Aviation plug health assessment method and device based on evidence reasoning

Abstract

The invention discloses an aviation plug health assessment method based on evidence reasoning, and relates to the technical field of equipment health assessment, and the method comprises the steps: determining assessment indexes reflecting the health state of an aviation plug, and obtaining the data of the aviation plug under each assessment index; obtaining a reference value corresponding to each health level in each evaluation index, converting data of the aviation plug under each evaluation index into confidence distribution of the reference value based on the reference value, and forming evidence of each evaluation index; for each health level, fusing the evidence of each evaluation index by using an evidence reasoning algorithm to obtain the evidence of each input evaluation index, and mapping the evidence into the confidence of output relative to each health level; and calculating a final utility value for representing the health state of the aviation plug according to the utility value of each health level and the confidence coefficient. According to the method, information generated in the electrical performance testing process and the mechanical performance testing process is comprehensively utilized, the uncertainty in the evaluation process is reduced, and the credibility of the evaluation result is improved.

Description

Technical Field

[0001] This invention belongs to the field of equipment health assessment technology, specifically relating to a method and apparatus for health assessment of aviation plugs based on evidence reasoning. Background Technology

[0002] Aviation connectors are crucial connection components in the electrical systems of aircraft, their core function being to build a conductive "bridge" for electrical equipment. With terminals made of high-quality conductive materials such as copper alloys, they efficiently and precisely transmit current from one device to another. Taking aircraft electronic systems as an example, aviation connectors act as a critical "energy hub," tightly connecting power modules to numerous key devices such as onboard computers and radar, ensuring these devices receive a stable and continuous supply of the necessary power to maintain the normal operation of the entire system. The complex and harsh working environment not only places extremely high demands on the design and performance of aviation connectors but also poses a severe challenge to their health monitoring. As aviation connectors operate for longer periods and are plugged in and out more frequently, they gradually degrade, affecting their lifespan. Therefore, conducting health assessments of aviation connectors and promptly identifying potential faults, followed by targeted preventative maintenance measures, can effectively prevent equipment failures or safety accidents caused by connector malfunctions, thus strengthening the defenses for aviation safety.

[0003] Currently, the health assessment of aviation connectors mainly relies on experienced quality inspectors to check for problems such as broken pins, deformation, and damage by visual inspection or the use of instruments. This manual inspection method is inefficient, costly, and cannot achieve intelligent and automated operation. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention provides a method and apparatus for assessing the health of aircraft connectors based on evidence-based reasoning. The technical problem to be solved by this invention is achieved through the following technical solution: In a first aspect, the present invention provides a method for health assessment of aircraft plugs based on evidence-based reasoning, comprising: Determine the assessment indicators that reflect the health status of the aviation connector, and obtain the data of the aviation connector under each of the assessment indicators; Obtain reference values ​​for each health level in each assessment indicator, and based on the reference values, convert the data of the aviation plug under each assessment indicator into a confidence distribution of the reference values ​​to form evidence for each assessment indicator; For each health level, the evidence of each assessment indicator is fused using an evidence reasoning algorithm to obtain the evidence mapping of each input assessment indicator as the confidence level of the output relative to each health level; The final utility value used to represent the health status of the aircraft plug is calculated based on the utility value of each health level and the confidence level.

[0005] In one embodiment of the present invention, the health level includes: best, good and sub-healthy, and the evaluation indicators include: the maximum pull force of the aviation plug during the insertion and removal process, the maximum contact resistance of each pin of the aviation plug during the connection process and the average contact resistance.

