A method, analysis system, device, and storage medium for optimizing gate opening and closing times.

Abstract

The application discloses a kind of opening and closing time optimization processing method and analysis system, device, storage medium, comprising: control each circuit breaker to carry out multiple opening and closing actions, obtain control instruction in each opening and closing action and electrical data at different time;According to electrical data analysis potential fault result, control instruction, electrical data and fault result are fitted out characteristic data;Characteristic data is iterated to random population based on black-winged kite algorithm model operation;Adjust the fitness value of black-winged kite algorithm model to make black-winged kite algorithm model reach iteration number and converge;Control target circuit breaker multiple opening and closing actions, collect electrical data in each opening and closing action of target circuit breaker;The electrical data collected by target circuit breaker is substituted into the black-winged kite algorithm model adjusted, and the control instruction of target circuit breaker is optimized by the black-winged kite algorithm model adjusted, the design is reasonably optimized to control instruction, improve operating stability.

Description

Technical Field

[0001] This invention relates to the field of computer optimization strategy technology, and in particular to a method, analysis system, device, and storage medium for optimizing gate opening and closing times. Background Technology

[0002] Condition monitoring of high-voltage circuit breakers is the prerequisite and foundation for fault diagnosis. Typically, sensors detect electrical data of the circuit breaker's operating status, and the control module analyzes the electrical data to adjust control commands for parameters such as the circuit breaker's opening and closing time and applied voltage, so as to control the circuit breaker to operate properly.

[0003] There are two main existing methods for monitoring the condition of circuit breakers. One method involves analyzing the vibration signals of the circuit breaker. This method uses vibration sensors to collect vibration signals when the circuit breaker operates, extracting information reflecting the state of the circuit breaker's mechanical structure. The advantage of using vibration signals to diagnose circuit breaker faults is that it can reflect the overall health of the circuit breaker. However, fault information extraction is difficult, and vibration signals are greatly affected by the sensor's installation location and the circuit breaker's structure. Establishing a correspondence between vibration signal characteristics and fault types requires a large amount of fault data, resulting in a large number of training samples. Furthermore, fault data differs for circuit breakers with different structures, making model construction quite complex.

[0004] Another approach is to analyze the current signal from the circuit breaker coil during its opening and closing operations. Although the current signal from the circuit breaker coil cannot reflect the overall state information of the circuit breaker, it is relatively easy to obtain, and the structures of circuit breaker coils are not significantly different, with essentially the same current characteristics. Furthermore, the circuit breaker coil is the initiating mechanism for opening and closing operations, playing a crucial role in these processes. Fault diagnosis of the opening and closing coils can effectively prevent circuit breaker maloperation and failure to operate. However, currently, there is no reasonable computational model to optimize the circuit breaker's operational control based on diagnostic data. Summary of the Invention

[0005] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes a method, analysis system, device, and storage medium for optimizing the opening and closing time of circuit breakers, monitoring the electrical data of circuit breaker coils, optimizing the control commands for the opening and closing actions of circuit breakers, and improving operational stability.

[0006] A method for optimizing the opening and closing time according to a first aspect of the present invention includes: controlling each circuit breaker to perform multiple opening and closing actions, acquiring control commands for each opening and closing action, and collecting electrical data at different times during each opening and closing action; analyzing potential fault results based on the electrical data, and fitting feature data to the control commands, electrical data, and fault results; performing iterative calculations on a random population based on the feature data using a Blackwing Kite algorithm model; adjusting the fitness value of the Blackwing Kite algorithm model so that the Blackwing Kite algorithm model reaches the required number of iterations and converges; controlling a target circuit breaker to perform multiple opening and closing actions, and collecting electrical data for each opening and closing action of the target circuit breaker; substituting the electrical data collected from the target circuit breaker into the adjusted Blackwing Kite algorithm model, wherein the adjusted Blackwing Kite algorithm model optimizes the control commands for the target circuit breaker, wherein the control commands are used to control the opening and closing time of the target circuit breaker.

