WO2014082516A1 - 元器件失效归零分析方法与系统 - Google Patents

元器件失效归零分析方法与系统 Download PDF

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Publication number
WO2014082516A1
WO2014082516A1 PCT/CN2013/086159 CN2013086159W WO2014082516A1 WO 2014082516 A1 WO2014082516 A1 WO 2014082516A1 CN 2013086159 W CN2013086159 W CN 2013086159W WO 2014082516 A1 WO2014082516 A1 WO 2014082516A1
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failure
component
fault
fault tree
node
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PCT/CN2013/086159
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English (en)
French (fr)
Inventor
何小琦
来萍
恩云飞
陈媛
王蕴辉
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工业和信息化部电子第五研究所
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Priority to US14/351,865 priority Critical patent/US20150168271A1/en
Publication of WO2014082516A1 publication Critical patent/WO2014082516A1/zh
Priority to US15/867,111 priority patent/US10191480B2/en

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0245—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a qualitative model, e.g. rule based; if-then decisions
    • G05B23/0248—Causal models, e.g. fault tree; digraphs; qualitative physics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00—Subject matter not provided for in other groups of this subclass
    • G01M99/008—Subject matter not provided for in other groups of this subclass by doing functionality tests
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0245—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a qualitative model, e.g. rule based; if-then decisions
    • G05B23/0251—Abstraction hierarchy, e.g. "complex systems", i.e. system is divided in subsystems, subsystems are monitored and results are combined to decide on status of whole system
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0267—Fault communication, e.g. human machine interface [HMI]
    • G05B23/0272—Presentation of monitored results, e.g. selection of status reports to be displayed; Filtering information to the user
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0706—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation the processing taking place on a specific hardware platform or in a specific software environment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/079—Root cause analysis, i.e. error or fault diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis

Definitions

  • the invention relates to the field of fault diagnosis technology, in particular to a component failure zero analysis method and system. Background technique
  • the purpose of the failure analysis of electronic components is to locate the failure and determine the failure mechanism through failure analysis, and propose improvement measures for the cause of failure, so as to achieve the zero return of the quality problem, that is, to achieve the failure of "accurate positioning, clear mechanism, effective measures" Return to zero requirements.
  • the existing component failure analysis techniques are mostly failure phenomenon observation techniques, but lack of failure information analysis techniques, and the given zero return conclusions are related to the analysis experience.
  • Fault tree analysis is a logical reasoning method for system reliability and security analysis. It analyzes and determines the logical relationship by various possible factors leading to the fault, and finds the cause of the system fault. The method is already in aviation and electronics. Systems and other fields are widely used. In order to meet the requirements of zeroing, from the beginning of this century, electronic components gradually draw on the electronic whole machine fault tree analysis method, and use fault tree analysis to analyze the components to zero-return, but the problem that needs to be solved now is how to establish component faults. tree.
  • Fault dictionary method is an effective method to realize fast fault location of complex electronic whole machine. The fault dictionary must reflect the relationship between the fault cause of the measured object and the measurable external parameter characteristics. To establish this relationship, it is commonly used. Fault tree event information to build this relationship.
  • the fault diagnosis and zeroing analysis using the fault tree and fault dictionary method have the above advantages. Therefore, the fault tree and fault dictionary method are generally used for fault diagnosis and positioning of the electronic whole machine, but for electronic components, due to the failure mode of the electronic components The complexity and complexity of the failure mechanism make the failure diagnosis and zeroing analysis of the general fault tree and fault dictionary method unable to accurately locate and diagnose the faults of electronic components. Summary of the invention
  • a component failure zero analysis method including steps:
  • the common physical characteristics of the component failure physicality include: a failure object, a failure mode, a failure site, a failure mechanism, a mechanism factor, and an influencing factor.
  • the step of converting the failed physical fault tree into a fault location fault tree comprises the steps of: determining an observable node between the failure mode and the failure mechanism, and employing an observable node event for the unmeasurable failure physical event.
  • the characteristic parameter is an observable parameter, and the observable parameter specifically includes: electrical property, thermal property, mechanical property, apparent property, gas Tightness and environmental adaptability;
  • Determining a failure event of the component by a node failure event characterizing the node failure event with the observable parameter; establishing a top event with the failure mode, an intermediate event with the observable node, and the failure
  • the mechanism causes the component failure of the bottom event to locate the fault tree.
  • the step of establishing a component fault dictionary corresponding to the failure mechanism cause and the failure feature according to the failure locating fault tree comprises the following steps:
  • the step of performing a zero-failure analysis on the component according to the failed physical fault tree and the component fault dictionary specifically includes:
  • the mechanism factors and influencing factors of the corresponding failure mechanism are searched in the failure physical fault tree, and measures against the failure mechanism are proposed.
  • a component failure zeroing analysis system comprising:
  • a failed physical fault tree building module configured to establish a failed physical fault tree of the component according to a common characteristic of the component failure physicality
  • a failure location fault tree establishing module configured to convert a failed physical event into an observable node event according to the failed physical fault tree, so that the failed physical fault tree is converted into a failure location fault tree;
  • the fault dictionary establishing module is configured to: according to the fault location fault tree, establish a component fault dictionary corresponding to the failure mechanism cause and the failure feature;
  • the fail-to-zero analysis module is configured to perform a zero-return analysis on the meta-device according to the failed physical fault tree and the component fault dictionary.
  • the common physical characteristics of the component failure physicality include: a failure object, a failure mode, a failure site, a failure mechanism, a mechanism factor, and an influencing factor.
  • the failure location fault tree establishing module specifically includes:
  • Event conversion unit used to determine an observable node between a failure mode and a failure mechanism, and to represent an unmeasurable failure physical event by an observable node event;
  • the characteristic parameter selection unit is configured to: according to the structural and performance characteristics of the component, select and characterize characteristic parameters of each node, wherein the characteristic parameter is an observable parameter, and the observable parameter specifically includes: electrical performance, thermal performance, mechanical Performance, apparent properties, air tightness and environmental adaptability;
  • a parameter characterization unit configured to represent a failure event of the component by a node failure event, and use the observable parameter to identify the node failure event;
  • the fault tree establishing unit is configured to establish a component failure locating fault tree with the failure mode as a top event, the observable node as an intermediate event, and the failure mechanism as a bottom event.
