CN116866807A

CN116866807A - Loudspeaker detection method and device

Info

Publication number: CN116866807A
Application number: CN202310833545.XA
Authority: CN
Inventors: 兰双城; 吴同海; 马玉帅
Original assignee: Goertek Inc
Current assignee: Goertek Inc
Priority date: 2023-07-07
Filing date: 2023-07-07
Publication date: 2023-10-10

Abstract

The invention discloses a detection method and a detection device of a loudspeaker, wherein the detection method comprises the following steps: collecting a sound signal played by a speaker to be tested; performing discrete short-time Fourier transform on the sound signal to obtain a time-frequency sound signal corresponding to each sampling frequency; the time-frequency sound signal comprises signal intensity at each sampling time corresponding to the sampling frequency; acquiring a first fundamental frequency of a sound signal, and filtering the time-frequency sound signal of each sampling frequency based on the first fundamental frequency to obtain a filtered time-frequency sound signal of each sampling frequency; dividing all sampling frequencies according to preset frequency intervals to obtain a plurality of frequency intervals; calculating the signal intensity sum of the sampling frequency in each frequency interval in the corresponding sampling time according to the filtered time-frequency sound signal corresponding to the sampling frequency in each frequency interval; and judging whether the speaker to be tested has abnormal sound faults or not according to the signal intensity.

Description

Loudspeaker detection method and device

Technical Field

The invention relates to the technical field of loudspeaker detection, in particular to a method and a device for detecting a loudspeaker.

Background

Along with the continuous rapid development of science and technology, the performance requirement on the loudspeaker is higher and higher, and the abnormal sound is a defect of the loudspeaker, so that the tone quality and the use feeling of the loudspeaker are directly influenced, and the loudspeaker is highly valued by users. At present, abnormal sound of a loudspeaker is mainly detected by means of higher harmonic distortion and artificial hearing.

In the detection method of harmonic distortion, a sound signal played through a speaker is collected, and the sound signal is directly analyzed by fourier transform. Because the Fourier transform has limitations, small changes in the time domain cannot be identified, and therefore, the detection method has low accuracy in detecting the abnormal sound of the loudspeaker.

The detection mode of manual listening plays sound signals through a loudspeaker, and a detection person subjectively detects listening. In this way, the requirement on the detection personnel is higher, and the detection efficiency is lower; on the other hand, the detection personnel are in a high noise environment for a long time, the hearing threshold can be improved, the sensitivity can be reduced, and erroneous judgment can be caused.

Disclosure of Invention

It is an object of embodiments of the present invention to provide a new solution that solves at least one of the above mentioned problems.

According to a first aspect of the present invention, there is provided a method of detecting a speaker, comprising:

collecting a sound signal played by a speaker to be tested;

performing discrete short-time Fourier transform on the sound signal to obtain a time-frequency sound signal corresponding to each sampling frequency; the time-frequency sound signal comprises signal intensity of corresponding sampling frequency at each sampling time;

acquiring a first fundamental wave frequency of the sound signal, and filtering the time-frequency sound signal of each sampling frequency based on the first fundamental wave frequency to obtain a filtered time-frequency sound signal of each sampling frequency;

dividing all sampling frequencies according to preset frequency intervals to obtain a plurality of frequency intervals;

calculating the signal intensity sum of the sampling frequency in each frequency interval in the corresponding sampling time according to the filtered time-frequency sound signal corresponding to the sampling frequency in each frequency interval;

and judging whether the speaker to be tested has abnormal sound faults or not according to the signal intensity and the signal intensity.

Optionally, the acquiring the first fundamental frequency of the sound signal includes:

and determining the sampling frequency corresponding to the maximum signal intensity according to the time-frequency sound signal of each sampling frequency as the first fundamental wave frequency.

Optionally, the filtered time-frequency sound signal is obtained by the following formula:

y[n]＝b[0]x[n]+b[1]x[n-1]-a[1]y[n-1]

wherein y n is the filtered time-frequency sound signal of the nth sampling frequency, y n-1 is the filtered time-frequency sound signal of the nth-1 sampling frequency, x n is the time-frequency sound signal of the nth sampling frequency, x n-1 is the time-frequency sound signal of the nth-1 sampling frequency; b < 0 >, b < 1 >, a < 1 > are filter coefficients determined based on the first fundamental frequency.

Optionally, the step of determining whether the speaker to be tested has an abnormal sound fault according to the signal strength includes:

determining a distribution curve of the signal intensity sum corresponding to each frequency interval according to the signal intensity sum;

and judging whether the speaker to be tested has abnormal sound faults or not according to the distribution curve of the signal intensity sum.

Optionally, the step of determining whether the speaker to be tested has a abnormal sound fault according to the distribution curve of the sum of the signal intensities includes:

determining a first qualified range corresponding to the signal intensity distribution curve from prestored first qualified ranges according to a frequency interval corresponding to the signal intensity distribution curve;

comparing whether the signal intensity distribution curve exceeds a corresponding first qualified range;

Under the condition that the distribution curve of the sum of the signal intensities of the N frequency intervals exceeds the corresponding first qualified range, judging that the speaker to be tested has abnormal sound faults; wherein N is a positive integer.

