Dynamic testing method and system for opening and closing characteristics of demagnetization switch based on synchronous recording

Abstract

The present invention provides a method and system for dynamic testing of the opening and closing characteristics of a demagnetization switch based on synchronous recording, which belongs to the field of switch testing technology. A test system is formed by a supercapacitor, a demagnetization 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 demagnetization switch under different operating conditions of the test motor, and the opening and closing characteristics test information of the demagnetization switch is determined by combining the multiple first waveform data corresponding to the test motor and the multiple second waveform data corresponding to the demagnetization switch. Through multi-channel synchronous recording technology, multiple signals can be directly detected, significantly improving the test efficiency; the supercapacitor can adjust the output current and simulate various working conditions of the demagnetization switch in actual operation, making the test results more practical and valuable for reference. Therefore, this technical solution can provide an efficient and accurate solution for the performance evaluation of the demagnetization switch.

Description

Technical Field

[0001] The present invention relates to the technical field of demagnetization switches, and in particular to a method and system for dynamically testing the opening and closing characteristics of a demagnetization switch based on a supercapacitor and multi-channel synchronous wave recording. Background Art

[0002] The deexcitation switch is a key device in the generator excitation system. Its primary function is to rapidly cut off the excitation current during normal motor shutdown or an emergency condition, transferring the rotor's magnetic field energy to the deexcitation resistor for rapid deexcitation. The performance of the deexcitation switch is directly related to the safe operation of the motor and excitation system. In particular, during an emergency trip, the deexcitation switch must rapidly arc and build voltage to ensure smooth transfer of rotor current to the nonlinear deexcitation resistor.

[0003] Existing detection methods mostly rely on a single voltage source or simple recording equipment, which makes it difficult to fully capture the dynamic characteristics of the demagnetization switch during the opening and closing process. Summary of the Invention

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

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A dynamic test method for the opening and closing characteristics of a demagnetization switch based on synchronous wave recording is provided. The supercapacitor is electrically connected to the demagnetization switch, which is connected to a test motor. The test motor is electrically connected to a drive system, which is in communication with a host computer. A multi-channel synchronous wave recording device is in communication with the host computer. The multi-channel synchronous wave recording device collects waveform data of the test motor and the demagnetization switch during operation.

[0007] Test methods include:

[0008] The host computer controls the drive system to control the operating state of the test motor, and controls the multi-channel synchronous recording equipment to collect waveform data of the test motor and the demagnetization switch under different test motor operating states;

[0009] Acquire a plurality of first waveform data collected by a multi-channel synchronous recording device on the test motor, wherein different first waveform data correspond to different operating states of the test motor;

[0010] Acquire multiple second waveform data collected by a multi-channel synchronous recording device on the demagnetization switch, where different second waveform data correspond to different operating states of the test motor;

[0011] Determine the opening and closing characteristic prediction test information of the demagnetization switch according to the first waveform data and the second waveform data.

[0012] Preferably, the host computer controls the driving 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 demagnetization switch under different operating states of the test motor. Specifically, the steps include:

[0013] Control the test motor to be in a fault state, which includes various types of faults, and control the multi-channel synchronous recording equipment to collect waveform data of the test motor and the demagnetization switch under different types of test motor fault states;

[0014] Control the test motor to be in the maintenance state, which includes various types of maintenance, and control the multi-channel synchronous recording equipment to collect waveform data of the test motor and demagnetization switch in different types of test motor maintenance states;

[0015] The test motor is controlled to be in a shutdown state, and the multi-channel synchronous recording equipment is controlled to respectively collect waveform data of the test motor and the demagnetization switch in the shutdown state.

[0016] Preferably, the plurality of first waveform data mentioned above include waveform data corresponding to a fault state of the test motor, waveform data corresponding to a maintenance state of the test motor, and waveform data corresponding to a shutdown state of the test motor;

[0017] A plurality of second waveform data, including waveform data corresponding to a demagnetization switch in a test motor fault state, waveform data corresponding to a test motor maintenance state demagnetization switch, and waveform data corresponding to a test motor shutdown state demagnetization switch;

[0018] The motor parameters involved in the waveform data corresponding to the motor fault state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the demagnetization switch test in the motor fault state test in the plurality of second waveform data are of the same type;

[0019] The motor parameters involved in the waveform data corresponding to the motor maintenance state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the demagnetization switch in the motor maintenance state test in the plurality of second waveform data are of the same type;

[0020] The motor parameters involved in the waveform data corresponding to the motor stop state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the motor stop state test in the plurality of second waveform data are of the same type.

[0021] Preferably, the above-mentioned determination of the opening and closing characteristic prediction test information of the demagnetization switch based on the first waveform data and the second waveform data specifically includes:

[0022] Determining a plurality of predicted motor operating states based on the plurality of first waveform data using a pre-trained first network model, wherein each first waveform data corresponds to a predicted motor operating state;

[0023] Determining first opening and closing characteristic prediction test information of the demagnetization switch according to the test motor operating states and the predicted motor operating states respectively corresponding to the plurality of first waveform data, wherein the first opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the test motor;

[0024] Determining second opening and closing characteristic prediction test information of the demagnetization switch based on the first opening and closing characteristic prediction test information and the second waveform data, wherein the second opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the demagnetization switch;

[0025] Target opening and closing characteristic test information is determined according to the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information.

[0026] Preferably, the supercapacitor is further electrically connected to a power parameter detection unit, and the first opening and closing characteristic prediction test information includes a first negative impact characteristic curve;

[0027] Determining second opening and closing characteristic prediction test information of the demagnetization switch according to the first opening and closing characteristic prediction test information and the second waveform data, specifically including:

[0028] Determining a curve feature of a first negative impact characteristic curve according to the first opening and closing characteristic prediction test information;

[0029] When the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtaining power parameters collected by the power parameter detection unit; determining second opening and closing characteristic test information of the demagnetization switch based on the power parameters and the second waveform data;

[0030] In a case where the curve characteristics of the first negative impact characteristic curve meet the preset curve characteristics, second opening and closing characteristic prediction test information of the demagnetization switch is determined according to the second waveform data.

[0031] Preferably, the above-mentioned determining the second opening and closing characteristic test information of the demagnetization switch based on the power supply parameters and the second waveform data specifically includes:

[0032] Through the pre-trained second network model, the second opening and closing characteristic prediction test information of the demagnetization switch is determined according to the power supply parameters and the second waveform data, wherein the training data corresponding to the pre-trained second network model includes: power supply parameter samples, waveform data samples and prediction labels, and the waveform data samples include waveform data corresponding to different test motor operating states.

