Aero-engine blade residual core detection method and system based on neutron imaging
By adaptively adjusting neutron imaging parameters and image processing techniques, the problems of noise and background interference in the detection of residual cores in aero-engine blades using neutron imaging technology have been solved, achieving high-quality residual core detection results.
Patent Information
- Application Number
- CN202610785859.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-02
- Publication Date
- 2026-08-25
AI Technical Summary
Existing neutron imaging technology is easily affected by factors such as scattered neutrons, detector noise, and uneven response of the conversion screen in the detection of residual cores in aero-engine blades, resulting in low image signal-to-noise ratio, insufficient contrast, and uneven background, making it difficult to effectively identify residual cores inside the blades.
By adaptively adjusting neutron flux, exposure time, and image acquisition parameters, combined with multi-frame image fusion, dark field correction, flat field correction, non-uniform background correction, and local contrast enhancement processing, image quality is optimized and noise is suppressed, improving the contrast and visibility of the residual core area.
It significantly improves the accuracy and interpretability of detecting residual cores inside aero-engine blades, achieving high-quality imaging and reliable residual core detection.
Smart Images
Figure CN122631676A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of aero-engine blade core detection technology, and more specifically, to a method and system for detecting aero-engine blade cores based on neutron imaging. Background Technology
[0002] Aero-engine blades have complex structures and operate in harsh environments. Residual core defects that may remain from the manufacturing process can significantly impact service reliability and safety, thus necessitating high-precision non-destructive testing. Among existing testing methods, X-ray imaging has good penetration capabilities for high-density materials, but it has low sensitivity to low atomic number materials or light element residues, making it difficult to effectively identify residual cores inside the blades. In contrast, neutron imaging offers a higher imaging contrast advantage for low atomic number materials, showing promising application prospects in the inspection of complex aero-engine structures.
[0003] However, neutron imaging is susceptible to factors such as scattered neutrons, detector noise, and uneven response of the conversion screen, leading to problems such as low signal-to-noise ratio, insufficient contrast, and uneven background, which in turn affect the accuracy and interpretability of the detection results. Existing neutron image processing methods do not adequately consider the noise characteristics of neutron imaging in the post-processing stage, and the processing strategies are mismatched with the physical characteristics of the noise, resulting in limited improvement in image quality, difficulty in effectively identifying residual core regions from complex backgrounds, and insufficient detection reliability.
[0004] Therefore, it is necessary to propose a method and system for detecting residual cores in aero-engine blades based on neutron imaging. Summary of the Invention
[0005] In order to overcome the above-mentioned technical problems, the purpose of this invention is to provide a method and system for detecting residual cores of aero-engine blades based on neutron imaging.
[0006] The objective of this invention can be achieved through the following technical solutions: A method for detecting residual cores in aero-engine blades based on neutron imaging includes the following steps: S1: Fix the aero-engine blade under test on the blade stage, and adaptively adjust the neutron flux, exposure time and image acquisition parameters of the neutron source and the image detector according to the material and structural characteristics of the blade under test. Use the neutron beam generated by the neutron source to illuminate the blade after collimation by the collimator, and acquire multiple frames of original images of neutron transmission through the imaging system. S2: Perform dark field correction and flat field correction on multiple frames of original images to eliminate uneven response of the image detector and background interference; S3: Perform denoising processing on the corrected image based on multi-frame image fusion, and introduce structure preservation constraints during the denoising process to preserve edge and detail information while suppressing noise; S4: Perform non-uniform background correction and contrast enhancement based on local statistical characteristics on the denoised image in sequence to improve the contrast and visibility between the residual core area and the background.
[0007] As a further aspect of the present invention: the image acquisition parameters in S1 include camera gain and the number of multi-frame accumulations, the camera gain is set to 150-300, the number of multi-frame accumulations is 5-10 frames, and the single-frame exposure time is 300 s-1000 s; in S2, dark field correction is achieved by acquiring a background image under neutron-free irradiation conditions, and flat field correction is achieved by acquiring a reference image under uniform neutron irradiation conditions.
