Method and system for dynamically testing opening and closing characteristics of field suppression switch based on synchronous wave recording

Abstract

The invention provides a method and a system for dynamically testing opening and closing characteristics of a field suppression switch based on synchronous wave recording, and belongs to the technical field of switch testing. The multi-channel synchronous wave recording equipment is used for collecting waveform data of the test motor and the field suppression switch in different test motor operation states, and the opening and closing characteristic test information of the field suppression switch is determined in combination with the multiple first waveform data corresponding to the test motor and the multiple second waveform data corresponding to the field suppression switch. Through a multi-channel synchronous wave recording technology, multi-channel signals can be directly detected, and the test efficiency is remarkably improved; and the super capacitor can adjust the output current and simulate various working conditions of the field suppression switch in actual operation, so that the test result has higher practicability and reference value. Therefore, the technical scheme can provide an efficient and accurate solution for performance evaluation of the field suppression switch.

Description

Technical Field

[0001] The present invention relates to the technical field of field discharge switches, and particularly relates to a dynamic test method and system for the opening and closing characteristics of a field discharge switch based on a super capacitor and multi-channel synchronous recording. Background Art

[0002] The field discharge switch is a key device in the generator excitation system. Its main function is to quickly cut off the excitation current under normal shutdown or accident conditions of the motor, and transfer the rotor magnetic field energy to the field discharge resistor to achieve rapid field extinction. The performance of the field discharge switch is directly related to the safe operation of the motor and the excitation system. Especially during accident tripping, the field discharge switch needs to quickly generate an arc and build voltage to ensure the smooth transfer of the rotor current to the non-linear field discharge resistor.

[0003] Existing detection methods mostly rely on a single voltage source or simple recording equipment, making it difficult to comprehensively capture the dynamic characteristics during the opening and closing processes of the field discharge switch. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a dynamic test method and system for the opening and closing characteristics of a field discharge switch based on a super capacitor and multi-channel synchronous recording. The dynamic test method for the opening and closing characteristics of a field discharge switch based on a super capacitor and multi-channel synchronous recording provides an efficient and accurate solution for the performance evaluation of the field discharge switch.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is as follows: For the dynamic test method for the opening and closing characteristics of a field discharge switch based on synchronous recording, the super capacitor is electrically connected to the field discharge switch, the field discharge switch is connected to the test motor, the test motor is electrically connected to the drive system, the drive system is communicatively connected to the upper computer, and the multi-channel synchronous recording device is communicatively connected to the upper computer. The multi-channel synchronous recording device collects waveform data during the operation of the test motor and the field discharge switch; The test method includes: The upper computer controls the drive system to control the operating state of the test motor, and controls the multi-channel synchronous recording device to collect waveform data of the test motor and the field discharge switch under different operating states of the test motor respectively; Obtain a variety of first waveform data collected by the multi-channel synchronous recording device for the test motor, and different first waveform data correspond to different operating states of the test motor; Obtain a variety of second waveform data collected by the multi-channel synchronous recording device for the field discharge switch, and different second waveform data correspond to different operating states of the test motor; Determine the predicted test information on the opening and closing characteristics of the field discharge switch according to the first waveform data and the second waveform data.

[0006] Preferably, the above host computer control drive system controls the operating state of the test motor, and controls the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different operating states of the test motor, specifically including: Control the test motor to be in a fault state, where the fault state includes various types of faults, and control the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different types of test motor fault states; Control the test motor to be in a maintenance state, where the maintenance state includes various types of maintenance, and control the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different types of test motor maintenance states; Control the test motor to be in a stopped state, and control the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch in the stopped state.

[0007] Preferably, among the above-mentioned multiple first waveform data, it includes waveform data corresponding to the fault state of the test motor, waveform data corresponding to the maintenance state of the test motor, and waveform data corresponding to the stopped state of the test motor; Multiple second waveform data, including waveform data of the field discharge switch corresponding to the fault state of the test motor, waveform data of the field discharge switch corresponding to the maintenance state of the test motor, and waveform data of the field discharge switch corresponding to the stopped state of the test motor; The motor parameters involved in the waveform data corresponding to the fault state of the test motor in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch corresponding to the fault state of the test motor in the multiple second waveform data belong to the same type; The motor parameters involved in the waveform data corresponding to the maintenance state of the test motor in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch corresponding to the maintenance state of the test motor in the multiple second waveform data belong to the same type; The motor parameters involved in the waveform data corresponding to the stopped state of the test motor in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch corresponding to the stopped state of the test motor in the multiple second waveform data belong to the same type.

[0008] Preferably, the above-mentioned determining the on-off characteristic prediction test information of the field discharge switch according to the first waveform data and the second waveform data specifically includes: Through a pre-trained first network model, respectively determine multiple predicted motor operating states according to multiple first waveform data, where each first waveform data corresponds to one predicted motor operating state; Determine the first on-off characteristic prediction test information of the field discharge switch according to the test motor operating state and the predicted motor operating state corresponding to various first waveform data. The first on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch on the test motor; Determine the second on-off characteristic prediction test information of the field discharge switch according to the first on-off characteristic prediction test information and the second waveform data. The second on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch on the field discharge switch; Determine the target on-off characteristic test information according to the first on-off characteristic prediction test information and the second on-off characteristic prediction test information.

[0009] Preferably, the above-mentioned super capacitor is also electrically connected to the power parameter detection unit. The first on-off characteristic prediction test information includes a first negative impact characteristic curve; Determine the second on-off characteristic prediction test information of the field discharge switch according to the first on-off characteristic prediction test information and the second waveform data, specifically including: Determine the curve characteristics of the first negative impact characteristic curve according to the first on-off characteristic prediction test information; When the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtain the power parameters collected by the power parameter detection unit; determine the second on-off characteristic test information of the field discharge switch according to the power parameters and the second waveform data; When the curve characteristics of the first negative impact characteristic curve meet the preset curve characteristics, determine the second on-off characteristic prediction test information of the field discharge switch according to the second waveform data.

[0010] Preferably, the above-mentioned determining the second on-off characteristic test information of the field discharge switch according to the power parameters and the second waveform data specifically includes: Through a pre-trained second network model, determine the second on-off characteristic prediction test information of the field discharge switch according to the power parameters and the second waveform data. The training data corresponding to the pre-trained second network model includes: power parameter samples, waveform data samples and prediction labels. The waveform data samples include waveform data corresponding to different test motor operating states.

[0011] Preferably, the above-mentioned second on-off characteristic prediction test information includes a second negative impact characteristic curve. Determining the on-off characteristic prediction test information of the field discharge switch according to the first on-off characteristic prediction test information and the second on-off characteristic prediction test information includes: Determine the target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve; Obtain the preset on-off characteristic curve of the field discharge switch; Determine the target switching characteristic prediction test information according to the target negative impact characteristic curve and the preset switching characteristic curve.

