Real-time prediction and identification method of substation remote radiation noise based on multi-point virtual sound source

Abstract

The present application relates to a kind of based on substation remote radiation noise real-time prediction and identification method of virtual sound source, belong to the field of measuring sound wave.The present application can find the most accurate noise source and sound source monitoring point arrangement mode, can remove loudspeaker, only keep sound source monitoring point, for 24 hours real-time monitoring noise spectrum signal under the actual working condition of substation, according to the frequency response function matrix that has been measured and using the above multi-channel least square method, noise source signal of substation can be monitored in real time, for further real-time prediction of distant target sound source monitoring point place noise characteristic provides reliable and accurate noise source input.

Description

Technical Field

[0001] This invention belongs to the field of sound wave measurement and relates to a method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources. Background Technology

[0002] Substation equipment generates a certain degree of environmental noise pollution during operation, and the degree of noise pollution tends to increase with the increase in transmission voltage levels and transmission capacity. At the same time, continuous urbanization has led to substations that were previously built in uninhabited or non-residential areas being built closer to residential and office buildings in towns and cities. The impact of noise generated by substations during operation on surrounding residential buildings and offices is becoming increasingly prominent, making the control of audible noise increasingly important.

[0003] In the process of substation noise pollution control, to explore noise pollution control measures suitable for the actual engineering situation, it is necessary not only to analyze the noise radiation source characteristics and generation mechanism of the substation itself, but also to analyze the transmission path characteristics of noise radiation to residential areas. Due to the increase in voltage levels, some equipment is installed at higher heights, resulting in longer noise propagation distances and more complex transmission paths. Furthermore, substation noise reaching residential areas is more easily interfered with or masked by other non-substation noise. This may lead residents to mistakenly identify other noise interference as substation noise, causing unnecessary disputes and hindering the identification of correct noise pollution control measures. Previously, the method of monitoring environmental noise around the substation was used, placing monitoring equipment at monitoring points to obtain the characteristics of substation radiated noise, thus providing data for noise pollution control. However, this monitoring method has many inconveniences in residential areas far from the substation, such as disturbing residents' normal lives, affecting the aesthetics of the residential area, and being easily damaged unintentionally by residents. On the other hand, general monitoring equipment cannot identify whether noise pollution in residential areas originates from the substation. If we can obtain a long-distance radiated noise prediction value with sufficient accuracy based on the noise source characteristics of the substation itself, and be able to identify whether it originates from the substation, it will help us find appropriate noise control measures, thereby effectively solving residents' complaints about substation noise problems. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources is as follows:

[0007] Noise sources are placed at the envelope of the substation;

[0008] Sound source monitoring points are set up around the substation, and the frequency response function matrix from the noise source point to the sound source monitoring point is measured. The substation noise source characteristics are extracted in real time based on the noise data monitored at the sound source monitoring points using the multi-channel least squares method.

[0009] The noise source is located by placing N at the envelope of the substation. s One speaker simulation;

[0010] The sound source monitoring point is located around the substation by placing N... r The sound source monitoring points are arranged to surround the substation, using a single microphone for simulation.

[0011] The interval between the sound source monitoring points shall not be greater than half the wavelength of the radiated noise;

[0012] Measurement of sound pressure spectrum vector under actual operating conditions of substation

[0013] Place N' at a slightly distance from the substation r At each verification monitoring point, the sound pressure spectrum vector was measured. The verification monitoring points are used to verify the accuracy of noise source extraction in subsequent steps, but do not participate in noise source extraction.

[0014] The frequency response function matrix from the loudspeaker to the two sound source monitoring points was measured using the logarithmic sinusoidal sweep method. and The microphones and speakers at the sound source monitoring points are connected to the ADC and DAC terminals of a multi-channel sound card, respectively. A logarithmic sweep signal is sent from the computer, which drives the speaker to produce sound. The microphone array collects the response sound pressure signal, which is transmitted to the computer via the sound card's ADC terminal. A MATLAB program then calculates the frequency response function matrix from the speaker to the two measurement points. and

[0015] Noise source signals are extracted using a multi-channel least squares feedback method;

[0016] After obtaining the noise source signal that most accurately reflects the noise characteristics of the substation, the long-distance radiated noise of the substation can be predicted and identified.