[0008] As a further aspect of the present invention: after S2 and before S3, the corrected multi-frame images are cumulatively processed. The cumulative processing adopts the mean superposition or weighted superposition method. Before S3, the single-frame image is also subjected to detail enhancement processing. The detail enhancement processing is achieved by local gradient enhancement or high-frequency component enhancement.
[0009] As a further aspect of the present invention: the denoising process based on multi-frame image fusion in S3 includes: aligning the input multi-frame images with moving blurred pixels, and suppressing noise by using temporal averaging or weighted fusion; introducing inter-frame consistency constraints during the denoising process to remove artifacts caused by scattered neutrons and transient noise.
[0010] As a further aspect of the present invention: the structure preservation constraint in S3 is achieved through gradient constraints.
[0011] As a further aspect of the present invention, the non-uniform background correction in S4 includes: estimating the background distribution using large-scale smoothing filtering, and eliminating the effects of neutron beam inhomogeneity and inconsistent image detector response through background subtraction or normalization processing.
[0012] As a further aspect of the present invention: the contrast enhancement processing based on local statistical characteristics in S4 includes: adaptive contrast enhancement based on the gray-scale statistical characteristics of local regions of the image, and limiting the contrast enhancement factor to 2 to 5 times.
[0013] A neutron imaging-based aero-engine blade core detection system, used to implement the neutron imaging-based aero-engine blade core detection method as described in any of the preceding claims, comprising: A neutron source, used to generate neutron beams; A collimator, located at the output of the neutron source, is used to collimate the neutron beam. A shielding body is disposed around the neutron source and the collimator to shield scattered neutrons and gamma rays; A blade mounting platform, positioned in the direction of the collimator's exit, is used to fix the tested aero-engine blade. An imaging system is disposed on the side of the blade stage away from the collimator, and is used to acquire neutron transmission images. The imaging system includes a scintillator conversion screen, an optical coupling component, and an image detector arranged sequentially along the optical path. The image processing unit is communicatively connected to the image detector. It receives image data acquired by the image detector and sequentially performs dark field and flat field correction, denoising processing based on multi-frame image fusion, and non-uniform background correction and local contrast enhancement to output a neutron image for blade core detection.
[0014] As a further aspect of the present invention: the neutron source is an accelerator neutron source, with an output neutron energy of 2.45 MeV and an adjustable neutron flux range of 10. 6 ~10¹ 0 The collimator has an L / D ratio of 50 to 200, and the shielding body adopts a composite structure of boron-containing polyethylene and lead, with a shielding thickness of 5 to 20 cm.
[0015] As a further aspect of the present invention: the thickness of the scintillator conversion screen is 0.2-1mm, the optical coupling component includes a reflector and an imaging lens, and the image detector is an industrial electronic multiplication CCD camera.
[0016] The beneficial effects of this invention include, but are not limited to: optimizing the quality of the original image from the source by adaptively adjusting the neutron flux, exposure time, and image acquisition parameters according to the material and structural characteristics of the tested blade; by performing moving blur pixel alignment, temporal averaging, or weighted fusion on multiple frames of images, and introducing inter-frame consistency constraints and structure preservation constraints, fully utilizing temporal statistical information to suppress white spot random noise and artifacts caused by scattered neutrons, while effectively preserving the edge and fine residual core structure during the denoising process; by sequentially performing non-uniform background correction and contrast enhancement based on local statistical characteristics on the denoised image, eliminating background interference caused by neutron beam inhomogeneity and detector response inconsistency, and significantly improving the contrast and visibility between low grayscale residual core areas and complex backgrounds, thereby achieving high-quality imaging of residual cores inside aero-engine blades, significantly improving the accuracy and interpretability of the detection results, and ensuring the reliability of residual core detection. Attached Figure Description
[0017] Figure 1 This is a step diagram of the method for detecting residual cores in aero-engine blades based on neutron imaging, which is a practical invention. Figure 2 This is a schematic diagram of the structure of the aero-engine blade core detection system based on neutron imaging according to the present invention; Figure 3This is a schematic diagram of the process of the present invention.
[0018] Explanation of reference numerals in the attached figures: 1. Neutron source; 2. Shielding body; 3. Collimator; 4. Blade stage; 5. Imaging system; 6. Image processing unit. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application are described clearly and completely below with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments described in this application without creative effort will fall within the scope of protection of this application.