[0012] Preferably, the above-mentioned preset switching characteristic curve includes testing the motor operating state, current parameters, voltage parameters, and resistance parameters, and the target negative impact characteristic curve includes the negative impact values corresponding to various motor operating states; Determine the target switching characteristic prediction test information according to the target negative impact characteristic curve and the preset switching characteristic curve, including: According to the negative impact values corresponding to various motor operating states included in the target negative impact characteristic curve, transform at least one of the current parameters, voltage parameters, and resistance parameters included in the preset switching characteristic curve to obtain the transformed switching characteristic curve; Determine the target switching characteristic prediction test information according to the transformed switching characteristic curve.

[0013] Preferably, the above-mentioned test method further includes: Evaluate the performance of the field discharge switch according to the switching characteristic prediction test information of the field discharge switch to obtain a performance evaluation result, and the performance evaluation result is used to characterize whether there is an abnormality in the field discharge switch; When the performance evaluation result is used to characterize that there is no abnormality in the field discharge switch, obtain the hardware information of the test motor and the hardware information of the super capacitor; Determine the motor hardware information and power supply hardware information adapted to the field discharge switch according to the switching characteristic prediction test information of the field discharge switch, the hardware information of the test motor, and the hardware information of the super capacitor.

[0014] Use the system of the above-mentioned dynamic test method and system for the switching characteristics of the field discharge switch based on synchronous recording, and the system includes a super capacitor, a field discharge switch, a test motor, a multi-channel synchronous recording device, a drive system, and a host computer; the host computer is used to execute the test method.

[0015] A dynamic test method and system for the switching characteristics of a field discharge switch based on a super capacitor and multi-channel synchronous recording mentioned in the present invention constitute a test system through a super capacitor, a field discharge switch, a test motor, and a multi-channel synchronous recording device. The multi-channel synchronous recording device is used to collect waveform data of the test motor and the field discharge switch under different motor operating states respectively. Combining various first waveform data corresponding to the test motor and various second waveform data corresponding to the field discharge switch, determine the switching characteristic prediction test information of the field discharge switch. Through multi-channel synchronous recording technology, multiple signals can be directly detected, significantly improving the test efficiency; the super capacitor can adjust the output current to simulate various working conditions of the field discharge switch in actual operation, making the test results more practical and valuable for reference. Description of the Drawings

[0016] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 is the structural block diagram of the dynamic test system for the opening and closing characteristics of the field discharge switch of the present invention; Figure 2 is the flowchart of the dynamic test method for the opening and closing characteristics of the field discharge switch of the present invention; Figure 3 is the schematic diagram of curve transformation in the embodiment of the present invention; Figure 4 is the block diagram of the dynamic test device for the opening and closing characteristics of the field discharge switch in the embodiment of the present invention; Figure 5 is the block diagram of the electronic device in the embodiment of the present invention.

[0017] Among them: super capacitor 1, field discharge switch 2, test motor 3, multi-channel synchronous recording device 4, drive system 5, upper computer 6, dynamic test device 400 for the opening and closing characteristics of the field discharge switch, control module 401, acquisition module 402, determination module 403, electronic device 500, processor 501, memory 502, multimedia component 503, input / output interface 504, communication component 505. Specific embodiments

[0018] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0019] Embodiment 1: A dynamic test method and system for the opening and closing characteristics of a field discharge switch based on synchronous recording. The super capacitor 1 is electrically connected to the field discharge switch 2. The field discharge switch 2 is connected to the test motor 3. The test motor 3 is electrically connected to the drive system 5. The drive system 5 is communicatively connected to the upper computer 6. The multi-channel synchronous recording device 4 is communicatively connected to the upper computer 6. The multi-channel synchronous recording device 4 collects waveform data during the operation of the test motor 3 and the field discharge switch 2. The test method includes: The upper computer 6 controls the drive system 5 to control the operating state of the test motor 3, and controls the multi-channel synchronous recording device 4 to collect waveform data of the test motor 3 and the field discharge switch 2 under different operating states of the test motor 3 respectively; Obtain a variety of first waveform data collected by the multi-channel synchronous recording device 4 for the test motor 3. Different first waveform data correspond to different operating states of the test motor 3; Obtain a variety of second waveform data collected by the multi-channel synchronous recording device 4 for the field discharge switch 2. Different second waveform data correspond to different operating states of the test motor 3; Determine the predicted test information of the opening and closing characteristics of the field discharge switch 2 according to the first waveform data and the second waveform data.

[0020] The above host computer 6 controls the operation state of the drive system 5 to control the test motor 3, and controls the multi-channel synchronous recording device 4 to collect the waveform data of the test motor 3 and the field discharge switch 2 under different operating states of the test motor 3, specifically including: Control the test motor 3 to be in a fault state, where the fault state includes various types of faults, and control the multi-channel synchronous recording device 4 to collect the waveform data of the test motor 3 and the field discharge switch 2 under different types of test motor fault states; Control the test motor 3 to be in a maintenance state, where the maintenance state includes various types of maintenance, and control the multi-channel synchronous recording device 4 to collect the waveform data of the test motor 3 and the field discharge switch 2 under different types of test motor maintenance states; Control the test motor 3 to be in a stopped state, and control the multi-channel synchronous recording device 4 to collect the waveform data of the test motor 3 and the field discharge switch 2 in the stopped state.

[0021] Preferably, among the above-mentioned multiple first waveform data, it includes waveform data corresponding to the fault state of the test motor 3, waveform data corresponding to the maintenance state of the test motor 3, and waveform data corresponding to the stopped state of the test motor 3; Multiple second waveform data, including waveform data of the field discharge switch 2 corresponding to the fault state of the test motor 3, waveform data of the field discharge switch 2 corresponding to the maintenance state of the test motor 3, and waveform data of the field discharge switch 2 corresponding to the stopped state of the test motor 3; The motor parameters involved in the waveform data corresponding to the fault state of the test motor 3 in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch 2 corresponding to the fault state of the test motor 3 in the multiple second waveform data belong to the same type; The motor parameters involved in the waveform data corresponding to the maintenance state of the test motor 3 in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch 2 corresponding to the maintenance state of the test motor 3 in the multiple second waveform data belong to the same type; The motor parameters involved in the waveform data corresponding to the stopped state of the test motor 3 in the multiple first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch 2 corresponding to the stopped state of the test motor 3 in the multiple second waveform data belong to the same type.

[0022] Preferably, the above-mentioned determining the on-off characteristic prediction test information of the field discharge switch 2 according to the first waveform data and the second waveform data specifically includes: Through a pre-trained first network model, determine multiple predicted motor operating states respectively according to the multiple first waveform data, where each first waveform data corresponds to one predicted motor operating state; Based on the operating states of the test motor 3 corresponding to various first waveform data and the predicted operating state of the motor, determine the first on-off characteristic prediction test information of the field discharge switch 2, where the first on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch 2 on the test motor 3; Based on the first on-off characteristic prediction test information and the second waveform data, determine the second on-off characteristic prediction test information of the field discharge switch 2, where the second on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch 2 on the field discharge switch 2; Based on the first on-off characteristic prediction test information and the second on-off characteristic prediction test information, determine the target on-off characteristic test information.

