Source: https://patents.google.com/patent/US20100235112A1/en
Timestamp: 2019-06-18 14:56:34
Document Index: 95603831

Matched Legal Cases: ['art 350', 'art 420', 'art 500', 'art 900', 'art 920', 'art 930']

US20100235112A1 - Managing non-destructive evaluation data - Google Patents
Managing non-destructive evaluation data Download PDF
US20100235112A1
US20100235112A1 US12/617,315 US61731509A US2010235112A1 US 20100235112 A1 US20100235112 A1 US 20100235112A1 US 61731509 A US61731509 A US 61731509A US 2010235112 A1 US2010235112 A1 US 2010235112A1
US12/617,315
US8521480B2 (en
Joseph M. Kesler
Uriah M. Liggett
II Richard A. Roth
Thomas D. Sharp
2009-03-12 Priority to US12/403,274 priority Critical patent/US8108168B2/en
2009-11-12 Application filed by Sheet Dynamics Ltd filed Critical Sheet Dynamics Ltd
2009-11-12 Priority to US12/617,315 priority patent/US8521480B2/en
2009-11-12 Assigned to SHEET DYNAMICS LTD. reassignment SHEET DYNAMICS LTD. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KESLER, JOSEPH M., LIGGETT, URIAH M., ROTH, RICHARD A., II, SHARP, THOMAS D.
2010-09-16 Publication of US20100235112A1 publication Critical patent/US20100235112A1/en
2010-10-18 Assigned to ETEGENT TECHNOLOGIES, LTD. reassignment ETEGENT TECHNOLOGIES, LTD. CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: SHEET DYNAMICS, LTD.
2013-06-25 Priority claimed from US13/926,517 external-priority patent/US9804997B2/en
2013-08-27 Publication of US8521480B2 publication Critical patent/US8521480B2/en
Embodiments of the invention include methods to manage non-destructive evaluation (“NDE”) data. The method includes receiving NDE data for at least a portion of an asset along with inspection information associated with the at least a portion of the asset, and determining at least one alignment algorithm to align the NDE data to a simulated model of the at least a portion of the asset based on at least one of the NDE data or the inspection information. The method further includes automatically aligning The NDE data to the simulated model with the at least one alignment algorithm and analyzing the aligned NDE data on the simulated model to determine coverage of the simulated model by the NDE data. Additional methods include retrieving NDE data that has previously been aligned to the simulated model and determining coverage or determining trends associated with indications thereof.
This application is a continuation-in-part of U.S. application Ser. No. 12/403,274 to Joseph M. Kesler et al., entitled “MANAGING NON-DESTRUCTIVE EVALUATION DATA,” filed Mar. 12, 2009 (SDL/08). This application is also related to U.S. application Ser. No. 12/557,136 to Joseph M. Kesler et al., entitled “MANAGING NON-DESTRUCTIVE EVALUATION DATA,” filed Sep. 10, 2009 (SDL/08A), which is a continuation of the aforementioned '274 application. The disclosures of both of these applications are hereby incorporated by reference herein.
Embodiments of the invention provide for a method, apparatus, and program product to manage non-destructive evaluation (“NDE”) data associated with at least a portion of an asset. In some embodiments, a method of managing NDE data comprises receiving NDE data for at least a portion of an asset, including receiving inspection information associated with the at least a portion of the asset. The method further comprises determining at least one alignment algorithm to align the NDE data to a simulated model of the at least a portion of the asset based upon at least one of the NDE data and the inspection information and automatically aligning the NDE data to the simulated model with the at least one alignment algorithm. The method further comprises analyzing the aligned NDE data on the simulated model to determine coverage of the simulated model by the NDE data.
In additional embodiments, a method of managing NDE data comprises retrieving NDE data for at least a portion of an asset, the NDE data having previously been aligned to a simulated model of the at least a portion of the asset, and determining coverage of the simulated model by the NDE data.
In still further additional embodiments, a method of managing NDE data comprises retrieving first NDE data for at least a portion of an asset, the first NDE data having previously been aligned to a simulated model of the at least a portion of the asset, and retrieving second NDE data for the at least a portion of the asset, the second NDE data having previously been aligned to the simulated model. The method further comprises determining an indication of a potential problem associated with at least one of the first NDE data and the second NDE data, including determining a trend associated with the indication in turn associated with a difference between the first NDE data and the second NDE data.