[0017] Optionally, the extraction of noise source signals using the multi-channel least squares feedback method specifically involves:

[0018] The collected sound pressure spectrum vector Input to the equalizer filter added before the sound card Equalization filter By N s ×N rThe complex matrix representation of N, where N s The noise source vector represents the total number of speakers in the speaker array and is calculated by a computer.

[0019]

[0020] To ensure that the extracted noise source vector can characterize the actual noise source characteristics of the substation, and The equilibrium system composed of each other satisfy:

[0021]

[0022] In the formula, I is the identity matrix, and Δ represents the delay of the hardware system;

[0023] Using the least squares method, and introducing the Tikhonov regularity parameter λ, the calculation is performed. for:

[0024]

[0025] The solution to the above equation is:

[0026]

[0027]

[0028] In the formula, H represents the transpose of the matrix; For N r ×N s The complex matrix represents the measured value of the actual physical transmission path matrix, and its elements are the frequency response functions between each microphone and loudspeaker in the microphone array and loudspeaker array.

[0029] The prediction and identification of long-distance radiated noise from substations specifically includes:

[0030] The noise source signal is input into the frequency response function matrix of a remote monitoring point. Calculate the noise spectrum vector at a distant monitoring point for:

[0031]

[0032] When no other noise interference sources are selected, the actual sound pressure collected by the microphone at a monitoring point at a certain distance is... Compared with the predicted sound pressure results at this time Compare the results to verify the accuracy of the predictions;

[0033] If the accuracy of the prediction results is verified to meet the requirements, then the microphones at the distant monitoring points will be removed. Using the microphones at the monitoring points inside the substation and the already measured frequency response function matrix, real-time monitoring of radiated noise at a certain distance from the substation will be achieved for investigation.

[0034] When complaints of excessive noise pollution are received at a certain distance, check the real-time monitoring signals of substation noise sources in that area. and predicted noise value

[0035] If both are found to be above normal, then check whether there is a fault in the substation itself, and check the faulty equipment according to the location of the abnormal sound source.

[0036] If neither of these values ​​exceeds the normal range, then first investigate the transmission path from the noise source to the distant monitoring point, i.e., the frequency response function matrix. Has anything changed? If there has been any construction or demolition of buildings, then a new measurement should be taken. And recalibrate the prediction model; if the prediction after calibration is If the noise level increases significantly, noise reduction measures should be implemented at the substation.

[0037] If neither of these values ​​exceeds the normal range and the transmission path remains unchanged, then the problem is determined to be caused by other interfering noise. Staff should be dispatched with noise monitoring equipment to that distance to conduct actual measurements. If the measured noise level at this point... Peak and If the peak frequencies are different, then the problem of excessive noise pollution is determined to originate from interference noise, rather than substation noise; if Peak and If the peak frequencies are the same, then according to Peak and The magnitude of the peak value in decibels is used to determine the problem; if the difference between the two is greater than 3dB, then the complaint is considered to originate from other interference noise.

[0038] Optionally, at the specified distance, the noise from each noise source point in the substation to the monitoring point at that location... The contribution is:

[0039]

[0040] In the formula and They are respectively and A single element; For noise source point m pairs The individual contribution; according to Based on the value, find the top n corresponding n-way transmission paths, and take noise reduction measures, where n is 2 to 5.

[0041] Optionally, in the microphone array and speaker array, the frequency response function between each microphone and speaker is measured by a logarithmic sine sweep frequency method.

