Self-adaptive noise control device for transformer and application of self-adaptive noise control device

Abstract

The invention relates to the technical field of noise control, and discloses a self-adaptive noise control device for a transformer and application of the self-adaptive noise control device. The device comprises a reference sound sensor, an error sound sensor, a self-adaptive control system and a secondary sound source, the adaptive control system is used for filtering the noise signal to obtain a first noise reduction parameter, superposing the noise signal and the first noise reduction parameter to obtain a first error signal, and optimizing the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter; the secondary sound source is used for generating an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave counteracts the noise signal; the adaptive control system is also used for optimizing the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter; the secondary sound source is also used for generating a target secondary sound wave based on the third noise reduction parameter, so that the target secondary sound wave counteracts the noise signal. According to the invention, active control of noise in the surrounding area of the transformer can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of noise control, and in particular to a transformer adaptive noise control device and application thereof. Background Art

[0002] To effectively improve urban power supply capabilities, substations are being built closer and closer to cities, and the resulting noise hazards are becoming increasingly apparent. Therefore, noise reduction of substation transformers is particularly important.

[0003] Methods for reducing transformer noise in substations are primarily categorized as active and passive. Currently, passive noise reduction measures are commonly employed, such as hanging shock-absorbing boxes on the transformer walls and installing sound barriers in key areas or at the factory boundary. Passive noise reduction effectively controls high-frequency noise from substation transformers, but is less effective for controlling low-frequency noise. Low-frequency noise from substation transformers has a long wavelength and is severely diffracted, making it difficult to be blocked by sound barriers. Active noise reduction can provide targeted noise reduction for low-frequency noise, but its limited range limits its application scenarios.

[0004] Therefore, in order to reduce noise pollution in substations, it is urgent to develop a device that can effectively monitor and reduce noise around transformers. Summary of the Invention

[0005] In order to achieve active control of transformer noise in a substation, the present invention provides a transformer adaptive noise control device and application thereof.

[0006] In a first aspect, an embodiment of the present invention provides a transformer adaptive noise control device, comprising: a reference sound sensor, an error sound sensor, an adaptive control system, and a secondary sound source; The reference acoustic sensor is used to collect the noise signal of the target transformer in real time; The adaptive control system is configured to filter the noise signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter; The secondary sound source is used to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; The error sound sensor is used to collect the second error signal of the target noise reduction area in real time; The adaptive control system is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter; The secondary sound source is further configured to generate a target secondary sound wave based on the third noise reduction parameter, so that the target secondary sound wave cancels the noise signal.

[0007] Preferably, the adaptive control system includes an adaptive controller; The reference acoustic sensor is used to preprocess the noise signal to obtain a reference signal; The adaptive controller is configured to filter the reference signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter; The adaptive controller is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter.

[0008] In a second aspect, an embodiment of the present invention provides a noise control method, which is applied to the above-mentioned transformer adaptive noise control device, comprising: Collecting the noise signal of the target transformer in real time, and preprocessing the noise signal to obtain a reference signal; performing secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; optimizing the secondary path transfer function based on the reference signal to obtain filter coefficients of the adaptive control system; Performing convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; A target secondary sound wave is generated based on the secondary path signal, so that the target secondary sound wave cancels the noise signal.

[0009] Preferably, the step of performing secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function comprises: Initializing the transformer adaptive noise control device to obtain a first secondary path transfer function; performing a convolution calculation on the reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; Superimposing the noise signal and the first noise reduction parameter to obtain a first error signal; iteratively optimizing the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; The first secondary path transfer function corresponding to the second noise reduction parameter is characterized as a secondary path transfer function.

[0010] Preferably, the optimizing the secondary path transfer function based on the reference signal to obtain the filter coefficients of the adaptive control system includes: performing a convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; generating an initial secondary sound wave based on the second noise reduction parameter so that the initial secondary sound wave cancels the noise signal; acquiring a second error signal in the target noise reduction area in real time, and iteratively optimizing the second noise reduction parameter by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; The secondary path transfer function corresponding to the third noise reduction parameter is represented as a filter coefficient of the adaptive control system.