[0023] Preferably, the above-mentioned super capacitor 1 is also electrically connected to the power parameter detection unit, and the first on-off characteristic prediction test information includes a first negative impact characteristic curve. Preferably, the above-mentioned determining the second on-off characteristic prediction test information of the field discharge switch 2 according to the first on-off characteristic prediction test information and the second waveform data specifically includes: Determine the curve characteristics of the first negative impact characteristic curve according to the first on-off characteristic prediction test information; When the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtain the power parameters collected by the power parameter detection unit; according to the power parameters and the second waveform data, determine the second on-off characteristic test information of the field discharge switch 2; When the curve characteristics of the first negative impact characteristic curve meet the preset curve characteristics, determine the second on-off characteristic prediction test information of the field discharge switch 2 according to the second waveform data.

[0024] Preferably, the above-mentioned determining the second on-off characteristic test information of the field discharge switch 2 according to the power parameters and the second waveform data specifically includes: Through a pre-trained second network model, according to the power parameters and the second waveform data, determine the second on-off characteristic prediction test information of the field discharge switch 2, where the training data corresponding to the pre-trained second network model includes: power parameter samples, waveform data samples, and prediction labels, and the waveform data samples include waveform data corresponding to different operating states of the test motor 3.

[0025] Preferably, the above-mentioned second on-off characteristic prediction test information includes a second negative impact characteristic curve. Determining the on-off characteristic prediction test information of the field discharge switch 2 according to the first on-off characteristic prediction test information and the second on-off characteristic prediction test information includes: Determine the target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve; Obtain the preset closing and opening characteristic curves of the field discharge switch 2; Determine the target closing and opening characteristic prediction test information according to the target negative impact characteristic curve and the preset closing and opening characteristic curves.

[0026] Preferably, the above-mentioned preset closing and opening characteristic curves include testing the operating state, current parameters, voltage parameters, and resistance parameters of the test motor 3, and the target negative impact characteristic curve includes the negative impact values corresponding to various operating states of the test motor 3; Determine the target closing and opening characteristic prediction test information according to the target negative impact characteristic curve and the preset closing and opening characteristic curves, including: According to the negative impact values corresponding to various operating states of the test motor 3 included in the target negative impact characteristic curve, transform at least one of the current parameters, voltage parameters, and resistance parameters included in the preset closing and opening characteristic curves to obtain the transformed closing and opening characteristic curves; Determine the target closing and opening characteristic prediction test information according to the transformed closing and opening characteristic curves.

[0027] Preferably, the above-mentioned test method further includes: Evaluate the performance of the field discharge switch according to the closing and opening characteristic prediction test information of the field discharge switch to obtain a performance evaluation result, and the performance evaluation result is used to characterize whether there is an abnormality in the field discharge switch; When the performance evaluation result is used to characterize that there is no abnormality in the field discharge switch, obtain the hardware information of the test motor and the hardware information of the super capacitor; Determine the motor hardware information and power supply hardware information adapted to the field discharge switch according to the closing and opening characteristic prediction test information of the field discharge switch, the hardware information of the test motor, and the hardware information of the super capacitor.

[0028] Use the system of the above-mentioned dynamic test method and system for the closing and opening characteristics of the field discharge switch based on synchronous recording. The system includes a super capacitor 1, a field discharge switch 2, a test motor 3, a multi-channel synchronous recording device 4, a drive system 5, and a host computer 6; the host computer 6 is used to execute the test method.

[0029] Embodiment 2: The field discharge switch is a key device in the generator excitation system. Its main function is to quickly cut off the excitation current and transfer the rotor magnetic field energy to the field discharge resistor under normal shutdown or accident conditions of the motor to achieve rapid field extinction. The performance of the field discharge switch is directly related to the safe operation of the motor and the excitation system. Especially during an accident trip, the field discharge switch needs to quickly draw an arc to build voltage to ensure that the rotor current is smoothly transferred to the non-linear field discharge resistor.

[0030] Existing detection methods mostly rely on a single voltage source or simple waveform recording devices, making it difficult to comprehensively capture the dynamic characteristics during the opening and closing processes of the field discharge switch.

[0031] Based on this, embodiments of the present disclosure provide a technical solution. A test system is constituted by a super capacitor, a field discharge switch, a test motor, and a multi-channel synchronous waveform recording device. The multi-channel synchronous waveform recording device is used to respectively collect waveform data of the test motor and the field discharge switch under different operating states of the test motor. By combining various first waveform data corresponding to the test motor and various second waveform data corresponding to the field discharge switch, the opening and closing characteristic test information of the field discharge switch is determined.

[0032] Through multi-channel synchronous waveform recording technology, multiple signals can be directly detected, significantly improving the test efficiency. The super capacitor can adjust the output current to simulate various operating conditions of the field discharge switch in actual operation, making the test results more practical and valuable for reference.

[0033] Therefore, this technical solution can provide an efficient and accurate solution for the performance evaluation of the field discharge switch.

[0034] Figure 1 is a structural block diagram of a dynamic test system for the opening and closing characteristics of a field discharge switch based on a super capacitor and multi-channel synchronous waveform recording shown according to an exemplary embodiment, as Figure 1 shown, the system includes: a super capacitor, a field discharge switch, a test motor, and a multi-channel synchronous waveform recording device that are electrically connected in sequence.

[0035] And, it further includes: a host computer, which is respectively communicatively connected to the multi-channel synchronous waveform recording device and the drive system of the test motor.

[0036] Regarding multi-channel synchronous waveform recording technology, it is an important technology used in fields such as power systems and industrial monitoring. It can collect and record waveform data of multiple channels in real time, providing key support for fault diagnosis, system analysis, and operation optimization.

[0037] Regarding the super capacitor, fast charge and discharge ability: The super capacitor can absorb and release a large amount of energy in a short time, and is suitable for scenarios requiring instantaneous high-power output. High-precision voltage control: Through a voltage sampling and analysis circuit and negative feedback control technology, high stability of the output voltage is achieved. Long service life and high reliability: The charge and discharge cycle life of the super capacitor can reach hundreds of thousands of times, far higher than that of traditional batteries. Excellent low-temperature performance: Some super capacitors can operate at temperatures as low as -40°C, suitable for extreme environments.

[0038] Therefore, the super capacitor can be used as the power supply of the system to provide a stable test power supply for the field discharge switch, ensuring the stability and adjustability of the current during the opening and closing processes.

[0039] The test motor also needs to be configured with a drive system that can drive the motor to run, and the drive instructions of the drive system can come from the host computer.

[0040] The multi-channel synchronous waveform recording device can simultaneously collect waveform data such as current and voltage of multiple channels to achieve multi-channel synchronous waveform recording; it has a high-speed communication interface to transmit the collected waveform data to the host computer in real time.

