CN105160171B - A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning - Google Patents
A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning Download PDFInfo
- Publication number
- CN105160171B CN105160171B CN201510543630.8A CN201510543630A CN105160171B CN 105160171 B CN105160171 B CN 105160171B CN 201510543630 A CN201510543630 A CN 201510543630A CN 105160171 B CN105160171 B CN 105160171B
- Authority
- CN
- China
- Prior art keywords
- electronic system
- probability
- thermal
- thermal failure
- state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Abstract
The invention discloses a kind of electronic system thermal reliability analysis based on multimode transductive reasoning and Forecasting Methodology; according to 26S Proteasome Structure and Function feature; electronic system is divided into four modules, they are energy conversion and protection module, electronic control module, link block, signal transmission and modular converter respectively；Each module be one can debug and repair can adjusting system, each module has thermal failure state and normal condition, and thermal failure state is a kind of random process for the Time Continuous and state discrete for obeying exponential distribution；Consider the failure properties and maintenance and debugging characteristic of each module, and they are regarded as a random process parameter, the analysis of electronic system thermal reliability is proposed based on multimode transductive reasoning theory, random theory and reliability theory and predicted, it effectively can analyze and calculate the thermally-stabilised availability and the thermally relieved degree and thermal failure probability in the different working times of electronic system, and hot mean down time.
Description
Technical field
The present invention relates to electronic system thermal reliability technical field, and in particular to a kind of electricity based on multimode transductive reasoning
Subsystem thermal reliability is analyzed and Forecasting Methodology.
Background technology
Internal high-power component can produce substantial amounts of heat to electronic system when in use, what long-term temperature alternating was produced
Thermal stress can cause system component to occur thermal fatigue failure, raising and the complexity of working environment with electronic system integrated level
Change, its heat generation density also more and more higher, the problems of excessive heat of electronic system has become the main cause of electronic system failure.It is quantitative
Ground predict and calculate electronic system hot steady-state availability, thermal failure probability and thermally relieved degree be prevention electronic system break down and
Ensure the reliable and stable work of electronic equipment it is most basic by way of, be also electronic system carry out thermal reliability design premise and base
Plinth, it improves thermal design for high density electronic system and provides foundation, so as to targetedly carry out thermal reliability optimization design.
It is external to proceed by the heat analysis of electronic system early in last century the eighties mid-term, comment warmly and estimate the work of aspect,
To the nineties in last century, Sachio, Yasufufu of Japanese Tosbiba companies are to electronic system particularly computer motherboard system
System, which comment warmly, to be estimated and quality control and has delivered scientific paper.In recent years, foreign countries were to element heat analysis in electronic system
There is certain research, LuisAntBnio, Waak Bambace of space research institute of Brazilian state-run association et al. is it is proposed that use side
The thermal life of each element on method (BIEM) the prediction mainboard of boundary's integration, this method is applicable and isotropism and anisotropic
Problem, its advantage is simple, easy, can be applicable for substantial amounts of practical problem.Irish School of Mechanical Engineering of state university
JohnLohan et al. with regard to thermal convection current in the case of dsc data analysis and forecasting research have been carried out to the element of electronic system.
China electronic system comment warmly estimate and analysis in terms of research start late, be originally all the warp of foreign
Test, the military then gives great attention to the thermal design of electronic system, has promulgated national military standard GJB/Z27-92 in July, 1992《Electricity
Sub- equipment dependability thermal design handbook》, it is the basic foundation for carrying out heat analysis；In September, 1993 has promulgated national military standard GJB/Z35-
93《Component derating criteria》, define various components thermal reliability value in the case of different application.
Because electronic system is in the presence of circulating temperature, hot-machine coupling relation is extremely complex, be one it is dynamic with
Machine process, thermal reliability analysis and prediction modeling are extremely difficult, and this causes the thermal reliability of the electronic system of China to analyze and pre-
The research of survey technology is less, and level is relatively low, and electronic system exploitation and research institute only make some preliminary thermal reliabilities by rule of thumb
Analysis and reliability prediction, so as to take certain control measure, do not carry out the thermal reliability analysis of accurate and science and assess
Work, this greatly constrains the development of electronic system development technique.
