Thermal runaway detection method, device and equipment, storage medium and program product

Abstract

The invention relates to the technical field of fault detection, and discloses a thermal runaway detection method, device and equipment, a storage medium and a program product. According to the method, initial delay summation output corresponding to a plurality of grid points is obtained through a multiple signal classification algorithm to serve as an iteration initial value, a plurality of sound source positions can be effectively positioned, a sound source recognition result is sharpened through multiple iterations, the main lobe width is reduced, side lobe interference is attenuated, the detection resolution is improved, and the detection accuracy is improved. The initial delay summation output corresponding to the multiple grid points is screened through the preset screening condition, the initial delay summation output which does not meet the preset screening condition is replaced with the preset value to directly serve as the output result, the output result does not participate in the subsequent iteration process, the calculation amount can be reduced, the detection efficiency can be improved, and therefore the thermal runaway detection accuracy can be improved when the thermal runaway detection function is achieved. And the resolution ratio and the efficiency are high.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fault detection, in particular to a thermal runaway detection method, device, equipment, storage medium and program product. BACKGROUND

[0002] Due to problems such as electrical abuse and improper thermal management, thermal runaway often occurs in lithium batteries, which poses a great safety hazard. During the thermal runaway process, a large amount of gas is generated in the lithium battery, and the internal pressure increases rapidly. When the gas pressure exceeds the pressure threshold of the pressure relief valve, the pressure relief valve opens to discharge the gas. Before and after the pressure relief valve opens, the sound amplitude at each frequency increases significantly, so the energy change of the frequency amplitude can be used to determine whether the battery has experienced thermal runaway. The sound source detection technology has the advantages of non-contact, strong instantaneity, strong anti-interference ability, high sensitivity, etc., and it is highly feasible to use sound source signal detection to detect thermal runaway of energy storage batteries.

[0003] In related technologies, sound data is captured by a sensor array, and then a beamforming algorithm is used to delay, weight, sum, and calculate the sound data to obtain the spatial position of the sound source, so as to locate the sound source and further locate the position of the fault module. However, this method has low resolution and insufficient detection accuracy when detecting the sound source of low-frequency signals. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a thermal runaway detection method, device, equipment, storage medium and program product to solve the problem of low resolution and insufficient detection accuracy when detecting the sound source in related technologies.

[0005] In a first aspect, the present application provides a thermal runaway detection method, which comprises: acquiring a plurality of sound signals of a target lithium battery on a sound source focusing grid surface; the plurality of sound signals are respectively collected by a plurality of sensors in a sensor array; the sound source focusing grid surface comprises a plurality of grid points; According to the plurality of sound signals, the initial delay-and-sum outputs corresponding to the plurality of grid points are calculated by a multiple signal classification algorithm; The initial delay-and-sum outputs corresponding to the plurality of grid points are filtered by a preset filtering condition, and the initial delay-and-sum outputs that do not meet the preset filtering condition are replaced with a preset value as the output result; otherwise, the initial delay-and-sum output is taken as the current delay-and-sum output; searching for a main lobe peak value from the current delay-and-sum output and calculating the contribution corresponding to the main lobe peak value; The contribution corresponding to the main lobe peak value is removed from the current delay-and-sum output to obtain an updated current delay-and-sum output; determining whether the updated current delay-sum output meets an iteration termination condition; if yes, obtaining an output result according to the updated current delay-sum output corresponding to each grid point; if no, taking the updated current delay-sum output as a current delay-sum output, and returning to the step of searching for the main-lobe peak value from the current delay-sum output; obtaining a thermal runaway acoustic source positioning result according to the output result.

[0006] In an optional implementation, the step of obtaining the initial delay-sum output corresponding to each grid point from the plurality of sound signals through a multiple signal classification algorithm comprises: grouping the plurality of sound signals into a sound vector, and calculating a current cross-spectral matrix of the sound vector; performing eigenvalue decomposition on the current cross-spectral matrix of the sound vector to obtain a noise subspace of the sound vector; calculating the initial delay-sum output corresponding to each grid point based on the noise subspace and a steering vector of the sound vector.

[0007] In an optional implementation, the step of removing the contribution of the main-lobe peak value from the current delay-sum output to obtain an updated current delay-sum output comprises: removing the contribution of the main-lobe peak value from the current cross-spectral matrix to obtain an updated current cross-spectral matrix; updating the current delay-sum output according to the updated current cross-spectral matrix to obtain the updated current delay-sum output.

[0008] In an optional implementation, the step of removing the contribution of the main-lobe peak value from the current cross-spectral matrix to obtain an updated current cross-spectral matrix comprises: searching for the main-lobe peak value from the current delay-sum output, and calculating a direction vector and a weighting vector of the main-lobe peak value; the direction vector / weighting vector is related to the distance between the main-lobe peak value position and the sensor; calculating a current coherent source component of the sound vector according to the current cross-spectral matrix, the weighting vector, and the current delay-sum output; calculating the contribution of the main-lobe peak value according to the current delay-sum output and the current coherent source component; removing the contribution of the main-lobe peak value from the current cross-spectral matrix to obtain an updated current cross-spectral matrix; the step of updating the current delay-sum output according to the updated current cross-spectral matrix to obtain the updated current delay-sum output comprises: The current delay-sum output is updated by using the updated current cross-spectrum matrix and the weight vector corresponding to each grid point except the main lobe peak position, to obtain an updated current delay-sum output.

[0009] In an optional implementation, the judging whether the updated current delay-sum output meets the iteration termination condition comprises: judging whether the norm of the updated current cross-spectrum matrix is not less than the norm of the previous current cross-spectrum matrix, and if yes, determining that the iteration termination condition is met; otherwise, determining that the iteration termination condition is met.

[0010] In an optional implementation, the obtaining the output result according to the updated current delay-sum output of each grid point comprises: After the contribution of the main lobe peak is calculated, the beamforming of the current round is calculated according to the contribution of the main lobe peak and is stored. The beamformings of the current round and previous rounds are summed to obtain a beamforming summation value. For the grid point meeting the preset screening condition, if the updated current delay-sum output meets the iteration termination condition, the beamforming summation value and the updated current delay-sum output are added as the output result. For the grid point not meeting the preset screening condition, if the updated current delay-sum output meets the iteration termination condition, the preset value is taken as the output result.

