Howling recognition device, method and system for electronic assembly and storage medium

Abstract

The invention provides a howling recognition device, method and system for an electronic assembly and a storage medium, and relates to the technical field of acoustic signal processing. The howling recognition device comprises a microphone array, a reference microphone and an acquisition and transmission device, wherein the acquisition and transmission device is also used for forwarding acoustic signals and noise signals to a data processing device; the data processing device is used for respectively eliminating environment noise in each acoustic signal based on the noise signal to obtain a plurality of target sound signals; the data processing device is further used for identifying the squeal source position of the electronic assembly based on the multiple target sound signals. According to the invention, the position of the howling source of the electronic assembly can be automatically identified without manual judgment, so that the positioning accuracy of the howling source is improved, the howling identification efficiency of the electronic assembly is improved, and finally the howling identification accuracy of the electronic assembly is improved; and the acoustic signals of the electronic assembly are acquired through the plurality of main microphones, so that the anti-interference capability is high, and the positioning accuracy of the howling source is further improved.

Description

Technical Field

[0001] This invention relates to the field of acoustic signal processing technology, and in particular to a howling recognition device, method, system and storage medium for electronic assemblies. Background Technology

[0002] During the operation of electronic assemblies (such as circuit boards), high-frequency components such as inductors and capacitors may generate high-frequency whistling noise due to mechanical vibration, magnetostriction, or electromagnetic interference. This type of noise is usually in the audible or ultrasonic range, which not only affects the reliability of the equipment but may also lead to the degradation of circuit performance. Therefore, it is necessary to identify the whistling noise in electronic assemblies, that is, to locate the source of the whistling noise and confirm whether the corresponding component has failed.

[0003] Currently, the source of howling in electronic assemblies is located by relying on manual listening or single-point microphone spectrum analysis. However, both manual judgment and single-point microphone spectrum analysis suffer from problems such as fuzzy localization and weak anti-interference ability, resulting in low accuracy in howling source identification. Summary of the Invention

[0004] This invention provides a howling source identification device, method, system, and storage medium for electronic assemblies, to solve the problem of low accuracy in howling source identification in the prior art, and to achieve efficient and high-quality howling source identification.

[0005] This invention provides a whistling detection device for electronic assemblies, comprising: A microphone array, comprising multiple main microphones, each of which is used to acquire acoustic signals from the electronic assembly; A reference microphone, used to collect ambient noise; The acquisition and transmission device is communicatively connected to the plurality of main microphones and the reference microphone, and is also communicatively connected to the data processing device. The acquisition and transmission device is used to acquire acoustic signals acquired by the plurality of main microphones and to acquire noise signals acquired by the reference microphone. The acquisition and transmission device is also used to forward the acoustic signals and the noise signals to the data processing device. The data processing device is used to eliminate environmental noise in each of the acoustic signals based on the noise signals to obtain multiple target sound signals; the data processing device is also used to identify the location of the howling source of the electronic assembly based on the multiple target sound signals.

[0006] According to the present invention, an electronic assembly feedback detection device is provided, wherein the acquisition and transmission device includes an analog-to-digital converter connected to each of the main microphones and the reference microphones respectively, and a control device; The control device is used to control each of the analog-to-digital converters to work synchronously, so as to synchronously collect and forward the acoustic signals converted into digital signals and the noise signals converted into digital signals to the data processing device.

[0007] According to the present invention, a howling detection device for an electronic assembly is provided, wherein the reference microphone is disposed at the center of the microphone array.

[0008] The whistling recognition device for an electronic assembly according to the present invention further includes: an image acquisition device; The image acquisition device is used to acquire surface images of the electronic assembly; The image acquisition device is communicatively connected to the data processing device; the data processing device is also used to acquire the surface image and mark the location of the howling source of the electronic assembly on the surface image.

[0009] According to the present invention, an electronic assembly whistling identification device is provided, wherein the whistling identification device is integrated and the relative positions of the components in the whistling identification device remain unchanged.

[0010] The present invention also provides a method for identifying howling noise in an electronic assembly, applied to a data processing device, wherein the data processing device is communicatively connected to the howling noise identification device for the electronic assembly as described in any of the above claims, and the howling noise identification method includes: Receives noise signals and multiple acoustic signals sent by the howling identification device; Based on the noise signal, environmental noise in each of the acoustic signals is eliminated to obtain multiple target sound signals; Based on the multiple target sound signals, the location of the howling source of the electronic assembly is identified.

[0011] According to the present invention, a method for identifying howling sources in an electronic assembly, wherein identifying the location of the howling source in the electronic assembly based on the plurality of target sound signals includes: Frequency domain data is obtained by performing a frequency domain transformation on the time domain data composed of the multiple target sound signals; The frequency domain data is divided into multiple overlapping sub-bands; The covariance matrix of the center frequency of each sub-band is multiplied by the focusing matrix on the left and right to obtain the focused covariance matrix of each sub-band; the focusing matrix is ​​used to focus to a preset reference frequency. The covariance matrix of the time-domain data is obtained by averaging the covariance matrices of each sub-band after focusing. The covariance matrix of the time-domain data is decomposed into eigenvalues ​​to obtain the signal subspace and the noise subspace. The location of the howling source of the electronic assembly is identified based on the spatial spectrum function generated using the signal subspace.

