An ultrasonic guided wave monitoring solid engine shell damage positioning method

Abstract

The application discloses a kind of ultrasonic guided wave monitoring solid engine shell damage positioning method, comprising the following steps: the monitoring area on the measured shell is arranged on the periphery of multiple sensor pairs, based on the arrival time of guided wave packet selects first order and second order A0 mode guided wave signal to carry out damage monitoring;The damage index of first order guided wave and second order guided wave of each sensor pair is fused;Based on the damage index after fusion, the damage probability of each pixel point is calculated and summed up;Damage probability is corrected using correction function;The damage probability result obtained is visualized and imaged, and the position of the maximum damage probability is the final defect position.The application utilizes two-order A0 mode and directly fuses its damage index, improves the sensitivity to damage;The damage probability is corrected using correction function, and the problem of false damage due to the damage probability of the intersection of different sensor paths being too large in the traditional probability imaging method is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of solid engine shell health monitoring, and particularly relates to an ultrasonic guided wave monitoring solid engine shell damage positioning method. BACKGROUND

[0002] The solid engine shell structure is subjected to various force loads (such as support pressure, overload, collision) and environmental loads (such as vibration, impact) in the storage and transportation process, and the structure is prone to produce debonding, cracking and other damages inside, which seriously threatens the normal work of the solid engine. In order to improve the safety and reliability of aerospace structures, structural health monitoring (SHM) is needed. The ultrasonic guided wave technology has attracted widespread attention from scholars due to its high sensitivity and wide monitoring range. The use of ultrasonic guided waves for damage imaging is expected to directly provide information such as damage location and damage degree on the solid engine shell, and the imaging method of ultrasonic guided waves has important significance. For ultrasonic guided waves, the imaging methods mainly include phased array imaging method, probability imaging method, elliptical positioning method, etc., and these methods have been used for damage positioning of plate structures.

[0003] The probability imaging method of ultrasonic guided waves is widely used. This method usually uses the signal difference coefficient (SDC) as the damage index, determines the damage probability near the path by the distribution function of the damage index on each path, superimposes the damage probabilities of multiple paths, and realizes damage positioning by taking the maximum value of the superimposed probability.

[0004] However, the probability imaging method of ultrasonic guided waves has the following problems when applied to cylindrical structures: 1. In the traditional probability imaging method used for pipeline damage imaging, the damage probability is obtained by superimposing the probability distribution of each sensing path, so the probability is more likely to reach the maximum value at the intersection point of the sensing paths, thereby directly affecting the damage positioning accuracy after imaging. For the damage distribution probability of an excitation-receiving path, no matter where the real damage is located, the closer the pixel point to the direct path of the excitation-receiving path, the greater the probability of damage, thus inevitably causing the calculation value of the damage index in the area near the intersection point of the paths to be higher than that in other areas, especially at multiple path intersection points, which affects the damage positioning accuracy. 2. In the existing pipeline damage imaging method, the damage index is usually calculated by using spiral guided waves, and there is still a lack of related methods for accurately selecting the order and mode of spiral guided waves, and how to fuse the results of spiral guided waves of different orders to improve the accuracy is a problem currently faced.

[0005] Therefore, it is necessary to improve one or more of the problems existing in the above-mentioned related technical solutions.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] This application provides a method for locating damage to a solid rocket motor casing using ultrasonic guided wave monitoring, characterized by the following steps:

[0008] Step 1: Sparsely arrange multiple sensor pairs around the monitoring area on the solid rocket motor casing under test, determine the propagation paths of the first-order and second-order guided waves of the sensor pairs, calculate the arrival time of guided wave packets of different modes, and select the first-order and second-order A0 mode guided wave signals for damage monitoring based on the arrival time of the guided wave packets.

[0009] Step 2: Based on the A0 mode guided wave signals of the first-order and second-order guided waves of each sensor pair, calculate their respective damage indices, and then fuse the two damage indices according to the following formula:

[0010] DI = w1 × DI1 + w2 × DI2

[0011] Wherein, DI1 and DI2 are the damage indices of the A0 mode guided wave signals of the first-order and second-order guided waves on the same path, respectively, DI is the damage index obtained after fusion, and w1 and w2 are the weights corresponding to DI1 and DI2 respectively.