[0041] The sampling frequency of the multi-channel synchronous waveform recording device is not less than 10 kHz to ensure that the transient changes during the opening and closing process of the field discharge switch can be captured.

[0042] In some multi-channel synchronous waveform recording devices, including: a buffer and control unit: each channel is equipped with dual memories, such as memory A and memory B, to alternately store waveform data. A clock and transmission control center: responsible for the orderly extraction and transmission of data. Adopt a time synchronization mechanism, such as achieving the time synchronization of the master and slave clocks through the FC-AE protocol to ensure the time consistency of multi-channel data.

[0043] Based on the above hardware support, the dynamic test of the opening and closing characteristics of the field discharge switch based on supercapacitors and multi-channel synchronous waveform recording can be realized.

[0044] It can be understood that Figure 1 The block diagram shown only involves key system components. In this system, there can also be other components that can implement corresponding system functions, such as: protection circuits, monitoring circuits, etc., and also for example: various electrical connection components, etc., which will not be introduced one by one here.

[0045] Figure 2 is a flowchart of a dynamic test method for the opening and closing characteristics of a field discharge switch based on supercapacitors and multi-channel synchronous waveform recording shown according to an exemplary embodiment. This method can be applied to Figure 1 the host computer shown. This method includes the following steps: Step S21, control the operating state of the test motor, and control the multi-channel synchronous waveform recording device to collect waveform data of the test motor and the field discharge switch under different operating states of the test motor respectively.

[0046] Step S22, obtain various first waveform data collected by the multi-channel synchronous waveform recording device for the test motor, and different first waveform data correspond to different operating states of the test motor.

[0047] Step S23, obtain various second waveform data collected by the multi-channel synchronous waveform recording device for the field discharge switch, and different second waveform data correspond to different operating states of the test motor.

[0048] Step S24, determine the predicted test information of the opening and closing characteristics of the field discharge switch according to the first waveform data and the second waveform data.

[0049] The host computer issues control instructions to the drive system of the test motor, and then the drive system drives and controls the test motor according to the control instructions to achieve the control of the operating state of the test motor.

[0050] The host computer issues recording instructions to the multi-channel synchronous recording device, and then the multi-channel recording device performs multi-channel recording to achieve the acquisition of waveform data of the test motor and the field discharge switch under different operating states of the test motor by the multi-channel synchronous recording device.

[0051] It can be understood that the test motor can be controlled to work in different operating states respectively, and then the waveform data under the corresponding operating states can be collected respectively.

[0052] Further, after the host computer obtains the waveform data corresponding to different motor operating states, the opening and closing characteristics of the field discharge switch are analyzed by combining these data.

[0053] In some embodiments, controlling the operating state of the test motor and controlling the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different operating states of the test motor may include: controlling the test motor to be in a fault state, where the fault state includes various types of fault states, and controlling the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different types of test motor fault states; controlling the test motor to be in a maintenance state, where the maintenance state includes various types of maintenance states, and controlling the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under different types of test motor maintenance states; controlling the test motor to be in a normal shutdown state, and controlling the multi-channel synchronous recording device to collect the waveform data of the test motor and the field discharge switch under the normal shutdown state.

[0054] In this implementation, the operating states of the test motor include: fault state, maintenance state, and normal shutdown state. And, the fault state and the maintenance state can respectively involve various types of states.

[0055] The field discharge switch will perform different switching actions under the above three motor operating states. Therefore, the waveform data under these operating states can be collected.

[0056] Fast field discharge in the fault state: When there is an internal fault or an outlet fault in the motor, the field discharge switch quickly cuts off the excitation power supply to prevent overvoltage and overcurrent from damaging the motor winding.

[0057] Safety isolation in the maintenance state: When the motor is under maintenance, the field discharge switch is disconnected to form an obvious disconnection point to ensure the safety of maintenance personnel.

[0058] Auxiliary field suppression in normal shutdown state: During normal shutdown, the field suppression switch is usually not directly disconnected, but the field is suppressed by inversion through the automatic excitation regulator.

[0059] The fault causes corresponding to different types of fault states can be different, and the maintenance methods corresponding to different types of maintenance states can be different.

[0060] Among the multiple first waveform data, there are waveform data corresponding to the fault state of the test motor, waveform data corresponding to the maintenance state of the test motor, and waveform data corresponding to the normal shutdown state of the test motor.

[0061] Among the multiple second waveform data, there are waveform data corresponding to the fault state of the test motor, waveform data corresponding to the maintenance state of the test motor, and waveform data corresponding to the normal shutdown state of the test motor.

[0062] The motor parameters involved in the waveform data corresponding to the fault state of the test motor included in the multiple first waveform data and the field suppression switch parameters involved in the waveform data corresponding to the fault state of the test motor included in the multiple second waveform data belong to the same type of parameters.

[0063] The same type of parameters can be: voltage, current, resistance, etc.

[0064] The motor parameters involved in the waveform data corresponding to the maintenance state of the test motor included in the multiple first waveform data and the field suppression switch parameters involved in the waveform data corresponding to the maintenance state of the test motor included in the multiple second waveform data belong to different types of parameters.

[0065] For example, the motor parameters can be voltage, current, etc.; the field suppression switch parameters can be: opening and closing time, resistance, etc.

[0066] In some embodiments, the motor parameters involved in the waveform data corresponding to the normal shutdown state of the test motor included in the multiple first waveform data and the field suppression switch parameters involved in the waveform data corresponding to the normal shutdown state of the test motor included in the multiple second waveform data belong to different types of parameters.

[0067] The motor parameters can be voltage, current, etc.; the field suppression switch parameters can be: opening and closing time, resistance, etc.

[0068] In some embodiments, in the case of involving multiple motor parameters, the multi-channel synchronous recording device can generate corresponding waveform data for each of the multiple motor parameters. In the case of involving multiple field suppression switch parameters, the multi-channel synchronous recording device can generate corresponding waveform data for each of the multiple field suppression switch parameters.

[0069] The field discharge switch may include multiple switch ports, and these multiple switch ports may respectively correspond to different waveform data.

[0070] Therefore, in step S22, a variety of first waveform data collected by the multi-channel synchronous recording device for the test motor can be obtained, and different first waveform data correspond to different test motor operating states. Moreover, various first waveform data may include waveforms corresponding to different motor parameters.

[0071] Moreover, in step S23, a variety of second waveform data collected by the multi-channel synchronous recording device for the field discharge switch can be obtained, and different second waveform data correspond to different test motor operating states. Moreover, various second waveform data may include waveforms corresponding to different field discharge switch parameters.

[0072] Further, in step S24, based on the first waveform data and the second waveform data, the prediction test information of the opening and closing characteristics of the field discharge switch is determined.