[0020] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used in the specification of this application is for the purpose of describing specific embodiments only and is not intended to limit this application; the terms "comprising," "including," "having," "containing," "comprise," etc., in the specification, claims, and accompanying drawings of this application are open-ended terms, indicating that a method comprises one or more steps, or an apparatus comprises one or more elements, but do not exclude the inclusion of other steps or elements. The terms "first," "second," etc., in the specification, claims, or accompanying drawings of this application are used to distinguish different objects, not to describe a specific order or primary / secondary relationship. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.
[0021] In the description of this application, it should be understood that the terms "upper", "lower", "left", "right", "front", "rear", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.
[0022] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "attachment" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0023] See Figures 1-3 An embodiment of the present invention provides a method for detecting residual cores in aero-engine blades based on neutron imaging, comprising the following steps: S1: The aero-engine blade under test is fixed on the blade stage 4. The neutron flux, exposure time, and image acquisition parameters of the image detector of the neutron source 1 are adaptively adjusted according to the material and structural characteristics of the blade under test. The neutron beam generated by the neutron source 1 is collimated by the collimator 3 and then irradiates the blade. The imaging system 5 acquires multiple frames of original images of neutron transmission. After the imaging system acquires multiple frames of original images of neutron transmission, it transmits the image data to the image processing unit 6. The image processing unit 6 performs the following steps in sequence: S2: Dark field correction and flat field correction are performed on the multiple frames of original images to eliminate uneven response of the image detector and background interference; S3: The corrected images are denoised based on multi-frame image fusion, and a structure preservation constraint is introduced in the denoising process to preserve edge and detail information while suppressing noise; S4: The denoised images are sequentially subjected to non-uniform background correction and contrast enhancement based on local statistical characteristics to improve the contrast and visibility between the residual core area and the background; After completing the above processing of S3 to S4, the image processing unit 6 outputs the neutron image for blade residual core detection.
[0024] In this embodiment, the quality of the original image is optimized from the source by adaptively adjusting the neutron flux, exposure time, and image acquisition parameters according to the material and structural characteristics of the tested blade. By performing moving blur pixel alignment, temporal averaging, or weighted fusion on multiple frames of images, and introducing inter-frame consistency constraints and structure preservation constraints, temporal statistical information is fully utilized to suppress random noise in white spots and artifacts caused by scattered neutrons. At the same time, the edges and small residual core structures are effectively preserved during the denoising process. By sequentially performing non-uniform background correction and contrast enhancement based on local statistical characteristics on the denoised image, the background interference caused by neutron beam inhomogeneity and detector response inconsistency is eliminated, and the contrast and visibility between low grayscale residual core areas and complex backgrounds are significantly improved. This achieves high-quality imaging of residual cores inside aero-engine blades, significantly improves the accuracy and interpretability of the detection results, and ensures the reliability of residual core detection.
[0025] See Figure 1 and Figure 3 Optionally, the image acquisition parameters in S1 include camera gain and the number of multi-frame accumulations. The camera gain is set to 150-300, the single-frame exposure time is 300 s-1000 s to avoid overexposure or underexposure, and the number of multi-frame accumulations is 5-10 frames to improve statistical stability. In S2, dark field correction is achieved by acquiring a background image under neutron-free irradiation conditions, and flat field correction is achieved by acquiring a reference image under uniform neutron irradiation conditions.
[0026] See Figure 1 and Figure 3 Optionally, after S2 and before S3, the corrected multi-frame images are accumulated. The accumulation processing adopts the mean superposition or weighted superposition method to improve the signal-to-noise ratio and reduce random noise. Before S3, the single-frame image is also subjected to detail enhancement processing. The detail enhancement processing is achieved by local gradient enhancement or high-frequency component enhancement to improve the response of the small residual core structure.
[0027] In this embodiment, the single-frame detail enhancement processing can use local windows (5×5, 7×7) to calculate the local contrast of the image and adaptively stretch low-contrast areas.
[0028] See Figure 1 and Figure 3 Optionally, the denoising process based on multi-frame image fusion in S3 includes: aligning the input multi-frame images with moving blurred pixels and suppressing noise using temporal averaging or weighted fusion; and introducing inter-frame consistency constraints during the denoising process to remove artifacts caused by scattered neutrons and transient noise.