FIG. 46 is a display representation of the distorted NDE data of FIG. 44 after at least a portion thereof has been adjusted consistent with embodiments of the invention;
FIG. 47 is a display representation of the adjusted NDE data of FIG. 46 aligned with and on the simulated model of FIG. 27;
FIG. 48 is a flowchart illustrating a sequence of operations that may be executed by the application of FIG. 3 to analyze aligned NDE data on a simulated model for coverage;
FIG. 49 is a flowchart illustrating a sequence of operations that may be executed by the application of FIG. 3 to detect user interaction with at least a portion of the display representation of a simulated model and display information related thereto; and
FIG. 50 is a flowchart illustrating a sequence of operations that may be executed by the application of FIG. 3 to determine a trend associated with coverage of a simulated model.
In addition to second computer 44, the computing system may include at least one storage server 48 and at least one NDE data collection device 50 which may in turn be in communication with the network 46. The storage server 48 may be configured with the at least one data structure 38 consistent with embodiments of the invention. In some embodiments, and as illustrated in FIG. 2, the at least one data structure 38 is a database. The storage server 48 may be accessed by the first computer 42 in response to a request from second computer 44. The storage server 48 may be in communication with the first computer 42 through the network 46 or through a direct communication link as at 52. In some embodiments, the at least one storage server 48 is configured to store NDE data and inspection information associated therewith in the at least one data structure 38. The at least one storage server 48 may be configured as a picture archiving and communication system (“PACS”) and store the NDE data as a digital image in the digital imaging and communication in non-destructive evaluation (“DICONDE”) standard as is well known in the art.
Although several components of the application 36 are illustrated in FIG. 3, one having ordinary skill in the art will appreciate that the application 36 may include more or fewer components without departing from the scope of the invention. For example, the application 36 may include an HTML generator (not shown), a shot descriptor parser to access and search through shot descriptor data structures (not shown), and/or another component as may be apparent to one having ordinary skill in the art. Moreover, one having ordinary skill in the art will appreciate that the application 36 may include fewer components and one or more of the individual components 61-66 may be separate applications without departing from the scope of the invention.
In general, the routines executed to implement the embodiments of the invention, whether implemented as part of an operating system or a specific application, component, algorithm, program, object, module or sequence of instructions, or even a subset thereof, will be referred to herein as “computer program code” or simply “program code.” Program code typically comprises one or more instructions or sequence of operations that are resident at various times in memory and storage devices in a computer, and that, when read and executed by at least one processor in a computer, cause that computer to perform the steps necessary to execute steps or elements embodying the various aspects of the invention. Moreover, while the invention has and hereinafter will be described in the context of fully functioning computers and computer systems, those skilled in the art will appreciate that the various embodiments of the invention are capable of being distributed as a program product in a variety of forms, and that the invention applies regardless of the particular type of computer readable media used to actually carry out the invention. Examples of computer readable media include, but are not limited to, recordable type media such as volatile and non-volatile memory devices, floppy and other removable disks, hard disk drives, tape drives, optical disks (e.g., CD-ROM's, DVD's, HD-DVD's, Blu-Ray Discs), among others, and transmission type media such as digital and analog communications links.
Moreover, various program code described hereinafter may be referred to as being able to align NDE data. However, it should be appreciated that the program code is configured to align not only NDE data to a simulated model, but is also configured to align indications of potential problems to a simulated model, align first NDE data to second NDE data, align additional information to a simulated model and/or align other data. It will be appreciated that an alignment algorithm may align NDE data to a model in a number of manners, including transforming (e.g., rotating, scaling, translating, registering, etc.) NDE data into the coordinate system for a model, transforming a model into the coordinate system for NDE data, or transforming both NDE data and a model to a common coordinate system. The embodiments hereinafter primarily focus on aligning NDE data to a model through transforming the NDE data into the coordinate system of a model; however, the invention is not limited as such.
FIG. 17 is a flowchart 350 illustrating a sequence of operations to assign a location descriptor to at least a portion of an asset and translate location information associated with NDE data (e.g., location information specifying the location of an indication, asset, portion of an asset, sub-portion of an asset, etc.) consistent with embodiments of the invention. Initially, a plurality of locations associated with a simulated model, and in turn associated with at least a portion of an asset, are identified (block 352). For example, one location may identify that the simulated model is associated with the left wing of an asset, a second location may identify a portion of the simulated model that is associated with a slat of the left wing, a third location may identify a portion of the simulated model that is associated with a spoiler of the left wing, a fourth location may identify that a portion of the simulated model is associated with a bolt of the left wing, the slat or the spoiler, etc. A plurality of location descriptors may then be assigned to at least some of the respective identified locations (block 354). For example, a location descriptor may describe the left wing as “WING2,” the slat as “SLAT1,” the spoiler as “SPOILT,” and the bolt as “BOLT289.”
