Inspection device, inspection method, and inspection program

Abstract

This inspection device comprises: an internal inspection unit that inspects a specimen for an internal abnormality; an estimation unit that estimates, on the basis of appearance information of the specimen, the degree of the internal abnormality for each portion of the specimen; and a setting unit that sets, within the internal inspection unit, a parameter corresponding to the estimated degree of the internal abnormality for each portion.

Description

Inspection device, inspection method, and inspection program

[0001] The present invention relates to an inspection device, an inspection method, and an inspection program.

[0002] In developed countries, the working population is shrinking due to an aging population, and as a result of the promotion of DX (Digital Transformation) to solve this problem, the automation of so-called lifecycle management is progressing. Lifecycle management includes everything from the manufacturing process to health assessment during use, remaining life prediction, repair based on maintenance inspections, reuse, recycling, etc.

[0003] For example, in mobility vehicles that transport people and goods, such as automobiles, aircraft, and rockets, regular maintenance and inspections are essential to ensure safety over long periods of time and over multiple uses. In particular, in the case of aircraft, maintenance and inspections to prevent accidents have been standardized, and the procedures have been compiled into manuals that are still in use today.

[0004] Furthermore, from the perspectives of both environmental friendliness and economic efficiency, efforts are being made to reduce the weight of mobility vehicles in order to improve energy efficiency. While heavy metals have traditionally been used, progress is being made in introducing light metals and even composite resins with light weight and high specific strength, such as carbon fiber reinforced plastics (CFRP).

[0005] As a method for non-destructively detecting and evaluating defects and damage in objects made of such composite resins, etc., detection devices and methods using ultrasonic waves are generally known. Ultrasonic devices are highly portable and are not harmful to the human body like X-rays, so they are suitable for detecting defects and evaluating damage in various shapes of mobility.

[0006] However, while typical ultrasonic detection devices and methods have the advantages of being highly portable and capable of non-destructively detecting and evaluating defects and damage inside objects that cannot be observed from the outside, they have a problem with inspection time. This is because the area that can be inspected at one time is approximately the size of the probe that transmits and receives the ultrasonic waves, and if the inspection area of ​​the object is large, it becomes necessary to bring the probe into contact with the entire inspection area, which is expected to result in an enormous inspection time.

[0007] Furthermore, detecting defects and damage inside an object made of a composite material, such as CFRP, which is a combination of two or more materials, requires adjusting many parameters in the ultrasonic device, unlike the inspection of a homogeneous material. The detection capability (the time required for parameter adjustment and the resulting detection results) depends heavily on the skill of the inspector.

[0008] Various techniques are known for evaluating the integrity of test objects and improving inspection efficiency. For example, Patent Document 1 discloses an inspection method that combines optical inspection with other techniques to improve inspection efficiency in semiconductor manufacturing processes. Patent Document 2 discloses a method for detecting cracks in bridge decks, in which infrared thermal images are used as a first method to identify potential flaw detection positions on the deck plate, and ultrasonic or other inspection methods are used as a second method. Patent Document 3 discloses a method that combines laser ultrasonic inspection with infrared thermography inspection to enable inspection of the internal structure of complex shapes.

[0009] JP 2002-026102 A JP 2010-133835 A JP 2010-512509 A

[0010] S. Hasebe, R. Higuchi, T. Yokozeki, S. Takeda, "Damage prediction using impact scar information of composite structures using decision tree-based multitask learning," Proceedings of the 2022 JSCE Conference, Vol. 27, June 2022, pp. 614-619. Y. Harano, S. Hasebe, R. Higuchi, T. Yokozeki, S. Takeda, "Estimation of post-impact compressive strength of CFRP using damage information," 13th Japan Composite Materials Conference. Xiaoyu Yang, Bing-Feng Ju, Mathias Kersemans, "Assessment of the 3D ply-by-ply fiber structure in impacted CFRP by means of planar ultrasound computed tomography (pU-CT)," Composite Structures 279 (2022) 114745.

[0011] However, a technology for efficiently inspecting defects and damage inside composite materials, such as CFRP, has not yet been disclosed (for example, a technology that can be inspected in a short time and that is automated to minimize dependence on the inspector's technique). To ensure the integrity of the test object, the inspector must manually adjust multiple parameters by bringing the probe into contact with the entire inspection area and taking into account the test object and the inspection conditions. As a result, when the test object is a relatively large object, such as a mobility object, which has various shapes and is made of different materials depending on the part, the existing technology is inefficient in inspection.

