Design support device and design support method

Abstract

To provide a design support device and a design support method that take into consideration a non-destructive inspection.SOLUTION: A design support device includes: an input processing unit 10 that receives input of a CAD model related to an object to be subjected to a non-destructive inspection, and also receives input of information related to a supposed anticipated defect and a design variable in the CAD model; a detection probability processing unit 30 that calculates a detection probability curve for the supposed defect; a sensitivity analysis unit 40 that calculates sensitivity of a detection probability, which is the degree of change in the detection probability curve when the design variable is changed; and a display processing unit 50 that outputs the detection probability and the sensitivity. The input processing unit 10 also includes a check unit 20 that receives characteristic information of an inspection probe for performing the non-destructive inspection and determines, on the basis of the characteristic information of an inspection probe and the CAD model, whether or not the inspection probe can be installed.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a design support device and a design support method. [Background technology]

[0002] In the structural design of power plants, railway bogies, aircraft, etc., it is common for designers to use a CAD (Computer-Aided-Design) system to create the design on a computer. This type of design using CAD is generally called CAD design.

[0003] Furthermore, manufacturing that utilizes 3D printers and CAE (Computer-Aided-Engineering), which analyzes the strength of products using numerical simulations on computers, is becoming more widespread. CAD design and CAE are making product structures more complex.

[0004] Due to the complexity of product design, there are cases where multiple design factors exist. In such cases, it is desirable to support the designer by evaluating the degree of influence of each design factor and presenting this to the designer at the CAD design stage.

[0005] For example, Patent Document 1 discloses a design support system for structures, etc., characterized by comprising: "orthogonal array allocation means (S10) for allocating data related to design variables and levels set based on an analysis object to columns and rows of an orthogonal array selected in accordance with the design variables and levels; structural analysis means (S20) for performing structural analysis or experiments on data for each row allocated to the orthogonal array; variance analysis means (S30) for performing a variance analysis based on the results of the structural analysis means; estimation formula creation means (S31) for extracting design variables and order components that have a large effect on characteristic values ​​that represent the properties of the analysis object based on the variance analysis and creating an estimation formula using an orthogonal function based on the extracted design variables and order components; optimization design means (S4) for performing a target optimization calculation based on a mathematical optimization calculation method after implementing the estimation formula creation means (S31); and reliability evaluation means (S5) for obtaining a numerical value representing an evaluation of reliability by applying a probability / statistical method after implementing the optimization design means (S4)" (see Claim 1). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 3313040 specification Summary of the Invention [Problem to be solved by the invention]

[0007] On the other hand, non-destructive testing is used for the purpose of product quality assurance, maintenance, and investigation when problems occur. There are various methods for non-destructive testing, but in ultrasonic testing, for example, a probe is placed on the surface of the product. The ultrasonic waves generated from the probe are reflected by defects and then reach the probe again, making it possible to detect defects.

[0008] In particular, ultrasonic flaw detection has limitations on its applicability, such as whether or not a probe can be installed and whether an ultrasonic wave propagation path can be secured. When CAD design is performed, the designer must take into consideration the applicability of the above-mentioned non-destructive testing for increasingly complex product structures. If the applicability of non-destructive testing is not taken into consideration, there is a possibility that a problem will arise in which there will be no inspection means available during maintenance or investigations after an accident. Patent Document 1 does not provide support for the applicability of the above-mentioned non-destructive testing.

[0009] The present invention has been made in view of the above background, and an object of the present invention is to provide design support that takes non-destructive testing into consideration. [Means for solving the problem]

[0010] In order to solve the above-mentioned problems, the present invention comprises an input processing unit that accepts input of design information related to an object to be non-destructively inspected, and also accepts input of information related to anticipated defects and design variables in the design information, a detection probability processing unit that calculates a detection probability curve for the anticipated defects, a sensitivity analysis unit that calculates the sensitivity of the detection probability, which is the degree of change in the detection probability curve when the design variables are changed, and an output processing unit that outputs the detection probability and the sensitivity. Other solutions will be described as appropriate in the embodiments. [Effects of the Invention]

[0011] According to the present invention, it is possible to provide design support using CAD design that takes non-destructive testing into consideration. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a functional block diagram showing a configuration of a design support apparatus according to an embodiment of the present invention; [Figure 2] FIG. 1 is a diagram illustrating a hardware configuration of a design support apparatus according to an embodiment of the present invention. [Figure 3] FIG. 10 is a conceptual diagram illustrating details of an input screen. [Figure 4] FIG. 2 is a functional block diagram showing the configuration of a check unit. [Figure 5A] FIG. 10 is a diagram (part 1) showing an example of a check result for a structure in which plate-like members are welded together by fillet welding. [Figure 5B] FIG. 2 is a diagram (part 2) showing an example of the check results for a structure in which plate-like members are welded together by fillet welding. [Figure 5C] FIG. 3 is a diagram (part 3) showing an example of the check results for a structure in which plate-like members are welded together by fillet welding. [Figure 6A] FIG. 10 is a diagram (part 1) showing an example of the check results for a structure in which plate-shaped members are butt-welded to each other. [Figure 6B] FIG. 2 is a diagram (part 2) showing an example of the check results for a structure in which plate-shaped members are butt-welded to each other. [Figure 6C] FIG. 10 is a diagram (part 3) showing an example of the check results for a structure in which plate-shaped members are butt-welded to each other. [Figure 7] FIG. 2 is a functional block diagram showing a configuration of a detection probability processing unit. [Figure 8] 10 is a conceptual diagram illustrating an example of a probability distribution stored in an inspection probability distribution storage unit. FIG. [Figure 9A] FIG. 1 is a conceptual diagram (part 1) illustrating the operation of a simulation execution unit. [Figure 9B] FIG. 2 is a conceptual diagram (part 2) illustrating the operation of the simulation execution unit. [Figure 10] FIG. 10 is a conceptual diagram illustrating an example of an operation result by a simulation execution unit. [Figure 11A] 10 is a conceptual diagram (part 1) illustrating an operation result of a detection probability calculation unit. [Figure 11A] 10 is a conceptual diagram (part 2) illustrating an operation result of the detection probability calculation unit. [Figure 12] 10A and 10B are conceptual diagrams illustrating operation results of a sensitivity analysis unit. [Figure 13] FIG. 10 is a conceptual diagram illustrating details of a result display screen displayed on a display unit. [Figure 14] 1 is a flowchart showing the overall procedure of a design support method. [Figure 15] 10 is a flowchart showing a detailed procedure of a check step. [Figure 16] 10 is a flowchart showing details of a detection probability processing step. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the drawings, the same components are designated by the same reference numerals, and detailed description of overlapping parts will be omitted.