[0011] In a second aspect, the present application provides a thermal runaway detection device, which comprises: a signal acquisition module, configured to acquire a plurality of sound signals of a target lithium battery on a sound source focusing grid surface; the plurality of sound signals are respectively collected by a plurality of sensors in a sensor array; the sound source focusing grid surface comprises a plurality of grid points; a delay summation module, configured to calculate initial delay summation outputs respectively corresponding to the plurality of grid points by using a multiple signal classification algorithm according to the plurality of sound signals; a screening module, configured to screen the initial delay summation outputs respectively corresponding to the plurality of grid points by using a preset screening condition, replace the initial delay summation output not meeting the preset screening condition with a preset value as an output result; otherwise, take the initial delay summation output as a current delay summation output; a main lobe searching module, configured to search a main lobe peak from the current delay summation output and calculate a contribution corresponding to the main lobe peak; a delay updating module, configured to remove the contribution corresponding to the main lobe peak from the current delay summation output to obtain an updated current delay summation output; a judging module configured to judge whether the updated current delay-sum output meets an iteration termination condition; if yes, obtain an output result according to the updated current delay-sum output corresponding to each grid point; if no, take the updated current delay-sum output as a current delay-sum output, and return to the step of searching for the main lobe peak value from the current delay-sum output; a positioning module configured to obtain a thermal runaway acoustic source positioning result according to the output result.

[0012] In a third aspect, the present application provides a computer device, comprising a memory and a processor, the memory and the processor are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the thermal runaway detection method in the first aspect or any of the corresponding embodiments thereof.

[0013] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make a computer execute the thermal runaway detection method in the first aspect or any of the corresponding embodiments thereof.

[0014] In a fifth aspect, the present application provides a computer program product, which comprises computer instructions, and the computer instructions are used to make a computer execute the thermal runaway detection method in the first aspect or any of the corresponding embodiments thereof.

[0015] The technical solution provided by the present application can include the following beneficial effects: The thermal runaway detection method provided by the present application can effectively locate multiple acoustic source positions by taking the initial delay-sum outputs corresponding to multiple grid points respectively as iteration initial values, and can clearly identify the acoustic source recognition result through multiple iterations, reduce the main lobe width, attenuate the sidelobe interference, improve the detection resolution, and filter the initial delay-sum outputs corresponding to the multiple grid points respectively through a preset filtering condition, replace the initial delay-sum outputs not meeting the preset filtering condition with a preset value, thereby reducing the calculation amount and improving the detection efficiency, and further improving the resolution and efficiency when the thermal runaway detection function is implemented. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creating any inventive labor.

[0017] Figure 1 is a flowchart of the thermal runaway detection method according to an embodiment of the present application; Figure 2 is a flowchart of another thermal runaway detection method according to an embodiment of the present application; Figure 3 is a schematic diagram of a beamforming sound source identification space according to an embodiment of the present application; Figure 4 is a flowchart of a thermal runaway detection method according to an embodiment of the present application; Figure 5 is a positioning error fold line graph of different algorithms under different signal-to-noise ratios according to an embodiment of the present application; Figure 6 is a 100Hz double sound source positioning simulation result graph according to an embodiment of the present application; Figure 7 is a 200Hz double sound source positioning simulation result graph according to an embodiment of the present application; Figure 8 is a 300Hz double sound source positioning simulation result graph according to an embodiment of the present application; Figure 9 is a 600Hz double sound source positioning simulation result graph according to an embodiment of the present application; Figure 10 is a positioning error graph of different algorithms according to an embodiment of the present application; Figure 11 is a structural block diagram of a thermal runaway detection device according to an embodiment of the present application; Figure 12 is a hardware structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person skilled in the art without creative work fall within the protection scope of the present application.

[0019] Electrochemical energy storage technology boasts advantages such as large capacity, wide adaptability, high efficiency, and durability, and its development is relatively mature. Among them, lithium iron phosphate batteries are widely used due to their high energy density, stable performance, and low cost. However, due to issues such as power abuse and improper thermal management, lithium batteries frequently experience thermal runaway, posing significant safety hazards. During thermal runaway, the lithium battery generates a large amount of gas, causing a rapid increase in internal pressure. When the gas pressure exceeds the pressure threshold of the pressure relief valve, the valve opens to release the gas. Before and after the pressure relief valve opens, except for changes in sound energy at a few frequencies such as 100Hz and 200Hz, the spectral distribution characteristics of sound signals in other frequency bands do not change significantly, but the sound amplitude at each frequency increases significantly. After an explosion or fire, sound fluctuations are obvious, and the frequency changes of the sound signal are significant. Before the explosion, the sound energy is mainly concentrated in the 1kHz range, while after the explosion, the sound energy is more concentrated in the 1~20kHz wide frequency band. Therefore, changes in the energy of the frequency amplitude can be used to determine whether a battery has experienced thermal runaway.

[0020] Sound source detection technology boasts advantages such as non-contact operation, strong immediacy, high anti-interference capability, and high sensitivity, making it highly feasible to detect thermal runaway in energy storage batteries using sound source signals. In related technologies, sound data is captured by a sensor array, and then beamforming algorithms are used to perform delay, weighting, and summation calculations on the sound data to obtain the spatial location of the sound source, thereby pinpointing the sound source. Simultaneously, a microphone array synchronously acquires image data. The calculated spatial location of the sound source is fused with the image to obtain acoustic imaging, making the sound visible. This allows for direct monitoring of the faulty module's location and effective early warning of dangerous situations such as lithium battery fires and explosions.

[0021] However, the above-mentioned scheme has problems such as low resolution and insufficient detection accuracy when performing sound source localization detection on low-frequency signals.

[0022] According to an embodiment of the present invention, a method for detecting thermal runaway is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0023] This embodiment provides a thermal runaway detection method, which can be used in desktop computers, laptops, servers, etc. Figure 1 This is a flowchart of a thermal runaway detection method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Acquire multiple sound signals of the target lithium battery on the sound source focusing grid surface.

[0024] The multiple sound signals are respectively collected by multiple sensors in a sensor array, which can be sensors with sound signal collection function, such as microphones. The sound source focusing grid plane is discretely obtained from the sound source calculation plane, and the sound source focusing grid plane includes multiple grid points. The plane where the sensor array is located can be parallel to the sound source focusing grid plane, and each sensor has a corresponding coordinate vector in the sound source focusing grid plane.