[0073] As an optional implementation manner, step S24 includes: respectively determining a variety of predicted motor operating states according to a variety of first waveform data through a pre-trained first network model, where each first waveform data corresponds to a predicted motor operating state; determining the first opening and closing characteristic prediction test information of the field discharge switch according to the test motor operating states and the predicted motor operating states respectively corresponding to the variety of first waveform data, and the first opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the field discharge switch on the motor; determining the second opening and closing characteristic prediction test information of the field discharge switch according to the first opening and closing characteristic prediction test information and the second waveform data, and the second opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the field discharge switch on the field discharge switch; determining the target opening and closing characteristic prediction test information according to the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information.

[0074] In this implementation manner, first, the opening and closing characteristics of the field discharge switch are analyzed from the dimension of motor operation to obtain the first opening and closing characteristic prediction test information that characterizes the negative impact of the opening and closing of the field discharge switch on the motor.

[0075] The pre-trained first network model can be an integrated model composed of a one-dimensional convolutional neural network and a large language model.

[0076] Among them, the one-dimensional convolutional neural network is used to process the waveform data and encode it into text features that the large language model can process, and the large language model is used to predict the motor operating state based on the encoded text features.

[0077] Regarding the one-dimensional convolutional neural network, the basic formula can be expressed as: y = f(W·x + b); where: y is the output feature vector; f is the activation function, which can be ReLU, Sigmoid, or Tanh, etc.; W is the weight matrix of the convolutional kernel or filter; x is the input feature vector, that is, waveform data; b is the bias term.

[0078] In the one-dimensional convolutional neural network, the convolutional kernel W slides along the time dimension of the input feature vector x to calculate the convolutional operation. Specifically, for each time step t of the input feature vector x, the convolutional kernel W performs a dot product operation with a subsequence of x, then adds the bias term b, and finally obtains the corresponding element of the output feature vector y through the activation function f.

[0079] Taking a specific example to illustrate, assuming the length of the input feature vector x is n and the length of the convolutional kernel W is k, then the length of the output feature vector y is n - k + 1 without considering boundary padding.

[0080] In practical applications, the one-dimensional convolutional neural network usually contains multiple convolutional layers, and each convolutional layer contains multiple convolutional kernels, which can extract multiple features of the input waveform data. In addition, the one-dimensional convolutional neural network can also be combined with pooling layers, such as max pooling or average pooling, to reduce the dimension of the feature vector and extract more abstract features.

[0081] By using the one-dimensional convolutional neural network as a text encoder, features corresponding to the waveform data can be extracted based on the waveform data.

[0082] Regarding large language models, they can include the following key components: Word embedding: Word embedding is a technique that maps words to a continuous vector space to capture the semantic relationships between words. Common methods include Word2Vec and GloVe: Word2Vec: CBOW continuous bag-of-words model: Given the context, predict the center word. Skip-Gram: Given the center word, predict the context; Training objective: ; where T is the size of the training data, w t is the word at time step t, P represents the conditional probability, P(w t+1 ∣w t ) and P(w t-1 ∣w t ) respectively represent the probabilities of predicting the next word w t and the previous word w t+1 when given the current word w t-1 ; GloVe: Learning word embeddings through matrix factorization tasks, training objective: ; Among them, X is the word vector matrix, Y is the context vector matrix, is the similarity of the word pair ( u , v ), P( y u ∣ x u ) represents the probability of the label x u when the given feature y u is a conditional probability.

[0083] Self-Attention mechanism: The self-attention mechanism is the core of the Transformer architecture, allowing the model to establish long-range dependencies between different time steps; the calculation formula is: ; Among them, Q is the query vector, K is the key vector, V is the value vector, d k is the dimension of the key vector.

[0084] Transformer architecture: Transformer is the core architecture of large language models, achieving efficient sequence modeling through the self-attention mechanism and the encoder-decoder structure. Main components: Multi-Head Attention: Parallel self-attention mechanisms, allowing the model to simultaneously focus on multiple different contexts.

[0085] Positional Encoding: Used to represent the position information in the sequence. Since Transformer has no sequence structure, positional encoding is needed to capture the sequence structure.

[0086] Residual Connection: Retains the input before each layer, accelerating the training process.

[0087] Layer Normalization: Normalizes the output of the model, reducing overfitting.

[0088] These technologies and formulas are the basis of large language models. However, actual large language models, such as GPT, LLaMA, etc., will perform large-scale pre-training on this basis and improve performance through complex optimization and fine-tuning.

[0089] The training data of the first network model for pre-training can include: sample waveform data corresponding to motor operating parameters, features corresponding to the sample waveform data, and motor operating state labels. This training data can be obtained through actual measurement or simulation testing.

[0090] Specifically, first, use the sample waveform data corresponding to the motor operating parameters and the text features corresponding to the sample waveform data to train a one-dimensional convolutional neural network so that the one-dimensional convolutional neural network has the ability of text encoding. Then, use the motor operating state labels and the text features corresponding to the sample waveform data to train a large language model so that the large language model can predict the motor operating state labels based on the text features.

[0091] Moreover, in order to improve the prediction accuracy of the large language model, the text features encoded by the one-dimensional convolutional neural network can also be used as additional training data for the large language model.

[0092] Input each type of first waveform data into the pre-trained first network model, and the predicted motor operating state output by the pre-trained first network model can be obtained, so that each type of first waveform data corresponds to a predicted motor operating state.

[0093] Furthermore, the test motor operating states and the predicted motor operating states corresponding to multiple types of first waveform data can be compared to obtain first switching characteristic prediction test information.

[0094] In some embodiments, the first switching characteristic prediction test information can include a first negative impact characteristic curve, and this first negative impact characteristic curve can characterize the negative impact values corresponding to multiple types of first waveform data respectively.

[0095] In some embodiments, if the test motor operating state and the predicted motor operating state corresponding to the first waveform data are the same, the negative impact value is 0; if the test motor operating state and the predicted motor operating state corresponding to the first waveform data are different, the negative impact value is 1.

[0096] Furthermore, according to the first switching characteristic prediction test information and the second waveform data, analyze from the dimension of the field discharge switch to obtain second switching characteristic prediction test information to characterize the negative impact of the switching of the field discharge switch on the field discharge switch.

[0097] In some embodiments, the supercapacitor is also electrically connected to a power parameter detection unit, which can detect parameters of the supercapacitor. For example, the discharge amount, rated voltage, etc. Regarding the implementation of this detection unit, reference can be made to the mature technologies in the art.

[0098] In some embodiments, when the first switching characteristic prediction test information includes a first negative influence characteristic curve, the determining of the second switching characteristic prediction test information of the field discharge switch according to the first switching characteristic prediction test information and the second waveform data may include: Determining the curve characteristics of the first negative influence characteristic curve according to the first switching characteristic prediction test information; when the curve characteristics of the first negative influence characteristic curve do not meet the preset curve characteristics, acquiring the power parameters collected by the power parameter detection unit; determining the second switching characteristic prediction test information of the field discharge switch according to the power parameters and the second waveform data; when the curve characteristics of the first negative influence characteristic curve meet the preset curve characteristics, determining the second switching characteristic prediction test information of the field discharge switch according to the second waveform data.

