Sensor accelerated life modeling method and system based on multi-stress coupling

Abstract

The invention provides a sensor accelerated life modeling method and system based on multi-stress coupling. The method comprises the following steps: constructing a multi-stress coupling accelerated life model considering an electromagnetic damp-heat coupling effect; acquiring accelerated life test data including an electric field, a magnetic field, a temperature and a temperature, which are acquired when the sensor sample is subjected to an accelerated life test; and according to the accelerated life test data, fitting and solving the model parameters of the multi-stress coupling accelerated life model by adopting a hierarchical coefficient method, and determining the multi-stress coupling accelerated life model of the sensor of which the accelerated life is to be predicted. According to the method and the system, a multi-stress accelerated life model containing an electromagnetic coupling item and a temperature and humidity coupling item is innovatively provided, quantitative description of four stress interaction is realized for the first time, and the theoretical accuracy of life prediction is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sensor reliability testing, and more particularly, to a sensor accelerated life modeling method and system based on multi-stress coupling. BACKGROUND

[0002] The accelerated life test technology has experienced important development from single stress to multi-stress, from simple model to coupling model. Early researches were mainly based on single stress acceleration methods such as Arrhenius model and inverse power law model, and then developed to models considering the joint action of temperature-humidity and other multi-stresses. However, the existing methods are still insufficient when facing the complex electro-magnetic-thermal-humidity multi-stress coupling environment of the actual operation of power sensors: on the one hand, the traditional acceleration model is difficult to accurately describe the coupling effect between multiple stresses; on the other hand, there is a lack of systematic test design and parameter fitting method, which limits the accuracy of life prediction and cannot meet the urgent needs of power sensor reliability evaluation in the construction of new power systems. SUMMARY

[0003] In order to solve the technical problems that the existing technology is difficult to accurately describe the coupling effect between multiple stresses when facing the complex electro-magnetic-thermal-humidity multi-stress coupling environment of the actual operation of power sensors, and the accuracy of life prediction is limited, the present application provides a sensor accelerated life modeling method and system based on multi-stress coupling.

[0004] According to one aspect of the present application, the present application provides a sensor accelerated life modeling method based on multi-stress coupling, comprising:

[0005] constructing a multi-stress coupling accelerated life model considering electromagnetic-humidity-thermal coupling effect;

[0006] obtaining accelerated life test data including electric field, magnetic field, temperature and temperature collected when performing accelerated life test on sensor samples;

[0007] According to the accelerated life test data, the model parameters of the multi-stress coupling accelerated life model are fitted and solved by using the hierarchical coefficient method, and the multi-stress coupling accelerated life model of the sensor to be predicted is determined.

[0008] According to another aspect of the present application, the present application provides a sensor accelerated life modeling system based on multi-stress coupling, the system comprising:

[0009] a model construction module for constructing a multi-stress coupling accelerated life model considering electromagnetic-humidity-thermal coupling effect;

[0010] a data acquisition module for acquiring accelerated life test data including electric field, magnetic field, temperature and temperature collected when performing accelerated life test on sensor samples;

[0011] a model determining module configured to determine a multi-stress coupling accelerated life model of the sensor for predicting the accelerated life according to the accelerated life test data, by using a hierarchical coefficient method to solve model parameter fitting of the multi-stress coupling accelerated life model.

[0012] According to still another aspect of the present application, a computer readable storage medium is provided, which stores a computer program, the program being executed by a processor to implement the method according to any one of the preceding aspects of the present application.

[0013] According to still another aspect of the present application, an electronic device is provided, which comprises: a processor; a memory for storing executable instructions of the processor; and the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of the preceding aspects of the present application.

[0014] The multi-stress coupling based accelerated life modeling method and system of the sensor, the method comprising: constructing a multi-stress coupling accelerated life model considering electromagnetic and thermal coupling effects; obtaining accelerated life test data of a sensor sample, including electric field, magnetic field, temperature and temperature; determining a multi-stress coupling accelerated life model of the sensor for predicting the accelerated life according to the accelerated life test data, by using a hierarchical coefficient method to solve model parameter fitting of the multi-stress coupling accelerated life model. The method and system innovatively propose a multi-stress accelerated model containing electromagnetic coupling terms and thermal coupling terms, first realize the quantitative description of the interaction of the four stresses, significantly improve the theoretical accuracy of life prediction, and solve the technical problem of prediction deviation caused by ignoring stress coupling effect in traditional models; in terms of test design, the orthogonal test matrix design method is used, only 9 groups of tests are needed to evaluate the four stress factors and their interactions completely, compared with 81 groups of tests in the comprehensive test, the test efficiency is improved by 89%, and the test cost and time cost are greatly reduced; in terms of test implementation, a simplified test process based on constant stress loading is established, through the comprehensive evaluation of the three failure criteria of insulation resistance, measurement error and surface corrosion, the comprehensiveness and reliability of the test results are ensured, and the problem of single criterion in traditional methods is solved; in terms of parameter calculation, a hierarchical successive approximation strategy is used to decompose the complex multi-parameter fitting problem into four levels, effectively avoiding the local optimal trap, the parameter fitting stability is improved by about 40%, and the model prediction accuracy is more than 90%. BRIEF DESCRIPTION OF DRAWINGS