Optionally, the detection method further includes:

obtaining standard sound signals played by at least one qualified loudspeaker; wherein the speaker to be tested and the at least one qualified speaker are driven by the same signal;

performing discrete short-time Fourier transform on the standard sound signals to obtain standard time-frequency sound signals corresponding to each sampling frequency; the standard time-frequency sound signal comprises standard signal intensity corresponding to sampling frequency at each sampling time;

acquiring a second fundamental wave frequency of the standard sound signal, and filtering the standard time-frequency sound signal of each sampling frequency based on the second fundamental wave frequency to obtain a filtered standard time-frequency sound signal of each sampling frequency;

obtaining a distribution curve of the standard signal intensity sum corresponding to each frequency interval according to the filtered standard time-frequency sound signal corresponding to the sampling frequency in each frequency interval;

and determining a first qualified range corresponding to each frequency interval according to the distribution curve of the standard signal intensity sum.

Optionally, the first qualified range includes a distribution curve of all corresponding standard signal intensity sums.

splicing the distribution curves of the signal intensity sums of all the frequency intervals to obtain a spliced distribution curve of the signal intensity sums;

comparing whether the distribution curve of the signal intensity sum after splicing exceeds a set second qualified range;

and under the condition that the distribution curve of the sum of the signal intensities after the splicing exceeds the second qualified range, judging that the speaker to be tested has abnormal sound faults.

Optionally, the detection method further includes:

splicing the distribution curves of the standard signal intensity sums of all the frequency intervals to obtain a distribution curve of the spliced standard signal intensity sums;

and determining the second qualified range according to the distribution curve of the sum of the standard signal intensities after the splicing.

According to a second aspect of the present invention, there is provided a detection apparatus for a speaker, comprising:

the first acquisition module is used for acquiring sound signals played by the loudspeaker to be tested;

the first transformation module is used for carrying out discrete short-time Fourier transformation on the sound signals to obtain time-frequency sound signals corresponding to each sampling frequency; the time-frequency sound signal comprises signal intensity of corresponding sampling frequency at each sampling time;

The first filtering module is used for acquiring a first fundamental frequency of the sound signal, and filtering the time-frequency sound signal of each sampling frequency based on the first fundamental frequency to obtain a filtered time-frequency sound signal of each sampling frequency;

the division module is used for dividing all sampling frequencies according to preset frequency intervals to obtain a plurality of frequency intervals;

the calculation module is used for calculating the signal intensity sum of the sampling frequency in each frequency interval in the corresponding sampling time according to the filtered time-frequency sound signal corresponding to the sampling frequency in each frequency interval; the method comprises the steps of,

and the judging module is used for judging whether the speaker to be tested has abnormal sound faults or not according to the signal intensity.

Optionally, the first filtering module is further configured to:

y[n]＝b[0]x[n]+b[1]x[n-1]-a[1]y[n-1]

Optionally, the judging module further includes:

a curve determining unit, configured to determine a distribution curve of the sum of signal intensities corresponding to each frequency interval according to the sum of signal intensities;

and the judging unit is used for judging whether the speaker to be tested has abnormal sound faults or not according to the distribution curve of the sum of the signal intensities.

Optionally, the judging unit further includes:

a range determining subunit, configured to determine, from first qualified ranges stored in advance, a first qualified range corresponding to the distribution curve of the signal intensity sum according to a frequency interval corresponding to the distribution curve of the signal intensity sum;

a first comparing subunit, configured to compare whether the distribution curve of the sum of signal intensities exceeds a corresponding first qualified range; the method comprises the steps of,

the first judging subunit is used for judging that the speaker to be tested has abnormal sound faults under the condition that the distribution curve of the sum of the signal intensities of the N frequency intervals exceeds the corresponding first qualified range; wherein N is a positive integer.

Optionally, the detection device further includes:

the second acquisition module is used for acquiring standard sound signals played by at least one qualified loudspeaker; wherein the speaker to be tested and the at least one qualified speaker are driven by the same signal;

The second transformation module is used for carrying out discrete short-time Fourier transformation on the standard sound signals to obtain standard time-frequency sound signals corresponding to each sampling frequency; the standard time-frequency sound signal comprises standard signal intensity corresponding to sampling frequency at each sampling time;

the second filtering module is used for acquiring a second fundamental wave frequency of the standard sound signal, and filtering the standard time-frequency sound signal of each sampling frequency based on the second fundamental wave frequency to obtain a filtered standard time-frequency sound signal of each sampling frequency;

the first curve determining module is used for obtaining a distribution curve of the standard signal intensity sum corresponding to each frequency interval according to the filtered standard time-frequency sound signals corresponding to the sampling frequency in each frequency interval;

and the first range determining module is used for determining a first qualified range corresponding to each frequency interval according to the distribution curve of the standard signal intensity sum.

Optionally, the first qualified range includes a distribution curve of the sum of all standard signal intensities of the corresponding frequency intervals.

Optionally, the judging unit further includes:

The splicing subunit is used for splicing the distribution curves of the signal intensity sums of all the frequency intervals to obtain a distribution curve of the spliced signal intensity sums;

the second comparison subunit is used for comparing whether the distribution curve of the signal intensity sum after splicing exceeds a set second qualified range;

and the second judging subunit is used for judging that the speaker to be tested has abnormal sound faults under the condition that the distribution curve of the sum of the signal intensities after the splicing exceeds the second qualified range.