[0099] In some embodiments, the curve characteristics of the first negative influence characteristic curve may be the curvature of the curve, the Z parameter of the curve, etc.

[0100] In some embodiments, the preset curve characteristics may be curve characteristics indicating no negative influence or very little negative influence on the motor parameters. For example, all the negative influence values on the curve are 1, or only a small part of the negative influence values are 0.

[0101] Furthermore, when the preset curve characteristics are not met, the switching characteristics of the field discharge switch can be further analyzed by combining the power parameters and the second waveform data.

[0102] When the preset curve characteristics are met, the second switching characteristic prediction test information of the field discharge switch can be determined only according to the second waveform data.

[0103] In some embodiments, determining the second switching characteristic prediction test information of the field discharge switch according to the power parameters and the second waveform data includes: determining the second switching characteristic prediction test information of the field discharge switch according to the power parameters and the second waveform data through a pre-trained second network model, where the training data corresponding to the pre-trained second network model includes: power parameter samples, waveform data samples, and prediction labels, and the waveform data samples include waveform data corresponding to different motor operating states.

[0104] In this embodiment, the pre-trained second network model needs to process waveform data. Therefore, the model architecture of the second network model can be the same as that of the first network model. However, the model parameters of the first network model and the second network model are different. Therefore, the implementation of the model network will not be repeated here.

[0105] In some embodiments, the training data corresponding to the pre-trained second network model includes: power parameter samples, waveform data samples, and prediction labels. The prediction label can be the negative impact value of the field discharge switch. The waveform data samples include waveform data corresponding to different motor operating states, and the waveform data involves field discharge switch parameters.

[0106] In some embodiments, the power parameters and the second waveform data are input into the pre-trained second network model to obtain the second closing and opening characteristic prediction test information output by the second network model.

[0107] In some embodiments, determining the second closing and opening characteristic prediction test information of the field discharge switch according to the second waveform data may include: inputting the second waveform data into the pre-trained second network model to obtain the second closing and opening characteristic prediction test information output by the second network model.

[0108] Alternatively, the second waveform data is compared with the preset standard waveform data to obtain the second closing and opening characteristic prediction test information.

[0109] In some embodiments, the second closing and opening characteristic prediction test information includes a second negative impact characteristic curve, and the second negative impact characteristic curve can represent the negative impact values corresponding to various second waveform data.

[0110] In some embodiments, the greater the difference between the second waveform data and the preset standard waveform data, the greater the negative impact value.

[0111] In some embodiments, the negative impact value can be limited within a specific impact value range, such as 0 to 1.

[0112] Furthermore, in the case where the first closing and opening characteristic prediction test information includes a first negative impact characteristic curve and the second closing and opening characteristic prediction test information includes a second negative impact characteristic curve, determining the target closing and opening characteristic prediction test information according to the first closing and opening characteristic prediction test information and the second closing and opening characteristic prediction test information may include: determining the target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve; obtaining the preset closing and opening characteristic curve of the field discharge switch; and determining the target closing and opening characteristic prediction test information according to the target negative impact characteristic curve and the preset closing and opening characteristic curve.

[0113] In this embodiment, the negative impact values characterized by the first negative impact characteristic curve and the second negative impact characteristic curve can be weighted and averaged to obtain the target negative impact value.

[0114] In some embodiments, the negative impact values corresponding to the same operating state of the test motor are weighted and averaged.

[0115] In some embodiments, the target negative impact characteristic curve characterizes the target negative impact values corresponding to the respective operating states of the test motors.

[0116] In some embodiments, a preset switching-on and switching-off characteristic curve is provided, including: motor operating state, current parameter, voltage parameter, and resistance parameter.

[0117] In some embodiments, according to the target negative impact characteristic curve and the preset switching-on and switching-off characteristic curve, target switching-on and switching-off characteristic prediction test information is determined, including: based on the negative impact values corresponding to the various operating states of the test motors included in the target negative impact characteristic curve, at least one of the time parameter, current parameter, voltage parameter, and resistance parameter included in the preset switching-on and switching-off characteristic curve is transformed to obtain a transformed switching-on and switching-off characteristic curve; according to the transformed switching-on and switching-off characteristic curve, the target switching-on and switching-off characteristic prediction test information is determined.

[0118] In some embodiments, the transformation methods of the field discharge switch parameters corresponding to different negative impact values under different motor operating states are preconfigured. Based on the preconfigured transformation methods, parameter changes can be performed to obtain the transformed switching-on and switching-off characteristic curve.

[0119] Exemplarily, in the fault state, since the field discharge switch is quickly cut off, both the current parameter and the voltage parameter decrease rapidly, and the resistance parameter increases rapidly. However, in the presence of a negative impact value, the minimum values of the current parameter and the voltage parameter cannot reach the ideal value, or cannot reach the ideal value quickly. Therefore, the slopes and peaks and valleys of the current parameter curve and the voltage parameter curve can be transformed.

[0120] Exemplarily, in the maintenance state, there is an obvious disconnection point in the field discharge switch, so there are specific parameters corresponding to the disconnection point. However, in the presence of a negative impact value, there may be a delay or other situations at this disconnection point. Therefore, the special points of the relevant parameter curves can be offset.

[0121] Exemplarily, in the normal shutdown state, the field discharge switch is not directly cut off, but is cut off at a normal speed. Therefore, the changes in the current parameter, voltage parameter, and resistance parameter are relatively slow. However, in the presence of a negative impact value, the changes in these parameters may be different. Therefore, the curvature of the change curves of the relevant parameters can be transformed.

[0122] It can be understood that when performing the transformation, the transformation is carried out according to the same operating state of the motor.

[0123] Moreover, it can be understood that in each parameter curve, the change is based on the time sequence.

[0124] Figure 3 It is a schematic diagram of a curve transformation shown according to an exemplary embodiment. As Figure 3 shown, in Figure 3 , the preset switching characteristics curve can involve any one or more change curves of current, voltage, and resistance. Only one is shown in the figure, and the change curve changes with the time sequence. When performing the curve change, the slope of the curve can be transformed; the peaks and valleys can be transformed; and specific parameter points can be transformed, etc.

[0125] In some embodiments, the higher the negative impact, the more parameters need to be transformed. The smaller the negative impact, the fewer parameters need to be transformed, and all can be pre-configured through methods such as offline testing or simulation testing.

[0126] Further, based on the transformed switching characteristics curve, the target switching characteristics prediction test information is determined.

[0127] In some embodiments, the preset switching characteristics curve itself is a kind of characteristic curve, but it is not dynamic. Therefore, after the transformation, the test of the dynamic characteristics is realized. Thus, the target switching characteristics prediction test information can be directly determined from the transformed switching characteristics curve.

[0128] Or, various parameter change characteristics of the curve can also be statistically analyzed based on the curve, and integrated with the curve to form the target switching characteristics prediction test information.

