A method, medium, and system for life assessment of a double-break circuit breaker

Abstract

The application discloses a life evaluation method, medium and system of a double-break circuit breaker, comprising: establishing a double-break circuit breaker simulation model; obtaining the cumulative transferred charge and energy of an arc caused by each ablation test; drawing a dynamic resistance-travel curve according to a dynamic resistance-travel measurement test corresponding to each ablation test, and obtaining characteristic parameters therefrom; taking the cumulative transferred charge and energy of the arc of different numbers of ablation tests and the characteristic parameters as first characteristic variables to form training samples; inputting the training samples into a trained neural network to obtain the contribution degree of each type of first characteristic variable; selecting a preset number of first characteristic variables with the largest contribution degree as second characteristic variables; collecting the second characteristic variables of an actual double-break circuit breaker and inputting the second characteristic variables into the trained neural network to output the life score of the actual double-break circuit breaker and determine the life grade. The application can accurately evaluate the life of the double-break circuit breaker.

Description

Technical Field

[0001] This invention relates to the field of double-break circuit breaker technology, and in particular to a method, medium and system for assessing the life of a double-break circuit breaker. Background Technology

[0002] High-voltage circuit breakers, as crucial components of power systems, primarily function as control and protection devices. They can interrupt normal load currents and overload currents, as well as various short-circuit currents. Therefore, the normal operation of circuit breakers directly impacts the reliability and stability of the power system. The operating mechanism of a double-break circuit breaker can operate normally for thousands or even tens of thousands of times, but its lifespan is only a few dozen times when interrupting rated short-circuit currents. Each of the two arc-extinguishing chambers of a double-break circuit breaker contains two pairs of contacts—main contacts and arc contacts—each composed of moving and stationary contacts, connected in parallel within the arc-extinguishing chamber. The main contacts primarily carry current, while the arc contacts ignite the electric arc. Both contacts undergo erosion during the opening and closing processes. Experiments have shown that the key factor affecting lifespan is the erosion of the arc contacts by current. As the number of interruptions and the interrupting current increase, contact erosion becomes increasingly severe. When it reaches a certain point, interruption failure may occur, even accompanied by explosions. Therefore, timely detection and assessment of the contact status of double-break circuit breakers can determine their lifespan and allow for the development of corresponding maintenance measures for circuit breakers with different lifespans.

[0003] The dynamic resistance-stroke curve can be obtained by measuring the relationship between the contact resistance between the breaks and the contact stroke during the opening process of a double-break circuit breaker. This curve can be used to determine the contact condition and subsequently assess the circuit's lifespan. Current research on dynamic resistance-stroke curves is primarily based on single-break circuit breakers, lacking studies on double-break circuit breakers. The dynamic resistance characteristic parameters extracted from single-break circuit breakers are not applicable to the lifespan assessment of double-break circuit breakers. Therefore, there is an urgent need to establish a lifespan assessment method for double-break circuit breakers. Summary of the Invention

[0004] This invention provides a method, medium, and system for assessing the lifespan of a double-break circuit breaker, addressing the problem that existing methods are not applicable to the lifespan assessment of double-break circuit breakers.

[0005] Firstly, a method for assessing the lifespan of a double-break circuit breaker is provided, including:

[0006] Establish a simulation model of a double-break circuit breaker;

[0007] After each ablation test using the dual-break circuit breaker simulation model, a dynamic resistance-stroke measurement test of the dual-break circuit breaker simulation model is performed until the measured dynamic resistance of the contacts exceeds a preset resistance threshold.

[0008] Obtain the cumulative charge and energy transferred by the arc caused by each ablation test;

[0009] Based on the dynamic resistance-stroke measurement test corresponding to each ablation test, a dynamic resistance-stroke curve is plotted, and characteristic parameters are obtained from the dynamic resistance-stroke curve;

[0010] The cumulative charge and energy transferred by the arc in different ablation tests, and the corresponding characteristic parameters, are used as the first characteristic variables to form a training sample.

[0011] The training samples are input into the trained neural network to obtain the contribution of the first feature variable for each class.

[0012] Select the first feature variable with the largest contribution as the second feature variable;

[0013] The second characteristic variable of the actual double-break circuit breaker in operation is collected and input into the trained neural network. The life score of the actual double-break circuit breaker is output, and the life rating of the actual double-break circuit breaker is determined according to the life score.

