Detection Modeling Method, Device, Equipment and Storage Medium for Aircraft Windshield Cracks

Abstract

The present application discloses a method, device, equipment and storage medium for detecting and modeling cracks in an aircraft windshield. The crack detection of the target windshield is carried out by ultrasonic detection technology; if there are cracks on the target windshield, the crack area and crack depth data on the target windshield are determined; the overhead image data corresponding to the crack area is collected, and the overhead image data and the crack depth data are input into a trained machine learning model, and the machine learning model is used to identify the crack projection position to obtain the corresponding crack projection position identification result; according to the standard module data, crack area, crack depth data and crack projection position identification result corresponding to the target windshield, the cracks of the target windshield are modeled to obtain a modeling result. This method can improve the accuracy of crack detection and the presentation effect of the detection result, which is beneficial to providing more valuable information for maintenance and improving the practicability of crack detection. The present application can be widely applied in the field of aircraft technology.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft, and in particular to a method, device, equipment and storage medium for detecting and modeling cracks in an aircraft windshield. Background Art

[0002] An aircraft is an aerial vehicle that can fly in the atmosphere. It usually relies on the lift generated by its wings to support the weight of the fuselage and moves forward through the thrust or pull provided by the engine. An aircraft windshield refers to the transparent glass installed in front of the aircraft cockpit, which is usually composed of multiple layers of materials. Its main function is to protect the pilot and passengers from the influence of air currents, rain, hail and other external factors, and at the same time be able to withstand the pressure and temperature changes during high-speed flight. Due to the complex flight conditions, cracks may occur in the aircraft windshield, and it is necessary to detect and analyze the cracks to facilitate the determination of corresponding maintenance strategies.

[0003] In the related art, when detecting cracks in an aircraft windshield, relevant detection equipment is often used to detect cracks at each site one by one. The obtained detection results can only indicate whether there are cracks, but it is difficult to clearly display the specific conditions of the cracks. The detection accuracy is low, and it is difficult to provide valuable information for maintenance, so the practicability is poor. Summary of the Invention

[0004] The purpose of the present application is to solve at least to some extent one of the technical problems existing in the related art.

[0005] To this end, an object of an embodiment of the present application is to provide a method, device, equipment and storage medium for detecting and modeling cracks in an aircraft windshield.

[0006] In order to achieve the above technical purpose, the technical solutions adopted in the embodiments of the present application include:

[0007] On the one hand, an embodiment of the present application provides a method for detecting and modeling cracks in an aircraft windshield, the method including:

[0008] Detecting cracks in a target windshield by ultrasonic detection technology;

[0009] If there are cracks on the target windshield, determining the crack area and crack depth data on the target windshield;

[0010] Collecting the top-view image data corresponding to the crack area, inputting the top-view image data and the crack depth data into a trained machine learning model, and identifying the crack projection position through the machine learning model to obtain the corresponding crack projection position identification result;

[0011] Model the crack of the target windshield based on the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position recognition result, to obtain a modeling result.

[0012] In addition, according to a method for detecting and modeling cracks in an aircraft windshield according to the above embodiments of the present application, the following additional technical features may also be provided:

[0013] Further, in an embodiment of the present application, the target windshield includes a first inorganic glass layer, a second inorganic glass layer, and an organic glass layer;

[0014] The first surface of the first inorganic glass layer is the outer surface of the target windshield, the second surface of the first inorganic glass layer is in contact with the first surface of the organic glass layer, the second surface of the organic glass layer is in contact with the first surface of the second inorganic glass layer, and the second surface of the second inorganic glass layer is the inner surface of the target windshield.

[0015] Further, in an embodiment of the present application, the crack detection of the target windshield by ultrasonic detection technology includes:

[0016] Send ultrasonic waves to any detection area on the target windshield and receive the echo data corresponding to the ultrasonic waves;

[0017] If the echo data is disordered, determine that there is a crack in the target windshield in the detection area;

[0018] Determine the target surface where the crack is located according to the time node when the echo data is disordered.

[0019] Further, in an embodiment of the present application, determining the crack depth data on the target windshield includes:

[0020] If the target surface is the first surface of the first inorganic glass layer, obtain the first duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the first inorganic glass layer;

[0021] Determine the crack depth data according to the product of the first duration and the reference propagation speed of the ultrasonic wave in the air.

[0022] Further, in an embodiment of the present application, determining the crack depth data on the target windshield includes:

[0023] If the target surface is the first surface of the plexiglass layer, obtain the second thickness data of the plexiglass layer, the second propagation speed of the ultrasonic wave in the plexiglass layer, the reference propagation speed of the ultrasonic wave in the air, the second reference duration of the ultrasonic wave passing through the plexiglass layer of the template windshield, the total reference duration of the ultrasonic wave passing through the template windshield, and the total duration of the ultrasonic wave passing through the target windshield; wherein, the template windshield is a windshield with the same model as the target windshield and without cracks.

