A method of calculating a damping loss factor curve for a vehicle window glass

Abstract

The present application relates to a kind of vehicle window glass damping loss factor curve calculation methods, comprising: preset first set, first element is 1 / 3 octave frequency set;The peak point of each frequency response curve is formed into second set, obtain the half-power bandwidth of each second element in second set and frequency bandwidth distance threshold value, select the difference of half-power bandwidth and frequency bandwidth distance threshold value is not greater than 0 each second element in second set forms third set;To third element in third set is removed and peak-free, and the third element after processing forms fourth set;According to the frequency of fourth element in each fourth set, obtain corresponding each first element, obtain the minimum frequency value in corresponding each first element, obtain weight score;Obtain the fourth element of minimum weight score in fourth set, and the fourth element of minimum weight score forms target peak point set.The present application realizes the standard selection of peak point by the above algorithm, improves the acquisition efficiency and accuracy of the corresponding peak point of target frequency.

Description

Technical Field

[0001] This invention relates to the field of vehicle noise and vibration control technology, specifically to a method for calculating the damping loss factor curve of vehicle window glass. Background Technology

[0002] The damping loss factor of automotive window glass is a parameter that measures a material's ability to absorb vibrational energy and convert it into heat. For automotive window glass, increasing its damping loss factor has several potential benefits: Reduced noise: High-damping materials can more effectively absorb the energy in sound waves, thereby reducing the noise level transmitted into the cabin through the window, which is crucial for improving driving comfort and passenger experience; Improved vehicle NVH performance: NVH refers to noise, vibration, and harshness. Using window glass with higher damping characteristics can help improve the overall NVH performance of the vehicle, making the ride smoother and quieter; Enhanced safety: In the event of a collision, glass with good damping properties can better disperse impact forces and is less likely to shatter into sharp fragments, helping to protect the safety of occupants; Extended service life: Good damping characteristics mean that the material is more resistant to fatigue damage under repeated stress, thus potentially helping to extend the service life of window glass and other related components.

[0003] Currently, when calculating the damping loss factor, the modal fitting method calculates it by the ratio of the half-power point bandwidth of the peak value of the steady-state frequency response function (i.e., admittance) of a single subsystem to the modal frequency corresponding to the peak value. The specific working principle is as follows: A suitable excitation device (such as a hammer or shaking table) is used to apply an excitation force to the structure, causing it to vibrate. Simultaneously, sensors (such as accelerometers) are used to measure the structure's response signal under excitation. Then, signal processing (such as Fast Fourier Transform) and modal parameter identification algorithms (such as frequency domain peak method and least squares method) are used to determine the modal parameters. The frequency domain signal obtained after signal processing will form a distinct peak value; the frequencies corresponding to these peak values ​​are the structure's natural frequencies. However, it is difficult to identify other modal parameters such as the damping ratio and mode shape because factors such as the width of the frequency domain peak value are related to the damping ratio, but the frequency domain peak method alone is insufficient to accurately determine the damping ratio. Furthermore, determining the mode shape requires combining measurement results from multiple sensors at different locations and further calculations; the frequency domain peak method itself cannot directly provide complete mode shape information. Moreover, the peak values ​​selected by the frequency domain peak method are basically the maximum values ​​within the frequency range corresponding to each test point, which will ignore more suitable peak points, thus affecting the damping factor loss curve obtained by calculation, and thus affecting the analysis of the car window glass. Summary of the Invention

[0004] This invention provides a method for calculating the damping loss factor curve of vehicle window glass, in order to solve the problem that improper selection of peak values ​​affects the damping loss factor curve and thus the analysis of vehicle window glass.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for calculating the damping loss factor curve of a vehicle window glass includes: S1: obtaining time-domain response signals corresponding to several test points of the vehicle window glass using a hammer impact method, and converting each time-domain response signal into a corresponding frequency response curve; S2: determining frequency intervals based on 1 / 3 octave bands, dividing each frequency response curve according to each frequency interval, and using each frequency interval as a first element, forming a first set from each first element; wherein each frequency interval is a continuous multi-segment frequency interval; defining the peak points of each frequency response curve as second elements, forming a second set from each second element, and determining the frequency bandwidth distance threshold and half-power bandwidth of each second element; selecting each second element whose difference between the half-power bandwidth and the frequency bandwidth distance threshold is not greater than 0, and defining it as a third element, wherein the third element group S3: Preprocess the third element in the third set, and define the preprocessed third element as the fourth element. The fourth elements together form the fourth set. S4: For each fourth element in the fourth set, determine the first element corresponding to the fourth element in the first set, and then determine the center frequency value in the first element. Obtain a weight score based on the half-power bandwidth of each fourth element and the frequency and the corresponding center frequency value. S5: Obtain the fourth element with the smallest weight score based on each first element, and define the fourth element with the smallest weight score as the target peak point. The target peak points together form the target peak point set. S6: Determine the damping loss factor based on each target peak point in the target peak point set, and draw the damping loss factor curve based on the damping loss factor.

