Method for suppressing high-frequency resonant switching noise, and device and medium

Abstract

A method for suppressing high-frequency resonant switching noise, and a device and a medium. The method comprises: using a high-frequency current sensor to collect a high-frequency switching noise signal segment of a power electronic device (S1); extracting a modal feature of the high-frequency switching noise segment (S2); on the basis of the modal feature of the high-frequency switching noise segment, initializing initial values of a particle swarm optimization algorithm, wherein parameters optimized by means of the particle swarm optimization algorithm are suppression coil parameters, comprising coil self-inductance, resonant capacitance and damping resistance (S3); using the particle swarm optimization algorithm to perform optimization on the suppression coil parameters, and determining suppression coil design parameters (S4); and sleeving a suppression coil in a non-contact manner over live and neutral wires that connect a power source and the power electronic device, and using the suppression coil to suppress the high-frequency resonant switching noise (S5).

Description

Methods, equipment, and dielectrics for suppressing high-frequency resonant switching noise.

[0001] This application claims priority to Chinese Patent Application No. 202411744949.2, filed with the Chinese Patent Office on December 2, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of high-frequency noise suppression technology, such as a method, device, and medium for suppressing high-frequency resonant switching noise. Background Technology

[0003] With the vigorous development of smart cities and the widespread application of power electronic equipment in urban cable tunnels, the electromagnetic environment within tunnels has become more complex, potentially interfering with cable condition monitoring. When power electronic equipment in light-emitting diode (LED) lighting devices in cable tunnels switches on and off at high speeds, it generates high du / dt and di / dt values ​​within the equipment. These high-frequency values ​​resonate with system parasitic parameters through high-frequency coupling, producing strong switching noise. This high-frequency resonant switching noise may intrude into the cable grounding system, threatening the reliability of online partial discharge monitoring. Therefore, it is necessary to effectively suppress the high-frequency switching noise generated by LED lighting devices in tunnels.

[0004] Patent CN202111349614.7 proposes a "common-mode interference suppression circuit." This circuit samples the voltage of the resonant inductor in the switching resonant circuit and the primary winding of the transformer. A voltage with the same frequency but opposite phase as the voltage at the midpoint of the switching transistor is applied to the common-mode suppression capacitor to cancel out the common-mode interference signal, thus eliminating common-mode interference in the switching resonant circuit. This application eliminates the need for large inductors or capacitors in the switching resonant circuit, thus avoiding excessive increases in its size. However, the impedance interaction between the suppression circuit and the conduction path affects the suppression effect on high-frequency switching noise, reducing the attenuation performance of the suppression circuit at high frequencies.

[0005] Patent CN202111352935.2 proposes a "targeted active suppression method and device for high-frequency switching oscillation current in a variable frequency motor". It utilizes the principle of resonant matching to perform frequency orientation and damping complementarity on the switching oscillation current of the variable frequency motor system, achieving targeted suppression of the target switching oscillation current. This application has a simple structure and low cost, and it has a certain suppression effect on high-frequency switching noise. However, this application does not consider the impact of the device itself on the original system, and the suppression effect has room for improvement.

[0006] High-frequency switching noise is the result of high-frequency resonance between the high-speed switching of power devices in LED lighting devices and parasitic parameters to ground. It manifests as a large transient amplitude / energy in the current time-domain waveform, and in the frequency spectrum, a significant resonance peak appears in the high-frequency range. This type of resonant high-frequency noise interference reduces the high-frequency attenuation performance of filters, making it difficult to effectively suppress high-frequency switching noise. Summary of the Invention

[0007] This application addresses the problem of the difficulty in effectively suppressing resonant high-frequency switching noise by providing a method, device, and medium for suppressing high-frequency resonant switching noise. By constructing a non-contact anti-resonant matching circuit, the impedance of the high-frequency common-mode resonant band is effectively increased, thereby achieving the suppression of switching oscillation modes. This method is safe, convenient, and efficient.

[0008] In a first aspect, this application provides a method for suppressing high-frequency resonant switching noise, the method comprising:

[0009] High-frequency current sensors are used to collect high-frequency switching noise signal segments from power electronic equipment.