[0012] An object of the present invention is to provide an inspection device, an inspection method, and an inspection program that can further improve the efficiency of non-destructive inspection of the inside of a test object.

[0013] The inspection device according to the present invention comprises an internal inspection unit that inspects an internal abnormality of a subject; an estimation unit that estimates the degree of internal abnormality for each external part of the subject based on external appearance information of the subject; and a setting unit that sets parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part.

[0014] The inspection method according to the present invention is an inspection method using an internal inspection unit, and includes estimating the degree of internal abnormality for each part of the specimen based on appearance information of the specimen; setting parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part; and inspecting the specimen for internal abnormalities using the internal inspection unit.

[0015] The inspection program of the present invention is an inspection program that uses an internal inspection unit, and causes a computer to execute the following processes: a process of estimating the degree of internal abnormality for each part of the test subject based on appearance information of the test subject; a process of setting parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part; and a process of inspecting the test subject for internal abnormalities using the internal inspection unit.

[0016] According to the present invention, it is possible to further improve the efficiency of non-destructive inspection of the inside of a test object.

[0017] Fig. 1 is a diagram schematically showing an example of the configuration of an inspection device according to an embodiment of the present invention. Fig. 2 is a flowchart showing an example of the operation of inspection processing of ultrasound data by a processing unit. Fig. 3 is a flowchart showing an example of the operation of inspection processing of ultrasound data by a processing unit. Fig. 4 is a diagram schematically showing an example of the configuration of an inspection device according to a modified example. Fig. 5 is a diagram corresponding to Fig. 1 , showing an example of a test object according to a modified example. Fig. 6 is a diagram corresponding to Fig. 1 , showing an example of a test object according to a modified example.

[0018] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will now be described in detail with reference to the accompanying drawings. Fig. 1 is a diagram schematically illustrating an example of the configuration of an inspection device 100 according to an embodiment of the present invention.

[0019] As shown in FIG. 1, the inspection device 100 non-destructively detects internal defects and damage (also called internal abnormalities) that cannot be seen from the outside of the test object 1, and provides a soundness evaluation that enables safe and secure operation of the test object 1.

[0020] Specifically, the inspection device 100 estimates the degree of internal abnormality for each part of the inspected object 1 based on the appearance information of the inspected object 1. Then, the inspection device 100 sets parameters corresponding to the estimated degree of internal abnormality for each part of the inspected object 1 in the internal inspection unit 140 (described later), and inspects the internal abnormality of the inspected object 1. Furthermore, the inspection device 100 uses the information on internal abnormalities based on the appearance information for screening, and inspects only the screened parts of the inspected object 1 in detail as the inspection target.

[0021] If the inspection results of the inspection device 100 indicate that the internal abnormality of the test object 1 is at a level that will adversely affect the operation of the test object 1, it becomes possible to carry out repairs and part replacements on the test object 1.

[0022] In this embodiment, the test object 1 is a moving object such as an automobile, an aircraft, or a rocket (including a reusable rocket) or an internal part of the moving object (e.g., a fuel tank), and is made of a composite material such as CFRP. The internal abnormality may be, for example, collision damage caused when the moving object collides with some object (e.g., a bird strike, a flying stone, etc.), or damage caused to the test object 1 when an inspector drops a personal item (e.g., a tool, a mobile phone, etc.) on the test object 1 during an inspection. The internal abnormality is not limited to these, and may be any defect or damage occurring inside the test object 1. FIG. 1 illustrates an example in which the test object 1 is a rocket. FIG. 5A illustrates an example in which the test object 1 is a reusable part of a reusable rocket, and FIG. 5B illustrates an example in which the test object 1 is a fuel tank.

[0023] The inspection device 100 includes an appearance inspection unit 110 , a processing unit 120 , a database 130 , and an internal inspection unit 140 .

[0024] The appearance inspection unit 110 detects appearance information of the subject 1 and may be, for example, an optical camera. The appearance information may be, for example, image information capturing the entire appearance of the subject 1.

[0025] Although the image quality of the appearance information obtained by an optical camera varies depending on the focus setting and lighting conditions, the optical camera can acquire appearance information without contact and is compact. Furthermore, the optical camera can be connected to the processing unit 120 by wire or wirelessly, making it suitable for use as the appearance inspection unit 110 to acquire appearance information.

[0026] The appearance information acquired by the appearance inspection unit 110 is used to estimate the degree of internal abnormality in the subject 1. The appearance information is also used to screen for parts of the subject 1 where there is a high possibility of an internal abnormality occurring.

