WO2019032356A1 - Systèmes et procédés de surveillance de composants - Google Patents

Systèmes et procédés de surveillance de composants Download PDF

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Publication number
WO2019032356A1
WO2019032356A1 PCT/US2018/044912 US2018044912W WO2019032356A1 WO 2019032356 A1 WO2019032356 A1 WO 2019032356A1 US 2018044912 W US2018044912 W US 2018044912W WO 2019032356 A1 WO2019032356 A1 WO 2019032356A1
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WO
WIPO (PCT)
Prior art keywords
analysis
image
imaging device
component
threshold
Prior art date
Application number
PCT/US2018/044912
Other languages
English (en)
Inventor
Basak Yuksel
Original Assignee
General Electric Company
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US15/670,124 external-priority patent/US20170358073A1/en
Application filed by General Electric Company filed Critical General Electric Company
Publication of WO2019032356A1 publication Critical patent/WO2019032356A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0016—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of aircraft wings or blades
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0041—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
    • G01M5/0091—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by using electromagnetic excitation or detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2260/00—Function
    • F05D2260/83—Testing, e.g. methods, components or tools therefor
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/80—Devices generating input signals, e.g. transducers, sensors, cameras or strain gauges
    • F05D2270/804—Optical devices
    • F05D2270/8041—Cameras
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/80—Devices generating input signals, e.g. transducers, sensors, cameras or strain gauges
    • F05D2270/808—Strain gauges; Load cells
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30136—Metal
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30164—Workpiece; Machine component
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection

Definitions

  • the present disclosure relates generally systems and method for monitoring components, and more particularly to systems and methods which facilitate improved imaging of surface features configured on the components.
  • apparatus components are subjected to numerous extreme conditions (e.g., high temperatures, high pressures, large stress loads, etc.). Over time, an apparatus's individual components may suffer creep and/or deformation that may reduce the component's usable life. Such concerns might apply, for instance, to some turbomachines.
  • a conventional gas turbine system includes a compressor section, a combustor section, and at least one turbine section.
  • the compressor section is configured to compress air as the air flows through the compressor section.
  • the air is then flowed from the compressor section to the combustor section, where it is mixed with fuel and combusted, generating a hot gas flow.
  • the hot gas flow is provided to the turbine section, which utilizes the hot gas flow by extracting energy from it to power the compressor, an electrical generator, and other various loads.
  • various components within the turbomachine and particularly within the turbine section of the turbomachine, such as turbine blades, may be subject to creep due to high temperatures and stresses.
  • creep may cause portions of or the entire blade to elongate so that the blade tips contact a stationary structure, for example a turbine casing, and potentially cause unwanted vibrations and/or reduced performance during operation.
  • components may be monitored for creep.
  • One approach to monitoring components for creep is to configure strain sensors on the components, and analyze the strain sensors at various intervals to monitor for deformations associated with creep strain.
  • One challenge in monitoring components and strain sensors thereon is obtaining images of the strain sensors that are of sufficient quality for subsequent deformation analyses to be accurate.
  • Factors such as the illumination of the strain sensors, the surface properties of the component and the strain sensors, the viewing parameters for an image capture device being utilized to obtain the images (and potential misconfigurations thereof), and the relative positions of the image capture device and strain sensors can lead to images that are of insufficient quality.
  • the images can be blurred and/or out of focus. This can lead to inaccuracies in post-processing analyses of the images, such as for deformation analysis.
  • the need for improved imaging is not limited to stain sensor applications. Such need exists in other component applications. For example, improved imaging of cooling holes defined in the exterior surface of a component and/or other surface features configured on the exterior surface of a component is desired.
  • a method for monitoring a component includes performing a first analysis of a first image of a surface feature configured on the exterior surface of the component, the first image obtained by an imaging device.
  • the method further includes adjusting a viewing parameter of the imaging device when a predetermined first analysis threshold for the first image is unsatisfied, and performing a subsequent first analysis of a second image of the surface feature, the second image obtained by the imaging device.
