Radiation inspection systems for pipes and other structures and estimation of material loss

Abstract

Some embodiments include a radiological inspection system comprising: a drive mechanism configured to move along the structure; a detector attached to the drive mechanism; a radiation source attached to the drive mechanism and positionable relative to the detector such that a width of the structure casts a radiation shadow on an active area of ​​the detector; and control logic coupled to the detector and configured to receive images from the detector, generate sidewall loss information based on the images, and generate bottom wall loss information based on the images. Some embodiments include a method, including acquiring an image of the structure, filtering the image of the structure to generate a filtered image, normalizing the image based on the filtered image to generate the normalized image, and scaling the normalized image based on a transfer function associated with the structure.

Description

Technical Field

[0001] A radiation inspection system can generate an image of an object such as a pipe. For example, the pipe may be surrounded by insulation material. Under the insulation material, the pipe may corrode. The radiation inspection system may be attached to the pipe to generate a plurality of images along the pipe. However, in a single section of the pipe, a plurality of images may be required to inspect the 360-degree appearance of the pipe. Further, the obtained images may only provide a qualitative indication of material loss.

Brief Description of the Drawings

[0002] [Figure 1A] It is a block diagram of a radiation inspection system and a heat-insulated pipe according to some embodiments. [Figure 1B] It is an orthographic projection view of a radiation inspection system and a heat-insulated pipe according to some embodiments. [Figure 2] It is a block diagram of the configuration of a radiation source of a radiation inspection system for a heat-insulated pipe according to some embodiments. [Figure 3] It is a block diagram of an image of a heat-insulated pipe of a radiation inspection system according to some embodiments. [Figure 4A] It is a block diagram illustrating the rotation of a radiation inspection system around a heat-insulated pipe according to some embodiments. [Figure 4B] It is a block diagram illustrating the rotation of a radiation inspection system around a heat-insulated pipe according to some embodiments. [Figure 5] It is a block diagram of a part of a modular radiation inspection system according to some embodiments. [Figure 6] It is a block diagram of a radiation inspection system of a positioning system according to some embodiments. [Figure 7A] It is a block diagram of a part of a radiation inspection system for a pipe support according to some embodiments. [Figure 7B]This is a partial block diagram of a radiation inspection system for pipe supports according to several embodiments. [Figure 8A] This is a block diagram of a radiation inspection system according to several embodiments. [Figure 8B] This is a block diagram of a radiation inspection system according to several embodiments. [Figure 8C] This is a block diagram of a radiation inspection system according to several embodiments. [Figure 8D] This is a block diagram of a radiation inspection system according to several embodiments. [Figure 9A] This flowchart shows a technique for using a radiographic inspection system according to some embodiments. [Figure 9B] This flowchart shows a technique for using a radiographic inspection system according to some embodiments. [Figure 10] This flowchart shows a technique for estimating material loss using a radiation inspection system according to several embodiments. [Figure 11A] This block diagram shows techniques for estimating material loss in several embodiments. [Figure 11B] This block diagram shows techniques for estimating material loss in several embodiments. [Figure 12A] This block diagram shows images obtained from techniques for estimating material loss in several embodiments. [Figure 12B] This block diagram shows images obtained from techniques for estimating material loss in several embodiments. [Figure 12C] This block diagram shows images obtained from techniques for estimating material loss in several embodiments. [Figure 12D] This block diagram shows images obtained from techniques for estimating material loss in several embodiments. [Figure 13] This is a block diagram of a radiation inspection system for radiation sources at different locations, according to several embodiments. [Figure 14]This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 15] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 16] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 17] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 18] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 19] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 20] This flowchart shows techniques for estimating material loss according to several embodiments. [Figure 21A] This block diagram shows a radiation inspection system, an insulated pipe with various defects, and corresponding images according to several embodiments. [Figure 21B] This block diagram shows a radiation inspection system, an insulated pipe with various defects, and corresponding images according to several embodiments. [Figure 21C] This block diagram shows a radiation inspection system, an insulated pipe with various defects, and corresponding images according to several embodiments. [Figure 21D] This block diagram shows a radiation inspection system, an insulated pipe with various defects, and corresponding images according to several embodiments. [Modes for carrying out the invention]

[0003] Some embodiments relate to radiographic inspection systems, and more specifically to radiographic inspection systems for pipes and other structures and for material loss estimation (MLE).

[0004] The pipeline may be equipped with insulation as protection against environmental conditions such as moisture. For example, when moisture reaches the pipe, it may cause corrosion. Such pipelines can span several miles or more. Crevice corrosion under insulation (CUI) is the corrosion of pipes and vessels that can occur under insulation as a result of water penetration, condensation, or other conditions. Measuring corrosion, especially the amount of corrosion, can be difficult. Some inspection tools require the removal of insulation as part of the inspection process.

[0005] CUI can be inspected using radiographic testing (RT). Radiography may be a suitable non-destructive testing (NDT) modality for determining CUI. Such tests may involve manual setting of recording media such as a radiation source and film for imaging the area of the pipeline. As a result, this inspection technique can only be used for spot measurements. Radiographic film is used as the recording medium because of its small installation area or relatively small dimensions. However, the film must then be processed to determine the condition of the inspection area.

[0006] Figure 1A is a block diagram of a radiation inspection system and insulated pipe according to several embodiments. Figure 1B is an orthographic projection of a radiation inspection system and insulated pipe according to several embodiments. Referring to Figures 1A and 1B, in some embodiments, the radiation inspection system 100 includes a detector 102, a drive mechanism 104, a radiation source 106, and a radiation source support arm (RSSA) 108. The system 100 is shown mounted on an insulated pipe 110, which includes pipe 110a and insulation material 110b. The insulated pipe 110 can have various sizes. Examples of such pipes include those with a diameter of about 1.5 inches (in.) to about 12 inches (about 3.81 to 30.5 centimeters (cm)) or more. The insulation material can have various thicknesses from about 1 inch to about 4 inches (about 2.43 cm to about 10.16 cm) or more. In some embodiments, the system 100 may be configured for a single insulated pipe 110 diameter. In other embodiments, the system 100 may be adjustable to accommodate insulated pipes 110 of a certain diameter range, wall thickness, and insulation thickness. The insulated pipes 110 are used as an example of a structure in which the radiation inspection system 100 may be installed, but the radiation inspection system 100 may be used in other structures such as conduits and cables.

[0007] Detector 102 is a system configured to generate an image based on incident radiation 112. Detector 102 includes a two-dimensional imaging array 111 of sensors configured to detect radiation 112 from radiation source 106. Detector 102 may include an amorphous silicon (a-Si), indium gallium zinc oxide (IGZO), or complementary metal oxide semiconductor (CMOS) flat panel detector, etc. In other embodiments, detector 102 may include a curved detector. In other embodiments, detector 102 may include a flexible detector that conforms to the curvature of the insulating pipe 110. In some embodiments, the curvature of the flexible detector 102 may be different from that of the insulating pipe 110 to accommodate the radial displacement of detector 102 from the insulating pipe 110. In other embodiments, detector 102 may include a line scanner having fewer pixels along the width than along the length. The line scanner can be used in continuous scanning applications or applications with continuous uniform movement of detector 102.

[0008] To convert radiation 112 to a wavelength detectable by the imaging array 111 of detector 102, detector 102 may include a conversion screen, a scintillator, etc. (using an indirect conversion sensor). For example, the scintillator may include gadolinium oxysulfide (Gd2O2S; GOS; Gadox), terbium-doped gadolinium oxysulfide (Gd2O2S:Tb), cesium iodide (CsI), etc. Although some materials of the scintillator are used as examples, in other embodiments, the material may be different depending on the specific radiation source 106. In other embodiments, the imaging array 111 may include a direct conversion type sensor (including cadmium telluride (CdTe), cadmium zinc telluride (CdZnTe or CZT), selenium, etc.) configured to directly convert radiation 112 into a signal.

[0009] The imaging array 111 can have various sizes. In some embodiments, the pixel area of ​​the imaging array 111 of the detector 102 may be approximately 14.6 cm x 14.6 cm (or 5.8 inches x 5.8 inches), 20.3 cm x 25.4 cm (or 8 inches x 10 inches), 35.6 cm x 43.2 cm (or 14 inches x 17 inches), etc. The imaging array 111 can have different sizes than these examples to accommodate different pipe diameters. The imaging array 111 may contain a 1152 x 1152 array of pixels. The pixel pitch may be approximately 127 microns (μm). The detector 102 may be configured to digitize the pixel output with at least 16-bit precision. The detector 102 may include a communication interface, such as a Universal Serial Bus (USB) interface, an Ethernet® interface, etc. Specific components and parameters such as the detector 102 and imaging array 111 are used as examples, but the parameters may differ in other embodiments.