[0015] The exemplary embodiments of the present application can be more fully understood by reference to the following drawings:

[0016] Figure 1A flow chart of a multi-stress coupling based sensor accelerated life modeling method according to a preferred embodiment of the present application;

[0017] Figure 2 A structural schematic diagram of a multi-stress coupling based sensor accelerated life modeling system according to a preferred embodiment of the present application;

[0018] Figure 3 A structural schematic diagram of an electronic device according to a preferred embodiment of the present application. DETAILED DESCRIPTION

[0019] Reference will now be made to the exemplary embodiments of the present application with reference to the accompanying drawings, however, the present application can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, provided herein are the embodiments in order to thoroughly and completely disclose the present application and to fully convey the scope of the present application to those skilled in the art. The terms used in the exemplary embodiments of the present application expressed in the accompanying drawings are not limited to the present application. In the drawings, like reference numerals refer to like elements throughout.

[0020] Unless otherwise defined, the terms (including technical terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. Also, it is to be understood that the terms defined by commonly used dictionaries are to be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0021] Exemplary method

[0022] Figure 1 A flow chart of a multi-stress coupling based sensor accelerated life modeling method according to a preferred embodiment of the present application. As shown in Figure 1 the multi-stress coupling based sensor accelerated life modeling method according to the preferred embodiment of the present application starts from step 101.

[0023] In step 101, a multi-stress coupling accelerated life model considering electromagnetic and thermal-hygro coupling effects is constructed.

[0024] Preferably, the multi-stress coupling accelerated life model considering electromagnetic and thermal-hygro coupling effects is constructed, wherein the expression of the multi-stress coupling accelerated life model is:

[0025]

[0026] wherein, AF - acceleration factor, life acceleration multiple in laboratory environment;

[0027] E s ,E u - accelerated electric field stress, using electric field stress;

[0028] B s ,B u —accelerating magnetic field stress, using magnetic field stress;

[0029] T s ,T u —accelerating temperature stress, using temperature stress;

[0030] H s ,H u —accelerating humidity stress, using humidity stress;

[0031] α, β, γ, δ, η —accelerating exponents of each stress term and coupling term determined by fitting;

[0032] E a —activation energy, unit: eV;

[0033] k —Boltzmann constant, taking the value of 8.617 x 10 -5 eV / K.

[0034] In step 102, the accelerating life test data including electric field, magnetic field, temperature and temperature collected when the sensor sample is subjected to the accelerating life test is obtained.

[0035] Preferably, the accelerating life test data including electric field, magnetic field, temperature and temperature collected when the sensor sample is subjected to the accelerating life test is obtained, including:

[0036] According to the stress terms involved in the accelerating life test, a multi-stress orthogonal test matrix is constructed, and the construction principle is as follows:

[0037] Each stress term includes three levels of low, medium and high, each level of each stress term appears uniformly, and the combination of any two stress terms is complete coverage;

[0038] According to the multi-stress orthogonal test matrix, a plurality of groups of accelerating life tests are performed on the sensor sample by loading stress combinations, and the test indicators are measured regularly, wherein the test indicators include insulation resistance, sensor sample measurement error and surface corrosion grade;

[0039] When the measured test indicators meet the set test termination conditions, the failure time of the sensor sample and the loaded stress combination group are recorded as the accelerating life test data of the group, wherein the test termination conditions include at least one of the following: the insulation resistance drop ratio is greater than the set ratio threshold, the measurement error is greater than the set error threshold, and visible corrosion occurs.

[0040] In step 103, according to the accelerated life test data, the model parameters of the multi-stress coupling accelerated life model are fitted and solved by using the stratification coefficient method to determine the multi-stress coupling accelerated life model of the sensor for predicting the accelerated life.