[0012] According to the present invention, a method for identifying howling sources in an electronic assembly, after identifying the location of the howling source of the electronic assembly based on the spatial spectrum function generated using the signal subspace, further includes: Based on the aforementioned spatial spectral function, several spectral peaks are determined; According to the order of the spectral peaks from largest to smallest, the sound source signals of several howling sources are separated from the time-domain data in sequence; the number of the several howling sources is the same as the number of the several spectral peaks. Based on the feature-type mapping relationship, the component type matching the acoustic feature of each sound source signal is determined respectively; the feature-type mapping relationship includes multiple first correspondences, and any first correspondence is used to indicate the matching relationship between an acoustic feature and a component type.

[0013] According to the present invention, a method for identifying howling sources in an electronic assembly, wherein identifying the location of the howling source in the electronic assembly based on a spatial spectrum function generated using the signal subspace includes: Based on the spatial spectrum function, the location result of the first howling source is determined; the location result of the first howling source includes the location results of the plurality of howling sources; Based on the type-location mapping relationship and the types of each component, a second howling source location result is determined; the second howling source location result includes location results that match each of the component types, and the type-location mapping relationship includes multiple second correspondence relationships, any second correspondence relationship being used to indicate the matching relationship between a component type and a location result; Based on the first and second howling source location results, the howling source location of the electronic assembly is determined.

[0014] The present invention also provides a howling recognition system for electronic assemblies, comprising: The whistling recognition device for electronic assemblies as described above; A data processing device for performing a whistling identification method for an electronic assembly as described in any of the above descriptions.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the whistling recognition method for electronic assemblies as described above.

[0016] The present invention provides a feedback noise recognition device, method, system, and storage medium for electronic assemblies. The feedback noise recognition device includes main microphones that collect acoustic signals from the electronic assembly, allowing a data processing device to automatically identify the location of the feedback noise source without manual intervention. This improves the accuracy of feedback noise source localization, increases feedback noise recognition efficiency, reduces feedback noise recognition costs, and ultimately enhances feedback noise recognition accuracy. Furthermore, the use of multiple main microphones to collect acoustic signals provides strong anti-interference capabilities, further improving feedback noise source localization accuracy and feedback noise recognition accuracy. A reference microphone in the feedback noise recognition device is used to collect ambient noise for data processing. The device is used to eliminate environmental noise from each acoustic signal based on a noise signal, obtaining multiple target sound signals. These target sound signals are then used to identify the location of the howling source in the electronic assembly, thereby improving the signal-to-noise ratio of the acoustic signals acquired by the main microphone, thus improving the accuracy of howling source localization and ultimately enhancing the accuracy of howling identification of the electronic assembly. Furthermore, the acquisition and transmission device is used to acquire acoustic signals from multiple main microphones and noise signals from a reference microphone. This device also forwards the acoustic and noise signals to a data processing device, enabling communication between the howling identification device and the data processing device, thus ensuring automatic identification of the howling source in the electronic assembly. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is one of the structural schematic diagrams of the whistling recognition device for electronic assemblies provided by the present invention.

[0019] Figure 2 This is the second structural schematic diagram of the whistling recognition device for electronic assemblies provided by the present invention.

[0020] Figure 3 This is the third schematic diagram of the structure of the whistling recognition device for electronic assemblies provided by the present invention.

[0021] Figure 4This is the fourth structural schematic diagram of the whistling recognition device for electronic assemblies provided by the present invention.

[0022] Figure 5 This is the fifth schematic diagram of the structure of the whistling recognition device for electronic assemblies provided by the present invention.

[0023] Figure 6 This is a flowchart illustrating the whistling recognition method for electronic assemblies provided by the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] In the description of the embodiments of the present invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of 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, they should not be construed as limitations on the embodiments of the present invention. In addition, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention based on the specific circumstances.

[0027] In embodiments of the present invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0028] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples, without contradiction. Additionally, the term "a plurality of" indicates two or more.

[0029] The present invention proposes the following embodiments. The following is a detailed description in conjunction with... Figures 1-6 The present invention describes a whistling detection device and a whistling detection method for electronic assemblies.

[0030] Figure 1 This is one of the structural schematic diagrams of the whistling recognition device for electronic assemblies provided by the present invention, such as... Figure 1 As shown, the howling detection device of the electronic assembly includes: a microphone array, a reference microphone 1, and a data acquisition and transmission device 2.

[0031] Here, electronic assembly includes electronic components, such as a printed circuit board (PCB).

[0032] The microphone array includes multiple main microphones 3, each of which is used to collect acoustic signals from the electronic assembly.

[0033] In one specific embodiment, each main microphone 3 is used to collect acoustic signals across the entire frequency band of the electronic assembly, thereby ensuring that all howling source signals can be identified, thus improving the accuracy of howling identification.

[0034] In one embodiment, each main microphone 3 is an analog microphone, meaning its output signal is an analog signal, and the analog-to-digital converter (ADC) is external to the main microphone 3. In another embodiment, each main microphone 3 is a digital microphone, meaning the ADC is built into the main microphone 3.

[0035] The number of microphones 3 can be set according to actual needs, such as 4, 6, 8, etc. Preferably, after extensive experiments, it has been proven that the number of microphones 3 is 6, that is, the microphone array includes six main microphones, which has the best effect.