  • the method further includes adjusting a distance between the imaging device and the surface feature when the predetermined first analysis threshold for the second image is unsatisfied, and performing a second analysis of a third image, the third image obtained by the imaging device.
  • a system for monitoring a component has an exterior surface.
  • the system includes an imaging device for obtaining images of a surface feature configured on the exterior surface of the component, and a processor in operable communication with the imaging device.
  • the processor is configured for performing a first analysis of a first image of the surface feature, the first image obtained by the imaging device.
  • the processor is further configured for adjusting a viewing parameter of the imaging device when a predetermined first analysis threshold for the first image is unsatisfied, and performing a subsequent first analysis of a second image of the surface feature, the second image obtained by the imaging device.
  • the processor is further configured for adjusting a distance between the imaging device and the surface feature when the predetermined first analysis threshold for the second image is unsatisfied, and performing a second analysis of a third image, the third image obtained by the imaging device.
  • FIG. 1 is a perspective view of an exemplary component comprising a passive strain indicator in accordance with one or more embodiments of the present disclosure
  • FIG. 2 is a top view of an exemplary passive strain indicator in accordance with one or more embodiments of the present disclosure
  • FIG. 3 is a perspective view of a system for monitoring a component during locating of a surface feature in accordance with one or more embodiments of the present disclosure
  • FIG. 4 is an image of a surface feature in accordance with one or more embodiments of the present disclosure.
  • FIG. 5 is an image of an edge of a surface feature utilized during a binary analysis of the image in accordance with one or more embodiments of the present disclosure
  • FIG. 6 is an image of an edge of a surface feature utilized during a greyscale analysis of the image in accordance with one or more embodiments of the present disclosure.
  • FIG. 7 is a flow chart illustrating a method in accordance with one or more embodiments of the present disclosure.
  • a component 10 is illustrated with plurality of surface features 30, in this embodiment passive strain indicators 40, configured thereon.
  • the component 10 (and more specifically the substrate of the overall component 10) can comprise a variety of types of components used in a variety of different applications, such as, for example, components utilized in high temperature applications (e.g., components comprising nickel or cobalt based superalloys).
  • the component 10 may comprise an industrial gas turbine or steam turbine component such as a combustion component or hot gas path
  • the component 10 may comprise a turbine blade, compressor blade, vane, nozzle, shroud, rotor, transition piece or casing. In other embodiments, the component 10 may comprise any other component of a turbine such as any other component for a gas turbine, steam turbine or the like.
  • the component may comprise a non-turbine component including, but not limited to, automotive components (e.g., cars, trucks, etc.), aerospace components (e.g., airplanes, helicopters, space shuttles, aluminum parts, etc.), locomotive or rail components (e.g., trains, train tracks, etc.), structural, infrastructure or civil engineering components (e.g., bridges, buildings, construction equipment, etc.), and/or power plant or chemical processing components (e.g., pipes used in high temperature applications).
  • automotive components e.g., cars, trucks, etc.
  • aerospace components e.g., airplanes, helicopters, space shuttles, aluminum parts, etc.
  • locomotive or rail components e.g., trains, train tracks, etc.
  • structural, infrastructure or civil engineering components e.g., bridges, buildings, construction equipment, etc.
  • power plant or chemical processing components e.g., pipes used in high temperature applications.
  • the component 10 has an exterior surface 11 on or beneath which passive strain indicators 40 may be configured.
  • Passive strain indicators 40 in accordance with the present disclosure may be configured on the exterior surface 11 using any suitable techniques, including deposition techniques; other suitable additive manufacturing techniques; subtractive techniques such as laser ablation, engraving, machining, etc.; appearance-change techniques such as annealing, direct surface discoloration, or techniques to cause local changes in reflectivity; mounting of previously formed passive strain indicators 40 using suitable mounting apparatus or techniques such as adhering, welding, brazing, etc.; or identifying pre-existing characteristics of the exterior surface 11 that can function as the components of a passive strain indicator 40.