[0012] Step 3: Based on the fused damage index, calculate the damage probability of each pixel and sum them to obtain the damage probability of pixels in the monitoring area, as shown in the following formula;

[0013]

[0014] Wherein, P(x p ,y p ) represents the pixel points (x) within the monitoring area. p ,y p The probability of damage, where N is the number of sensor pairs, and P is the number of sensor pairs. ij (x p ,y p ) is the result of the sensor on k ij The obtained pixel points (x p ,y p The probability of damage, β is the maximum relative range of the damage effect, and R is the damage probability. ij (x p ,y p ) is the pixel (x) p ,yp ) to sensor pair k ij The relative distance;

[0015] Step 4: Use a correction function to correct the pixel damage probability within the affected area, and finally obtain the corrected damage probability as follows:

[0016]

[0017] Where, P′(x p ,y p (x) represents the pixels within the corrected area of ​​influence. p ,y p The probability of damage, c is the width parameter of the exponential function, e is the natural constant, K is the intercept of the correction function, and d k For the sensor at the intersection of the propagation path (x) k ,y k ) to pixel (x p ,y p The distance ω k The weight is M, and the number of intersections within the affected area is M.

[0018] Step 5: Visualize and image the damage probability results obtained in Step 4. The location with the highest damage probability is the final location of the defect.

[0019] Furthermore, in step 2, the damage index DI of the A0 mode guided wave signals of the first-order and second-order guided waves along the same path is... i It is calculated using the following formula:

[0020]

[0021] Where the subscript h represents the healthy state, the subscript uh represents the damaged state, E is the wave packet energy, and t s Let t be the start time of the wave packet. f V(t) represents the end time of the wave packet and is the A0 mode guided wave signal.

[0022] Furthermore, in step 2, the weights w1 and w2 satisfy w1 + w2 = 2.

[0023] Furthermore, in step 3, the pixel (x) p ,y p The relative distance Rij(xp,yp) from the sensor to kij is the distance between the pixel (xp and yp). p ,y p The ratio of the sum of the distances to excitation sensor i and receiving sensor j to the distance between excitation sensor i and receiving sensor j.

[0024] Furthermore, in step 3, the pixel points (x) obtained by the sensor from kijp ,y p ) is calculated according to the formula P ij (x p ,y p ) = DI ij × W n (x p ,y p ), wherein DI ij is the damage index of the sensor pair kij after fusion obtained according to step 2, and W n (x p ,y p ) is a weight factor.

[0025] Further, the weight factor W n (x p ,y p ) is calculated according to the formula

[0026]

[0027] .

[0028] Further, the maximum relative range β of damage influence is 1.05.

[0029] Further, in step 4, d k is calculated according to the formula

[0030]

[0031] , wherein R max is the maximum damage probability influence range.

[0032] Further, in step 4, the parameter c and the parameter K are obtained in the following manner:

[0033] A simulation damage pre-experiment is performed, and the c parameter and the K parameter in the correction function are determined by comparing the positioning errors of the simulation damage positioning under different parameters, so as to ensure that the positioning error is minimum.

[0034] Further, the influence area is a circular range with the intersection (x k ,y k ) of the sensor pair propagation path as the center and the maximum radius of the correction area as the radius.

[0035] Beneficial effects:

[0036] The technical scheme provided by the embodiments of the present application can include the following beneficial effects:

[0037] The damage positioning method of the application makes full use of the second-order A0 mode which is more sensitive to damage, and directly fuses the damage indicators of the second-order A0 mode, thereby improving the sensitivity to damage; then, a correction function is used to improve the traditional probability imaging method, thereby reducing the influence of the change of the damage probability index at the intersection of the sensor paths, solving the problem of false damage caused by the traditional probability imaging method which has a larger damage probability at the intersection of different sensor paths, and further improving the accuracy of damage positioning. BRIEF DESCRIPTION OF DRAWINGS

[0038] The drawings incorporated in the specification and constituting a part thereof illustrate embodiments consistent with the application and, together with the specification, serve to explain the principles of the application. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained from these drawings without creative labor for those skilled in the art.