[0042] Optionally, the verification of the accuracy of the noise source extraction specifically includes:

[0043] Extracted noise source spectrum vector Input to the frequency response function matrix of the verification monitoring point That is, N' r ×N s Calculate and verify the spectrum vector of the monitoring points for:

[0044]

[0045] Verify the spectral prediction values ​​of the monitoring points Compared with measured values The comparison, i.e., subtracting the decibel values, yields the error vector.

[0046] Adjust the number and arrangement of loudspeakers and sound source monitoring points to reduce errors, improve the accuracy of noise source extraction, and find the most accurate noise source and sound source monitoring point arrangement.

[0047] Optionally, after finding the most accurate noise source and the arrangement of the sound source monitoring points, the loudspeakers are removed, leaving only the sound source monitoring points. This enables 24-hour real-time monitoring of the noise spectrum signal under the actual operating conditions of the substation, based on the measured frequency response function matrix. By employing the aforementioned multi-channel least squares method, the noise source signal of the substation is monitored in real time, enabling real-time prediction of the noise characteristics at the distant target sound source monitoring point and providing noise source input.

[0048] The beneficial effects of this invention are as follows: This invention can find the most accurate noise source and sound source monitoring point arrangement method, and can remove loudspeakers, retaining only the sound source monitoring points, for 24-hour real-time monitoring of noise spectrum signals under actual substation operating conditions. Based on the measured frequency response function matrix and using the above-mentioned multi-channel least squares method, the substation noise source signal can be monitored in real time, providing a reliable and accurate noise source input for further real-time prediction of noise characteristics at distant target sound source monitoring points.

[0049] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0050] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0051] Figure 1 To simplify the model for transmission path analysis;

[0052] Figure 2 Layout diagram of substations and monitoring points in remote residential areas;

[0053] Figure 3 A schematic diagram showing the layout of noise source points and sound source monitoring points extracted from substation noise sources;

[0054] Figure 4 This is a schematic diagram of the hardware connections for a substation noise source monitoring system.

[0055] Figure 5 Flowchart for noise source extraction using the multi-channel least squares method;

[0056] Figure 6 This is a typical substation noise spectrum diagram. Detailed Implementation

[0057] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0058] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0059] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0060] The basic principle of this invention is source path analysis or transmission path analysis theory. First, the substation is equivalent to a set of virtual noise sources enveloping its surface. The noise source input signal of this set of noise sources is extracted using a multi-channel least squares method. Second, monitoring microphones are placed in residential areas at a distance from the substation to measure the frequency response function matrix from the noise source point to the monitoring point. Then, based on the multi-channel source path principle and matrix multiplication, the long-distance radiated noise of the substation can be predicted, such as... Figure 1 As shown, since the predicted substation radiated noise only originates from the noise source at the virtual noise source point, the predicted noise value can accurately reflect the noise pollution situation of the substation to the residential area. By comparing the noise values ​​under two conditions—relatively quiet and relatively noisy—from the real-time noise monitoring results at this location with the predicted results, the proportion of substation radiation sources and other interfering noise sources at this location can be further identified.

[0061] To achieve the above objectives, the present invention provides the following technical solution:

[0062] The overall layout of the plan is as follows Figure 2 As shown. First, place an N at the envelope surface near the transformer (usually the main noise source) inside the substation. s One to three speakers can be placed near each surface at a certain distance from the ground, acting as virtual noise sources. Since the radiated sound power in substations is mainly concentrated below 200Hz, subwoofers with sufficient sound power can be selected. N speakers should be placed near the transformer. r Each microphone is used as a noise source monitoring point, with the interval between monitoring points not exceeding half the wavelength of the main radiated noise. The sound pressure spectrum vector under the actual operating conditions of the substation is measured. The number of monitoring points should be determined according to actual needs, and they should be placed around the substation as much as possible. Figure 3 As shown; at the same time, place N' at a slightly distance from the substation. r At each verification monitoring point, the sound pressure spectrum vector was measured. These monitoring points are not involved in noise source extraction; they are only set up to verify the accuracy of noise source extraction later. Additionally, N250" monitoring stations are placed at a distance from the substation (such as inside or on the roof of residential buildings with severe noise pollution complaints). r One to two microphones are typically placed as long-distance monitoring points, with one to two microphones positioned in each key monitoring area. The frequency response function matrix from the loudspeaker to the three monitoring points is measured using a logarithmic sinusoidal sweep method. and The microphones and speakers at the monitoring points are connected to the ADC and DAC terminals of a multi-channel sound card, respectively. A logarithmic sweep signal is sent from the computer, which drives the speakers to produce sound. The microphone array collects the response sound pressure signal, which is transmitted to the computer via the sound card's ADC terminal. A MATLAB program then calculates the frequency response function matrix from the speakers to the two measurement points. and The hardware connection diagram of the entire test system is as follows: Figure 4 As shown.