[0010] The detector 102 may include a control logic circuit 109. The control logic circuit 109 may include a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit, a microcontroller, a programmable logic circuit, a discrete circuit, or a combination of such devices. The control logic circuit 109 may include external interfaces, such as an address and data bus interface or an interrupt interface. The control logic circuit 109 may also include other interface devices for connecting the control logic circuit 109 to internal and external components, such as a logic chipset, a hub, a memory controller, or a communication interface. The control logic circuit 109 may be configured to control various operations described herein.

[0011] The drive mechanism 104 is a device configured to move axially along the insulated pipe 110. The drive mechanism 104 is coupled to the detector 102 so that the drive mechanism 104 can move the detector 102 along the insulated pipe 110. In some embodiments, the drive mechanism 104 may be coupled to control logic 109 or other control logic of the detector 102 and may be configured to be automatically or manually controlled to move the drive mechanism 104 and the detector 102 along the insulated pipe 110.

[0012] In some embodiments, the drive mechanism 104 may include wheels, tracks, guides, sensors, an inertial measurement unit (IMU), a positioning system, and the like. These components allow the drive mechanism 104 to position itself on the insulated pipe 110, maintain its position while acquiring images using the detector 102, move the system 100 along the insulated pipe 110 so that different portions of the insulated pipe 110 can be imaged and inspected, and / or maintain the relative rotational direction of the system 100 with respect to the insulated pipe 110 so that the system 100 can move in a straight direction and remain on the insulated pipe 110.

[0013] The radiation source 106 is configured to generate radiation 112. The radiation source 106 is mounted on the drive mechanism 104 and is positionable relative to the detector 102 such that the width of the insulated pipe 110 and / or pipe 110a casts a "shadow" of radiation onto the active area of ​​the detector 102 or the imaging array 111.

[0014] The radiation source 106 may include various devices configured to produce radiation 112. For example, the radiation source 106 may include radioisotopes such as Ir-192, an X-ray source (e.g., an X-ray tube), a gamma-ray source, and the like. In certain examples, the radiation source 106 may include radioisotopes and a radiation collimator configured to shape the radiation 112.

[0015] The entire radiation source 106 may be built into the radiation inspection system 100. For example, the exposure device, exposure tube, radiation collimator, etc., may be coupled to the drive mechanism 104 and configured to move together with it. The radiation source 106 may include a structure that can extend and retract the radioactive isotope toward the radiation collimator. For example, the radiation source 106 may be coupled to a cable 120. The cable 120 may be operated, for example by activating a motor or actuator, to move the radioactive isotope toward the collimator. The radioactive isotope can be extended into the collimator to generate radiation 112 and acquire an image. When moving the radiation inspection system 100 to image different parts of the insulated pipe 110, the radioactive isotope can be retracted.

[0016] If the radiation source 106 is a power device, the entire radiation source 106 is self-contained and can be powered within the radiation inspection systems 100, 100e (Figure 8B). The power source 192a may be a battery, solar cell, fuel cell, generator, or other mechanism for providing portable power.

[0017] The radiation source 106 may be rigidly and / or adjustablely coupled to the detector 102 by a radiation source support arm 108. The radiation source support arm 108 may provide zero or more degrees of freedom for positioning the radiation source 106 relative to the detector 102. For example, the radiation source support arm 108 may include a C-shaped arm for rigidly connecting the radiation source 106 to the detector 102. Such a system 100 may be designed for a single-diameter pipe. In other examples, the radiation source support arm 108 may include multiple degrees of freedom for rotating and / or translating the radiation source 106 relative to the detector 102. The radiation source support arm 108 may be configured to fix the radiation source 106 to the detector 102 rigidly (or semi-permanently) after adjustment. For example, the radiation source support arm 108 can be indexed for quick semi-fixed adjustment for different pipe diameters and pipe configurations. Thus, the orientation of the radiation source 106 and the detector 102 may be fixed during their operation. However, for other operations, for example, when moving the system 100 to pipes of different diameters, the radiation source support arm 108 may be adjusted to accommodate the difference in pipe diameter. In some embodiments, the radiation source support arm 108 may include a series of joints for adjusting the position and orientation of the radiation source 106. Independently, the radiation source support arm 108 may be configured to be fixed after adjustment so that the relative position between the detector 102 and the radiation source 106 remains substantially the same as the detector 102 moves around the pipe 110. Substantially the same may include the same position, but may also include some variation due to mechanical tolerances, distortion of the radiation source support arm 108, etc.

[0018] In some embodiments, the radiation source support arm 108 may include joints or actuators controllable by the control logic 109. For example, the radiation source support arm 108 may include actuators and rotatable and / or translatable joints controlled by the control logic 109, so that the radiation source 106 can be positioned in various locations relative to the detector 102 and / or the insulation pipe 110.

[0019] In the example shown in Figure 1B, the drive mechanism 104' includes a number of wheels 105. The wheels 105 may be controllable by the control logic 109 and / or other control logic of the drive mechanism 104 to move the system 100 along the insulated pipe 110, maintain the orientation of the system 100 on the insulated pipe 110, rotate the system 100 around the insulated pipe 110, etc. A power source 192a, which will be described in more detail below, is attached to the drive mechanism 104. The position, orientation, configuration, etc., of the system 100 are used as examples in Figure 1B, but the configuration may differ in other embodiments.

[0020] Figure 2 is a block diagram of the configuration of a radiation source for a radiation inspection system relative to an insulated pipe according to several embodiments. Figure 3 is a block diagram of an image of an insulated pipe for a radiation inspection system according to several embodiments. Referring to Figures 1A to 3, the radiation source 106 is positioned relative to the array 111 and the insulated pipe 110 such that the radiation 112 extends across the width of the insulated pipe 110. For example, the radiation source 106 can be positioned at a distance D from the pipe which is at least twice the diameter of the insulated pipe 110. In some embodiments, the distance D may be four to five times or more the diameter of the insulated pipe 110. In another example, the angle of the radiation 112 may be selected so that the beam extends beyond the perimeter of the insulated pipe 110.

[0021] As a result, the entire width of the structure can be imaged. The detector array 111 of detector 102 is shown along with various regions 112a to 112d of radiation 112 incident on the array 111. Region 112a corresponds to radiation 112 that has passed through both walls of pipe 110a. Region 112b corresponds to radiation 112 that has passed tangentially through the walls of pipe 110a. Region 112c corresponds to radiation 112 that has passed tangentially through the insulator 110b. Finally, region 112d corresponds to radiation 112 that has not passed through any part of the insulated pipe 110. Each of these regions 112a to 112d has corresponding regions 160a to 160d in image 160.

[0022] In some embodiments, image 160 may be used in combination with a tangential profile and a double-wall dual-image (DWDI) and / or double-wall single-image (DWSI) radiograph. Region 160b of image 160 corresponds to the tangential profile of the wall of pipe 110a and can be used to determine the wall thickness by comparing it with a calibrated sample, such as a steel ball. Region 160a corresponds to the top and bottom walls. As used herein, the bottom wall is the wall of the pipe closest to the array 111, while the top wall is the wall of the insulated pipe 110 furthest from the array 111. In some embodiments, wall loss information can be generated for both the top and bottom walls. As a result, a complete 360-degree scan of wall loss information can be performed using a single image 160 of the insulated pipe 110. That is, wall loss information can be generated from a single image 160 for the top wall, bottom wall, and both side walls. Estimates of the top and bottom wall losses can be combined. However, the estimate can still be used to determine whether wall loss at that location along the insulated pipe 110 requires further inspection.

[0023] Figures 4A to 4B are block diagrams illustrating the rotation of a radiation inspection system around an insulated pipe according to several embodiments. Referring to Figures 1A, 1B, 3, 4A, and 4B, in some embodiments, the radiation source 106 and the detector 102, and thus the array 111, are configured to rotate at least partially or completely around the insulated pipe 110. For example, the drive mechanism 104 may include a chain belt, roller chain, flexible structure, etc., which wraps at least partially or completely around the pipe 110. In certain examples, the chain belt may rotatably couple the detector 102 to the insulated pipe 110, while a motor, wheel, or other structure maintains and / or rotates the position of the detector 102 around the insulated pipe 110.

[0024] In particular, the region 113 of the insulated pipe 110 may be closer to the edge of region 160a of image 160. By rotating the detector 102 as shown in Figure 4B, region 113 can be brought closer to the center of region 112a of radiation 112, and therefore can appear in image 160 closer to the center of region 160a. The accuracy of the wall loss estimation can be higher the closer it is to the center of region 160a. This can improve the accuracy of the wall loss in region 113.

