A method and system for predicting the temperature rise of a moving coil loudspeaker

Abstract

An embodiment of the present invention provides a method and system for predicting the temperature rise of a moving coil loudspeaker. For a target loudspeaker, the impedance factor of the loudspeaker is introduced, and the first predicted temperature rise of the equal-pressure single-frequency input signal at each frequency is predicted by combining the frequency-domain signal IN(i) after Fourier transform, which effectively reflects the relationship between the predicted temperature rise and the frequency of the input signal. On the basis of the first predicted temperature rise, a cascaded filter bank function Hs(s) is constructed to correct the impedance value Rf(i) at each frequency, and the second predicted temperature rise of the equal-pressure single-frequency input signal at each frequency is predicted by combining the frequency-domain signal IN(i), reducing the influence of forced convection introduced by the large diaphragm displacement amplitude in the low-frequency band and the eddy current effect in the high-frequency band on the voice coil temperature rise, and greatly improving the accuracy of the voice coil temperature rise prediction of the moving coil loudspeaker.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of voice coil temperature control, and in particular to a method and system for predicting the temperature rise of a moving coil loudspeaker. Background Art

[0002] For traditional Smart PA (intelligent power amplifier), the temperature of the speaker can be calculated through IV feedback, but this is only a post-feedback, and the timeliness of temperature control is not high. If the temperature of the speaker can be predicted in advance, the temperature protection of the speaker can be carried out in time, which is very useful for both Smart PA (intelligent power amplifier) and PA (power amplifier).

[0003] By using the thermal model of the moving coil loudspeaker to analogize the analog circuit equation of the circuit and sorting it out, the thermal model filter of the loudspeaker can be obtained. By inputting the real-time power P of the thermal model analog circuit into the thermal model filter, the real-time temperature rise output corresponding to the voice coil can be obtained.

[0004] For equal-amplitude input signals of different frequencies, if the power is calculated based on the rated resistance of the speaker, since the voltage amplitude and the resistance are the same, the calculated power is the same across the entire frequency band. Then, the temperature rise of the voice coil output by the above thermal model filter is equal, that is, the predicted temperature rise of constant-voltage signals of different frequencies is the same across the entire frequency band, which does not match the actual temperature rise. Summary of the Invention

[0005] Therefore, the embodiments of the present invention provide a method and system for predicting the temperature rise of a moving coil loudspeaker to solve the technical problem that for equal-amplitude input signals of different frequencies, the predicted temperature rise obtained by calculating the power based on the rated resistance of the speaker is the same across the entire frequency band, which does not match the actual temperature rise.

[0006] To achieve the above object, the embodiments of the present invention provide the following technical solutions:

[0007] According to the first aspect of the embodiments of the present invention, the embodiments of the present application provide a method for predicting the temperature rise of a moving coil loudspeaker. The method is applied to a thermal model analog circuit, and the method includes:

[0008] For a target loudspeaker, input equal-voltage single-frequency signals of different preset frequencies into the thermal model analog circuit;

[0009] Detect the actual temperature rise data of each preset frequency equal-voltage single-frequency signal, and generate the first relationship curve between the actual temperature rise T m (i) and the frequency of the corresponding single-frequency signal;

[0010] Based on the impedance curve filter model of the moving coil loudspeaker, obtain the impedance value Rf(i) of each frequency equal-voltage single-frequency signal;

[0011] Receive isobaric single-frequency input signals of different frequencies, perform time-frequency conversion through Fourier transform to obtain a frequency-domain signal IN(i);

[0012] Use the impedance value Rf(i) and the frequency-domain signal IN(i) to predict the first predicted temperature rise of the isobaric single-frequency input signals at each frequency

[0013] Use the first predicted temperature rise at the same frequency point and the actual temperature rise T m (i), combined with the ambient temperature T a to obtain the filter gain coefficient g;

[0014] Use the cut-off frequency f of the analysis frequency point and the sampling rate fs of the input signal to obtain the pre-distortion tangent value K;

[0015] Based on the filter gain coefficient g and the pre-distortion tangent value K, construct a cascaded filter bank function Hs(s);

[0016] Use the cascaded filter bank function Hs(s) to correct the impedance value Rf(i) at each frequency to obtain the corrected impedance value Rf(i) at each frequency adjusted ; and

[0017] Use the corrected impedance value Rf(i) adjusted and the frequency-domain signal IN(i) to predict the second predicted temperature rise of the isobaric single-frequency input signals at each frequency

[0018] Furthermore, the thermal model analog circuit includes: voice coil thermal resistance R tv , voice coil heat capacity C tv , magnetic system thermal resistance R tm , magnetic system heat capacity C tm , the voice coil thermal resistance R tv and the voice coil heat capacity C tv are in parallel, the magnetic system thermal resistance R tm and the magnetic system heat capacity C tm are in parallel, the power input terminal of the magnetic system thermal resistance R tm and the magnetic system heat capacity C tm is connected to the power output terminal of the voice coil thermal resistance R tv , the power output terminals of the voice coil heat capacity C tv , the magnetic system thermal resistance R tm , the magnetic system heat capacity C tm are connected together, and the power output terminal of the magnetic system thermal resistance R tm is grounded.