The content of the invention
In view of the deficienciess of the prior art, it is an object of the invention to provide a kind of electricity based on multimode transductive reasoning
Subsystem thermal reliability is analyzed and Forecasting Methodology, the method effectively can analyze and calculate the thermally-stabilised availability of electronic system with
In the thermally relieved degree and thermal failure probability of different working times, and hot mean down time.It solves electronic system heat
The key technology of fail-safe analysis, design and prediction.
To achieve the above object, the invention provides following technical scheme：A kind of electronics based on multimode transductive reasoning
System thermal reliability is analyzed and Forecasting Methodology, is comprised the following steps：
(1) according to 26S Proteasome Structure and Function feature, electronic system is divided into four modules, they are energy conversion respectively and protected
Module, electronic control module, link block, signal transmission and modular converter, each module regard that one can debug and tie up as
Repair can adjusting system, they have two kinds of states：Thermal failure state and normal condition, and thermal failure state is regarded as a kind of
Obey the Time Continuous of exponential distribution and the random process of state discrete；
(2) Principle of Random Process is combined, thermal failure thermal failure transition probability equation group group is obtained；
(3) according to total probability formula and thermal failure transition probability equation group, conversion obtains probability derivative equation；
(4) infinite limit is asked to the time variable in probability derivative equation and value is zero, probability derivative equation is changed
Linear matrix equation；
(5) it is complete event according to linear matrix equation and state sumFeature, with reference to electronic system four
The thermal failure rate and debugging maintenance rate of module, export thermal reliability consolidated equation group：
Solve the hot steady-state availability that equation group obtains electronic system：
(6) any one module thermal failure probability in electronic system is made to be equal to 1, debugging maintenance rate is equal to 0, makes Department of Electronics
System enters absorbing state, according to the feature of absorbing state and probability derivative equation, obtains the thermally relieved degree of electronic system with fortune
The changing rule of row time：
Thermal failure probability is with the changing rule of run time：
To thermally relieved degree integration, the electronic system hot mean down time is tried to achieve：
The present invention is further arranged to：Step (2) includes following sub-step：
(2.1) with λ1,λ2,λ3, and λ4Respectively represent energy conversion and protection module, electronic control module, link block,
Signal transmits the thermal failure rate with modular converter, μ1,μ2,μ3, and μ4Respectively energy conversion and protection module, electronic control module,
The debugging maintenance rate of link block, signal transmission and modular converter.Electronic system thermal failure state is encoded with numeral, 0
Expression normal condition, 1,2,3,4, electronic control module, link block, signal transmission module and signal conversion module are represented respectively
In thermal failure state.
(2.2) according to the coding of thermal failure state, it is P to define the t-t+ Δ t times interior state transition probability from i → jij
(Δ t), wherein i, j=0,1,2,3,4.
(2.3) according to memoryless Principle of Random Process, thermal failure thermal failure transition probability equation group group is obtained.
State transition probability Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]
Wherein, X (t) represents the state variable in the t times.
As i ≠ j, Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]=aijΔt+o(Δt)
aijIt is the state transition probability in the unit interval, it correspond to the debugging maintenance rate and crash rate of electronic system.
a01,a02,a03,a04, respectively equal to λ1,λ2,λ3,λ4；a10,a20,a30,a40, respectively equal to μ1,μ2,μ3,μ4；aij=0, i ≠ j and j
≠ 0 and i ≠ 0；(Δ t) is Δ t higher order indefinite small to o.
Due to：
Obtain i=j state transition probability：
Analyzed more than summarizing, obtaining thermal failure thermal failure transition probability equation group group is：
The present invention is further arranged to：Step (3) includes following sub-step：
(3.1) had according to total probability formula：
Thermal failure transition probability equation group group is substituted into above formula, j state Δs t deflection probability, j=0,1,2,3,4 is obtained.
