Circuit breaker arc extinguishing performance online detection method, device and system

Abstract

The invention provides a method, a device and a system for online detection of arc extinguishing performance of a circuit breaker, and belongs to the field of online detection of electrical equipment of a power system. The method comprises the following steps: acquiring a circuit breaker closing current i (t); selecting a sampling point corresponding to the moment that i (t) is greater than 0.01 kA as a closing current sampling initial value for backward sampling to form a closing current sequence; performing empirical mode decomposition on each item in the sequence to obtain a closing current sequence trend item sequence, performing accumulation on each item to obtain an accumulation result k (N), and adding the accumulation result k (N) into a sequence k (n = N); when N is greater than or equal to 15, clustering the sequence k (n is equal to N) by adopting a K-means algorithm, and determining whether the number K of clustering centers is greater than 1 based on a clustering error square sum threshold condition; if not, determining that the current arc extinguishing performance of the circuit breaker is good; if the judgment result is yes, determining that the current arc extinguishing performance of the circuit breaker is abnormal; and when the arc extinguishing performance state of the circuit breaker is abnormal, generating an early warning signal for early warning prompt.

Description

Technical Field

[0001] The present invention belongs to the field of online detection of electrical equipment in a power system, and in particular relates to an online detection method, device and system for arc extinguishing performance of a circuit breaker. Background Art

[0002] In the power system, when the power facilities are affected by the surrounding environment or external forces and fail, the relay protection device in the power system will send a tripping instruction to the circuit breaker, and the circuit breaker will perform a tripping operation after receiving the tripping instruction. When the circuit breaker contacts are completely separated and the arc between the contacts of the circuit breaker completely disappears, the circuit breaker tripping operation is completed.

[0003] During this process, the contacts and nozzles in the arc extinguishing chamber of the circuit breaker are subjected to the dual effects of arc erosion and mechanical fatigue for a long time, which can easily lead to a significant degradation of its arc extinguishing performance. In the subsequent breaking operation, the weakening of the arc extinguishing ability can easily trigger the risk of reignition, breaking failure and even equipment explosion, posing a serious threat to the safe and stable operation of the power grid. Therefore, it is necessary to regularly monitor the arc extinguishing performance of the circuit breaker. Summary of the invention

[0004] In view of this, the present invention provides a method, device and system for online detection of the arc extinguishing performance of a circuit breaker. By analyzing the potential correlation between the instantaneous current data and the arc extinguishing performance of the circuit breaker during the switching operation, real-time and rapid evaluation of the arc extinguishing performance of the circuit breaker can be achieved, thereby improving the overall operating stability and safety of the power grid.

[0005] The technical solution adopted by the embodiment of the present invention to solve the technical problem is:

[0006] A method for online detection of arc extinguishing performance of a circuit breaker, comprising:

[0007] Step S1, obtaining the circuit breaker closing current i(t);

[0008] Step S2, selecting the instantaneous corresponding sampling point satisfying i(t)>0.01kA as the initial value of closing current sampling and performing backward sampling to form a closing current sequence {i(m)};

[0009] Step S2, perform empirical mode decomposition on each item in the sequence {i(m)} to obtain the closing current sequence trend item sequence {i r (m)};

[0010] Step S3, accumulating the sequence {i r (m)}, and add k(N) to the sequence k(n=N), where N represents the total number of records, k(n=N)={k(n)};

[0011] Step S4: Determine whether N≥15 is satisfied currently. If not, let N = N + 1 and jump to Step S1 to wait for the next closing of the circuit breaker; if satisfied, continue to execute Step S5;

[0012] Step S5: Use the K - means algorithm to cluster the sequence k(n = N), and confirm whether the number of cluster centers is greater than 1 based on the clustering error sum - of - squares threshold condition; among them, when the judgment result is no, it is determined that the current arc - extinguishing performance of the circuit breaker is good; when the judgment result is yes, it is determined that there is an abnormality in the current arc - extinguishing performance of the circuit breaker;

[0013] Step S6: When there is an abnormality in the arc - extinguishing performance state of the circuit breaker, generate a warning signal for warning.