[0025] Figure 5 is a partial block diagram of a modular radiation inspection system according to several embodiments. System 100a may be similar to system 100 described above. However, system 100a may be formed from modular components. Here, the drive mechanism 104a, detector 102a, radiation source 106a, and radiation source support arm 108a may each include a removable mounting structure configured to be detachably coupled to other components. For example, components may include screws, bolts, quick-release structures, etc., so that various different components can be connected together for a particular application. The detector 102a may have various sizes, and the drive mechanism 104a may have various structures for mounting to pipes 110 of various different sizes. The radiation source support arm 108a may include a fixed arm for pipes of different diameters, or a configurable arm for a range of diameters of the insulated pipe 110. The radiation source 106a may have various different radiation angles 112.

[0026] In certain examples, the size of the detector 102a and the size and / or shape of the radiation source support arm 108a may be selected based on the diameter of the insulated pipe 110, the clearance between the insulated pipe 110 and other structures, etc. In other examples, the type and / or intensity of the radiation source 106a may be selected based on the wall thickness and / or material of the insulated pipe 110.

[0027] In certain cases, the user may arrive at a work site. An insulated pipe 110 having a specific diameter may be present at the work site. The user can select the detector 102a, drive mechanism 104a, radiation source support arm 108a, and radiation source 106a based on specific conditions at the work site, including the insulated pipe 110, support structure, obstacle clearance, etc. After assembling the modular system 100a, the user can scan for the insulated pipe 110. When moving to a new work site with potentially different types of insulated pipes or other conditions, the system 100a may be configured by the user using different components specific to the insulated pipe 110 and / or the conditions of that work site.

[0028] Figure 6 is a block diagram of a radiation inspection system of a positioning system according to several embodiments. System 100b may be similar to systems 100 and 100a. However, in some embodiments, system 100b includes a positioning system 115. Although the positioning system 115 is shown as part of the detector 102, the positioning system 115 may be part of the drive mechanism 104 or another component of system 100b.

[0029] The positioning system 115 may include various systems configured to determine the position of system 100b. For example, the positioning system 115 may include a Global Positioning System (GPS), an inertial positioning system, a cellular communication system, or other systems capable of providing absolute and / or relative position information.

[0030] In some embodiments, location information from the positioning system 115 may be associated with one or more images 160 generated using the detector 102. For example, location information from the positioning system 115 may be embedded in the metadata of the image 160.

[0031] Figures 7A and 7B are partial block diagrams of a radiographic inspection system for a pipe support according to several embodiments. Referring to Figure 7A, system 100c may be similar to systems 100, 100a, 100b, etc., described herein. In some embodiments, system 100c can be installed on an insulated pipe 110 supported by pipe supports 165. The pipe supports 165 can be periodically arranged along the insulated pipe 110 to support the insulated pipe 110 above the ground 167.

[0032] The system 100c may be configured such that the drive mechanism 104 moves along the opposite side of the insulated pipe 110 from the pipe support 165. In some embodiments, the detector 102, the drive mechanism 104, etc., may be larger than the radiation source 106. By positioning the radiation source 106 on the side of the pipe having the pipe support 165, the system 100c can be maneuvered to approach the pipe support 165. As a result, much more of the pipe 110a, including the area around the pipe support 165, can be imaged and inspected.

[0033] In some embodiments, if the system is modular as described above, the work required to move system 100c beyond the pipe support 165 may be minimal. For example, while system 100c is moving through the pipe support 165, only the radiation source support arm 108 and the radiation source 106 can be removed from system 100c. Once system 100c is away from the pipe support 165, the radiation source support arm 108 and the radiation source 106 can be reattached.

[0034] In some embodiments, the drive mechanism 104 may be configured to maintain the relative orientation of the system 100c along the insulated pipe 110a. In some embodiments, the weight distribution of the system 100c may be greater on the side of the insulated pipe 110 furthest from the ground 167. The drive mechanism 104 may be configured to actively maintain the orientation of the system 100c as the system 100c moves along the insulated pipe 110 and acquires an image for inspection.

[0035] In some embodiments, the radiation source 106, the detector 102, and / or the drive mechanism 104 are configured to rotate or move at least partially around the insulated pipe 110, as described with respect to Figures 4A to 4B. This is to avoid fixed structures of the pipeline, such as the pipe support 165.

[0036] In various embodiments, the detector 102, the drive mechanism 104, etc., can be positioned on a specific side of the pipe 110, while in other embodiments, the detector 102, the drive mechanism 104, or other components of system 100c can be positioned on a specific side of the insulated pipe 110. For example, Figures 1A, 1B, 7A, and 7B show the drive mechanism 104 located on the top of the insulated pipe 110. In other examples (not shown), the drive mechanism 104 may be located on the side or bottom of the insulated pipe 110. The orientation of the drive mechanism 104 relative to the insulated pipe 110 can be designed or configured to avoid obstacles or minimize delays caused by obstacles, based on the pipeline configuration and the location of obstacles in the pipeline (e.g., pipe support 165). In some embodiments, when used in the field, different modular components can be selected based on the location and / or configuration of obstacles such as pipe support 165, as described above with respect to Figure 5.

[0037] Referring to Figure 7B, in some embodiments, the system 100c can be at least partially arranged around an insulated pipe 110 having different supports 165b, where the pipe supports 165b may be located on only one side of the insulated pipe 110. The majority of the system 100c, such as the detector 102 and the drive mechanism 104, can be located on the opposite side of the insulated pipe 110. In some embodiments, only the radiation source 106 can be moved and / or removed and reinstalled to remove the pipe supports 165b.

[0038] Figures 8A to 8D are block diagrams of radiation inspection systems according to several embodiments. Referring to Figure 8A, in some embodiments, system 100d may be similar to systems 100 to 100c described above. System 100d may include a power supply 192. In some embodiments, the detector 102 is configured to receive and / or communicate power through one or more cables 124.

[0039] Power supply 192 can include various different power sources. For example, power supply 192 can include connections to a battery, a mains power supply, or an alternating current (AC) power supply. Power supply 192 may be separate from system 100d. Cable 124 may be configured to maintain the connection between power supply 192 and system 100d as system 100d moves along a structure.

[0040] Referring to Figure 8B, in some embodiments, system 100e may be similar to systems 100 to 100c described above. The power supply 192a may be mounted on the drive mechanism 104. The power supply 192a may be configured to move with the drive mechanism 104. For example, the power supply 192a may include a portable power source such as a battery or an energy storage device. Although the power supply 192a is shown to be positioned in a specific location relative to the drive mechanism 104 and / or the detector 102, the power supply 192a may be positioned in a different location.

[0041] Referring to Figure 8C, in some embodiments, system 100e may be similar to systems 100 to 100e described above. Detector 102 may be configured to communicate wirelessly. For example, detector 102 may include a wireless communication system 117 for operation via Wi-Fi®, Bluetooth®, cellular data networks, satellite communication networks, etc. In some embodiments, control logic 109 may be configured to communicate images, processed images, results of image analysis, parameters of system 100e (such as position, orientation, and / or configuration), etc., via the wireless communication system 117.

[0042] The wireless communication system 117 may be used to create a communication link 126 between the control logic 109 and the remote computer 125. The remote computer may include a laptop, tablet computer, desktop computer, workstation, etc. Accordingly, data created by system 100f may be sent to various destinations as needed, and / or system 100f may be remotely controlled.

[0043] Referring to Figure 8D, in some embodiments, system 100g may be similar to system 100f described above. However, system 100g can be connected to a remote computer 125 via a wired communication link 126'. In some embodiments, the wired communication link 126' may be formed via the cable 124 described above.

[0044] Regardless of the communication medium, in some embodiments, a communication link 126 or 126' allows a user of a remote computer 125 to operate systems 100f, 100g, etc.

[0045] Figures 9A and 9B are flowcharts illustrating techniques for using a radiation inspection system according to some embodiments. System 100 in Figures 1A and 1B is used as an example, but the operation can be applied to other systems 100a through 100g, etc. Referring to Figures 1A and 9A, in 900, the drive mechanism 104, the detector 102, and the radiation source 106 may be at least partially arranged around a structure such as an insulated pipe 110. However, in other embodiments, the structure may be a different type of structure such as a conduit or cable. In some embodiments, arranging the drive mechanism 104, the detector 102, and the radiation source 106 at least partially around the pipe 110 may include arranging the drive mechanism 104 and the detector 102 in the pipe 110, and, as described above, arranging the radiation source 106 offset from the pipe 110 on the opposite side of the pipe 110 from the detector 102. Arranging the drive mechanism, the detector, and the radiation source may include assembling the system 100 at least partially around the pipe 110. In some embodiments, the system 100 may be assembled before being positioned at least partially around the pipe 110, and in other embodiments, the system 100 may be assembled on the pipe 110 as part of positioning its components at least partially around the pipe 110.

[0046] In 910, an image of a section of a structure can be generated using a detector 102 and a radiation source 106 that includes at least the width of the structure. For example, the width of an insulated pipe 110 can be illuminated by the radiation source 106. The radiation 112 can be detected by an array 111 of detectors 102 to generate an image 160. In the case of the structure of the insulated pipe 110, at least the width of the structure includes at least the pipe wall 110a and may or may not include insulation material 110b on the outer tangential or transverse edge (i.e., 112c in Figures 2, 4A to 4B).