  • passive strain indicators 40 can be configured beneath exterior surface 11 using suitable embedding techniques during or after manufacturing of the component 10.
  • a passive strain indicator 40 generally comprises at least two reference points 41 and 42 that can be used to measure a distance D between said at least two reference points 41 and 42 at a plurality of time intervals. As should be appreciated to those skilled in the art, these measurements can help determine the amount of strain, strain rate, creep, fatigue, stress, etc. at that region of the component 10.
  • the at least two reference points 41 and 42 can be disposed at a variety of distances and in a variety of locations depending on the specific component 10 so long as the distance D there between can be measured.
  • the at least two reference points 41 and 42 may comprise dots, lines, circles, boxes or any other geometrical or non-geometrical shape so long as they are consistently identifiable and may be used to measure the distance D there between.
  • the passive strain indicator 40 may comprise a variety of different configurations and cross-sections such as by incorporating a variety of differently shaped, sized, and positioned reference points 41 and 42.
  • the passive strain indicator 40 may comprise a variety of different reference points comprising various shapes and sizes.
  • Such embodiments may provide for a greater variety of distance measurements D such as between the outer most reference points (as illustrated), between two internal or external reference points, or any combination there between.
  • the greater variety may further provide a more robust strain analysis on a particular portion of the component 10 by providing strain measurements across a greater variety of locations.
  • the values of various dimensions of the passive strain indicator 40 may depend on, for example, the component 10, the location of the passive strain indicator 40, the targeted precision of the measurement, application technique, and optical measurement technique.
  • the passive strain indicator 40 may comprise a length and width ranging from less than 1 millimeter to greater than 300 millimeters.
  • the passive strain indicator 40 may comprise any thickness that is suitable for application and subsequent optical identification without significantly impacting the performance of the underlying component 10. Notably, this thickness may be a positive thickness away from the surface 11 (such as when additive techniques are utilized) or a negative thickness into the surface 11 (such as when subtractive techniques are utilized).
  • the passive strain indicator 40 may comprise a thickness of less than from about 0.01 millimeters to greater than 1 millimeter. In some embodiments, the passive strain indicator 40 may have a substantially uniform thickness. Such embodiments may help facilitate more accurate measurements for subsequent strain calculations between the first and second reference points 41 and 42.
  • the passive strain indicator 40 may comprise a positively applied square or rectangle wherein the first and second reference points 41 and 42 comprise two opposing sides of said square or rectangle.
  • the passive strain indicator 40 may comprise at least two applied reference points 41 and 42 separated by a negative space 45 (i.e., an area in which the passive strain indicator material is not applied).
  • the negative space 45 may comprise, for example, an exposed portion of the exterior surface 11 of the component 10.
  • the negative space 45 may comprise a subsequently applied visually contrasting material that is distinct from the material of the at least two reference points 41 and 42 (or vice versa).
  • the passive strain indicator 40 may include a unique identifier 47 (hereinafter "UID").
  • the UID 47 may comprise any type of barcode, label, tag, serial number, pattern or other identifying system that facilitates the identification of that particular passive strain indicator 40.
  • the UID 47 may additionally or alternatively comprise information about the component 10 or the overall assembly that the passive strain indicator 40 is configured on. The UID 47 may thereby assist in the identification and tracking of particular passive strain indicators 40, components 10 or even overall assemblies to help correlate measurements for past, present and future operational tracking.
  • the passive strain indicator 40 may thereby be configured in one or more of a variety of locations of various components 10.
  • the passive strain indicator 40 may be configured on a blade, vane, nozzle, shroud, rotor, transition piece or casing.
  • the passive strain indicator 40 may be configured in one or more locations known to experience various forces during unit operation such as on or proximate airfoils, platforms, tips or any other suitable location.
  • the passive strain indicator 40 may be configured in one or more locations known to experience elevated temperatures.
  • the passive strain indicator 40 may be configured on a hot gas path or combustion component 10.
  • multiple passive strain indicators 40 may be configured on a single component 10 or on multiple components 10.