[0014] Preferably, the method for collecting the closing current i(t) is: measure the closing current through the current transformer already installed on the circuit breaker or by mounting a Rogowski coil on the circuit breaker, the measurement sampling rate f is greater than 10 kHz, and the total number of sampling points m is greater than 0.003*f.

[0015] Preferably, for the closing current i N (m) collected for the Nth time, the expression for empirical mode decomposition is:

[0016]

[0017] In the formula, i Nqj (m) is the q - order intrinsic mode function sequence of the Nth closing current sequence i N (m); i Nr (m) is the trend - term sequence of the Nth closing current sequence.

[0018] Preferably, the expression for the cumulative result k(N) corresponding to the Nth closing is:

[0019]

[0020] Preferably, the step of analyzing whether the number of cluster centers of the sequence k(n = N) is greater than 1 in Step S5 includes:

[0021] Step S51: Randomly select P data points from the sequence k(n = N) as the initial cluster centers C p of P cluster clusters I p , p ∈ [1, P], P < N, and let the initial value of P be taken as 1;

[0022] Step S52: Calculate the distance d(k(n), C p ) between each item in the sequence k(n = N) and each cluster center C p :

[0023]

[0024] And assign each data point of sequence k (n=N) to the nearest cluster center to form P clusters I p :

[0025] {k(n)∈I p |min[d(k(n),C p )]}

[0026] Calculate the cluster I p The mean of all data points in cluster I is taken as the cluster p The new cluster center of

[0027] Step S53, calculate the sum of square errors SSE of the sequence k (n=N) clustering P :

[0028]

[0029] Step S54, let P = P + 1, repeat steps S51 to S53, cluster P + 1 as the total number of cluster centers and calculate SSE P+1 ;

[0030] Step S55, calculate the ratio D, D = SSE P / SSE P+1 When D>1.5 is satisfied, the number of cluster centers of sequence k (n=N) is 1; when D>1.5 is not satisfied, the number of cluster centers of sequence k (n=N) is greater than 1.

[0031] An online detection device for arc extinguishing performance of a circuit breaker comprises: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the aforementioned method.

[0032] Preferably, the invention is also used for reflecting the arc extinguishing capability of the arc extinguishing chamber of the circuit breaker by the changing trend of the closing current based on the arc gap energy balance principle.

[0033] A circuit breaker arc extinguishing performance online detection system comprises the above-mentioned circuit breaker arc extinguishing performance online detection device and a current acquisition device, wherein the current acquisition device is used to acquire the circuit breaker closing current.

[0034] Preferably, the current acquisition device adopts a current transformer or a Rogowski coil.

[0035] Preferably, it further includes a cloud server and a receiving terminal, and the circuit breaker arc extinguishing performance online detection device sends a warning signal to the cloud server; the circuit breaker arc extinguishing performance online detection device sends the warning signal to the receiving terminal.

[0036] It can be seen from the above technical scheme that an embodiment of the present invention provides an online detection method, device and system for the arc extinguishing performance of a circuit breaker. First, the closing current i(t) of the circuit breaker is obtained; the sampling point corresponding to the instant i(t)>0.01kA is selected as the initial value of the closing current sampling for backward sampling to form a closing current sequence; the items in the sequence are subjected to empirical mode decomposition to obtain a sequence of trend items of the closing current sequence, and the accumulated results k(N) are obtained by accumulating the items and adding them to the sequence k(n=N); when N≥15 is satisfied, the sequence k(n=N) is clustered using the K-means algorithm, and the number of cluster centers is determined to be greater than 1 based on the threshold condition of the sum of squares of clustering errors; wherein, when the judgment result is no, it is determined that the current arc extinguishing performance of the circuit breaker is good; when the judgment result is yes, it is determined that the current arc extinguishing performance of the circuit breaker is abnormal; when the arc extinguishing performance state of the circuit breaker is abnormal, an early warning signal is generated for early warning prompt. The present invention realizes real-time and rapid evaluation of the arc extinguishing performance of the circuit breaker by analyzing the potential correlation between transient current data and the arc extinguishing performance of the circuit breaker during switching operations, thereby effectively improving the overall operational stability and safety of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The flowchart of the on-line detection method of arc extinguishing performance of a circuit breaker of the present invention is shown in FIG.

