Order analysis method and system based on microphone array

Abstract

The embodiment of the invention provides an order analysis method and system based on a microphone array, and the method comprises the steps: setting the microphone array and a shooting module covering the microphone array, enabling the microphone array to collect a sound signal of target equipment, and enabling the shooting module to synchronously collect a pulse signal of the target equipment when collecting a video signal; based on the initial orientation of the positioning target device, calculating the time delay of the sound signal reaching the microphone array in combination with the geometric coordinates of the microphone array, designing a corresponding filter, and calculating a filter coefficient in combination with the time delay; based on the sound signal and the filter coefficient, convolution operation is carried out on each microphone, signal superposition and noise reduction are carried out, and a pure audio signal is output; and based on the pulse signal, calculating a rotating speed curve of the target equipment, performing resampling, generating a corresponding order atlas, and generating a diagnosis report of the target equipment according to the order atlas.

Description

Technical Field

[0001] This invention relates to the field of microphone array technology, and in particular to a method and system for order analysis based on microphone arrays. Background Technology

[0002] Traditional order analysis is an important technique for analyzing vibration and noise signals in rotating machinery. It is mainly used to study the frequency components of vibration or noise signals that are related to rotational speed. Its core idea is to dynamically correlate the frequency characteristics of the signal with the rotational speed of the rotating machinery, thereby eliminating the influence of speed changes on the spectrum analysis and more accurately identifying fault characteristics or optimizing the design.

[0003] Current order analysis technologies commonly employ vibration sensors and speed sensors. Vibration sensors collect vibration signals from the system, while speed sensors acquire rotational speeds; these are then combined for order analysis. However, existing methods suffer from low efficiency when analyzing complex systems, such as those with multiple coupled gears, irregular blades, or multi-layered structures. These methods require extensive data processing to eliminate interference and cannot differentiate between data segments. Summary of the Invention

[0004] To address the problems existing in the prior art, embodiments of the present invention provide a method and system for order analysis based on a microphone array.

[0005] This invention provides a method for order analysis based on a microphone array, the method comprising:

[0006] A microphone array and a shooting module covering the microphone array are provided. The microphone array collects the sound signal of the target device, and the shooting module collects the pulse signal of the target device simultaneously when collecting the video signal.

[0007] Based on the initial orientation of the target device located by the video signal, and combined with the geometric coordinates of the microphone array, the time delay of the sound signal reaching the microphone array is calculated, and a corresponding filter is designed for each microphone in the microphone array. The filter coefficients are then calculated based on the time delay.

[0008] Based on the sound signal and filter coefficients, convolution operation is performed on each microphone in the microphone array, and signal superposition and noise reduction are performed to output a clean audio signal;

[0009] Based on the pulse signal, the rotational speed curve of the target device is calculated, and the pure audio signal is resampled based on the rotational speed curve to generate a corresponding order spectrum. A diagnostic report for the target device is then generated based on the order spectrum.

[0010] In one embodiment, the method further includes:

[0011] Based on the video signal, the initial azimuth angle of the target device relative to the microphone array is calculated using a preset image algorithm, and then the estimated distance between the target device and each microphone is calculated by combining the coordinates of the microphones.

[0012] Calculate the standard distance to the target device based on the geometric center of the microphone array;

[0013] Calculate the time difference between the estimated distance and the standard distance for the sound signal to travel, and determine the time delay for the sound signal to reach the microphone array.

[0014] In one embodiment, calculating the filter coefficients includes:

[0015] The filter coefficients are calculated using the sinc function interpolation method, and the calculation formula is as follows:

[0016] h i [n]=sin c (π(n-Δ))

[0017] Where Δ=τ i *Fs, h i [n] represents the filter coefficients, Fs represents the sampling rate, and τ i Let n be the time delay and n be the filter order.

[0018] In one embodiment, the method further includes:

[0019] Based on the pulse time difference and the number of pulses per revolution of the pulse signal, the instantaneous rotational speed is calculated, and the rotational speed curve of the target equipment is constructed by combining the interpolation method.

[0020] Integrate the rotational speed curve to calculate the cumulative angle-time function, set the angle sampling rate, and create equally spaced angle axes;

[0021] Based on the cumulative angle-time function, for each point on the equally spaced angle axis, the corresponding non-equally spaced time points on the pure audio signal are calculated in reverse.