[0025] In step S102, according to the multiple sound signals, the initial delay-and-sum outputs corresponding to the multiple grid points are obtained by a multiple signal classification algorithm.

[0026] The multiple sound signals collected are processed by a multiple signal classification algorithm. Based on the orthogonal property of signal and noise subspaces, a minimum value exists in the sound source signal due to the existence of noise. Therefore, the sound source signal can be accurately separated from the mixed signal of the multiple sound signals by searching for the spectral peak value, and the specific position of the sound source can also be accurately determined for low-frequency signals, thereby obtaining the initial delay-and-sum outputs corresponding to the multiple grid points.

[0027] In step S103, the initial delay-and-sum outputs corresponding to the multiple grid points are filtered by a preset filtering condition. The initial delay-and-sum outputs that do not meet the preset filtering condition are replaced by a preset value as the output result; otherwise, the initial delay-and-sum output is taken as the current delay-and-sum output.

[0028] Since the calculation amount required for identifying the multiple grid points one by one is large and the efficiency is low, the initial delay-and-sum outputs corresponding to the multiple grid points are filtered by setting a preset filtering condition. The initial delay-and-sum outputs that meet the preset filtering condition are retained, and the initial delay-and-sum outputs that do not meet the preset filtering condition are replaced by a preset value as the output result; otherwise, the initial delay-and-sum output is taken as the current delay-and-sum output. That is, for the grid points that meet the preset filtering condition, the initial delay-and-sum output of the grid point is taken as the current delay-and-sum output of the grid point; for the grid points that do not meet the preset filtering condition, the preset value is taken as the output result of the grid point and does not participate in subsequent calculation, so that only the current delay-and-sum outputs corresponding to the grid points that meet the preset filtering condition participate in subsequent calculation, the calculation amount is reduced, the current delay-and-sum outputs corresponding to the grid points that do not meet the preset filtering condition are avoided to interfere with the calculation, and the efficiency and accuracy of the thermal runaway detection are improved.

[0029] In step S104, the main lobe peak value is searched from the current delay-and-sum output, and the contribution corresponding to the main lobe peak value is calculated.

[0030] Since the sound source position detected by the sound source detection technology in the related art has a large main lobe and corresponding side lobes, which affects the accuracy of sound source positioning, the main lobe peak value can be searched out from the current delay and sum output based on the association of the side lobe with the plate making, and the contribution corresponding to the main lobe peak value is calculated for subsequent calculation.

[0031] In step S105, the contribution corresponding to the main lobe peak value is removed from the current delay and sum output to obtain an updated current delay and sum output.

[0032] After calculating the contribution corresponding to the main lobe peak value, the contribution corresponding to the main lobe peak value can be removed from the current delay and sum output to clarify the interference of the side lobe, thereby clarifying the sound source positioning result and obtaining a clean beam. The updated current delay and sum output is not affected by the main lobe peak value.

[0033] In step S106, it is judged whether the updated current delay and sum output meets the iteration termination condition; if yes, the output result is obtained according to the updated current delay and sum output corresponding to each grid point; if no, the updated current delay and sum output is taken as the current delay and sum output, and the step of searching the main lobe peak value from the current delay and sum output is returned.

[0034] It is judged whether the updated current delay and sum output meets the iteration termination condition, and the iteration termination condition is used to indicate whether all side lobes have been searched.

[0035] The iteration of each round includes steps S104 to S106. If the iteration termination condition is not met, the updated current delay and sum output of the current round needs to be taken as the current delay and sum output of the next round, and step S104 is returned for iteration of the next round. Steps S104 to S106 are re-executed until the iteration termination condition is met, and the output result is obtained according to the updated current delay and sum output corresponding to each grid point in each round.

[0036] In step S107, the thermal runaway sound source positioning result is obtained according to the output result.

[0037] The positioning information is included in the output result, so that the thermal runaway sound source positioning result can be obtained according to the output result, the thermal runaway of the target lithium battery is positioned, and the related technical personnel can timely perform battery maintenance according to the thermal runaway sound source positioning result, so as to avoid safety hazards.

[0038] The heat run-away detection method provided by the embodiment can effectively locate multiple sound source positions by taking the initial delay-and-sum outputs corresponding to the multiple grid points as iteration initial values, and can clearly identify the sound source by multiple iterations, reduce the main lobe width, attenuate the sidelobe interference, improve the detection resolution, and replace the initial delay-and-sum outputs that do not meet the preset screening condition with preset values as output results directly, so as to reduce the calculation amount and improve the detection efficiency. Therefore, the heat run-away detection function is realized with high resolution and high efficiency.

[0039] A heat run-away detection method is provided in the embodiment, which can be used in the mobile terminal such as a mobile phone, a tablet computer, a desktop computer, a notebook computer, a server, etc. Figure 2 The flowchart of the heat run-away detection method according to the embodiment of the present application is shown in FIG. 2, which includes the following steps: Figure 2 The flowchart of the heat run-away detection method according to the embodiment of the present application is shown in FIG. 2, which includes the following steps: In step S201, multiple sound signals of a target lithium battery on a sound source focusing grid plane are acquired.

[0040] The multiple sound signals are respectively collected by multiple sensors in a sensor array. The sound source focusing grid plane includes multiple grid points, and each grid point is a focusing point.

[0041] For example, Figure 3 The beamforming sound source identification space schematic diagram according to the embodiment of the present application is shown in FIG. 1, which includes a sensor array composed of multiple sensors in the plane of x-axis and y-axis, and the sound source focusing grid plane is perpendicular to the z-axis direction of the plane. The sound source focusing grid plane includes M grid points, and r n (n=1, 2, …, N) is the coordinate vector of the nth sensor, N is the total number of sensors, and r is the coordinate vector of the sound source focusing grid plane.

[0042] In step S202, the initial delay-and-sum outputs corresponding to the multiple grid points are calculated by a multiple signal classification algorithm according to the multiple sound signals.

[0043] Specifically, the multiple sound signals are first combined into a sound vector, the current cross-spectrum matrix of the sound vector is calculated, the current cross-spectrum matrix of the sound vector is then subjected to eigenvalue decomposition to calculate the noise subspace of the sound vector, and the initial delay-and-sum outputs corresponding to the multiple grid points are calculated based on the noise subspace and the steering vector of the sound vector.