[0041] Preferably, according to the accelerated life test data, the model parameters of the multi-stress coupling accelerated life model are fitted and solved by using the stratification coefficient method to determine the multi-stress coupling accelerated life model of the sensor for predicting the accelerated life, comprising:

[0042] Select the accelerated life test data of at least one stress in the low level group, and simplify the multi-stress coupling accelerated life model to a form containing only the temperature term, and obtain the initial value of the normalized activation energy E a / k by one-dimensional linear regression;

[0043] Fix the initial value of the activation energy E a / k, and perform single stress fitting on the electric field term, the humidity term and the magnetic field term, specifically:

[0044] Select the accelerated life test data of at least one stress in the low level group other than the stress term to be fitted, simplify the multi-stress coupling accelerated life model to a form containing only the stress term to be fitted, and determine the initial values of the electric field acceleration coefficient α, the humidity acceleration coefficient β and the magnetic field acceleration coefficient γ;

[0045] Fix the activation energy E a / k, the initial values of the electric field acceleration coefficient α, the humidity acceleration coefficient β and the magnetic field acceleration coefficient γ, and perform coupling stress fitting on the electromagnetic coupling term and the temperature and humidity coupling term, specifically:

[0046] Select the accelerated life test data of the stress term with a small product value other than the coupling stress term to be fitted, simplify the multi-stress coupling accelerated life model to a form containing only the coupling stress term to be fitted, and determine the initial values of the electromagnetic coupling coefficient δ and the temperature and humidity coupling coefficient η;

[0047] Based on the activation energy E a / k, the initial values of the electric field acceleration coefficient α, the humidity acceleration coefficient β, the magnetic field acceleration coefficient γ, the electromagnetic coupling coefficient δ and the temperature and humidity coupling coefficient η, perform global fitting on the multi-stress coupling accelerated life model by using multi-linear regression to calculate the final values of the activation energy E a / k, the electric field acceleration coefficient α, the humidity acceleration coefficient β, the magnetic field acceleration coefficient γ, the electromagnetic coupling coefficient δ and the temperature and humidity coupling coefficient η, and determine the multi-stress coupling accelerated life model of the sensor for predicting the accelerated life.

[0048] In the preferred embodiment, the leakage current sensor of the arrester is selected as the sensor sample of the embodiment of the method of the application, which is directly installed in the grounding circuit of the arrester and long-term bears:

[0049] ① Strong electric field stress: the monitored object is the leakage current under kilovolt-level power frequency voltage and impulse voltage

[0050] ② Strong magnetic field stress: in the transient strong magnetic field environment generated when the arrester operates

[0051] ③ Temperature stress: affected by the heating of the arrester body and the change of the ambient temperature

[0052] ④ Humidity stress: facing the humidity influence of rainwater, condensation and the like in outdoor operation

[0053] Such a complex stress environment perfectly meets the needs of the multi-stress coupling accelerated test, and the quantity required in the field is extremely large, with at least 1 million sensors installed in the field every year. Therefore, the leakage current sensor of the arrester is selected as the sample of the embodiment.

[0054] According to the working environment of the sensor, the values of the low, medium and high levels of the set stress items are shown in Table 1.

[0055] Stress term Low level Medium level High level Units Electric field (E) 0 20 50 kV / m Magnetic field (B) 0 0.1 0.2 mT Temperature (T) 80 85 90 ℃ Humidity (H) 30 60 90 % RH

[0056] According to Table 1, there are 4 stress items, each with 3 levels, therefore, an L9(3 4 ) orthogonal table is selected, which has 4 columns, each column has 3 levels, and there are 9 rows, i.e. 9 tests.

[0057] According to the working environment of the typical power sensor and the failure characteristics of the power sensor, a multi-stress orthogonal test matrix as shown in Table 2 is constructed, including typical failure modes: insulation aging (electric field), magnetic error (magnetic field), and wet heat corrosion (temperature and humidity), the innovation lies in the proposed key coupling effects of electromagnetic interference accelerating wet heat corrosion (δ·EB) and high temperature aggravating moisture diffusion (η·TH).

[0058] Table 2

[0059]

[0060]

[0061] Nine samples were taken from the sensors that had not been used after leaving the factory, and after determining that each function was in a normal state, the nine sensor samples were loaded with stress combinations according to the nine groups of data in Table 2. The insulation resistance, sensor sample measurement error, and surface corrosion level were measured every 8 hours. When the sensor sample met any one of the following conditions: the insulation resistance decreased by more than 50%, the measurement error was greater than 3%, and visible corrosion appeared on the surface, the sensor sample failure time was recorded. The final sensor sample accelerated life test data is shown in Table 3.

[0062] Table 3

[0063]

[0064] According to the above data, the preferred embodiment adopts a hierarchical successive approximation strategy to divide the six parameters to be solved of the multi-stress coupling accelerated life model into four levels for sequential solving, effectively solving the technical problem that simultaneous fitting of multiple parameters is prone to local optimal solution. The method significantly improves the stability and accuracy of parameter fitting through hierarchical mode from primary to secondary and from single stress to coupled stress.