[0036] In one embodiment, the microphone array is a ring-shaped microphone array, i.e., multiple main microphones are arranged in a ring, which facilitates the efficient and accurate generation of the topological relationship corresponding to the microphone array, such as facilitating the efficient and accurate generation of the manifold matrix of the microphone array. Of course, the microphone array can also be a circular microphone array or a planar microphone array, etc.

[0037] The reference microphone 1 is used to collect ambient noise (background noise), i.e., to collect noise signals. The reference microphone 1 collects ambient noise as a noise reduction benchmark for each acoustic signal collected by the microphone array.

[0038] The number of reference microphones is usually one, but multiple reference microphones can be set according to actual needs. If there are multiple reference microphones, they can be set in different positions to improve the comprehensiveness and accuracy of environmental noise collection.

[0039] For example, such as Figure 2 As shown, the microphone array is a circular microphone array, with multiple main microphones 3 arranged in a ring, and the reference microphone 1 located at the center of the microphone array.

[0040] The acquisition and transmission device 2 is communicatively connected to multiple main microphones 3, and also communicatively connected to a reference microphone 1. Furthermore, it is communicatively connected to a data processing device. The acquisition and transmission device 2 is used to acquire acoustic signals collected by the multiple main microphones 3, and noise signals collected by the reference microphone 1. It also forwards the acoustic and noise signals to the data processing device. This communication connection can be wired or wireless.

[0041] In one embodiment, the acquisition and transmission device 2 includes analog-to-digital converters connected to each main microphone 3 and reference microphone 1 respectively, so that the acquisition and transmission device 2 can forward the acoustic signals converted to digital signals and the noise signals converted to digital signals to the data processing device.

[0042] In one embodiment, the acquisition and transmission device 2 can synchronously acquire and forward each acoustic signal and noise signal to the data processing device, thereby ensuring that the data acquisition time of each acoustic signal and noise signal is consistent, thereby improving the accuracy of noise reduction, as well as the accuracy of howling source localization, and ultimately improving the accuracy of howling recognition.

[0043] Furthermore, the acquisition and transmission device 2 is connected to the data processing device via a high-speed USB interface, thereby improving data transmission efficiency and thus improving the efficiency of howling detection.

[0044] The data processing unit is used to eliminate environmental noise from each acoustic signal based on the noise signal, thereby obtaining multiple target sound signals. It should be understood that by cleverly setting up a reference microphone, the environmental noise of the main microphone can be eliminated based on the noise signal collected by the reference microphone, thus improving the signal-to-noise ratio of the acoustic signal collected by the main microphone and ultimately improving the accuracy of howling detection.

[0045] The data processing device can be configured according to actual needs, such as a host computer, desktop computer, laptop computer, server, etc.

[0046] The data processing device is also used to identify the location of the howling source of the electronic assembly based on multiple target sound signals. In one specific embodiment, a Music (Multiple Signal Classification) algorithm is used to identify the location of the howling source of the electronic assembly based on multiple target sound signals. Specifically, the execution process of the data processing device can be referred to the embodiments of the howling identification method for electronic assemblies described below, and will not be repeated here.

[0047] Here, the howling source is the sound source that causes the howling. The number of howling source locations can be one or more, meaning that howling can occur from multiple locations simultaneously.

[0048] Furthermore, the whistling recognition device also includes an image acquisition device for acquiring surface images of the electronic assembly.

[0049] In one embodiment, the image acquisition device is communicatively connected to the acquisition and transmission device, thereby enabling the acquisition and transmission device to acquire surface images captured by the image acquisition device and forward the surface images to the data processing device. The data processing device then uses these surface images to mark the location of the howling source of the electronic assembly, thus visualizing the howling source and improving the user experience. More specifically, the image acquisition device is communicatively connected to the control device within the acquisition and transmission device.

[0050] The feedback noise recognition device for electronic assemblies provided in this embodiment of the invention includes main microphones for collecting acoustic signals from the electronic assembly, thereby enabling a data processing device to automatically identify the location of the feedback source without manual judgment. This improves the accuracy of feedback source localization, increases feedback recognition efficiency, reduces feedback recognition costs, and ultimately enhances feedback recognition accuracy. Furthermore, by collecting acoustic signals from multiple main microphones, the device exhibits strong anti-interference capabilities, further improving feedback source localization accuracy and feedback recognition accuracy. A reference microphone is included to collect ambient noise, which is then used by the data processing device to analyze noise signals. The system eliminates environmental noise from each acoustic signal to obtain multiple target sound signals. Based on these multiple target sound signals, the location of the howling source in the electronic assembly is identified, thereby improving the signal-to-noise ratio of the acoustic signals collected by the main microphone, thus improving the accuracy of howling source localization and ultimately improving the accuracy of howling identification of the electronic assembly. The acquisition and transmission device is used to acquire the acoustic signals collected by the multiple main microphones and the noise signals collected by the reference microphone. The acquisition and transmission device is also used to forward each acoustic signal and noise signal to the data processing device. Thus, the howling identification device and the data processing device can be connected through the acquisition and transmission device to ensure that the howling source of the electronic assembly can be automatically identified.

[0051] Based on any of the above embodiments Figure 3 This is the third structural schematic diagram of the whistling recognition device for electronic assemblies provided by the present invention, as shown below. Figure 3 As shown, the acquisition and transmission device 2 includes multiple analog-to-digital converters 201 and a control device 202.