[0029] See Figure 1 and Figure 3Optionally, the structure preservation constraint in S3 is achieved through gradient constraints to prevent the fine residual core structure from being smoothed.
[0030] See Figure 1 and Figure 2 Optionally, the non-uniform background correction in S4 includes: estimating the background distribution using large-scale smoothing filtering (Gaussian kernel size 15×15~51×51), and eliminating the effects of neutron beam inhomogeneity and inconsistent image detector response through background subtraction or normalization.
[0031] See Figure 1 and Figure 3 Optionally, the contrast enhancement processing based on local statistical characteristics in S4 includes: adaptive contrast enhancement based on the gray-scale statistical characteristics of local regions of the image, and limiting the contrast enhancement factor to 2 to 5 times.
[0032] Specifically, this method includes fixing the blade to be tested on the stage during the detection process, adjusting the relative positions of the neutron source 1, collimator 3 and detector so that the neutron beam covers the target area, and setting the exposure time and the number of acquisition frames.
[0033] Multiple frames of raw neutron image sequences were obtained through continuous acquisition. Let the i-th frame be... ,in For spatial coordinates, the number of acquisition frames is... .
[0034] Accumulation processing of multiple frames of images to improve the signal-to-noise ratio can be expressed in its basic form as follows:
[0035] in This is the accumulated image. This processing effectively reduces random noise, and its noise variance decreases as the number of frames increases.
[0036] Before multi-frame fusion, detail enhancement processing is performed on the individual frame images. This is achieved by extracting high-frequency components of the image to enhance detail information, for example:
[0037] in, This represents the Gaussian smoothing operator. This is an enhancement factor. This method can highlight edges and fine structures.
[0038] In the denoising process, structure preservation constraints are introduced, such as adjustments based on gradient information:
[0039] in, Represents the gradient operator, These are weighting coefficients used to balance noise reduction and detail preservation.
[0040] Non-uniform background correction is performed on the denoised image. First, a background estimate is obtained through large-scale smoothing. Then, normalization is performed:
[0041] in To prevent the use of tiny constants with a denominator of zero, this step can effectively eliminate the effects of uneven irradiation.
[0042] Based on background correction, local contrast enhancement processing is performed, for example, by using local statistical normalization:
[0043] in and These represent the local mean and standard deviation, respectively, thereby improving the contrast between low-grayscale areas and the background.
[0044] See also Figures 1-3 Another embodiment of the present invention provides a neutron imaging-based aero-engine blade core detection system for use with any of the neutron imaging-based aero-engine blade core detection methods described above, comprising: a neutron source 1 for generating a neutron beam; a collimator 3 disposed at the output end of the neutron source 1 for collimating the neutron beam; a shield 2 disposed around the neutron source 1 and the collimator 3 for shielding scattered neutrons and gamma rays; a blade stage 4 disposed in the exit direction of the collimator 3 for fixing the aero-engine blade under test; and an imaging system 5 disposed at the blade stage. The stage 4, located away from the collimator 3, is used to acquire neutron transmission images. The imaging system 5 includes a scintillator conversion screen, an optical coupling component, and an image detector arranged sequentially along the optical path. Neutrons are converted into visible light signals by the scintillator and transmitted to the image detector for acquisition via the optical coupling component. The image processing unit 6 is communicatively connected to the image detector and is used to receive the image data acquired by the image detector. It sequentially performs dark field and flat field correction, denoising processing based on multi-frame image fusion, and non-uniform background correction and local contrast enhancement to output a neutron image for blade core detection.
[0045] In this embodiment, the neutron source 1, shield 2, collimator 3, blade stage 4, and imaging system 5 are arranged sequentially along the neutron propagation direction to ensure the stability of the imaging link and maintain coaxial alignment of the neutron propagation path, thereby reducing the impact of geometric distortion on the imaging results. The modules are connected via standard interfaces for easy installation, debugging, and subsequent maintenance. In the system layout, the distances between the neutron source 1 and collimator 3, between the collimator 3 and the blade under test, and between the blade and imaging system 5 are all optimized to balance imaging resolution and neutron flux utilization efficiency. Furthermore, the system is equipped with an environmental protection structure to reduce the impact of external vibration, electromagnetic interference, and temperature changes on imaging stability, thereby ensuring the repeatability and reliability of the detection process. The environmental protection structure includes a vibration-damping support platform, an electromagnetic shielding shell, and a temperature control device. The vibration-damping support platform reduces the impact of external mechanical vibration on imaging stability; the electromagnetic shielding shell reduces external electromagnetic interference; and the temperature control device maintains a stable operating temperature for the imaging system 5.