[0022] For the time points with non-equal intervals, an interpolation algorithm is used to calculate the corresponding amplitude sequence interpolation.

[0023] In one embodiment, the microphone array includes 208 microphone channels.

[0024] This invention provides a microphone array-based order analysis system, the system comprising:

[0025] The acquisition module is used to set up a microphone array and a shooting module covering the microphone array. The microphone array acquires the sound signal of the target device, and when the shooting module acquires the video signal, it simultaneously acquires the pulse signal of the target device.

[0026] The filtering module is used to locate the initial orientation of the target device based on the video signal, calculate the time delay of the sound signal reaching the microphone array in combination with the geometric coordinates of the microphone array, design a corresponding filter for each microphone in the microphone array, and calculate the filter coefficients in combination with the time delay.

[0027] The noise reduction module is used to perform convolution operations on each microphone in the microphone array based on the sound signal and filter coefficients, and to perform signal superposition and noise reduction to output a clean audio signal.

[0028] The diagnostic module is used to calculate the rotational speed curve of the target device based on the pulse signal, resample the pure audio signal based on the rotational speed curve to generate a corresponding order spectrum, and generate a diagnostic report of the target device based on the order spectrum.

[0029] In one embodiment, the system further includes:

[0030] The orientation module is used to calculate the initial azimuth angle of the target device relative to the microphone array based on the video signal using a preset image algorithm, and then calculate the estimated distance between the target device and each microphone by combining the coordinates of the microphones.

[0031] The central module is used to calculate the standard distance to the target device based on the geometric center of the microphone array;

[0032] The delay module is used to calculate the time difference between the estimated distance and the standard distance for the sound signal to travel, and to determine the time delay for the sound signal to reach the microphone array.

[0033] In one embodiment, the system further includes:

[0034] The speed module is used to calculate the instantaneous speed based on the pulse time difference of the pulse signal and the number of pulses per revolution, and to construct the speed curve of the target device by combining interpolation.

[0035] The sampling rate module is used to integrate the rotational speed curve, calculate the cumulative angle-time function, set the angle sampling rate, and create equally spaced angle axes.

[0036] The inverse calculation module is used to inversely calculate the non-equally spaced time points on the pure audio signal for each point on the equally spaced angle axis based on the cumulative angle-time function;

[0037] The interpolation module is used to calculate the corresponding amplitude sequence interpolation for the non-equal interval time points using an interpolation algorithm.

[0038] This invention provides an electronic device, including a processor and a memory;

[0039] The processor is connected to the memory;

[0040] The memory is used to store executable program code;

[0041] The processor runs a program corresponding to the executable program code stored in the memory to perform the methods described in one or more embodiments.

[0042] This invention provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described microphone array-based order analysis method.

[0043] In view of the above, in one or more embodiments of this specification, a microphone array and a shooting module covering the microphone array are provided. The microphone array collects the sound signal of the target device, and the shooting module collects the pulse signal of the target device simultaneously while collecting the video signal. Based on the video signal, the initial orientation of the target device is located. Combined with the geometric coordinates of the microphone array, the time delay of the sound signal reaching the microphone array is calculated, and a corresponding filter is designed for each microphone in the microphone array. The filter coefficients are calculated based on the time delay. Based on the sound signal and the filter coefficients, convolution operation is performed on each microphone in the microphone array, and signal superposition and noise reduction are performed to output a clean audio signal. Based on the pulse signal, the rotation speed curve of the target device is calculated, and the clean audio signal is resampled based on the rotation speed curve to generate a corresponding order spectrum. A diagnostic report of the target device is generated based on the order spectrum. In this way, by setting different filter coefficients for each microphone channel of the microphone array and performing order analysis after resampling, different components of the sound signal can be distinguished, and corresponding processing can be performed on sound signals of different orders, thereby improving the data processing efficiency. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart of an order analysis method based on a microphone array provided in one embodiment of this specification.

[0046] Figure 2 This is a 3D spectrum diagram of an electric fan provided in one embodiment of this specification.

[0047] Figure 3 This is a cross-sectional view of an electric fan provided in one embodiment of this specification.

[0048] Figure 4 This is a schematic diagram of the structure of a microphone array-based order analysis system provided in one embodiment of this specification.

