WO2019245556A1 - Inspection de revêtement de surface par pulvérisation d'eau et modélisation numérique - Google Patents

Inspection de revêtement de surface par pulvérisation d'eau et modélisation numérique Download PDF

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Publication number
WO2019245556A1
WO2019245556A1 PCT/US2018/038691 US2018038691W WO2019245556A1 WO 2019245556 A1 WO2019245556 A1 WO 2019245556A1 US 2018038691 W US2018038691 W US 2018038691W WO 2019245556 A1 WO2019245556 A1 WO 2019245556A1
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WIPO (PCT)
Prior art keywords
surface coating
thermographic
computer
liquid agent
temperature data
Prior art date
Application number
PCT/US2018/038691
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English (en)
Inventor
Letchuman Sripragash
Valeri Golovlev
Matthias Goldammer
Martin KÖRDEL
Original Assignee
Siemens Aktiengesellschaft
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
Application filed by Siemens Aktiengesellschaft filed Critical Siemens Aktiengesellschaft
Priority to PCT/US2018/038691 priority Critical patent/WO2019245556A1/fr
Publication of WO2019245556A1 publication Critical patent/WO2019245556A1/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
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/02—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness
    • G01B21/08—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness for measuring thickness
    • G01B21/085—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness for measuring thickness using thermal means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
    • G01N15/088—Investigating volume, surface area, size or distribution of pores; Porosimetry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N25/00—Investigating or analyzing materials by the use of thermal means
    • G01N25/72—Investigating presence of flaws

Definitions

  • Flash thermographic nondestructive evaluation utilizes flash thermography to inspect the thickness and other material properties of a surface coating such as a thermal barrier coating. Flash thermography involves instantaneously heating the surface of an object to be inspected and monitoring the surface temperature using an infrared camera. More specifically, in flash thermography, a pulse of heat (“flash”) is applied to the surface of the object to be inspected in order to raise the temperature of the surface to a level sensitive enough to be captured by an infrared camera. The temperature evolution can then be used to quantitatively characterize the material involved.
  • flash pulse of heat
  • FIG. 1 is a schematic diagram illustrating flash thermographic nondestructive evaluation in accordance with one or more example embodiments.
  • FIG. 2 is a process flow diagram of an illustrative method for performing flash thermographic nondestructive evaluation using a liquid agent with a high wetting affinity for a surface coating to be evaluated in accordance with one or more example embodiments.
  • FIG. 3 is a process flow diagram of an illustrative method for applying a numerical model having a log-normal distribution for modeling a flash response to experimental flash thermographic data to determine one or more material properties of a surface coating and determining a correlation between the surface coating when dry and the surface coating when saturated with a liquid agent in accordance with one or more example embodiments.
  • FIG. 4 is a process flow diagram of an illustrative method for performing regression analysis as part of applying the numerical model to the experimental flash thermographic data in accordance with one or more example embodiments.
  • FIG. 5 is a schematic diagram of an illustrative computing device configured to implement one or more example embodiments.
  • Example embodiments include, among other things, methods and techniques for performing nondestructive flash thermographic evaluation of a surface coating with the aid of a liquid agent.
  • the liquid agent is applied to a surface coating to be evaluated.
  • the liquid agent has a high wetting affinity for the material of the surface coating and can be easily removed from the coating if, for example, additional layers of the coating need to be applied after the evaluation is performed.
  • example embodiments include, among other things, systems, methods, and computer-readable media for generating and applying a numerical model having a log-normal flash response distribution to experimental flash
  • thermographic data to determine one or more parameters/material properties of the surface coating.
  • Flash thermographic nondestructive evaluation can be used to inspect and evaluate a surface coating of an object such as a thermal barrier coating (TBC).
  • TBC thermal barrier coating
  • flash thermography can be used to determine TBC thickness and/or other material properties.
  • the quality of a TBC depends on a number of factors and process limitations can make it difficult to produce a TBC that is defect-free.
  • the TBC may be formed using a plasma spray method (a type of thermal spray method), in which case, factors/parameters that may have an influence include spray distance, spray angle, spray velocity, powder distribution, or the like.