[0011] In a third aspect, an embodiment of the present invention provides a noise control system, which is applied to the noise control method described above, including: A reference signal determination module is used to collect the noise signal of the target transformer in real time and preprocess the noise signal to obtain a reference signal; A secondary path identification module is used to perform secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; a coefficient determination module, configured to optimize the secondary path transfer function based on the reference signal to obtain filter coefficients of the adaptive control system; A convolution calculation module is used to perform convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; and a cancellation sound wave generation module is used to generate a target secondary sound wave based on the secondary path signal so that the target secondary sound wave cancels the noise signal.

[0012] Preferably, the secondary path identification module includes: an initialization unit, configured to initialize the transformer adaptive noise control device to obtain a first secondary path transfer function; a first convolution calculation unit, configured to perform a convolution calculation on the reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; a superposition operation unit, configured to superimpose the noise signal and the first noise reduction parameter to obtain a first error signal; a first iterative optimization unit, configured to iteratively optimize the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; The first characterization unit is configured to characterize the first secondary path transfer function corresponding to the second noise reduction parameter as a secondary path transfer function.

[0013] Preferably, the coefficient determination module includes: a second convolution calculation unit, configured to perform a convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; a sound wave generating unit, configured to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; a second iterative optimization unit, configured to collect a second error signal of the target noise reduction area in real time, and iteratively optimize the second noise reduction parameter by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; The second characterization unit is configured to characterize the secondary path transfer function corresponding to the third noise reduction parameter as a filter coefficient of the adaptive control system.

[0014] In a third aspect, an embodiment of the present invention provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the noise control method as described above when executing the computer program.

[0015] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the noise control method as described above.

[0016] Compared with the prior art, the transformer adaptive noise control device and its application in the embodiment of the present invention have the following beneficial effects: first, a first noise reduction parameter is generated based on the reference sound sensor signal, a second noise reduction parameter is obtained through preliminary superposition optimization, and then the third noise reduction parameter is further optimized in combination with the second error signal (actual noise reduction effect) collected by the error sound sensor, forming a dual correction of "pre-filtering + real-time feedback", effectively improving the phase and amplitude matching between the secondary sound wave and the original noise, and being able to achieve fixed-point and directional control of the noise in the area around the transformer, so as to achieve active control of environmental noise. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 1 is a schematic structural diagram of a transformer adaptive noise control device according to an embodiment of the present invention; Figure 2 2 is a schematic diagram showing the principle of superimposing and generating a first error signal in an adaptive control system according to an embodiment of the present invention; Figure 3 1 is a flow chart of a noise control method according to an embodiment of the present invention; Figure 4 This is a schematic structural diagram of a noise control system according to an embodiment of the present invention; Figure 5This is a schematic structural diagram of a terminal device according to an embodiment of the present invention; Reference numerals: 1. Reference sound sensor; 2. Error sound sensor; 3. Adaptive control system; 4. Secondary sound source; 01. Reference signal determination module; 02. Secondary path identification module; 03. Coefficient determination module; 04. Convolution calculation module; 05. Cancelling sound wave generation module; 5000, terminal device; 5001, processor; 5002, bus; 5003, memory; 5004, transceiver. DETAILED DESCRIPTION

[0018] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0019] In the description of the present invention, it should be understood that the terms "first" and "second" etc. are used in the present invention to distinguish different objects rather than to describe a specific order.

[0020] In describing the present invention, it should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. Those skilled in the art will understand the specific meanings of the above terms in the present invention in specific circumstances.

[0021] like Figure 1 As shown, an embodiment of the present invention provides a transformer adaptive noise control device, including: a reference sound sensor 1, an error sound sensor 2, an adaptive control system 3 and a secondary sound source 4.

[0022] The reference acoustic sensor is used to collect the noise signal of the target transformer in real time.

[0023] The adaptive control system is used to filter the noise signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter.

[0024] The secondary sound source is used to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal.

[0025] The error sound sensor is used to collect the second error signal of the target noise reduction area in real time.