(3.2) deflection probability is transplanted and probability differential equation is obtained to Δ t derivations：
(3.3) make Δ t level off to zero, try to achieve probability derivative equation：
It is an advantage of the invention that：Electronic system is resolved into four modules：Energy is changed and protection module, Electronic Control mould
Block, link block, signal transmission and modular converter, consider the failure properties and maintenance and debugging characteristic of each module, and handle
They regard a random process parameter as, are proposed based on multimode transductive reasoning theory, random theory and reliability theory
The new method that electronic system thermal reliability is analyzed and predicted.The thermally-stabilised of electronic system effectively can be analyzed and calculate to the method, which, to be had
Validity and the thermally relieved degree and thermal failure probability in the different working times, and hot mean down time.It solves electronics
The key technology of the analysis of system thermal reliability, design and prediction.
With reference to Figure of description and specific embodiment, the invention will be further described.
Brief description of the drawings
Fig. 1 be electronic system in the embodiment of the present invention thermal failure and it is normal between state transition graph；
Fig. 2 for electronic system of the embodiment of the present invention thermal failure and it is normal between absorbing state transition diagram；
In Fig. 3 embodiment of the present invention hot steady-state availability with module thermal failure rate changing rule figure；
Fig. 4 is the thermally relieved degree of system of the embodiment of the present invention with the changing rule figure of run time；
Fig. 5, which is that system of the embodiment of the present invention is thermally relieved, spends the thermal failure probability with system with the changing rule of run time
Figure；
Fig. 6 is that the embodiment of the present invention is advised in the thermally relieved degree of different run time systems with the change of the crash rate of module
Rule figure.
Embodiment
Referring to Fig. 1 to Fig. 6, a kind of electronic system thermal reliability analysis based on multimode transductive reasoning disclosed by the invention
And Forecasting Methodology, comprise the following steps：
(1) according to 26S Proteasome Structure and Function feature, electronic system is divided into four modules, they are energy conversion respectively and protected
Module, electronic control module, link block, signal transmission and modular converter, each module regard that one can debug and tie up as
Repair can adjusting system, they have two kinds of states：Thermal failure state and normal condition, and thermal failure state is regarded as a kind of
Obey the Time Continuous of exponential distribution and the random process of state discrete, the conversion of state, referring to Fig. 1；
(2) Principle of Random Process is combined, thermal failure thermal failure transition probability equation group group is obtained；
(3) according to total probability formula and thermal failure transition probability equation group, conversion obtains probability derivative equation；
(4) infinite limit is asked to the time variable in probability derivative equation and value is zero, probability derivative equation is changed
Linear matrix equation；
(5) it is complete event according to linear matrix equation and state sumFeature, with reference to electronic system four
The thermal failure rate and debugging maintenance rate of individual module, export thermal reliability consolidated equation group：
Solve the hot steady-state availability that equation group obtains electronic system：
(6) any one module thermal failure probability in electronic system is made to be equal to 1, debugging maintenance rate is equal to 0, makes Department of Electronics
System enters absorbing state, and as shown in Figure 2, according to the feature of absorbing state and probability derivative equation, the heat for obtaining electronic system can
By spending the changing rule with run time：
Thermal failure probability is with the changing rule of run time：
To thermally relieved degree integration, the electronic system hot mean down time is tried to achieve：
As preferred：Step (2) includes following sub-step：
(2.1) with λ1,λ2,λ3, and λ4Respectively represent energy conversion and protection module, electronic control module, link block,
Signal transmits the thermal failure rate with modular converter, μ1,μ2,μ3, and μ4Respectively energy conversion and protection module, electronic control module,
The debugging maintenance rate of link block, signal transmission and modular converter.Electronic system thermal failure state is encoded with numeral, 0
Expression normal condition, 1,2,3,4, electronic control module, link block, signal transmission module and signal conversion module are represented respectively
In thermal failure state.
(2.2) according to the coding of thermal failure state, it is P to define the t-t+ Δ t times interior state transition probability from i → jij
(Δ t), wherein i, j=0,1,2,3,4.
(2.3) according to memoryless Principle of Random Process, thermal failure thermal failure transition probability equation group group is obtained.State turns
Change probability Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]
Wherein, X (t) represents the state variable in the t times.
