Method, system and device for extracting electromagnetic pulse signal of IGBT switch of flexible direct current valve submodule and medium

Abstract

The present application belongs to the technical field of health state monitoring of flexible direct current valve sub-modules, and discloses a method, system, device and medium for extracting electromagnetic pulse signals of IGBT switches of flexible direct current valve sub-modules, to solve the problems of loss of pulse rising edge, improper interception length, inability to adapt to variable noise and disorder of probe direction caused by the existing single threshold method. The method comprises: acquiring continuous voltage signals by an electromagnetic pulse probe and performing discrete sampling; generating an energy envelope curve through sliding window absolute value low-pass smoothing; adaptively calculating double thresholds based on background noise statistical characteristics; when the envelope curve exceeds the high threshold, determining the starting point through left backtracking, determining the termination point through right maintenance confirmation window, and extracting complete pulses; using the asymmetric law that IGBT turn-on is faster than turn-off, calibrating the probe polarity through the rising time of the cumulative integral curve of adjacent pulses, and classifying the pulses into turn-on or turn-off signals accordingly.

Description

Technical Field

[0001] This invention belongs to the field of health status monitoring technology for flexible DC converter valve submodules, specifically relating to the method, system, equipment, and medium for extracting electromagnetic pulse signals from IGBT switching in flexible DC converter valve submodules. Background Technology

[0002] In flexible DC transmission technology, the converter valve submodule is the core unit constituting the converter. In actual engineering projects, a converter station is typically composed of hundreds or thousands of cascaded submodules, and the health status of a single submodule directly affects the safe and stable operation of the entire transmission system. Therefore, accurate condition assessment and early fault diagnosis of submodules are of significant engineering importance.

[0003] During the turn-on and turn-off processes, the IGBT devices inside the submodule generate drastic voltage and current changes, which in turn radiate electromagnetic pulse signals into space. Research shows that these electromagnetic pulse signals contain rich characteristic information about the IGBT switching process and can effectively reflect the health status of the devices. Therefore, analyzing these electromagnetic pulse signals to infer the operating state of the IGBTs has become a feasible technical approach.

[0004] However, IGBTs operate at high frequencies during long-term operation, and electromagnetic pulse probes continuously acquire massive amounts of signals in the form of transient pulses over long periods. Whether using expert systems for feature identification or artificial intelligence models such as deep learning for state assessment, it is essential to first accurately segment and extract each individual pulse signal from the continuous signal stream. This plays a fundamental role in the accuracy of subsequent analysis.

[0005] In existing technologies, the segmentation and extraction of electromagnetic pulse signals mainly employs a single threshold triggering method. This method has significant technical drawbacks: First, recording only begins when the signal amplitude reaches a preset threshold, resulting in the loss of pulse rise edge information, which precisely contains the key characteristics of the IGBT turn-on process. Second, the turn-on and turn-off pulses exhibit opposite trends in their time-domain waveform changes and have different durations, making it difficult for a single threshold to automatically adapt to the different durations of the two pulses, easily leading to inappropriate truncation lengths. Third, the background electromagnetic noise intensity of the flexible DC converter valve submodule varies significantly under different operating conditions, and the current magnitude during IGBT switching also directly affects the amplitude of the induced signal. A fixed threshold cannot adapt to these variations, leading to easy false triggering in low-noise environments and easy missed triggering in high-noise environments. Summary of the Invention

[0006] Based on the aforementioned shortcomings and deficiencies in the prior art, one of the objectives of this invention is to at least solve one or more of the aforementioned problems in the prior art. In other words, one of the objectives of this invention is to provide a method, system, device, and medium for extracting IGBT switching electromagnetic pulse signals of a flexible DC converter valve submodule that meets one or more of the aforementioned requirements, so as to achieve adaptive, complete, and accurate extraction and identification of IGBT switching electromagnetic pulse signals.