  • the fault dictionary establishing module specifically includes: a failure mode set determining unit, configured to determine, according to the positioning fault tree, a failure mode set of the component, where the failure mode set includes a plurality of failure mode subsets;
  • An observable node determining unit configured to determine, according to the positioning fault tree, an observable node of the failure mode subset in a failure mode;
  • the feature value obtaining unit is configured to: according to the positioning fault tree, obtain an observation parameter from the observable node, and judge the observed parameter, and obtain an observable node characteristic value of the failure mode;
  • Feature vector obtaining unit configured to determine feature vectors of various failure modes of the component according to the observable node feature value
  • a failure mechanism determining unit configured to determine a cause of failure mechanism of the component according to the positioning fault tree; a fault dictionary forming unit: configured to establish the failure according to the failure mechanism cause and the observable node feature value The component fault dictionary corresponding to the node event failure feature.
  • the fail-to-zero analysis module specifically includes:
  • An observation unit configured to observe the component according to a node parameter of the component fault dictionary, and obtain a feature value of the observation vector;
  • Aligning unit configured to compare the feature value of the observation vector with the component fault dictionary to determine a cause of failure mechanism of the component
  • the searching unit is configured to find a mechanism factor and an influencing factor of the corresponding failure mechanism in the failed physical fault tree according to the failure mechanism, and propose measures against the failure mechanism.
  • the component failure zeroing analysis method and system of the invention can locate the component fault to the internal physical structure through the fault location fault tree, and give a clear failure path, and quickly determine the component failure mode corresponding through the failure feature vector analysis of the fault dictionary.
  • the failure mechanism, the mechanism factor and influencing factors of the relevant failure mechanism are determined by the failure physical fault tree, and the targeted failure control measures are proposed to realize the rapid and accurate positioning and diagnosis of electronic component failure.
  • FIG. 1 is a schematic flow chart of one embodiment of a component failure zero analysis method according to the present invention.
  • FIG. 2 is a detailed flow chart of one embodiment of a component failure zero analysis method according to the present invention.
  • FIG. 3 is a schematic structural view of one embodiment of a component failure return-to-zero analysis system of the present invention.
  • FIG. 4 is a detailed structural diagram of one embodiment of a component failure return-to-zero analysis system of the present invention. detailed description
  • the basic principle of the component zero-return analysis method and system of the present invention is: due to the similarity of each type of component structure and process, the physical failure tree of the component can be established, and the physical event of the failed physical fault tree can be established. It can be described by observable event transitions, which can be characterized by electrical properties, or thermal properties, or mechanical properties, or surface properties, or airtightness, so that the relationship between single-mechanism causes and node failure characteristics is formed.
  • the fault dictionary if the acquired failure feature vector is the same as a row vector of the fault dictionary, determines the mechanism cause of the failure mode, and then proposes improvement measures for the mechanism factor and the influencing factors to achieve "accurate positioning, clear mechanism, and effective measures". Zero analysis.
  • a component failure zero analysis method includes the following steps:
  • S100 Establish a failed physical fault tree of the component according to a common characteristic of the physical failure of the component.
  • the failure physical fault tree of such components can be established according to the common characteristics of component failure physics.
  • the common characteristics of the components are fault object, failure mode, failure location, failure mechanism, mechanism factor and influencing factors, so that the six common features can completely cover the fault characteristics and failure causes of the component.
  • the component failure physical fault tree is established in six levels: fault object, failure mode, failure location, failure mechanism, mechanism factor and influencing factors.
  • the correlation between the upper and lower events between the fault object, the failure mode, the failure part and the failure mechanism in the fault tree is an OR logic gate, and its upper and lower levels
  • the OR gate structure function of the event ⁇ ⁇ " ⁇ is the state of the upper event, X is the state of the lower event; if the event of the lower event ⁇ occurs, the value is 1, and if it does not occur, the value is o, describing the state of the event of the superior event ⁇
  • the structure function indicates that as long as there is a subordinate event, the superior event will occur. .
  • the failure mechanism, the mechanism factor, and the influence of the upper and lower event correlations between the primes are "AND" logic gates or "or” logic gates, where the AND gate structure function ⁇ ( )_ ⁇ ', if If the event xi occurs, the value is 1, if it does not occur, the value is o, and the function describing the state of the upper event ⁇ is 15 ⁇ 1 ⁇ . The value is also 1 when it occurs, and 0 when it does not occur. This function indicates that only the lower level all events occur, and the superior events only occur.
  • Fault Tree Second to Sixth Layer Each physical layer event can be decomposed into 1-3 events, forming a variety of component fault tree events for six physical layer n-level events. It is easy to understand that n is a minimum of 6.
  • S200 Convert the failed physical event into an observable node event according to the failed physical fault tree, so that the failed physical fault tree is converted into a failed positioning fault tree.
  • step S200 specifically includes:
  • Step S220 determining an observable node between the failure mode and the failure mechanism, and expressing the unmeasurable failure physical event by using an observable node event;
  • Step S240 Select, according to the structure and performance characteristics of the component, select characteristic parameters of each node, where the feature parameter is an observable parameter, and the observable parameter specifically includes: electrical performance, thermal performance, mechanical performance, apparent Characteristics, air tightness and environmental adaptability;
  • Step S260 The node failure event represents a failure event of the component, and the node failure event is characterized by the observable parameter;
  • Step S280 Establish a component failure location fault tree with the failure mode as a top event, the observable node as an intermediate event, and the failure mechanism as a bottom event.
  • step S300 specifically includes:
  • Step S310 Determine, according to the positioning fault tree, a failure mode set of the component, where the failure mode set includes multiple failure mode subsets;
  • Step S320 determining, according to the positioning fault tree, the observable node of the failure mode subset in the failure mode;
  • Step S330 obtaining, according to the positioning fault tree, the observation parameter by the observable node, the criterion Observing the observed parameters, and obtaining the eigenvalues of the observable nodes of the failure mode;
  • Step S340 Determine, according to the eigenvalue of the observable node, a feature vector of various failure modes of the component;
  • Step S350 Determine, according to the locating fault tree, a cause of failure mechanism of the component;
  • Step S360 Establish a component fault dictionary corresponding to the failure mechanism cause and the node event failure feature according to the failure mechanism cause and the observable node feature value.