[0024] Establish a first system of equations, and the formula of the first system of equations is:

[0025] H 2 = v 0 * t 21 + v 2 * t 22

[0026] t 21 + t 22 - t 2 = t 总 - t

[0027] In the formula, H 2 represents the second thickness data of the plexiglass layer, v 0 represents the reference propagation speed of the ultrasonic wave in the air, t 21 represents the second duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the plexiglass layer, v 2 represents the second propagation speed of the ultrasonic wave in the plexiglass layer, t 22 represents the third duration corresponding to the propagation of the ultrasonic wave in the plexiglass layer except for the crack, t 2 represents the second reference duration of the ultrasonic wave passing through the plexiglass layer of the template windshield, t 总 represents the total reference duration of the ultrasonic wave passing through the template windshield, and t represents the total duration of the ultrasonic wave passing through the target windshield;

[0028] Solve the first system of equations to obtain the second duration;

[0029] Determine the crack depth data according to the second duration and the reference propagation speed of the ultrasonic wave in the air.

[0030] Further, in an embodiment of the present application, determining the crack depth data on the target windshield includes:

[0031] If the target surface is the second surface of the second inorganic glass layer, obtain the third thickness data of the second inorganic glass layer, the third propagation speed of the ultrasonic wave in the second inorganic glass layer, the first reference duration for the ultrasonic wave to pass through the first inorganic glass layer, the second reference duration for the ultrasonic wave to pass through the organic glass layer of the template windshield, and the total duration for the ultrasonic wave to pass through the target windshield; wherein, the template windshield is a windshield with the same model as the target windshield and without cracks.

[0032] Calculate the difference obtained by subtracting the first reference duration and the second reference duration from the total duration to obtain a fourth duration.

[0033] Obtain a fourth thickness data based on the product of the fourth duration and the third propagation speed.

[0034] Calculate the difference between the third thickness data and the fourth thickness data to obtain the crack depth data.

[0035] On the other hand, an embodiment of the present application provides a detection and modeling device for cracks in an aircraft windshield, and the device includes:

[0036] A detection unit for detecting cracks in the target windshield through ultrasonic detection technology.

[0037] A processing unit for determining the crack area and crack depth data on the target windshield if there are cracks on the target windshield.

[0038] An identification unit for collecting the top-view image data corresponding to the crack area, inputting the top-view image data and the crack depth data into a trained machine learning model, and identifying the crack projection position through the machine learning model to obtain a corresponding crack projection position identification result.

[0039] An integration unit for modeling the cracks in the target windshield according to the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position identification result to obtain a modeling result.

[0040] Further, in an embodiment of the present application, the target windshield includes a first inorganic glass layer, a second inorganic glass layer, and an organic glass layer.

[0041] The first surface of the first inorganic glass layer is the outer surface of the target windshield, the second surface of the first inorganic glass layer is in contact with the first surface of the organic glass layer, the second surface of the organic glass layer is in contact with the first surface of the second inorganic glass layer, and the second surface of the second inorganic glass layer is the inner surface of the target windshield.

[0042] On the other hand, an embodiment of the present application provides a computer device, including:

[0043] At least one processor;

[0044] At least one memory for storing at least one program;

[0045] When the at least one program is executed by the at least one processor, the at least one processor is caused to implement the above-mentioned method for detecting and modeling cracks in an aircraft windshield.

[0046] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, in which a program executable by a processor is stored, and the program executable by the processor is used to implement the above-mentioned method for detecting and modeling cracks in an aircraft windshield when executed by the processor.

[0047] The advantages and beneficial effects of the present application will be partially given in the following description, partially will become obvious from the following description, or will be understood through the practice of the present application:

[0048] A method for detecting and modeling cracks in an aircraft windshield disclosed in an embodiment of the present application performs crack detection on a target windshield through ultrasonic detection technology; if there are cracks on the target windshield, the crack area and crack depth data on the target windshield are determined; the top-down image data corresponding to the crack area is collected, and the top-down image data and the crack depth data are input into a trained machine learning model, and the crack projection position is identified through the machine learning model to obtain a corresponding crack projection position identification result; according to the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position identification result, the cracks on the target windshield are modeled to obtain a modeling result. This method can perform modeling processing on cracks by integrating the crack area, crack depth data, and crack projection position information on the aircraft windshield, can improve the accuracy of crack detection and the presentation effect of detection results, and thus is beneficial to providing more valuable information for maintenance processing and improving the practicality of crack detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following introduces the accompanying drawings related to the technical solutions in the embodiments of the present application or the prior art. It should be understood that the accompanying drawings in the following introduction are only for conveniently and clearly presenting some embodiments of the technical solutions in the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative efforts.

[0050] Figure 1 It is a schematic diagram of the implementation environment of a method for detecting and modeling cracks in an aircraft windshield provided in an embodiment of the present application;

[0051] Figure 2 It is a schematic flowchart of a method for detecting and modeling cracks in an aircraft windshield provided in an embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of the top-view image data of cracks provided in an embodiment of the present application;

[0053] Figure 4 It is a schematic diagram of the projection position of cracks provided in an embodiment of the present application;

[0054] Figure 5 It is a schematic diagram of an aircraft windshield provided in an embodiment of the present application;

[0055] Figure 6 It is a schematic diagram of cracks existing on the first surface of a first inorganic glass layer provided in an embodiment of the present application;

[0056] Figure 7 It is a schematic diagram of cracks existing on the first surface of an organic glass layer provided in an embodiment of the present application;

[0057] Figure 8 It is a schematic diagram of cracks existing on the second surface of a second inorganic glass layer provided in an embodiment of the present application;

[0058] Figure 9 It is a schematic structural diagram of a computer device provided in an embodiment of the present application. Detailed implementation manners

[0059] The present application will be further described below in conjunction with the accompanying drawings of the specification and specific embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present application.