Optionally, the detection device further includes:

the third acquisition module is used for acquiring standard sound signals played by at least one qualified loudspeaker; wherein the speaker to be tested and the at least one qualified speaker are driven by the same signal;

the third transformation module is used for carrying out discrete short-time Fourier transformation on the standard sound signals to obtain standard time-frequency sound signals corresponding to each sampling frequency; the standard time-frequency sound signal comprises standard signal intensity corresponding to sampling frequency at each sampling time;

the third filtering module is used for acquiring a second fundamental wave frequency of the standard sound signal, and filtering the standard time-frequency sound signal of each sampling frequency based on the second fundamental wave frequency to obtain a filtered standard time-frequency sound signal of each sampling frequency;

The second curve determining module is used for obtaining a distribution curve of the standard signal intensity sum corresponding to each frequency interval according to the filtered standard time-frequency sound signals corresponding to the sampling frequency in each frequency interval;

the splicing module is used for splicing the distribution curves of the standard signal intensity sum of all the frequency intervals to obtain a spliced distribution curve of the standard signal intensity sum;

and the second range determining module is used for determining the second qualified range according to the distribution curve of the sum of the spliced standard signal intensities.

The invention has the beneficial effect that whether the abnormal sound fault exists in the loudspeaker can be rapidly and effectively detected by the detection mode. In addition, by the detection mode in the embodiment, the accuracy of the detection result of the abnormal sound fault of the loudspeaker can be higher. In addition, noise injury to the inspector can be reduced.

Other features of the present invention and its advantages will become apparent from the following detailed description of exemplary embodiments of the invention, which proceeds with reference to the accompanying drawings.

Drawings

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

Fig. 1 is a block schematic diagram of an implementation of a detection system for a loudspeaker according to the invention.

Fig. 2 is a flowchart of a first embodiment of a method of detecting a speaker according to the present invention;

fig. 3 is a flow chart of a second embodiment of a method of detecting a speaker according to the present invention;

FIG. 4a is a graph showing a distribution curve of a sum of signal intensities in a first frequency range;

FIG. 4b is a graph showing the distribution curve of the sum of the signal intensities in the second frequency range;

FIG. 4c is a graph showing the distribution curve of the sum of the signal intensities in the third frequency interval;

fig. 5 is a flowchart of a third embodiment of a method of detecting a speaker according to the present invention;

FIG. 6a is a diagram illustrating a pass range of a first frequency bin;

FIG. 6b is a diagram illustrating the pass range of the second frequency bin;

FIG. 6c is a diagram illustrating a pass range of a third frequency bin;

fig. 7 is a flowchart of a fourth embodiment of a method of detecting a speaker according to the present invention;

FIG. 8a is a comparison curve of a first frequency interval;

FIG. 8b is a comparison curve of a second frequency interval;

fig. 9 is a flowchart of a fifth embodiment of a method of detecting a speaker according to the present invention;

FIG. 10 is a schematic diagram of a distribution curve of the sum of signal intensities after splicing;

Fig. 11 is a flowchart of a sixth embodiment of a method of detecting a speaker according to the present invention;

FIG. 12 is a graph of comparison after stitching;

fig. 13 is a block schematic diagram of a first embodiment of a detection device of a speaker according to the present invention;

fig. 14 is a block schematic diagram of a second embodiment of a detection device of a speaker according to the present invention;

fig. 15 is a block schematic diagram of a third embodiment of a detection device of a speaker according to the present invention;

fig. 16 is a block schematic diagram of a fourth embodiment of a detection device of a speaker according to the present invention.

Detailed Description

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.

The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.

Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of exemplary embodiments may have different values.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.

Fig. 1 is a block schematic diagram of one implementation of a detection system for a speaker. The detection system may be as shown in fig. 1, and the detection system of a speaker may include a speaker driving module 1100, and a detection device 1200 of a speaker, where the speaker driving module 1100 may output a signal for driving a connected speaker to be tested to sound, so that the speaker to be tested can play a sound signal. The detection device 1200 of the speaker executes the detection method of the embodiment of the present invention, so as to realize the detection of the abnormal sound fault of the speaker to be detected.

Further, the speaker detection system may further include a connector for connecting a speaker to be tested. Then, the speaker driving module 1100 may be connected to the connector, so that the speaker driving module 1100 may output a signal for driving the speaker to be tested connected to the connector to sound. Through setting up the connector of connecting the speaker that awaits measuring, can be convenient for be connected the speaker that awaits measuring to this detecting system in, improve the efficiency of connecting the speaker that awaits measuring, and then can improve the efficiency of detecting the abnormal sound trouble of speaker that awaits measuring.

Fig. 2 is a flowchart of an embodiment of a method for detecting a speaker according to the present invention.

As shown in fig. 2, the detection method includes the following steps S2100 to S2600.

In step S2100, a sound signal played by the speaker to be tested is collected.

Specifically, the speaker to be tested may be driven by a signal output by a speaker driving module in the detection system shown in fig. 1, so that the speaker to be tested may play a sound signal. The signal output by the speaker driving module may be, for example, but not limited to, a sinusoidal sweep signal, a sliding frequency signal, a voice signal, a music signal, or a noise signal.

Further, the sound signal played by the speaker may be collected by a microphone. Because the amplitude of the sound signal collected by the microphone is smaller, the accuracy of detecting the loudspeaker is reduced, and therefore, the sound signal collected by the microphone can be amplified.

On the basis, the power amplifier can amplify the sound signals collected by the microphone.

Step S2200, performing discrete short-time Fourier transform on the sound signal to obtain a time-frequency sound signal corresponding to each sampling frequency.

The time-frequency sound signal comprises signal intensity at each sampling time corresponding to the sampling frequency.