[0065] (1) First layer: temperature dominant layer parameter fitting

[0066] The test data (test 1) in Table 2 with an electric field E = 0 kV / m and a humidity H close to the lowest level of 30% RH were selected for temperature term fitting.

[0067] Simplified model:

[0068] ln(t s )=C+(E a / k)×(1 / T u -1 / T s )

[0069] Wherein: the letter C represents the constant term (intercept)

[0070] Calculation process:

[0071] 1) Test 1 data: Ts = 80°, then the Fahrenheit temperature is 80 + 273.15 = 353.15 K, and 1 / Ts = 0.002832

[0072] 2) 1 / T u -1 / T s = 0.000523, wherein Tu = 25°, and 1 / Tu is converted to Fahrenheit temperature calculation;

[0073] 3) ln(ts) = ln(9120) = 9.118

[0074] 4) Combined with the temperature data of test 2 and test 3, a linear regression equation is established, and the computer tool (python scikit-learn, etc.) is used to solve:

[0075] Test 1: Ts = 80 ° = 353.15 K, 1 / Ts = 0.002832, 1 / Tu-1 / Ts = 0.003355-0.002832 = 0.000523, ln(ts) = ln(9120) = 9.118

[0076] Test 2: Ts = 85 ° = 358.15 K, 1 / Ts = 0.002792, 1 / Tu-1 / Ts = 0.003355-0.002792 = 0.000563, ln(ts) = ln(3000) = 8.006

[0077] Test 3: Ts = 90 ° = 363.15 K, 1 / Ts = 0.002754, 1 / Tu-1 / Ts = 0.003355-0.002754 = 0.000601, ln(ts) = ln(1080) = 6.984

[0078] 5) Calculation: Ea / k = 8450 K

[0079] 6) Goodness of fit: R 2 = 0.978

[0080] (2) Second layer: single stress expansion layer parameter fitting

[0081] After fixing the temperature term parameters, the intermediate variable is calculated:

[0082] Y' = ln(t s )-8450×(1 / T u -1 / T s )

[0083] 1) Fitting of electric field term coefficient a:

[0084] Selected data: test 1 (E = 0, ts = 9120h), test 5 (E = 20, ts = 2040h), test 9 (E = 50, ts = 1440h)

[0085] Establish equation:

[0086] Y' = C + a x E s / E u

[0087] Where: the letter C represents the constant term (intercept), Eu = 0.001 kV / m, and a = 0.0158 is obtained by least squares method.

[0088] 2) Humidity term coefficient β fitting:

[0089] Selected data: Test 1 (H = 30, ts = 9120h), Test 2 (H = 60, ts = 3000h), Test 3 (H = 90, ts = 1080h)

[0090] Establish equation:

[0091] Y' = C + β × (H s -H u )

[0092] Where: letter C represents constant term (intercept), Hu = 50% RH

[0093] Calculated: β = 0.0232

[0094] 3) Magnetic field term coefficient γ fitting:

[0095] Selected data: Test 1 (B = 0, ts = 9120h), Test 2 (B = 0.1, ts = 3000h), Test 3 (B = 0.2, ts = 1080h)

[0096] Establish equation:

[0097] Y' = C + γ × (B s -B u )

[0098] Where: letter C represents constant term (intercept), Bu = 0.001mT, calculated:

[0099] γ = -1.95

[0100] (3) Third layer: coupling stress layer parameter fitting

[0101] Fix all main effect parameters, calculate intermediate variables:

[0102] Y" = ln(t s )-[0.0158 × ln(E s / E u )+8450 × (1 / T u -1 / T s )-0.0232 × (H s -H u )-1.95 × (B s -B u )]

[0103] 1) Electromagnetic coupling coefficient δ fitting:

[0104] Selected data: Since the temperature and humidity coupling term Ts × Hs value is relatively small, select Test 5, 6, 8, 9 data

[0105] Equation:

[0106] Y" = C + δ x (E s x B s )

[0107] Where: letter C represents constant term (intercept)

[0108] Calculated: δ = -0.0085

[0109] 2) Humidity coupling coefficient η fitting:

[0110] Select data: test 1, 4, 7 (electromagnetic coupling term Es x Bs = 0)

[0111] Equation:

[0112] Y" = C + η x (T s x H s )

[0113] Where: letter C represents constant term (intercept)

[0114] Calculated: η = -0.000042

[0115] (4) Fourth layer: global fine-tuning and verification

[0116] The aforementioned parameters are used as initial values, and multiple linear regression is used to globally fit the complete model, and the fitting results are:

[0117] α = 0.0162 ± 0.0018 (P = 0.018)

[0118] Ea / k = 8480 ± 195 (P = 0.008)

[0119] β = -0.0238 ± 0.0015 (P = 0.012)

[0120] γ = -2.02 ± 0.72 (P = 0.035)

[0121] δ = -0.0092 ± 0.0028 (P = 0.021)

[0122] η = -0.000045 ± 0.000008 (P = 0.009)

[0123] Significance test shows that the P value of all parameters is less than 0.05, which is statistically significant.

