Automated testing method and system for sound equipment

Abstract

The invention relates to the technical field of sound equipment testing, and discloses a sound equipment automatic testing method and system, and the method comprises the following steps: S1, building a time sequence control process: triggering a sound equipment power supply on-off instruction through a control module, synchronously completing equipment wake-up and wireless pairing processes, and forming a continuous automatic test starting sequence; s2, multi-channel audio acquisition and detection: capturing a sound output signal by using a multi-channel acquisition device, and performing feature extraction and standard comparison on the signal through a signal processing unit to complete sound quality parameter detection; and S3, multi-channel parallel testing: distributing independent communication channels for the plurality of tested sound boxes through the multi-channel radio frequency switching device. A time sequence control process is constructed through the control module to realize automatic starting of equipment awakening and wireless pairing, so that the problems of low test efficiency and poor process continuity caused by the fact that most of traditional sound equipment tests adopt manual operation are solved.

Description

Technical Field

[0001] This invention relates to the field of audio testing technology, specifically to an automated audio testing method and system. Background Technology

[0002] Audio equipment is an electronic device that converts electrical signals into sound waves. Sound is reproduced through the vibration of speakers, and it is widely used in home entertainment, stage performances, car audio systems, and other scenarios. Common types include home stereo systems, portable Bluetooth speakers, and professional stage speakers. Audio equipment manufacturing encompasses two main stages: the production of core components and overall assembly. Among the core components, the speaker is crucial, consisting of a diaphragm, voice coil, and magnetic circuit system. The diaphragm material is often pulp, plastic, or metal, affecting sound quality. The amplifier module amplifies the audio signal, while the audio processing chip optimizes the sound effects. The manufacturing process typically begins with the casing, using processes such as injection molding, stamping, or CNC machining to create a plastic or metal casing. Then, a leak-proof material such as EV foam is embedded, connecting the speaker, electronic components, and control panel. End caps are then installed and secured, followed by high-voltage testing and sound quality testing.

[0003] Traditional audio testing mostly relies on manual operation. Because each stage of the test depends on human intervention and lacks coordination, it results in low testing efficiency and poor process continuity. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an automated audio testing method and system, which solves the problem that traditional audio testing mostly relies on manual operation. Due to the dependence on manual intervention and lack of coordination in each testing stage, the testing efficiency is low and the process is not smooth.

[0005] In a first aspect, the present invention provides the following technical solution: an automated audio testing method, comprising the following steps: S1. Construct a timing control process: Trigger the power on / off command of the speaker through the control module to simultaneously complete the device wake-up and wireless pairing process, forming a continuous automated test start sequence; S2. Multi-channel audio acquisition and detection: A multi-channel acquisition device is used to capture the audio output signal. The signal processing unit performs feature extraction and standard comparison on the signal to complete the detection of sound quality parameters. S3, Multi-channel parallel testing: By using a multi-channel RF switching device to allocate independent communication channels to multiple speakers under test, parallel processing of audio testing of multiple devices can be completed simultaneously; S4. Full-process data processing: The test data is bound and stored with the identification information of the audio device under test to form a traceable test record, and production quality analysis is performed based on the test record.

[0006] Using the above technical solution, a timing control process is constructed through a control module to achieve automated startup of device wake-up and wireless pairing. A multi-channel acquisition device and signal processing unit are used to complete the detection of sound quality parameters. A multi-channel radio frequency switching device is used to achieve parallel testing of multiple devices. Combined with full-process data processing, a traceable record is formed, thereby realizing full-process automation of audio testing. This improves the problem that traditional audio testing mostly relies on manual operation. Because each testing link depends on human intervention and lacks coordination, it results in low testing efficiency and poor process continuity.

[0007] Preferably, in S1, the timing control process includes: the control module triggers the power supply of the speaker to be turned on and off according to a preset time sequence, and calls the wireless communication protocol stack command to complete the sending of the wake-up command and the response to the pairing request of the speaker under test.

[0008] Preferably, S1 further includes: obtaining the model information of the speaker under test through the identification unit, and matching the corresponding timing parameters based on the model information, wherein the timing parameters include the power on / off interval duration and the wireless pairing timeout threshold.

