A method and system for impact positioning and energy detection based on dynamic time warping

Abstract

The present invention relates to the field of structural health monitoring technology, and in particular to a method and system for impact positioning and energy detection based on dynamic time warping. The impact positioning and energy detection method uses the DTW algorithm and the K-nearest neighbor algorithm to roughly locate the impact area, and on this basis, accurately locates the specific impact position within the impact area through a DTW-based centroid weighted algorithm; at the same time, the impact energy is characterized by the energy of the impact response signal. This method has accurate positioning, high impact inversion efficiency, and simple operation. It not only avoids the influence of structural complexity on positioning accuracy, but also effectively controls the impact energy estimation error. While reducing maintenance costs, it also effectively improves the efficiency of positioning and detection.

Description

Technical Field

[0001] The present invention relates to the technical field of structural health monitoring, and in particular to an impact positioning and energy detection method and system based on dynamic time warping. Background Art

[0002] Composite materials offer advantages such as high specific strength, large specific modulus, and structural design flexibility, offering significant advantages in lightweight manufacturing, economical operation and maintenance, and advanced design. Consequently, they are widely used in the aerospace sector. However, composite structures are inevitably subject to impact during manufacturing, service, and maintenance, which can cause various nearly invisible internal damage, degrading the load-bearing performance of the structure and seriously threatening the in-service safety of aerospace equipment. Therefore, online impact monitoring of composite structures to ensure equipment safety is an urgent engineering challenge.

[0003] Conventional nondestructive testing technologies currently used for impact damage detection include ultrasonic scanning, eddy current, and thermal imaging. These methods usually require point-by-point and area-by-area scanning and measurement of the structure, which is time- and economically expensive for large structures. Furthermore, they can only be monitored offline, making it difficult to meet the needs of airborne online monitoring. Existing impact location methods for complex composite structures generally use a location method based on the propagation velocity of stress waves, which involves extracting the time-domain features of stress waves and compensating for velocities in different propagation directions. This method has a large workload and its accuracy is greatly affected by the structure. The use of a system model-based method involves solving the transfer function through the impact response and constructing a system model. This method requires a large amount of mathematical calculations and parameter adjustments to achieve model convergence, resulting in low efficiency.

[0004] Impact energy, another characteristic parameter characterizing impact damage in composite structures, is crucial for assessing the structural condition of composite materials. Existing techniques typically estimate impact energy by inverting the time history of the impact load using a response model. However, this requires a complex system identification model for structures with dense ribs.

[0005] Therefore, based on the shortcomings of existing technologies and the needs of engineering applications, there is an urgent need for a method of impact positioning and energy detection that can more accurately, simply and effectively monitor the impact damage of composite structures online. Summary of the Invention

[0006] To address the shortcomings of the above-mentioned prior art methods for impact location and energy detection of composite materials, such as inaccurate positioning, low impact inversion efficiency, and complex operation, the present invention provides a method for impact location and energy detection based on dynamic time warping, comprising the following steps:

[0007] The region processing step is to arrange a plurality of sensors for receiving external impact signals on the composite material structure to be inspected, and divide the surface of the composite material structure to be inspected into at least M regions.

[0008] The sample acquisition step includes performing impact tests on a plurality of training points and marking points in each of the areas to obtain a first sample database and a second sample database containing impact signals; and impacting the surface of the composite material structure with a fixed energy E0, and obtaining a characterization value E under the fixed energy E0 impact according to the impact signals received by the plurality of sensors. s .

[0009] In the rough positioning step, if an impact event occurs, several sensors will receive the impact signal S impact ; Calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij , to obtain the set Q; according to the set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the coarse positioning.

[0010] In the fine positioning step, based on the impact area determined by coarse positioning, the impact signal S is calculated according to the DTW algorithm. impact The DTW distance L of all the markers in the impact area of ​​the second sample database i ; The obtained L i The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to complete precise positioning.