[0014] In a second aspect, a computer-readable storage medium is provided, wherein computer program instructions are stored on the computer-readable storage medium; when executed by a processor, the computer program instructions implement the life assessment method for a dual-break circuit breaker as described in the first aspect embodiment above.

[0015] Thirdly, a life assessment system for a dual-break circuit breaker is provided, comprising: a computer-readable storage medium as described in the second aspect embodiment above.

[0016] Thus, in this embodiment of the invention, by simulating ablation tests and measuring dynamic resistance-stroke curve tests, feature values ​​that can accurately characterize the contact state of the two breaks during the opening process are extracted from the curves. The influence weight of each feature value on the life of the double-break circuit breaker is determined by using a neural network combined with an average influence value algorithm. An objective and accurate life assessment method for double-break circuit breakers is established, which is of great significance for the online monitoring and life assessment of double-break circuit breakers in the field. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the life assessment method for a dual-break circuit breaker according to an embodiment of the present invention;

[0019] Figure 2 This is a circuit diagram of the ablation test of the simulation model of the double-break circuit breaker according to an embodiment of the present invention;

[0020] Figure 3 This is a circuit diagram of the dynamic resistance-stroke measurement test of the simulation model of the double-break circuit breaker according to an embodiment of the present invention;

[0021] Figure 4 This is a voltage and current waveform diagram of the tripping action in the simulation model of the double-break circuit breaker according to an embodiment of the present invention;

[0022] Figure 5 This is a typical dynamic resistance-stroke curve of the simulation model of the double-break circuit breaker in this embodiment of the invention;

[0023] Figure 6 This is a slope curve of the dynamic resistance-stroke curve of the simulation model of the double-break circuit breaker in this embodiment of the invention within the range of 26.8-28.4mm. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] This invention discloses a method for assessing the lifespan of a double-break circuit breaker. For example... Figure 1 As shown, the method includes the following steps:

[0026] Step S101: Establish a simulation model of a double-break circuit breaker.

[0027] Specifically, the model is established in the following way:

[0028] A simulation model of a double-break circuit breaker is created by connecting the lower port of the first phase of one of the two adjacent phases of a single-break circuit breaker to the upper port of the second phase. In other words, an actual double-break circuit breaker is simulated by connecting two adjacent phases of a single-break circuit breaker in series.

[0029] For example, connecting the lower port of phase B of a single-break SF6 circuit breaker to the upper port of phase C simulates an actual double-break circuit breaker.

[0030] Step S102: After each ablation test using the double-break circuit breaker simulation model, a dynamic resistance-stroke measurement test of the double-break circuit breaker simulation model is performed until the measured dynamic resistance of the contacts exceeds the preset resistance threshold.

[0031] Specifically, the ablation test can be constructed using the following test circuit:

[0032] like Figure 2 As shown, the power frequency transformer 8, current-limiting resistor 9, rectifier element 10, charging switch 11, and capacitor 12 are connected sequentially to form a charging circuit. The positive plate of capacitor 12 is connected to charging switch 11, and the negative plate of capacitor 12 is connected to power frequency transformer 8 and grounded. The two ends of inductor 13 are connected to the positive plate of capacitor 12 and one end of auxiliary closing circuit breaker 14, respectively. The other end of auxiliary closing circuit breaker 14 is connected to the upper port of the first phase of the double-break circuit breaker simulation model 1. The two ends of protection circuit breaker 16 are connected to the negative plate of capacitor 12 and the lower port of the second phase of the double-break circuit breaker simulation model 1, respectively. A Hall sensor 3 is installed in the connection circuit between protection circuit breaker 16 and the lower port of the second phase of the double-break circuit breaker simulation model 1. Vacuum circuit breakers can be used for auxiliary closing circuit breaker 14 and protection circuit breaker 16. Voltage sensors 15 are installed at the upper and lower ports of the first phase and the upper and lower ports of the second phase of the double-break circuit breaker simulation model 1. The voltage sensors 15 can be high-voltage probes with an attenuation ratio of 200:1. Hall effect sensors 3 and all four voltage sensors 15 are connected to an oscilloscope 7.

[0033] Through the circuit design described above, an LC series resonant circuit is used to provide power frequency attenuated oscillating currents of different amplitudes. Since the contact erosion in the actual breaking process of the double-break circuit breaker simulation model 1 mainly comes from the large current, and a large transient recovery voltage is only generated when the current crosses zero, the LC resonant circuit can meet the needs of simulating the actual erosion process.

