Method and device for detecting active noise reduction performance, storage medium and program product

Abstract

This specification provides one or more embodiments of a method, apparatus, storage medium, and program product for detecting the performance of active noise cancellation. The method includes: controlling an active noise cancellation device to play an excitation signal; acquiring a response signal collected by an error microphone corresponding to the active noise cancellation device; and detecting the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal, thereby effectively detecting the actual performance of the speaker in the active noise cancellation system and fundamentally optimizing the detection principle.

Description

Technical Field

[0001] This specification relates to one or more embodiments in the field of noise reduction technology, and more particularly to a method, apparatus, storage medium and program product for detecting active noise reduction performance. Background Technology

[0002] To enhance driving comfort, active noise cancellation technology is widely adopted in vehicles. This technology generates secondary sound sources within the passenger compartment that are out of phase with the original noise, achieving sound wave interference cancellation. It primarily targets engine noise and road noise. The performance of such active noise cancellation systems is highly dependent on the acoustic characteristics of the onboard speakers, especially the stability and accuracy of the acoustic transfer function formed by the speakers, controller, and error microphone. To ensure effective noise reduction, rapid and accurate performance testing of the active noise cancellation speakers before the vehicle rolls off the assembly line has become a critical industry requirement.

[0003] In related technologies, the offline testing methods for vehicle active noise cancellation speakers largely follow the testing approaches of traditional audio systems. For example, they monitor the speaker's operating voltage and switch to backup power in case of abnormalities to achieve basic functional verification and protection. However, active noise cancellation systems have unique performance requirements for speakers. Their noise reduction effect depends not only on whether the speaker can produce sound, but also on the degree of matching between the speaker and the entire system in its actual installation state within the vehicle. The above methods only remain at the qualitative level of "whether there is output," making it difficult to effectively evaluate the actual performance of the speaker in the active noise cancellation system. This falls significantly short of the refined testing requirements of active noise cancellation systems. Traditional testing methods only remain at the qualitative level of "whether there is output," failing to effectively evaluate the actual performance of the speaker in the active noise cancellation system. Summary of the Invention

[0004] In view of the above, one or more embodiments of this specification provide the following technical solutions: According to a first aspect of one or more embodiments of this specification, a method for detecting active noise reduction performance is provided, the method comprising: Controls the excitation signal played by the active noise cancellation device; Acquire the response signal collected by the error microphone corresponding to the active noise cancellation device; The performance of the active noise cancellation device is detected based on the relative relationship of signal characteristics between the excitation signal and the response signal.

[0005] According to a second aspect of one or more embodiments of this specification, an active noise reduction performance detection device is provided, the device comprising: The signal control unit is used to control the excitation signal played by the active noise cancellation device; The signal acquisition unit is used to acquire the response signal collected by the error microphone corresponding to the active noise cancellation device; The performance detection unit is used to detect the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal.

[0006] According to a third aspect of this specification, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0007] According to a fourth aspect of this specification, a computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the method described in the first aspect.

[0008] As can be seen from the above embodiments, this specification achieves performance testing by controlling the excitation signal played by the active noise cancellation device and simultaneously acquiring the response signal collected by the system error microphone, and then analyzing the relative relationship of the signal characteristics between the two. This core step establishes a complete signal comparison link from excitation to response, thereby elevating the detection essence from an isolated "export presence or absence" judgment to a quantitative evaluation of the correlation characteristics of the device's input and output. This enables effective detection of the actual performance of the speaker in the active noise cancellation system, achieving a fundamental optimization of the detection principle. Attached Figure Description

[0009] Figure 1 This is a system architecture diagram of an active noise reduction performance detection system shown in the embodiments disclosed in this specification; Figure 2 This is a schematic flowchart illustrating an active noise cancellation performance testing method according to the embodiments disclosed in this specification; Figure 3 This is a schematic flowchart illustrating another method for detecting active noise cancellation performance as shown in the embodiments disclosed in this specification; Figure 4 This is a schematic structural diagram of an electronic device shown in the embodiments of this specification; Figure 5 This is a block diagram of an active noise cancellation performance testing device shown in the embodiments of this specification. Detailed Implementation

[0010] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this manual are all information and data authorized by the user or fully authorized by all parties. The collection, use and processing of related data shall comply with the relevant laws, regulations and standards of the relevant regions, and corresponding operation portals shall be provided for users to choose to authorize or refuse.