[0011] Energy detection step, based on the impact signal S received by sensors in all areas impact Obtain energy characterization value E s ', calculate the energy E of the impact according to the following formula est :

[0012]

[0013] In one embodiment, the region processing step further includes numbering each region to obtain a signal label; and in the sample acquisition step, the impact signal in each region is mapped into a corresponding signal label for storage.

[0014] In one embodiment, in the sample acquisition step, the sample acquisition step of the first sample database is as follows: N (N≥1) training points are selected in each of the regions and impact tests are performed to obtain corresponding impact signals, and then the impact signals at each training point in each of the regions are mapped into corresponding signal labels and stored in the first sample database;

[0015] The sample acquisition step of the second sample database is: selecting B marking points in each area and performing impact tests respectively to obtain corresponding impact signals, and then storing the impact signals obtained from the impact tests of each marking point in each area as samples.

[0016] In one embodiment, in the coarse positioning step, determining the impact area where the impact event occurred using the K-nearest neighbor algorithm specifically includes:

[0017] The DTW distance L in the set Q ij Arrange in ascending order and take the first K (K is an odd number not greater than N) items L ij , and count the first K DTW distances L ij The corresponding area, where the position corresponding to the area with the largest DTW distance Lij is determined as the impact area.

[0018] In one embodiment, in the fine positioning step, the obtained L i The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm, specifically including the following formula:

[0019]

[0020]

[0021] Among them, W i Represents the weighting coefficient of all marked points in the impact area; x i ,y i They represent the coordinate positions of all marked points in the impact area; x and y are the impact position coordinates of the impact event.

[0022] In one embodiment, in the sample acquisition step, the characteristic value E under the impact of fixed energy E0 is obtained specifically by the following formula: s :

[0023]

[0024]

[0025] Where f(t) is the expression of the impact signal obtained by the sensor, E is the energy value of the corresponding impact signal; n is the number of sensors deployed on the composite material structure to be tested, E i is the energy value of the impulse response signal corresponding to the i-th sensor;

[0026] In the energy detection step, the energy characterization value E when the impact event occurs is obtained specifically by the following formula: s ′:

[0027]

[0028] Among them, E i ′ is the energy value of the shock response signal corresponding to the i-th sensor when the shock event occurs.

[0029] In one embodiment, the step of obtaining an energy correction coefficient is further included. After performing a test on the surface of the composite material structure with a fixed energy E0, one of the regions is selected as a reference region, and the energy characterization value E of the reference region is obtained. R , calculate the energy correction coefficient R of each area relative to the reference area i , the formula is as follows:

[0030]

[0031]

[0032] Where n′ is the number of sensors in the reference area, E i′ is the energy value of the impulse response signal corresponding to the i′th sensor in the reference area.

[0033] In one embodiment, an energy correction step is further included, wherein the impact area determined based on the coarse positioning is corrected according to the energy correction coefficient R i Obtain the energy correction coefficient R of the impact area relative to the reference area, and obtain the corrected impact energy value E using the following formula: impact :

[0034] E impact =E est ·R.

[0035] The present invention also provides an impact location and energy detection system based on dynamic time warping, comprising a region processing module, a plurality of sensors for receiving external impact signals are arranged on the composite material structure to be detected, and the surface of the composite material structure to be detected is divided into at least M regions;

[0036] The sample acquisition module performs impact tests on a plurality of training points and marking points in each of the areas to obtain a first sample database and a second sample database containing impact signals; and impacts the surface of the composite material structure with a fixed energy E0, and obtains a characterization value E under the fixed energy E0 impact according to the impact signals received by a plurality of sensors. s ;

[0037] Coarse positioning module, if a certain impact event occurs, some of the sensors will receive the impact signal S impact ; Calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij, to obtain set Q; based on set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the rough positioning;

[0038] The fine positioning module calculates the impact signal S based on the impact area determined by the coarse positioning according to the DTW algorithm. impact The DTW distance L of all the markers in the impact area of ​​the second sample database i ; The obtained L i The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to complete precise positioning;