[0014] A design support device 1 according to an embodiment of the present invention will be described with reference to FIGS.

[0015] (Design support device 1) FIG. 1 is a functional block diagram showing the configuration of a design support device 1 according to this embodiment.

[0016] 1, the design support device 1 includes an input processing unit 10, a check unit 20, a detection probability processing unit 30, a sensitivity analysis unit 40, a display processing unit 50 which is an output processing unit, an input unit 61, and a display unit 62.

[0017] The input processing unit 10 receives a CAD model CM (see FIG. 3) and feature quantities including an assumed defect position D1 (see FIG. 3) input via the input unit 61. Specifically, the input processing unit 10 receives input of a CAD model CM (design information) related to an object to be subjected to non-destructive testing. The input processing unit 10 also receives input of information (assumed defect position D1) related to an assumed defect D2 (see FIGS. 5A to 6C) and design variables in the CAD model CM. The design variables are the objects to be analyzed by the sensitivity analysis unit 40, which will be described later. The design variables will be described later.

[0018] The input processing unit 10 also receives characteristic information of the inspection probe P (see FIGS. 5A to 6C) that performs the non-destructive inspection. The characteristic information of the inspection probe P includes information such as the type of the inspection probe P (see FIGS. 5A to 5C), the size of the inspection probe P, the ultrasonic wave incident angle, etc.

[0019] The check unit 20 determines whether the inspection probe P can be installed based on the characteristic information of the inspection probe P and the design information.

[0020] The detection probability processing unit 30 calculates a detection probability curve 510 (see FIGS. 11A and 11B) for the assumed defect D2. Specifically, the detection probability processing unit 30 calculates the detection probability curve 510 (see FIGS. 11A and 11B), which is a distribution curve of the detection probability of the assumed defect D2 occurring at the assumed defect position D1. The detection probability curve 510 is not limited to a curve, and may be a combination of straight lines or a combination of straight lines and curves.

[0021] The sensitivity analysis unit 40 analyzes the sensitivity of the detection probability by sensitivity analysis. Specifically, the sensitivity analysis unit 40 calculates the sensitivity of the detection probability, which is the degree of change in the detection probability curve 510 when the design variables are changed.

[0022] The display processing unit 50 displays (outputs) the results of the sensitivity analysis (sensitivity) and the detection probability from the sensitivity analysis unit 40 on the display unit 62. Details of the processing performed by each of the input processing unit 10 to the display processing unit 50 will be described later. In this embodiment, ultrasonic flaw detection will be particularly described as an example, but the present invention can also be applied to other non-destructive inspection methods, such as eddy current flaw detection and radiographic testing.

[0023] (Hardware configuration diagram) FIG. 2 is a diagram showing the hardware configuration of the design support device 1 according to this embodiment.

[0024] The design support device 1 is configured by a PC (Personal Computer) or the like, and includes a memory 81, a calculation device 82, a storage device 83, an input device 84, and a display device 85.

[0025] The memory 81 is composed of a RAM (Random Access Memory) or the like. The arithmetic device 82 is composed of a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), or the like. The storage device 83 is composed of an HDD (Hard Disk Drive), an SSD (Solid State Drive), or the like. The input device 84 is composed of a keyboard, a mouse, or the like (not shown). The display device 85 is composed of a display, or the like (not shown).

[0026] In this way, the design support device 1 of this embodiment is realized as an information processing device that operates by software on a computer having hardware resources such as a CPU, a ROM, a RAM, and a HDD.

[0027] 1 corresponds to the input device 84 in FIG. 2, and the display unit 62 in FIG. 1 corresponds to the display device 85 in FIG.

[0028] Furthermore, a program stored in the storage device 83 is loaded into the memory 81, and the loaded program is executed by the arithmetic device 82. As a result, the input processing unit 10 to the display processing unit 50 shown in FIG.

[0029] (Input information) 3 is a conceptual diagram illustrating details of the input screen 100. FIG. 1 will be referred to as appropriate.

[0030] The input screen 100 is composed of a CAD model display section 110, an inspection probe setting section 120, and a design variable setting section .

[0031] In the CAD model display unit 110, the designer operates a mouse pointer 111 or the like on the CAD model CM, which is the target of design support, using an input device (input unit 61) such as a mouse. This sets the assumed defect position D1, which is information about the assumed defect D2 (FIGS. 5A to 6C), and each part of the CAD model CM. The assumed defect position D1 is the position where a defect is thought to occur, and is set by manual input by the designer. The assumed defect position D1 is set by the designer by estimating the location where a load is applied, etc.

[0032] 3, the object to be inspected is composed of two plate-shaped members M1 and M2 connected in an L-shape, with two holes H1 and H2 formed in one of the plate-shaped members M1. An assumed defect position D1 is set at the connection between the two plate-shaped members M1 and M2.

[0033] In the inspection probe setting unit 120, the type of inspection probe P (see FIGS. 5A to 5C) expected to be used during inspection and information about the inspection probe P are set as characteristic information. For example, as shown in FIG. 3, if an ultrasonic flaw detector is expected to be used as the inspection probe P, characteristics of the inspection probe P such as the frequency of ultrasonic waves, the size of the ultrasonic flaw detector, and the ultrasonic incident angle are set. Information such as whether the inspection probe is a longitudinal wave or a transverse wave may also be set as a characteristic of the inspection probe P set in the inspection probe setting unit 120.