[0033] Preferably, the second opening and closing characteristic prediction test information includes a second negative influence characteristic curve, and determining the demagnetization switch 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 includes:

[0034] determining a target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve;

[0035] Obtain the preset opening and closing characteristic curve of the demagnetization switch;

[0036] According to the target negative impact characteristic curve and the preset opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

[0037] Preferably, the above-mentioned preset opening and closing characteristic curve includes the test motor operating state, current parameters, voltage parameters and resistance parameters, and the target negative impact characteristic curve includes negative impact values ​​corresponding to multiple test motor operating states;

[0038] Determining target opening and closing characteristic prediction test information according to the target negative impact characteristic curve and the preset opening and closing characteristic curve includes:

[0039] transforming at least one parameter among current parameters, voltage parameters, and resistance parameters included in a preset opening and closing characteristic curve according to negative influence values ​​corresponding to a plurality of test motor operating states included in the target negative influence characteristic curve, to obtain a transformed opening and closing characteristic curve;

[0040] According to the transformed opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

[0041] Preferably, the above-mentioned testing method further comprises:

[0042] The performance of the demagnetization switch is evaluated based on the predicted test information of the demagnetization switch's opening and closing characteristics to obtain a performance evaluation result. The performance evaluation result is used to characterize whether the demagnetization switch has an abnormality;

[0043] The performance evaluation result is used to indicate that there is no abnormality in the demagnetization switch, and to obtain hardware information of the test motor and hardware information of the supercapacitor;

[0044] The test information, the hardware information of the test motor and the hardware information of the supercapacitor are predicted based on the opening and closing characteristics of the demagnetization switch, and the motor hardware information and power supply hardware information adapted to the demagnetization switch are determined.

[0045] A system using the above-mentioned method and system for dynamic testing of the opening and closing characteristics of a demagnetization switch based on synchronous recording includes a supercapacitor, a demagnetization 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.

[0046] The present invention relates to a method and system for dynamically testing the opening and closing characteristics of a demagnetization switch based on a supercapacitor and multi-channel synchronous recording. The system comprises a supercapacitor, a demagnetization 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 demagnetization switch under different operating conditions of the test motor. The waveform data corresponding to the various first waveform data of the test motor and the various second waveform data corresponding to the demagnetization switch are combined to determine predictive test information for the opening and closing characteristics of the demagnetization switch. The multi-channel synchronous recording technology allows for direct detection of multiple signals, significantly improving test efficiency. The supercapacitor can adjust the output current to simulate various operating conditions of the demagnetization switch in actual operation, making the test results more practical and valuable for reference. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention will be further described below with reference to the accompanying drawings and examples:

[0048] Figure 1 This is a structural block diagram of the dynamic testing system for the opening and closing characteristics of a demagnetization switch according to the present invention;

[0049] Figure 2 This is a flow chart of a method for dynamically testing the opening and closing characteristics of a demagnetization switch according to the present invention;

[0050] Figure 3 Schematic diagram of curve transformation in an embodiment of the present invention;

[0051] Figure 4 A block diagram of a dynamic testing device for the opening and closing characteristics of a demagnetization switch in an embodiment of the present invention;

[0052] Figure 5 4 is a block diagram of an electronic device in an embodiment of the present invention.

[0053] Among them: supercapacitor 1, demagnetization switch 2, test motor 3, multi-channel synchronous recording equipment 4, drive system 5, host computer 6, demagnetization switch opening and closing characteristics dynamic testing device 400, 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. DETAILED DESCRIPTION

[0054] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0055] Example 1:

[0056] A method and system for dynamically testing the opening and closing characteristics of a demagnetization switch based on synchronous wave recording, wherein a supercapacitor 1 is electrically connected to a demagnetization switch 2, which is connected to a test motor 3, which is electrically connected to a drive system 5, which is in communication with a host computer 6, and a multi-channel synchronous wave recording device 4 is in communication with the host computer 6. The multi-channel synchronous wave recording device 4 collects waveform data of the test motor 3 and the demagnetization switch 2 when they are in operation;

[0057] Test methods include:

[0058] The host 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 demagnetization switch 2 under different operating states of the test motor 3;

[0059] Acquire a plurality of first waveform data collected by the multi-channel synchronous recording device 4 on the test motor 3, wherein different first waveform data correspond to different operating states of the test motor 3;

[0060] Acquire multiple second waveform data collected by the multi-channel synchronous recording device 4 on the demagnetization switch 2, where different second waveform data correspond to different operating states of the test motor 3;

[0061] The opening and closing characteristic prediction test information of the demagnetization switch 2 is determined according to the first waveform data and the second waveform data.

[0062] The host 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 demagnetization switch 2 under different operating states of the test motor 3. Specifically, the following steps are performed:

[0063] Controlling the test motor 3 to be in a fault state, which includes various types of faults, and controlling the multi-channel synchronous recording device 4 to collect waveform data of the test motor 3 and the demagnetization switch 2 under different types of test motor fault states;

[0064] Control the test motor 3 to be in a maintenance state, which 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 demagnetization switch 2 in different types of test motor maintenance states;

[0065] The test motor 3 is controlled to be in a stop state, and the multi-channel synchronous recording device 4 is controlled to respectively collect waveform data of the test motor 3 and the demagnetization switch 2 in the stop state.

[0066] Preferably, the plurality of first waveform data include waveform data corresponding to a fault state of the test motor 3, waveform data corresponding to a maintenance state of the test motor 3, and waveform data corresponding to a shutdown state of the test motor 3;

[0067] A plurality of second waveform data, including waveform data corresponding to the demagnetization switch 2 of the test motor 3 in a fault state, waveform data corresponding to the demagnetization switch 2 of the test motor 3 in a maintenance state, and waveform data corresponding to the demagnetization switch 2 of the test motor 3 in a stop state;

[0068] The motor parameters involved in the waveform data corresponding to the fault state of the test motor 3 in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the demagnetization switch 2 in the fault state of the test motor 3 in the plurality of second waveform data are of the same type;

[0069] The motor parameters involved in the waveform data corresponding to the maintenance state of the test motor 3 in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the demagnetization switch 2 in the maintenance state of the test motor 3 in the plurality of second waveform data are of the same type;

[0070] The motor parameters involved in the waveform data corresponding to the test motor 3 in the stop state in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the test motor 3 in the stop state demagnetization switch 2 in the plurality of second waveform data are of the same type.