[0039] Energy detection module, based on the impact signal S received by sensors in all areas impact Obtain energy characterization value E s ', calculate the energy E of the impact according to the following formula est :

[0040]

[0041] In one embodiment, an energy correction module is further included. After performing a test of impacting the surface of the composite material structure with a fixed energy E0, one of the regions is selected as a reference region, and an energy characterization value E of the reference region is obtained. R , calculate the energy correction coefficient R of each area relative to the reference area i ;

[0042] Based on the impact area determined by coarse positioning, the energy correction coefficient R i Obtain the energy correction coefficient R of the impact area relative to the reference area, and obtain the corrected impact energy value E using the following formula: impact :

[0043] E impact =E est ·R.

[0044] Based on the above, compared with the existing technology, the impact location and energy detection method based on dynamic time warping provided by the present invention uses the DTW algorithm and the K-nearest neighbor algorithm to roughly locate the impact area. On this basis, the specific impact position within the impact area is accurately located using a DTW-based centroid weighted algorithm. At the same time, the impact energy is characterized by the energy of the response signal. This not only avoids the influence of structural complexity on positioning accuracy, but also effectively controls the impact energy estimation error. This method reduces maintenance costs while effectively improving the efficiency of positioning and detection.

[0045] Other features and beneficial effects of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The objectives and other beneficial effects of the present invention can be achieved and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work. The positional relationships described in the drawings in the following description are based on the directions of the components drawn in the diagrams, unless otherwise specified.

[0047] Figure 1 A flowchart of the steps of the impact location and energy detection method provided by the present invention;

[0048] Figure 2 Flowchart of the coarse positioning steps;

[0049] Figure 3 Schematic diagram of the DTW calculation process;

[0050] Figure 4 Flowchart of precise positioning steps;

[0051] Figure 5 It is a flow chart of energy detection steps;

[0052] Figure 6 It is a flow chart of energy detection steps and energy correction steps;

[0053] Figure 7 A flowchart of the steps of an impact location and energy detection method according to another embodiment of the present invention;

[0054] Figure 8 A schematic diagram of the impact location and energy detection system provided by the present invention;

[0055] Figure 9 A schematic diagram of the structure of the regional processing steps for the composite stiffened panel;

[0056] Figure 10 Select the location of the marker point in the area;

[0057] Figure 11 Schematic diagram of the coarse positioning result;

[0058] Figure 12 Schematic diagram of the precise positioning results;

[0059] Figure 13 Schematic diagram comparing the impact energy estimation errors before and after regional correction compensation. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments; the technical features designed in different implementation modes of the present invention described below can be combined with each other as long as they do not conflict with each other; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0061] In the description of the present invention, it should be noted that all terms used in the present invention (including technical terms and scientific terms) have the same meanings as those generally understood by ordinary technicians in the field to which the present invention belongs, and should not be understood as limiting the present invention; it should be further understood that the terms used in the present invention should be understood to have meanings consistent with the meanings of these terms in the context of this specification and in the relevant fields, and should not be understood in an idealized or overly formal sense, unless explicitly defined as such in the present invention.

[0062] To solve the existing problems of impact location and impact energy detection methods for complex composite structures, such as the location results are greatly affected by the structure, the system modeling workload is large, and the impact inversion efficiency is low. Figure 1 The present invention provides a method for impact location and energy detection based on dynamic time warping, which comprises at least the following steps:

[0063] The region processing step involves deploying a plurality of sensors on the composite material structure to be inspected for receiving external impact signals, and dividing the surface of the composite material structure to be inspected into at least M regions. This step also includes assigning a region number to each region to obtain a signal label, thereby facilitating subsequent identification of each region.