[0009] Preferably, step S1 further includes dynamic adjustment and anomaly handling steps: Based on the response delay data of the tested speaker, the adjusted control command trigger time is calculated using a dynamic timing adjustment formula. When the tested speaker is found to be unresponsive, a preset number of retry operations are automatically executed, the anomaly type is recorded, and an alarm signal is triggered. The response delay data is obtained by recording the time difference between the wireless pairing request and the device response. The interval between retry operations is a preset fixed value. The anomaly types include power failure and wireless module failure.

[0010] Preferably, in step S2, the multi-channel acquisition device includes multiple signal acquisition channels, a noise sensor, and a temperature and humidity sensor. Each signal acquisition channel is equipped with an analog-to-digital converter (ADC). The ADC is used to convert the analog audio signal output by the speaker into a digital signal. The noise sensor is used to output a noise signal, and the temperature and humidity sensor is used to output a temperature and humidity signal. The signal processing unit receives the digital signal, the noise signal, and the temperature and humidity signal. It first performs noise filtering and amplification preprocessing on the digital signal, and then performs parameter compensation on the preprocessed digital signal based on the temperature and humidity signal.

[0011] Preferably, in step S2, feature extraction includes the following steps: Spectral analysis of digital signals is performed using the Fast Fourier Transform algorithm. The spectral amplitude of the digital signal is calculated using the Fast Fourier Transform formula; Extract frequency response characteristics within a preset frequency range; The preset frequency range is 20Hz-20kHz, and the frequency response characteristics are divided into 63 segments, with each segment spaced 300Hz apart.

[0012] Preferably, in step S2, the standard comparison includes the following steps: The extracted sound quality parameters are compared with the pre-stored standard template to calculate the error. The average error value is obtained using the average error calculation formula. The sound quality detection and determination are completed by comparing the average error value with a preset error threshold. Based on the error calculation results, the sound quality defects are classified into types, and a visual report containing abnormal segment identifiers is generated. The sound quality parameters include intermodulation distortion, transient response time, and sound pressure level dynamic range.

[0013] Preferably, in step S3, the multi-channel RF switching device divides communication time slots using time division multiple access (TDMA) technology, allocating a dedicated time slot for each audio device under test. Simultaneously, a channel quality monitoring unit monitors the signal-to-noise ratio (SNR) of each channel in real time. When the SNR falls below a preset threshold, the device automatically switches the test task of the corresponding device to an idle channel and dynamically adjusts the communication frequency using a frequency hopping algorithm. The frequency hopping algorithm randomly selects the next communication frequency based on a preset frequency set, which includes multiple discrete frequency points within the range of 2.402-2.480 GHz. The multi-channel RF switching device supports 16-channel expansion and the number of channels can be configured via a DIP switch.

[0014] Preferably, in S3, the multi-channel RF switching device adopts a dual-channel hot-backup core switching chip. When the main chip fails, it automatically switches to the backup chip within a preset time and triggers an alarm. The device also integrates multiple wireless communication protocol processing units, including Bluetooth and Wi-Fi protocols, to adapt to the audio devices under test with different communication types and complete the testing of audio devices with wireless audio stream transmission capabilities.

[0015] Secondly, the present invention provides the following technical solution: an automated audio testing system, comprising: The timing control module is used to trigger the power on / off command of the audio system, synchronously complete the device wake-up and wireless pairing process, and form a continuous automated test start sequence. The audio acquisition and processing module is used to capture the audio output signal using a multi-channel acquisition device, and to perform feature extraction and standard comparison of the signal through the signal processing unit to complete the detection of sound quality parameters. The parallel testing module is used to allocate independent communication channels to multiple speakers under test through a multi-channel RF switching device, so as to complete the parallel processing of audio testing of multiple devices at the same time. The data processing module is used to bind and store test data with the identification information of the tested audio equipment to form a traceable test record, and to perform production quality analysis based on the test record.

[0016] This invention provides an automated testing method and system for audio equipment. It offers the following advantages: 1. This invention achieves automated device wake-up and wireless pairing by constructing a timing control process through a control module, uses a multi-channel acquisition device and signal processing unit to complete the detection of sound quality parameters, and uses a multi-channel radio frequency switching device to achieve parallel testing of multiple devices. Combined with full-process data processing, a traceable record is formed, thereby realizing full-process automation of audio testing. This improves the problem that traditional audio testing mostly relies on manual operation. Because each testing link depends on human intervention and lacks coordination, it results in low testing efficiency and poor process continuity.