[0026] The adaptive control system is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter.

[0027] The secondary sound source is further configured to generate a target secondary sound wave based on a third noise reduction parameter, so that the target secondary sound wave cancels the noise signal.

[0028] like Figure 2 As shown in FIG, it is a schematic diagram of the principle of the adaptive control system according to an embodiment of the present invention for generating a first error signal by superposition. The adaptive control system includes an adaptive controller.

[0029] The reference acoustic sensor is used to preprocess the noise signal to generate a reference signal. Specifically, the reference acoustic sensor transmits the collected noise signal through a reference channel to generate a reference signal, which is then output to the adaptive controller. It should be understood that preprocessing, the process of converting the noise signal through the reference channel into a reference signal, aims to convert the original noise signal into a standard input signal suitable for processing by the adaptive controller, thereby ensuring the accuracy of subsequent secondary sound wave generation.

[0030] The adaptive controller is configured to filter a reference signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter. Specifically, the adaptive controller adjusts parameters according to a preset control objective to change the first noise reduction parameter. This process is repeated multiple times until the adaptive controller's convergence condition is met, resulting in the second noise reduction parameter.

[0031] The adaptive controller is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter.

[0032] It should be noted that after the composition structure of the transformer adaptive noise control device is determined, it is of great significance to optimize the parameters of the secondary sound source, which will directly affect the noise reduction effect of the device. As for the optimization of the parameters of the secondary sound source, it is generally carried out through analytical methods and optimization algorithms. The analytical method is to obtain the expression of the objective function when the sound field conditions can be determined, so as to optimize the parameters of the secondary sound source. Although this method is relatively simple and direct, it requires a very clear function expression in each step of the calculation. In a more complex sound field system, the steps of obtaining each function expression are cumbersome and the amount of calculation is large. Once a writing error in the function expression occurs, it may lead to solution failure. The optimization algorithm is more flexible than the analytical rule. It can continuously iterate to obtain the optimal solution of the objective function. Even for a more complex sound field system, it can be solved quickly.

[0033] Currently, the more common optimization algorithms include genetic algorithm and particle swarm algorithm. According to the characteristics of the transformer adaptive noise control device, the present invention selects genetic algorithm and combines different transformer equivalent sound source models to optimize the parameters of the secondary sound source.

[0034] Specifically, the secondary sound source parameters are divided into two groups: amplitude and phase angle, and position and number. Optimization is performed based on the genetic algorithm. The main optimization steps include: 1) Determine the source strength of the secondary sound source and, within a selected interval, use a genetic algorithm to combine and filter the amplitude and phase angle of the secondary sound source, selecting the amplitude and phase angle that maximizes noise reduction. The number of secondary sound sources is not limited and is randomly determined by the genetic algorithm. 2) The source strength of the secondary sound source is fixed according to the amplitude and phase angle determined in step 1), and then the genetic algorithm is used to select a combination of the position and number of secondary sound sources with better noise reduction effect. However, since the size of the number of secondary sound sources will affect the cost of the transformer adaptive noise control device, economic considerations should be appropriately considered when determining the combination of the position and number of secondary sound sources in this step; 3) Using the combination of the position and number of secondary sound sources determined in step 2), the genetic algorithm is used to further optimize the secondary sound source parameters determined in the first two steps to achieve further optimization of the noise reduction effect.

[0035] An embodiment of the present invention provides an adaptive noise control device for a transformer. The device first generates a first noise reduction parameter based on a reference sound sensor signal, obtains a second noise reduction parameter through preliminary superposition optimization, and then further optimizes the third noise reduction parameter based on a second error signal (actual noise reduction effect) collected by the error sound sensor, thereby forming a dual correction of "pre-filtering + real-time feedback", effectively improving the phase and amplitude matching between the secondary sound wave and the original noise, and can achieve fixed-point and directional control of the noise in the area around the transformer, thereby achieving active control of environmental noise.