[0038] Figure 2 This is the equivalent circuit diagram of the circuit breaker switching.

[0039] Figure 3 This is the empirical mode decomposition diagram of the circuit breaker closing current.

[0040] Figure 4a This is the closing current waveform of a circuit breaker with good arc extinguishing performance.

[0041] Figure 4b This is the closing current waveform of the circuit breaker with deteriorated arc extinguishing performance.

[0042] Figure 5a Schematic diagram of clustering results of circuit breakers with good arc extinguishing performance.

[0043] Figure 5b Schematic diagram of clustering results of circuit breakers with degraded arc extinguishing performance. DETAILED DESCRIPTION

[0044] The technical scheme and technical effects of the present invention are further elaborated in detail below in conjunction with the accompanying drawings of the present invention.

[0045] When the circuit breaker contacts are connected, a burning arc will be generated. The burning and extinction of the arc depends on the size of the energy generated and the energy dissipated. When the energy dissipated by the arc gap is greater than the energy generated, the arc gradually tends to extinguish. Under unit time and unit length, there are three forms of heat dissipation: conduction heat dissipation P T , radiative heat dissipation P S , convection heat dissipation P K , the energy balance equation of the arc is expressed as follows:

[0046] P=P T +P S +P K (1)

[0047] Where: P is the energy generated by the arc per unit length, P T , P S , P K The power is positively correlated with the arc extinguishing capacity of the arc extinguishing chamber. When the arc extinguishing chamber of the circuit breaker is working normally, P T , P S , P K The sum of the three is greater than P circuit breaker, and the arc resistance value decreases. However, the arc resistance cannot be measured directly. In order to find the same characterization value, an equivalent model of circuit breaker switching is built. Figure 2 As shown. Among them; U a is the bus power supply; R, L, and C are the equivalent resistance, inductance, and capacitance of the loop respectively; R a is the nonlinear arc resistance.

[0048] According to Kirchhoff's law loop expression:

[0049]

[0050] where u R (t),u L (t),u C (t),u Ra (t) represent the equivalent resistance voltage, equivalent inductance voltage, equivalent capacitance voltage, and arc resistance voltage, respectively.

[0051] When the arc enters the stable burning stage, the closing current expression can be solved by equation (2):

[0052]

[0053] Among them I a is the initial stable burning current amplitude of the arc, ω 0 is the oscillation frequency, α is the attenuation coefficient, which is defined as:

[0054]

[0055] From equations (3) and (5), it can be seen that the attenuation characteristics of the closing current i(t) mainly depend on (R+R a (t)) / (2L), under the same circuit breaker working condition, R and L are fixed, i(t) attenuation is affected by the arc resistance value R a Direct impact, and the previous analysis knows that R a The change of is related to the arc extinguishing capacity of the arc extinguishing chamber, so the i(t) attenuation trend term sequence can indirectly describe the arc extinguishing capacity of the arc extinguishing chamber.