[0027] Furthermore, the parameters of the visual inspection unit 110 may be set by the processing unit 120 (parameter determination unit 122). Specifically, the processing unit 120 acquires risk information and inspection position information from the database 130, determines the conditions for the visual inspection of the specimen 1, and sets the parameters of the visual inspection unit 110.

[0028] For example, if the appearance inspection unit 110 is an optical camera, the parameters of the appearance inspection unit 110 may be information on shooting conditions such as lighting arrangement and intensity, focus position, and data acquisition range.

[0029] The processing unit 120 is, for example, a device, such as a personal computer, having a central processing unit (CPU), read-only memory (ROM), random access memory (RAM), etc. The processing unit 120 controls the appearance inspection unit 110, the internal inspection unit 140, etc., and realizes each function by, for example, the CPU referencing a control program and various data stored in the ROM and RAM and executing the control program. Specifically, the processing unit 120 has an analysis unit 121 and a parameter determination unit 122.

[0030] Some or all of these functions may be realized by an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), a PLD (Programmable Logic Device), a dedicated hardware circuit, etc. Examples of PLDs include FPGAs (Field Programmable Gate Arrays). Some or all of these functions may be configured to be executed by a GPU (Graphics Processing Unit).

[0031] The analysis unit 121 imports the appearance information acquired by the appearance inspection unit 110 and performs image processing operations to analyze the appearance information. The analysis unit 121 calculates appearance abnormality information based on the appearance information. Here, the appearance abnormality information includes at least one of the presence or absence of dents or scratches on the appearance and / or surface of the test object 1, their extent and depth, texture, and changes in color information. The appearance abnormality information is linked to spatial position information on the appearance and / or surface of the test object 1. The processing unit 120 can identify the spatial position of an abnormal area on the test object 1 based on the calculated appearance abnormality information. Note that the association of the appearance abnormality information with the spatial position information may be performed by comparing an appearance image based on an optical camera with a correct image. Alternatively, the association of the appearance abnormality information with the spatial position information may be performed by comparing the results of the appearance irregularity detection based on an optical sensor with the appearance surface state under normal conditions.

[0032] The database 130 stores a data set in which shape information of appearance anomalies and internal anomaly information are linked. The database 130 corresponds to the "storage unit" of the present invention. For example, the internal anomaly information is information on the extent and shape of internal damage estimated based on the extent and depth of an appearance dent, the volume derived therefrom, and the like. For each shape of appearance anomaly, the data set records the corresponding degree of shape of internal anomalies as internal anomaly information. Examples of the degree of shape of internal anomalies include the size, area, volume, and number and length of cracks in the peeled CFRP layer.

[0033] When an external impact causes a dent on the surface of CFRP, the impact energy propagates into the interior of the CFRP, causing delamination between the layers of the prepreg, which is made up of multiple layers, resulting in an internal abnormality. Delamination impairs the toughness of the CFRP. When delamination occurs in CFRP used in the structure of a mobile object, the fracture may propagate from the location of the delamination, potentially making it impossible to safely operate the mobile object.

[0034] Damage such as delamination occurs in the shallow area (near the surface) around the dent on the impact surface, and the delamination generally progresses concentrically around the center of the dent as it progresses from the surface to the deeper part of the impact surface. CFRP has mechanical strength and orientation in the direction of the carbon fibers, and delamination tends to progress in the direction of the fiber orientation.

[0035] In addition, while dents are also influenced by the shape of the colliding object, it is known that there is a high correlation between the impact energy, which is determined by the mass and speed of the object, and shape information such as the volume of the dent, and that there is also a high correlation between the dent information and the area over which delamination develops.

[0036] For example, Non-Patent Document 1 describes the tendency of the degree of internal abnormality to change depending on the shape of the external dent in a CFRP member.

[0037] Specifically, when a spherical object collides with a CFRP member, spherical damage occurs in the member. In this case, the internal anomaly is damage that has a shape that spreads out to a certain extent relative to the dent. Also, when the apex of a conical object collides with a CFRP member, damage in the shape of a crack occurs in the member. In this case, the internal anomaly is damage that has a shape that spreads out along the crack, resulting in damage over a wider area than in the case of a spherical object.