[0034] In the design variable setting section 130, design variables associated with the parts defined in the CAD model display section 110 are set.

[0035] 3, the plate thickness of plate-shaped member M1 (described as "plate A" in the design variable setting unit 130) and the position of hole H1 (described as "hole A" in the design variable setting unit 130) are selected as design variables. In other words, the plate thickness of plate-shaped member M1 and the position of hole H1 can be changed at the design stage.

[0036] (Check section 20) Next, details of the check unit 20 and the operation of the check unit 20 will be described with reference to FIGS. 4 to 6C.

[0037] FIG. 4 is a functional block diagram showing the configuration of the check unit 20.

[0038] 4, the checking unit 20 includes a determination rule specifying unit 21, a determination rule storage unit 22, a shape recognition unit 23, a shape recognition module storage unit 24, and a determination unit 25. The checking unit 20 uses information stored in a CAD model storage unit 71 and an inspection probe storage unit 72 to determine whether or not inspection is possible using the set inspection probe P (see FIGS. 5A to 5C).

[0039] The CAD model storage unit 71 stores the CAD model CM received by the input processing unit 10, the assumed defect position D1 (see FIG. 3), and shape information of each part of the CAD model CM. The CAD model storage unit 71 also stores information such as the size and depth of the assumed defect D2 (see FIGS. 5A to 6C). The information such as the size and depth of the assumed defect D2 is information that the designer inputs via the input unit 51 in the CAD model display unit 110 shown in FIG.

[0040] The shape information is information about the shape of the CAD model CM, such as the sizes of the holes H1 and H2 (see FIG. 3).

[0041] The inspection probe storage unit 72 stores information about the inspection probe P received by the input processing unit 10. Specifically, the information set by the inspection probe setting unit 120 in FIG.

[0042] The judgment rule storage unit 22 stores judgment rules. A judgment rule describes installation conditions under which an ultrasonic inspection probe P (ultrasonic flaw detection device) can detect a predicted defect D2. A plurality of judgment rules are stored as a database in the judgment rule storage unit 22. The judgment rules may be set by a designer using an input screen 200 shown in FIG. 3. In this way, an appropriate judgment rule can be set.

[0043] The determination rule specifying unit 21 specifies a determination rule to be applied from the determination rule storage unit 22 based on the conditions stored in the CAD model storage unit 71 and the inspection probe storage unit 72. That is, the determination rule specifying unit 21 specifies a determination rule for determining whether or not the inspection probe P can be installed based on the design information and characteristic information of the inspection probe P (see FIGS. 5A to 6C).

[0044] The shape recognition module storage unit 24 stores a shape recognition module. The shape recognition module is a procedural function that can be called on a computer and applied to the CAD model CM. Specifically, the shape recognition module is a group of basic processes that can generate shape information such as the length of an edge, curvature, area of ​​a face, volume of a part, distances between edges, faces, and parts, and angles on the CAD model CM.

[0045] The shape recognition unit 23 configures the procedures required to check the judgment rules by combining shape recognition modules stored in the shape recognition module storage unit 24. Here, the procedure refers to the process of calculating information (such as plate thickness) required for the judgment performed by the judgment unit 25. The shape recognition modules are modules assigned to processes such as the inspection probe installation range (described later), which is a type of shape information, and the process of calculating the volume of a part, for example. In other words, one shape recognition module calculates the inspection probe installation range, and another shape recognition module calculates, for example, the volume of a part. The procedures required to check the judgment rules are configured by combining the required shape recognition modules.

[0046] In this way, the shape recognition unit 23 uses the combined shape recognition modules to generate, from the CAD model CM, shape information other than the shape information registered in the CAD model CM.

[0047] The shape information registered in the CAD model CM may not be sufficient as the shape information to be used in the determination rules. The shape recognition unit 23 (shape recognition module) generates shape information other than the shape information registered in the CAD model CM, thereby enabling the determination unit 25 to make a stable determination.

[0048] The determination unit 25 determines whether or not the conditions defined by the determination rule identified by the determination rule identification unit 21 are met. The determination unit 25 makes the determination based on the shape information generated by the procedure (combined shape recognition modules) configured by the shape recognition unit 23 and the shape information set in the CAD model CM. In other words, the determination unit 25 makes the determination based on the characteristic information of the inspection probe P and the shape information of the object based on the design information.

[0049] The details of the operation performed by the check unit 20 will be explained using the examples shown in FIGS.

[0050] 5A to 5C are diagrams showing examples of check results for structures 210a to 210c in which plate-shaped members M1 and M2 are welded by fillet welding. A weld bead B is provided at the fillet welded weld.

[0051] 5A to 5C, it is assumed that ultrasonic testing is being performed on the assumed defect D2a (D2) by an inspection probe P, which is an ultrasonic testing device. Note that the inspection probe P shown in FIGS. 5A to 5C is not actually installed, but is virtually installed in the CAD model CM (see FIG. 3). The determination rule in FIGS. 5A to 5C is that the inspection probe P can be installed on the top surface of the plate-like member M1 and that an ultrasonic propagation path W exists.

[0052] The judgment rule is that the specified inspection probe installation range must be free of other parts, irregularities, holes H (see Figures 5B and 5C), etc. that may obstruct the installation of the inspection probe. The specified inspection probe installation range is set as a range centered at a position a distance "x = 2t tan θ" (reference numeral 221) away from the assumed defect D2a. "t" is the plate thickness of the plate-like member M1, which is shape information, and "θ" is the ultrasonic transmission / reception angle, which is characteristic information. The plate thickness "t" and the inspection probe installation range required for the judgment made by the judgment unit 25 are each calculated by individual shape recognition modules as necessary.

[0053] In the example shown in FIG. 5A, the above judgment rule is satisfied, and the inspection probe P can be installed. In other words, the judgment unit 25 judges that the judgment rule is met. Compliance with the judgment rule is indicated by a "◯" mark on the inspection probe P. FIG. 5A shows that the assumed defect D2a is an allowable defect.