[0049] Figure 5 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this specification. Detailed Implementation

[0050] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed merely to enable those skilled in the art to better understand and implement the subject matter described herein, and are not intended to limit the scope, applicability, or examples set forth in the claims. The function and arrangement of the elements discussed may be changed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the various examples. For example, the described methods may be performed in a different order than described, and steps may be added, omitted, or combined. Furthermore, features described in some examples may be combined in other examples.

[0051] As used herein, the term "comprising" and its variations are open terms meaning "including but not limited to". The term "based on" means "at least partially based on". The terms "one embodiment" and "an embodiment" mean "at least one embodiment". The term "another embodiment" means "at least one other embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other definitions, whether explicit or implicit, may be included below. Unless explicitly indicated by the context, the definition of a term shall remain consistent throughout the specification.

[0052] like Figure 1 As shown, this embodiment of the invention provides a method for order analysis based on a microphone array, including:

[0053] Step S102: Set up a microphone array and a shooting module covering the microphone array. The microphone array collects the sound signal of the target device. When the shooting module collects the video signal, it simultaneously collects the pulse signal of the target device.

[0054] Specifically, when noise detection and analysis of the target device is required, a corresponding microphone array and corresponding parameters are set, including array aperture, distance, etc. In this embodiment, the number of channels of the microphone array can be set to 208. The high number of channels (208) of the array can provide a hardware foundation for high-precision beamforming and noise reduction in subsequent steps. The distance between the microphone array and the target device is balanced between "ensuring far-field sound field conditions" and "receiving sufficiently strong sound pressure signals". The imaging module can clearly cover the target device and the microphone array, thereby assisting in locating the sound source. Furthermore, a corresponding encoder is installed on the target device. The encoder is installed on the main rotating shaft or a shaft with a certain transmission ratio to the main shaft. This ensures that each pulse emitted by the encoder strictly corresponds to a fixed rotation angle of the main shaft.

[0055] Furthermore, while acquiring data from the target device, audio signals are simultaneously acquired through the multi-channel microphone array, along with pulse signals generated by the encoder, and the camera module begins recording. The target device can represent a complete operational process (e.g., from stop to normal operation and then back to stop), thereby obtaining relevant data about the target device during operation. This includes audio signals acquired by the microphones in the microphone array, with a length of N sampling points, as well as precise timestamps of the rising / falling edges of the encoder pulses. Additionally, a video clip covering the target device and the microphone array is included, with the first frame of the video clip aligned in time with the first sampling point of the audio data, thus achieving time base alignment and ensuring that the audio signals from the microphone channels, the encoder pulse timestamps, and the video time are aligned.

[0056] Step S104: Based on the initial orientation of the target device located by the video signal, and combined with the geometric coordinates of the microphone array, calculate the time delay of the sound signal reaching the microphone array, design a corresponding filter for each microphone in the microphone array, and calculate the filter coefficients based on the time delay.

[0057] Specifically, based on the video data in the video signal, the initial orientation of the target device is determined. This can be achieved by processing the video data using image processing algorithms such as video motion magnification algorithms. The azimuth of arrival of the sound signal relative to the microphone array is then determined. The geometric coordinates of the microphone array are set, and the initial azimuth and estimated distance of the target device (or a target point on the target device that generates noise due to vibration / rotation) relative to the microphone array are determined. Based on the initial azimuth and the precise geometric coordinates of the microphone array, the precise theoretical time delay of the sound wave from the target device to each microphone in the microphone array is calculated. The delay calculation process may include:

[0058] Determine the coordinates of the sound source (target device, or a point on the target device that generates noise due to vibration / rotation) and the coordinates of each microphone in the microphone array. Calculate the distance of the sound signal from each microphone. Define a reference point, which can be the geometric center of the microphone array, and calculate the standard distance of the sound signal to the reference point. Then, calculate the time difference between the sound signal reaching the geometric center (standard distance) and each microphone in the current environment; this is the time delay of the sound signal reaching the microphone array.