[0034] Using the above-described ablation test circuit, the ablation test is conducted according to the following procedure:

[0035] (1) Set the dual-break circuit breaker simulation model 1 to the closed state, the auxiliary closing circuit breaker 14 to the open state, and the protection circuit breaker 16 to the closed state.

[0036] (2) Close the charging switch 11 and charge the capacitor 12 through the power frequency transformer 8. After the capacitor is charged to the preset voltage, disconnect the charging switch 11.

[0037] (3) The auxiliary closing circuit breaker 14 is closed, and the power frequency current appears in the circuit. After a preset delay time, the double-break circuit breaker simulation model 1 is opened to interrupt the current and generate an arc in the arc-extinguishing chamber of the double-break circuit breaker simulation model 1, which erodes the contacts of the double-break circuit breaker simulation model 1.

[0038] Specifically, the circuit breaker's opening sequence can be controlled by the level signal output by the timing control system. The delay time can be 5ms.

[0039] (5) After the arc is extinguished, a simulation of a double-break circuit breaker ablation test is completed.

[0040] (6) Record the following data using oscilloscope 7: voltage to ground of the upper and lower ports of the first phase of the simulated double-break circuit breaker model 1 collected by voltage sensor 15 during the simulated double-break circuit breaker ablation test, voltage to ground of the upper and lower ports of the second phase of the simulated double-break circuit breaker model 1, and current collected by Hall sensor 3.

[0041] The loop current serves as the trigger signal recorded by oscilloscope 7. The acquired signals are as follows: Figure 4 As shown in the figure. In the figure, 17 represents the arc ignition time of phase C, 18 represents the arc ignition time of phase B, and 19 represents the arc extinction time.

[0042] Specifically, the dynamic resistance-stroke measurement test can be set up with the following test circuit:

[0043] like Figure 3 As shown, the upper port of the first phase and the lower port of the second phase of the double-break circuit breaker simulation model 1 are connected to the two plates of the supercapacitor 2, respectively. A DC power supply 5 is connected to the operating mechanism of the double-break circuit breaker simulation model 1, and a rotation sensor 4 is connected to the crank arm shaft inside the operating mechanism housing of the double-break circuit breaker simulation model 1. A Hall sensor 3 is installed in the connection circuit between the lower port of the second phase of the double-break circuit breaker simulation model 1 and the supercapacitor 2. A Rogowski coil 6 is installed in the connection circuit between the DC power supply 5 and the operating mechanism of the double-break circuit breaker simulation model 1. An oscilloscope 7 is connected to the upper port of the first phase and the lower port of the second phase of the double-break circuit breaker simulation model 1, the rotation sensor 4, the Hall sensor 3, and the Rogowski coil 6.

[0044] With the circuit structure described above, the voltage and current during the tripping process of the double-break circuit breaker simulation model 1 can be measured using the four-wire method, so as to calculate the contact resistance of the contacts using Ohm's law.

[0045] Supercapacitor 2 can provide a stable, high-amplitude DC current when measuring small resistances at the micro-ohm level, and can output a DC current of 2kA. Compared with the disadvantages of batteries, such as being heavy and difficult to carry, and providing only one type of current, supercapacitor 2 can change the amplitude of the DC current it provides by adjusting the charging voltage, is lighter in weight, and can provide a variety of stable DC currents.

[0046] The DC power supply 5 adopts a 110V / 220V specification, which provides the opening and closing current for the opening and closing coils.

[0047] The rotary sensor 4 can be bolted to the crank arm box shaft and fixed to the main body of the double-break circuit breaker simulation model 1 via a magnetic base to measure the rotation angle during the tripping action, which can be converted into contact stroke parameters. Compared to linear sensors, which need to be installed inside the control box and require additional fixing points, the rotary sensor 4 is easier to install and has a lower cost.

[0048] Hall sensor 3 is used to measure the current signal in the circuit when the circuit is tripped.

[0049] The Rogowski coil 6 is used to measure the current of the opening and closing coils. Its open-loop structure allows it to be installed in a convenient location without the need for separate wiring in series with the circuit.

[0050] The oscilloscope 7 features a high sampling rate, which can avoid data distortion, better reflect changes in signals such as voltage and current, and enable data presentation and storage.

[0051] The measurement test was conducted using the dynamic resistance-stroke measurement test circuit described above, following the procedure outlined below:

[0052] (1) Set the double-break circuit breaker simulation model 1 to the open state, and the spring is already energized.

