A multimodal performance detection system and method for high aspect ratio rod-shaped preform

Abstract

The present invention discloses a multimodal performance detection system and method for a rod-shaped preform with a high aspect ratio, which relates to the field of bolt detection technology, and includes: a data acquisition module, a microstructure performance detection module, a dimensional stability evaluation module, a comprehensive performance evaluation module, and a preform database. The present invention analyzes the initial dimensional accuracy data of each preform sample in view of the characteristics of the rod-shaped preform with a high aspect ratio, thereby avoiding the error caused by the traditional bolt performance test due to its incompatibility with the preform. By analyzing the fiber distribution data through microstructure performance detection, the uniformity of the microstructure of the preform can be accurately evaluated, thereby improving the accuracy of the performance evaluation. The present invention evaluates the comprehensive performance of the preform sample from the two perspectives of microstructure uniformity and dimensional stability, which is helpful for the subsequent analysis of the performance of the preform in different application scenarios, and ensures the reliability and applicability of the preform in various complex environments.

Description

Technical Field

[0001] The present invention relates to the technical field of bolt detection, and in particular to a multi-modal performance detection system and method for a high aspect ratio rod-shaped preform. Background Art

[0002] With the widespread application of composite materials in the industrial field, the preparation materials of bolt preforms have been developed. Due to their special geometric shapes and application requirements, high aspect ratio rod preforms have important application value in aerospace, precision instruments, optical fiber communications and other fields. In order to ensure that such preforms can meet strict engineering standards, detailed performance testing is required.

[0003] For example, the invention patent with publication number CN117969311A is a device for testing the mechanical properties of bolts, including a testing body and a fatigue and impact resistance testing component arranged on the testing body, and also including a temperature difference dynamic mechanical properties testing mechanism and a marine environment corrosion performance testing mechanism. The temperature difference dynamic mechanical properties testing mechanism is arranged on the testing body, and the marine environment corrosion performance testing mechanism is arranged in the testing body; the application provides a device for testing the mechanical properties of bolts, through which the influence of temperature on the strength of the bolts can be evaluated, and the shear strength test can help evaluate the influence of these temperature changes on the strength of the bolts. By comparing the shear strength before and after treatment, the performance difference of the bolts under different temperature conditions can be understood.

[0004] For example, the invention patent with the announcement number CN117309598B is a bolt detection device, including a detection schematic component, a tensile moving component, a clamping component, a device base and a supporting pole. This application belongs to the field of bolt detection, and specifically refers to a bolt detection device; in order to solve the problem that it is difficult to intuitively evaluate the tensile resistance of multiple bolts in the existing bolt detection process, the application proposes a detection schematic component, which drives the automatic embedded fluorescent bar to move through the limit plate, and the position of the automatic embedded fluorescent bar can be directly observed through the transparent observation window, which also indicates the position of the bolt body fracture. The multiple groups of automatic embedded fluorescent bars indicate the fracture positions of multiple bolt bodies in the transparent observation window. The fracture position on the bolt body can be evaluated through the automatic embedded fluorescent bars displayed in the multiple transparent observation windows, reflecting the tensile resistance of the bolt body.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application discovered that the above technology has at least the following technical problems: the current bolt performance test can evaluate the mechanical properties of the bolt in different environments through fatigue impact resistance testing and corrosion performance testing, but for high aspect ratio rod-shaped preforms, their performance is mainly determined by the internal fiber distribution, and the test accuracy and applicability of traditional bolt performance tests are limited. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a multi-modal performance detection system and method for a rod-shaped preform with a high aspect ratio, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: In the first aspect, the present invention provides a multimodal performance detection system for high aspect ratio rod-shaped preforms, including: a data acquisition module, used to obtain high aspect ratio rod-shaped preform performance detection samples from the same production batch, marked as each preform sample, collect the initial dimensional accuracy data of each preform sample, and analyze the reference abnormal parameters of each preform sample based on the initial dimensional accuracy data of each preform sample.

[0008] The microstructure performance detection module is used to obtain the fiber distribution data of each preform sample, and obtain the microstructure uniformity evaluation value of each preform sample through comprehensive analysis based on the fiber distribution data of each preform sample.

[0009] The dimensional stability evaluation module is used to perform high temperature environment tests on each preform sample to obtain the test dimensional accuracy data of each preform sample, and to obtain the dimensional stability evaluation value of each preform sample through comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample.

[0010] The comprehensive performance evaluation module is used to obtain the comprehensive performance evaluation value of the preform production batch based on the reference abnormal parameters, dimensional stability evaluation value and microstructure uniformity evaluation value of each preform sample through comprehensive analysis, and to provide evaluation feedback on the comprehensive performance of the preform production batch.

[0011] As a further method, the reference abnormal parameters of each preform sample are analyzed based on the initial dimensional accuracy data of each preform sample. The specific analysis process is: a number of dimensional monitoring points are deployed on the surface of each preform sample, including pitch monitoring points, thread depth monitoring points and thread angle monitoring points.

[0012] The initial dimensional accuracy data includes an initial thread pitch of each thread pitch monitoring point, an initial thread depth of each thread depth monitoring point, and an initial thread angle of each thread angle monitoring point.

[0013] The reference specification pitch, reference specification thread depth and reference specification thread angle are obtained from the prefabricated body database, and the reference abnormal parameters of each prefabricated body sample are obtained through comprehensive analysis.

[0014] As a further method, the fiber distribution data of each preform sample is comprehensively analyzed to obtain the microstructure uniformity evaluation value of each preform sample. The specific analysis process is: the fiber distribution data includes the spacing between adjacent fiber bundles and the fiber volume fraction of each type of fiber material.

[0015] The reference value of fiber volume fraction and allowable deviation fiber volume fraction of various fiber materials are obtained from the preform database, and the microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis.

[0016] As a further method, the dimensional stability evaluation value of each preform sample is obtained by comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample. The specific analysis process is: high temperature environment test is performed on each preform sample, and the dimensional accuracy data of each preform sample after the high temperature environment test is collected and marked as the test dimensional accuracy data of each preform sample.

[0017] The test dimensional accuracy data includes a test pitch of each pitch monitoring point, a test thread depth of each thread depth monitoring point, and a test thread angle of each thread angle monitoring point.

[0018] The allowable thermal deviation pitch, allowable thermal deviation thread depth and allowable thermal deviation thread angle are obtained from the preform database, and the dimensional stability evaluation value of each preform sample is obtained through comprehensive analysis.

[0019] As a further method, the comprehensive analysis obtains the comprehensive performance evaluation value of the preform production batch, and the specific analysis process is: obtaining the reference abnormal parameters of each preform sample, and extracting the maximum reference abnormal parameter and marking it as the abnormal critical parameter.

[0020] Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is performed to obtain the comprehensive performance evaluation value of the preform production batch.

[0021] As a further method, the comprehensive performance of the preform production batch is evaluated and fed back, and the specific process is: obtaining the comprehensive performance evaluation threshold of the preform production batch from the preform database, comparing the comprehensive performance evaluation value of the preform production batch with the comprehensive performance evaluation threshold of the preform production batch, if the comprehensive performance evaluation value of the preform production batch is greater than or equal to the comprehensive performance evaluation threshold of the preform production batch, then the preform production batch is evaluated as a preliminary qualified batch, if the comprehensive performance evaluation value of the preform production batch is less than the comprehensive performance evaluation threshold of the preform production batch, then the preform production batch is evaluated as an unqualified batch.

[0022] Conduct a secondary assessment on the initially qualified batches, obtain the assessment results and feed back the assessment results to relevant personnel.

[0023] As a further method, the preliminary qualified batch is subjected to a secondary evaluation, and the specific process is: obtaining the critical number of unqualified samples, the microstructure uniformity evaluation threshold and the dimensional stability evaluation threshold from the preform database.

[0024] The microstructure uniformity evaluation value and dimensional stability evaluation value of each preform sample are compared with the microstructure uniformity evaluation threshold and the dimensional stability evaluation threshold respectively. If the microstructure uniformity evaluation value of a preform sample is greater than or equal to the microstructure uniformity evaluation threshold, and the dimensional stability evaluation value of the preform sample is greater than or equal to the dimensional stability evaluation threshold, the preform sample is marked as a qualified sample.

[0025] If the microstructure uniformity evaluation value of a preform sample is less than the microstructure uniformity evaluation threshold, or the dimensional stability evaluation value of the preform sample is less than the dimensional stability evaluation threshold, the preform sample is marked as an unqualified sample.

[0026] Count the number of unqualified samples in the preliminary qualified batch, and compare the number of unqualified samples with the critical number of unqualified samples. If the number of unqualified samples is less than the critical number of unqualified samples, the preliminary qualified batch will be evaluated as a formal qualified batch; if the number of unqualified samples is greater than or equal to the critical number of unqualified samples, the preliminary qualified batch will be evaluated as an unqualified batch.

[0027] The second aspect of the present invention provides a multimodal performance detection method for a high aspect ratio rod-shaped preform, comprising: obtaining performance detection samples of high aspect ratio rod-shaped preforms from the same production batch, marking them as preform samples, collecting initial dimensional accuracy data of each preform sample, and analyzing the reference abnormal parameters of each preform sample based on the initial dimensional accuracy data of each preform sample.

[0028] The fiber distribution data of each preform sample is obtained, and based on the fiber distribution data of each preform sample, a microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis.

[0029] A high temperature environment test is performed on each preform sample to obtain the test dimensional accuracy data of each preform sample. According to the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample, a comprehensive analysis is performed to obtain the dimensional stability evaluation value of each preform sample.

[0030] Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is conducted to obtain the comprehensive performance evaluation value of the preform production batch, and evaluation feedback is provided on the comprehensive performance of the preform production batch.

[0031] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0032] (1) The present invention provides a multimodal performance detection system and method for high aspect ratio rod-shaped preforms. The system analyzes the initial dimensional accuracy data of each preform sample based on the characteristics of the high aspect ratio rod-shaped preforms. The fiber distribution data is analyzed through microstructure performance detection, which can accurately evaluate the uniformity of the preform microstructure and improve the accuracy of performance evaluation. By evaluating the comprehensive performance of the preform samples, it is helpful to subsequently analyze the performance of the preform in different application scenarios and ensure the reliability and applicability of the preform in various complex environments.

[0033] (2) The present invention quantitatively evaluates the dimensional accuracy of the bolt preform by comprehensively considering the pitch, thread depth and angle, which can make the threaded connection tighter and more stable, reduce the risk of failure caused by loosening, slipping or leakage, and ensure that the threaded connection meets technical specifications and quality requirements. By analyzing the relationship between pitch, thread depth and angle, more accurate guidance can be provided for the design and manufacture of threads, which helps to develop a more optimized threaded connection solution.

[0034] (3) The present invention can obtain a more accurate microstructure uniformity evaluation value by comprehensively considering the spacing between adjacent fiber bundles and the fiber volume fraction, which is helpful to measure the quality of the preform and provide a basis for product quality control and optimization. Understanding the relationship between the spacing between adjacent fiber bundles and the fiber volume fraction can provide more accurate guidance for the manufacturing process of high aspect ratio rod-shaped preforms, making the microstructure of the preform more uniform, thereby improving the performance stability of the material and achieving better microstructure uniformity.

[0035] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0037] Figure 2 It is a schematic diagram of the method flow of the present invention.

[0038] Figure 3 The figure is a curve showing the functional relationship between the pitch variation value and the dimensional stability evaluation value involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0041] Reference Figure 1 As shown, the first aspect of the present invention provides a multimodal performance detection system for high aspect ratio rod-shaped preforms, including: a data acquisition module, used to obtain high aspect ratio rod-shaped preform performance detection samples from the same production batch, marked as each preform sample, collect initial dimensional accuracy data of each preform sample, and analyze the reference abnormal parameters of each preform sample based on the initial dimensional accuracy data of each preform sample.

[0042] It should be understood that the high aspect ratio rod-shaped preform in this embodiment is a new type of preform. The core is a cylindrical structure composed of multiple fiber bundles arranged in the same direction, which is used for shear or tensile load bearing. Its direction is parallel to the bolt axis, and the circumferential shear load can be evenly borne without difference. The cladding is a tubular fiber bundle braided structure wrapped around the outer surface of the core structure by a braiding method. The core is wrapped to maintain the cylindrical shape and is used to process the thread at the same time, so that the fiber reinforcement in the thread teeth is evenly distributed, ensuring that the strength of the thread teeth is consistent on the entire circumference, and avoiding the phenomenon of local broken teeth. At the same time, the core and cladding preforms are separated, so that the cracks in the thread teeth will not extend into the core body, so that the maximum load of the thread teeth and the maximum load of the stud can be achieved at the same time in theory.

[0043] The novel preform structure prepared by the present invention is closely combined with the core through the suturing effect of the molten glass fibers, which helps the thread teeth of the outer shell of the cladding to have better toughness, and the core unidirectional fiber bundles give full play to the fiber toughness. When the core structure is kept straight, a fiber bundle cladding is woven on its outer peripheral surface by a weaving method, and the fiber bundle weaving tension is set, so that the core structure is subjected to the compressive stress of the cladding structure. This pretension not only allows the preform to maintain a straight state and achieve a higher aspect ratio, but also helps the core and cladding to contact more tightly, thereby improving the load transfer efficiency between the two.

[0044] The microstructure performance detection module is used to obtain the fiber distribution data of each preform sample, and obtain the microstructure uniformity evaluation value of each preform sample through comprehensive analysis based on the fiber distribution data of each preform sample.

[0045] The dimensional stability evaluation module is used to perform high temperature environment tests on each preform sample to obtain the test dimensional accuracy data of each preform sample, and to obtain the dimensional stability evaluation value of each preform sample through comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample.

[0046] The comprehensive performance evaluation module is used to obtain the comprehensive performance evaluation value of the preform production batch based on the reference abnormal parameters, dimensional stability evaluation value and microstructure uniformity evaluation value of each preform sample through comprehensive analysis, and to provide evaluation feedback on the comprehensive performance of the preform production batch.

[0047] Specifically, according to the initial dimensional accuracy data of each preform sample, the reference abnormal parameters of each preform sample are analyzed. The specific analysis process is: a number of dimensional monitoring points are deployed on the surface of each preform sample, including each pitch monitoring point, thread depth monitoring point and thread angle monitoring point.

[0048] It should be understood that the size monitoring point in this embodiment is a monitoring point deployed at the top of the thread.

[0049] The initial dimensional accuracy data includes an initial thread pitch of each thread pitch monitoring point, an initial thread depth of each thread depth monitoring point, and an initial thread angle of each thread angle monitoring point.

[0050] It should be understood that the pitch in this embodiment refers to the axial distance between two adjacent spirals on the thread, that is, the axial distance between the pitch monitoring point and the corresponding point of the adjacent thread. The initial pitch can be obtained by using a thread micrometer or a special pitch measuring tool, or by directly collecting the distance between the corresponding points of two adjacent teeth on the mid-diameter line through a laser scanner. Appropriate and uniform pitch can make the threaded connection evenly stressed during the screwing process and avoid local stress concentration. When the pitch meets the design requirements, the bolt and nut fit tightly, and when subjected to external forces such as tension and shear force, it is not easy to loosen or slip, thereby ensuring the reliability and stability of the connection.

[0051] It should be understood that the thread depth in this embodiment refers to the vertical distance from the top of the thread to the bottom of the thread on the side of the thread. The initial thread depth of each thread depth monitoring point can be directly collected by a thread depth gauge or a laser scanner. Sufficient thread depth can provide a larger contact area and friction, so that the threaded connection has higher strength when subjected to axial tension and shear force. If the thread depth is insufficient, the connection part may become loose or break easily. The thread depth determines the screwing length of the bolt and the nut. The appropriate screwing length can ensure the reliability of the connection while avoiding material waste and installation difficulties caused by excessive screwing length.

[0052] It should be understood that the thread angle in this embodiment refers to the helix angle of the thread, that is, the angle between the spiral line of the thread on the cylindrical surface and the cylindrical axis. This angle determines the tightness and strength of the thread. The initial thread angle of each thread angle monitoring point can be directly collected by a universal angle ruler or a laser scanner. The correct thread angle can enable the bolt and nut to cooperate smoothly during the screwing process, avoiding jamming or inability to screw in. If the thread angle deviation is large, the threaded connection cannot be installed normally, affecting the production schedule and the normal operation of the equipment.

[0053] The reference specification pitch, reference specification thread depth and reference specification thread angle are obtained from the prefabricated body database, and the reference abnormal parameters of each prefabricated body sample are obtained through comprehensive analysis.

[0054] In a specific embodiment, the allowable deviation pitch, the allowable deviation thread depth and the allowable deviation thread angle are obtained from the preform database, and the specific numerical expressions of the reference abnormal parameters of each preform sample are:

[0055] ;

[0056] In the formula, represents the reference abnormal parameter of the i-th preform sample, represents the initial pitch of the jth pitch monitoring point of the i-th preform sample, represents the initial thread depth of the qth thread depth monitoring point of the i-th preform sample, represents the initial thread angle of the tth thread angle monitoring point of the i-th preform sample, Indicates the reference specification pitch, Indicates the reference specification thread depth, Indicates the reference specification thread angle, Indicates the allowable deviation pitch, Indicates the allowable deviation thread depth, Indicates the allowable deviation thread angle, Indicates the abnormal parameter influence factor corresponding to the preset pitch, Indicates the abnormal parameter influence factor corresponding to the preset thread depth, represents the abnormal parameter influencing factor corresponding to the preset thread angle, i represents the number of each preform sample, i=1,2,3,...,n, n represents the total number of preform samples, j represents the number of each pitch monitoring point, j=1,2,3,...,m, m represents the total number of pitch monitoring points, q represents the number of each thread depth monitoring point, q=1,2,3,...,k, k represents the total number of thread depth monitoring points, t represents the number of each thread angle monitoring point, t=1,2,3,...,s, s represents the total number of thread angle monitoring points.