[0060] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0062] Before further elaborating on the embodiments of the present application, the nouns and terms involved in the embodiments of the present application are described. The nouns and terms involved in the embodiments of the present application are applicable to the following explanations:

[0063] 1) Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a way similar to human intelligence. Artificial intelligence also studies the design principles and implementation methods of various intelligent machines, enabling machines to have the functions of perception, reasoning, and decision-making.

[0064] Artificial intelligence technology is an interdisciplinary subject with a wide range of fields, including both hardware-level and software-level technologies. The basic technologies of artificial intelligence generally include sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, pre-trained model technology, operation / interaction systems, mechatronics, etc. Among them, the pre-trained model, also known as the large model or the foundation model, can be widely applied to downstream tasks in various directions of artificial intelligence after fine-tuning. The software technologies of artificial intelligence mainly include computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning in several major directions.

[0065] 2) Machine Learning (ML) is an interdisciplinary subject that involves multiple disciplines such as probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. It specifically studies how computers simulate or implement human learning behaviors to acquire new knowledge or skills and reorganize the existing knowledge structure to continuously improve their own performance. Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent, and its applications cover all fields of artificial intelligence. Machine learning and deep learning usually include technologies such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and rote learning. The pre-trained model is the latest development result of deep learning, integrating the above technologies.

[0066] 3) Crack projection position: Place the aircraft windshield flat downwards and look down. The projection of the deepest point of each crack on the aircraft windshield on the top-down plane is the crack projection position.

[0067] An aircraft is an aerial vehicle capable of flying in the atmosphere. It usually relies on the lift generated by its wings to support the weight of the fuselage and moves forward through the thrust or pull provided by the engine. The aircraft windshield refers to the transparent glass installed in front of the aircraft cockpit, usually composed of multiple layers of materials. Its main function is to protect the pilot and passengers from the influence of airflows, rain, hail and other external factors, and at the same time be able to withstand the pressure and temperature changes during high-speed flight. Due to the complex flight conditions, cracks may appear in the aircraft windshield, and it is necessary to detect and analyze the cracks to facilitate the determination of corresponding maintenance strategies.

[0068] In the related art, when detecting cracks in an aircraft windshield, relevant detection equipment is often used to detect cracks at each point one by one. The obtained detection results can only indicate whether there are cracks, but it is difficult to clearly display the specific conditions of the cracks. The detection accuracy is low, and it is difficult to provide valuable information for maintenance, so the practicability is poor.

[0069] In view of this, in the embodiments of the present application, a method for detecting and modeling cracks in an aircraft windshield is provided. The crack detection of the target windshield is carried out by ultrasonic detection technology; if there are cracks on the target windshield, the crack area and crack depth data on the target windshield are determined; the top-view image data corresponding to the crack area is collected, and the top-view image data and the crack depth data are input into a trained machine learning model. The machine learning model is used to identify the crack projection position to obtain the corresponding crack projection position recognition result; according to the standard module data corresponding to the target windshield, the crack area, the crack depth data and the crack projection position recognition result, the cracks on the target windshield are modeled to obtain a modeling result. This method can realize the modeling process of cracks by integrating the crack area, crack depth data and crack projection position information on the aircraft windshield, improve the accuracy of crack detection and the presentation effect of detection results, thus facilitating the provision of more valuable information for maintenance and improving the practicability of crack detection.

[0070] Refer to Figure 1 , Figure 1 shows a schematic diagram of the implementation environment of a method for detecting and modeling cracks in an aircraft windshield provided in the embodiments of the present application. In this implementation environment, the main software and hardware entities involved include a terminal device 110 and a background server 120.

[0071] In the embodiments of the present application, relevant application programs can be installed in the terminal device 110, and these application programs can be used to implement the detection and modeling of aircraft windshield cracks. The background server 120 can be the background server of the application program. The terminal device 110 and the background server 120 can be communicatively connected to each other. The background server 120 can be used to process the service data related to the application program and realize the relevant application program functions through the interaction with the terminal device 110. The method for detecting and modeling aircraft windshield cracks provided in the embodiments of the present application can be implemented independently by the terminal device 110 or can be implemented based on the interaction between the terminal device 110 and the background server 120.

[0072] Among them, the terminal device 110 in the above embodiments can include a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart watch, a vehicle-mounted terminal, etc., but is not limited thereto.

[0073] The background server 120 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0074] A communication connection can be established between the terminal device 110 and the background server 120 through a wireless network or a wired network. The wireless network or wired network uses standard communication technologies and / or protocols. The network can be set to the Internet or any other network, such as including but not limited to any combination of a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or a virtual private network. Moreover, among the above-mentioned software and hardware entities, the same communication connection method or different communication connection methods can be adopted, and the present application does not make specific limitations on this.