In response to retrieving NDE data and/or inspection information associated therewith (block 356), location information associated with the NDE data and/or the inspection information may be determined (358). In particular, the determined location information may include location information specifying the at least a portion of the asset associated with the NDE data and/or the inspection information. Additionally and/or alternatively, the determined location information may include location information specifying the location of an indication of a potential problem in turn associated with the NDE data and/or the inspection information. In response to determining the location information, a first location among the plurality of locations associated with the location information may be determined (block 360) and a respective first location descriptor among the plurality of location descriptors associated with the first location may be assigned to the determined location information (block 362). Thus, a location associated with the NDE data and/or the location of an indication may be automatically determined and assigned to that NDE data.
FIG. 20 is a flowchart 420 illustrating a sequence of operations to display indications from a plurality of datasets of NDE data associated with a similar portion of a plurality of assets consistent with embodiments of the invention. For example, user input specifying a type of asset is received (block 422) and user input specifying at least a portion of that type of asset is also received (block 424). In response to the specification of at least a portion of the type of asset, a plurality of datasets of NDE data and/or respective inspection information associated with the at least a portion of the type of asset may be retrieved (block 426) and indications associated with the plurality of datasets of NDE data and/or respective inspection information may be automatically aligned to a simulated model associated with the at least a portion of the type of asset (block 428). As such, a display representation of the indications associated with the plurality of datasets of NDE data and/or the respective inspection information on the simulated model is generated (block 430).
FIG. 24 is a flowchart 500 illustrating a sequence of operations to display a plurality of indications of portions of at least one asset that are substantially structurally similar, but that may be located at different locations on the at least one asset or that are oriented in different manners respective to each other. For example, the sequence of operations 500 may be used to display a first and second indication associated with a respective first and second wing (e.g., of the same or different assets) on a simulated model of the first wing by transforming the location of the second indication on the second wing into a location on the first wing. Thus, first NDE data is automatically aligned to a first simulated model associated with the first NDE data (block 502) and a first indication associated with the first NDE data is automatically aligned to a first location on the first simulated model (block 504). Similarly, second NDE data is automatically aligned to a second simulated model associated with the second NDE data (block 506) and a second indication associated with the second NDE data is automatically aligned to a second location on the second simulated model (block 508). The second location of the second indication on the second simulated model is then transformed to a corresponding third location on the first simulated model (block 510). For example, when the first NDE data is NDE data from a right wing of an asset and the second NDE data is NDE data from a left wing of the asset, the transformation between the simulated models associated with the respective first and second NDE data may include a minor reflection transformation between the simulated models associated with the respective first and second NDE data. Also for example, the transformation may include transforming a location across at least one axis of transformation between the simulated model associated with the respective first and second NDE data. A display representation of the first indication at the first location on the first simulated model, as well as the second indication at the third location on the first simulated model, is then generated (block 512). In this manner, indications of portions of at least one asset that are substantially structurally similar but otherwise oriented in different manner respective to each other may be viewed on a single simulated model. Thus, a user may view trends for at least two different portions of at least one asset on one simulated model.
FIG. 48 is a flowchart 900 illustrating a sequence of operations to analyze at least one dataset of NDE data with respect to coverage. For example, first and/or second NDE data may be automatically aligned to a simulated model associated therewith as previously described (block 902). In various embodiments, the first NDE data may be associated with the second NDE data in that both are NDE data associated with the same portion of an asset, that the first NDE data is adjacent to the second NDE data, that the first NDE data and the second NDE data are associated with the same asset, and/or that the first NDE data and the second NDE data are associated with the same inspection. In particular, the first and/or second NDE data may be aligned with one alignment algorithm or with respective first and second alignment algorithms consistent with embodiments of the invention. Once aligned, the first and/or second NDE data, as well as the simulated model, may be analyzed to determine coverage of the first and/or second NDE data in relation a simulated model (e.g., coverage of NDE data on the simulated model, which may be expressed in a statistical measure), coverage of the first and/or second NDE data in relation to a portion of the simulated model (e.g., actual coverage of NDE data on a portion of the simulated model, and in particular a specifically defined portion of the simulated model, which may be expressed in a statistical measure), and/or coverage of the first and/or second NDE data in relation to each other and/or the expected coverage thereof (e.g., whether the first and second NDE data overlap and/or have a gap therebetween and whether the first and second NDE data are supposed to be configured as such). As such, it will be appreciated that one or more of the analysis blocks 904-908 may be executed, and that an analysis of the coverage of the first and/or second NDE data may not require all such blocks.