[0057] It should be understood that in this embodiment, the pitch, thread depth and thread angle are combined to obtain a reference abnormal parameter through comprehensive analysis. In the formula, there is a close relationship between the pitch, thread depth and thread angle. The pitch determines the spacing between the thread teeth, while the thread depth and angle jointly affect the load-bearing capacity and tightness of the thread. If the pitch is large, but the thread depth is insufficient or the angle is inappropriate, the strength of the threaded connection may be reduced, and it is easy to loosen or slip. On the contrary, if the thread depth is too large or the angle is too steep, the effect of the pitch may not be fully exerted, affecting the smoothness of the connection. By comprehensively considering the pitch, thread depth and angle, the threaded connection can be made tighter and more stable, reducing the risk of failure caused by looseness, slippage or leakage, and ensuring that the threaded connection meets technical specifications and quality requirements. By analyzing the relationship between the pitch, thread depth and angle, more accurate guidance can be provided for the design and manufacture of threads, which helps to formulate a more optimized threaded connection scheme.

[0058] Table 1 Examples of reference abnormal parameter data of prefabricated samples

[0059] Sample No. Initial pitch (mm) Initial thread depth (mm) Initial thread angle (degrees) Refer to abnormal parameters 1 2.05 1.55 61 0.567 2 1.96 1.46 59 0.483 3 2 1.49 60 0.053 4 2.1 1.6 62 1.133 5 1.98 1.48 58 0.467

[0060] In a specific embodiment, m=k=s=1, =2mm, =0.1mm, =1.5mm, =0.075mm, =60°, =2°, =0.3, =0.4, =0.3, for five groups of preform samples, examples of reference abnormal parameter data of each preform sample are shown in Table 1. In this embodiment, the reference abnormal parameter of each preform sample is used to quantitatively evaluate the abnormal degree of dimensional accuracy of each preform sample, and provide a basis for subsequent sample data analysis. The more the initial pitch, initial thread depth and initial thread angle deviate from the reference specification value, the larger the corresponding reference abnormal parameter is, indicating that the dimensional accuracy of the preform sample is more abnormal.

[0061] In this embodiment , and They are the abnormal parameter influencing factors corresponding to the pitch, thread depth and thread angle preset in the preform database, respectively, and represent the numerical values ​​of the influence degree of the pitch, thread depth and thread angle on the reference abnormal parameters, which can be directly obtained from the preform database when used. For example, a mapping set is formed by combining the specification diameter of the preform with the abnormal parameter influencing factors corresponding to the pitch, thread depth and thread angle preset in the preform database, and the abnormal parameter influencing factors corresponding to the pitch, thread depth and thread angle are obtained according to the specification diameter of the preform input mapping set, wherein the mapping relationship is a one-to-many relationship. In this embodiment, the value range of the influencing factor is between 0 and 1.

[0062] Specifically, according to the fiber distribution data of each preform sample, a microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis. The specific analysis process is as follows: the fiber distribution data includes the spacing between adjacent fiber bundles and the fiber volume fraction of each type of fiber material.

[0063] It should be understood that the spacing between adjacent fiber bundles in this embodiment refers to the spacing between the center points of adjacent fiber bundles in the core structure of the preform sample, and adjacent fiber bundles refer to fiber bundles that are close to each other in space and are usually arranged side by side or in layers. The tomographic image of the core structure of the preform sample can be obtained by X-ray tomography, and the fiber bundle spacing at different positions can be directly measured. It can be understood that there is an adjacent fiber bundle spacing between every two adjacent fiber bundles. The consistency and reliability of the composite material need to meet specific quality and performance standards by controlling the fiber bundle spacing. Uneven fiber bundle spacing may cause stress concentration, thereby affecting the long-term performance of the material.

[0064] It should be understood that the fiber volume fraction of each type of fiber material in this embodiment refers to the proportion of each type of fiber material in the total volume of the preform sample, wherein each type of fiber material includes carbon fiber, silicon carbide fiber and silicon nitride fiber, and the fiber volume fraction of each type of fiber material can be directly obtained by ultrasonic testing. Accurate determination of the fiber volume fraction is crucial to optimizing the design and performance of composite materials. By adjusting the fiber volume fraction, the strength, stiffness and fatigue resistance of the material can be improved, while the weight and cost of the material can be controlled.

[0065] The reference value of fiber volume fraction and allowable deviation fiber volume fraction of various fiber materials are obtained from the preform database, and the microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis.

[0066] In a specific embodiment, the numerical expression of the microstructure uniformity evaluation value of each preform sample is:

[0067] ;

[0068] In the formula, represents the microstructure uniformity evaluation value of the i-th preform sample, e represents the natural constant, represents the distance between the dth adjacent fiber bundles of the i-th preform sample, represents the fiber volume fraction of the rth type of fiber material of the i-th preform sample, represents the reference value of fiber volume fraction of type r fiber material, represents the allowable deviation fiber volume fraction, Indicates the microstructure uniformity influence factor corresponding to the preset fiber bundle spacing, represents the microstructure uniformity influencing factor corresponding to the preset fiber volume fraction, d represents the number of the distances between adjacent fiber bundles, d=1,2,3,...,w, w represents the total number of distances between adjacent fiber bundles, r represents the number of each fiber material, r=1,2,3,...,h, h represents the number of types of fiber materials.

[0069] It should be understood that in this embodiment, the distance between adjacent fiber bundles and the fiber volume fraction are combined to obtain a microstructure uniformity evaluation value through comprehensive analysis. There is a close correlation between the distance between adjacent fiber bundles and the fiber volume fraction in the formula, and the distance between adjacent fiber bundles will affect the distribution of the fiber volume fraction. If the distance between fiber bundles is too small, it may cause fiber accumulation, making the local fiber volume fraction too high; conversely, if the distance is too large, the fiber distribution may be too sparse, reducing the fiber volume fraction. The fiber volume fraction will also affect the distance between adjacent fiber bundles in turn. A higher fiber volume fraction may reduce the distance between fiber bundles, while a lower fiber volume fraction may increase the distance. The distance between adjacent fiber bundles and the fiber volume fraction jointly determine the microstructure uniformity of the high aspect ratio rod-shaped preform. Appropriate fiber bundle spacing and stable fiber volume fraction can make the preform have good uniformity at the microscopic level, thereby ensuring the stability and reliability of its performance.