[0071] Preferably, the above-mentioned determination of the opening and closing characteristic prediction test information of the demagnetization switch 2 based on the first waveform data and the second waveform data specifically includes:

[0072] Determining a plurality of predicted motor operating states based on the plurality of first waveform data using a pre-trained first network model, wherein each first waveform data corresponds to a predicted motor operating state;

[0073] Determine first opening and closing characteristic prediction test information of the demagnetization switch 2 according to the operating states of the test motor 3 and the predicted motor operating states respectively corresponding to the plurality of first waveform data, wherein the first opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch 2 on the test motor 3;

[0074] Determine second opening and closing characteristic prediction test information of the demagnetization switch 2 based on the first opening and closing characteristic prediction test information and the second waveform data, where the second opening and closing characteristic prediction test information is used to characterize the negative impact of opening and closing of the demagnetization switch 2 on the demagnetization switch 2;

[0075] Target opening and closing characteristic test information is determined according to the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information.

[0076] Preferably, the supercapacitor 1 is also electrically connected to the power parameter detection unit, and the first opening and closing characteristic prediction test information includes a first negative impact characteristic curve.

[0077] Preferably, the above-mentioned determination of the second opening and closing characteristic prediction test information of the demagnetization switch 2 based on the first opening and closing characteristic prediction test information and the second waveform data specifically includes:

[0078] Determining a curve feature of a first negative impact characteristic curve according to the first opening and closing characteristic prediction test information;

[0079] When the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtaining the power supply parameters collected by the power supply parameter detection unit; determining the second opening and closing characteristic test information of the demagnetization switch 2 based on the power supply parameters and the second waveform data;

[0080] In a case where the curve characteristics of the first negative influence characteristic curve meet the preset curve characteristics, the second opening and closing characteristic prediction test information of the demagnetization switch 2 is determined according to the second waveform data.

[0081] Preferably, the above-mentioned determination of the second opening and closing characteristic test information of the demagnetization switch 2 based on the power supply parameters and the second waveform data specifically includes:

[0082] Through the pre-trained second network model, the second opening and closing characteristic prediction test information of the demagnetization switch 2 is determined according to the power supply parameters and the second waveform data, wherein the training data corresponding to the pre-trained second network model includes: power supply 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.

[0083] Preferably, the second opening and closing characteristic prediction test information includes a second negative influence characteristic curve, and determining the demagnetization switch 2 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 includes:

[0084] determining a target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve;

[0085] Obtaining a preset opening and closing characteristic curve of the demagnetization switch 2;

[0086] According to the target negative impact characteristic curve and the preset opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

[0087] Preferably, the above-mentioned preset opening and closing characteristic curve includes the operating state, current parameters, voltage parameters and resistance parameters of the test motor 3, and the target negative impact characteristic curve includes negative impact values ​​corresponding to multiple operating states of the test motor 3;

[0088] Determining target opening and closing characteristic prediction test information according to the target negative impact characteristic curve and the preset opening and closing characteristic curve includes:

[0089] According to the negative impact values ​​corresponding to the various operating states of the test motor 3 included in the target negative impact characteristic curve, at least one parameter among the current parameter, the voltage parameter and the resistance parameter included in the preset opening and closing characteristic curve is transformed to obtain a transformed opening and closing characteristic curve;

[0090] According to the transformed opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

[0091] Preferably, the above-mentioned testing method further comprises:

[0092] The performance of the demagnetization switch is evaluated based on the predicted test information of the opening and closing characteristics of the demagnetization switch 2 to obtain a performance evaluation result, which is used to indicate whether there is any abnormality in the demagnetization switch;

[0093] The performance evaluation result is used to indicate that there is no abnormality in the demagnetization switch, and to obtain hardware information of the test motor and hardware information of the supercapacitor;

[0094] The test information, the hardware information of the test motor and the hardware information of the supercapacitor are predicted based on the opening and closing characteristics of the demagnetization switch, and the motor hardware information and power supply hardware information adapted to the demagnetization switch are determined.

[0095] A system using the above-mentioned method and system for dynamic testing of the opening and closing characteristics of a demagnetization switch based on synchronous recording includes a supercapacitor 1, a demagnetization 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.

[0096] Example 2:

[0097] The deexcitation switch is a key device in the generator excitation system. Its primary function is to rapidly cut off the excitation current during normal motor shutdown or an emergency condition, transferring the rotor's magnetic field energy to the deexcitation resistor for rapid deexcitation. The performance of the deexcitation switch is directly related to the safe operation of the motor and excitation system. In particular, during an emergency trip, the deexcitation switch must rapidly arc and build voltage to ensure smooth transfer of rotor current to the nonlinear deexcitation resistor.

[0098] Existing detection methods mostly rely on a single voltage source or simple recording equipment, which makes it difficult to fully capture the dynamic characteristics of the demagnetization switch during the opening and closing process.

[0099] Based on this, the embodiment of the present disclosure provides a technical solution, which consists of a test system composed of a supercapacitor, a demagnetization 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 demagnetization switch under different test motor operating states respectively, and the test information of the opening and closing characteristics of the demagnetization switch is determined by combining the multiple first waveform data corresponding to the test motor and the multiple second waveform data corresponding to the demagnetization switch.

[0100] Through multi-channel synchronous recording technology, multiple signals can be directly detected, significantly improving test efficiency; supercapacitors can adjust the output current and simulate various working conditions of the demagnetization switch in actual operation, making the test results more practical and valuable for reference.

[0101] Therefore, this technical solution can provide an efficient and accurate solution for the performance evaluation of demagnetization switches.

[0102] Figure 1 FIG. 1 is a structural block diagram of a dynamic test system for opening and closing characteristics of a demagnetization switch based on supercapacitors and multi-channel synchronous wave recording according to an exemplary embodiment. Figure 1 As shown, the system includes: a super capacitor, a demagnetization switch, a test motor and a multi-channel synchronous recording device that are electrically connected in sequence.

[0103] Furthermore, the device further comprises: a host computer, which is communicatively connected with the multi-channel synchronous wave recording device and the driving system of the test motor respectively.

[0104] Multi-channel synchronous recording technology is an important technology used in power systems, industrial monitoring and other fields. It can collect and record waveform data of multiple channels in real time, providing key support for fault diagnosis, system analysis and operation optimization.

[0105] Regarding supercapacitors, they offer rapid charge and discharge capabilities: They can absorb and release large amounts of energy in a short period of time, making them suitable for applications requiring instantaneous high power output. High-precision voltage control: Through voltage sampling and analysis circuits and negative feedback control technology, they achieve high output voltage stability. Long life and high reliability: Supercapacitors can achieve charge and discharge cycle lifespans of up to hundreds of thousands of times, far exceeding those of traditional batteries. Excellent low-temperature performance: Some supercapacitors can operate in temperatures as low as -40°C, making them suitable for use in extreme environments.