[0054] In the example shown in FIG. 5B, a hole H exists at the position where the inspection probe P is to be installed. Therefore, the judgment unit 25 judges that the judgment rule has been violated. The violation of the judgment rule is indicated by an "x" mark on the inspection probe P. Note that in the example shown in FIG. 5B, the signal strength TW (see FIGS. 9A and 9B) described below is "0", and the detection probability described below is also processed as "0".

[0055] In the example shown in FIG. 5B, the designer can make the position of the hole H conform to the judgment rule by changing the design, as shown in FIG. 5C. Conformity to the judgment rule is indicated by a "circle" mark on the inspection probe P. The design change is made by the designer based on the calculation results of the sensitivity, which will be described later. The design change shown in FIG. 5C may also be made by the design support device 1.

[0056] 6A to 6C are diagrams showing examples of check results for structures 220a to 220c in which plate-shaped members M3 and M4 are butt-welded.

[0057] 6A to 6C, the defect is assumed to be poor welding penetration. As with the examples of FIGS. 5A to 5C, the judgment rules for FIGS. 6A to 6C also require that the inspection probe P can be placed on the top surface of the plate-like member M4 and that an ultrasonic propagation path W exists. As with FIGS. 5A to 5C, the inspection probe P shown in FIGS. 6A to 6C is not actually placed, but is virtually placed on the CAD model CM (see FIG. 3).

[0058] The judgment rule in Figures 6A to 6C is that the specified inspection probe installation range must be free of other parts, irregularities, holes H (see Figures 5B and 5C), etc. that may obstruct the installation of the inspection probe. The specified inspection probe installation range is a range centered at a position a distance "x = t tan θ" (reference numeral 221) away from the assumed defect D2b (D2). "t" is the plate thickness of the plate-shaped member M4, which is shape information, and "θ" is the ultrasonic transmission / reception angle (characteristic information). The plate thickness "t" and the inspection probe installation range required for the judgment performed by the judgment unit 25 are each calculated by individual shape recognition modules as necessary.

[0059] In the example shown in Fig. 6A, the above judgment rule is satisfied. Therefore, the judgment unit 25 judges that the judgment rule is satisfied and that the inspection probe P can be installed. Compliance with the judgment rule is indicated by a "◯" mark on the inspection probe P. Fig. 6A shows that the assumed defect D2b is an allowable defect.

[0060] In the example shown in FIG. 5B, a weld bead Bb due to poor penetration is present at the position where the inspection probe P should be placed. Therefore, the determination unit 25 determines that the determination rule has been violated. The violation of the determination rule is indicated by an "x" mark on the inspection probe P. Note that in the example shown in FIG. 6B, the signal strength TW (see FIGS. 9A and 9B), which will be described later, is "0," and the detection probability, which will be described later, is also processed as "0."

[0061] In this case, for example, as shown in the example of FIG. 6C, the designer can make a design change to remove the weld bead Bc, thereby making the design conform to the judgment rule. Conformity to the judgment rule is indicated by a "◯" mark on the inspection probe P. The design change is made by the designer based on the sensitivity calculation results described below. The design change to remove the weld bead Bc may also be made by the design support device 1.

[0062] As described above, the check unit 20 can determine whether the selected inspection probe P can be installed based on the geometric positional relationship between the selected assumed defect D2 (D2a, D2b) and the inspection probe P. If there is a violation of the determination rules, the designer can take measures as shown in Figures 5C and 6C and make design changes, or change the inspection probe P, to search for appropriate inspection conditions. Note that design changes are made by the designer depending on the results of the sensitivity analysis described below.

[0063] (Detection probability processing unit 30) Next, the details of the detection probability processing unit 30 and the operation of the detection probability processing unit 30 will be described with reference to FIGS.

[0064] (Detection probability processing unit 30) FIG. 7 is a functional block diagram showing the configuration of the detection probability processing unit 30.

[0065] The detection probability processing unit 30 includes a simulation execution unit 31, an inspection probability distribution storage unit 32, a detection probability calculation unit 33, and a random number generation unit 34. The detection probability processing unit 30 performs a detection probability curve 510 (see FIGS. 11A and 11B) and sensitivity analysis using information stored in a CAD model storage unit 71 and an inspection probe storage unit 72. The CAD model storage unit 71 and the inspection probe storage unit 72 have the same configurations as the CAD model storage unit 71 and the inspection probe storage unit 72 in FIG. 4.

[0066] The inspection probability distribution storage unit 32 stores a probability distribution for assumed defects D2 (see FIGS. 5A to 6C) detected in an actual inspection. For example, the inspection probability distribution storage unit 32 stores a probability distribution for each design variable, such as the size of assumed defect D2, the orientation of assumed defect D2, the installation position of inspection probe P, and the probability distribution of irradiation angle. As such, the inspection probability is based on an actual inspection and is the probability that a value of a design variable occurs. In contrast, the detection probability is based on a simulation and is the probability that assumed defect D1 will be detected by the simulation.

[0067] The simulation execution unit 31 calculates, by simulation, a received signal in an inspection by the inspection probe P based on characteristic information of the inspection probe P (see FIGS. 5A to 6C). Specifically, the simulation execution unit 31 samples design variables based on the CAD model storage unit 71, the inspection probe storage unit 72, and the inspection probability distribution storage unit 32, and constructs a simulation model. At this time, the simulation execution unit 31 uses the values ​​of the design variables randomly sampled by the random number generation unit 34 for the simulation.

[0068] Based on the results of the simulation by the simulation execution unit 31, the detection probability calculation unit 33 calculates a detection probability curve 510 (see FIGS. 11A and 11B) which is a distribution curve of the probability of detecting an assumed defect.

[0069] (Inspection probability distribution storage unit 32) FIG. 8 is a conceptual diagram illustrating the probability distribution stored in the inspection probability distribution storage unit 32.