[0059] Furthermore, a corresponding FIR filter needs to be designed to introduce a corresponding delay in the audio signal. Since the delay is usually not an integer multiple of the encoder sampling interval, direct shifting will introduce errors. Therefore, a filter delay needs to be applied to each microphone. The delay strategy can be implemented using sinc function interpolation to design the FIR filter. The impulse response of an ideal fractional delay filter is a shifted sinc function: h i [n]=sin c (π(n-Δ)), where Δ=τ i *Fs (Fs is the sampling rate, τ) i (This refers to the time delay), i.e., the number of sampling points that need to be delayed. Since the sinc function is infinitely long, it needs to be windowed (such as by a Kaiser window) to truncate it to a finite length, thus obtaining the final FIR filter coefficients h. i [n], n=0,1,...,L-1 (L is the filter order)

[0060] This allows for the design of a corresponding FIR filter for each microphone channel in the microphone array. The FIR filter can calculate the corresponding precise time delay and determine 208 sets of FIR filter coefficients.

[0061] Step S106: Based on the sound signal and filter coefficients, perform convolution operation on each microphone in the microphone array, and perform signal superposition and noise reduction to output a clean audio signal.

[0062] Specifically, the calculated filter coefficients are used to process the original audio signal and extract the target sound source. The audio signal from each microphone in the microphone array is input into the corresponding FIR filter. That is, the audio signal from the microphone array is convolved with the corresponding filter coefficients. Through the convolution operation, an audio signal with a precise delay of τi is output, achieving waveform alignment of the audio signals in each channel. In other words, the same sound event (such as an impact) peaks at the same time point in all channels, achieving phase calibration of the signal.

[0063] Then, the aligned audio signals are summed and averaged, combining the audio signals from each aligned channel into one. This utilizes acoustic wave interference to enhance the target signal and suppress noise. This involves summing the audio signals from each channel and then averaging them to achieve spatial filtering and improve the signal-to-noise ratio. For the target device's sound source, the signals are aligned (coherent) in each channel. Theoretically, the amplitude enhancement after superposition can reach 208 times (number of microphone channels), and the power enhancement can reach 208^2 times. This results in a one-dimensional clean audio signal that includes significantly enhanced target sound and significantly suppressed ambient noise. The maximum noise reduction can reach 20 * log10 (√number of microphones). For example, using a 208-channel microphone array, the maximum noise reduction can reach 23.1 dB.

[0064] Step S108: Based on the pulse signal, calculate the rotational speed curve of the target device, and resample the pure audio signal based on the rotational speed curve to generate a corresponding order spectrum, and generate a diagnostic report for the target device based on the order spectrum.

[0065] Specifically, the rotational speed curve of the target device is calculated based on pulse signals. For each pulse, the instantaneous rotational speed is determined by the time interval between it and the previous pulse; the calculation formula can be, for example, RPM. k =60 / ((t k -t k-1 )*PPR), where PPR is the number of pulses per encoder revolution, t k -t k-1 RPM is the time difference between two adjacent pulses. k This is the instantaneous rotational speed. Because t k By constructing a continuous speed curve for discrete points, the calculated RPM can be obtained through interpolation. k The value is assigned to time point t k Then, interpolation is performed between these points to obtain a continuous rotational speed curve corresponding to the audio signal time axis t.

[0066] Furthermore, integrating the rotational speed curve yields the function of cumulative rotation angle over time: θ(t) = ∫(RPM(t) * 2π / 60) dt. Here, 2π / 60 is the coefficient for converting the unit from revolutions per minute to radians per second. For the target device, an angle sampling rate is set, for example, 1024 points / revolution. This means that 1024 data points are obtained for each revolution of the target device (spindle). Based on the angle sampling rate, corresponding equally spaced angle cycles are created. Then, the time point corresponding to each angle point on the angle axis is determined, and the amplitude value corresponding to that time point is found in the pure audio signal. By inverting the cumulative rotation angle function θ(t), the angle-time mapping relationship t = θ is obtained. -1(θ_new). For each point on the equally spaced angle axis, calculate its corresponding time point. Since each time point is in most cases not an integer sampling point on the original audio signal's time axis, an interpolation algorithm (such as cubic spline interpolation) is needed to calculate the amplitude value corresponding to these time points in the clean audio signal. This yields the resampled angle domain signal, thus converting the non-stationary time domain signal into a stationary angle domain signal.