In some embodiments, the coverage of NDE data on a simulated model may be determined by projecting a plurality of lines from the simulated model to the aligned NDE data and/or from the aligned NDE data to the simulated model. In specific embodiments, the plurality of lines are projected along the axis of alignment of the NDE data to the simulated model. When the projection intersects both the NDE data and the simulated model, then it is determined that the NDE data “covers” the simulated model at the point. As such, the aligned first and/or second NDE data may be analyzed with respect to coverage of the simulated model (block 904). In some embodiments, the analysis in block 904 may include determining information about at least one area of the simulated model covered by the first and/or second NDE data. Alternatively, the analysis in block 904 may include determining information about at least one area of the simulated model that is not covered by the first and/or second NDE data. For example, if the first NDE data covers about 20% of the simulated model, information about coverage of the simulated model may include data indicating that the percentage of coverage of the first NDE data is about 20%, and the information about coverage of the simulated model may include data indicating that the percentage of area of the simulated model that is not covered by the first NDE data is about 80%. It will be appreciated that, in some embodiments, the coverage of the simulated model may be determined with respect to more than one dataset of NDE data. In particular, the coverage may be determined with respect to a plurality of datasets of NDE data. For example, the coverage of a plurality of datasets of NDE data, including the first and/or second NDE data, may indicate that the plurality of datasets of NDE data cover about 98% of the simulated model. Alternatively, the coverage of the plurality of datasets of NDE data may indicate that the percentage of area of the simulated model that is not covered by the plurality of datasets of NDE data is about 2%. Additionally, the coverage of the plurality of datasets of NDE data may be compared to at least one previous coverage of another plurality of datasets and the variability of coverage over time may be indicated in a statistical measure, and more specifically a chart or graph of a plurality of statistical measures.
The analysis of the first and/or second NDE data with respect to coverage of the simulated model may be performed in one or more of a plurality of ways. For example, a point-by-point hit test of a point on the simulated model and a corresponding point on aligned NDE data may be analyzed to determine coverage. The simulated model is analyzed at the point and the first and/or second NDE data is analyzed at a corresponding point to determine if there is matching data. The points may include a pixel or a plurality of pixels. In some embodiments, the coverage at a point may be determined by projecting a plurality of lines from the simulated model to the aligned NDE data and/or from the aligned NDE data to the simulated model at respective points. In specific embodiments, the plurality of lines are projected along the axis of alignment of the NDE data to the simulated model at their respective points. When a projection intersects both aligned NDE data and the simulated model, then it is determined that the NDE data “covers” the simulated model at the point. If there is not matching data (such as when there is simulated model data but not NDE data at the point), there is no coverage at both points. Alternatively, a vertex-by-vertex hit test, a feature-by-feature hit test, and/or a features-by-features hit test may operate similarly to the point-by-point hit test, with the exception of focusing on a respective vertex of the simulated model, respective feature of the simulated model and/or respective plurality of features of the simulated model, the first NDE data and/or the second NDE data.
Furthermore, the analysis of the first and/or second NDE data with respect to coverage of the simulated model may be performed with a floodfill algorithm. In some embodiments, a floodfill algorithm is configured to define and fill a boundary of the simulated model. It may then be determined whether the area defined by the boundary is associated with the first and/or second NDE data. In some embodiments, the floodfill algorithm may be configured to fill in any areas of the simulated model that are not associated with the first and/or second NDE data, while in alternative embodiments the floodfill algorithm may be configured to fill in any areas of the simulated model that are associated with the first and/or second NDE data. From the floodfilled areas, the coverage of the simulated model, and/or the first and/or second NDE data, may be determined. Information about coverage of the simulated model, and/or the first and/or second NDE data, may be provided in a report and/or on a display representation of the simulated model.