[0052] Multiple analog-to-digital converters (ADCs) 201 are connected to each main microphone 3 and reference microphone 1, respectively. That is, one ADC is connected to each microphone, and each microphone is connected to an independent ADC. The ADC 201 is used to convert the analog signals output by the microphones into digital signals for easier transmission and subsequent processing.

[0053] Here, the control device 202 can be configured according to actual needs, for example, it can be an FPGA (Field-Programmable Gate Array) chip.

[0054] The control device 202 is used to control the synchronous operation of each analog-to-digital converter 201 to synchronously acquire and forward the acoustic signals and noise signals converted into digital signals to the data processing device. For example, the FPGA controls the synchronous operation of each analog-to-digital converter 201 through a unified clock to ensure consistent data acquisition time.

[0055] Furthermore, the control device 202 stores the converted acoustic signals and converted noise signals into digital signals in its buffer before uploading them to the data processing device. For example, the FPGA stores the converted digital signals in its FPGA buffer and then uploads them to the data processing device via high-speed USB.

[0056] The feedback recognition device for electronic assemblies provided in this embodiment of the invention includes an analog-to-digital converter (ADC) connected to each main microphone and a reference microphone, and a control device. The control device controls each ADC to work synchronously, so as to synchronously collect and forward each acoustic signal converted into a digital signal and noise signal converted into a digital signal to the data processing device, thereby ensuring that the data collection time of each acoustic signal and noise signal is consistent, thereby improving the noise reduction accuracy and the positioning accuracy of the feedback source, and ultimately further improving the feedback recognition accuracy of the electronic assembly.

[0057] Based on any of the above embodiments, in this howling recognition device, the reference microphone 1 is located at the center of the microphone array.

[0058] Considering that in practical applications, the microphone array is also located in the central area of ​​the electronic assembly, the reference microphone 1 is also located in the central area of ​​the electronic assembly, thereby better collecting the environmental noise of the electronic assembly, improving the noise reduction accuracy, and ultimately improving the accuracy of howling recognition; for example, the microphone array is located in the central area of ​​the howling recognition device, and the howling recognition device is located above the central area of ​​the electronic assembly, so the reference microphone 1 is also located above the central area of ​​the electronic assembly; for example, if the microphone array is a circular microphone array, then the reference microphone 1 is located at the center of the circle corresponding to the circular microphone array.

[0059] For example, such as Figure 2 As shown, the microphone array is a circular microphone array, with multiple main microphones 3 arranged in a ring, and the reference microphone 1 located at the center of the microphone array.

[0060] The feedback recognition device for electronic assemblies provided in this embodiment of the invention uses a reference microphone 1 located at the center of a microphone array, so that the noise signal it collects can be better used as a noise reduction benchmark, thereby improving the noise reduction accuracy and ultimately improving the accuracy of feedback recognition.

[0061] Based on any of the above embodiments Figure 4 This is the fourth structural schematic diagram of the whistling recognition device for electronic assemblies provided by the present invention, as shown below. Figure 4 As shown, the whistling recognition device also includes an image acquisition device 4.

[0062] The image acquisition device 4 is used to acquire surface images of the electronic assembly. For example, the image acquisition device 4 is a camera, which captures surface images of the electronic assembly (such as a circuit board).

[0063] In one specific embodiment, the image acquisition device 4 is positioned at the center of the microphone array, so that the surface image it acquires can better cover the electronic assembly, thereby improving the visualization of the howling source. Specifically, considering that in practical applications, the microphone array is also positioned at the center of the electronic assembly, the image acquisition device 4 is also positioned at the center of the electronic assembly, thus better acquiring the surface image of the electronic assembly; for example, the microphone array is located in the center of the howling recognition device, and the howling recognition device is positioned above the center of the electronic assembly, so the image acquisition device 4 is also positioned above the center of the electronic assembly; for example, if the microphone array is a circular microphone array, then the image acquisition device 4 is positioned at the center of the circle corresponding to the circular microphone array.

[0064] The number of image acquisition devices 4 is usually 1, but multiple image acquisition devices can be set according to actual needs. If there are multiple image acquisition devices, they can be set in different positions according to actual needs to improve the comprehensiveness and accuracy of surface image acquisition.

[0065] For example, such as Figure 5 As shown, the microphone array is a circular microphone array, with multiple main microphones 3 arranged in a ring, a reference microphone 1 located at the center of the microphone array, and an image acquisition device 4 also located at the center of the microphone array.

[0066] The image acquisition device 4 is communicatively connected to the data processing device. The data processing device also acquires surface images and marks the location of the howling source of the electronic assembly on the surface images. This visualizes the location of the howling source, thereby improving the user experience. The communication connection can be wired or wireless.

[0067] Specifically, the data processing device is also used to display the marked surface image, thereby visualizing the source of the howling and improving the user experience.

[0068] The whistling recognition device for electronic assemblies provided in this embodiment of the invention further includes an image acquisition device, which is communicatively connected to a data processing device. The data processing device can acquire a surface image of the electronic assembly acquired by the image acquisition device, and mark the location of the whistling source on the surface image, thereby visualizing the location of the whistling source and ultimately improving the user experience. Furthermore, the image acquisition device and the data processing device are directly communicatively connected, eliminating the need for an acquisition and transmission device, thus improving image transmission efficiency and consequently enhancing the whistling recognition efficiency of the electronic assembly.