[0067] In the angular domain, any vibration / noise component related to rotational speed (such as the 1st, 2nd, and gear meshing orders) exhibits a constant order. For example, the meshing vibration of a gear is a pure sine wave of 1024 points / revolution in the angular domain (if the gear has 32 teeth, the order is 32).

[0068] Furthermore, an FFT is performed on the stationary angle-domain signal. Since the signal is typically sampled at equal intervals in the angle domain, the horizontal axis after the FFT directly represents the order, which physically represents the frequency component's multiple relative to the rotational frequency, thus determining the order spectrum. Further, based on the order spectrum, diagnostic spectra can be further determined, including 3D spectrograms (such as...). Figure 2 As shown in Figure 3, which is a 3D spectrum diagram of the order of an electric fan: The data of the entire speed change process is divided into many small segments. Each segment of data is resampled and subjected to FFT to calculate its order spectrum. All these order spectra are arranged according to the speed to form a three-dimensional matrix. This can identify resonance and speed-related faults. Order cross-sectional diagram (Figure 3 shows a cross-sectional diagram of the order of an electric fan): A two-dimensional slice is "cut" from the 3D spectrum diagram. It is an order-amplitude diagram at a constant speed, or a diagram showing the change of a certain constant order with the speed. It can accurately read the precise amplitude values ​​of each order (such as the 1st order, 2nd order, gear meshing order, bearing fault order) under specific operating conditions (speed).

[0069] Based on the corresponding spectrum, a corresponding diagnostic report for the target equipment is generated. Typical diagnostic rules may include, but are not limited to: Imbalance: manifested as a large first-order vibration that does not change with load. Misalignment: manifested as prominent second-order vibration, often accompanied by first-order vibration. Tooth wear: increased amplitude of gear meshing order (tooth number). Gear tooth breakage: increased amplitude of meshing order accompanied by sidebands of the rotational speed frequency. Bearing failure: the appearance of specific non-integer orders, usually less than first order, etc. Order analysis decomposes the sound signal into frequency components (orders) that are strictly related to the rotational speed. For example, first order might come from rotor imbalance, 3.5 order might come from a bearing failure, and 97th order might come from a gear with 97 teeth. This allows for the differentiation of sounds emitted by different fault mechanisms originating from the same component.

[0070] This invention provides a microphone array-based order analysis method. The method involves setting up a microphone array and a camera module covering it. The microphone array acquires audio signals from a target device, while the camera module acquires video signals and simultaneously acquires pulse signals from the target device. The initial orientation of the target device is located based on the video signal. Combining this with the geometric coordinates of the microphone array, the time delay of the audio signal reaching the microphone array is calculated. A corresponding filter is designed for each microphone in the microphone array, and the filter coefficients are calculated based on the time delay. Based on the audio signal and the filter coefficients, convolution operations are performed on each microphone in the microphone array, followed by signal superposition and noise reduction to output a clean audio signal. Based on the pulse signal, the rotational speed curve of the target device is calculated, and the clean audio signal is resampled based on the rotational speed curve to generate a corresponding order spectrum. A diagnostic report for the target device is then generated based on the order spectrum. This method, by setting different filter coefficients for each microphone channel of the microphone array and performing order analysis after resampling, can distinguish different components of the audio signal and can process audio signals of different orders accordingly, thus improving data processing efficiency.

[0071] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a microphone array-based order analysis system provided in an embodiment of this application. Figure 4 As shown, the system includes:

[0072] The acquisition module S402 is used to set up a microphone array and a shooting module covering the microphone array. The microphone array acquires the sound signal of the target device, and when the shooting module acquires the video signal, it simultaneously acquires the pulse signal of the target device.

[0073] The filtering module S404 is used to locate the initial orientation of the target device based on the video signal, calculate the time delay of the sound signal reaching the microphone array in combination with the geometric coordinates of the microphone array, design a corresponding filter for each microphone in the microphone array, and calculate the filter coefficients in combination with the time delay.

[0074] The noise reduction module S406 is used to perform convolution operation on each microphone in the microphone array based on the sound signal and filter coefficients, and to perform signal superposition and noise reduction to output a clean audio signal.

[0075] The diagnostic module S408 is used to calculate the rotational speed curve of the target device based on the pulse signal, resample the pure audio signal based on the rotational speed curve to generate a corresponding order spectrum, and generate a diagnostic report of the target device based on the order spectrum.

