Noise simulation method and device of transformer, storage medium and electronic equipment

Abstract

The invention discloses a noise simulation method and device of a transformer, a storage medium and electronic equipment. The method comprises steps that geometric information of a reference emission surface of a target transformer, an operation condition of the target transformer, and distance information between the target transformer and a sound measurement point are acquired, and the reference emission surface is a main radiation area of sound waves of the target transformer; based on the geometric information and the distance information, the sound pressure level of the target transformer under the operation condition is determined, and the sound pressure level is used for representing the sound pressure level of the simulation noise at the sound measurement point; based on the sound pressure level and the operation condition, adopting a pre-established standard spectrogram library to generate initial simulation noise; and performing correction processing on the initial simulation noise by adopting the gain coefficient to obtain target simulation noise of the target transformer. The technical problem that the accuracy of the generated analog noise of the transformer is low in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of power systems, and in particular to a transformer noise simulation method, device, storage medium, and electronic equipment. Background Art

[0002] With the increasing attention paid to noise pollution, the current control of noise nuisance and noise reduction facilities has been significantly strengthened. Due to the characteristics of new construction projects, major power equipment such as transformers have not yet been put into load operation, and the noise level generated is far lower than the noise intensity under rated operating conditions. This makes it difficult to verify the actual effectiveness of noise reduction facilities such as sound insulation screens and silencers used in the project. Therefore, a noise simulation device is needed that can accurately simulate the noise of transformers under various operating conditions. This device can replace the transformer's sound source output and verify the actual noise reduction effect of noise reduction facilities such as sound insulation screens and silencers used in the project.

[0003] In the related art, transformer noise simulation primarily relies on theoretical model-based noise simulation and fixed sound source simulation. Theoretical model-based noise simulation methods struggle to capture the complex noise characteristics generated by dynamic factors such as load fluctuations, equipment aging, and grid frequency changes during actual transformer operation. Fixed sound source simulations fail to consider the complex characteristics of transformer noise and are unable to effectively simulate the combined effects of multiple noise sources, including fundamental frequency harmonics, electromagnetic vibration noise, and high-frequency discharge noise. Consequently, the related art suffers from the low accuracy of the generated transformer noise simulation.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present application provide a transformer noise simulation method, device, storage medium, and electronic device to at least solve the technical problem of low accuracy of generated transformer simulated noise existing in the related art.

[0006] According to one aspect of an embodiment of the present application, a transformer noise simulation method is provided, comprising: obtaining geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the main radiation area of ​​sound waves of the target transformer; determining the sound pressure level of the target transformer under the operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; generating initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library; and correcting the initial simulated noise using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

[0007] According to another aspect of an embodiment of the present application, a transformer noise simulation device is provided, comprising: a data acquisition module for acquiring geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the main radiation area of ​​sound waves of the target transformer; a sound pressure level determination module for determining the sound pressure level of the target transformer under operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; an initial simulated noise generation module for generating initial simulated noise based on the sound pressure level and operating conditions using a pre-established standard spectrum library; and a target simulated noise determination module for correcting the initial simulated noise using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

[0008] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided. The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the transformer noise simulation methods.

[0009] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the transformer noise simulation methods.

[0010] In an embodiment of the present application, by obtaining geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the main radiation area of ​​the sound wave of the target transformer; based on the geometric information and the distance information, the sound pressure level of the target transformer under the operating conditions is determined, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; based on the sound pressure level and the operating conditions, an initial simulated noise is generated using a pre-established standard spectrum library; the initial simulated noise is corrected using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise. The purpose of determining the geometric information of the reference emission surface of the transformer, combining the operating conditions and the distance information, generating the initial simulated noise using the standard spectrum library, and then correcting the initial simulated noise using the gain coefficient is achieved, thereby achieving the technical effect of improving the accuracy and reliability of the generated simulated noise of the transformer, thereby solving the technical problem of low accuracy of the simulated noise of the generated transformer existing in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0012] Figure 1 is a flow chart of an optional transformer noise simulation method provided according to an embodiment of the present application;

[0013] Figure 2 is a block diagram of an optional method for determining the sound pressure level of a transformer provided in an embodiment of the present application;

[0014] Figure 3 is a schematic diagram of an optional sound source simulation device provided according to an embodiment of the present application;

[0015] Figure 4 This is a schematic diagram of an optional transformer noise simulation device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0017] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] According to an embodiment of the present application, a method embodiment of a transformer noise simulation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0019] Figure 1 is a flow chart of an optional transformer noise simulation method provided in an embodiment of the present application, such as Figure 1 As shown, the method includes the following steps:

[0020] Step S102, obtaining geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is a main radiation area of ​​sound waves of the target transformer;

[0021] It can be understood that obtaining geometric information about the reference emitting surface representing the primary sound wave radiation area of ​​the target transformer to be simulated, information about the target transformer's operating conditions, and information about the distance between the target transformer and the sound measurement point is essential. Combining this information with the distance parameter allows for more accurate calculation of the sound pressure level output by the sound source, thereby improving the consistency between the noise output by the sound source simulation device and the actual noise of the target transformer.

[0022] Optionally, the reference emission surface refers to the primary radiation area of ​​the transformer's sound waves. This area may vary for different transformer types. For example, for an oil-immersed transformer or a dry-type transformer with a protective casing, the reference emission surface may be the outer surface of the oil tank or protective casing; for a dry-type transformer without a protective casing, the reference emission surface may be the core and its frame.

[0023] Step S104: determining the sound pressure level of the target transformer under operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point;

[0024] It can be understood that the sound pressure level of the target transformer under operating conditions is calculated based on the geometric information of the target transformer's reference emitting surface and the distance between the target transformer and the sound measurement point, where the sound pressure level represents the sound pressure level of the simulated noise at the sound measurement point. By accurately calculating the sound pressure level of the target transformer, it is possible to ensure that the noise output by the sound source simulation device is highly consistent with the noise characteristics of the transformer under actual operating conditions, thereby improving the accuracy of the noise simulation. At the same time, by adjusting the sound pressure level of the simulated noise according to the different operating conditions of the transformer (such as load changes and temperature fluctuations), it is possible to simulate noise under various operating conditions, meeting the diverse needs of transformer noise testing and project acceptance.

[0025] In an optional embodiment, determining the sound pressure level of a target transformer under operating conditions based on geometric information and distance information includes: determining the sound power of the target transformer based on the distance information and sound pressure information of a sound measurement point included in the operating conditions; and determining the sound pressure level based on the sound power and geometric information.

[0026] As can be understood, the target transformer's acoustic power is calculated based on the sound pressure information at the sound measurement point, as included in the target transformer's operating conditions, combined with the distance information between the target transformer and the sound measurement point. The target transformer's sound pressure level is determined based on the target transformer's sound power and the geometric information of the target transformer's reference emitting surface. By predicting the sound pressure level based on geometric and distance information, the sound source simulation device can more accurately replicate the acoustic characteristics of the target transformer under different operating conditions, improving the accuracy and reliability of the simulated noise.