[0007] Based on the above technical means, by screening and processing the peak points layer by layer, we can avoid wasting computing resources on a large amount of irrelevant or inaccurate peak point data. Instead, we can focus on processing the target peak points that are most likely to represent the true damping characteristics of the window, thereby improving the calculation efficiency of the damping loss factor and reducing unnecessary calculation time and cost waste.

[0008] First, the response signal of the test point of the car window glass is obtained by hammer impact method and converted into frequency response curve. This method is relatively simple and easy to implement, and can quickly collect raw data related to the vibration characteristics of the car window glass, laying the data foundation for the entire calculation process.

[0009] Then, the peaks of each frequency response curve are initially screened, and the frequencies corresponding to the frequency response curves are divided into continuous frequency intervals to form the first set. This partitioning approach helps to analyze the relevant characteristics of window damping from the perspective of different frequency bands. Then, peaks with a half-power bandwidth and frequency bandwidth difference of no more than 0 are selected to form the third set. This bandwidth-based screening method can eliminate some abnormal peaks that may be caused by noise or resolution interference factors, so as to more accurately locate the peaks closely related to the inherent vibration characteristics of the window. Based on the frequency of the fourth element in the fourth set (i.e., the effective peaks after deduplication and peak-free processing), the minimum frequency value in the corresponding first element is obtained to calculate the weight score. This data processing method fully considers the distribution of peaks in the entire frequency interval. Through scientific weight allocation and comparison, the target peak set can be determined more reasonably, avoiding the one-sided influence of a single factor or simple judgment on the selection of peaks. This makes the entire data processing process more scientific and rigorous, thereby improving the reliability of damping loss factor calculation.

[0010] Finally, the damping loss factor is calculated based on the target peak points in the target peak point set, and the damping loss factor curve is plotted, along with its corresponding frequency and amplitude, so that the obtained damping loss factor result can truly reflect the damping performance of the vehicle window glass under actual working conditions.

[0011] Further, the frequency bandwidth distance threshold in S2 is obtained through the following steps: obtaining the corresponding first element according to the frequency of the second element in each second set, and obtaining the minimum frequency value and maximum frequency value of the corresponding first element; and obtaining the frequency bandwidth distance threshold by combining the obtained minimum frequency value and maximum frequency value with the frequency bandwidth distance threshold algorithm.

[0012] Based on the aforementioned technical means, the corresponding first element is determined according to the frequency of each second element in the second set, thereby accurately obtaining the minimum and maximum frequency values ​​of the first element. Combined with a specialized frequency bandwidth distance threshold algorithm, it provides a key quantitative standard for peak point screening from the dimension of frequency range definition.

[0013] Furthermore, the frequency bandwidth distance threshold algorithm is specifically as follows:

[0014]

[0015] Where L is the frequency bandwidth distance threshold, X i+1 X represents the maximum frequency value of the i-th element in the first set. i γ is the minimum frequency value of the i-th element in the first set, and γ is the preset peak width weighting coefficient.

[0016] Furthermore, the half-power bandwidth in S2 is obtained through the following steps: obtaining the frequencies of the two half-power points corresponding to each of the second elements using the half-power formula, and obtaining the half-power bandwidth of each of the second elements based on the frequencies of the two half-power points.

[0017] Based on the above technical means, the half-power bandwidth reflects the frequency range corresponding to the system when the energy decays to half. It is closely related to the damping characteristics of the system and can show the characteristics of the peak point from the perspective of energy distribution. By comparing the half-power bandwidth and the frequency bandwidth distance threshold, sharper peaks can be filtered out during the initial screening of peak points in the second set, making the peak point data more representative, stable and reliable.

