Portable airplane automatic accelerator S switch in-situ test system

Abstract

The invention discloses a portable airplane automatic accelerator S switch in-situ test system, and relates to the technical field of test, and the technical scheme comprises the following steps: screening based on a test feature identification library to obtain target actual measurement data of a switch to be tested; obtaining an actual test index of the target actual measurement data, obtaining abnormal test data according to the actual test index and the standard test parameter, and obtaining a test deviation coefficient of the abnormal test data according to an actual parameter measurement value; obtaining a first environment test coefficient of the test environment according to the abnormal data parameter of the abnormal test data in the test environment and the test deviation coefficient; marking a switch corresponding to the abnormal test data as an abnormal switch, and obtaining a second environment test coefficient of the test environment according to abnormal equipment parameters of the abnormal switch in the test environment; the effect is that a clear basis is provided for maintenance or replacement of the electric switch.

Description

Technical Field

[0001] This invention relates to the field of testing technology, and specifically to a portable aircraft autothrottle S-switch in-situ testing system. Background Technology

[0002] In an aircraft's automatic throttle system, the S-switch is a critical component, and its performance directly affects the aircraft's power control and flight safety. Traditional switch testing relies heavily on manual operation, which, due to the lack of a unified identifier library, is prone to data confusion or omissions, resulting in low testing efficiency.

[0003] In existing technologies, the judgment of abnormal data relies heavily on experience, making it difficult to accurately quantify the degree of deviation and resulting in insufficient accuracy in anomaly identification. Traditional methods often focus only on anomalies at the data level, neglecting the impact of abnormal equipment changes on the testing environment, leading to a single evaluation dimension. Furthermore, the evaluation of abnormal switches lacks comprehensive consideration from multiple dimensions such as stability and overall deviation, making it difficult to fully reflect the actual condition of the switches. These problems make traditional testing methods insufficient in terms of comprehensiveness and efficiency to meet the needs of modern aircraft switch testing. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a portable aircraft autothrottle S-switch in-situ testing system.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A portable aircraft autothrottle (S-type) switch in-situ testing system includes: Filtering module: Based on the test feature identifier library, the target measured data of the switch to be tested are obtained; First processing module: Obtain the actual test indicators of the target measured data, obtain abnormal test data based on the actual test indicators and standard test parameters, and obtain the test deviation coefficient of the abnormal test data based on the measured values ​​of the actual parameters. The second processing module: obtains the first environmental test coefficient of the test environment based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment; marks the gates corresponding to the abnormal test data as abnormal gates; and obtains the second environmental test coefficient of the test environment based on the abnormal device parameters of the abnormal gates in the test environment. First output module: Obtains the first test pass rate of the test environment based on the first environmental test coefficient and the second environmental test coefficient; The second output module acquires the equipment anomaly information parameters corresponding to the abnormal test data of the abnormal switch, and obtains the second test pass rate of the abnormal switch based on the equipment anomaly information parameters.

[0006] Optionally, the target measured data of the switch to be tested is obtained by filtering based on the test feature identifier library, specifically including the following steps: The target test identifier is obtained by matching the core test identifier code of the test feature identifier library with the actual test data of the switch to be tested. Based on the target test identification code, the measured data is classified and extracted to obtain the target measured data corresponding to the target test identification code.

[0007] By matching the core test identifier codes in the test feature identifier library with the actual test data of the throttle switch under test, the target test identifier code can be accurately determined, ensuring the accuracy of data screening and avoiding erroneous screening due to unclear data identification. This lays a reliable data foundation for subsequent testing. Secondly, data classification and extraction based on the target test identifier codes enables efficient screening of the target test data, greatly improving data processing efficiency and reducing the tedious process and time cost of manual screening. This precise and efficient screening method gives the entire testing system high reliability and timeliness in the data acquisition stage, facilitating the smooth progress of subsequent abnormal data identification, environmental test coefficient calculation, and other stages, thereby improving the performance and practicality of the entire portable aircraft autothrottle S-switch in-situ testing system.

