Material information management system of civil aircraft product basic material knowledge base

Abstract

The invention relates to the technical field of civil aircraft knowledge base management, and discloses a material information management system of a civil aircraft product basic material knowledge base, which comprises a data input module, the data input module is used for constructing a login system interface, and an operator logs in a system by inputting a user name and a password; after login, an operator can input material information data into the knowledge base, wherein the material information data comprises type data, purpose data and specification data. According to the system, the character matching technology is used for comparing newly-input data with existing data of a knowledge base in real time, the maximum similarity value is obtained, a redundancy judgment mode is established, and misjudgment caused by inherent similarity of key attributes in description is effectively prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of civil aircraft knowledge base management, and particularly to a material information management system for a knowledge base of basic materials of civil aircraft products. Background Art

[0002] The basic materials of civil aircraft products refer to various materials used in the manufacture and maintenance of civil aircraft. These materials play a crucial role in the structure, systems, and components of the aircraft, directly affecting flight safety, performance, and economy. By establishing a knowledge base for the basic materials of civil aircraft products and creating a management system for the material information in the knowledge base of basic materials of civil aircraft products, an integrated data management platform can be formed, aiming to provide comprehensive material information for engineers, designers, quality control personnel, and other relevant personnel in the aviation industry, including material properties, characteristics, compliance, application cases, and relevant standards.

[0003] When establishing a management system for the knowledge base of basic materials of civil aircraft products, existing material information management systems usually rely on manual data entry. During the data entry process, when faced with a large amount of material information, operators may accidentally enter the same material record repeatedly, especially when there is no effective real-time feedback and prompting mechanism. Such human errors easily lead to multiple entries of the same material, causing information redundancy, and currently many material information management systems lack effective deduplication algorithms and real-time data verification mechanisms, and cannot automatically identify and prevent the generation of duplicate records during data entry. Summary of the Invention

[0004] Aiming at the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a material information management system for a knowledge base of basic materials of civil aircraft products, which can avoid the problem of redundant data caused by operators entering duplicate material information in the knowledge base, thereby improving the accuracy and reliability of the material information in the knowledge base.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: A material information management system for a knowledge base of basic materials of civil aircraft products, comprising: A data entry module, which includes building a login system interface. Operators can log in to the system by entering a username and password. After logging in, operators can enter material information data into the knowledge base, and the material information data includes type data, usage data, and specification data; A data comparison module, which includes comparing the entered material information data with the existing material information data in the knowledge base for similarity when operators enter material information, and obtaining the maximum similarity value; The data deduplication module includes setting a duplication threshold, comparing the maximum similarity value with the duplication threshold. When the maximum similarity value of the material information data entered by the operator this time is greater than or equal to the duplication threshold, the system determines that the material information data entered this time is redundant data; The data judgment module includes, when the data deduplication module determines that the material information data entered by the operator is redundant data, obtaining an execution weighted coincidence degree value based on the type data, usage data, and specification data in the input material information data, and judging whether the entered material information data is redundant according to the weighted coincidence degree value; The calculation formula for the weighted coincidence degree value Y is: Y = (W1×S1 + W2×S2 + W3×S3)×α, and α is an adjustment factor. When Y is greater than 1, it is maintained that the material information data entered this time is redundant data, and the operator is required to pause the input and perform further manual data comparison; when Y is less than or equal to 1, it is determined that the material information data entered this time is normal data and is allowed to continue to be entered; When the obtained weighted coincidence degree value Y is greater than 1, an association ratio value T = M÷C is obtained according to the additional description amount M existing in the key attribute data and the capacity C occupied by the key attribute data, and an association threshold β is set. The association ratio value T of the material information data is compared with the association threshold β. When the association ratio value is greater than the association threshold, a similarity data analysis strategy is executed; when the association ratio value is less than or equal to the association threshold, the system should execute the previous determination without additional operations.

[0006] In some embodiments, when the system determines that the material information data entered by the operator is redundant data, the type data, usage data, and specification data of the entered material information are respectively marked as key attribute data W1, W2, and W3, and similarity data S1, S2, and S3 are set. The similarity data S1, S2, and S3 respectively match the key attribute data W1, W2, and W3.