[0053] This prevents damage to equipment such as the supercapacitor from being connected to the circuit.

[0054] (2) After charging the supercapacitor 2, power is supplied to the closing coil of the double-break circuit breaker simulation model 1 so that the double-break circuit breaker simulation model 1 performs the closing action for a preset time. Then, power is supplied to the opening coil of the double-break circuit breaker simulation model 1 so that the double-break circuit breaker simulation model 1 performs the opening action. The voltage, current and travel signals are recorded by the oscilloscope 7.

[0055] Using the closing coil current as a trigger signal for other measuring devices can achieve synchronization of measurement signals.

[0056] (3) The dynamic resistance of the contacts of the double-break circuit breaker simulation model is obtained by calculating the quotient of voltage and current recorded at the same acquisition time.

[0057] The dynamic resistance of this contact is the contact resistance.

[0058] To ensure greater accuracy of the characteristic parameters obtained from the dynamic resistance-stroke curve in subsequent steps, it is preferable to perform multiple dynamic resistance-stroke measurement tests for each ablation test. For example, in this embodiment of the invention, five dynamic resistance-stroke measurement tests are performed for each ablation test. This allows the average value of multiple measurements to be used in subsequent steps, thereby improving accuracy.

[0059] Step S103: Obtain the cumulative charge and energy transferred by the arc caused by each ablation test.

[0060] By integrating the voltage and current to ground collected in each ablation test, the corresponding cumulative charge and energy transferred by the arc can be obtained.

[0061] Specifically, the arc voltage generated during the ablation process can be obtained by subtracting the voltage at the port to ground. The steep rise point of the voltage waveform obtained by the subtraction is taken as the arc ignition moment, and the zero crossing point of the current is taken as the arc extinguishing moment. The duration of the arc can be obtained by subtracting the arc ignition moment from the arc extinguishing moment. Using the arc ignition moment and the arc extinguishing moment as the upper and lower limits of integration, the current and the product of current and voltage are integrated respectively to obtain the amount of charge transferred and the arc energy during the arc ignition process.

[0062] The term "cumulative" can be understood as follows: for example, the amount of charge transferred in the second cumulative transfer is the sum of the amount of charge transferred in the first ablation test and the amount of charge transferred in this ablation test. Similarly, the cumulative transferred energy is calculated in the same way.

[0063] Step S104: Based on the dynamic resistance-stroke measurement test corresponding to each ablation test, plot the dynamic resistance-stroke curve and obtain the characteristic parameters from the dynamic resistance-stroke curve.

[0064] Specifically, a dynamic resistance-stroke curve is plotted using the travel distance of travel signals acquired at the same time as the horizontal axis and the dynamic resistance of the contact as the vertical axis.

[0065] For the dynamic resistance of the contacts of a double-break circuit breaker, the movement of the contacts of the two breaks is not completely synchronized, resulting in the following stages: the main contacts of both breaks have not yet separated and are in the contact stage, at which point the curve shows a significant jump point, which serves as the dividing point; the main contacts of one break have separated and are no longer in contact, transitioning to arc contact, while the main contacts of the other break are still in contact, at which point the curve jumps again to a certain maximum value, which serves as the dividing point; when the resistance rises to infinity and exceeds the range, the tripping action is completed, and the main contacts of both breaks are completely separated, both in the arc contact state.

[0066] Therefore, the process of extracting feature parameters includes:

[0067] (1) Extract the first stroke, second stroke and third stroke from the dynamic resistance-stroke curve.

[0068] Among them, the first leg L m1 The first stroke is the travel of both breaks of the double-break circuit breaker during the main contact phase. The endpoint of the first stroke is the point where the dynamic resistance is greater than a first preset resistance and the slope suddenly drops sharply. The first preset resistance can be set empirically; for example, in this embodiment of the invention, the first preset resistance is 200 μΩ.

[0069] The "point where the slope suddenly drops sharply" refers to the first point of minimum slope during the phase where the resistance value first increases sharply after exceeding the first preset resistance. Specifically, for example... Figure 6 The point indicated by point 26 corresponds to 27.7mm.

[0070] Among them, the second stroke L m2 The second stroke is the travel phase during which one break of the double-break circuit breaker is engaged by the main contact and the other break is engaged by the arc contact. The endpoint of the second stroke is the first maximum point where the dynamic resistance exceeds a second preset resistance. The second preset resistance can be set empirically; for example, in this embodiment of the invention, the second preset resistance is 400 μΩ. It should be understood that the second stroke encompasses the first stroke.