[0018] Furthermore, the formula for calculating the weighted score is as follows:

[0019] W = |(S i -F i )|×T1+(F2-F1)×T2,

[0020] Where W is the weight score, F i S is the i-th element in the third set. i F1 is the intermediate frequency value of the i-th element in the first set, F2 and F1 are the corresponding first half-power point and second half-power point, T1 is the preset first weighting coefficient, and T2 is the preset second weighting coefficient.

[0021] Further, the preprocessing in S4 includes peak-free processing, which specifically includes: for the Nth first element in the first set, obtaining the intermediate frequency value of the Nth first element, and determining each of the third elements corresponding to the Nth first element as corresponding elements of the intermediate frequency value of the Nth first element; determining whether the Nth first element includes each of the corresponding elements; if the Nth first element does not include any of the corresponding elements, then copying the third element corresponding to the (N-1)th first element, and defining the third element corresponding to the (N-1)th first element as the fourth element; wherein, the first set is N consecutive and sequentially increasing frequency intervals, and N is a positive integer not less than 1.

[0022] Based on the above technical means, by performing peakless processing on each of the third elements, it is ensured that the minimum frequency value of each first element has a corresponding peak point, which effectively solves the problem of possible data gaps. This ensures that the entire data set can remain relatively complete during the processing, avoiding data gaps caused by the absence of corresponding peak points (third elements) in some intervals (frequency intervals corresponding to the first elements). This ensures that subsequent calculations, analyses, and other work based on these data will not be hindered by data loss, thereby improving the accuracy and reliability of the entire analysis work.

[0023] Further, S1 specifically includes: S11: acquiring the acceleration and excitation force pulse signals at each test point using the hammer impact method; S12: determining whether the excitation force can continuously produce the same origin frequency response function curve at each test point. If the continuously generated origin frequency response function curves are consistent, proceed to step S13; otherwise, return to step S11 until the continuously generated origin frequency response function curves are consistent; S13: converting the acceleration signal into a frequency response curve and performing windowing processing. If there is no attenuation, the time constant of the exponential window function needs to be increased to ensure that the attenuation degree of the acceleration signal meets a first preset value; if the attenuation of the acceleration signal exceeds the preset value, the time constant of the exponential window function needs to be decreased. If the time constant of the exponential window function is such that the attenuation of the acceleration signal meets the first preset value, then proceed to step S14; otherwise, return to step S11 until the attenuation of the acceleration signal meets the first preset value. S14: Ensure that the coherence function of the frequency response curve is greater than the second preset value. If the coherence function of the frequency response curve is less than the second preset value, then it is necessary to re-acquire the time domain signal of the test point and repeat steps S12-S14 until the frequency response function curves of the continuously generated excitation force signals are consistent, the attenuation of the acceleration signal meets the first preset value, and the coherence function is greater than the second preset value.

[0024] Based on the aforementioned technical means, by judging the frequency response curve converted from the excitation force and acceleration signals and the coherence function of the frequency response curve, the inspection and adjustment operations of multiple links, including signal acquisition, original frequency response curve verification, acceleration signal attenuation adjustment and coherence function assurance, are realized. Each link cooperates with each other and is subject to layer-by-layer checks, forming a rigorous closed-loop process. This ensures to the greatest extent that the collected data and the signals processed by the data are reliable. It is conducive to achieving standardized operations in actual vehicle window glass performance testing, improving work efficiency and the comparability of test results.

[0025] Further, the damping loss factor in S6 is obtained through the following steps: S61: Based on the target peak point in the target set, obtain the frequencies of the two half-power points corresponding to the target peak point; S62: By combining the frequencies of the two half-power points and the frequency of the target peak point with the damping loss factor algorithm, obtain the damping loss factor corresponding to the target peak point.

[0026] Based on the above technical means, the calculation method of the half-power point damping loss factor is directly based on the frequency response characteristics of the system, without the need for complex mathematical models or additional testing equipment; moreover, the half-power point damping loss factor is calculated using data from multiple frequency points in a continuous frequency band, which can reduce the error caused by single frequency point data and improve the accuracy of test results.

[0027] Furthermore, the formula for calculating the damping loss factor is as follows:

[0028]

[0029] Where η is the damping loss factor, F' i Let F2 be the i-th target peak in the target set, and F1 be F'. i The corresponding first half-power point and second half-power point.