[0039] Figure 1 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0040] Figure 2 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0041] Figure 3 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0042] Figure 4 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0043] Figure 5 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0044] Figure 6 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0045] Figure 7 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application;

[0046] Figure 8 (a) A simulation diagram of a specimen and (b) an experimental specimen in an exemplary embodiment of the application; DETAILED DESCRIPTION

[0047] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0048] Furthermore, the accompanying drawings are merely illustrative of this application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0049] This example embodiment provides a method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring. Taking a simulated solid rocket motor casing—a cylindrical specimen made of T300 carbon fiber composite material—as an example, the improved probabilistic imaging method of this invention is further described in detail. The specimen is 1000 mm long, with an inner diameter of 367 mm, an outer diameter of 370 mm, and a thickness of 3 mm. The fiber layup direction is [0 / 90 / 0 / 90 / 0 / 90]2s, with each layer being 0.125 mm thick, for a total of 24 layers.

[0050] Step 1: Sparsely arrange multiple sensor pairs around the monitoring area on the cylindrical specimen. Each sensor pair consists of an excitation sensor and a receiving sensor, surrounding the monitoring area. The piezoelectric sheet used in the experiment is a P5-1 circular piezoelectric sheet with a diameter of 8 mm and a thickness of 0.3 mm. Eight piezoelectric sheets are arranged in two rows and attached to the specimen, as shown in the diagram. Figure 1 As shown in the diagram. The blue circles represent the excitation and receiving sensors, forming a rectangular sensor array. A magnet with a diameter of 20mm and a thickness of 24mm is used to simulate damage, with the simulated damage location at (220, 195). Figure 1 As shown in the orange circle, after a single piezoelectric element is excited, a helical guided wave is generated. This is used to determine the propagation paths of the first-order and second-order guided waves of the sensor pair. The propagation path of the first-order guided wave is the shortest direct wave. The propagation path of the second-order guided wave is to reach the receiving sensor after circling the shell once. Based on the group velocity of the composite material in different propagation directions, the arrival time of the guided wave packets of different modes is calculated. On this basis, the excitation signal is input, and the first-order and second-order A0 guided wave signals are selected for damage monitoring.

[0051] Input the excitation signal, measure the first-order and second-order A0 mode ultrasonic guided wave signals of each sensor pair of the cylinder specimen in the healthy state as the benchmark, and store them.

[0052] Input the excitation signal, measure the ultrasonic guided wave receiving signals of the cylinder specimen in the simulated damage state, and store them.

[0053] Step 2: For the A0 mode guided wave signals of each sensor pair, the direct wave of the corresponding wave packet is used to calculate the damage index of each sensor pair based on the first-order guided wave and the second-order guided wave A0 mode guided wave signals, and the two damage indexes are fused according to the following formula:

[0054] DI = w1 x DI1 + w2 x DI2

[0055] Where DI1 and DI2 are the damage indexes of the first-order guided wave and the second-order guided wave A0 mode guided wave signals on the same path, DI is the damage index after fusion, w1 and w2 are the respective weights of DI1 and DI2, and w1 + w2 = 2.

[0056] The damage index DI of the first-order guided wave and the second-order guided wave A0 mode guided wave signals on the same path i is calculated by the following formula:

[0057]

[0058] Where subscript h represents the healthy state, subscript uh represents the damage state, E is the wave packet energy, t s is the start time of the wave packet, t f is the end time of the wave packet, and V(t) is the A0 mode guided wave signal.

[0059] Step 3: The propagation path of the first-order guided wave (direct wave) of each sensor pair is used for probabilistic imaging, and the damage probability of each pixel point is calculated based on the fused damage index and summed to obtain the damage probability of the pixel points in the monitoring area, as shown in the following formula:

[0060]

[0061] Where P(x p ,y p ) is the damage probability of the pixel point (x p ,y p ) in the monitoring area, N is the number of sensor pairs, P ij (x p ,y p ) is the pixel point (x ij ,y p ) obtained by the sensor pair k p .The probability of damage is R, where β is the maximum relative range of the damage effect, and the probability of damage beyond this range is zero. ij (x p ,y p ) is the pixel (x) p ,y p The relative distance from the sensor to the kij.