[0075] Of course, it can be understood that Figure 1 the implementation environment in Figure 1 is only some optional application scenarios of the method for detecting and modeling aircraft windshield cracks provided in the embodiments of the present application, and the actual application is not fixed to the

[0076] software and hardware environment shown. Next, in combination with the introduction of the foregoing implementation environment, a method for detecting and modeling aircraft windshield cracks provided in the embodiments of the present application will be introduced and described.

[0077] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of a method for detecting and modeling cracks in an aircraft windshield provided by an embodiment of the present application. Referring to Figure 2 , the method for detecting and modeling cracks in an aircraft windshield includes but is not limited to:

[0078] Step 210: Detect cracks in the target windshield through ultrasonic detection technology;

[0079] Step 220: If there are cracks on the target windshield, determine the crack area and crack depth data on the target windshield;

[0080] Step 230: Collect the top-down image data corresponding to the crack area, input the top-down image data and the crack depth data into a trained machine learning model, and identify the crack projection position through the machine learning model to obtain the corresponding crack projection position identification result;

[0081] Step 240: Model the cracks in the target windshield according to the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position identification result to obtain a modeling result.

[0082] In an embodiment of the present application, a method for detecting and modeling cracks in an aircraft windshield is provided. This method can comprehensively use the crack area, crack depth data, and crack projection position information on the aircraft windshield to implement modeling processing for cracks, which can improve the accuracy of crack detection and the presentation effect of detection results, thereby facilitating providing more valuable information for maintenance processing and improving the practicality of crack detection.

[0083] In an embodiment of the present application, ultrasonic detection technology and machine learning methods are used to detect and model cracks in an aircraft windshield. Specifically, the windshield to be detected is denoted as the target windshield. First, an ultrasonic probe can be used to scan the windshield to detect whether there are cracks. Ultrasonic detection is a non-destructive detection method that can effectively detect internal defects in materials, such as cracks. If cracks are detected, the position area of the cracks on the target windshield can be further determined. In an embodiment of the present application, it is denoted as the crack area. Exemplarily, for example, in some embodiments, the target windshield can be divided into multiple areas to be detected in advance, and then the ultrasonic probe is used to detect each area in turn. If a crack is found in a certain area, it can be determined as the crack area. Or, in some embodiments, detection can also be performed in the form of position points. When a certain position point is determined as the crack position point, the area near the position point can be determined as the crack area. In an embodiment of the present application, the specific size and shape of the crack area are not limited.

[0084] When it is determined that there is a crack, in the embodiments of the present application, the crack depth data corresponding to the crack can also be determined. Then, the top-down image data corresponding to the crack area can be collected, and the top-down image data and the crack depth data are input into the trained machine learning model. By using the machine learning model to identify the crack projection position, the corresponding crack projection position recognition result can be obtained.

[0085] In the embodiments of the present application, the crack projection position is the line segment formed by the deepest points of the crack. Exemplarily, please refer to Figure 3 , Figure 3 which shows a schematic diagram of the top-down image data of a crack provided in the embodiments of the present application. From Figure 3 it can be seen that in the top-down image data, the crack as a whole is an area. Although this image can reflect the shape characteristics of the crack to a certain extent, it is difficult to directly obtain the specific gully trend inside the crack. Therefore, in the embodiments of the present application, the specific bottom position points can be identified by combining the top-down image data of the crack and the crack depth data and using a machine learning model to process, so as to obtain the information of the crack projection position. Please refer to Figure 4 , Figure 4 which shows a schematic diagram of a crack projection position provided in the embodiments of the present application. Figure 4 The crack projection position in Figure 3 is determined from the top-down image data of

[0086] it can be seen that the crack projection position can clearly indicate the gully trend of the deepest points of the crack, which can facilitate the determination of the specific structure of the crack, thereby providing more valuable information for maintenance and improving the practicality of crack detection.

[0087] After obtaining the crack area, crack depth data, and crack projection position recognition result of the target windshield, the crack of the target windshield can be modeled in combination with the standard module data corresponding to the target windshield to obtain a modeling result. Here, the standard module data corresponding to the target windshield can record the shape and related parameter information of the target windshield without cracks, and it can be established in advance. For example, based on the template windshield corresponding to the target windshield, the standard module data can be established by scanning the template windshield from multiple angles. The template windshield has the same model as the target windshield and has no cracks. In the embodiments of the present application, the modeling result can comprehensively and accurately display the crack situation in the target windshield and improve the presentation effect of the detection result.

[0088] It can be understood that in the method for detecting and modeling cracks in an aircraft windshield provided in the embodiments of the present application, ultrasonic detection technology is used to detect cracks in the target windshield; if there are cracks on the target windshield, the crack area and crack depth data on the target windshield are determined; the top-view image data corresponding to the crack area is collected, and the top-view image data and the crack depth data are input into a trained machine learning model. The machine learning model is used to identify the crack projection position to obtain the corresponding crack projection position recognition result; according to the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position recognition result, the crack of the target windshield is modeled to obtain a modeling result. This method can comprehensively model the cracks by integrating the crack area, crack depth data, and crack projection position information on the aircraft windshield, improve the accuracy of crack detection and the presentation effect of the detection result, thereby facilitating providing more valuable information for maintenance and improving the practicality of crack detection.