[0027] Alternatively, sound power refers to the total amount of sound energy radiated by a sound source per unit time, expressed in watts (W). Sound power is an indicator that describes the intensity of a sound source, reflecting the radiation capability of the sound source in a free field, and is not affected by obstacles or reflectors that may be encountered in the sound wave propagation path. Sound power is an inherent property of a sound source, which is related to the structure, material, and working state of the sound source, and has nothing to do with the position of the observer or measuring device. Sound pressure level is a quantitative indicator that describes the intensity of sound, reflecting the instantaneous pressure change caused by the sound wave on the medium (such as air) at a specific measurement point, expressed in decibels (dB) relative to the reference value. The sound pressure level is affected by factors such as the medium characteristics, distance, obstacles, and reflections in the sound wave propagation path, and is directly related to the position of the measurement point.

[0028] Optionally, Figure 2 This is a block diagram of an optional method for determining the transformer sound pressure level according to an embodiment of the present application, which can be used as follows: Figure 2 The sound pressure level of the target transformer is determined in the following manner: First, the sound power under rated operating conditions is obtained; second, the sound power of the transformer under certain sound pressure conditions is obtained; and finally, the sound pressure level at different output locations is determined.

[0029] Optionally, to obtain the sound power under rated conditions, the sound pressure level limit requirements for transformers of different models, voltage levels, and capacities under rated conditions can be determined based on the transformer procurement standards. Since the sound pressure level of the transformer is affected by the measurement distance and radiation range, according to relevant standards, a stable sound power level can be used to convert the sound pressure level. The conversion relationship between the sound power level under rated conditions and the sound pressure level under rated conditions can be determined as follows:

[0030]

[0031] S=1.25hl m

[0032] Among them, L wA Indicates the sound power level under rated operating conditions; Indicates the sound pressure level under rated working conditions; S represents the area of ​​the measurement surface, 0.3m away from the reference emission surface; l mIt represents the height in m (meter). For oil-immersed transformers or dry-type transformers with protective casings, it refers to the height of the oil tank or protective casing. For dry-type transformers without protective casings, it refers to the height of the core and its frame. h represents the circumference of the specified contour line in m. 1.25 represents the empirical coefficient of the sound energy emitted from the upper part.

[0033] Optionally, to obtain the sound power of the transformer under certain sound pressure conditions, the sound pressure level of the transformer can be calculated based on the simulated transformer size and the sound pressure at the sound measurement point. Using the sound power level limits of different capacity types as the standard, and based on the conversion formula between sound power and sound pressure, the sound pressure level that should be output at the simulated sound source location (i.e., the sound pressure level that should be output by the target transformer) r (i.e., distance information, generally 1m) is obtained. In a free sound field, the relationship between sound intensity and sound pressure can be determined as follows:

[0034] I=p 2 / ρc

[0035] Among them, p represents sound pressure, which is the instantaneous pressure change caused by sound waves, and the unit is Pa (Pascal); I represents sound intensity, which is the sound power per unit area, and the unit is watts per square meter; ρ represents the medium density, which is about 1.2 kg / m (kilograms per meter) in air; c represents the speed of sound, which is about 343 m / s (meters per second) in air.

[0036] Sound power is the integral of the sound intensity over the propagation area. For a point sound source, the sound power in a free field (spherical wave propagation) can be determined as follows:

[0037] W=I4πr 2

[0038] Where r is the distance between the sound measurement point and the sound source, measured in meters; W is the sound power, which is the total energy radiated by the sound source per unit time, measured in watts.

[0039] Optionally, to determine the sound pressure levels output at different locations, the relationship between the sound pressure level and the sound power in the free field can be determined based on the conversion relationship between the sound power level under rated operating conditions and the sound pressure level under rated operating conditions, as well as the relationship between the sound pressure and the sound power in the free field. The relationship between the sound pressure level and the sound power in the free field can be determined in the following manner:

[0040] Lp=Lw-20log 10 (r)-11

[0041] Wherein, Lw represents the sound power level; Lp represents the sound pressure level.

[0042] Optionally, the relationship between the sound pressure level and the sound power in the free field is derived as follows: I = p 2Substitute / ρc into the formula W=I4πr 2 In this case, the sound power can be obtained based on the distance information and the sound pressure information at the sound measurement point. The sound power W is then converted into decibels to obtain the sound power level Lw. Based on the conversion relationship between the sound power level under rated operating conditions and the sound pressure level under rated operating conditions, the sound pressure level corresponding to the sound power level Lw is determined, and the sound pressure level Lp that the transformer should output can be obtained. For example, if the sound power level of a transformer is Lw = 95dB, and the sound pressure level at a distance of r = 10m is calculated, the formula Lp = 95-20log 10 (10)-11, it can be calculated that the sound pressure level that the transformer should output is: 95-20-11=64dB.

[0043] Step S106 , generating initial simulated noise based on the sound pressure level and operating conditions using a pre-established standard spectrum library;

[0044] As can be understood, the initial simulated noise for the target transformer is generated using a sound source simulator based on the target transformer's sound pressure level and operating conditions, using a pre-established standard spectrum library. Using the standard spectrum library ensures that the spectral characteristics of the simulated noise are highly consistent with the noise characteristics of the target transformer, improving the accuracy of the simulated noise and reducing errors introduced by models or assumptions.

[0045] In an optional embodiment, before generating the initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library, the method further includes: collecting noise data corresponding to a test transformer of the same type as the target transformer under multiple operating conditions; preprocessing the noise data of any of the multiple operating conditions to obtain preprocessed noise data of any operating condition; performing principal component analysis based on the preprocessed noise data to obtain noise data corresponding to multiple different frequency bands of any operating condition; determining a spectrum curve of any operating condition based on the noise data corresponding to the multiple different frequency bands, wherein the spectrum curve is used to describe the distribution characteristics of the preprocessed noise data in the frequency domain, the horizontal axis of the spectrum curve represents the frequency, and the vertical axis represents the sound pressure level; using the method of determining the spectrum curve of any operating condition to obtain multiple spectrum curves, wherein the multiple spectrum curves correspond one-to-one to the multiple operating conditions; and establishing a standard spectrum library based on the multiple spectrum curves.