The short-time fourier transform can reflect the law of the frequency content over time. The discrete short-time fourier transform is to divide the sound signal into L segments in time by using a window function with a proper width, wherein the sound signal of each segment is x (n), n=0, 1, …, L-1, and perform fourier transform on each segment of sound signal to obtain a time-frequency sound signal corresponding to each discrete frequency.

Specifically, the short-time fourier transform can be performed on the sound signal x (n) by the following formula:

wherein m represents the mth sampling time, and m is a positive integer; k represents the kth sampling frequency; n is the step size of the movement on the time axis; m is the number of points dividing a frequency period 2 pi; g ^* (n-mN) is a conjugate function of the window function g (n-mN).

By performing discrete short-time fourier transform on the sound signal, a time-frequency diagram of the sound signal can be obtained, and STFT [ m, k ] represents amplitudes corresponding to sampling time and sampling frequency in the time-frequency diagram.

In an embodiment of the present invention, the time-frequency sound signal includes a signal strength at each sampling time corresponding to a sampling frequency. Therefore, the signal strength may be STFT [ m, k ] obtained by the above equation one, may be a square of STFT [ m, k ], or may be a value obtained by performing other operations on STFT [ m, k ].

Step S2300, obtaining a first fundamental frequency of the sound signal, and performing filtering processing on the time-frequency sound signal of each sampling frequency based on the first fundamental frequency, to obtain a filtered time-frequency sound signal of each sampling frequency.

In this embodiment, the low-frequency filtering process may be performed on the time-frequency sound signals with all sampling frequencies to filter out the signal intensity of the cut-off frequency at each sampling time.

Wherein the cutoff frequency may be determined from the first fundamental frequency.

In one embodiment, the cutoff frequency may be a set multiple of the first fundamental frequency. The set multiple may be a positive number set in advance according to an application scenario or specific requirements, for example, the set multiple may be 5.

In this embodiment, the signal intensity of the time-frequency sound signal corresponding to the sampling frequency smaller than the cut-off frequency is higher, the signal intensity of the time-frequency sound signal corresponding to the sampling frequency larger than the cut-off frequency is higher and lower, and the abnormal sound fault usually occurs in the sampling frequency larger than the cut-off frequency, so that the signal intensity of the time-frequency sound signal corresponding to the sampling frequency smaller than the cut-off frequency is filtered, and then the abnormal sound fault detection is performed on the loudspeaker according to the filtered time-frequency sound signal of each sampling frequency, so that the interference of the time-frequency sound signal with higher signal intensity to the time-frequency sound signal with lower signal intensity, which is easy to detect the abnormal sound fault, can be avoided, and the abnormal sound detection result of the loudspeaker is more accurate.

In one embodiment of the present disclosure, acquiring a first fundamental frequency of a sound signal includes:

In another embodiment of the present disclosure, the first fundamental frequency may be a predetermined empirical value.

In one embodiment of the present disclosure, the filtered time-frequency sound signal may be obtained by the following formula:

y[n]＝b[0]x[n]+b[1]x[n-1]-a[1]y[n-1]

Step S2400 divides all sampling frequencies according to a preset frequency interval to obtain a plurality of frequency intervals.

All sampling frequencies in this embodiment include all ranges of values for k. In the case that the preset frequency interval is v, k=0, 1, …, M-1, the obtained frequency interval may include [0, Δr ], [ Δr+1,2Δr+1], …, [ M-1- Δr, M-1], where each frequency interval includes v sampling frequencies, and v is a positive integer.

V can be preset in advance according to a test scene, and the smaller the value of V is, the larger the calculated amount of the detection method of the embodiment is executed, and the more accurate the detection result is. Conversely, the larger the value of V, the smaller the calculation amount of the detection method of the present embodiment is performed, and the larger the error of the detection result. Therefore, V can be set in advance in consideration of the amount of calculation to perform the detection method of the present embodiment and the accuracy of the detection result.

Step S2500, calculating the sum of the signal intensities of the sampling frequencies in each frequency interval at the corresponding sampling time according to the filtered time-frequency sound signals corresponding to the sampling frequencies in each frequency interval.

Specifically, the signal intensity sum of the sampling frequency in a frequency interval at the corresponding sampling time may be calculated by: the sum of the signal strengths of all sampling frequencies within the frequency interval at each sampling time is calculated.

For example, in the case where the signal intensity at any sampling frequency at any sampling time is STFT [ m, k ], the signal intensity sum can be calculated by the following formula two:

r＝0,1,…,M-1，r ₀ =0, 1, …, M-1, and r-r ₀ ＝Δr。

Wherein P (m) represents a frequency interval Δr=r-r ₀ The sum of the signal intensities at the mth sampling time.

Step S2600, judging whether the speaker to be tested has abnormal sound fault according to the signal intensity and the signal intensity.

In one embodiment of the present invention, the signal intensity and the threshold value corresponding to each frequency interval at each sampling time may be pre-stored, and whether the speaker to be tested has the abnormal sound fault is determined by comparing each signal intensity obtained by calculation with the signal intensity and the threshold value corresponding to the frequency interval at the corresponding sampling time one by one. Specifically, the signal strength and the signal strength at the same sampling time at the same frequency may be compared with a threshold value.

The abnormal sound fault of the speaker to be tested can be judged under the condition that the sum of the signal intensities of all frequency intervals at all sampling time comprises more than x signal intensity sums which are larger than the signal intensity sum threshold value of the corresponding frequency interval at the corresponding sampling time. Wherein x may be any predetermined positive integer.