As i ≠ j, Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]=aijΔt+o(Δt)
aijIt is the state transition probability in the unit interval, it correspond to the debugging maintenance rate and crash rate of electronic system.
a01,a02,a03,a04, respectively equal to λ1,λ2,λ3,λ4；a10,a20,a30,a40, respectively equal to μ1,μ2,μ3,μ4；aij=0, i ≠ j and j
≠ 0 and i ≠ 0；(Δ t) is Δ t higher order indefinite small to o.
Due to：
Obtain i=j state transition probability：
Analyzed more than summarizing, obtaining thermal failure thermal failure transition probability equation group group is：
As preferred：Step (3) includes following sub-step：
(3.1) had according to total probability formula：
Thermal failure transition probability equation group group is substituted into above formula, j state Δs t deflection probability, j=0,1,2,3,4 is obtained.
(3.2) deflection probability is transplanted and probability differential equation is obtained to Δ t derivations：
(3.3) make Δ t level off to zero, try to achieve probability derivative equation：
Illustrated below using convertible frequency air-conditioner indoor electronic control system as embodiment：
(1) according to 26S Proteasome Structure and Function feature, convertible frequency air-conditioner indoor electronic control system is divided into four modules, they distinguish
It is energy conversion and protection module, electronic control module, link block, signal transmission and modular converter, each module is regarded as
One can debug and repair can adjusting system, they have two kinds of states：Thermal failure state and normal condition, and heat mistake
Effect state regards a kind of random process for the Time Continuous and state discrete for obeying exponential distribution, the conversion of state, referring to figure as
1；
(2) Principle of Random Process is combined, the thermal failure thermal failure conversion for obtaining convertible frequency air-conditioner indoor electronic control system is general
Rate equation group group；
(2.1) with λ1,λ2,λ3, and λ4Respectively represent energy conversion and protection module, electronic control module, link block,
Signal transmits the thermal failure rate with modular converter, μ1,μ2,μ3, and μ4Respectively energy conversion and protection module, electronic control module,
The debugging maintenance rate of link block, signal transmission and modular converter.Electronic system thermal failure state is encoded with numeral, 0
Expression normal condition, 1,2,3,4, electronic control module, link block, signal transmission module and signal conversion module are represented respectively
In thermal failure state.λ1,λ2,λ3, and λ4, μ1,μ2,μ3, and μ4Value be shown in Table 1.
| Module and parameter | Crash rate (104FIT) | Debug maintenance rate (h–1) |
| Energy is changed and protection module | 2.00 | 0.585 |
| Electronic control module | 1.50 | 0.326 |
| Link block | 1.00 | 0.255 |
| Signal is transmitted and modular converter | 2.50 | 0.685 |
Table 1
(2.2) according to the coding of thermal failure state, it is P to define the t-t+ Δ t times interior state transition probability from i → jij
(Δ t), wherein i, j=0,1,2,3,4.
(2.3) according to memoryless Principle of Random Process, thermal failure thermal failure transition probability equation group group is obtained.
State transition probability Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]
Wherein, X (t) represents the state variable in the t times.
As i ≠ j, Pij(Δ t)=P [X (t+ Δs t)=jX (t)=i]=aijΔt+o(Δt)
aijIt is the state transition probability in the unit interval, it correspond to the debugging maintenance rate and crash rate of electronic system.
a01,a02,a03,a04, respectively equal to λ1,λ2,λ3,λ4；a10,a20,a30,a40, respectively equal to μ1,μ2,μ3,μ4；aij=0, i ≠ j and j
≠ 0 and i ≠ 0；(Δ t) is Δ t higher order indefinite small to o.
Due to：
Obtain i=j state transition probability：
Analyzed more than summarizing, obtaining thermal failure thermal failure transition probability equation group group is：
(3) according to total probability formula and thermal failure transition probability equation group, conversion obtains probability derivative equation；
(3.1) had according to total probability formula：
Thermal failure transition probability equation group group is substituted into above formula, j state Δs t deflection probability is obtained,
J=0,1,2,3,4.