[0070] In this embodiment, by comprehensively considering the spacing between adjacent fiber bundles and the fiber volume fraction, the microstructure of the preform can be made more uniform, thereby improving the performance stability of the material. Understanding the relationship between the spacing between adjacent fiber bundles and the fiber volume fraction can provide more accurate guidance for the manufacturing process of high aspect ratio rod-shaped preforms. By adjusting process parameters such as fiber arrangement, impregnation process, etc., the fiber bundle spacing and fiber volume fraction can be controlled to achieve better microstructural uniformity. By comprehensively analyzing the spacing between adjacent fiber bundles and the fiber volume fraction, a more accurate microstructural uniformity evaluation value can be obtained, which helps to measure the quality of the preform and provide a basis for product quality control and optimization.

[0071] It should be understood that the microstructure uniformity evaluation value of each preform sample in the present embodiment is used to quantitatively evaluate the microstructure uniformity of each preform sample, which is jointly determined by the spacing between adjacent fiber bundles and the fiber volume fraction. The smaller the deviation between the spacing between adjacent fiber bundles, the closer the fiber volume fraction of each type of fiber material is to the corresponding reference value, and the larger the corresponding microstructure uniformity evaluation value is, indicating that the microstructure of the preform sample is more uniform.

[0072] In this embodiment and They are respectively the microstructure uniformity influencing factors corresponding to the fiber bundle spacing and fiber volume fraction preset in the preform database, and respectively represent the numerical values ​​of the degree of influence of the fiber bundle spacing and fiber volume fraction on the microstructure uniformity evaluation value, and can be directly obtained from the preform database when used. For example, a mapping set is formed by combining the specification diameter of the preform with the microstructure uniformity influencing factors corresponding to the fiber bundle spacing and fiber volume fraction preset in the preform database, and the microstructure uniformity influencing factors corresponding to the fiber bundle spacing and fiber volume fraction are obtained according to the specification diameter of the preform input mapping set, wherein the mapping relationship is a one-to-many relationship. In this embodiment, the value range of the influencing factor is between 0 and 1.

[0073] Specifically, based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample, a comprehensive analysis is performed to obtain the dimensional stability evaluation value of each preform sample. The specific analysis process is: perform a high-temperature environment test on each preform sample, and collect the dimensional accuracy data of each preform sample after the high-temperature environment test, which are marked as the test dimensional accuracy data of each preform sample.

[0074] It should be understood that in this embodiment, each preform sample is subjected to a high temperature environment test, and the specific process is: obtaining the working environment temperature and the working simulation duration of the preform sample, that is, the working environment temperature and the possible maximum working duration of the same type of product actually put into use, and marking them as the test temperature and the test duration, respectively. The high temperature environment test is performed according to the test temperature and the test duration to simulate the long-term high temperature working conditions that the preform sample may face in actual use.

[0075] In a specific embodiment, the high temperature test of the preform sample will be carried out in a high temperature furnace that can accurately control and maintain the set temperature. During the test, the preform sample is placed on a sample holder in the high temperature furnace to ensure uniform heating. The temperature in the furnace is monitored in real time using a temperature recorder to ensure that the temperature remains stable throughout the test. During the test, the sample status should be checked regularly and any visible changes should be recorded. After the test is completed, the sample is removed from the high temperature furnace and allowed to cool naturally, and the dimensional accuracy data of the preform sample after the high temperature test is collected.

[0076] The test dimensional accuracy data includes a test pitch of each pitch monitoring point, a test thread depth of each thread depth monitoring point, and a test thread angle of each thread angle monitoring point.

[0077] The allowable thermal deviation pitch, allowable thermal deviation thread depth and allowable thermal deviation thread angle are obtained from the preform database, and the dimensional stability evaluation value of each preform sample is obtained through comprehensive analysis.

[0078] It should be understood that the allowable thermal deviation pitch, allowable thermal deviation thread depth and allowable thermal deviation thread angle in this embodiment refer to the maximum allowable deviation values ​​of pitch, thread depth and thread angle when working in a high temperature environment.

[0079] In a specific embodiment, the numerical expression of the dimensional stability evaluation value of each preform sample is:

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] In the formula, represents the dimensional stability evaluation value of the i-th preform sample, represents the pitch variation value of the i-th preform sample, represents the thread depth variation value of the i-th preform sample, represents the thread angle variation value of the i-th preform sample, represents the test pitch of the jth pitch monitoring point of the i-th preform sample, represents the test thread depth of the qth thread depth monitoring point of the i-th preform sample, represents the test thread angle of the tth thread angle monitoring point of the i-th preform sample, Indicates the allowable thermal deviation pitch, Indicates the allowable thermal deviation thread depth, Indicates the allowable thermal deviation thread angle, Indicates the dimensional stability influencing factor corresponding to the preset pitch, Indicates the dimensional stability influencing factor corresponding to the preset thread depth, Indicates the dimensional stability influencing factor corresponding to the preset thread angle.

[0085] like Figure 3 As shown, in a specific embodiment, =0.3, =0.4, =0.3, =1, if =0.2, the functional relationship between the pitch variation value and the dimensional stability evaluation value is shown in curve a; if =0.5, the functional relationship between the pitch variation value and the dimensional stability evaluation value is shown in curve b; if =1.6, the functional relationship between the pitch variation value and the dimensional stability evaluation value is shown in curve c.

[0086] In this embodiment, the dimensional stability evaluation value of each preform sample is used to quantitatively evaluate the dimensional stability of each preform sample in a high temperature environment, the pitch variation value is used to measure the variation degree of the pitch of the preform sample in a high temperature environment, the thread depth variation value is used to measure the variation degree of the thread depth of the preform sample in a high temperature environment, and the thread angle variation value is used to measure the variation degree of the thread angle of the preform sample in a high temperature environment. The larger the pitch variation value, the thread depth variation value, and the thread angle variation value, the smaller the corresponding dimensional stability evaluation value, indicating that the dimensional stability of the preform sample in a high temperature environment is worse.

[0087] It should be understood that the more the test pitch deviates from the initial pitch, the greater the pitch variation value, and the greater the variation degree of the pitch of the preform sample in a high temperature environment; the more the test thread depth deviates from the initial thread depth, the greater the thread depth variation value, and the greater the variation degree of the thread depth of the preform sample in a high temperature environment; the more the test thread angle deviates from the initial thread angle, the greater the thread angle variation value, and the greater the variation degree of the thread angle of the preform sample in a high temperature environment.