[0062] Pixel (x) p ,y p ) to sensor pair k ij relative distance R ij (x p ,y p ) is the pixel (x) p ,y p The ratio of the sum of the distances to excitation sensor i and receiving sensor j to the distance between excitation sensor i and receiving sensor j.

[0063] By sensor for k ij The obtained pixel points (x p ,y p The probability of damage P) ij (x p ,y p According to formula P ij (x p ,y p ) = DI ij ×W n (x p ,y p ) is calculated to obtain, where DI ij To determine the damage index of the fused Kij sensor obtained in step 2, W n (x p ,y p W is the weighting factor. n (x p ,y p According to the formula

[0064]

[0065] Calculated.

[0066] like Figure 2 As shown, the greater the relative distance from the sensor pair, the lower the probability of damage.

[0067] The maximum relative range of the damage's impact, β, is set to 1.05. A value that is too small (β) typically leads to localization failure, while a value that is too large (β) reduces the resolution of the imaging algorithm.

[0068] Step 4: Correct the pixel damage probability within the affected area using a correction function. The correction function consists of a negative exponential function, a quadratic function, and a decreasing linear function, with its origin located at the intersection of the propagation paths between the sensor pairs, as shown in the following equation:

[0069]

[0070] Where c is the width parameter of the exponential function, and e is the natural constant. Standardize the exponential function, where K is the intercept of the correction function, and d k For the sensor at the intersection of the propagation path (x) k ,y k ) to pixel (x p ,y p The distance dk is calculated according to the formula.

[0071]

[0072] The calculation yields R, where R is the largest known value. max This represents the range affected by the maximum probability of damage.

[0073] Taking the intersection of a certain sensor's propagation path as an example, such as Figure 3 As shown, with the intersection of the sensor and the propagation path as the center, the maximum influence range R is... max A circular region is established with a radius of 1. Circular influence regions are then established at the intersection of each sensor pair's propagation path. Based on the number of excitation-reception propagation paths within the monitored area and the number of intersection points of the sensor pair's propagation paths, the damage probability of each pixel is corrected. The final corrected damage probability is:

[0074]

[0075] Where, P′(x p ,y p (x) represents the pixels within the corrected area of ​​influence. p ,y p The damage probability of ) is ωk, where ωk is the weight, and its magnitude depends on the intersection point (x) with the sensor on the propagation path. k ,y k The number of intersecting paths, where M is the number of intersection points within the affected area.

[0076] like Figure 4 As shown, the correction functions corresponding to different values ​​of c and K are obtained in the following ways:

[0077] A magnet was used as a simulated damage source within the piezoelectric sensor monitoring area to conduct a preliminary damage simulation experiment. In the preliminary experiment, the initial parameters of the correction function were K = 0.15 and R... max=150mm, c=0.50, w1=w2=1. The propagation path of the A0 mode guided wave is as follows: Figure 5 As shown, the damage monitoring area is 300mm × 500mm, with 16 excitation-receiver paths. The sensor intersects the propagation paths at 27 points, indicated by red circles in the figure. Based on the corrected damage localization error within the damage monitoring area, the parameters (K and c) of the correction function are adjusted, along with the parameters (w1 and w2) of the fused damage index. A set of parameters with the smallest localization error is then selected, such as... Figure 6 As shown, when K = 0.15, the positioning error is minimized when c is 0.6. Subsequently, c = 0.6 was fixed, and the positioning error corresponding to different K values ​​was calculated. The positioning error is minimized when K = 0.25. Therefore, the final selection of the correction function parameters is K = 0.25 and c = 0.6.

[0078] Step 5: Visualize and image the damage probability results obtained in Step 4. The location with the highest damage probability is the final location of the defect.

[0079] After preliminary testing, the positioning error was compared with that obtained using the traditional probabilistic imaging method. The results of the traditional probabilistic imaging method and the improved probabilistic imaging method proposed in this application are as follows: Figure 7 and Figure 8 As shown in the figure, the proposed improved probabilistic imaging method further enhances imaging accuracy and reduces positioning error.

[0080] The above description is merely a specific embodiment of the present invention, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the scope of the technology disclosed in this invention, and these modifications or substitutions should all be covered within the scope of protection of this application.