[0106] Therefore, supercapacitors can be used as the power supply for the system to provide a stable test power supply for the demagnetization switch, ensuring the stability and adjustability of the current during the opening and closing process.

[0107] The test motor also needs to be configured with a drive system, which can drive the motor to operate, and the drive instructions of the drive system can come from the host computer.

[0108] The multi-channel synchronous recording equipment can simultaneously collect waveform data such as current and voltage of multiple channels to realize multi-channel synchronous recording; it has a high-speed communication interface to transmit the collected waveform data to the host computer in real time.

[0109] The sampling frequency of the multi-channel synchronous recording equipment shall not be less than 10kHz to ensure that the transient changes during the opening and closing process of the demagnetization switch can be captured.

[0110] Some multi-channel synchronous waveform recording equipment includes: a cache and control unit: Each channel is equipped with dual memories, such as memory A and memory B, which alternately store waveform data. A clock and transmission control center: This is responsible for the orderly extraction and transmission of data. A time synchronization mechanism, such as the FC-AE protocol, is used to synchronize master and slave clocks to ensure the time consistency of multi-channel data.

[0111] Based on the above hardware support, dynamic testing of the opening and closing characteristics of the demagnetization switch based on supercapacitors and multi-channel synchronous recording can be achieved.

[0112] I understand. Figure 1 The block diagram shown only involves key system components. The system may also include other components that can realize corresponding system functions, such as: protection circuits, monitoring circuits, etc., as well as various electrical connection components, etc., which are not introduced one by one here.

[0113] Figure 2 This is a flow chart showing a method for dynamic testing of the opening and closing characteristics of a demagnetization switch based on supercapacitors and multi-channel synchronous recording according to an exemplary embodiment. Figure 1 The host computer shown in FIG. 1 includes the following steps:

[0114] Step S21 , controlling the operating state of the test motor, and controlling a multi-channel synchronous recording device to respectively collect waveform data of the test motor and the demagnetization switch under different operating states of the test motor.

[0115] Step S22 , obtaining a plurality of first waveform data collected by a multi-channel synchronous recording device on the test motor, wherein different first waveform data correspond to different operating states of the test motor.

[0116] Step S23 , obtaining a plurality of second waveform data collected by a multi-channel synchronous recording device on the demagnetization switch, wherein different second waveform data correspond to different operating states of the test motor.

[0117] Step S24: Determine the opening and closing characteristic prediction test information of the demagnetization switch according to the first waveform data and the second waveform data.

[0118] The host computer sends 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 control of the operating state of the test motor.

[0119] The host computer sends a recording instruction to the multi-channel synchronous recording device, and then the multi-channel recording device performs multi-channel recording to enable the multi-channel synchronous recording device to collect waveform data of the test motor and the demagnetization switch under different test motor operating conditions.

[0120] It can be understood that the test motor can be controlled to operate in different operating states, and then waveform data under the corresponding operating states can be collected respectively.

[0121] Furthermore, after the host computer obtains the waveform data corresponding to different motor operating states, it combines these data to perform demagnetization switch opening and closing characteristics analysis.

[0122] In some embodiments, the operating state of the test motor is controlled, and a multi-channel synchronous recording device is controlled to collect waveform data of the test motor and the demagnetization switch under different operating states of the test motor. This may include: controlling the test motor to be in a fault state, which includes multiple types of fault states, and controlling the multi-channel synchronous recording device to collect waveform data of the test motor and the demagnetization switch under different types of test motor fault states; controlling the test motor to be in a maintenance state, which includes multiple types of maintenance states, and controlling the multi-channel synchronous recording device to collect waveform data of the test motor and the demagnetization 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 waveform data of the test motor and the demagnetization switch under normal shutdown state.

[0123] In this embodiment, the test motor operating state includes: a fault state, a maintenance state, and a normal shutdown state. In addition, the fault state and the maintenance state can each involve multiple types of states.

[0124] The demagnetization switch will perform different switching actions in the above three motor operating states. Therefore, the waveform data under these operating states can be collected.

[0125] Rapid de-excitation under fault conditions: When there is an internal fault in the motor or a fault at the output end, the de-excitation switch quickly cuts off the excitation power supply to prevent overvoltage and overcurrent from damaging the motor windings.

[0126] Safety isolation during maintenance: When the motor is being maintained, disconnecting the demagnetization switch forms an obvious disconnection point to ensure the safety of maintenance personnel.

[0127] Auxiliary deexcitation under normal shutdown state: During normal shutdown, the deexcitation switch is usually not disconnected directly, but inverter deexcitation is performed through the automatic excitation regulator.

[0128] Different types of fault states may correspond to different fault causes, and different types of maintenance states may correspond to different maintenance methods.

[0129] The multiple types of first waveform data include waveform data corresponding to a fault state of the test motor, waveform data corresponding to a maintenance state of the test motor, and waveform data corresponding to a normal shutdown state of the test motor.

[0130] The multiple types of second waveform data include waveform data corresponding to a fault state of the test motor, waveform data corresponding to a maintenance state of the test motor, and waveform data corresponding to a normal shutdown state of the test motor.

[0131] The motor parameters involved in the waveform data corresponding to the test motor fault state included in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the test motor fault state included in the plurality of second waveform data are parameters of the same type.

[0132] Parameters of the same type can be: voltage, current, resistance, etc.

[0133] The motor parameters involved in the waveform data corresponding to the test motor maintenance state included in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the test motor maintenance state included in the plurality of second waveform data belong to different types of parameters.

[0134] For example, motor parameters may be voltage and current, etc.; demagnetization switch parameters may be opening and closing time, resistance, etc.

[0135] In some embodiments, the motor parameters involved in the waveform data corresponding to the normal stop state of the test motor included in the multiple first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the normal stop state of the test motor included in the multiple second waveform data belong to different types of parameters.

[0136] Motor parameters can be voltage and current, etc.; demagnetization switch parameters can be: opening and closing time, resistance, etc.

[0137] In some embodiments, when multiple motor parameters are involved, the multi-channel synchronous recording device can generate corresponding waveform data for each of the multiple motor parameters. When multiple demagnetization switch parameters are involved, the multi-channel synchronous recording device can generate corresponding waveform data for each of the multiple demagnetization switch parameters.

[0138] The demagnetization switch may include multiple switch ports, and the multiple switch ports may respectively correspond to different waveform data.