[0038] Furthermore, Non-Patent Document 2 discloses the results of verification of the estimation of the compressive strength after impact of a CFRP member using a machine learning model created based on damage information and information on a test specimen (impact object). This shows that the accuracy of the machine learning model was significantly improved by adding the depth of the dents on the exterior of the CFRP member to the feature amount.

[0039] As described above, since there is a correlation between the shape of the dent and the shape of the internal abnormality, the degree of the internal abnormality of the CFRP member can be estimated from the appearance abnormality information. Therefore, the database 130 stores the internal abnormality information estimated from the appearance information, linked to the shape information of the appearance abnormality of the specimen 1. The internal abnormality information stored in the database 130 may be information measured in advance by an experiment or the like.

[0040] In addition, the data set stored in the database 130 also records the setting parameters of the internal inspection unit 140, which are set based on the appearance abnormality information, linked to each shape of internal damage.

[0041] The setting parameters are parameter values ​​of the internal inspection unit 140 that are set when data is acquired by the internal inspection unit 140, and different values ​​are associated with them depending on the degree of the shape of the internal abnormality. The setting parameters are, for example, transmission and reception conditions, coefficients used during analysis, etc. The transmission and reception conditions are, for example, transmission frequency, transmission intensity, focus position, data acquisition range, etc. The coefficients used during analysis are, for example, coefficient values ​​used in an evaluation formula such as formula (1) described below.

[0042] The analysis unit 121 refers to the database 130 and extracts internal abnormality information corresponding to the appearance abnormality information calculated from the appearance information. In this way, the analysis unit 121 estimates internal abnormality information for each part of the subject 1 based on the appearance information. The analysis unit 121 corresponds to the "estimation unit" of the present invention.

[0043] The internal anomaly information may be estimated, for example, by linear interpolation between the data set stored in the database 130 and the appearance anomaly information based on the appearance information acquired from the appearance inspection unit 110. Alternatively, the internal anomaly information may be estimated by selecting internal anomaly information linked to shape information of an appearance anomaly similar to the appearance anomaly information based on the appearance information.

[0044] In this way, it is possible to easily estimate the degree of internal abnormality in the specimen 1 without contacting it using the visual inspection unit 110. However, the internal abnormality information acquired in this manner is an estimated value based on the data set stored in the database 130, and may differ from the actual state of the internal abnormality. In other words, although the method of extracting internal abnormality information based on visual abnormality information is efficient, it may lack reliability from the perspective of ensuring safe and secure operation of mobile objects that transport people and cargo.

[0045] Therefore, the inspection device 100 according to this embodiment is used for screening internal abnormality information estimated from appearance information. Specifically, the analysis unit 121 identifies an inspection range in the specimen 1 based on a comparison result between the estimated internal abnormality information and a predetermined threshold.

[0046] The predetermined threshold is a threshold for comparison with parameters of the internal abnormality (for example, internal abnormality information estimated based on the depth of the external indentation, the area of ​​the external indentation, or the volume of the external indentation), and is a value that can be set appropriately. The predetermined threshold may be a different value for each part of the subject 1. For example, the predetermined threshold may be set to a relatively low value for parts of the subject 1 that require mechanical strength and are at high risk in consideration of damage that may occur due to damage. Furthermore, the predetermined threshold may be set to a relatively high value for parts at low risk in consideration of the above-mentioned damage.

[0047] High-risk parts are parts that could affect the operation of the moving body if damaged, such as parts that require mechanical strength in the structure or drive unit of the moving body, and parts that are exposed to increases or changes in temperature and humidity due to heat sources such as engines or the surrounding environment.

[0048] Low-risk parts are parts of a moving body that, even if damaged, do not affect the operation of the moving body, such as parts that only constitute the design of the moving body or parts that are away from heat sources.

[0049] Furthermore, if the value indicating the degree of the internal abnormality is equal to or greater than a predetermined threshold (within a predetermined range), the analysis unit 121 identifies the external appearance part corresponding to the internal abnormality as an area requiring closer inspection. Furthermore, if the value indicating the degree of the internal abnormality is less than the predetermined threshold (outside the predetermined range), the analysis unit 121 identifies the area corresponding to the internal abnormality as an area not requiring closer inspection and excludes it from the inspection target.

[0050] The parameter determination unit 122 sets, in the internal inspection unit 140, setting parameters according to the shape of the internal abnormality for each region of the subject 1 identified as the examination region. This makes it possible to automatically set the internal inspection unit 140 for each region. The parameter determination unit 122 corresponds to the "setting unit" of the present invention.