[0044] Optionally, when the multiple sound signals are combined into a sound vector, the sound signals are first transformed from time domain to frequency domain by Fourier transform to obtain frequency domain sound signals . Then, the frequency domain sound signals are combined into a sound vector The sound vector is composed of the sound signals measured by each sensor, and the current cross-spectrum matrix of the sound vector is calculated

[0045] where the superscript represents the conjugate transpose.

[0046] Next, the current cross-spectrum matrix is subjected to a matrix eigenvalue calculation to perform eigenvalue decomposition on the current cross-spectrum matrix , and the formula is as follows:

[0047] where each column of is an eigenvector of the cross-spectrum matrix , and is a diagonal matrix of eigenvalues.

[0048] Finally, the eigenvalues of the M grid points in the current cross-spectrum matrix are obtained as to , and the M eigenvalues are arranged in descending order according to the size, that is:

[0049] Among these eigenvalues, the larger eigenvalues correspond to the calculation of the corresponding signal subspace , and the smaller eigenvalues correspond to the calculation of the corresponding noise subspace . The multiple signal classification algorithm uses the decomposition of the cross-spectrum matrix of the signal to obtain the characteristics of the signal and noise subspaces. Due to the orthogonal properties of the signal and noise subspaces, the sound source signal can be accurately separated from the mixed signal by searching for the spectral peak value. The calculation expression output by the multiple signal classification algorithm is as follows:

[0050] where contains the position information of the sound source signal, and is called a steering vector. In the above formula, the scalar product of the steering vector and the matrix corresponding to the noise subspace is taken as the denominator. When there is a sound source signal, the steering vector and each column of the noise matrix are orthogonal to each other, resulting in a denominator of zero. However, in actual measurement, the presence of noise causes the denominator to be non-zero, but has a minimum value, so that in the actual sound source map, the sound source signal will be significantly highlighted, achieving high-resolution identification of the sound source position through the multiple signal classification algorithm.

[0051] Then, the multiple signal classification algorithm is used for beamforming to obtain the initial value of the delay-and-sum output (initial delay-and-sum output)​ is:

[0052] and the current cross-spectrum matrix is taken as the initial value of the cross-spectrum matrix for subsequent iteration:

[0053] In step S203, the initial delay-sum output corresponding to each grid point is screened by a preset screening condition, and the initial delay-sum output that does not meet the preset screening condition is replaced by a preset value as the output result; otherwise, the initial delay-sum output is taken as the current delay-sum output.

[0054] Optionally, the preset screening condition is not less than a preset threshold, and the initial delay-sum output that is not less than the preset threshold is taken as the current delay-sum output of the corresponding grid point; otherwise, the initial delay-sum output is replaced by a preset value as the output result of the corresponding grid point.

[0055] For example, the preset threshold is set to , and the preset screening condition is:

[0056] If the preset screening condition is not met, the initial delay-sum output is replaced by a preset value as the output result of the corresponding grid point, as follows:

[0057] The preset value is much smaller than the preset threshold, i.e. . The preset threshold is used for iterative optimization in the result of the multiple signal classification algorithm to search for the sound source position, and the size of the preset threshold has a great influence on the search result, including the search main lobe width and the ability to attenuate side lobes.

[0058] In step S204, the main lobe peak value is searched from the current delay-sum output, and the contribution corresponding to the main lobe peak value is calculated.

[0059] First, the contribution of the main lobe peak value is removed from the current cross-spectrum matrix to obtain an updated current cross-spectrum matrix.

[0060] Specifically, the main lobe peak is searched from the current delay summation output, and the direction vector and weighting vector of the main lobe peak are calculated. The direction vector is related to the distance between the main lobe peak position and the sensor. The weighting vector is also related to the distance between the main lobe peak position and the sensor. Next, the current coherent source component of the sound vector is calculated based on the current cross-spectrum matrix, the weighting vector, and the current delay summation output. Then, the contribution of the main lobe peak is calculated based on the current delay summation output and the current coherent source component. The contribution of the main lobe peak is removed from the current cross-spectrum matrix to obtain the updated current cross-spectrum matrix.

[0061] Specifically, the direction vector is obtained based on the norm of the difference between the main lobe peak position and the sensor coordinate vector. Then, the square of the norm of this direction vector is calculated to obtain an intermediate value. Finally, the quotient of this direction vector and the intermediate value is calculated to obtain the weighted vector.

[0062] Optionally, the current cross-spectral matrix and the weighted vector are multiplied together and then divided by the current delay to obtain the current coherent source component of the sound vector.

[0063] Optionally, the contribution of the main lobe peak is obtained by multiplying the current delay summation output, the current coherent source component, and the conjugate transpose of the current coherent source component. The contribution of the main lobe peak is used to indicate the cross-spectral matrix generated by the grid points corresponding to the main lobe peak position.

[0064] Optionally, the contribution of the main lobe peak is multiplied by the cyclic gain to obtain the contribution gain value, and then the contribution gain value is subtracted from the current cross-spectral matrix to obtain the updated current cross-spectral matrix. The cyclic gain is generally set between 0 and 1.

[0065] For example, suppose the current delayed summation output is ,exist The iterative process is executed periodically. The summation is calculated from the current delay and output. Search for the main lobe peak value in the corresponding sound source image and calculate... Related direction vectors and weighted vector The formula is as follows:

[0066]

[0067] in, It is the first The main lobe peak position found in the second search With the One sensor Corresponding coordinate vector The distance between them, j is the imaginary unit, k is the wave number, k=2πf / c, f is the frequency, c is the speed of sound.

[0068] Next, since the sound source in real-world applications is not necessarily an ideal monopole point sound source, this embodiment assumes the main lobe peak position... The resulting cross-spectral matrix (i.e., the contribution of the main lobe peak) ) composed of a single coherent source component This leads to improved computational efficiency and resolution. The contribution of the main lobe peak is calculated. The formula is as follows:

[0069]

[0070] Next, update the current cross-spectral matrix (which was in the first iteration). In the i-th iteration, it is This yields the updated cross-spectral matrix after removing the influence of the main lobe peak. :

[0071] in, For cyclic gain, usually .

[0072] Step S205: Calculate and store the sharpened beam for the current round based on the contribution of the main lobe peak.

[0073] After calculating the contribution corresponding to the main lobe peak, the sharpening beam for the current round is calculated based on the contribution of the main lobe peak and the parameters used to determine the bandwidth, and stored according to the number of rounds.