[0088] It should be understood that in this embodiment, the pitch variation value, thread depth variation value and thread angle variation value are combined to obtain a dimensional stability evaluation value through a comprehensive analysis. The pitch variation value, thread depth variation value and thread angle variation value are interrelated and jointly reflect the dimensional change of the thread structure under a high temperature environment. If the pitch variation is large, it may affect the fitting accuracy of the thread, thereby causing the thread depth and angle to change. The thread depth variation value and the thread angle variation value will also affect the pitch variation in turn. If the thread depth decreases or the angle changes, the measured value of the pitch may change, thereby affecting the size of the pitch variation value. The pitch variation value, thread depth variation value and thread angle variation value jointly determine the dimensional stability of the thread structure under a high temperature environment. The appropriate variation value range can ensure that the thread structure maintains a relatively stable size at high temperatures, thereby ensuring the reliability and sealing of the connection.

[0089] This embodiment can better evaluate the reliability of threaded connections in high temperature environments by comprehensively considering the pitch variation value, thread depth variation value, and thread angle variation value. If the variation value is small, it means that the size of the threaded structure changes less at high temperatures, and the tightness and stability of the connection are higher. By comprehensively analyzing the pitch variation value, thread depth variation value, and thread angle variation value, a more accurate dimensional stability evaluation value can be obtained, which can help measure the performance of the threaded structure in a high temperature environment and provide a basis for product quality control and optimization.

[0090] In this embodiment , and The dimensional stability influencing factors corresponding to the pitch, thread depth and thread angle preset in the preform database respectively represent the numerical values ​​of the influence degree of the pitch, thread depth and thread angle on the dimensional stability evaluation value, and can be directly obtained from the preform database when used. For example, a mapping set is formed by combining the specification diameter of the preform with the dimensional stability influencing factors corresponding to the pitch, thread depth and thread angle preset in the preform database, and the dimensional stability influencing factors corresponding to the pitch, thread depth and thread angle are obtained according to the specification diameter of the preform input mapping set, wherein the mapping relationship is a one-to-many relationship. The value range of the influencing factor in this embodiment is between 0 and 1.

[0091] Specifically, a comprehensive performance evaluation value of a preform production batch is obtained through comprehensive analysis. The specific analysis process is: obtaining reference abnormal parameters of each preform sample, and extracting the maximum reference abnormal parameter and marking it as an abnormal critical parameter.

[0092] Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is performed to obtain the comprehensive performance evaluation value of the preform production batch.

[0093] In a specific embodiment, the specific numerical expression of the comprehensive performance evaluation value of the preform production batch is:

[0094] ;

[0095] In the formula, Represents the comprehensive performance evaluation value of the preform production batch, Indicates abnormal critical parameters, represents the reference abnormal parameter of the i-th preform sample, represents the microstructure uniformity evaluation value of the i-th preform sample, represents the dimensional stability evaluation value of the i-th preform sample, Indicates the comprehensive performance evaluation influencing factor corresponding to the preset microstructure uniformity evaluation value, It represents the comprehensive performance evaluation influencing factor corresponding to the preset dimensional stability evaluation value, i represents the number of each preform sample, i=1,2,3,...,n, and n represents the total number of preform samples.

[0096] It should be understood that the comprehensive performance evaluation value of the preform production batch in this embodiment is used to quantitatively evaluate the comprehensive performance of the high aspect ratio rod-shaped preforms of the production batch corresponding to the preform sample. The larger the microstructure uniformity evaluation value and the dimensional stability evaluation value of each preform sample, the larger the corresponding comprehensive performance evaluation value of the preform production batch, indicating that the comprehensive performance of the high aspect ratio rod-shaped preform is better. In the formula, the reference abnormal parameter of each preform sample is used to measure the degree of influence of the comprehensive performance of each preform sample on the overall performance evaluation. If the reference abnormal parameter of a preform sample is larger, it indicates that the deviation between the actual size of the preform sample and the specification size is larger, and the corresponding comprehensive performance of the preform sample The smaller the degree of influence on the overall performance evaluation is, it helps to improve the accuracy of the overall performance evaluation.

[0097] It should be understood that in this embodiment and The influencing factors of comprehensive performance evaluation corresponding to the microstructure uniformity evaluation value and the dimensional stability evaluation value preset in the preform database respectively represent the numerical values ​​of the influence degree of the microstructure uniformity evaluation value and the dimensional stability evaluation value on the comprehensive performance evaluation value of the preform production batch respectively, and can be directly obtained from the preform database when used. For example, the specification diameter of the preform and the comprehensive performance evaluation influencing factors corresponding to the microstructure uniformity evaluation value and the dimensional stability evaluation value preset in the preform database form a mapping set, and the mapping set is input according to the specification diameter of the preform to obtain the comprehensive performance evaluation influencing factors corresponding to the microstructure uniformity evaluation value and the dimensional stability evaluation value, wherein the mapping relationship is a one-to-many relationship. In this embodiment, the value range of the influencing factor is between 0 and 1.

[0098] In this embodiment, the microstructure uniformity evaluation value and the dimensional stability evaluation value are combined to obtain the comprehensive performance evaluation value of the preform production batch through comprehensive analysis. The microstructure uniformity evaluation value and the dimensional stability evaluation value in the formula will affect each other. If the microstructure uniformity of the preform is good, then under high temperature and other environments, its internal stress distribution is relatively uniform, which is more conducive to maintaining dimensional stability. By comprehensively considering the microstructure uniformity and dimensional stability, the quality and reliability of the preform can be more comprehensively evaluated, which helps to understand the performance of the preform in different application scenarios and provide a decision-making basis for the application of the product.

[0099] Specifically, the comprehensive performance of the preform production batch is evaluated and fed back, and the specific process is: obtain the comprehensive performance evaluation threshold of the preform production batch from the preform database, compare the comprehensive performance evaluation value of the preform production batch with the comprehensive performance evaluation threshold of the preform production batch, if the comprehensive performance evaluation value of the preform production batch is greater than or equal to the comprehensive performance evaluation threshold of the preform production batch, then the preform production batch is evaluated as a preliminary qualified batch, if the comprehensive performance evaluation value of the preform production batch is less than the comprehensive performance evaluation threshold of the preform production batch, then the preform production batch is evaluated as an unqualified batch.