[0036] like Figure 3 As shown, an embodiment of the present invention provides a noise control method, which is applied to the transformer adaptive noise control device as described above, comprising the steps of: S1. Real-time acquisition of the noise signal of the target transformer and preprocessing of the noise signal to obtain a reference signal; The reference acoustic sensor is installed near the target transformer to collect noise signals in real time, and the noise signals are converted into reference signals after being transmitted through the reference channel.

[0037] S2. performing secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; The secondary path is the path between the secondary sound source and the error sound sensor. Specifically, step S2 includes: 1) Initializing the transformer adaptive noise control device to obtain a first secondary path transfer function; The secondary paths are determined by the specific transformer adaptive noise control device. One path of noise reduction corresponds to two secondary paths. One path of error sound is collected by the sensor, and one path is superimposed and generated, and then identified. The purpose of initialization is to give the secondary path transfer function an initial value to facilitate subsequent path identification.

[0038] 2) performing convolution calculation on the reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; The physical meaning of convolution calculation is to let the input signal (reference signal) pass through a filter (first secondary path transfer function), and the output is the filtered signal (first noise reduction parameter).

[0039] 3) Superimposing the noise signal and the first noise reduction parameter to obtain a first error signal; The noise signal and the first noise reduction parameter have opposite phases, and sound wave cancellation can be achieved through superposition operation, thereby obtaining a first error signal.

[0040] 4) iteratively optimizing the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; The first error signal serves as a convergence condition for iterative optimization. When the first error signal is less than a preset threshold, i.e., when the first error signal is sufficiently small, the iterative optimization is terminated, and the second noise reduction parameter is output. It should be noted that the iterative optimization is performed by looping through steps 2) and 3), continuously adjusting the first secondary path transfer function until the first error signal is less than the preset threshold.

[0041] 5) Characterizing the first secondary path transfer function corresponding to the second noise reduction parameter as a secondary path transfer function.

[0042] In the secondary path identification, when the first secondary path transfer function is stable, the first secondary path transfer function finally obtained is the secondary path transfer function. In other words, the first secondary path transfer function corresponding to the second noise reduction parameter is the secondary path transfer function.

[0043] S3. Optimizing the secondary path transfer function based on the reference signal to obtain filter coefficients of the adaptive control system; specifically, step S3 includes: 1) performing convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; The physical meaning of convolution calculation is to let the input signal (reference signal) pass through a filter (secondary path transfer function), and the output is the filtered signal (second noise reduction parameter).

[0044] 2) generating an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; The secondary sound source generates an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal.

[0045] 3) The second error signal of the target noise reduction area is collected in real time, and the second noise reduction parameter is iteratively optimized by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; the error sound sensor is installed in the target noise reduction area, and the second error signal of the target noise reduction area (actual noise reduction effect) is collected in real time. The second error signal serves as the convergence condition of the iterative optimization. When the second error signal is less than the preset threshold, that is, when the second error signal is small enough, the iterative optimization is stopped, and the third noise reduction parameter is output at this time. It should be noted that the iterative optimization is performed by cyclically executing steps 1) to 2), continuously adjusting the secondary path transfer function until the second error signal is less than the preset threshold.

[0046] 4) The secondary path transfer function corresponding to the third noise reduction parameter is represented as a filter coefficient of the adaptive control system.

[0047] In the process of determining the filter coefficient, when the secondary path transfer function stabilizes, the secondary path transfer function finally obtained is the secondary path transfer function. In other words, the secondary path transfer function corresponding to the third noise reduction parameter is the filter coefficient of the adaptive control system.

[0048] S4, performing convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; The physical meaning of convolution calculation is to let the input signal (reference signal) pass through a filter (filter coefficient), and the output is the filtered signal (secondary path signal).

[0049] S5. Generate a target secondary sound wave based on the secondary path signal, so that the target secondary sound wave cancels the noise signal.

[0050] The secondary sound source generates a target secondary sound wave based on the secondary path signal so that the target secondary sound wave cancels the noise signal.