[0008] Optionally, abnormal test data can be obtained based on actual test metrics and standard test parameters, specifically including the following steps: The actual test indicators include the actual parameter measurement values ​​corresponding to the target measured data; wherein, the actual parameter measurement values ​​correspond to the parameter qualification thresholds of the test item type; If the measured data shows that the actual parameter measurement value exceeds the corresponding qualified threshold of the standard test parameter, then the measured data is judged as abnormal test data.

[0009] Clearly defining the actual test indicators includes the measured values ​​of actual parameters corresponding to the pass thresholds of the test item type parameters, providing a clear reference standard for anomaly judgment and ensuring the standardization of the judgment logic. By comparing the measured values ​​of actual parameters with the pass thresholds of standard test parameters, data exceeding the threshold is judged as abnormal test data. This judgment method is objective and accurate, effectively avoiding the subjectivity and error of manual judgment and significantly improving the accuracy of anomaly data identification. This precise anomaly data identification provides a reliable basis for subsequent calculations of test deviation coefficients, evaluation of the test environment, and abnormal switches, ensuring the accuracy and depth of the entire test system's analysis of abnormal situations. This, in turn, improves the overall reliability and practicality of the portable aircraft autothrottle S-switch in-situ testing system, helps to promptly detect potential switch problems, and ensures aircraft flight safety.

[0010] Optionally, the test deviation coefficient of the abnormal test data is obtained based on the actual parameter measurement values, specifically including the following steps: The actual parameter measurement values ​​that exceed the parameter qualification threshold are marked as deviation parameter values; The test deviation coefficient of abnormal test data is obtained based on the deviation parameter value and the parameter qualification threshold.

[0011] Marking actual parameter measurements exceeding the acceptable threshold as deviation parameter values ​​clarifies the source of abnormal data deviation, providing a clear target for subsequent analysis and ensuring the relevance of deviation analysis. Calculating the test deviation coefficient based on the deviation parameter value and the acceptable threshold allows for a quantitative assessment of the degree of abnormality, transforming the deviation from a qualitative description into a quantitative indicator, significantly improving the accuracy and objectivity of the analysis. This quantified deviation coefficient provides crucial quantitative evidence for subsequent stages such as calculating the first environmental test coefficient and assessing the second test pass rate of abnormal switches, ensuring the scientific rigor and accuracy of the entire testing system in the evaluation phase. This, in turn, helps the portable aircraft autothrottle S-switch in-situ testing system more accurately identify switch anomalies, providing strong support for switch performance judgment and maintenance decisions.

[0012] Optionally, the first environment test coefficient of the test environment is obtained based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment, specifically including the following steps: Set the item type weight of abnormal test data based on the test item type corresponding to the abnormal test data; The comprehensive deviation coefficient of abnormal test data is obtained based on the test deviation coefficient and the project type weight of the abnormal test data; among which, the abnormal data parameter includes the number of abnormal data entries in the abnormal test data in the test environment; The first deviation evaluation coefficient is obtained based on the number of abnormal data entries and the comprehensive deviation coefficient; Obtain the total number of measured data points of the switch under test in the test environment, and obtain the second deviation evaluation coefficient of the test environment based on the total number of measured data points and the number of abnormal data points; The first environmental test coefficient of the test environment is obtained based on the first deviation evaluation coefficient and the second deviation evaluation coefficient.

[0013] By assigning weights to different test items based on the test item types corresponding to the abnormal test data, the varying impacts of different test items on the switch performance are fully considered, making the weight allocation more reasonable and laying a scientific foundation for the subsequent calculation of the comprehensive deviation coefficient. Secondly, the comprehensive deviation coefficient is obtained by combining the test deviation coefficient of the abnormal test data with the item type weights, achieving a weighted quantification of the degree of deviation in abnormal data and making the deviation analysis more closely reflect the importance levels of actual test scenarios. The number of abnormal data entries is included in the abnormal data parameter, and combined with the comprehensive deviation coefficient, a first deviation evaluation coefficient is obtained, considering the impact of abnormal data on the test environment from two dimensions: data quantity and deviation degree. A second deviation evaluation coefficient is calculated by combining the total number of measured data entries and the number of abnormal data entries, reflecting the proportion of abnormal data from the perspective of overall data scale. Finally, the first and second deviation evaluation coefficients are merged to obtain the first environmental test coefficient, achieving a multi-dimensional and comprehensive evaluation of the test environment deviation, making the evaluation results more comprehensive and accurate. This multi-dimensional evaluation method provides a reliable and accurate basis for calculating the pass rate of the first test in the subsequent test environment, greatly improving the ability of the portable aircraft autothrottle S-switch in-situ test system to evaluate the test environment, helping to more accurately determine whether the test environment meets the requirements, and thus ensuring the effectiveness and reliability of the switch test.