[0007] According to an embodiment of the present invention, a method for optimizing the opening and closing time of a gate has at least the following beneficial effects:

[0008] This invention provides a method for optimizing the opening and closing time of circuit breakers. It collects electrical data from the opening and closing actions of each circuit breaker, fits the control commands, electrical data, and fault results from each action to form feature data, and uses this feature data to construct a Black-Winged Kite algorithm model. The Black-Winged Kite algorithm model undergoes iterative computation, and its fitness value is adjusted to ensure it reaches the required number of iterations and eventually converges. When optimizing the control commands of the target circuit breaker, the adjusted Black-Winged Kite algorithm model is used to analyze the electrical data generated by the opening and closing actions of the target circuit breaker and optimize the control commands accordingly. This design monitors the electrical data of the circuit breaker coils and rationally optimizes the control commands for the opening and closing actions of the circuit breaker, thereby improving operational stability.

[0009] According to some embodiments of the present invention, the electrical data includes one or more of the following: the maximum current value of the circuit breaker coil during closing operation, the maximum current value of the circuit breaker coil during opening operation, the rate of change of current of the circuit breaker coil before and after closing, the rate of change of current of the circuit breaker coil before and after opening, the average current of the circuit breaker coil during opening operation, and the average current of the circuit breaker coil during closing operation.

[0010] According to some embodiments of the present invention, the control command is used to control electrical variable targets acting on the circuit breaker coil, the electrical variable targets including the voltage amplitude applied across the circuit breaker coil, the voltage pulse width applied across the circuit breaker coil, and the slope of the current rising edge of the circuit breaker coil; the iterative calculation of the feature data on the random population based on the Black-winged Kite algorithm model includes: using the electrical variable targets as decision variables of the Black-winged Kite algorithm model to form an individual position vector.

[0011] According to some embodiments of the present invention, in adjusting the fitness value of the Blackwing Kite algorithm model so that the Blackwing Kite algorithm model reaches the required number of iterations and converges, the fitness value is calculated by weighting the control commands to the circuit breaker coil and the operating requirements.

[0012] According to some embodiments of the present invention, the control command includes controlling the closing time t of the circuit breaker. h Control the opening time t of the circuit breaker f And the power consumption current I of the control circuit breaker coil w The operational requirements include a failure rate f a ;

[0013] Fitness value = w1 × t h +w2×t f +w3×I w +w4×f a ;

[0014] Where w1 is the weighting coefficient for controlling the closing time of the circuit breaker, w2 is the weighting coefficient for controlling the opening time of the circuit breaker, w3 is the weighting coefficient for controlling the power consumption current of the circuit breaker coil, and w4 is the weighting coefficient for the failure rate.

[0015] According to some embodiments of the present invention, fitting feature data from control commands, electrical data, and fault results includes: using a least squares support vector machine algorithm to fit feature data from control commands, electrical data, and fault results.

[0016] According to some embodiments of the present invention, after collecting electrical data at different times during each opening and closing operation, the method includes: comparing the collected electrical data with a preset electrical anomaly range, and removing electrical data that exceeds the electrical anomaly range.

[0017] An analysis system according to a second aspect of the present invention includes: a data acquisition module for acquiring electrical data of each circuit breaker and a target circuit breaker; and a control module connected to the data acquisition module, wherein the control module is used to execute the opening and closing time optimization processing method disclosed in any of the above embodiments to optimize the control commands for the target circuit breaker.

[0018] The analysis system according to embodiments of the present invention has at least the following beneficial effects:

[0019] The analysis system of this invention utilizes the opening and closing time optimization processing method disclosed in any of the above embodiments to optimize the control commands for the target circuit breaker, monitor the electrical data of the circuit breaker coil, and reasonably optimize the control commands for the opening and closing actions of the circuit breaker to improve operational stability.

[0020] According to a third aspect of the present invention, the control device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the gate opening and closing time optimization processing method disclosed in any of the above embodiments.

[0021] According to a fourth aspect of the present invention, a computer-readable storage medium stores a computer program, characterized in that, when the computer program is executed by a processor, it implements the opening and closing time optimization processing method disclosed in any of the above embodiments.

[0022] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0023] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0024] Figure 1 This is a flowchart of one embodiment of the gate opening and closing time optimization method of the present invention;

[0025] Figure 2 This is a schematic diagram of the current waveforms of the circuit breaker's opening and closing coils;

[0026] Figure 3 This is a schematic diagram of the principle structure of one embodiment of the analysis system of the present invention;

[0027] Figure 4 This is a schematic diagram of the control device of the present invention in one embodiment.