[0046] Specifically, neutron source 1 generates a neutron beam, which is collimated by collimator 3 and then irradiates the tested aero-engine blade. After the neutrons penetrate the blade, the scintillator conversion screen in imaging system 5 converts the neutron signal into a visible light signal. Subsequently, it is transmitted to the image detector through an optical coupling component for image acquisition. The acquired raw image data is transmitted to the host computer of image processing unit 6, and processed by the image processing module of image processing unit 6 based on a preset algorithm. Finally, the detection image is output.
[0047] It should be noted that this system generates a stable and collimated neutron beam through the coordinated configuration of neutron source 1 and collimator 3. The shield 2 effectively shields scattered neutrons and gamma rays, reducing background noise and protecting the imaging detector. The blade stage 4 stably fixes and precisely positions the blades, ensuring positional consistency during multi-frame imaging. The sequential arrangement of the scintillator conversion screen, optical coupling components, and image detector along the optical path in the imaging system 5 achieves efficient neutron-visible light-electric signal conversion and acquisition. The image processing unit 6 sequentially processes the image data, forming a complete capability from raw data acquisition to final detection image output. Through the above structural design, a stable and continuous neutron imaging process can be achieved, providing a stable and reliable hardware platform for the implementation of the aforementioned detection method. This approach balances imaging resolution and neutron flux utilization efficiency, achieving integrated optimization from imaging hardware configuration to image processing, and ensuring the repeatability and reliability of the detection process.
[0048] Preferably, the blade stage 4 employs a multi-degree-of-freedom adjustable mechanism, including a horizontal movement component, a vertical lifting component, and an angle adjustment component, to achieve precise control over the blade's position and attitude. The stage can be manufactured using high-rigidity materials, such as aluminum alloy or stainless steel, to improve overall stability and reduce the impact of vibration. To ensure positional consistency during multi-frame imaging, the stage can be equipped with a locking mechanism to fix each degree of freedom after position adjustment, thereby preventing displacement during acquisition. Furthermore, the stage can be configured with positioning marks or reference scales to assist in rapid blade clamping and repeated positioning. Preferably, the stage positioning accuracy can be controlled within 0.1 mm to meet the requirements of high-resolution neutron imaging. Through the above structural design, not only can the stability of the imaging process be improved, but also image blurring and artifacts caused by positional shifts can be reduced, thus providing a reliable data foundation for subsequent multi-frame fusion and denoising processing.
[0049] Optionally, neutron source 1 is an accelerator neutron source with an output neutron energy of 2.45 MeV and an adjustable neutron flux range of 10. 6 ~10¹ 0 To meet the detection requirements of blades with different thicknesses, the collimator 3 has an L / D ratio of 50 to 200. The shield 2 adopts a composite structure of boron-containing polyethylene and lead to reduce the interference of scattered neutrons and gamma rays on the detector. Its shield thickness is 5 to 20 cm.
[0050] In this embodiment, the accelerator neutron source is preferably an inductively coupled accelerator neutron source.
[0051] Optionally, the thickness of the scintillator conversion screen is 0.2 to 1 mm, balancing spatial resolution and detection efficiency. The optical coupling components include a reflector and an imaging lens. The image detector is an industrial electronic multiplication CCD camera, and the imaging lens is an industrial lens with a focal length of 25 mm to 85 mm.
[0052] In this embodiment, the reflector is preferably set as a 45° reflector to change the direction of light propagation, so as to reduce the direct impact of neutron radiation on the image detector. The imaging lens is used to focus the visible light signal generated by the scintillator onto the photosensitive surface of the image detector.
[0053] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.