[0019] Furthermore, the calculation formula for the impedance value Rf(i) is:

[0020]

[0021]

[0022] s = j·ω = j·2πf

[0023] where i is the analysis frequency point index, Rf(i) is the impedance value at the i-th frequency point, s is the complex frequency domain variable, Z(s) is the complex frequency domain representation of the impedance curve, fs is the input signal sampling rate, f is the analog frequency value of the analysis frequency point, j is the imaginary unit, N is the Fourier transform length, R e is the DC resistance, R ms is the mechanical impedance, M ms is the vibration mass, C ms is the mechanical compliance, and Bl is the magnetic conversion factor.

[0024] Furthermore, the first predicted temperature rise of the isobaric single-frequency input signal at each frequency is predicted by using the impedance value Rf(i) and the frequency domain signal IN(i). It includes:

[0025] Calculate the first real-time power P 1 (i), and the calculation formula of the first real-time power P 1 (i) is:

[0026]

[0027] where N is the Fourier transform length, i is the analysis frequency point index, IN(0) is the DC component signal of the input signal, IN(i) is the frequency domain signal after time-frequency conversion of the input time-domain signal at the i-th frequency point, and Rf(0) is the DC resistance value;

[0028] Based on the first real-time power P 1 (i), calculate the first predicted temperature rise The first predicted temperature rise The calculation formula is:

[0029]

[0030] where R tv is the voice coil thermal resistance, C tv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

[0031] Furthermore, the calculation formula of the filter gain coefficient g is:

[0032]

[0033] Among them, T a is the ambient temperature.

[0034] Furthermore, the calculation formula for the pre-distortion tangent value K is:

[0035]

[0036] Among them, f is the cut-off frequency of the analysis frequency point, and fs is the sampling rate of the input signal.

[0037] Furthermore, based on the filter gain coefficient g and the pre-distortion tangent value K, a cascaded filter bank function Hs(s) is constructed, including:

[0038] Based on the filter gain coefficient g and the pre-distortion tangent value K, the first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2 are calculated respectively. The first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2 are respectively:

[0039]

[0040]

[0041]

[0042]

[0043]

[0044] Among them, Q is the filter quality factor;

[0045] Using the first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2, the cascaded filter bank function Hs(s) is obtained. The calculation formula for the cascaded filter bank function Hs(s) is:

[0046]

[0047]

[0048] Among them, s is the complex frequency domain variable, i is the filter index value in the filter bank, and Hs(s) is the filter system function.

[0049] Further, the impedance values Rf(i) at each frequency are corrected using the cascaded filter bank function Hs(s) to obtain the corrected impedance values Rf(i) at each frequency adjusted , including:

[0050] The impedance values Rf(i) at each frequency are corrected using the cascaded filter bank function Hs(s) to obtain the corrected impedance values Rf(i) at each frequency adjusted , the corrected impedance values Rf(i) at each frequency adjusted The correction formula is:

[0051]

[0052] Z adjusted (s) = Z(s) · Hs(s)

[0053] where i is the analysis frequency point index, s is the complex frequency domain variable, Z adjusted (s) is the complex frequency domain representation of the corrected impedance curve, Z(s) is the complex frequency domain representation of the impedance curve before correction, fs is the input signal sampling rate, j is the imaginary unit, and N is the Fourier transform length

[0054] Further, the second predicted temperature rise of the equal-pressure single-frequency input signal at each frequency is predicted using the corrected impedance value Rf(i) adjusted and the frequency domain signal IN(i) , including:

[0055] The second real-time power P adjusted (i) is calculated using the corrected impedance value Rf(i) 2 and the frequency domain signal IN(i). The calculation formula for the second real-time power P 2 (i) is:

[0056]

[0057] where N is the Fourier transform length, i is the analysis frequency point index, IN(0) is the DC component signal of the input signal, IN(i) is the frequency domain signal after time-frequency conversion of the input time domain signal at the i-th frequency point, and Rf(0) adjusted is the corrected DC resistance value

