Product false alarm rate determination method and device, electronic equipment and storage medium

Abstract

This disclosure relates to a method and apparatus for determining the false alarm rate of a product, an electronic device, and a storage medium. The method includes: determining various potential faults of each component in the product under test (TBD), and the frequency ratios corresponding to each type of fault; classifying the various faults based on false alarm judgment criteria to obtain false alarm-prone faults and non-false alarm faults, wherein the false alarm judgment criteria include an assessment of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold; obtaining the failure rate corresponding to each component; determining, based on the failure rate and the frequency ratios, a first sum of probabilities of false alarm-prone faults occurring in each component of the TBD, and a second sum of probabilities of non-false alarm faults occurring; and determining a first false alarm rate corresponding to the TBD based on the first sum of probabilities and the second sum of probabilities. This improves the interpretability and accuracy of the false alarm rate.

Description

Technical Field

[0001] This disclosure relates to the field of system testing technology, and in particular to a method and apparatus for determining the false alarm rate of a product, an electronic device, and a storage medium. Background Technology

[0002] False alarm rate, also known as false alarm rate, represents the probability of an incorrect alarm. It is a core indicator for measuring product reliability and can also serve as a fundamental metric for product optimization.

[0003] Typically, false alarm rates can be assessed based on the product itself or actual operational data from similar products. However, the lack of actual operational data during the product design phase hinders false alarm rate assessment.

[0004] As a second-best option, one can test the prototype product during the design phase to obtain test data, and then use this data to assess the false alarm rate. However, the interpretability and accuracy of the assessment results are not high. Summary of the Invention

[0005] In view of this, this disclosure proposes a scheme for determining the false alarm rate of a product.

[0006] According to one aspect of this disclosure, a method for determining the false alarm rate of a product is provided. The method includes: determining various potential faults of each component in the product under test, and the frequency ratios corresponding to each type of fault; classifying the various types of faults based on false alarm judgment criteria to obtain false alarm-prone faults and non-false alarm faults, wherein the false alarm judgment criteria include an assessment of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold; obtaining the failure rate corresponding to each component; determining, based on the failure rate and the frequency ratios, a first sum of probabilities of false alarm-prone faults occurring in each component of the product under test, and a second sum of probabilities of non-false alarm faults occurring; and determining a first false alarm rate corresponding to the product under test based on the first sum of probabilities and the second sum of probabilities.

[0007] In one possible implementation, the method further includes: comparing the first false alarm rate and the warning rate threshold; if the first false alarm rate is greater than the false alarm rate threshold, adjusting the product under test to obtain a new product under test; iteratively performing operations to determine the potential faults of each component in the product under test and to adjust the product under test until the first false alarm rate is not greater than the false alarm rate threshold, stopping the iteration, and obtaining the iterated product and the target false alarm rate.

[0008] In one possible implementation, determining the potential types of faults in each component of the product under test, and the frequency ratios corresponding to the types of faults, includes: obtaining test result data based on a comprehensive test of the product under test; determining the types of faults based on the test result data; and querying reliability standard data to determine the frequency ratios corresponding to the types of faults.

[0009] In one possible implementation, after the comprehensive testing, test link data is also obtained; the distinction between various types of faults based on false alarm judgment criteria to obtain false alarm-prone faults and non-false alarm faults includes: determining the faults corresponding to the test link data and / or test result data that meet the false alarm judgment criteria as false alarm-prone faults; the false alarm judgment criteria include one or more of the following: test link hardware failure; the tested component is normal, but the test result data is abnormal; the test result data falls into the threshold critical region.

[0010] In one possible implementation, obtaining the failure rate corresponding to each component includes: looking up the failure rate in a failure table based on the type and operating parameters of each component to obtain the baseline failure rate of each component; and determining the failure rate corresponding to each component based on the baseline failure rate and the adjustment coefficient.