[0069] Based on any of the above embodiments, the howling recognition device is integrated, and the relative positions of the components in the howling recognition device remain unchanged.

[0070] The whistling recognition device for electronic assemblies provided in this embodiment of the invention is an integrated device in which the relative positions of each component remain unchanged, i.e., each component in the whistling recognition device is fixedly set. Therefore, the whistling recognition device can be directly deployed on the electronic assembly without assembling each component to obtain the whistling recognition device in the actual whistling recognition process, thereby improving the whistling recognition efficiency of the electronic assembly.

[0071] Based on any of the above embodiments, the present invention also provides a method for identifying howling sounds in an electronic assembly. This method is applied to a data processing device, which is communicatively connected to the howling sound identification device of the electronic assembly as described in any of the above embodiments. Figure 6 This is a flowchart illustrating the whistling recognition method for electronic assemblies provided by the present invention, as shown below. Figure 6 As shown, the howling identification method includes steps 610, 620 and 630.

[0072] Step 610: Receive noise signals and multiple acoustic signals sent by the howling identification device.

[0073] Specifically, it receives noise signals and multiple acoustic signals sent by the acquisition and transmission device in the howling identification device.

[0074] In one specific embodiment, after receiving the audio signal sent by the howling recognition device, the audio signal is separated to obtain a noise signal and multiple acoustic signals.

[0075] Furthermore, the noise signal and multiple acoustic signals sent by the howling detection device are preprocessed. For example, the signal preprocessing method is frequency domain shaping. Based on this, the noise reduction accuracy and the positioning accuracy of the howling source are improved, ultimately improving the howling detection accuracy of the electronic assembly. In a specific embodiment, the noise signal and multiple acoustic signals sent by the howling detection device are subjected to FIR digital filter frequency domain shaping.

[0076] Step 620: Based on the noise signal, eliminate the environmental noise in each of the acoustic signals to obtain multiple target sound signals.

[0077] Specifically, based on noise signals, the ambient noise from the same source in each acoustic signal is eliminated, and multiple target sound signals are retained.

[0078] Step 630: Based on the multiple target sound signals, identify the location of the howling source of the electronic assembly.

[0079] In one specific embodiment, frequency domain transformation is performed on time domain data composed of multiple target sound signals to obtain frequency domain data; based on the frequency domain data, a covariance matrix of the time domain data is constructed; eigenvalue decomposition is performed on the covariance matrix of the time domain data to obtain a signal subspace and a noise subspace; based on the spatial spectrum function generated using the signal subspace, the location of the howling source of the electronic assembly is identified.

[0080] Furthermore, based on the spatial spectral function, several spectral peaks are determined; according to the order of these spectral peaks from largest to smallest, the sound source signals of several howling sources are sequentially separated from the time-domain data; the number of howling sources is the same as the number of spectral peaks. Based on this, for complex electronic assemblies, embodiments of the present invention can also distinguish the core howling source, that is, the howling source corresponding to the largest spectral peak is the core howling source, thereby realizing the differentiation of the core fault point when multiple noise sources are superimposed.

[0081] Furthermore, based on the feature-type mapping relationship, the component type matching for the acoustic features of each sound source signal is determined. The feature-type mapping relationship includes multiple first correspondences, each of which indicates the matching relationship between an acoustic feature and a component type. Based on this, component types can also be matched based on the acoustic features of each sound source signal, thereby not only identifying the howling source but also determining the component type of the howling source, thus improving the accuracy of howling recognition and enhancing the user experience.

[0082] Furthermore, based on the spatial spectral function, a first howling source location result is determined; the first howling source location result includes the location results of the plurality of howling sources; based on the type-position mapping relationship and the types of each component, a second howling source location result is determined; the second howling source location result includes the location results matched with each component type, and the type-position mapping relationship includes multiple second correspondences, any second correspondence being used to indicate the matching relationship between a component type and a location result; based on the first and second howling source location results, the howling source position of the electronic assembly is determined. Based on this, the second howling source location result can also be obtained based on the component type, thereby improving the accuracy of howling source location and thus improving the howling recognition accuracy of the electronic assembly.

[0083] In one embodiment, a surface image of the electronic assembly sent by an image acquisition device is also received. The image acquisition device acquires the surface image of the electronic assembly and marks the location of the howling source on the surface image, thereby visualizing the location of the howling source and ultimately improving the user experience. For example, a howling source location marker can be superimposed on the surface image; this marker can be set according to actual needs, such as a red dot or a circle. Furthermore, distortion correction and coordinate system calibration can be performed on the surface image to provide a spatial reference, thereby improving the accuracy of the howling source location marker.

[0084] Furthermore, while displaying the marked surface image, the spectrum and waveform of the howling source signal can be displayed simultaneously, thereby achieving visualized fault diagnosis.