[0058] The second predicted temperature rise is calculated based on the second real-time power P′(i) The calculation formula for the second predicted temperature rise is:

[0059]

[0060] where R tv is the voice coil thermal resistance, Ctv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

[0061] According to the second aspect of the embodiments of the present invention, an embodiment of the present application provides a moving coil loudspeaker temperature rise prediction system, which is applied to a thermal model analog circuit. The system includes:

[0062] An actual temperature rise detection module, configured to input an isobaric single-frequency signal with different preset frequencies to the thermal model analog circuit for a target loudspeaker; detect the actual temperature rise data of each preset frequency isobaric single-frequency signal, and generate an actual temperature rise T m (i) and the first relationship curve between the frequencies of the corresponding single-frequency signals;

[0063] An impedance calculation module, configured to obtain the impedance value Rf(i) of each frequency isobaric single-frequency signal based on the impedance curve filter model of the moving coil loudspeaker;

[0064] A receiving module, configured to receive isobaric single-frequency input signals with different frequencies, perform time-frequency conversion through Fourier transform, and obtain a frequency domain signal IN(i);

[0065] A first temperature rise prediction module, configured to predict the first predicted temperature rise of each frequency isobaric single-frequency input signal by using the impedance value Rf(i) and the frequency domain signal IN(i)

[0066] A cascade filter bank function construction module, configured to use the first predicted temperature rise and the actual temperature rise T m (i), combined with the ambient temperature T a to obtain a filter gain coefficient g; use the analysis frequency point simulation frequency f and the input signal sampling rate fs to obtain a pre-distortion tangent value K; based on the filter gain coefficient g and the pre-distortion tangent value K, construct a cascade filter bank function Hs(s);

[0067] An impedance correction module, configured to correct the impedance value Rf(i) of each frequency by using the cascade filter bank function Hs(s) to obtain a corrected impedance value Rf(i) of each frequency adjusted ; and

[0068] A second temperature rise prediction module, configured to predict the second predicted temperature rise of each frequency isobaric single-frequency input signal by using the corrected impedance value Rf(i) adjusted and the frequency domain signal IN(i)

[0069] According to a third aspect of an embodiment of the present invention, there is provided a moving coil loudspeaker temperature rise prediction device, the device comprising: a processor and a memory;

[0070] The memory is used for storing one or more program instructions;

[0071] The processor is configured to run one or more program instructions for performing the steps of a moving coil loudspeaker temperature rise prediction method as described in any one of the above.

[0072] According to a fourth aspect of an embodiment of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of a moving coil loudspeaker temperature rise prediction method as described in any one of the above are implemented.

[0073] Compared with the prior art, a moving coil loudspeaker temperature rise prediction method and system provided by an embodiment of the present application introduce an impedance factor of a loudspeaker for a target loudspeaker, and use an impedance value Rf(i) to combine with a frequency-domain signal IN(i) after Fourier transform to predict a first predicted temperature rise of an isobaric single-frequency input signal at each frequency. Effectively reflects the relationship between the predicted temperature rise and the input signal frequency. Based on the first predicted temperature rise a cascade filter bank function Hs(s) is constructed, and the impedance value Rf(i) at each frequency is corrected by using the cascade filter bank function Hs(s), and the corrected impedance value Rf(i) adjusted and the frequency-domain signal IN(i) are used to predict a second predicted temperature rise of an isobaric single-frequency input signal at each frequency. Reduces the influence of forced convection introduced by a large diaphragm displacement amplitude in the low-frequency band and the eddy current effect in the high-frequency band on the voice coil temperature rise, and greatly improves the accuracy of the moving coil loudspeaker voice coil temperature rise prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, without creative efforts, other implementation drawings can be obtained according to the provided drawings.

[0075] The structures, ratios, sizes, etc. illustrated in this specification are only used to cooperate with the content disclosed in the specification for those skilled in this technology to understand and read, and are not used to limit the implementation conditions of the present invention. Therefore, they do not have substantial technical significance. Any modification of the structure, change in the ratio relationship, or adjustment of the size, without affecting the efficacy and purpose that the present invention can achieve, should still fall within the scope covered by the technical content disclosed in the present invention.