[0007] To achieve the above-mentioned objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for extracting the electromagnetic pulse signal of an IGBT switch in a flexible DC converter valve submodule, comprising the following steps: S1. Obtain the continuous voltage signal during the IGBT switching process through an electromagnetic pulse probe and perform discrete sampling to obtain a discrete long-time voltage signal sequence; S2. According to the preset discrete sliding window, the discrete long-time voltage signal sequence is subjected to absolute value low-pass mean smoothing to generate a continuous sliding energy envelope for characterizing the waveform profile of the IGBT switching electromagnetic pulse signal. S3. Obtain the background noise signal before the IGBT switching action, calculate the statistical characteristics of the background noise signal, and calculate the start extraction threshold and end extraction threshold based on the statistical characteristics; S4. Compare the continuous sliding energy envelope with the start extraction threshold and the end extraction threshold. When the energy envelope exceeds the start extraction threshold, determine the starting point of the current IGBT switching electromagnetic pulse signal by backtracking to the left and determine its ending point by maintaining the confirmation window to the right. Extract multiple complete switching electromagnetic pulse signals from the continuous sliding energy envelope. S5. Utilizing the asymmetric physical law that the IGBT's turn-on speed is faster than its turn-off speed, calculate the rise time of the cumulative integral curve of the extracted two adjacent switching electromagnetic pulse signals, perform polarity calibration on the arrangement direction of the electromagnetic pulse probe, and classify the extracted switching electromagnetic pulse signals into turn-on electromagnetic pulse signals or turn-off electromagnetic pulse signals based on the calibration results.

[0008] Secondly, the present invention provides a system for extracting electromagnetic pulse signals of IGBT switching in a flexible DC converter valve submodule, for implementing the extraction method described in the first aspect.

[0009] Thirdly, the present invention provides an electronic device, the electronic device including a memory, a processor and a computer program, wherein the computer program, when executed by the processor, implements the extraction method as described in the first aspect.

[0010] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the extraction method as described in the first aspect.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention extracts the background noise signal before IGBT switching, calculates its absolute mean and standard deviation, and adaptively calculates the start and end extraction thresholds based on preset threshold confidence multipliers. Since the dual thresholds dynamically adjust with the statistical characteristics of the background noise, the thresholds automatically decrease to avoid missed triggering when the converter valve submodule is in a low-noise operating condition, and automatically increase to avoid false triggering when in a high-noise operating condition. Therefore, this invention can adapt to changes in the electromagnetic environment under different operating currents and voltage levels, and compared to traditional methods using fixed thresholds, it has higher extraction accuracy and robustness in complex and variable flexible DC converter valve operating scenarios.

[0012] 2. This invention employs a dual-threshold extraction strategy combining leftward backtracking and rightward maintenance confirmation window. When the energy envelope exceeds the start extraction threshold, the system searches point by point to the left, starting from the current sampling point, until the first critical point where the energy envelope value is lower than the end extraction threshold is found and marked as the starting point. This mechanism avoids the problem of losing the pulse's initial rising edge due to threshold lag in traditional methods. Simultaneously, when the energy envelope value is lower than the end extraction threshold, extraction is not immediately terminated; instead, a pre-set length of supplementary sampling sequence is searched to the right. The termination point is only confirmed when the energy envelope values ​​of all sampling points within this sequence are lower than the end extraction threshold. This mechanism effectively avoids premature pulse truncation caused by zero-crossing points or local instantaneous dips in the energy envelope due to parasitic high-frequency oscillations in the circuit during IGBT switching transients. Therefore, each electromagnetic pulse signal extracted by this invention contains complete rising edge and tail information, providing a complete data foundation for subsequent feature analysis and fault diagnosis.

[0013] 3. This invention utilizes the time-domain asymmetry of the physical law that the IGBT's turn-on speed is faster than its turn-off speed. By extracting two adjacent switching electromagnetic pulse signals under the same operating current, the rise time of their cumulative integral curves is calculated. The signal with the shorter rise time is identified as the turn-on electromagnetic pulse signal. The placement direction of the electromagnetic pulse probe is determined based on the sign of the integral value of this signal (positive integral value for forward placement, negative integral value for reverse placement). Based on this, a classification formula is adaptively selected according to the determined probe direction (the integral value is directly taken for forward placement, and the opposite of the integral value is taken for reverse placement) to classify all subsequent pulses. Therefore, this invention eliminates the need for manual confirmation of the probe's physical orientation on-site, achieving non-directional probe deployment and eliminating polarity errors caused by manual installation differences. This significantly improves the deployment efficiency and reliability of the converter valve submodule's sensing test and long-term online monitoring.