[0051] Based on the above noise control method, such as Figure 4 As shown, an embodiment of the present invention provides a noise control system, including: Reference signal determination module 01 is used to collect the noise signal of the target transformer in real time and preprocess the noise signal to obtain a reference signal; A secondary path identification module 02 is used to perform secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; Specifically, the secondary path identification module includes: an initialization unit for initializing the transformer adaptive noise control device to obtain a first secondary path transfer function; a first convolution calculation unit for performing a convolution calculation on a reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; a superposition operation unit, configured to superimpose the noise signal and the first noise reduction parameter to obtain a first error signal; a first iterative optimization unit, configured to iteratively optimize the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; The first characterization unit is configured to characterize the first secondary path transfer function corresponding to the second noise reduction parameter as a secondary path transfer function.

[0052] The coefficient determination module 03 is used to optimize the secondary path transfer function based on the reference signal to obtain the filter coefficients of the adaptive control system; Specifically, the coefficient determination module includes: a second convolution calculation unit, configured to perform a convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; a sound wave generation unit, configured to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; a second iterative optimization unit, configured to collect a second error signal of the target noise reduction area in real time, and iteratively optimize the second noise reduction parameter by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; The second characterization unit is configured to characterize the secondary path transfer function corresponding to the third noise reduction parameter as a filter coefficient of the adaptive control system.

[0053] The convolution calculation module 04 is used to perform convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; the cancellation sound wave generation module 05 is used to generate a target secondary sound wave based on the secondary path signal so that the target secondary sound wave cancels the noise signal.

[0054] It should be noted that the various modules in the aforementioned noise control system can be implemented in whole or in part through software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each of these modules. For the specific definition of a noise control system, please refer to the definition of a noise control method above. Both have the same functions and effects and will not be elaborated here.

[0055] An embodiment of the present invention further provides a terminal device, comprising: processor, memory, and bus; The bus is used to connect the processor and the memory; The memory is used to store operation instructions; The processor is configured to call the operation instruction, and the executable instruction enables the processor to perform the operation corresponding to the noise control method described above in the present invention.

[0056] In an optional embodiment, a terminal device is provided, such as Figure 5 As shown, Figure 5 The terminal device 5000 shown includes a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are connected, for example, via a bus 5002. Optionally, the terminal device 5000 may further include a transceiver 5004. It should be noted that in actual applications, the number of transceivers 5004 is not limited to one, and the structure of the terminal device 5000 does not constitute a limitation on the embodiments of the present invention.

[0057] Processor 5001 may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the present disclosure. Processor 5001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0058] The bus 5002 may include a path for transmitting information between the above components. The bus 5002 may be a PCI bus or an EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0059] The memory 5003 can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an EEPROM, CD-ROM or other optical disk storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0060] The memory 5003 is used to store application code for executing the solution of the present invention, and the execution is controlled by the processor 5001. The processor 5001 is used to execute the application code stored in the memory 5003 to implement the content shown in any of the above method embodiments.

[0061] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the noise control method of the present invention is implemented.

[0062] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0063] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0066] In summary, the embodiment of the present invention provides a transformer adaptive noise control device and its application, which first generates a first noise reduction parameter based on the reference sound sensor signal, obtains a second noise reduction parameter through preliminary superposition optimization, and then further optimizes it into a third noise reduction parameter in combination with the second error signal (actual noise reduction effect) collected by the error sound sensor, forming a dual correction of "pre-filtering + real-time feedback", effectively improving the phase and amplitude matching between the secondary sound wave and the original noise, and can realize fixed-point and directional regulation of the noise in the area around the transformer, so as to achieve active control of environmental noise.

[0067] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the various technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A transformer adaptive noise control device, characterized in that: include: Reference acoustic sensor, error acoustic sensor, adaptive control system and secondary acoustic source; The reference acoustic sensor is used to collect the noise signal of the target transformer in real time; The adaptive control system is configured to filter the noise signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter; The secondary sound source is used to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; The error sound sensor is used to collect the second error signal of the target noise reduction area in real time; The adaptive control system is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter; The secondary sound source is further configured to generate a target secondary sound wave based on the third noise reduction parameter, so that the target secondary sound wave cancels the noise signal.