In some embodiments, the aligned first and/or second NDE data may be analyzed with respect to coverage of a portion of the simulated model and/or expected coverage thereof (block 906). For example, the portion of the simulated model may be a portion associated with the first and/or second NDE data, such as an expected portion that the first and/or second NDE data are supposed to cover. Specifically, the particular portion of the simulated model may be defined by a region which, in turn, may be defined by a boundary (e.g., a parallelogram, a circle, an abstract boundary that follows the contours of a portion of NDE data or a simulated model, etc.). Data associated with the first and/or second NDE data may then be compared to the edge of a boundary and/or the area within to determine coverage. Specifically, a region of the simulated model may be established and it may be determined whether an area of the region is associated with at least a portion of the first and/or second NDE data. Similarly, a boundary of the region of the simulated model may be established and it may be determined whether the boundary of the region is associated with a corresponding boundary in the first and/or second NDE data, and/or whether data associated with the boundary of the region is associated with corresponding data associated with a corresponding boundary of a region in the first and/or second NDE data. In specific embodiments, it may be known that a particular dataset of NDE data should encompass a rectangular area defined by four lines. A line by line comparison may then be performed against the plurality of lines defining the boundary of the dataset of NDE data and the boundary of the dataset of NDE data to determine the coverage thereof. Alternatively, an area comparison may be performed against the area defined by the plurality of lines and the area of the dataset of NDE data to determine the coverage thereof. Alternatively, any of the methods described above (e.g., portion-by-portion, vertex-based, feature-based, floodfill algorithm) may be used to analyze the aligned first and/or second NDE data with respect to coverage of the portion of the simulated model and/or the expected coverage thereof. Information about coverage of the portion of the simulated model may be provided in a report and/or on a display representation of the simulated model. In some embodiments, areas of the simulated model that are filled by the floodfill algorithm and also associated with the first and/or second NDE data may be removed from a display representation of the aligned first and/or second NDE data, leaving only those portions of the simulated model that were not covered by the first and/or second NDE data. This allows a user to quickly view those portions of the simulated model that are not covered.
In some embodiments, the aligned first and/or second NDE data may be analyzed with respect to coverage of a portion of the simulated model in relation to each other (block 908). For example, the first NDE data may be associated with a portion of an asset and the second NDE data may be associated with the same portion. As such, the coverage of the first and second NDE data on the same simulated model may be analyzed to determine if there is missed coverage. Specifically, it may be desirable that the areas covered by the first and second NDE data match so as to indicate consistency in scans at the same or different times. When the areas don't match, those portions that are associated with first NDE data but not the second NDE data may be reported and/or indicated. Additionally, when the areas don't match, those portion that are associated with second NDE data but not the first NDE data may be reported and/or indicated. In specific embodiments, areas of the simulated model that are associated with first NDE data but not the second NDE data and/or areas of the simulated model that are associated with the second NDE data but not the first NDE data may be provided on a display representation of the simulated model.
Also for example, the first NDE data may be associated with a portion of an asset and the second NDE data may be associated with an adjacent portion. As such, coverage of the first and second NDE data on the same simulated model may be analyzed to determine if there is overlapping coverage. Specifically, it may be desirable that there is at least some area of overlap between the first and second NDE data so as to ensure coverage of an asset. When there is overlap, those portions that are associated with first NDE data and the NDE data may be reported and/or indicated. When there is no overlap but there is overlap expected (e.g., such as specified through a shot descriptor file or other data associating the first and second NDE data), those portions that should have been overlapped may be reported and/or indicated. In specific embodiments, areas of the simulated model that are associated with overlap of the first and second NDE data and/or areas of the simulated model that are not associated with overlap of the first and second NDE data but were expected to be associated with overlap may be indicated on a display representation of the simulated model.
In some embodiments, the statistical measure may indicate the degree of overlap of the a plurality of datasets of NDE data as well as the variability of overlap over time. For example, the degree of overlap may indicate the average degree of overlap between adjacent datasets of NDE data. More specifically, the statistical measure may indicate that the average degree of overlap between datasets of NDE data is about two to four inches. Alternatively, the statistical measure may indicate that the degree of overlap between datasets of NDE data is never less than two inches. As such, a process to obtain that NDE data may be adjusted to provide a greater or lesser degree of overlap, depending on the required degree of overlap. Moreover, a statistical measure, and more specifically a chart or graph of a plurality of statistical measures, may indicate the variability of overlap over time. When the variability of overlap over time is low, that may indicate that the method(s) used to obtain datasets of NDE data are sufficiently efficient and stable. When the variability of overlap over time is high, this may indicate that the method(s) used to obtain datasets of NDE data need improvement in reliability.
In some embodiments, and in an optional step, the analysis of any of blocks 904-908 may be used to determine if a coverage has satisfied a predetermined condition relating thereto (e.g., whether the coverage is “OK”) (block 910). In specific embodiments, the predetermined condition may be that a particular statistical measure of coverage has been achieved or that a particular statistical measure of coverage has not been achieved. Alternatively, the predetermined condition may be that the first and/or second NDE data did not provide proper coverage in relation to a specific region, boundary, perimeter and/or plurality of lines that define the region, boundary and/or perimeter (e.g., the first and/or second NDE data did not cover the region, boundary, perimeter and/or plurality of lines that define the region, boundary and/or perimeter, either partially or fully), that a specific feature was not properly covered (e.g., the specific feature was not covered either partially or fully), that specific plurality of features were not properly covered (e.g., the specific plurality of features were not covered either partially or fully), and/or that the first and second NDE data did not provide proper overlap. Thus, when the coverage has not satisfied the predetermined condition (“No” branch of decision block 910) the coverage deficiency may be provided in a report and/or on a display representation of the simulated model as discussed above (block 912). However, when the coverage has satisfied the predetermined condition (“Yes” branch of decision block 910) information about the coverage may be provided in a report and/or on a display representation of the simulated model as discussed above (block 914).