[0011] Figure 1This is a schematic diagram of the architecture of an active noise reduction performance detection system provided in an exemplary embodiment. For example... Figure 1 As shown, the system may include at least a performance testing device 12, an active noise cancellation device 14, and an error microphone 16.

[0012] The performance testing device 12 is the core device for executing the testing methods described in this specification. It may include testing control and processing software and a high-precision audio interface. This device establishes a communication connection with the onboard active noise cancellation system via the vehicle bus, and is responsible for generating and outputting high-precision excitation signals. It also receives, processes, and analyzes the response signals acquired by the error microphone. The testing control and processing software serves as the algorithm carrier, coordinating the entire testing process and performing tasks such as signal generation, synchronous acquisition, data analysis, and final performance determination, thus constituting the control and processing center of the testing system.

[0013] The active noise cancellation device 14, as the object under test, includes an on-board active noise cancellation control unit and a speaker unit under test connected to it. During the testing process, this device can receive commands and excitation electrical signals from the performance testing device 12, and its control unit accurately transmits the signals to the designated speaker unit under test. The speaker unit under test, as an acoustic actuator, is responsible for converting the received electrical signals into corresponding acoustic signals and playing them, thereby generating the acoustic excitation required for testing within the vehicle cabin. Its performance is the direct objective of this method's evaluation.

[0014] Error microphone 16 is an acoustic sensor pre-installed in the vehicle's active noise cancellation system, and it is reused as a key signal acquisition device in this testing method. It is typically located inside the vehicle compartment and is used to receive acoustic signals emitted by the speaker unit under test during the testing process, converting them into a response signal in the form of an electrical signal. This response signal is transmitted back to the performance testing equipment 12 for analysis via the active noise cancellation control unit. By utilizing the existing error microphone in the system, high-fidelity acquisition of the acoustic response can be achieved without adding additional sensors, ensuring the convenience of testing and the authenticity of the signal path.

[0015] Figure 2 This is a schematic flowchart illustrating an exemplary embodiment of an active noise cancellation performance testing method. Figure 2 As shown, the method may include the following steps: Step S202: Control the excitation signal played by the active noise cancellation device.

[0016] The aforementioned excitation signal is generated by the detection control and processing software in the performance testing equipment, output via a high-precision audio interface, and sent to the on-board active noise cancellation control unit via the vehicle bus. Subsequently, the active noise cancellation control unit uses the received excitation electrical signal to drive the designated speaker unit under test, causing it to play the corresponding acoustic test signal inside the vehicle cabin.

[0017] It is worth mentioning that the aforementioned excitation signal can be a composite excitation signal with specific energy distribution characteristics in the frequency domain. Its energy is intentionally concentrated in the target frequency band where the active noise reduction device needs to operate, such as the frequency band of interest for engine order noise control and active road noise control. This design ensures that the detected energy can be efficiently concentrated in the critical frequency band of system performance, not only avoiding ineffective excitation of irrelevant frequency bands of the speaker and improving detection efficiency. Simultaneously, it also helps to accurately extract the system impulse response from the speaker to the error microphone through subsequent processing such as cross-correlation analysis in a noisy offline testing workshop; or, it can ensure that the signal has high power efficiency, enabling the system to drive the speaker to emit sufficiently loud sound in a short time, thereby effectively improving the signal-to-noise ratio of the detected signal and laying the foundation for subsequent high-precision performance analysis.

[0018] To achieve the above characteristics, the composite excitation signal can be in various preferred signal forms suitable for system identification, such as a pseudo-random sequence optimized by linear frequency modulated Z-transform, a maximum length sequence, or a multi-sine signal with a specific amplitude and phase relationship. This specification does not impose any restrictions on this.

[0019] Step S204: Obtain the response signal collected by the error microphone corresponding to the active noise cancellation device.

[0020] The system utilizes an error microphone pre-installed in the vehicle for active noise cancellation to synchronously acquire the actual acoustic signals generated by the speaker unit under test. This acoustic signal is converted into an electrical response signal by the error microphone and then transmitted back to the detection, control, and processing software via the active noise cancellation control unit for subsequent analysis.

[0021] Step S206: Detect the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal.

[0022] Finally, the aforementioned detection, control, and processing software can compare and analyze the known excitation signal and the acquired response signal. By calculating and evaluating the correlation and differences in signal characteristics between the two in the frequency domain, time-frequency domain, and other dimensions, it can comprehensively determine whether the performance status of the active noise cancellation device meets the preset standards.