[0064] It should be noted that the sensors may be piezoelectric sensors, acoustic emission sensors, or other types. The number of sensors deployed can be set based on actual needs and is not limited here. Preferably, to facilitate subsequent calculations and analysis, the surface of the composite material structure to be inspected can be divided into M regions of equal or identical area.

[0065] The sample acquisition step includes performing impact tests on a plurality of training points and marking points in each of the areas to obtain a first sample database and a second sample database containing impact signals; and impacting the surface of the composite material structure with a fixed energy E0, and obtaining a characterization value E under the fixed energy E0 impact according to the impact signals received by the plurality of sensors. s .

[0066] In specific implementation, the sample acquisition steps of the first sample database are as follows: N (N≥1) training points are selected in each area and impact tests are performed to obtain corresponding impact signals, and then the impact signals at each training point in each area are mapped into corresponding signal labels and stored in the first sample database. The mapping relationship of the first sample database can be referred to as shown in the following table:

[0067]

[0068]

[0069] The sample acquisition step of the second sample database is as follows: select B marking points in each area and perform impact tests to obtain corresponding impact signals, and then store the impact signals obtained from the impact tests of each marking point in each area as samples. The mapping relationship of the second sample database can be referred to the following table:

[0070]

[0071] For coarse positioning steps, see Figure 2 If a shock event occurs, some of the sensors will receive a shock signal S impact ; Calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij , to obtain the set Q; according to the set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the coarse positioning.

[0072] In this embodiment, the DTW (Dynamic Time Warping) algorithm is applied to the coarse positioning of impact positioning. It does not involve the wave velocity measurement in the traditional way. It is less affected by the anisotropic properties of composite materials. Therefore, it can still achieve a relatively accurate positioning effect on a complex plane containing a rib reinforcement structure. Specifically, the DTW algorithm mainly compares the similarity of the time series of two impact signals, that is, calculates the Euclidean distance of the two time series. The specific calculation process is as follows: Figure 3As shown, taking time series X and time series Y as an example, under the premise of aligning time series X and time series Y, the distance matrix between each point of the two sequences is calculated, and then the minimum value of the sum of the path distances calculated according to the DTW path mapping relationship in the path composed of p1~pk is found. This path distance is the DTW distance L ij The impact signal S sent by this impact event is converted into impact The impulse signals of all samples in the first sample database are calculated to obtain a set Q, where the expression of the set Q is Q={L ij =DTW(S imapct ,d ij ), 1≤i≤M, 1≤j≤N}. The corresponding mapping relationship in the set Q can be referred to the following table:

[0073]

[0074] Then, in the set Q, the K-nearest neighbor (KNN) classification algorithm is used to determine the impact area where the impact event occurs. The specific steps are to calculate the DTW distance L in the set Q. ij Arrange in ascending order and take the first K (K is an odd number not greater than N) items L ij , and count the first K DTW distances L ij The corresponding area, where the DTW distance L ij The location with the most corresponding areas is determined as the impact area. To explain the process more intuitively, the following table shows the DTW distance L of a set Q arranged in ascending order from small to large. ij And the corresponding signal labels, where each signal label corresponds to an area. When K is 5, it can be determined that there are 3 signal labels "2" and 2 signal labels "1" in the first 5 DTW distances, that is, the number of signal labels 2 is the largest. Then the result of the K-nearest neighbor algorithm is 2, which means that the impact area is determined to be area 2.

[0075] DTW distance <![CDATA[L 21 ]]> <![CDATA[L 24 ]]> <![CDATA[L 13 ]]> <![CDATA[L 22 ]]> <![CDATA[L 11 ]]> <![CDATA[L 23 ]]> … Signal Label 2 2 1 2 1 2 …

[0076] For precise positioning steps, please refer to Figure 4 Based on the impact area determined by coarse positioning, the impact signal S is calculated according to the DTW algorithm. impact The DTW distance L of all the markers in the impact area of ​​the second sample database i ; The obtained L i The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to complete precise positioning.