[0051] The internal inspection unit 140 is, for example, an ultrasound device including a probe capable of transmitting and receiving ultrasound, and acquires data for detailed inspection of the region to be inspected in the subject 1 .

[0052] For example, the internal inspection unit 140 generates ultrasonic waves by energizing a piezoelectric element included in the probe to generate vibrations while the probe is in contact with a screened portion of the subject 1 (a portion identified as a portion to be examined). The transmission level (transmission intensity) of the generated ultrasonic waves is adjustable. In this way, ultrasonic waves are transmitted to the portion of the subject 1 that is in contact with the probe.

[0053] The internal inspection unit 140 receives ultrasonic waves reflected from inside the subject 1 and converts the received signals into electrical signals. The internal inspection unit 140 converts the converted electrical signals into internal scan data as a digital signal sequence through analog-to-digital conversion.

[0054] The ultrasonic waves, which are internal scan data, are largely reflected by the CFRP surface, with some of them penetrating the CFRP surface. The transmitted ultrasonic waves are then reflected at the interface between the different materials, the resin-rich and carbon-rich layers of the CFRP. As the ultrasonic waves propagate, the wave motion is converted into heat and reduced in size, and the signal strength actually received by the probe is significantly attenuated due to the effects of internal scattering. In other words, in areas of the CFRP component where no internal abnormalities exist, the reflected signal strength follows an exponential, but monotonically decaying curve (attenuation curve) from shallow to deep.

[0055] When there is an internal defect such as delamination between layers of a CFRP member, a value called acoustic impedance (calculated as the product of the sound speed of ultrasonic waves and the density of the material) changes significantly at the boundary surface, causing a relatively large reflection at the location where the internal defect exists.

[0056] Therefore, in a region where an internal anomaly exists in a CFRP member, the reflected signal is observed as a value that exceeds the attenuation curve. Based on this principle, it is possible to identify the location of the internal anomaly in the CFRP member by observing the depth, from shallow to deep, at which the attenuation curve is exceeded.

[0057] As an example, if the reflected signal intensity obtained by the internal inspection unit 140 satisfies the following formula (1) (see non-patent document 3), the analysis unit 121 evaluates that, for example, peeling has occurred in the area of ​​the specimen 1 inspected by the internal inspection unit 140.

[0058] |A1(t)|>β×A2×exp(-α×(t-T2))...(1)

[0059] t is the time of flight from transmitting the ultrasonic wave to receiving the reflected signal. A1(t) is the reflected signal strength at a certain flight time t. A2 is the reflected signal strength from the CFRP surface. T2 is the time of flight of the reflected signal from the CFRP surface. α and β are implementation coefficients and can be set to appropriate values. These implementation coefficients may be included in the above setting parameters, or may be different values ​​for each shape of the internal anomaly.

[0060] In this embodiment, since the purpose is to evaluate the specimen 1 using the calibration curve, the evaluation formula used for the evaluation is not limited to the above formula (1). Furthermore, when performing the evaluation, the parameter determination unit 122 may select and determine an optimal evaluation formula from among a plurality of evaluation formulas according to the degree of appearance abnormality of the specimen 1, or may determine coefficient values, evaluation ranges, etc.

[0061] Furthermore, the inspection results obtained by the processing unit 120 may be output to a predetermined display device 2 or may be stored in the database 130 or the like. The predetermined display device 2 may be, for example, a display device included in the processing unit 120 itself, or a display device connected to the processing unit 120 by wire or wirelessly (for example, a display device of an ultrasound device, a display device of a mobile terminal, etc.).

[0062] Next, a description will be given of the flow of processing by the processing unit 120. Fig. 2 is a flowchart showing an example of the operation of inspection processing of ultrasound data by the processing unit 120. This control is started when inspection processing of the subject 1 by the inspection device 100, which will be described below, is started.

[0063] 2, the processing unit 120 acquires appearance information of the inspected object 1 from the appearance inspection unit 110 (step S101). Prior to step S101, the processing unit 120 may acquire risk information and inspection position information from the database 130, determine the conditions for the appearance inspection of the inspected object 1, and set parameters for the appearance inspection unit 110. After acquiring the appearance information, the processing unit 120 extracts internal anomaly information from the appearance anomaly information for each region (step S102). Specifically, the processing unit 120 calculates appearance anomaly information for each region of the inspected object 1, and, with reference to the database 130, extracts internal anomaly information linked to shape information corresponding to the appearance anomaly information.