In some embodiments, the report may be provided as a database entry, a comma-separated value file, a printed report, a spreadsheet, an electronic document, or combinations thereof. Additionally, the report may be provided as a window generated by the program code that includes report information (e.g., the report information may be provided in a software-generated window). The report may indicate information about the coverage of simulated model with the first and/or second NDE data. Moreover, the report may indicate data about the first and/or second NDE data (e.g., including information from inspection data related thereto), the simulated model and/or the coverage of a portion of the simulated model with the first and/or second NDE data. Additionally, the report may include a display representation of the simulated model with a graphical representation of coverage thereupon.
In regard to providing the display representation of the simulated model to indicate coverage, the display representation may include a simulated model, one or more datasets of NDE data, and may be modified to change the color, pattern and/or another aspect of a background to highlight areas of missing coverage on the simulated model. Similarly, the display representation may be modified to change the color, pattern and/or another aspect of the background behind only the simulated model to highlight areas of missing coverage on the simulated model. For example, the simulated model is may be represented through a plurality of lines and the NDE data may be aligned and represented as discussed above. By adjusting a color of a background of a display representation to red, those areas of the simulated model that are not covered by NDE data are more easily visible. Alternatively, the display representation may be modified by changing the color, pattern and/or another aspect of the simulated model itself. For example, the plurality of lines may have their color modified to be red such that those lines that are not covered by NDE data are more easily visible. Even further alternatively, the display representation may be modified by changing the color, pattern and/or another aspect of aligned NDE data. For example, the aligned NDE data may be filled in, or otherwise replaced, with black boxes that occlude portions of the simulated model such that those areas of the simulated model that are not covered by NDE data are more easily visible.
Additionally, and still with regard to providing the display representation of the simulated model to indicate coverage, the display representation may be modified by highlighting those sections of the simulated model that are not covered by NDE data. Moreover, the display representation may be modified by removing portions of the simulated model that are not associated with NDE data, or alternatively removing portions of the simulated model that are associated with NDE data. Furthermore, and still with regard to providing the display representation of the simulated model to indicate coverage, those datasets of NDE data that are not providing proper coverage may be displayed on the simulated model and those vertexes and/or features that were not properly covered may be highlighted (as discussed above) and/or displayed on the simulated model. In the above examples, the color, pattern and/or other aspect of the background and/or simulated model may again be changed to more easily illustrate missed coverage.
FIG. 49 is a flowchart 920 illustrating a sequence of operations to detect user interaction with a portion of a simulated model and provide information related thereto. For example, user interaction with at least a portion of a simulated model aligned with at least one dataset of NDE data may be detected (block 922). In particular, the user interaction may be a selection and/or activation of the portion of the simulated model with a mouse. In response to the detection of user interaction, it may be determined whether the portion is associated with NDE data (block 924). When the portion is associated with NDE data (e.g., such as when a user selects a portion of the simulated model that is in turn associated with aligned NDE data) (“Yes” branch of decision block 924) information associated with the aligned NDE data in turn associated with the portion is displayed (block 926). The information may include information associated with the inspection information of the NDE data. However, when the portion is not associated with NDE data (e.g., such as when a user selects a portion of the simulated model that is not associated with aligned NDE data) (“No” branch of decision block 924) a dataset of NDE data that should be associated with the selected portion, as well as information associated therewith, may be determined (block 928). For example, if the selected portion is in a region that should be associated with one or more adjacent datasets of NDE data, an indication of the identity of the one or more adjacent datasets of NDE data will be determined, along with information associated therewith. Also for example, if the selected portion is in a region that was not associated with NDE data but a shot descriptor file for at least one other dataset of NDE data indicates that it should have been (e.g., the shot descriptor file for at least one other dataset of NDE data indicates that the “missing” NDE data is part of a sequence with that at least one dataset of NDE data), information about the missing NDE data (e.g., the sequence with which it is associated, the date it should have been taken, the inspector who should have taken it, etc.) may be determined. In some embodiments, the determined at least one dataset of NDE data that should have been associated with the selected portion, as well as the information associated therewith, may be provided to the user in a report and/or a display representation. In particular embodiments, that information is displayed through a pop-up information module. Alternatively, that information may be displayed in a selected indication information component that is configured to display information about selected indications.