Claims
1. A method for detecting residual cores in aero-engine blades based on neutron imaging, characterized in that, Includes the following steps: S1: Fix the test aero-engine blade on the blade stage (4), and adaptively adjust the neutron flux, exposure time and image acquisition parameters of the neutron source (1) and the image detector according to the material and structural characteristics of the test blade. Use the neutron beam generated by the neutron source (1) to collimate the blade after collimation by the collimator (3), and acquire multiple frames of original images of neutron transmission through the imaging system (5). S2: Perform dark field correction and flat field correction on multiple frames of original images to eliminate uneven response of the image detector and background interference; S3: Perform denoising processing on the corrected image based on multi-frame image fusion, and introduce structure preservation constraints during the denoising process to preserve edge and detail information while suppressing noise; S4: Perform non-uniform background correction and contrast enhancement based on local statistical characteristics on the denoised image in sequence to improve the contrast and visibility between the residual core area and the background.
2. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, In S1, the image acquisition parameters include camera gain and the number of multi-frame accumulations. The camera gain is set to 150-300, the number of multi-frame accumulations is 5-10 frames, and the single-frame exposure time is 300 s-1000 s. In S2, dark field correction is achieved by acquiring a background image under neutron-free conditions, and flat field correction is achieved by acquiring a reference image under uniform neutron irradiation conditions.
3. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, After S2 and before S3, the corrected multi-frame images are accumulated. The accumulation process adopts the mean superposition or weighted superposition method. Before S3, the single-frame image is also enhanced in detail. The detail enhancement is achieved by local gradient enhancement or high-frequency component enhancement.
4. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, The denoising process based on multi-frame image fusion in S3 includes: moving and blurring pixel alignment of the input multi-frame images, and using temporal averaging or weighted fusion to suppress noise; introducing inter-frame consistency constraints during the denoising process to remove artifacts caused by scattered neutrons and transient noise.
5. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, In S3, the structure preservation constraint is achieved through gradient constraints.
6. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, Non-uniform background correction in S4 includes: estimating the background distribution using large-scale smoothing filtering, and eliminating the effects of neutron beam inhomogeneity and inconsistent image detector response through background subtraction or normalization.
7. The method for detecting residual core of aero-engine blades based on neutron imaging according to claim 1, characterized in that, The contrast enhancement processing based on local statistical characteristics in S4 includes: adaptive contrast enhancement based on the gray-level statistical characteristics of local regions of the image, and limiting the contrast enhancement factor to 2 to 5 times.
8. A neutron imaging-based aero-engine blade core detection system, used to implement the neutron imaging-based aero-engine blade core detection method according to any one of claims 1-7, characterized in that, include: Neutron source (1), which is used to generate neutron beams; A collimator (3) is disposed at the output end of the neutron source (1) and is used to collimate the neutron beam; A shield (2) is disposed around the neutron source (1) and the collimator (3) to shield scattered neutrons and gamma rays; The blade mounting platform (4) is positioned in the firing direction of the collimator (3) and is used to fix the tested aero-engine blade. An imaging system (5) is set on the side of the blade stage (4) away from the collimator (3) and is used to acquire neutron transmission images. The imaging system (5) includes a scintillator conversion screen, an optical coupling component and an image detector arranged sequentially along the optical path. The image processing unit (6) is connected in communication with the image detector and is used to receive the image data collected by the image detector and sequentially perform dark field and flat field correction, noise reduction processing based on multi-frame image fusion, and non-uniform background correction and local contrast enhancement to output a neutron image for blade core detection.
9. The aero-engine blade core detection system based on neutron imaging according to claim 8, characterized in that, The neutron source (1) is an accelerator neutron source with an output neutron energy of 2.45 MeV and an adjustable neutron flux range of 10. 6 ~10¹ 0 The collimator (3) has an L / D ratio of 50 to 200, and the shield (2) adopts a composite structure of boron-containing polyethylene and lead, with a shielding thickness of 5 to 20 cm.
10. The aero-engine blade core detection system based on neutron imaging according to claim 8, characterized in that, The thickness of the scintillator conversion screen is 0.2-1mm, the optical coupling assembly includes a reflector and an imaging lens, and the image detector is an industrial electronic multiplication CCD camera.