[0074] For example, the sharpened beam obtained in each iteration is stored. :

[0075] in, These are parameters used to determine bandwidth.

[0076] Step S206: Remove the contribution corresponding to the main lobe peak from the current delay summation output to obtain the updated current delay summation output.

[0077] The current delay summation output is updated based on the updated current cross-spectral matrix to obtain the updated current delay summation output.

[0078] Specifically, the current delay summation output is updated by using the updated current cross-spectral matrix and the weighted vectors corresponding to each grid point except for the main lobe peak position, thus obtaining the updated current delay summation output.

[0079] The sound source positioning map is updated, and the contribution of the peak source is subtracted in the i-1th iteration process to obtain an updated current delay-sum output not affected by the peak

[0080] wherein, the weight vector corresponding to the grid point meeting the preset screening condition is

[0081]

[0082] wherein, the direction vector corresponding to the grid point meeting the preset screening condition is

[0083] In step S207, it is determined whether the updated current delay-sum output meets the iteration termination condition. If yes, an output result is obtained according to the updated current delay-sum output corresponding to each grid point. If no, the updated current delay-sum output is taken as the current delay-sum output, and the step of searching for the main lobe peak value from the current delay-sum output is returned.

[0084] Optionally, when the output result is obtained according to the updated current delay-sum output corresponding to each grid point, firstly, the beamforming beams in the current round and the previous rounds are summed to obtain a beamforming beam summation value. Then, for the grid point meeting the preset screening condition, if the updated current delay-sum output meets the iteration termination condition, the beamforming beam summation value (the sum of the beamforming beams stored in each round) and the updated current delay-sum output (the residual acoustic image) are added as the output result. For the grid point not meeting the preset screening condition, if the updated current delay-sum output meets the iteration termination condition, the preset value is taken as the output result.

[0085] Optionally, the iteration process includes steps S204 to S207. When it is determined whether the updated current delay-sum output meets the iteration termination condition, it is determined whether the norm of the updated current cross-spectrum matrix is not less than the norm of the previous current cross-spectrum matrix. If yes, it is determined that the iteration termination condition is met. Otherwise, it is determined that the iteration termination condition is not met, and the step of searching for the main lobe peak value from the current delay-sum output, i.e., step S204, is returned.

[0086] Optionally, the iteration termination condition is:

[0087] ​​​​I is the corresponding number of rounds of the last iteration calculation, that is, the iteration calculation is from the ith time to the Ith time, I+1 indicates the corresponding number of rounds of the iteration termination, that is, the I+1th time judges the iteration termination condition to meet the iteration termination condition.

[0088] The output result is:

[0089] Step S208, according to the output result, the thermal runaway sound source positioning result is obtained.

[0090] The output result has the recognized spatial position of the sound source. The output result can be image fused with the image data collected synchronously by the sensor array to obtain an acoustic imaging image, that is, the thermal runaway sound source positioning result. Thus, the fault module position of the lithium battery can be intuitively monitored to perform fault early warning on the lithium battery and effectively prevent dangerous situations such as fire of the lithium battery.

[0091] The thermal runaway detection method provided in the embodiment can effectively locate multiple sound source positions by taking the initial delay-and-sum outputs of multiple grid points as initial values of iteration, and clearly the sound source recognition result by multiple iterations, reduce the main lobe width, attenuate the sidelobe interference, and improve the detection resolution. The initial delay-and-sum outputs of the multiple grid points are filtered by the preset filtering condition, the initial delay-and-sum outputs that do not meet the preset filtering condition are replaced by a preset value as the output result directly, and do not participate in the subsequent iteration process. Thus, the calculation amount can be reduced, the detection efficiency can be improved, and the resolution and efficiency are high when the thermal runaway detection function is implemented.

[0092] As one or more specific application embodiments of the embodiment of the present application, the optimal implementation scheme or the scheme that the inventor wants to embody most is described below in combination with a specific application scenario.

[0093] For example, Figure 4 The flowchart is a thermal runaway detection method according to the embodiment of the present application. The present application adopts the CLEAN-SC-MUSIC algorithm to perform thermal runaway detection. Specifically, the initial delay-and-sum output is obtained by processing the collected sound signals by the MUSIC algorithm Then, it is judged whether the initial delay-and-sum output corresponding to each grid point is not less than a preset threshold value. If not, the is directly taken as the calculation result output; if yes, the main lobe peak value position and the corresponding current delay-and-sum output are searched, the direction vector and the weighting vector are calculated, the contribution of the main lobe peak value is calculated , and the updated cross-spectrum matrix is updated The output is the sum of the updated current delay, which is unaffected by the peak value of the main lobe in this round. Seeking a clearer beam The results are stored, and then it is determined whether the iteration termination condition is met. If yes, the calculation result is output; otherwise, the round number is incremented by 1, and the process of searching for the main lobe peak position is returned. The iteration process is repeated until the iteration termination condition is met.

[0094] For example, firstly, a focal point model is established on the sound source plane, and assumptions are made about the distribution of the sound source. A 112-channel spiral microphone array model is then established at a distance of 1.5m from the sound source plane. The sound source plane and the array plane are parallel, and the centers of the two planes are on the same straight line. In the simulation, a low signal-to-noise ratio condition for the reverberation environment is set, and the sharpening beamwidth is set to 0.02m. The cyclic gain α = 0.1. To verify the correctness of the algorithm design, the performance of four algorithms was compared under different signal-to-noise ratios (SNRs). The results of the sound source localization error comparison for the Delay Summation Beamforming Algorithm (DAS), Multi-Signal Classification Algorithm (MUSIC), Sharpening Beamforming Algorithm (CLEAN-SC), and the Multi-Signal Classification Sharpening Beamforming Algorithm (CLEAN-SC-MUSIC) used in this invention as a function of SNR are presented.

[0095] Figure 5 These are line graphs showing the positioning errors of different algorithms under different signal-to-noise ratios according to embodiments of the present invention. Figure 6 This is a simulation result diagram of 100Hz dual sound source localization according to an embodiment of the present invention; Figure 7 This is a simulation result diagram of 200Hz dual sound source localization according to an embodiment of the present invention; Figure 8 This is a simulation result diagram of 300Hz dual sound source localization according to an embodiment of the present invention; Figure 9 This is a simulation result of 600Hz dual sound source localization according to an embodiment of the present invention.