[0007] In some embodiments, the type data, usage data, and specification data in the entered material information data are respectively compared with the corresponding type data in the knowledge base for similarity, and the maximum type information similarity, the maximum usage information similarity, and the maximum specification information similarity are obtained. The maximum type information similarity, the maximum usage information similarity, and the maximum specification information similarity are respectively compared with the duplication threshold, and the values of the similarity data are set according to the comparison results.

[0008] In some embodiments, if the maximum type information similarity is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to its type in the material information data entered this time, and S1 is set to 1, otherwise it is 0; If the maximum similarity of the usage information is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to the usage of the material information data entered this time, then S2 is set to 1; otherwise, it is 0. If the maximum similarity of the specification information is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to the specification of the material information data entered this time, then S3 is set to 1; otherwise, it is 0.

[0009] In some embodiments, the similarity data analysis strategy includes obtaining the actual similarity by comparing the maximum similarity of the corresponding key attribute data with the duplication threshold, calculating the similarity difference Sc = Cy - Sd by subtracting the actual similarity Sd from the duplication threshold Cy, calculating the correlation difference Tc = T - β by subtracting the correlation threshold β from the correlation ratio value T, comparing the magnitudes of the similarity difference and the correlation difference, and making corresponding responses according to the comparison results.

[0010] In some embodiments, if the similarity difference is greater than the correlation difference, the system maintains the previous determination without performing additional operations; if the similarity difference is less than or equal to the correlation difference, the system will change the specific value of the corresponding similarity data from 1 to 0 and recalculate the weighted coincidence degree value once.

[0011] The present invention further provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the above-mentioned material information management system for the basic material knowledge base of civil aircraft products.

[0012] The technical solution provided by the present invention has the following beneficial effects compared with the prior art: First, through the refined data entry, comparison, deduplication and judgment mechanisms, the system realizes the efficient and accurate management of the data in the basic material knowledge base of civil aircraft products, supports batch import and export, can automatically organize, format and perform unit conversion, meets the data format requirements of engineering software, and has a highly intelligent data preprocessing ability.

[0013] Second, the system uses character matching technology to compare the newly entered data with the existing data in the knowledge base in real time, obtains the maximum similarity value and establishes a redundancy judgment method, effectively preventing misjudgment caused by the inherent similarity in the description of key attributes.

[0014] Third, the system further judges the key attributes such as the type data, usage data and specification data of the material to ensure that the data with truly repeated characteristics is confirmed, and effective data is not misjudged due to local high similarity.

[0015] Fourthly, when the system detects that the proportion of extra descriptions in the input data is too high, it can correct the interference of extra information in the description of key attributes. By comparing the difference between the actual similarity and the duplication threshold with the difference in the correlation ratio, it automatically adjusts the judgment result, avoiding misjudging the data as redundant due to the influence of annotation information and improving the judgment accuracy. Brief Description of the Drawings

[0016] Figure 1 It is a schematic diagram of the principle of a material information management system for a basic material knowledge base of a civil aircraft product according to the present invention; Figure 2 It is a schematic diagram of the modules of a material information management system for a basic material knowledge base of a civil aircraft product according to the present invention. Detailed Embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] It can be understood that the term "one" should be understood as "at least one" or "one or more". That is, in one embodiment, the number of an element can be one, while in other embodiments, the number of the element can be multiple. The term "one" cannot be understood as a limitation on the number.