[0006] In one embodiment of the present invention, the step of obtaining a reference value corresponding to each health level in each assessment indicator, and based on the reference value, converting the data of the aviation plug under each assessment indicator into a confidence distribution of the reference value to form evidence for each assessment indicator includes: Obtain the reference value for each health level in each assessment indicator; Based on the reference value, the data of the aviation plug under each of the evaluation indicators are converted into a confidence distribution of the reference value: ; In the formula, Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of evaluation indicators. This indicates that the collected aviation plug was in the first... Data under each evaluation indicator express Switch to confidence level express Switch to confidence level Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of health levels; Evidence for each evaluation indicator is formed using the confidence distribution: ; In the formula, Indicates the first Evidence for the evaluation indicators.

[0007] In one embodiment of the present invention, for the first The health level is determined by integrating evidence from various assessment indicators using the following formula: ; In the formula, Indicates the first The preset weights of the evaluation indicators Indicates intermediate variables. The evidence mapping of the input evaluation metric to the output relative to the first... Confidence level of the health grade.

[0008] In one embodiment of the present invention, the step of calculating a final utility value representing the health status of the aircraft plug based on the utility values ​​of each health level includes: Using the utility values ​​of each health level, the evidence mapping of each input evaluation indicator is used to weight the output with respect to the confidence level of each health level, and the final utility value is obtained.

[0009] In one embodiment of the present invention, data of the aviation plug under each of the evaluation indicators are collected using a data acquisition platform; The data acquisition platform comprises a power unit, a slide rail guiding unit, and a testing unit, wherein... The power unit employs an air compressor system, which controls the insertion and removal speed of the aviation plug by adjusting the air pressure and simulates the insertion and removal process. The slide rail guide unit is used to move the aviation plug along the slide rail to simulate the insertion and removal process of the aviation plug. The test unit is used to measure the change in tension of the aviation plug during the insertion and removal process using a force sensor, and to measure the maximum and average contact resistance of each pin of the aviation plug during the connection process using high-precision micro-resistance testing technology.

[0010] Secondly, the present invention also provides an aviation plug health assessment device based on evidence reasoning, comprising: The data acquisition module is used to determine the assessment indicators reflecting the health status of the aviation connector and to acquire the data of the aviation connector under each assessment indicator. The conversion module is used to obtain the reference value corresponding to each health level in each assessment indicator, and based on the reference value, convert the data of the aviation plug under each assessment indicator into a confidence distribution of the reference value to form evidence for each assessment indicator. The fusion module is used to fuse the evidence of various assessment indicators for each health level using an evidence reasoning algorithm, and obtain the evidence mapping of the input assessment indicators as the confidence level of the output relative to each health level. The calculation module is used to calculate the final utility value representing the health status of the aircraft plug based on the utility value of each health level and the confidence level.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method and apparatus for health assessment of aviation connectors based on evidence reasoning. It selects the maximum pull force of the aviation connector during insertion and removal, as well as the maximum and average contact resistance of each pin during connection, as assessment indicators. By integrating information from multiple assessment indicators through evidence reasoning algorithms, it combines information generated during electrical and mechanical performance testing, thereby effectively assessing the health of aviation connectors. This not only reduces uncertainty in the assessment process but also improves the reliability of the assessment results, providing a solid guarantee for the reliability and safety of aviation connectors.

[0012] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0013] Figure 1 This is a flowchart of an aviation plug health assessment method based on evidence reasoning provided in an embodiment of the present invention; Figure 2 This is a structural block diagram of the data acquisition platform provided in an embodiment of the present invention; Figure 3 This is a health trend change curve of the aviation plug provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a structure of an aviation plug health assessment device based on evidence reasoning provided in an embodiment of the present invention. Detailed Implementation

[0014] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0015] Figure 1 This is a flowchart of an evidence-based reasoning-based aviation plug health assessment method provided in an embodiment of the present invention. Figure 1 As shown, this embodiment of the invention provides a method for assessing the health of aircraft plugs based on evidence-based reasoning, including: S1. Determine the assessment indicators that reflect the health status of the aviation connector and obtain data on the aviation connector under each assessment indicator.

[0016] To determine assessment metrics that can reflect the health status of aviation connectors, this embodiment considers contact resistance testing in electrical performance testing and insertion / extraction force testing in mechanical performance testing.