[0010] Extract modal features of high-frequency switching noise segments;

[0011] The initial values ​​of the particle swarm optimization algorithm are initialized based on the modal characteristics of high-frequency switching noise segments. The parameters optimized by the particle swarm optimization algorithm are the suppression coil parameters, including the coil self-inductance, resonant capacitance, and damping resistance.

[0012] The parameters of the suppression coil are optimized using the particle swarm optimization algorithm to determine the design parameters of the suppression coil.

[0013] The suppression coil is non-contactly sleeved on the live and neutral wires connecting the power supply and power electronic equipment to suppress high-frequency resonant switching noise.

[0014] In some embodiments, the high-frequency current sensor is non-contactly sleeved onto the live and neutral wires of the power electronic equipment to collect high-frequency switching noise signals, and a high-frequency switching noise signal segment i is extracted from the collected high-frequency switching noise signals. sw (t), the power electronic equipment is an LED lighting device for cable tunnels.

[0015] In some embodiments, the high-frequency switching noise segment modal characteristics include the power electronic equipment side resonant frequency F1 and damping ratio ξ1.

[0016] In some embodiments, the method for extracting the modal features of the high-frequency switching noise segment is the half-power bandwidth method.

[0017] In some embodiments, the half-power bandwidth method includes: analyzing high-frequency switching noise signal segments isw (t) Frequency domain curves, with the frequency corresponding to the spectral peak as the resonant frequency F1 on the high-frequency switching noise power electronic equipment side, and the half-power region defined as the signal spectral amplitude greater than The region of octave peaks is defined in the half-power region. The two frequencies corresponding to the peak value are half-power frequencies f1 and f2. The damping ratio ξ1 of the high-frequency switching noise signal segment is calculated using half-power frequencies f1 and f2.

[0018] In some embodiments, the initial values ​​of the initial particle swarm optimization algorithm are obtained as follows: based on the matching of the resonant frequency F2 of the suppression coil with the resonant frequency F1 of the power electronic equipment side, and the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 of the power electronic equipment side, the initial values ​​of the initial self-inductance L0 of the suppression coil, the initial value of the resonant capacitance C0, and the initial value of the damping resistance R0 are obtained.

[0019] In some embodiments, based on the matching of the resonant frequency F2 of the suppression coil with the resonant frequency F1 on the power electronic equipment side, the L0 and C0 of the suppression coil are determined using the following formula:

[0020] ;

[0021] ;

[0022] Where μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, N is the number of turns of the winding, and H is the height of the winding;

[0023] Based on the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 on the system side, the resistance R0 of the suppression coil is determined using the following formula:

[0024] .

[0025] In some embodiments, the particle swarm optimization algorithm is used to suppress the equivalent impedance Z introduced by the coil into the power electronic equipment side in the half-power region of the target suppression mode. reg (s) is the objective function; parameter optimization is performed:

[0026] ;

[0027] ;

[0028] Where F2 is the resonant frequency of the suppression coil, μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, ξ2 is the damping ratio introduced by the suppression coil, and f1 and f2 are the left and right boundary point frequencies of the half-power region, respectively.

[0029] Secondly, this application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the high-frequency resonant switching noise suppression method described above.

[0030] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for suppressing high-frequency resonant switching noise. Attached Figure Description

[0031] Figure 1 is a flowchart of the high-frequency resonant switching noise suppression method of this application;

[0032] Figure 2 is a schematic diagram of modal feature extraction in this application;

[0033] Figure 3 is a schematic diagram of the high-frequency switching noise suppression system for the LED lighting device of this application;

[0034] Figure 4 is an EMI spectrum diagram of high-frequency switching noise in an LED lighting device in one embodiment;

[0035] Figure 5 is a comparison diagram of high-frequency switching noise suppression in an LED lighting device in one embodiment, where (a) is the time-domain waveform of high-frequency switching noise and (b) is the frequency-domain waveform of high-frequency switching noise.