[0071] Among them, the third stroke L a This refers to the travel of a double-break circuit breaker when both breaks are in the arc contact stage. It should be understood that the start of the third travel is the end of the second travel.

[0072] (2) Calculate the average value of the dynamic resistance of the first stroke to obtain the resistance value when both breaks are in contact with the main contacts.

[0073] (3) Calculate the average value of the dynamic resistance of the third stroke to obtain the resistance value when both breaks are in arc contact.

[0074] (4) The resistance values ​​of the first stroke, the second stroke, the third stroke, the two breaks being in contact with the main contact, and the two breaks being in contact with the arc contact are taken as characteristic parameters.

[0075] It should be understood that when each ablation test is performed and multiple dynamic resistance-stroke measurement tests are conducted, each of the above-mentioned characteristic parameters is the average value of the corresponding values ​​extracted from multiple dynamic resistance-stroke curves.

[0076] For example, such as Figure 5 As shown, 20 represents the contact resistance of the main contact, and 21 represents the initial contact stroke L of the main contact. m1 22 indicates the contact resistance of the arc contact, and 23 indicates the contact stroke L of the main contact after the main contact. m2 24 indicates the arc contact stroke La .

[0077] Step S105: The amount of charge and energy transferred by the arc from different ablation tests, and the corresponding characteristic parameters, are used as the first characteristic variable to form a training sample.

[0078] As mentioned earlier, the characteristic parameters are the first stroke, the second stroke, the third stroke, the resistance value when both breaks are in contact with the main contact and the resistance value when both breaks are in contact with the arc contact. Then, adding the amount of charge and energy transferred by the arc, there are a total of seven first characteristic variables.

[0079] Let the training samples be denoted as Input = [X1, X2, X3, ..., X...]. j ], j = 7.

[0080] Among them, X j Given a sequence of input parameters, X j =[x j1 ,x j2 ,x j3 ,…,x jn ] where n is the total number of training samples for a single first feature variable. x jn It represents the nth value of the j-th first feature variable, meaning there are a total of n training samples.

[0081] Preferably, to make subsequent calculations more accurate, the training samples can be normalized, as shown in the following formula:

[0082]

[0083] Where y represents the normalized value of the training sample, y max y min Let x represent the maximum and minimum values ​​of the normalized training samples, respectively. These maximum and minimum values ​​are pre-defined based on experience. Let x represent the value of the training sample before normalization. max x min These represent the maximum and minimum values ​​of the training samples before normalization, respectively. For example, for a training sample x in the first leg of the process, x can be determined from n training samples. max x min Then, for each x, the above formula is used to calculate each normalized y.

[0084] Step S106: Input the training samples into the trained neural network to obtain the contribution of the first feature variable of each class.

[0085] Before inputting the training samples into the trained neural network, the neural network is first trained using the training samples. The specific process is as follows:

[0086] (1) Determine the life fraction of the double-break circuit breaker corresponding to different numbers of ablation tests.

[0087] For the lifespan fraction, the lifespan of a double-break circuit breaker is defined as any value between 0 and 100, where 0 indicates the circuit breaker has reached its lifespan and has not yet been put into use; 100 indicates that the circuit breaker's lifespan has reached its limit, i.e., the end of its lifespan. Therefore, the correspondence between lifespan status and lifespan fraction can be set based on experience.

[0088] Based on the above relationships, this step specifically includes:

[0089] ① When the double-break circuit breaker simulation model undergoes an ablation test, the lifespan fraction of the double-break circuit breaker simulation model is determined by observing its lifespan status.

[0090] ② After this ablation test, the number of ablation tests is correlated with the lifetime score of that test.

[0091] (2) Train the neural network using training samples until the error between the lifetime score corresponding to the training sample output by the neural network and the lifetime score corresponding to the number of ablation tests of the training sample is less than the preset error.

[0092] Among them, a BP neural network can be selected.

[0093] Specifically, the training samples can be divided into a training set and a validation set in a 4:1 ratio. Training is performed using the training set, and validation is performed using the validation set.

[0094] The preset error is 10%. If the error is less than 10%, the training effect is considered good, and training is complete. If the error is not less than 10%, training continues, and the average influence value algorithm can be used to continue training.