[0028] Figure label:

[0029] Circuit breaker 200; control module 300; acquisition module 400; processor 510; memory 520; input / output interface 530; communication interface 540; bus 550. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0031] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0033] like Figure 1 As shown, a method for optimizing the opening and closing time according to a first aspect embodiment of the present invention includes:

[0034] S110: Control each circuit breaker to perform multiple opening and closing actions, acquire control commands for each opening and closing action, and collect electrical data at different times during each opening and closing action.

[0035] S120. Based on the analysis of potential fault results from electrical data, feature data is fitted from control commands, electrical data, and fault results.

[0036] S130. Iteratively calculate the feature data on a random racial group based on the Black-winged Kite algorithm model;

[0037] S140. Adjust the fitness value of the Black-winged Kite algorithm model so that the Black-winged Kite algorithm model reaches the required number of iterations and converges.

[0038] S150: Control the target circuit breaker to perform multiple opening and closing actions, and collect electrical data during each opening and closing action of the target circuit breaker.

[0039] S160. Substitute the electrical data collected by the target circuit breaker into the adjusted Blackwing Kite algorithm model. The adjusted Blackwing Kite algorithm model optimizes the control instructions for the target circuit breaker, wherein the control instructions are used to control the opening and closing time of the target circuit breaker.

[0040] A current transformer can be installed in the coil of the circuit breaker 200 to detect the current information of the circuit breaker 200 as electrical data. In the electrical system, the opening and closing time of each circuit breaker 200 is controlled by the control module 300. Specifically, the control module 300 may include a processor such as a CPU and its auxiliary circuits, as well as a drive unit composed of a switching transistor or a relay. The drive unit is connected to the coil of the circuit breaker 200. The processor outputs control commands to control the drive unit to close, energizing the coil of the circuit breaker 200. The energized coil of the circuit breaker 200 drives the circuit breaker 200 to open and close.

[0041] Among them, during the opening and closing process of the circuit breaker, such as Figure 2 As shown, it includes the following stages:

[0042] Stage 1: t0~t1; t0 is the time when the circuit breaker opening and closing command is issued. The circuit breaker coil is energized at t0 and the current increases exponentially. t1 is the time when the closing coil core begins to move and the current begins to decrease. This stage can reflect the state of the circuit breaker coil.

[0043] Phase 2: t1~t2; At time t1, due to the increase of the circuit breaker coil current, the iron core begins to accelerate under the action of electromagnetic force, and the current begins to decrease. t2 indicates that the iron core touches the load of the operating mechanism, the moving contact begins to move, and the iron core stops moving. This phase reflects the movement state of the electromagnet core, whether there is jamming, tripping, energy release, mechanical load changes, etc.

[0044] Stage 3: t2~t3, the process of the operating mechanism driving the contacts to close the circuit breaker. When the iron core hits the closing locking device to lock the door or valve, the iron core stops moving or has a brief bounce, the current begins to increase, causing the opening spring to open the circuit breaker.

[0045] Stage 4: t3~t4, this stage is a continuation of stage 3. The current continues to increase slowly until it reaches an approximate steady state, and the switching process continues.

[0046] Stage 5: t4~t5. At time t4, the circuit breaker auxiliary contacts are cut off, and the current decreases rapidly. At time t5, the circuit current decreases to zero. During this stage, the auxiliary switch is disconnected, and an arc is generated and stretched in the auxiliary switch contact key. The arc voltage will rise rapidly, forcing the coil current to decrease rapidly. The contacts are completely separated, and the equivalent resistance between the contacts increases rapidly until the arc is completely extinguished.

[0047] This invention provides a method for optimizing the opening and closing time of circuit breakers. It collects electrical data from the opening and closing actions of each circuit breaker, fits the control commands, electrical data, and fault results from each action to form feature data, and uses this feature data to construct a Black-Winged Kite algorithm model. The Black-Winged Kite algorithm model undergoes iterative computation, and its fitness value is adjusted to ensure it reaches the required number of iterations and eventually converges. When optimizing the control commands of the target circuit breaker, the adjusted Black-Winged Kite algorithm model is used to analyze the electrical data generated by the opening and closing actions of the target circuit breaker and optimize the control commands accordingly. This design monitors the electrical data of the circuit breaker coils and rationally optimizes the control commands for the opening and closing actions of the circuit breaker, thereby improving operational stability.