  • a plurality of passive strain indicators 40 may be configured on a single component 10 (e.g., a blade) at various locations such that the strain may be determined at a greater number of locations about the individual component 10.
  • a plurality of like components 10 may each have a passive strain indicator 40 configured in a standard location so that the amount of strain experienced by each specific component 10 may be compared to other like components 10.
  • multiple different components 10 of the same assembly e.g., blades and vanes for the same
  • turbomachine may each have a passive strain indicator 40 configured thereon so that the amount of strain experienced at different locations within the overall assembly (i.e. turbomachine, etc.) may be determined.
  • suitable surface features 30 include cooling holes defined in the exterior surface, coating layers applied to the exterior surface 11 (wherein the exterior surface 11 is defined as that of a base component of the component 10), etc.
  • a coordinate system is additionally illustrated in FIGS. 1 and 2.
  • the coordinate system includes an X-axis 50, a Y-axis 52, and a Z-axis 54, all of which are mutually orthogonal to each other. Additionally, a roll angle 60 (about the X-axis 50), a pitch angle 62 (about the Y-axis 52) and a yaw angle 64 (about the Z-axis 54) are illustrated.
  • System 100 may include, for example, one or more surface features 30 which are configurable on the exterior surface 11 of one or more components 10 as discussed above.
  • System 100 further includes an image capture device 102 and a processor 104.
  • the image capture device 102 generally obtains images of the surface feature(s) 30, and the processor 104 generally analyzes the images and performs other functions as discussed herein.
  • systems 100 in accordance with the present disclosure provide improved imaging by utilizing an iterative process that results in images of increased quality for post-processing.
  • resulting images that are utilized for post-processing may have sufficient sharpness for use in various types of post-processing.
  • the resulting images may be sufficient for use in deformation analysis, and may result in suitable accurate deformation analysis.
  • Imaging device 102 may include a lens assembly 110 and an image capture device 112, and may further include an illumination device, i.e. a light.
  • Lens assembly 110 may generally magnify images viewed by the lens assembly 110 for processing by the image capture device 112.
  • Lens assembly 110 in some
  • Image capture device 112 may generally be in communication with the lens assembly 110 for receiving and processing light from the lens assembly 110 to generate images.
  • image capture device 112 may be a camera sensor which receives and processes light from a camera lens to generate images, such as digital images, as is generally understood.
  • Imaging device 102 may further include a variety of settings, or viewing parameters, which may be applied and modified during operation thereof. The viewing parameters may affect the quality of the images obtained by the imaging device 102.
  • the viewing parameters may be setting that can be applied at various levels to the lens assembly 100 by the image capture device 112 or applied during processing of received light to obtain images by the image capture device 112.
  • Viewing parameters may include, for example, aperture size, shutter speed, ISO setting, brightness setting, contrast setting, illumination level, etc. Each viewing parameter may be adjusted as required (and as discussed herein) to adjust the quality of an obtained image.
  • Image capture device 112 (and device 102 generally) may further be in communication with processor 104, via for example a suitable wired or wireless connection, for storing and analyzing the images from the image capture device 112 and device 102 generally.
  • processor 104 operates imaging devices 102 to perform various disclosed steps.
  • system 100 may further include a processor 104.
  • processor refers not only to integrated circuits referred to in the art as being included in a computer, but also refers to a controller, a
  • Processor 104 may also include various input/output channels for receiving inputs from and sending control signals to various other components with which the processor 104 is in communication, such as the imaging device 102, a robotic arm (discussed herein), etc. Processor 104 may generally perform various steps as discussed herein. Further, it should be understood that a processor 104 in accordance with the present disclosure may be a single master processor 104 in communication with the other various components of system 100, and/or may include a plurality of individual component processors, i.e. an imaging device processor, a data acquisition device processor, a robotic arm processor, etc.
  • individual component processors i.e. an imaging device processor, a data acquisition device processor, a robotic arm processor, etc.