[0014] 4. After completing probe orientation calibration, this invention automatically determines the type of each extracted switching electromagnetic pulse signal based on the sign of the integral value: a positive value indicates an on / off electromagnetic pulse signal, while a negative value indicates an off electromagnetic pulse signal. This classification mechanism requires no manual intervention and can automatically label hundreds or thousands of pulse signals acquired over long time series as on or off, directly providing labeled training samples and monitoring data for subsequent deep learning-based intelligent diagnostic models, significantly improving the automation level of data preprocessing.

[0015] 5. This invention introduces a safety constant mechanism in the calculation of the number of sampling points in the discrete sliding window: when the number of window sampling points calculated based on the ratio of the time width of the time-domain sliding window to the sampling time step is less than a preset safety constant, the number of window sampling points is forcibly set to this safety constant. This mechanism prevents numerical calculation errors caused by the number of window sampling points being too small or even zero at extremely high sampling rates, while ensuring the smoothness and stability of the energy envelope, ensuring that the algorithm can run stably under all extreme parameter combinations.

[0016] Further or more detailed beneficial effects will be described in conjunction with specific embodiments in the detailed implementation. Attached Figure Description

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

[0018] Figure 1 This is a flowchart illustrating the extraction method described in Embodiment 1 of the present invention.

[0019] Figure 2 This is a full-time-domain waveform diagram of the original electromagnetic pulse signal collected under working condition 1 as described in Embodiment 1 of the present invention.

[0020] Figure 3 This is the energy envelope curve obtained by processing the original electromagnetic pulse signal under working condition 1 as described in Embodiment 1 of the present invention through moving average processing.

[0021] Figure 4 This is a schematic diagram of local interception and extraction based on typical turn-on and turn-off electromagnetic pulses with dual thresholds under working condition 1 as described in Embodiment 1 of the present invention.

[0022] Figure 5 This is an overview diagram of the extraction results of all on and off electromagnetic pulses under operating condition 1 as described in Embodiment 1 of the present invention.

[0023] Figure 6 This is a full-time-domain waveform diagram of the original electromagnetic pulse signal collected under working condition 2 as described in Embodiment 1 of the present invention.

[0024] Figure 7 This is the energy envelope curve obtained by processing the original electromagnetic pulse signal under working condition 2 as described in Embodiment 1 of the present invention through moving average processing.

[0025] Figure 8 This is a schematic diagram of local interception and extraction based on typical turn-on and turn-off electromagnetic pulses with dual thresholds under working condition 2 as described in Embodiment 1 of the present invention.

[0026] Figure 9 This is an overview diagram of the extraction results of all on and off electromagnetic pulses under working condition 2 as described in Embodiment 1 of the present invention.

[0027] Figure 10 This is a comparison chart of the original waveforms and cumulative integral curves of the electromagnetic pulse signals turned on and off under the same operating current as described in Embodiment 1 of the present invention.

[0028] Figure 11 This is a structural diagram of the electronic device described in Embodiment 3 of the present invention.

[0029] Icon labels: 1100. Electronic equipment; 1101. Processor; 1102. Communication bus; 1103. User interface; 1104. Network interface; 1105. Memory. Detailed Implementation

[0030] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0031] In the following description, several embodiments of the present invention are provided. Different embodiments can be substituted or combined. Therefore, the present invention can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present invention should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.

[0032] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of the invention. Various processes or components may be appropriately omitted, substituted, or added to the various examples. For example, the described methods may be performed in different orders, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0033] To facilitate a better understanding of the embodiments of the present invention, its application scenarios will be explained before providing a detailed explanation of the specific implementation methods.

[0034] The extraction method described in the embodiments of this specification is applied to the online status monitoring and fault diagnosis system of the flexible DC converter valve submodule. In these scenarios, the application of the extraction method aims to adaptively and completely extract the electromagnetic pulse signal generated by each IGBT switching action from the long-time massive signal continuously collected by the electromagnetic pulse probe, and automatically distinguish between the turn-on pulse and the turn-off pulse, so as to provide an accurate and reliable data preprocessing foundation for subsequent health status assessment and fault feature analysis based on expert systems or deep learning models.

[0035] The following is a brief explanation of the flexible DC converter valve submodule, IGBT switch, electromagnetic pulse signal, electromagnetic pulse probe, sliding energy envelope, background noise signal, left backtracking, and right sustaining confirmation window involved in several embodiments of this specification: The flexible DC converter valve submodule is the basic power unit of the flexible DC transmission converter valve. It integrates components such as IGBTs and capacitors. Multiple submodules are cascaded to form a converter, realizing the conversion between high-voltage DC and AC power. The health status of a single submodule directly affects the safe and stable operation of the entire power transmission system.