[0056] The present invention uses the closing current i(t) generated when the circuit breaker is closed as the basis for evaluating the arc extinguishing performance of the circuit breaker, decomposes the collected closing current to obtain the eigenterm sequence and the trend term sequence, and then performs sequence point accumulation calculation after obtaining the closing current trend term sequence. The calculation result is recorded as k(1), and the data results k(1), k(2),...k(n) of multiple measurements are recorded as sequence k (n=N). The K-means clustering algorithm is used to perform cluster analysis on the sequence k. K-means clustering is performed on the sequence k to realize the detection and analysis of multiple groups of current trend term sequences to extract characteristic parameters, and the extracted characteristic parameters are used as the standard for judging the arc extinguishing performance status of the circuit breaker. If there is at least one clustering center, it is considered that the arc extinguishing performance of the arc extinguishing chamber is abnormal and power outage for maintenance is required. Figure 1 The present invention provides a method for online detection of arc extinguishing performance of a circuit breaker, the specific steps of which include:

[0057] Step S1, obtaining the closing current i(t) of the circuit breaker; specifically, the closing current can be measured by a current transformer installed on the circuit breaker or a Rogowski coil mounted on the circuit breaker, the measurement sampling rate f is greater than 10kHz, and the total number of sampling points m is greater than 0.003*f;

[0058] Step S2, selecting the instantaneous corresponding sampling point satisfying i(t)>0.01kA as the initial value of closing current sampling and performing backward sampling to form a closing current sequence {i(m)};

[0059] Step S2, perform empirical mode decomposition on each item in the sequence {i(m)} to obtain the closing current sequence trend item sequence {i r (m)}; for the closing current i collected for the Nth time N (m) The expression for empirical mode decomposition is:

[0060]

[0061] In the formula, i Nqj (m) is the Nth closing current sequence i N (m) is a sequence of q-order eigenterms; i Nr(m) is the sequence of trend terms of the Nth closing current; by performing empirical mode decomposition on the closing current data when a certain branch circuit breaker trips, the sequence of trend terms of the original current signal can be obtained, as shown in Figure 3 shown;

[0062] Step S3, accumulate each item in the sequence {i r (m)} to obtain the accumulation result k(N), and add k(N) to the sequence k(n = N), where N represents the total number of records, and k(n = N) = {k(n)}; the expression for the accumulation result k(N) corresponding to the Nth closing is:

[0063]

[0064] Step S4, determine whether N≥15 is satisfied currently, that is, whether the number of recorded closing currents is less than 15 times. If not satisfied, let N = N + 1 and jump to Step S1 to wait for the next closing of the circuit breaker; if satisfied, continue to execute Step S5;

[0065] Step S5, use the K - means algorithm to cluster the sequence k(n = N), and confirm whether the number of cluster centers is greater than 1 based on the condition of the sum of squared clustering errors threshold; among them, when the judgment result is no, it is determined that the current arc extinguishing performance of the circuit breaker is good; when the judgment result is yes, it is determined that there is an abnormality in the current arc extinguishing performance of the circuit breaker;

[0066] Step S51, randomly select P data points from the sequence k(n = N) as the initial cluster centers C p of P cluster clusters I p , p∈[1, P], P < N, and let the initial value of P be taken as 1;

[0067] Step S52, calculate the distance d(k(n), C p ) between each item in the sequence k(n = N) and each cluster center C p :

[0068]

[0069] And assign each data point of the sequence k(n = N) to the cluster center with the closest distance to form P cluster clusters I p :

[0070] {k(n)∈I p |min[d(k(n), C p )]} (9)

[0071] Calculate the mean value of all data points in each cluster cluster I p as the new cluster center of the cluster cluster I p ;

[0072] Step S53: Since the clustering error sum of squares SSE reflects the degree of data point aggregation, the clustering error sum of squares SSE of sequence k (n=N) is calculated. P :

[0073]

[0074] Step S54, let P = P + 1, repeat steps S51 to S53, cluster P + 1 as the total number of cluster centers and calculate SSE P+1 ;

[0075] Step S55, calculate the ratio D, D = SSE P / SSE P+1 When D>1.5 is satisfied, the number of cluster centers of sequence k (n=N) is 1; when D>1.5 is not satisfied, the number of cluster centers of sequence k (n=N) is greater than 1.

[0076] Step S6: When there is an abnormality in the arc extinguishing performance state of the circuit breaker, a warning signal is generated to provide a warning prompt.