  • step S400 Perform a failure zeroing analysis on the component according to the failed physical fault tree and the component fault dictionary.
  • step S400 specifically includes:
  • Step S420 Observing the component according to a node parameter of the fault dictionary, and obtaining a feature value of the observation vector;
  • Step S440 Aligning the feature value of the observation vector with the fault dictionary to determine a cause of failure mechanism of the component
  • Step S460 Find a mechanism factor and an influencing factor of the corresponding failure mechanism in the failed physical fault tree according to the failure mechanism, and propose measures against the failure mechanism.
  • the component fault can be located to the internal physical structure through the fault location fault tree, and a clear failure path is given, and the failure characteristic vector analysis of the fault dictionary is used to quickly determine the corresponding component failure mode.
  • the failure mechanism, the mechanism factor and influencing factors of the relevant failure mechanism are determined by the failure physical fault tree, and the targeted failure control measures are proposed to realize the rapid and accurate positioning and diagnosis of electronic component failure.
  • Step one establish a hybrid integrated circuit failure physical fault tree
  • the failure physical fault tree of the failure mode is established.
  • the hybrid integrated circuit failure physical fault tree is established in six levels: fault object, failure mode, failure location, failure mechanism, mechanism factor and influencing factors.
  • the first, second, third and the The four layers of events are OR-gate logical relationships, and the fourth, fifth, and sixth-level events are OR gates and AND gates.
  • the failed physical fault tree has six failed physical layers and a total of eight levels of event fault trees. .
  • Step 2 Convert the failed physical fault tree into a fault location fault tree
  • the failed physical fault tree established in step 1 it is converted into a fault location fault tree with a failure mechanism as the bottom event.
  • the non-measureable component welding/viscosity degradation, wire bonding point degradation and other non-measureable failure physical events are converted.
  • One or more node events that are measurable and observable, such as high thermal resistance of components, poor wire bonding strength, and apparent MC, are used as intermediate events in the failure location tree.
  • the converted hybrid integrated circuit electrical parameter drift failure locating fault tree is a cause of 15 failure mechanisms, a total of 8 things The fault location tree of the fault.
  • Step 3 establishing a hybrid integrated circuit electrical parameter drift fault dictionary
  • a component fault dictionary corresponding to the failure feature of the node event is established.
  • the characteristic parameters of the node that characterize the HIC parameter drift caused by internal component failure are: component parametric drift, component microcracking, ESD damage and surface contamination leakage; etc.
  • the characteristic parameters of the node that characterize the assembly failure cause HIC parameter drift are: Soldering/heat-resistance thermal resistance, bonding interface IMC and bonding point corrosion, etc.;
  • the characteristic parameters of the node that characterize the insulation degradation leading to HIC drift are: pin/case insulation resistance and insulation resistance between solder joints.
  • the range of values of sp refers to the qualification criteria of the hybrid integrated circuit and component related standards, that is, the range of values observed by each node.
  • a fault code dictionary of the hybrid integrated circuit electrical parameter drift failure mode is established by the correspondence between the failure characteristics of each observation node and the cause of the failure mechanism. See Table 1: HIC "Electrical Parameter Drift” Failure Mode Fault Dictionary.
  • Step 4 Zeroing the failure of the electric parameter drift according to the fault tree and the fault dictionary According to the fault dictionary established in step 3 and the failed physical fault tree established in step 1, the zero-return analysis of the hybrid integrated circuit electrical parameter drift is performed.
  • the component has a corresponding single mechanism ( ⁇ ) cause failure. After determining the cause of the failure mechanism, find the mechanism factors and influencing factors of the corresponding failure mechanism in the failed physical fault tree, and propose control measures for the failure mechanism.
  • the output voltage is out of tolerance.
  • the fault tree and the faulty dictionary method are used to zero the analysis, find the cause of the failure mechanism, determine the failure path, and propose the failure control measures.
  • the failure control measure is to select a chip with a higher junction temperature upper limit T Mj and use it for thermal derating design.
  • a component failure zero analysis system includes:
  • the failed physical fault tree establishing module 100 is configured to establish a failed physical fault tree of the component according to a common characteristic of the component failure physicality
  • the failure locating fault tree establishing module 200 is configured to convert the failed physical event into an observable node event according to the failed physical fault tree, so that the failed physical fault tree is converted into a failure locating fault tree;
  • the fault dictionary establishing module 300 is configured to: according to the fault location fault tree, establish a component fault dictionary corresponding to a failure mechanism cause and a failure feature;
  • the fail-to-zero analysis module 400 is configured to perform a zero-failure analysis on the component according to the failed physical fault tree and the component fault dictionary.
  • the component failure zeroing analysis system of the invention can locate the component fault to the internal physical structure through the fault location fault tree, and give a clear failure path, and quickly determine the failure corresponding to the component failure mode by the failure feature vector analysis of the fault dictionary.
  • Mechanism, the mechanism factor and influencing factors of the relevant failure mechanism are determined by the failure physical fault tree, and the targeted failure control measures are proposed to realize the rapid and accurate positioning and diagnosis of electronic component failure.
  • the common physical characteristics of the component failure physicality include: a failure object, a failure mode, a failure location, a failure mechanism, a mechanism factor, and an influencing factor.
  • the failure location fault tree establishing module 200 specifically includes:
  • the event conversion unit 220 is configured to determine an observable node between the failure mode and the failure mechanism, and represent the unmeasurable failure physical event by using an observable node event;
  • the feature parameter selection unit 240 is configured to select, according to the structure and performance characteristics of the component, a feature parameter that characterizes each node, where the feature parameter is an observable parameter, and the observable parameter specifically includes: electrical performance, thermal performance, Mechanical properties, apparent properties and air tightness;
  • Parameter characterization unit 260 configured to represent a failure event of the component by a node failure event, and characterizing the node failure event with the observable parameter;
  • the fault tree establishing unit 280 is configured to establish a component failure locating fault tree with the failure mode as a top event, the observable node as an intermediate event, and the failure mechanism as a bottom event.