FIG. 50 is a flowchart 930 illustrating a sequence of operations to determine trend information associated with coverage of a plurality of datasets of NDE data. For example, determined plurality of NDE datasets may be automatically aligned to a simulated model associated therewith as discussed above (block 932). As such, the aligned plurality of NDE datasets may be analyzed with respect to coverage of the simulated model as discussed above (block 934). Thus, at least one trend in the coverage of the simulated model in relation to at least one previous alignment with at least one separate plurality of NDE datasets may be determined (block 936). In particular, the determination in block 936 may occur when there has been at least two alignments of at least two pluralities of NDE datasets, each of the pluralities of NDE datasets associated with respective inspections. As such, at least one trend associated with lack of coverage between the at least two alignments may indicate an area that has repeatedly lacked coverage over a plurality of inspections. This information may be subsequently provided to inspectors to relieve the deficiencies. To detail the at least one trend in coverage, a display representation illustrating the at least one trend in coverage may be generated on the simulated model (block 938). For example, when the trend in coverage indicates that an area is consistently associated with NDE data over the at least two inspections, a corresponding area on the simulated model associated therewith may be colored a first color, such as green. However, when the trend in coverage indicates that an area is inconsistently associated with NDE data over at least two inspections, a corresponding area on the simulated model associated therewith may be colored a second color, such as yellow or red. It will be appreciated that trends in coverage may be illustrated in various shades of colors on the simulated model, and the three colors discussed above are not intended to be limiting.
Although FIG. 48 refers to first and/or second NDE data, one having ordinary skill in the art will appreciate that one dataset of NDE data or a plurality of datasets of NDE data may be analyzed to determine the coverage thereof. Similarly, although FIG. 50 refers to determining at least one trend in coverage in relation to previous alignments with separate pluralities of NDE datasets, one having ordinary skill in the art will appreciate that the at least one trend may be determined in relation to the currently aligned plurality of NDE datasets. Similarly, although FIG. 50 refers to pluralities of NDE datasets, one having ordinary skill in the art will appreciate that an inspection may include only one dataset of NDE data, and thus the determination of at least one trend in coverage of the simulated model may be performed in relation to at least one previous alignment with a separate NDE dataset.
After capturing the NDE data 740, it may be advantageous to align the NDE data 740 (e.g., first NDE data 740) with additional NDE data (e.g., second NDE data) and/or a simulated model associated with the fan blade 720. Specifically, it may be desirable to associate the first NDE data 740 with the second NDE data and determine the location of the indication 742 on both. To associate the datasets of NDE data, a plurality of projections of the first NDE data 740 through the second NDE data may be generated. By way of example, FIG. 42 is a diagrammatic illustration 750 of a projection of the first NDE data 740 through second NDE data of the fan blade 752 (e.g., an x-ray of the fan blade 720 face-on) and a three-dimensional simulated model of the fan blade 754 while FIG. 43A and FIG. 43B are respective projections 760 and 765 of the first NDE data 740 through the second NDE data 752 illustrating various manners in which the first NDE data 740 may be projected through the second NDE data 752 and/or simulated model 754. A projection of the first NDE data 740 that results in an acceptable alignment on the second NDE data 752 and/or simulated model 754 may be chosen. In this manner, the location of the indication 742 on the second NDE data 752 and/or the simulated model 754 may be determined. It will be appreciated that FIGS. 39-42 and FIGS. 43A and 43B are merely exemplary to illustrate the process to align first NDE data to second NDE data and/or a simulated model associated with both the first and second NDE data. Thus, it will be appreciated that FIGS. 39-42 and FIGS. 43A and 43B may or may not be displayed consistent with embodiments of the invention, and as such the FIGS. 39-42 and FIGS. 43A and 43B are merely illustrated of the applicants' broader inventive concept.
receiving NDE data for at least a portion of an asset, including receiving inspection information associated with the at least a portion of the asset;
determining at least one alignment algorithm to align the NDE data to a simulated model of the at least a portion of the asset based upon at least one of the NDE data and the inspection information;
automatically aligning the NDE data to the simulated model with the at least one alignment algorithm; and
analyzing the aligned NDE data on the simulated model to determine coverage of the simulated model by the NDE data.
determining an area of at least a portion of the simulated model that is covered with the aligned NDE data.
indicating a statistical measure of coverage of the simulated model with the aligned NDE data based at least in part upon the area that is covered.