[0077] In specific implementation, this embodiment obtains the precise impact position within the impact area through the weighted centroid positioning algorithm (WCA) based on the rough positioning. It has the characteristics of simple calculation and strong adaptability. The specific steps are to first construct a rectangular coordinate system for each area, and then calculate the impact signal S using the DTW algorithm. impact The DTW distance L of all the markers in the impact area of ​​the second sample database i , and then the obtained DTW distance L i The weight factor of the weighted centroid positioning algorithm is used to calculate the impact position coordinates (x, y) within the impact area, specifically including the following formula:

[0078]

[0079]

[0080] Among them, W i Represents the weighting coefficient of all marked points in the impact area; x i ,y i They represent the coordinate positions of all marked points in the impact area; x and y are the impact position coordinates of the impact event.

[0081] Through the above DTW distance L i The impact position coordinates calculated after weighting have high positioning accuracy and can accurately locate the impact position.

[0082] Energy detection steps, see Figure 5 , according to the impact signal S received by sensors in all areas impact Obtain energy characterization value E s ', calculate the energy E of the impact according to the following formula est :

[0083]

[0084] Where, E0 and E s The acquisition of can be obtained through the above sample acquisition step, that is: pre-impact the surface of the composite material structure with a fixed energy E0, and obtain the characterization value E under the fixed energy E0 impact based on the impact signal received by several sensors. s Specifically, the characterization value E under fixed energy E0 impact is obtained through the following formula: s :

[0085]

[0086]

[0087] Where f(t) is the expression of the impact signal obtained by the sensor, E is the energy value of the corresponding impact signal; n is the number of sensors deployed on the composite material structure to be tested, E i is the energy value of the impulse response signal corresponding to the i-th sensor; E i It can be calculated according to the formula of E.

[0088] In the formula, the energy representation value E when the impact event occurs is obtained by the following formula: s ′:

[0089]

[0090] Among them, E i ′ is the energy value of the shock response signal corresponding to the i-th sensor when the shock event occurs.

[0091] Finally, E0, E s 、E s 'Substitute the above information about the impact energy E est The formula can effectively estimate the impact energy of the impact area.

[0092] In order to generalize the above method to other impact areas, the present invention also provides a regional compensation correction method for impact energy, see Figure 6 Specifically, it includes the energy correction coefficient acquisition step, after performing a test on the surface of the composite material structure with a fixed energy E0, selecting one area as a reference area, and obtaining the energy representation value E of the reference area. R , calculate the energy correction coefficient R of each area relative to the reference area i , the formula is as follows:

[0093]

[0094]

[0095] Where n′ is the number of sensors in the reference area, E i′ is the energy value of the impulse response signal corresponding to the i′th sensor in the reference area.

[0096] Energy correction step, based on the impact area determined by coarse positioning, according to the energy correction coefficient R i Obtain the energy correction coefficient R of the impact area relative to the reference area, and obtain the corrected impact energy value E using the following formula: impact :

[0097] E impact =E est ·R.

[0098] The energy detection method of this embodiment uses an impact response signal to characterize the impact energy and makes corrections based on regional characteristics to obtain an accurate impact energy value. Compared with traditional methods, this method does not require the construction of a complex system response identification model. It has the advantages of a simple method, efficient impact energy inversion, and accurate energy detection.

[0099] See also Figure 7 The impact positioning and energy detection method based on dynamic time warping provided by the above embodiment can not only avoid the influence of structural complexity on positioning accuracy, but also achieve effective control of impact energy estimation error, and has good application prospects.