  • the fault dictionary establishing module 300 specifically includes:
  • the failure mode set determining unit 310 is configured to determine, according to the positioning fault tree, a failure mode set of the component, where the failure mode set includes a plurality of failure mode subsets;
  • Observable node determining unit 320 configured to determine, according to the positioning fault tree, an observable node of the failure mode subset in a failure mode;
  • the feature value obtaining unit 330 is configured to: according to the positioning fault tree, obtain an observation parameter from the observable node, and determine the observed parameter to obtain an observable node feature value of the failure mode;
  • Feature vector obtaining unit 340 configured to determine a feature vector of various failure modes of the component according to the observable node feature value;
  • the failure mechanism determining unit 350 is configured to determine a cause of the failure mechanism of the component according to the positioning fault tree, and the fault dictionary forming unit 360 is configured to establish a location according to the failure mechanism cause and the observable node feature value.
  • the fail-to-zero analysis module 400 specifically includes:
  • the observing unit 420 is configured to perform observation on the component according to a node parameter of the fault dictionary to obtain a feature value of the observation vector;
  • Aligning unit 440 configured to compare a feature value of the observation vector with the fault dictionary to determine a cause of failure mechanism of the component;
  • the searching unit 460 is configured to find a mechanism factor and an influencing factor of the corresponding failure mechanism in the failed physical fault tree according to the failure mechanism, and propose measures against the failure mechanism.
  • the component failure zeroing analysis method and system of the present invention can locate the component fault to the internal physical structure through the fault location fault tree, and give a clear failure path, which is quickly determined by the failure feature vector analysis of the fault dictionary.
  • the failure mechanism corresponding to the failure mode of the component determines the mechanism factor and influencing factors of the relevant failure mechanism through the failure physical fault tree, and proposes targeted failure control measures to truly achieve the "accurate positioning", "clear mechanism” and "effective measures”. " .

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Abstract

提供一种元器件失效归零分析方法与系统，所述方法建立元器件失效物理故障树，将失效物理故障树转换为失效定位故障树，建立机理原因与失效特征相对应的元器件故障字典，根据故障树和故障字典进行元器件失效归零分析。所述元器件失效归零分析方法与系统，能够通过失效定位故障树将元器件故障定位到内部物理结构，给出清晰的失效路径，通过故障字典的失效特征向量分析快速确定元器件失效模式对应的失效机理，通过失效物理故障树确定相关失效机理的机理因子和影响因素，提出针对性的失效控制措施，实现对电子元器件故障的快速、准确定位和诊断。

Description

元器件失效归零分析方法与系统 技术领域
本发明涉及故障诊断技术领域， 特别是涉及元器件失效归零分析方法与系统。 背景技术
电子元器件失效归零分析的目的是通过失效分析进行失效定位和确定失效机理， 提出针 对失效原因的改进措施， 进而实现质量问题归零， 即达到失效 "定位准确、 机理清楚、 措施 有效" 的归零要求。 为实现元器件失效归零， 人们采用了各种技术手段。 但现有的元器件失 效分析技术， 多为失效现象观测技术， 而缺少失效信息分析技术， 给出的归零结论与分析经 验的多少有关。 因此， 如何系统应用失效观测结果及失效信息进行归零分析， 做到 "定位准 确"给出元器件内部的失效部位和失效路径， "机理清楚"给出导致失效的机理原因， "措 施有效"提出针对机理原因的有效改进措施， 这是失效归零的关键所在。
故障树分析是一种用于系统可靠性、 安全性分析的逻辑推理方法， 它通过对导致故障的 各种可能因素进行分析和确定逻辑关系， 找出系统故障原因， 该方法已在航空、 电子系统等 领域得到广泛应用。 为适应归零要求， 从本世纪初开始， 电子元器件逐步借鉴电子整机故障 树分析方法， 应用故障树分析对元器件进行失效归零分析， 但目前需要解决的问题是如何建 立元器件故障树。 故障字典法是实现复杂电子整机故障快速定位的一种有效方法， 所建立的 故障字典必须能反映被测对象的故障原因与可测量外部参数特征之间的关系， 为建立这种关 系， 常用故障树事件信息来构建这种关系。
采用故障树及故障字典法的失效诊断和归零分析有上述优点， 所以对于电子整机一般会 采用故障树及故障字典法进行故障诊断和定位， 但对于电子元器件， 由于电子元器件失效模 式的多样性和失效机理的复杂性， 使得一般的故障树及故障字典法的失效诊断和归零分析无 法准确对电子元器件进行故障定位和诊断。 发明内容
基于此， 有必要针对一般的故障树及故障字典法的失效诊断和归零分析无法准确对电子 元器件进行故障诊断和定位问题， 提供一种元器件失效归零分析方法与系统， 实现对电子元 器件故障的快速、 准确定位和诊断。
一种元器件失效归零分析方法， 包括步骤：
根据所述元器件失效物理的共性特点， 建立所述元器件的失效物理故障树；
根据所述失效物理故障树将失效物理事件转为可观测的节点事件， 以使所述失效物理故 障树转换为失效定位故障树；
根据所述失效定位故障树， 建立失效机理原因与失效特征相对应的元器件故障字典； 根据所述失效物理故障树与所述元器件故障字典， 对所述元器件进行失效归零分析。 在其中一个实施例中， 所述元器件失效物理的共性特点包括： 故障对象、 失效模式、 失 效部位、 失效机理、 机理因子和影响因素。