  • an inspection technique such as flash thermographic evaluation is important to ensure TBC quality. It should be appreciated that while example embodiments may be described in connection with a TBC, such embodiments are applicable to any suitable surface coating formed of any suitable material.
  • Flash thermography involves the application of a pulse of heat to a surface of an object to be inspected in order to raise the surface temperature to a level that is detectable by a detection device such as an infrared camera.
  • the surface temperature may then be monitored over time to produce temperature evolution plots that can be used to quantitatively characterize the TBC material.
  • the temperature evolution can be used to determine a thickness of the TBC.
  • the temperature data can be used to identify embedded defects in the TBC. More particularly, when a defect is present in the TBC, the heat flow from the applied heat pulse will be obstructed through the portion containing the defect, and as a result, the surface temperature above the defect will be higher in relation to the surface temperature elsewhere.
  • the planar location of this surface temperature deviation may provide an indication of the planar location of the defect, and a time at which the deviation is observed (as determined from the temperature evolution plots) may indicate a depth of the defect.
  • Thermography is generally deemed to be a suitable method for such evaluation because it is non-contact, and thus nondestructive, and can be performed relatively rapidly.
  • the surface of the object to be inspected may be“black-painted.” Black painting may involve the application of a coating to an exposed surface of the TBC to minimize non-uniformity in the surface emissivity.
  • a TBC may be applied to a metal substrate that may serve as a heat sink. As such, when a heat pulse is applied to the TBC, the heat travels from a surface layer of the TBC, through potentially multiple layers of the TBC, and ultimately to the metal substrate.
  • the volume heating effect the quantitative characterization of the TBC can be negatively impacted.
  • non-uniform surface emissivity may occur as a result of surface irregularities which may also cause non-uniform IR emission.
  • the TBC may be black-painted.
  • black painting may also avoid problems that result from IR translucency of the TBC material.
  • the heat at the surface may include not only IR emission from the surface layer of the TBC, but IR emission from interior layers of the TBC as well which could alter the temperature measurements and make it difficult to monitor the surface temperature.
  • Application of the black paint to the TBC cuts off IR emission at the surface from the interior layers of the TBC - which would otherwise result from the IR translucency of the TBC - leaving only the IR emission from the surface layer of the TBC. As such, application of the black paint avoids the surface temperature monitoring problems associated with the translucency of the TBC.
  • Black painting suffers from at least one significant drawback.
  • one of the reasons for performing flash thermographic evaluation is to determine the thickness of the TBC, with the ultimate goal of coating a component with additional layers of the TBC if the thickness is deemed insufficient.
  • Black painting introduces unwanted debris to the TBC surface, thereby preventing additional TBC layers from being applied if needed. While the black paint may be removable, this is a time-intensive and costly process.
  • flash thermographic evaluation is performed without applying black paint, a clear indication of variation in thermal thickness (which is a function of thickness and thermal diffusivity) cannot be obtained.
  • Example embodiments address at least the aforementioned drawback associated with black painting by applying a liquid agent to the surface of the TBC in lieu of black paint.
  • the liquid agent may be selected from a group of liquids having a high wetting affinity for the TBC material.
  • the liquid agent may be a substance that has a wetting affinity for the TBC material that is above some threshold value.
  • the liquid agent may be a substance that demonstrates favorable spectroscopic properties for delivering a thermographic response.
  • the liquid agent may be water.
  • other liquid agents may be used.
  • mixtures of liquid agents may be used, where the mixtures may be optimized for desirable wetting and thermographic properties.
  • the liquid agent may be easily removed after the thermographic evaluation is performed, thereby permitting additional layers of the TBC coating to be applied, if necessary.
  • use of a liquid agent that has a high wetting affinity for the TBC material but that can be easily removed to permit deposition of additional TBC material layers retains the benefit of black painting of being able to distinguish thermal thickness differences by detecting a rate of change in the thermographic response over time, but eliminates the drawback of black painting of introducing debris to the TBC and preventing further TBC layer deposition.
  • the liquid agent may be opaque to IR waves, and thus, may also provide the benefit of black painting of minimizing/eliminating problems that may result from IR translucency of the TBC as well as problems that may result from non-uniformity in the surface emissivity of the TBC or the volume heating effect.