And if the sum of the signal intensities of each frequency interval exceeding z frequency intervals in all sampling time is larger than the sum of the signal intensities of the corresponding frequency interval in the corresponding sampling time, judging that the abnormal sound fault exists in the loudspeaker to be tested. Wherein y and z may be any predetermined positive integer.

In another embodiment of the present invention, step S2600 may further include steps S2610 to S2620 as shown in fig. 3.

Step S2610, determining a distribution curve of the signal intensity sum of the corresponding frequency interval according to the signal intensity sum.

Specifically, a distribution curve of the signal intensity sum corresponding to each frequency interval can be obtained according to the signal intensity sum of the frequency interval. For example, the obtained distribution curve of the sum of signal intensities corresponding to the first frequency interval may be as shown in fig. 4a, the obtained distribution curve of the sum of signal intensities corresponding to the second frequency interval may be as shown in fig. 4b, and the obtained distribution curve of the sum of signal intensities corresponding to the third frequency interval may be as shown in fig. 4 c.

In the distribution curves of the signal intensity sums shown in fig. 4a to 4c, the abscissa represents the sampling time, the ordinate represents the signal intensity sum of the corresponding frequency interval at the corresponding sampling time, and f4a represents the distribution curve of the signal intensity sum of the first frequency interval; f4b represents the distribution curve of the signal intensity sum of the second frequency interval; f4c represents the distribution curve of the sum of the signal intensities of the third frequency interval.

Step S2620, judging whether the speaker has abnormal sound fault according to the distribution curve of the sum of the signal intensities.

In one embodiment of the present disclosure, the step S2620 may further include steps S2621a to S2563a as shown in fig. 5.

Step S2621a, determining a first qualified range corresponding to the distribution curve of the signal intensity sum from the pre-stored first qualified ranges according to the frequency interval corresponding to the distribution curve of the signal intensity sum.

Specifically, a first qualification range corresponding to each frequency bin may be stored in advance, and the first qualification range may be a region below a qualification curve generated by the signal strength and the threshold value of each sampling time corresponding to the frequency bin, as shown in fig. 6a to 6 c. In the distribution curves of the standard signal intensity sums shown in fig. 6a to 6c, the abscissa represents the sampling time, the ordinate represents the standard signal intensity sum of the corresponding frequency interval at the corresponding sampling time, f1 represents the first qualification range of the corresponding first frequency interval, f2 represents the first qualification range of the corresponding second frequency interval, and f3 represents the first qualification range of the corresponding third frequency interval.

Further, the first qualification range in the present embodiment may be empirically set in advance.

In one example, the first pass range may also be determined according to steps S7100-S7500 as shown in fig. 7.

Step S7100, a standard sound signal played by at least one qualified speaker is obtained.

Wherein the speaker to be tested and the qualified speaker in the present embodiment may be driven by the same signal.

The qualified speaker in this embodiment may be determined by an existing detection method, or may be determined by a detection method of the present invention.

In step S7200, discrete short-time Fourier transform is performed on the standard sound signal to obtain a standard time-frequency sound signal corresponding to each sampling frequency.

The standard time-frequency sound signal comprises standard signal intensity at each sampling time corresponding to the sampling frequency.

And performing short-time Fourier transform on the standard sound signal to obtain a standard time-frequency sound signal corresponding to each sampling frequency.

The specific manner of performing step S7200 can refer to step S2200, and will not be described herein.

Step S7300, obtaining the second fundamental frequency of the standard sound signal, and filtering the standard time-frequency sound signal of each sampling frequency based on the second fundamental frequency to obtain a filtered standard time-frequency sound signal of each sampling frequency.

Specifically, the method of obtaining the second fundamental frequency may refer to the method of obtaining the first fundamental frequency in step S2300, the method of filtering the standard time-frequency sound signal of each sampling frequency based on the second fundamental frequency to obtain the filtered standard time-frequency sound signal of each sampling frequency, and the method of filtering the time-frequency sound signal of each sampling frequency based on the first fundamental frequency in step S2300 to obtain the filtered time-frequency sound signal of each sampling frequency, which will not be described herein.

Step S7400, according to the filtered standard time-frequency sound signal corresponding to the sampling frequency in each frequency interval, obtaining a distribution curve of the standard signal intensity sum corresponding to each frequency interval.

Specifically, according to the filtered standard time-frequency sound signal corresponding to the sampling frequency in each frequency interval, the standard signal intensity sum of each sampling time in each frequency interval can be obtained. The calculation method of the standard signal strength sum of each sampling time in each frequency interval can refer to the step S2400 described above, and will not be described herein.

According to the standard signal strength sum of each sampling time in each frequency interval, a distribution curve corresponding to the standard signal strength sum of each frequency interval can be obtained, and the specific manner can refer to the above step S2610, which is not described herein.

Step S7500, determining a first qualified range corresponding to each frequency interval according to the distribution curve of the standard signal intensity sum.

In the case of acquiring the standard sound signal played by one qualified speaker in step S7100, the following steps S7200 to S7400 are performed on the standard sound signal to obtain a distribution curve of the standard signal intensity sum corresponding to each frequency interval. And determining a first qualified range corresponding to each frequency interval according to the distribution curve of the signal intensity sum corresponding to each frequency interval.