[0085] The feedback noise recognition method for electronic assemblies provided in this invention includes a feedback noise recognition device where each main microphone is used to collect acoustic signals from the electronic assembly. This allows the data processing device to automatically identify the location of the feedback noise source without manual intervention, thereby improving the accuracy of feedback noise source localization, increasing feedback noise recognition efficiency, reducing feedback noise recognition costs, and ultimately improving the accuracy of feedback noise recognition. Furthermore, by using multiple main microphones to collect acoustic signals from the electronic assembly, the method exhibits strong anti-interference capabilities, further improving the accuracy of feedback noise source localization and ultimately enhancing the accuracy of feedback noise recognition. The feedback noise recognition device also includes a reference microphone for collecting ambient noise, allowing the data processing device to automatically identify the location of the feedback noise source based on the noise signal. The device eliminates environmental noise from each acoustic signal to obtain multiple target sound signals. These signals are then used to identify the location of the howling source in the electronic assembly, thereby improving the signal-to-noise ratio of the acoustic signals collected by the main microphone, thus improving the accuracy of howling source localization and ultimately enhancing the accuracy of howling identification in the electronic assembly. Furthermore, the howling identification device includes a data acquisition and transmission unit for acquiring acoustic signals from multiple main microphones and noise signals from a reference microphone. This unit also forwards the acoustic and noise signals to a data processing unit, enabling communication between the howling identification device and the data processing unit, thus ensuring automatic identification of howling sources in the electronic assembly.

[0086] Based on any of the above embodiments, in this method, step 630 includes steps 631 to 636.

[0087] Step 631: Perform frequency domain transformation on the time domain data composed of the multiple target sound signals to obtain frequency domain data.

[0088] Here, the time-domain data is a vector composed of multiple target sound signals. In one specific embodiment, a Fourier transform is performed on the time-domain data to obtain the frequency-domain data.

[0089] Step 632: Divide the frequency domain data into multiple overlapping sub-bands.

[0090] Specifically, the frequency domain signal corresponding to the frequency domain data is divided into multiple continuous frequency bandwidths (sub-bands). Each sub-band covers a specific frequency range, and there is partial frequency overlap between the sub-bands (such as 50% overlap) to ensure the continuity of frequency components and avoid information loss. Step 633: Multiply the covariance matrix of the center frequency of each sub-band by the focusing matrix on the left and right respectively to obtain the focused covariance matrix of each sub-band.

[0092] Here, the covariance matrix is ​​the matrix representing the correlation between the channels of the multi-channel signal.

[0093] The focusing matrix is ​​used to focus on a preset reference frequency. This focusing matrix is ​​a linear transformation matrix used to align the covariance matrices of different frequency sub-bands to the reference frequency, eliminating frequency dependence and making the spatial spectrum estimation of the broadband signal more consistent, thereby improving the accuracy of the howling source location. The preset reference frequency is a pre-set center frequency (such as the mean of the sub-band center frequencies) used as the reference for focusing.

[0094] Step 634: Average the covariance matrices of each sub-band after focusing to obtain the covariance matrix of the time-domain data.

[0095] Specifically, the covariance matrices of multiple sub-bands after focusing are added together and averaged to integrate full-band information, enhance signal commonality, and suppress noise.

[0096] It should be understood that, in order to overcome the signal subspace dispersion problem caused by the broadband characteristics of howling signals from electronic assemblies (such as circuit boards), frequency domain smoothing technology is used to focus the covariance matrix, thereby improving the positioning accuracy of the howling source.

[0097] Step 635: Perform eigenvalue decomposition on the covariance matrix of the time-domain data to obtain the signal subspace and the noise subspace.

[0098] Here, the signal subspace is the space spanned by the eigenvectors corresponding to the large eigenvalues, representing the signal components. The noise subspace is the space spanned by the eigenvectors corresponding to the small eigenvalues, representing noise and interference.

[0099] Step 636: Identify the location of the howling source of the electronic assembly based on the spatial spectrum function generated using the signal subspace.

[0100] Specifically, a manifold matrix of the microphone array is constructed, and the location of the howling source of the electronic assembly is identified based on the manifold matrix and the spatial spectral function.

[0101] In one specific embodiment, by comparing the orthogonality of each vector in the signal subspace and the manifold matrix, the azimuth and elevation parameters that cause the spatial spectrum to reach an extreme value are determined. Based on these azimuth and elevation parameters, the location of the howling source is determined. Furthermore, the location of the howling source in the electronic assembly can be determined by combining a time difference of arrival (TDOA) compensation algorithm, thereby improving the accuracy of howling source localization.

[0102] It should be understood that by analyzing the phase difference and energy distribution of multi-microphone signals using the improved MUSIC algorithm in this embodiment of the invention, the three-dimensional coordinates of the howling source can be accurately calculated, thereby improving the accuracy of howling source localization.

[0103] The feedback identification method for electronic assemblies provided in this invention addresses the signal subspace dispersion problem caused by the broadband characteristics of feedback signals from electronic assemblies. By focusing and aligning the signal subspaces of different frequency points, the accuracy of the covariance matrix of time-domain data is improved, thereby improving the accuracy of feedback source localization and ultimately enhancing the accuracy of feedback identification for electronic assemblies.

[0104] Based on any of the above embodiments, after step 636, the method further includes steps 637 to 639.

[0105] Step 637: Based on the spatial spectral function, determine several spectral peaks.

[0106] Specifically, the spatial spectral function is calculated by traversing the pre-defined three-dimensional spatial mesh of the electronic assembly to determine several spectral peaks. The number of these peaks can be one or more, but is usually multiple, i.e., including multiple howling sources.