[0124] Therefore, the final acceleration model is:

[0125]

[0126] The multi-stress coupling based sensor accelerated life modeling method of the preferred embodiment proposes a multi-stress accelerated life model containing electromagnetic coupling terms and temperature and humidity coupling terms, adopts an orthogonal test matrix design method, obtains accelerated life experiment data through comprehensive evaluation of three failure criteria of insulation resistance, measurement error and surface corrosion, and adopts a layered successive approximation strategy to decompose the complex multi-parameter fitting problem into four levels to solve model parameters, significantly improves the theoretical accuracy of life prediction on the basis of quantitative description of the interaction of the four stresses, and makes the model prediction accuracy reach more than 90%.

[0127] Exemplary system

[0128] Figure 2 The structure diagram of the multi-stress coupling based sensor accelerated life modeling system according to the preferred embodiment of the application is shown in Fig. 1. Figure 2 As shown in Fig. 1, the multi-stress coupling based sensor accelerated life modeling system 200 of the preferred embodiment includes:

[0129] A model construction module 201 for constructing a multi-stress coupling accelerated life model considering electromagnetic and thermal-humidity coupling effects;

[0130] A data acquisition module 202 for acquiring accelerated life test data including electric field, magnetic field, temperature and temperature acceleration test data collected when performing accelerated life test on sensor samples;

[0131] A model determination module 203 for determining a multi-stress coupling accelerated life model of the sensor to be predicted according to the accelerated life test data, using a layered coefficient method to solve model parameter fitting of the multi-stress coupling accelerated life model.

[0132] Preferably, the model construction module 201 constructs a multi-stress coupling accelerated life model considering electromagnetic and thermal-humidity coupling effects, wherein the expression of the multi-stress coupling accelerated life model is:

[0133]

[0134] In the formula, AF is an acceleration factor, a life acceleration multiple in a laboratory environment;

[0135] E s ,E u E is an accelerated electric field stress and a used electric field stress;

[0136] B s ,B u B is an accelerated magnetic field stress and a used magnetic field stress;

[0137] T s ,T u—accelerated temperature stress, use temperature stress;

[0138] H s ,H u —accelerated humidity stress, use humidity stress;

[0139] α, β, γ, δ, η—accelerated exponents of each stress term and coupling term determined by fitting;

[0140] E a —activation energy, unit: eV;

[0141] k—Boltzmann constant, taking 8.617 x 10 -5 eV / K.

[0142] Preferably, the data acquisition module 202 acquires the accelerated life test data of the sensor sample, including electric field, magnetic field, temperature and temperature, when the sensor sample is subjected to accelerated life test, including:

[0143] According to the stress terms involved in the accelerated life test, a multi-stress orthogonal test matrix is constructed, and the construction principle is as follows:

[0144] Each stress term includes three levels of low, medium and high, each level of each stress term appears uniformly, and the combination of any two stress terms is complete coverage;

[0145] According to the multi-stress orthogonal test matrix, a plurality of groups of accelerated life tests are performed on the sensor sample under the stress combination, and the test indicators are measured regularly, wherein the test indicators include insulation resistance, sensor sample measurement error and surface corrosion grade;

[0146] When the measured test indicators meet the set test termination conditions, record the failure time of the sensor sample and the loaded stress combination group as the accelerated life test data of the group, wherein the test termination conditions include at least one of the following: insulation resistance drop ratio is greater than the set proportion threshold, measurement error is greater than the set error threshold, and visible corrosion appears.

[0147] Preferably, the model solving module 203 determines the multi-stress coupling accelerated life model of the sensor for predicting the accelerated life according to the accelerated life test data, and adopts the hierarchical coefficient method to solve the model parameter fitting of the multi-stress coupling accelerated life model, including:

[0148] Select the accelerated life test data of at least one of the groups with low level of electric field, magnetic field and humidity, and simplify the multi-stress coupling accelerated life model into a form containing only temperature term, and obtain the initial value of normalized activation energy E a / k by one-dimensional linear regression;

[0149] Fixing the activation energy E a The initial values of the activation energy E

[0150] The acceleration life data of at least one stress term at a low level is selected in sequence, the multi-stress coupling acceleration life model is simplified to a form containing only the stress term to be fitted, and the initial values of the electric field acceleration coefficient a, the humidity acceleration coefficient b and the magnetic field acceleration coefficient g are determined.