[0089] Specifically, in some embodiments, the target windshield includes a first inorganic glass layer, a second inorganic glass layer, and an organic glass layer;

[0090] The first surface of the first inorganic glass layer is the outer surface of the target windshield. The second surface of the first inorganic glass layer is in contact with the first surface of the organic glass layer. The second surface of the organic glass layer is in contact with the first surface of the second inorganic glass layer. The second surface of the second inorganic glass layer is the inner surface of the target windshield.

[0091] In the embodiments of the present application, the target windshield can be composed of three layers of glass, specifically including a first inorganic glass layer, a second inorganic glass layer, and an organic glass layer. Please refer to Figure 5 , Figure 5The figure shows a schematic diagram of an aircraft windshield provided in an embodiment of the present application. In the embodiment of the present application, the first surface of the first inorganic glass layer 510 is the outer surface of the target windshield, the second surface is bonded to the organic glass layer 520, the other surface of the organic glass layer 520 is bonded to the second inorganic glass layer 530, and the other surface of the second inorganic glass layer 530 is the inner surface of the target windshield. The thickness of the first inorganic glass layer 510 can be denoted as H 1 , the thickness of the organic glass layer 520 can be denoted as H 2 , the thickness of the third inorganic glass layer 530 can be denoted as H 3 .

[0092] Specifically, in some embodiments, the crack detection of the target windshield by ultrasonic detection technology includes:

[0093] Sending ultrasonic waves to any detection area on the target windshield and receiving the echo data corresponding to the ultrasonic waves;

[0094] If the echo data is disordered, it is determined that there is a crack in the target windshield in the detection area;

[0095] According to the time node when the echo data is disordered, the target surface where the crack is located is determined.

[0096] In the embodiment of the present application, when detecting cracks in the target windshield, ultrasonic waves can be sent to any detection area therein, and the echo data corresponding to the ultrasonic waves can be received. Ultrasonic waves are sound waves with a frequency higher than the human audible range, usually above 20 kHz. Its propagation speed is different in different media, but it propagates relatively fast in air and most solid materials. When an ultrasonic pulse propagates inside the windshield glass, it will encounter different interfaces (such as air - glass interface, glass - crack interface, etc.) and reflect back at these interfaces. The receiver will capture these echo signals and record their time and intensity information. These data constitute the echo data. The collected echo data will be analyzed. Under normal circumstances, if there are no cracks or other defects, the echo data should show a certain regularity. If there is a crack, the interface reflection at the crack will cause the echo data to be abnormal, manifested as disorders in aspects such as the intensity, time, and shape of the echo signal. By analyzing the echo data, if obvious disorder phenomena are found, it can be determined that there is a crack in the corresponding detection area. In addition, the approximate location of the crack can also be inferred based on the time point when the echo signal appears disordered. This is because the propagation speed of ultrasonic waves in different media is known. By calculating the time difference for the echo signal to reach the receiver, the distance between the crack and the transmitter can be estimated. Further, based on the characteristics of the echo signal caused by the crack, it can be determined which surface of the windshield glass the crack is located on. In the embodiment of the present application, it can be denoted as the target surface.

[0097] Specifically, in some embodiments, determining the crack depth data on the target windshield includes:

[0098] If the target surface is the first surface of the first inorganic glass layer, obtain a first duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the first inorganic glass layer;

[0099] Determine the crack depth data according to the product of the first duration and the reference propagation speed of the ultrasonic wave in the air.

[0100] In the embodiments of the present application, with reference to Figure 6 , Figure 6 shows a schematic diagram of a crack existing on the first surface of the first inorganic glass layer. If the target surface is the first surface of the first inorganic glass layer, the total thickness of the first inorganic glass layer is H 1 , where the thickness of the cracked part is H 11 , that is, the crack depth data. In the embodiments of the present application, the duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the first inorganic glass layer can be obtained, denoted as the first duration. Specifically, generally speaking, if there is no crack in the first inorganic glass layer, the position where the echo data first becomes disordered will be between the first inorganic glass layer and the organic glass layer. It is easy to understand that when there is a crack on the first surface of the first inorganic glass layer, the time node at which the corresponding echo data becomes disordered will be greatly advanced. Therefore, when obtaining the first duration, the time node at which the echo data first becomes disordered can be referred to. If this time node is the same as the case where there is no crack in the first inorganic glass layer, it means that there is no crack in the first inorganic glass layer. If this time node is advanced relative to the case where there is no crack in the first inorganic glass layer, it means that there is a crack in the first inorganic glass layer, and the first duration can be directly determined according to this time node. Then, the crack depth data can be determined according to the product of the first duration and the reference propagation speed of the ultrasonic wave in the air.