[0095] Specifically, obtaining the contribution of each category's first feature variable involves the following process:

[0096] (1) For each first feature variable, the size of the training sample of the first feature variable in the training sample is increased and decreased by a preset percentage respectively to obtain the first training sample and the second training sample.

[0097] For example, with a preset percentage of 10% and the first characteristic variable being the third stroke, the size of the third stroke is increased by 10% and decreased by 10% respectively.

[0098] (2) Input the first training sample and the second training sample into the trained neural network model respectively, and output the first simulation result and the second simulation result respectively.

[0099] (3) Adopt Calculate the MIV value.

[0100] Among them, MIV j This represents the MIV value of the first feature variable of the j-th class. This represents the first simulation result corresponding to the first training sample of the first feature variable of the j-th class. Let represent the second simulation result corresponding to the i-th second training sample of the first feature of the j-th class, and n represent the total number of training samples.

[0101] (4) Adopt Calculate the contribution of the first characteristic variable.

[0102] Among them, C j This represents the contribution of the first characteristic variable in the j-th category, and m represents the total number of the first characteristic variables, specifically 7.

[0103] Step S107: Select the first feature variable with the largest preset quantity as the second feature variable.

[0104] The preset quantity can be selected based on experience.

[0105] Step S108: Collect the second characteristic variable of the actual double-break circuit breaker in operation on site, input it into the trained neural network, output the life score of the actual double-break circuit breaker, and determine the life level of the actual double-break circuit breaker according to the life score.

[0106] According to DL / T 1686-2017, the guidelines for condition-based maintenance of sulfur hexafluoride high-voltage circuit breakers, circuit breaker conditions are divided into normal conditions, warning conditions, abnormal conditions, and critical conditions, corresponding to lifespan scores. Specifically, the relationship between lifespan scores and lifespan levels is as follows:

[0107] (1) When the lifespan score is within the range of [0, 25), the lifespan level is the normal state level.

[0108] (2) When the life score is within the range of [25, 50), the life level is the attention level.

[0109] (3) When the lifespan score is within the range of [50, 75), the lifespan level is an abnormal state level.

[0110] (4) When the life score is within the range of [75, 100], the life level is a severe state level.

[0111] Therefore, the lifespan level can be determined based on the numerical range in which the output lifespan score falls.

[0112] The evaluation accuracy of the method in this embodiment of the invention is over 90% as verified by the test set.

[0113] This invention also discloses a computer-readable storage medium storing computer program instructions; when executed by a processor, the computer program instructions implement the life assessment method for a double-break circuit breaker as described in the above embodiments.

[0114] This invention also discloses a life assessment system for a dual-break circuit breaker, comprising: a computer-readable storage medium as described in the above embodiments.

[0115] In summary, this invention simulates an actual double-break circuit breaker by connecting two phases of a single-break circuit breaker in series. This allows for simulated ablation tests and dynamic resistance-stroke curve measurements. The test results are accurate, and the collected data is sufficient. By extracting feature values ​​from the curves that accurately characterize the contact state of the two breaks during the opening process, and using a BP neural network combined with an average influence value algorithm, the influence weights of each feature value on the lifespan of the double-break circuit breaker are determined. This establishes an objective and accurate lifespan assessment method for double-break circuit breakers, which is of great significance for online monitoring and lifespan assessment of double-break circuit breakers in the field.