[0030] Furthermore, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the program to implement the method described in any one of claims 1 to 9.

[0031] The beneficial effects of this invention are:

[0032] 1. By performing layer-by-layer screening and targeted processing on all peaks on each frequency response curve, we avoid wasting computational resources on a large amount of irrelevant or inaccurate peak data. Instead, we focus on processing the target peaks that are most likely to represent the true damping characteristics of the window. In this way, by improving the calculation efficiency of the damping loss factor of the peaks, we reduce unnecessary computation time and cost waste.

[0033] 2. Dividing the frequencies corresponding to several frequency response curves into continuous multiple frequency intervals to form the first set, this analytical approach of partitioning helps to analyze the damping-related characteristics of car window glass from the perspective of different frequency bands. It can more meticulously grasp the performance patterns in different frequency ranges, making the entire data analysis process more scientific and comprehensive, and meeting the requirements for in-depth exploration of complex physical characteristics.

[0034] 3. By comparing the difference between the half-power bandwidth and the frequency bandwidth and the threshold for initial screening, sharp peaks that may interfere with subsequent analysis can be effectively eliminated, and then peaks that meet the conditions can be selected to form a third set. This bandwidth-based screening method can eliminate some abnormal peaks that may be caused by noise or resolution interference factors, so as to more accurately locate peaks that are closely related to the inherent vibration characteristics of the car window.

[0035] 4. By deduplicating and removing peaks from the third set, this cleaning method eliminates abnormal or unacceptable peak data that may interfere with the final result. This helps to focus on the key peaks that are truly valuable and can accurately reflect the damping characteristics of the car window glass, further ensuring the accuracy of the results.

[0036] 5. The weight scores are determined based on the frequency of the elements in the fourth set and the corresponding minimum frequency value. By using reasonable mathematical logic to assign weights based on the existing filtered data, the importance of different elements in the final calculation can be objectively measured, providing a scientific basis for accurately locating key target peaks. Attached Figure Description

[0037] Figure 1 This is a schematic diagram illustrating the specific implementation process of the present invention;

[0038] Figure 2 This is a flowchart of the peakless processing of the present invention;

[0039] Figure 3 This is a flowchart of the data acquisition process for this invention;

[0040] Figure 4 This is a schematic diagram illustrating the specific implementation process of the damping loss factor of the present invention.

[0041] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the scope of this patent. To better illustrate this embodiment, some components in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings. The same or similar reference numerals correspond to the same or similar components. The terms describing positional relationships in the drawings are for illustrative purposes only and should not be construed as limiting the scope of this patent. Detailed Implementation

[0042] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0043] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0044] In the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" and "second" may explicitly or implicitly include one or more of that feature.

[0045] In the embodiments of this application, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a direct connection or an indirect connection through an intermediate medium.

[0046] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0047] This invention provides a method for calculating the damping loss factor curve of vehicle window glass, such as... Figure 1As shown, it includes: S1: Obtaining time-domain response signals corresponding to several test points on the car window glass using the hammer impact method, and converting each time-domain response signal into a corresponding frequency response curve; S2: Determining frequency intervals based on 1 / 3 octave bands, dividing each frequency response curve according to each frequency interval, and using each frequency interval as the first element, forming a first set; wherein, each frequency interval is a continuous multi-segment frequency interval; defining the peak points of each frequency response curve as the second element, forming a second set of the second elements, determining the frequency bandwidth distance threshold and half-power bandwidth of each second element; selecting each second element whose difference between the half-power bandwidth and the frequency bandwidth distance threshold is not greater than 0, and defining it as the third element, forming a third set of the third elements; S3: For the first... The third element in the three sets is preprocessed, and the preprocessed third element is defined as the fourth element. All fourth elements form the fourth set. S4: For each fourth element in the fourth set, the first element corresponding to the fourth element is determined in the first set, and then the center frequency value in the first element is determined. The weight score is obtained according to the half-power bandwidth of each fourth element and the frequency and the corresponding center frequency value. S5: The fourth element with the smallest weight score is obtained according to each first element. The fourth element with the smallest weight score is defined as the target peak point. All target peak points form the target peak point set. S6: The damping loss factor is determined according to each target peak point in the target peak point set, and the damping loss factor curve is plotted according to the damping loss factor.