[0151] Fixing the activation energy E a The initial values of the activation energy E

[0152] The acceleration life data of at least one stress term at a low level is selected in sequence, the multi-stress coupling acceleration life model is simplified to a form containing only the stress term to be fitted, and the initial values of the electric field acceleration coefficient a, the humidity acceleration coefficient b and the magnetic field acceleration coefficient g are determined.

[0153] Based on the activation energy E a The initial values of the activation energy E a The final values of the activation energy E

[0154] The multi-stress coupling sensor acceleration life modeling system based on the preferred embodiment of the application and the multi-stress coupling sensor acceleration life modeling method solve the steps of the multi-stress coupling acceleration life model, and achieve the same technical effects. Here, it is not repeated.

[0155] Exemplary electronic device

[0156] Figure 3 The structure of the electronic device according to the preferred embodiment of the application is shown in the schematic diagram. As shown in the figure Figure 3 The electronic device includes one or more processors 301 and a memory 302.

[0157] The processor 301 can be a central processing unit (CPU) or other forms of processing units with data processing capability and / or instruction execution capability, and can control other components in the electronic device to perform desired functions.

[0158] The memory 302 can include one or more computer program products that can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like. The non-volatile memory, for example, can include read-only memory (ROM), hard disk drives, solid-state drives, and / or the like. The computer-readable storage media can store one or more computer program instructions executable by the processor 301 to implement the multi-stress coupling based sensor accelerated life modeling method of various embodiments disclosed above and / or other desired functions. In one example, the electronic device can further include an input device 303 and an output device 304, which are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0159] In addition, the input device 303 can include, for example, a keyboard, a mouse, and / or the like.

[0160] The output device 304 can output various information to the outside. The output device 304 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and / or the like.

[0161] Of course, in order to simplify, Figure 3 Only some of the components of the electronic device related to the present disclosure are shown in FIG. 3, and components such as a bus, an input / output interface, and / or the like are omitted. In addition, the electronic device can further include any other appropriate components according to a specific application.

[0162] Exemplary computer program product and computer readable storage medium

[0163] In addition to the above-mentioned method and device, embodiments of the present disclosure can be a computer program product including computer program instructions that, when executed by a processor, cause the processor to perform steps of the multi-stress coupling based sensor accelerated life modeling method according to various embodiments of the present disclosure described in the above "Exemplary Methods" section of the specification.

[0164] The computer program product can be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, C++, and / or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote cloud device or server.

[0165] Furthermore, an embodiment of the present disclosure can also be a computer readable storage medium, having stored thereon computer program instructions which, when executed by a processor, cause the processor to carry out the steps described in the above-mentioned “Exemplary Method” section of the present specification for a sensor accelerated life modeling method based on multi-stress coupling according to various embodiments of the present disclosure.

[0166] The computer readable storage medium can take the form of one or more combinations of any type of computer readable medium. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0167] The above describes the basic principles of the present disclosure in conjunction with specific embodiments, but it should be noted that the advantages, benefits, effects and the like mentioned in the present disclosure are only examples and are not limiting, and these advantages, benefits, effects and the like cannot be considered as necessary for each embodiment of the present disclosure. In addition, the above specific details are only for the purpose of example and for the purpose of understanding, and the above details do not limit the present disclosure to be necessarily implemented with the above specific details.

[0168] Each embodiment in the present specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between each embodiment can be understood by mutual reference. For system embodiments, since they basically correspond to method embodiments, the description is relatively simple, and the relevant parts can be understood by referring to the part of the method embodiment.

[0169] The block diagrams of the devices, apparatuses, equipment, systems involved in the present disclosure are only illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be as shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as “include”, “contain”, “have” and the like are open-ended words, mean “including but not limited to”, and can be used interchangeably. The words “or” and “and” used herein mean the word “and / or”, and can be used interchangeably unless the context clearly indicates otherwise. The word “such as” used herein means the phrase “such as but not limited to”, and can be used interchangeably.

[0170] The apparatus and methods of the present disclosure can be implemented in numerous ways. For example, the apparatus and methods of the present disclosure can be implemented using software, hardware, firmware, or any combination of software, hardware, and firmware. The order of any steps of the methods described above is merely exemplary and the steps of the methods of the present disclosure need not be performed in the order described unless otherwise specified. Furthermore, in some embodiments, the present disclosure can also be implemented as a program for use with a computer-based system, the program including a machine-readable instruction for implementing the methods according to the present disclosure. Thus, the present disclosure also covers record media storing the program for implementing the methods according to the present disclosure.