[0014] Optionally, a second environmental test coefficient for the test environment is obtained based on the abnormal device parameters of the abnormal power gate in the test environment, specifically including the following steps: The abnormal device parameters include the number of abnormal devices with abnormal switches in the test environment and the number of historical abnormal devices. Based on the historical number of abnormal devices and the total number of abnormal devices, the abnormal change rate of the abnormal switches in the test environment is obtained. The second environmental test coefficient of the test environment is obtained based on the abnormal change rate of the equipment.

[0015] The abnormal equipment parameters are clearly defined as the number of abnormal devices with abnormal switches in the test environment and the number of historical abnormal devices, covering both current and historical equipment anomalies and providing comprehensive basic data for subsequent analysis. Secondly, the equipment anomaly change rate is calculated based on the number of historical and current abnormal devices, which intuitively reflects the changing trend of the number of abnormal switches in the test environment, demonstrating the development of equipment anomalies over time. Finally, a second environmental test coefficient is obtained based on the equipment anomaly change rate, enabling a quantitative assessment of equipment anomaly changes in the test environment and enriching the evaluation dimensions. This evaluation method complements the first environmental test coefficient, providing a key basis for the comprehensive evaluation of the first test pass rate of the test environment, greatly improving the comprehensiveness and accuracy of the portable aircraft autothrottle S-switch in-situ testing system's test environment assessment, helping to more accurately judge the overall condition of the test environment and ensuring the reliability of the switch test results.

[0016] Optionally, the first test pass rate of the test environment is obtained based on the first environmental test coefficient and the second environmental test coefficient, specifically including the following steps: Set the first evaluation weight and the second evaluation weight; The first test pass rate corresponding to the test environment is obtained based on the first evaluation weight, the first environmental test coefficient, the second evaluation weight, and the second environmental test coefficient.

[0017] Optionally, the device anomaly information parameters include the frequency of continuous anomalies.

[0018] Optionally, the second test pass rate of the abnormal switch is obtained based on the equipment abnormality information parameters, specifically including the following steps: The equipment stability coefficient of the abnormal switch is obtained based on the continuous abnormal frequency. The total deviation coefficient of the abnormal switch is calculated by summing the comprehensive deviation coefficients corresponding to the abnormal test data based on the number of abnormal data occurrences. The second test pass rate of the abnormal switch is obtained based on the equipment stability coefficient and the equipment total deviation coefficient.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention, based on a test feature identifier library, can quickly and accurately filter the target measured data of the switch under test, avoiding the tediousness and errors of manual screening, significantly improving the efficiency of data screening, saving time for subsequent testing stages, and making the entire testing process more timely. It identifies abnormal test data by comparing actual test indicators with standard test parameters, and calculates the test deviation coefficient based on the actual parameter measurements, realizing the quantification of the degree of deviation of abnormal data. This makes the judgment and analysis of abnormal data more scientific and accurate, providing reliable basic data for subsequent environmental and equipment evaluation. The first environmental test coefficient of the test environment is obtained based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment; the switch corresponding to the abnormal test data is marked as an abnormal switch, and the second environmental test coefficient of the test environment is obtained based on the abnormal equipment parameters of the abnormal switches in the test environment. This comprehensively considers the data deviation and abnormal changes of equipment in the test environment, enabling the evaluation of the test environment to accurately reflect the overall condition of the test environment. By calculating the pass rate of the second test from two dimensions—equipment stability and total deviation—using equipment anomaly information parameters, accurate and targeted assessment of abnormal switches is achieved. This helps to quickly locate switch malfunctions and provides a clear basis for switch repair or replacement. This not only improves the efficiency and accuracy of in-situ testing of the aircraft autothrottle S-switch but also provides comprehensive and detailed evaluation results for the test environment and abnormal switches, which is of great significance for ensuring the performance and safety of the aircraft autothrottle system. Attached Figure Description