[0036] Figure 6 is a comparison of high-frequency switching noise suppression before and after algorithm optimization in one embodiment. (a) is a comparison of suppression before and after without using particle swarm optimization algorithm for parameter optimization, and (b) is a comparison of suppression results before and after using particle swarm optimization algorithm for parameter optimization. Detailed Implementation

[0037] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort should fall within the scope of protection of this application.

[0038] Example 1

[0039] This embodiment provides a method for suppressing high-frequency resonant switching noise in LED lighting devices for cable tunnels, as shown in Figure 1. The method includes the following steps:

[0040] S1 uses a high-frequency current sensor to collect high-frequency switching noise signal segments from power electronic equipment.

[0041] A high-frequency current sensor is non-contactly attached to the live and neutral wires of an LED lighting device to collect high-frequency switching noise signals. These noise signals have a frequency greater than 1MHz, a duration of 2μs-5μs, and are characterized as damped, oscillating, attenuating pulse resonant signals. A segment i of the high-frequency switching noise signal is extracted from the collected signal. sw (t), the power electronic equipment is an LED lighting device for cable tunnels.

[0042] S2, extract the modal features of high-frequency switching noise segments.

[0043] The modal characteristics of high-frequency switching noise segments include the resonant frequency F1 and damping ratio ξ1 on the power electronic equipment side. The extraction method used in this embodiment is the half-power bandwidth method.

[0044] Analysis of high-frequency switching noise signal segment i sw (t) Frequency domain curves, with the frequency corresponding to the spectral peak as the resonant frequency F1 on the high-frequency switching noise power electronic equipment side, as shown in Figure 2. The half-power region is defined as the signal spectral amplitude being greater than The region of octave peaks is defined in the half-power region. The two frequencies corresponding to the peak value are half-power frequencies f1 and f2. The damping ratio ξ1 of the high-frequency switching noise signal segment is calculated using half-power frequencies f1 and f2.

[0045] .

[0046] S3. Initialize the initial values ​​of the particle swarm optimization algorithm based on the modal characteristics of the high-frequency switching noise segment. The parameters optimized by the particle swarm optimization algorithm are the suppression coil parameters, including the coil self-inductance, resonant capacitance and damping resistance.

[0047] Based on the matching of the suppression coil resonant frequency F2 with the power electronic equipment side resonant frequency F1, and the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 of the power electronic equipment side, the initial values ​​for the particle swarm optimization algorithm are obtained: the initial value of the suppression coil's coil self-inductance L0, the initial value of the resonant capacitance C0, and the initial value of the damping resistance R0. Specifically:

[0048] The L0 and C0 of the suppression coil are determined using the following formula:

[0049] ;

[0050] ;

[0051] Where μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, N is the number of turns in the winding, and H is the height of the winding.

[0052] Based on the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 on the system side, the resistance R0 of the suppression coil is determined using the following formula:

[0053] .

[0054] S4. The particle swarm optimization algorithm is used to optimize the parameters of the suppression coil and determine the design parameters C1, L1, and R1 of the suppression coil.

[0055] Particle swarm optimization algorithm is used to suppress the equivalent impedance Z introduced into the power electronic equipment side by the coil in the half-power region of the target suppression mode. reg (s) is the objective function; parameter optimization is performed:

[0056] ;

[0057] ;

[0058] Where F2 is the resonant frequency of the suppression coil, μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, ξ2 is the damping ratio introduced by the suppression coil, and f1 and f2 are the left and right boundary point frequencies of the half-power region, respectively.

[0059] After parameter optimization using the particle swarm optimization algorithm, the relatively optimal design parameters for the coil self-inductance L1, resonant capacitor C1, and damping resistor R1 are determined.

[0060] S5 involves non-contactly attaching the suppression coil to the live and neutral wires connecting the power supply and power electronic equipment, thereby suppressing high-frequency resonant switching noise.