[0077] The detection method is started by checking whether the absolute value of the circuit breaker current amplitude obtained by the acquisition is greater than the monitoring trigger. The monitoring trigger value is 0.01kA. If it is greater than the monitoring trigger, the current value in the line is recorded; otherwise, return and continue to measure the current value.

[0078] In step S5, the above implementation adopts one cycle, that is, only the sum of squared errors in the cases of P=1 and P+1=2 is calculated, and the sum of squared errors is calculated according to the ratio D=SSE 1 / SSE 2 Whether D>1.5 is satisfied or not, confirm whether the number of cluster centers is P=1; as an optional implementation, step S5 can be adjusted. After step S55 calculates the ratio D, if D>1.5 is not satisfied, jump to execute step S54 again, increase the total number of cluster centers by 1, and continue to calculate SSE and the ratio D until D>1.5 is satisfied and stop the calculation, and determine whether the P value satisfying D>1.5 is greater than 1.

[0079] Furthermore, the present invention provides an online detection device for the arc extinguishing performance of a circuit breaker, comprising: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the aforementioned method.

[0080] Based on the arc gap energy balance principle, the arc extinguishing capacity of the circuit breaker arc extinguishing chamber is reflected by the changing trend of the closing current.

[0081] The process of online monitoring of arc extinguishing performance of arc extinguishing chamber is as follows: Figure 1 As shown, when the circuit breaker is actually tested, the cumulative results of the sequence points of the trend items of the closing current of the circuit breaker for the previous N times can be calculated by K-means clustering. If there is no more than one cluster center in the previous N measurements, a warning signal is issued if this situation occurs. If the circuit breaker status is not continuously monitored, the cumulative calculation result of the next current trend item sequence is recorded as k(N+1) during real-time monitoring, and a new sequence is formed from k(2) to k(N+1) to determine whether the state of the arc extinguishing chamber of the K-means clustering circuit breaker is normal. If the state is abnormal, a warning signal is issued. If the state is normal, the above steps are repeated to perform state detection.

[0082] Furthermore, the present invention provides an online detection system for the arc extinguishing performance of a circuit breaker, comprising the aforementioned online detection device for the arc extinguishing performance of the circuit breaker and a current acquisition device, wherein the current acquisition device is used to acquire the closing current of the circuit breaker. In the system, the current acquisition device uses a current transformer or a Rogowski coil to monitor the instantaneous value i(t) of the current before the circuit breaker is fully closed in real time. The sampling rate f of the real-time monitoring of the circuit breaker current should be greater than 10kHz. The arc extinguishing performance detection method starts the detection method by checking whether the absolute value of the circuit breaker current obtained by the acquisition is greater than the monitoring trigger. The monitoring trigger value is 0.01kA. If it is greater than the monitoring trigger, the current value in the line is recorded; otherwise, it returns and continues to measure the current value; the entire arcing time during the closing process is about 3-5ms. When i(t) is detected to be greater than 0.01kA, the corresponding sampling point is the initial value of the closing current sampling. In the subsequent time window, m sampling points are taken to form a closing current sequence i(m), and m is recommended to be greater than 0.003*f.

[0083] The circuit breaker arc extinguishing performance online detection system also includes a cloud server and a receiving terminal. The circuit breaker arc extinguishing performance online detection device sends the circuit breaker arc extinguishing performance judgment result and early warning signal to the cloud server; the circuit breaker arc extinguishing performance online detection device sends the circuit breaker arc extinguishing performance judgment result and early warning signal to the receiving terminal.