[0017] 2. This invention captures audio output signals through a multi-channel acquisition device, and the signal processing unit performs feature extraction and standard comparison on the signals to complete the detection of sound quality parameters, thereby realizing the objective analysis and judgment of sound quality parameters. This improves the problem that traditional audio sound quality detection mostly relies on subjective human judgment, which leads to poor consistency and insufficient accuracy of detection results due to large differences in individual perception.

[0018] 3. This invention allocates independent communication channels to multiple audio devices under test through a multi-channel radio frequency switching device, enabling parallel processing of audio testing on multiple devices simultaneously, thereby increasing the testing capacity per unit time. This improves upon the problem that traditional audio testing mostly uses serial testing on a single device, which results in slow production pace and difficulty in increasing capacity because the testing tasks cannot be carried out in parallel.

[0019] 4. This invention binds and stores test data with the identification information of the tested audio equipment to form a traceable test record, and performs production quality analysis based on the test record, thereby realizing the systematic management of test data and production optimization. This improves the problem that traditional audio test data is mostly stored in a scattered manner, and due to the lack of correlation with the product and in-depth analysis, it causes difficulties in after-sales traceability and the inability to accurately locate production quality problems. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating an automated audio testing method proposed in this invention. Figure 2 This is a flowchart illustrating the dynamic adjustment and anomaly handling process in an automated audio testing method proposed in this invention. Figure 3 This is a schematic diagram of the feature extraction process in an automated audio testing method proposed in this invention; Figure 4This is a schematic diagram of the standard comparison process in an automated audio testing method proposed in this invention; Figure 5 This is a schematic diagram of the architecture of an automated audio testing system proposed in this invention. Detailed Implementation

[0021] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: In a first embodiment of the present invention, the present invention provides an automated audio testing method, such as... Figures 1-2 As shown, it includes the following steps: S1. Construct a timing control process: Trigger the power on / off command of the speaker through the control module to simultaneously complete the device wake-up and wireless pairing process, forming a continuous automated test start sequence; Furthermore, in S1, the timing control process includes: the control module triggers the power supply of the speaker to be turned on and off according to a preset time sequence, and calls the wireless communication protocol stack command to complete the sending of the wake-up command and the response to the pairing request of the speaker under test; Furthermore, S1 also includes: obtaining the model information of the speaker under test through the identification unit, and matching the corresponding timing parameters based on the model information. The timing parameters include the power on / off interval duration and the wireless pairing timeout threshold. Furthermore, S1 also includes dynamic adjustment and exception handling steps: Based on the response delay data of the tested speaker, the adjusted control command trigger time is calculated using a dynamic timing adjustment formula. When the tested speaker does not respond, a preset number of retry operations are automatically executed, the abnormality type is recorded, and an alarm signal is triggered. The response delay data is obtained by recording the time difference between the wireless pairing request and the device response. The interval between retry operations is a preset fixed value. Abnormality types include power failure and wireless module failure. The dynamic timing adjustment formula is: t adj =t base +k·Δt; Among them, t adj The adjusted instruction trigger time, t base The baseline trigger time is denoted by k, which is an adjustment coefficient ranging from 1 to 2. Δt is the measured response delay value from the previous test, i.e., the difference between the actual wake-up time and the preset time.

[0023] Specifically, the dynamic timing adjustment formula is tadj =t base +k·Δt where the input data includes the baseline trigger time t base The input data includes the adjustment coefficient k and the measured response delay Δt from the previous test. Substituting these input data into the formula, the output result is the adjusted command trigger time t. adj This result is used by the control module to subsequently trigger power on / off commands for the audio system and wireless pairing related commands, in order to adapt to the actual response of the audio system under test.

[0024] S1 constructs a timing control process by triggering the power on / off of the audio system according to a preset time sequence through the control module and calling wireless communication protocol stack commands to complete the wake-up command sending and pairing request response, forming a continuous automated test start sequence. This achieves basic automation of device wake-up and wireless pairing: The identification unit obtains the model information of the audio system under test and matches it with corresponding timing parameters such as the power on / off interval and wireless pairing timeout threshold, enabling timing control to adapt to different device models; based on the time difference between the wireless pairing request and the device response, response delay data is obtained, and the dynamic timing adjustment formula t is used... adj =t base The adjusted control command trigger time is calculated using +k·Δt, which optimizes timing accuracy. When a device is found to be unresponsive, a preset number of retry operations are performed at a preset fixed interval. Anomalies such as power failure and wireless module failure are recorded and alarm signals are triggered, ensuring the continuity of the timing control process. This enables the construction of an automated test start sequence.