  • use of a liquid agent in lieu of black painting in accordance with example embodiments of the invention provides a technological benefit over conventional flash thermographic evaluation techniques.
  • use of a liquid agent as disclosed herein provides a technical benefit over the conventional use of black painting because it can be easily removed, thereby allowing additional TBC layers to be deposited.
  • example embodiments also relate to an improved data processing algorithm for processing the thermographic data.
  • a data processing algorithm for processing the thermographic data may, in accordance with example embodiments, take the form of a numerical model that utilizes a log-normal flash response distribution curve. More specifically, a log-normal distribution curve may be used to model the flash characteristics (e.g., the shape of the flash in a plot of emitted flash energy vs. time) and may eliminate early disturbances due purely to the flash. The log-normal distribution curve helps to control two parameters of the flash, specifically, the point at which maximum intensity occurs and the total duration or time constant of the flash.
  • the numerical model may utilize a regression method to fit the experimental temperature data to the model.
  • the parameters utilized in the numerical model that fit the experimental temperature data would be the unknown parameters and would be determined via application of the model.
  • the parameters may include various material properties of the TBC that influence the flash thermography response (assuming no volume heating or IR translucency) such as thickness, thermal conductivity, density, heat capacity, or the like. Any two of these parameters can be determined from non-linear regression analysis.
  • a numerical model in accordance with example embodiments utilizes a log-normal flash response distribution.
  • the rise time required to reach the maximum heat energy i.e., the time taken to reach from 10% to 90% of the maximum flash intensity
  • a time constant term is utilized in either an exponential decay function or a Larson and Koyama function.
  • the rise time or the flash initiation time must be established.
  • using a numerical model in accordance with example embodiments allows for the rise time and the time constant that together define the correct flash response to be determined by trial and error.
  • FIG. 1 is a schematic diagram illustrating flash thermographic nondestructive evaluation in accordance with one or more example embodiments.
  • FIG. 2 is a process flow diagram of an illustrative method 200 for performing flash thermographic nondestructive evaluation using a liquid agent with a high wetting affinity for a surface coating to be evaluated in accordance with one or more example embodiments.
  • FIG. 2 will be described in conjunction with FIG. 1 hereinafter.
  • FIG. 1 depicts an example object to be inspected using flash thermographic nondestructive evaluation.
  • the object may include a metal substrate 102 having a surface coating 104 applied thereon.
  • the surface coating 104 may be formed of any suitable material.
  • the surface coating 104 may be a thermal barrier coating.
  • the surface coating 104 may be applied in multiple layers such that the surface coating 104 includes an exposed surface layer and one or more interior layers.
  • a liquid agent 106 may be applied to the surface coating 104, or more specifically, to an exposed surface layer of the surface coating 104.
  • the liquid agent 106 may be selected from a group of liquids having a high wetting affinity for a material of the surface coating 104.
  • the liquid agent 106 may be a substance that demonstrates favorable spectroscopic properties for delivering a thermographic response.
  • the liquid agent 106 may be opaque to IR waves, and thus, similar to black painting, use of the liquid agent 106 may avoid the temperature data alterations that may occur as a result of IR translucency of the surface coating 104.
  • the liquid agent 106 may be water.
  • the liquid agent 106 may be used in lieu of black painting.
  • a pulse of heat 110 may be applied to the surface coating 104. More specifically, a heat source 108 may be provided for applying the heat pulse 110 to the surface coating 104 having the liquid agent 106 applied thereon. Application of the heat pulse 110 may cause the surface temperature to become elevated to a level that is detectable by a detection device.
  • the surface temperature can be monitored over time to obtain experimental temperature data 116.
  • a detection device such as an IR camera 112 can be used to measure IR emission 114 from the surface of the object being inspected over a period of time.
  • the temperature measurements captured by the IR camera 112 may be provided as input (in the form of the experimental temperature data 116) to a numerical model 118.
  • Application of the numerical model 118 to the experimental temperature data 116 will be described in more detail in reference to FIG. 3.
  • the liquid agent 106 can be easily removed after the thermographic evaluation is performed, thereby permitting additional layers of the surface coating 104 to be applied, if necessary.