[0129] Further, the switching characteristics prediction test information of the field discharge switch can also be applied.

[0130] As an optional implementation manner, the method further includes: evaluating the performance of the field discharge switch according to the switching characteristics prediction test information of the field discharge switch to obtain a performance evaluation result, and the performance evaluation result is used to characterize whether there is an abnormality in the field discharge switch; when the performance evaluation result is used to characterize that there is no abnormality in the field discharge switch, obtaining the hardware information of the test motor and obtaining the hardware information of the super capacitor; determining the motor hardware information and power supply hardware information adapted to the field discharge switch according to the switching characteristics prediction test information of the field discharge switch, the hardware information of the test motor, and the hardware information of the super capacitor.

[0131] In this implementation manner, there are various implementation manners for evaluating the performance of the field discharge switch. For example: evaluation is achieved through artificial intelligence; evaluation is achieved by comparing with big data, etc. Specifically, reference can be made to the mature technologies in the field.

[0132] In some embodiments, the performance evaluation result is used to characterize whether there is an abnormality in the field discharge switch, and it may also involve specific types of abnormalities, such as: disconnection abnormality, field discharge resistor abnormality, etc.

[0133] In some embodiments, when the performance evaluation result is used to characterize that there is no abnormality in the field discharge switch, the hardware information of the test motor is obtained, and the hardware information of the supercapacitor is obtained.

[0134] Furthermore, the test information predicted according to the opening and closing characteristics of the field discharge switch, the hardware information of the test motor, and the hardware information of the supercapacitor can be used to determine the motor hardware information and power supply hardware information adapted to the field discharge switch.

[0135] In this implementation manner, the test information predicted according to the opening and closing characteristics of the field discharge switch, the hardware information of the test motor, and the hardware information of the supercapacitor can be associated, and the hardware information of the test motor and the hardware information of the supercapacitor can be correspondingly extended to obtain an adaptation relationship, that is, to determine the motor hardware information and power supply hardware information adapted to the field discharge switch.

[0136] Exemplarily, based on the rated power of the test motor, it can be adaptively reduced or increased to obtain the adapted motor rated power.

[0137] Exemplarily, based on the discharge amount of the supercapacitor, it can be adaptively reduced or increased to obtain the adapted supercapacitor discharge amount.

[0138] Furthermore, the obtained motor hardware information and power supply hardware information adapted to the field discharge switch can be used for subsequent application of the field discharge switch to select a suitable application scenario.

[0139] In some embodiments, when the performance evaluation result is used to characterize that there is an abnormality in the field discharge switch, in the test scenario, the field discharge switch can be marked as an abnormal field discharge switch to wait for relevant personnel to handle it, such as: returning to the factory, scrapping, etc.

[0140] Figure 4 FIG. 400 is a block diagram of a dynamic test device for the opening and closing characteristics of a field discharge switch based on a supercapacitor and multi-channel synchronous recording according to an exemplary embodiment. The device includes: A control module 401, configured to control the operating state of the test motor and control a multi-channel synchronous recording device to collect waveform data of the test motor and the field discharge switch under different operating states of the test motor.

[0141] An acquisition module 402 is configured to acquire various first waveform data collected by the multi-channel synchronous waveform recording device for the test motor, where different first waveform data correspond to different operating states of the test motor. Acquire various second waveform data collected by the multi-channel synchronous waveform recording device for the field discharge switch, where different second waveform data correspond to different operating states of the test motor.

[0142] A determination module 403 is configured to determine prediction test information on the opening and closing characteristics of the field discharge switch according to the first waveform data and the second waveform data.

[0143] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0144] Figure 5 is a block diagram of an electronic device 500 shown according to an exemplary embodiment. As Figure 5 shown, the electronic device 500 may include: a processor 501, a memory 502. The electronic device 500 may further include one or more of a multimedia component 503, an input / output (I / O) interface 504, and a communication component 505.

[0145] Among them, the processor 501 is used to control the overall operation of the electronic device 500 to complete all or part of the steps in the above-mentioned dynamic test method for the opening and closing characteristics of the magnetic extinction switch based on supercapacitors and multi-channel synchronous recording. The memory 502 is used to store various types of data to support the operation of the electronic device 500. These data may include, for example, instructions for any application or method operating on the electronic device 500, as well as application-related data, such as contact data, received and sent messages, pictures, audio, video, and so on. The memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM for short), Electrically Erasable Programmable Read-Only Memory (EEPROM for short), Erasable Programmable Read-Only Memory (EPROM for short), Programmable Read-Only Memory (PROM for short), Read-Only Memory (ROM for short), magnetic memory, flash memory, magnetic disk, or optical disk. The multimedia component 503 may include a screen and an audio component. Among them, the screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signals can be further stored in the memory 502 or sent through the communication component 505. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 504 provides an interface between the processor 501 and other interface modules. The above-mentioned other interface modules can be a keyboard, a mouse, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 505 is used for wired or wireless communication between the electronic device 500 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC for short), 2G, 3G, or 4G, or a combination of one or more of them. Therefore, the corresponding communication component 505 may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0146] In an exemplary embodiment, the electronic device 500 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the above-mentioned dynamic test method for the opening and closing characteristics of the field discharge switch based on supercapacitors and multi-channel synchronous recording.

[0147] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-mentioned dynamic test method for the opening and closing characteristics of the field discharge switch based on supercapacitors and multi-channel synchronous recording are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 502 including program instructions, and the above program instructions may be executed by the processor 501 of the electronic device 500 to complete the above-mentioned dynamic test method for the opening and closing characteristics of the field discharge switch based on supercapacitors and multi-channel synchronous recording.

[0148] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program that can be executed by a processor. When the computer program is executed by the processor, the steps of the above-mentioned dynamic test method for the opening and closing characteristics of the field discharge switch based on supercapacitors and multi-channel synchronous recording are implemented.

Claims

1. A dynamic test method for the opening and closing characteristics of a field discharge switch based on synchronized waveform recording, characterized in that, The super capacitor (1) is electrically connected to the field discharge switch (2), the field discharge switch (2) is connected to the test motor (3), the test motor (3) is electrically connected to the drive system (5), the drive system (5) is communicatively connected to the upper computer (6), and the multi-channel synchronous recording device (4) is communicatively connected to the upper computer (6). The multi-channel synchronous recording device (4) collects waveform data during the operation of the test motor (3) and the field discharge switch (2). The test method includes: The upper computer (6) controls the drive system (5) to control the operating state of the test motor (3), and controls the multi-channel synchronous recording device (4) to collect waveform data of the test motor (3) and the field discharge switch (2) under different operating states of the test motor (3). Obtain a variety of first waveform data collected by the multi-channel synchronous recording device (4) for the test motor (3). Different first waveform data correspond to different operating states of the test motor (3). Obtain a variety of second waveform data collected by the multi-channel synchronous recording device (4) for the field discharge switch (2). Different second waveform data correspond to different operating states of the test motor (3). Based on the first waveform data and the second waveform data, determine the prediction test information of the opening and closing characteristics of the field discharge switch (2).

2. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized recording wave according to claim 1, wherein The upper computer (6) controls the drive system (5) to control the operating state of the test motor (3), and controls the multi-channel synchronous recording device (4) to collect waveform data of the test motor (3) and the field discharge switch (2) under different operating states of the test motor (3) specifically includes: Control the test motor (3) to be in a fault state. The fault state includes various types of faults, and control the multi-channel synchronous recording device (4) to collect waveform data of the test motor (3) and the field discharge switch (2) under different types of test motor fault states. Control the test motor (3) to be in a maintenance state. The maintenance state includes various types of maintenance, and control the multi-channel synchronous recording device (4) to collect waveform data of the test motor (3) and the field discharge switch (2) under different types of test motor maintenance states. Control the test motor (3) to be in a shutdown state, and control the multi-channel synchronous recording device (4) to collect waveform data of the test motor (3) and the field discharge switch (2) in the shutdown state.

3. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized recording wave according to claim 2, characterized in that, Among the various first waveform data, it includes waveform data corresponding to the fault state of the test motor (3), waveform data corresponding to the maintenance state of the test motor (3), and waveform data corresponding to the shutdown state of the test motor (3). A variety of second waveform data includes waveform data of the field discharge switch (2) corresponding to the fault state of the test motor (3), waveform data of the field discharge switch (2) corresponding to the maintenance state of the test motor (3), and waveform data of the field discharge switch (2) corresponding to the shutdown state of the test motor (3). The motor parameters involved in the waveform data corresponding to the fault state of the test motor (3) among the various first waveform data and the field discharge switch parameters involved in the waveform data of the field discharge switch (2) corresponding to the fault state of the test motor (3) among the various second waveform data belong to the same type. The motor parameters involved in the waveform data corresponding to the maintenance state of the test motor (3) among the multiple first waveform data are of the same type as the field discharge switch parameters involved in the waveform data of the field discharge switch (2) corresponding to the maintenance state of the test motor (3) among the multiple second waveform data; The motor parameters involved in the waveform data corresponding to the shutdown state of the test motor (3) among the multiple first waveform data are of the same type as the field discharge switch parameters involved in the waveform data of the field discharge switch (2) corresponding to the shutdown state of the test motor (3) among the multiple second waveform data.

4. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized recording wave according to claim 3, wherein Determining the on-off characteristic prediction test information of the field discharge switch (2) according to the first waveform data and the second waveform data specifically includes: Through a pre-trained first network model, respectively determine multiple predicted motor operating states according to the multiple first waveform data, wherein each first waveform data corresponds to one predicted motor operating state; According to the operating states of the test motor (3) corresponding to the multiple first waveform data and the predicted motor operating states, determine the first on-off characteristic prediction test information of the field discharge switch (2), and the first on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch (2) on the test motor (3); According to the first on-off characteristic prediction test information and the second waveform data, determine the second on-off characteristic prediction test information of the field discharge switch (2), and the second on-off characteristic prediction test information is used to characterize the negative impact of the on-off of the field discharge switch (2) on the field discharge switch (2); According to the first on-off characteristic prediction test information and the second on-off prediction characteristic test information, determine the target on-off characteristic prediction test information.

5. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized waveform recording according to claim 4, characterized in that, The super capacitor (1) is also electrically connected to the power parameter detection unit, and the first on-off characteristic prediction test information includes a first negative impact characteristic curve; Determining the second on-off characteristic prediction test information of the field discharge switch (2) according to the first on-off characteristic prediction test information and the second waveform data specifically includes: Determine the curve characteristics of the first negative impact characteristic curve according to the first on-off characteristic prediction test information; In the case where the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtain the power parameters collected by the power parameter detection unit; according to the power parameters and the second waveform data, determine the second on-off characteristic prediction test information of the field discharge switch (2); In the case where the curve characteristics of the first negative impact characteristic curve meet the preset curve characteristics, determine the second on-off characteristic prediction test information of the field discharge switch (2) according to the second waveform data.

6. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized waveform recording according to claim 5, wherein Determining the second on-off characteristic prediction test information of the field discharge switch (2) according to the power parameters and the second waveform data specifically includes: Through a pre-trained second network model, according to the power parameters and the second waveform data, determine the second on-off characteristic prediction test information of the field discharge switch (2), wherein the training data corresponding to the pre-trained second network model includes: power parameter samples, waveform data samples and prediction labels, and the waveform data samples include waveform data corresponding to different operating states of the test motor (3).

7. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized recording as claimed in claim 6, wherein The second on-off characteristic prediction test information described above includes a second negative impact characteristic curve. Based on the first on-off characteristic prediction test information and the second on-off characteristic prediction test information, the on-off characteristic prediction test information of the field discharge switch (2) is determined, including: Based on the first negative impact characteristic curve and the second negative impact characteristic curve, a target negative impact characteristic curve is determined; Obtain the preset on-off characteristic curve of the field discharge switch (2); Based on the target negative impact characteristic curve and the preset on-off characteristic curve, determine the target on-off characteristic prediction test information.

8. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized fault recording according to claim 7, wherein, The preset on-off characteristic curve includes the operating state of the test motor (3), current parameters, voltage parameters, and resistance parameters. The target negative impact characteristic curve includes negative impact values corresponding to various operating states of the test motor (3); Based on the target negative impact characteristic curve and the preset on-off characteristic curve, determine the target on-off characteristic prediction test information, including: Based on the negative impact values corresponding to various operating states of the test motor (3) included in the target negative impact characteristic curve, at least one of the current parameters, voltage parameters, and resistance parameters included in the preset on-off characteristic curve is transformed to obtain a transformed on-off characteristic curve; Based on the transformed on-off characteristic curve, determine the target on-off characteristic prediction test information.

9. The dynamic test method for the opening and closing characteristics of the field discharge switch based on synchronized waveform recording according to claim 8, characterized in that The test method further includes: Evaluate the performance of the field discharge switch according to the on-off characteristic prediction test information of the field discharge switch to obtain a performance evaluation result, and the performance evaluation result is used to characterize whether there is an abnormality in the field discharge switch; When the performance evaluation result is used to characterize that there is no abnormality in the field discharge switch, obtain the hardware information of the test motor and the hardware information of the super capacitor; Based on the on-off characteristic prediction test information of the field discharge switch, the hardware information of the test motor, and the hardware information of the super capacitor, determine the motor hardware information and power supply hardware information adapted to the field discharge switch.

10. A system using the dynamic testing method for the opening and closing characteristics of the field discharge switch based on synchronized recording wave according to any one of claims 1 to 9, characterized in that, The system includes a super capacitor (1), a field discharge switch (2), a test motor (3), a multi-channel synchronous recording device (4), a drive system (5), and a host computer (6); the host computer (6) is used to execute the test method.

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