[0101] Specifically, in some embodiments, determining the crack depth data on the target windshield includes:

[0102] If the target surface is the first surface of the organic glass layer, obtain the second thickness data of the organic glass layer, the second propagation speed of the ultrasonic wave in the organic glass layer, the reference propagation speed of the ultrasonic wave in the air, the second reference duration of the ultrasonic wave passing through the organic glass layer of the template windshield, the total reference duration of the ultrasonic wave passing through the template windshield, and the total duration of the ultrasonic wave passing through the target windshield; wherein, the template windshield is a windshield with the same model as the target windshield and without cracks;

[0103] Establish a first set of equations, and the formula of the first set of equations is:

[0104] H 2 = v 0 * t 21 + v 2 * t 22

[0105] t 21 + t 22 - t 2 = t 总 - t

[0106] In the formula, H 2 represents the second thickness data of the plexiglass layer, v 0 represents the reference propagation speed of the ultrasonic wave in the air, t 21 represents the second duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the plexiglass layer, v 2 represents the second propagation speed of the ultrasonic wave in the plexiglass layer, t 22 represents the third duration corresponding to the propagation of the ultrasonic wave in the plexiglass layer except for the crack, t 2 represents the second reference duration of the ultrasonic wave passing through the plexiglass layer of the template windshield, t 总 represents the total reference duration of the ultrasonic wave passing through the template windshield, and t represents the total duration of the ultrasonic wave passing through the target windshield;

[0107] Solve the first set of equations to obtain the second duration;

[0108] Determine the crack depth data according to the second duration and the reference propagation speed of the ultrasonic wave in the air.

[0109] In the embodiment of the present application, referring to Figure 7 , Figure 7 shows a schematic diagram of a crack existing on the first surface of the plexiglass layer. If the target surface is the first surface of the plexiglass layer, then the thickness of the ultrasonic wave passing through the plexiglass layer can be expressed as:

[0110] H 2 = v 0 * t 21 + v 2 * t 22

[0111] Among them, the result of v 0 * t 21 is the thickness H 21 of the crack part in the plexiglass layer, v 2 * t 22The result is the propagation distance H of the ultrasonic wave in the plexiglass layer except for the crack 22 .

[0112] It can be understood that when there is a crack in the plexiglass layer, the total time t for the ultrasonic wave to pass through the entire target windshield relative to the total reference time t for passing through the template windshield 总 will change, and this change is caused by the time taken to pass through the plexiglass layer. It can be expressed by the formula as follows:

[0113] t 21 +t 22 -t 2 =t 总 -t

[0114] Due to the thickness H of the plexiglass layer 2 , the second propagation speed v of the ultrasonic wave in the plexiglass layer 2 , the reference propagation speed v of the ultrasonic wave in the air 0 , the second reference time t for the ultrasonic wave to pass through the plexiglass layer of the template windshield 2 , the total reference time t for the ultrasonic wave to pass through the template windshield 总 , the total time t for the ultrasonic wave to pass through the target windshield can be directly obtained. Therefore, by combining these two formulas, the second time t 21 can be calculated, and then the thickness H of the cracked part in the plexiglass layer 21 can be determined, that is, the crack depth data.

[0115] It should be noted that when the target surface is the second surface of the plexiglass layer, the calculation strategy is the same as that on the first surface above. Only the characters corresponding to the thickness of the cracked part and the non-cracked part in the plexiglass layer need to be adjusted, which will not be elaborated here.

[0116] Specifically, in some embodiments, if the target surface is the second surface of the second inorganic glass layer, obtain the third thickness data of the second inorganic glass layer, the third propagation speed of the ultrasonic wave in the second inorganic glass layer, the first reference time for the ultrasonic wave to pass through the first inorganic glass layer, the second reference time for the ultrasonic wave to pass through the plexiglass layer of the template windshield, and the total time for the ultrasonic wave to pass through the target windshield; wherein, the template windshield is the same model as the target windshield and has no cracks;

[0117] Calculate the difference between the total time minus the first reference time and the second reference time to obtain the fourth time;

[0118] According to the product of the fourth time and the third propagation speed, obtain the fourth thickness data;

[0119] Calculate the difference between the third thickness data and the fourth thickness data to obtain the crack depth data.

[0120] In the embodiments of the present application, with reference to Figure 8 , Figure 8 FIG. shows a schematic diagram of a crack existing on the second surface of the second inorganic glass layer. If the target surface is the second surface of the second inorganic glass layer, then there is no reflection surface after the ultrasonic wave passes through the crack, and the total time t for the ultrasonic wave to pass through the target windshield does not include the time passing through the crack. The crack depth data can be calculated by the following formula:

[0121] H 32 = H 3 - v 3 *(t - t 1 - t 2 )

[0122] In the formula, H 32 represents the crack depth data of the crack on the second surface of the second inorganic glass layer, H 3 represents the thickness of the second inorganic glass layer, v 3 represents the third propagation speed of the ultrasonic wave in the second inorganic glass layer, t represents the total time for the ultrasonic wave to pass through the target windshield, t 1 represents the first reference time for the ultrasonic wave to pass through the first inorganic glass layer of the template windshield, t 2 represents the second reference time for the ultrasonic wave to pass through the plexiglass layer of the template windshield, v 3 *(t - t 1 - t 2 ) is the length of H Figure 7 in 31 , that is, the fourth thickness data.