  • use of a liquid agent 106 that has a high wetting affinity for the surface coating material but that can be easily removed to permit deposition of additional surface coating layers allows for thermal thickness differences to be distinguished based on the rate of change in the thermographic response over time, but eliminates the drawback associated with black painting of introducing debris to the surface coating 104 and preventing further surface coating layer deposition. Further, in certain example embodiments, evaporative cooling of the liquid agent 106 may occur.
  • FIG. 3 is a process flow diagram of an illustrative method 300 for applying a numerical model having a log-normal distribution to experimental flash thermographic data to determine one or more material properties of a surface coating as well as to determine a correlation between the surface coating when dry and the surface coating when saturated with a liquid agent in accordance with one or more example
  • FIG. 4 is a process flow diagram of an illustrative method 400 for performing regression analysis as part of applying the numerical model to the
  • FIGS. 3 and 4 will each be described in conjunction with FIG. 1 hereinafter.
  • each operation of the method 300 and/or the method 400 may be performed by one or more of the computer-implemented program modules or the like depicted in FIGS. 1 or 4, whose operation will be described in more detail hereinafter.
  • These program modules may be implemented in any combination of hardware, software, and/or firmware.
  • one or more of these program modules may be implemented, at least in part, as software and/or firmware modules that include computer-executable instructions that when executed by a processing circuit cause one or more operations to be performed.
  • a system or device described herein as being configured to implement example embodiments may include one or more processing circuits, each of which may include one or more processing units or nodes.
  • Computer-executable instructions may include computer-executable program code that when executed by a processing unit may cause input data contained in or referenced by the computer-executable program code to be accessed and processed to yield output data.
  • a numerical model 118 may be generated for evaluating the flash thermographic data (e.g., the experimental temperature data 116).
  • the numerical model 118 may have a log-normal flash response distribution.
  • the numerical model 118 may be applied to the experimental temperature data 116. More specifically, the experimental temperature data 116 may be fit to the numerical model 118 to determine one or more material properties 120 of the surface coating 104.
  • the material properties 120 may include thickness, thermal conductivity, density, heat capacity, and so forth. Spraying of the liquid agent 106 on the surface coating 104 prior to flash thermographic evaluation provides the capability to
  • a correlation between the surface coating 104 when dry and the surface coating 104 when saturated with the liquid agent 106 may be determined. Then, at block 308 of the method 300, the determined correlation between the dry surface coating 104 and the saturated surface coating 104 may be used to determine a porosity level of the surface coating 104.
  • the material of the surface coating 104 may be a porous material, and thus, may eventually become soaked or saturated with the liquid agent 106 as the liquid agent 106 is absorbed into the surface coating 104. Due to this liquid absorption by the surface coating 104, thermal thickness values that are obtained at block 304 may differ from the actual thermal thicknesses.
  • the determined correlation between the dry and saturated surface coatings 104 may be used to produce more accurate thermal thickness estimates as well.
  • laser flash analysis LFA
  • the correlation may be obtained by applying the liquid agent to only a portion of the surface coating 104 and obtaining experimental surface temperature data for the portion of the surface coating 104 having the liquid agent 106 applied thereon and the portion of the surface coating 104 that does not have the liquid agent 106 applied.
  • a grid of property data may be generated at block 402 of the method 400.
  • the grid of property data may be generated based at least in part on estimates of ranges of material properties of interest (e.g., thickness and thermal conductivity of the surface coating 104).
  • a respective set of one or more numerical thermographic profiles may be generated for each grid point in the grid of property data.
  • a region of a thermographic evolution curve (e.g., a second derivative curve) may be selected for application of the numerical model 118.
  • the region may be selected such that a midpoint of the selected region is a negative peak of the thermographic evolution curve.
  • the range may be defined in the logarithmic time scale.
  • the best-fit may correspond to values of the material properties of interest that yield the best- fit between the numerical model 118 and the experimental temperature data 116.
  • the generation and use of the numerical thermographic profiles as well as the selection of a region of a thermographic evolution curve for regression analysis in the manner described above enable faster automated analysis of the experimental temperature data 116.