[0025] Please refer to Figure 1 and Figure 3 and Figure 4 S2, Multi-channel audio acquisition and detection: A multi-channel acquisition device is used to capture the audio output signal. The signal processing unit performs feature extraction and standard comparison on the signal to complete the detection of sound quality parameters. Furthermore, in S2, the multi-channel acquisition device includes multiple signal acquisition channels, a noise sensor, and a temperature and humidity sensor. Each signal acquisition channel is equipped with an analog-to-digital converter (ADC) to convert the analog audio signal output by the speaker into a digital signal. The noise sensor outputs a noise signal, and the temperature and humidity sensor outputs a temperature and humidity signal. The signal processing unit receives the digital signal, the noise signal, and the temperature and humidity signal. It first performs noise filtering and amplification preprocessing on the digital signal, and then performs parameter compensation on the preprocessed digital signal based on the temperature and humidity signal. Furthermore, in S2, feature extraction includes the following steps: Spectral analysis of digital signals is performed using the Fast Fourier Transform algorithm. The spectral amplitude of the digital signal is calculated using the Fast Fourier Transform formula; Extract frequency response characteristics within a preset frequency range; The preset frequency range is 20Hz-20kHz, and the frequency response characteristics are divided into 63 segments, with each segment spaced 300Hz apart. The formula for Fast Fourier Transform is: Where X(k) is the spectral amplitude at point k, x(n) is the digital signal value at the nth sampling point, N is the number of sampling points, k is the frequency index, and 0 ≤ k <N; Furthermore, in S2, the standard comparison includes the following steps: The extracted sound quality parameters are compared with the pre-stored standard template to calculate the error. The average error value is obtained using the average error calculation formula. Sound quality detection and judgment are completed by comparing the average error value with a preset error threshold. Based on the error calculation results, the sound quality defects are classified into types, and a visual report containing abnormal segment identifiers is generated. Sound quality parameters include intermodulation distortion, transient response time, and sound pressure level dynamic range; The formula for calculating the average error is: Where e is the average error value, M is the total number of parameters, and P i Let S be the measured value of the i-th parameter. i Let be the value of the i-th standard parameter, and θ be the preset error threshold; when e ≤ θ, the sound quality test is deemed qualified.

[0026] Specifically, the formula for the Fast Fourier Transform is as follows: The input data consists of the sampling point value x(n) of the digital signal, which is obtained by converting the analog audio signal output by the audio system using an analog-to-digital converter; the number of sampling points N is determined by the sampling settings of the multi-channel acquisition device; and the frequency point S|k. Substituting the above input data into the formula, the output result is the spectral amplitude X(k) of the k-th point. This result is used to extract the frequency response characteristics divided into 63 segments within the preset frequency range of 20Hz-20kHz, providing a basis for subsequent sound quality parameter detection. The formula for calculating the average error is: The input data includes the i-th measured sound quality parameter value P. i Features such as intermodulation distortion, transient response time, and sound pressure level dynamic range are obtained from the feature extraction step and are pre-stored in the standard template as the i-th standard parameter value S. i The input data is denoted as M, and the total number of parameters is M. After substituting the above input data into the formula, the output result is the average error value e. This result is used to compare with the preset error threshold θ to complete the sound quality detection and judgment. At the same time, based on this result, the sound quality defects are classified and a visual report containing abnormal segment identifiers is generated.

[0027] The S2 multi-channel audio acquisition and detection system utilizes multiple signal acquisition channels, noise sensors, temperature and humidity sensors, and analog-to-digital converters (ADCs) configured in each channel to capture analog audio signals from the speaker output and convert them into digital signals, output noise signals, and temperature and humidity signals. The signal processing unit receives these signals, first performing noise filtering and amplification preprocessing on the digital signals, and then performing parameter compensation based on the temperature and humidity signals to ensure signal accuracy. Finally, a fast Fourier transform algorithm is used to perform spectral analysis on the preprocessed digital signals, employing the formula... The spectral amplitude is calculated, and frequency response features divided into 63 segments within a preset frequency range of 20Hz-20kHz are extracted to complete feature extraction. The extracted sound quality parameters, such as intermodulation distortion, transient response time, and sound pressure level dynamic range, are compared with pre-stored standard templates using formulas. The average error value e is calculated, and the detection judgment is completed by comparing e with the preset error threshold θ. Based on the results, the sound quality defects are classified and a visual report containing abnormal segment identifiers is generated, thus realizing the complete process of sound quality parameter detection.