在其中一个实施例中，所述步骤将失效物理故障树转换为失效定位故障树具体包括步骤: 确定失效模式与失效机理之间可观测节点， 将不可测量的失效物理事件采用可观测的节 点事件表示；
根据所述元器件的结构和性能特点， 选择表征各节点的特征参数， 所述特征参数为可观 测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性能、 表观特性、 气密性和环境 适应性；
将节点失效事件表示所述元器件的失效事件，用所述可观测参数表征所述节点失效事件; 建立以所述失效模式为顶事件、 以所述可观测节点为中间事件和以所述失效机理原因为 底事件的元器件失效定位故障树。
在其中一个实施例中， 所述步骤根据所述失效定位故障树， 建立失效机理原因与失效特 征相对应的元器件故障字典具体包括步骤：
根据所述定位故障树， 确定所述元器件的失效模式集， 所述失效模式集包括多个失效模 式子集；
根据所述定位故障树， 确定所述失效模式子集在失效模式下的可观测节点；
根据所述定位故障树， 由所述可观测节点得出观测参数， 判据所述观测参数， 得出失效 模式的可观测节点特征值；
根据所述可观测节点特征值， 确定所述元器件各种失效模式的特征向量；
根据所述定位故障树， 确定所述元器件的失效机理原因； 根据所述失效机理原因与所述 可观测节点特征值，建立所述失效机理原因与所述节点事件失效特征相应的元器件故障字典。 在其中一个实施例中， 所述步骤根据所述失效物理故障树与所述元器件故障字典， 对所 述元器件进行失效归零分析具体包括：
根据所述元器件故障字典的节点参数， 对所述元器件进行观测， 得到观测向量的特征值; 比对所述观测向量的特征值与所述元器件故障字典， 确定所述元器件的失效机理原因； 根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机理的机理因子和影响 因素， 提出针对所述失效机理的措施。
一种元器件失效归零分析系统， 包括：
失效物理故障树建立模块： 用于根据所述元器件失效物理的共性特点， 建立所述元器件 的失效物理故障树；
失效定位故障树建立模块： 用于根据所述失效物理故障树将失效物理事件转为可观测的 节点事件， 以使所述失效物理故障树转换为失效定位故障树；
故障字典建立模块： 用于根据所述失效定位故障树， 建立失效机理原因与失效特征相对 应的元器件故障字典；
失效归零分析模块： 用于根据所述失效物理故障树与所述元器件故障字典， 对所述元器 件进行失效归零分析。
在其中一个实施例中， 所述元器件失效物理的共性特点包括： 故障对象、 失效模式、 失 效部位、 失效机理、 机理因子和影响因素。
在其中一个实施例中， 所述失效定位故障树建立模块具体包括：
事件转换单元： 用于确定失效模式与失效机理之间可观测节点， 将不可测量的失效物理 事件采用可观测的节点事件表示；
特征参数选取单元： 用于根据所述元器件的结构和性能特点， 选择表征各节点的特征参 数， 所述特征参数为可观测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性能、 表观特性、 气密性和环境适应性；
参数表征单元： 用于将节点失效事件表示所述元器件的失效事件， 用所述可观测参数表 征所述节点失效事件；
故障树建立单元： 用于建立以所述失效模式为顶事件、 以所述可观测节点为中间事件和 以所述失效机理原因为底事件的元器件失效定位故障树。
在其中一个实施例中， 所述故障字典建立模块具体包括： 失效模式集确定单元： 用于根据所述定位故障树， 确定所述元器件的失效模式集， 所述 失效模式集包括多个失效模式子集；
可观测节点确定单元： 用于根据所述定位故障树， 确定所述失效模式子集在失效模式下 的可观测节点；
特征值获取单元： 用于根据所述定位故障树， 由所述可观测节点得出观测参数， 判据所 述观测参数， 得出失效模式的可观测节点特征值；
特征向量获取单元： 用于根据所述可观测节点特征值， 确定所述元器件各种失效模式的 特征向量；
失效机理确定单元： 用于根据所述定位故障树， 确定所述元器件的失效机理原因； 故障字典形成单元： 用于根据所述失效机理原因与所述可观测节点特征值， 建立所述失 效机理原因与所述节点事件失效特征相应的元器件故障字典。
在其中一个实施例中， 所述失效归零分析模块具体包括：
观测单元： 用于根据所述元器件故障字典的节点参数， 对所述元器件进行观测， 得到观 测向量的特征值；
比对单元： 用于比对所述观测向量的特征值与所述元器件故障字典， 确定所述元器件的 失效机理原因；
查找单元： 用于根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机理的 机理因子和影响因素， 提出针对所述失效机理的措施。
本发明元器件失效归零分析方法与系统， 能够通过失效定位故障树将元器件故障定位到 内部物理结构， 给出清晰的失效路径， 通过故障字典的失效特征向量分析快速确定元器件失 效模式对应的失效机理， 通过失效物理故障树确定相关失效机理的机理因子和影响因素， 提 出针对性的失效控制措施， 实现对电子元器件故障的快速、 准确定位和诊断。 附图说明
图 1为本发明元器件失效归零分析方法其中一个实施例的流程示意图；
图 2为本发明元器件失效归零分析方法其中一个实施例的详细流程示意图；
图 3为本发明元器件失效归零分析系统其中一个实施例的结构示意图；
图 4为本发明元器件失效归零分析系统其中一个实施例的详细结构示意图。 具体实施方式
为了使本发明的目的、 技术方案及优点更加清楚明白， 以下根据附图及实施例， 对本发 明进行进一步详细说明。 应当理解， 此处所描述的具体实施仅仅用以解释本发明， 并不限定 本发明。
本发明元器件失效归零分析方法与系统的基本原理是： 由于每一类元器件结构和工艺的 相似性， 故可以建立该类元器件的失效物理故障树， 而失效物理故障树的物理事件可以通过 可观测事件转换进行描述， 这些可观测事件可选择电性能、 或热性能、 或机械性能、 或表面 特性、 或气密性等物理参数表征， 故形成单机理原因与节点失效特征对应关系的故障字典， 若采集的失效特征向量与故障字典的某行向量相同， 则确定了失效模式的机理原因， 进而针 对机理因子和影响因素提出改进措施， 实现 "定位准确、机理清楚、措施有效" 的归零分析。
如图 1、 图 2所示， 一种元器件失效归零分析方法， 包括步骤：
S100: 根据所述元器件失效物理的共性特点， 建立所述元器件的失效物理故障树。
在这里由于每一类元器件结构和工艺的相似性， 故可以根据元器件失效物理的共性特点 建立该类元器件的失效物理故障树。
在其中一个实施例中， 元器件的共性特点为故障对象、 失效模式、 失效部位、 失效机理、 机理因子和影响因素， 这样 6个共性特点能完整全面覆盖元器件的故障特征和失效原因， 在 整理好了 6个共性特点之后就分别以故障对象、 失效模式、 失效部位、 失效机理、 机理因子 和影响因素六个层次建立元器件失效物理故障树。
在这个失效物理故障树中， 根据元器件失效物理的关联性， 该故障树中故障对象、 失效 模式、 失效部 和失效机理之间的上下级事件关联性为 "或"逻辑门， 其上下级事件的或门 结构函数^^ ^""， Φ为上级事件状态， X为下级事件状态； 若下级事件^发生则取值为 1， 不发生则取值为 o， 描述上级事件发生状态 Φ的结构函数可写为 Φ( )=1_Ρ(1_ )，取值亦为发 生时取值为 1， 不发生时取值为 0， 该结构函数表示只要有一个下级事件发生， 上级事件就会 发生。 该故障树中失效机理、 机理因子、 影响因„素之间的上下级事件关联性， 为 "与"逻辑 门或者 "或"逻辑门， 其中与门结构函数 Φ( )_ Χ'， 若 级事件 xi发生则取值为 1、 不发生 则取值为 o， 描述上级事件发生状态 Φ的函数为15^^1^ 取值亦为发生时取值为 1， 不发 生时取值为 0， 该函数表示只有下级全部事件发生， 上级事件才发生。 故障树第二〜第六层 的每一物理层事件可在分解成 1-3级事件， 形成六个物理层 n级事件的各类元器件故障树事 件， 很容易理解这里 n最小为 6。
S200 : 根据所述失效物理故障树将失效物理事件转为可观测的节点事件， 以使所述失效 物理故障树转换为失效定位故障树。
在其中一个实施例中步骤 S200具体包括：
步骤 S220 : 确定失效模式与失效机理之间可观测节点， 将不可测量的失效物理事件采用 可观测的节点事件表示；
步骤 S240 : 根据所述元器件的结构和性能特点， 选择表征各节点的特征参数， 所述特征 参数为可观测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性能、 表观特性、 气 密性和环境适应性；
步骤 S260 : 将节点失效事件表示所述元器件的失效事件， 用所述可观测参数表征所述节 点失效事件；
步骤 S280 : 建立以所述失效模式为顶事件、 以所述可观测节点为中间事件和以所述失效 机理原因为底事件的元器件失效定位故障树。
S300 : 根据所述失效定位故障树， 建立失效机理原因与失效特征相对应的元器件故障字 曲.