In the case of acquiring standard sound signals played by a plurality of qualified speakers in step S7100, the following methods of steps S7200 to S7400 are performed for each standard sound signal, so as to obtain a distribution curve of a plurality of standard signal intensity sums corresponding to each frequency interval. And determining a first qualified range corresponding to each frequency interval according to the distribution curve of the sum of the signal intensities corresponding to each frequency interval.

Further, the distribution curve including the sum of all the signal intensities in any one of the frequency intervals in the first qualified range corresponding to the frequency interval may be specifically as shown in fig. 6a to 6 c. In the distribution curves of the standard signal intensity sums shown in fig. 6a to 6c, the abscissa represents the sampling time, the ordinate represents the standard signal intensity sum of the corresponding frequency interval at the corresponding sampling time, f6a represents the first qualification range of the corresponding first frequency interval, f6b represents the first qualification range of the corresponding second frequency interval, f6c represents the first qualification range of the corresponding third frequency interval, and the remaining curves represent the distribution curves of the standard signal intensity sums in the corresponding frequency interval.

In step S2622a, whether the distribution curve of the signal intensity sum exceeds the corresponding first qualified range is compared.

Specifically, the first pass range may be integrated into the distribution curve of the sum of signal intensities, resulting in a comparison curve as shown in fig. 8a or fig. 8 b.

As shown in fig. 8a, the abscissa indicates the sampling time, the ordinate indicates the sum of signal intensities of the corresponding frequency intervals at the corresponding sampling time, f80 indicates the first qualified range of the first frequency interval, and f8a indicates the distribution curve of the sum of signal intensities of the first frequency interval. As can be seen from fig. 8a, the distribution curve of the sum of the signal intensities in the first frequency interval does not exceed the corresponding first qualification range.

As shown in fig. 8b, the abscissa indicates the sampling time, the ordinate indicates the sum of signal intensities of the corresponding frequency interval at the corresponding sampling time, f82 indicates the first qualified range of the second frequency interval, and f8b indicates the distribution curve of the sum of signal intensities of the second frequency interval. As can be seen from fig. 8b, the distribution curve of the sum of the signal intensities of the second frequency interval exceeds the corresponding first pass range.

Step S2623a, determining that the speaker to be tested has an abnormal sound fault when the distribution curve of the sum of the signal intensities corresponding to the N frequency intervals exceeds the corresponding first qualified range. Wherein N is a positive integer.

Specifically, N is a fixed value set in advance according to an application scenario. For example, N may be 1, and then, if the energy distribution curve corresponding to any one of the frequency intervals exceeds the corresponding first qualified range, it may be determined that the speaker to be tested has an abnormal sound fault. Therefore, by the detection mode, whether the abnormal sound fault exists in the loudspeaker can be detected rapidly and effectively. In addition, by the detection mode in the embodiment, the accuracy of the detection result of the abnormal sound fault of the loudspeaker can be higher. In addition, noise injury to the inspector can be reduced.

In another embodiment of the present disclosure, determining whether the speaker has an abnormal sound fault according to the distribution curve of the sum of the signal intensities may further include steps S2621b to S2563b as shown in fig. 9.

Step 2621b, the distribution curves of the signal intensity sums of all the frequency intervals are spliced to obtain the distribution curve of the spliced signal intensity sums.

In one embodiment, the distribution curves of the signal intensity sums of all the frequency intervals are spliced according to the order from small to large or the order from large to small of the sampling frequencies in the frequency intervals in the dimension of the sampling time, so as to obtain the distribution curve of the spliced signal intensity sums.

In the case where the distribution curve of the signal intensity sum corresponding to the first frequency interval is shown as f4a in fig. 4a, the distribution curve of the signal intensity sum corresponding to the second frequency interval is shown as f4b in fig. 4b, and the distribution curve of the signal intensity sum corresponding to the third frequency interval is shown as f4c in fig. 4c, the distribution curve f4a of the signal intensity sum of the first frequency interval, the distribution curve f4b of the signal intensity sum of the second frequency interval, and the distribution curve f4c of the signal intensity sum of the third frequency interval are spliced, and the obtained distribution curve of the spliced signal intensity sum may be shown as f10 in fig. 10. In the distribution curve shown in fig. 10, the abscissa represents the sampling time, and the ordinate represents the standard signal intensity sum of the corresponding frequency interval at the corresponding sampling time.

Step S2622b, comparing whether the distribution curve of the signal intensity sum after the splicing exceeds the set second qualified range.

Specifically, a second qualification range may be stored in advance, and the second qualification range may be a region below a second qualification curve generated by the signal strength and the threshold value of each frequency interval at each sampling time.

Further, the signal strength and the threshold value in the present embodiment may be empirically set in advance.

In one example, the second pass range may also be determined according to steps S11100-S11600 as shown in FIG. 11.

Step S11100, obtaining standard sound signals played by at least one qualified loudspeaker; wherein the speaker under test and the at least one qualified speaker are driven by the same signal.

In step S11200, discrete short-time fourier transform is performed on the standard sound signal, so as to obtain a standard time-frequency sound signal corresponding to each sampling frequency.

The specific manner of performing step S11200 may refer to step S2200, and will not be described herein.

Step S11300, obtaining a second fundamental frequency of the standard sound signal, and performing filtering processing on the standard time-frequency sound signal of each sampling frequency based on the second fundamental frequency, so as to obtain a filtered standard time-frequency sound signal of each sampling frequency.

Step S11400, obtaining a distribution curve of the sum of standard signal intensities corresponding to each frequency interval according to the filtered standard time-frequency sound signal corresponding to the sampling frequency in each frequency interval.