[0064] After extracting the internal abnormality information, the processing unit 120 identifies the inspection region and the non-inspection region (step S103). Specifically, the processing unit 120 compares the value indicating the degree of internal abnormality with a predetermined threshold for each region of the subject 1, and if the value indicating the degree of internal abnormality is equal to or greater than the predetermined threshold, identifies the region as the inspection region. On the other hand, if the value indicating the degree of internal abnormality is less than the predetermined threshold, the processing unit 120 identifies the region as the non-inspection region and excludes it from the inspection target.

[0065] After identifying the inspection region and the non-inspection region, the processing unit 120 automatically sets the setting parameters for each inspection region (step S104). Specifically, the processing unit 120 refers to the database 130, extracts the setting parameters associated with the internal abnormality information in the inspection region, and sets the extracted setting parameters in the internal inspection unit 140 when inspecting the inspection region.

[0066] After automatically setting the setting parameters, the processing unit 120 acquires internal scan data for each part (step S105). After acquiring the internal scan data, the processing unit 120 analyzes the internal scan data and evaluates the degree of internal abnormality (step S106). The processing unit 120 then outputs the inspection results (step S107). After that, this control ends.

[0067] The effects of this embodiment configured as described above will be described. The inspection method using an ultrasonic device is as described above, but in actual inspections, it is not easy to accurately detect the location of internal abnormalities. Reflection is large on the surface of CFRP, and it is generally not easy to transmit short-wavelength pulses with an ultrasonic device due to the device's configuration. Therefore, for damage in the shallow part of the CFRP surface, if the attenuation curve is set from just below the surface position, a reflected signal with a value larger than the attenuation curve may be received even when no damage is present, which may result in an erroneous determination that damage exists.

[0068] Furthermore, since the ultrasonic signal has the characteristic of exponentially attenuating as it propagates deeper into the CFRP, the reflected signal itself has a relatively small value at deep locations. Therefore, it is difficult to distinguish whether the signal is a reflection due to damage or a signal due to noise, etc., and there is a possibility that accurate evaluation cannot be performed using a detection method based on the attenuation curve.

[0069] In particular, CFRP is not identical depending on the manufacturer, material, and manufacturing process, and there is also variation in inspection results depending on the inspection location of the specimen. These factors make it more difficult to detect internal abnormalities compared to relatively homogeneous objects such as metals. Therefore, inspectors change various adjustable parameters while checking the output results and output images of the ultrasound device in real time to detect internal abnormalities.

[0070] Such methods are highly dependent on the skill of the examiner, and while experienced examiners can perform the test efficiently in a short time, inexperienced examiners cannot. This skill dependency affects not only efficiency but also detection ability, which can undermine the reliability of the test itself, which is intended for safe and secure operation. Furthermore, improving testing efficiency and improving testing ability are a trade-off even for experienced examiners, and improving one generally results in a decrease in the other.

[0071] In contrast, in this embodiment, the parts to be inspected are screened from the internal abnormality information predicted based on the appearance information, and only the screened parts are inspected in detail by the internal inspection unit 140 .

[0072] As a result, any locations that have not been screened based on the predicted internal anomaly information are excluded from the inspection target by the internal inspection unit 140. As a result, compared to an apparatus that inspects the entire specimen 1 in detail, inspection efficiency can be significantly improved, and ultimately both the inspection efficiency and the detectability of internal anomalies and damage in the CFRP can be improved.

[0073] As described above, it is known that there is a correlation between the appearance abnormality information of the CFRP and the internal abnormality and the extent of damage. Therefore, by storing the appearance information acquired from the appearance of the specimen 1 and the associated internal abnormality information in the database 130, it is possible to easily estimate the internal abnormality information from the appearance information.

[0074] Therefore, when calculating the degree of internal anomaly from the internal scan data acquired by the internal inspection unit 140, the presence of the predicted internal anomaly information enables automatic correction of the attenuation curve. This correction can be adaptively performed by comparing the set position of the attenuation curve, the internal anomaly determination criteria, the internal anomaly spread area, and the internal anomaly information. Furthermore, the attenuation curve can be corrected, for example, by changing α and β in the above equation (1). The determination criteria may be a threshold for determining whether the reflected signal has exceeded the attenuation curve or a threshold for determining whether it is due to noise.

[0075] The above means that inspections that have previously been performed by an inspector while changing various adjustable parameters can now be performed automatically and instantly, with extremely high detection capabilities.

[0076] That is, in this embodiment, the internal inspection unit 140 can efficiently inspect the CFRP for internal abnormalities in a short time, and can do so with high detection capability.