[0017] Specifically, electrical performance testing includes multiple aspects such as conductivity and insulation. Among the various performance indicators of aviation connectors, conductivity is a key factor in measuring their ability to achieve accurate electrical signal transmission and stable power supply. Conductivity testing is mainly accomplished by measuring the resistance or current of the contacts. This embodiment uses the contact resistance value during the connection process of the aviation connector as one of the information for its health assessment. In practical applications, it is generally desirable for the contact resistance value to be as low as possible, indicating high pin conductivity. Therefore, contact resistance is strongly correlated with the health status of the aviation connector.

[0018] Furthermore, the mechanical performance testing includes multiple tests such as insertion / extraction force testing, insertion / extraction life testing, and mechanical life testing. The insertion / extraction force test is primarily used to accurately assess the connection force of the aviation connector during insertion and removal operations. This test ensures that the aviation connector possesses stable and reliable connection performance in actual use, thus providing a solid guarantee for the safe operation of aviation equipment. In practical applications, the pull-out force needs to be stable within a certain range; too low a pull-out force may cause poor contact in the aviation connector, affecting the normal operation of the aircraft. Therefore, pull-out force can also be selected as one of the health assessment indicators for aviation connectors.

[0019] In summary, this embodiment selects the contact resistance and pull force of the aviation connector as evaluation indicators. It should be noted that the pull force changes as a curve during the insertion and removal of the aviation connector; therefore, the maximum pull force during a single insertion and removal can be selected as the evaluation indicator. Furthermore, the contact resistance measurement results include the contact resistance of all eight pins, meaning each measurement yields eight resistance values. This embodiment selects the maximum and average contact resistance of each pin during the connection process as evaluation indicators.

[0020] In this embodiment, a data acquisition platform can be selectively used to collect data on the aviation plug under various evaluation indicators. Figure 2 This is a structural block diagram of the data acquisition platform provided in an embodiment of the present invention. Please refer to [link / reference]. Figure 2The data acquisition platform consists of a power unit, a slide rail guide unit, and a testing unit. The power unit uses an air compressor system to control the insertion and removal speed of the aviation connector and simulate the insertion and removal process by adjusting the air pressure. The power unit mainly consists of a motor, air tank, switch, exhaust valve, and muffler. The slide rail guide unit moves the aviation connector along the slide rail to simulate the insertion and removal process. It includes the slide rail, traction slide, aviation connector unlocking steel cable clamp, high-speed, high-precision controllable cylinder, buffer, aviation connector fixing bracket, tension sensor, and platform cabinet. The testing unit uses a force sensor to measure the tension change of the aviation connector during insertion and removal, and employs high-precision micro-resistance testing technology to measure the maximum and average contact resistance of each pin during connection. It includes the main unit, test cable, and 485 data cable.

[0021] S2. Obtain the reference value corresponding to each health level in each assessment indicator. Based on the reference value, convert the data of the aviation plug under each assessment indicator into a confidence distribution of the reference value to form evidence for each assessment indicator.

[0022] For example, health levels include: best, good, and sub-healthy, with utility values ​​of 1, 0.8, and 0.6, respectively. Table 1 shows the evaluation indicators selected in this embodiment and the reference values ​​corresponding to each health level in each evaluation indicator. H 1. H 2. H The numbers 2 represent three health levels: optimal, good, and sub-healthy. It should be understood that, within the normal range, a higher tensile strength generally indicates a healthier connector, and conversely, lower contact resistance generally indicates a healthier connector. Therefore, to facilitate the conversion of evaluation indicators, the reference values ​​for these indicators are typically set to decrease or increase with the optimal, good, and sub-healthy health levels. Specifically, for the evaluation indicator of maximum tensile strength... H 1. H 2. H The corresponding reference values ​​for 2 are 5kg, 3kg, and 2kg, respectively. Regarding the maximum contact resistance as an evaluation indicator, H 1. H 2. H The corresponding reference values ​​for 2 are 0.6mΩ, 0.75mΩ, and 0.9mΩ, respectively. As for the average contact resistance, this is an evaluation metric. H 1. H 2. H The corresponding reference values ​​for 2 are 0.4mΩ, 0.55mΩ, and 0.7mΩ, respectively.