  • processor 104 may be in communication with each other and may further be in communication with a master processor, and these components may collectively be referred to as processor 104. Further, it should be noted that image capture device 112 may be a sub-component of processor 104, or may be a separate component from processor 104 which is in communication with processor 104.
  • system 100 may include a robotic arm 130.
  • the robotic arm 130 may support and facilitate movement of other components system 100, such as the imaging device 102 and/or the processor 104.
  • the imaging device 102 may be mounted to the robotic arm 130.
  • Processor 104 may be in communication with the robotic arm 130, such as with the various motors and/or drive components thereof, and may actuate the robotic arm 130 to move as required. Such movement may, in exemplary embodiments, position the imaging device 102 relative to the component 10 and surface feature(s) 30 thereon.
  • system 100 may include other suitable devices for supporting and facilitating movement of other components system 100, such as the imaging device 102 and/or the processor 104. Such devices may, for example, be in communication with processor 104.
  • system 100 may include a horoscope, mobile robot (such as a snake robot), gantry system, or other suitable device. Some such devices may facilitate performance of various steps as discussed herein when the component 10 is in situ in an associated assembly, such as a turbomachine (i.e. a gas turbine 10). Alternatively, component 10 may be removed from the assembly when such steps are performed.
  • a turbomachine i.e. a gas turbine 10
  • methods 200 for monitoring components 10 Similar to systems 100, methods 200 may be utilized to obtain quality images of the surface features 30, such as for postprocessing purposes.
  • processor 104 may be utilized to perform various of the method steps 200 discussed herein. Accordingly, systems 100 and methods 200 may be configured for operation as discussed herein.
  • Method 200 may include, for example, the step 210 of performing a first analysis of a first image 212' of a surface feature 30.
  • the first image 212' may be obtained by the imaging device 102, as discussed herein.
  • FIG. 4 illustrates one embodiment of an image 212 of a surface feature 30, which may for example be obtained via imaging device 102 as discussed herein.
  • Any suitable image analysis method which can evaluate the quality of the image 212' may be utilized when performing the first analysis.
  • a suitable pixel analysis which evaluates the sharpness of the image 212 based on comparisons of neighboring pixels of the image may be utilized.
  • the first analysis is a binary pixel analysis.
  • This analysis is generally an analysis which differentiates a reference object (for example, the surface feature 30 or a portion thereof, such as an edge) from a background (for example, the component and background, respectively) on the basis of differences in color depth (i.e. differences in color or in greyscale).
  • the analysis may be performed on each individual pixel 218 or groups of pixels 219 defining the image 212. For a binary analysis to occur, the number of bits-per-pixel of the image i.e. 128, 256, etc., is divided into two groups (generally a group which includes the lighter color depths and a group which includes the darker color depths). Each group is categorized as a reference object portion or a background portion.
  • the binary color depth analysis may categorize pixels or multi-pixel groups that are darker or lighter color depths as denoting a reference object (i.e. a surface feature or component thereof relative to a background), and may categorize pixels or multi-pixel groups that are the other of darker or lighter color depths as denoting a background .
  • such binary analysis is performed on a component of the surface feature 30, such as an edge 214 thereof.
  • a width 216 of the edge 214 may be measured during such analysis.
  • the number of pixels that are characterized in the group for the edge 214 may be counted (such as along the X-axis 50 as shown or other width-wise axis). In general, a greater number of pixels in such group indicates a lower quality image 212' .
  • the first analysis is a color scale or greyscale analysis on the bits-per-pixel of the image 212, i.e. 128, 256, etc.
  • the first analysis is a 256 bit-per-pixel greyscale analysis. This analysis differentiates a reference object from a background on the basis of differences in color depth. Such analysis may be performed on each individual pixel 218 of an image 212, or on sub-sections of individual pixels. For example, pixels 218 may be divided into 100 sub-sections, 1000 sub-sections, 10,000 sub-sections, or any other suitable number of subsections, and the analysis may be performed on each individual sub-section. As discussed, a color scale or greyscale analysis is performed on the bits-per-pixel of the image i.e. 128, 256, etc.