[0011] In one possible implementation, determining the first sum of probabilities of false alarm-prone faults and the second sum of probabilities of non-false alarm faults for each component in the product under test based on the failure rate and the frequency ratio includes: determining the false alarm probability corresponding to the same component based on the frequency ratio of various false alarm-prone faults of the same component and the failure rate of the same component; determining the non-false alarm probability corresponding to the same component based on the frequency ratio of various non-false alarm faults of the same component and the failure rate of the same component; determining the first sum of probabilities based on each of the false alarm probabilities; and determining the second sum of probabilities based on each of the non-false alarm probabilities.

[0012] In one possible implementation, the product under test is the airborne electrical equipment of an aircraft; the comprehensive test includes at least three types of tests: in-flight testing, redundancy comparison, sensor signal analysis, external automated equipment testing, and manual inspection.

[0013] According to another aspect of this disclosure, a product false alarm rate determination apparatus is provided, the apparatus comprising:

[0014] The fault and frequency ratio determination unit is used to determine the potential faults of each component in the product under test, and the frequency ratios corresponding to each fault.

[0015] The fault classification unit is used to classify the various faults based on the false alarm judgment criteria to obtain false alarm faults and non-false alarm faults. The false alarm judgment criteria include the evaluation of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold.

[0016] A failure rate determination unit is used to obtain the failure rate corresponding to each component.

[0017] The unit for determining the sum of probabilities of false alarm faults and non-false alarm faults is used to determine the first sum of probabilities of false alarm faults occurring in each component of the product under test and the second sum of probabilities of non-false alarm faults occurring based on the fault rate and the frequency ratio.

[0018] The first false alarm rate determination unit is used to determine the first false alarm rate corresponding to the product under test based on the first probability sum and the second probability sum.

[0019] In one possible implementation, the device further includes:

[0020] The product under test adjustment unit is used to compare the first false alarm rate and the warning rate threshold. If the first false alarm rate is greater than the false alarm rate threshold, the product under test is adjusted to obtain a new product under test.

[0021] An iterative control unit is used to iteratively determine various potential faults in each component of the product under test and adjust the product under test until the first false alarm rate is not greater than the false alarm rate threshold, at which point the iteration stops, resulting in the iterated product and the target false alarm rate.

[0022] In one possible implementation, the fault and frequency ratio determination unit is further configured to:

[0023] Based on a comprehensive test of the product under test, test result data was obtained;

[0024] Based on the test results data, the various types of faults are determined;

[0025] Query reliability standard data to determine the frequency ratio corresponding to the various types of faults.

[0026] In one possible implementation, after the comprehensive testing, test link data is also obtained;

[0027] The fault classification unit is further used for:

[0028] Faults corresponding to test link data and / or test result data that meet the false alarm judgment criteria are identified as faults that can trigger false alarms.

[0029] The false alarm judgment criteria include one or more of the following:

[0030] Test link hardware failure;

[0031] The tested component is normal, but the test results are abnormal;

[0032] The test result data falls within the threshold critical zone.

[0033] In one possible implementation, the failure rate determination unit is further configured to:

[0034] Based on the type and operating parameters of each component, a lookup table is performed in the failure table to obtain the baseline failure rate of each component;

[0035] Based on the baseline failure rate and adjustment coefficient, the failure rate corresponding to each component is determined.

[0036] In one possible implementation, the unit for determining the sum of probabilities of false alarm faults and non-false alarm faults is further configured to:

[0037] Based on the frequency ratio of various false alarm faults of the same component and the failure rate of the same component, the false alarm probability corresponding to the same component is determined.

[0038] Based on the frequency ratio of various non-false alarm faults of the same component and the failure rate of the same component, the non-false alarm probability corresponding to the same component is determined.

[0039] Based on each of the aforementioned false alarm probabilities, the sum of the first probabilities is determined;

[0040] The second sum of probabilities is determined based on each of the non-false alarm probabilities.

[0041] In one possible implementation, the product under test is the airborne electrical equipment of an aircraft.

[0042] The comprehensive testing includes at least three types of testing: in-machine testing, redundancy comparison, sensor signal analysis, external automated equipment testing, and manual inspection.