[0096] The four algorithms were compared and analyzed under several scenarios with a signal frequency of 500Hz and signal-to-noise ratios of -10, -5, 0, 5, 10, 15, and 20. The results are as follows: Figures 6-10It can be seen from the figure that under the low frequency signal of 500 Hz, the main lobe and side lobe of the DAS algorithm are completely fused, the positioning error changes slightly with the change of signal-to-noise ratio, and the anti-interference ability is the worst. With the increase of SNR, the positioning error of MUSIC algorithm, CLEAN-SC algorithm and CLEAN-SC-MUSIC algorithm gradually becomes smaller, and this situation is very obvious at 5dB, the positioning error is greatly reduced, and the positioning error of MUSIC algorithm and CLEAN-SC-MUSIC algorithm reaches the minimum value of 0.01m at 5dB, and the error minimum value of CLEAN-SC algorithm is 0.03m at 20dB. Among the four algorithms, the anti-interference ability of MUSIC algorithm and CLEAN-SC-MUSIC algorithm is the best, the anti-interference ability of CLEAN-SC algorithm is the second, and the anti-interference ability of DAS algorithm is the worst.

[0097] Next, the recognition effect of CLEAN-SC-MUSIC algorithm on multiple sound sources under the condition of low signal-to-noise ratio in reverberation environment is analyzed, the sound sources are set to two independent point sound sources with coordinates (-0.2m, 0m, 1.5m) and (0.1m, 0m, 1.5m), and the frequencies of the sound sources are 100Hz and 200Hz respectively. The dynamic range displayed is 30dB (0~-30dB).

[0098] Figure 6 Figures (a), (b), (c) and (d) correspond to the sound source positioning simulation results of DAS algorithm, MUSIC algorithm, CLEAN-SC algorithm and CLEAN-SC-MUSIC algorithm respectively. The given 100Hz double sound source positioning diagram, due to the characteristics of small sound source spacing, low frequency and poor resolution of DAS algorithm, the two sound sources are completely fused into a circular acoustic center, and the positioning result occupies the whole plane, which cannot be distinguished. The two sound sources are positioned by MUSIC algorithm, and the two sound source centers are fused. Moreover, the main lobe is wide, the side lobe is multiple, and the resolution is low. CLEAN-SC algorithm depends on the result of DAS algorithm as the initial value, because the main lobe of DAS algorithm is seriously fused, the result output is the maximum peak position of aliasing, which leads to the error positioning of CLEAN-SC algorithm to the maximum peak position. The CLEAN-SC-MUSIC algorithm takes the MUSIC algorithm result as the initial value, effectively locates the two sound source positions, and clearly identifies the sound source recognition result through multiple iterations, reduces the main lobe width, attenuates the side lobe interference, and has high resolution.

[0099] Figure 7The simulation results of the sound source positioning of (a), (b), (c) and (d) correspond to DAS algorithm, MUSIC algorithm, CLEAN-SC algorithm and CLEAN-SC-MUSIC algorithm respectively. In the given 200Hz double sound source positioning diagram, the MUSIC algorithm locates two sound source points, the main lobe width is reduced compared to 100Hz, the sound source center is slightly fused, there is a side lobe, and the resolution is low. The positioning result of the CLEAN-SC algorithm can only locate the acoustic center of the DAS algorithm result. The CLEAN-SC-MUSIC algorithm successfully locates the sound source position and has high resolution.

[0100] Figure 8 In the given 300Hz double sound source positioning diagram, the positioning results of each algorithm are roughly the same as those at 200Hz, the main lobe width of the DAS algorithm and the MUSIC algorithm is reduced, the CLEAN-SC-MUSIC algorithm successfully locates the sound source position and has high resolution.

[0101] Figure 9 The simulation results of the sound source positioning of (a), (b), (c) and (d) correspond to DAS algorithm, MUSIC algorithm, CLEAN-SC algorithm and CLEAN-SC-MUSIC algorithm respectively. In the given 200Hz double sound source positioning diagram, the MUSIC algorithm can locate two sound source points, there are many side lobes, and the resolution is low. The positioning result of the CLEAN-SC algorithm appears false sound source, because the number of peak values of the output result of the DAS algorithm is more than the number of target sound sources, which causes errors when the CLEAN-SC algorithm calculates the sound source position. The CLEAN-SC-MUSIC algorithm can effectively locate the sound source position.

[0102] The simulation results show that the traditional CLEAN-SC algorithm cannot effectively locate the sound source when the main lobe of the DAS algorithm output is severely fused, and the CLEAN-SC-MUSIC algorithm proposed in the application can better improve this defect, and compared with the MUSIC algorithm, the CLEAN-SC-MUSIC algorithm effectively attenuates the side lobe, has the highest resolution in a complex reverberation environment under low signal-to-noise ratio conditions, and has an advantage.

[0103] The positioning results of the double sound source positioning under several frequencies and different algorithms are analyzed, and the sound source positions (x, y) coordinates corresponding to the positioning results are shown in the following table: Table 1 is a related data table of the delay and sum beam forming algorithm DAS: Table 1: Related data table of the delay and sum beam forming algorithm DAS.

[0104]

[0105] Table 2 is a related data table of the multiple signal classification algorithm MUSIC: Table 2: Relevant data table of the multiple signal classification algorithm MUSIC.

[0106]

[0107] Table 3 is a relevant data table of the clean beamforming algorithm CLEAN-SC: Table 3: Relevant data table of the clean beamforming algorithm CLEAN-SC.

[0108]

[0109] Table 4 is a relevant data table of the multiple signal classification clean beamforming algorithm CLEAN-SC-MUSIC: Table 4: Relevant data table of the multiple signal classification clean beamforming algorithm CLEAN-SC-MUSIC.