  • each pixel 218 or sub-section thereof is categorized as having a particular color depth per the 128, 256, etc. color depth scale.
  • such color scale or greyscale analysis is performed on a component of the surface feature 30, such as an edge 214 thereof.
  • a width 217 of the edge 214 may be measured during such analysis.
  • the number of pixels or sub-sections thereof that are included in a transition between a first color depth and a second, different color depth may be counted (such as along the X-axis 50 as shown or other width-wise axis). In general, a greater number of pixels in such transition indicates a lower quality image 212' .
  • Such analyses generally allow for the sharpness of the image 212 to be analyzed by, for example, analyzing the width in pixels 218 or sub-sections thereof of the surface feature 30 or various portions thereof. For example, it is generally desirable for the measured width 216, 217 to be low, thus indicating the relative sharpness of the image 212, and thus the quality of the image 212 for, for example, post-processing purposes.
  • Method 200 may further include, for example, the step 220 of adjusting one or more viewing parameters, as discussed herein, of the imaging device 102.
  • Step 220 may occur, for example, when a predetermined first analysis threshold for the first image 212' is unsatisfied, thus indicating that the quality of the image 212 is below a predetermined quality threshold.
  • the predetermined first analysis threshold may be a first width threshold for the surface feature 30 or a component thereof, such as edge 214, of which a width 216 was measured. The first analysis threshold in these embodiments may be satisfied when the width 216 is below the first width threshold, and unsatisfied when the width 216 is above the first width threshold.
  • the predetermined first analysis threshold may be a second width threshold for the surface feature 30 or a component thereof, such as edge 214, of which a width 217 was measured.
  • the first analysis threshold in these embodiments may be satisfied when the width 217 is below the second width threshold, and unsatisfied when the width 217 is above the second width threshold.
  • Adjustment of one or more viewing parameters may be performed when the predetermined first analysis threshold for the image 212 is unsatisfied, in an effort to obtain suitable levels for the viewing parameter(s) that result in images 212 of sufficient quality, as discussed herein.
  • steps 210 and 220 may be repeated as desired to evaluate the quality of images 212 obtained by the imaging device 102.
  • the predetermined first analysis threshold for an image 212 may be satisfied.
  • Post-processing may then, in some embodiments, occur using that image 212 and subsequent images with no further adjustment of the imaging device 102.
  • additional evaluation and adjustment may occur.
  • method 200 may further include, for example, the step 230 of performing a subsequent first analysis (as discussed herein) of a second image 212" of the surface feature 30.
  • the second image 212" image may, for example, be obtained by the imaging device 202 as discussed herein.
  • Method 200 may further include, for example, the step 240 of adjusting a distance 242 (for example along the Z-axis 54) (see, e.g., FIG. 3) between the imaging device 102 and the surface feature 30 when the predetermined first analysis threshold (as discussed herein) for the second image 212" is unsatisfied.
  • arm 130 or another suitable device of system 100 may move the imaging device 102 (such as the lens assembly 110) thereof relative to the surface feature 30 to adjust distance 242.
  • method 200 may include, for example, the step 250 of performing a second analysis of a third image 212" '.
  • the third image 212" ' may, for example, be obtained by the imaging device 102, and may be obtained after step 240 (and/or 220).
  • the first and second analyses may be different.
  • the first and second analyses may be the same.
  • the second analysis may be a binary pixel analysis, as discussed herein, while in alternative embodiments, the second analysis may be a color scale or grey scale analysis, as discussed herein.
  • Method 200 may further include, for example, the step 260 of adjusting a viewing parameter of the imaging device 102, as discussed herein.
  • Such step may occur, for example, when a predetermined second analysis threshold for the first image 212" ' is unsatisfied, thus indicating that the quality of the image 212 is below a predetermined quality threshold.
  • the predetermined second analysis threshold may be a first width threshold for the surface feature 30 or a component thereof, such as edge 214, of which a width 216 was measured.