[0063] Noise source signals are extracted using a multi-channel least squares feedback method, such as... Figure 5 As shown. First, the collected sound pressure spectrum vector is... Input to the equalizer filter added before the sound card (by N) s ×N r The complex matrix representation of N, where N s The noise source vector (representing the total number of loudspeakers in the loudspeaker array) is calculated by the computer using equation (1).

[0064]

[0065] In order for the extracted noise source vector to characterize the actual noise source characteristics of the substation, and The equilibrium system composed of each other Should meet:

[0066]

[0067] In equation (2), I is the identity matrix, and Δ represents the delay of the hardware system. The least squares method is used, and the Tikhonov regularization parameter λ is introduced to calculate... for:

[0068]

[0069] The solution to equation (3) is:

[0070]

[0071]

[0072] In equation (5), H represents the transpose of the matrix; For N r ×N s The complex matrix represents the measured value of the actual physical transmission path matrix. Its elements are the frequency response functions between each microphone and loudspeaker in the microphone array and loudspeaker array, which can be measured by the logarithmic sine sweep method.

[0073] To verify the accuracy of the extracted noise sources, the extracted noise source spectrum vectors were... Input to the frequency response function matrix of the verification monitoring point Calculate the spectrum vector of the verification monitoring point The result is obtained by calculation using equation (6):

[0074]

[0075] Since the verification monitoring point is located not far from the main noise source, the transformer, and is situated inside the substation, the substation perimeter wall provides some insulation against external interference noise. Therefore, the noise measured at the verification monitoring point can be considered to originate primarily from the transformer itself. The predicted spectral values ​​of the verification monitoring point... Compared with measured values By comparing (subtracting the decibel values), the error vector can be obtained. Finally, adjust the number and arrangement of speakers and monitoring points to minimize errors and improve the accuracy of noise source extraction.

[0076] After finding the most accurate noise source and sound source monitoring point layout using the above method, the loudspeakers can be removed, leaving only the sound source monitoring points for 24-hour real-time monitoring of the noise spectrum signal under actual substation operating conditions. Since the frequency response function from the noise source to the sound source monitoring point is independent of the noise source and the influence of weather is ignored, the measured frequency response function matrix can be considered... It does not change over time, therefore the measured values ​​are used. and real-time sound pressure at sound source monitoring points The above-mentioned multi-channel least squares method can be used to monitor substation noise source signals in real time.

[0077] Predicting and identifying long-distance radiated noise from substations

[0078] After obtaining the noise source signal that accurately reflects the noise characteristics of the substation using the above method, the noise source signal is input into the frequency response function matrix of the remote monitoring point. Calculate the noise spectrum vector at a distant monitoring point for:

[0079]

[0080] The actual sound pressure level collected by the microphone at a distant monitoring point under relatively quiet conditions (without other noise interference sources) Compared with the sound pressure result predicted by the above method at this time By comparing the results, the accuracy of the prediction can be verified. If the accuracy of the prediction is verified to meet the requirements, then even if the microphone at the remote monitoring point is removed, real-time prediction or monitoring of the radiated noise at a distance (key area of ​​concern) of the substation can still be achieved through the microphone at the monitoring point inside the substation and the already measured frequency response function matrix.