[0020] Figure 1 This invention provides a schematic diagram of a portable aircraft autothrottle S-switch in-situ testing system. Figure 2 This invention provides a schematic diagram illustrating the steps for obtaining the first environmental test coefficient in a portable aircraft automatic throttle S-switch in-situ testing system. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0024] Reference Figures 1-2 As shown, the portable aircraft automatic throttle S-switch in-situ testing system proposed in this invention will be further explained.

[0025] A portable aircraft autothrottle (S-type) switch in-situ testing system includes: Filtering module: Based on the test feature identifier library, the target measured data of the switch to be tested are obtained; First processing module: Obtain the actual test indicators of the target measured data, obtain abnormal test data based on the actual test indicators and standard test parameters, and obtain the test deviation coefficient of the abnormal test data based on the measured values ​​of the actual parameters. The second processing module: obtains the first environmental test coefficient of the test environment based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment; marks the gates corresponding to the abnormal test data as abnormal gates; and obtains the second environmental test coefficient of the test environment based on the abnormal device parameters of the abnormal gates in the test environment. First output module: Obtains the first test pass rate of the test environment based on the first environmental test coefficient and the second environmental test coefficient; The second output module acquires the equipment anomaly information parameters corresponding to the abnormal test data of the abnormal switch, and obtains the second test pass rate of the abnormal switch based on the equipment anomaly information parameters.

[0026] The core of the filtering module is to filter target test data based on a test feature identifier library. Using the core test identifier codes in the library, the test data of the switch to be tested is matched to determine the target test identifier code. Then, based on this identifier code, the test data is classified and extracted, ultimately yielding the target test data of the switch to be tested.

[0027] The first processing module is primarily responsible for identifying abnormal test data and calculating the test deviation coefficient. It first acquires the actual test indicators of the target measured data, which include actual parameter measurements corresponding to the parameter pass thresholds for the test item type. The actual parameter measurements are compared to the parameter pass thresholds for standard test parameters. If the actual parameter measurements exceed the thresholds, the data is determined to be abnormal. These exceeding-threshold actual parameter measurements are marked as deviation parameter values. The test deviation coefficient is then calculated by combining the deviation parameter values ​​and the parameter pass thresholds, thereby quantifying the degree of deviation in the abnormal data.

[0028] The second processing module obtains the first environmental test coefficient based on the abnormal data parameters and test deviation coefficients of the abnormal test data in the test environment. First, it assigns project type weights to the abnormal data according to the test project type, and then combines the test deviation coefficient and project type weights to obtain a comprehensive deviation coefficient. Simultaneously, it obtains a first deviation evaluation coefficient by combining the number of abnormal data entries and the comprehensive deviation coefficient, and a second deviation evaluation coefficient by combining the total number of measured data entries and the number of abnormal data entries. Finally, it merges these two coefficients to obtain the first environmental test coefficient. The switches corresponding to the abnormal test data are marked as abnormal switches. The second environmental test coefficient is obtained based on the abnormal device parameters of the abnormal switches in the test environment. These parameters include the number of abnormal devices and the historical number of abnormal devices. The device abnormality change rate is calculated using these two quantities to obtain the second environmental test coefficient.

[0029] The first output module evaluates the passability of the test environment, i.e., the first test passability. By setting a first evaluation weight and a second evaluation weight, the first environment test coefficient and the second environment test coefficient are weighted and fused to obtain the first test passability corresponding to the test environment, reflecting the overall condition of the test environment.

[0030] The second output module is used to evaluate the pass / fail status of the abnormal switch, i.e., the second test pass / fail status. It first acquires the equipment anomaly information parameters corresponding to the abnormal test data of the abnormal switch, including the frequency of continuous anomalies; based on the frequency of continuous anomalies, it obtains the equipment stability coefficient of the abnormal switch; simultaneously, based on the number of anomalies, it accumulates the comprehensive deviation coefficients corresponding to the abnormal test data to calculate the total equipment deviation coefficient; finally, it merges the equipment stability coefficient and the total equipment deviation coefficient to obtain the second test pass / fail status of the abnormal switch, reflecting the pass / fail status of the abnormal switch itself.