  • example embodiments In addition to the technological improvement provided by water spraying in lieu of black painting, example embodiments also provide various technical features, technical effects, and/or improvements to computer technology. For instance, example embodiments provide the technical effect of generating and utilizing a numerical model having a log-normal flash response distribution that produces more accurate estimates of material properties of a component (e.g., a surface coating) being evaluated using flash thermographic nondestructive evaluation. This technical effect provides an improvement to computer technology - specifically an improvement to flash thermographic numerical computer-based models.
  • One or more illustrative embodiments of the disclosure are described herein. Such embodiments are merely illustrative of the scope of this disclosure and are not intended to be limiting in any way. Accordingly, variations, modifications, and equivalents of embodiments disclosed herein are also within the scope of this disclosure.
  • FIG. 4 is a schematic diagram of an illustrative computing device 502 configured to implement one or more example embodiments of the disclosure.
  • the computing device 502 may be any suitable device including, without limitation, a server, a personal computer (PC), a tablet, a smartphone, a wearable device, a voice-enabled device, or the like. While any particular component of the computing device 502 may be described herein in the singular, it should be appreciated that multiple instances of any such component may be provided, and functionality described in connection with a particular component may be distributed across multiple ones of such a component.
  • the computing device 502 may be configured to communicate with one or more other devices, systems, datastores, or the like via one or more networks.
  • network(s) may include, but are not limited to, any one or more different types of communications networks such as, for example, cable networks, public networks (e.g., the Internet), private networks (e.g., frame-relay networks), wireless networks, cellular networks, telephone networks (e.g., a public switched telephone network), or any other suitable private or public packet- switched or circuit-switched networks.
  • Such network(s) may have any suitable communication range associated therewith and may include, for example, global networks (e.g., the Internet), metropolitan area networks (MANs), wide area networks (WANs), local area networks (LANs), or personal area networks (PANs).
  • network(s) may include communication links and associated networking devices (e.g., link- layer switches, routers, etc.) for transmitting network traffic over any suitable type of medium including, but not limited to, coaxial cable, twisted-pair wire (e.g., twisted-pair copper wire), optical fiber, a hybrid fiber-coaxial (HFC) medium, a microwave medium, a radio frequency communication medium, a satellite communication medium, or any combination thereof.
  • coaxial cable twisted-pair wire (e.g., twisted-pair copper wire)
  • optical fiber e.g., twisted-pair copper wire
  • HFC hybrid fiber-coaxial
  • the computing device 502 may include one or more processors (processor(s)) 504, one or more memory devices 506 (generically referred to herein as memory 506), one or more input/output (“I/O”) interface(s) 508, one or more network interfaces 510, and data storage 514.
  • the computing device 502 may further include one or more buses 512 that functionally couple various components of the computing device 502.
  • the bus(es) 512 may include at least one of a system bus, a memory bus, an address bus, or a message bus, and may permit the exchange of information (e.g., data (including computer-executable code), signaling, etc.) between various components of the computing device 502.
  • the bus(es) 512 may include, without limitation, a memory bus or a memory controller, a peripheral bus, an accelerated graphics port, and so forth.
  • the bus(es) 512 may be associated with any suitable bus architecture including, without limitation, an Industry Standard Architecture (ISA), a Micro Channel Architecture (MCA), an Enhanced ISA (EISA), a Video Electronics Standards Association (VESA) architecture, an Accelerated Graphics Port (AGP) architecture, a Peripheral Component Interconnects (PCI) architecture, a PCI-Express architecture, a Personal Computer Memory Card International Association (PCMCIA) architecture, a Universal Serial Bus (USB) architecture, and so forth.
  • ISA Industry Standard Architecture
  • MCA Micro Channel Architecture
  • EISA Enhanced ISA
  • VESA Video Electronics Standards Association
  • AGP Accelerated Graphics Port
  • PCI Peripheral Component Interconnects
  • PCMCIA Personal Computer Memory Card International Association
  • USB Universal Serial Bus
  • the memory 506 may include volatile memory (memory that maintains its state when supplied with power) such as random access memory (RAM) and/or non volatile memory (memory that maintains its state even when not supplied with power) such as read-only memory (ROM), flash memory, ferroelectric RAM (FRAM), and so forth.