[0107] In one specific embodiment, the spatial spectral function is calculated by traversing the preset three-dimensional spatial grid of the electronic assembly, and the peak search process is optimized by using Newton's iteration method.

[0108] Step 638: Separate the sound source signals of several howling sources from the time domain data in descending order of the several spectral peaks.

[0109] In one specific embodiment, a recursive orthogonal projection algorithm is used to estimate and separate each sound source component (sound source signal) from the time-domain data (mixed signal) in descending order of signal strength. Specifically, the waveform of the strongest sound source is first estimated, and its projection component is subtracted from the mixed signal; then the second strongest sound source is estimated from the remaining signal, and so on recursively until the sound source signals of all howling sources are separated.

[0110] It should be noted that, usually, when multiple spectral peaks are detected, the sound source signals of several howling sources are separated from the time-domain data in descending order of size.

[0111] The number of the plurality of howling sources is the same as the number of the plurality of spectral peaks.

[0112] Step 639: Based on the feature-type mapping relationship, determine the component type that matches the acoustic features of each sound source signal.

[0113] The feature-type mapping relationship includes multiple first correspondences, each of which indicates the matching relationship between an acoustic feature and a component type. This feature-type mapping relationship can be represented by a database, such as a circuit board component layout database.

[0114] In some embodiments, the acoustic features are spectral features. For any sound source signal, a Fourier transform (such as a short-time Fourier transform) is performed on the sound source signal to obtain a frequency domain signal, and then the spectral features are extracted from the frequency domain signal. The spectral features may include, but are not limited to, at least one of the following: fundamental frequency, harmonic distribution, and modulation sideband features, etc.

[0115] Furthermore, the data processing device can also be used to display the spectral characteristics of each sound source signal.

[0116] The feedback noise identification method for electronic assemblies provided in this embodiment of the invention can also match the component types based on the acoustic characteristics of each sound source signal, thereby not only determining the feedback noise source, but also determining the component type of the feedback noise source, thus improving the comprehensiveness and accuracy of feedback noise identification for electronic assemblies and enhancing the user experience.

[0117] Based on any of the above embodiments, in this method, step 636 includes: Based on the spatial spectrum function, the location result of the first howling source is determined; the location result of the first howling source includes the location results of the plurality of howling sources; Based on the type-location mapping relationship and the types of each component, a second howling source location result is determined; the second howling source location result includes location results that match each of the component types, and the type-location mapping relationship includes multiple second correspondence relationships, any second correspondence relationship being used to indicate the matching relationship between a component type and a location result; Based on the first and second howling source location results, the howling source location of the electronic assembly is determined.

[0118] This type and its location mapping relationship can be represented by a database, such as a circuit board component layout database.

[0119] Since the locations corresponding to each component type are known, the location of the howling source can be determined directly based on the component type. Of course, one component type can correspond to multiple components, that is, multiple component locations.

[0120] The whistling identification method for electronic assemblies provided in this embodiment of the invention can also obtain a second whistling source location result based on the component type through the above method. In this way, the first whistling source location result determined by the spatial spectrum function and the second whistling source location result can be combined to determine the whistling source location of the electronic assembly, thereby improving the accuracy of whistling source location and ultimately improving the accuracy of whistling identification of the electronic assembly.

[0121] Based on the above embodiments, the sound field signal of electronic assemblies (such as circuit boards) can be collected by a microphone array, and the three-dimensional positioning and frequency analysis of the howling source can be realized by combining the spatial spectrum analysis algorithm. This allows for the accurate identification of abnormal noise sources caused by inductors, capacitors or high-frequency circuits in electronic assemblies, and is applicable to scenarios such as industrial production line testing, circuit debugging and noise suppression optimization.

[0122] The following describes the whistling identification system for electronic assemblies provided by the present invention. The whistling identification system described below corresponds to and can be referred to in conjunction with the whistling identification device and whistling identification method for electronic assemblies described above. The whistling identification system for electronic assemblies includes: a whistling identification device and a data processing device as described in any of the above embodiments.

[0123] The data processing device is used to execute the whistling recognition method for electronic assemblies as described in any of the above embodiments.

[0124] This invention proposes a howling recognition system for electronic assemblies, which integrates a microphone array hardware architecture and a spatial spectrum estimation algorithm to accurately locate howling sources. It can realize the location and visualization of abnormal noise sources such as howling from circuit boards, thereby improving the efficiency of fault diagnosis.

[0125] The data processing apparatus provided by the present invention will be described below. The data processing apparatus described below and the squeal recognition method for electronic assemblies described above can be referred to in correspondence.

[0126] The data processing device includes a receiving module, a noise reduction module, and an identification module.

[0127] The receiving module is used to receive noise signals and multiple acoustic signals sent by the howling identification device.

[0128] The noise reduction module is used to eliminate environmental noise in each of the acoustic signals based on the noise signals, thereby obtaining multiple target sound signals.

[0129] The identification module is used to identify the location of the howling source of the electronic assembly based on the multiple target sound signals.

[0130] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the howling recognition method for electronic assemblies provided by the above methods. The method includes: receiving a noise signal and a plurality of acoustic signals sent by the howling recognition device; based on the noise signal, eliminating environmental noise in each of the acoustic signals to obtain a plurality of target sound signals; and based on the plurality of target sound signals, identifying the howling source location of the electronic assembly.