[0043] According to another aspect of this disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0044] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described method.

[0045] According to another aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0046] This disclosure proposes a novel method for estimating false alarm rates. It comprehensively determines the various types of faults and their frequency ratios (the proportion of different types of faults for the same component) of each component in the product under test. Using false alarm judgment criteria, it accurately identifies false alarm-prone and non-false alarm faults from among the various types of faults. This allows for the determination of the probability of a false alarm-prone fault occurring (i.e., the first probability sum) and the probability of a non-false alarm fault occurring (i.e., the second probability sum) by combining the frequency ratios corresponding to false alarm-prone and non-false alarm faults with the corresponding component failure rates. This improves the interpretability and accuracy of the first and second probability sums, thereby enhancing the interpretability and accuracy of the false alarm rate determined using the first and second probability sums.

[0047] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0048] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0049] Figure 1 This is a flowchart illustrating the product false alarm rate determination method provided in this embodiment of the disclosure.

[0050] Figure 2 A schematic diagram of the structure of the product false alarm rate determination device provided in the embodiments of this disclosure.

[0051] Figure 3 This is a schematic diagram of the structure of an electronic device for determining the false alarm rate of a product, provided in an embodiment of this disclosure. Detailed Implementation

[0052] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0053] As used herein, the terms “comprising,” “including,” “having,” or variations thereof are open-ended and include one or more of the stated features, integrals, elements, steps, components, or functions, but do not exclude the presence or addition of one or more other features, integrals, elements, steps, components, functions, or groups thereof.

[0054] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0055] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another. Therefore, without departing from the teachings of the inventive concept, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0056] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0057] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0058] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0059] Figure 1 A flowchart illustrating a method for determining the false alarm rate of a product provided in this embodiment of the disclosure. The method includes:

[0060] S11, determine the potential types of faults of each component in the product under test, and the frequency ratio of each type of fault.

[0061] The product under test (DUT) can be a prototype product in the design phase. In this embodiment, each component in the DUT can be tested directly, or test records of each component in other products can be obtained to identify potential faults in various components. Other products can be similar to the DUT and have already entered the testing phase or are already in use. The components referred to here can be individual components in the DUT; or they can be components examined to determine the false alarm rate. The components examined to determine the false alarm rate can be multiple or all components in the DUT.

[0062] In this embodiment, the frequency ratio of various types of faults of a component can characterize the occurrence proportion of each type of fault of that component. For example, the faults corresponding to component A include fault a, fault b, and fault c. Wherein, if component A experiences 10 faults, fault a occurs 3 times, fault b occurs 5 times, and fault c occurs 2 times. Therefore, it can be determined that for component A, the frequency ratio corresponding to fault a is 30%, the frequency ratio corresponding to fault b is 50%, and the frequency ratio corresponding to fault c is 20%.

[0063] In this embodiment, various types of faults and their corresponding frequency ratios can be determined for each component in the product under test. This provides a comprehensive understanding of the possible faults and their occurrence rates in the product under test. Even if the product under test is a prototype in the design phase, comprehensive fault data can be obtained.

[0064] S12, based on the false alarm judgment criteria, classify the various types of faults to obtain false alarm faults and non-false alarm faults. The false alarm judgment criteria include the evaluation of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold.

[0065] False alarm judgment criteria can determine the validity of various identified faults. If a fault is determined to be valid, it can be classified as a non-false alarm fault; if a fault is determined to be invalid, it can be classified as a potential false alarm fault. False alarm judgment criteria can include criteria for verifying fault validity. These criteria include judging at least one of the following aspects during testing: test link validity, test result accuracy, and test threshold reasonableness. This allows for accurate identification of the validity of various faults in each component.

[0066] S13, obtain the failure rate corresponding to each component.

[0067] In this embodiment of the disclosure, the failure rate of each component can be determined based on the test results obtained by directly testing each component in the product under test, or based on the test records of each component in other products. This is only one example, and other methods can also be used to determine the failure rate of components, which are not limited in this embodiment of the disclosure. Other methods for determining the failure rate will be described below.