(3.2) deflection probability is transplanted and probability differential equation is obtained to Δ t derivations：
(3.3) make Δ t level off to zero, try to achieve probability derivative equation：
(4) infinite limit is asked to the time variable in probability derivative equation and value is zero, probability derivative equation is changed
Linear matrix equation；
(5) it is complete event according to linear matrix equation and state sumFeature, with reference in convertible frequency air-conditioner room
The thermal failure rate and debugging maintenance rate of four modules of electronic control system, export thermal reliability consolidated equation group：
Solve the hot steady-state availability that equation group obtains electronic system：
(6) any one module thermal failure probability in convertible frequency air-conditioner indoor electronic control system is made to be equal to 1, debugging maintenance
Rate is equal to 0, electronic system is entered absorbing state, as shown in Figure 2, according to the feature of absorbing state and probability derivative equation, obtains
Thermally relieved degree to convertible frequency air-conditioner indoor electronic control system is with the changing rule of run time：
Thermal failure probability is with the changing rule of run time：
By above thermal reliability characteristic quantity, the thermally relieved degree and thermal failure probability of electronic control system are analyzed and predicted
With the changing rule of run time, as shown in Figure 4 and 5.And electronic control system is obtained in different run time systems
Thermally relieved degree with the crash rate of module changing rule, as shown in Figure 6.
To thermally relieved degree integration, the electronic system hot mean down time is tried to achieve：
By the analysis and prediction of the present embodiment, convertible frequency air-conditioner indoor electronic control system operation 20,000 hour it
Before, its thermally relieved degree drastically declines, and the increase then as run time is gently reduced.The 5,000h when system operation,
During 10,000h, 15,000h, and 20,000h, thermally relieved degree is respectively 0.7047,0.4966,0.3499, and 0.2466, mould
The disturbance of block crash rate has a great impact to the thermally relieved degree of whole system, the result of this and actual motion be it is consistent,
As shown in Figure 6.
The present invention can realize that effective thermal reliability is assessed and predicted to electronic system, greatly improve electronic system operation
Safety and reliability.It effectively can analyze and calculate the thermally-stabilised availability of electronic system and in the different working times
Thermally relieved degree and thermal failure probability, and hot mean down time.It solves the analysis of electronic system thermal reliability, designed and pre-
The key technology of survey.
Above-described embodiment is served only for that the present invention is further described, it is impossible to be interpreted as to the specific descriptions of the present invention
Limiting the scope of the present invention, it is non-that the technician of this area makes some according to the content of foregoing invention to the present invention
The modifications and adaptations of essence are each fallen within protection scope of the present invention.
Claims (4)
1. a kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning, it is characterised in that：Including
Following steps：
(1) according to 26S Proteasome Structure and Function feature, electronic system is divided into four modules, they are energy conversion and protection mould respectively
Block, electronic control module, link block, signal transmission and modular converter；Each module be one can debug and repair can
Adjusting system, each module has thermal failure state and normal condition, and thermal failure state is a kind of time for obeying exponential distribution
The random process of continuous and state discrete；
(2) Principle of Random Process is combined, thermal failure thermal failure transition probability equation group group is obtained；
(3) according to total probability formula and thermal failure transition probability equation group, conversion obtains probability derivative equation；
(4) infinite limit is asked to the time variable in probability derivative equation and value is zero, probability derivative equation is converted into line
Property matrix equation；
(5) according to linear matrix equation, with reference to the thermal failure rate and debugging maintenance rate of four modules of electronic system, export thermally relieved
Property consolidated equation group, solve equation group obtain electronic system hot steady-state availability；
(6) any one module thermal failure probability in electronic system is made to be equal to 1, debugging maintenance rate is equal to 0, enters electronic system
Enter absorbing state, according to the feature of absorbing state and probability differential equation, when obtaining the thermally relieved degree of electronic system with operation
Between changing rule, thermally relieved degree is integrated, the electronic system hot mean down time is tried to achieve.