[0110]

[0111] Table 1 is the sound source position calculated by the DAS algorithm, the main lobe width is large, reaching 1.6 m, occupying the entire grid plane, and the acoustic center of the main lobe of each sound source is seriously fused due to the large width, resulting in only one sound source point being displayed in the positioning result, and the positioning error of the left and right sound sources reaches 0.14~0.17 m; Table 2 is the sound source position calculated by the MUSIC algorithm, and the positioning error of the left and right sound sources is 0.01~0.03 m, because the positioning accuracy of the MUSIC algorithm is high, but the side lobe appears, and the sound source center is fused, the main lobe width becomes smaller and smaller with the increase of frequency, but it is still 0.21 m at the highest frequency of 600 Hz; Table 3 is the sound source position calculated by the CLEAN-SC algorithm, and the side lobe is attenuated in each iteration process, so the main lobe width is 0.02 m, but the positioning accuracy depends on the DAS output, resulting in large positioning error, and the positioning error of the left and right sound sources reaches 0.14~0.16 m at 100~300 Hz, and decreases with the increase of frequency, but at 600 Hz, the positioning error is still about 0.5 m; Table 4 is the sound source position calculated by the CLEAN-SC-MUSIC algorithm, which combines the advantages of the CLEAN-SC algorithm and the MUSIC algorithm, so that the main lobe width reaches 0.02 m, and the positioning error of the left and right sound sources is 0.01~0.03 m.

[0112] In order to more intuitively analyze the positioning accuracy of the algorithm, Figure 10Positioning error maps of different algorithms according to embodiments of the present application are shown in FIG. 6, which are used to measure the sound source recognition performance of each algorithm. The positioning error is the difference between the theoretical sound source point position and the actual measured sound source point position, which is defined as the positioning error, so as to quantify the positioning accuracy of the algorithm. It can be seen that the positioning error of the DAS algorithm is the largest, the positioning error of the CLEAN-SC algorithm under low frequency signal is consistent with that of the DAS algorithm, and gradually decreases with the increase of frequency, but the positioning error is still large at 600 Hz, the positioning errors of the CLEAN-SC-MUSIC algorithm and the MUSIC algorithm are consistent, and are less than or equal to 0.03 m, and the positioning error of the CLEAN-SC-MUSIC algorithm remains unchanged with the change of frequency. The above results show that the CLEAN-SC-MUSIC algorithm has small positioning error, high positioning accuracy under low frequency signal, and maintains a narrow acoustic center, and has the highest resolution among the four algorithms.

[0113] In this embodiment, a thermal runaway detection device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, which have been described and will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and contemplated.

[0114] The present embodiment provides a thermal runaway detection device, as shown in Figure 11 comprises: The signal acquisition module 1101 is configured to acquire a plurality of sound signals of a target lithium battery on a sound source focusing grid surface; the plurality of sound signals are respectively collected by a plurality of sensors in a sensor array; and the sound source focusing grid surface comprises a plurality of grid points. The delay sum module 1102 is configured to calculate initial delay sum outputs respectively corresponding to the plurality of grid points by a multiple signal classification algorithm according to the plurality of sound signals. The screening module 1103 is configured to screen the initial delay sum outputs respectively corresponding to the plurality of grid points by a preset screening condition, replace the initial delay sum outputs that do not meet the preset screening condition with a preset value as an output result; otherwise, replace the initial delay sum outputs with a current delay sum output. The main lobe searching module 1104 is configured to search for a main lobe peak value from the current delay sum output and calculate a contribution corresponding to the main lobe peak value. The delay updating module 1105 is configured to remove the contribution corresponding to the main lobe peak value from the current delay sum output to obtain an updated current delay sum output. The judging module 1106 is configured to judge whether the updated current delay-and-sum output meets an iteration termination condition; if yes, obtain an output result according to the updated current delay-and-sum output corresponding to each grid point; if no, take the updated current delay-and-sum output as a current delay-and-sum output, and return to the step of searching for the main lobe peak value from the current delay-and-sum output. The positioning module 1107 is configured to obtain a thermal runaway sound source positioning result according to the output result.

[0115] In an optional implementation, the delay-and-sum module is further configured to: compose a sound vector from the plurality of sound signals, and calculate a current cross-spectral matrix of the sound vector; perform eigenvalue decomposition on the current cross-spectral matrix of the sound vector, and obtain a noise subspace of the sound vector; based on the noise subspace and a steering vector of the sound vector, calculate initial delay-and-sum outputs corresponding to the plurality of grid points respectively.

[0116] In an optional implementation, the delay updating module is further configured to: remove the contribution of the main lobe peak value from the current cross-spectral matrix to obtain an updated current cross-spectral matrix; update the current delay-and-sum output according to the updated current cross-spectral matrix to obtain an updated current delay-and-sum output.

[0117] In an optional implementation, the delay updating module is further configured to: search for a main lobe peak value from the current delay-and-sum output, calculate a direction vector and a weighting vector of the main lobe peak value; the direction vector / weighting vector is related to the distance between the main lobe peak value position and the sensor; calculate a current coherent source component of the sound vector according to the current cross-spectral matrix, the weighting vector, and the current delay-and-sum output; calculate the contribution of the main lobe peak value according to the current delay-and-sum output and the current coherent source component; remove the contribution of the main lobe peak value from the current cross-spectral matrix to obtain an updated current cross-spectral matrix; The updating of the current delay-and-sum output according to the updated current cross-spectral matrix to obtain an updated current delay-and-sum output comprises: updating the current delay-and-sum output according to the updated current cross-spectral matrix and the weighting vector corresponding to each grid point except the main lobe peak value position to obtain the updated current delay-and-sum output.

[0118] In an optional implementation, the judging module is further configured to: The judging module is further configured to judge whether the norm of the updated current cross-spectrum matrix is not less than the norm of the previous current cross-spectrum matrix, and if yes, determine that the iteration termination condition is met; otherwise, determine that the iteration termination condition is met.

[0119] In an optional embodiment, the judging module is further configured to: After the contribution of the main lobe peak value is calculated, the beam in the current round is calculated according to the contribution of the main lobe peak value and stored. The beams in the current round and previous rounds are summed to obtain a sum of the beams. For the grid points satisfying the preset screening condition, if the updated current delay sum output meets the iteration termination condition, the sum of the beams is added to the updated current delay sum output as an output result. For the grid points not satisfying the preset screening condition, if the updated current delay sum output meets the iteration termination condition, the preset value is taken as the output result.

[0120] Further function descriptions of the above modules and units are the same as those of the corresponding embodiments, and will not be repeated here.

[0121] The thermal runaway detection device in the embodiment is in the form of a functional unit. The unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above functions.

[0122] The embodiment of the present application also provides a computer device having the above Figure 11 thermal runaway detection device.