[0076] In another embodiment, a microphone array-based order analysis system further includes:

[0077] The orientation module is used to calculate the initial azimuth angle of the target device relative to the microphone array based on the video signal using a preset image algorithm, and then calculate the estimated distance between the target device and each microphone by combining the coordinates of the microphones.

[0078] The central module is used to calculate the standard distance to the target device based on the geometric center of the microphone array;

[0079] The delay module is used to calculate the time difference between the estimated distance and the standard distance for the sound signal to travel, and to determine the time delay for the sound signal to reach the microphone array.

[0080] In another embodiment, a microphone array-based order analysis system further includes:

[0081] The speed module is used to calculate the instantaneous speed based on the pulse time difference of the pulse signal and the number of pulses per revolution, and to construct the speed curve of the target device by combining interpolation.

[0082] The sampling rate module is used to integrate the rotational speed curve, calculate the cumulative angle-time function, set the angle sampling rate, and create equally spaced angle axes.

[0083] The inverse calculation module is used to inversely calculate the non-equally spaced time points on the pure audio signal for each point on the equally spaced angle axis based on the cumulative angle-time function;

[0084] The interpolation module is used to calculate the corresponding amplitude sequence interpolation for the non-equal interval time points using an interpolation algorithm.

[0085] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit (IC), etc.

[0086] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.

[0087] See Figure 5 It shows a schematic diagram of the structure of an electronic device according to an embodiment of this application, which can be used to implement... Figure 1 The method in the illustrated embodiment. (As shown) Figure 5As shown, the electronic device 500 may include: at least one processor 501, at least one network interface 504, user interface 503, memory 505, and at least one communication bus 502.

[0088] The communication bus 502 is used to enable communication between these components.

[0089] The user interface 503 may include a display screen and a camera. Optionally, the user interface 503 may also include a standard wired interface and a wireless interface.

[0090] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0091] The processor 501 may include one or more processing cores. The processor 501 connects to various parts within the electronic device 500 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and by calling data stored in the memory 505. Optionally, the processor 501 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 501 may integrate one or a combination of several of the following: a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), and a modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 501 and may be implemented as a separate chip.

[0092] The memory 505 may include random access memory (RAM) or read-only memory. Optionally, the memory 505 may include a non-transitory computer-readable storage medium. The memory 505 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 505 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 505 may also be at least one storage device located remotely from the aforementioned processor 501. Figure 5 As shown, the memory 505, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0093] exist Figure 5 In the illustrated electronic device 500, the user interface 503 is mainly used to provide an input interface for the user and acquire user input data; while the processor 501 can be used to call the image-based interactive application stored in the memory 505 and specifically perform the following operations: setting up a microphone array and a shooting module covering the microphone array; the microphone array acquires the sound signal of the target device; when the shooting module acquires the video signal, it simultaneously acquires the pulse signal of the target device; based on the video signal, the initial orientation of the target device is located; combined with the geometric coordinates of the microphone array, the time delay of the sound signal reaching the microphone array is calculated; and a corresponding filter is designed for each microphone in the microphone array, and the filter coefficients are calculated; based on the sound signal and the filter coefficients, convolution operation is performed on each microphone in the microphone array, and signal superposition and noise reduction are performed to output a clean audio signal; based on the pulse signal, the rotation speed curve of the target device is calculated, and the clean audio signal is resampled based on the rotation speed curve to generate a corresponding order spectrum; and a diagnostic report of the target device is generated based on the order spectrum.

[0094] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0095] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0096] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0098] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0101] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0102] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

Claims

1. A method for order analysis based on a microphone array, characterized in that, include: A microphone array and a shooting module covering the microphone array are provided. The microphone array collects the sound signal of the target device, and the shooting module collects the pulse signal of the target device simultaneously when collecting the video signal. Based on the initial orientation of the target device located by the video signal, and combined with the geometric coordinates of the microphone array, the time delay of the sound signal reaching the microphone array is calculated, and a corresponding filter is designed for each microphone in the microphone array. The filter coefficients are then calculated based on the time delay. Based on the sound signal and filter coefficients, convolution operation is performed on each microphone in the microphone array, and signal superposition and noise reduction are performed to output a clean audio signal; Based on the pulse signal, the rotational speed curve of the target device is calculated, and the pure audio signal is resampled based on the rotational speed curve to generate a corresponding order spectrum. A diagnostic report for the target device is then generated based on the order spectrum.