  • volatile memory memory that maintains its state when supplied with power
  • non volatile memory memory that maintains its state even when not supplied with power
  • ROM read-only memory
  • flash memory flash memory
  • FRAM ferroelectric RAM
  • Persistent data storage may include non-volatile memory.
  • volatile memory may enable faster read/write access than non-volatile memory.
  • certain types of non-volatile memory e.g., FRAM may enable faster read/write access than certain types of volatile memory.
  • the memory 506 may include multiple different types of memory such as various types of static random access memory (SRAM), various types of dynamic random access memory (DRAM), various types of unalterable ROM, and/or writeable variants of ROM such as electrically erasable programmable read-only memory (EEPROM), flash memory, and so forth.
  • the memory 506 may include main memory as well as various forms of cache memory such as instruction cache(s), data cache(s), translation lookaside buffer(s) (TLBs), and so forth.
  • cache memory such as a data cache may be a multi-level cache organized as a hierarchy of one or more cache levels (Ll, L2, etc.).
  • the data storage 514 may include removable storage and/or non-removable storage including, but not limited to, magnetic storage, optical disk storage, and/or tape storage.
  • the data storage 514 may provide non-volatile storage of computer-executable instructions and other data.
  • the memory 506 and the data storage 514, removable and/or non-removable, are examples of computer-readable storage media (CRSM) as that term is used herein.
  • CRSM computer-readable storage media
  • the data storage 514 may store computer-executable code, instructions, or the like that may be loadable into the memory 506 and executable by the processor(s) 504 to cause the processor(s) 504 to perform or initiate various operations.
  • the data storage 514 may additionally store data that may be copied to memory 506 for use by the processor(s) 504 during the execution of the computer-executable instructions.
  • output data generated as a result of execution of the computer-executable instructions by the processor(s) 504 may be stored initially in memory 506 and may ultimately be copied to data storage 514 for non-volatile storage.
  • the data storage 514 may store one or more operating systems (O/S) 516; one or more database management systems (DBMS) 518 configured to access the memory 506 and/or one or more external datastores 428 (which may include the data repository 116); and one or more program modules, applications, engines, managers, computer-executable code, scripts, or the like such as, for example, a numerical model 520 having a log-normal flash response distribution.
  • O/S operating systems
  • DBMS database management systems
  • program modules, applications, engines, managers, computer-executable code, scripts, or the like such as, for example, a numerical model 520 having a log-normal flash response distribution.
  • Any of the components depicted as being stored in data storage 514 may include any combination of software, firmware, and/or hardware.
  • the software and/or firmware may include computer-executable instructions (e.g., computer-executable program code) that may be loaded into the memory 506 for execution by one or more of the processor(s) 504 to perform any of the operations described earlier in connection with correspondingly named modules.
  • computer-executable instructions e.g., computer-executable program code
  • the data storage 514 may further store various types of data utilized by components of the computing device 502 (e.g., data stored in the datastore(s) 522). Any data stored in the data storage 514 may be loaded into the memory 506 for use by the processor(s) 504 in executing computer-executable instructions. In addition, any data stored in the data storage 514 may potentially be stored in the external datastore(s) 522 and may be accessed via the DBMS 518 and loaded in the memory 506 for use by the processor(s) 504 in executing computer-executable instructions.
  • the processor(s) 504 may be configured to access the memory 506 and execute computer-executable instructions loaded therein.
  • the processor(s) 504 may be configured to execute computer-executable instructions of the various program modules, applications, engines, managers, or the like of the computing device 502 to cause or facilitate various operations to be performed in accordance with one or more embodiments of the disclosure.
  • the processor(s) 504 may include any suitable processing unit capable of accepting data as input, processing the input data in accordance with stored computer-executable instructions, and generating output data.
  • the processor(s) 504 may include any type of suitable processing unit including, but not limited to, a central processing unit, a microprocessor, a Reduced Instruction Set Computer (RISC) microprocessor, a Complex Instruction Set Computer (CISC) microprocessor, a microcontroller, an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), a System-on-a-Chip (SoC), a digital signal processor (DSP), and so forth. Further, the processor(s) 504 may have any suitable microarchitecture design that includes any number of constituent components such as, for example, registers, multiplexers, arithmetic logic units, cache controllers for controlling read/write operations to cache memory, branch predictors, or the like.