[0047] Wall loss information can be generated from an image. This wall loss information can take various forms. For example, it can represent the wall thickness at various locations. In another example, it can represent the deviation from the nominal wall thickness. Wall loss can be represented in various ways.

[0048] In 920, sidewall loss information can be generated based on an image. For example, region 160b can be compared to a calibrated object having a known size. In some embodiments, the calibrated object can be placed in the path of radiation 112 such that the sample is a corresponding portion of image 160. The sidewall loss can be determined by comparing that portion to a tangent portion of region 160b. For example, the pixel-level width of the sidewall can be compared to the pixel-level width of the calibrated object, which is of known width. In other embodiments, the wall loss can be estimated by converting the wall thickness in the image to an actual thickness using a magnification that converts pixels to distance. In other embodiments, different techniques may be used to generate wall loss information by converting the pixels of region 160b to wall thickness.

[0049] In 950, side wall loss information can be generated based on an image. As will be described in more detail below with respect to Figures 10 to 20, region 160a of image 160 can be used to generate bottom wall loss information. In particular, the generated wall loss information may include quantitative wall loss information. In 960, in some embodiments, top wall loss information can be generated based on image 160. Similar to the bottom wall loss information, top wall loss information can be generated using region 160a.

[0050] In some embodiments, the loss information from the top and bottom walls can be combined as a result of the position of the radiation source 106. For example, referring to Figure 2, if the radiation source 106 is located further away from the pipe 110, the radiation in region 112a incident on the imaging array 111 may include contributions from both the bottom wall (the wall closest to the imaging array 111) and the top wall (the wall closest to the radiation source 106). That is, the image data for region 160a can be based on both the top and bottom walls. In other embodiments, the radiation source 106 can be located in different positions. For example, as shown in Figure 13, if the radiation source 106 is located on or adjacent to the insulated pipe 110, data from the entire bottom wall may contribute to the image region 160a. However, only data from a smaller portion of the top wall may contribute to the image region 160a, and this may spread across the entire region 160a.

[0051] In some embodiments, wall loss information can be generated for the entire perimeter of a structure based on an image. That is, a combination of bottom wall loss, top wall loss, and side wall loss can be obtained from a single image.

[0052] The control logic 109 may be configured to control the operation of the detector 102, the radiation source 106, etc., to perform operations such as 910, 920, 950, and / or 960. However, in some embodiments, the control logic 109 may be configured to perform fewer operations than all of them. For example, the control logic 109 may be configured to operate the detector 102 and the radiation source 106 to generate an image. The control logic 109 may be configured to transmit the image, such as sending the image to the remote computer 125 as described above. The remote computer 125 or other system may be configured to perform operations as described in 920, 950, 960, etc.

[0053] In some embodiments, positioning the radiation source at 900 may include positioning the radiation source away from the structure at a distance greater than twice the diameter of the structure. This position of the radiation source 106 can result in collimated radiation 112 that illuminates the entire width of the structure.

[0054] Referring to Figures 1A, 1B, and 9B, in some embodiments, the operation at 970 includes moving the detector and radiation source along the structure to a second section of the structure. The operations at 900, 910, 920, 950, or other operations described herein, may be performed again on the second section of the structure. As a result, different parts of the structure may be imaged and inspected. By repeating this operation, the entire length of the structure can be imaged and inspected. In some embodiments, moving the detector 102 and radiation source 106 may include rotating the detector 102 and radiation source 106 around the structure.

[0055] Figure 10 is a flowchart illustrating techniques for estimating material loss using a radiation inspection system according to several embodiments. Figures 11A to 11B are block diagrams illustrating techniques for estimating material loss according to several embodiments. Referring to Figures 1A to 3, Figure 10, Figure 11A, and Figure 11B, system 100 and insulated pipe 110 are used as examples. However, in other embodiments, different systems can be used. In particular, a system 100 can be used that does not image the entire width of the insulated pipe 110, including a system 100 in which the radiation source 106 is positioned adjacent to the insulated pipe 110.

[0056] In some embodiments, an image 1100 of the insulated pipe 110 is acquired at 1004. Image 1100 may be similar to image 160 described above. However, in other embodiments, image 1100 may include only a portion of region 160a, depending on the specific configuration of the detector 102, the radiation source 106, and the insulated pipe 110. In some embodiments, acquiring an image of the structure involves generating radiation directed at the structure and detecting the radiation after it has passed through the structure. The radiation source 106 can generate radiation 112 directed at the insulated pipe 110 and the detector 102. The detector 102 can generate image 160 as described above.

[0057] In 1010, the pipe image 1100 is filtered to produce the filtered image 1110. Image filtering can include various types of filtering. For example, filtering can include nonlinear digital filtering, median filtering, mean filtering, modal filtering, spatial low-pass filtering, spatial smoothing, etc. Filtering can be any type of filtering that reduces the variation between pixels across image 1100 in the filtered image 1110. In some embodiments, the use of filtering can reduce the variation in image 1100 to approximate the overall gray level distribution of image 1100. For example, filtering can wash away or smooth out defects in image 1100 to obtain an approximation of the background, i.e., a portion of the image without defects.

[0058] In some embodiments, filtering can use a kernel size with a radius of approximately 100 pixels. The shape of the kernel can be square, circular, elliptical, symmetrical, aligned to major image features such as the axes of pipe 110, or varied across the entire image. In some embodiments, the kernel size can be based on the expected size of defects. In particular, the kernel size may be larger than the expected largest defect. In some embodiments, the kernel size can be based on the pipe, such as the pipe size or the thickness of the pipe walls. In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and other filtering. Filtering is performed by performing convolution between the kernel and the image. The kernel size is the size of the matrix.

[0059] In 1020, image 1100 is normalized using the filtered image to produce the normalized image 1120. For example, image 1100 can be divided by the filtered image 1110. The filtered image 1110 can be subtracted from the result of the division to produce the normalized image 1120.

[0060] In 1050, the normalized image is scaled based on a transfer function associated with the insulated pipe 110. This transfer function represents a conversion between the normalized gray level (or normalized contrast) in the normalized image 1120 and the wall thickness, such as the gray level per unit length. The normalized image 1120 can be divided by the transfer function to convert the gray levels of the normalized image 1120 to lengths in the scaled image 1130. In some embodiments, the process described herein may result in each pixel of the scaled image 1130 representing the wall thickness. As described below with respect to Figure 14, the transfer function can be generated using measurements of a sample with a known thickness under various conditions. The transfer function can be selected based on a particular insulated pipe 110. As a result, the transfer function can be applied to the gray levels of the normalized image 1120 to convert the gray levels to wall thickness.

[0061] The resulting scaled image 1130 is a quantitative result representing the actual wall thickness. That is, the scaled image 1130 goes beyond a qualitative result that merely shows the difference in thickness relative to another part of the insulation pipe 110 in an image without the magnitude of the difference or the actual thickness.

[0062] Figures 12A to 12C are block diagrams illustrating techniques for estimating material loss according to several embodiments. Referring to Figure 12A, image 1100a is an example of image 1100 from Figures 11A to 11B, where a defect 1200 is present in image 1100a. Referring to Figure 12B, a kernel 1210 of a filter, such as a nonlinear digital filter (e.g., a median filter), is selected. The size of kernel 1210 is larger than the size of the defect. In some embodiments, the kernel size selection can be made based on the actual defect and / or variation in image 1100a. In other embodiments, the selection can be made based on the expected size of the defect.

[0063] Referring to Figure 12C, filtered image 1110a is an example of image 1100a filtered by kernel 1210. As a result, the effects 1220 of the image defect 1200 are spread to filtered image 1110a. This filtered image 1110a can be used to normalize image 1100a as described above.

[0064] In some embodiments, the operations described herein can eliminate the effects of integration time, isotope source, and / or other factors. Such factors can be eliminated by normalization. For example, normalization can correct for the non-constant Curie intensity of the isotope source or radiation source. Defect-free regions may have a relative value of 1 in the normalized image 1120. That is, the normalized image 1120 may be at least somewhat independent of the absolute values ​​of image 1100.

[0065] Referring to Figure 12D, the scaled image 1130a is an example of the image 1100a, which is normalized by the filtered image 1110a and scaled by the transfer function. The defects 1200 in image 1100a are converted to defect thicknesses 1200', where each pixel represents the actual wall thickness.