[0023] The analysis and performance testing of the aforementioned signal characteristic relationships are mainly achieved through the following two parallel and complementary technical paths, which can be executed individually or in combination: The first technical approach is transfer function accuracy analysis, which involves performing frequency domain analysis on the excitation and response signals, calculating the measured transfer function based on their frequency domain relationship, and then comparing it with a pre-stored standard transfer function to quantitatively evaluate the accuracy of the system's acoustic path model.

[0024] The second technical approach is output sound quality diagnosis, which involves performing time-frequency analysis on the response signal to identify and locate abnormal frequency components that do not belong to the original excitation signal, such as harmonic distortion and stray noise, and then assessing the sound purity of the speaker unit itself.

[0025] The above two analyses, from the two core dimensions of system model matching degree and unit sound quality, together complete a refined and comprehensive test of the performance of active noise cancellation equipment.

[0026] The following section will provide a detailed introduction to the first technical approach mentioned above, namely, transfer function accuracy analysis.

[0027] First, before performing the accuracy analysis of the transfer function, a frequency domain analysis of the time-domain excitation signal x(t) and response signal y(t) at time t is required. Specifically, the system can perform Fast Fourier Transform on the previously generated excitation signal x(t) and the response signal y(t) acquired by the error microphone, respectively, to obtain their corresponding frequency domain representations, namely the spectra X(f) and Y(f), where f represents the frequency, and X(f) and Y(f) represent the complex amplitude values ​​of the excitation and response signals at different frequencies, respectively. Based on this, by calculating the ratio of Y(f) to X(f), the measured acoustic transfer function H_meas(f) = Y(f) / X(f) from the excitation point to the acquisition point can be obtained. This function fully contains the amplitude and phase response information of the tested system in the frequency dimension, providing a direct frequency domain data basis for subsequent quantitative comparison with the standard transfer function.

[0028] Subsequently, the system calculates the frequency domain difference between the measured transfer function and the preset standard transfer function to obtain a comprehensive error integral value. Mathematically, this value characterizes the overall deviation of the two function curves across the entire or specific frequency band. A larger value indicates a greater deviation between the measured response and the ideal model, meaning lower accuracy of the transfer function; in other words, the two are negatively correlated. The method further compares the calculated error integral value with a preset detection threshold to form a clear pass / fail determination. This detection threshold can be a pre-calibrated boundary based on system tolerance requirements. Specifically, if the error integral value is lower than this threshold, the transfer function is considered accurate; otherwise, it is considered unacceptable. This comparison mechanism based on quantitative integral error and a preset threshold achieves objective and accurate pass / fail detection of the system's acoustic transfer function performance, overcoming the limitations of traditional methods that can only make qualitative judgments.

[0029] Furthermore, in the process of comparing the aforementioned error integral value with the preset detection threshold, in addition to using a single global error threshold, a frequency band error calculation and judgment strategy can be introduced to improve the pertinence and engineering practicality of the evaluation. Specifically, this method can predefine multiple target frequency bands closely related to the active noise reduction function, such as a first target frequency band related to engine order noise and / or a second target frequency band related to road noise, referred to in the following embodiments as the engine order control core frequency band F1 and the road noise active control core frequency band F2, and configure independent detection thresholds for each target frequency band.

[0030] In one embodiment, the system can calculate the error integral value Ei of the measured transfer function H_meas(f) and the standard transfer function H_std(f) measured under ideal conditions in the i-th target frequency band, i.e., Fi. This error integral value can be expressed by the following formula: The calculated integral interval is the target frequency band Fi. This formula quantifies the degree of local deviation of the system from the ideal model within this specific operating frequency band. In summary, the final qualification judgment can follow the multi-frequency band joint judgment principle, that is, the system compares the error integral value Ei calculated for each frequency band with the detection threshold specifically configured for that frequency band one by one. Only when the error integral value Ei of all target frequency bands is lower than their respective corresponding thresholds can the overall accuracy of the transfer function of the active noise cancellation device be judged to be qualified. Obviously, this frequency band refined evaluation mechanism ensures targeted verification of the control capabilities of the vehicle active noise cancellation system for different noise types, such as order noise and broadband road noise, making the test conclusions more meaningful for engineering guidance.

[0031] Next, we will introduce the second technical approach mentioned above, namely, output sound quality diagnosis.