[0171] It is also noted that the apparatus, devices, and methods of the present disclosure can be embodied in a variety of other forms. The above description is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0172] The above description has been presented for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although various example aspects and embodiments have been discussed above, those of ordinary skill in the art will appreciate a variety of modifications, alternative constructions, adaptations, and equivalents.

Claims

1. A sensor accelerated lifetime modeling method based on multi-stress coupling, characterized in that, The method includes: Construct a multi-stress coupling accelerated life model that takes into account electromagnetic and humid-thermal coupling effects; Acquire accelerated life test data, including electric field, magnetic field, temperature, and temperature, collected during accelerated life testing of sensor samples; Based on the accelerated life test data, the model parameters of the multi-stress coupled accelerated life model are fitted and solved using the hierarchical coefficient method to determine the multi-stress coupled accelerated life model of the sensor to be predicted for accelerated life.

2. The method according to claim 1, characterized in that, A multi-stress coupling accelerated life model considering electromagnetic-hydrothermal coupling effects is constructed, wherein the expression of the multi-stress coupling accelerated life model is: In the formula, AF is the acceleration factor, which is the lifespan acceleration factor under laboratory conditions. E s E u —Accelerate electric field stress, utilize electric field stress; B s B u —Accelerate magnetic field stress, utilize magnetic field stress; T s ,T u —Accelerated temperature stress, service temperature stress; H s H u —Accelerate humidity stress, utilize humidity stress; α,β,γ,δ,η—acceleration exponents of each stress term and coupling term determined by the fitting; E a —Activation energy, in eV; k—Boltzmann constant, with a value of 8.617 × 100 -5 eV / K.

3. The method according to claim 2, characterized in that, Acquire accelerated life test data, including electric field, magnetic field, temperature, and humidity, collected during accelerated life testing of sensor samples. A multi-stress orthogonal test matrix is ​​constructed based on the stress terms involved in accelerated life testing, and the construction principle is as follows: Each stress item includes three levels: low, medium, and high. Each level of each stress item appears evenly, and any combination of two stress items completely covers the stress. Several sets of accelerated life tests were conducted on the sensor sample under stress combinations according to the multi-stress orthogonal test matrix, and the set test indicators were measured periodically. The test indicators include insulation resistance, sensor sample measurement error and surface corrosion level. When the measured test indicators meet the set test termination conditions, the sensor sample failure time and the stress combination group are recorded as the accelerated life test data of that group. The test termination conditions include at least one of the following: the insulation resistance decrease ratio is greater than the set ratio threshold, the measurement error is greater than the set error threshold, and visible corrosion occurs.

4. The method according to claim 3, characterized in that, Based on the accelerated life test data, the model parameters of the multi-stress coupled accelerated life model are fitted and solved using the stratified coefficient method to determine the multi-stress coupled accelerated life model of the sensor to be predicted for accelerated life, including: Accelerated life test data from groups where at least one of the electric field, magnetic field, and humidity is at a low level were selected. The multi-stress coupled accelerated life model was simplified to include only a temperature term, and the normalized activation energy E was obtained through univariate linear regression. a The initial value of / k; Fixed activation energy E a The initial value of / k is used to perform single-stress fitting on the electric field, humidity, and magnetic field terms, specifically: By sequentially selecting at least one low-level accelerated lifetime data from other stress terms besides the fitted stress term, the multi-stress coupled accelerated lifetime model is simplified to a form containing only the fitted stress term, and the initial values ​​of the electric field acceleration coefficient α, the humidity acceleration coefficient β, and the magnetic field acceleration coefficient γ are determined. Fixed activation energy E a / k, the initial values ​​of the electric field acceleration coefficient α, the humidity acceleration coefficient β, and the magnetic field acceleration coefficient γ, are used to fit the coupling stress of the electromagnetic coupling term and the temperature and humidity coupling term, specifically: By sequentially selecting accelerated life data with smaller product values ​​of stress terms other than the fitted coupled stress term, the multi-stress coupled accelerated life model is simplified to a form containing only the fitted coupled stress term, and the initial values ​​of the electromagnetic coupling coefficient δ and the temperature and humidity coupling coefficient η are determined. Based on activation energy E a The initial values ​​of / k, electric field acceleration coefficient α, humidity acceleration coefficient β, magnetic field acceleration coefficient γ, electromagnetic coupling coefficient δ, and temperature and humidity coupling coefficient η are used to globally fit the multi-stress coupled accelerated lifetime model, and the activation energy E is calculated. a The final values ​​of / k, electric field acceleration coefficient α, humidity acceleration coefficient β, magnetic field acceleration coefficient γ, electromagnetic coupling coefficient δ, and temperature and humidity coupling coefficient η are used to determine the multi-stress coupling accelerated lifetime model of the sensor to be predicted for accelerated lifetime.