[0066] Figure 13 is a block diagram of a radiation inspection system for radiation sources at different locations according to several embodiments. In some embodiments, material loss estimation techniques can be applied to images generated in a different manner than in system 100 in Figures 1A and 1B. For example, in system 100h, as shown in Figure 13, the radiation source 106 may be positioned closer to the insulated pipe 110. For example, the distance D' between the radiation source 106 and the insulated pipe 110 can be reduced to be closer to the insulated pipe 110 than twice the diameter of the insulated pipe 110. In some embodiments, the radiation source 106 may be positioned in the insulated pipe 110. The image generated by system 100h can reduce the influence of walls closer to the radiation source 106. That is, walls closer to the radiation source 106 may not contribute to the image, or may contribute only a substantially uniform amount across the entire image, and the material loss estimation may not include the contribution of those walls. In some embodiments, system 100h may be rotated similarly to system 100 shown in Figures 4A and 4B.

[0067] In some embodiments, the radiation source 106 may be used in the manner shown in the system 100 of Figures 1A and 1B, starting from a location at least twice the diameter of the insulated pipe 110. However, the radiation source 106 may be moved closer after a defect is found in order to further investigate the defect. The radiation source support arm 108 can be configured to controllly move the radiation source 106 in response to control logic 109, from the position shown in Figures 1A and 1B to the position shown in Figure 13, and then back to the position shown in Figures 1A and 1B.

[0068] Figures 14 to 20 are flowcharts illustrating techniques for estimating material loss according to several embodiments. The operation can be performed in the same manner as described above. Referring to Figure 14, in 1000, a transfer function is generated based on the attributes of the pipe. The transfer function can be generated by various techniques and may have various inputs. In some embodiments, multiple transfer functions can be experimentally generated for various different pipe types, diameters, wall thicknesses, materials in the pipe, radiation sources 106, detector attributes 102, etc. Using experimental results from samples, a transfer function can be generated with inputs associated with pipe attributes (e.g., pipe type, diameter, wall thickness, wall material, insulation thickness, and insulation), attributes of the material in the pipe (e.g., air, water, multiphase, or other fluid or gas), attributes of the radiation source (e.g., isotope source or X-ray tube), and / or attributes of the detector (e.g., standard imaging or pixel binning). Pixel binning is a process that combines charges from adjacent pixels in an image sensor during reading to result in a larger effective pixel size. Pixel binning (e.g., 2x2 and 4x4 pixel binning) improves contrast (or gray level) and speeds up imaging. Values ​​associated with various attributes, such as pipe attributes, material attributes within the pipe, radiation source attributes, or detector attributes, can be various inputs to the transfer function. In some embodiments, different inputs to the sample-based transfer function can be stored in a lookup table as constants that can be used to convert normalized contrast into material loss estimates for various attributes and / or pipe configurations. The contrast or gray level of the image may change with variations in various attributes.

[0069] In some embodiments, a pipe may have a known thickness and a series of holes or defects, each with different known wall losses. For example, a pipe may have holes with wall losses of 10%, 20%, 30%, 40%, and 50%. A pipe with holes can be imaged and normalized as described above. The values ​​of the normalized image can be associated with a range of wall thicknesses where the wall loss is between 0% and 50%. A curve can be fitted to a tuple of normalized image values ​​and thickness. The relationship between the normalized image values ​​may be linear. Furthermore, the normalized image value at 0% loss should be zero. As a result, the curve can be defined solely by its slope. This process can be repeated for various attributes and / or pipe configurations, resulting in the association of slopes of normalized image values ​​to thickness for various attributes and / or pipe configurations. For example, the slope can be determined for various different pipe diameters and materials within the pipe. Using this data, a transfer function can be generated with the normalized image values ​​and matching field attributes and pipe configurations as inputs, and thickness as the output.

[0070] In some embodiments, various different attributes and / or pipe configurations can be converted to iron (Fe) equivalents (or any other pipe material equivalents). A curve can be fitted to a gradient and Fe equivalent tuple to generate a transfer function. The pipe in the field may also be an Fe equivalent. As described above, Fe equivalents can be used as input to obtain a gradient for converting the normalized image values ​​to thickness.

[0071] In some embodiments, the transfer function can be adapted to an n-tuple of gradients and various attributes and / or pipe configurations. Thus, the transfer function may include normalized image values ​​and matching field attributes and pipe configurations as inputs and thickness as an output.

[0072] In some embodiments, two measurements can be performed on a sample with known thickness and defects. One image is acquired with a known defect in the bottom wall, and the other image is acquired with a known defect in the top wall. Even when imaging the same known defect, the normalized image values ​​of the resulting defect may differ. In field use, the two resulting transfer functions can be used to determine whether the wall loss is in the top wall or the bottom wall.

[0073] Referring to Figure 15, in 1004a, obtaining an image of the structure includes obtaining an image of the structure including its width. As described above, an image 160 of a structure such as a pipe 110 can be obtained. The operations described herein can be performed on the entire image, region 160a, smaller regions within region 160a, etc. In some embodiments, the techniques described in Figures 14 and 15 can be combined to use the width of the structure from the image to determine the input to the transfer function used for material loss estimation.

[0074] Referring to Figure 16, in 1010a, a nonlinear digital filter is applied to the structural image to produce a filtered image. Referring to Figure 17, in 1005a, the kernel size of the nonlinear digital filter is selected based on the structure. Referring to Figure 18, in 1005b, the kernel size of the nonlinear digital filter is selected based on the expected largest defect. Referring to Figure 19, in 1020a, normalizing the image based on the filtered image includes dividing the image by the filtered image and subtracting the filtered image to produce a normalized image.

[0075] Referring to Figure 20, in 1060, the scaled, normalized image is transformed into a material loss estimate image showing wall loss greater than a predetermined threshold. For example, the scaled image may be transformed to highlight material loss. In some embodiments, material loss may be further transformed into a percentage of material loss. The percentage range can be transformed into a color in the color image. In certain examples, percentages of material loss in the range of 0% to 20% may be colored black. The manufacturing tolerance of the structure may be about 20%. Therefore, material loss results below a predetermined percentage, such as 20%, can be considered within the normal tolerance. The range of 20% to 30% may be colored green. The range of 30% to 40% may be colored blue. The range of 40% to 50% may be colored yellow. The range above 50% may be colored red. Thus, lost wall may be transformed into a color that is more easily recognizable to the user. Black or colors other than black and green may indicate areas where further inspection of the structure is performed. For example, further examinations can be performed using the same system 100, a system 100 configured in a different way, another similar system, or another type of system such as an ultrasound system.

[0076] Figures 21A to 21D are block diagrams illustrating several embodiments of a radiation inspection system, an insulated pipe with various defects, and corresponding images. Referring to Figure 21A, the system 100h of Figure 13 is used as an example, but in other embodiments, the operation relating to the different systems 100 described above can be used. In this example, pipe 110a has a defect 113a in its upper wall (the one furthest from the imaging array 111).

[0077] In some embodiments, a transfer function can be generated based on a defect in the top wall as described above, and another transfer function can be generated based on a defect in the bottom wall as described above. For example, an insulated pipe 110 with a calibrated defect in the bottom wall (closest to the imaging array 111) can be analyzed as described above to generate a bottom wall transfer function. Similarly, an insulated pipe 110 with a calibrated defect in the top wall (closest to the imaging array 111) can be analyzed as described above to generate a top wall transfer function. Since the contrast generated by the calibrated defect in the top wall is smaller than that when the same defect is present in the bottom wall, the top wall transfer function can scale the image more than the bottom wall transfer function.

[0078] Image 2130a-1 was generated using the bottom wall transfer function, and image 2130a-2 was generated using the top wall transfer function. The defect 113a on the top wall results in artifact 2135a-1. Artifact 2135a-1 is shown by a dashed line and represents the reduction in contrast caused by defect 113a on the top wall.

[0079] Image 2130a-2 has artifact 2135a-2 corresponding to defect 113a. In contrast to image 2130a-1, artifact 2135a-2 is shown by a solid line representing slight contrast. That is, the upper wall transfer function was generated using a calibrated defect in the upper wall, and the upper wall defect 113a results in artifact 2135a-2 with slight contrast.

[0080] In some embodiments, the contrast of artifact 2135a-1 may be too low to be registered as a defect. For example, if the contrast indicates a wall loss of less than approximately 20%, the wall loss may be classified as no wall loss. In some embodiments, both the top wall and bottom wall transfer functions may be used to generate images such as images 2130c-1 and 2130c-2. Both can be analyzed to determine whether a defect exists. Thus, the possibility of missing a defect in the top wall can be reduced.

[0081] Referring to Figure 21B, the system 100h in Figure 13 is again used as an example, but in other embodiments, the operation relating to a different system 100 described above can be used. In this example, pipe 110a has a defect 113b in its bottom wall (closest to the imaging array 111).

[0082] Image 2130b-1 was generated using the bottom wall transfer function, and image 2130b-2 was generated using the top wall transfer function. The defect 113b in the bottom wall results in artifact 2136b-1. Artifact 2136b-1 is shown with a solid line to represent the slight contrast caused by defect 113b in the bottom wall. The contrast of artifact 2136b-1 is slight because image 2130b-1 was generated using the bottom wall transfer function, and defect 113b, which results in 2136b-1, is located in the bottom wall.