2. The transformer adaptive noise control device according to claim 1, characterized in that: The adaptive control system includes an adaptive controller; The reference acoustic sensor is used to preprocess the noise signal to obtain a reference signal; The adaptive controller is configured to filter the reference signal to obtain a first noise reduction parameter, superimpose the noise signal and the first noise reduction parameter to obtain a first error signal, and optimize the first noise reduction parameter based on the first error signal to obtain a second noise reduction parameter; The adaptive controller is further configured to optimize the second noise reduction parameter based on the second error signal to obtain a third noise reduction parameter.

3. A noise control method, applied to the transformer adaptive noise control device according to any one of claims 1 to 2, characterized in that: include: Collecting the noise signal of the target transformer in real time, and preprocessing the noise signal to obtain a reference signal; performing secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; optimizing the secondary path transfer function based on the reference signal to obtain filter coefficients of the adaptive control system; Performing convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; A target secondary sound wave is generated based on the secondary path signal, so that the target secondary sound wave cancels the noise signal.

4. The noise control method according to claim 3, characterized in that: The performing secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function includes: Initializing the transformer adaptive noise control device to obtain a first secondary path transfer function; performing a convolution calculation on the reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; Superimposing the noise signal and the first noise reduction parameter to obtain a first error signal; iteratively optimizing the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; The first secondary path transfer function corresponding to the second noise reduction parameter is characterized as a secondary path transfer function.

5. The noise control method according to claim 4, characterized in that: The optimizing the secondary path transfer function based on the reference signal to obtain the filter coefficients of the adaptive control system includes: performing a convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; generating an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; collecting a second error signal of the target noise reduction area in real time, and iteratively optimizing the second noise reduction parameter by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; The secondary path transfer function corresponding to the third noise reduction parameter is represented as a filter coefficient of the adaptive control system.

6. A noise control system, applied to the noise control method according to any one of claims 3 to 5, characterized in that: include: A reference signal determination module is used to collect the noise signal of the target transformer in real time and preprocess the noise signal to obtain a reference signal; A secondary path identification module is used to perform secondary path identification on the transformer adaptive noise control device to obtain a secondary path transfer function; a coefficient determination module, configured to optimize the secondary path transfer function based on the reference signal to obtain filter coefficients of the adaptive control system; A convolution calculation module, configured to perform convolution calculation on the reference signal and the filter coefficient to obtain a secondary path signal; The cancellation sound wave generating module is used to generate a target secondary sound wave based on the secondary path signal, so that the target secondary sound wave cancels the noise signal.

7. The noise control system according to claim 6, characterized in that: The secondary path identification module includes: an initialization unit, configured to initialize the transformer adaptive noise control device to obtain a first secondary path transfer function; a first convolution calculation unit, configured to perform a convolution calculation on the reference signal and the first secondary path transfer function to obtain a first noise reduction parameter; a superposition operation unit, configured to superimpose the noise signal and the first noise reduction parameter to obtain a first error signal; a first iterative optimization unit, configured to iteratively optimize the first noise reduction parameter by adjusting the first secondary path transfer function based on the first error signal until the first error signal is less than a preset threshold, thereby obtaining a second noise reduction parameter; and a first characterization unit, configured to characterize the first secondary path transfer function corresponding to the second noise reduction parameter as a secondary path transfer function.

8. The noise control system according to claim 7, characterized in that: The coefficient determination module includes: a second convolution calculation unit, configured to perform a convolution calculation on the reference signal and the secondary path transfer function to obtain a second noise reduction parameter; a sound wave generating unit, configured to generate an initial secondary sound wave based on the second noise reduction parameter, so that the initial secondary sound wave cancels the noise signal; a second iterative optimization unit, configured to collect a second error signal of the target noise reduction area in real time, and iteratively optimize the second noise reduction parameter by adjusting the secondary path transfer function based on the second error signal until the second error signal is less than a preset threshold, thereby obtaining a third noise reduction parameter; The second characterization unit is configured to characterize the secondary path transfer function corresponding to the third noise reduction parameter as a filter coefficient of the adaptive control system.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the noise control method according to any one of claims 3 to 5 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the noise control method according to any one of claims 3 to 5.

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