  • the second analysis threshold in these embodiments may be satisfied when the width 216 is below the first width threshold, and unsatisfied when the width 216 is above the first width threshold.
  • the predetermined second analysis threshold may be a second width threshold for the surface feature 30 or a component thereof, such as edge 214, of which a width 217 was measured.
  • the second analysis threshold in these embodiments may be satisfied when the width 217 is below the second width threshold, and unsatisfied when the width 217 is above the second width threshold.
  • Adjustment of one or more viewing parameters may be performed when the predetermined second analysis threshold for the image 212 is unsatisfied, in an effort to obtain suitable levels for the viewing parameter(s) that result in images 212 of sufficient quality, as discussed herein.
  • the predetermined first analysis threshold and the predetermined second analysis threshold may be different.
  • the predetermined first analysis threshold and the predetermined second analysis threshold may be same.
  • Additional adjustments of the viewing parameters and/or the distance 242 may be performed as necessarily in accordance with the present disclosure, such as until one of both of the predetermined first and second analysis thresholds are satisfied.
  • the images 212 are deemed to be of sufficient quality for post-processing, as discussed herein.
  • various steps 210, 220, 230, 240, 250 and/or 260 as discussed herein may be performed automatically. Accordingly, no user input may be required (i.e. between steps) for such steps to be performed.
  • processor 104 may perform such steps automatically in order to obtain images 212 of sufficient quality for post processing.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Electromagnetism (AREA)
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Abstract

La présente invention concerne des systèmes et des procédés permettant de surveiller des composants. Un composant a une surface extérieure. Un procédé comprend la réalisation d'une première analyse d'une première image d'une caractéristique de surface configurée sur la surface extérieure du composant, la première image étant obtenue par un dispositif d'imagerie. Le procédé comprend en outre l'ajustement d'un paramètre de visualisation du dispositif d'imagerie lorsqu'un premier seuil d'analyse prédéterminé pour la première image n'est pas satisfait, et la réalisation d'une première analyse ultérieure d'une seconde image de la caractéristique de surface, la seconde image étant obtenue par le dispositif d'imagerie. Le procédé comprend en outre l'ajustement d'une distance entre le dispositif d'imagerie et la caractéristique de surface lorsque le premier seuil d'analyse prédéterminé pour la seconde image n'est pas satisfait, et la réalisation d'une seconde analyse d'une troisième image, la troisième image étant obtenue par le dispositif d'imagerie.
PCT/US2018/044912 2017-08-07 2018-08-02 Systèmes et procédés de surveillance de composants WO2019032356A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US15/670,124 US20170358073A1 (en) 2015-11-16 2017-08-07 Systems and Methods for Monitoring Components
US15/670,124 2017-08-07

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WO2019032356A1 true WO2019032356A1 (fr) 2019-02-14

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100175484A1 (en) * 2007-05-02 2010-07-15 Fathi Saigh Sensor device to monitor deformation in structural members, such as solid structures
US20150346058A1 (en) * 2014-05-30 2015-12-03 General Electric Company Methods for producing strain sensors on turbine components
WO2016113551A1 (fr) * 2015-01-13 2016-07-21 Bae Systems Plc Détection de dommages structuraux
US20170140515A1 (en) * 2015-11-16 2017-05-18 General Electric Company Systems and methods for monitoring components
US20170176174A1 (en) * 2015-12-17 2017-06-22 General Electric Company Methods for monitoring turbine components

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100175484A1 (en) * 2007-05-02 2010-07-15 Fathi Saigh Sensor device to monitor deformation in structural members, such as solid structures
US20150346058A1 (en) * 2014-05-30 2015-12-03 General Electric Company Methods for producing strain sensors on turbine components
WO2016113551A1 (fr) * 2015-01-13 2016-07-21 Bae Systems Plc Détection de dommages structuraux
US20170140515A1 (en) * 2015-11-16 2017-05-18 General Electric Company Systems and methods for monitoring components
US20170176174A1 (en) * 2015-12-17 2017-06-22 General Electric Company Methods for monitoring turbine components

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