2. a kind of analysis of electronic system thermal reliability and prediction side based on multimode transductive reasoning according to claim 1
Method, it is characterised in that：Step (2) includes following sub-step：
(2.1) with λ1,λ2,λ3, and λ4Represent that energy conversion and protection module, electronic control module, link block, signal are passed respectively
The thermal failure rate of defeated and modular converter, μ1,μ2,μ3, and μ4Energy is changed and protection module, electronic control module, connection mould respectively
The debugging maintenance rate of block, signal transmission and modular converter；Electronic system thermal failure state is encoded with numeral, 0 represents just
Normal state, 1,2,3,4, represent that electronic control module, link block, signal transmission module and signal conversion module are in heat respectively
Failure state；
(2.2) according to the coding of thermal failure state, it is P to define the t-t+ Δ t times interior state transition probability from i → jij(Δt),
Wherein i, j=0,1,2,3,4；
(2.3) Principle of Random Process is combined, thermal failure thermal failure transition probability equation group group is obtained.
3. a kind of analysis of electronic system thermal reliability and prediction side based on multimode transductive reasoning according to claim 2
Method, it is characterised in that：Step (2.3) the thermal failure thermal failure transition probability equation group group is：
Wherein, aij=0, i ≠ j and j ≠ 0 and i ≠ 0；(Δ t) is Δ t higher order indefinite small to o.
4. a kind of analysis of electronic system thermal reliability and prediction side based on multimode transductive reasoning according to claim 3
Method, it is characterised in that：Step (3) includes following sub-step：
(3.1) according to total probability formula：
Thermal failure transition probability equation group group is substituted into above formula, j state Δs t deflection probability, j=0,1,2,3,4 is obtained；
(3.2) deflection probability is transplanted and probability differential equation is obtained to Δ t derivations：
(3.3) make Δ t level off to zero, try to achieve probability derivative equation：
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510543630.8A CN105160171B (en) | 2015-08-28 | 2015-08-28 | A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510543630.8A CN105160171B (en) | 2015-08-28 | 2015-08-28 | A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105160171A CN105160171A (en) | 2015-12-16 |
| CN105160171B true CN105160171B (en) | 2017-09-29 |
Family
ID=54801027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510543630.8A Active CN105160171B (en) | 2015-08-28 | 2015-08-28 | A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105160171B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106021917B (en) * | 2016-05-18 | 2018-12-04 | 温州大学 | A kind of high-speed rail power supply system supports that connecting component structural reliability calculates and prediction technique |
| CN108763041A (en) * | 2018-05-03 | 2018-11-06 | 温州大学 | A kind of thermally relieved degree calculating of server based on heat flow statistics and probability distribution and monitoring method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5465321A (en) * | 1993-04-07 | 1995-11-07 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | Hidden markov models for fault detection in dynamic systems |
| US6571202B1 (en) * | 1999-03-17 | 2003-05-27 | General Electric Company | Method for applying design for reliability into design for six sigma |
| CN102663201A (en) * | 2012-04-24 | 2012-09-12 | 北京航空航天大学 | Electronic product reliability predicting method considering electric interconnection structure reliability |
| CN103413023A (en) * | 2013-07-11 | 2013-11-27 | 电子科技大学 | Multi-state system dynamic reliability assessment method |
| CN103778295A (en) * | 2014-01-26 | 2014-05-07 | 南京航空航天大学 | Method for evaluating operating reliability of multi-model integrated aero-engine under multiple failure modes |
| CN104537224A (en) * | 2014-12-19 | 2015-04-22 | 北京航空航天大学 | Multi-state system reliability analysis method and system based on self-adaptive learning algorithm |
-
2015
- 2015-08-28 CN CN201510543630.8A patent/CN105160171B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5465321A (en) * | 1993-04-07 | 1995-11-07 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | Hidden markov models for fault detection in dynamic systems |
| US6571202B1 (en) * | 1999-03-17 | 2003-05-27 | General Electric Company | Method for applying design for reliability into design for six sigma |