[0019] The present invention provides a material information management system for a basic material knowledge base of a civil aircraft product, as Figure 1 and Figure 2 shown, including: Data entry module, which includes building a login system interface. Operators log in to the system by entering a username and password for identity verification, ensuring the security and traceability of the data entry process. Only authorized operators can input and modify data, thus reducing potential security risks. After logging in, operators can enter material information data into the knowledge base. The material information data includes material type data, usage data, and specification data. During the data entry process, the system automatically records the entry time, operator information, and its modification history for each piece of data. These functions not only enhance the credibility of the data but also facilitate subsequent auditing and tracing. The system can also provide import and export functions, supporting batch import of data from other systems or files to further improve work efficiency. This module also supports the function of exporting material cards, that is, the material information entered by the operator can be real-time converted into a text file format that meets the requirements of engineering applications, such as bdf, inp, etc. formats that can be recognized by software such as NASTRAN and ABAQUS. Specifically, the various material data input or modified by the operator in the system will be automatically sorted and formatted by the system. According to the output requirements selected by the operator, the system exports the data as a file in the corresponding format. This file format not only supports direct reading and application by engineering software but also preprocesses the data during export, including unit conversion. It should be noted that during the unit conversion process, in order to ensure data consistency and accurate transmission, the system adopts the truncation principle instead of the traditional rounding method. Adopting the truncation principle can better maintain the original accuracy of the data and avoid the small but cumulative errors that may be caused by rounding, thus ensuring the true reflection of material parameters. In addition, the exported material cards are optimized in format and layout, enabling engineers and technicians to conveniently view, analyze, and modify material data after importing the file into the corresponding design or analysis software. The system supports operators to customize the export template and data content to meet the personalized needs of different projects and application scenarios, thus greatly improving the efficiency of data sharing and integration. This function not only realizes the seamless connection from data collection to data output but also enhances the intelligent level of the entire material information management, helping enterprises shorten the R & D cycle, improve work efficiency, and reduce the risks brought by data conversion errors. Through this formatted, standardized, and refined material card output mechanism, operators can more accurately apply material data in projects, ensuring the scientificity and accuracy of engineering design and analysis.

[0020] The data comparison module includes, when an operator enters material information, comparing the entered data with the existing material information in the database in real time through character matching technology. The comparison steps include character matching of descriptive text, field similarity calculation, and feature extraction. The character matching technology identifies similar content by analyzing the character composition of the entered data and the existing records in the database. For example, when an operator enters the name of a certain material, the system quickly identifies the existing records similar to it, providing a basis for subsequent data comparison. When an operator enters material information data, compare the entered material information data with the existing material information data in the knowledge base for similarity and obtain the maximum similarity value.

[0021] The data deduplication module includes setting a duplication threshold, such as 80%. Compare the maximum similarity value with the duplication threshold. If the maximum similarity value of the material information data entered by the operator this time is less than the duplication threshold, then the material information data entered this time is normally entered into the knowledge base; if the maximum similarity value of the material information data entered by the operator this time is greater than or equal to the duplication threshold, then the system determines that the material information data entered this time is redundant data and prompts the operator on the operation interface, asking the operator to carefully compare the data. The purpose of this design is to eliminate redundant data and ensure the uniqueness and accuracy of the information in the database. The existence of redundant data will not only lead to duplication and confusion of information, but may also have a negative impact on subsequent data analysis and decision-making. Therefore, it is particularly important to build an efficient data deduplication mechanism.

[0022] The data judgment module includes, when the data deduplication module determines that the material information data entered by the operator is redundant data, obtaining an execution weighted coincidence degree value based on the type data, usage data, and specification data in the input material information data, and judging whether the entered material information data is redundant according to the weighted coincidence degree value.