[0076] Figure 1 It is a schematic diagram of the logical structure of a moving coil loudspeaker temperature rise prediction system provided by an embodiment of the present invention;

[0077] Figure 2 It is a schematic diagram of the process of a moving coil loudspeaker temperature rise prediction method provided by an embodiment of the present invention;

[0078] Figure 3 It is a schematic diagram of the process of the basic thermal model analog circuit of a moving coil loudspeaker provided by an embodiment of the present invention;

[0079] Figure 4 It is a curve graph of the predicted temperature rise and the actual temperature rise of equal - pressure single - frequency signals at each frequency under constant resistance provided by an embodiment of the present invention;

[0080] Figure 5 It is a curve graph of the first predicted temperature rise and the actual temperature rise of equal - pressure single - frequency signals at each frequency provided by an embodiment of the present invention;

[0081] Figure 6 It is a curve graph of the second predicted temperature rise and the actual temperature rise of equal - pressure single - frequency signals at each frequency provided by an embodiment of the present invention. Specific Embodiments

[0082] The following specific embodiments illustrate the implementation manners of the present invention. Those skilled in this technology can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope protected by the present invention.

[0083] The purpose of this application is as follows: Embodiments of the present invention provide a moving coil loudspeaker temperature rise prediction method and system. Based on the thermal model filter of the moving coil loudspeaker, impedance factors are introduced. At the same time, by constructing a cascaded filter bank function, full - frequency band prediction of the voice coil temperature rise is performed to solve the technical problem that the predicted temperature rise does not match the actual temperature rise.

[0084] To solve the above - mentioned technical problems, as Figure 1As shown in the figure, an embodiment of the present application provides a moving coil loudspeaker temperature rise prediction system, which is applied to a thermal model analog circuit, and specifically includes: an actual temperature rise detection module 1, an impedance calculation module 2, a receiving module 3, a first temperature rise prediction module 4, a cascaded filter bank function construction module 5, an impedance correction module 6, and a second temperature rise prediction module 7.

[0085] Further, the actual temperature rise detection module 1 is used to input an isobaric single-frequency signal with different preset frequencies to the thermal model analog circuit for the target loudspeaker; detect the actual temperature rise data of each isobaric single-frequency signal with the preset frequency, and generate the actual temperature rise T m (i) The first relationship curve with the frequency of the corresponding single-frequency signal.

[0086] The impedance calculation module 2 is used to obtain the impedance value Rf(i) of each frequency isobaric single-frequency signal based on the impedance curve filter model of the moving coil loudspeaker.

[0087] The receiving module 3 is used to receive the isobaric single-frequency input signals with different frequencies, perform time-frequency conversion through Fourier transform to obtain the frequency-domain signal IN(i); the first temperature rise prediction module 4 uses the impedance value Rf(i) and the frequency-domain signal IN(i) to predict the first predicted temperature rise of each frequency isobaric single-frequency input signal

[0088] The cascaded filter bank function construction module 5 is used to use the first predicted temperature rise at the same frequency point And the actual temperature rise T m (i), combined with the ambient temperature T a To obtain the filter gain coefficient g; use the analysis frequency point analog frequency f and the input signal sampling rate fs to obtain the pre-distortion tangent value K; based on the filter gain coefficient g and the pre-distortion tangent value K, construct the cascaded filter bank function Hs(s).

[0089] The impedance correction module 6 is used to correct the impedance value Rf(i) of each frequency by using the cascaded filter bank function Hs(s) to obtain the corrected impedance value Rf(i) of each frequency adjusted .

[0090] The second temperature rise prediction module 7 is used to use the corrected impedance value Rf(i) adjusted And the frequency-domain signal IN(i) to predict the second predicted temperature rise of each frequency isobaric single-frequency input signal

[0091] Compared with the prior art, a moving coil loudspeaker temperature rise prediction system provided by an embodiment of the present application introduces the impedance factor of the loudspeaker for the target loudspeaker, and uses the impedance value Rf(i) combined with the frequency-domain signal IN(i) after Fourier transform to predict the first predicted temperature rise of each frequency isobaric single-frequency input signal Effectively reflects the relationship between the predicted temperature rise and the input signal frequency. Based on the first predicted temperature rise , a cascaded filter bank function Hs(s) is constructed. The impedance value Rf(i) of each frequency is corrected using the cascaded filter bank function Hs(s), and the second predicted temperature rise of the isobaric single-frequency input signal of each frequency is predicted using the corrected impedance value Rf(i) adjusted and the frequency-domain signal IN(i). Reduces the influence of forced convection introduced by the large diaphragm displacement amplitude in the low-frequency band and the eddy current effect in the high-frequency band on the voice coil temperature rise, and greatly improves the accuracy of the voice coil temperature rise prediction of the moving coil loudspeaker.