[0084] The on-line detection device for arc extinguishing performance of circuit breaker is also used for: establishing an equivalent model of circuit breaker switching; based on the arc gap energy balance principle, reflecting the arc extinguishing ability of the circuit breaker arc extinguishing chamber by the changing trend of the closing current; obtaining the current measurement data in the actual operation of the circuit breaker; judging whether the closing current has entered the steady-state combustion stage by setting a relationship; decomposing the closing current signal into eigenterms and trend terms by using empirical mode decomposition to realize the extraction of the closing current trend term sequence; integrating the closing current trend term sequence, and realizing clustering and extracting characteristic parameters after performing the shortest distance iterative calculation on several calculated integral values; after the clustering process is completed, issuing a warning for abnormal arc extinguishing performance of the arc extinguishing chamber according to the number of cluster centers.

[0085] The method of the present invention does not limit the arc extinguishing mode of the circuit breaker to be detected, vacuum circuit breaker, SF6 The arc extinguishing performance of circuit breakers that extinguish arcs to switch lines can be tested online using this method.

[0086] In order to explain the method clearly, the monitoring current of the circuit breaker with good arc extinguishing performance and the circuit breaker with deteriorated arc extinguishing performance and the restrike accident is taken as an example. The closing current of the circuit breaker with good arc extinguishing performance and the circuit breaker with deteriorated arc extinguishing performance are respectively as follows: Figure 4a and Figure 4b shown.

[0087] The calculation of the integral value of the closing current trend item sequence of the two circuit breakers is shown in Table 1:

[0088] Table 1 Cumulative values ​​of closing current trend item sequence of circuit breakers with good arc extinguishing performance and poor arc extinguishing performance

[0089]

[0090] Then perform clustering calculations on the A and B phase data respectively, where the horizontal axis is the number of data and the vertical axis is the cumulative value. The results are as follows: Figure 5a and Figure 5b shown.

[0091] There are two cluster centers in the closing current of the circuit breaker with degraded arc extinguishing performance, and a restrike accident also occurred, which verifies the effectiveness of the proposed detection method.

[0092] The present invention provides an online detection method, device and system for the arc extinguishing performance of a circuit breaker, including: collecting the closing current signal generated during the closing process of the circuit breaker as a basis for analyzing and evaluating the arc extinguishing performance of the circuit breaker; signal analysis, decomposing the multiple closing current signals collected, extracting the eigenterms representing the high-frequency and transient components in the signal, representing the medium- and long-term change trend term of the signal, performing sequence point accumulation calculation on the current trend term sequence obtained by multiple measurements, and using the K-means clustering algorithm to perform cluster analysis on these accumulated trend term sequences. The clustering results can reflect the distribution characteristics of the closing current under different arc extinguishing states, thereby judging the state of the arc extinguishing performance of the circuit breaker. The present invention can utilize the dynamic change characteristics of the closing current generated when the circuit breaker is closed, effectively reflect the change trend of the arc extinguishing performance of the circuit breaker, and can realize online real-time detection of the arc extinguishing performance of the circuit breaker. The principle is simple, and timely discovery of arc extinguishing performance problems of the circuit breaker is conducive to improving the stability of power grid operation.

[0093] The present invention uses a current transformer or Rogowski coil installed on the circuit breaker to measure the current signal, and synchronously monitors the arc extinguishing performance of the circuit breaker online through the dynamic change of the current signal. The current signal change trend is used as the characteristic parameter. The operation is convenient, the principle is intuitive and easy to understand, and potential arc extinguishing performance problems can be quickly identified and warned, which is of great significance for improving the overall operation stability and safety of the power grid.

[0094] What is disclosed above is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of rights of the present invention. A person skilled in the art can understand that all or part of the processes of the above embodiments and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A method for online detection of arc extinguishing performance of a circuit breaker, characterized in that: include: Step S1, obtaining the circuit breaker closing current i(t); Step S2, selecting the instantaneous corresponding sampling point satisfying i(t)>0.01kA as the initial value of closing current sampling and performing backward sampling to form a closing current sequence {i(m)}; Step S2, perform empirical mode decomposition on each item in the sequence {i(m)} to obtain the closing current sequence trend item sequence {i r (m)}; Step S3, accumulating the sequence {i r (m)}, and add k(N) to the sequence k(n=N), where N represents the total number of records, k(n=N)={k(n)}; Step S4, judging whether N≥15 is satisfied at present, if not, setting N=N+1 and jumping to step S1, waiting for the circuit breaker to close next time; if satisfied, continuing to step S5; Step S5, clustering the sequence k (n=N) using the K-means algorithm, and confirming whether the number of cluster centers is greater than 1 based on the cluster error square sum threshold condition; wherein, when the judgment result is no, it is determined that the current arc extinguishing performance of the circuit breaker is good; when the judgment result is yes, it is determined that the current arc extinguishing performance of the circuit breaker is abnormal; Step S6: When there is an abnormality in the arc extinguishing performance state of the circuit breaker, a warning signal is generated to provide a warning prompt.

2. The method for online detection of arc extinguishing performance of a circuit breaker according to claim 1, characterized in that: The method of collecting the closing current i(t) is: measuring the closing current through a current transformer installed on the circuit breaker or a Rogowski coil mounted on the circuit breaker, the measurement sampling rate f is greater than 10kHz, and the total number of sampling points m is greater than 0.003*f.

3. The method for online detection of arc extinguishing performance of a circuit breaker according to claim 2, characterized in that: For the closing current i collected for the Nth time N (m) The expression for empirical mode decomposition is: In the formula, i Nqj (m) is the Nth closing current sequence i N (m) is a sequence of q-order eigenterms; i Nr (m) is the trend item sequence of the Nth closing current sequence.

4. The method for online detection of arc extinguishing performance of a circuit breaker according to claim 3, characterized in that: The expression of the accumulated result k(N) corresponding to the Nth closing is:

5. The method for online detection of arc extinguishing performance of a circuit breaker according to claim 4, characterized in that: The step S5 analyzes whether the number of cluster centers of the sequence k (n=N) is greater than 1, and the steps include: Step S51: Randomly select P data points from the sequence k(n = N) as the initial clustering centers C of P clustering clusters I p , where p ∈ [1, P], P < N, and let the initial value of P be taken as 1; p ​ Step S52, calculate the relationship between each item in the sequence k (n=N) and each cluster center C p The distance d(k(n),C p ): And assign each data point of sequence k (n=N) to the nearest cluster center to form P clusters I p : {k(n)∈I p |min[d(k(n),C p )]} Calculate the cluster I p The mean of all data points in cluster I is taken as the cluster p The new cluster center of Step S53, calculate the sum of square errors SSE of the sequence k (n=N) clustering P : Step S54, let P = P + 1, repeat steps S51 to S53, cluster P + 1 as the total number of cluster centers and calculate SSE P+1 ; Step S55, calculate the ratio D, D = SSE P / SSE P+1 When D>1.5 is satisfied, the number of cluster centers of sequence k (n=N) is 1; when D>1.5 is not satisfied, the number of cluster centers of sequence k (n=N) is greater than 1.

6. An online detection device for arc extinguishing performance of a circuit breaker, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 5.

7. The circuit breaker arc extinguishing performance online detection device according to claim 6, characterized in that: It is also used for: Based on the arc gap energy balance principle, the changing trend of closing current reflects the arc extinguishing capacity of the circuit breaker arc extinguishing chamber.

8. An online detection system for arc extinguishing performance of a circuit breaker, characterized in that: include: The circuit breaker arc extinguishing performance online detection device and current acquisition device as described in any one of claims 6-7, wherein the current acquisition device is used to obtain the circuit breaker closing current.

9. The circuit breaker arc extinguishing performance online detection system according to claim 8, characterized in that: The current acquisition device adopts a current transformer or a Rogowski coil.

10. The circuit breaker arc extinguishing performance online detection system according to claim 9, characterized in that: It also includes a cloud server and a receiving terminal. The circuit breaker arc extinguishing performance online detection device sends an early warning signal to the cloud server; the circuit breaker arc extinguishing performance online detection device sends the early warning signal to the receiving terminal.

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