Noise online monitoring method and system for multi-blade centrifugal fan

Abstract

The invention discloses a noise on-line monitoring method and system for a multi-blade centrifugal fan, and relates to the technical field of noise signal data processing.The method comprises the steps that a noise time domain signal of the centrifugal fan is obtained; inputting the noise time-domain signal into a noise separation model to obtain a separated noise time-domain signal; respectively calculating first sound pressure levels according to the separation noise time domain signals; performing discrete Fourier transform on the noise time-domain signal to obtain a noise frequency-domain signal; calculating a second sound pressure level according to the noise frequency domain signal; and the centrifugal fan is adjusted according to the first sound pressure level and the second sound pressure level. According to the method, the time domain signals of the noise of the centrifugal fan are obtained, the time domain signals of the volute noise and the time domain signals of the mechanical noise are separated from the time domain signals, the first sound pressure levels of the time domain signals are calculated, the time domain signals are converted into the frequency domain signals, the second sound pressure level is calculated, the noise is monitored in real time, and the centrifugal fan is adjusted according to the monitoring result. The noise of the centrifugal fan is reduced, and the working efficiency of the centrifugal fan is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of noise signal data processing, and in particular to an online noise monitoring method and system for a multi-blade centrifugal fan. Background Art

[0002] A centrifugal fan is a widely used mechanical device that converts kinetic energy into static pressure energy by rotating an impeller, generating airflow to transport gas. Centrifugal fans are widely used in various commercial and residential environments due to their high efficiency, reliability and versatility.

[0003] In scenarios where a quiet environment is required, such as hospitals, laboratories, or bedrooms, systems equipped with centrifugal fans, such as ventilation systems or air conditioning systems, need to pay attention to noise issues. Therefore, it is necessary to design the centrifugal fan with low noise and monitor the noise of the centrifugal fan during use. Existing noise monitoring of centrifugal fans is based on the perspective of protecting safety. By comparing the size of the sound emitted by the centrifugal fan with a reference value that damages hearing, the centrifugal fan is inspected and maintained when the noise exceeds the reference value. This monitoring method ignores the sensitivity of humans to noise, resulting in high noise from the centrifugal fan, and is unable to monitor problems with the centrifugal fan in a timely manner, resulting in low efficiency of the centrifugal fan. Summary of the invention

[0004] The object of the present invention is to provide a method and system for online noise monitoring of a multi-blade centrifugal fan. The present invention obtains a time domain signal of the centrifugal fan noise, separates the time domain signals of the volute noise and the mechanical noise from the time domain signal, calculates the first sound pressure level thereof respectively, converts the time domain signal into a frequency domain signal, calculates the second sound pressure level of the total noise, monitors the noise in real time, and adjusts the centrifugal fan according to the first sound pressure level and the second sound pressure level obtained by monitoring and calculating, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan.

[0005] The purpose of the present invention is achieved by the following technical means: In a first aspect, the present invention provides a method for online noise monitoring of a multi-blade centrifugal fan, comprising: Obtain the noise time domain signal of the centrifugal fan; Inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal; Calculating first sound pressure levels respectively according to the separated noise time domain signals; Performing discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; Calculating a second sound pressure level according to the noise frequency domain signal; adjusting a centrifugal fan according to the first sound pressure level and the second sound pressure level; The separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal.

[0006] Preferably, before inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal, the method further comprises: Get multiple simulated volute noises and simulated mechanical noises; Randomly mixing the simulated volute noise and the simulated mechanical noise to obtain an original data set; The original data set is randomly sampled in a fixed time window, and the noise data obtained by sampling is gain-summed to form new noise data to obtain a training sample set; The noise separation model is trained using the training sample set.

[0007] Preferably, the training of the noise separation model by using the training sample set includes: Performing short-time Fourier transform on the noise data of the training sample set to obtain a characteristic signal; Performing block mask calculation on the characteristic signal to obtain a separated signal spectrum; Performing an inverse short-time Fourier transform on the separated signal spectrum to obtain the separated noise time domain signal; The separated noise time domain signal is evaluated and the parameter weights of the noise separation model are modified.