[0083] Image 2130b-2 has artifact 2136b-2 corresponding to defect 113b. In contrast to image 2130b-1, artifact 2136b-2 is shown with higher contrast, represented by solid black shading. The top wall transfer function scales image 2130b-2 more than the bottom wall transfer function. As a result, the contrast due to defect 113b on the bottom wall results in relatively high contrast.

[0084] Referring to Figure 21C, the system 100h in Figure 13 is again used as an example, but in other embodiments, the operation relating to different systems 100 described above can be used. In this example, pipe 110a contains a defect 113b on its bottom wall (closest to the imaging array 111) and a defect 113a on its top wall (farthest from the imaging array 111). Since both defects 113a and 113b are in the path of the X-ray beam 112, both defects 113a and 113b contribute to the resulting images 2130c-1 and 2130c-2. Defects 113a and 113b may result in artifacts 2137a-1 and 2137b-1 in image 2130c-1 and artifacts 2137a-2 and 2137b-2 in image 2130c-2, as in Figures 21A and 21B. Even though defects 113a and 113b result in superimposed artifacts in images 2130c-1 and 2130c-2, individual defects 113a and 113b can be analyzed as described above. As a result, virtually all defects in the wall can be identified, regardless of their location.

[0085] Referring to Figures 21A, 21B, and 21D, the system 100h in Figure 13 is again used as an example, but in other embodiments, the operations relating to different systems 100 described above can be used. In some embodiments, images 2130b-1 and 2130b-2 may be generated as shown in Figure 21B. System 100h can be rotated around the insulated pipe 110 to the opposite side of the insulated pipe 110. As a result, defect 113b, which was previously close to the imaging array 111, may not be far from the imaging array 111, as shown in Figure 21D. Images 2130d-1 and 2130d-2 were generated using bottom-wall and top-wall transfer functions, respectively. The resulting artifacts 2138b-1 and 2138b-2 in images 2130d-1 and 2130d-2 may be similar to artifacts 2135a-1 and 2135a-2 shown in Figure 21A.

[0086] In particular, the same defect 113b resulted in two changes to the image artifact: both the relative size and contrast of the artifact changed. In some embodiments, one or both of the changes in the size and contrast of the artifact can be used to determine which wall of the insulation pipe 110 the relevant defect 113b is located on. Thus, when analyzing that particular defect 113b, a quantitative wall loss can be estimated by selecting the transfer function corresponding to the wall on which the defect 113b is located.

[0087] While one defect 113b is used as an example, in other embodiments, more defects can be analyzed in a single set of images. Furthermore, some artifacts in an image can be scaled using the top wall transfer function, while others can be scaled using the bottom wall transfer function. In some embodiments, images can be selected to allow the use of the bottom wall transfer function. For example, after determining that defect 113b is on the bottom wall in the orientation of system 100h in Figure 21B, image 2130b-1 may be selected and scaled using the bottom wall transfer function to generate a quantitative wall loss. Image 2130d-2 in Figure 21D may have reduced accuracy because it used a higher magnification from the top wall transfer function used to generate image 2130d-2.

[0088] As an example of the degree to which system 100h rotates, a 180-degree rotation can be used, but in other embodiments, the rotation and generation of the two sets of images may differ. For example, system 100h can generate four sets of images by increasing the rotation by 90 degrees around the insulated pipe 110, six sets of images by increasing the rotation by 60 degrees, eight sets of images by increasing the rotation by 45 degrees, twelve sets of images by increasing the rotation by 30 degrees, and so on.

[0089] Referring to Figures 21A, 21B, and 21C, wall defects can be identified by using the top wall transfer function together with the bottom wall transfer function, and / or by comparing the image generated using the top wall transfer function with that of the bottom wall transfer function. As shown in Figures 21A, 21B, and 21D, wall defects can be identified using images obtained at multiple rotational positions around the structure.

[0090] Some embodiments include radiation inspection systems 100 to 100h comprising a drive mechanism 104 configured to move along a structure 110, a detector 102 attached to the drive mechanism 104, a radiation source 106 attached to the drive mechanism 104 and positionable relative to the detector 102 such that the width of the structure 110 casts a radiation shadow on the active area of ​​the detector 102, and control logic 109 coupled to the detector 102 and configured to receive an image from the detector 102, generate side wall loss information based on the image, and generate bottom wall loss information based on the image.

[0091] In some embodiments, the control logic 109 is further configured to generate upper wall loss information based on the image.

[0092] In some embodiments, the drive mechanism 104 is configured to rotate the detector 102 and the radiation source 106 at least partially around the structure 110.

[0093] In some embodiments, the control logic 109 is further configured to filter at least a portion of the image to generate a filtered image, normalize at least a portion of the image based on the filtered image to generate a normalized image, and scale at least a portion of the normalized image based on a transfer function associated with the structure 110.

[0094] In some embodiments, at least one of the detector 102 and the radiation source 106 is detachable from the drive mechanism 104.

[0095] In some embodiments, systems 100 to 100h further include a positioning system 115 configured to generate location information, and control logic 109 is configured to associate at least one of the following with the location information: an image, side wall loss information, and bottom wall loss information.

[0096] In some embodiments, the drive mechanism 104 and the detector 102 are configured to move along the side of the structure 110 opposite to the support of the structure 110.

[0097] In some embodiments, systems 100 to 100h further include a power supply 192 attached to the drive mechanism 104.

[0098] In some embodiments, systems 100 to 100h further include communication interfaces 109, 117, and control logic 109 is configured to communicate at least one of the following over the communication interfaces 109, 117: image, sidewall loss data, and bottomwall loss data.

[0099] Some embodiments include a method for operating a radiation inspection system 100 to 100h, which includes arranging a drive mechanism 104, a detector 102, and a radiation source 106 around a structure 110; using the detector 102 and the radiation source 106 to generate an image of a section of the structure 110 including at least the width of the structure 110; generating side wall loss information based on the image; and generating bottom wall loss information based on the image.

[0100] In some embodiments, locating the radiation source 106 involves positioning the radiation source 106 at a distance greater than twice the diameter of the structure 110 from the structure 110.

[0101] In some embodiments, this method further includes generating upper wall loss information based on an image.

[0102] In some embodiments, this method further includes generating wall loss information for the entire perimeter of the structure 110 based on an image.

[0103] In some embodiments, generating an image of a section of structure 110 includes generating an image of the section of structure 110 and a calibrated object adjacent to structure 110, and generating sidewall loss information based on the image includes generating sidewall loss information based on a portion of the image of a calibrated object adjacent to structure 110.

[0104] In some embodiments, the method further includes moving the detector 102 and radiation source 106 along the structure 110 to a second section of the structure 110; using the detector 102 and radiation source 106 to generate an image of the second section of the structure 110 including at least the width of the second section of the structure 110; generating side wall loss information based on the image of the second section; and generating bottom wall loss information based on the image of the second section.

[0105] In some embodiments, the method further includes rotating the detector 102 and the radiation source 106 around the structure 110.

[0106] In some embodiments, the method further includes filtering an image of the structure 110 to generate a filtered image, normalizing an image of at least a portion of the image based on the filtered image to generate a normalized image, and scaling an image of at least a portion of the normalized image based on a transfer function associated with the structure 110.

[0107] In some embodiments, the method further includes adjusting the position of the radiation source 106.

[0108] Some embodiments include radiation inspection systems 100 to 100h comprising means for generating radiation, means for generating an image based on radiation coupled to the means for generating radiation, means for moving the means for generating radiation and the means for generating an image based on radiation, and means for generating side wall loss information and bottom wall loss information based on the image.

[0109] Examples of means for generating radiation include a radiation source 106. Examples of means for generating an image based on radiation coupled to means for generating radiation include a detector 102 and an imaging array 111. Examples of means for moving means for generating radiation and means for generating an image based on radiation include a drive mechanism 104 and a radiation source support arm 108. Examples of means for generating side wall loss information and bottom wall loss information based on the image include control logic 109 and a computer 125.

[0110] In some embodiments, means for generating side wall loss information and bottom wall loss information based on an image further comprises means for generating top wall loss information based on an image. Examples of means for generating top wall loss information based on an image include control logic 109 and computer 125.

[0111] Some embodiments include a method that includes obtaining an image of the structure 110, filtering the image of the structure 110 to generate a filtered image, normalizing the image based on the filtered image to generate a normalized image, and scaling the normalized image based on a transfer function associated with the structure 110.

[0112] In some embodiments, the method further includes generating a transfer function based on the attributes of the structure 110.

[0113] In some embodiments, generating a transfer function involves obtaining a normalized image of known defects in structures 110s having at least one distinct attribute, and generating a transfer function based on the normalized image, and scaling the normalized image based on the transfer function associated with the structure 110 involves bringing at least one attribute of the structure 110 as input to the transfer function.