[0061] In summary, this application proposes a high-frequency switching noise suppression method for LED lighting devices based on resonant matching. By constructing a non-contact anti-resonant matching circuit, the impedance of the high-frequency resonant band is effectively increased, thereby achieving mode suppression of switching noise. Compared to direct matching for suppression, the parameters obtained after considering the coil's self-inductance and undergoing particle swarm optimization show better suppression performance. The proposed method suppresses high-frequency switching noise non-contactly, offering advantages such as safety, effectiveness, simple structure, and low cost. In the experiment, the suppression coil was threaded through the live and neutral wires to achieve high-frequency switching noise suppression in the LED lighting device.

[0062] Compared with related technologies, this application has the following advantages:

[0063] (1) Easy installation: This application can select different sizes according to the actual system. After designing the suppression coil, it only needs to be put into the grounding circuit to complete the suppression. For complex systems, a bayonet-type magnetic ring can be selected for installation.

[0064] (2) Safe and inexpensive: This application uses a non-contact sleeve in the grounding circuit, which will not interfere with the normal operation of the system or affect the original hardware structure of the system. The magnetic ring material and anti-resonance matching circuit are low in cost and have practical value.

[0065] (3) High efficiency suppression: Compared with direct matching of modal frequencies and damping characteristics, the target mode matching after optimization by particle swarm optimization algorithm is more accurate, introduces greater impedance, and has a more significant suppression effect.

[0066] Example 2

[0067] This embodiment verifies the feasibility and effectiveness of the method described in Embodiment 1 through experiments. The experimental system, as shown in Figure 3, consists of an AC power supply, a frequency converter, a current transformer, a suppression coil, and an LED lighting device. The basic parameters of the suppression coil are shown in Table 1. To evaluate the high-frequency switching noise suppression effect of the LED lighting device, a high-frequency current sensor was installed in the grounding circuit of the LED lighting device, and experimental data was recorded. The signal acquisition unit used was a PICO 5444DMSO with a sampling frequency of 125 MS / s. The current probe used in the experiment was a CP9030S high-frequency current probe (30A / 100MHz, accuracy 1%) with a bandwidth of 50MHz.

[0068] Table 1 Basic parameters of the suppression coil

[0069]

[0070] Figure 4 shows the electromagnetic interference (EMI) spectrum of high-frequency switching noise in an LED lighting device. It can be found that there are two modes around 5.3MHz and 13.8MHz in the LED lighting device system. This experiment mainly focuses on suppressing the dominant mode of 5.3MHz, which has a large interference in the system.

[0071] Figure 5 shows the experimental comparison results of high-frequency switching noise suppression in LED lighting devices. As can be seen in Figure 5(a), the high-frequency switching noise was significantly suppressed after the introduction of the suppression coil, with the oscillation attenuation decreasing from 8 cycles to 3-4 cycles, a reduction of half the attenuation time. In Figure 5(b), the frequency domain peak was effectively suppressed. The experimental results demonstrate that this application can effectively suppress the high-frequency switching noise present in LED lighting devices, significantly reduce the oscillation amplitude of high-frequency switching noise in LED lamps, reduce interference with monitoring equipment in cable tunnels, and improve the safety and reliability of cable tunnel monitoring equipment. Figure 6(a) shows that even without parameter optimization using the particle swarm optimization algorithm, this application can still suppress noise. However, combined with Figure 6(b), it can be seen that parameter optimization using the particle swarm optimization algorithm achieves a better suppression effect.

[0072] Example 3

[0073] The electronic device of this application includes a Central Processing Unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) or loaded from storage units into random access memory (RAM). The RAM can also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0074] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0075] The processing unit executes the various methods and processes described above, such as methods S1 to S5. For example, in some embodiments, methods S1 to S5 may be implemented as computer software programs tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of methods S1 to S5 described above may be performed. In other embodiments, the CPU may be configured to execute methods S1 to S5 by any other suitable means (e.g., by means of firmware).

[0076] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used include: Field-Programmable Gate Array (FPGA), Application-Specific Integrated Circuit (ASIC), Application-Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), and so on.