[0092] Corresponding to the above-disclosed temperature rise prediction system of a moving coil loudspeaker, an embodiment of the present invention also discloses a temperature rise prediction method for a moving coil loudspeaker. The following details a temperature rise prediction method for a moving coil loudspeaker disclosed in an embodiment of the present invention in combination with the above-described temperature rise prediction system of a moving coil loudspeaker.

[0093] As Figure 2 shown, the following details the specific steps of a temperature rise prediction method for a moving coil loudspeaker provided in an embodiment of the present application.

[0094] A temperature rise prediction method for a moving coil loudspeaker provided in an embodiment of the present application is applied to a thermal model analog circuit. Referring to Figure 3 , the thermal model analog circuit specifically includes: voice coil thermal resistance R tv , voice coil heat capacity C tv , magnetic system thermal resistance R tm , magnetic system heat capacity C tm . The voice coil thermal resistance R tv and the voice coil heat capacity C tv are in parallel. The magnetic system thermal resistance R tm and the magnetic system heat capacity C tm are in parallel. The power input end of the magnetic system thermal resistance R tm and the magnetic system heat capacity C tm is connected to the power output end of the voice coil thermal resistance R tv . The power output ends of the voice coil heat capacity C tv , the magnetic system thermal resistance R tm , and the magnetic system heat capacity C tm are connected. The power output end of the magnetic system thermal resistance R tm is grounded.

[0095] According to the analogy relationship between power and current, temperature difference and voltage, heat capacity and capacitance, and thermal resistance and resistance, the analogy circuit equation of Figure 3 can be obtained as follows:

[0096]

[0097] Among them, Rtv is the voice coil thermal resistance, C tv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

[0098] After arrangement, the thermal model filter of the loudspeaker is obtained, and the model formula of the thermal model filter is as follows:

[0099]

[0100] The input of this thermal model filter is the real-time power P, and the output is the real-time temperature rise T corresponding to the voice coil vc .

[0101] In the embodiment of the present invention, for the target loudspeaker, isobaric single-frequency signals with different preset frequencies are input into the thermal model analog circuit.

[0102] The actual temperature rise detection module 1 detects the actual temperature rise data of each preset frequency isobaric single-frequency signal and generates the actual temperature rise T m (i) The first relationship curve between the corresponding single-frequency signal frequency.

[0103] Specifically, the above steps specifically include: capturing the actual temperature rise data and the corresponding power data of each preset frequency isobaric single-frequency signal; extracting the steady-state temperature of each frequency from the actual temperature rise data, and thus obtaining the actual temperature transfer function curve of the isobaric single-frequency signal, that is, the actual temperature rise T m (i) The first relationship curve between the corresponding single-frequency signal frequency.

[0104] For isochoric input signals with different frequencies, if the power is calculated based on the rated resistance of the loudspeaker, since the voltage amplitude and the resistance are the same, the calculated power is consistent across the entire frequency band. Then, the temperature rise of the voice coil output by the above thermal model filter is equal, that is, the predicted temperature rise of constant-voltage signals with different frequencies is the same across the entire frequency band, which does not match the actual temperature rise. The curve graphs of the predicted temperature rise and the actual temperature rise of isobaric single-frequency signals with different frequencies under constant resistance are as Figure 4 shown.

[0105] In order to reflect the corresponding relationship between the temperature rise and the frequency, the impedance curve factor of the loudspeaker is introduced. The impedance calculation module 2 obtains the impedance value Rf(i) of each frequency isobaric single-frequency signal based on the impedance curve filter model of the moving coil loudspeaker.

[0106] Specifically, the impedance curve filter model formula of the moving coil loudspeaker is:

[0107]

[0108] s = j·ω = j·2πf

[0109] Among them, s is the complex frequency domain variable, Z(s) is the complex frequency domain representation of the impedance curve, f is the simulated frequency value of the analysis frequency point, j is the imaginary unit, ω is the simulated angular frequency of the analysis frequency point, R e is the DC resistance, R ms is the mechanical impedance, M ms is the vibration mass, C ms is the mechanical compliance, and Bl is the magnetic conversion factor.

[0110] Furthermore, the calculation formula for the impedance value Rf(i) is:

[0111]

[0112] Among them, i is the analysis frequency point index, Rf(i) is the impedance value at the i-th frequency point, fs is the input signal sampling rate, j is the imaginary unit, and N is the Fourier transform length.

[0113] The receiving module 3 receives isobaric single-frequency input signals of different frequencies, performs time-frequency conversion through Fourier transform, and obtains the frequency domain signal IN(i).