Step S11500, the distribution curves of the standard signal intensity sum of all the frequency intervals are spliced, and the distribution curve of the spliced standard signal intensity sum is obtained.

Specifically, the manner of splicing the distribution curves of the standard signal intensity sums of all the frequency intervals to obtain the distribution curve of the spliced standard signal intensity sums may refer to step S2621b in the foregoing embodiment, which is not described herein again.

And step S11600, determining the second qualified range according to the distribution curve of the sum of the spliced standard signal intensities.

Specifically, the manner of determining the second qualified range according to the distribution curve of the sum of the standard signal intensities after the splicing may refer to step S7500 in the foregoing embodiment, which is not described herein again.

Step S2623b, determining that the speaker to be tested has an abnormal sound fault when the distribution curve of the sum of the signal intensities after the splicing exceeds the second qualified range.

Specifically, the second qualified range may be integrated into the distribution curve of the sum of the signal intensities after the splicing, so as to obtain a comparison curve as shown in fig. 12.

As shown in fig. 12, the abscissa in the figure represents the sampling time, the ordinate represents the sum of signal intensities of the corresponding frequency interval at the corresponding sampling time, f12a represents the first qualified range of the first frequency interval, f12b represents the distribution curve of the sum of signal intensities of the first speaker after the splice, and f12c represents the distribution curve of the sum of signal intensities of the second speaker after the splice. As can be seen from fig. 12, the profile of the sum of the spliced signal intensities of the first speaker does not exceed the second acceptable range, and the profile of the sum of the spliced signal intensities of the second speaker exceeds the second acceptable range.

Thus, the first speaker does not have a foreign sound malfunction and the second speaker has a foreign sound malfunction.

In this embodiment, by splicing the distribution curves of the standard signal intensity sum of all the frequency intervals, and then judging whether the speaker has an abnormal sound fault according to the obtained distribution curve of the standard signal intensity sum after splicing, the number of qualified ranges for detecting the abnormal sound fault can be reduced, the detection process can be accelerated, and the judging efficiency of the abnormal sound fault can be improved.

Corresponding to the method, the invention also provides a detection device of the loudspeaker. Fig. 13 is a block schematic diagram of an implementation structure of a detection device of a speaker according to the present invention.

According to fig. 13, the detection device includes a first acquisition module 13100, a first transformation module 13200, a first filtering module 13300, a segmentation module 13400, a calculation module 13500, and a judgment module 13600. The first acquisition module 13100 is configured to acquire a sound signal played by a speaker to be tested; the first transform module 13200 is configured to perform discrete short-time fourier transform on the sound signal to obtain a time-frequency sound signal corresponding to each sampling frequency; the time-frequency sound signal comprises signal intensity at each sampling time corresponding to the sampling frequency; the first filtering module 13300 is configured to obtain a first fundamental frequency of the sound signal, and perform filtering processing on a time-frequency sound signal of each sampling frequency based on the first fundamental frequency, so as to obtain a filtered time-frequency sound signal of each sampling frequency; the dividing module 13400 is configured to divide all sampling frequencies according to a preset frequency interval to obtain a plurality of frequency intervals; the calculating module 13500 is configured to calculate a signal strength sum of the sampling frequency in the frequency interval at the corresponding sampling time according to the filtered time-frequency sound signal corresponding to the sampling frequency in the frequency interval; the judging module 13600 is configured to judge whether the speaker to be tested has a abnormal sound fault according to the signal strength and the signal strength.

In one embodiment of the present invention, the first filtering module 13300 is further configured to: and determining the sampling frequency corresponding to the maximum signal intensity according to the time-frequency sound signal of each sampling frequency as the first fundamental wave frequency.

In one embodiment of the present invention, the filtered time-frequency sound signal is obtained by the following formula:

y[n]＝b[0]x[n]+b[1]x[n-1]-a[1]y[n-1]

In one embodiment of the present invention, the judging module 13600 further includes a curve determining unit 13610 and a judging unit 13620 as shown in fig. 14. The curve determining unit 13610 is configured to determine a distribution curve of signal intensity sums corresponding to frequency intervals according to the signal intensity sums; the judging unit 13620 is configured to judge whether the speaker to be tested has a abnormal sound fault according to the distribution curve of the sum of the signal intensities.

In one embodiment of the present disclosure, the judging unit 13620 further includes a range determining subunit 13621a, a first comparing subunit 13622a, and a first judging subunit 13623a as shown in fig. 15. The range determination subunit 13621a is configured to determine, from all the first qualified ranges stored in advance, a first qualified range corresponding to the distribution curve of the signal intensity sum according to a frequency interval corresponding to the distribution curve of the signal intensity sum; the first comparing subunit 13622a is configured to compare whether the distribution curve of the sum of signal intensities exceeds a corresponding first acceptable range; the first judging subunit 13623a is configured to judge that the speaker to be tested has a abnormal sound fault when the distribution curve of the sum of signal intensities corresponding to N frequency intervals exceeds a corresponding first qualified range, where N is a positive integer.