[0077] The internal inspection unit 140 (ultrasonic probe) basically requires water or a contact medium, and therefore has limitations on its scanning speed. In contrast, in this embodiment, screening is performed by the appearance inspection unit 110, which does not need to come into contact with the specimen 1 and can scan at a relatively high speed. This improves efficiency by narrowing the inspection area of ​​the specimen 1, and enables automatic and high-speed processing of ultrasound data using various parameters derived from internal anomaly information based on anomaly information calculated from appearance information from the appearance inspection unit 110. As a result, inspection efficiency and detectability not available in conventional technology can be achieved.

[0078] In the above embodiment, the appearance information is acquired by the appearance inspection unit 110, but the present invention is not limited to this. For example, the internal inspection unit 140 may acquire the appearance information of the specimen 1. In this case, the inspection device 100 does not need to have the appearance inspection unit 110.

[0079] When inspecting the internal state of the subject 1, the ultrasonic device needs to set different parameters depending on the degree of internal abnormality. However, when inspecting the surface shape of the subject 1, there is no need to set detailed parameters, and inspection can be performed simply and quickly.

[0080] Therefore, the inspection device 100 acquires appearance information using the internal inspection unit 140, and inspects in detail only the areas screened using the appearance information using the internal inspection unit 140.

[0081] Even with this configuration, it is possible to improve both the inspection efficiency and the detectability of internal abnormalities and damage in CFRP.

[0082] The inspection device 100 may also be configured to acquire appearance information from an external device. The external device may be any device, such as an optical camera or an ultrasound device, as long as it is capable of acquiring appearance information of the subject 1.

[0083] In the above embodiment, the non-inspection areas are not inspected, but the present invention is not limited to this. For example, if the non-inspection areas include an area requiring inspection, the area may be added to the inspection areas.

[0084] The inspection-required area is a location that requires inspection regardless of whether or not there is a dent in the exterior. For example, the inspection-required area may be a fuel tank or an engine.

[0085] Next, another processing flow by the processing unit 120 will be described. Fig. 3 is a flowchart showing another example of the operation of the processing unit 120 for inspecting ultrasound data. This control is started when the inspection process of the subject 1 by the inspection device 100, which will be described below, is started. Note that the processing of steps S101 to S106 in the flowchart shown in Fig. 3 is the same as that in the flowchart shown in Fig. 2, and therefore detailed description thereof will be omitted.

[0086] 3, after the process of step S103, the processing unit 120 determines whether or not there is a region requiring inspection in the non-inspection region (step S108). If the result of the determination is that there is no region requiring inspection in the non-inspection region (step S108, NO), the process proceeds to step S104.

[0087] On the other hand, if there is an area requiring inspection in the non-review area (step S108, YES), the processing unit 120 adds the area requiring inspection to the review area (step S109). After step S109, the process proceeds to step S104.

[0088] The process of step S108 may be performed before the detailed examination region and the non-detailed examination region are identified in step S103. In this case, when a region of the region requiring examination is identified as a non-detailed examination region in step S103, the region is not excluded from the examination target.

[0089] According to this configuration, regions that require inspection are inspected reliably, so inspection omissions can be eliminated.

[0090] Furthermore, although the above embodiment does not particularly mention updating of the database 130, the present invention is not limited to this. For example, the database 130 may be updated for each examination of the subject 1.

[0091] 4, the processing unit 120 has a data updating unit 123 in addition to the components shown in Fig. 1. The data updating unit 123 stores internal abnormality information, parameter information set by the internal inspection unit 140, evaluation formula information, etc. in the database 130 after an inspection of the subject 1 is performed. The data updating unit 123 updates the information stored in the database 130 every time an inspection of the subject 1 is performed.

[0092] The timing of the data update by the data update unit 123 may be, for example, after the processing of step S105 in Fig. 2. For example, after the processing of step S105, when the parameter determination unit 122 changes the coefficients of the evaluation formula based on the internal scan data, the data update unit 123 updates the values ​​stored in the database 130 to the changed values. This makes it possible to use the evaluation formula to which the updated coefficients have been applied when an evaluation is performed.

[0093] The timing of the data update by the data update unit 123 may be, for example, after the processing of step S106 in Fig. 2. For example, the data update unit 123 may add the result of the evaluation of the degree of internal abnormality obtained in the processing of step S106 to the database 130 as an update.