[0123] The embodiments of the present application further provide a detection and modeling device for cracks in an aircraft windshield. The device includes:

[0124] A detection unit for detecting cracks in the target windshield through ultrasonic detection technology;

[0125] A processing unit for determining the crack area and crack depth data on the target windshield if there are cracks on the target windshield;

[0126] An identification unit for collecting the top-view image data corresponding to the crack area, inputting the top-view image data and the crack depth data into a trained machine learning model, and identifying the crack projection position through the machine learning model to obtain the corresponding crack projection position identification result;

[0127] An integration unit, configured to model the crack of the target windshield according to the standard module data corresponding to the target windshield, the crack area, the crack depth data, and the crack projection position recognition result, so as to obtain a modeling result.

[0128] It can be understood that Figure 2 The content in the embodiment of the method for detecting and modeling cracks in an aircraft windshield shown is applicable to the embodiment of the device for detecting and modeling cracks in an aircraft windshield of the present application. The functions specifically implemented by the embodiment of the device for detecting and modeling cracks in an aircraft windshield of the present application are the same as those Figure 2 in the embodiment of the method for detecting and modeling cracks in an aircraft windshield shown, and the beneficial effects achieved are the same as those Figure 2 in the embodiment of the method for detecting and modeling cracks in an aircraft windshield shown.

[0129] Referring to Figure 9 , an embodiment of the present application also discloses a computer device, including:

[0130] At least one processor 901;

[0131] At least one memory 902, configured to store at least one program;

[0132] When at least one program is executed by at least one processor 901, at least one processor 901 is caused to implement the embodiment of the method for detecting and modeling cracks in an aircraft windshield as Figure 2 shown.

[0133] It can be understood that, as Figure 2 in the embodiment of the method for detecting and modeling cracks in an aircraft windshield shown, the content is applicable to the embodiment of the present computer device. The functions specifically implemented by the embodiment of the present computer device are the same as those in the embodiment of the method for detecting and modeling cracks in an aircraft windshield as Figure 2 shown, and the beneficial effects achieved are the same as those in the embodiment of the method for detecting and modeling cracks in an aircraft windshield as Figure 2 shown.

[0134] An embodiment of the present application also discloses a computer-readable storage medium, in which a program executable by a processor is stored. The program executable by the processor is used to implement the embodiment of the method for detecting and modeling cracks in an aircraft windshield as Figure 2 shown.

[0135] It can be understood that, as Figure 2 in the embodiment of the method for detecting and modeling cracks in an aircraft windshield shown, the content is applicable to the embodiment of the present computer-readable storage medium. The functions specifically implemented by the embodiment of the present computer-readable storage medium are the same as those Figure 2The same as the embodiment of a method for detecting and modeling cracks in an aircraft windshield shown, and the beneficial effects achieved are the same as those achieved by the embodiment of a method for detecting and modeling cracks in an aircraft windshield shown in Figure 2 the embodiment of a method for detecting and modeling cracks in an aircraft windshield shown.

[0136] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two consecutive blocks shown may actually be executed substantially simultaneously or the blocks can sometimes be executed in the reverse order. Additionally, the embodiments presented and described in the flowcharts of the present application are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are contemplated where the order of various operations is changed and where sub-operations described as part of a larger operation are executed independently.

[0137] Furthermore, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated in a single physical system and / or software module, or one or more functions and / or features may be implemented in separate physical systems or software modules. It can also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present application. Rather, given the attributes, functions, and internal relationships of the various functional modules in the system disclosed herein, the actual implementation of the module will be understood within the ordinary skill of an engineer. Thus, those skilled in the art can implement the present application as set forth in the claims without undue experimentation. It can also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the appended claims and their equivalents.

[0138] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0139] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definitional sequence list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution system, system or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, system or device), or used in conjunction with these instruction execution systems, systems or devices. For the purposes of this specification, a "computer-readable medium" can be any system that can contain, store, communicate, propagate or transport a program for use by or in conjunction with an instruction execution system, system or device.

[0140] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic system), a portable computer diskette (magnetic system), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber system, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation or, if necessary, other suitable processing, and then stored in a computer memory.

[0141] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0142] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0143] Although the embodiments of the present application have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present application. The scope of the present application is defined by the claims and their equivalents.

[0144] The above has specifically described the preferred embodiments of the present application, but the present application is not limited to the embodiments. Those skilled in the art can make various equivalent deformations or substitutions without departing from the spirit of the present application, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present application.

[0145] In the description of this specification, the description with reference to terms such as "one embodiment", "another embodiment", or "certain embodiments" means that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0146] Although the embodiments of the present application have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present application. The scope of the present application is defined by the claims and their equivalents.

Claims

1. A detection modeling method for aircraft windshield cracks, characterized in that: The method comprises: Detect cracks on target windshields using ultrasonic detection technology; If cracks exist on the target windshield, determine crack area and crack depth data on the target windshield; Collecting overhead image data corresponding to the crack area, inputting the overhead image data and the crack depth data into a trained machine learning model, identifying the crack projection position through the machine learning model, and obtaining a corresponding crack projection position identification result; wherein the crack projection position identification result is used to characterize the projection position of each deepest point of the crack on the overhead plane when the target windshield is in a downwardly laid state; The crack of the target windshield is modeled according to the standard module data corresponding to the target windshield, the crack area, the crack depth data and the crack projection position identification result to obtain a modeling result.