On this basis, the detection apparatus may further include a second acquisition module 1101, a second transformation module 1102, a second filtering module 1103, a first curve determination module 1104, and a first range determination module 1105 as shown in fig. 15. The second obtaining module 1101 is configured to obtain a standard sound signal played by at least one qualified speaker; wherein the speaker to be tested and at least one qualified speaker are driven by the same signal; the second transformation module 1102 is configured to perform discrete short-time fourier transformation on the standard sound signal to obtain a standard time-frequency sound signal corresponding to each sampling frequency; the standard time-frequency sound signal comprises standard signal intensity corresponding to the sampling frequency at each sampling time; the second filtering module 1103 is configured to obtain a second fundamental frequency of the standard sound signal, and perform filtering processing on the standard time-frequency sound signal of each sampling frequency based on the second fundamental frequency, so as to obtain a filtered standard time-frequency sound signal of each sampling frequency; the first curve determining module 1104 is configured to obtain a distribution curve of a sum of standard signal intensities corresponding to each frequency interval according to a standard time-frequency sound signal corresponding to a sampling frequency in each frequency interval; the first range determining module 1105 is configured to determine a first qualified range corresponding to each frequency interval according to the distribution curve of the sum of standard signal strengths.

Specifically, the first qualified range includes a distribution curve of the sum of all standard signal intensities of the corresponding frequency intervals.

In one embodiment of the present disclosure, the judging unit 13620 further includes a splicing subunit 13621b, a second comparing subunit 13622b, and a second judging subunit 13623b as shown in fig. 16, where the splicing subunit 13621b is configured to splice the distribution curves of the signal intensity sums of all frequency intervals to obtain a distribution curve of the spliced signal intensity sums; the second comparing subunit 13622b is configured to compare whether the distribution curve of the sum of signal intensities after the splicing exceeds a set second acceptable range; the second judging subunit 13623b is configured to judge that the speaker to be tested has a abnormal sound fault when the distribution curve of the sum of the signal intensities after the splicing exceeds the second acceptable range.

On this basis, the detection apparatus may further include a third acquisition module 1601, a third transformation module 1602, a third filtering module 1603, a second curve determination module 1604, a splicing module 1605, and a second range determination module 1606 as shown in fig. 16. The third acquiring module 1601 is configured to acquire a standard sound signal played by at least one qualified speaker; wherein the speaker to be tested and the at least one qualified speaker are driven by the same signal; the third transformation module 1602 is configured to perform discrete short-time fourier transformation on the standard sound signal to obtain a standard time-frequency sound signal corresponding to each sampling frequency; the standard time-frequency sound signal comprises standard signal intensity corresponding to sampling frequency at each sampling time; the third filtering module 1603 is configured to obtain a second fundamental frequency of the standard sound signal, and perform filtering processing on the standard time-frequency sound signal of each sampling frequency based on the second fundamental frequency, so as to obtain a filtered standard time-frequency sound signal of each sampling frequency; the second curve determining module 1604 is configured to obtain a distribution curve of a standard signal intensity sum corresponding to each frequency interval according to the filtered standard time-frequency sound signal corresponding to the sampling frequency in each frequency interval; the splicing module 1605 is used for splicing the distribution curves of the standard signal intensity sum of all frequency intervals to obtain the distribution curve of the spliced standard signal intensity sum; the second range determining module 1606 is configured to determine the second acceptable range according to the distribution curve of the sum of the standard signal intensities after the splicing.

The embodiments described above mainly focus on differences from other embodiments, but it should be clear to a person skilled in the art that the embodiments described above may be used alone or in combination with each other as desired.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are referred to each other, and each embodiment is mainly described as different from other embodiments, but it should be apparent to those skilled in the art that the above embodiments may be used alone or in combination with each other as required. In addition, for the device embodiment, since it corresponds to the method embodiment, description is relatively simple, and reference should be made to the description of the corresponding part of the method embodiment for relevant points. The system embodiments described above are merely illustrative, in that the modules illustrated as separate components may or may not be physically separate.

The present invention may be an apparatus, method and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present invention.

The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.

The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.

Computer program instructions for carrying out operations of the present invention may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information for computer readable program instructions, which can execute the computer readable program instructions.

Various aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are all equivalent.

The foregoing description of embodiments of the invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvement of the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.

Claims

1. A method for detecting a speaker, comprising:

collecting a sound signal played by a speaker to be tested;

2. The method of detecting according to claim 1, wherein the acquiring the first fundamental frequency of the sound signal includes:

3. The method of claim 1, wherein the filtered time-frequency sound signal is obtained by the following formula:

y[n]＝b[0]x[n]+b[1]x[n-1]-a[1]y[n-1]

4. The method according to claim 1, wherein the step of determining whether the speaker to be tested has a abnormal sound fault based on the signal strength comprises:

5. The method according to claim 4, wherein the step of judging whether the speaker to be tested has an abnormal sound fault according to the distribution curve of the sum of the signal intensities comprises:

determining a first qualified range corresponding to the distribution curve of the signal intensity sum from the prestored first qualified range according to a frequency interval corresponding to the distribution curve of the signal intensity sum;

comparing whether the distribution curve of the signal intensity sum exceeds a corresponding first qualified range;

6. The method of detecting according to claim 5, further comprising:

7. The method of claim 6, wherein the first acceptable range includes a distribution curve of a sum of all standard signal intensities corresponding to a frequency bin.

8. The method according to claim 4, wherein the step of judging whether the speaker to be tested has an abnormal sound fault according to the distribution curve of the sum of the signal intensities comprises:

9. The method of detection of claim 8, further comprising: obtaining standard sound signals played by at least one qualified loudspeaker; wherein the speaker to be tested and the at least one qualified speaker are driven by the same signal;

10. A detection device for a speaker, comprising: