Graphite felt closed type compression device and graphite felt detection method applied to graphite felt closed type compression device

Abstract

The invention discloses a graphite felt closed compression device and a graphite felt detection method applied to the graphite felt closed compression device. Wherein the graphite felt closed compression device comprises a cavity, a pressing plug and a cover body, the cavity is provided with an opening, and the cavity is made of an X-ray penetrable material; the cover body shields the opening and is in threaded connection with the cavity; the pressing plug is located in the cavity and can reciprocate in the preset direction relative to the cavity, the end, in the preset direction, of the pressing plug and the cavity define a containing space capable of containing the graphite felt, and the other end, in the preset direction, of the pressing plug corresponds to the cover body. The cover body can synchronously and linearly move towards the pressing plug so as to correspondingly abut against the pressing plug, or the cover body can synchronously and linearly move back to the pressing plug so as to correspondingly abut against or loosen the pressing plug, so that the cover body can drive the pressing plug to compress the graphite felt in the rotating process; it is guaranteed that the graphite felt of the graphite felt closed type compression device is detected under different compression ratios, and continuous compression can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of closed compression devices, and in particular to a graphite felt closed compression device and a graphite felt detection method applied thereto. Background Art

[0002] With the rapid growth of renewable energy capacity, such as wind power and photovoltaics, the demand for long-term energy storage (generally more than four hours) is becoming increasingly prominent. Flow batteries, due to their scalability, safety, and long cycle life, are considered an ideal choice for regulating grid fluctuations and improving energy efficiency. The active surface area and electrochemical stability of the electrode material directly determine the power density, energy efficiency, and service life of the vanadium battery. Among the many carbon and metal materials, felt electrodes, such as graphite felt and carbon felt, are widely used as electrode materials in commercial vanadium batteries due to their strong corrosion resistance, good conductivity, large specific surface area, high mechanical strength, and low cost.

[0003] First, the structure of the porous electrode is crucial to the transport of active materials and the impact on resistance within the battery. To reduce the battery's resistance during operation, the compression ratio needs to be increased to enhance contact between the porous fibers, thereby reducing the electrode's electronic resistance. However, excessively high compression ratios often result in smaller electrode pores, increasing the battery's transport resistance. This, on the one hand, affects the transport of active materials and increases concentration polarization. On the other hand, it increases pump power losses at the inlet and outlet, affecting pump power efficiency. Therefore, the compression state of the porous structure (such as the compression ratio) significantly affects electrolyte mass transfer and reaction kinetics.

[0004] Secondly, when the porous electrodes are assembled in the battery, the different forces inside the battery lead to different compression rates of the electrodes in different places. For example, when the battery stack is assembled, the pressure close to the bolts is often relatively large, and the electrode compression is more obvious, while the porous electrodes in the central area of ​​the battery stack away from the bolts are less compressed, and some areas are even in a semi-constrained free state. This non-uniform deformation urgently needs to be studied so as to optimize the mechanical structure of the liquid flow battery and improve battery performance.

[0005] In addition, more and more flow field battery structures are being adopted. In flow field batteries, the flow field consists of two parts: ribs and flow channels. The electrodes above the ribs are squeezed. Part of the electrode above the flow channel may be squeezed into the flow channel. This non-uniform deformation will also have a significant impact on the distribution of active materials and battery resistance. Understanding the specific conditions of the deformation is crucial for optimizing the flow channel structure and thus improving battery performance. However, there is currently a lack of corresponding graphite felt compression devices. Summary of the Invention

[0006] The compressibility and non-uniform deformation of porous electrodes have a significant impact on battery performance. Obtaining information about the electrode structure of flow batteries at different compression rates is crucial for optimizing the component design and mechanical design of batteries. Existing methods for adjusting the compression rate of compressed graphite felt CT scanning devices include: (1) using gaskets to increase or decrease the number of stacked metal or polyethylene naphthalate sheets that are not easily deformed. This method is highly complex to operate, and the thickness of the gasket is fixed, making it impossible to achieve continuous compression of the graphite felt. (2) adjusting the compression rate by changing the thickness of the contact area between the device and the graphite felt. In this method, each set of devices corresponds to only one compression rate, so if you want to obtain data at different compression rates, you need to process more devices, which increases the cost and complexity of the operation. (3) adjusting the compression rate by replacing graphite felts of different thicknesses or by changing the number of stacked graphite felts. This method requires the use of more graphite felts, cannot avoid the differences between different graphite felts, and cannot achieve continuous adjustment of the compression rate. The enclosed graphite felt compression device of this application adjusts the compression rate simply by rotating the lid, with the degree of rotation being continuously adjustable. The compression displacement is directly proportional to the degree of lid rotation, thus achieving continuous adjustment of the compression rate. Compared to existing devices, the device of this application offers advantages including continuous adjustability of the graphite felt compression rate.

[0007] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a graphite felt closed compression device and a graphite felt detection method applied thereto.

[0008] In a first aspect, an embodiment of the present invention provides a graphite felt closed compression device, comprising: A cavity, wherein the cavity is provided with an opening and the material of the cavity is a material transparent to X-rays; a cover body, the cover body covering the opening and being threadedly connected to the cavity; A pressing plug is located in the cavity and is capable of reciprocating along a preset direction relative to the cavity, one end of the pressing plug along the preset direction and the cavity enclose an accommodating space for accommodating graphite felt, and the other end of the pressing plug along the preset direction is correspondingly arranged with the cover body; During the rotation of the cover body relative to the cavity body, the cover body can synchronously move linearly toward the press plug to correspondingly abut against the press plug, or the cover body can synchronously move linearly away from the press plug to correspondingly abut against or release the press plug.

[0009] Optionally, the cover body includes a groove body and a boss portion, the inner circumferential surface of the groove body is provided with an internal thread, and the boss portion is provided on the inner bottom surface of the groove body and protrudes relative to the inner bottom surface of the groove body; The cavity is provided with an external thread on the outer peripheral surface of one end of the opening, which extends into the groove body and the external thread cooperates with the internal thread. The boss portion extends into the cavity along the opening and abuts against the plug.

[0010] Optionally, the cavity has an upper limit mark for indicating the capacity of the graphite felt, the graphite felt capacity in the cavity is lower than or equal to the upper limit mark, and at the initial moment when the cover body is threadedly engaged with the cavity, the cover body and the press plug are separated from each other or just in contact.

[0011] Optionally, the cavity has a position mark for indicating the maximum compression position of the plunger, wherein the depth a of the groove body, the length b of the plunger along the preset direction, the distance c between the inner bottom end of the cavity and the position mark, and the distance H between the inner bottom surface of the cavity and the opening satisfy: a+b+c>H.

[0012] Optionally, the axial length of the external thread is greater than or equal to the axial length of the internal thread.

[0013] Optionally, the X-ray transparent material comprises plastic; and / or The material of the plug is also the X-ray transparent material; and / or The cover is also made of the X-ray transparent material.

[0014] Optionally, the surface of the end of the press plug close to the accommodating space is a smooth surface; or One or more flow channels are provided on a surface of the press plug at one end close to the accommodating space; or One or more raised ribs are provided on a surface of the press plug at one end close to the accommodating space.

[0015] Optionally, a portion of the side wall of the cavity is configured as a thinned wall, and at least a portion of the thinned wall is located on the side of the accommodating space.

[0016] Optionally, the outer surface of the thinned wall is flush with the outer surface of the side wall of the cavity, or is recessed relative to the outer surface of the side wall of the cavity, and the inner surface of the thinned wall is recessed relative to the inner surface of the side wall of the cavity.

[0017] Optionally, the side wall of the cavity is provided with a through hole, the through hole penetrates the side wall of the cavity along the thick wall direction of the side wall of the cavity, and the through hole is located on the side of the accommodating space; A film is wrapped around the outer circumference of the cavity, and the film closes the through hole.

[0018] Optionally, the cavity includes a bottom wall and a circumferential side wall, the bottom wall is arranged at one end of the circumferential side wall, the other end of the circumferential side wall forms the opening, the bottom wall, a portion of the circumferential side wall and the press plug form the accommodating space; the thickness of the bottom wall is greater than the thickness of the circumferential side wall.

[0019] In a second aspect, an embodiment of the present invention provides a graphite felt detection method applied to a graphite felt closed compression device. The graphite felt detection method applied to the graphite felt closed compression device is applied to the graphite felt closed compression device as described above. The graphite felt detection method applied to the graphite felt closed compression device includes: If the graphite felt is in an extruded state, obtaining a CT image of the graphite felt in the extruded state; determining a CT scanning mode of the graphite felt according to the CT image; The graphite felt closed compression device is tested according to the CT scanning mode to obtain a plurality of fiber images of the graphite felt; wherein the compression rates corresponding to the plurality of fiber images are different; determining a change region corresponding to the graphite felt according to the plurality of fiber images; The performance grade of the graphite felt is determined according to the change area corresponding to the graphite felt.

[0020] Optionally, if the graphite felt is in an extruded state, obtaining a CT image of the graphite felt in the extruded state includes: If the graphite felt is in an extruded state by the plug, the rotation angle of the cover relative to the cavity is determined, and the compression rate of the graphite felt is determined according to the rotation angle of the cover relative to the cavity, the specifications of the plug, and the specifications of the cavity; Determine the initial compression shape of the graphite felt according to the compression rate of the graphite felt and the model of the graphite felt; Based on the preliminary compression shape of the graphite felt and the model of the CT scanning device, the CT scanning mode corresponding to the graphite felt is determined; Based on the CT scanning mode, the CT scanning device is controlled to scan the graphite felt to obtain a CT image of the graphite felt in a compressed state.

[0021] Optionally, determining the CT scanning mode of the graphite felt according to the CT image includes: determining a plurality of morphological characteristics of the graphite felt based on the CT image; The CT scanning mode of the graphite felt is determined according to the multiple morphological features, the detection position of the graphite felt and the specification information of the graphite felt.

[0022] Optionally, determining multiple morphological features of the graphite felt based on the CT image includes: Divide the CT image into multiple morphological regions; For each morphological region, identifying the morphological region and determining the morphological features of the morphological region; The morphological features corresponding to the multiple morphological regions are used to determine multiple morphological features of the graphite felt.

[0023] Optionally, determining the CT scanning mode of the graphite felt according to the multiple morphological features, the detection position of the graphite felt, and the specification information of the graphite felt includes: determining a first mode coefficient based on the plurality of morphological features and a detection position of the graphite felt; determining a second mode coefficient based on the plurality of morphological features and the model of the graphite felt; The CT scanning mode of the graphite felt is determined based on the first mode coefficient, the second mode coefficient and a preset CT scanning mode matching table, wherein the CT scanning mode includes the following modes: local detection scanning mode, overall detection scanning mode or directional detection scanning mode.

[0024] Optionally, the detecting the graphite felt closed compression device according to the CT scanning mode to obtain a plurality of fiber images of the graphite felt includes: Based on the CT scanning mode, the CT scanning device is controlled to detect the graphite felt closed compression device; During the testing process, the state nodes of graphite felt at different compression rates are determined; The CT scanning device is controlled to detect the closed compression device of the graphite felt when the graphite felt is at state nodes with different compression rates, so as to obtain fiber images of the graphite felt at different compression rates.

[0025] Optionally, determining the change region corresponding to the graphite felt according to the multiple fiber images includes: A plurality of fiber images with different compression rates are compared to determine a change portion between the plurality of fiber images, and an area corresponding to the change portion is determined as a change area corresponding to the graphite felt.

[0026] Optionally, determining the performance level of the graphite felt according to the change area corresponding to the graphite felt includes: Determining a plurality of change parameters of the graphite felt according to the change area corresponding to the graphite felt; For each change parameter, determining a state diagram corresponding to the change parameter according to the change parameter; Determining a state distribution diagram of the graphite felt based on the state schematic diagrams corresponding to the multiple change parameters; The performance grade of the graphite felt is determined according to the state distribution diagram of the graphite felt.

[0027] Optionally, determining a plurality of change parameters of the graphite felt according to the change area corresponding to the graphite felt includes: For each change region, determining a region detection mode corresponding to the change region according to the position, shape, and corresponding compression rate of the change region, and determining a change parameter of the change region according to the change region and the region detection mode corresponding to the change region; The change parameters of all the change areas are taken as multiple change parameters of the graphite felt.

[0028] Optionally, determining the state schematic diagram corresponding to the change parameter according to the change parameter includes: According to the change parameter, the shape of the graphite felt and the compression rate of the graphite felt, a state schematic diagram corresponding to the change parameter is determined.

[0029] Optionally, determining the state distribution diagram of the graphite felt based on the state schematic diagrams corresponding to the multiple change parameters respectively includes: The state schematic diagrams corresponding to the multiple change parameters are placed in the same schematic diagram frame for synthesis to determine the state distribution diagram of the graphite felt, and multiple state parameters of the graphite felt at different compression rates are marked in the state distribution diagram of the graphite felt.

[0030] Optionally, determining the performance level of the graphite felt according to the state distribution diagram of the graphite felt includes: determining a first-level coefficient according to a plurality of state parameters of the graphite felt at different compression rates and compression morphologies of the graphite felt at different compression rates; determining a second level coefficient according to a plurality of state parameters of the graphite felt at different compression rates and a plurality of compression rates corresponding to the graphite felt; The performance grade of the graphite felt is determined based on the first grade coefficient, the second grade coefficient and a preset performance grade mapping relationship.

[0031] Compared with the prior art, the present invention has the following beneficial effects: In an embodiment of the present invention, the cavity is provided with an opening, and the material of the cavity is an X-ray transparent material; the cover body covers the opening and is threadedly connected to the cavity; the plug is located in the cavity and can reciprocate relative to the cavity in a preset direction, one end of the plug along the preset direction and the cavity form a accommodating space that can be used to accommodate graphite felt, and the other end of the plug along the preset direction is arranged corresponding to the cover body. During the rotation of the cover body relative to the cavity, the cover body can synchronously move linearly toward the plug to correspondingly abut against the plug, or the cover body can synchronously move linearly away from the plug to correspondingly abut against or release the plug, so that the cover body drives the plug to compress the graphite felt during rotation, ensuring that the graphite felt of the closed graphite felt compression device is detected at different compression rates, and can achieve continuous compression, with high convenience and high clarity. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 1 is a flow chart of a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 2 1 is a flow chart of step S11 in a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 3 1 is a flow chart of step S12 in a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 4 1 is a flow chart of step S13 in a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 5 1 is a flow chart of step S14 in a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 6 1 is a flow chart of step S15 in a graphite felt detection method applied to a graphite felt closed compression device in an embodiment of the present invention; Figure 7 A schematic diagram of a closed graphite felt compression device according to an embodiment of the present application is shown.

[0033] Figure 8 A cross-sectional view of a graphite felt closed compression device according to one embodiment of the present application is shown.

[0034] Figure 9 Shown Figure 8 A partial enlarged view of point A in the middle.

[0035] Figure 10 A dimension diagram of a closed graphite felt compression device according to an embodiment of the present application is shown.

[0036] Figure 11 A schematic diagram showing a smooth surface of a press plug of a graphite felt closed compression device according to an embodiment of the present application is shown.

[0037] Figure 12 A schematic diagram showing a flow channel on the surface of a press plug of a closed graphite felt compression device according to an embodiment of the present application is shown.

[0038] Figure 13 A schematic diagram showing ribs on the surface of a press plug of a closed graphite felt compression device according to an embodiment of the present application.

[0039] Figure 14 A cross-sectional view of a cavity of a graphite felt closed compression device according to an embodiment of the present application is shown.

[0040] Figure 15 A schematic diagram of a cavity of a graphite felt closed compression device according to an embodiment of the present application is shown.

[0041] Reference numerals: 100. Graphite felt closed compression device; 10. Cavity; 10a. Opening; 10b. Through hole; 11. External thread; 12. Thinned wall; 13. Guide groove; 20. Cover body; 21. Groove body; 211. Internal thread; 22. Boss portion; 30. Press plug; 31. Guide arm. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0043] Please refer to the attached Figures 1 to 15 The embodiment of the present application provides a graphite felt closed compression device 100 and a graphite felt detection method applied to the graphite felt closed compression device. The graphite felt closed compression device 100 detects graphite felt at different compression rates.

[0044] Please refer to the attached Figures 7 to 15In the embodiment of the present application, the graphite felt closed compression device 100 includes a cavity 10, a cover 20 and a pressure plug 30. The cavity 10 is provided with an opening 10a, and the material of the cavity 10 is X-ray transparent material; the cover 20 covers the opening 10a and is threadedly connected to the cavity 10; the pressure plug 30 is located in the cavity 10 and can reciprocate relative to the cavity 10 in a preset direction. One end of the pressure plug 30 in the preset direction and the cavity 10 form a storage space for accommodating graphite felt, and the other end of the pressure plug 30 in the preset direction is connected to the cavity 10. The cover body 20 is correspondingly arranged. During the rotation of the cover body 20 relative to the cavity 10, the cover body 20 can synchronously move linearly toward the pressure plug 30 to correspondingly abut against the pressure plug 30, or the cover body 20 can synchronously move linearly away from the pressure plug 30 to correspondingly abut against or release the pressure plug 30, so that the cover body 20 drives the pressure plug 30 to compress the graphite felt during the rotation process, ensuring that the graphite felt of the graphite felt closed compression device 100 is tested at different compression rates and can achieve continuous compression, with high convenience and high clarity. Optionally, when the graphite felt closed compression device 100 is placed in the up and down direction, the preset direction is the up and down direction; the other end of the pressure plug 30 along the preset direction is arranged corresponding to the cover body 20, and the upper end of the pressure plug 30 can contact the inner wall of the cover body 20 facing the cavity 10.

[0045] Please refer to the attached Figures 7 to 15 In the embodiment of the present application, the cavity 10 is provided with an opening 10a, which is located at the upper end of the cavity 10, so that the graphite felt can enter or leave the cavity 10 through the opening 10a. The material of the cavity 10 is an X-ray transparent material; The cover 20 covers the opening 10 a and is threadedly connected to the cavity 10 , so as to facilitate adjustment of the upper and lower positions of the cover 20 relative to the cavity 10 .

[0046] The plug 30 is located in the cavity 10 and can reciprocate in a preset direction relative to the cavity 10. One end of the plug 30 along the preset direction and the cavity 10 form an accommodating space that can be used to accommodate graphite felt. The other end of the plug 30 along the preset direction is arranged corresponding to the cover body 20. During the rotation of the cover body 20 relative to the cavity 10, the cover body 20 can synchronously move linearly toward the plug 30 to correspondingly abut against the plug 30, or the cover body 20 can synchronously move linearly away from the plug 30 to correspondingly abut against or release the plug 30, so that the cover body 20 drives the plug 30 to compress the graphite felt during the rotation process, thereby ensuring that the graphite felt of the graphite felt closed compression device 100 is tested under different compression rates.

[0047] Please refer to the attached Figures 7-9 In the embodiment of the present application, the cover body 20 includes a groove body 21 and a boss portion 22. The inner circumferential surface of the groove body 21 is provided with an internal thread 211. The boss portion 22 is provided on the inner bottom surface of the groove body 21 and protrudes relative to the inner bottom surface of the groove body 21. The cavity 10 is provided with an external thread 11 on the outer peripheral surface of one end of the opening 10a, which extends into the groove body 21 and cooperates with the internal thread 211 to realize the threaded connection between the cover body 20 and the cavity 10, so as to facilitate the cover body 20 to adjust the height position relative to the cavity 10 during the rotation process. The boss portion 22 extends into the cavity 10 along the opening 10a and abuts against the press plug 30, so that the boss portion 22 drives the press plug 30 to compress the graphite felt, ensuring that the graphite felt of the graphite felt closed compression device 100 is tested under different compression rates.

[0048] Please refer to the attached Figures 7-9 In this embodiment of the present application, the cavity 10 has an upper limit mark for indicating the graphite felt capacity. The graphite felt capacity in the cavity 10 is less than or equal to the upper limit mark. At the initial moment when the cover 20 is threadedly engaged with the cavity 10, the cover 20 and the press plug 30 are separated from each other or just in contact. At this time, the upper limit mark is used to preliminarily define the capacity, so that the difference between the graphite felt capacity in the cavity 10 and the upper limit mark of the graphite felt capacity can be intuitively compared. Optionally, the upper limit mark refers to the height of the ink layer in the unpressurized state.

[0049] Please refer to the attached Figure 10 In the embodiment of the present application, the cavity 10 has a position mark for indicating the maximum compression position of the pressure plug 30, wherein the depth a of the groove body 21, the length b of the pressure plug 30 along the preset direction, the distance c between the inner bottom end of the cavity 10 and the position mark, and the distance H between the inner bottom surface of the cavity 10 and the opening 10a satisfy: a+b+c>H, and the axial length of the external thread 11 is greater than or equal to the axial length of the internal thread 211, so as to facilitate the threaded engagement between the cover body 20 and the cavity 10. At the same time, the peripheral side wall of the pressure plug 30 is provided with a guide arm 31, and the inner side wall of the cavity 10 is provided with a guide groove 13. The guide arm 31 and the guide groove 13 form a guiding connection structure to facilitate the installation of the pressure plug 30 relative to the cavity 10, ensure the movement stability of the pressure plug 30, and improve the position accuracy of the pressure plug 30.

[0050] As an embodiment of the present application, in order to perform effective CT tomography scanning, the material of the cavity 10 should not have a strong absorption effect on X-rays during the CT scanning process, that is, the material of the cavity 10 should be X-ray transparent. Optionally, the X-ray transparent material includes plastic. The material of the plug 30 is also plastic, and the material of the cover 20 is also plastic to facilitate scanning of the graphite felt. Furthermore, the plastic includes acrylic and polypropylene. Optionally, when the cover 20 is designed as a hexagon, the magnitude of the compression torque is displayed using a torque-measuring wrench.

[0051] In another embodiment of the present application, the material of the press plug 30 is also the X-ray transparent material, and the X-ray transparent material is acrylic or polypropylene, so as to facilitate scanning of the graphite felt.

[0052] In another embodiment of the present application, the cover 20 is also made of the X-ray transparent material, and the X-ray transparent material is acrylic or polypropylene, so as to facilitate scanning of the graphite felt.

[0053] It should be noted that the above embodiments encompass eight combinations. For example, the X-ray transparent material is acrylic, the tampon 30 is acrylic, and the cover 20 is also made of acrylic. The X-ray transparent material is polypropylene, the tampon 30 is polypropylene, and the cover 20 is also made of polypropylene. The X-ray transparent material is acrylic, the tampon 30 is acrylic, and the cover 20 is also made of polypropylene. Other combinations are not listed here.

[0054] Please refer to the attached Figure 11 In the embodiment of the present application, the surface of the pressing plug 30 at one end close to the accommodating space is a smooth surface; so that the pressing plug 30 can apply uniform pressure to the graphite felt to ensure consistent compression rate at all locations.

[0055] Please refer to the attached Figure 12 In another embodiment of the present application, one or more flow channels are provided on the surface of the plug 30 close to one end of the accommodating space, and the one or more flow channels guide the graphite felt to flow in the cavity 10. This embodiment can simulate the non-uniform compression caused by the existence of the flow channels in an actual liquid flow battery.

[0056] Please refer to the attached Figure 13 In another embodiment of the present application, one or more raised ribs are provided on the surface of the plug 30 near one end of the accommodating space. The ribs can simulate the non-uniform compression of the flow channel in the actual battery. The ribs are easier to design than the flow channel and have less interference with CT scanning.

[0057] Please refer to the attached Figure 14 In another embodiment of the present application, a portion of the sidewall of the cavity 10 is configured as a thinned wall 12, with at least a portion of the thinned wall 12 located to the side of the accommodating space. The thinned wall 12 is annular in appearance, and a portion of the original thickness can be symmetrically retained on the thinned wall 12 to maintain mechanical strength. Because during the compression of the graphite felt, the cavity 10 is subjected to a large vertical positive pressure and shear force caused by the rotation process. Optionally, the outer surface of the thinned wall 12 is flush with the outer surface of the sidewall of the cavity 10, or is recessed relative to the outer surface of the sidewall of the cavity 10, and the inner surface of the thinned wall 12 is recessed relative to the inner surface of the sidewall of the cavity 10.

[0058] Please refer to the attached Figure 15In another embodiment of the present application, the sidewall of cavity 10 is provided with a through hole 10b, which extends through the sidewall of cavity 10 along the thickness direction of the sidewall and is located to the side of the storage space. A thin film is wrapped around the outer periphery of cavity 10, sealing through hole 10b to facilitate X-ray penetration. This prevents X-rays from being obstructed by the sidewall of cavity 10, greatly improving CT scanning imaging. However, the non-fully enclosed structure formed by thinning wall 12 may cause contamination of the CT scanner. In practice, this problem can be addressed by wrapping a plastic film around the sidewall.

[0059] Reference Attachment Figures 8 to 15 In the embodiment of the present application, the cavity 10 includes a bottom wall and a surrounding side wall. The bottom wall is arranged at one end of the surrounding side wall, and the other end of the surrounding side wall forms an opening 10a. The bottom wall, a portion of the surrounding side wall and the press plug 30 form an accommodating space; the thickness of the bottom wall is greater than the thickness of the surrounding side wall. Based on the different force conditions of the bottom wall and the surrounding side wall of the cavity 10, the bottom wall of the cavity 10 needs to bear more weight and pressure, so a thicker wall thickness is required to ensure its strength.

[0060] Please refer to 1 to Figure 6 , a graphite felt detection method applied to a graphite felt closed compression device, applied to a graphite felt closed compression device. Figure 1 As shown, the graphite felt testing method used in the graphite felt closed compression device includes: S11: If the graphite felt is in an extruded state, obtaining a CT image of the graphite felt in the extruded state; S12: Determining a CT scanning mode of the graphite felt according to the CT image; S13: Detecting the graphite felt closed compression device according to the CT scanning mode to obtain a plurality of fiber images of the graphite felt; wherein the compression rates corresponding to the plurality of fiber images are different; S14: determining a change region corresponding to the graphite felt according to the multiple fiber images; S15: Determine the performance level of the graphite felt according to the change area corresponding to the graphite felt.

[0061] refer to Figure 2 In S11, if the graphite felt is in an extruded state, a CT image of the graphite felt in the extruded state is acquired, that is, when the graphite felt is plugged and extruded, a CT image of the graphite felt in the extruded state is acquired; In the specific implementation process of the present invention, the specific steps are: S111: If the graphite felt is in an extruded state by the plug, determine a rotation angle of the cover relative to the cavity, and determine a compression rate of the graphite felt according to the rotation angle of the cover relative to the cavity, specifications of the plug, and specifications of the cavity; S112: determining a preliminary compression shape of the graphite felt according to the compression rate of the graphite felt and the model of the graphite felt; S113: Determine a CT scanning mode corresponding to the graphite felt based on the preliminary compression shape of the graphite felt and the model of the CT scanning device; S114: Based on the CT scanning mode, controlling the CT scanning device to scan the graphite felt to obtain a CT image of the graphite felt in a compressed state.

[0062] In an embodiment of the present application, the rotation angle of the cover body relative to the cavity is collected, and the compression rate of the graphite felt is determined based on the rotation angle of the cover body relative to the cavity, the specifications of the press plug and the specifications of the cavity. This takes into account the overall consideration of the rotation angle of the cover body relative to the cavity, the specifications of the press plug and the specifications of the cavity, thereby ensuring the accuracy of the compression rate of the graphite felt.

[0063] At this time, the compression force exerted by the plug on the graphite felt is indirectly reflected by measuring the rotation angle of the cover relative to the cavity; the change in the rotation angle is usually proportional to the magnitude of the compression force; at this time, an angle sensor or encoder is installed on the compression device, and the sensor is connected to the cover or the plug, which can record the change in the rotation angle in real time; ensure that the sensor has sufficient accuracy and stability to accurately reflect the rotation angle; record the collected rotation angle data in the data log for subsequent analysis and processing.

[0064] The compression rate of the graphite felt is calculated using information such as the rotation angle of the cover relative to the cavity, the specifications of the plug (such as diameter, length, material, etc.) and the specifications of the cavity (such as inner diameter, height, material, etc.); at this time, the initial volume or height of the graphite felt when it is not compressed is determined based on the specifications of the plug and the cavity; the compressive displacement applied by the plug to the graphite felt is calculated based on the change in the rotation angle, which usually involves geometric transformation and mechanical analysis and requires the use of mathematical models or simulation software; the compression displacement is compared with the initial volume or height of the graphite felt to calculate the compression rate; the compression rate is expressed as a volume compression rate (the ratio of the compressed volume to the initial volume) or a height compression rate (the ratio of the compressed height to the initial height); the calculated compression rate is recorded in the data log and associated with the rotation angle data.

[0065] Optionally, assume that there is a graphite felt compression device, in which the diameter of the plunger is 100 mm, the length is 200 mm, and the material is acrylic; the inner diameter of the cavity is 110 mm, the height is 250 mm, and the material is acrylic; during the compression process, an angle sensor with an accuracy of 0.1° is installed to measure the rotation angle of the cover relative to the cavity; when the plunger starts to compress the graphite felt, the angle sensor starts to record the change in the rotation angle; assuming that during the compression process, the rotation angle increases from 0° to 30°; according to the specifications of the plunger and the change in the rotation angle, the angle sensor is calculated. Calculate the compressive displacement applied by the plug to the graphite felt. This usually involves some geometric and mechanical calculations, but for simplicity, assume that the compressive displacement is proportional to the rotation angle; therefore, estimate the compressive displacement to be approximately a certain value (which depends on the specific geometric and mechanical models); assume that the initial height of the graphite felt is 240 mm (slightly smaller than the cavity height to leave some space for compression); calculate the height compression rate based on the calculated compressive displacement and the initial height of the graphite felt; for example, if the compressive displacement is 10 mm, the height compression rate is 10 mm / 240 mm ≈ 4.17%.

[0066] Furthermore, the preliminary compression form of the graphite felt is determined according to the compression rate of the graphite felt and the model of the graphite felt. Based on the preliminary compression form of the graphite felt and the model of the CT scanning device, the CT scanning mode corresponding to the graphite felt is determined. Based on the CT scanning mode, the CT scanning device is controlled to scan the graphite felt to obtain a CT image of the graphite felt in an extruded state, which takes into account the overall consideration of the preliminary compression form of the graphite felt and the model of the CT scanning device, thereby ensuring the accuracy of the corresponding CT scanning mode.

[0067] At this point, understanding the morphological changes of graphite felt at a specific compression rate provides a basis for subsequent CT scanning parameter settings; at this point, a database containing the morphological changes of different types of graphite felt at different compression rates is established, and this database is obtained through experiments or simulations; based on the current compression rate and model of the graphite felt, its preliminary compression morphology is searched or predicted in the database, which involves the extraction of morphological parameters (such as fiber direction, density distribution, porosity change, etc.); and the preliminary compression morphology of the graphite felt is output.

[0068] Ensure that the CT scan can clearly and accurately capture the internal structure of the graphite felt in a compressed state; at this time, evaluate the density changes, fiber arrangement and internal structural characteristics of the graphite felt, which will affect the visibility and resolution of the CT scan; select appropriate scanning parameters based on the preliminary compression morphology of the graphite felt and the model of the CT scanning device (the model of the CT scanning device can reflect the type of X-ray source, detector array, reconstruction algorithm, etc.), including tube voltage, tube current, scanning speed, layer thickness, reconstruction filter, etc.; consider the radiation sensitivity and scanning time of the graphite felt, and optimize the scanning protocol to balance image quality and radiation dose; output detailed parameter settings for the CT scanning mode, including scanning parameters and scanning protocol.

[0069] Perform a CT scan to obtain a three-dimensional image of the graphite felt in an extruded state. Ensure that the graphite felt sample is in a stable compressed state and is correctly placed within the scanning area of ​​the CT scanning device. Set the CT scanning mode parameters determined above on the control interface of the CT scanning device. Start the CT scanning device and scan the graphite felt according to the set scanning protocol. Ensure that the graphite felt remains stationary during the scanning process to avoid motion artifacts. The CT scanning device outputs three-dimensional CT image data of the graphite felt in an extruded state.

[0070] Specifically, assuming that there is a graphite felt of model "GF-A" with a compression rate of 10% (as calculated in step S111); the CT scanning device used is model "Scanner-X" with a high-energy X-ray source and an advanced detector array; the morphological changes of the GF-A graphite felt under a compression rate of 10% are searched or predicted in the database; assuming that the database shows that under a compression rate of 10%, the fiber direction of GF-A changes slightly, the density distribution becomes more uniform, and the porosity decreases slightly; based on the preliminary compression morphology of GF-A and the Scanner-X Based on the model characteristics, a higher tube voltage (such as 120kV) was selected to penetrate the denser graphite felt structure, a lower tube current was used to reduce the radiation dose, a thinner slice thickness (such as 0.5mm) was used to improve the resolution, and a reconstruction filter suitable for uniform density distribution was selected. The GF-A sample was placed in the scanning area of ​​Scanner-X, and the scan was started according to the set scanning parameters (tube voltage 120kV, moderate tube current, slice thickness 0.5mm, etc.). After the scan was completed, Scanner-X output the 3D CT image data of GF-A at a compression rate of 10%.

[0071] refer to Figure 3 In S12, a CT scanning mode of the graphite felt may be determined according to the CT image. Specifically, a plurality of morphological features of the graphite felt may be determined according to the CT image, and the CT scanning mode of the graphite felt may be determined according to the plurality of morphological features, a detection position of the graphite felt, and specification information of the graphite felt; In the specific implementation process of the present invention, the specific steps are: S121: dividing the CT image into multiple morphological regions; S122: for each morphological region, identifying the morphological region and determining the morphological features of the morphological region; S123: Determine multiple morphological features of the graphite felt based on the morphological features corresponding to the multiple morphological regions; S124: determining a first mode coefficient according to the plurality of morphological features and the detection position of the graphite felt; S125: determining a second mode coefficient according to the plurality of morphological features and the model of the graphite felt; S126: Determine a CT scanning mode of the graphite felt based on the first mode coefficient, the second mode coefficient, and a preset CT scanning mode matching table, wherein the CT scanning mode includes one of the following modes: a local detection scanning mode, an overall detection scanning mode, or a directional detection scanning mode.

[0072] In an embodiment of the present application, a CT image is collected, a plurality of morphological regions are determined based on the division of the CT image, and a plurality of morphological features of the graphite felt are determined based on the identification of the plurality of morphological regions. This combines the overall consideration of the identification of the plurality of morphological regions and ensures the accuracy of the plurality of morphological features of the graphite felt.

[0073] At this time, detailed image data of the internal structure of the graphite felt is obtained through CT scanning technology; at this time, the graphite felt sample is scanned using high-resolution CT scanning equipment; ensure that the scanning parameters (such as tube voltage, tube current, scanning speed, etc.) have been optimized according to the characteristics of the graphite felt and the detection requirements; obtain a series of two-dimensional slice images or three-dimensional reconstructed images, which show the structural details inside the graphite felt.

[0074] Divide the CT image into different morphological regions so that each region can be analyzed independently later; Methods: At this point, the CT images were preprocessed with filtering and denoising to improve image quality. Image segmentation algorithms (such as threshold segmentation, edge detection, and region growing) were used to divide the images into different morphological regions based on characteristics such as pixel intensity, texture, and shape. Multiple morphological regions were obtained after division, and each region represented a part with similar characteristics inside the graphite felt.

[0075] For each morphological region, the morphological region is identified and the morphological characteristics of the morphological region are determined. Specifically, feature extraction and analysis are performed on each morphological region to determine multiple morphological characteristics of the graphite felt. At the same time, for each morphological region, morphological characteristics of the morphological region are extracted, such as region size, shape, density distribution, porosity, fiber direction, etc. The morphological characteristics of these morphological regions are automatically extracted through image processing algorithms or dedicated software. The morphological characteristics of the extracted morphological regions are analyzed and compared to identify structural differences and potential problems within the graphite felt. Finally, the morphological characteristics corresponding to each of the multiple morphological regions are used to determine multiple morphological characteristics of the graphite felt, thereby obtaining multiple morphological characteristics of the graphite felt. These morphological characteristics include numerical characteristics (such as density, porosity) and geometric characteristics (such as shape, fiber direction).

[0076] Specifically, suppose there is a graphite felt sample, and a CT scan is performed to evaluate the uniformity of its internal structure and potential defects; CT images are collected: the graphite felt sample is scanned using a high-resolution CT scanning device to obtain a series of two-dimensional slice images (i.e., CT images), which show the fiber structure, pore distribution and other details inside the graphite felt; the CT images are preprocessed and segmented; the image is divided into high-density areas (fiber-dense parts), low-density areas (pores or defect parts) and medium-density areas (transition parts between fibers and pores) through a threshold segmentation algorithm; features are extracted and analyzed for each morphological area; in the high-density area, the diameter, direction and arrangement density of the fibers are measured; in the low-density area, the size, shape and distribution density of the pores are calculated; in the medium-density area, the transition between fibers and pores is analyzed; through these morphological characteristics, the uniformity of the graphite felt, the regularity of the fiber arrangement, and the existence and distribution of potential defects are evaluated.

[0077] Furthermore, the detection position of the graphite felt is collected, and the first mode coefficient is determined based on multiple morphological characteristics and the detection position of the graphite felt. The second mode coefficient is determined based on multiple morphological characteristics and the model of the graphite felt. This is compatible with the overall consideration of multiple morphological characteristics and the detection position of the graphite felt, ensuring the accuracy of the first mode coefficient.

[0078] At this time, the detection positions of the graphite felt are collected, which are potential defects, abnormal structures or key performance areas; at this time, the key detection positions in the graphite felt are manually marked through visual analysis of the CT image, and these positions are marked based on abnormal density, shape changes or other significant features in the image; the marked detection positions are recorded in the image coordinate system or the physical coordinate system for subsequent analysis and reference; the coordinates and descriptions of the key detection positions in the graphite felt are obtained.

[0079] Combining the morphological characteristics of the graphite felt and the detection position information, a mode coefficient reflecting the importance of local characteristics is calculated; at this time, the morphological characteristics near the detection position (such as density, porosity, fiber direction, etc.) are integrated to form a feature vector; according to the degree of contribution of the feature to the importance of the detection position, a weight is assigned to each feature, and these weights are based on experience, experimental data or expert judgment; the first mode coefficient is calculated through weighted summation or other appropriate algorithms. This coefficient reflects the importance of the characteristics of the detection position and its surrounding areas to the overall evaluation; and the specific value of the first mode coefficient is obtained.

[0080] Combining the morphological characteristics and model information of the graphite felt, a mode coefficient reflecting the overall structure and model characteristics is calculated; at this time, key features are extracted from the model information of the graphite felt, which include material composition, manufacturing process, intended use, etc.; the extracted morphological features (such as density distribution, pore structure, etc.) are integrated with the model characteristics to form a comprehensive feature set; based on the comprehensive feature set, the second mode coefficient is calculated, which reflects the influence of the overall structure and model characteristics of the graphite felt on the evaluation results; and the specific value of the second mode coefficient is obtained.

[0081] Specifically, assuming there is a graphite felt sample, several key inspection positions are identified through CT scanning and analysis, and relevant morphological features are extracted; two potential defect positions (such as pore aggregation areas and fiber breakage areas) are manually marked in the CT image, and their coordinates are recorded; for each inspection position, nearby morphological features (such as porosity, fiber direction changes, etc.) are integrated, and weights are assigned according to the importance of these features to the thermal management performance; through the weighted summation algorithm, the first mode coefficients of the two inspection positions are calculated, which respectively reflect the degree of their importance to the overall thermal management performance.

[0082] Combined with the model information of graphite felt (such as unique material composition and manufacturing process), the model features were extracted and fused with the morphological features; using machine learning algorithms (such as support vector machines or random forests), a model was trained based on the comprehensive feature set, and the second mode coefficient was calculated. This coefficient reflects the influence of the overall structure and model characteristics of the graphite felt on the thermal management performance evaluation; through these steps, two mode coefficients were obtained, which together provide an important basis for the performance evaluation and subsequent processing of graphite felt. These coefficients are used to guide further detection, analysis or optimization measures.

[0083] Therefore, the CT scanning mode of the graphite felt is determined based on the first mode coefficient, the second mode coefficient and the CT scanning mode matching table. The CT scanning mode is local detection, overall detection or directional detection, which is compatible with the overall consideration of the first mode coefficient, the second mode coefficient and the CT scanning mode matching table, thereby ensuring the accuracy of the CT scanning mode of the graphite felt.

[0084] At this time, a matching table is created to determine the most suitable CT scanning mode based on the first mode coefficient, the second mode coefficient and other factors (such as the model of the graphite felt, the expected detection target, etc.); at this time, first clarify which factors will be used in the matching process, including the first mode coefficient, the second mode coefficient, the graphite felt model, the expected detection target (such as defect detection, structural analysis, performance evaluation, etc.); the structure of the matching table is designed according to the matching factors, usually including one or more dimensions (such as coefficient range, model classification, detection target, etc.) and corresponding scanning modes (such as local detection scanning mode, overall detection scanning mode or directional detection scanning mode, etc.); based on experimental data, the corresponding scanning mode is filled in for each entry in the CT scanning mode matching table, which requires multiple iterations and adjustments to ensure the accuracy and practicality of the CT scanning mode matching table and obtain a complete CT scanning mode matching table.

[0085] According to the CT image and model information of the graphite felt, the first mode coefficient and the second mode coefficient are calculated; at this time, based on the detection position and morphological characteristics of the graphite felt, an appropriate algorithm or model is used to calculate the first mode coefficient, which reflects the importance of the characteristics of the detection position and its surrounding area to the overall evaluation; at the same time, combined with the morphological characteristics and model information of the graphite felt, the second mode coefficient is calculated using machine learning algorithms, statistical models or expert systems, which reflects the influence of the overall structure and model characteristics of the graphite felt on the evaluation results; and the specific values ​​of the first mode coefficient and the second mode coefficient are obtained.

[0086] The most appropriate CT scanning mode is determined based on the calculated first mode coefficient and second mode coefficient, as well as the CT scanning mode matching table. At this time, the entry that best matches the first mode coefficient and the second mode coefficient is searched in the CT scanning mode matching table, which requires interpolation, approximate matching or other algorithms to handle incomplete matching situations. Based on the matching results, the corresponding CT scanning mode is selected from the CT scanning mode matching table, which includes local detection (focusing on specific areas or defects), overall detection (comprehensive evaluation of the structure and performance of graphite felt) or directional detection (scanning in specific directions or layers). The determined CT scanning mode and its related parameters (such as scanning range, resolution, scanning speed, etc.) are obtained.

[0087] Specifically, assume there is a graphite felt sample, model GF-XYZ. Through the previous steps, the first mode coefficient (0.85, indicating the high importance of a key inspection location) and the second mode coefficient (0.70, indicating that the overall structure and model characteristics of the graphite felt have a significant impact on the evaluation results) have been calculated. Based on experience, a matching table was designed, which includes the first mode coefficient range (0-1), the second mode coefficient range (0-1), the graphite felt model classification (such as GF-XYZ, other models), and the expected inspection objectives (such as defect detection, structural analysis). For each entry, the most appropriate CT scanning mode was determined based on these factors. The first mode coefficient (0.85) and the second mode coefficient (0.70) have been obtained, and it is known that the graphite felt model is GF-XYZ, and the expected inspection objectives are defect detection and structural analysis.

[0088] In the CT scan pattern matching table, the entry that best matches the first pattern coefficient (0.85) and the second pattern coefficient (0.70) was found. Since both coefficients were high, a corresponding entry was found, which suggested using a local detection mode and paying special attention to the areas near the key detection positions in the graphite felt. In addition, since the model of the graphite felt is GF-XYZ, the scanning parameters were adjusted according to the model characteristics to ensure that the existing defects can be accurately detected and the structural characteristics of the graphite felt can be comprehensively analyzed. Through these steps, the CT scanning mode and its related parameters that are most suitable for the graphite felt sample were finally determined, providing an important basis for subsequent detection and analysis.

[0089] In some embodiments of the present application, it is assumed that there is a pre-designed CT scan pattern matching table, which determines the most appropriate scan pattern based on the first pattern coefficient, the second pattern coefficient, and specific properties of the graphite felt (such as model, application, etc.); the CT scan pattern matching table is shown in Table 1: Table 1 CT scan pattern matching table Now, suppose there is a graphite felt sample with a first mode coefficient of 0.75, a second mode coefficient of 0.8, and a model of GF-ABC; according to the matching table, the first mode coefficient range is searched: 0.75 falls within the range of 0.5 ~ 0.8, but is also close to the range of 0.9 ~ 1.0; however, since the matching table usually follows the most specific matching principle, the range of 0.5~ 0.8 is considered first; the second mode coefficient range is searched: 0.8 falls within the range of 0.7~1.0; considering the graphite felt model: the sample model is GF-ABC; according to the matching table, when the first mode coefficient is in the range of 0.5 - 0.8, the second mode coefficient is in the range of 0.7 - 1.0, and the model is GF-ABC, the most suitable scanning mode is directional detection; therefore, according to the matching table, the CT scanning mode of the graphite felt sample is determined to be directional detection.

[0090] refer to Figure 4 , in S13, the graphite felt closed compression device is detected according to the CT scanning mode to obtain a plurality of fiber images of the graphite felt; In the specific implementation process of the present invention, the specific steps are: S131: Based on the CT scanning mode, controlling the CT scanning device to detect the graphite felt closed compression device; S132: During the detection process, determining state nodes of the graphite felt at different compression rates; S133: Control the CT scanning device to detect the closed compression device of the graphite felt when the graphite felt is at state nodes with different compression rates, and obtain fiber images of the graphite felt at different compression rates.

[0091] In an embodiment of the present application, a CT scanning mode is acquired, and a CT scanning device is triggered to detect the graphite felt closed compression device based on the CT scanning mode, and a corresponding fiber image is introduced during the detection process.

[0092] At this point, detailed information about the CT scanning mode is obtained from the previous steps or preset configurations. This information will guide the CT scanning device on how to detect the graphite felt closed compression device. At the same time, the CT scanning device is configured based on the acquired CT scanning mode information to ensure that it can perform detection according to the predetermined mode. At this point, parameters such as the scanning range, resolution, and X-ray energy in the CT scanning mode are input into the control system of the CT scanning device. According to the requirements of the scanning mode, a suitable image reconstruction algorithm is selected to obtain a high-quality fiber image. The CT scanning device has been configured according to the predetermined scanning mode.

[0093] The CT scanning device is started to detect the graphite felt placed in the closed compression device and capture the corresponding fiber image; at this time, a scanning program is started in the control system of the CT scanning device; it is ensured that the graphite felt is correctly placed in the closed compression device and the device is closed and fixed; the CT scanning device is triggered to start the scanning process, and the scanning progress and image quality are monitored at the same time; and a set of fiber images of the graphite felt in the closed compression device is obtained.

[0094] Specifically, assume that a new type of graphite felt material is being studied, and it is necessary to evaluate the changes in its fiber structure under different compression states; the CT scanning mode has been predetermined as "high-resolution local scanning" based on the characteristics of the graphite felt and the detection target, which focuses on the fiber structure of a specific area in the graphite felt and provides high-definition images; the detailed information of the "high-resolution local scanning" mode is read from the preset configuration, including the scanning range of a specific cubic volume in the central area of ​​the graphite felt, a resolution of 0.1 mm, an X-ray energy of 120 kV, etc.; these parameters are input into the control system of the CT scanning device, and a reconstruction algorithm suitable for high-resolution images is selected.

[0095] The new graphite felt material was placed in a closed compression device, and the device was adjusted to reach the initial compression state of interest; then, the CT scanning device was started and the graphite felt was inspected in "high-resolution local scanning" mode; during the scanning process, the scanning progress and image quality were monitored to ensure clear fiber images; finally, a series of high-resolution fiber images of the graphite felt at different compression states in the closed compression device were obtained, which will be used for subsequent structural analysis and performance evaluation.

[0096] Furthermore, the rotation of the cover relative to the cavity in the closed compression device of the graphite felt is monitored in real time, and the state nodes of the graphite felt at different compression rates are determined. At the state nodes of the graphite felt at different compression rates, the CT scanning device detects the closed compression device of the graphite felt to collect fiber images of the graphite felt at different compression rates, and collects multiple fiber images of the graphite felt at different compression rates, introducing the collection of multiple fiber images of the graphite felt at different compression rates.

[0097] At this time, the rotation state of the cover in the monitoring device is used to ensure the accuracy and controllability of the compression process, and it also serves as one of the signals to trigger the CT scan. At this time, a rotation sensor is installed on the cover or cavity of the graphite felt closed compression device to monitor the rotation angle or position of the cover in real time. The sensor transmits real-time data to the control system, and the control system processes the data to determine whether the rotation state of the cover is as expected. Real-time data of the cover rotation and status judgment results based on these data are obtained.

[0098] According to the experimental design or research requirements, the key compression rate nodes of the graphite felt where fiber images need to be collected during the compression process are determined; at this time, according to the characteristics of the graphite felt and the research objectives, a series of compression rate gradients are set, such as 10%, 20%, 30%, etc.; based on the compression rate gradients and the initial state of the device, the rotation position of the cover or the required compression force when each compression rate is reached is calculated; a list of state nodes of the graphite felt at different compression rates is obtained, including the compression rate of each node and the corresponding rotation position of the cover or compression force.

[0099] When the graphite felt reaches each preset compression rate state node, the CT scanning device is triggered to perform detection to collect fiber images at the corresponding compression rate; at this time, when the cover of the graphite felt closed compression device rotates to the preset state node position, the control system sends a synchronization signal to the CT scanning device; after receiving the synchronization signal, the CT scanning device immediately starts the scanning program to perform a fast and high-quality CT scan on the graphite felt; after the scan is completed, the control system automatically collects the fiber image and performs necessary preprocessing, such as denoising, contrast enhancement and other preprocessing; the fiber images of the graphite felt at different compression rates are obtained, and the fiber image at each compression rate includes images of multiple perspectives or levels collected at the compression rate.

[0100] Specifically, assume that the changes in the fiber structure of graphite felt material during the compression process are being studied to evaluate its mechanical properties; a series of compression rate gradients are set, including 10%, 20%, 30%, 40% and 50%, and it is planned to collect fiber images of the graphite felt when each compression rate is reached; a rotation sensor is installed on the cover of the compression device and connected to the control system; during the compression process, the sensor transmits the rotation data of the cover to the control system in real time, and the control system determines whether the rotation state of the cover is as expected; based on the set compression rate gradient, the rotation position of the cover when each compression rate is reached is calculated; for example, when the compression rate reaches 10%, the cover should rotate to a specific angle; when it reaches 20%, it rotates to another angle, and so on.

[0101] When the cover of the closed graphite felt compression device rotates to a preset state node position, the control system automatically sends a synchronization signal to the CT scanning device; after receiving the signal, the CT scanning device immediately starts the scanning program and quickly scans the graphite felt; after the scan is completed, the control system automatically collects fiber images and performs preprocessing; a set of fiber images of the graphite felt at compression rates of 10%, 20%, 30%, 40% and 50% is obtained. Each set contains images collected from different perspectives or levels at the compression rate. These images will be used for subsequent structural analysis and performance evaluation to help understand the changes in the fiber structure of the graphite felt during the compression process and its relationship with mechanical properties.

[0102] In some embodiments of the present application, a compression rate matching table is used to associate the rotation state of the cover (or other measurable indicators such as compression force, displacement, etc.) with a preset compression rate state node; the compression rate matching table is shown in Table 2: Table 2 Compression ratio matching table In actual operation, when the cover of the graphite felt closed compression device rotates to the angle range specified in the matching table (or reaches the corresponding compression force / displacement range), the control system will decide whether to start the CT scanning device for image acquisition based on the judgment of the "Whether to trigger CT scanning" column.

[0103] refer to Figure 5 In S14, the change area corresponding to the graphite felt is determined based on the multiple fiber images.

[0104] In the specific implementation process of the present invention, the specific S14 includes the following steps, specifically: S141: comparing multiple fiber images with different compression rates, determining a changed portion between the multiple fiber images, and determining a region corresponding to the changed portion as a changed region corresponding to the graphite felt; In an embodiment of the present application, multiple fiber images at different compression rates are collected, and the multiple fiber images at different compression rates are compared. The changed part is determined based on the comparison of the multiple fiber images at different compression rates, and the area corresponding to the changed part is determined as the changed area corresponding to the graphite felt, which is compatible with the overall consideration of the regional detection of the changed part and ensures the accuracy of the corresponding changed area.

[0105] At this time, the fiber structure images of the graphite felt under different compression states are obtained to provide basic data for subsequent comparison and analysis; by comparing the fiber images under different compression rates, the areas where the fiber structure has changed significantly are identified; at this time, the collected fiber images are preprocessed, such as denoising, contrast enhancement, etc., to improve the image quality; the preprocessed images are superimposed or displayed side by side for intuitive comparison; through automatic algorithms, the areas where the fiber density, direction, morphology, etc. have changed significantly are identified; and a comparison report or image collection with the areas with significant changes marked is obtained.

[0106] Based on the comparison results, the specific areas where the fiber structure of the graphite felt changes at different compression rates are accurately determined; at this time, the images marked with significant change areas are further analyzed to determine the specific location, size and shape of the change areas; based on the characteristics of the change areas, such as whether they show regularity or whether they are concentrated in specific areas, the change areas are classified and named; a report or data set containing detailed information on the change areas of the graphite felt at different compression rates is obtained. Specifically, assume that the changes in the fiber structure of a new type of graphite felt material during compression are being studied; according to the previous steps, fiber images of the graphite felt at compression rates of 0%, 10%, 20%, 30% and 40% have been collected using a high-resolution CT scanning device; five groups of fiber images have been obtained, each group of images corresponds to a specific compression rate, and these images clearly show the fiber structure of the graphite felt under different compression states; the images are preprocessed using image processing software and compared by displaying them in parallel; through careful observation, it is found that with the increase in compression rate, the fiber density in the central area of ​​the graphite felt gradually increases, while the fiber direction in the edge area deflects; these areas with significant changes are marked; further analysis of the images of the marked change areas determines that the central area is the main area of ​​fiber density change, while the edge area is the main area of ​​fiber direction change; the specific position, size and morphology of these change areas are also measured, and the relevant information is recorded; through these steps, the specific areas where the fiber structure of the graphite felt changes at different compression rates are successfully determined, providing an important basis for subsequent analysis and research.

[0107] refer to Figure 6 In S15, the performance level of the graphite felt is determined according to the change area corresponding to the graphite felt.

[0108] As an embodiment of the present invention, S15 includes the following steps, specifically: S151: Determine multiple change parameters of the graphite felt based on the change regions corresponding to the graphite felt. For example, for each change region, determine the region detection mode corresponding to the change region based on the position, shape, and corresponding compression rate of the change region, and determine the change parameters of the change region based on the change region and the region detection mode corresponding to the change region; and use the change parameters of all change regions as multiple change parameters of the graphite felt. S152: For each change parameter, determine a state diagram corresponding to the change parameter according to the change parameter.

[0109] For example, according to the change parameter, the shape of the graphite felt, and the compression rate of the graphite felt, a state schematic diagram corresponding to the change parameter is determined.

[0110] S153: Determine a state distribution diagram of the graphite felt based on the state schematic diagrams corresponding to each of the plurality of change parameters.

[0111] For example, the state schematic diagrams corresponding to the multiple change parameters are placed in the same schematic diagram frame for synthesis to determine the state distribution diagram of the graphite felt, and multiple state parameters of the graphite felt at different compression rates are marked in the state distribution diagram of the graphite felt.

[0112] S154: Determine the performance level of the graphite felt according to the state distribution diagram of the graphite felt.

[0113] For example, a first grade coefficient is determined based on multiple state parameters of the graphite felt at different compression rates and the compression form of the graphite felt at different compression rates; a second grade coefficient is determined based on multiple state parameters of the graphite felt at different compression rates and multiple compression rates corresponding to the graphite felt; and the performance grade of the graphite felt is determined based on the mapping relationship between the first grade coefficient, the second grade coefficient and a preset performance grade.

[0114] Furthermore, in each change area, the corresponding area detection mode is determined based on the position, shape and corresponding compression rate of the change area, and multiple change parameters of the graphite felt are determined according to each change area and the area detection mode corresponding to the change area, which is compatible with the overall consideration of each change area and the corresponding area detection mode, and ensures the accuracy of multiple change parameters of the graphite felt.

[0115] At this time, according to the location, morphology and corresponding compression rate of the changed area, select the appropriate detection mode to accurately capture and analyze the change characteristics of these areas; at this time, analyze the location distribution of the changed area to determine whether it is a local change or a global change, and whether the change is concentrated in a specific area; observe the morphology of the changed area, such as the arrangement direction of the fibers, whether the density change is uniform, etc.; combine the compression rate information to understand the relationship between the change and the degree of compression; based on the above analysis, select the appropriate detection mode, such as local region of interest (ROI) analysis, global statistical analysis, directional analysis, etc.; determine the appropriate detection mode for each changed area.

[0116] Under a certain detection mode, parameters that can quantitatively describe the changes in the fiber structure of graphite felt are extracted; at this time, for local ROI analysis, parameters such as fiber density, fiber diameter, and fiber direction angle are extracted; for global statistical analysis, statistical indicators such as the average value and standard deviation of the fiber density in the entire area are calculated; for directional analysis, the deflection angle and directional consistency of the fiber direction are measured; according to the needs of the detection mode, appropriate image processing algorithms or tools are selected for parameter extraction; and a series of quantitative parameters describing the changes in the fiber structure of graphite felt under different compression rates are obtained.

[0117] Specifically, suppose a study is underway on the changes in the fiber structure of graphite felt during compression, and several key areas of change have been identified through previous steps. It was found that in the central area of ​​the graphite felt, the fiber density increased significantly with increasing compression, and this change was local and concentrated in the central area. Therefore, local ROI analysis was selected as the detection mode for this area. In the edge area, the fiber direction was significantly deflected, and this deflection was relatively consistent throughout the edge area. Therefore, directional analysis was selected as the detection mode for this area.

[0118] For the local ROI analysis of the central area, the fiber density was extracted as the key parameter, and the image processing algorithm was used to calculate the fiber density value of the central area under different compression rates; for the directional analysis of the edge area, the deflection angle of the fiber direction was measured, and the average and standard deviation of the deflection angle were calculated to quantitatively describe the degree of change in the fiber direction; through these steps, not only the detection mode suitable for each change area was determined, but also a series of parameters that can quantitatively describe the changes in the graphite felt fiber structure were extracted, providing important data support for subsequent analysis and research.

[0119] Therefore, multiple changing parameters are collected, and the corresponding state schematic diagram is determined based on the multiple changing parameters, the morphology of the graphite felt, and the compression rate of the graphite felt. This takes into account the overall consideration of the multiple changing parameters, the morphology of the graphite felt, and the compression rate of the graphite felt, ensuring the accuracy of the corresponding state schematic diagram.

[0120] At this point, all parameters related to the changes in the graphite felt fiber structure determined in the previous step are summarized to provide data support for drawing the state diagram; at this point, all parameters related to the changes in the fiber structure of the graphite felt at different compression rates are collected from the previous analysis, such as fiber density, fiber direction deflection angle, morphological changes, etc.; ensure that each parameter is associated with a specific compression rate and graphite felt morphology, and record them; a database or data table containing all the changing parameters.

[0121] The collected variation parameters are combined with the morphology and compression rate of the graphite felt to analyze and determine the characteristics of the graphite felt under different compression states; at this time, the variation parameters are statistically analyzed, such as calculating the mean value, standard deviation, etc., to understand the variation trend of the parameters with the compression rate; combined with the original morphology of the graphite felt, the effect of the parameter change on the overall structure of the graphite felt is analyzed; based on the analysis results, the typical state characteristics of the graphite felt under different compression rates are determined; an analysis report describing the characteristics of the graphite felt under different compression states is prepared.

[0122] According to the analysis results, draw a state diagram that can intuitively show the changes in the fiber structure of the graphite felt under different compression states; at this time, select appropriate drawing tools or software, such as CAD, Photoshop, etc.; according to the original shape and compression rate of the graphite felt, draw the outline of the graphite felt under different states; in the schematic diagram, use different colors, lines or patterns to represent the changes in the fiber structure, such as the increase in fiber density, deflection of direction, etc.; add necessary annotations and explanations so that readers can accurately understand the information expressed by the schematic diagram; output a state diagram containing the changes in the fiber structure of the graphite felt under different compression states.

[0123] Specifically, assume that a study is being conducted on the changes in the fiber structure of graphite felt during compression, and several key change parameters have been determined through previous steps; parameters such as the fiber density and fiber direction deflection angle of the graphite felt at different compression rates (such as 0%, 10%, 20%, 30%, and 40%) are collected. These parameters are associated with specific compression rates and graphite felt morphologies and are recorded; a statistical analysis is performed on the collected parameters, and it is found that with the increase in compression rate, the fiber density in the central area of ​​the graphite felt gradually increases, while the fiber direction in the edge area deflects; combined with the original morphology of the graphite felt, the typical state characteristics of the graphite felt at different compression rates are determined, such as the degree of increase in fiber density in the central area and the deflection angle of the fiber direction in the edge area.

[0124] CAD software was selected as the drawing tool; the outline of graphite felt in different states was drawn according to the original form and compression rate of the graphite felt; in the schematic diagram, different colors were used to represent the change of fiber density, such as the darker the color, the greater the fiber density; at the same time, arrows were used to represent the deflection of the fiber direction, the direction of the arrow indicated the direction of deflection, and the length of the arrow indicated the degree of deflection; finally, necessary annotations and explanations were added to the schematic diagram, such as compression rate, fiber density variation range, fiber direction deflection angle, etc., so that readers can accurately understand the information expressed by the schematic diagram; through these steps, a schematic diagram of the state of the fiber structure change of graphite felt under different compression states was successfully drawn, providing intuitive visual support for subsequent analysis and research.

[0125] In some embodiments of the present application, a schematic diagram matching table is collected, and the schematic diagram matching table is shown in Table 3: Table 3 Schematic diagram matching table In an embodiment of the present application, multiple state schematic diagrams are collected, the multiple state schematic diagrams are placed in the same schematic diagram frame, and are synthesized in the schematic diagram frame to determine a state distribution diagram of the graphite felt. The state distribution diagram of the graphite felt marks multiple state parameters of the graphite felt at different compression rates, and the state distribution diagram of the graphite felt is introduced to mark multiple state parameters of the graphite felt at different compression rates.

[0126] At this point, obtain multiple state diagrams of graphite felt at different compression rates from previous analysis or experiments. These diagrams should be able to clearly show the key features of graphite felt in different compression states, such as fiber structure, density, and direction; integrate all the collected state diagrams into a unified diagram framework for synthesis and comparison; at this point, select a suitable drawing software or tool, such as Photoshop, Illustrator or CAD; create a new work area or canvas as a diagram framework; adjust the size, scale and position of the diagrams as needed to ensure that they can be neatly arranged in the frame while maintaining their respective details and clarity; output a unified diagram framework containing all state diagrams.

[0127] In the schematic diagram framework, the various state schematic diagrams are synthesized to form an overall state distribution diagram. This distribution diagram should be able to intuitively show the state changes of the graphite felt under different compression rates; at this time, the synthesis or layer overlay function in the drawing software is used to merge the various state schematic diagrams into an overall image; during the synthesis process, the relative position and proportional relationship between the various schematic diagrams are maintained to ensure the accuracy and readability of the state distribution diagram; parameters such as transparency, color or contrast are adjusted as needed to enhance the visual effect of the state distribution diagram; and a synthesized graphite felt state distribution diagram is output.

[0128] In the state distribution diagram, mark out multiple key state parameters of the graphite felt at different compression rates, such as fiber density, directional deflection angle, degree of morphological change, etc. These parameters will provide important basis for subsequent performance evaluation; at this time, use the text or annotation tools in the drawing software to add necessary text descriptions or arrow indications on the state distribution diagram; ensure that each state parameter is clearly and accurately marked and associated with the corresponding schematic area; add color coding or symbol marks as needed to more intuitively show the differences and change trends between different parameters; output a graphite felt state distribution diagram marked with multiple key state parameters.

[0129] Specifically, assume that a study on the compression performance of graphite felt is being conducted, and the state diagrams of graphite felt at different compression rates (such as 0%, 10%, 20%, and 30%) have been obtained through the previous steps; four state diagrams that can represent the state of graphite felt at different compression rates are selected from the previous experimental results. These state diagrams clearly show the fiber structure, density, and direction characteristics of graphite felt at different compression rates; use Photoshop software to create a new working area as a schematic diagram frame, and arrange the four state diagrams in the frame in order of compression rate; by adjusting the size and proportion of the diagrams, ensure their neat arrangement and clear display in the frame.

[0130] In Photoshop, the layer overlay function was used to merge the four state diagrams into an overall image; during the synthesis process, the relative position and proportional relationship between the various diagrams were maintained, and parameters such as transparency and contrast were adjusted to enhance the visual effect; finally, a synthesized graphite felt state distribution map was obtained, that is, the state distribution map of the graphite felt was determined; on the state distribution map, the text tool was used to add necessary text descriptions and arrow indicators to mark the key state parameters; for example, in the diagram under 0% compression rate, the original fiber density and direction were marked; in the diagram under 10% compression rate, the slight increase in fiber density and the slight deflection of direction were marked; through these marks, the state changes of graphite felt under different compression rates and its key parameters can be intuitively displayed.

[0131] Furthermore, the compression shape of the graphite felt is collected, and the first-level coefficient is determined based on multiple state parameters and the compression shape of the graphite felt, which is compatible with the overall consideration of multiple state parameters and the compression shape of the graphite felt and ensures the accuracy of the first-level coefficient.

[0132] At this point, obtain the actual morphological data of the graphite felt under different compression conditions, which will be used for subsequent analysis and grade assessment; review and analyze the multiple state parameters collected in the previous steps (such as fiber density, directional deflection angle, degree of morphological change, etc.), which will be used to evaluate the performance of the graphite felt during the compression process; at this point, organize and summarize the data of all state parameters to ensure the accuracy and completeness of the data; analyze each parameter separately to understand its changing trend during the compression process of the graphite felt and its impact on the performance; if necessary, use statistical analysis methods (such as correlation analysis, regression analysis, etc.) to further explore the relationship between state parameters and their comprehensive impact on the performance of the graphite felt; output an analysis report of the state parameters, which includes the changing trend of the parameters, their mutual relationship, and the evaluation of their impact on the performance of the graphite felt.

[0133] Combined with the compression morphology data of the graphite felt and the analysis results of multiple state parameters, a first-level coefficient is determined for the compression performance of the graphite felt, that is, the first-level coefficient is determined based on the multiple state parameters of the graphite felt at different compression rates and the compression morphology of the graphite felt at different compression rates. This first-level coefficient will reflect the structural stability and performance of the graphite felt during the compression process; at this time, according to experimental requirements and industry standards, a grade assessment standard or criterion is formulated, and this standard is formulated based on the morphological changes of the graphite felt, the range of changes in state parameters, or the comprehensive performance; the compression morphology data and state parameter analysis results of the graphite felt are compared with the grade assessment standard to determine the grade range to which the graphite felt belongs; within the grade range, a specific first-level coefficient is assigned to the graphite felt based on its specific performance (such as morphology retention ability, fiber structure stability, etc.), and this coefficient is in the form of a numerical value, letter, or symbol, etc., depending on the design and requirements of the grade assessment system; the first-level coefficient of the graphite felt is output to represent its performance grade during the compression process.

[0134] Specifically, assume that an experimental study on the evaluation of the compression performance of graphite felt is being conducted; the morphological data and multiple state parameters of the graphite felt at different compression rates have been collected through previous steps; a digital microscope is used to record the morphological changes of the graphite felt after being subjected to different compression forces (such as compression rates of 10%, 20%, and 30%); attention is paid to indicators such as the thickness change, arrangement and density of the fiber structure of the graphite felt, and the corresponding data are recorded; the data of state parameters such as fiber density and directional deflection angle collected in the previous steps are reviewed; through comparative analysis, it is found that with the increase of compression rate, the fiber density of the graphite felt gradually increases, and the directional deflection angle also gradually increases; at the same time, statistical analysis methods are used to explore the relationship between these state parameters and their comprehensive influence on the performance of the graphite felt.

[0135] Determine the first-grade coefficient: According to experimental requirements and industry standards, a grading standard based on the morphological changes and state parameter performance of graphite felt was developed; the compression morphological data and state parameter analysis results of the graphite felt were compared with the grading standard, and it was found that the graphite felt can still maintain good morphological stability and fiber structure integrity when subjected to a high compression rate; therefore, according to the specific performance of the graphite felt, it was assigned a higher first-grade coefficient (such as "A" grade), indicating that its performance during the compression process was excellent; through the above steps, the first-grade coefficient of the graphite felt was successfully determined, providing an important reference basis for subsequent performance evaluation and application.

[0136] Therefore, the second grade coefficient is determined based on multiple state parameters and the compressibility of the graphite felt, that is, based on multiple state parameters of the graphite felt at different compressibility ratios and multiple compressibility ratios corresponding to the graphite felt. The performance grade of the graphite felt is determined based on the mapping relationship between the first grade coefficient, the second grade coefficient, and the performance grade. This takes into account the overall mapping relationship between the first grade coefficient, the second grade coefficient, and the performance grade, ensuring the accuracy of the performance grade of the graphite felt.

[0137] At this time, a second-level coefficient is determined for the compression performance of the graphite felt by integrating multiple state parameters and the compression rate information of the graphite felt. This coefficient will reflect the comprehensive performance of the graphite felt under different compression rates. At this time, all the collected state parameter data (such as fiber density, directional deflection angle, degree of morphological change, etc.) and the compression rate data of the graphite felt are sorted out. According to the experimental requirements or industry standards, a weight is assigned to each state parameter to indicate the importance of the parameter in evaluating the compression performance of the graphite felt. Based on the state parameter data and weight assignment, a performance score is calculated for the graphite felt state under each compression rate, which is achieved through weighted summation or other appropriate statistical methods. According to the distribution of the performance scores, a grade classification standard is formulated. Then, the performance score under each compression rate is compared with the grade classification standard to determine the corresponding second-level coefficient.

[0138] Combine the first-grade coefficient and the second-grade coefficient to establish a performance grade mapping relationship, which corresponds different grade coefficient combinations to the performance grades of the graphite felt; at this time, list all combinations of the first-grade coefficient and the second-grade coefficient; define a specific performance grade for each grade coefficient combination according to experimental requirements or industry standards, and this grade is formulated based on the comprehensive performance of the graphite felt in multiple aspects such as structural stability, shape retention ability, and fiber structure integrity during the compression process; establish a mapping table or database (i.e., a preset performance grade mapping relationship) for the grade coefficient combination and the corresponding performance grade, so that in the subsequent evaluation process, the performance grade of the graphite felt can be quickly found and determined from the preset performance grade mapping relationship; thereby obtaining the preset performance grade mapping relationship, for example, a performance grade mapping relationship table or database.

[0139] The performance grade of the graphite felt is finally determined according to the mapping relationship between the first grade coefficient, the second grade coefficient and the preset performance grade; at this time, the first grade coefficient and the second grade coefficient of the graphite felt are determined; the performance grade corresponding to the two grade coefficients is searched in the performance grade mapping relationship table or database; the performance grade of the graphite felt is determined according to the mapping result; and the performance grade evaluation result of the graphite felt is output.

[0140] Specifically, assume that an experimental study on the evaluation of the compression performance of graphite felt is underway, and the first-level coefficient, multiple state parameters and compression rate data of the graphite felt at different compression rates have been obtained through the previous steps; determine the second-level coefficient: first, organize the data of state parameters such as fiber density and directional deflection angle, as well as the data of graphite felt at compression rates of 10%, 20%, and 30%; according to the experimental requirements, assign different weights to fiber density and directional deflection angle (for example, fiber density 0.6, directional deflection angle 0.4); then, calculate the performance score for the graphite felt state at each compression rate (for example, the score at a compression rate of 10% is 85, 20% is 80, and 30% is 75); finally, based on the distribution of performance scores, a grade classification standard is formulated, and the performance score at each compression rate is compared with the standard to determine the corresponding second-level coefficient (for example, 10% is grade A, 20% is grade B, and 30% is grade C).

[0141] All combinations of first-grade coefficients and second-grade coefficients are listed (for example, the first-grade coefficient is A, and the second-grade coefficients are combinations of A, B, and C); according to the experimental requirements, specific performance levels are defined for each grade coefficient combination (for example, AA is excellent, AB is good, AC is fair, etc.); then, a performance level mapping relationship table is established to match the grade coefficient combinations with the corresponding performance levels; assuming that the first-grade coefficient of graphite felt is A, and the second-grade coefficient at a compression rate of 10% is A, 20% is B, and 30% is C; the performance levels corresponding to these grade coefficients are searched in the performance level mapping relationship table; based on the mapping results, it is determined that the performance level of graphite felt at a compression rate of 10% is excellent, 20% is good, and 30% is fair.

[0142] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A graphite felt closed compression device, characterized in that: include: A cavity, wherein the cavity is provided with an opening and the material of the cavity is a material transparent to X-rays; a cover body, the cover body covering the opening and being threadedly connected to the cavity; A pressing plug is located in the cavity and is capable of reciprocating along a preset direction relative to the cavity, one end of the pressing plug along the preset direction and the cavity enclose an accommodating space for accommodating graphite felt, and the other end of the pressing plug along the preset direction is correspondingly arranged with the cover body; During the rotation of the cover body relative to the cavity body, the cover body can synchronously move linearly toward the press plug to correspondingly abut against the press plug, or the cover body can synchronously move linearly away from the press plug to correspondingly abut against or release the press plug.

2. The graphite felt closed compression device according to claim 1, characterized in that: The cover body includes a groove body and a boss portion, the inner circumference of the groove body is provided with an internal thread, and the boss portion is provided on the inner bottom surface of the groove body and protrudes relative to the inner bottom surface of the groove body; The cavity is provided with an external thread on the outer peripheral surface of one end of the opening, which extends into the groove body and the external thread cooperates with the internal thread. The boss portion extends into the cavity along the opening and abuts against the plug.

3. The graphite felt closed compression device according to claim 1, characterized in that: The surface of the end of the press plug close to the accommodating space is a smooth surface; or One or more flow channels are provided on a surface of the press plug at one end close to the accommodating space; or One or more raised ribs are provided on a surface of the press plug at one end close to the accommodating space.

4. The graphite felt closed compression device according to claim 1, characterized in that: A portion of the sidewall of the cavity is configured as a thinned wall, and at least a portion of the thinned wall is located on the side of the accommodating space.

5. The closed graphite felt compression device according to claim 4, characterized in that: The outer surface of the thinned wall is flush with the outer surface of the side wall of the cavity, or is recessed relative to the outer surface of the side wall of the cavity, and the inner surface of the thinned wall is recessed relative to the inner surface of the side wall of the cavity.

6. The closed graphite felt compression device according to claim 1, 4 or 5, characterized in that: The side wall of the cavity is provided with a through hole, the through hole penetrates the side wall of the cavity along the thick wall direction of the side wall of the cavity, and the through hole is located on the side of the accommodating space; A film is wrapped around the outer circumference of the cavity, and the film closes the through hole.

7. The closed graphite felt compression device according to claim 1, characterized in that: The cavity comprises a bottom wall and a peripheral side wall, wherein the bottom wall is arranged at one end of the peripheral side wall, and the other end of the peripheral side wall forms the opening, and the bottom wall, a portion of the peripheral side wall and the press plug form the accommodating space; The thickness of the bottom wall is greater than the thickness of the peripheral side wall.

8. A graphite felt detection method applied to a graphite felt closed compression device, characterized in that: The graphite felt detection method applied to the graphite felt closed compression device is applied to the graphite felt closed compression device according to any one of claims 1 to 7, and the graphite felt detection method applied to the graphite felt closed compression device includes: If the graphite felt is in an extruded state, obtaining a CT image of the graphite felt in the extruded state; determining a CT scanning mode of the graphite felt according to the CT image; Detecting the graphite felt closed compression device according to the CT scanning mode to obtain a plurality of fiber images of the graphite felt, wherein the compression rates corresponding to the plurality of fiber images are different; determining a change region corresponding to the graphite felt according to the plurality of fiber images; The performance grade of the graphite felt is determined according to the change area corresponding to the graphite felt.

9. The graphite felt detection method applied to the graphite felt closed compression device according to claim 8, characterized in that: If the graphite felt is in an extruded state, obtaining a CT image of the graphite felt in the extruded state includes: If the graphite felt is in an extruded state by the plug, the rotation angle of the cover relative to the cavity is determined, and the compression rate of the graphite felt is determined according to the rotation angle of the cover relative to the cavity, the specifications of the plug, and the specifications of the cavity; Determine the initial compression shape of the graphite felt according to the compression rate of the graphite felt and the model of the graphite felt; Based on the preliminary compression shape of the graphite felt and the model of the CT scanning device, the CT scanning mode corresponding to the graphite felt is determined; Based on the CT scanning mode, the CT scanning device is controlled to scan the graphite felt to obtain a CT image of the graphite felt in a compressed state.

10. The graphite felt detection method applied to the graphite felt closed compression device according to claim 8, characterized in that: Determining the performance level of the graphite felt according to the change area corresponding to the graphite felt includes: Determining a plurality of change parameters of the graphite felt according to the change area corresponding to the graphite felt; For each change parameter, determining a state diagram corresponding to the change parameter according to the change parameter; Determining a state distribution diagram of the graphite felt based on the state schematic diagrams corresponding to the multiple change parameters; The performance grade of the graphite felt is determined according to the state distribution diagram of the graphite felt.

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