[0100] Conduct a secondary assessment on the initially qualified batches, obtain the assessment results and feed back the assessment results to relevant personnel.

[0101] Specifically, a secondary evaluation is conducted on the preliminary qualified batches, and the specific process is as follows: the critical number of unqualified samples, the microstructure uniformity evaluation threshold, and the dimensional stability evaluation threshold are obtained from the preform database.

[0102] It should be understood that the critical number of unqualified samples in this embodiment is a preset sample quantity threshold. When the number of unqualified samples reaches or exceeds this limit, the entire batch of products or processes may be considered unqualified. It is generally determined directly according to industry standards or internal quality requirements.

[0103] The microstructure uniformity evaluation value and dimensional stability evaluation value of each preform sample are compared with the microstructure uniformity evaluation threshold and the dimensional stability evaluation threshold respectively. If the microstructure uniformity evaluation value of a preform sample is greater than or equal to the microstructure uniformity evaluation threshold, and the dimensional stability evaluation value of the preform sample is greater than or equal to the dimensional stability evaluation threshold, the preform sample is marked as a qualified sample.

[0104] If the microstructure uniformity evaluation value of a preform sample is less than the microstructure uniformity evaluation threshold, or the dimensional stability evaluation value of the preform sample is less than the dimensional stability evaluation threshold, the preform sample is marked as an unqualified sample.

[0105] Count the number of unqualified samples in the preliminary qualified batch, and compare the number of unqualified samples with the critical number of unqualified samples. If the number of unqualified samples is less than the critical number of unqualified samples, the preliminary qualified batch will be evaluated as a formal qualified batch; if the number of unqualified samples is greater than or equal to the critical number of unqualified samples, the preliminary qualified batch will be evaluated as an unqualified batch.

[0106] In a specific embodiment, if the production batch corresponding to the preform sample is an unqualified batch, the production activities of the preform batch need to be stopped immediately, and a technical team is organized to troubleshoot the production line of the batch. If the production batch corresponding to the preform sample is a formal qualified batch, the preform is shipped according to the normal procedure and delivered to the customer or used in the next production link.

[0107] The preform database is used to store relevant data of high aspect ratio rod-shaped preforms, including reference specification pitch, reference specification thread depth, reference specification thread angle, etc. The data in the preform database can be directly obtained from the industry standard related database, or obtained by collecting experimental data.

[0108] In a specific embodiment, the present invention provides a multimodal performance detection system and method for a high aspect ratio rod-shaped preform. According to the characteristics of the high aspect ratio rod-shaped preform, the initial dimensional accuracy data of each preform sample is analyzed, and the fiber distribution data is analyzed through microstructure performance detection, so that the uniformity of the microstructure of the preform can be accurately evaluated, thereby improving the accuracy of performance evaluation. By evaluating the comprehensive performance of the preform sample, it is helpful to subsequently analyze the performance of the preform in different application scenarios, and ensure the reliability and applicability of the preform in various complex environments.

[0109] Reference Figure 2 As shown, the second aspect of the present invention provides a multimodal performance detection method for a high aspect ratio rod-shaped preform, comprising: obtaining performance detection samples of high aspect ratio rod-shaped preforms from the same production batch, marking them as preform samples, collecting initial dimensional accuracy data of each preform sample, and analyzing the reference abnormal parameters of each preform sample based on the initial dimensional accuracy data of each preform sample.

[0110] The fiber distribution data of each preform sample is obtained, and based on the fiber distribution data of each preform sample, a microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis.

[0111] A high temperature environment test is performed on each preform sample to obtain the test dimensional accuracy data of each preform sample. According to the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample, a comprehensive analysis is performed to obtain the dimensional stability evaluation value of each preform sample.

[0112] Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is conducted to obtain the comprehensive performance evaluation value of the preform production batch, and evaluation feedback is provided on the comprehensive performance of the preform production batch.

[0113] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. A multimodal performance detection system for a high aspect ratio rod-shaped preform, characterized in that: include: The data acquisition module is used to obtain performance test samples of high aspect ratio rod-shaped preforms from the same production batch, mark them as preform samples, collect initial dimensional accuracy data of each preform sample, and analyze and obtain reference abnormal parameters of each preform sample based on the initial dimensional accuracy data of each preform sample; A microstructure performance detection module is used to obtain the fiber distribution data of each preform sample, and obtain the microstructure uniformity evaluation value of each preform sample through comprehensive analysis based on the fiber distribution data of each preform sample; The dimensional stability evaluation module is used to perform a high temperature environment test on each preform sample to obtain the test dimensional accuracy data of each preform sample, and obtain the dimensional stability evaluation value of each preform sample through comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample; A comprehensive performance evaluation module is used to obtain a comprehensive performance evaluation value of a preform production batch based on the reference abnormal parameters, dimensional stability evaluation value and microstructure uniformity evaluation value of each preform sample through comprehensive analysis, and to provide evaluation feedback on the comprehensive performance of the preform production batch; The reference abnormal parameters of each preform sample are analyzed based on the initial dimensional accuracy data of each preform sample. The specific analysis process is: deploying a number of dimensional monitoring points on the surface of each preform sample, including each pitch monitoring point, thread depth monitoring point and thread angle monitoring point; The initial dimensional accuracy data includes the initial pitch of each pitch monitoring point, the initial thread depth of each thread depth monitoring point, and the initial thread angle of each thread angle monitoring point; Obtain reference specification thread pitch, reference specification thread depth and reference specification thread angle from the prefabricated body database, and comprehensively analyze to obtain reference abnormal parameters of each prefabricated body sample; The microstructure uniformity evaluation value of each preform sample is obtained by comprehensive analysis based on the fiber distribution data of each preform sample. The specific analysis process is as follows: the fiber distribution data includes the distance between each adjacent fiber bundle and the fiber volume fraction of each type of fiber material; The reference value of fiber volume fraction and allowable deviation fiber volume fraction of various fiber materials are obtained from the preform database, and the microstructure uniformity evaluation value of each preform sample is obtained through comprehensive analysis.

2. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 1, characterized in that: The dimensional stability evaluation value of each preform sample is obtained by comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample. The specific analysis process is as follows: Performing a high temperature environment test on each preform sample, and collecting dimensional accuracy data of each preform sample after the high temperature environment test, and marking it as the test dimensional accuracy data of each preform sample; The test dimensional accuracy data includes the test pitch of each pitch monitoring point, the test thread depth of each thread depth monitoring point, and the test thread angle of each thread angle monitoring point; The allowable thermal deviation pitch, allowable thermal deviation thread depth and allowable thermal deviation thread angle are obtained from the preform database, and the dimensional stability evaluation value of each preform sample is obtained through comprehensive analysis.

3. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 2, characterized in that: The comprehensive analysis obtains the comprehensive performance evaluation value of the preform production batch, and the specific analysis process is as follows: Obtaining reference abnormal parameters of each preform sample, and extracting the maximum reference abnormal parameter and marking it as an abnormal critical parameter; Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is performed to obtain the comprehensive performance evaluation value of the preform production batch.

4. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 3, characterized in that: The specific process of evaluating and feeding back the comprehensive performance of the prefabricated body production batch is as follows: Obtaining a comprehensive performance evaluation threshold of a preform production batch from a preform database, comparing the comprehensive performance evaluation value of the preform production batch with the comprehensive performance evaluation threshold of the preform production batch, if the comprehensive performance evaluation value of the preform production batch is greater than or equal to the comprehensive performance evaluation threshold of the preform production batch, then evaluating the preform production batch as a preliminary qualified batch, if the comprehensive performance evaluation value of the preform production batch is less than the comprehensive performance evaluation threshold of the preform production batch, then evaluating the preform production batch as an unqualified batch; Conduct a secondary assessment on the initially qualified batches, obtain the assessment results and feed back the assessment results to relevant personnel.

5. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 4, characterized in that: The specific process of conducting a secondary evaluation on the initially qualified batches is as follows: Obtaining the critical number of unqualified samples, the microstructure uniformity evaluation threshold and the dimensional stability evaluation threshold from the preform database; The microstructure uniformity evaluation value and the dimensional stability evaluation value of each preform sample are compared with the microstructure uniformity evaluation threshold and the dimensional stability evaluation threshold, respectively. If the microstructure uniformity evaluation value of a preform sample is greater than or equal to the microstructure uniformity evaluation threshold, and the dimensional stability evaluation value of the preform sample is greater than or equal to the dimensional stability evaluation threshold, the preform sample is marked as a qualified sample; If the microstructure uniformity evaluation value of a preform sample is less than the microstructure uniformity evaluation threshold, or the dimensional stability evaluation value of the preform sample is less than the dimensional stability evaluation threshold, the preform sample is marked as an unqualified sample; Count the number of unqualified samples in the preliminary qualified batch, and compare the number of unqualified samples with the critical number of unqualified samples. If the number of unqualified samples is less than the critical number of unqualified samples, the preliminary qualified batch will be evaluated as a formal qualified batch; if the number of unqualified samples is greater than or equal to the critical number of unqualified samples, the preliminary qualified batch will be evaluated as an unqualified batch.

6. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 1, characterized in that: The specific numerical expression of the reference abnormal parameter of each preform sample is: ； In the formula, represents the reference abnormal parameter of the i-th preform sample, represents the initial pitch of the jth pitch monitoring point of the i-th preform sample, represents the initial thread depth of the qth thread depth monitoring point of the i-th preform sample, represents the initial thread angle of the tth thread angle monitoring point of the i-th preform sample, Indicates the reference specification pitch, Indicates the reference specification thread depth, Indicates the reference specification thread angle, Indicates the allowable deviation pitch, Indicates the allowable deviation thread depth, Indicates the allowable deviation thread angle, Indicates the abnormal parameter influence factor corresponding to the preset pitch, Indicates the abnormal parameter influence factor corresponding to the preset thread depth, represents the abnormal parameter influencing factor corresponding to the preset thread angle, i represents the number of each preform sample, i=1,2,3,...,n, n represents the total number of preform samples, j represents the number of each pitch monitoring point, j=1,2,3,...,m, m represents the total number of pitch monitoring points, q represents the number of each thread depth monitoring point, q=1,2,3,...,k, k represents the total number of thread depth monitoring points, t represents the number of each thread angle monitoring point, t=1,2,3,...,s, s represents the total number of thread angle monitoring points.

7. The multimodal performance detection system for a high aspect ratio rod-shaped preform according to claim 1, characterized in that: The specific numerical expression of the comprehensive performance evaluation value of the preform production batch is: ； In the formula, Represents the comprehensive performance evaluation value of the preform production batch, Indicates abnormal critical parameters, represents the reference abnormal parameter of the i-th preform sample, represents the microstructure uniformity evaluation value of the i-th preform sample, represents the dimensional stability evaluation value of the i-th preform sample, Indicates the comprehensive performance evaluation influencing factor corresponding to the preset microstructure uniformity evaluation value, It represents the comprehensive performance evaluation influencing factor corresponding to the preset dimensional stability evaluation value, i represents the number of each preform sample, i=1,2,3,...,n, and n represents the total number of preform samples.

8. A method for a multimodal performance detection system for a high aspect ratio rod-shaped preform according to any one of claims 1 to 7, characterized in that: include: Obtaining performance test samples of rod-shaped preforms with high aspect ratio from the same production batch, marking them as various preform samples, collecting initial dimensional accuracy data of various preform samples, and analyzing and obtaining reference abnormal parameters of various preform samples based on the initial dimensional accuracy data of various preform samples; Obtain fiber distribution data of each preform sample, and obtain a microstructure uniformity evaluation value of each preform sample through comprehensive analysis based on the fiber distribution data of each preform sample; Conducting a high temperature environment test on each preform sample to obtain the test dimensional accuracy data of each preform sample, and obtaining the dimensional stability evaluation value of each preform sample through comprehensive analysis based on the initial dimensional accuracy data and the test dimensional accuracy data of each preform sample; Based on the reference abnormal parameters, dimensional stability evaluation values ​​and microstructure uniformity evaluation values ​​of each preform sample, a comprehensive analysis is conducted to obtain the comprehensive performance evaluation value of the preform production batch, and evaluation feedback is provided on the comprehensive performance of the preform production batch.

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