[0031] The target measured data of the switch to be tested is obtained by filtering based on the test feature identifier library, specifically including the following steps: The target test identifier is obtained by matching the core test identifier code of the test feature identifier library with the actual test data of the switch to be tested. Based on the target test identification code, the measured data is classified and extracted to obtain the target measured data corresponding to the target test identification code.

[0032] The test feature identifier library stores various core test identifier codes, which are key identifiers for distinguishing different test objects and test items. When processing the measured data of the throttle switch to be tested, the core test identifier codes in the test feature identifier library are called, and a one-to-one identifier matching operation is performed between them and the measured data. If the test feature identifier library contains a core test identifier code for voltage testing of a certain model of automatic throttle switch (S switch), and the measured data contains voltage test data for that switch, the system can obtain the corresponding voltage test target identifier code through matching.

[0033] After obtaining the target test identifier code, all measured data are categorized and extracted based on this identifier code. All measured data with this target test identifier code are filtered from the massive dataset; these filtered data are the target measured data corresponding to the target test identifier code. For example, if the target test identifier code is voltage test, then all measured data belonging to that voltage test are extracted.

[0034] The process of obtaining abnormal test data based on actual test metrics and standard test parameters includes the following steps: Actual test indicators include the actual parameter measurement values ​​corresponding to the target measured data; among them, the actual parameter measurement values ​​correspond to the parameter qualification thresholds of the test item type; If the measured data shows that the actual parameter measurement value exceeds the corresponding qualified threshold of the standard test parameter, then the measured data is judged as abnormal test data.

[0035] The actual test indicators include the actual parameter measurements corresponding to the target measured data, and there is a one-to-one correspondence between the actual parameter measurements and the parameter pass thresholds for the test item type. For example, for the current test item of the aircraft autothrottle S switch, the parameter pass threshold is a specific current range, and the actual parameter measurement value is the specific current value obtained when the current is tested on the switch. This value is based on the target measured data.

[0036] When identifying abnormal test data, the actual parameter measurement value is compared with the corresponding acceptable threshold value for the standard test parameter. If the actual parameter measurement value exceeds the acceptable threshold value, the corresponding measured data is determined to be abnormal test data. For example, assuming the acceptable threshold value for a certain test item type is 5A-10A, if the actual parameter measurement value is 12A, since 12A exceeds the range of 5A-10A, the measured data will be determined to be abnormal test data.

[0037] The test deviation coefficient for abnormal test data is obtained based on the actual parameter measurement values, specifically including the following steps: The actual parameter measurement values ​​that exceed the parameter qualification threshold are marked as deviation parameter values; The test deviation coefficient of abnormal test data is obtained based on the deviation parameter value and the parameter qualification threshold.

[0038] When testing ignition switches, each test item has a corresponding acceptable threshold value. For example, the acceptable threshold value for the resistance test item of a certain type of automatic throttle switch (S switch) is set between 100 ohms and 200 ohms. When the actual measured parameter value exceeds this range, for example, a measured value of 220 ohms, then 220 ohms is marked as a deviation parameter value.

[0039] After obtaining the deviation parameter value, the test deviation coefficient is calculated based on the acceptable threshold value for the test item. The acceptable threshold value is 100 ohms to 200 ohms, and the deviation parameter value is 220 ohms. By comparing the difference between the upper and lower limits of the deviation parameter value and the acceptable threshold value, the degree of deviation can be quantified. The quantified result is the test deviation coefficient. It can intuitively reflect the degree to which abnormal test data deviates from the acceptable range, providing a key basis for subsequent judgment of the degree of abnormality of the switch and the condition of the test environment.