[0028] Please refer to Figure 1 S3, Multi-channel parallel testing: By using a multi-channel RF switching device to allocate independent communication channels to multiple audio devices under test, parallel processing of audio testing of multiple devices at the same time is completed. Furthermore, in S3, the multi-channel RF switching device divides communication time slots using time division multiple access (TDMA) technology, allocating a dedicated time slot for each speaker under test. Simultaneously, the channel quality monitoring unit monitors the signal-to-noise ratio (SNR) of each channel in real time. When the SNR falls below a preset threshold, the device automatically switches the test task to an idle channel and dynamically adjusts the communication frequency using a frequency hopping algorithm. The frequency hopping algorithm randomly selects the next communication frequency based on a preset frequency set, which includes multiple discrete frequency points within the 2.402-2.480 GHz range. The multi-channel RF switching device supports 16-channel expansion and the number of channels can be configured via a DIP switch. Furthermore, in S3, the multi-channel RF switching device employs a dual-channel hot-backup core switching chip. When the main chip fails, it automatically switches to the backup chip within a preset time and triggers an alarm. The device also integrates multiple wireless communication protocol processing units, including Bluetooth and Wi-Fi protocols, to adapt to speakers under test with different communication types and complete the testing of speakers with wireless audio streaming capabilities.

[0029] Specifically, the S3 multi-channel parallel testing utilizes a multi-channel RF switching device with time-division multiple access (TDMA) technology to divide communication time slots, assigning a dedicated time slot to each speaker under test, thus enabling simultaneous testing of multiple devices. Simultaneously, a channel quality monitoring unit monitors the signal-to-noise ratio (SNR) of each channel in real time. When the SNR falls below a preset threshold, the test task for the corresponding device is automatically switched to an idle channel. A frequency-hopping algorithm is used to randomly select the next communication frequency from a preset frequency set containing multiple discrete frequency points within the 2.402-2.480 GHz range, dynamically adjusting the communication frequency to reduce interference. The device supports 16-channel expansion and allows configuration of the number of channels via a DIP switch, enhancing parallel testing capabilities. The multi-channel RF switching device employs a dual-channel hot-backup core switching chip. When the main chip fails, it automatically switches to the backup chip within a preset time and triggers an alarm, ensuring continuous testing. The device also integrates processing units for various wireless communication protocols such as Bluetooth and Wi-Fi, adapting to speakers under test with different communication types, and completing tests on speakers with wireless audio streaming capabilities. This allows for the allocation of independent communication channels to multiple speakers under test and the parallel processing of simultaneous audio testing.

[0030] Please refer to Figure 1 S4. Full-process data processing: The test data is bound and stored with the identification information of the audio device under test to form a traceable test record, and production quality analysis is carried out based on the test record.

[0031] Specifically, by binding and storing test data with the identification information of the speakers under test, the test information of each speaker is associated with its own identification, forming a traceable test record and realizing the correspondence between test data and specific equipment; at the same time, production quality analysis is carried out based on the formed traceable test record to extract production process information reflected in the test data.

[0032] Example 2: Please see the appendix Figure 5 In a second embodiment of the present invention, the present invention provides an automated audio testing system, including: a timing control module, used to trigger an audio power on / off command, synchronously complete the device wake-up and wireless pairing process, and form a continuous automated test start sequence, including triggering power on / off, sending a wake-up command, completing wireless pairing, dynamic timing adjustment and anomaly handling; The audio acquisition and processing module is used to capture audio output signals using a multi-channel acquisition device, and to perform feature extraction and standard comparison on the signals through the signal processing unit to complete the detection of sound quality parameters. It includes a multi-channel acquisition device, a noise sensor, a temperature and humidity sensor and a signal processing unit. The multi-channel acquisition device captures audio signals, and the signal processing unit performs feature extraction, standard comparison and defect classification. The parallel testing module is used to allocate independent communication channels to multiple speakers under test through a multi-channel RF switching device, so as to complete the parallel processing of audio testing of multiple devices at the same time. The multi-channel RF switching device includes a channel quality monitoring unit, a dual-channel hot backup chip, a multi-protocol processing unit and a channel configuration component, which allocates independent communication channels to multiple speakers under test to complete parallel testing. The data processing module is used to bind and store test data with the identification information of the tested audio equipment to form a traceable test record, and to perform production quality analysis based on the test record. This includes binding and storing test data with audio equipment identification information in a blockchain database, generating traceable test records, and performing production quality analysis.

[0033] A large audio equipment manufacturing workshop needs to test 5,000 audio equipment of various models daily. Traditional testing relies on manual operation: workers connect the power and manually pair Bluetooth with each unit, which is time-consuming and prone to interruption due to inconsistent operation sequences. Sound quality testing is judged by human hearing, and different workers may have up to 15% different opinions on the sound quality of the same audio equipment. Serial testing on a single device limits the number of units tested to only 80 per hour, which is insufficient to meet production capacity requirements. Test data is only recorded by hand on paper documents, making it difficult to quickly trace the corresponding production information when quality problems occur after sales, and it is also difficult to optimize the production process through data. To solve the above problems, an automated audio equipment testing system provided by this invention is adopted, the structure of which is as follows: Figure 5 As shown. The specific implementation process of this system is as follows: After the timing control module starts, it automatically triggers the power on / off command of the speaker under test, and synchronously calls the Bluetooth protocol stack to complete the device wake-up and pairing. For different speaker models, the corresponding power on / off interval and timing parameters are matched by the identification unit, and the command triggering time is dynamically adjusted. When the device does not respond, it automatically retryes and records the abnormality. This process does not require manual intervention, which shortens the test start-up time of a single speaker and reduces the test interruption rate. The audio acquisition and processing module captures the audio output signal through a multi-channel acquisition device, converts it into a digital signal through an analog-to-digital converter, and then performs filtering and parameter compensation in combination with the signals from the noise sensor and temperature and humidity sensor. Finally, it extracts 63 frequency response features in the 20Hz-20kHz frequency band through fast Fourier transform, compares them with the standard template to calculate the error, automatically classifies the sound quality defects and generates a report, thereby eliminating subjective errors in sound quality detection and improving detection accuracy. The parallel testing module divides time slots through a multi-channel RF switching device, assigning independent channels to 16 speakers. Combined with frequency hopping algorithms to avoid interference, dual-channel hot backup chips ensure stable operation of the equipment. It is also compatible with Bluetooth and Wi-Fi protocols for speaker testing, increasing the testing capacity to 640 units per hour to meet daily production capacity requirements. The data processing module binds the test data of each speaker to its traceability identifier and stores it in the system database to form a traceable record. Based on the record, a quality dashboard is generated, and analysis shows that high-frequency faults are concentrated in the speaker installation process. This drives the optimization of the production process, reduces the after-sales traceability time from 2 hours to 5 minutes, and improves the product qualification rate.

[0034] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automated testing method for audio equipment, characterized in that, Includes the following steps: S1. Construct a timing control process: Trigger the power on / off command of the speaker through the control module to simultaneously complete the device wake-up and wireless pairing process, forming a continuous automated test start sequence; S2. Multi-channel audio acquisition and detection: A multi-channel acquisition device is used to capture the audio output signal. The signal processing unit performs feature extraction and standard comparison on the signal to complete the detection of sound quality parameters. S3, Multi-channel parallel testing: By using a multi-channel RF switching device to allocate independent communication channels to multiple speakers under test, parallel processing of audio testing of multiple devices can be completed simultaneously; S4. Full-process data processing: The test data is bound and stored with the identification information of the audio device under test to form a traceable test record, and production quality analysis is performed based on the test record.

2. The automated audio testing method according to claim 1, characterized in that, In S1, the timing control process includes: the control module triggers the power supply of the speaker to be turned on and off according to a preset time sequence, and calls the wireless communication protocol stack command to complete the sending of the wake-up command and the response to the pairing request of the speaker under test.