[0100] The present invention also provides an impact location and energy detection system based on dynamic time warping, please refer to Figure 8 , including a region processing module, for arranging a plurality of sensors for receiving external impact signals on the composite material structure to be detected, and dividing the surface of the composite material structure to be detected into at least M regions;

[0101] The sample acquisition module is used to perform impact tests on a plurality of training points and marking points in each of the areas to obtain a first sample database and a second sample database containing impact signals; and to impact the surface of the composite material structure with a fixed energy E0, and obtain a characterization value E under the fixed energy E0 impact according to the impact signals received by a plurality of sensors. s ;

[0102] Coarse positioning module, if a certain impact event occurs, some of the sensors will receive the impact signal S impact ; Used to calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij , to obtain set Q; based on set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the rough positioning;

[0103] The fine positioning module is used to calculate the impact signal S according to the DTW algorithm based on the impact area determined by the coarse positioning. impact The DTW distance L of all the markers in the impact area of ​​the second sample database i ; The obtained L i The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to complete precise positioning;

[0104] Energy detection module, used to detect the impact signal S received by sensors in all areas impact Obtain energy characterization value E s ', calculate the energy E of the impact according to the following formula est:

[0105]

[0106] Preferably, an energy correction module may be included, which is used to select one area as a reference area after performing a test of impacting the surface of the composite material structure with a fixed energy E0, and obtain the energy characterization value E of the reference area. R , calculate the energy correction coefficient R of each area relative to the reference area i ;

[0107] Then based on the impact area determined by coarse positioning, the energy correction coefficient R i Obtain the energy correction coefficient R of the impact area relative to the reference area, and obtain the corrected impact energy value E using the following formula: impact :

[0108] E impact =E est ·R.

[0109] In order to better illustrate the impact location and energy detection method based on dynamic time warping provided by the present invention, the implementation process of the method of the present invention is described in detail below using a specific composite material stiffened plate as an example:

[0110] (1) The monitoring area (360 mm × 360 mm) of a composite reinforced plate with a size of 480 mm × 480 mm is divided into 16 rectangular areas of equal area, such as Figure 9 As shown, and numbered with letters A to P; piezoelectric sensors are arranged at the four boundary intersections of the monitoring area.

[0111] (2) In each region, 10 training points were selected to conduct 10 random shock tests and the region number was used as the signal label to construct the first sample database containing 16×10 groups of shock signals.

[0112] A rectangular coordinate system is constructed in each area, and 5 marking points are selected for impact testing to construct a second sample database for precise positioning, such as Figure 10 As shown, 5 marking points evenly distributed in the area are selected, namely NO.1, NO.2, NO.3, NO.4, and NO.5.

[0113] (3) Randomly perform 5 impact tests in each area to verify the reliability of the impact area identification. That is, according to the rough positioning step provided by the present invention, the DTW algorithm and the KNN algorithm are used to identify the impact area. In order to avoid the situation where the number of label signals of the first K elements is the same (such as AB, AABB) and the decision result is not unique, in this case, when the KNN algorithm is used for decision making, the K value is 1. The rough positioning result is as follows: Figure 11As shown in the figure, the horizontal axis represents the actual impact area and the vertical axis represents the identified impact position. Figure 11 It can be seen that the method proposed in the present invention can effectively identify the impact area with an accuracy rate of up to 98.75% (79 / 80). The only recognition error is that the impact of area C is identified as area D.

[0114] (4) According to the precise positioning step provided by the present invention, the DTW algorithm and the weighted centroid positioning algorithm are used to identify the impact position of the impact area. The precise positioning result is as follows: Figure 12 As shown in the figure, the precise positioning results are very close to the actual position, the maximum absolute error of the impact position does not exceed 40 mm, and the maximum average error does not exceed 20 mm, which is much smaller than the minimum boundary length of 90 mm for dividing the area. This further proves the effectiveness and accuracy of the positioning method provided by the present invention.

[0115] (5) Figure 9 As shown, taking area G as a reference, a rubber ball with a height of 40mm is subjected to free fall impact in each area, and the correction coefficient of each area is calculated. Then, a rubber ball with a height of 60mm is subjected to free fall impact in area G, and the impact energy is tested and corrected according to the energy detection steps provided by the invention. The energy detection results are shown as follows: Figure 13 As shown, according to Figure 13 It can be seen that before correction and compensation, the average error of impact energy estimation was 69.51%, and the estimation error of individual areas such as A, N, I, and P even exceeded 70%. After correction and compensation, the overall average error was only 8.70%. Although the average error after compensation in individual areas was slightly greater than the average error before compensation, the overall energy estimation method after error compensation is more stable and can continuously output highly reliable results. Therefore, the energy detection step provided by the present invention has the advantages of high stability and lower average error, which is more meaningful for practical application scenarios.

[0116] It should also be noted that the method and system provided by this invention are applicable not only to composite flat panels but also to complex structures with dense ribs, such as aircraft fuselage panels and wing skins. When applied to aircraft structural maintenance, repair work can be confined to a limited area. Furthermore, energy estimation can provide a priori knowledge of composite material damage, thereby reducing maintenance costs and improving repair efficiency.

[0117] In summary, compared with existing technologies, the impact location and energy detection method and system based on dynamic time warping provided by the present invention boasts accurate positioning, high impact inversion efficiency, and simple operation. It not only avoids the impact of structural complexity on positioning accuracy but also effectively controls impact energy estimation errors. While reducing maintenance costs, it also effectively improves positioning and detection efficiency, promising broad application prospects.

[0118] In addition, those skilled in the art should understand that, although there are many problems in the prior art, each embodiment or technical solution of the present invention may be improved in only one or several aspects, without having to simultaneously solve all the technical problems listed in the prior art or background art. Those skilled in the art should understand that any content not mentioned in a claim should not be construed as limiting the claim.

[0119] Although this document frequently uses terms such as sensor, training point, marker point, first sample database, second sample database, impact signal, DTW algorithm, K-nearest neighbor algorithm, and weighted centroid positioning algorithm, the possibility of using other terms is not excluded. These terms are used only to more conveniently describe and explain the essence of the present invention; interpreting them as any additional limitations is contrary to the spirit of the present invention; the terms "first," "second," and the like (if any) in the description and claims of the embodiments of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for impact location and energy detection based on dynamic time warping, characterized in that: The following steps are involved: an area processing step of disposing a plurality of sensors for receiving external impact signals on the composite material structure to be inspected, and dividing the surface of the composite material structure to be inspected into at least M areas; The sample acquisition step is to perform impact tests on a plurality of training points and marking points in each of the areas to obtain a first sample database and a second sample database containing impact signals; and Impact the surface of the composite material structure and obtain the fixed energy according to the impact signal received by several sensors Characteristic value under impact ; In the rough positioning step, if an impact event occurs, several sensors will receive the impact signal S impact ; Calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij , to obtain the set Q; According to the set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the rough positioning; In the fine positioning step, based on the impact area determined by coarse positioning, the impact signal S is calculated according to the DTW algorithm. impact DTW distance to all markers in the impact area of ​​the second sample database ; The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to achieve precise positioning; Energy detection step, based on the impact signal S received by sensors in all areas impact Obtain energy characterization value Calculate the energy of the impact according to the following formula : The method also includes an energy correction coefficient acquisition step, wherein after performing a test on the surface of the composite material structure with a fixed energy E0, one of the regions is selected as a reference region, and an energy characterization value of the reference region is obtained. , calculate the energy correction coefficient of each area relative to the reference area , the formula is as follows: ; ； in, is the number of sensors in the reference area, In the reference area The energy value of the impact signal corresponding to each sensor.

2. The impact location and energy detection method based on dynamic time warping according to claim 1, characterized in that: The region processing step further includes numbering each region to obtain a signal label; and in the sample acquisition step, the impact signal in each region is mapped into a corresponding signal label for storage.

3. The impact location and energy detection method based on dynamic time warping according to claim 2, characterized in that: In the sample acquisition step, the sample acquisition step of the first sample database is as follows: N (N≥1) training points are selected in each of the regions and impact tests are performed to obtain corresponding impact signals, and then the impact signals at each training point in each of the regions are mapped into corresponding signal labels and stored in the first sample database; The sample acquisition step of the second sample database is: selecting B marking points in each area and performing impact tests respectively to obtain corresponding impact signals, and then storing the impact signals obtained from the impact tests of each marking point in each area as samples.

4. The impact location and energy detection method based on dynamic time warping according to claim 3, characterized in that: In the coarse positioning step, the K-nearest neighbor algorithm is used to determine the impact area where the impact event occurred, specifically including: The DTW distance L in the set Q ij Sort in ascending order and take the first K items L ij , K is an odd number not greater than N, and the first K DTW distances L are counted ij The corresponding area, where the DTW distance L ij The location with the most corresponding areas is determined as the impact area.

5. The impact location and energy detection method based on dynamic time warping according to claim 3, characterized in that: In the fine positioning step, the obtained The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm, specifically including the following formula: , ； ， ； in, Represents the weighting coefficient of all marked points in the impact area; 、 Respectively represent the coordinate positions of all marked points in the impact area; 、 is the impact position coordinate of the impact event.

6. The impact location and energy detection method based on dynamic time warping according to claim 1, characterized in that: In the sample acquisition step, the following formula is used to obtain the fixed energy Characteristic value under impact : ； ； in, is the expression of the shock signal obtained by the sensor, is the energy value of the corresponding impact signal; is the number of sensors deployed on the composite material structure to be detected, For the The energy value of the impact signal corresponding to each sensor; In the energy detection step, the energy characterization value when the impact event occurs is obtained by the following formula: : ； in, When the shock event occurs The energy value of the impact signal corresponding to each sensor.

7. The impact location and energy detection method based on dynamic time warping according to claim 1, characterized in that: The energy correction step is also included, based on the impact area determined by the rough positioning, according to the energy correction coefficient Obtain the energy correction coefficient of the impact area relative to the reference area And the corrected impact energy value is obtained by the following formula : 。 8. An impact location and energy detection system based on dynamic time warping, characterized by: include an area processing module, configured to arrange a plurality of sensors for receiving external impact signals on the composite material structure to be inspected, and to divide the surface of the composite material structure to be inspected into at least M areas; The sample acquisition module performs impact tests on a number of training points and marking points in each area to obtain a first sample database and a second sample database containing impact signals; and Impact the surface of the composite material structure and obtain the fixed energy according to the impact signal received by several sensors Characteristic value under impact ; Coarse positioning module, if a certain impact event occurs, some of the sensors will receive the impact signal S impact ; Used to calculate the impact signal S according to the DTW algorithm impact The DTW distance L of all samples in the first sample database ij , to obtain the set Q; According to the set Q, the K nearest neighbor algorithm is used to determine the impact area where the impact event occurs to complete the rough positioning; The fine positioning module is used to calculate the impact signal S according to the DTW algorithm based on the impact area determined by the coarse positioning. impact DTW distance to all markers in the impact area of ​​the second sample database ; the obtained The impact position coordinates (x, y) within the impact area are calculated as the weight factor of the weighted centroid positioning algorithm to achieve precise positioning; Energy detection module, used to detect the impact signal S received by sensors in all areas impact Obtain energy characterization value Calculate the energy of the impact according to the following formula : The energy correction module is also included. After performing a test on the surface of the composite material structure with a fixed energy E0, one of the areas is selected as a reference area to obtain the energy characterization value of the reference area. , calculate the energy correction coefficient of each area relative to the reference area , the formula is as follows: ; ； in, is the number of sensors in the reference area, In the reference area The energy value of the impact signal corresponding to each sensor.

9. The impact location and energy detection device based on dynamic time warping according to claim 8, characterized in that: The energy correction module is also used to determine the impact area based on the rough positioning, according to the energy correction coefficient Obtain the energy correction coefficient of the impact area relative to the reference area And the corrected impact energy value is obtained by the following formula : 。

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