[0131] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program implements a howling recognition method for an electronic assembly provided by the above methods. The method includes: receiving a noise signal and a plurality of acoustic signals sent by the howling recognition device; based on the noise signal, eliminating environmental noise in each of the acoustic signals to obtain a plurality of target sound signals; and based on the plurality of target sound signals, identifying the howling source location of the electronic assembly.

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0133] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A whistling detection device for an electronic assembly, characterized in that, include: A microphone array, comprising multiple main microphones, each of which is used to acquire acoustic signals from the electronic assembly; A reference microphone, used to collect ambient noise; The acquisition and transmission device is communicatively connected to the plurality of main microphones and the reference microphone, and is also communicatively connected to the data processing device. The acquisition and transmission device is used to acquire acoustic signals acquired by the plurality of main microphones and noise signals acquired by the reference microphone. The acquisition and transmission device is also used to forward the acoustic signals and the noise signals to the data processing device. The data processing device is used to eliminate environmental noise in each of the acoustic signals based on the noise signals to obtain multiple target sound signals; the data processing device is also used to identify the location of the howling source of the electronic assembly based on the multiple target sound signals.

2. The whistling recognition device for electronic assemblies according to claim 1, characterized in that, The acquisition and transmission device includes an analog-to-digital converter connected to each of the main microphones and the reference microphones, and a control device. The control device is used to control each of the analog-to-digital converters to work synchronously, so as to synchronously collect and forward the acoustic signals converted into digital signals and the noise signals converted into digital signals to the data processing device.

3. The whistling recognition device for electronic assemblies according to claim 1, characterized in that, The reference microphone is positioned at the center of the microphone array.

4. The whistling recognition device for electronic assemblies according to claim 1, characterized in that, Also includes: Image acquisition device; The image acquisition device is used to acquire surface images of the electronic assembly; The image acquisition device is communicatively connected to the data processing device; the data processing device is also used to acquire the surface image and mark the location of the howling source of the electronic assembly on the surface image.

5. The whistling recognition device for an electronic assembly according to any one of claims 1 to 4, characterized in that, The howling detection device is an integrated unit, and the relative positions of the components in the howling detection device remain unchanged.

6. A method for identifying howling noise in an electronic assembly, characterized in that, Applied to a data processing device, the data processing device being communicatively connected to a howling recognition device for an electronic assembly as described in any one of claims 1 to 5, the howling recognition method comprising: Receives noise signals and multiple acoustic signals sent by the howling identification device; Based on the noise signal, environmental noise in each of the acoustic signals is eliminated to obtain multiple target sound signals; Based on the multiple target sound signals, the location of the howling source of the electronic assembly is identified.

7. The method for identifying howling sounds in an electronic assembly according to claim 6, characterized in that, The step of identifying the location of the howling source of the electronic assembly based on the plurality of target sound signals includes: Frequency domain data is obtained by performing a frequency domain transformation on the time domain data composed of the multiple target sound signals; The frequency domain data is divided into multiple overlapping sub-bands; The covariance matrix of the center frequency of each sub-band is multiplied by the focusing matrix on the left and right to obtain the focused covariance matrix of each sub-band; the focusing matrix is ​​used to focus to a preset reference frequency; The covariance matrix of the time-domain data is obtained by averaging the covariance matrices of each sub-band after focusing. The covariance matrix of the time-domain data is decomposed into eigenvalues ​​to obtain the signal subspace and the noise subspace. The location of the howling source of the electronic assembly is identified based on the spatial spectrum function generated using the signal subspace.

8. The method for identifying howling sounds in an electronic assembly according to claim 7, characterized in that, After identifying the location of the squealing source of the electronic assembly based on the spatial spectrum function generated using the signal subspace, the method further includes: Based on the aforementioned spatial spectral function, several spectral peaks are determined; According to the order of the spectral peaks from largest to smallest, the sound source signals of several howling sources are separated from the time-domain data in sequence; the number of the several howling sources is the same as the number of the several spectral peaks. Based on the feature-type mapping relationship, the component type matching the acoustic feature of each sound source signal is determined respectively; the feature-type mapping relationship includes multiple first correspondences, and any first correspondence is used to indicate the matching relationship between an acoustic feature and a component type.

9. The method for identifying howling sounds in an electronic assembly according to claim 8, characterized in that, The method of identifying the location of the howling source of the electronic assembly based on the spatial spectrum function generated using the signal subspace includes: Based on the spatial spectrum function, the location result of the first howling source is determined; the location result of the first howling source includes the location results of the plurality of howling sources; Based on the type-location mapping relationship and the types of each component, a second howling source location result is determined; the second howling source location result includes location results that match each of the component types, and the type-location mapping relationship includes multiple second correspondence relationships, any second correspondence relationship being used to indicate the matching relationship between a component type and a location result; Based on the first and second howling source location results, the howling source location of the electronic assembly is determined.

10. A whistling recognition system for an electronic assembly, characterized in that, include: The whistling recognition device for an electronic assembly as described in any one of claims 1 to 5; A data processing device for performing the whistling identification method for an electronic assembly as described in any one of claims 6 to 9.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the whistling recognition method for the electronic assembly as described in any one of claims 6 to 9.

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