[0123] Please refer to Figure 12 , Figure 12 is a structural schematic diagram of a computer device provided by an optional embodiment of the present application, as Figure 12As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 12 Take a processor 10 as an example.

[0124] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0125] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0126] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0127] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0128] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 can be connected by a bus or other means, Figure 12 The bus connection is taken as an example.

[0129] The input device 30 can receive inputted digital or character information, and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), a tactile feedback device (e.g., a vibration motor), etc. The display device includes, but is not limited to, a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0130] The embodiments of the present application also provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and stored in a local storage medium, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk or a solid state disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that the computer, processor, microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code, which, when accessed and executed by the computer, processor or hardware, implements the method shown in the above embodiments.

[0131] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present application can be called or provided. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source file, executable file, installation package file, etc., and accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0132] While embodiments of the present application have been described in conjunction with the appended drawings, various modifications and changes are possible within the spirit and scope of the present application, and such modifications and changes are intended to fall within the scope of the inventive concepts described herein.

Claims

1. A method for detecting thermal runaway, characterized in that, The method includes: Multiple sound signals from the target lithium battery at the sound source focusing grid surface are acquired; the multiple sound signals are collected by multiple sensors in a sensor array; the sound source focusing grid surface includes multiple grid points; Based on the multiple sound signals, the initial delay summation output corresponding to the multiple grid points is obtained by using a multi-signal classification algorithm; The initial delay summation outputs corresponding to the multiple grid points are filtered by preset filtering conditions. The initial delay summation outputs that do not meet the preset filtering conditions are replaced with preset values ​​as the output results; otherwise, the initial delay summation outputs are used as the current delay summation outputs. Search for the main lobe peak value from the current delay summation output, and calculate the contribution corresponding to the main lobe peak value; The contribution corresponding to the main lobe peak is removed from the current delay summation output to obtain the updated current delay summation output; Determine whether the updated current delay summation output meets the iteration termination condition; if yes, obtain the output result based on the updated current delay summation output corresponding to each grid point; if no, use the updated current delay summation output as the current delay summation output and return to the step of searching for the main lobe peak from the current delay summation output. Based on the output results, the location of the thermal runaway sound source is obtained.

2. The method according to claim 1, characterized in that, The step of obtaining the initial delay summation output corresponding to each of the multiple grid points based on the multiple sound signals using a multi-signal classification algorithm includes: The multiple sound signals are combined into a sound vector, and the current cross-spectral matrix of the sound vector is calculated. The noise subspace of the sound vector is obtained by performing eigenvalue decomposition on the current cross-spectral matrix of the sound vector. Based on the noise subspace and the guiding vector of the sound vector, the initial delay summation output corresponding to the plurality of grid points is calculated respectively.

3. The method according to claim 2, characterized in that, The step of removing the contribution corresponding to the main lobe peak from the current delay summation output to obtain the updated current delay summation output includes: The contribution of the main lobe peak is removed from the current cross-spectrum matrix to obtain the updated current cross-spectrum matrix; The current delay summation output is updated based on the updated current cross-spectral matrix to obtain the updated current delay summation output.

4. The method according to claim 3, characterized in that, The step of removing the contribution of the main lobe peak from the current cross-spectrum matrix to obtain the updated current cross-spectrum matrix includes: Search for the main lobe peak from the current delay summation output, and calculate the direction vector and weighted vector of the main lobe peak; the direction vector / weighted vector is related to the position of the main lobe peak and the distance between the sensor. Based on the current cross-spectral matrix, weighted vector, and current delay summation output, calculate the current coherent source component of the sound vector; The contribution of the main lobe peak is calculated based on the current delay summation output and the current coherent source component. The contribution of the main lobe peak is removed from the current cross-spectrum matrix to obtain the updated current cross-spectrum matrix; The step of updating the current delay summation output based on the updated current cross-spectrum matrix to obtain the updated current delay summation output includes: The updated current delay summation output is obtained by updating the current cross-spectral matrix and the weighted vectors corresponding to each grid point except the main lobe peak position.

5. The method according to claim 4, characterized in that, The step of determining whether the updated current delayed summation output meets the iteration termination condition includes: Determine whether the norm of the updated cross-spectral matrix is ​​not less than the norm of the unupdated cross-spectral matrix. If so, the iteration termination condition is met; otherwise, the iteration termination condition is met.

6. The method according to any one of claims 1 to 5, characterized in that, The output result is obtained by summing the updated current delays corresponding to each grid point, including: After calculating the contribution corresponding to the main lobe peak, the sharpening beam for the current round is calculated and stored based on the contribution of the main lobe peak. The sharpened beams of the current round and the previous rounds are summed to obtain the sharpened beam sum value; For grid points that meet the preset screening conditions, if the updated current delay summation output meets the iteration termination condition, the sharpened beam summation value is added to the updated current delay summation output as the output result. For grid points that do not meet the preset filtering conditions, if the updated current delay summation output meets the iteration termination condition, the preset value is used as the output result.

7. A thermal runaway detection device, characterized in that, The device includes: The signal acquisition module is used to acquire multiple sound signals of the target lithium battery on the sound source focusing grid surface; the multiple sound signals are collected by multiple sensors in the sensor array; the sound source focusing grid surface includes multiple grid points; The delay summation module is used to calculate the initial delay summation output corresponding to each of the multiple grid points based on the multiple sound signals using a multi-signal classification algorithm; The filtering module is used to filter the initial delay summation outputs corresponding to the multiple grid points according to preset filtering conditions, and replace the initial delay summation outputs that do not meet the preset filtering conditions with preset values ​​as the output results; otherwise, the initial delay summation output is used as the current delay summation output. The main lobe search module is used to search for the main lobe peak from the current delay summation output and calculate the contribution corresponding to the main lobe peak. The delay update module is used to remove the contribution corresponding to the main lobe peak from the current delay summation output to obtain the updated current delay summation output; The judgment module is used to determine whether the updated current delay summation output meets the iteration termination condition; if yes, the output result is obtained according to the updated current delay summation output corresponding to each grid point; if no, the updated current delay summation output is used as the current delay summation output, and the step of searching for the main lobe peak from the current delay summation output is returned. The positioning module is used to obtain the positioning result of the thermal runaway sound source based on the output result.

8. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the thermal runaway detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the thermal runaway detection method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer instructions for causing a computer to execute the thermal runaway detection method according to any one of claims 1 to 6.

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