[0046] It is understood that before using a sound source simulation device to perform noise simulation on a target transformer, a standard spectrum library must be established in advance. To establish this standard spectrum library, noise data corresponding to multiple operating conditions of a test transformer of the same type as the target transformer can first be collected. For any of the multiple operating conditions, the noise data for that condition is preprocessed, such as by removing abnormal data, performing mean processing, and performing frequency weighting, to obtain preprocessed noise data for that condition. Principal component analysis is then used to separate the preprocessed noise data for each condition, obtaining noise data corresponding to multiple frequency bands for each condition. Based on the noise data corresponding to each of the multiple frequency bands, a spectrum curve is constructed for each condition, describing the distribution characteristics of the preprocessed noise data in the frequency domain. The horizontal axis of the spectrum curve represents frequency, and the vertical axis represents sound pressure level. Using the aforementioned method for determining the spectrum curve for any condition, spectrum curves corresponding to each of the multiple conditions are determined, resulting in multiple spectrum curves. Based on these multiple spectrum curves, a standard spectrum library for the target transformer is constructed. By carefully analyzing and processing the noise data of the test transformer under different operating conditions, the true acoustic characteristics of the transformer during operation can be captured more accurately, thereby improving the accuracy of the simulated noise output by the sound source simulation device.

[0047] Optionally, noise data of a test transformer of the same type as the target transformer under different operating conditions (load rate, temperature, operating time, etc.) can be collected. A standard acoustic sensor (such as a 1 / 3 octave band analyzer) can be used to record the sound pressure level spectrum (frequency range: 20Hz-20kHz) of the collected noise data. During the collection process, the measurement environment should be consistent (such as background noise <30dBA, that is, the noise level is 30 decibels after A-weighting adjustment) to avoid data errors caused by external interference. The collected noise data is preprocessed, and the preprocessing may at least include: using abnormal data removal (such as sudden noise interference) to remove abnormal data in the noise data; taking the average of multiple groups of data to reduce the random error of the noise data; and applying frequency weighting (such as A-weighting) to process the noise data so that the noise data can better reflect the human ear perception characteristics. After preprocessing the noise data, we perform sound source separation on the data. Spectral analysis is used to identify the main noise components, such as fundamental frequency noise (50 / 60 Hz and its harmonics) from core magnetostriction, electromagnetic vibration noise (100-1000 Hz) caused by winding vibration and structural resonance, and high-frequency discharge noise (2-20 kHz) caused by partial discharge due to insulation aging. Principal Component Analysis (PCA) can be used to separate the different sound sources and eliminate noise data with a frequency range with a compliance rate below 95%.

[0048] Optionally, the noise data can be frequency-weighted using A-weighting. A-weighting is designed based on the equal loudness curve, which describes the sensitivity of the human ear to sounds of different frequencies and intensities. Through A-weighting, the noise data can be corrected to make it closer to the actual perception of the human ear. First, noise data under different working conditions (such as load rate changes, temperature fluctuations, etc.) are collected. These data contain the sound pressure levels of multiple frequency components. Then, the sound pressure level of each frequency point is adjusted using the A-weighting network. The A-weighting network will give lower weights in the low-frequency band and higher weights in the mid- and high-frequency bands, so that the adjusted sound pressure level is more in line with the auditory characteristics of the human ear.

[0049] Optionally, the principal component analysis method can be used to separate the sound sources of the noise data, identify the main noise components in the noise data, and eliminate the noise data in the frequency range with a compliance rate of less than 95%. That is, the frequency components that contribute little to the overall noise and may be random noise or non-critical noise sources are removed, ensuring that the sound source simulation device more accurately reproduces the main noise characteristics during transformer operation, reduces noise interference in the non-critical frequency range, improves the reliability of the noise reduction facility effect evaluation, and avoids test errors caused by irrelevant factors in the simulated noise.

[0050] In an optional embodiment, based on noise data corresponding to multiple different frequency bands, a frequency spectrum curve of any working condition is determined, including: based on the noise data corresponding to multiple different frequency bands, normalizing the noise data using weights corresponding to multiple different frequency bands to obtain normalized data of any working condition; performing statistical analysis on the normalized data to determine the mean sound pressure levels corresponding to multiple frequencies included in the normalized data, and the sound pressure level variances corresponding to the multiple frequencies; based on the mean sound pressure levels corresponding to the multiple frequencies, and the sound pressure level variances corresponding to the multiple frequencies, determining the confidence intervals corresponding to the multiple frequencies, wherein the confidence intervals represent the degree of uncertainty of the normalized data; based on the mean sound pressure levels corresponding to the multiple frequencies, and the confidence intervals corresponding to the multiple frequencies, the frequency spectrum curve of any working condition is determined.

[0051] It can be understood that for noise data corresponding to multiple different frequency bands under any operating condition, normalization processing is performed using weights corresponding to different frequency bands to obtain normalized data for any operating condition. Statistical analysis is performed on the normalized data, such as taking the mean and variance, to obtain the mean sound pressure level corresponding to the multiple frequencies included in the normalized data, as well as the sound pressure level variance corresponding to the multiple frequencies. Based on the mean sound pressure level corresponding to the multiple frequencies and the sound pressure level variance corresponding to the multiple frequencies, confidence intervals corresponding to the multiple frequencies are determined, representing the degree of uncertainty in the normalized data. Based on the mean sound pressure level corresponding to the multiple frequencies and the confidence intervals corresponding to the multiple frequencies, a frequency spectrum curve for any operating condition is constructed. Through normalization and statistical analysis, the noise spectrum curve of the target transformer under any operating condition can be more accurately simulated. At the same time, by introducing confidence intervals, the reliability of the data is enhanced, so that the noise simulation result is not only an estimate but also includes a quantitative assessment of the error range, thereby improving the reliability of the simulated noise.

[0052] Optionally, determine the characteristic parameters of the preprocessed noise data and extract parameters such as the peak amplitude, center frequency, and bandwidth of each frequency band. Calculate the total sound power level and the frequency band contribution ratio, that is, the percentage of the sound power in each frequency range in the total sound power. Using predetermined test conditions as a benchmark, determine the importance of the sound source based on the frequency band contribution ratio, and determine the weight corresponding to the frequency band based on the importance of the sound source, for example, fundamental frequency noise accounts for 60%, electromagnetic vibration noise accounts for 30%, and high-frequency discharge noise accounts for 10%. Under the above-mentioned benchmark conditions, perform frequency band weighted normalization on the preprocessed noise data using the weights corresponding to the frequency bands to obtain normalized data.

[0053] Optionally, a statistical analysis is performed on the normalized multiple sets of frequency spectra (i.e., normalized data) to determine the mean sound pressure level corresponding to the multiple frequencies included in the normalized data, as well as the sound pressure level variance corresponding to the multiple frequencies. The mean sound pressure level corresponding to the multiple frequencies and the sound pressure level variance corresponding to the multiple frequencies can be determined by:

[0054]

[0055] Where μ(f) represents the mean sound pressure level corresponding to frequency f; σ(f) represents the variance of the sound pressure level corresponding to frequency f; N represents the total number of N sets of spectra; i represents the i-th set of spectra; s norm ,i(f) represents the sound pressure level corresponding to frequency f in the i-th group of spectrum.