[0036] IGBT switching: The switching action of an Insulated Gate Bipolar Transistor (IGBT) in a flexible DC converter valve submodule. During high-frequency switching, the IGBT generates drastic voltage and current changes, directly contributing to the electromagnetic pulse signals produced by the submodule.

[0037] Electromagnetic pulse signals refer to transient electromagnetic wave signals radiated into space during the switching process of an IGBT due to the instantaneous and drastic changes in voltage and current. This signal contains rich characteristic information about the IGBT switching process and can effectively reflect the health status of the device, serving as the fundamental data source for condition monitoring and fault diagnosis in this invention.

[0038] An electromagnetic pulse probe is a sensor device located on the IGBT side inside the flexible DC converter valve submodule. Based on the principle of electromagnetic induction, it senses the spatially changing electromagnetic field generated during the IGBT switching process in real time and outputs it as a continuous voltage signal. This probe is the signal acquisition front end of this invention.

[0039] The sliding energy envelope is a characteristic curve obtained by applying a low-pass average smoothing process to the absolute value of a discretely sampled voltage signal sequence within a sliding window. This curve can suppress high-frequency random noise, highlight the macroscopic waveform profile of the IGBT switching electromagnetic pulse signal, and is used to assist in determining the start and end points of the pulse.

[0040] Background noise signal refers to the signal collected by an electromagnetic pulse probe during the period before the IGBT switches. This signal mainly originates from electromagnetic interference in the operating environment of the converter valve submodule and does not contain IGBT switching pulse components. This invention adaptively calculates dual thresholds by analyzing the absolute mean and standard deviation of the background noise signal.

[0041] Leftward backtracking refers to the process of searching point by point to the left from the current sampling point after detecting that the energy envelope value exceeds the start extraction threshold, until the first critical point where the energy envelope value is lower than the end extraction threshold is found. This mechanism is used to accurately locate the start point of an electromagnetic pulse signal, solving the problem of missing the rising edge in traditional thresholding methods.

[0042] The rightward maintenance confirmation window means that when the energy envelope value falls below the end extraction threshold, pulse extraction is not immediately terminated. Instead, it continues to search for a pre-set length of supplementary sampling sequence to the right. The pulse is only confirmed to have ended when the energy envelope values ​​of all sampling points in this sequence are below the end extraction threshold. This mechanism is used to avoid premature pulse truncation caused by parasitic high-frequency oscillations in the circuit during IGBT switching transients, ensuring the complete extraction of the tail portion of the pulse.

[0043] Example 1: like Figure 1As shown, this embodiment provides a method for extracting the electromagnetic pulse signal of the IGBT switch in a flexible DC converter valve submodule, including the following steps: Step S1, Signal Acquisition and Discrete Sampling: An electromagnetic pulse probe, positioned on one side of the IGBT inside the flexible DC converter valve submodule, is used to sense the spatial electromagnetic changes generated by the IGBT during switching in real time and outputs a corresponding continuous voltage signal. This continuous voltage signal is then input to a high-speed analog-to-digital converter for discrete sampling to obtain a discrete long-time-series voltage signal sequence.

[0044] Step S2, Energy Envelope Construction: The number of sampling points included in the discrete sliding window is calculated based on the ratio of the preset time width of the time-domain sliding window to the sampling time step. The calculation formula is as follows: , In the formula, This indicates the number of sampling points contained in the discrete sliding window. This represents the floor function. Indicates the time width. Indicates the sampling time step.

[0045] To prevent the calculated value from becoming too small or even zero at extremely high sampling rates, when the calculated number of window sampling points is less than a preset safety constant, the number of window sampling points is forcibly set to the preset safety constant. Preferably, in this embodiment, the value of the preset safety constant is set to 5. This discrete sliding window is used to perform absolute value low-pass mean smoothing on the discrete long-time-series voltage signal sequence, that is, to calculate the average of the sum of the absolute values ​​of the voltage signals at each sampling point within the window, which is used as the energy envelope value at the current moment, thereby generating a continuous sliding energy envelope. : , In the formula, Indicates the index number of the discrete sampling point. It represents a discrete long-time voltage signal sequence.