在其中一个实施例中步骤 S300具体包括：
步骤 S310 : 根据所述定位故障树， 确定所述元器件的失效模式集， 所述失效模式集包括 多个失效模式子集；
步骤 S320 : 根据所述定位故障树， 确定所述失效模式子集在失效模式下的可观测节点； 步骤 S330 : 根据所述定位故障树， 由所述可观测节点得出观测参数， 判据所述观测参数， 得出失效模式的可观测节点特征值；
步骤 S340 : 根据所述可观测节点特征值， 确定所述元器件各种失效模式的特征向量； 步骤 S350 : 根据所述定位故障树， 确定所述元器件的失效机理原因；
步骤 S360 : 根据所述失效机理原因与所述可观测节点特征值， 建立所述失效机理原因与 所述节点事件失效特征相应的元器件故障字典。
S400 : 根据所述失效物理故障树与所述元器件故障字典， 对所述元器件进行失效归零分 析。 在其中一个实施例中步骤 S400具体包括：
步骤 S420: 根据所述故障字典的节点参数， 对所述元器件进行观测， 得到观测向量的特 征值；
步骤 S440: 比对所述观测向量的特征值与所述故障字典， 确定所述元器件的失效机理原 因；
步骤 S460: 根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机理的机理 因子和影响因素， 提出针对所述失效机理的措施。
实施本发明元器件失效归零分析方法， 能够通过失效定位故障树将元器件故障定位到内 部物理结构， 给出清晰的失效路径， 通过故障字典的失效特征向量分析快速确定元器件失效 模式对应的失效机理， 通过失效物理故障树确定相关失效机理的机理因子和影响因素， 提出 针对性的失效控制措施， 实现了对电子元器件故障的快速、 准确定位和诊断。
为了更进一步详细解释本发明元器件失效归零分析方法的技术方案， 下面将以混合集成 电路 "电参漂移" 的归零分析这个具体实施例为例， 详细介绍本发明元器件失效归零分析方 法的技术方案以及带来的有益效果。
步骤一， 建立混合集成电路失效物理故障树
根据混合集成电路 "电参漂移"失效物理的特点， 建立该失效模式的失效物理故障树。 分别以故障对象、 失效模式、 失效部位、 失效机理、 机理因子、 影响因素六个层次建立 混合集成电路失效物理故障树， 在这个失效物理故障树中， 第一、 第二、 第三层和第四层事 件之间为或门逻辑关系， 第四、 第五、 第六层事件之间为或门和与门逻辑关系， 失效物理故 障树有六个失效物理层、 共计 8级事件的故障树。
步骤二， 将失效物理故障树转换为失效定位故障树
根据步骤一建立的失效物理故障树，将其转换为以失效机理为底事件的失效定位故障树。 首先， 针对建立的混合集成电路失效物理故障树， 在故障对象顶事件与失效机理事件之 间， 把不可测量的元器件焊 /粘退化、 引线键合点退化等不可直接测量的失效物理事件， 转换 为采用元器件热阻过高、 引线键合强度不达标、 界面明显 MC等可测量和可观察的一个或多 个节点事件， 作为失效定位故障树的中间事件。
对各节点失效事件， 选择结温 Tj、 键合强度、 界面 IMC、 水汽含量等特征参数表征。 转换后的混合集成电路电参漂移失效定位故障树， 为含有 15个失效机理原因、共 8级事 件的失效定位故障树。
步骤三， 建立混合集成电路电参漂移故障字典
根据步骤二建立的失效定位故障树， 建立单一失效机理原因与节点事件失效特征相对应 的元器件故障字典。
由失效定位故障树， 确定电参漂移失效模式 下面 23个可观测节点及其特征参数。其中 表征内部元器件失效导致 HIC参漂的节点特征参数有： 元器件参漂、 元器件微裂、 ESD损伤 和表面沾污漏电等； 表征组装失效导致 HIC参漂的节点特征参数有： 元器件焊 /粘热阻热阻、 键合界面 IMC和键合点腐蚀等； 表征绝缘性退化导致 HIC参漂的节点特征参数有： 引脚 /外壳 绝缘电阻和焊点之间绝缘电阻等。 节点失效特征参数为 = {Χ , Χ^, -,Χ,^}»
由节点失效特征参数 = {Xu， ,2，…， X 23}，按其取值范围由下式求出相应的特征值 F^, 组成特征向量 Fu= {F^, F,,, -,^,,3}. 其中， sp 的取值范围参照混合集成电路、 元器件相 关标准的合格判据， 即各节点观测的取值范围。
1,J I 0 Xyesp
混合集成电路电参漂移有 15个失效机理原因， 机理原因集 Μ^= {Μ^, Μΐ!2, -,Μ,15}0 根 据电参漂移失效定位故障树的节点事件间逻辑关系， 列表给出各观测节点失效特征与失效机 理原因的对应关系式。
由各观测节点失效特征与失效机理原因的对应关系式， 建立混合集成电路电参漂移失效 模式的故障代码字典。 见表 1: HIC "电参漂移"失效模式故障字典。
Figure imgf000010_0001
表 1
步骤四， 根据故障树和故障字典对电参漂移失效进行归零分析 根据步骤三建立的故障字典、 步骤一建立的失效物理故障树， 对混合集成电路电参漂移 进行失效归零分析。
按照故障字典的节点参数， 对混合集成电路进行观测， 把实测的观测向量 Fu = { F^ F^—J^ }特征值与故障字典比较， 若与故障字典的某行向量相同， 则可确定元器件 发生了相应单一机理 （Μ^ ) 原因失效。 确定失效机理原因后， 在失效物理故障树中查找相应 失效机理 的机理因子、 影响因素， 针对该失效机理提出控制措施。
应用上述得到混合集成电路电参漂移故障树和故障字典进行一次归零分析。
某线性电源混合集成电路在高温稳态寿命试验后， 出现输出电压超差， 采用故障树和故 障字典法对其分析归零， 查找失效的机理原因、 确定失效路径、 提出失效控制措施。