[0139] Therefore, in step S22, a variety of first waveform data collected by the multi-channel synchronous recording device on the test motor can be obtained, and different first waveform data correspond to different test motor operating states. In addition, the various first waveform data may include waveforms corresponding to different motor parameters.

[0140] Furthermore, in step S23, a plurality of second waveform data collected by the multi-channel synchronous recording device for the demagnetization switch can be obtained, wherein different second waveform data correspond to different operating states of the test motor. Furthermore, the various second waveform data may include waveforms corresponding to different demagnetization switch parameters.

[0141] Furthermore, in step S24, the opening and closing characteristic prediction test information of the demagnetization switch is determined based on the first waveform data and the second waveform data.

[0142] As an optional implementation, step S24 includes: determining multiple predicted motor operating states based on multiple first waveform data through a pre-trained first network model, wherein each type of first waveform data corresponds to a predicted motor operating state; determining the first opening and closing characteristic prediction test information of the demagnetization switch based on the test motor operating states and the predicted motor operating states corresponding to the multiple first waveform data, the first opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the motor; determining the second opening and closing characteristic prediction test information of the demagnetization switch based on the first opening and closing characteristic prediction test information and the second waveform data, the second opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the demagnetization switch; determining the target opening and closing characteristic prediction test information based on the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information.

[0143] In this embodiment, the opening and closing characteristics of the demagnetization switch are first analyzed from the dimension of motor operation to obtain first opening and closing characteristic prediction test information characterizing the negative impact of the opening and closing of the demagnetization switch on the motor.

[0144] The pre-trained first network model may be an integrated model consisting of a one-dimensional convolutional neural network and a large language model.

[0145] Among them, a one-dimensional convolutional neural network is used to process the waveform data and encode it into text features that can be processed by a large language model. The large language model is used to predict the motor operating status based on the encoded text features.

[0146] Regarding one-dimensional convolutional neural networks, 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; W is the weight matrix of the convolution kernel or filter; x is the input feature vector, that is, the waveform data; and b is the bias term.

[0147] In a one-dimensional convolutional neural network, the convolution kernel W slides along the time dimension of the input feature vector x to perform the convolution operation. Specifically, for each time step t of the input feature vector x, the convolution kernel W performs a dot product operation with a subsequence of x, then adds a bias term b, and finally passes through the activation function f to obtain the corresponding element of the output feature vector y.

[0148] To illustrate with a specific example, assuming that the length of the input feature vector x is n and the length of the convolution kernel W is k, then the length of the output feature vector y is n-k+1, without considering the border filling.

[0149] In practical applications, one-dimensional convolutional neural networks typically consist of multiple convolutional layers, each of which contains multiple convolution kernels. This allows them to extract multiple features from the input waveform data. Furthermore, one-dimensional convolutional neural networks can be combined with pooling layers, such as max pooling or average pooling, to reduce the dimensionality of the feature vector and extract more abstract features.

[0150] By using a one-dimensional convolutional neural network as a text encoder, the features corresponding to the waveform data can be extracted based on the waveform data.

[0151] Regarding large language models, the following key components can be included:

[0152] Word embedding: Word embedding is a technique for mapping words into a continuous vector space to capture the semantic relationship between words. Common methods include Word2Vec and GloVe:

[0153] Word2Vec: CBOW continuous bag-of-words model: predicts the central word given the context. Skip-Gram: predicts the context given the central word; training objectives:

[0154] ;

[0155] 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 given current word w t When predicting the next word wt+1 and the previous word w t-1 probability;

[0156] GloVe: Learn word embeddings through matrix decomposition tasks, training objectives:

[0157] ;

[0158] in, X is the word vector matrix, Y is the context vector matrix, is a word pair ( u , v ) similarity, P( y u ∣ x u ) represents a given feature x u Time Tags y u The probability of is a conditional probability.

[0159] Self-Attention Mechanism: The self-attention mechanism is the core of the Transformer architecture, allowing the model to establish long-distance dependencies between different time steps; the calculation formula is:

[0160] ;

[0161] in, Q is the query vector, K is the key vector, V is a value vector, d k is the dimension of the key vector.

[0162] Transformer architecture: Transformer is the core architecture of large language models, which implements efficient sequence modeling through self-attention mechanism and encoder-decoder structure. Main components:

[0163] Multi-Head Attention: A parallel self-attention mechanism that allows the model to focus on multiple different contexts simultaneously.

[0164] Positional Encoding: It is used to represent the position information in the sequence. Since Transformer has no sequence structure, it is necessary to capture the sequence structure through positional encoding.

[0165] Residual Connection: Retains the previous input of each layer to speed up the training process.

[0166] Layer Normalization: Normalize the output of the model to reduce overfitting.

[0167] These technologies and formulas are the basis of large language models, but actual large language models, such as GPT and LLaMA, will conduct large-scale pre-training on this basis and improve performance through complex optimization and fine-tuning.

[0168] The training data of the pre-trained first network model may include: sample waveform data corresponding to motor operating parameters, features corresponding to the sample waveform data, and motor operating status labels. The training data may be obtained through actual measurement or simulation testing.

[0169] Specifically, a one-dimensional convolutional neural network is trained using sample waveform data corresponding to motor operating parameters and the text features associated with the sample waveform data, enabling it to encode text. Next, a large language model is trained using the motor operating status label and the text features associated with the sample waveform data, enabling the large language model to predict the motor operating status label based on the text features.

[0170] In addition, in order to improve the prediction accuracy of the large language model, the text features encoded by the one-dimensional convolutional neural network can be used as additional training data for the large language model.

[0171] By inputting each type of first waveform data into the pre-trained first network model, a 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.

[0172] Furthermore, the test motor operating states corresponding to the plurality of first waveform data may be compared with the predicted motor operating states to obtain first opening and closing characteristic prediction test information.

[0173] In some embodiments, the first opening and closing characteristic prediction test information may include a first negative impact characteristic curve, and the first negative impact characteristic curve may represent negative impact values ​​corresponding to a plurality of first waveform data.

[0174] 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.

[0175] Furthermore, based on the first opening and closing characteristic prediction test information and the second waveform data, analysis is performed from the dimension of the demagnetization switch to obtain the second opening and closing characteristic prediction test information to characterize the negative impact of the opening and closing of the demagnetization switch on the demagnetization switch.

[0176] In some embodiments, the supercapacitor is further electrically connected to a power parameter detection unit, which can detect supercapacitor parameters, such as discharge capacity, rated voltage, etc. The implementation of this detection unit can refer to mature technologies in the art.