[0068] S14, based on the failure rate and the frequency ratio, determine the first total probability of a false alarm fault occurring in each component of the product under test, and the second total probability of a non-false alarm fault occurring.

[0069] A potential component failure can cause a product under test (DUT) failure. A component experiencing a false alarm-like failure can cause the DUT to experience a false alarm-like failure. A component experiencing a non-false alarm-like failure can cause the DUT to experience a non-false alarm-like failure. Therefore, the first probability sum represents the probability of the DUT experiencing a false alarm-like failure. The second probability sum represents the probability of the DUT experiencing a non-false alarm-like failure. The first probability of a component can be obtained by summing the products of the frequency ratios of its false alarm-like failures and the component's failure rate. The second probability of a component can be obtained by summing the first probabilities for each component in the DUT.

[0070] For ease of understanding, formulas (1) and (2) can be used to represent the process of determining the first probability sum, and formulas (3) and (4) can be used.

[0071] (1)

[0072] (2)

[0073] in, This indicates the failure rate of component i. This represents the frequency ratio of the j-th non-false alarm fault of component i, where m represents the total number of non-false alarm faults corresponding to component i. Let represent the second probability of element i, and n represent the number of elements to be examined in determining the false alarm rate. This represents the sum of the second probabilities.

[0074] (3)

[0075] (4)

[0076] in, This represents the frequency ratio of the t-th false alarm fault of component i, where k indicates that component i corresponds to a total of k false alarm faults. This represents the first probability of element i. This represents the sum of the first probabilities.

[0077] S15, based on the first probability sum and the second probability sum, determine the first false alarm rate corresponding to the product under test.

[0078] In this embodiment of the disclosure, the failure probability of the product under test (PUT) can be determined based on the first probability sum and the second probability sum. Furthermore, based on the first probability sum and the failure probability, the proportion of false alarm-prone failures occurring in the PUT out of all actual failures can be determined, and this proportion is defined as the first false alarm rate. The first false alarm rate represents the probability of a false alarm-prone failure occurring in the PUT. That is, the first false alarm rate characterizes the probability of a false alarm being triggered by the PUT.

[0079] For ease of understanding, the process of determining the first false alarm rate can be represented by formula (5).

[0080] (5)

[0081] in, Indicates the first false alarm rate. This represents the sum of the second probabilities. This represents the sum of the first probabilities.

[0082] This disclosure proposes a novel method for estimating false alarm rates. It comprehensively determines the various types of faults and their frequency ratios (the proportion of different types of faults for the same component) of each component in the product under test. Using false alarm judgment criteria, it accurately identifies false alarm-prone and non-false alarm faults from among the various types of faults. This allows for the determination of the probability of a false alarm-prone fault occurring (i.e., the first probability sum) and the probability of a non-false alarm fault occurring (i.e., the second probability sum) by combining the frequency ratios corresponding to false alarm-prone and non-false alarm faults with the corresponding component failure rates. This improves the interpretability and accuracy of the first and second probability sums, thereby enhancing the interpretability and accuracy of the false alarm rate determined using the first and second probability sums.

[0083] In one possible implementation, the method further includes: comparing the first false alarm rate and the warning rate threshold; if the first false alarm rate is greater than the false alarm rate threshold, adjusting the product under test to obtain a new product under test; iteratively performing operations to determine the potential faults of each component in the product under test and to adjust the product under test until the first false alarm rate is not greater than the false alarm rate threshold, stopping the iteration, and obtaining the iterated product and the target false alarm rate.

[0084] The false alarm rate threshold represents the upper limit of the acceptable false alarm rate for a product under test. The false alarm rate threshold can be determined based on national standards, industry standards, or specific scenario requirements for the product under test.