[0114] In some embodiments, scaling an image normalized based on a transfer function associated with the structure 110 includes scaling an image normalized based on an upper wall transfer function and scaling an image normalized based on a bottom wall transfer function.

[0115] In some embodiments, obtaining an image of the structure 110 includes generating radiation directed at the structure 110 and detecting the radiation after it has passed through the structure 110.

[0116] In some embodiments, obtaining an image of the structure 110 includes obtaining an image of the structure 110 that includes the width of the structure 110.

[0117] In some embodiments, filtering an image of structure 110 to generate a filtered image includes applying a nonlinear digital filter to the image of structure 110.

[0118] In some embodiments, the method further includes selecting the size of the kernel of the nonlinear digital filter based on the structure 110.

[0119] In some embodiments, the method further includes selecting the size of the kernel of the nonlinear digital filter based on the expected largest defect.

[0120] In some embodiments, normalizing an image based on a filtered image includes dividing the image by the filtered image and subtracting the filtered image to generate a normalized image.

[0121] In some embodiments, the method further includes converting a scaled, normalized image into a material loss estimation image that shows wall loss greater than a predetermined threshold.

[0122] In some embodiments, filtering the image of structure 110 to generate a filtered image includes filtering a subset of the image, and normalizing the image based on the filtered image to generate a normalized image includes normalizing a subset of the image based on the filtered image to generate a normalized image.

[0123] Some embodiments include systems 100 to 100h comprising a radiation source 106, a detector 102 positioned between the radiation source 106 and the detector 102 to receive radiation having a structure 110, and control logic 109 configured to use the detector 102 to acquire an image of the structure 110, filter the image of the structure 110 to generate a filtered image, normalize the image based on the filtered image to generate a normalized image, and scale the normalized image based on a transfer function associated with the structure 110.

[0124] In some embodiments, the control logic 109 is further configured to generate a transfer function based on the attributes of the structure 110.

[0125] In some embodiments, the control logic 109 is further configured to acquire an image of the structure 110, including its width.

[0126] In some embodiments, the control logic 109 is further configured to apply a nonlinear digital filter to the image of the structure 110.

[0127] In some embodiments, the control logic 109 is further configured to select the size of the kernel of the nonlinear digital filter based on the structure 110.

[0128] In some embodiments, the control logic 109 is further configured to select the size of the kernel of the nonlinear digital filter based on the expected maximum damage.

[0129] In some embodiments, the control logic 109 is further configured to divide the image by the filtered image and subtract the filtered image to generate a normalized image.

[0130] In some embodiments, the control logic 109 is further configured to convert the scaled, normalized image into a material loss estimation image that shows wall loss greater than a predetermined threshold.

[0131] Some embodiments include a system 100 to 100h, which includes means for acquiring an image of structure 110, means for filtering the image of structure 110 to generate a filtered image, means for normalizing the image based on the filtered image to generate a normalized image, and means for scaling the normalized image based on a transfer function associated with structure 110.

[0132] Examples of means for acquiring an image of the structure include a detector 102, an imaging array 111, and a radiation source 106. Examples of means for filtering the image of the structure and generating a filtered image include control logic 109 and a computer 125. Examples of means for normalizing the image based on the filtered image and generating a normalized image include control logic 109 and a computer 125. Examples of means for scaling the normalized image based on a transfer function related to the structure include control logic 109 and a computer 125.

[0133] In some embodiments, the means for normalizing an image include means for dividing the image by a filtered image and subtracting the filtered image to generate a normalized image. Examples of means for dividing the image by a filtered image and subtracting the filtered image to generate a normalized image include control logic 109 and computer 125.

[0134] While structures, devices, methods, and systems are described according to specific embodiments, those skilled in the art will readily recognize that many modifications are possible to specific embodiments, and therefore any modifications should be considered to fall within the spirit and scope disclosed herein. Accordingly, many modifications can be made by those skilled in the art without departing from the spirit and scope of the appended claims.

[0135] The claims following the disclosure in this document are hereby explicitly incorporated into the disclosure in this document, and each claim stands as a separate embodiment in itself. This disclosure includes all substitutions of independent claims for dependent claims. Furthermore, additional embodiments that can be derived from the following independent and dependent claims are also explicitly incorporated into the description in this document. These additional embodiments are determined by replacing the dependency of a given dependent claim with the phrase "any of the claims beginning with claim [x] and ending with the claim immediately preceding this claim," where the parenthetical term "[x]" is replaced with the number of the most recently described independent claim. For example, for a first set of claims beginning with independent claim 1, claim 3 may depend on either claim 1 or 2, and these separate dependencies may result in two different embodiments; claim 4 may depend on any one of claims 1, 2, or 3, and these separate dependencies may result in three different embodiments; claim 5 may depend on any one of claims 1, 2, 3, or 4, and these separate dependencies may result in four different embodiments, and so on.

[0136] The description in the claim of the term “First” relating to a feature or element does not necessarily imply the existence of a second or additional such feature or element. Where present, elements specifically described in means-plus-function form are intended to be interpreted in accordance with Section 112(f) of the U.S. Patent Act to encompass the corresponding structures, materials or functions and their equivalents described herein. Embodiments of the Invention for which exclusive ownership or privilege is claimed are defined as follows: (Item 1) A radiation inspection system, A drive mechanism configured to move along the structure, A detector attached to the above-mentioned drive mechanism, A radiation source that is attached to the above-mentioned drive mechanism and can be positioned relative to the detector such that the width of the above-mentioned structure casts a radiation shadow on the active area of ​​the detector, and Combined with the above detector, The detector receives an image from the above detector, Based on the above image, side wall loss information is generated. A radiation inspection system including control logic configured to generate bottom wall loss information based on the above image. (Item 2) The radiation inspection system described in item 1, wherein the control logic described above is further configured to generate upper wall loss information based on the image described above. (Item 3) The radiation inspection system according to item 1, wherein the drive mechanism is configured to rotate the detector and the radiation source at least partially around the structure. (Item 4) The above control logic further, Filter at least a portion of the above image to generate a filtered image. Based on the filtered image described above, at least a portion of the image is normalized to generate a normalized image. The radiographic inspection system according to item 1, configured to scale at least a portion of the normalized image based on the transfer function associated with the above structure. (Item 5) The radiation inspection system according to item 1, wherein at least one of the above-mentioned detector and the above-mentioned radiation source is detachable from the above-mentioned drive mechanism. (Item 6) The radiation inspection system according to item 1, further comprising a positioning system configured to generate location information, wherein the control logic is configured to associate at least one of the image, the side wall loss information, and the bottom wall loss information with the location information. (Item 7) The radiation inspection system according to item 1, wherein the drive mechanism and the detector are configured to move along the side of the structure opposite to the structural support. (Item 8) The radiation inspection system described in item 1, further comprising a power supply attached to the above-mentioned drive mechanism. (Item 9) Further including a communication interface, The radiation inspection system according to item 1, wherein the control logic described above is configured to communicate at least one of the image, the side wall loss data, and the bottom wall loss data via the communication interface described above. (Item 10) A method for operating a radiation inspection system, The drive mechanism, detector, and radiation source are arranged around the structure. Using the detector and radiation source, which include at least the width of the above structure, to generate an image of a section of the above structure, Based on the above image, generate side wall loss information, and A method including generating bottom wall loss information based on the above image. (Item 11) The method according to item 10, wherein the placement of the radiation source includes placing the radiation source at a distance from the structure greater than twice the diameter of the structure. (Item 12) The method according to item 10, further comprising generating upper wall loss information based on the above image. (Item 13) The method according to item 12, further comprising generating wall loss information for the entire perimeter of the above structure based on the above image. (Item 14) Generating the above image of the above section of the above structure includes generating images of the above section of the above structure and of calibrated objects adjacent to the above structure. The method according to item 10, wherein generating loss information for the side wall based on the above image includes generating loss information for the side wall based on a portion of the above image based on the calibrated object adjacent to the above structure. (Item 15) Moving the above detector and the above radiation source along the above structure to the second section of the above structure, In the second section described above, an image of the second section of the structure is generated using the detector and radiation source, which include at least the width of the structure. To generate sidewall loss information based on the image in the second section above, and The method of item 10, further comprising generating bottom wall loss information based on the image in the second section above. (Item 16) The method according to item 10, further comprising rotating the detector and the radiation source around the above structure. (Item 17) To filter at least a portion of the above image of the above structure and generate a filtered image, Based on the filtered image described above, normalize at least a portion of the image to generate a normalized image. The method according to item 10, further comprising scaling at least a portion of the normalized image based on the transfer function associated with the above structure. (Item 18) The method according to item 10, further comprising adjusting the position of the above-mentioned radiation source. (Item 19) A radiation inspection system, Means for generating radiation, A means for generating an image based on the above radiation, coupled to the means for generating the above radiation, Means for moving the means for generating the above radiation, and means for moving the means for generating the above image based on the above radiation, A radiation inspection system comprising means for generating side wall loss information and bottom wall loss information based on the above image. (Item 20) The radiation inspection system according to item 19, wherein the means for generating side wall loss information and bottom wall loss information based on the above image further comprises means for generating top wall loss information based on the above image. (Item 21) To obtain an image of the structure, Filter the above image of the above structure to generate a filtered image. Based on the filtered image above, normalize the image and generate a normalized image, and A method comprising scaling the normalized image based on the transfer function associated with the above structure. (Item 22) The method according to item 221, further comprising generating the transfer function based on the attributes of the above structure. (Item 23) The above transfer function can be generated. To obtain a normalized image of a known defect in a structure that has at least one different attribute, This includes generating the above transfer function based on the above normalized image, The method according to item 222, wherein scaling the normalized image based on the transfer function associated with the above structure comprises providing the above at least one attribute of the structure as input to the transfer function. (Item 24) Scaling the normalized image based on the transfer function associated with the above structure is Scaling the normalized image based on the upper wall transfer function, and The method according to item 221, which includes scaling the normalized image based on the bottom wall transfer function. (Item 25) To obtain the above image of the above structure, The method according to item 221, which includes obtaining the above image of the above structure, including the width of the above structure. (Item 26) The method according to item 221, wherein filtering the image of the above structure to generate the filtered image includes applying a nonlinear digital filter to the image of the above structure. (Item 27) The method according to item 226, further comprising selecting the size of the kernel of the nonlinear digital filter based on the above structure. (Item 28) The method according to item 226, further comprising selecting the size of the kernel of the nonlinear digital filter based on the expected largest defect. (Item 29) The method of item 226, wherein normalizing the above image based on the above filtered image comprises dividing the above image by the above filtered image and subtracting the above filtered image to produce the above normalized image. (Item 30) The method according to item 221, further comprising converting the above-described scaled normalized image into a material loss estimation image showing wall loss greater than a predetermined threshold. (Item 31) Filtering the above image of the above structure to generate a filtered image includes filtering a subset of the above image, The method according to item 221, wherein normalizing the above image based on the above filtered image to generate a normalized image includes normalizing the above subset of the above image based on the above filtered image to generate the above normalized image. (Item 32) It is a system, radiation source, A detector that can be positioned to receive the above radiation, relating to a structure placed between the above radiation source and the above detector, and The control logic comprises, Using the above detector, an image of the above structure is obtained. The above image of the above structure is filtered to generate a filtered image. Based on the filtered image above, the image is normalized to generate a normalized image. A system configured to scale the normalized image based on the transfer function associated with the above structure. (Item 33) The control logic described above is further configured to generate the transfer function described above based on the attributes of the structure described above, as in the system described in item 32. (Item 34) The above control logic is: The system described in item 32, further configured to obtain the above image of the above structure, including the width of the above structure. (Item 35) The control logic described above is further configured to apply a nonlinear digital filter to the above image of the structure, as described in item 32. (Item 36) The control logic described above is further configured to select the size of the kernel of the nonlinear digital filter based on the above structure and at least one of the greatest anticipated defects, as described in item 35. (Item 37) The control logic described above is further configured to divide the above image by the above filtered image and subtract the above filtered image to generate the above normalized image, as described in item 35. (Item 38) The control logic described above is further configured to convert the scaled normalized image into a material loss estimation image showing wall loss greater than a predetermined threshold, as described in item 32. (Item 39) It is a system, Means for obtaining an image of the structure, A means for filtering the above-mentioned image of the above structure and generating a filtered image, Means for normalizing the above filtered image and generating a normalized image, and A system comprising means for scaling the normalized image based on the transfer function associated with the above structure. (Item 40) The system according to item 39, wherein the means for normalizing the above image includes means for dividing the above image by the filtered image and subtracting the filtered image to generate the normalized image.