[0077] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0078] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. A machine-readable storage medium can include electrical connections based on one or more wires, a portable computer disk, a hard disk, RAM, ROM, erasable programmable read-only memory (EPROM), flash memory, optical fiber, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

Claims

1. A method for suppressing high-frequency resonant switching noise, comprising: High-frequency current sensors are used to collect high-frequency switching noise signal segments from power electronic equipment. Extract modal features of high-frequency switching noise segments; The initial values ​​of the particle swarm optimization algorithm are initialized based on the modal characteristics of high-frequency switching noise segments. The parameters optimized by the particle swarm optimization algorithm are the suppression coil parameters, including the coil self-inductance, resonant capacitance, and damping resistance. The parameters of the suppression coil are optimized using the particle swarm optimization algorithm to determine the design parameters of the suppression coil. The suppression coil is non-contactly sleeved on the live and neutral wires connecting the power supply and power electronic equipment to suppress high-frequency resonant switching noise.

2. The method for suppressing high-frequency resonant switching noise according to claim 1, wherein, The method of acquiring high-frequency switching noise signal segments from power electronic equipment using a high-frequency current sensor includes: A high-frequency current sensor is non-contactly mounted on the live and neutral wires of power electronic equipment to collect high-frequency switching noise signals. A segment of the high-frequency switching noise signal is then extracted from the collected signal. sw (t), the power electronic equipment is a cable tunnel light-emitting diode (LED) lighting device.

3. The method for suppressing high-frequency resonant switching noise according to claim 1, wherein, The high-frequency switching noise segment modal characteristics include the power electronic equipment side resonant frequency F1 and damping ratio ξ1.

4. The method for suppressing high-frequency resonant switching noise according to claim 3, wherein, The method for extracting the modal features of the high-frequency switching noise segment is the half-power bandwidth method.

5. The method for suppressing high-frequency resonant switching noise according to claim 4, wherein, The half-power bandwidth method includes: analyzing high-frequency switching noise signal segments i sw (t) Frequency domain curves, with the frequency corresponding to the spectral peak as the resonant frequency F1 on the high-frequency switching noise power electronic equipment side, and the half-power region defined as the signal spectral amplitude greater than The region of octave peaks is defined in the half-power region. The two frequencies corresponding to the peak value are half-power frequencies f1 and f2. The damping ratio ξ1 of the high-frequency switching noise signal segment is calculated using half-power frequencies f1 and f2.

6. The method for suppressing high-frequency resonant switching noise according to claim 3, wherein, The initial values ​​for the particle swarm optimization algorithm are: Based on the matching of the resonant frequency F2 of the suppression coil with the resonant frequency F1 of the power electronic equipment side, and the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 of the power electronic equipment side, the initial values ​​of the particle swarm optimization algorithm are obtained: the initial value of the coil self-inductance L0 of the suppression coil, the initial value of the resonant capacitance C0, and the initial value of the damping resistance R0.

7. The method for suppressing high-frequency resonant switching noise according to claim 6, wherein, The initial values ​​for the particle swarm optimization algorithm based on the modal features of high-frequency switching noise segments include: Based on the matching of the resonant frequency F2 of the suppression coil with the resonant frequency F1 of the power electronic equipment side, the L0 and C0 of the suppression coil are determined using the following formula: ； ； Where μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, N is the number of turns of the winding, and H is the height of the winding; Based on the matching of the damping ratio ξ2 introduced by the suppression coil with the damping ratio ξ1 on the system side, the resistance R0 of the suppression coil is determined using the following formula: 。 8. The method for suppressing high-frequency resonant switching noise according to claim 4, wherein, The process of optimizing the suppression coil parameters using a particle swarm optimization algorithm to determine the suppression coil design parameters includes: Particle swarm optimization algorithm is used to suppress the equivalent impedance Z introduced into the power electronic equipment side by the coil in the half-power region of the target suppression mode. reg (s) is the objective function; parameter optimization is performed: ； ； Where F2 is the resonant frequency of the suppression coil, μ0 is the permeability, a is the inner diameter of the suppression coil, b is the outer diameter of the suppression coil, h is the height of the suppression coil, ξ2 is the damping ratio introduced by the suppression coil, and f1 and f2 are the left and right boundary point frequencies of the half-power region, respectively.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of claims 1 to 8.

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