  • RISC Reduced Instruction Set Computer
  • CISC Complex Instruction Set Computer
  • DSP digital signal processor
  • microarchitecture design of the processor(s) 504 may be capable of supporting any of a variety of instruction sets.
  • the O/S 516 may be loaded from the data storage 514 into the memory 506 and may provide an interface between other application software executing on the computing device 502 and hardware resources of the computing device 502. More specifically, the O/S 516 may include a set of computer-executable instructions for managing hardware resources of the computing device 502 and for providing common services to other application programs. In certain example embodiments, the O/S 516 may include or otherwise control the execution of one or more of the program modules, engines, managers, or the like depicted as being stored in the data storage 514.
  • the O/S 516 may include any operating system now known or which may be developed in the future including, but not limited to, any server operating system, any mainframe operating system, or any other proprietary or non-proprietary operating system.
  • the DBMS 518 may be loaded into the memory 506 and may support functionality for accessing, retrieving, storing, and/or manipulating data stored in the memory 506, data stored in the data storage 514, and/or data stored in external datastore(s) 522.
  • the DBMS 518 may use any of a variety of database models (e.g., relational model, object model, etc.) and may support any of a variety of query languages.
  • the DBMS 518 may access data represented in one or more data schemas and stored in any suitable data repository.
  • Data stored in the datastore(s) 522 may include, for example, experimental surface temperature data, model parameter data, and so forth.
  • External datastore(s) 522 that may be accessible by the computing device 502 via the DBMS 518 may include, but are not limited to, databases (e.g., relational, object-oriented, etc.), file systems, flat files, distributed datastores in which data is stored on more than one node of a computer network, peer-to-peer network datastores, or the like.
  • databases e.g., relational, object-oriented, etc.
  • file systems e.g., flat files, distributed datastores in which data is stored on more than one node of a computer network, peer-to-peer network datastores, or the like.
  • the input/output (I/O) interface(s) 508 may facilitate the receipt of input information by the computing device 502 from one or more I/O devices as well as the output of information from the computing device 502 to the one or more I/O devices.
  • the I/O devices may include any of a variety of components such as a display or display screen having a touch surface or touchscreen; an audio output device for producing sound, such as a speaker; an audio capture device, such as a microphone; an image and/or video capture device, such as a camera; a haptic unit; and so forth. Any of these components may be integrated into the computing device 502 or may be separate.
  • the I/O devices may further include, for example, any number of peripheral devices such as data storage devices, printing devices, and so forth.
  • the I/O interface(s) 508 may also include an interface for an external peripheral device connection such as universal serial bus (USB), FireWire, Thunderbolt, Ethernet port or other connection protocol that may connect to one or more networks.
  • USB universal serial bus
  • FireWire FireWire
  • Thunderbolt Thunderbolt
  • Ethernet port or other connection protocol that may connect to one or more networks.
  • the I/O interface(s) 508 may also include a connection to one or more antennas to connect to one or more networks via a wireless local area network (WLAN) (such as Wi Fi) radio, Bluetooth, and/or a wireless network radio, such as a radio capable of communication with a wireless communication network such as a Long Term Evolution (LTE) network, WiMAX network, 3G network, etc.
  • WLAN wireless local area network
  • LTE Long Term Evolution
  • the computing device 502 may further include one or more network interfaces 510 via which the computing device 502 may communicate with any of a variety of other systems, platforms, networks, devices, and so forth.
  • the network interface(s) 510 may enable communication, for example, with one or more other devices via one or more of the network(s).
  • the program modules/engines e.g., the numerical model 520 depicted in FIG. 4 as being stored in the data storage 514 are merely illustrative and not exhaustive and that processing described as being supported by any particular module may alternatively be distributed across multiple modules, engines, or the like, or performed by a different module, engine, or the like.
  • various program module(s), script(s), plug-in(s), Application Programming Interface(s) (API(s)), or any other suitable computer-executable code hosted locally on the computing device 502 and/or other computing devices accessible via one or more networks may be provided to support functionality provided by the modules depicted in FIG. 4 and/or additional or alternate functionality.