[0085] A false alarm rate exceeding the false alarm rate threshold indicates that the product under test (DUT) does not meet requirements and needs adjustment to complete an iteration. This adjustment may include reducing the workload of the DUT and / or replacing one or more components with more reliable ones. For example, the workload of the DUT can be reduced by decreasing the workload of components and / or other parts. For ease of description, the adjusted DUT will be named the new DUT. A single iteration may include performing operations ranging from identifying potential faults in the components of the DUT to adjusting the DUT.

[0086] If the first false alarm rate is not greater than the false alarm rate threshold, it means that the product under test meets the requirements, and the iteration can be stopped to obtain the iterated product. The first false alarm rate determined in the last iteration is taken as the target false alarm rate.

[0087] Through iterations in the embodiments of this disclosure, product iterations aimed at achieving a required false alarm rate were completed, thereby improving product reliability. Furthermore, an interpretable target false alarm rate was accurately determined synchronously with the product iterations.

[0088] In one possible implementation, determining the potential types of faults in each component of the product under test, and the frequency ratios corresponding to the types of faults, includes: obtaining test result data based on a comprehensive test of the product under test; determining the types of faults based on the test result data; and querying reliability standard data to determine the frequency ratios corresponding to the types of faults.

[0089] A comprehensive test can include at least three of the following test items: in-machine testing, redundancy comparison, sensor signal analysis, external automated equipment testing, and manual inspection.

[0090] In this embodiment of the disclosure, comprehensive testing can be performed on the entire device under test (DUT) and each component. Each component can correspond to one or more test result data points. The test result data can characterize the normality of a component when the DUT is running or when the component is running independently. Therefore, the test result data can characterize the probability and type of component failure. For example, the test result data can be compared with a preset result threshold to determine whether a failure has occurred and the type of failure. Another example is that the presence of indicative data in the test results (e.g., under normal circumstances, type A data does not appear, but type A data appears when failure a occurs) can determine whether a failure has occurred and the type of failure.

[0091] In this embodiment of the disclosure, the reliability standard data can be industry or national standard documents. For example, the product under test can be the airborne electrical equipment of an aircraft, and the reliability standard data can be the Chinese national military standard "Reliability Prediction Manual for Electronic Equipment". Based on identified types of faults, the reliability standard data can be queried to obtain the frequency ratios corresponding to each type of fault. The frequency ratios of various faults for each component in the reliability standard data are more reliable and accurate.

[0092] In this embodiment of the disclosure, comprehensive testing of the product under test improves the comprehensiveness of fault identification. Furthermore, the identified faults are more specific to the product under test; the use of reliability standard data enhances the reliability of the frequency ratio. This, in turn, improves the accuracy of subsequent determination of the first false alarm rate.

[0093] In one possible implementation, after the comprehensive testing, test link data is also obtained; the distinction between various types of faults based on false alarm judgment criteria to obtain false alarm-prone faults and non-false alarm faults includes: determining the faults corresponding to the test link data and / or test result data that meet the false alarm judgment criteria as false alarm-prone faults; the false alarm judgment criteria include one or more of the following: test link hardware failure; the tested component is normal, but the test result data is abnormal; the test result data falls into the threshold critical region.

[0094] A test link can be the physical and logical path connecting test equipment and the electronic component under test. Its core purpose is to transmit test signals and collect response data to verify whether the component's function and performance are normal.

[0095] A failure of one or more hardware components in the test link can cause the test link to fail, thereby triggering a false alarm. For example, a failure in a component such as a sensor, comparator, or reference voltage in the test link (e.g., a sampling resistor short-circuited to the negative power supply) will directly output an over-limit code value.

[0096] As mentioned earlier, at least three tests can be performed. Therefore, the normality of a component can be verified in multiple ways. For example, a component might show abnormal test results in one test, but its test results in other tests are normal. Another example is that a component was tested before being installed in the product under test and proven to be normal, but the test results show that the component is abnormal. Such situations—where the component is normal but the test results are abnormal, or where only a few tests (one or two tests) indicate that the component is abnormal—suggest that the test results indicating the component's abnormality are inaccurate, the test validity corresponding to these results is low or invalid, and thus trigger false alarms. For instance, interface / environmental disturbances causing signal transients to exceed limits, coupled with a lack of effective filtering / debouncing in the internal test equipment, can lead to false alarms.