[0114] The first temperature rise prediction module 4 uses the impedance value Rf(i) and the frequency domain signal IN(i) to predict the first predicted temperature rise of the isobaric single-frequency input signals of each frequency

[0115] Specifically, the above steps specifically include: calculating the first real-time power P 1 (i), and the calculation formula for the first real-time power P 1 (i) is:

[0116]

[0117] Among them, N is the Fourier transform length, i is the analysis frequency point index, IN(0) is the DC component signal of the input signal, IN(i) is the frequency domain signal after time-frequency conversion of the input time domain signal at the i-th frequency point, and Rf(0) is the DC resistance value;

[0118] Based on the first real-time power P 1 (i), calculate the first predicted temperature rise The first predicted temperature rise The calculation formula for is:

[0119]

[0120] Among them, R tv is the voice coil thermal resistance, C tv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

[0121] After calculating the real-time power according to the above formula and feeding it into the thermal model filter, the first predicted temperature rise in this case is obtained. It is no longer fixed across the entire frequency band, but shows a negative correlation with impedance. The comparison of the curves of the first predicted temperature rise and the actual temperature rise of the equal-pressure single-frequency signals at each frequency is as Figure 5 shown.

[0122] Figure 5 There are still significant differences between the curves of the first predicted temperature rise and the actual temperature rise in []. The main reason is that in the low-frequency band, forced convection is introduced due to the large diaphragm displacement amplitude, and there is an eddy current effect in the high-frequency band. These different phenomena all affect the temperature rise process of the voice coil. To address this, a simulation model is established by cascading filter banks.

[0123] The cascaded filter bank function construction module 5 uses the first predicted temperature rise at the same frequency point and the actual temperature rise T m (i), combined with the ambient temperature T a to obtain the filter gain coefficient g.

[0124] Specifically, the calculation formula for the filter gain coefficient g is:

[0125]

[0126] where T a is the ambient temperature.

[0127] The cascaded filter bank function construction module 5 uses the analysis frequency point simulation frequency f and the input signal sampling rate fs to obtain the pre-distortion tangent value K.

[0128] Specifically, the calculation formula for the pre-distortion tangent value K is:

[0129]

[0130] where f is the analysis frequency point simulation frequency and fs is the input signal sampling rate.

[0131] The cascaded filter bank function construction module 5 constructs the cascaded filter bank function Hs(s) based on the filter gain coefficient g and the pre-distortion tangent value K.

[0132] Specifically, the above steps specifically include: based on the filter gain coefficient g and the pre-distortion tangent value K, calculating the first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2 respectively. The first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2 are respectively:

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] Among them, Q is the filter quality factor;

[0139] Using the first filter coefficient a0, the second filter coefficient a1, the third filter coefficient a3, the fourth filter coefficient b1, and the fifth filter coefficient b2, the cascaded filter bank function Hs(s) is obtained. The calculation formula of the cascaded filter bank function Hs(s) is:

[0140]

[0141]

[0142] Among them, s is the complex frequency domain variable, i is the filter index value in the filter bank, and Hs(s) is the filter system function.

[0143] The impedance correction module 6 uses the cascaded filter bank function Hs(s) to correct the impedance value Rf(i) at each frequency, and obtains the corrected impedance value Rf(i) at each frequency adjusted .

[0144] Specifically, the above steps specifically include: using the cascaded filter bank function Hs(s) to correct the impedance value Rf(i) at each frequency, and obtaining the corrected impedance value Rf(i) at each frequency adjusted , the corrected impedance value Rf(i) at each frequency adjusted The correction formula is:

[0145]

[0146] Z adjusted (s) = Z(s) · Hs(s)

[0147] Among them, i is the analysis frequency point index, s is the complex frequency domain variable, Z adjusted (s) is the complex frequency domain representation of the corrected impedance curve, Z(s) is the complex frequency domain representation of the impedance curve before correction, fs is the input signal sampling rate, j is the imaginary unit, and N is the Fourier transform length.

[0148] The second temperature rise prediction module 7 uses the corrected impedance value Rf(i) adjustedThe second predicted temperature rise of each frequency isobaric single-frequency input signal is obtained by predicting the sum-frequency domain signal IN(i).

[0149] Specifically, the above steps specifically include: using the corrected impedance value Rf(i) adjusted and the sum-frequency domain signal IN(i) to calculate the second real-time power P 2 (i). The calculation formula of the second real-time power P 2 (i) is:

[0150]

[0151] where N is the Fourier transform length, i is the analysis frequency point index, IN(0) is the DC component signal of the input signal, IN(i) is the frequency domain signal after time-frequency conversion of the input time-domain signal at the i-th frequency point, and Rf(0) adjusted is the corrected DC resistance value;

[0152] Calculate the second predicted temperature rise based on the second real-time power P′(i) The second predicted temperature rise The calculation formula is:

[0153]

[0154] where R tv is the voice coil thermal resistance, C tv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

[0155] At this time, the curve comparison between the second predicted temperature rise and the actual temperature rise of each frequency isobaric single-frequency signal is as Figure 6 shown. Figure 6 The maximum relative error between the second predicted temperature rise and the actual temperature rise is controlled at about 5%.