  • functionality may be modularized in any suitable manner such that processing described as being performed by a particular module may be performed by a collection of any number of program modules, or functionality described as being supported by any particular module may be supported, at least in part, by another module.
  • program modules that support the functionality described herein may be executable across any number of cluster members in accordance with any suitable computing model such as, for example, a client-server model, a peer-to-peer model, and so forth.
  • any of the functionality described as being supported by any of the modules depicted in FIG. 4 may be implemented, at least partially, in hardware and/or firmware across any number of devices.
  • the computing device 502 may include alternate and/or additional hardware, software, or firmware components beyond those described or depicted without departing from the scope of the disclosure. More particularly, it should be appreciated that software, firmware, or hardware components depicted as forming part of the computing device 502 are merely illustrative and that some components may not be present or additional components may be provided in various embodiments. While various illustrative modules have been depicted and described as software modules stored in data storage 514, it should be appreciated that functionality described as being supported by the modules may be enabled by any combination of hardware, software, and/or firmware. It should further be appreciated that each of the above-mentioned modules may, in various embodiments, represent a logical partitioning of supported functionality.
  • One or more operations of the method 300 and/or the method 400 may be performed by a computing device 502 having the illustrative configuration depicted in FIG. 4, or more specifically, by one or more program modules, engines, applications, or the like executable on such a device. It should be appreciated, however, that such operations may be implemented in connection with numerous other device
  • FIGS. 2-4 The operations described and depicted in the illustrative methods of FIGS. 2-4 may be carried out or performed in any suitable order as desired in various example embodiments of the disclosure. Additionally, in certain example embodiments, at least a portion of the operations may be carried out in parallel. Furthermore, in certain example embodiments, less, more, or different operations than those depicted in FIGS. 2-4 may be performed.
  • the present disclosure may be a system, a method, and/or a computer program product.
  • the computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.
  • the computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device.
  • the computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing.
  • a non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing.
  • RAM random access memory
  • ROM read-only memory
  • EPROM or Flash memory erasable programmable read-only memory
  • SRAM static random access memory
  • CD-ROM compact disc read-only memory
  • DVD digital versatile disk
  • memory stick a floppy disk
  • a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon
  • a computer readable storage medium is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
  • Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network.
  • the network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.
  • a network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
  • Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.
  • the computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
  • electronic circuitry including, for example, programmable logic circuitry, field- programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
  • These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a
  • the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
  • the computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • the flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure.
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s).
  • the functions noted in the block may occur out of the order noted in the figures.
  • two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

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Abstract

L'invention concerne des procédés et des techniques pour effectuer une évaluation thermographique flash non destructrice d'un revêtement de surface à l'aide d'un agent liquide. L'agent liquide est appliqué sur un revêtement de surface à évaluer. L'agent liquide présente une affinité de mouillage élevée pour le matériau du revêtement de surface et peut être facilement retiré du revêtement si, par exemple, des couches supplémentaires du revêtement doivent être appliquées après la réalisation de l'évaluation. L'invention concerne également des systèmes, des procédés et des supports lisibles par ordinateur pour générer et appliquer un modèle numérique possédant une répartition de réponse flash log-normale à des données thermographiques flash expérimentales afin de déterminer un ou plusieurs paramètres/une ou plusieurs propriétés matérielles du revêtement de surface.
PCT/US2018/038691 2018-06-21 2018-06-21 Inspection de revêtement de surface par pulvérisation d'eau et modélisation numérique WO2019245556A1 (fr)

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CN113536560A (zh) * 2021-07-07 2021-10-22 广东科学技术职业学院 薄膜涂层结构的层间应力检测方法、计算机装置及计算机可读存储介质
CN114719805A (zh) * 2022-02-18 2022-07-08 中国航发北京航空材料研究院 一种测量叶片热障涂层厚度的方法及装置

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EP1797416A1 (fr) * 2004-10-04 2007-06-20 Siemens Aktiengesellschaft Procede pour determiner des parametres materiels d'un objet a partir de donnees temperature-contre-temps
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CN113536560A (zh) * 2021-07-07 2021-10-22 广东科学技术职业学院 薄膜涂层结构的层间应力检测方法、计算机装置及计算机可读存储介质
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