[0023] Although the system initially determines that the record is redundant data, during the actual input process, material data often has a high degree of similarity in key attributes (such as type data, usage data, and specification data, etc.). For example, there are differences in length and diameter, but it is also possible that information data with a high degree of similarity is not duplicate data. Therefore, when the system first determines that the material information data entered by the operator is redundant data, the type data, usage data, and specification data of the entered material information are respectively marked as key attribute data W1, W2, and W3. Each key attribute data is less than 1, and the sum of all key attribute data should be equal to 1. The data sizes of different key attribute data can be preset according to historical data and requirements. The setting of the data sizes of key attribute data can reflect the importance of the key attributes of each different type of material when determining redundant data. Then, by setting similarity data S1, S2, and S3, the similarity data S1, S2, and S3 are respectively matched with the key attribute data W1, W2, and W3. The type data, usage data, and specification data in the entered material information data are respectively compared with the corresponding type of data in the knowledge base for similarity, obtaining the maximum type information similarity, the maximum usage information similarity, and the maximum specification information similarity. And the maximum type information similarity, the maximum usage information similarity, and the maximum specification information similarity are respectively compared with the duplication threshold for size. If the maximum type information similarity is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to its type in the material information data entered this time, then S1 is set to 1, otherwise it is 0; if the maximum usage information similarity is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to its usage in the material information data entered this time, then S2 is set to 1, otherwise it is 0; if the maximum specification information similarity is greater than the duplication threshold, it means that there is data in the knowledge base that is similar to its specification in the material information data entered this time, then S3 is set to 1, otherwise it is 0; More specifically, the calculation formula for the weighted coincidence degree value is: Y = (W1×S1 + W2×S2 + W3×S3) × α, where α is an adjustment factor. When Y is greater than 1, it is determined that the material information data entered this time is redundant data, and the operator is required to pause the input and perform further manual data comparison; when Y is less than or equal to 1, it is determined that the material information data entered this time is normal data, and the operator is allowed to continue entering. For example, the key attribute data representing type, use, and specification are W1 = 0.5, W2 = 0.3, W3 = 0.2 respectively. And there are data similar to its type and specification in the knowledge base, but there is no data similar to its use. Then S1 = 1, S2 = 0, S3 = 1. Set the adjustment factor α to 1.3, then Y = (0.5×1 + 0.3×0 + 0.2×1) × 1.3 = 0.91. At this time, Y is less than 1, so it is determined that the data is normal data entry, and the material information data entered this time is added to the knowledge base, and the system allows the operator to continue entering.

[0024] Generally speaking, when the system initially determines that the material information data is redundant data, it does not directly reject the record, but makes a secondary determination of the key attributes in the material data. The advantage of this mechanism is that it can effectively overcome the misjudgment problem caused by the inherent similarity of key attributes in traditional data comparison. When processing material information with similar physical dimensions (such as length, diameter, etc.), it will not misjudge as duplicate due to the high local similarity of key data, thus avoiding data omission caused by misjudgment. At the same time, by assigning different weights to different key attributes, the judgment result is more flexible and accurate, and can dynamically adjust the judgment standard according to different scenarios and material characteristics. In addition, the introduction of the adjustment factor α makes the system have higher controllability and adaptability, can effectively integrate multiple similarity indicators, improve the accuracy of redundant data discrimination, and ensure that data with truly duplicate characteristics is promptly reminded and manually reviewed. Generally speaking, this design not only improves the intelligent level and efficiency of data entry, but also reduces the data risk caused by misjudging redundancy, ensures the data integrity and reliability of the material information knowledge base, and has a positive promoting effect on the scientificity and accuracy of data establishment in the civil aircraft product basic material knowledge base.

[0025] On the other hand, during the above determination process, by collecting data of key attribute data, when the weighted coincidence degree value Y obtained is greater than 1, it is determined that the material information data entered this time is redundant data. However, when entering data into the basic material knowledge base of civil aircraft products, in addition to the key attribute data (type data, usage data, and specification data) in the material information data, additional descriptions (i.e., annotations) of these three key attribute data of type data, usage data, and specification data are also required. Moreover, the proportion of the amount of information occupied by the additional description in different key attribute data will vary. According to the additional description amount M existing in the key attribute data and the capacity C occupied by the key attribute data, the correlation ratio value T = M÷C is obtained, and a correlation threshold β is set. The correlation ratio value T of the material information data is compared with the correlation threshold β. When the correlation ratio value is greater than the correlation threshold, it indicates that in the description of this key attribute data, the additional description amount occupies a large proportion in the overall data information volume. That is to say, when obtaining the specific value (0 or 1) of the similarity data, the additional description will have a greater impact on the specific value of the similarity data, resulting in the problem that the obtained specific value of the similarity data is inaccurate. Then, the similarity data analysis strategy is executed; when the correlation ratio value is less than or equal to the correlation threshold, it indicates that in the description of this key attribute data, the additional description amount occupies a relatively low proportion in the overall data information volume, and the system should execute the previous determination without additional operations.