[0048] Preferably, the frequency range in step S2 is obtained through the following steps: defining an intermediate frequency value, specifically 1000Hz; using the intermediate frequency value calculation formula, obtaining the intermediate frequency value corresponding to each frequency range; then using the intermediate frequency value calculation formula, obtaining the frequency range corresponding to each intermediate frequency value; each frequency range divides the frequencies corresponding to several frequency response curves into multiple continuous frequency ranges, and defines each frequency range as a first element, with each first element forming a first set.

[0049] Preferably, the formula for calculating the intermediate frequency value is:

[0050] Intermediate frequency values ​​greater than 1000Hz: f n+1 =2 a ×f n Intermediate frequency values ​​less than 1000Hz: Among them, f n f is the preset intermediate frequency value. n-1 and f n+1 f n The corresponding adjacent intermediate frequency value, where 'a' is the preset frequency band.

[0051] Specifically, the formula for calculating the frequency range is: Upper limit frequency of the frequency range: Lower limit frequency of the frequency range: Among them, f n f is the intermediate frequency value. l f is the minimum frequency value within the frequency range corresponding to the intermediate frequency value. u The maximum frequency value of the frequency range corresponding to the intermediate frequency value is denoted as 'a', where 'a' is a preset frequency band.

[0052] More preferably, the aforementioned intermediate frequency value and the upper and lower limit frequencies of the frequency range are both selected as integer values.

[0053] This invention avoids wasting computational resources on a large amount of irrelevant or inaccurate peak data by screening and processing peaks in a layered manner. Instead, it focuses on processing the target peaks that are most likely to represent the true damping characteristics of the window, thereby improving the computational efficiency of the damping loss factor and reducing unnecessary computation time and cost waste.

[0054] First, the response signal of the test point of the car window glass is obtained by hammer impact method and converted into frequency response curve. This method is relatively simple and easy to implement, and can quickly collect raw data related to the vibration characteristics of the car window glass, laying the data foundation for the entire calculation process.

[0055] Then, the peaks of each frequency response curve are initially screened, and the frequencies corresponding to the frequency response curves are divided into continuous frequency intervals to form the first set. This partitioning approach helps to analyze the relevant characteristics of window damping from the perspective of different frequency bands. Then, peaks with a half-power bandwidth and frequency bandwidth difference of no more than 0 are selected to form the third set. This bandwidth-based screening method can eliminate some abnormal peaks that may be caused by noise or resolution interference factors, so as to more accurately locate the peaks closely related to the inherent vibration characteristics of the window. Based on the frequency of the fourth element in the fourth set (i.e., the effective peaks after deduplication and peak-free processing), the minimum frequency value in the corresponding first element is obtained to calculate the weight score. This data processing method fully considers the distribution of peaks in the entire frequency interval. Through scientific weight allocation and comparison, the target peak set can be determined more reasonably, avoiding the one-sided influence of a single factor or simple judgment on the selection of peaks. This makes the entire data processing process more scientific and rigorous, thereby improving the reliability of damping loss factor calculation.

[0056] Finally, the damping loss factor is calculated based on the target peak points in the target peak point set, and the damping loss factor curve is plotted, along with its corresponding frequency and amplitude, so that the obtained damping loss factor result can truly reflect the damping performance of the vehicle window glass under actual working conditions.

[0057] In this embodiment, the frequency bandwidth distance threshold in S2 is obtained through the following steps: based on the frequency of the second element in each second set, the corresponding first element is obtained, and the minimum frequency value and maximum frequency value of the corresponding first element are obtained; the frequency bandwidth distance threshold is obtained by combining the obtained minimum frequency value and maximum frequency value with the frequency bandwidth distance threshold algorithm.

[0058] The first element is determined based on the frequency of each second element in the second set, and then the minimum and maximum frequency values ​​of the first element are accurately obtained. Combined with a special frequency bandwidth distance threshold algorithm, it provides a key quantitative standard for peak point screening from the dimension of frequency range definition.

[0059] In this embodiment, the frequency bandwidth distance threshold algorithm is specifically as follows:

[0060]

[0061] Where L is the frequency bandwidth distance threshold, X i+1 X represents the maximum frequency value of the i-th element in the first set. i γ is the minimum frequency value of the i-th element in the first set, and γ is the preset peak width weighting coefficient.

[0062] In this embodiment, the half-power bandwidth in S2 is obtained through the following steps: the frequencies of the two half-power points corresponding to each second element are obtained through the half-power formula, and the half-power bandwidth of each second element is obtained based on the frequencies of the two half-power points.

[0063] Half-power bandwidth reflects the frequency range corresponding to when the system's energy decays to half. It is closely related to the system's damping characteristics and can show the characteristics of peak points from the perspective of energy distribution. By comparing the half-power bandwidth and the frequency bandwidth distance threshold, sharper peaks can be filtered out during the initial screening of peak points in the second set, making the peak point data more representative, stable, and reliable.

[0064] In this embodiment, the formula for calculating the weighted score is:

[0065] W = |(S i -F i )|×T1+(F2-F1)×T2;

[0066] Where W is the weight score, F i S is the i-th element in the third set. i F1 is the intermediate frequency value of the i-th element in the first set, F2 and F1 are the corresponding first half-power point and second half-power point, T1 is the preset first weighting coefficient, and T2 is the preset second weighting coefficient.

[0067] like Figure 2 As shown, in this embodiment, preprocessing 1 in S4 includes peak-free processing, which specifically includes: for the Nth first element in the first set, obtaining the intermediate frequency value of the Nth first element, and determining each third element corresponding to the Nth first element as the corresponding element of the intermediate frequency value of the Nth first element; determining whether the Nth first element includes each corresponding element; if the Nth first element does not include any of the corresponding elements, then copying the third element corresponding to the (N-1)th first element, and defining the third element corresponding to the (N-1)th first element as the fourth element; wherein, the first set is N consecutive and sequentially increasing frequency intervals, and N is a positive integer not less than 1.

[0068] By performing peakless processing on each third element, it is ensured that the minimum frequency value of each first element has a corresponding peak, effectively solving the problem of potential data gaps. This ensures that the entire dataset remains relatively complete during processing, avoiding data gaps caused by the absence of corresponding peaks (third elements) in certain intervals (frequency intervals corresponding to the first element). This ensures that subsequent calculations and analyses based on these data will not be hindered by data loss, thereby improving the accuracy and reliability of the entire analysis.

[0069] like Figure 3 As shown, in this embodiment, S1 specifically includes: S11: Obtaining the pulse signals of acceleration and excitation force at each test point using the hammer impact method; S12: Determining whether the excitation force can continuously produce the same origin frequency response function curve at each test point. If the continuously generated origin frequency response function curves are consistent, proceed to step S13; otherwise, return to step S11 until the continuously generated origin frequency response function curves are consistent; S13: Converting the acceleration signal into a frequency response curve and performing windowing processing. If there is no attenuation, the time constant of the exponential window function needs to be increased to ensure that the attenuation degree of the acceleration signal meets the first preset value; if the attenuation of the acceleration signal exceeds the preset value, then... If the time constant of the exponential window function is reduced to meet the first preset value for the attenuation of the acceleration signal, then proceed to step S14; otherwise, return to step S11 until the attenuation of the acceleration signal meets the first preset value. S14: Ensure that the coherence function of the frequency response curve is greater than the second preset value. If the coherence function of the frequency response curve is less than the second preset value, then it is necessary to re-acquire the time domain signal of the test point and repeat steps S12-S14 until the frequency response function curves of the continuously generated excitation force signals are consistent, the attenuation of the acceleration signal meets the first preset value, and the coherence function is greater than the second preset value.

[0070] In actual testing, the location of the test points needs to reflect the mode shapes corresponding to all elements within the first set. Therefore, during testing, 2 to 6 acceleration sensors are typically arranged according to the size of the car window glass. The acceleration sensors are installed on the outer surface of the car window and fixed with a suitable adhesive. For consistency, the sensor orientation is specified to use a unified vehicle coordinate system, such as: with the driver's seat as the origin, the positive X direction is along the length of the vehicle body backward, the positive Y direction is along the width of the vehicle body towards the passenger seat, and the positive Z direction is along the height of the vehicle body upward.

[0071] By analyzing the frequency response curves converted from excitation force and acceleration signals, and the coherence function of these frequency response curves, the system achieves verification and adjustment of multiple stages, including signal acquisition, original frequency response curve verification, acceleration signal attenuation adjustment, and coherence function assurance. Each stage cooperates with the others, with each layer ensuring quality control, forming a rigorous closed-loop process. This maximizes the reliability of the collected data and the signals subsequently processed from this data, facilitating standardized operations in actual vehicle window glass performance testing, improving work efficiency, and enhancing the comparability of test results.