[0070] The probability distribution for each design variable is stored as probability density functions 321 to 324 in the inspection probability distribution storage unit 32. The design variables include the size (assumed defect size) of the assumed defect D2 (see FIGS. 5A to 6C), the installation position of the inspection probe P (probe position), the direction of the assumed defect D2 (assumed defect direction), and the ultrasonic irradiation angle. For example, the probability density function 321 of the size (assumed defect size) of the assumed defect D2 is set as a uniform distribution, and the probability density function 322 of the probe position is set as a normal distribution. In addition, the probability density functions 323 and 324 of the direction (assumed defect direction) of the assumed defect D2 and the irradiation angle are set as normal distributions.

[0071] Setting items may be provided on the input screen 100 so that the designer can set these probability density functions 321 to 324. That is, the probability density functions 321 to 324 stored in the inspection probability distribution storage unit 32 can be set by the designer. In this way, appropriate probability density functions 321 to 324 can be set. Alternatively, the probability density functions 321 to 324 may be stored in advance in the inspection probability distribution storage unit 32.

[0072] (Operation of simulation execution unit 31) 9A and 9B are conceptual diagrams illustrating the operation of the simulation execution unit 31. FIG.

[0073] FIG. 9A shows an example in which the installation position and irradiation angle of the inspection probe P are somewhat flexible. FIG. 9B shows an example in which the installation position and irradiation angle of the inspection probe P are limited due to the presence of a hole H in the plate-like member M1. Note that the structure 210a shown in FIG. 9A has a configuration similar to the structure 210a shown in FIG. 5A. Also, the structure 210c shown in FIG. 9B has a configuration similar to that shown in FIG. 5C. Therefore, in FIGS. 9A and 9B, the same components as those in FIGS. 5A and 5C are denoted by the same reference numerals, and their descriptions are omitted as appropriate. Note that the "◯" mark shown on the inspection probe P in FIG. 9A indicates that the inspection probe P is installed in a more preferable position compared to FIG. 9B. Conversely, the "X" mark shown on the inspection probe P in FIG. 9B indicates that the inspection probe P is installed in an unfavorable position compared to FIG. 9A.

[0074] As shown in FIG. 9A, when there are no constraints on the design variables, the signal strength TW1 (TW; that is, the received signal strength received by the inspection probe P) is evaluated as the signal strength emitted by the inspection probe P.

[0075] Furthermore, when there are restrictions on the design variables as shown in Fig. 9B, the signal strength TW2(TW) is evaluated to be smaller than the signal strength TW1 shown in Fig. 9A. Note that when the checking unit 20 determines that a determination rule has been violated as in Fig. 5B and Fig. 6B, the signal strength TW is always evaluated to be "0" as described above.

[0076] A general analytical method such as the finite element method can be used for the simulation by the simulation execution unit 31. The signal intensities TW1 and TW2 shown in Figures 9A and 9B are based on the propagation waveforms analyzed by such a method (such as the finite element method).

[0077] FIG. 10 is a conceptual diagram illustrating an example of the operation result by the simulation execution unit 31. As shown in FIG.

[0078] 10 plots the received signal strength of the inspection probe P calculated by the simulation execution unit 31. In the graph shown in Fig. 10, the horizontal axis represents the assumed defect size, and the vertical axis represents the received signal strength. For example, plot point 401 is the calculation result of one simulation, and the number of plot points 401 increases as sampling and simulation are repeated many times.

[0079] 10 shows the simulation results for the assumed defect size as one of the design variables, but similar simulations are also performed for other design variables such as the probe position, assumed defect direction, and irradiation angle shown in Fig. 8. In this case, the simulation execution unit 31 uses the random number generation unit 34 to randomly sample each design variable and use it as the input for the simulation.

[0080] (Detection probability calculation unit 33) Next, the operation of detection probability calculation section 33 will be described with reference to FIGS. 10 to 11B.

[0081] In Fig. 10, line 402 is a graph showing a threshold value for determining whether or not detection is possible. If the received signal strength indicated by plot point 401 is smaller than line 402, detection is impossible, and if it is greater than line 402, detection is possible. Then, detection probability calculation unit 33 calculates probability of detection (POD) curve 510 (see Figs. 11A and 11B) using the simulation results shown in Fig. 10. Note that in Fig. 10, line 403 is a regression line of plot point 401.

[0082] The detection probability calculation unit 33 sets a value of "1" when the simulated received signal strength is greater than the threshold (line 402), and a value of "0" when the simulated received signal strength is less than the threshold (line 402). Based on these results, the detection probability calculation unit 33 calculates a detection probability curve 510 (see FIGS. 11A and 11B). One method for calculating such a detection probability curve 510 is the Hit / Miss method, which calculates the detection probability for each assumed defect size using a maximum likelihood estimation method. Another method for calculating the detection probability curve 510 is the a-hat vs. a method, which calculates the detection probability from the fitting results of the received signal strength. Either method may be used in this embodiment.

[0083] In the example shown in FIG. 10, the number of plot points 401 increases as the assumed defect size increases, and therefore, as the assumed defect size increases, the detection probability also increases.

[0084] When the calculated detection probability curve 510 is expressed as a mathematical formula, it is assumed to have the form shown in, for example, formula (1).

[0085]

number

[0086] In equation (1), "erfc" is a complementary error function, and "β1," "β2," and "β3" are estimated parameters. Furthermore, "a" is the value of a design variable. Furthermore, in equation (1), a case where "β3 = 1" is fixed, or a four-parameter model in which the detection probability is non-zero even when the assumed defect size is "0," may be used as the detection probability curve 510. Alternatively, a curve assuming a sigmoid function may be used as the detection probability curve 510. In this manner, a wide variety of patterns can be used for the detection probability curve 510. In this embodiment, the explanation will be given using the function form expressed by equation (1), but the same applies when other function forms such as those described above are assumed. Furthermore, an item for specifying which function form to use may be displayed on the input screen 100.