[0177] In some embodiments, when the first opening and closing characteristic prediction test information includes a first negative influence characteristic curve, determining the second opening and closing characteristic prediction test information of the demagnetization switch according to the first opening and closing characteristic prediction test information and the second waveform data may include:

[0178] Determine the curve characteristics of the first negative influence characteristic curve based on the first opening and closing characteristic prediction test information; when the curve characteristics of the first negative influence characteristic curve do not meet the preset curve characteristics, obtain the power supply parameters collected by the power supply parameter detection unit; determine the second opening and closing characteristic prediction test information of the demagnetization switch based on the power supply parameters and the second waveform data; when the curve characteristics of the first negative influence characteristic curve meet the preset curve characteristics, determine the second opening and closing characteristic prediction test information of the demagnetization switch based on the second waveform data.

[0179] In some embodiments, the curve feature of the first negative impact characteristic curve may be the curvature of the curve, the Z parameter of the curve, etc.

[0180] In some embodiments, the preset curve feature may be a curve feature indicating that there is no negative impact or a very small negative impact on the motor parameters. For example, all negative impact values ​​on the curve are 1, or only a few negative impact values ​​are 0.

[0181] Furthermore, when the preset curve characteristics are not met, the opening and closing characteristics of the demagnetization switch can be further analyzed in combination with the power supply parameters and the second waveform data.

[0182] When the preset curve characteristics are met, the second opening and closing characteristic prediction test information of the demagnetization switch can be determined based only on the second waveform data.

[0183] In some embodiments, the second opening and closing characteristic prediction test information of the demagnetization switch is determined based on the power supply parameters and the second waveform data, including: using a pre-trained second network model, the second opening and closing characteristic prediction test information of the demagnetization switch is determined based on the power supply parameters and the second waveform data, wherein the training data corresponding to the pre-trained second network model includes: power supply parameter samples, waveform data samples and prediction labels, and the waveform data samples include waveform data corresponding to different motor operating states.

[0184] In this embodiment, the pre-trained second network model needs to be processed based on waveform data. Therefore, the model architecture of the second network model can be the same as the model architecture of the first network model, but the model parameters of the first network model and the model parameters of the second network model are different. Therefore, the embodiment of the model network is not repeated here.

[0185] In some embodiments, the training data corresponding to the pre-trained second network model includes: power supply parameter samples, waveform data samples and prediction labels. The prediction label can be the negative impact value of the demagnetization switch. The waveform data sample includes waveform data corresponding to different motor operating states, and the waveform data involves the demagnetization switch parameters.

[0186] In some embodiments, the power supply parameters and the second waveform data are input into a pre-trained second network model to obtain second opening and closing characteristic prediction test information output by the second network model.

[0187] In some embodiments, determining the second opening and closing characteristic prediction test information of the demagnetization switch based on the second waveform data may include: inputting the second waveform data into a pre-trained second network model to obtain the second opening and closing characteristic prediction test information output by the second network model.

[0188] Alternatively, the second waveform data is compared with preset standard waveform data to obtain second opening and closing characteristic prediction test information.

[0189] In some embodiments, the second opening and closing characteristic prediction test information includes a second negative impact characteristic curve, and the second negative impact characteristic curve can represent negative impact values ​​corresponding to a plurality of second waveform data.

[0190] In some embodiments, the greater the difference between the second waveform data and the preset standard waveform data, the greater the negative impact value.

[0191] In some embodiments, the negative impact value may be limited to a specific impact value range, such as 0-1.

[0192] Furthermore, in the case where the first opening and closing characteristic prediction test information includes a first negative influence characteristic curve, and the second opening and closing characteristic prediction test information includes a second negative influence characteristic curve, determining the target opening and closing characteristic prediction test information based on the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information may include: determining the target negative influence characteristic curve based on the first negative influence characteristic curve and the second negative influence characteristic curve; obtaining the preset opening and closing characteristic curve of the demagnetization switch; and determining the target opening and closing characteristic prediction test information based on the target negative influence characteristic curve and the preset opening and closing characteristic curve.

[0193] In this embodiment, a weighted average of the negative impact values ​​represented by the first negative impact characteristic curve and the second negative impact characteristic curve may be performed to obtain a target negative impact value.

[0194] In some embodiments, a weighted average is performed on the negative impact values ​​corresponding to the same test motor operating state.

[0195] In some embodiments, the target negative impact characteristic curve represents the target negative impact value corresponding to each test motor operating state.

[0196] In some embodiments, the preset opening and closing characteristic curve includes: motor operating state, current parameters, voltage parameters and resistance parameters.

[0197] In some embodiments, target opening and closing characteristic prediction test information is determined based on the target negative impact characteristic curve and the preset opening and closing characteristic curve, including: according to the negative impact values ​​corresponding to the multiple test motor operating states included in the target negative impact characteristic curve, at least one parameter among the time parameters, current parameters, voltage parameters and resistance parameters included in the preset opening and closing characteristic curve is transformed to obtain the transformed opening and closing characteristic curve; based on the transformed opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

[0198] In some embodiments, demagnetization switch parameter transformation methods corresponding to different negative impact values ​​under different motor operating states are pre-configured. Based on the pre-configured transformation methods, parameter changes can be performed to obtain the transformed opening and closing characteristic curve.

[0199] For example, in a fault state, the demagnetization switch is quickly disconnected, so the current and voltage parameters decrease rapidly, while the resistance parameter increases rapidly. However, in the presence of negative impact values, the minimum values ​​of the current and voltage parameters cannot reach the ideal values, or cannot reach the ideal values ​​quickly. Therefore, the slope and peak-valley of the current and voltage parameter curves can be transformed.

[0200] For example, in the maintenance state, the demagnetization switch has a clear disconnection point, so there will be specific parameters corresponding to the disconnection point. However, in the case of negative impact values, the disconnection point may be delayed or have other conditions, so the specific point of the relevant parameter curve can be offset.

[0201] For example, in a normal shutdown state, the demagnetization switch does not cut off immediately, but cuts off at a normal speed, so the changes in current parameters, voltage parameters, and resistance parameters are relatively slow. However, in the presence of negative impact values, the changes in these parameters may be different, so the curvature of the change curve of the relevant parameters can be changed.

[0202] It can be understood that when the transformation is performed, the transformation is performed according to the same motor operating state.

[0203] And, it can be understood that in each parameter curve, changes are made based on time sequence.

[0204] Figure 3 is a schematic diagram showing a curve transformation according to an exemplary embodiment, such as Figure 3 As shown, in Figure 3 The preset opening and closing characteristic curve can involve any one or more variation curves of current, voltage, and resistance. Only one variation curve is shown in the figure. The variation curve changes over time. When changing the curve, the slope of the curve can be changed; the peaks and troughs of the curve can be changed; and specific parameter points can be changed.