[0097] The threshold critical zone can be a numerical region near or within a preset test result threshold. If multiple test results from the same test fall within the threshold critical zone, it indicates that the threshold margin of the test results is insufficient; or that the situation of multiple fault coupling has not been considered, resulting in an unreasonable threshold setting for the test results, which in turn triggers an early warning.

[0098] Therefore, this application uses early warning judgment criteria to distinguish between false alarm faults and non-false alarm faults, which can improve the accuracy and reliability of determining false alarm faults and non-false alarm faults.

[0099] In one possible implementation, obtaining the failure rate corresponding to each component includes: looking up the failure rate in a failure table based on the type and operating parameters of each component to obtain the baseline failure rate of each component; and determining the failure rate corresponding to each component based on the baseline failure rate and the adjustment coefficient.

[0100] Operating parameters may include data such as electrical stress (voltage, current), thermal stress (junction temperature or ambient temperature), and duty cycle in the actual operating environment. Failure tables may include component failure rates (baseline failure rates) recorded in industry or national standard documents. For example, a failure table could be a component failure rate data table from the Chinese national military standard "Reliability Prediction Manual for Electronic Equipment."

[0101] In this embodiment of the disclosure, the adjustment factor can be data characterizing the environment in which the component in the device under test is located, the individual characteristics of the component, or the characteristics of a single batch of components. For example, the adjustment factor may include: an environmental factor, a quality factor, and a temperature stress factor.

[0102] In one example, the component's model, package, and quality grade can be extracted from the bill of materials to determine the component type. The component's operating parameters under actual operating conditions are then determined. Based on the component type and operating parameters, a failure table is consulted to determine the component's baseline failure rate. An adjustment factor for the component in the product under test is determined; based on the baseline failure rate and the adjustment factor, the component's overall failure rate is then calculated.

[0103] For ease of understanding, the failure rate of a component can be expressed using formula (6).

[0104] (6)

[0105] Where λ represents the failure rate of the component, Indicates the baseline failure rate. Represents the environmental factor. Indicates the quality coefficient. This represents the temperature stress coefficient.

[0106] In this embodiment, the use of component type and operating parameters fully considers the unique characteristics of each component, improving the accuracy of matching the determined baseline failure rate with the components. Furthermore, the use of a failure table enhances the reliability of the baseline failure rate. In determining the failure rate, an adjustment coefficient is used to fully consider the environment in which the components operate, further improving the reliability of the determined failure rate.

[0107] In one possible implementation, determining the first sum of probabilities of false alarm-prone faults and the second sum of probabilities of non-false alarm faults for each component in the product under test based on the failure rate and the frequency ratio includes: determining the false alarm probability corresponding to the same component based on the frequency ratio of various false alarm-prone faults of the same component and the failure rate of the same component; determining the non-false alarm probability corresponding to the same component based on the frequency ratio of various non-false alarm faults of the same component and the failure rate of the same component; determining the first sum of probabilities based on each of the false alarm probabilities; and determining the second sum of probabilities based on each of the non-false alarm probabilities.

[0108] In this embodiment, the product of the component's failure rate and the frequency ratio of each false alarm fault can be used as the probability of each type of false alarm fault occurring, thus obtaining the false alarm probability corresponding to that component. Similarly, the product of the component's failure rate and the frequency ratio of each non-false alarm fault can be used as the probability of each type of non-false alarm fault occurring, thus obtaining the non-false alarm probability corresponding to that component. Furthermore, the false alarm probabilities corresponding to each component can be summed to obtain a first probability sum; and the non-false alarm probabilities of each component can be summed to obtain a second probability sum. The calculation process of the first and second probability sums is simple, has a low error rate, and is interpretable, improving the accuracy, reliability, and interpretability of the first false alarm rate.