[0094] Furthermore, in the above embodiment, the details of the internal abnormality (such as peeling) are used as the inspection result, but the present invention is not limited to this. For example, the inspection result may be an estimated result of the compressive strength after impact of a CFRP member. In this case, only the estimated result of the compressive strength after impact may be displayed on the display device 2, or both the details of the internal abnormality and the estimated result of the compressive strength after impact may be displayed on the display device 2 as the inspection result. As a method for estimating the compressive strength after impact, a known method such as that described in Non-Patent Document 2 may be applied. Furthermore, the evaluation formula, algorithm, hyperparameters in machine learning, etc. used to estimate the strength of the specimen 1 may be determined by the parameter determination unit by referring to the database 130, etc.

[0095] In the above embodiment, the internal inspection unit 140 is an ultrasonic device that can generate ultrasonic waves based on a piezoelectric element and transmit and receive ultrasonic waves, but the present invention is not limited to this. For example, the internal scanner unit may be a device that does not generate ultrasonic waves but can receive ultrasonic waves generated by irradiating waves different from ultrasonic waves, such as light, such as an optical ultrasonic device, a laser ultrasonic device, or an electromagnetic ultrasonic device.

[0096] Furthermore, in the above embodiment, the specimen 1 is made of CFRP, but the present invention is not limited to this, and may be made of a composite material other than CFRP, such as GFRP (Glass Fiber Reinforced Plastic).

[0097] Furthermore, in the above embodiment, the processing unit 120 and the internal inspection unit 140 are separate, but the present invention is not limited to this, and for example, the processing unit may be built into the internal scanner unit.

[0098] Furthermore, in the above embodiment, the estimation unit and the setting unit are included in the processing unit, but the present invention is not limited to this, and the estimation unit and the setting unit may be provided separately.

[0099] Furthermore, the above-described embodiments are merely examples of specific embodiments for carrying out the present invention, and the technical scope of the present invention should not be construed as being limited by these embodiments. In other words, the present invention can be carried out in various forms without departing from the gist or main features thereof.

[0100] The disclosures of the specification, drawings and abstract contained in Japanese Patent Application No. 2024-026795, filed February 26, 2024, are incorporated herein by reference in their entirety.

[0101] REFERENCE SIGNS LIST 1 Inspection object 100 Inspection device 110 Visual inspection unit 120 Processing unit 121 Analysis unit 122 Parameter determination unit 123 Data update unit 130 Database 140 Internal inspection unit

Claims

1. An inspection device comprising: an internal inspection unit that inspects an internal abnormality of a test subject; an estimation unit that estimates the degree of internal abnormality for each external part of the test subject based on external appearance information of the test subject; and a setting unit that sets parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part.

2. The inspection device according to claim 1, further comprising a memory unit that stores a data set in which the external appearance anomaly information and internal anomaly information of the subject are linked, and the estimation unit extracts from the memory unit the internal anomaly information corresponding to the shape of the depression calculated from the external appearance information.

3. The inspection device according to claim 2, wherein the visual abnormality information is information about the shape of a depression on the exterior of the subject.

4. The inspection device according to claim 1, wherein the setting unit excludes from the inspection target of the internal inspection unit any portion for which the value indicating the estimated degree of internal abnormality is outside a predetermined range.

5. The inspection device according to claim 4, wherein the setting unit sets a region in the subject requiring inspection as the inspection target, regardless of whether it has been excluded from the inspection target.

6. The inspection device according to claim 1, wherein the internal inspection unit is an ultrasonic device.

7. The inspection device according to claim 1, further comprising an appearance inspection unit that detects appearance information of the subject.

8. The inspection device according to claim 7, wherein the appearance inspection unit is an optical camera.

9. The inspection device according to claim 1, wherein the test object is made of carbon fiber reinforced plastic.

10. The inspection device according to claim 1, wherein the setting unit sets different parameter values ​​depending on the degree of internal abnormality of the subject.

11. An inspection method using an internal inspection unit, comprising: estimating the degree of internal abnormality for each part of a test subject based on external appearance information of the test subject; setting parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part; and inspecting the test subject for internal abnormalities using the internal inspection unit.

12. An inspection program using an internal inspection unit, which causes a computer to execute the following processes: a process of estimating the degree of internal abnormality for each part of a test subject based on external appearance information of the test subject; a process of setting parameters in the internal inspection unit according to the estimated degree of internal abnormality for each part; and a process of inspecting the test subject for internal abnormalities using the internal inspection unit.

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