[0156] Compared with the prior art, a method for predicting the temperature rise of a moving coil loudspeaker provided by an embodiment of the present application introduces the impedance factor of the loudspeaker for the target loudspeaker, and uses the impedance value Rf(i) combined with the frequency domain signal IN(i) after Fourier transform to predict the first predicted temperature rise of each frequency isobaric single-frequency input signal which effectively reflects the relationship between the predicted temperature rise and the input signal frequency. On the basis of the first predicted temperature rise , a cascade filter bank function Hs(s) is constructed, and the impedance value Rf(i) of each frequency is corrected by using the cascade filter bank function Hs(s). The second predicted temperature rise of each frequency isobaric single-frequency input signal is predicted by using the corrected impedance value Rf(i) adjusted and the frequency domain signal IN(i). It reduces the influence of forced convection introduced by the large diaphragm displacement amplitude in the low-frequency band and the eddy current effect in the high-frequency band on the temperature rise of the voice coil, and greatly improves the accuracy of predicting the temperature rise of the voice coil of the moving coil loudspeaker.

[0157] In addition, an embodiment of the present invention further provides a moving coil loudspeaker temperature prediction device, and the device includes: a processor and a memory; the memory is used to store one or more program instructions; the processor is used to run one or more program instructions to execute the steps of a moving coil loudspeaker temperature rise prediction method as described in any one of the above.

[0158] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of a moving coil loudspeaker temperature rise prediction method as described in any one of the above are implemented.

[0159] In an embodiment of the present invention, the processor may be an integrated circuit chip with signal processing capabilities. The processor may be a general-purpose processor, a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0160] It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention may be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The processor reads the information in the storage medium and combines its hardware to complete the steps of the above method.

[0161] The storage medium may be a memory, for example, it may be a volatile memory or a non-volatile memory, or may include both a volatile memory and a non-volatile memory.

[0162] Among them, the non-volatile memory can be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash memory.

[0163] The volatile memory can be a Random Access Memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

[0164] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0165] Those skilled in the art should be able to realize that, in one or more of the above examples, the functions described in the present invention can be implemented by a combination of hardware and software. When applying software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. The computer-readable medium includes computer storage media and communication media, where the communication media includes any medium that facilitates the transfer of a computer program from one place to another. The storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0166] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it on the basis of the present invention, which will be obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of the present invention claimed.

Claims

1. A method for predicting the temperature rise of a moving coil loudspeaker, characterized in that, The method is applied to a thermal model analog circuit, and the method includes: For the target loudspeaker, an isobaric single-frequency signal with different preset frequencies is input into the thermal model analog circuit; the actual temperature rise data of each isobaric single-frequency signal with a preset frequency is detected to generate the actual temperature rise T m (i) The first relationship curve between the corresponding single-frequency signal frequency Based on the impedance curve filter model of a moving coil loudspeaker, obtaining the impedance value Rf(i) of an isobaric single-frequency signal at each frequency; Receiving isobaric single-frequency input signals of different frequencies, performing time-frequency conversion through Fourier transform, and obtaining the frequency-domain signal IN(i); The first predicted temperature rise of the isobaric single-frequency input signal at each frequency is predicted using the impedance value Rf(i) and the frequency-domain signal IN(i). Using the first predicted temperature rise at the same frequency point and the actual temperature rise T m (i), combined with the ambient temperature T a to obtain the filter gain coefficient g; Using the analysis frequency point analog frequency f and the input signal sampling rate fs to obtain the pre-distortion tangent value K; Based on the filter gain coefficient g and the pre-distortion tangent value K, constructing a cascaded filter bank function Hs(s); The impedance values Rf(i) at each frequency are corrected by using the cascaded filter bank function Hs(s) to obtain the corrected impedance values Rf(i) at each frequency adjusted ; and Using the corrected impedance value Rf(i) adjusted and the predicted second predicted temperature rise of the isobaric single-frequency input signal at each frequency obtained from the frequency-domain signal IN(i) 2. The method for predicting the temperature rise of a moving coil loudspeaker according to claim 1, characterized in that, The thermal model analog circuit includes: voice coil thermal resistance R tv , voice coil heat capacity C tv , magnetic system thermal resistance R tm , magnetic system heat capacity C tm . The voice coil thermal resistance R tv and the voice coil heat capacity C tv are in parallel. The magnetic system thermal resistance R tm and the magnetic system heat capacity C tm are in parallel. The power input terminal of the magnetic system thermal resistance R tm and the magnetic system heat capacity C tm is connected to the power output terminal of the voice coil thermal resistance R tv . The power output terminals of the voice coil heat capacity C tv , the magnetic system thermal resistance R tm , and the magnetic system heat capacity C tm are connected to each other. The power output terminal of the magnetic system thermal resistance R tm is grounded.