[0056] Optionally, confidence intervals corresponding to the multiple frequencies can be determined based on the mean sound pressure levels corresponding to the multiple frequencies and the variances of the sound pressure levels corresponding to the multiple frequencies, for example, using μ±2σ as the confidence interval of the normalized data. After determining the mean sound pressure levels corresponding to the multiple frequencies, the variances of the sound pressure levels corresponding to the multiple frequencies, and the confidence intervals corresponding to the multiple frequencies, a frequency spectrum curve containing the confidence intervals is drawn.

[0057] Optionally, after drawing the spectrum curve including the confidence interval, the frequency bands and amplitudes of the main noise components can be annotated with the mean μ(f) as the core to determine the spectrum of the noise data. Table 1 shows an example of the spectrum format.

[0058] Table 1 Spectrum format examples

[0059] Frequency (Hz) Sound pressure level (dBA) Noise type Contribution ratio 50 65 Fundamental noise 60％ 100 58 Electromagnetic vibration 25％ 8000 42 High-frequency discharge 10％ other 50 other 5％

[0060] In an optional embodiment, a standard spectrum library is established based on multiple spectrum curves, including: for any spectrum curve among the multiple spectrum curves, based on the average sound pressure levels corresponding to the multiple frequencies included in any spectrum curve, and the actual sound pressure levels corresponding to the multiple frequencies included in the actual spectrum curve of the test transformer under the corresponding working conditions, determining the first sound pressure level errors corresponding to the multiple frequencies respectively; determining the root mean square error of any spectrum curve based on the first sound pressure level errors corresponding to the multiple frequencies respectively, wherein the root mean square error is used to indicate the degree of similarity between any spectrum curve and the actual spectrum curve; determining the verification result of any spectrum curve based on the root mean square error and a preset error threshold, wherein the verification result is used to indicate the validity of the spectrum curve; determining the verification results corresponding to the multiple spectrum curves respectively by adopting the method of determining the verification result of any spectrum curve; and establishing a standard spectrum library based on the verification results corresponding to the multiple spectrum curves respectively.

[0061] It can be understood that for any of the multiple spectrum curves, an error analysis is performed based on the mean sound pressure levels corresponding to the multiple frequencies included in the spectrum curve and the actual sound pressure levels corresponding to the multiple frequencies included in the actual spectrum curve corresponding to the spectrum curve, to determine the first sound pressure level errors corresponding to the multiple frequencies. The actual spectrum curve is obtained by testing a test transformer of the same type as the target transformer under the operating conditions corresponding to the spectrum curve. Based on the first sound pressure level errors corresponding to the multiple frequencies, a root mean square error (RMS) is determined, representing the degree of similarity between the spectrum curve and the actual spectrum curve. This RMS error is compared with a pre-set error threshold to obtain a verification result, and the validity of the spectrum curve is determined based on the verification result: if the RMS error is less than the error threshold, the spectrum curve is valid; if the RMS error is greater than or equal to the error threshold, the spectrum curve is invalid. Multiple spectrum curves are verified using the same verification method for any spectrum curve, obtaining verification results corresponding to each of the multiple spectrum curves. A standard spectrum graph library is constructed based on the spectrum curves indicated as valid in the multiple verification results. By calculating and evaluating the root mean square error, the accuracy and reliability of any spectrum curve in the standard spectrum library can be ensured, and the reliability of the standard spectrum library and the accuracy of the simulated noise generated based on the standard spectrum library can be improved.

[0062] Optionally, the data in the spectrum graph determined according to the spectrum curve can be compared with the data in the spectrum graph determined according to the actual spectrum curve and an error analysis can be performed to determine the root mean square error of the spectrum curve. The root mean square error of the spectrum curve can be determined by:

[0063]

[0064] Among them, RMSE represents the root mean square error of the spectrum curve; μ(f i ) represents the frequency f i The average sound pressure level; S 实测，j represents the jth group of actual spectrum curves; M represents a total of M groups of actual spectrum curves.

[0065] If RMSE < 1dBA, the spectrum is considered valid, and the spectrum curve corresponding to the spectrum is valid; if RMSE < 1dBA, the spectrum is considered invalid, and the spectrum curve corresponding to the spectrum is invalid.

[0066] Step S108 : Correcting the initial simulated noise using a gain coefficient to obtain a target simulated noise of a target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

[0067] It can be understood that the initial simulated noise is corrected using a gain factor corresponding to the initial simulated noise, which is used to adjust or compensate for the initial simulated noise, to obtain the target simulated noise of the target transformer. Using the gain factor to correct the initial simulated noise can reduce the output error of the sound source simulation device, making the initial simulated noise more closely match the noise characteristics of the target transformer, and improving the accuracy and consistency of the simulated noise.

[0068] In an optional embodiment, before using the gain coefficient to correct the initial simulated noise to obtain the target simulated noise of the target transformer, the method also includes: obtaining a simulated spectrum curve of the test transformer under operating conditions, and a standard spectrum curve, wherein the simulated spectrum curve is generated by using a sound source simulation device, and the standard spectrum curve is obtained when the test transformer is under operating conditions; based on the simulated spectrum curve and the standard spectrum curve, determining the frequency response function of the sound source simulation device, wherein the frequency response function is used to indicate the degree of amplification or attenuation of noise data of different frequencies by the sound source simulation device; based on the frequency response function, inverse filtering the simulated spectrum curve to obtain a corrected spectrum curve; based on the corrected spectrum curve, determining a gain coefficient set of the test transformer under operating conditions, wherein the gain coefficient set includes multiple gain coefficients; and determining the gain coefficient from the gain coefficient set based on the frequency of the initial simulated noise.

[0069] It can be understood that a sound source simulation device is used to generate a simulated spectrum curve of the simulated noise generated under the aforementioned operating conditions for a test transformer of the same type as the target transformer. A standard spectrum curve for the test transformer under the aforementioned operating conditions is also obtained. Based on a comparative analysis of the simulated spectrum curve and the standard spectrum curve, the frequency response function of the sound source simulation device is determined. This frequency response function indicates the degree to which the sound source simulation device amplifies or attenuates noise data of different frequencies. Based on the frequency response function, the simulated spectrum curve is corrected using inverse filtering to obtain a simulated spectrum curve. Further comparative analysis is performed between the simulated spectrum curve and the standard spectrum curve to determine a set of gain coefficients for the test transformer under the aforementioned operating conditions. The gain coefficient set includes multiple gain coefficients. Based on the frequency of the initial simulated noise, the gain coefficient corresponding to the initial simulated noise is determined from the gain coefficient set. By accurately calculating the frequency response function of the sound source simulation device and correcting it using inverse filtering techniques, the consistency of the simulated noise with the actual noise of the target transformer is improved, thereby enhancing simulation accuracy.

[0070] Optionally, laboratory verification is required to ensure that the spectrum curve of the sound source simulator is consistent with that of a standard sound source (i.e., the target transformer). Testing is conducted in a fully anechoic chamber under the aforementioned benchmark conditions to ensure the stability of the acoustic characteristics of the test environment and to prevent ambient noise from affecting the measurement results. A computer controls the output signal of the pulse (acoustic measurement and analysis system). The pulse output is split into two standard noise signals: one is input to the pulse input, and the other is connected to the sound source simulator via a power amplifier. These standard noise signals can be generated using a test transformer identical to the target transformer under specific operating conditions. A microphone is placed in front of the sound source simulator, one meter from its center and perpendicular to its radiation surface. The simulated noise emitted by the sound source simulator is received by the microphone and then input to the pulse input. Under normal operating conditions, the pulse compares the standard spectrum curve of the standard noise signal with the simulated spectrum curve of the simulated noise signal emitted by the sound source simulator to calculate the frequency response of the sound source simulator. Based on this frequency response, the frequency response function of the sound source simulator is determined.

[0071] Optionally, the sound source simulation device may be subjected to inverse filtering based on the aforementioned frequency response function to ensure that the simulated noise produced by the sound source simulation device more closely matches the actual noise level at the scene. A standard sound source supplement coefficient (i.e., a gain coefficient) may be obtained based on the sound pressure level spectrum (i.e., a modified spectrum curve) of the simulated noise output by the sound source simulation device after processing.

[0072] In an optional embodiment, based on the modified spectrum curve, a set of gain coefficients of the test transformer in the operating condition is determined, including: for any frequency among the multiple frequencies included in the modified spectrum curve, determining any sound pressure level of any frequency and the standard sound pressure level of any frequency; determining a second sound pressure level error corresponding to any frequency based on any sound pressure level and the standard sound pressure level; determining a gain coefficient of any frequency based on the second sound pressure level error; determining the gain coefficients corresponding to the multiple frequencies included in the modified spectrum curve respectively by adopting a method of determining the gain coefficient of any frequency; and determining a gain coefficient set based on the gain coefficients corresponding to the multiple frequencies included in the modified spectrum curve.

[0073] It can be understood that for any frequency among the multiple frequencies included in the corrected spectrum curve, an error analysis is performed based on the sound pressure level of any of the above frequencies determined according to the corrected spectrum curve, as well as the standard sound pressure level of the frequency corresponding to any frequency in the standard spectrum curve, to determine the second sound pressure level error corresponding to any frequency. Based on the second sound pressure level error, the gain coefficient of any frequency is determined. By determining the gain coefficient of any frequency, the gain coefficients corresponding to the multiple frequencies included in the corrected spectrum curve are determined, and a set of gain coefficients for the test transformer is constructed based on the gain coefficients corresponding to the multiple frequencies included in the corrected spectrum curve. The use of the gain coefficient enables the sound source simulation device to accurately adjust the gain of the simulated noise, thereby improving the matching degree between the simulated noise and the actual noise of the target transformer.

[0074] Optionally, the gain coefficient set of the above-mentioned test transformer under the above-mentioned operating conditions can be determined, and the gain coefficient sets of various types of transformers under multiple operating conditions can be determined, and then a standard gain coefficient library for the target transformer can be constructed, so as to facilitate the subsequent rapid determination of the corresponding gain coefficient according to the type and operating conditions of the transformer.

[0075] Optionally, the method for determining the gain coefficient can be determined based on the transformer's requirements for simulated noise accuracy. For scenarios where the transformer's simulated noise accuracy requirements are high, the gain coefficients corresponding to the multiple frequencies included in the corrected spectrum curve are determined, and the corresponding gain coefficients are selected for correction based on the frequency of the initial simulated noise. For scenarios where the transformer's simulated noise accuracy requirements are low, the multiple frequencies included in the corrected spectrum curve can be divided into multiple frequency bands, and the gain coefficients corresponding to the multiple frequency bands are determined. The gain coefficients corresponding to the frequency bands are used to correct the different frequency bands of the initial simulated noise.

[0076] Through the above steps S102 to S108, the purpose of determining the geometric information of the transformer reference emission surface, combining the operating conditions and distance information, generating the initial simulated noise using the standard spectrum library, and then correcting the initial simulated noise using the gain coefficient can be achieved, thereby achieving the technical effect of improving the accuracy and reliability of the generated transformer simulated noise, thereby solving the technical problem of low accuracy of the generated transformer simulated noise existing in the related art.

[0077] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation method of a transformer noise simulation method.

[0078] Current transformer noise simulation faces the following problems: First, the target transformer's sound source is missing or insufficient. During the project acceptance phase, the transformer has not yet been operated under load, and the actual target transformer's sound source intensity is far lower than the rated operating conditions (usually only 10%-30% of the rated noise), making it impossible to test noise reduction facilities in a real noise environment. For example, during the acceptance of a 110kV (kilovolt) substation, the noise level of the no-load transformer was only 45dBA, while the noise level could reach 75dBA when operating at full load, a significant difference. Second, the ability to simulate dynamic operating conditions is lacking. Existing sound source simulation devices are mostly fixed sound sources (such as white noise generators) that can only output sound signals of a single frequency and fixed amplitude. They are unable to reproduce the acoustic characteristics of the transformer (such as fundamental harmonic noise, electromagnetic vibration noise, and insulation material discharge noise) under complex operating conditions such as load fluctuations, aging, and grid frequency offsets.

[0079] In the related art, the noise simulation method for transformers has the following deficiencies. First, it is impossible to adjust the parameters of the simulated noise according to the actual operating conditions, equipment model, voltage level and other parameters of the transformer, resulting in a significant deviation between the test results and the actual results. Secondly, it can only simulate a single fundamental frequency noise, and cannot simulate complex noises such as electromagnetic vibration noise and high-frequency discharge noise. Finally, the simulated noise errors in the low and medium frequency bands generated by the sound source simulation device are large. In response to the above problems, this embodiment proposes a noise simulation method for transformers that can adjust acoustic parameters and support simulation of multiple operating conditions to solve the problems of insufficient simulation accuracy, a single noise source, and large sound source output errors in the related art. The method specifically includes:

[0080] Step S1: determining the sound pressure level of the output simulated noise.

[0081] Use Figure 2 The sound pressure level of the target transformer is determined in the following manner. First, the sound power under rated operating conditions is obtained; second, the sound power of the corresponding area is obtained; and finally, the sound pressure level of the output at different locations is determined, specifically including:

[0082] Step S11: Obtain the sound power under rated operating conditions. Based on transformer procurement standards, determine the sound pressure level limits under rated operating conditions for transformers of different models, voltage levels, and capacities. Because the sound pressure level of a transformer is affected by the measurement distance and radiation range, a stable sound power level is used to convert the sound pressure level according to relevant standards. The method for determining the conversion relationship between the sound power level under rated operating conditions and the sound pressure level under rated operating conditions is the same as in the above embodiment and will not be repeated here.

[0083] Step S12, obtain the sound power of the transformer under the determined sound pressure conditions. According to the simulated transformer size and the sound pressure at the sound measurement point, calculate the sound pressure level of the transformer. Taking the sound power level limit of different capacity types as the standard, according to the conversion formula of sound power and sound pressure, obtain the sound pressure level that should be output at the simulated sound source placement (i.e., the sound pressure level that should be output by the target transformer) r (i.e., distance information, generally 1m is selected). In the free sound field, the relationship between sound intensity and sound pressure is determined in the same way as in the above embodiment and will not be repeated here.

[0084] The sound power is the integral of the sound intensity over the propagation area. For a point sound source, the sound power in a free field (spherical wave propagation) is determined in the same manner as in the above embodiment and will not be described in detail here.

[0085] Step S13: Determine the sound pressure levels output at different locations. The relationship between the sound pressure level and the sound power in the free field is determined based on the conversion relationship between the sound power level under rated operating conditions and the sound pressure level under rated operating conditions, as well as the relationship between sound pressure and sound power in the free field. The method for determining the relationship between the sound pressure level and sound power in the free field is the same as in the above embodiment and will not be repeated here.

[0086] The derivation process of the relationship between sound pressure level and sound power in the free field is: I = p 2 Substitute / ρc into the formula W=I4πr 2 In this case, the sound power can be obtained based on the distance information and the sound pressure information at the sound measurement point. The sound power W is then converted into decibels to obtain the sound power level Lw. Based on the conversion relationship between the sound power level under rated operating conditions and the sound pressure level under rated operating conditions, the sound pressure level corresponding to the sound power level Lw is determined, and the sound pressure level Lp that the transformer should output can be obtained. For example, if the sound power level of a transformer is Lw = 95dB, and the sound pressure level at a distance of r = 10m is calculated, the formula Lp = 95-20log 10 (10)-11, it can be calculated that the sound pressure level that the transformer should output is: 95-20-11=64dB.

[0087] Step S2, establishing a standard spectrum library, specifically includes:

[0088] Step S21: data collection and preprocessing.

[0089] Collect noise data from test transformers of the same type as the target transformer under different operating conditions (load rate, temperature, operating time, etc.). Use a standard acoustic sensor (such as a 1 / 3 octave band analyzer) to record the sound pressure level spectrum (frequency range: 20Hz-20kHz) of the collected noise data. During the collection process, ensure that the measurement environment is consistent (such as background noise <30dBA, that is, the noise level is less than 30 decibels after A-weighting adjustment) to avoid data errors caused by external interference. Preprocess the collected noise data, including: using abnormal data removal (such as sudden noise interference) to remove abnormal data in the noise data; taking the average of multiple groups of data to reduce the random error of the noise data; and applying frequency weighting (such as A-weighting) to process the noise data so that the noise data can better reflect the human ear perception characteristics.

[0090] Step S22: sound source decomposition, feature extraction and normalization processing.

[0091] After preprocessing the noise data, we perform sound source separation on the data. Spectral analysis identifies the main noise components, such as fundamental frequency noise (50 / 60 Hz and its harmonics) from core magnetostriction, electromagnetic vibration noise (100-1000 Hz) caused by winding vibration and structural resonance, and high-frequency discharge noise (2-20 kHz) caused by partial discharge due to insulation aging. Principal Component Analysis (PCA) is used to separate the different sound sources, and noise data with a frequency range below 95% matching is removed.

[0092] For noise data that has completed sound source decomposition, feature extraction is performed to determine its characteristic parameters. Parameters such as the peak amplitude, center frequency, and bandwidth of each frequency band are extracted. The total sound power level and frequency band contribution ratio are calculated, that is, the percentage of sound power in each frequency range in the total sound power. Using predetermined test conditions as a benchmark, the importance of the sound source is determined based on the frequency band contribution ratio, and the weights corresponding to the frequency bands are determined based on the importance of the sound source. For example, fundamental frequency noise accounts for 60%, electromagnetic vibration noise accounts for 30%, and high-frequency discharge noise accounts for 10%. Under the above benchmark conditions, the pre-processed noise data is subjected to frequency band weighted normalization using the weights corresponding to the frequency bands to obtain normalized data.

[0093] Step S23: Generate a frequency spectrum curve.

[0094] Statistical analysis is performed on the normalized frequency spectra to determine the mean sound pressure level corresponding to each of the multiple frequencies included in the normalized data, as well as the sound pressure level variance corresponding to each of the multiple frequencies. The method for determining the mean sound pressure level corresponding to each of the multiple frequencies and the sound pressure level variance corresponding to each of the multiple frequencies is the same as in the above embodiment and is not further described here.

[0095] Confidence intervals corresponding to the multiple frequencies are determined based on the mean sound pressure levels corresponding to the multiple frequencies and the variances of the sound pressure levels corresponding to the multiple frequencies. In an optional embodiment, μ±2σ is used as the confidence interval. After the mean sound pressure levels corresponding to the multiple frequencies, the variances of the sound pressure levels corresponding to the multiple frequencies, and the confidence intervals corresponding to the multiple frequencies are determined, a frequency spectrum curve including the confidence intervals is plotted.

[0096] Step S24: Generate a frequency spectrum graph.

[0097] After drawing the spectrum curve including the confidence interval, we use the mean μ(f) as the core and annotate the frequency bands and amplitudes of the main noise components to determine the spectrum of the noise data. Table 1 shows an example of the spectrum format.

[0098] Step S24: Verification of the spectrum curve and spectrum diagram.

[0099] The data in the spectrogram determined based on the spectrum curve is compared with the data in the spectrogram determined based on the actual spectrum curve, and an error analysis is performed to determine the root mean square error (RMSE) of the spectrum curve. The root mean square error of the spectrum curve is determined in the same manner as in the above embodiment and will not be repeated here. If the RMSE is less than 1 dBA, the spectrum is considered valid, and the spectrum curve corresponding to the spectrum is valid; if the RMSE is less than 1 dBA, the spectrum is considered invalid, and the spectrum curve corresponding to the spectrum is invalid.

[0100] Step S3, determining the gain coefficient, specifically includes:

[0101] Step S31: determining the frequency response function.

[0102] To ensure that the spectrum curve of the sound source simulator is consistent with that of the standard sound source (i.e., the target transformer), laboratory verification is required. Testing is conducted in a fully anechoic chamber under the aforementioned benchmark conditions to ensure the stability of the test environment's acoustic characteristics and prevent ambient noise from affecting the measurement results. A computer controls the output signal of the pulse (acoustic measurement and analysis system), splitting the pulse output into two standard noise signals. One standard noise signal is input to the pulse input, while the other standard noise signal is connected to the sound source simulator via a power amplifier. These standard noise signals can be generated using a test transformer identical to the target transformer under specific operating conditions. A microphone is placed in front of the sound source simulator, one meter from its center and perpendicular to its radiation surface. The simulated noise emitted by the sound source simulator is received by the microphone and then input to the pulse input. Under normal operating conditions, the pulse compares the standard spectrum curve of the standard noise signal with the simulated spectrum curve of the simulated noise signal emitted by the sound source simulator to calculate the frequency response of the sound source simulator. Based on this frequency response, the frequency response function of the sound source simulator is determined.

[0103] Step S32: determining the gain coefficient.

[0104] Based on the frequency response function, the sound source simulator is inversely filtered to ensure that the simulated noise produced by the simulator more closely matches the actual noise level at the scene. The standard sound source supplement coefficient (i.e., gain coefficient) is obtained based on the sound pressure level spectrum (i.e., the corrected spectrum curve) of the simulated noise output by the simulator after processing.

[0105] Step S4, simulating the output of noise, specifically includes:

[0106] Figure 3 is a schematic diagram of an optional sound source simulation device provided according to an embodiment of the present application, such as Figure 3 As shown, by inputting the transformer type, dimensions (length and width), sound pressure level at the test point (i.e., the sound measurement point), the corresponding sound power, and the gain factor into the transformer parameter and calculation area of ​​the sound source simulator (i.e., the transformer sound playback software), the target simulated noise of the target transformer can be generated. The playback control area allows you to determine the playback gain, current gain, and input gain of the simulated noise. The playback of the simulated noise can also be controlled using the Play, Stop, and Loop buttons in the playback control area.

[0107] This optional implementation generates noise across multiple frequency bands through multi-dimensional dynamic simulation, including fundamental noise, electromagnetic vibration noise, and high-frequency discharge noise. This improves simulation accuracy by over 40% and supports automated testing in multiple scenarios and operating conditions. Furthermore, this optional implementation reduces the simulated noise error in mid- and low-frequency bands to within 10% by obtaining a gain coefficient, improving both accuracy and reliability.

[0108] The above optional implementation methods can at least achieve the following effects: through the sound pressure level prediction based on geometric information and distance information, the sound source simulation device can more accurately reproduce the acoustic characteristics of the target transformer under different operating conditions, thereby improving the accuracy and reliability of the simulated noise; using a standard spectrum library to ensure that the spectrum characteristics of the simulated noise are highly consistent with the noise characteristics of the target transformer, thereby improving the accuracy of the simulated noise and reducing errors caused by models or assumptions; by accurately calculating the frequency response function of the sound source simulation device and adopting inverse filtering technology to correct it, the consistency of the simulated noise with the actual noise of the target transformer is improved, thereby improving the simulation accuracy; the use of the gain coefficient enables the sound source simulation device to accurately adjust the gain of the simulated noise, thereby improving the matching degree between the simulated noise and the actual noise of the target transformer.

[0109] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0110] This embodiment also provides a transformer noise simulation device for implementing the aforementioned embodiments and preferred implementations. Details already described will not be repeated. As used below, the terms "module" and "device" may refer to a combination of software and / or hardware that implements a predetermined function. While the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0111] According to an embodiment of the present application, a device embodiment for implementing a transformer noise simulation method is also provided. Figure 4 is a schematic diagram of a transformer noise simulation device according to an embodiment of the present application, such as Figure 4 As shown, the noise simulation device for the transformer includes a data acquisition module 402, a sound pressure level determination module 404, an initial simulated noise generation module 406, and a target simulated noise determination module 408. The device is described below.

[0112] A data acquisition module 402 is configured to acquire geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the primary radiation area of ​​the sound waves of the target transformer;

[0113] A sound pressure level determination module 404 is connected to the data acquisition module 402 and is used to determine the sound pressure level of the target transformer under operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point;

[0114] The initial simulated noise generating module 406 is connected to the sound pressure level determining module 404 and is used to generate the initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library;

[0115] The target simulated noise determination module 408 is connected to the initial simulated noise generation module 406 and is used to modify the initial simulated noise using a gain coefficient to obtain a target simulated noise of a target transformer, wherein the gain coefficient is used to adjust or compensate the initial simulated noise.

[0116] In a transformer noise simulation device provided by an embodiment of the present application, a data acquisition module 402 is set to obtain geometric information of a reference emission surface of a target transformer, the operating conditions of the target transformer, and the distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the main radiation area of ​​the sound wave of the target transformer; a sound pressure level determination module 404 is connected to the data acquisition module 402 and is used to determine the sound pressure level of the target transformer under the operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; an initial simulated noise generation module 406 is connected to the sound pressure level determination module 404 and is used to generate an initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library; a target simulated noise determination module 408 is connected to the initial simulated noise generation module 406 and is used to correct the initial simulated noise using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise. The purpose is achieved by determining the geometric information of the transformer reference emission surface, combining the operating conditions and distance information, using the standard spectrum library to generate initial simulated noise, and then using the gain coefficient to correct the initial simulated noise, thereby achieving the technical effect of improving the accuracy and reliability of the generated transformer simulated noise, thereby solving the technical problem of low accuracy of the generated transformer simulated noise existing in the related art.

[0117] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0118] It should be noted that the data acquisition module 402, sound pressure level determination module 404, initial simulated noise generation module 406, and target simulated noise determination module 408 correspond to steps S102 to S108 in the embodiment. The examples and application scenarios implemented by these modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules, as part of the device, can be run on a computer terminal.

[0119] It should be noted that the optional or preferred implementation of this embodiment can be found in the relevant description in the embodiment, which will not be repeated here.

[0120] The noise simulation device for the above-mentioned transformer may further include a processor and a memory. The data acquisition module 402, the sound pressure level determination module 404, the initial simulated noise generation module 406, the target simulated noise determination module 408, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to implement corresponding functions.

[0121] The processor includes a kernel, which retrieves the corresponding program unit from memory. There can be one or more kernels. Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0122] An embodiment of the present application provides a non-volatile storage medium having a program stored thereon, which implements a transformer noise simulation method when executed by a processor.

[0123] An embodiment of the present application provides an electronic device comprising a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: obtaining geometric information of a reference emission surface of a target transformer, the operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the primary radiation area of ​​sound waves from the target transformer; determining the sound pressure level of the target transformer under operating conditions based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of simulated noise at the sound measurement point; generating initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library; and correcting the initial simulated noise using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise. The device herein may be a server, a PC, or the like.

[0124] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: obtaining geometric information of a reference emission surface of a target transformer, operating conditions of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is the main radiation area of ​​sound waves of the target transformer; based on the geometric information and distance information, determining the sound pressure level of the target transformer under operating conditions, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; based on the sound pressure level and operating conditions, using a pre-established standard spectrum library to generate initial simulated noise; using a gain coefficient to correct the initial simulated noise to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

[0125] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0126] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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 steps in the process. 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.

[0127] 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.

[0128] 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.

[0129] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0130] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0131] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0132] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0133] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A transformer noise simulation method, characterized in that: include: Acquire geometric information of a reference emission surface of a target transformer, an operating condition of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is a primary radiation area of ​​sound waves of the target transformer; Determine a sound pressure level of the target transformer under the operating condition based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; Based on the sound pressure level and the operating conditions, an initial simulated noise is generated using a pre-established standard spectrum library; The initial simulated noise is corrected by using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

2. The method according to claim 1, characterized in that The determining, based on the geometric information and the distance information, the sound pressure level of the target transformer under the operating condition includes: Determining the sound power of the target transformer based on the distance information and the sound pressure information of the sound measurement point included in the operating condition; The sound pressure level is determined based on the sound power and the geometric information.

3. The method according to claim 1, characterized in that Before generating the initial simulated noise based on the sound pressure level and the operating conditions using a pre-established standard spectrum library, the method further includes: Collecting noise data corresponding to multiple operating conditions of a test transformer of the same type as the target transformer; Preprocessing the noise data of any one of the multiple working conditions to obtain preprocessed noise data of the any one of the working conditions; Performing principal component analysis on the preprocessed noise data to obtain noise data corresponding to a plurality of different frequency bands of any working condition; Determining a frequency spectrum curve for any of the operating conditions based on the noise data corresponding to the multiple different frequency bands, wherein the frequency spectrum curve is used to describe the distribution characteristics of the preprocessed noise data in the frequency domain, and the horizontal axis of the frequency spectrum curve represents frequency, and the vertical axis represents sound pressure level; A plurality of frequency spectrum curves are obtained by determining a frequency spectrum curve of any one of the operating conditions, wherein the plurality of frequency spectrum curves correspond one-to-one to the plurality of operating conditions; The standard spectrum library is established based on the multiple spectrum curves.

4. The method according to claim 3, characterized in that The determining of the frequency spectrum curve of any working condition based on the noise data corresponding to the multiple different frequency bands includes: Based on the noise data corresponding to the multiple different frequency bands, normalization processing is performed using weights corresponding to the multiple different frequency bands to obtain normalized data for any working condition; Performing statistical analysis on the normalized data to determine mean values ​​of sound pressure levels corresponding to a plurality of frequencies included in the normalized data, and variances of the sound pressure levels corresponding to the plurality of frequencies; Determining confidence intervals corresponding to the multiple frequencies based on mean values ​​of the sound pressure levels corresponding to the multiple frequencies and variances of the sound pressure levels corresponding to the multiple frequencies, wherein the confidence intervals represent a degree of uncertainty of the normalized data; A frequency spectrum curve of any working condition is determined based on the mean values ​​of the sound pressure levels corresponding to the multiple frequencies and the confidence intervals corresponding to the multiple frequencies.

5. The method according to claim 3, characterized in that The step of establishing the standard spectrum library based on the plurality of spectrum curves includes: For any one of the multiple frequency spectrum curves, based on an average of sound pressure levels corresponding to multiple frequencies included in the any one frequency spectrum curve and actual sound pressure levels corresponding to multiple frequencies included in an actual frequency spectrum curve of the test transformer under the corresponding working condition, determining first sound pressure level errors corresponding to the multiple frequencies respectively; Determining a root mean square error of any one of the frequency spectrum curves based on the first sound pressure level errors respectively corresponding to the multiple frequencies, wherein the root mean square error is used to indicate a degree of similarity between any one of the frequency spectrum curves and the actual frequency spectrum curve; Determining a verification result of any one of the spectrum curves based on the root mean square error and a preset error threshold, wherein the verification result is used to indicate the validity of the spectrum curve; Determine the verification results corresponding to the multiple spectrum curves respectively by determining the verification result of any one spectrum curve; The standard spectrum library is established based on the verification results corresponding to the multiple spectrum curves.

6. The method according to any one of claims 1 to 5, characterized in that Before the step of correcting the initial simulated noise by using the gain coefficient to obtain the target simulated noise of the target transformer, the method further includes: Obtaining a simulated spectrum curve and a standard spectrum curve of the test transformer under the operating condition, wherein the simulated spectrum curve is generated by using a sound source simulation device, and the standard spectrum curve is obtained by the test transformer under the operating condition; Determining a frequency response function of the sound source simulation device based on the simulated spectrum curve and the standard spectrum curve, wherein the frequency response function is used to indicate the degree of amplification or attenuation of noise data of different frequencies by the sound source simulation device; Based on the frequency response function, performing inverse filtering on the simulated spectrum curve to obtain a modified spectrum curve; Determining a gain coefficient set of the test transformer in the operating condition based on the modified spectrum curve, wherein the gain coefficient set includes a plurality of gain coefficients; The gain coefficient is determined from the set of gain coefficients based on a frequency of the initial simulated noise.

7. The method according to claim 6, characterized in that The step of determining a gain coefficient set of the test transformer under the operating condition based on the modified spectrum curve includes: For any frequency among the multiple frequencies included in the modified frequency spectrum curve, determining any sound pressure level of the any frequency and a standard sound pressure level of the any frequency; determining a second sound pressure level error corresponding to the any frequency based on the any sound pressure level and the standard sound pressure level; determining a gain coefficient of the any one frequency based on the second sound pressure level error; Determine the gain coefficients corresponding to the multiple frequencies included in the modified spectrum curve by adopting a method of determining the gain coefficient of any frequency; The gain coefficient set is determined based on the gain coefficients corresponding to a plurality of frequencies included in the modified frequency spectrum curve.

8. A transformer noise simulation device, characterized in that: include: a data acquisition module, configured to acquire geometric information of a reference emission surface of a target transformer, an operating condition of the target transformer, and distance information between the target transformer and a sound measurement point, wherein the reference emission surface is a primary radiation area of ​​sound waves from the target transformer; a sound pressure level determination module, configured to determine the sound pressure level of the target transformer under the operating condition based on the geometric information and the distance information, wherein the sound pressure level is used to represent the sound pressure level of the simulated noise at the sound measurement point; an initial simulated noise generating module, configured to generate an initial simulated noise based on the sound pressure level and the operating condition using a pre-established standard spectrum library; The target simulated noise determination module is configured to modify the initial simulated noise using a gain coefficient to obtain a target simulated noise of the target transformer, wherein the gain coefficient is used to adjust or compensate for the initial simulated noise.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by the transformer noise simulation method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the transformer noise simulation method according to any one of claims 1 to 7.

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