CN110532116B - System reliability modeling method and device - Google Patents
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Abstract
The invention discloses a system reliability modeling method and a device, wherein the method comprises the following steps: collecting standard working data of a working part when the system has no fault; detecting and recording working data of working parts of the system in real time in the process from the initial working moment to the failure of the system; selecting failure data of the working part from the working data of the working part by taking standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts; drawing a failure curve graph of the working part according to the failure data of the working part; according to the failure curve graph of the working part, calculating the failure rate of the working part; and establishing a reliability model of the system according to the failure rate of the working parts. The invention can detect the reliability of the product system aiming at the product in use, thereby enabling a user to predict the service life of the product which can normally work and the time point of the product failure in real time.
Description
Technical Field
The invention relates to the field of system reliability detection, in particular to a system reliability modeling method and device.
Background
When the electronic product is produced and delivered, the reliability of the product system is often detected through tests so as to obtain more knowledge of the service life of the product and the performance parameters of various components included in the product system. The existing reliability detection is generally performed in a laboratory simulation test environment, specifically, a certain product is selected from a batch of products as a sample to perform the reliability test, the reliability of the batch of products is represented by the test result of the sample, but the reliability result detected by the method is not strong in accuracy, the reliability detection can not be performed for each product, and for the product in use, the method for detecting the reliability of the product in the laboratory is not suitable, so that the normal service life of the product and the time point of the product failure can not be predicted when the product is used.
Disclosure of Invention
The invention provides a system reliability modeling method and device, which can detect the reliability of a product system aiming at a product in use, so that a user can predict the service life of the product capable of working normally and the time point of the product failure in real time.
According to one aspect of the present invention, there is provided a system reliability modeling method including the steps of:
collecting standard working data of a working part when the system has no fault;
detecting and recording working data of working parts of the system in real time in the process from the initial working moment to the failure of the system;
selecting failure data of the working part from the working data of the working part by taking the standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts;
drawing a failure curve graph of the working part according to the failure data of the working part;
according to the failure curve graph of the working part, calculating the failure rate of the working part;
and establishing a reliability model of the system according to the failure rate of the working part.
Preferably, after establishing the reliability model of the system according to the failure rate of the working component, the method further comprises the following steps:
detecting instant working data of a working part of a system to be tested when working;
and inputting the instant working data of the working parts of the system to be tested in the reliability model to obtain the reliability coefficient of the system to be tested.
Preferably, after detecting the instant working data when the working component of the system to be tested works, the method further comprises the following steps:
calculating the bearing capacity of the working part according to the failure curve graph of the working part;
acquiring the total load of the system to be tested;
inputting instant working data of the working parts of the system to be tested in the reliability model to obtain the reliability coefficient of the system to be tested, wherein the method specifically comprises the following steps: and analyzing the relation between the bearing capacity of the working component and the total load of the system to be tested, and inputting instant working data of the working component of the system to be tested when working into the reliability model to obtain the reliability coefficient of the system to be tested.
Preferably, the failure rate of the working component is calculated according to the failure curve chart of the working component, and the method comprises the following steps:
according to the failure curve graph of the working parts, the total number of the working parts and the total working time length are counted;
according to the failure curve graph of the working parts, counting the number of failed working parts and the failure time of each failed working part;
according to the calculation formula of failure rate
Calculating the failure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δ (t) represents total working time of the working components, N represents the total number of the working components, ni represents failed working components, and ti represents failure time of failed working components ni.
According to another aspect of the present invention, there is also provided a system reliability modeling apparatus including:
the collecting unit is used for collecting standard working data of the working parts when the system has no faults;
the first detection unit is used for detecting and recording working data of a working part of the system in real time in the process from the initial working moment to the system failure of the system;
the data selecting unit is used for selecting failure data of the working part from the working data of the working part by taking the standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts;
a drawing unit, configured to draw a failure graph of the working component according to failure data of the working component;
a first calculation unit, configured to calculate a failure rate of the working component according to a failure graph of the working component;
and the model building unit is used for building a reliability model of the system according to the failure rate of the working part.
Preferably, the system reliability modeling apparatus further includes:
the second detection unit is used for detecting instant working data of the working component of the system to be tested when working after the model building unit builds a reliability model of the system according to the failure rate of the working component;
the first acquisition unit is used for inputting the instant working data of the working parts of the system to be tested when working into the reliability model to obtain the reliability coefficient of the system to be tested.