[0205] 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 both can be configured in advance through offline testing or simulation testing.

[0206] Furthermore, based on the transformed opening and closing characteristic curve, target opening and closing characteristic prediction test information is determined.

[0207] In some embodiments, the preset opening and closing characteristic curve is a characteristic curve, but it is not dynamic. Therefore, after transformation, dynamic characteristic testing is achieved. Thus, the transformed opening and closing characteristic curve can be directly used to determine the target opening and closing characteristic prediction test information.

[0208] Alternatively, the variation characteristics of various parameters may be statistically analyzed based on the curve, and the characteristics may be integrated with the curve to form target opening and closing characteristic prediction test information.

[0209] Furthermore, the information on the prediction test of the opening and closing characteristics of the demagnetization switch can also be applied.

[0210] As an optional implementation, the method also includes: evaluating the performance of the demagnetization switch based on the test information predicting the opening and closing characteristics of the demagnetization switch to obtain a performance evaluation result, and the performance evaluation result is used to characterize whether there is an abnormality in the demagnetization switch; when the performance evaluation result is used to characterize that there is no abnormality in the demagnetization switch, obtaining the hardware information of the test motor and the hardware information of the supercapacitor; determining the motor hardware information and power supply hardware information adapted to the demagnetization switch based on the test information predicting the opening and closing characteristics of the demagnetization switch, the hardware information of the test motor and the hardware information of the supercapacitor.

[0211] In this embodiment, there are many ways to evaluate the performance of the demagnetization switch, for example, evaluation through artificial intelligence; evaluation through comparison with big data, etc. For details, reference can be made to mature technologies in this field.

[0212] In some embodiments, the performance evaluation result is used to characterize whether the demagnetization switch has an abnormality, and may also involve a specific abnormality type, such as a disconnection abnormality, a demagnetization resistance abnormality, etc.

[0213] In some embodiments, when the performance evaluation result is used to indicate that there is no abnormality in the demagnetization switch, hardware information of the test motor and hardware information of the supercapacitor are obtained.

[0214] Furthermore, the test information, the hardware information of the test motor, and the hardware information of the supercapacitor can be predicted based on the opening and closing characteristics of the demagnetization switch to determine the motor hardware information and power supply hardware information adapted to the demagnetization switch.

[0215] In this embodiment, the demagnetization switch's opening and closing characteristic prediction test information, the test motor's hardware information, and the supercapacitor's hardware information can be associated, and the test motor's hardware information and the supercapacitor's hardware information can be expanded accordingly to obtain an adaptation relationship, i.e., to determine the motor hardware information and power supply hardware information adapted to the demagnetization switch.

[0216] For example, the rated power of the tested motor can be adaptively reduced or increased to obtain an adapted rated power of the motor.

[0217] For example, based on the discharge capacity of the supercapacitor, the discharge capacity can be adaptively reduced or increased to obtain an adapted supercapacitor discharge capacity.

[0218] Furthermore, the obtained motor hardware information and power supply hardware information adapted to the demagnetization switch can be used for subsequent application of the demagnetization switch and selection of appropriate application scenarios.

[0219] In some embodiments, when the performance evaluation result is used to characterize an abnormality in the demagnetization switch, the demagnetization switch can be marked as an abnormal demagnetization switch in the test scenario, waiting for relevant personnel to handle it, such as returning it to the factory, scrapping it, etc.

[0220] Figure 4 1 is a block diagram showing a device 400 for dynamically testing the opening and closing characteristics of a demagnetization switch based on a supercapacitor and multi-channel synchronous waveform recording according to an exemplary embodiment. The device includes:

[0221] The control module 401 is used 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 demagnetization switch under different operating states of the test motor.

[0222] Acquisition module 402 is configured to acquire a plurality of first waveform data items collected by the multi-channel synchronous recording device on the test motor, wherein different first waveform data items correspond to different operating states of the test motor. Acquisition module 402 is configured to acquire a plurality of second waveform data items collected by the multi-channel synchronous recording device on the demagnetization switch, wherein different second waveform data items correspond to different operating states of the test motor.

[0223] The determination module 403 is configured to determine the opening and closing characteristic prediction test information of the demagnetization switch according to the first waveform data and the second waveform data.

[0224] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0225] Figure 5 FIG. 5 is a block diagram of an electronic device 500 according to an exemplary embodiment. Figure 5 As shown, the electronic device 500 may include: a processor 501 , a memory 502 , and may further include one or more of a multimedia component 503 , an input / output (I / O) interface 504 , and a communication component 505 .

[0226] 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 method for dynamically testing the opening and closing characteristics of a demagnetizing switch based on supercapacitors and multi-channel synchronous waveform recording. The memory 502 is used to store various types of data to support the operation of the electronic device 500. For example, this data may include instructions for any application or method operating on the electronic device 500, as well as application-related data, such as contact information, sent and received messages, pictures, audio, video, etc. 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), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 503 may include a screen and an audio component. The screen may 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 for receiving external audio signals. The received audio signal may 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 may be a keyboard, a mouse, buttons, etc. These buttons may 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), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 505 may include: a Wi-Fi module, a Bluetooth module, an NFC module.

[0227] In an exemplary embodiment, the electronic device 500 can 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 to perform the above-mentioned dynamic test method for the opening and closing characteristics of a demagnetization switch based on supercapacitors and multi-channel synchronous recording.

[0228] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When executed by a processor, the program instructions implement the steps of the above-described method for dynamically testing the opening and closing characteristics of a demagnetization switch based on a supercapacitor and multi-channel synchronous waveform recording. For example, the computer-readable storage medium may be the aforementioned memory 502 including the program instructions. The program instructions may be executed by the processor 501 of the electronic device 500 to perform the above-described method for dynamically testing the opening and closing characteristics of a demagnetization switch based on a supercapacitor and multi-channel synchronous waveform recording.