[0048] In some embodiments of the present invention, the electrical data includes one or more of the following: the maximum current value of the circuit breaker coil during closing operation, the maximum current value of the circuit breaker coil during opening operation, the rate of change of current of the circuit breaker coil before and after closing, the rate of change of current of the circuit breaker coil before and after opening, the average current of the circuit breaker coil during opening operation, and the average current of the circuit breaker coil during closing operation.

[0049] In some embodiments of the present invention, the control command is used to control electrical variable targets acting on the circuit breaker coil, the electrical variable targets including the voltage amplitude applied across the circuit breaker coil, the voltage pulse width applied across the circuit breaker coil, and the slope of the current rising edge of the circuit breaker coil; the iterative calculation of the feature data on the random population based on the Black-winged Kite algorithm model includes: using the electrical variable targets as decision variables of the Black-winged Kite algorithm model to form an individual position vector.

[0050] Specifically, the Black Winged Kite Algorithm (BKA) optimizes the parameters of the LSSVM by iteratively calculating random populations to find the optimal solution.

[0051] In step S130, the matrix of the Black-winged Kite algorithm model is first constructed as the initial population, and a set of random solutions is created. The following matrix can be used to represent the position of each Black-winged Kite (BK):

[0052]

[0053] Where pop represents the number of potential solutions, dim represents the dimension of the given problem, and BK represents the value of the solution. i，j It is the position of the j-th black-winged kite in the i-th row, to ensure that the position of each black-winged kite is evenly distributed.

[0054] Therefore, we can conclude that:

[0055] X i =BK lb +rand(BK ub -BK lb );

[0056] Where i is an integer between 1 and pop, BK kb Let BK be the lower bound value of the i-th black-winged kite in the j-th row. ub is the upper limit value of the i-th black-winged kite in the j-th row, and rand is a value randomly selected between [0, 1].

[0057] The individual with the best fitness in the initial population, selected by the Black-winged Kite algorithm model, is chosen as the leader, X. L This position is considered the optimal position for the Black-winged Kite. Taking the minimum value as an example, the initial leader X... L The mathematical representation of is:

[0058] f best =min(f(X) i ));

[0059] X L =X(find(f) best =f(X) i )));

[0060] A mathematical model simulating the attack behavior of black-winged kites in the black-winged kite algorithm model:

[0061]

[0062] in, This represents the position of the j-th black-winged kite in the i-th row during the t-th iteration. The position of the j-th black-winged kite in the i-th row during the (t+1)-th iteration is represented by r, which is a random number from 0 to 1, p is a constant value of 0.9, T is the total number of iterations, and t is the number of iterations completed so far.

[0063] The simulation of Blackwing Kite attack behavior can include different attack behaviors targeting global exploration and search.

[0064] Bird migration is typically led by a leader. Therefore, a hypothesis based on bird migration is proposed: if the fitness value of the current population is lower than that of a random population, the leader will relinquish leadership and join the migrating population, indicating that it is unsuitable to lead the group. Conversely, if the fitness value of the current population is higher than that of a random population, the leader will guide the group until it reaches its destination. The following is a mathematical model of the migratory behavior of the black-winged kite:

[0065]

[0066] m = 2 × sin(r + π / 2);

[0067] in, This indicates the leader of the black-winged kite in the j-th dimension during the t-th iteration so far. This represents the position of the j-th black-winged kite in the i-th row during the t-th iteration. F represents the position of the j-th black-winged kite in the i-th row during the (t+1)-th iteration. i F represents the current position in the j-th dimension obtained by any black-winged kite in t iterations. ri Let C(0, 1) represent the fitness value of a random position in the j-th dimension obtained from any black-winged kite in t iterations, and let C(0, 1) represent a Cauchy mutation.

[0068] The Cauchy mutation is defined as a continuous probability distribution with two parameters in a one-dimensional Cauchy distribution.

[0069] The probability density function of a one-dimensional Cauchy distribution:

[0070]

[0071] When δ = 1 and μ = 0, the probability density function will become in its standard form, i.e.:

[0072]

[0073] In some embodiments of the present invention, in adjusting the fitness value of the Blackwing Kite algorithm model so that the Blackwing Kite algorithm model reaches the required number of iterations and converges, the fitness value is calculated by weighting the control commands to the circuit breaker coil and the operating requirements.