[0026] The similarity data analysis strategy includes obtaining the actual similarity by comparing the maximum similarity of the corresponding key attribute data with the duplication threshold, calculating the similarity difference Sc = Cy - Sd by subtracting the actual similarity Sd from the duplication threshold Cy, calculating the correlation difference Tc = T - β by subtracting the correlation threshold β from the correlation ratio value T, and comparing the magnitudes of the similarity difference and the correlation difference, and making corresponding responses according to the comparison results: If the similarity difference is greater than the correlation difference, it indicates that although the proportion of the additional description amount in the overall data information volume is relatively large, when comparing the maximum similarity of the corresponding key attribute with the duplication threshold, the gap between the correlation ratio value and the correlation threshold is more significant. Even if there is a large amount of additional description in the data information volume of the key attribute, it will not change the result of the similarity data. Then the system maintains the previous determination and does not perform additional operations; If the similarity difference is less than or equal to the correlation difference, it indicates that after comparing the maximum similarity of the key attribute with the duplication threshold, the main reason for the maximum similarity reaching the duplication threshold is that there is a large amount of additional description in the data information volume of the key attribute. The fact that the additional description is the same as the description in the knowledge base does not mean that the material information entered this time is redundant. Then the system will change the specific value of the corresponding similarity data from 1 to 0 and re - execute the determination of whether the data is redundant (i.e., recalculate the weighted coincidence degree value). For example, assume the duplication threshold is 0.8, and the maximum similarity of the use information in the entered material information data is 90%. Since it is greater than the duplication threshold of 0.8, the system determines that the similarity data S2 matching the use is 1, and the similarity difference can be obtained as 0.1. When the calculated weighted coincidence degree value Y is greater than 1 and it is determined that the material information data entered this time is redundant data, then the correlation ratio value of the use information in the entered material information data is 0.7, the correlation threshold β is set to 0.5, and the correlation difference is 0.2. Since the similarity difference of 0.1 is less than the correlation difference of 0.2, it indicates that the additional description occupies most of the information volume of the use information entered this time. The similarity data S2 is changed from 1 to 0, and the weighted coincidence degree value is recalculated. This mechanism can effectively prevent misjudgment problems caused by excessive annotation information, ensure that the redundant data determined by the system is closer to the actual situation, improve the accuracy of data determination, and by introducing the comparison of the correlation ratio and the threshold, the system can automatically identify which key attributes are more affected by additional descriptions, and adjust the similarity calculation targeted, thereby reducing the misclassification caused by the interference of description information.

[0027] In the setup of the above system, aiming at the problem that the existence of redundant data in the civil aircraft knowledge base directly affects the accuracy and reliability of the material information in the knowledge base, through a refined data entry, comparison, deduplication and judgment mechanism, efficient and accurate management of the data in the basic material knowledge base of civil aircraft products is achieved. Moreover, the system supports batch import and export, can automatically organize, format and perform unit conversion, meets the data format requirements of engineering software, and has a highly intelligent data preprocessing ability. This system uses character matching technology to compare newly entered data with the existing data in the knowledge base in real time, obtains the maximum similarity value, establishes a preliminary redundancy judgment, and effectively prevents misjudgment caused by the inherent similarity in the description of key attributes (such as length, diameter, etc.). On the basis of the preliminary determination of redundancy, the system further judges key attributes such as the type data, usage data and specification data of materials to ensure that the data with truly duplicate characteristics is confirmed, and valid data is not misjudged due to local high similarity. At the same time, when the system detects that the proportion of additional descriptions in the input data is too high, it can correct the interference of additional information in the description of key attributes. By comparing the difference between the actual similarity and the repetition threshold with the difference in the correlation ratio, the judgment result is automatically adjusted to avoid misjudging the data as redundant due to the influence of annotation information and improve the judgment accuracy. This multi-level and dynamically adjusted mechanism not only improves the intelligent level and work efficiency of data entry, but also reduces the risk brought by data conversion errors and the phenomenon of redundant data in the knowledge base through automatic preprocessing and intelligent judgment, ensuring the integrity and accuracy of the data in the knowledge base.

[0028] In the disclosed embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. The disclosed embodiments of the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part, and / or installed from a removable medium. When the computer program is executed by the central processing unit, the above-mentioned functions defined in the methods of the present application are executed. It should be noted that the above-mentioned computer-readable medium in the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wire segments, a portable computer disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device. In the present application, the computer-readable signal medium can include a data signal propagated in the baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or combined with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wireless, wire segments, optical cables, RF, etc., or any suitable combination of the above.