[0229] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a processor, and when the computer program is executed by the processor, the steps of the above-mentioned dynamic testing method of the opening and closing characteristics of the demagnetization 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 demagnetization switch based on synchronous wave recording, characterized in that: The supercapacitor is electrically connected to the demagnetization switch, the demagnetization 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 host computer, the multi-channel synchronous wave recording device is communicatively connected to the host computer, and the multi-channel synchronous wave recording device collects waveform data of the test motor and the demagnetization switch when they are running; Test methods include: The host computer controls the drive system to control the operating state of the test motor and controls the multi-channel synchronous recording equipment to collect waveform data of the test motor and demagnetization switch under different test motor operating states; the test motor operating states include: fault state, maintenance state and normal shutdown state; Acquire a plurality of first waveform data collected by a multi-channel synchronous recording device on the test motor, wherein different first waveform data correspond to different operating states of the test motor; the plurality of first waveform data include waveform data corresponding to a fault state of the test motor, waveform data corresponding to a maintenance state of the test motor, and waveform data corresponding to a shutdown state of the test motor; Acquire multiple second waveform data of the demagnetization switch collected by the multi-channel synchronous recording device, where different second waveform data correspond to different operating states of the test motor; the multiple second waveform data include waveform data corresponding to the demagnetization switch in the fault state of the test motor, waveform data corresponding to the demagnetization switch in the maintenance state of the test motor, and waveform data corresponding to the demagnetization switch in the shutdown state of the test motor; Determining the demagnetization switch opening and closing characteristic prediction test information based on the first waveform data and the second waveform data; specifically including: Determining a plurality of predicted motor operating states based on the plurality of first waveform data using a pre-trained first network model, wherein each first waveform data corresponds to a predicted motor operating state; Determining first opening and closing characteristic prediction test information of the demagnetization switch according to the test motor operating states and the predicted motor operating states respectively corresponding to the plurality of first waveform data, wherein the first opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the test motor; Determining second opening and closing characteristic prediction test information of the demagnetization switch based on the first opening and closing characteristic prediction test information and the second waveform data, wherein the second opening and closing characteristic prediction test information is used to characterize the negative impact of the opening and closing of the demagnetization switch on the demagnetization switch; Target opening and closing characteristic prediction test information is determined according to the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information.

2. The method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to claim 1 is characterized in that: The host computer control drive system controls 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 demagnetization switch under different test motor operating states. Specifically, the following steps are performed: Control the test motor to be in a fault state, which includes various types of faults, and control the multi-channel synchronous recording equipment to collect waveform data of the test motor and the demagnetization switch under different types of test motor fault states; Control the test motor to be in the maintenance state, which includes various types of maintenance, and control the multi-channel synchronous recording equipment to collect waveform data of the test motor and demagnetization switch in different types of test motor maintenance states; The test motor is controlled to be in a shutdown state, and the multi-channel synchronous recording equipment is controlled to respectively collect waveform data of the test motor and the demagnetization switch in the shutdown state.

3. The method for dynamic testing of demagnetization switch opening and closing characteristics based on synchronous wave recording according to claim 2 is characterized in that: The motor parameters involved in the waveform data corresponding to the motor fault state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the motor fault state test in the plurality of second waveform data are of the same type; The motor parameters involved in the waveform data corresponding to the motor maintenance state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the demagnetization switch in the motor maintenance state test in the plurality of second waveform data are of the same type; The motor parameters involved in the waveform data corresponding to the motor stop state test in the plurality of first waveform data and the demagnetization switch parameters involved in the waveform data corresponding to the motor stop state test in the plurality of second waveform data are of the same type.

4. The method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to claim 3 is characterized in that: The supercapacitor is also electrically connected to the power parameter detection unit, and the first opening and closing characteristic prediction test information includes a first negative impact characteristic curve; The determining of the second opening and closing characteristic prediction test information of the demagnetization switch based on the first opening and closing characteristic prediction test information and the second waveform data specifically includes: Determining a curve feature of a first negative impact characteristic curve according to the first opening and closing characteristic prediction test information; When the curve characteristics of the first negative impact characteristic curve do not meet the preset curve characteristics, obtaining power parameters collected by the power parameter detection unit; determining the second opening and closing characteristic prediction test information of the demagnetization switch based on the power parameters and the second waveform data; In a case where the curve characteristics of the first negative impact characteristic curve meet the preset curve characteristics, second opening and closing characteristic prediction test information of the demagnetization switch is determined according to the second waveform data.

5. The method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to claim 4 is characterized in that: The determining of the second opening and closing characteristic prediction test information of the demagnetization switch based on the power supply parameters and the second waveform data specifically includes: Through the pre-trained second network model, the second opening and closing characteristic prediction test information of the demagnetization switch is determined according to the power supply parameters and the second waveform data, wherein the training data corresponding to the pre-trained second network model includes: power supply parameter samples, waveform data samples and prediction labels, and the waveform data samples include waveform data corresponding to different test motor operating states.

6. The method for dynamic testing of demagnetization switch opening and closing characteristics based on synchronous wave recording according to claim 5 is characterized in that: The second opening and closing characteristic prediction test information includes a second negative influence characteristic curve. Determining the demagnetization switch opening and closing characteristic prediction test information based on the first opening and closing characteristic prediction test information and the second opening and closing characteristic prediction test information includes: determining a target negative impact characteristic curve according to the first negative impact characteristic curve and the second negative impact characteristic curve; Obtain the preset opening and closing characteristic curve of the demagnetization switch; According to the target negative impact characteristic curve and the preset opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

7. The method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to claim 6 is characterized in that: The preset opening and closing characteristic curve includes the test motor operating state, current parameters, voltage parameters and resistance parameters, and the target negative impact characteristic curve includes the negative impact values ​​corresponding to the various test motor operating states; Determining target opening and closing characteristic prediction test information according to the target negative impact characteristic curve and the preset opening and closing characteristic curve includes: transforming at least one parameter among current parameters, voltage parameters, and resistance parameters included in a preset opening and closing characteristic curve according to negative influence values ​​corresponding to a plurality of test motor operating states included in the target negative influence characteristic curve, to obtain a transformed opening and closing characteristic curve; According to the transformed opening and closing characteristic curve, the target opening and closing characteristic prediction test information is determined.

8. The method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to claim 7 is characterized in that: The testing method further comprises: The performance of the demagnetization switch is evaluated based on the predicted test information of the demagnetization switch's opening and closing characteristics to obtain a performance evaluation result. The performance evaluation result is used to characterize whether the demagnetization switch has an abnormality; The performance evaluation result is used to indicate that there is no abnormality in the demagnetization switch, and to obtain hardware information of the test motor and hardware information of the supercapacitor; The test information, the hardware information of the test motor and the hardware information of the supercapacitor are predicted based on the opening and closing characteristics of the demagnetization switch, and the motor hardware information and power supply hardware information adapted to the demagnetization switch are determined.

9. A system using the method for dynamic testing of opening and closing characteristics of a demagnetization switch based on synchronous wave recording according to any one of claims 1 to 8, characterized in that: The system includes a supercapacitor, a demagnetization 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.

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