[0032] The core of the aforementioned output sound quality diagnosis lies in the in-depth time-frequency analysis of the acquired response signal to detect and quantify unwanted acoustic defects generated by the speaker unit itself. Specifically, the system can perform time-frequency analysis such as short-time Fourier transform on the response signal to generate a time-spectrum diagram that simultaneously displays the signal frequency components and their changes over time. In this spectrum diagram, the system locates and extracts all abnormal frequency components that do not belong to the original excitation signal by comparing them with known excitation signal frequency components. These components can typically manifest as higher harmonics at integer multiples of the excitation signal, also known as harmonic distortion, or discrete spectral peaks or broadband noise appearing at non-harmonic frequency points, also known as stray noise or abnormal sounds.

[0033] At this point, the system can quantitatively assess sound quality issues. The system calculates the total energy E_abnormal of the extracted abnormal frequency components and compares it with the energy of the remaining signal energy in the response signal (excluding the abnormal frequency components), i.e., the energy E_main of the normal portion. The ratio of these two values ​​is calculated as the noise ratio, i.e., noise ratio = E_abnormal / E_main. This noise ratio directly characterizes the relative strength of the abnormal acoustic components; the higher the value, the more severe the speaker distortion or abnormal noise problem, and the worse the output sound quality.

[0034] Finally, the system compares the calculated noise ratio with a preset sound quality pass threshold. If the noise ratio is below the threshold, the speaker output sound quality is considered pure and acceptable; otherwise, a sound quality defect is identified. This diagnostic method based on time-frequency analysis and noise ratio quantification, as described in this manual, enables objective and effective offline testing of the speaker unit's own sound quality.

[0035] The following is based on Figure 3 For example, the specific process for determining the level of motion sickness is introduced, such as... Figure 3 As shown, the method may include the following steps: Step S302: Initialize the detection system and load parameters.

[0036] In one embodiment, after the vehicle enters the testing station, the detection control and processing software can establish communication with the on-board active noise cancellation control unit, complete system initialization, and load preset detection parameters for the current vehicle model, including the standard transfer function model H_std(f), each target frequency band including EOC band F1 and RNC band F2, as well as the corresponding threshold, noise ratio threshold, and identification information of the speaker under test.

[0037] Step S304: Generate and play a composite excitation signal to the speaker under test.

[0038] In one embodiment, the detection control and processing software can generate a designed composite excitation signal x(t), which is a pseudo-random sequence optimized by linear frequency modulation Z-transform, and has the characteristics of strong frequency band specificity, rapid autocorrelation decay and low peak-to-average power ratio. Subsequently, the software sends the digital signal to the active noise cancellation control unit through a high-precision audio interface and the vehicle bus, and the unit drives the designated speaker under test to play the corresponding acoustic test signal in the cabin.

[0039] Step S306: Synchronously trigger the error microphone to acquire the response signal.

[0040] In one embodiment, at the same moment the excitation signal begins to play, the detection control and processing software synchronously triggers the error microphone associated with the target speaker, collects the acoustic signal in the carriage and converts it into a response signal y(t) in the form of an electrical signal, which is then transmitted back to the detection system through the active noise cancellation control unit.

[0041] Step S308: Perform frequency domain transformation on the excitation and response signals.

[0042] In one embodiment, the detection control and processing software performs fast Fourier transform on the known excitation signal x(t) and the acquired response signal y(t) respectively to obtain their frequency domain representations X(f) and Y(f).

[0043] Step S310: Calculate the measured transfer function and calculate the error integral value by frequency band.

[0044] In one embodiment, the detection control and processing software calculates the measured acoustic transfer function based on the frequency domain signals X(f) and Y(f) using the formula H_meas(f)=Y(f) / X(f); then, it compares the measured acoustic transfer function with the pre-stored standard transfer function H_std(f), and calculates the error integral value Ei for each predefined target frequency band Fi (e.g., EOC core frequency band F1 and RNC core frequency band F2) according to the above formula.

[0045] Step S312: Determine the accuracy of the frequency band transfer function.

[0046] In one embodiment, the detection control and processing software compares the error integral value Ei calculated for each target frequency band with the tolerance threshold configured independently for that frequency band. Only when the error integral values ​​of all target frequency bands are lower than their corresponding thresholds is the transfer function accuracy deemed qualified.

[0047] Step S314: Perform time-frequency analysis on the response signal.

[0048] In one embodiment, the detection control and processing software performs a short-time Fourier transform on the response signal y(t) to generate a time-spectrum graph that can simultaneously display frequency components and time variations.

[0049] Step S316: Detect abnormal frequency components.