[0040] The first environment test coefficient of the test environment is obtained based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment, specifically including the following steps: Set the item type weight of abnormal test data based on the test item type corresponding to the abnormal test data; The comprehensive deviation coefficient of abnormal test data is obtained based on the test deviation coefficient and the project type weight of the abnormal test data; among which, the abnormal data parameter includes the number of abnormal data entries in the abnormal test data in the test environment; The first deviation evaluation coefficient is obtained based on the number of abnormal data entries and the comprehensive deviation coefficient; Obtain the total number of measured data points of the switch under test in the test environment, and obtain the second deviation evaluation coefficient of the test environment based on the total number of measured data points and the number of abnormal data points; The first environmental test coefficient of the test environment is obtained based on the first deviation evaluation coefficient and the second deviation evaluation coefficient.

[0041] First, set the weight of each test item type based on the test item type corresponding to the abnormal test data. Different test items have different degrees of impact on throttle performance, so different weights should be assigned to them. For example, the signal transmission accuracy test item for the automatic throttle (S) is crucial to the throttle function, so a weight of 0.6 is set; while the appearance wear test item is relatively less important, so a weight of 0.3 is set.

[0042] The overall deviation coefficient is obtained based on the test deviation coefficient of the abnormal test data and the weight of the item type. For example, if the test deviation coefficient of a certain abnormal test data is 0.4 and its item type weight is 0.5, then the overall deviation coefficient is 0.4 × 0.5 = 0.2. The abnormal data parameter here includes the number of abnormal data entries in the test environment.

[0043] The first deviation evaluation coefficient is obtained based on the number of abnormal data entries and the comprehensive deviation coefficient. For example, if there are 5 abnormal data entries, and the comprehensive deviation coefficients for each entry are 0.2, 0.3, 0.2, 0.1, and 0.2 respectively, these comprehensive deviation coefficients are added together to obtain a total of 1.0. Then, the first deviation evaluation coefficient is obtained by dividing the total by the number of abnormal data entries.

[0044] Obtain the total number of measured data points for the switch under test in the test environment. Calculate the second deviation evaluation coefficient based on the total number of measured data points and the number of abnormal data points. For example, if the total number of measured data points is 20 and the number of abnormal data points is 5, then the second deviation evaluation coefficient is 5 ÷ 20 = 0.25.

[0045] The first environmental test coefficient is obtained based on the first deviation evaluation coefficient and the second deviation evaluation coefficient. For example, if the first deviation evaluation coefficient is set to a weight of 0.6 and the second deviation evaluation coefficient is set to a weight of 0.4, then the first environmental test coefficient is 0.2 × 0.6 + 0.25 × 0.4 = 0.22. The first environmental test coefficient reflects the overall deviation of the switch test data under the test environment, providing a basis for judging whether the test environment is qualified.

[0046] The second environmental test coefficient of the test environment is obtained based on the abnormal device parameters of the abnormal power gate in the test environment, which specifically includes the following steps: Abnormal device parameters include the number of abnormal devices with abnormal switches in the test environment and the number of historical abnormal devices. Based on the historical number of abnormal devices and the total number of abnormal devices, the abnormal change rate of the abnormal switches in the test environment is obtained. The second environmental test coefficient of the test environment is obtained based on the abnormal change rate of the equipment.

[0047] The abnormal device parameters include the number of abnormal devices with abnormal switches in the test environment and the number of abnormal devices in the past. For example, if there are currently 3 abnormal automatic throttle switches (S switches) detected in a certain test environment, and the number of abnormal switches in this environment in the historical records is 2, then the number of abnormal devices is 3, and the number of abnormal devices in the past is 2.

[0048] The abnormality rate of the abnormal switches in the test environment is obtained based on the number of historical abnormal devices and the total number of abnormal devices. The abnormality rate is calculated by dividing the current number of abnormal devices by the number of historical abnormal devices, i.e., (3-2)÷2=0.5. This value reflects the magnitude of change in the number of abnormal switches.

[0049] The second environmental test coefficient is obtained based on the equipment anomaly change rate. For example, if the equipment anomaly change rate is 0.5, it is converted into the second environmental test coefficient through a weighted calculation using a formula. This coefficient is used to measure the degree of impact of changes in switch anomalies on the test environment, providing a key indicator for the overall evaluation of the test environment.