[0046] This energy envelope is used to characterize the waveform profile of the IGBT switching electromagnetic pulse signal. Through this nonlinear absolute value low-pass averaging smoothing process, the interference of high-frequency random noise on the original signal can be effectively suppressed, while preserving the overall energy variation trend of the switching pulse, providing a smooth and stable characteristic curve for subsequent threshold comparison and pulse extraction.

[0047] Step S3, Adaptive dual threshold calculation: In the phase before the IGBT action is triggered, a segment of length is extracted. Continuous signals without switching action are considered background noise. The absolute mean and standard deviation of this background noise signal are calculated using the following formulas: , , In the formula, This represents the absolute mean of the background noise signal. The standard deviation of the background noise signal. Indicates the first Discrete voltage signals at discrete sampling points.

[0048] Set the first threshold confidence multiplier. Second threshold confidence multiplier And satisfy Based on the above statistical characteristics, the start and end extraction thresholds are adaptively calculated using the following formulas: , , This dual threshold can automatically adjust according to changes in background electromagnetic noise intensity under different operating conditions. Compared with the traditional fixed threshold method, the adaptive dual threshold of this embodiment can avoid false triggering caused by excessively low threshold in low noise environment, and avoid missed triggering caused by excessively high threshold in high noise environment, thereby adapting to the operating conditions of the flexible DC converter valve submodule under different operating currents and voltage levels.

[0049] Step S4, Dual-threshold pulse extraction: Continuous sliding energy envelope With the start extraction threshold and end extraction threshold Comparison is performed. When the energy envelope value of a certain sampling point is detected... When an IGBT switching action is detected, the pulse extraction process is triggered, including: Leftward backtracking to determine the starting point: Specifically, starting from this sampling point, the search proceeds point by point to the left until the first energy envelope value less than [a certain value is found]. The critical point is determined, and the time corresponding to this critical point is marked as the starting point of the current IGBT switching electromagnetic pulse signal. This mechanism solves the problem of rising edge loss caused by the traditional single-threshold method.

[0050] Right-click to confirm the end point in the confirmation window: Specifically, when the detected energy envelope value is lower than Instead of immediately terminating the extraction, it continues searching to the right for a pre-defined supplementary sampling sequence. The length of this supplementary sampling sequence is... Based on the tail oscillation period of IGBT switching With sampling time step The ratio is determined and is not less than the preset minimum length value: , Among them, the switching tail oscillation period Pre-determined by a double-pulse test before project implementation. Only when the energy envelope values ​​of all sampling points within this supplementary sampling sequence are below [a certain value]. Only when the current search point is reached will it be marked as the termination point of the current IGBT switching electromagnetic pulse signal.

[0051] By combining the leftward backtracking and rightward maintenance confirmation window, multiple complete switching electromagnetic pulse signals containing rising edges and tail-end characteristics are automatically extracted from the continuous sliding energy envelope. The leftward backtracking mechanism ensures accurate positioning of the pulse start point, avoiding the loss of rising edges due to threshold lag in traditional methods. The rightward maintenance confirmation window, by setting a supplementary sampling sequence, effectively avoids premature pulse truncation caused by zero-crossing or local instantaneous dips in the energy envelope due to parasitic high-frequency oscillations in the IGBT switching transient process, thus ensuring that the extracted pulses contain complete tail-end information. In this embodiment, complete signals were extracted according to the above steps under operating condition 1, as shown below. Figures 2 to 5 As shown, in operating condition 2, the complete signal was extracted according to the above steps. Figures 6 to 9 As shown.

[0052] Step S5, Polarity Calibration and Signal Classification: By utilizing the time-domain asymmetry of the physical law that the IGBT's turn-on speed is faster than its turn-off speed, the extracted switching electromagnetic pulse signals are polarity calibrated and classified.

[0053] like Figure 10 (a) and Figure 10 As shown in (b), a single switching action is issued through the flexible DC converter valve submodule. Two adjacent switching electromagnetic pulse signals under the same operating current are extracted, and their cumulative integral curves and rise times are calculated respectively. Figure 10 (c) and Figure 10 As shown in (d), signals with shorter rise times are identified as the electromagnetic pulse signal to turn on, and signals with longer rise times are identified as the electromagnetic pulse signal to turn off. The integral value of the electromagnetic pulse signal to turn on is calculated: if the integral value is positive, the electromagnetic pulse probe is determined to be arranged in the forward direction; if the integral value is negative, the electromagnetic pulse probe is determined to be arranged in the reverse direction.

