutdown stage risk index SHRI with the set risk thresholds respectively. Judge which risk level interval the risk index of each stage is in and determine the current risk level of the power distribution cabinet.

[0181] According to the determined risk level, automatically trigger and execute the corresponding warning strategy.

[0182] Embodiment 2

[0183] According to Embodiment 1 of the present application, there is provided a device for a power distribution cabinet safety warning method based on a progressive warning method. The device includes:

[0184] Operation stage division and parameter acquisition module: Used to sequentially divide the complete operation cycle of the power distribution cabinet into a start-up stage, a normal operation stage, and a shutdown stage; deploy a variety of sensors in each stage to collect the operation parameters affecting the power distribution cabinet in real time;

[0185] PSRI calculation module: used to calculate the preliminary risk index PSRI in the startup stage through the dynamic weighted summation algorithm based on the operating parameters;

[0186] PNRI calculation module: used for the normal operation stage including the light load operation stage and the full load operation stage, to calculate the risk index NRI-L in the light load operation stage and the risk index NRI-H in the full load operation stage based on the operating parameters, and fuse NRI-L and NRI-H according to the weights through the dynamic fusion algorithm based on the sliding time window to obtain the preliminary risk index PNRI in the normal operation stage;

[0187] PSHRI calculation module: used to calculate the preliminary risk index PSHRI in the shutdown stage through the dynamic weighted summation algorithm with reference to the operating parameters at shutdown;

[0188] Progressive factor calculation module: used to calculate the SHRI-SRI progressive factor, SRI-NRI progressive factor, and NRI-SHRI progressive factor, and obtain the risk index SRI in the startup stage, the risk index NRI in the normal operation stage, and the risk index SHRI in the shutdown stage through the calculation of the progressive factor and the corresponding preliminary risk factor;

[0189] Risk level classification and early warning strategy execution module: used to classify the risk levels in each stage into four levels: normal, attention, warning, and emergency, formulate an early warning strategy based on the risk level, set the risk thresholds for each level, and obtain the early warning strategy through the judgment of the risk index and the risk threshold.

[0190] According to Embodiment 1 of the present application, a computer device is provided, and the computer device includes: a processor and a memory. At least one instruction, at least one program, a code set, or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the power distribution cabinet safety early warning method based on the progressive early warning method as described in Embodiment 1.

[0191] According to Embodiment 1 of the present application, a computer-readable storage medium is provided. At least one instruction, at least one program, a code set, or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the power distribution cabinet safety early warning method based on the progressive early warning method as described in Embodiment 1.

[0192] The basic principles of the present application have been described in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations. It cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. Additionally, the specific details disclosed above are only for illustrative and facilitating understanding purposes, rather than limitations. These details do not limit the present application to necessarily implementing with the above specific details.

[0193] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present application are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The word "or" and "and" used herein refer to the phrase "and / or", and can be used interchangeably with each other, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to", and can be used interchangeably with each other.

[0194] It should also be noted that in the devices, equipment, and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present application.

[0195] The above description of the disclosed aspects enables any person skilled in the art to make or use the present application. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

[0196] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, etc. made within the spirit and principles of the present application shall be included within the protection scope of the present application.

Claims

1. A power distribution cabinet safety early warning method based on a progressive early warning method, characterized in that: include: The complete operation cycle of the power distribution cabinet is divided into the startup phase, the normal operation phase, and the shutdown phase in sequence; Deploy a variety of sensors at each stage to collect real-time data on parameters that affect the operation of the power distribution cabinet; According to the operating parameters, the initial risk index PSRI of the startup phase is calculated by a dynamic weighted summation algorithm; The normal operation stage includes the light load operation stage and the full load operation stage. According to the operation parameters, the risk index NRI-L of the light load operation stage and the risk index NRI-H of the full load operation stage are calculated. The dynamic fusion algorithm based on the sliding time window fuses NRI-L and NRI-H according to the weight to obtain the preliminary risk index PNRI of the normal operation stage. Referring to the operating parameters during shutdown, the preliminary risk index PSHRI of the shutdown phase is calculated through a dynamic weighted summation algorithm; Calculate the SHRI-SRI progressive factor, SRI-NRI progressive factor, and NRI-SHRI progressive factor. By calculating the progressive factors and the corresponding preliminary risk factors, the startup phase risk index SRI, the normal operation phase risk index NRI, and the shutdown phase risk index SHRI are obtained. The risk levels at each stage are divided into four levels: normal, concern, warning and emergency, and an early warning strategy based on the risk level is formulated. The risk thresholds for each level are set, and the early warning strategy is obtained through risk index and risk threshold judgment.

2. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 1 is characterized in that: During the startup phase, the operating parameters monitored and collected include: startup current peak value, voltage fluctuation amplitude, temperature rise rate in the cabinet, initial vibration peak value, and ambient temperature and humidity gradient; During the normal operation phase, the operating parameters monitored and collected include: current harmonic content, voltage deviation, cabinet temperature average, humidity value and current transient characteristics; During the shutdown phase, the operating parameters monitored and collected include: current decay rate, voltage drop curve, residual temperature in the cabinet, shutdown vibration decay rate, and environmental particle deposition rate.

3. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 2 is characterized in that: The steps of calculating the initial risk index PSRI in the startup phase by a dynamic weighted summation algorithm include: Determine the weight of each operating parameter during the startup phase; Based on the weights of various operating parameters in the startup phase, the initial risk index PSRI of the startup phase is calculated using the following formula: Among them, PSRI is the initial risk index in the startup phase, x ni is the normalized value of the ith parameter in the startup phase, ω i (t) is the weight corresponding to the i-th operating parameter; Among them, the weight calculation formula of each operating parameter in the startup phase is: Among them, ω i (t) is the weight corresponding to the i-th operating parameter, is the real-time change rate of the i-th operating parameter, is the corresponding time interval, β i is the empirical coefficient of the ith operating parameter.

4. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 2 is characterized in that: The light load operation stage refers to the operating state when the load carried by the distribution cabinet is equal to or less than 60% of its rated load; The full load operation stage is the operating state when the load carried by the distribution cabinet is higher than 60% of its rated load; The formula for calculating the risk index NRI-L in the light load operation stage is: Where x1 represents the current harmonic content I h , x2 represents the voltage deviation ΔV, x3 represents the average temperature T in the cabinet avg , x4 represents the humidity value H, x5 represents the current transient characteristic T tr , and They represent the coefficients of a single parameter, the coefficients of the interaction term between two parameters, and the coefficients of the interaction term between three parameters respectively; The formula for calculating the risk index NRI-H during the full load operation phase is: Where x1 represents the current harmonic content I h ′, x2 represents the voltage deviation ΔV′, and x3 represents the average temperature in the cabinet T a ' vg , x4 represents the humidity value H′, x5 represents the current transient characteristic T tr ′,s i is the grade score according to the severity of each parameter, r i is the evaluation coefficient of the probability of risk occurrence; The steps for calculating the preliminary risk index PNRI during the normal operation phase include: Set the sliding time window length T, the time window slides on the operation time axis of the distribution cabinet, each sliding a fixed time interval Δt, where Δt <T; Calculate the light load operation time ratio P L and the full load operation time ratio P H : And P L +P H =1, where P L is the proportion of light load operation time, P H is the proportion of full load operation time, T L is the duration of light load operation, T H is the full load running time, By using the formula: PNRI = P L ×NRI-L+P H ×NRI-H, calculate the preliminary risk index PNRI during the normal operation stage.

5. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 2 is characterized in that: The steps of calculating the preliminary risk index PSHRI of the shutdown phase by a dynamic weighted sum algorithm include: Determine the weight of each operating parameter during the shutdown phase; Based on the weights of the operating parameters during the shutdown phase, the preliminary risk index PSHRI during the shutdown phase is calculated using the following formula: Among them, PSRRI is the initial risk index of the shutdown phase, x′ ni is the normalized value of the ith parameter in the shutdown phase, ω i ′(t) is the weight corresponding to the i-th operating parameter; Among them, the weight calculation formula of each operating parameter in the shutdown stage is: Among them, ω i ′(t) is the weight corresponding to the i-th operating parameter, is the real-time change rate of the i-th operating parameter, is the corresponding time interval, β i ′ is the empirical coefficient of the i operating parameters.

6. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 1 is characterized in that: The calculation formulas for the SHRI-SRI progression factor, SRI-NRI progression factor and SRI-NRI progression factor are: Among them, K SHRI-SRI is the SHRI-SRI progression factor, K SRI-NRI is the SRI-NRI progressive factor, λ1 and σ1, λ2 and σ2, and λ3 and σ3 are the adjustment coefficients corresponding to the SHRI-SRI progressive factor, SRI-NRI progressive factor and NRI-SHRI progressive factor respectively.

7. The power distribution cabinet safety early warning method based on the progressive early warning method according to claim 6 is characterized in that: The calculation formulas for the startup phase risk index SRI, the normal operation phase risk index NRI, and the shutdown phase risk index SHRI are as follows: SRI=PSRI×(1+K SHRI-SRI ); NRI=PNRI×(1+K SRI-NRI ); SHRI=PSHRI×(1+K NRI-SHRI )。 8. A device for a power distribution cabinet safety early warning method based on a progressive early warning method, characterized in that: The device includes: Operation phase division and parameter collection module: used to divide the complete operation cycle of the power distribution cabinet into the startup phase, normal operation phase, and shutdown phase in sequence; Deploy a variety of sensors at each stage to collect real-time data on parameters that affect the operation of the power distribution cabinet; PSRI calculation module: used to calculate the initial risk index PSRI in the startup phase through a dynamic weighted summation algorithm based on operating parameters; PNRI calculation module: used in the normal operation stage, including the light load operation stage and the full load operation stage. According to the operation parameters, the risk index NRI-L of the light load operation stage and the risk index NRI-H of the full load operation stage are calculated. The dynamic fusion algorithm based on the sliding time window fuses NRI-L and NRI-H according to the weight to obtain the preliminary risk index PNRI of the normal operation stage. PSHRI calculation module: used to refer to the operating parameters during shutdown and calculate the preliminary risk index PSHRI during shutdown by a dynamic weighted summation algorithm; Progressive factor calculation module: used to calculate the SHRI-SRI progressive factor, SRI-NRI progressive factor, and NRI-SHRI progressive factor. By calculating the progressive factor and the corresponding preliminary risk factor, the startup phase risk index SRI, the normal operation phase risk index NRI, and the shutdown phase risk index SHRI are obtained; Risk level classification and early warning strategy execution module: used to classify the risk levels of each stage into four levels: normal, concern, warning and emergency, and formulate early warning strategies based on risk levels, set risk thresholds for each level, and obtain early warning strategies through risk index and risk threshold judgment.

9. A computer device, characterized in that: The computer device includes: a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the distribution cabinet safety warning method based on the progressive warning method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the distribution cabinet safety warning method based on the progressive warning method as described in any one of claims 1 to 7.

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