2. The detection modeling method for aircraft windshield cracks according to claim 1 is characterized in that: The target windshield comprises a first inorganic glass layer, a second inorganic glass layer and an organic glass layer; The first surface of the first inorganic glass layer is the outer surface of the target windshield, the second surface of the first inorganic glass layer is in contact with the first surface of the organic glass layer, the second surface of the organic glass layer is in contact with the first surface of the second inorganic glass layer, and the second surface of the second inorganic glass layer is the inner surface of the target windshield.

3. The detection modeling method for aircraft windshield cracks according to claim 2 is characterized in that: The method of detecting cracks on a target windshield by using ultrasonic detection technology includes: Sending ultrasonic waves to any detection area on the target windshield, and receiving echo data corresponding to the ultrasonic waves; If the echo data is disordered, determining that the target windshield has a crack in the detection area; The target surface where the crack is located is determined according to the time node at which the echo data is disturbed.

4. The detection modeling method for aircraft windshield cracks according to claim 3 is characterized in that: Determining crack depth data on the target windshield includes: If the target surface is the first surface of the first inorganic glass layer, obtaining a first time duration corresponding to the propagation of the ultrasonic wave in the crack on the first surface of the first inorganic glass layer; The crack depth data is determined according to the product of the first time length and a reference propagation speed of the ultrasonic wave in the air.

5. The detection modeling method for aircraft windshield cracks according to claim 3 is characterized in that: Determining crack depth data on the target windshield includes: If the target surface is the first surface of the organic glass layer, obtain the second thickness data of the organic glass layer, the second propagation speed of the ultrasonic wave in the organic glass layer, the reference propagation speed of the ultrasonic wave in the air, the second reference time length of the ultrasonic wave passing through the organic glass layer of the template windshield, the total reference time length of the ultrasonic wave passing through the template windshield, and the total time length of the ultrasonic wave passing through the target windshield; wherein the template windshield is a windshield of the same model as the target windshield and has no cracks; A first set of equations is established, wherein the formula of the first set of equations is: H2=v0*t 21 +v2*t 22 t21+t22-t2=ttotal-t Wherein, H2 represents the second thickness data of the organic glass layer, v0 represents the reference propagation speed of the ultrasonic wave in the air, and t 21 represents the second time duration corresponding to the ultrasonic wave propagating in the crack on the first surface of the organic glass layer, v2 represents the second propagation speed of the ultrasonic wave in the organic glass layer, t 22 represents the third time duration corresponding to the propagation of the ultrasonic wave in the organic glass layer except for the cracks, t2 represents the second reference time duration of the ultrasonic wave passing through the organic glass layer of the template windshield, t 总 represents the total reference time length of the ultrasonic wave passing through the template windshield, and t represents the total time length of the ultrasonic wave passing through the target windshield; Solving the first set of equations to obtain the second time length; The crack depth data is determined according to the second time length and a reference propagation speed of the ultrasonic wave in the air.

6. The detection modeling method for aircraft windshield cracks according to claim 3 is characterized in that: Determining crack depth data on the target windshield includes: If the target surface is the second surface of the second inorganic glass layer, obtain the third thickness data of the second inorganic glass layer, the third propagation speed of the ultrasonic wave in the second inorganic glass layer, the first reference time length of the ultrasonic wave passing through the first inorganic glass layer, the second reference time length of the ultrasonic wave passing through the organic glass layer of the template windshield, and the total time length of the ultrasonic wave passing through the target windshield; wherein the template windshield is a windshield of the same model as the target windshield and has no cracks; Calculate the total duration minus the difference between the first reference duration and the second reference duration to obtain a fourth duration; Obtain fourth thickness data according to the product of the fourth time length and the third propagation speed; The difference between the third thickness data and the fourth thickness data is calculated to obtain the crack depth data.

7. A detection modeling device for aircraft windshield cracks, characterized in that: The device comprises: A detection unit, used for performing crack detection on a target windshield by using ultrasonic detection technology; a processing unit, configured to determine crack area and crack depth data on the target windshield if cracks exist on the target windshield; an identification unit, for collecting overhead image data corresponding to the crack area, inputting the overhead image data and the crack depth data into a trained machine learning model, identifying the crack projection position through the machine learning model, and obtaining a corresponding crack projection position identification result; wherein the crack projection position identification result is used to characterize the projection position of each deepest point of the crack on the overhead plane when the target windshield is in a downwardly laid state; The integration unit is used to model the crack of the target windshield according to the standard module data corresponding to the target windshield, the crack area, the crack depth data and the crack projection position identification result to obtain a modeling result.

8. The aircraft windshield crack detection modeling device according to claim 7, characterized in that: The target windshield comprises a first inorganic glass layer, a second inorganic glass layer and an organic glass layer; The first surface of the first inorganic glass layer is the outer surface of the target windshield, the second surface of the first inorganic glass layer is in contact with the first surface of the organic glass layer, the second surface of the organic glass layer is in contact with the first surface of the second inorganic glass layer, and the second surface of the second inorganic glass layer is the inner surface of the target windshield.

9. A computer device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the aircraft windshield crack detection modeling method according to any one of claims 1 to 6.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to implement a detection and modeling method for aircraft windshield cracks as described in any one of claims 1 to 6 when executed by the processor.

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