[0050] The first test pass level of the test environment is obtained based on the first environmental test coefficient and the second environmental test coefficient, specifically including the following steps: Set the first evaluation weight and the second evaluation weight; The first test pass rate corresponding to the test environment is obtained based on the first evaluation weight, the first environmental test coefficient, the second evaluation weight, and the second environmental test coefficient.

[0051] A first evaluation weight and a second evaluation weight are set. These weights reflect the difference in importance between the first and second environmental test coefficients in assessing the pass rate of the test environment. The first pass rate of the test environment is calculated based on these weights and the corresponding environmental test coefficients. Assuming the first environmental test coefficient is 0.7, the second environmental test coefficient is 0.8, and the first evaluation weight is 0.6 and the second evaluation weight is 0.4, then the first pass rate is 0.7 × 0.6 + 0.8 × 0.4 = 0.74. This value comprehensively considers both test data deviation and abnormal equipment changes, and directly reflects whether the test environment meets the requirements. The closer the value is to 1, the higher the pass rate of the test environment.

[0052] Equipment anomaly information parameters include the frequency of consecutive anomalies.

[0053] The second test pass rate of the faulty switch is determined based on the equipment fault information parameters, specifically including the following steps: The equipment stability coefficient of the abnormal switch is obtained based on the continuous abnormal frequency. The total deviation coefficient of the abnormal switch is calculated by summing the comprehensive deviation coefficients corresponding to the abnormal test data based on the number of abnormal data occurrences. The second test pass rate of the abnormal switch is obtained based on the equipment stability coefficient and the equipment total deviation coefficient.

[0054] First, the equipment stability coefficient of the faulty switch is obtained based on the continuous anomaly frequency. The continuous anomaly frequency refers to the frequency at which the faulty switch exhibits anomalies during continuous testing. For example, if an automatic throttle switch (S) exhibits anomalies 7 out of 10 consecutive tests, the continuous anomaly frequency is 70%. Generally, the higher the continuous anomaly frequency, the worse the switch's stability, and the lower the equipment stability coefficient. Assume the following relationship: when the continuous anomaly frequency is 0%, the equipment stability coefficient is 1; for every 20% increase in the continuous anomaly frequency, the equipment stability coefficient decreases by 0.2. For a switch with a continuous anomaly frequency of 70%, its equipment stability coefficient is 1 - (70% ÷ 20%) × 0.2 = 0.3.

[0055] Secondly, the total deviation coefficient of the faulty switch is calculated by summing the comprehensive deviation coefficients corresponding to the abnormal test data based on the number of abnormal data occurrences. The number of abnormal data occurrences refers to the number of times abnormal test data appears for the faulty switch, and the comprehensive deviation coefficient is the product of the test deviation coefficient of each abnormal test data and the weight of the corresponding item type. For example, if a faulty switch has 3 abnormal data occurrences, the corresponding comprehensive deviation coefficients are 0.4, 0.3, and 0.2, respectively. Summing these three values, i.e., 0.4 + 0.3 + 0.2 = 0.9, the total deviation coefficient of the switch is 0.9, reflecting the cumulative degree of all abnormal deviations of the switch.

[0056] The second test pass rate of the abnormal switch is determined based on the equipment stability coefficient and the equipment total deviation coefficient. These two coefficients reflect the condition of the abnormal switch from different dimensions: the equipment stability coefficient reflects the switch's stable performance, and the equipment total deviation coefficient reflects the cumulative degree of deviation. The second test pass rate is usually calculated using a weighted average method. Assuming the weight of the equipment stability coefficient is 0.4 and the weight of the equipment total deviation coefficient is 0.6, if a switch has an equipment stability coefficient of 0.5 and an equipment total deviation coefficient of 0.6, then the second test pass rate is 0.5 × 0.4 + 0.6 × 0.6 = 0.56. The closer this value is to 1, the higher the pass rate of the abnormal switch, and vice versa.