[0050] In one embodiment, the detection control and processing software locates and extracts frequency components that do not belong to the original excitation signal in the time spectrum diagram, including higher harmonics at integer multiples of the excitation signal and spurious spectral peaks or burst noise appearing at non-harmonic frequencies.

[0051] Step S318: Calculate the noise ratio.

[0052] In one embodiment, the detection control and processing software calculates the total energy E_abnormal of the extracted abnormal frequency components and compares it with the energy E_main of the main excitation component in the response signal to obtain the noise ratio of the quantization sound quality problem = E_abnormal / E_main.

[0053] Step S320: Sound quality compliance assessment.

[0054] In one embodiment, the detection control and processing software compares the calculated noise ratio with a preset sound quality threshold. If the noise ratio is lower than the threshold, the speaker output sound quality is deemed acceptable; otherwise, a sound quality defect is deemed to exist.

[0055] Step S322: Comprehensive performance assessment and result reporting.

[0056] In one embodiment, the detection control and processing software integrates the accuracy of the transfer function and the output sound quality as two judgment results: only when both judgments are qualified, the tested speaker is marked as "qualified" as a whole; if either judgment is unqualified, it is marked as "unqualified", and the specific failure reason, such as "EOC band transfer function out of tolerance" or "mid-frequency harmonic distortion", is reported to the factory quality management system.

[0057] Figure 4 This is a schematic structural diagram of an electronic device according to an exemplary embodiment. Please refer to... Figure 4 At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile storage, and may also include other necessary hardware. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it, forming a detection device based on active noise reduction performance at the logical level. Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. That is to say, the execution subject of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0058] Figure 5 This specification illustrates a block diagram of an active noise cancellation performance testing device. Please refer to... Figure 5 The device includes: The signal control unit 502 is used to control the excitation signal played by the active noise cancellation device; The signal acquisition unit 504 is used to acquire the response signal collected by the error microphone corresponding to the active noise cancellation device; The performance detection unit 506 is used to detect the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal.

[0059] Optionally, the performance detection unit 506 is specifically used for: Frequency domain analysis is performed on the excitation signal and the response signal. Based on their frequency domain relationship, a measured transfer function is calculated, and the measured transfer function is compared with a standard transfer function to detect the accuracy of the transfer function of the active noise cancellation device; and / or, Time-frequency analysis is performed on the response signal to identify abnormal frequency components in the response signal that do not belong to the excitation signal, and the output sound quality of the active noise cancellation device is detected based on the abnormal frequency components.

[0060] Optionally, the performance detection unit 506 is specifically used for: Determine the integral value of the error between the measured transfer function and the standard transfer function, wherein the integral value of the error is negatively correlated with the accuracy of the transfer function; The error integral value is compared with a preset detection threshold to determine whether the accuracy of the transfer function is acceptable.

[0061] Optionally, the performance detection unit 506 is specifically used for: For each target frequency band among the preset multiple frequency bands, the error integral values ​​of the measured transfer function and the standard transfer function in the corresponding target frequency band are compared, and the calculated error integral value is compared with the detection threshold configured for the target frequency band.

[0062] Optionally, the plurality of frequency bands may include at least: a first target frequency band related to engine order noise, and / or a second target frequency band related to road noise.

[0063] Optionally, the performance detection unit 506 is specifically used for: The ratio of the total energy of the abnormal frequency components to the energy of the remaining signals in the response signal excluding the abnormal frequency components is used as the noise ratio. The noise ratio is compared with a preset audio quality threshold to detect whether the output audio quality is up to standard.

[0064] Optionally, the excitation signal is a composite excitation signal, and the energy of the composite excitation signal is concentrated within the operating frequency band of the active noise cancellation device.

[0065] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and 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 the solution in this specification according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0066] Based on the same concept as the methods described above, this specification also provides a computer-readable storage medium having computer instructions stored thereon that, when executed by a processor, implement the steps of the methods as described in any of the above embodiments.

[0067] Based on the same concept as the methods described above, this specification also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the methods as described in any of the above embodiments.

[0068] The embodiments of the subject matter and functional operation described in this specification can be implemented in the following ways: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or combinations thereof. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier for execution by a data processing apparatus or for controlling the operation of a data processing apparatus. Alternatively or additionally, the program instructions may be encoded on artificially generated propagation signals, such as machine-generated electrical, optical, or electromagnetic signals, which are generated to encode information and transmit it to a suitable receiving device for execution by the data processing apparatus. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or combinations thereof.