[0087] 11A and 11B are conceptual diagrams illustrating the operation results of the detection probability calculation unit 33. As shown in Fig. 9A, Fig. 11A corresponds to an example in which the installation position and irradiation angle of the inspection probe P are somewhat free. Also, as shown in Fig. 9B, Fig. 11B corresponds to an example in which the installation position and irradiation angle of the inspection probe P are limited.

[0088] The detection probability curve 511 shows the detection probability under optimal conditions, with the horizontal axis of the graph representing the assumed defect size and the vertical axis representing the detection probability. The optimal conditions mean that the installation environment (installation position, irradiation angle) of the inspection probe P is ideal. Note that the optimal conditions are actually unknown, and the detection probability curve 511 is a hypothetical curve.

[0089] The detection probability curve 512 represents the change in the detection probability when the simulation conditions are slightly changed from the detection probability curve 511. The conditions to be changed include, for example, design variables related to the inspection, such as the installation position of the inspection probe P, and design variables such as the plate thickness. The magnitude of the difference between the detection probability curve 511 and the detection probability curve 512 indicates the stability of the inspection with respect to the design variables. In other words, if the difference between the detection probability curve 511 and the detection probability curve 512 is small (smaller than a predetermined value), the detection probability calculation unit 33 determines that the inspection is stable with respect to the design variables. Conversely, if the difference between the detection probability curve 511 and the detection probability curve 512 is large (larger than a predetermined value), the detection probability calculation unit 33 determines that the inspection is not stable with respect to the design variables.

[0090] The detection probability curve 513 shown in FIG. 11B indicates the detection probability under optimal conditions with limited inspection conditions, as shown in FIG. 9B. The detection probability curve 514 shown in FIG. 11B indicates the change in detection probability when the simulation conditions (design conditions) are slightly changed relative to the detection probability curve 513. The difference between the detection probability curve 513 and the detection probability curve 514 is larger than the difference between the detection probability curve 511 and the detection probability curve 512 shown in FIG. 11A. In other words, in the example shown in FIG. 11B, the detection probability drops significantly with a slight change in the design variables. In other words, the example shown in FIG. 11B indicates that the stability of the inspection decreases when the inspection conditions are limited. Conversely, the detection probability curve 510 can be brought closer to the optimal conditions by changing the design variables.

[0091] As described above, by evaluating the extent to which the detection probability curve 510 changes due to changes in the design variables, a guideline for modifying the design is provided to the designer.

[0092] The detection probability processing unit 30 includes a simulation execution unit 31 and a detection probability calculation unit 33, and performs the processes shown in Figures 8 to 10, thereby making it possible to calculate the detection probability curve 510 without actually performing nondestructive testing. In particular, the random number generation unit 34 performs random sampling of design variables, making it easy to perform simulations based on random sampling.

[0093] (Sensitivity analysis part 40) The sensitivity analysis unit 40 performs sensitivity analysis to evaluate how the detection probability curve 510 changes with changes in the design variables. In particular, sensitivity evaluation is performed for the design variables specified in the design variable setting unit 130 on the input screen 100. For the design variable "x," the parameters that are characteristic values ​​of the detection probability curve 510 in Equation (1) are expressed as functions of the design variable "x," such as "β1(x)," "β2(x)," and "β3(x)." When the parameters "β1(x)," "β2(x)," and "β3(x)" change, the detection probability curve 510 shown in FIGS. 11A and 11B changes. The rate of change of the parameters of the detection probability curve 510 with respect to the design variable "x" is expressed by the respective amounts of change shown in Equation (2). The rate of change shown in Equation (2) is the sensitivity. This sensitivity represents the amount of change in the parameter that occurs with a unit change in the design variable. In other words, the sensitivity indicates the quantitative influence (contribution) of the design factors on the detection probability.

[0094]

number

[0095] The parameters "β1(x)", "β2(x)", and "β3(x)" of the detection probability curve 510 may be used themselves. Alternatively, any combination of "β1(x)", "β2(x)", and "β3(x)" may be used as the parameters of the detection probability curve 510. For example, "a50" defined in equation (3) as a combination of "β1(x)", "β2(x)", and "β3(x)" may be set as the characteristic value.

[0096] a50=exp[-β1(x) / β2(x)] ···(3)

[0097] "a50" in formula (3) represents the assumed defect size at which the probability of detecting assumed defect D2 (see Figures 5A to 6C) during inspection is 50%, and is the characteristic value that is the lower limit of detection. The rate of change of "a50" in formula (4) represents the sensitivity of the lower limit of detection with changes in the design variables.

[0098]

number

[0099] Furthermore, "β3(x)" represents the detection probability when the assumed defect D2 is sufficiently large, and is a characteristic value that represents the appropriateness of the inspection method.

[0100] The sensitivity is calculated using the detection probability curve 510 calculated by simulation. That is, the sensitivity analysis unit 40 calculates the sensitivity by calculating how much the characteristic value of the detection probability curve 510 calculated by simulation changes when the design variables are changed.

[0101] In this embodiment, the sensitivity of the detection probability is calculated based on the characteristic values ​​(β1 to β3, α50, etc.) of the detection probability curve 510, but this is not limiting. For example, the sensitivity may be calculated based on the square sum error between the detection probability curve 511 and the detection probability curve 512 (or the detection probability curve 513 and the detection probability curve 514).

[0102] In this way, the sensitivity analysis unit 40 calculates the amount of change in the detection probability curve 510 in response to changes in the design variables as the sensitivity of the detection probability, thereby providing a specific method for calculating the sensitivity of the detection probability.

[0103] (Operation results of sensitivity analysis unit 40) FIG. 12 is a conceptual diagram illustrating the operation result of the sensitivity analysis unit 40. In FIG.

[0104] The graph shown in Figure 12 shows the sensitivity of each design variable related to inspection to the characteristic values ​​mentioned above. In the graph shown in Figure 12, the horizontal axis represents the design variable and the vertical axis represents the sensitivity. According to the example shown in Figure 12, the "hole A position" has the highest sensitivity. Note that "hole A" corresponds to hole H1 in Figure 3. In other words, changing the position of "hole A" (hole H1) results in a large change in detection by the inspection probe P. Also, the "probe angle" has a negative sensitivity. This means that moving the "probe angle" in the negative direction increases the sensitivity.