indicating a statistical measure of coverage of the at least a portion of the simulated model with the aligned NDE data based at least in part upon the area that is covered.
determining an area of at least a portion of the simulated model that is not covered with the aligned NDE data.
indicating a statistical measure of the lack of coverage of the simulated model with the aligned NDE data based at least in part upon the area that is not covered.
indicating a statistical measure of the lack of coverage of the at least a portion of the simulated model with the aligned NDE data based at least in part upon the area that is not covered.
determining whether the coverage of the simulated model satisfies a predetermined condition related to the coverage thereof.
in response to user interaction with at least a second portion of the simulated model that is not associated with aligned NDE data, selectively determining at least one dataset of NDE data that should have been associated with that second portion.
in response to user interaction with at least a second portion of the simulated model that is not associated with aligned NDE data, selectively determining information about at least one dataset of NDE data that should have been associated with that second portion.
11. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
determining the location of a vertex of the simulated model; and
determining whether a portion of the NDE data is aligned with the vertex of the simulated model.
12. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
determining whether a portion of the simulated model is associated with a corresponding portion of the NDE data.
13. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
utilizing a floodfill algorithm to determine a boundary of at least a portion of the simulated model; and
determining whether an area of the simulated model defined by the boundary is associated with at least a portion of the NDE data.
14. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
detecting a feature associated with the simulated model; and
determining whether the feature is associated with a corresponding feature of the NDE data.
15. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
determining a plurality of features associated with the simulated model; and
determining whether the NDE data is associated with a corresponding number of plurality of features.
16. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
establishing a region of the simulated model to determine coverage thereof, the region defined by a boundary; and
determining whether an area within the boundary of the region is associated with at least a portion of the NDE data.
17. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
establishing a boundary of a region of the simulated model to determine the coverage thereof; and
determining whether the boundary of the region is associated with a corresponding boundary in the NDE data.
18. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
establishing a boundary of a region on the simulated model; and
determining whether data associated with the boundary of the region is associated with corresponding data associated with a corresponding boundary of a region in the NDE data.
19. The method of claim 1, wherein analyzing the aligned NDE data on the simulated model to determine the coverage of the simulated model by the NDE data includes:
determining a statistical measure of the coverage of the simulated model by the NDE data.
20. The method of claim 1, wherein automatically aligning the NDE data to the simulated model includes:
transforming a coordinate system of the NDE data to a coordinate system for the simulated model.
21. A method of managing non-destructive evaluation (NDE) data in a system of the type that includes at least one processing unit and a memory, the method comprising:
retrieving NDE data for at least a portion of an asset, the NDE data having previously been aligned to a simulated model of the at least a portion of the asset; and
determining coverage of the simulated model by the NDE data.
22. A method of managing non-destructive evaluation (NDE) data in a system of the type that includes at least one processing unit and a memory, the method comprising:
retrieving first NDE data for at least a portion of an asset, the first NDE data having previously been aligned to a simulated model of the at least a portion of the asset;
retrieving second NDE data for the at least a portion of the asset, the second NDE data having previously been aligned to the simulated model; and
determining an indication of a potential problem associated with at least one of the first NDE data and the second NDE data, including determining a trend associated with the indication in turn associated with a difference between the first NDE data and the second NDE data.
US12/617,315 2009-03-12 2009-11-12 Managing non-destructive evaluation data Active 2031-02-24 US8521480B2 (en)
US12/403,274 US8108168B2 (en) 2009-03-12 2009-03-12 Managing non-destructive evaluation data
US12/617,315 US8521480B2 (en) 2009-03-12 2009-11-12 Managing non-destructive evaluation data
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US13/926,517 US9804997B2 (en) 2009-03-12 2013-06-25 Managing non-destructive evaluation data
US15/799,583 US20180067897A1 (en) 2009-03-12 2017-10-31 Managing non-destructive evaluation data
US12/403,274 Continuation-In-Part US8108168B2 (en) 2009-03-12 2009-03-12 Managing non-destructive evaluation data
US12/403,274 Continuation US8108168B2 (en) 2009-03-12 2009-03-12 Managing non-destructive evaluation data
US13/926,517 Continuation US9804997B2 (en) 2009-03-12 2013-06-25 Managing non-destructive evaluation data
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US12/617,315 Active 2031-02-24 US8521480B2 (en) 2009-03-12 2009-11-12 Managing non-destructive evaluation data
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Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KESLER, JOSEPH M.;LIGGETT, URIAH M.;ROTH, RICHARD A., II;AND OTHERS;REEL/FRAME:023509/0284