[0072] like Figure 4 As shown, in this embodiment, the damping loss factor in S6 is obtained through the following steps: S61: Based on the target peak point in the target set, obtain the frequencies of the two half-power points corresponding to the target peak point; S62: By combining the frequencies of the two half-power points and the frequency of the target peak point with the damping loss factor algorithm, obtain the damping loss factor corresponding to the target peak point.

[0073] The method for calculating the damping loss factor at half power point is directly based on the frequency response characteristics of the system, without the need for complex mathematical models or additional testing equipment. Furthermore, the method for calculating the damping loss factor at half power point uses data from multiple frequency points in a continuous frequency band, which can reduce the error caused by data from a single frequency point and improve the accuracy of the test results.

[0074] In this embodiment, the formula for calculating the damping loss factor is:

[0075] Where η is the damping loss factor, F i ′ Let F1 be the i-th target peak in the target set, and F2 and F1 be F... i ′ The corresponding first half-power point and second half-power point.

[0076] This embodiment also relates to an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the program to implement the method described in any one of claims 2 to 6.

[0077] In summary, a method for calculating the damping loss factor curve of a vehicle window includes the following steps:

[0078] S1: Obtain the time-domain response signals of several test points on the car window glass using the hammer impact method, and determine whether the original frequency response function curves of the excitation force signals continuously generated in the time-domain signal are consistent, whether the attenuation degree of the acceleration signal meets the first preset value, and whether the coherence function is greater than the second preset value. If all the frequency response curves meet the requirements, proceed to step S2; otherwise, it is necessary to re-obtain the time-domain response signal until the excitation force signal, acceleration signal, and coherence function all meet the above conditions.

[0079] S2: Define an intermediate frequency value, specifically 1000Hz. Based on this intermediate frequency value, obtain the intermediate frequency value corresponding to each frequency interval using the intermediate frequency value calculation formula. Then, based on each intermediate frequency value, obtain the frequency interval corresponding to each intermediate frequency value using the frequency interval calculation formula. Each frequency interval divides the frequencies corresponding to several frequency response curves into multiple continuous frequency intervals, and defines each frequency interval as the first element. Each first element forms the first set.

[0080] The peak points of each frequency response curve are defined as the second element, and the second elements form the second set. The frequency bandwidth distance threshold and half-power bandwidth of each second element are determined. The second elements whose difference between the half-power bandwidth and the frequency bandwidth distance threshold is not greater than 0 are selected as the third element, and the third elements form the third set.

[0081] S3: Based on the frequency of the third element in each third set, obtain the corresponding first element, and obtain the minimum frequency value and maximum frequency value of each first element. Select the third element near the minimum frequency value and the third element near the maximum frequency value respectively. Perform peakless processing on the third element corresponding to the minimum frequency value and the maximum frequency value. The processed third element is defined as the fourth element. The fourth elements form the fourth set.

[0082] S4: For each fourth element in the fourth set, determine the first element corresponding to the fourth element in the first set, then determine the intermediate frequency value in the first element, and obtain the weight score based on the frequency of each fourth element and the corresponding intermediate frequency value.

[0083] S5: Based on each first element, obtain the fourth element with the smallest weight score, define the fourth element with the smallest weight score as the target peak point, and form a target peak point set.

[0084] S6: Determine the damping loss factor based on each target peak in the target peak set, and plot the damping loss factor curve based on the damping loss factor.

[0085] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

Claims

1. A method for calculating the damping loss factor curve of a vehicle window glass, characterized in that, Includes the following steps: S1: Obtain the time-domain response signals corresponding to several test points of the car window glass by hammer impact method, and convert each time-domain response signal into the corresponding frequency response curve; S2: Determine the frequency range based on 1 / 3 octave, divide the frequency response curve according to each frequency range, and take each frequency range as the first element, and form a first set with each first element; wherein, each frequency range is a continuous multi-segment frequency range; The peak points of each frequency response curve are defined as second elements, and the second elements form a second set. The frequency bandwidth distance threshold and half-power bandwidth of each second element are determined. Each second element whose difference between the half-power bandwidth and the frequency bandwidth distance threshold is not greater than 0 is selected and defined as a third element. The third elements form a third set. S3: Preprocess the third element in the third set, and define the preprocessed third element as the fourth element. All the fourth elements form the fourth set. S4: For each fourth element in the fourth set, in the first set, determine the first element corresponding to the fourth element, then determine the center frequency value in the first element, and obtain a weight score based on the half-power bandwidth of each fourth element and the frequency and the corresponding center frequency value. S5: Obtain the fourth element with the smallest weight score according to each of the first elements, define the fourth element with the smallest weight score as the target peak point, and form a target peak point set with each of the target peak points. S6: Determine the damping loss factor based on each target peak in the target peak set, and plot the damping loss factor curve based on the damping loss factor.

2. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 1, characterized in that, The frequency bandwidth distance threshold in S2 is obtained through the following steps: Based on the frequency of the second element in each of the second sets, obtain the corresponding first element, and obtain the minimum frequency value and maximum frequency value of the corresponding first element; By combining the obtained minimum and maximum frequency values ​​with the frequency bandwidth distance threshold algorithm, the frequency bandwidth distance threshold is obtained.

3. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 2, characterized in that, The frequency bandwidth distance threshold algorithm is specifically as follows: ； Where L is the frequency bandwidth distance threshold. The maximum frequency value of the i-th element in the first set; Let be the minimum frequency value of the i-th element in the first set. This is the preset peak width weighting coefficient.

4. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 3, characterized in that, The half-power bandwidth in S2 is obtained through the following steps: the frequencies of the two half-power points corresponding to each second element are obtained by using the half-power formula, and the half-power bandwidth of each second element is obtained based on the frequencies of the two half-power points.

5. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 1, characterized in that, The formula for calculating the weighted score is: ； Where W is the weight score, For the i-th element in the third set, Let be the median frequency value of the i-th element in the first set. and They are respectively The corresponding first half-power point and second half-power point, The preset first weighting coefficient, This is the preset second weighting coefficient.

6. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 1, characterized in that, The preprocessing in S3 includes peak-free processing, which specifically includes: For the Nth first element in the first set, obtain the intermediate frequency value of the Nth first element, and determine each of the third elements corresponding to the Nth first element as the corresponding elements of the intermediate frequency value of the Nth first element; Determine whether the Nth first element includes all the corresponding elements. If the Nth first element does not include any of the corresponding elements, then copy the third element corresponding to the (N-1)th first element and define the third element corresponding to the (N-1)th first element as the fourth element. Wherein, the first set consists of N consecutive and sequentially increasing frequency intervals, and N is a positive integer not less than 1.

7. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 1, characterized in that, S1 specifically includes: S11: Obtain the pulse signals of acceleration and excitation force at each test point by hammering method; S12: Determine whether the excitation force can continuously produce the same origin frequency response function curve at each of the test points. If the continuously generated origin frequency response function curves are consistent, proceed to step S13; otherwise, return to step S11 until the continuously generated origin frequency response function curves are consistent. S13: Convert the acceleration signal into a frequency response curve and perform windowing processing. If there is no attenuation, the time constant of the exponential window function needs to be increased so that the attenuation degree of the acceleration signal meets the first preset value. If the attenuation of the acceleration signal exceeds the preset value, the time constant of the exponential window function is decreased so that the attenuation degree of the acceleration signal meets the first preset value, and then proceed to step S14. Otherwise, return to step S11 until the attenuation degree of the acceleration signal meets the first preset value. S14: Ensure that the coherence function of the frequency response curve is greater than the second preset value. If the coherence function of the frequency response curve is less than the second preset value, the time domain signal of the test point needs to be re-acquired, and steps S12-S14 are repeated until the frequency response function curve of the origin generated by the excitation force signal is consistent, the attenuation degree of the acceleration signal meets the first preset value, and the coherence function is greater than the second preset value.

8. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 1, characterized in that, The damping loss factor in step S6 is obtained through the following steps: S61: Based on the target peak points in the target peak point set, obtain the frequencies of the two half-power points corresponding to the target peak points; S62: By combining the frequencies of the two half-power points and the frequency of the target peak point with the damping loss factor algorithm, the damping loss factor corresponding to the target peak point is obtained.

9. The method for calculating the damping loss factor curve of a vehicle window glass according to claim 8, characterized in that, The formula for calculating the damping loss factor is as follows: ； in, The damping loss factor is... For the i-th target peak in the set of target peaks, and They are respectively The corresponding first half-power point and second half-power point.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1 to 9.

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