[0054] After determining the probe orientation based on the calibration results, all extracted switching electromagnetic pulse signals are classified: if the probe is positioned forward, the integral value of the current signal is directly calculated as the judgment value; if the probe is positioned backward, the negative of the integral value of the current signal is calculated as the judgment value. If the judgment value is positive, the signal is determined to be an on electromagnetic pulse signal; if the judgment value is negative, it is determined to be an off electromagnetic pulse signal.

[0055] Through the above steps, this embodiment achieves automatic and complete extraction of IGBT switching electromagnetic pulse signals from long-sequence raw signals, and accurately distinguishes between turn-on and turn-off pulses. Since the physical law that the IGBT turn-on speed is inherently faster than the turn-off speed does not change with variations in operating current, the polarity calibration performed in this embodiment based on this law has strong robustness. Simultaneously, by determining the probe direction through the positive or negative integral value and adaptively selecting the classification formula, the polarity misalignment problem caused by inconsistent probe orientations during on-site manual placement can be eliminated, achieving non-directional probe deployment and improving deployment efficiency and long-term online monitoring reliability.

[0056] Example 2: This embodiment provides a system for extracting electromagnetic pulse signals from IGBT switches in a flexible DC converter valve submodule, used to implement the extraction method described in Embodiment 1.

[0057] Example 3: like Figure 11 As shown, this embodiment provides an electronic device, which may include: at least one processor, at least one network interface, a user interface, a memory, and at least one communication bus.

[0058] The communication bus can be used to enable communication between the various components mentioned above.

[0059] The user interface may include buttons, and optional user interfaces may also include standard wired interfaces and wireless interfaces.

[0060] The network interface may include, but is not limited to, Bluetooth modules, NFC modules, Wi-Fi modules, etc.

[0061] The processor may include one or more processing cores. It connects various parts of the electronic device via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in memory, and accessing data stored in memory to perform various functions and process data. Optionally, the processor can be implemented using at least one hardware form of DSP, FPGA, or PLA. The processor may integrate one or more of the following: CPU, GPU, and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor.

[0062] The memory may include RAM or ROM. Optionally, the memory may include a non-transitory computer-readable medium. The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor. The memory, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an extraction application. The processor can be used to call the extraction application stored in the memory and execute the steps of the extraction methods mentioned in the foregoing embodiments.

[0063] Example 4: This embodiment provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform the above-described instructions. Figure 1 One or more steps in the illustrated embodiment. If the constituent modules of the above-described electronic device are implemented as software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0064] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0065] Those skilled in the art will understand that all or part of the processes in the method of Embodiment 1 described above can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and the implementation scheme can be combined arbitrarily.

[0066] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, as some steps can be performed in other orders or simultaneously according to the present invention. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0067] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0068] The foregoing description is merely an exemplary embodiment of the present invention and should not be construed as limiting the scope of the invention. Any equivalent changes and modifications made in accordance with the teachings of this invention are still within the scope of this invention. Those skilled in the art will readily conceive of embodiments of the invention upon considering the specification and practicing the disclosure herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include knowledge or means in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of the invention are defined by the claims.

Claims

1. A method for extracting the electromagnetic pulse signal of an IGBT switch in a flexible DC-DC converter valve submodule, characterized in that, Including the following steps: S1. Obtain the continuous voltage signal during the IGBT switching process through an electromagnetic pulse probe and perform discrete sampling to obtain a discrete long-time voltage signal sequence; S2. According to the preset discrete sliding window, the discrete long-time voltage signal sequence is subjected to absolute value low-pass mean smoothing to generate a continuous sliding energy envelope for characterizing the waveform profile of the IGBT switching electromagnetic pulse signal. S3. Obtain the background noise signal before the IGBT switching action, calculate the statistical characteristics of the background noise signal, and calculate the start extraction threshold and end extraction threshold based on the statistical characteristics; S4. Compare the continuous sliding energy envelope with the start extraction threshold and the end extraction threshold. When the energy envelope exceeds the start extraction threshold, determine the starting point of the current IGBT switching electromagnetic pulse signal by backtracking to the left and determine its ending point by maintaining the confirmation window to the right. Extract multiple complete switching electromagnetic pulse signals from the continuous sliding energy envelope. S5. Utilizing the asymmetric physical law that the IGBT's turn-on speed is faster than its turn-off speed, calculate the rise time of the cumulative integral curve of the extracted two adjacent switching electromagnetic pulse signals, perform polarity calibration on the arrangement direction of the electromagnetic pulse probe, and classify the extracted switching electromagnetic pulse signals into turn-on electromagnetic pulse signals or turn-off electromagnetic pulse signals based on the calibration results.