[0023] Table 1

[0024] Further, step S2 includes: S201. Obtain the reference value for each health level in each assessment indicator; S202. Based on reference values, convert the data of the aviation plug under each evaluation index into a confidence distribution of the reference values: ; In the formula, Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of evaluation indicators. This indicates that the collected aviation plug was in the first... Data under each evaluation indicator express Switch to confidence level express Switch to confidence level Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of health levels; S203. Using confidence distributions to generate evidence for each evaluation indicator: ; In the formula, Indicates the first Evidence for the evaluation indicators.

[0025] S3. For each health level, use the evidence reasoning algorithm to fuse the evidence of each evaluation indicator, and obtain the evidence mapping of the input evaluation indicators as the confidence level of the output relative to each health level.

[0026] Optionally, for the first The health level is determined by integrating evidence from various assessment indicators using the following formula: ; In the formula, Indicates the first The preset weights of the evaluation indicators Indicates intermediate variables. The evidence mapping of the input evaluation metric to the output relative to the first... Confidence level of the health grade.

[0027] S4. Calculate the final utility value used to represent the health status of the aircraft plug based on the utility value and confidence level of each health level.

[0028] Specifically, by using the utility values ​​of each health level, the evidence mapping of each input assessment indicator is used to calculate the weighted sum of the output confidence levels relative to each health level, thus obtaining the final utility value.

[0029] Figure 3 This is a health trend change curve of the aviation plug provided in an embodiment of the present invention. As can be seen, Figure 3 The vertical axis represents the final utility value, and the horizontal axis represents the data number of the collected aviation plug under each evaluation index. The health trend change curve can not only reflect the health status of the aviation plug, but also predict potential failures through the inflection point of the health trend change curve.

[0030] Figure 4 This is a schematic diagram of a structure of an aviation plug health assessment device based on evidence reasoning provided in an embodiment of the present invention. Figure 4 As shown, this embodiment of the invention also provides an aviation plug health assessment device based on evidence reasoning, comprising: The data acquisition module 410 is used to determine the assessment indicators reflecting the health status of the aviation connector and to acquire data of the aviation connector under each assessment indicator. The conversion module 420 is used to obtain the reference value corresponding to each health level in each assessment indicator, and based on the reference value, convert the data of the aviation plug under each assessment indicator into the confidence distribution of the reference value to form evidence for each assessment indicator. The fusion module 430 is used to fuse the evidence of various evaluation indicators for each health level using an evidence reasoning algorithm, and obtain the confidence of the output relative to each health level by mapping the evidence of the input evaluation indicators. The calculation module 440 is used to calculate the final utility value representing the health status of the aircraft plug based on the utility value and confidence level of each health level.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method and apparatus for health assessment of aviation connectors based on evidence reasoning. It selects the maximum pull force of the aviation connector during insertion and removal, as well as the maximum and average contact resistance of each pin during connection, as assessment indicators. By integrating information from multiple assessment indicators through evidence reasoning algorithms, it combines information generated during electrical and mechanical performance testing, thereby effectively assessing the health of aviation connectors. This not only reduces uncertainty in the assessment process but also improves the reliability of the assessment results, providing a solid guarantee for the reliability and safety of aviation connectors.