[0105] The designer can design a better detection probability curve 510 by trying to select design variables or inspection probes P according to the sensitivity changes as shown in FIG.

[0106] (Result display screen 600) FIG. 13 is a conceptual diagram illustrating details of the result display screen 600 displayed on the display unit 62.

[0107] On the result display screen 600, the results of the check section 20, the detection probability processing section 30, and the sensitivity analysis section 40 are all presented to the designer.

[0108] Specifically, the result display screen 600 includes a CAD model display section 610, a detection probability display section 620, and a sensitivity analysis display section 630.

[0109] The CAD model display unit 610 displays the CAD model CM of the design support target and the assumed defect position D1 received by the input processing unit 10. The CAD model CM and assumed defect position D1 displayed on the CAD model display unit 610 are the same as those shown in Fig. 3, so they are denoted by the same reference numerals as in Fig. 3 and will not be described in Fig. 13.

[0110] The detection probability display section 620 displays the detection probability calculated by the detection probability processing section 30.

[0111] The sensitivity analysis display section 630 displays the sensitivity to each design variable calculated by the sensitivity analysis section 40.

[0112] By analyzing the sensitivity with the sensitivity analysis unit 40, it becomes possible to quantitatively evaluate whether stable inspection (detection of defects) is possible.

[0113] By displaying such a result display screen 600 on the display unit 62, the designer can receive design support that takes non-destructive testing into consideration at the design stage. In particular, the sensitivity analysis display unit 630 allows the designer to intuitively recognize which design variables should be changed to increase the detection probability. This allows the designer to receive design support that takes non-destructive testing into consideration at the design stage. The designer can then recognize the design change policy.

[0114] (Design support method) 14 to 16, a design support method using the design support device 1 will be described. Details of the operation in each operation step are the same as the operations of each part of the design support device 1 already described.

[0115] FIG. 14 is a flowchart showing the overall procedure of the design support method.

[0116] In the following description, reference will be made to FIGS. 1 to 13 as appropriate.

[0117] First, in input step S1, the input processing unit 10 accepts input of design information related to an object to be non-destructively inspected. Furthermore, in input step S1, the input processing unit 10 accepts input of information related to an assumed defect D2 including an assumed defect position D1, and design variables in the design information. That is, in input step S1, the designer inputs a CAD model CM and feature quantities including the assumed defect position D1 via the input unit 61. The processing content of input step S1 is the content described with reference to FIG. 3.

[0118] Then, in the check step S2, the check unit 20 uses the input feature amount to determine whether or not the inspection probe P can be installed. The process content of the check step S2 is the content that has been described with reference to Figs. 4 to 6C.

[0119] Then, in detection probability processing step S3, detection probability processing unit 30 calculates detection probability curve 510 of the defect (assumed defect D2) occurring at assumed defect position D1. The processing content of detection probability processing step S3 is the content described with reference to FIGS. 7 to 11B.

[0120] Subsequently, in a sensitivity analysis step S4, the sensitivity analysis unit 40 calculates the sensitivity of the detection probability, which is the degree of change in the detection probability curve 510 when the design variables are changed. Specifically, in the sensitivity analysis step S4, the sensitivity analysis unit 40 performs the sensitivity analysis by calculating the amount of change in the detection probability curve 510 in response to the change in the design variables specified in the input step S11. The processing content of the sensitivity analysis step S4 is the content described with reference to FIGS. 11A to 12.

[0121] Then, in the output step S5, the display processing unit 50 displays (outputs) the detection probability and the result (sensitivity) of the sensitivity analysis on the display unit 62. The processing content of the output step S5 is the content that has been described with reference to FIG.

[0122] As shown in FIG. 3, the feature quantities that can be input in the input step S1 include the characteristics of the inspection probe P and design variables that are the targets of sensitivity analysis.

[0123] (Details of check step S2) 15 is a flowchart showing the detailed procedure of check step S2, with reference to FIGS. 3, 4 and 14 as appropriate.

[0124] First, in a determination rule specifying step S21, the determination rule specifying unit 21 specifies a determination rule to be applied based on the characteristics of the CAD model CM and the inspection probe P input in the input step S1. The processing content of the determination rule specifying step S21 is the content described with reference to FIG.

[0125] Next, in a shape recognition step S22, the shape recognition modules combined by the shape recognition unit 23 generate shape information (such as plate thickness and inspection probe installation range) related to the shape from the CAD model CM. The processing content of the shape recognition step S22 is the same as that described with reference to Fig. 4. That is, the shape recognition unit 23 generates shape information (such as plate thickness and inspection probe installation range) related to the shape from the CAD model CM.

[0126] Subsequently, in a determination step S23, the determination unit 25 determines whether or not the condition defined by the determination rule identified in the determination rule identification step S21 is satisfied based on the shape information calculated in the shape recognition step. The processing content of the determination step S23 is the content described with reference to Figures 5A to 6C.

[0127] Then, in a storing or displaying step S24, the determining unit 25 stores the determination result in the storage device 83, or the display processing unit 50 displays the determination result on the display unit 62.

[0128] (Details of detection probability processing step S3) 16 is a flowchart showing the details of the detection probability processing step S3, with reference to FIGS. 3, 7, and 14 as appropriate.

[0129] In the sampling step S31, the simulation execution unit 31 samples design variables according to the probability distribution of measurements in the inspection. At this time, random sampling is performed using the random number generation unit 34. The processing content of the sampling step S31 is the content described with reference to FIG.

[0130] Next, in a simulation execution step S32, the simulation execution unit 31 executes a simulation. Specifically, the simulation execution unit 31 calculates the received signal strength in the inspection by simulation based on the characteristics of the CAD model CM and the inspection probe P input in the input step S1 of Fig. 14. The processing contents of the simulation execution step S32 are the same as those described with reference to Figs. 8 to 9B.