Claims

1. To obtain an image of the structure, Filtering the image of the aforementioned structure to generate a filtered image, Based on the filtered image, normalize the image and generate a normalized image, and A method comprising scaling the normalized image based on a transfer function associated with the structure.

2. The method according to claim 1, further comprising generating the transfer function based on the attributes of the structure.

3. The method according to claim 1, wherein filtering the image of the structure to generate the filtered image includes applying a nonlinear digital filter to the image of the structure.

4. The method according to claim 3, further comprising selecting the size of the kernel of the nonlinear digital filter based on the above structure.

5. The method according to claim 3, further comprising selecting the size of the kernel of the nonlinear digital filter based on the expected largest defect.

6. To obtain an image of the structure, Filtering the image of the aforementioned structure to generate a filtered image, Based on the filtered image, the image is normalized to generate a normalized image. To generate a transfer function based on the attributes of the aforementioned structure, and This includes scaling the normalized image based on the transfer function associated with the structure, To generate the aforementioned transfer function, To obtain a normalized image of a known defect in a structure having at least one different attribute, and This includes generating the transfer function based on the normalized image, A method for scaling the normalized image based on the transfer function associated with the structure, comprising providing the at least one attribute of the structure as input to the transfer function.

7. To obtain an image of the structure, Filtering the image of the aforementioned structure to generate a filtered image, Based on the filtered image, normalize the image and generate a normalized image, and This includes scaling the normalized image based on the transfer function associated with the structure, A method for normalizing an image based on the filtered image, comprising dividing the image by the filtered image and subtracting the filtered image to generate the normalized image.

8. The structure is a pipe having a bottom wall closest to the detector and an upper wall closest to the radiation source, Scaling the normalized image based on the transfer function associated with the structure is Scaling the normalized image based on the upper wall transfer function, and The method according to any one of claims 1 to 7, comprising scaling the normalized image based on the bottom wall transfer function.

9. To obtain the image of the aforementioned structure, The method according to any one of claims 1 to 7, comprising obtaining an image of the structure including the width of the structure.

10. The method according to any one of claims 1 to 7, further comprising converting the scaled normalized image into a material loss estimation image that shows material loss greater than a predetermined threshold for material loss from the walls of the structure.

11. Filtering the image of the structure to generate a filtered image includes filtering a subset of the image, The method according to any one of claims 1 to 7, wherein generating a normalized image by normalizing the image based on the filtered image includes normalizing the subset of the image based on the filtered image to generate the normalized image.

12. The method according to any one of claims 1 to 7, wherein the transfer function changes according to the attributes of the structure given as input to the transfer function.

13. It is a system, radiation source, A detector that can be positioned to receive radiation relating to a structure placed between the radiation source and the detector, and The control logic comprises, Using the detector, an image of the structure is acquired. The image of the aforementioned structure is filtered to generate a filtered image. Based on the filtered image, the image is normalized to generate a normalized image. A system configured to scale the normalized image based on the transfer function associated with the structure.

14. The system according to claim 13, wherein the control logic is further configured to apply a nonlinear digital filter to the image of the structure.

15. The system according to claim 14, wherein the control logic is further configured to select the size of the kernel of the nonlinear digital filter based on the structure and at least one of the largest expected defects.

16. A system, radiation source, A detector that can be positioned to receive radiation relating to a structure placed between the radiation source and the detector, and The control logic comprises, Using the detector, an image of the structure is acquired. The image of the aforementioned structure is filtered to generate a filtered image. Based on the filtered image, the image is normalized to generate a normalized image. Based on the transfer function associated with the structure, the normalized image is scaled. A system configured to generate a normalized image by dividing the aforementioned image by the filtered image and subtracting the filtered image.

17. The system according to any one of claims 13 to 16, wherein the control logic is further configured to generate the transfer function based on the attributes of the structure.

18. The control logic described above is The system according to any one of claims 13 to 16, further configured to acquire an image of the structure including the width of the structure.

19. The system according to any one of claims 13 to 16, wherein the control logic is further configured to convert the scaled normalized image into a material loss estimate image showing a material loss greater than a predetermined threshold for material loss from the walls of the structure.

20. The system according to any one of claims 13 to 16, wherein the transfer function changes depending on the attributes of the structure given as input to the transfer function.

21. It is a system, Means for obtaining an image of the structure, Means for filtering the image of the aforementioned structure and generating a filtered image, Means for normalizing the image based on the filtered image and generating a normalized image, and A system comprising means for scaling the normalized image based on a transfer function associated with the structure.

22. A system, Means for obtaining an image of the structure, Means for filtering the image of the aforementioned structure and generating a filtered image, Means for normalizing the image based on the filtered image and generating a normalized image, and The means for scaling the normalized image based on the transfer function associated with the structure is included. The means for normalizing the image includes means for dividing the image by the filtered image and subtracting the filtered image to generate the normalized image.

23. The system according to claim 21 or 22, wherein the transfer function changes depending on the attributes of the structure given as input to the transfer function.

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