[0109] Figure 2 A schematic diagram of the product false alarm rate determination device provided in this embodiment of the disclosure. The device 20 includes:

[0110] The fault and frequency ratio determination unit 21 is used to determine the potential faults of each component in the product under test, and the frequency ratios corresponding to the various faults.

[0111] The fault classification unit 22 is used to classify the various faults based on the false alarm judgment criteria to obtain false alarm faults and non-false alarm faults. The false alarm judgment criteria include the evaluation of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold.

[0112] Failure rate determination unit 23 is used to obtain the failure rate corresponding to each component;

[0113] The unit 24 for determining the sum of probabilities of false alarm faults and non-false alarm faults is used to determine the first sum of probabilities of false alarm faults and the second sum of probabilities of non-false alarm faults for each component in the product under test based on the fault rate and the frequency ratio.

[0114] The first false alarm rate determination unit 25 is used to determine the first false alarm rate corresponding to the product under test based on the first probability sum and the second probability sum.

[0115] In one possible implementation, the device 20 further includes:

[0116] The product under test adjustment unit is used to compare the first false alarm rate and the warning rate threshold. If the first false alarm rate is greater than the false alarm rate threshold, the product under test is adjusted to obtain a new product under test.

[0117] An iterative control unit is used to iteratively determine various potential faults in each component of the product under test and adjust the product under test until the first false alarm rate is not greater than the false alarm rate threshold, at which point the iteration stops, resulting in the iterated product and the target false alarm rate.

[0118] In one possible implementation, the fault and frequency ratio determination unit 21 is further configured to:

[0119] Based on a comprehensive test of the product under test, test result data was obtained;

[0120] Based on the test results data, the various types of faults are determined;

[0121] Query reliability standard data to determine the frequency ratio corresponding to the various types of faults.

[0122] In one possible implementation, after the comprehensive testing, test link data is also obtained;

[0123] The fault classification unit 22 is further used for:

[0124] Faults corresponding to test link data and / or test result data that meet the false alarm judgment criteria are identified as faults that can trigger false alarms.

[0125] The false alarm judgment criteria include one or more of the following:

[0126] Test link hardware failure;

[0127] The tested component is normal, but the test results are abnormal;

[0128] The test result data falls within the threshold critical zone.

[0129] In one possible implementation, the failure rate determination unit 23 is further configured to:

[0130] Based on the type and operating parameters of each component, a lookup table is performed in the failure table to obtain the baseline failure rate of each component;

[0131] Based on the baseline failure rate and adjustment coefficient, the failure rate corresponding to each component is determined.

[0132] In one possible implementation, the unit 24 for determining the sum of probabilities of false alarm faults and non-false alarm faults is further configured to:

[0133] Based on the frequency ratio of various false alarm faults of the same component and the failure rate of the same component, the false alarm probability corresponding to the same component is determined.

[0134] Based on the frequency ratio of various non-false alarm faults of the same component and the failure rate of the same component, the non-false alarm probability corresponding to the same component is determined.

[0135] Based on each of the aforementioned false alarm probabilities, the sum of the first probabilities is determined;

[0136] The second sum of probabilities is determined based on each of the non-false alarm probabilities.

[0137] In one possible implementation, the product under test is the airborne electrical equipment of an aircraft.

[0138] The comprehensive testing includes at least three types of testing: in-machine testing, redundancy comparison, sensor signal analysis, external automated equipment testing, and manual inspection.

[0139] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0140] This disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0141] This disclosure also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0142] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0143] Figure 3This is a schematic diagram of an electronic device for determining the false alarm rate of a product, provided as an embodiment of this disclosure. For example, device 1900 can be provided as a server or terminal device. (Refer to...) Figure 3 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0144] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output interface 1958 (I / O interface). Device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM macOS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0145] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0146] Computer-readable storage media can be tangible devices capable of holding and storing programs / instructions used by instruction execution devices. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0147] The computer program (or computer-readable program instructions) described herein can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage medium in the respective computing / processing device.

[0148] The computer program (or computer program instructions) used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions to implement various aspects of this disclosure.