[0057] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0058] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A portable aircraft automatic throttle S-switch in-situ testing system, characterized in that, include: Filtering module: Based on the test feature identifier library, the target measured data of the switch to be tested are obtained; First processing module: Obtain the actual test indicators of the target measured data, obtain abnormal test data based on the actual test indicators and standard test parameters, and obtain the test deviation coefficient of the abnormal test data based on the measured values ​​of the actual parameters. The second processing module: obtains the first environmental test coefficient of the test environment based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment; marks the gates corresponding to the abnormal test data as abnormal gates; and obtains the second environmental test coefficient of the test environment based on the abnormal device parameters of the abnormal gates in the test environment. First output module: Obtains the first test pass rate of the test environment based on the first environmental test coefficient and the second environmental test coefficient; The second output module acquires the equipment anomaly information parameters corresponding to the abnormal test data of the abnormal switch, and obtains the second test pass rate of the abnormal switch based on the equipment anomaly information parameters.

2. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 1, characterized in that, The target measured data of the switch to be tested is obtained by filtering based on the test feature identifier library, specifically including the following steps: The target test identifier is obtained by matching the core test identifier code of the test feature identifier library with the actual test data of the switch to be tested. Based on the target test identification code, the measured data is classified and extracted to obtain the target measured data corresponding to the target test identification code.

3. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 1, characterized in that, The process of obtaining abnormal test data based on actual test metrics and standard test parameters includes the following steps: The actual test indicators include the actual parameter measurement values ​​corresponding to the target measured data; wherein, the actual parameter measurement values ​​correspond to the parameter qualification thresholds of the test item type; If the measured data shows that the actual parameter measurement value exceeds the corresponding qualified threshold of the standard test parameter, then the measured data is judged as abnormal test data.

4. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 3, characterized in that, The test deviation coefficient for abnormal test data is obtained based on the actual parameter measurement values, specifically including the following steps: The actual parameter measurement values ​​that exceed the parameter qualification threshold are marked as deviation parameter values; The test deviation coefficient of abnormal test data is obtained based on the deviation parameter value and the parameter qualification threshold.

5. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 4, characterized in that, The first environment test coefficient of the test environment is obtained based on the abnormal data parameters and test deviation coefficient of the abnormal test data in the test environment, specifically including the following steps: Set the item type weight of abnormal test data based on the test item type corresponding to the abnormal test data; The comprehensive deviation coefficient of abnormal test data is obtained based on the test deviation coefficient and the project type weight of the abnormal test data; among which, the abnormal data parameter includes the number of abnormal data entries in the abnormal test data in the test environment; The first deviation evaluation coefficient is obtained based on the number of abnormal data entries and the comprehensive deviation coefficient; Obtain the total number of measured data points of the switch under test in the test environment, and obtain the second deviation evaluation coefficient of the test environment based on the total number of measured data points and the number of abnormal data points; The first environmental test coefficient of the test environment is obtained based on the first deviation evaluation coefficient and the second deviation evaluation coefficient.

6. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 5, characterized in that, The second environmental test coefficient of the test environment is obtained based on the abnormal device parameters of the abnormal power gate in the test environment, which specifically includes the following steps: The abnormal device parameters include the number of abnormal devices with abnormal switches in the test environment and the number of historical abnormal devices. Based on the historical number of abnormal devices and the total number of abnormal devices, the abnormal change rate of the abnormal switches in the test environment is obtained. The second environmental test coefficient of the test environment is obtained based on the abnormal change rate of the equipment.

7. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 6, characterized in that, The first test pass level of the test environment is obtained based on the first environmental test coefficient and the second environmental test coefficient, specifically including the following steps: Set the first evaluation weight and the second evaluation weight; The first test pass rate corresponding to the test environment is obtained based on the first evaluation weight, the first environmental test coefficient, the second evaluation weight, and the second environmental test coefficient.

8. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 7, characterized in that, The equipment anomaly information parameters include the frequency of continuous anomalies.

9. The portable aircraft automatic throttle S-switch in-situ testing system according to claim 8, characterized in that, The second test pass rate of the faulty switch is determined based on the equipment fault information parameters, specifically including the following steps: The equipment stability coefficient of the abnormal switch is obtained based on the continuous abnormal frequency. The total deviation coefficient of the abnormal switch is calculated by summing the comprehensive deviation coefficients corresponding to the abnormal test data based on the number of abnormal data occurrences. The second test pass rate of the abnormal switch is obtained based on the equipment stability coefficient and the equipment total deviation coefficient.

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