[0032] In the description of this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0033] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for assessing the health of aircraft plugs based on evidence-based reasoning, characterized in that, include: Determine the assessment indicators that reflect the health status of the aviation connector, and obtain the data of the aviation connector under each of the assessment indicators; Obtain reference values ​​for each health level in each assessment indicator, and based on the reference values, convert the data of the aviation plug under each assessment indicator into a confidence distribution of the reference values ​​to form evidence for each assessment indicator; For each health level, the evidence of each assessment indicator is fused using an evidence reasoning algorithm to obtain the evidence mapping of each input assessment indicator as the confidence level of the output relative to each health level; The final utility value used to represent the health status of the aircraft plug is calculated based on the utility value of each health level and the confidence level.

2. The aviation plug health assessment method based on evidence reasoning according to claim 1, characterized in that, The health levels include: best, good, and sub-healthy. The evaluation indicators include: the maximum pull force of the aviation plug during insertion and removal, the maximum contact resistance of each pin of the aviation plug during connection, and the average contact resistance.

3. The aviation plug health assessment method based on evidence reasoning according to claim 2, characterized in that, The steps of obtaining reference values ​​for each health level in each assessment indicator, and based on the reference values, converting the data of the aviation plug under each assessment indicator into a confidence distribution of the reference values ​​to form evidence for each assessment indicator, include: Obtain the reference value for each health level in each assessment indicator; Based on the reference value, the data of the aviation plug under each of the evaluation indicators are converted into a confidence distribution of the reference value: ； In the formula, Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of evaluation indicators. This indicates that the collected aviation plug was in the first... Data under each evaluation indicator express Switch to confidence level express Switch to confidence level Indicates the first The first of the evaluation indicators Reference values ​​corresponding to each health level , Indicates the number of health levels; Evidence for each evaluation indicator is formed using the confidence distribution: ； In the formula, Indicates the first Evidence for the evaluation indicators.

4. The aviation plug health assessment method based on evidence reasoning according to claim 3, characterized in that, Regarding the first The health level is determined by integrating evidence from various assessment indicators using the following formula: ； In the formula, Indicates the first The preset weights of the evaluation indicators Indicates intermediate variables. The evidence mapping of the input evaluation metric to the output relative to the first... Confidence level of the health grade.

5. The aviation plug health assessment method based on evidence reasoning according to claim 4, characterized in that, The steps for calculating the final utility value representing the health status of the aircraft plug, based on the utility values ​​of each health level, include: Using the utility values ​​of each health level, the evidence mapping of each input evaluation indicator is used to weight the output with respect to the confidence level of each health level, and the final utility value is obtained.

6. The aviation plug health assessment method based on evidence reasoning according to claim 1, characterized in that, Data on the aviation plug under each of the aforementioned evaluation indicators were collected using a data acquisition platform; The data acquisition platform comprises a power unit, a slide rail guiding unit, and a testing unit, wherein... The power unit employs an air compressor system, which controls the insertion and removal speed of the aviation plug by adjusting the air pressure and simulates the insertion and removal process. The slide rail guide unit is used to move the aviation plug along the slide rail to simulate the insertion and removal process of the aviation plug. The test unit is used to measure the change in tension of the aviation plug during the insertion and removal process using a force sensor, and to measure the maximum and average contact resistance of each pin of the aviation plug during the connection process using high-precision micro-resistance testing technology.

7. An aviation plug health assessment device based on evidence reasoning, characterized in that, include: The data acquisition module is used to determine the assessment indicators reflecting the health status of the aviation connector and to acquire the data of the aviation connector under each assessment indicator. The conversion module is used to obtain the reference value corresponding to each health level in each assessment indicator, and based on the reference value, convert the data of the aviation plug under each assessment indicator into a confidence distribution of the reference value to form evidence for each assessment indicator. The fusion module is used to fuse the evidence of various assessment indicators for each health level using an evidence reasoning algorithm, and obtain the evidence mapping of the input assessment indicators as the confidence level of the output relative to each health level. The calculation module is used to calculate the final utility value representing the health status of the aircraft plug based on the utility value of each health level and the confidence level.

Images