[0029] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0030] Those skilled in the art should understand that the above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application.

Claims

1. A material information management system for a basic material knowledge base of civil aircraft products, characterized in that: include: The data entry module includes building a login system interface, where operators log in to the system by entering a user name and password. After logging in, the operators can enter material information data into the knowledge base, where the material information data includes type data, usage data, and specification data; A data comparison module includes a method of comparing the input material information data with the existing material information data in the knowledge base when the operator enters the material information, and obtaining the maximum similarity value; The data deduplication module includes setting a duplication threshold, comparing the maximum similarity value with the duplication threshold, and when the maximum similarity value of the material information data entered by the operator is greater than or equal to the duplication threshold, the system determines that the material information data entered this time is redundant data; A data judgment module, comprising: when the material information data entered by the operator is judged as redundant data in the data deduplication module, obtaining a weighted fit value according to the type data, the usage data and the specification data in the input material information data, and judging whether the entered material information data is redundant according to the weighted fit value; The calculation formula of the weighted coincidence value Y is: Y = (W1 × S1 + W2 × S2 + W3 × S3) × α, and α is the adjustment factor. When Y is greater than 1, the material information data entered this time is considered redundant data, and the operator is required to suspend input and conduct further manual data comparison; when Y is less than or equal to 1, the material information data entered this time is considered normal data and is allowed to continue entering; When the obtained weighted combination value Y is greater than 1, the association ratio value T=M÷C is obtained according to the additional description amount M in the key attribute data and the capacity occupied by the key attribute data C, and the association threshold β is set. The association ratio value T of the material information data is compared with the association threshold β. When the association ratio value is greater than the association threshold, the similarity data analysis strategy is executed; When the correlation ratio value is less than or equal to the correlation threshold, the system should execute the previous judgment without performing additional operations.

2. A material information management system for a basic material knowledge base of civil aircraft products according to claim 1, characterized in that: When the system determines that the material information data entered by the operator is redundant data, the system marks the type data, usage data and specification data of the entered material information as key attribute data W1, W2 and W3 respectively, and sets the similarity data S1, S2 and S3. The similarity data S1, S2 and S3 are matched with the key attribute data W1, W2 and W3 respectively.

3. A material information management system for a basic material knowledge base of civil aircraft products according to claim 2, characterized in that: The type data, usage data and specification data in the input material information data are compared with the corresponding type data in the knowledge base for similarity, and the maximum similarity of type information, usage information and specification information are obtained. The maximum similarity of type information, usage information and specification information are compared with the repetition threshold respectively, and the value of the similarity data is set according to the comparison result.

4. A material information management system for a basic material knowledge base of civil aircraft products according to claim 3, characterized in that: If the maximum similarity of type information is greater than the repetition threshold, it means that there is data of similar type in the knowledge base among the material information data entered this time, and S1 is set to 1, otherwise it is 0; If the maximum similarity of the usage information is greater than the duplication threshold, it means that there is data with similar usage in the knowledge base among the material information data entered this time, and S2 is set to 1, otherwise it is 0; If the maximum similarity of the specification information is greater than the repetition threshold, it means that there is data with similar specifications in the knowledge base for the material information data entered this time, and S3 is set to 1, otherwise it is 0.

5. A material information management system for a basic material knowledge base of civil aircraft products according to claim 4, characterized in that: The similarity data analysis strategy includes obtaining the actual similarity of the maximum similarity of the corresponding key attribute data compared with the repetition threshold, using the repetition threshold Cy to calculate the difference between the actual similarity Sd to obtain the similarity difference Sc=Cy-Sd, calculating the difference between the association ratio value T and the association threshold β to obtain the association difference Tc=T-β, and comparing the similarity difference with the association difference, and making corresponding responses according to the comparison results.

6. A material information management system for a basic material knowledge base of civil aircraft products according to claim 5, characterized in that: If the similarity difference is greater than the correlation difference, the system maintains the previous judgment and does not perform additional operations; if the similarity difference is less than or equal to the correlation difference, the system will change the specific value of the corresponding similarity data from 1 to 0 and re-calculate the weighted combination value.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement a material information management system of a basic material knowledge base of a civil aircraft product as described in any one of claims 1 to 6.

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