5. A sensor accelerated lifetime modeling system based on multi-stress coupling, characterized in that, The system includes: The model building module is used to build multi-stress coupling accelerated life models that take into account electromagnetic-hygrothermal coupling effects. The data acquisition module is used to acquire accelerated life test data, including electric field, magnetic field, temperature and humidity, collected during accelerated life testing of sensor samples. The model determination module is used to fit and solve the model parameters of the multi-stress coupled accelerated life model based on the accelerated life test data using the hierarchical coefficient method, and determine the multi-stress coupled accelerated life model of the sensor to be predicted for accelerated life.

6. The system according to claim 5, characterized in that, The model building module constructs a multi-stress coupling accelerated life model considering electromagnetic-hygrothermal coupling effects, wherein the expression of the multi-stress coupling accelerated life model is: In the formula, AF is the acceleration factor, which is the lifespan acceleration factor under laboratory conditions. E s E u —Accelerate electric field stress, utilize electric field stress; B s B u —Accelerate magnetic field stress, utilize magnetic field stress; T s ,T u —Accelerated temperature stress, service temperature stress; H s H u —Accelerate humidity stress, utilize humidity stress; α,β,γ,δ,η—acceleration exponents of each stress term and coupling term determined by the fitting; E a —Activation energy, in eV; k—Boltzmann constant, with a value of 8.617 × 100 -5 eV / K.

7. The system according to claim 6, characterized in that, The data acquisition module acquires accelerated life test data, including electric field, magnetic field, temperature, and humidity, collected during accelerated life testing of the sensor sample. A multi-stress orthogonal test matrix is ​​constructed based on the stress terms involved in accelerated life testing, and the construction principle is as follows: Each stress item includes three levels: low, medium, and high. Each level of each stress item appears evenly, and any combination of two stress items completely covers the stress. Several sets of accelerated life tests were conducted on the sensor sample under stress combinations according to the multi-stress orthogonal test matrix, and the set test indicators were measured periodically. The test indicators include insulation resistance, sensor sample measurement error and surface corrosion level. When the measured test indicators meet the set test termination conditions, the sensor sample failure time and the stress combination group are recorded as the accelerated life test data of that group. The test termination conditions include at least one of the following: the insulation resistance decrease ratio is greater than the set ratio threshold, the measurement error is greater than the set error threshold, and visible corrosion occurs.

8. The system according to claim 7, characterized in that, The model solving module, based on the accelerated life test data, uses the hierarchical coefficient method to fit and solve the model parameters of the multi-stress coupled accelerated life model, determining the multi-stress coupled accelerated life model of the sensor to be predicted for accelerated life, including: Accelerated life test data from groups where at least one of the electric field, magnetic field, and humidity is at a low level were selected. The multi-stress coupled accelerated life model was simplified to include only a temperature term, and the normalized activation energy E was obtained through univariate linear regression. a The initial value of / k; Fixed activation energy E a The initial value of / k is used to perform single-stress fitting on the electric field, humidity, and magnetic field terms, specifically: By sequentially selecting at least one low-level accelerated lifetime data from other stress terms besides the fitted stress term, the multi-stress coupled accelerated lifetime model is simplified to a form containing only the fitted stress term, and the initial values ​​of the electric field acceleration coefficient α, the humidity acceleration coefficient β, and the magnetic field acceleration coefficient γ are determined. Fixed activation energy E a / k, the initial values ​​of the electric field acceleration coefficient α, the humidity acceleration coefficient β, and the magnetic field acceleration coefficient β, are used to fit the coupling stress of the electromagnetic coupling term and the temperature and humidity coupling term, specifically: By sequentially selecting accelerated life data with smaller product values ​​of stress terms other than the fitted coupled stress term, the multi-stress coupled accelerated life model is simplified to a form containing only the fitted coupled stress term, and the initial values ​​of the electromagnetic coupling coefficient δ and the temperature and humidity coupling coefficient η are determined. Based on activation energy E a The initial values ​​of / k, electric field acceleration coefficient α, humidity acceleration coefficient γ, magnetic field acceleration coefficient γ, electromagnetic coupling coefficient δ, and temperature and humidity coupling coefficient η are used to globally fit the multi-stress coupled accelerated lifetime model, and the activation energy E is calculated. a The final values ​​of / k, electric field acceleration coefficient α, humidity acceleration coefficient β, magnetic field acceleration coefficient γ, electromagnetic coupling coefficient δ, and temperature and humidity coupling coefficient η are used to determine the multi-stress coupling accelerated lifetime model of the sensor to be predicted for accelerated lifetime.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1-4.

10. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-4.

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