2. The extraction method according to claim 1, characterized in that, The method for calculating the start extraction threshold and end extraction threshold in step S3 is as follows: Calculate the absolute mean and standard deviation of the background noise signal; Set a first threshold confidence multiplier and a second threshold confidence multiplier, wherein the first threshold confidence multiplier is greater than the second threshold confidence multiplier; The absolute value mean plus the product of the first threshold confidence multiplier and the standard deviation is used as the extraction threshold; The absolute mean plus the product of the second threshold confidence multiplier and the standard deviation is used as the end extraction threshold.

3. The extraction method according to claim 1, characterized in that, The specific method by which the rightward maintenance confirmation window in step S4 is used to determine the termination point is as follows: When the energy envelope value of a certain sampling point in the continuous sliding energy envelope is detected to be lower than the end extraction threshold, the system continues to search for a supplementary sampling sequence of a preset length to the right. Only when the energy envelope values ​​of all sampling points in the supplementary sampling sequence are lower than the end extraction threshold will the current sampling point be marked as the termination point of the current IGBT switching electromagnetic pulse signal. The length of the supplementary sampling sequence is determined based on the ratio of the IGBT switch tail oscillation period to the sampling time step, and this length is not less than the preset minimum length value. The switching tail oscillation period is predetermined by a double-pulse test.

4. The extraction method according to claim 1, characterized in that, The specific method for calibrating the polarity of the electromagnetic pulse probe's orientation in step S5 is as follows: Calculate the cumulative integral curves and rise times of two adjacent switching electromagnetic pulse signals respectively, and determine the one with the shorter rise time as the turn-on electromagnetic pulse signal; Calculate the integral value of the electromagnetic pulse signal to activate it. If the integral value is positive, the electromagnetic pulse probe is determined to be arranged in the forward direction. If the integral value is negative, the electromagnetic pulse probe is determined to be arranged in the reverse direction.

5. The extraction method according to claim 1 or 3, characterized in that, The specific method for determining the starting point through left backtracking in step S4 is as follows: When the energy envelope value of a certain sampling point in the continuous sliding energy envelope is detected to be higher than the start extraction threshold, the current sampling point is used as the starting point to search point to the left until a critical point where the energy envelope value is less than the end extraction threshold is found. The time corresponding to the critical point is marked as the starting point of the current IGBT switching electromagnetic pulse signal.

6. The extraction method according to claim 1 or 4, characterized in that, The specific method for classifying the extracted switching electromagnetic pulse signals in step S5 is as follows: If the electromagnetic pulse probe is determined to be in the forward orientation, the integral value of the switch electromagnetic pulse signal is calculated and directly used as the determination value. If the electromagnetic pulse probe is determined to be arranged in reverse, the integral value of the switch electromagnetic pulse signal is calculated and its opposite is taken as the determination value. If the determination value is positive, the switch electromagnetic pulse signal is determined to be an on electromagnetic pulse signal; if it is negative, it is determined to be an off electromagnetic pulse signal.

7. The extraction method according to claim 1, characterized in that, The discrete sliding window in step S2 is determined in the following way: The number of sampling points contained in the discrete sliding window is calculated based on the ratio of the time width of the time-domain sliding window to the sampling time step. When the calculated number of window sampling points is less than the preset safety constant, the current number of window sampling points is set to the preset safety constant; The average value of the sum of the absolute values ​​of the voltage signals at each sampling point within the window is calculated using the discrete sliding window, and this average value is used as the energy envelope value at the current moment.

8. A system for extracting electromagnetic pulse signals from IGBT switching in a flexible DC converter valve submodule, characterized in that, Used to implement the extraction method as described in any one of claims 1 to 7.

9. An electronic device, the electronic device comprising a memory, a processor, and a computer program, characterized in that, When the computer program is executed by a processor, it implements the extraction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the extraction method as described in any one of claims 1 to 7.

Images