3. The method for predicting the temperature rise of a moving coil loudspeaker according to claim 2, wherein, The calculation formula for the impedance value Rf(i) is: S = j·ω = j·2πf Among them, i is the analysis frequency point index, Rf(i) is the impedance value at the i-th frequency point, s is the complex frequency domain variable, Z(s) represents the complex frequency domain of the speaker impedance curve, fs is the input signal sampling rate, f is the analog frequency value of the analysis frequency point, j is the imaginary unit, N is the Fourier transform length, R e is the DC resistance, R ms is the mechanical impedance, M ms is the moving mass, C ms is the mechanical compliance, and Bl is the magnetic force conversion factor.

4. The method for predicting the temperature rise of a moving coil loudspeaker according to claim 3, wherein, Predicting a first predicted temperature rise of the isobaric single-frequency input signals at each frequency by using the impedance value Rf(i) and the frequency-domain signal IN(i). Comprising: Calculate the first real-time power P using the impedance value Rf(i) and the frequency-domain signal IN(i). 1 (i), where the calculation formula for the first real-time power P 1 (i) is as follows: where N is the length of the Fourier transform, i is the analysis frequency point index, IN(0) is the DC component signal of the input signal, IN(i) is the frequency-domain signal after time-frequency conversion of the input time-domain signal at the i-th frequency point, and Rf(0) is the DC resistance value; Based on the first real-time power P 1 (i) Calculate the first predicted temperature rise The first predicted temperature rise The calculation formula is as follows: Among them, R tv is the voice coil thermal resistance, C tv is the voice coil heat capacity, R tm is the magnetic system thermal resistance, C tm is the magnetic system heat capacity, and s is the complex frequency domain variable.

5. The method for predicting the temperature rise of a moving coil loudspeaker according to claim 4, characterized in that, The calculation formula for the filter gain coefficient g is: Among them, T a is the ambient temperature.

6. The temperature rise prediction method of a moving coil loudspeaker according to claim 5, wherein, The calculation formula for the pre-distortion tangent value K is: where f is the analysis frequency point analog frequency and fs is the input signal sampling rate.

7. A moving coil loudspeaker temperature rise prediction system, characterized in that The system is applied to a thermal model analog circuit, and the system includes: An actual temperature rise detection module is configured to input isobaric single-frequency signals with different preset frequencies into a thermal model analog circuit for a target speaker, detect actual temperature rise data of the isobaric single-frequency signals at each preset frequency, and generate an actual temperature rise T m (i) a first relationship curve between the actual temperature rise and the frequency of the corresponding single-frequency signal; An impedance calculation module, configured to obtain the impedance value Rf(i) of an isobaric single-frequency signal at each frequency based on the impedance curve filter model of a moving coil loudspeaker; A receiving module, configured to receive isobaric single-frequency input signals of different frequencies, perform time-frequency conversion through Fourier transform, and obtain the frequency-domain signal IN(i); The first temperature rise prediction module is used to predict the first predicted temperature rise of the isobaric single-frequency input signal at each frequency by using the impedance value Rf(i) and the frequency-domain signal IN(i). The cascade filter bank function construction module is used to use the first predicted temperature rise at the same frequency point and the actual temperature rise T m (i), combined with the ambient temperature T a to obtain the filter gain coefficient g; use the analysis frequency point cut-off frequency f and the input signal sampling rate fs to obtain the pre-distortion tangent value K; based on the filter gain coefficient g and the pre-distortion tangent value K, construct the cascade filter bank function Hs(s); An impedance correction module, configured to correct the impedance value Rf(i) at each frequency by using the cascaded filter bank function Hs(s) to obtain the corrected impedance value Rf(i) at each frequency adjusted ; and The second temperature rise prediction module is used to utilize the corrected impedance value Rf(i) adjusted and the frequency-domain signal IN(i) to predict the second predicted temperature rise of each frequency isobaric single-frequency input signal

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