[0008] Preferably, the step of evaluating the separated noise time domain signal and correcting the parameter weights of the noise separation model comprises: Performing short-time Fourier transform on the simulated volute noise and the simulated mechanical noise in the training sample set to obtain a real signal spectrum; According to the separated signal spectrum and the true signal spectrum, construct a loss function to evaluate the separated noise time domain signal; The calculation formula of the loss function is as follows: ; in, is the loss function, is the real signal spectrum, To separate the signal spectrum.

[0009] Preferably, the calculating the first sound pressure level respectively according to the separated noise time domain signal comprises: Calculating the effective sound pressure of the separated noise in the time domain according to the separated noise time domain signal; Calculating the first sound pressure level according to the effective sound pressure of the separated noise in time domain; The calculation formula of the effective sound pressure of the separated noise in the time domain is as follows: ; in, To separate the effective sound pressure of noise in time domain, is the sampling number of the noisy time domain signal, For the The sound pressure at each sampling moment; The calculation formula of the first sound pressure level is as follows: ; in, is the first sound pressure level, To separate the effective sound pressure of noise in time domain, is the atmospheric reference sound pressure.

[0010] Preferably, calculating the second sound pressure level according to the noise frequency domain signal includes: Calculating the noise frequency domain amplitude according to the noise frequency domain signal; Calculating the effective sound pressure in the noise frequency domain according to the noise frequency domain amplitude; Calculating the second sound pressure level according to the effective sound pressure in the noise frequency domain; The calculation formula of the noise frequency domain amplitude is as follows: ; in, is the noise frequency domain amplitude, is the noise frequency domain signal, is the weighting operation symbol, is the frequency point number, is the sampling rate of the noisy time domain signal, is the sampling number of the noisy time domain signal; The calculation formula of the effective sound pressure in the noise frequency domain is as follows: ; in, is the effective sound pressure in the noise frequency domain, is the sampling number of the noisy time domain signal, is the noise frequency domain amplitude; The calculation formula of the second sound pressure level is as follows: ; in, is the second sound pressure level, is the effective sound pressure in the noise frequency domain, is the atmospheric reference sound pressure.

[0011] Preferably, adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level includes: Comparing the first sound pressure level with the first sound pressure level to obtain a maximum first sound pressure level; Comparing the maximum first sound pressure level with a working threshold of a noise time domain signal corresponding to the maximum first sound pressure level, and when the maximum first sound pressure level is greater than the working threshold, shutting down the centrifugal fan and issuing an abnormal alarm; When the maximum first sound pressure level is less than the working threshold, the second sound pressure level is compared with a sensitive threshold, and when the second sound pressure level is greater than the sensitive threshold, the rotation speed of the centrifugal fan is reduced.

[0012] In a second aspect, the present invention provides an online noise monitoring system for a multi-blade centrifugal fan, which is applied to the above-mentioned online noise monitoring method for a multi-blade centrifugal fan, comprising: A time domain signal acquisition module is used to acquire the noise time domain signal of the centrifugal fan; A time domain signal separation module, used for inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal; A first sound pressure level calculation module, used to calculate the first sound pressure level according to the separated noise time domain signal; A frequency domain signal acquisition module, used for performing discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; A second sound pressure level calculation module, used for calculating a second sound pressure level according to the noise frequency domain signal; a centrifugal fan adjustment module, configured to adjust the centrifugal fan according to the first sound pressure level and the second sound pressure level; The separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal.

[0013] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory is used to store computer program code, and the computer program code comprises computer instructions. When the processor executes the computer instructions, the electronic device executes the above-mentioned method for online noise monitoring of a multi-blade centrifugal fan.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions, and when the program instructions are executed by a processor of an electronic device, the processor executes the above-mentioned method for online noise monitoring of a multi-blade centrifugal fan.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains the time domain signal of the centrifugal fan noise, separates the time domain signals of the volute noise and the mechanical noise from the time domain signal, calculates the first sound pressure level of each noise, converts the time domain signal into a frequency domain signal, calculates the second sound pressure level of the total noise, monitors the noise in real time, and adjusts the centrifugal fan according to the first sound pressure level and the second sound pressure level obtained by monitoring and calculation, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan. The present invention performs mixed random sampling of multiple simulated volute noises and multiple simulated mechanical noises, performs gain summation on the sampled noise data to form a training sample set, and trains the noise separation model through the training sample set, thereby improving the noise separation performance of the noise separation model; The present invention measures the similarity between the separated signal spectrum and the real signal spectrum by constructing a loss function, thereby correcting the parameter weights of the noise separation model and improving the noise separation performance of the noise separation model; The present invention provides a data basis for subsequent adjustment of the centrifugal fan by calculating the sound pressure levels of the two noises according to the volute noise time domain signal and the mechanical noise time domain signal; The present invention performs weighted correction on the noise frequency domain signal, removes the signal frequency to which humans are insensitive, calculates the sound pressure level of the total noise of the centrifugal fan, and provides a data basis for the subsequent adjustment of the centrifugal fan. The present invention adjusts the working state of a centrifugal fan by combining a first sound pressure level and a second sound pressure level. The first sound pressure level is used to monitor whether the centrifugal fan has an abnormality. On this basis, the centrifugal fan is adjusted in consideration of human sensitivity to noise signals, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 A schematic flow chart of a method for online noise monitoring of a multi-blade centrifugal fan provided in this embodiment; Figure 2 A schematic diagram of the process of step S20 provided in this embodiment; Figure 3 A schematic diagram of the process of step S14 provided in this embodiment; Figure 4 A schematic diagram of the process of step S144 provided in this embodiment; Figure 5 A schematic diagram of the process of step S30 provided in this embodiment; Figure 6 A schematic diagram of the process of step S50 provided in this embodiment; Figure 7 A schematic diagram of the process of step S60 provided in this embodiment; Figure 8 A schematic diagram of the structure of an online noise monitoring system for a multi-blade centrifugal fan provided in this embodiment; Fig. 9 A schematic diagram of the structure of an electronic device provided in this embodiment. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0021] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0022] The present invention provides a method for online noise monitoring of a multi-blade centrifugal fan. Figure 1 As shown, the following steps are included: S10, obtaining a noise time domain signal of the centrifugal fan; S20, inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal; S30, calculating first sound pressure levels respectively according to the separated noise time domain signals; S40, performing discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; S50, calculating a second sound pressure level according to the noise frequency domain signal; S60, adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level; The separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal.

[0023] It should be noted that the noise separation model is a deep learning model. The trained noise separation model can separate the volute noise time domain signal and the mechanical noise time domain signal from the noise time domain signal of the centrifugal fan. Therefore, the first sound pressure level of the volute noise time domain signal and the first sound pressure level of the mechanical noise signal can be calculated respectively.

[0024] In this embodiment, by acquiring the time domain signal of the centrifugal fan noise, separating the time domain signals of the volute noise and the mechanical noise from the time domain signal, and calculating the first sound pressure levels thereof respectively, the time domain signal is converted into a frequency domain signal to calculate the second sound pressure level of the total noise to monitor the noise in real time, and adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level obtained by monitoring and calculating, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan.

[0025] In some embodiments, step S20, the noise time domain signal is input into the noise separation model to obtain the separated noise time domain signal, such as Figure 2 As shown, the following steps are also included: S11, obtaining a plurality of simulated volute noises and simulated mechanical noises; S12, randomly mix the simulated volute noise and the simulated mechanical noise to obtain the original data set; S13, randomly sampling the original data set in a fixed time window, performing gain summation on the noise data obtained by the sampling to form new noise data, and obtaining a training sample set; S14, training the noise separation model using the training sample set.

[0026] It should be noted that the data set is made by mixing simulated volute noise and simulated mechanical noise. Volute noise may be caused by various reasons such as impeller wear, volute deformation, or foreign matter inside the volute, while mechanical noise may also be caused by various reasons such as bearing wear, poor lubrication, or fan overload. In order to improve the separation performance of the noise separation model, mixed noise data is dynamically created to train the model. The gain can be obtained by generating a random number sequence to ensure that the signal-to-noise ratio of the volute noise and the mechanical noise is within the required range. The obtained training sample set data has no artificial tendency, and can simulate the situation where multiple problems occur in combination, so that the noise separation model can fully learn the noise data.

[0027] In this embodiment, multiple simulated volute noises and multiple simulated mechanical noises are mixed and randomly sampled, the sampled noise data are gain-summed to form a training sample set, and the noise separation model is trained with the training sample set, thereby improving the noise separation performance of the noise separation model.

[0028] In some embodiments, step S14, the noise separation model is trained using a training sample set, such as Figure 3 As shown, the following steps are included: S141, performing short-time Fourier transform on the noise data of the training sample set to obtain a characteristic signal; S142, performing block mask calculation on the characteristic signal to obtain a separated signal spectrum; S143, performing an inverse short-time Fourier transform on the separated signal spectrum to obtain a separated noise time domain signal; S144, evaluating the separated noise time domain signal and correcting the parameter weights of the noise separation model.

[0029] It should be noted that the noise separation model performs Fourier transform on the noise signal and converts it into a characteristic signal for representation. The characteristic signal is divided into overlapping blocks for feature extraction and estimation of the spectrum mask. The spectrum mask is multiplied by the characteristic signal to obtain the volute noise frequency domain signal and the mechanical noise frequency domain signal.

[0030] In this embodiment, the noise data is subjected to short-time Fourier transform, block division, and modeling calculation to obtain a separated signal spectrum, and the separated signal spectrum is inversely transformed to obtain a separated noise time domain signal, which provides a data basis for subsequent noise monitoring.

[0031] In some embodiments, step S144 evaluates the separated noise time domain signal and modifies the parameter weights of the noise separation model, such as Figure 4 As shown, the following steps are included: S1441, performing short-time Fourier transform on the simulated volute noise and simulated mechanical noise in the training sample set to obtain a true signal spectrum; S1442, constructing a loss function to evaluate the separated noise time domain signal according to the separated signal spectrum and the true signal spectrum; The loss function is calculated as follows: ; in, is the loss function, is the real signal spectrum, To separate the signal spectrum.

[0032] It should be noted that in the process of noise separation, the noise time domain signal is converted into a noise frequency domain signal for convolution modeling. Therefore, when constructing the loss function, the output of the noise separation model is evaluated by measuring the similarity between the predicted signal, i.e., the separated signal, and the true signal in the spectral domain.

[0033] In this embodiment, a loss function is constructed to measure the similarity between the separated signal spectrum and the true signal spectrum, thereby correcting the parameter weights of the noise separation model and improving the noise separation performance of the noise separation model.

[0034] In some embodiments, in step S30, the first sound pressure level is calculated according to the separated noise time domain signal, such as Figure 5 As shown, the following steps are included: S31, calculating the effective sound pressure of the separated noise in the time domain according to the separated noise time domain signal; S32, calculating a first sound pressure level according to the effective sound pressure of the separated noise in the time domain; The calculation formula for the effective sound pressure in the time domain of separated noise is as follows: ; in, To separate the effective sound pressure of noise in time domain, is the sampling number of the noisy time domain signal, For the The sound pressure at each sampling moment; The calculation formula for the first sound pressure level is as follows: ; in, is the first sound pressure level, To separate the effective sound pressure of noise in time domain, is the atmospheric reference sound pressure.

[0035] It should be noted that the first sound pressure level is the strength of the volute noise and the mechanical noise, and is used to reflect the volute noise and the mechanical noise when the centrifugal fan is working. By obtaining the sound pressure value of each sampling moment of the time domain signal, when the number of samples is large, the effective sound pressure of the noise can be calculated by the sound pressure value at each sampling moment, thereby calculating the first sound pressure level of the volute noise and the first sound pressure level of the mechanical noise.

[0036] In this embodiment, the sound pressure levels of the two noises are calculated according to the volute noise time domain signal and the mechanical noise time domain signal, thereby providing a data basis for subsequent adjustment of the centrifugal fan.

[0037] In some embodiments, step S50 calculates the second sound pressure level according to the noise frequency domain signal, such as Figure 6 As shown, the following steps are included: S51, calculating the noise frequency domain amplitude according to the noise frequency domain signal; S52, calculating the effective sound pressure in the noise frequency domain according to the noise frequency domain amplitude; S53, calculating a second sound pressure level according to the effective sound pressure in the noise frequency domain; The calculation formula of the noise frequency domain amplitude is as follows: ; in, is the noise frequency domain amplitude, is the noise frequency domain signal, is the weighting operation symbol, is the frequency point number, is the sampling rate of the noisy time domain signal, is the sampling number of the noisy time domain signal; The calculation formula for the effective sound pressure in the noise frequency domain is as follows: ; in, is the effective sound pressure in the noise frequency domain, is the sampling number of the noisy time domain signal, is the noise frequency domain amplitude; The calculation formula for the second sound pressure level is as follows: ; in, is the second sound pressure level, is the effective sound pressure in the noise frequency domain, is the atmospheric reference sound pressure.

[0038] It should be noted that in scenarios such as when a quieter environment is needed during sleep, the monitoring and control of the centrifugal fan of the air conditioner cannot be performed through the first sound pressure level. The first sound pressure level is the noise intensity of each component of the centrifugal fan, which is used to judge the working status of the centrifugal fan. In the above scenario, a smaller noise threshold is required to control the working status of the centrifugal fan. The second sound pressure value is the strength of the total noise of the centrifugal fan after removing the signal frequency to which humans are insensitive. When calculating the amplitude of the noise frequency domain, the amplitude of each frequency point is weighted and corrected so that the noise frequency domain signal matches human hearing.

[0039] In this embodiment, by performing weighted correction on the noise frequency domain signal, signal frequencies to which humans are insensitive are removed, and the sound pressure level of the total noise of the centrifugal fan is calculated, thereby providing a data basis for subsequent adjustment of the centrifugal fan.

[0040] In some embodiments, in step S60, the centrifugal fan is adjusted according to the first sound pressure level and the second sound pressure level, such as Figure 7 As shown, the following steps are included: S61, comparing the first sound pressure level with the second sound pressure level to obtain a maximum first sound pressure level; S62, comparing the maximum first sound pressure level with the working threshold of the noise time domain signal corresponding to the maximum first sound pressure level, and when the maximum first sound pressure level is greater than the working threshold, shutting down the centrifugal fan and issuing an abnormal alarm; S63, when the maximum first sound pressure level is less than the working threshold, comparing the second sound pressure level with the sensitive threshold, and when the second sound pressure level is greater than the sensitive threshold, reducing the rotation speed of the centrifugal fan.

[0041] It should be noted that by comparing the sound pressure level of the volute noise with the sound pressure level of the mechanical noise, the noise with a larger sound pressure level indicates that the noise is the main noise contributed by the centrifugal fan in this working state. By comparing the normal sound pressure level threshold of the noise time domain signal during operation with the calculated first sound pressure level, it can be known whether there is a problem with the centrifugal fan. When the maximum first sound pressure level is greater than the working threshold, an abnormal alarm message is issued. When there is no problem with the centrifugal fan, the second sound pressure level is compared with the sensitive threshold. The sensitive threshold is the minimum value of the sound pressure level that humans feel uncomfortable with the noise signal. It can be set according to the actual situation. When the second sound pressure level is greater than the sensitive threshold, the speed of the centrifugal fan is reduced.

[0042] In this embodiment, the working state of the centrifugal fan is adjusted by combining the first sound pressure level and the second sound pressure level. The first sound pressure level is used to monitor whether the centrifugal fan is abnormal. On this basis, the centrifugal fan is adjusted considering human sensitivity to noise signals, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan.

[0043] The present invention provides a noise online monitoring system for a multi-blade centrifugal fan, which uses the above-mentioned noise online monitoring method for a multi-blade centrifugal fan, such as Figure 8 As shown, including: A time domain signal acquisition module is used to acquire the noise time domain signal of the centrifugal fan; A time domain signal separation module is used to input the noise time domain signal into the noise separation model to obtain a separated noise time domain signal; A first sound pressure level calculation module, used to calculate the first sound pressure level according to the separated noise time domain signal; A frequency domain signal acquisition module is used to perform discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; A second sound pressure level calculation module, used for calculating a second sound pressure level according to the noise frequency domain signal; A centrifugal fan adjustment module, used for adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level; The separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal.

[0044] In this embodiment, by acquiring the time domain signal of the centrifugal fan noise, separating the time domain signals of the volute noise and the mechanical noise from the time domain signal, and calculating their first sound pressure levels respectively, the time domain signal is converted into a frequency domain signal to calculate the second sound pressure level of the total noise to monitor the noise in real time, and adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level obtained by monitoring, thereby reducing the noise of the centrifugal fan and improving the working efficiency of the centrifugal fan.

[0045] It should be understood that the disclosed system can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of the above modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, each functional module can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0046] The present invention provides an electronic device 2, such as Fig. 9 As shown, a processor 21 and a memory 22, the memory 22 is used to store computer program codes, the computer program codes include computer instructions, when the processor 21 executes the computer instructions, the electronic device executes the above-mentioned method for online noise monitoring of a multi-blade centrifugal fan.

[0047] The electronic device 2 includes a processor 21, a memory 22, an output device 23, and an input device 24. The processor 21, the memory 22, the output device 23, and the input device 24 are coupled via a connector, and the connector includes various interfaces, transmission lines, or buses, etc., which are not limited in the embodiments of the present invention. It should be understood that in various embodiments of the present invention, coupling refers to mutual connection in a specific manner, including direct connection or indirect connection through other devices, for example, through various interfaces, transmission lines, buses, etc.

[0048] The processor 21 may be one or more graphics processing units (GPUs). When the processor 21 is a GPU, the GPU may be a single-core GPU or a multi-core GPU. Optionally, the processor 21 may be a processor group consisting of multiple GPUs, and the multiple processors are coupled to each other via one or more buses. Optionally, the processor 21 may also be other types of processors, etc., which are not limited in the embodiments of the present invention.

[0049] The memory 22 can be used to store computer program instructions and various computer program codes including program codes for executing the scheme of the present invention. Optionally, the memory 22 includes but is not limited to random access memory (RAM), read-only memory (ROM), erasable programmable read only memory (EPROM), or portable read only memory (CD-ROM), and the memory 22 is used for related instructions and data.

[0050] The input device 24 is used to input data and / or signals, and the output device 23 is used to output data and / or signals. The output device 23 and the input device 24 can be independent devices or an integrated device.

[0051] The present invention provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the above-mentioned method for online noise monitoring of a multi-blade centrifugal fan.

[0052] The above are only specific embodiments of the present invention, which enable those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for online noise monitoring of a multi-blade centrifugal fan, characterized in that: include: Obtain the noise time domain signal of the centrifugal fan; Inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal; Calculating first sound pressure levels respectively according to the separated noise time domain signals; Performing discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; Calculating a second sound pressure level according to the noise frequency domain signal; adjusting a centrifugal fan according to the first sound pressure level and the second sound pressure level; Wherein, the separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal; The calculating the first sound pressure level respectively according to the separated noise time domain signal comprises: Calculating the effective sound pressure of the separated noise in the time domain according to the separated noise time domain signal; Calculating the first sound pressure level according to the effective sound pressure of the separated noise in time domain; The calculation formula of the effective sound pressure of the separated noise in the time domain is as follows: ； in, To separate the effective sound pressure of noise in time domain, is the sampling number of the noisy time domain signal, For the The sound pressure at each sampling moment; The calculation formula of the first sound pressure level is as follows: ； in, is the first sound pressure level, To separate the effective sound pressure of noise in time domain, is the atmospheric reference sound pressure.

2. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 1, characterized in that: Before inputting the noise time domain signal into the noise separation model to obtain the separated noise time domain signal, the method further includes: Get multiple simulated volute noises and simulated mechanical noises; Randomly mixing the simulated volute noise and the simulated mechanical noise to obtain an original data set; The original data set is randomly sampled in a fixed time window, and the noise data obtained by sampling is gain-summed to form new noise data to obtain a training sample set; The noise separation model is trained using the training sample set.

3. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 2, characterized in that: The step of training the noise separation model by using the training sample set includes: Performing short-time Fourier transform on the noise data of the training sample set to obtain a characteristic signal; Performing block mask calculation on the characteristic signal to obtain a separated signal spectrum; Performing an inverse short-time Fourier transform on the separated signal spectrum to obtain the separated noise time domain signal; The separated noise time domain signal is evaluated and the parameter weights of the noise separation model are modified.

4. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 3, characterized in that: The step of evaluating the separated noise time domain signal and correcting the parameter weights of the noise separation model includes: Performing short-time Fourier transform on the simulated volute noise and the simulated mechanical noise in the training sample set to obtain a real signal spectrum; According to the separated signal spectrum and the true signal spectrum, a loss function is constructed to evaluate the separated noise time domain signal.

5. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 4, characterized in that: The calculation formula of the loss function is as follows: ； in, is the loss function, is the real signal spectrum, To separate the signal spectrum.

6. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 1, characterized in that: The step of calculating the second sound pressure level according to the noise frequency domain signal comprises: Calculating the noise frequency domain amplitude according to the noise frequency domain signal; Calculating the effective sound pressure in the noise frequency domain according to the noise frequency domain amplitude; Calculating the second sound pressure level according to the effective sound pressure in the noise frequency domain; The calculation formula of the noise frequency domain amplitude is as follows: ； in, is the noise frequency domain amplitude, is the noise frequency domain signal, is the weighting operation symbol, is the frequency point number, is the sampling rate of the noisy time domain signal, is the sampling number of the noisy time domain signal; The calculation formula of the effective sound pressure in the noise frequency domain is as follows: ； in, is the effective sound pressure in the noise frequency domain, is the sampling number of the noisy time domain signal, is the noise frequency domain amplitude; The calculation formula of the second sound pressure level is as follows: ； in, is the second sound pressure level, is the effective sound pressure in the noise frequency domain, is the atmospheric reference sound pressure.

7. The method for online noise monitoring of a multi-blade centrifugal fan according to claim 1, characterized in that: The adjusting the centrifugal fan according to the first sound pressure level and the second sound pressure level includes: Comparing the first sound pressure level with the first sound pressure level to obtain a maximum first sound pressure level; Comparing the maximum first sound pressure level with a working threshold of a noise time domain signal corresponding to the maximum first sound pressure level, and when the maximum first sound pressure level is greater than the working threshold, shutting down the centrifugal fan and issuing an abnormal alarm; When the maximum first sound pressure level is less than the working threshold, the second sound pressure level is compared with a sensitive threshold, and when the second sound pressure level is greater than the sensitive threshold, the rotation speed of the centrifugal fan is reduced.

8. An online noise monitoring system for a multi-blade centrifugal fan, using the online noise monitoring method for a multi-blade centrifugal fan as claimed in any one of claims 1 to 7, characterized in that: include: A time domain signal acquisition module is used to acquire the noise time domain signal of the centrifugal fan; A time domain signal separation module, used for inputting the noise time domain signal into a noise separation model to obtain a separated noise time domain signal; A first sound pressure level calculation module, used to calculate the first sound pressure level according to the separated noise time domain signal; A frequency domain signal acquisition module, used for performing discrete Fourier transform on the noise time domain signal to obtain a noise frequency domain signal; A second sound pressure level calculation module, used for calculating a second sound pressure level according to the noise frequency domain signal; a centrifugal fan adjustment module, configured to adjust the centrifugal fan according to the first sound pressure level and the second sound pressure level; The separated noise time domain signal includes a volute noise time domain signal and a mechanical noise time domain signal.

9. An electronic device, characterized in that: It includes a processor and a memory, the memory is used to store computer program code, the computer program code includes computer instructions, when the processor executes the computer instructions, the electronic device executes the noise online monitoring method of a multi-blade centrifugal fan as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes a method for online noise monitoring of a multi-blade centrifugal fan as described in any one of claims 1 to 7.

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