[0116] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method of life assessment of a double-break circuit breaker, characterized in that, The method comprises the following steps: establishing a double-break circuit breaker simulation model; after each ablation test is performed using the double-break circuit breaker simulation model, performing a dynamic resistance-travel measurement test of the double-break circuit breaker simulation model until the measured dynamic resistance of the contact exceeds a preset resistance threshold; obtaining the amount of charge and energy of the arc cumulative transfer caused by each ablation test; according to the dynamic resistance-travel measurement test corresponding to each ablation test, drawing a dynamic resistance-travel curve and obtaining characteristic parameters from the dynamic resistance-travel curve; using the amount of charge and energy of the arc cumulative transfer of different numbers of ablation tests and the corresponding characteristic parameters as first characteristic variables to form a training sample; inputting the training sample into a trained neural network to obtain the contribution degree of each type of first characteristic variable; selecting a preset number of first characteristic variables with the largest contribution degree as second characteristic variables; collecting second characteristic variables of an actual double-break circuit breaker in field operation and inputting the second characteristic variables into the trained neural network to output a service life score of the actual double-break circuit breaker and determine a service life grade of the actual double-break circuit breaker according to the service life score; the step of extracting characteristic parameters from the dynamic resistance-travel curve comprises: extracting a first travel, a second travel and a third travel from the dynamic resistance-travel curve, wherein the first travel is a travel in which both breaks of the double-break circuit breaker are in a main contact contact stage, the second travel is a travel in which one break of the double-break circuit breaker is in a main contact contact stage and the other break is in an arc contact contact stage, and the third travel is a travel in which both breaks of the double-break circuit breaker are in an arc contact contact stage, the end point of the first travel is a point at which the dynamic resistance is greater than a first preset resistance and the slope suddenly decreases, and the end point of the second travel is a first maximum value point at which the dynamic resistance is greater than a second preset resistance; calculating the average of the dynamic resistance of the first travel to obtain a resistance value when both breaks are in a main contact contact stage; calculating the average of the dynamic resistance value of the third travel to obtain a resistance value when both breaks are in an arc contact contact stage; using the first travel, the second travel, the third travel, the resistance value when both breaks are in a main contact contact stage and the resistance value when both breaks are in an arc contact contact stage as the characteristic parameters.

2. The life assessment method of a double-break circuit breaker according to claim 1, characterized by, Before the step of inputting the training sample into the trained neural network, the method comprises the following steps: determining the service life score of the double-break circuit breaker simulation model corresponding to different numbers of ablation tests; training a neural network using the training sample until the error between the service life score output by the neural network and the service life score corresponding to the number of ablation tests corresponding to the training sample is less than a preset error.

3. The life assessment method of a double-break circuit breaker according to claim 2, characterized by, The step of determining the service life score of the double-break circuit breaker simulation model corresponding to different numbers of ablation tests comprises: When the double-break circuit breaker simulation model performs the ablation test once, the life fraction of the double-break circuit breaker simulation model is determined by observing the life state of the double-break circuit breaker simulation model; After the ablation test, the number of the ablation test and the life fraction of the ablation test are corresponded.

4. The life assessment method of a double-break circuit breaker according to claim 1, characterized by, The step of obtaining the contribution degree of each type of the first characteristic variable comprises: For each first characteristic variable, the size of the training sample of the first characteristic variable in the training sample is respectively increased and decreased by a preset percentage to obtain a first training sample and a second training sample; The first training sample and the second training sample are respectively input into the trained neural network model to respectively output a first simulation result and a second simulation result; MIV values are calculated using MIV values of the first feature variables of the first class, MIV values of the first feature variables of the first class, j MIV values of the first feature variables of the first class, the first simulation result corresponding to the first training sample of the first feature variable of the first class, j the first simulation result corresponding to the first training sample of the first feature variable of the first class, i the first simulation result corresponding to the first training sample of the first feature variable of the first class, the second simulation result corresponding to the second training sample of the first feature variable of the first class, j the second simulation result corresponding to the second training sample of the first feature variable of the first class, i the second simulation result corresponding to the second training sample of the first feature variable of the first class, n the total number of training samples; Adopting calculating the contribution degree of the first characteristic variable, wherein, denotes the first characteristic variable of the first class, j denotes the contribution degree of the first characteristic variable of the first class, m denotes the total number of the first characteristic variables.

5. The life evaluation method of the double-break circuit breaker according to claim 1, characterized in that, When the life fraction is in the [0, 25) numerical interval, the life level is a normal state level; When the life fraction is in the [25, 50) numerical interval, the life level is an attention state level; When the life fraction is in the [50, 75) numerical interval, the life level is an abnormal state level; When the life fraction is in the [75, 100] numerical interval, the life level is a serious state level.

6. The life assessment method of a double-break circuit breaker according to claim 1, characterized by, The step of establishing the double-break circuit breaker simulation model comprises: The lower port of the first phase and the upper port of the second phase in the adjacent two phases of the single-break circuit breaker are connected to simulate the double-break circuit breaker simulation model.

7. The method for life assessment of a double-break circuit breaker according to claim 1, characterized in that: The neural network is a BP neural network.

8. A computer-readable storage medium, characterized in that: The computer readable storage medium stores computer program instructions; the computer program instructions are executed by the processor to realize the life evaluation method of the double-break circuit breaker according to any one of claims 1-7.

9. A life assessment system for a double-break circuit breaker, characterized by Comprise: The computer readable storage medium according to claim 8.

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