[0074] The fitness value of the Blackwing Kite algorithm model and whether it can reach the expected fitness value determine the quality of the optimization results of the Blackwing Kite algorithm model. The fitness value can be set by the control commands and operating requirements of the circuit breaker coil. The control commands can be used to obtain requirements such as the circuit breaker coil's on / off time, applied voltage, and power consumption current. The operating requirements are the user's requirements for the circuit breaker's failure rate or operational stability.

[0075] In some embodiments of the present invention, the control command includes controlling the closing time t of the circuit breaker. h Control the opening time t of the circuit breaker f And the power consumption current I of the control circuit breaker coil w The operational requirements include a failure rate f a ;

[0076] Fitness value = w1 × t h +w2×t f +w3×I w+w4×f a ;

[0077] Where w1 is the weighting coefficient for controlling the closing time of the circuit breaker, w2 is the weighting coefficient for controlling the opening time of the circuit breaker, w3 is the weighting coefficient for controlling the power consumption current of the circuit breaker coil, and w4 is the weighting coefficient for the failure rate.

[0078] In some embodiments of the present invention, fitting control commands, electrical data, and fault results into feature data includes:

[0079] The least squares support vector machine algorithm is used to fit feature data to control commands, electrical data, and fault results.

[0080] The least squares formula is mathematically known as curve fitting, which includes linear regression equations and matrix least squares. The formula for linear least squares is a = y - bx.

[0081] Support Vector Machines (SVMs) are a type of generalized linear classifier that performs binary classification of data using supervised learning. Their decision boundary is the hyperplane with the maximum margin calculated from the learning samples.

[0082] By using the least squares method and support vector machine algorithm, the optimization index adopts the square term, and the equality constraint replaces the inequality constraint of the support vector machine, the quadratic programming problem is transformed into a system of linear equations to be solved, which reduces the computational complexity and speeds up the solution.

[0083] In some embodiments of the present invention, after collecting electrical data at different times during each opening and closing operation, the method includes: comparing the collected electrical data with a preset electrical anomaly range, and removing electrical data that exceeds the electrical anomaly range.

[0084] Understandably, staff can set an electrical anomaly range to clean the acquired electrical data. Abnormal data that exceeds the electrical anomaly range is clearly inconsistent with the operating characteristics of the circuit breaker, so such electrical data is discarded to prevent interference with the construction of the Blackwing Kite algorithm model.

[0085] An analysis system according to a second aspect embodiment of the present invention, such as Figure 3 As shown, it includes: a data acquisition module 400, used to acquire electrical data of each circuit breaker 200 and the target circuit breaker 200; and a control module 300, connected to the data acquisition module 400, the control module 300 being used to execute the opening and closing time optimization processing method disclosed in any of the above embodiments to optimize the control commands for the target circuit breaker 200.

[0086] The acquisition module 400 may include a current transformer installed in the coil of the circuit breaker 200, which is used to detect the current information of the circuit breaker 200 as electrical data. The control module 300 may include an MCU or CPU and its auxiliary circuits. The control module 300 is connected to the circuit breaker 200 to control the operation of the circuit breaker 200.

[0087] The analysis system of this invention utilizes the opening and closing time optimization processing method disclosed in any of the above embodiments to optimize the control commands for the target circuit breaker 200, monitor the electrical data of the circuit breaker 200 coil, and reasonably optimize the control commands for the opening and closing actions of the circuit breaker 200 to improve operational stability.

[0088] According to a third aspect of the present invention, the control device includes a memory 520 and a processor 510. The memory 520 stores a computer program, and the processor 510 executes the computer program to implement the opening and closing time optimization processing method disclosed in any of the above embodiments.

[0089] The control device can be any intelligent terminal, including a central computer, a remote equipment terminal computer, or any other intelligent terminal.

[0090] like Figure 4 As shown, Figure 4 The hardware structure of a control device according to another embodiment is also illustrated. The control device includes:

[0091] The processor 510 can be implemented using a general-purpose central processing unit (CPU), a microprocessor 510, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0092] The memory 520 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 520 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 520 and is called and executed by the processor 510 to execute the opening and closing time optimization processing method of the embodiments of this application.