| CN102663201A (en) * | 2012-04-24 | 2012-09-12 | 北京航空航天大学 | Electronic product reliability predicting method considering electric interconnection structure reliability |
| CN103413023A (en) * | 2013-07-11 | 2013-11-27 | 电子科技大学 | Multi-state system dynamic reliability assessment method |
| CN103778295A (en) * | 2014-01-26 | 2014-05-07 | 南京航空航天大学 | Method for evaluating operating reliability of multi-model integrated aero-engine under multiple failure modes |
| CN104537224A (en) * | 2014-12-19 | 2015-04-22 | 北京航空航天大学 | Multi-state system reliability analysis method and system based on self-adaptive learning algorithm |
Non-Patent Citations (2)
| Title |
|---|
| 《基于Markov过程的多状态可维修系统可靠性建模与仿真》;胡康;《万方数据》;20140522;第2-5章 * |
| 基于Markov模型的可维修双机热备系统可靠性分析;于敏，等;《计算机工程与设计》;20090602;第30卷(第8期);第2010-2042+2046页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105160171A (en) | 2015-12-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104240781B (en) | Signal distribution method and signal distribution system of digital instrument control system (DCS) of nuclear power plant | |
| CN104657613B (en) | A kind of complex electromechanical systems service life appraisal procedure | |
| CN103955568A (en) | Physics-of-failure-based MOS (metal oxide semiconductor) device reliability simulation evaluation method | |
| CN104299116A (en) | Quantitative evaluation method for security risk of operation of power network | |
| CN105160171B (en) | A kind of analysis of electronic system thermal reliability and Forecasting Methodology based on multimode transductive reasoning | |
| CN104050607A (en) | Power distribution network operational risk evaluation method | |
| Li et al. | Development of low voltage network templates—Part II: Peak load estimation by clusterwise regression | |
| CN103675355A (en) | Anemometer monitoring method and system | |
| Liu et al. | Probabilistic steady-state and dynamic security assessment of power transmission system | |
| CN111191872A (en) | Power grid multi-dimensional toughness evaluation system and method | |
| CN105391168A (en) | Transformer load real-time control method | |
| Biswal et al. | Modeling, Control, and Monitoring of $\hbox {S}^{3}\hbox {RS} $-Based Hydrogen Cooling System in Thermal Power Plant | |
| Zheng et al. | Cyber security risk assessment for industrial automation platform | |
| CN103675357A (en) | Anemometer fault warning method and system | |
| Singh et al. | Reliability and economic analysis of a power generating system comprising one gas and one steam turbine with random inspection | |
| CN103698680B (en) | A kind of components and parts resistant to total dose survival ability predictor method | |
| Toft et al. | Response load extrapolation for wind turbines during operation based on average conditional exceedance rates | |
| CN106289754A (en) | A kind of fired power generating unit component capabilities based on Statistical Control Technique change decision method | |
| CN103020431A (en) | Oil-immersed transformer status evaluation modeling method and oil-immersed transformer status evaluation system | |
| CN102856884B (en) | Heat accumulation based frequency converter overload method | |
| Zhang et al. | A model for residual life prediction based on brownian motion in framework of similarity | |
| CN105760985A (en) | Low frequency risk comprehensive evaluation method for nuclear power accessed to grid | |
| CN105893726B (en) | A kind of monitoring method of characteristic signal monitoring point | |
| Wu et al. | Performance assessment of hydropower generator unit with the nonlinear transmissibility function method | |
| Deng et al. | The risk-based assessment of static voltage stability issues with consideration of load and wind power uncertainties |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 325000 Zhejiang Economic Development Zone, Ouhai, South East Road, No. 38, Wenzhou National University Science Park Incubator Applicant after: Wenzhou University Address before: 325000 Zhejiang province Chashan Wenzhou Higher Education Park Applicant before: Wenzhou University |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20151216 Assignee: Huizhi digital technology (Ningbo) Co.,Ltd. Assignor: Wenzhou University Contract record no.: X2021330000823 Denomination of invention: A thermal reliability analysis and prediction method of electronic system based on multi state transition reasoning Granted publication date: 20170929 License type: Common License Record date: 20211220 |
|
| EE01 | Entry into force of recordation of patent licensing contract |