2. The order analysis method based on a microphone array according to claim 1, characterized in that, The initial orientation of the target device based on the video signal, combined with the geometric coordinates of the microphone array, is used to calculate the time delay of the sound signal reaching the microphone array, including: Based on the video signal, the initial azimuth angle of the target device relative to the microphone array is calculated using a preset image algorithm, and then the estimated distance between the target device and each microphone is calculated by combining the coordinates of the microphones. Calculate the standard distance to the target device based on the geometric center of the microphone array; Calculate the time difference between the estimated distance and the standard distance for the sound signal to travel, and determine the time delay for the sound signal to reach the microphone array.

3. The order analysis method based on a microphone array according to claim 2, characterized in that, The calculation of filter coefficients includes: The filter coefficients are calculated using the sinc function interpolation method, and the calculation formula is as follows: h i [n]=sin c (π(n-Δ)) where Δ = τ i *Fs, h i [n] is the filter coefficient, Fs is the sampling rate, τ i is the time delay, and n is the filter order.

4. The order analysis method based on a microphone array according to claim 1, characterized in that, The step of calculating the rotational speed curve of the target device based on the pulse signal and resampling the pure audio signal includes: Based on the pulse time difference and the number of pulses per revolution of the pulse signal, the instantaneous rotational speed is calculated, and the rotational speed curve of the target equipment is constructed by combining the interpolation method. Integrate the rotational speed curve to calculate the cumulative angle-time function, set the angle sampling rate, and create equally spaced angle axes; Based on the cumulative angle-time function, for each point on the equally spaced angle axis, the corresponding non-equally spaced time points on the pure audio signal are calculated in reverse. For the time points with non-equal intervals, an interpolation algorithm is used to calculate the corresponding amplitude sequence interpolation.

5. The order analysis method based on a microphone array according to claim 1, characterized in that, The microphone array contains 208 microphone channels.

6. A microphone array-based order analysis system, characterized in that, The system includes: The acquisition module is used to set up a microphone array and a shooting module covering the microphone array. The microphone array acquires the sound signal of the target device, and when the shooting module acquires the video signal, it simultaneously acquires the pulse signal of the target device. The filtering module is used to locate the initial orientation of the target device based on the video signal, calculate the time delay of the sound signal reaching the microphone array in combination with the geometric coordinates of the microphone array, design a corresponding filter for each microphone in the microphone array, and calculate the filter coefficients. The noise reduction module is used to perform convolution operations on each microphone in the microphone array based on the sound signal and filter coefficients, and to perform signal superposition and noise reduction to output a clean audio signal. The diagnostic module is used to calculate the rotational speed curve of the target device based on the pulse signal, resample the pure audio signal based on the rotational speed curve to generate a corresponding order spectrum, and generate a diagnostic report of the target device based on the order spectrum.

7. The order analysis system based on a microphone array according to claim 6, characterized in that, The system also includes: The orientation module is used to calculate the initial azimuth angle of the target device relative to the microphone array based on the video signal using a preset image algorithm, and then calculate the estimated distance between the target device and each microphone by combining the coordinates of the microphones. The central module is used to calculate the standard distance to the target device based on the geometric center of the microphone array; The delay module is used to calculate the time difference between the estimated distance and the standard distance for the sound signal to travel, and to determine the time delay for the sound signal to reach the microphone array.

8. The order analysis system based on a microphone array according to claim 6, characterized in that, The system also includes: The speed module is used to calculate the instantaneous speed based on the pulse time difference of the pulse signal and the number of pulses per revolution, and to construct the speed curve of the target device by combining interpolation. The sampling rate module is used to integrate the rotational speed curve, calculate the cumulative angle-time function, set the angle sampling rate, and create equally spaced angle axes. The inverse calculation module is used to inversely calculate the non-equally spaced time points on the pure audio signal for each point on the equally spaced angle axis based on the cumulative angle-time function; The interpolation module is used to calculate the corresponding amplitude sequence interpolation for the non-equal interval time points using an interpolation algorithm.

9. An electronic device, comprising a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, in order to perform the method as described in any one of claims 1-5.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of claims 1-5.

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