[0093] The input / output interface 530 is used to implement information input and output;

[0094] The communication interface 540 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0095] Bus 550 transmits information between various components of the device (e.g., processor 510, memory 520, input / output interface 530, and communication interface 540);

[0096] The processor 510, memory 520, input / output interface 530 and communication interface 540 are connected to each other within the device via bus 550.

[0097] According to a fourth aspect of the present invention, a computer-readable storage medium stores a computer program, characterized in that, when executed by a processor 510, the computer program implements the opening and closing time optimization processing method disclosed in any of the above embodiments.

[0098] Memory 520, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 520 may optionally include memory remotely located relative to the processor, and this remote memory can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0099] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0100] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0101] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0103] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0104] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. An open-close time optimization processing method, characterized by, The method comprises the following steps: controlling each circuit breaker to perform multiple opening and closing operations, obtaining control instructions in each opening and closing operation, and collecting electrical data at different time points in each opening and closing operation; analyzing potential fault results according to the electrical data, fitting the control instructions, the electrical data, and the fault results into feature data; performing iterative operation on a random population based on the black kite algorithm model of the feature data; adjusting the fitness value of the black kite algorithm model so that the black kite algorithm model reaches the number of iterations and converges; controlling the target circuit breaker to perform multiple opening and closing operations, and collecting electrical data of the target circuit breaker in each opening and closing operation; putting the collected electrical data of the target circuit breaker into the adjusted black kite algorithm model, and the adjusted black kite algorithm model optimizes the control instructions of the target circuit breaker, wherein the control instructions are used to control the opening and closing time of the target circuit breaker; the electrical data includes one or more of the maximum current value of the circuit breaker coil in the closing operation, the maximum current value of the circuit breaker coil in the opening operation, the current change rate of the circuit breaker coil before and after the closing operation, the current change rate of the circuit breaker coil before and after the opening operation, the average current of the circuit breaker coil in the opening operation, and the average current of the circuit breaker coil in the closing operation; the control instructions are used to control the electrical variable target acting on the circuit breaker coil, and the electrical variable target includes the voltage amplitude applied across the circuit breaker coil, the voltage pulse width applied across the circuit breaker coil, and the slope of the current rising edge of the circuit breaker coil; in the iterative operation on the random population based on the black kite algorithm model of the feature data, the electrical variable target is used as the decision variable of the black kite algorithm model to form an individual position vector; in the adjustment of the fitness value of the black kite algorithm model so that the black kite algorithm model reaches the number of iterations and converges, the fitness value is calculated by weighting the control instructions of the circuit breaker coil and the operation requirements.

2. The method of claim 1, wherein, the control instructions include a closing time of the circuit breaker , an opening time of the circuit breaker , and a power consumption current of a coil of the circuit breaker , the operating requirements include a failure rate ; ； wherein, is a weight coefficient for controlling the closing time of the circuit breaker, is a weight coefficient for controlling the opening time of the circuit breaker, is a weight coefficient for controlling the power consumption current of the circuit breaker coil, is a weight coefficient for the failure rate.

3. The method of claim 1, wherein the method further comprises: in the fitting of the control instructions, the electrical data, and the fault results into the feature data, the least squares support vector machine algorithm is used to fit the control instructions, the electrical data, and the fault results into the feature data. after collecting the electrical data at different time points in each opening and closing operation, the collected electrical data is compared with the preset electrical abnormal range, and the electrical data exceeding the electrical abnormal range is removed.

4. The method of claim 1, wherein, The method comprises the following steps: a collection module is configured to collect electrical data of each circuit breaker and a target circuit breaker; 5. An analytical system characterized by, a control module is connected to the collection module, and the control module is configured to execute the opening and closing time optimization processing method according to any one of claims 1 to 4 to optimize the control instructions of the target circuit breaker. The method comprises the following steps: one or more memories; 6. A control device characterized by comprising: one or more processors configured to execute one or more computer programs stored in the one or more memories, and further configured to execute the opening and closing time optimization processing method according to any one of claims 1 to 4. The instructions, when executed on a computer, cause the computer to execute the opening and closing time optimization processing method according to any one of claims 1 to 4. ​ 7. A computer-readable storage medium, characterized in that, ​

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