[0069] The processing and logic flow described in this specification can be executed by one or more programmable computers that execute one or more computer programs to perform corresponding functions by operating on input data and generating output. The processing and logic flow can also be executed by dedicated logic circuitry—such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the device can also be implemented as dedicated logic circuitry.

[0070] Computers suitable for executing computer programs include, for example, general-purpose and / or special-purpose microprocessors, or any other type of central processing unit. Typically, the central processing unit receives instructions and data from read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as disks, magneto-optical disks, or optical disks, or the computer will be operatively coupled to such mass storage devices to receive data from or transfer data to them, or both. However, a computer is not required to have such devices. Furthermore, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a GPS receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0071] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, such as semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. Processors and memory may be supplemented by or incorporated into dedicated logic circuitry.

[0072] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any invention or the scope of the claims, but rather are primarily intended to describe features of specific embodiments of a particular invention. Certain features described in the various embodiments herein may also be implemented in combination in a single embodiment. Conversely, various features described in a single embodiment may also be implemented separately in various embodiments or in any suitable sub-combination. Furthermore, while features may function in certain combinations as described above and even initially claimed in this way, one or more features from a claimed combination may be removed from that combination in some cases, and a claimed combination may refer to a sub-combination or a variation thereof.

[0073] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or requiring all illustrated operations to be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system modules and components in the above embodiments should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0074] Therefore, specific embodiments of the subject matter have been described. Furthermore, the processes depicted in the figures are not necessarily shown in a specific order or sequence to achieve the desired result. In some implementations, multitasking and parallel processing may be advantageous.

[0075] The above description is merely a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of protection of this specification.

Claims

1. A method for detecting active noise reduction performance, characterized in that, include: Controls the excitation signal played by the active noise cancellation device; Acquire the response signal collected by the error microphone corresponding to the active noise cancellation device; The performance of the active noise cancellation device is detected based on the relative relationship of signal characteristics between the excitation signal and the response signal.

2. The method according to claim 1, characterized in that, The step of detecting the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal includes: Frequency domain analysis is performed on the excitation signal and the response signal. Based on their frequency domain relationship, a measured transfer function is calculated, and the measured transfer function is compared with a standard transfer function to detect the accuracy of the transfer function of the active noise cancellation device; and / or, Time-frequency analysis is performed on the response signal to identify abnormal frequency components in the response signal that do not belong to the excitation signal, and the output sound quality of the active noise cancellation device is detected based on the abnormal frequency components.

3. The method according to claim 2, characterized in that, The step of comparing the measured transfer function with the standard transfer function to detect the accuracy of the transfer function of the active noise cancellation device includes: Determine the integral value of the error between the measured transfer function and the standard transfer function, wherein the integral value of the error is negatively correlated with the accuracy of the transfer function; The error integral value is compared with a preset detection threshold to determine whether the accuracy of the transfer function is acceptable.

4. The method according to claim 3, characterized in that, The step of comparing the error integral value with a preset detection threshold includes: For each target frequency band among the preset multiple frequency bands, the error integral values ​​of the measured transfer function and the standard transfer function in the corresponding target frequency band are compared, and the calculated error integral value is compared with the detection threshold configured for the target frequency band.

5. The method according to claim 4, characterized in that, The plurality of frequency bands includes at least: a first target frequency band related to engine order noise, and / or a second target frequency band related to road noise.

6. The method according to claim 2, characterized in that, The step of detecting the output sound quality of the active noise cancellation device based on the abnormal frequency components includes: The ratio of the total energy of the abnormal frequency components to the energy of the remaining signals in the response signal excluding the abnormal frequency components is used as the noise ratio. The noise ratio is compared with a preset audio quality threshold to detect whether the output audio quality is up to standard.

7. The method according to any one of claims 1 to 6, characterized in that, The excitation signal is a composite excitation signal, and the energy of the composite excitation signal is concentrated within the operating frequency band of the active noise reduction device.

8. A device for detecting active noise reduction performance, characterized in that, include: The signal control unit is used to control the excitation signal played by the active noise cancellation device; The signal acquisition unit is used to acquire the response signal collected by the error microphone corresponding to the active noise cancellation device; The performance detection unit is used to detect the performance of the active noise cancellation device based on the relative relationship of signal characteristics between the excitation signal and the response signal.

9. A computer-readable storage medium, characterized in that, It stores computer instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, Includes a computer program / instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 7.

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