3. The automated audio testing method according to claim 1, characterized in that, The S1 further includes: obtaining the model information of the speaker under test through the identification unit, and matching the corresponding timing parameters based on the model information, wherein the timing parameters include the power on / off interval duration and the wireless pairing timeout threshold.

4. The automated audio testing method according to claim 1, characterized in that, S1 also includes dynamic adjustment and anomaly handling steps: Based on the response delay data of the tested audio system, the adjusted control command trigger time is calculated using a dynamic timing adjustment formula. When the tested speaker is found to be unresponsive, it will automatically perform a preset number of retries, record the type of abnormality, and trigger an alarm signal. The response delay data is obtained by recording the time difference between the wireless pairing request being sent and the device response. The interval between retry operations is a preset fixed value. The anomaly types include power failure and wireless module failure.

5. The automated audio testing method according to claim 1, characterized in that, In S2, the multi-channel acquisition device includes multiple signal acquisition channels, a noise sensor, and a temperature and humidity sensor. Each signal acquisition channel is equipped with an analog-to-digital converter (ADC). The ADC is used to convert the analog audio signal output by the speaker into a digital signal. The noise sensor is used to output a noise signal, and the temperature and humidity sensor is used to output a temperature and humidity signal. The signal processing unit receives the digital signal, the noise signal, and the temperature and humidity signal. It first performs noise filtering and amplification preprocessing on the digital signal, and then performs parameter compensation on the preprocessed digital signal based on the temperature and humidity signal.

6. The automated audio testing method according to claim 1, characterized in that, In step S2, feature extraction includes the following steps: Spectral analysis of digital signals is performed using the Fast Fourier Transform algorithm. The spectral amplitude of the digital signal is calculated using the Fast Fourier Transform formula; Extract frequency response characteristics within a preset frequency range; The preset frequency range is 20Hz-20kHz, and the frequency response characteristics are divided into 63 segments, with each segment spaced 300Hz apart.

7. The automated audio testing method according to claim 1, characterized in that, In S2, the standard comparison includes the following steps: The extracted sound quality parameters are compared with the pre-stored standard template to calculate the error. The average error value is obtained using the average error calculation formula. The sound quality detection and determination are completed by comparing the average error value with a preset error threshold. Based on the error calculation results, the sound quality defects are classified into types, and a visual report containing abnormal segment identifiers is generated. The sound quality parameters include intermodulation distortion, transient response time, and sound pressure level dynamic range.

8. The automated audio testing method according to claim 1, characterized in that, In S3, the multi-channel RF switching device divides communication time slots using time division multiple access (TDMA) technology, allocating a dedicated time slot for each audio device under test. Simultaneously, the channel quality monitoring unit detects the signal-to-noise ratio (SNR) of each channel in real time. When the SNR is lower than a preset threshold, the device's test task is automatically switched to an idle channel, and the communication frequency is dynamically adjusted using a frequency hopping algorithm. The frequency hopping algorithm randomly selects the next communication frequency based on a preset frequency set, which includes multiple discrete frequency points in the range of 2.402-2.480 GHz. The multi-channel RF switching device supports 16-channel expansion and the number of channels can be configured via a DIP switch.

9. The automated audio testing method according to claim 1, characterized in that, In S3, the multi-channel RF switching device adopts a dual-channel hot-backup core switching chip. When the main chip fails, it automatically switches to the backup chip within a preset time and triggers an alarm. The device also integrates multiple wireless communication protocol processing units, including Bluetooth and Wi-Fi protocols, to adapt to the audio devices under test with different communication types and complete the testing of audio devices with wireless audio stream transmission capabilities.

10. An automated audio testing system, characterized in that, An automated audio testing method according to any one of claims 1-9, the system comprising: The timing control module is used to trigger the power on / off command of the audio system, synchronously complete the device wake-up and wireless pairing process, and form a continuous automated test start sequence. The audio acquisition and processing module is used to capture the audio output signal using a multi-channel acquisition device, and to perform feature extraction and standard comparison of the signal through the signal processing unit to complete the detection of sound quality parameters. The parallel testing module is used to allocate independent communication channels to multiple speakers under test through a multi-channel RF switching device, so as to complete the parallel processing of audio testing of multiple devices at the same time. The data processing module is used to bind and store test data with the identification information of the tested audio equipment to form a traceable test record, and to perform production quality analysis based on the test record.

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