对电路分析和观测后， 把实测的观测向量 Fu= { F^, F^, -, ^,^ }特征值与电参漂移故 障字典表 1比较，其中结合某芯片特征参数的向量结果与第一行机理 Μ1Λ向量相同，认为失效 机理 Μ1Λ : 器件退化或超限使用引起电参漂移， 是导致电路输出电压超差原因。 由失效物理故 障树， 结合试验的高温和该芯片的最高允许结温上限 TMj， 确认电源电路输出电压超差是由于 该芯片电参漂移所致， 漂移的原因是芯片结温超限使用； 因此， 失效控制措施是选择具有结 温上限 TMj更高等级的芯片， 并进行热降额设计使用。
如图 3所示， 一种元器件失效归零分析系统， 包括：
失效物理故障树建立模块 100: 用于根据所述元器件失效物理的共性特点， 建立所述元 器件的失效物理故障树；
失效定位故障树建立模块 200: 用于根据所述失效物理故障树将失效物理事件转为可观 测的节点事件， 以使所述失效物理故障树转换为失效定位故障树；
故障字典建立模块 300: 用于根据所述失效定位故障树， 建立失效机理原因与失效特征 相对应的元器件故障字典；
失效归零分析模块 400: 用于根据所述失效物理故障树与所述元器件故障字典， 对所述 元器件进行失效归零分析。
本发明元器件失效归零分析系统， 能够通过失效定位故障树将元器件故障定位到内部物 理结构， 给出清晰的失效路径， 通过故障字典的失效特征向量分析快速确定元器件失效模式 对应的失效机理， 通过失效物理故障树确定相关失效机理的机理因子和影响因素， 提出针对 性的失效控制措施， 实现了对电子元器件故障的快速、 准确定位和诊断。 在其中一个实施例中， 所述元器件失效物理的共性特点包括： 故障对象、 失效模式、 失 效部位、 失效机理、 机理因子和影响因素。
这样 6个共性特点能完整全面的对元器件进行故障诊断与定位， 在整理好了 6个共性特 点之后就分别以故障对象、 失效模式、 失效部位、 失效机理、 机理原因和影响因素六个层次 建立元器件失效物理故障树。
如图 4所示， 失效定位故障树建立模块 200具体包括：
事件转换单元 220 : 用于确定失效模式与失效机理之间可观测节点， 将不可测量的失效 物理事件采用可观测的节点事件表示；
特征参数选取单元 240 : 用于根据所述元器件的结构和性能特点， 选择表征各节点的特 征参数， 所述特征参数为可观测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性 能、 表观特性和气密性；
参数表征单元 260 : 用于将节点失效事件表示所述元器件的失效事件， 用所述可观测参 数表征所述节点失效事件；
故障树建立单元 280 : 用于建立以所述失效模式为顶事件、 以所述可观测节点为中间事 件和以所述失效机理原因为底事件的元器件失效定位故障树。
如图 4所示， 故障字典建立模块 300具体包括：
失效模式集确定单元 310 : 用于根据所述定位故障树， 确定所述元器件的失效模式集， 所述失效模式集包括多个失效模式子集；
可观测节点确定单元 320 : 用于根据所述定位故障树， 确定所述失效模式子集在失效模 式下的可观测节点；
特征值获取单元 330 : 用于根据所述定位故障树， 由所述可观测节点得出观测参数， 判 据所述观测参数， 得出失效模式的可观测节点特征值；
特征向量获取单元 340 : 用于根据所述可观测节点特征值， 确定所述元器件各种失效模 式的特征向量；
失效机理确定单元 350 : 用于根据所述定位故障树， 确定所述元器件的失效机理原因； 故障字典形成单元 360 : 用于根据所述失效机理原因与所述可观测节点特征值， 建立所 述失效机理原因与所述节点事件失效特征相应的元器件故障字典。
如图 4所示， 失效归零分析模块 400具体包括： 观测单元 420 : 用于根据所述故障字典的节点参数， 对所述元器件进行观测， 得到观测 向量的特征值；
比对单元 440 : 用于比对所述观测向量的特征值与所述故障字典， 确定所述元器件的失 效机理原因；
查找单元 460 : 用于根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机 理的机理因子和影响因素， 提出针对所述失效机理的措施。
综上所述， 本发明元器件失效归零分析方法与系统， 能够通过失效定位故障树将元器件 故障定位到内部物理结构， 给出清晰的失效路径， 通过故障字典的失效特征向量分析快速确 定元器件失效模式对应的失效机理， 通过失效物理故障树确定相关失效机理的机理因子和影 响因素， 提出针对性的失效控制措施， 真正做到失效 "定位准确" 、 "机理清楚" 、 "措施 有效" 。
以上所述实施例仅表达了本发明的几种实施方式， 其描述较为具体和详细， 但并不能因 此而理解为对本发明专利范围的限制。 应当指出的是， 对于本领域的普通技术人员来说， 在 不脱离本发明构思的前提下， 还可以做出若干变形和改进， 这些都属于本发明的保护范围。 因此， 本发明专利的保护范围应以所附权利要求为准。

Claims

权利 要 求
1、 一种元器件失效归零分析方法， 其特征在于， 包括步骤：
根据所述元器件失效物理的共性特点， 建立所述元器件的失效物理故障树；
根据所述失效物理故障树将失效物理事件转为可观测的节点事件， 以使所述失效物理故 障树转换为失效定位故障树；
根据所述失效定位故障树， 建立失效机理原因与失效特征相对应的元器件故障字典； 根据所述失效物理故障树与所述元器件故障字典， 对所述元器件进行失效归零分析。