[0131] Subsequently, in the detection probability processing step S33, the detection probability calculation unit 33 calculates the detection probability curve 510 based on the simulation results. At this time, as described above, the detection probability calculation unit 33 calculates the detection probability curve 510 using the Hit / Miss method or the a-hat vs. a method. The processing content of the detection probability processing step S33 is the content that has been described with reference to FIGS. 10 to 11B.

[0132] Then, in a result storage or display step S 34 , the detection probability calculation unit 33 stores the calculated detection probability in the storage device 83 , or the display processing unit 50 displays the calculated detection probability on the display unit 62 .

[0133] By performing such processing, the design support device 1 can provide design support that takes non-destructive testing into consideration at the design stage.

[0134] It should be noted that the present invention is not limited to the above-described embodiment, and includes various modifications. For example, the above-described examples have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those having all of the described configurations.

[0135] In addition, in this embodiment, the processing results of the design support device 1 are displayed on the display unit 62 (display device 85), but this is not limiting. For example, various outputs may be performed, such as output to a printer (not shown) or output to the Internet.

[0136] Furthermore, the assumed defect position D1 is set by manual input by the designer as shown in FIG. 3, but the design support device 1 may set the assumed defect position D1 based on the load or the like.

[0137] In this embodiment, it is assumed that the design support device 1 is realized by one PC, but this is not limited to this. For example, a cloud system configured by a terminal device (not shown) and a cloud server (not shown) may be used. When a cloud system is used, the terminal device includes the input unit 61, input processing unit 10, display processing unit 50, and display unit 62 shown in FIG. 1, and the cloud server includes the check unit 20 to the sensitivity analysis unit 40 shown in FIG. 1.

[0138] The design support device 1 according to this embodiment is applicable to design support for structures such as railways, automobiles, aircraft, and plants.

[0139] Furthermore, the above-described components, functions, input processing unit 10 to display processing unit 50, determination rule identification unit 21, shape recognition unit 23, determination unit 25, simulation execution unit 31, detection probability calculation unit 33, random number generation unit 34, CAD model storage unit 71, inspection probe storage unit 72, determination rule storage unit 22, shape recognition module storage unit 24, inspection probability distribution storage unit 32, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. Furthermore, the above-described components, functions, etc. may be implemented in software by a processor interpreting and executing a program that realizes each function. Information such as the programs, tables, and files that realize each function can be stored in memory 81, a storage device such as a hard disk or SSD (Solid State Drive), or a storage medium such as an IC card, SD card, or DVD.

[0140] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0141] 1 Design support equipment 10 Input processing section 20 Check Department 21. Judgment rule specification unit 22 Judgment rule memory unit 23 Shape recognition section 24 Shape recognition module memory section 25 Judgment section 30 Detection probability processing section 31 Simulation execution unit 32 Inspection probability distribution memory unit 33 Detection probability calculation unit 34 Random Number Generator 40 Sensitivity Analysis Section 50 Display processing section (output processing section) 61 Input section 62 Display section 71 CAD model storage section 72 Inspection probe memory unit 81 memory 110 CAD model display area (shape information is entered) 120 Inspection probe setting unit (characteristic information of inspection probe P is input) 130 Design variable setting section 221 Code (shape information) 222 Code (shape information) 510,511~514 Detection probability curve 600 Results display screen 610 CAD model display section 620 Detection probability display section (detection probability is displayed) 630 Sensitivity analysis display section (sensitivity is displayed) CM CAD model (design information) D1 Estimated defect location D2, D2a, D2b Expected defects P Inspection probe S1 Input step S3 Detection probability processing step S4 Sensitivity analysis step S5 Output Step

Claims

1. an input processing unit that receives input of design information related to an object to be subjected to non-destructive testing, and also receives input of information related to anticipated defects and design variables in the design information; a detection probability processing unit that calculates a detection probability curve of the assumed defect; a sensitivity analysis unit that calculates a sensitivity of the detection probability, which is a degree of change in the detection probability curve when the design variable is changed; an output processing unit that outputs the detection probability and the sensitivity; A design support device having:

2. the input processing unit receives characteristic information of an inspection probe that performs the non-destructive inspection; The detection probability processing unit a simulation execution unit that calculates a received signal in a test using the test probe by simulation based on the characteristic information of the test probe; a detection probability calculation unit that calculates the detection probability curve, which is a distribution curve of the probability of detecting the assumed defect, based on the result of the simulation; 2. The design support device according to claim 1, further comprising:

3. The simulation execution unit The values ​​of the design variables randomly sampled by the random number generator are used for the simulation.

3. The design support device according to claim 2.

4. The sensitivity analysis unit A change amount of the detection probability curve corresponding to a change in the design variable is calculated as a degree of change of the detection probability curve.

2. The design support device according to claim 1.

5. the input processing unit receives characteristic information of an inspection probe that performs the non-destructive inspection; a check unit that determines whether the inspection probe can be installed based on the characteristic information and the design information of the inspection probe; 2. The design support device according to claim 1, further comprising:

6. The checking unit a determination rule specifying unit that specifies a determination rule for determining whether or not the inspection probe can be installed based on the design information and the characteristic information of the inspection probe; a determination unit that determines whether or not a condition defined by the determination rule identified by the determination rule identification unit is satisfied based on the characteristic information of the inspection probe and shape information of the object based on the design information; 6. The design support device according to claim 5, further comprising:

7. a shape recognition unit that generates, from the design information, shape information other than the shape information registered in the design information; 7. The design support device according to claim 6, further comprising:

8. A design support device that supports the design of objects subject to non-destructive testing is provided. an input step of accepting input of design information related to an object to be subjected to non-destructive testing, and accepting input of information related to anticipated defects and design variables in the design information; a detection probability processing step of calculating a detection probability curve of the assumed defect; a sensitivity analysis step of calculating a sensitivity of the detection probability, which is a degree of change in the detection probability curve when the design variables are changed; an output step of outputting the detection probability and the sensitivity; A design support method for carrying out the above.

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