[0081] When complaints of excessive noise pollution arise in a region of concern, the first step is to check the real-time monitoring signals of the substation noise sources in that area. and predicted noise value If both are found to be within normal limits, it can be preliminarily determined that the noise is likely caused by other interfering noise. In this case, staff should bring noise monitoring equipment to the area to conduct actual measurements. If the measured noise level is... Peak and If the peak frequencies are different, it's easy to determine that the excessive noise pollution originates from interference noise, not substation noise; if Peak and If the peak frequencies are the same, then according to Peak and The peak decibel value is used to determine the source. If the difference is small (within 2dB), it is considered to be mainly caused by substation noise. If the difference is around 3dB, it is considered that the contribution of interference noise and substation noise is roughly equal. If the difference is greater than 5dB, it is considered to be mainly caused by interference noise. The above investigation work must first ensure the transmission path (frequency response function matrix) from the noise source to the distant monitoring point. No major changes have occurred, such as checking for any new construction or demolition of buildings. If such changes are found, a new measurement is required. And recalibrate the prediction model.

[0082] In addition, this invention can also analyze the noise level at a distant monitoring point from each noise source point in a substation according to the following formula. Contribution amount:

[0083]

[0084] In the formula and They are respectively and A single element. For noise source point m pairs The individual contribution. Identify the larger ones from this. For each of the several transmission paths corresponding to the value, corresponding noise reduction measures should be taken, such as adding a sound barrier in front of the noise source. This will enable a more targeted noise reduction solution and improve the effectiveness of noise pollution control.

[0085] Figure 6 This is a typical substation noise spectrum diagram.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources, characterized in that: The method is as follows: Noise sources are placed at the envelope of the substation; Sound source monitoring points are set up around the substation, and the frequency response function matrix from the noise source point to the sound source monitoring point is measured. The substation noise source characteristics are extracted in real time based on the noise data monitored at the sound source monitoring points using the multi-channel least squares method. The noise source is located by placing N at the envelope of the substation. s One speaker simulation; The sound source monitoring point is located around the substation by placing N... r The sound source monitoring points are arranged to surround the substation, using a single microphone for simulation. The interval between the sound source monitoring points shall not be greater than half the wavelength of the radiated noise; Measurement of sound pressure spectrum vector under actual operating conditions of substation Place N' at a slightly distance from the substation r At each verification monitoring point, the sound pressure spectrum vector was measured. The verification monitoring points are used to verify the accuracy of noise source extraction in subsequent steps, but do not participate in noise source extraction. The frequency response function matrix from the loudspeaker to the two sound source monitoring points was measured using the logarithmic sinusoidal sweep method. and The microphones and speakers at the sound source monitoring points are connected to the ADC and DAC terminals of a multi-channel sound card, respectively. A logarithmic sweep signal is sent from the computer, which drives the speaker to produce sound. The microphone array collects the response sound pressure signal, which is transmitted to the computer via the sound card's ADC terminal. A MATLAB program then calculates the frequency response function matrix from the speaker to the two measurement points. and Noise source signals are extracted using a multi-channel least squares feedback method; After obtaining the noise source signal that most accurately reflects the noise characteristics of the substation, the long-distance radiated noise of the substation can be predicted and identified.

2. The method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources according to claim 1, characterized in that: The extraction of noise source signals using the multi-channel least squares feedback method specifically involves: The collected sound pressure spectrum vector Input to the equalizer filter added before the sound card Equalization filter By N s ×N r The complex matrix representation of N, where N s The noise source vector represents the total number of speakers in the speaker array and is calculated by a computer. To ensure that the extracted noise source vector can characterize the actual noise source characteristics of the substation, and The equilibrium system composed of each other satisfy: In the formula, I is the identity matrix, and Δ represents the delay of the hardware system; Using the least squares method, and introducing the Tikhonov regularity parameter λ, the calculation is performed. for: The solution to the above equation is: In the formula, H represents the transpose of the matrix; For N r ×N s The complex matrix represents the measured value of the actual physical transmission path matrix, and its elements are the frequency response functions between each microphone and loudspeaker in the microphone array and loudspeaker array. The prediction and identification of long-distance radiated noise from substations specifically includes: The noise source signal is input into the frequency response function matrix of a remote monitoring point. Calculate the noise spectrum vector at a distant monitoring point for: When no other noise interference sources are selected, the actual sound pressure collected by the microphone at a monitoring point at a certain distance is... Compared with the predicted sound pressure results at this time Compare the results to verify the accuracy of the predictions; If the accuracy of the prediction results is verified to meet the requirements, then the microphones at the distant monitoring points will be removed. Using the microphones at the monitoring points inside the substation and the already measured frequency response function matrix, real-time monitoring of radiated noise at a certain distance from the substation will be achieved for investigation. When complaints of excessive noise pollution are received at a certain distance, check the real-time monitoring signals of substation noise sources in that area. and predicted noise value If both are found to be above normal, then check whether there is a fault in the substation itself, and check the faulty equipment according to the location of the abnormal sound source. If neither of these values ​​exceeds the normal range, then first investigate the transmission path from the noise source to the distant monitoring point, i.e., the frequency response function matrix. Has anything changed? If there has been any construction or demolition of buildings, then a new measurement should be taken. And recalibrate the prediction model; if the prediction after calibration is If the noise level increases significantly, noise reduction measures should be implemented at the substation. If neither of these values ​​exceeds the normal range and the transmission path remains unchanged, then the problem is determined to be caused by other interfering noise. Staff should be dispatched with noise monitoring equipment to that distance to conduct actual measurements. If the measured noise level at this point... Peak and If the peak frequencies are different, then the problem of excessive noise pollution is determined to originate from interference noise, rather than substation noise; if Peak and If the peak frequencies are the same, then according to Peak and The magnitude of the peak value in decibels is used to determine the problem; if the difference between the two is greater than 3dB, then the complaint is considered to originate from other interference noise.

3. The method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources according to claim 2, characterized in that: At a certain distance, the noise from each noise source point of the substation relative to the noise level at the monitoring point is... The contribution is: In the formula and They are respectively and A single element; For noise source point m pairs The individual contribution; according to The value is used to find the top n corresponding n-way transmission paths, and noise reduction measures are taken, where n is 2 to 5.

4. The method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources according to claim 2, characterized in that: In the microphone array and speaker array, the frequency response function between each microphone and speaker is measured by the logarithmic sine sweep frequency method.

5. The method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources according to claim 2, characterized in that: The specific steps for verifying the accuracy of the extracted noise source are as follows: Extracted noise source spectrum vector Input to the frequency response function matrix of the verification monitoring point That is, N' r ×N s Calculate and verify the spectrum vector of the monitoring points for: Verify the spectral prediction values ​​of the monitoring points Compared with measured values The comparison, i.e., subtracting the decibel values, yields the error vector. Adjust the number and arrangement of loudspeakers and sound source monitoring points to reduce errors, improve the accuracy of noise source extraction, and find the most accurate noise source and sound source monitoring point arrangement.

6. The method for real-time prediction and identification of long-distance radiated noise in substations based on multi-point virtual sound sources according to claim 5, characterized in that: After finding the most accurate noise source and the arrangement of the sound source monitoring points, the loudspeakers are removed, leaving only the sound source monitoring points. This enables 24-hour real-time monitoring of the noise spectrum signal under the actual operating conditions of the substation, based on the measured frequency response function matrix. By employing the aforementioned multi-channel least squares method, the noise source signal of the substation is monitored in real time, enabling real-time prediction of the noise characteristics at the distant target sound source monitoring point and providing noise source input.

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