[0149] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0150] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0151] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0152] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0153] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining the false alarm rate of a product, characterized in that, include: Identify the potential types of faults in each component of the product under test, and the frequency ratios corresponding to each type of fault; Based on the false alarm judgment criteria, the various types of faults are classified to obtain false alarm faults and non-false alarm faults. The false alarm judgment criteria include the evaluation of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold. Obtain the failure rate corresponding to each component; Based on the failure rate and the frequency ratio, the first total probability of a false alarm fault occurring in each component of the product under test and the second total probability of a non-false alarm fault are determined. Based on the first probability sum and the second probability sum, the first false alarm rate corresponding to the product under test is determined.

2. The method according to claim 1, characterized in that, The method further includes: The first false alarm rate and the warning rate threshold are compared numerically. If the first false alarm rate is greater than the false alarm rate threshold, the product to be tested is adjusted to obtain a new product to be tested. The process iterates through identifying potential faults in each component of the product under test and adjusting the product until the first false alarm rate is no greater than the false alarm rate threshold. The iteration is then stopped, resulting in the iterated product and the target false alarm rate.

3. The method according to claim 1, characterized in that, The determination of potential faults in each component of the product under test, and the frequency ratios corresponding to each fault, includes: Based on a comprehensive test of the product under test, test result data was obtained; Based on the test results data, the various types of faults are determined; Query reliability standard data to determine the frequency ratio corresponding to the various types of faults.

4. The method according to claim 3, characterized in that, Following the comprehensive testing, test link data was also obtained; The false alarm judgment criterion distinguishes the various types of faults to obtain false alarm-prone faults and non-false alarm faults, including: Faults corresponding to test link data and / or test result data that meet the false alarm judgment criteria are identified as faults that can trigger false alarms. The false alarm judgment criteria include one or more of the following: Test link hardware failure; The tested component is normal, but the test results are abnormal; The test result data falls within the threshold critical zone.

5. The method according to claim 1, characterized in that, The process of obtaining the failure rate corresponding to each component includes: Based on the type and operating parameters of each component, a lookup table is performed in the failure table to obtain the baseline failure rate of each component; Based on the baseline failure rate and adjustment coefficient, the failure rate corresponding to each component is determined.

6. The method according to claim 1, characterized in that, The determination of the first total probability of a false alarm-like fault occurring in each component of the product under test and the second total probability of a non-false alarm fault, based on the failure rate and the frequency ratio, includes: Based on the frequency ratio of various false alarm faults of the same component and the failure rate of the same component, the false alarm probability corresponding to the same component is determined. Based on the frequency ratio of various non-false alarm faults of the same component and the failure rate of the same component, the non-false alarm probability corresponding to the same component is determined. Based on each of the aforementioned false alarm probabilities, the sum of the first probabilities is determined; The second sum of probabilities is determined based on each of the non-false alarm probabilities.

7. The method according to claim 3, characterized in that, The product under test is the airborne electrical equipment of an aircraft. The comprehensive testing includes at least three types of testing: in-machine testing, redundancy comparison, sensor signal analysis, external automated equipment testing, and manual inspection.

8. A device for determining the false alarm rate of a product, characterized in that, include: The fault and frequency ratio determination unit is used to determine the potential faults of each component in the product under test, and the frequency ratios corresponding to each fault. The fault classification unit is used to classify the various faults based on the false alarm judgment criteria to obtain false alarm faults and non-false alarm faults. The false alarm judgment criteria include the evaluation of the effectiveness of the test link, and / or the accuracy of the test results, and / or the reasonableness of the test threshold. A failure rate determination unit is used to obtain the failure rate corresponding to each component. The unit for determining the sum of probabilities of false alarm faults and non-false alarm faults is used to determine the first sum of probabilities of false alarm faults occurring in each component of the product under test and the second sum of probabilities of non-false alarm faults occurring based on the fault rate and the frequency ratio. The first false alarm rate determination unit is used to determine the first false alarm rate corresponding to the product under test based on the first probability sum and the second probability sum.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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