[0081] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

Claims

1. A method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring, characterized in that, Includes the following steps: Step 1: Sparsely arrange multiple sensor pairs around the monitoring area on the solid rocket motor casing under test, determine the propagation paths of the first-order and second-order guided waves of the sensor pairs, calculate the arrival time of guided wave packets of different modes, and select the first-order and second-order A0 mode guided wave signals for damage monitoring based on the arrival time of the guided wave packets. Step 2: Based on the A0 mode guided wave signals of the first-order and second-order guided waves of each sensor pair, calculate their respective damage indices, and then fuse the two damage indices according to the following formula: DI = w1 × DI1 + w2 × DI2 Wherein, DI1 and DI2 are the damage indices of the A0 mode guided wave signals of the first-order and second-order guided waves on the same path, respectively; DI is the damage index after fusion; and w1 and w2 are the weights of DI1 and DI2 respectively. Step 3: Based on the fused damage index, calculate the damage probability of each pixel and sum them to obtain the damage probability of pixels in the monitoring area, as shown in the following formula; Wherein, P(x p ,y p ) represents the pixel points (x) within the monitoring area. p ,y p The probability of damage, where N is the number of sensor pairs, and P is the number of sensor pairs. ij (x p ,y p ) is the result of the sensor on k ij The obtained pixel points (x p ,y p The probability of damage, β is the maximum relative range of the damage effect, and R is the damage probability. ij (x p ,y p ) is the pixel (x) p ,y p ) to sensor pair k ij The relative distance; Step 4: Use a correction function to correct the damage probability of pixels within the affected area, and finally obtain the corrected damage probability as follows: Where, P′(x p ,y p (x) represents the pixels within the corrected area of ​​influence. p ,y p The probability of damage, c is the width parameter of the exponential function, e is the natural constant, K is the intercept of the correction function, and d k For the sensor at the intersection of the propagation path (x) k ,y k ) to pixel (x p ,y p The distance ω k The weight is M, and the number of intersections within the affected area is M. Step 5: Visualize and image the damage probability results obtained in Step 4. The location with the highest damage probability is the final location of the defect.

2. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, In step 2, the damage index DI of the A0 mode guided wave signals of the first-order and second-order guided waves along the same path is... i It is calculated using the following formula: Where the subscript h represents the healthy state, the subscript uh represents the damaged state, E is the wave packet energy, and t s Let t be the start time of the wave packet. f V(t) represents the end time of the wave packet and is the A0 mode guided wave signal.

3. The method for locating damage to a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, In step 2, the weights w1 and w2 satisfy w1 + w2 = 2.

4. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, In step 3, the pixel (x) p ,y p The relative distance Rij(xp,yp) from the sensor to kij is the distance between the pixel (xp and yp). p ,y p The ratio of the sum of the distances to excitation sensor i and receiving sensor j to the distance between excitation sensor i and receiving sensor j.

5. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 4, characterized in that, In step 3, the pixel points (x) obtained by the sensor from kij p ,y p The probability of damage P) ij (x p ,y p According to formula P ij (x p ,y p ) = DI ij ×W n (x p ,y p ) is calculated to obtain, where DI ij To determine the damage index of the fused Kij sensor obtained in step 2, W n (x p ,y p ) is the weighting factor.

6. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 5, characterized in that, Weighting factor W n (x p ,y p According to the formula Calculated.

7. The method for locating damage to a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 6, characterized in that, The maximum relative range of the damage effect, β, is set to 1.

05.

8. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, In step 4, d k According to the formula The calculation yields R, where R is the largest known value. max This represents the range affected by the maximum probability of damage.

9. The method for locating damage in a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, In step 4, parameters c and K are obtained in the following way: A simulated damage pre-experiment was conducted. By comparing the errors in simulated damage localization under different parameters, the c and K parameters in the correction function were determined to ensure that the localization error was minimized.

10. The method for locating damage to a solid rocket motor casing using ultrasonic guided wave monitoring according to claim 1, characterized in that, The affected area refers to the point (x) at the intersection of the propagation paths as observed by the sensor. k ,y k The circle is defined by a radius of 1, where 1 is the center and the maximum radius of the correction area is 1.

Images