2、 根据权利要求 1所述的元器件失效归零分析方法， 其特征在于， 所述元器件失效物理 的共性特点包括： 故障对象、 失效模式、 失效部位、 失效机理、 机理因子和影响因素。
3、 根据权利要求 1或 2所述的元器件失效归零分析方法， 其特征在于， 所述步骤将失效 物理故障树转换为失效定位故障树具体包括步骤：
确定失效模式与失效机理之间可观测节点， 将不可测量的失效物理事件采用可观测的节 点事件表示；
根据所述元器件的结构和性能特点， 选择表征各节点的特征参数， 所述特征参数为可观 测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性能、 表观特性、 气密性和环境 适应性；
用节点失效事件表示所述元器件的失效事件，用所述可观测参数表征所述节点失效事件; 建立以所述失效模式为顶事件、 以所述可观测节点为中间事件和以所述失效机理原因为 底事件的元器件失效定位故障树。
4、 根据权利要求 1或 2所述的元器件失效归零分析方法， 其特征在于， 所述步骤根据所 述失效定位故障树， 建立失效机理原因与失效特征相对应的元器件故障字典具体包括步骤： 根据所述定位故障树， 确定所述元器件的失效模式集， 所述失效模式集包括多个失效模 式子集；
根据所述定位故障树， 确定所述失效模式子集在失效模式下的可观测节点；
根据所述定位故障树， 由所述可观测节点得出观测参数， 判据所述观测参数， 得出失效 模式的可观测节点特征值；
根据所述可观测节点特征值， 确定所述元器件各种失效模式的特征向量； 根据所述定位故障树， 确定所述元器件的失效机理原因；
根据所述失效机理原因与所述可观测节点特征值， 建立所述失效机理原因与所述节点事 件失效特征相应的元器件故障字典。
5、 根据权利要求 1或 2所述的元器件失效归零分析方法， 其特征在于， 所述步骤根据所 述失效物理故障树与所述元器件故障字典， 对所述元器件进行失效归零分析具体包括步骤： 根据所述元器件故障字典的节点参数， 对所述元器件进行观测， 得到观测向量的特征值; 比对所述观测向量的特征值与所述元器件故障字典， 确定所述元器件的失效机理原因； 根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机理的机理因子和影响 因素， 提出针对所述失效机理的措施。
6、 一种元器件失效归零分析系统， 其特征在于， 包括：
失效物理故障树建立模块： 用于根据所述元器件失效物理的共性特点， 建立所述元器件 的失效物理故障树；
失效定位故障树建立模块： 用于根据所述失效物理故障树将失效物理事件转为可观测的 节点事件， 以使所述失效物理故障树转换为失效定位故障树；
故障字典建立模块： 用于根据所述失效定位故障树， 建立失效机理原因与失效特征相对 应的元器件故障字典；
失效归零分析模块： 用于根据所述失效物理故障树与所述元器件故障字典， 对所述元器 件进行失效归零分析。
7、 根据权利要求 6所述的元器件失效归零分析系统， 其特征在于， 所述元器件失效物理 的共性特点包括： 故障对象、 失效模式、 失效部位、 失效机理、 机理因子和影响因素。
8、 根据权利要求 6或 7所述的元器件失效归零分析系统， 其特征在于， 所述失效定位故 障树建立模块具体包括：
事件转换单元： 用于确定失效模式与失效机理之间可观测节点， 将不可测量的失效物理 事件采用可观测的节点事件表示；
特征参数选取单元： 用于根据所述元器件的结构和性能特点， 选择表征各节点的特征参 数， 所述特征参数为可观测参数， 所述可观测参数具体包括： 电性能、 热性能、 机械性能、 表观特性、 气密性和环境适应性；
参数表征单元： 用于用节点失效事件表示所述元器件的失效事件， 用所述可观测参数表 征所述节点失效事件；
故障树建立单元： 用于建立以所述失效模式为顶事件、 以所述可观测节点为中间事件和 以所述失效机理原因为底事件的元器件失效定位故障树。
9、 根据权利要求 6或 7所述的元器件失效归零分析系统， 其特征在于， 所述故障字典建 立模块具体包括：
失效模式集确定单元： 用于根据所述定位故障树， 确定所述元器件的失效模式集， 所述 失效模式集包括多个失效模式子集；
可观测节点确定单元： 用于根据所述定位故障树， 确定所述失效模式子集在失效模式下 的可观测节点；
特征值获取单元： 用于根据所述定位故障树， 由所述可观测节点得出观测参数， 判据所 述观测参数， 得出失效模式的可观测节点特征值；
特征向量获取单元： 用于根据所述可观测节点特征值， 确定所述元器件各种失效模式的 特征向量；
失效机理确定单元： 用于根据所述定位故障树， 确定所述元器件的失效机理原因； 故障字典形成单元： 用于根据所述失效机理原因与所述可观测节点特征值， 建立所述失 效机理原因与所述节点事件失效特征相应的元器件故障字典。
10、 根据权利要求 6或 7所述的元器件失效归零分析系统， 其特征在于， 所述失效归零 分析模块具体包括：
观测单元： 用于根据所述元器件故障字典的节点参数， 对所述元器件进行观测， 得到观 测向量的特征值；
比对单元： 用于比对所述观测向量的特征值与所述元器件故障字典， 确定所述元器件的 失效机理原因；
查找单元： 用于根据所述失效机理原因， 在所述失效物理故障树中查找相应失效机理的 机理因子和影响因素， 提出针对所述失效机理的措施。
PCT/CN2013/086159 2012-11-30 2013-10-29 元器件失效归零分析方法与系统 WO2014082516A1 (zh)

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