Preferably, the system reliability modeling apparatus further includes:
the second calculation unit is used for calculating the bearing capacity of the working component according to the failure curve graph of the working component after the second detection unit detects the instant working data of the working component of the system to be detected when the working component works;
the second acquisition unit is used for acquiring the total load of the system to be tested;
the first obtaining unit is specifically configured to analyze a relationship between a bearing capacity of the working component and a total load of the system to be tested, and input instant working data of the working component of the system to be tested when working into the reliability model to obtain a reliability coefficient of the system to be tested.
Preferably, the first computing unit includes:
the first statistics module is used for counting the total number of the working parts and the total working time according to the failure curve graph of the working parts;
the second statistics module is used for counting the number of the invalid working parts and the invalid time of each invalid working part according to the invalid graph of the working parts;
the calculation module is used for calculating a formula according to the failure rate
Calculating the failure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δ (t) represents total working time of the working components, N represents the total number of the working components, ni represents failed working components, and ti represents failure time of failed working components ni.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the working data of a plurality of product systems are collected firstly, and then the working data of the invalid working parts are selected, so that the failure rate of the product systems is calculated, the reliability model of the product systems can be built according to the failure rate, and when the reliability of the product to be detected is required to be detected, the reliability coefficient of the product can be obtained only by inputting the instant working data of the product systems into the reliability model. Therefore, not only the reliability of the product which is not delivered from the factory can be detected so as to detect whether the product is qualified or not, but also the reliability of the product in work can be detected, and further the service life of the product and the time point when the product possibly breaks down can be predicted more conveniently and accurately by a user.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the accompanying drawings:
FIG. 1 is a flow chart of a system reliability modeling method according to an embodiment of the present invention;
FIG. 2 is a block diagram of a system reliability modeling apparatus according to an embodiment of the present invention;
fig. 3 is a flow chart of another system reliability modeling method according to a first embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described below with reference to the accompanying drawings, but the described embodiments are only some embodiments of the present invention, and all other embodiments obtained by those skilled in the art without making any inventive effort based on the embodiments of the present invention are within the scope of the protection of the present invention.
The embodiment of the invention provides a system reliability modeling method, and fig. 1 is a flow chart of the system reliability modeling method according to the embodiment of the invention, as shown in fig. 1, and comprises the following steps:
step S101: collecting standard working data of a working part when the system has no fault;
step S102: detecting and recording working data of working parts of the system in real time in the process from the initial working moment to the failure of the system;
step S103: selecting failure data of the working part from the working data of the working part by taking standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts;
step S104: drawing a failure curve graph of the working part according to the failure data of the working part;
step S105: according to the failure curve graph of the working part, calculating the failure rate of the working part;
step S106: and establishing a reliability model of the system according to the failure rate of the working parts.
In the implementation process, after step S106, the instant working data of the working components of the system to be tested during working can be detected; and then inputting the instant working data of the working parts of the system to be tested in the reliability model to obtain the reliability coefficient of the system to be tested.
Further, after detecting the instant working data of the working component of the system to be tested in working, the bearing capacity of the working component can be calculated according to the failure curve chart of the working component; acquiring the total load of a system to be tested; inputting instant working data of the working parts of the system to be tested in working into a reliability model to obtain the reliability coefficient of the system to be tested, wherein the method specifically comprises the following steps: and analyzing the relation between the bearing capacity of the working part and the total load of the system to be tested, and inputting the instant working data of the working part of the system to be tested in a reliability model to obtain the reliability coefficient of the system to be tested.
In step S105, according to the failure graph of the working parts, the total number of the working parts and the total working time length are counted; according to the failure graph of the working parts, counting the number of failed working parts and the failure time of each failed working part; according to the calculation formula of failure rate
Calculating the failure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δt represents total working time of the working components, N represents total number of working components, ni represents failed working components, and ti represents failure time of failed working components ni.
Through the steps, the reliability of the product which is not delivered can be detected so as to detect whether the product is qualified or not, and the reliability of the product in work can be detected, so that a user can more conveniently and accurately predict the service life of the product and the time point when the product possibly fails.
The embodiment of the invention also provides a system reliability modeling device 20 for realizing the system reliability modeling method.
Fig. 2 is a block diagram of a system reliability modeling apparatus 20 according to an embodiment of the present invention, and as shown in fig. 2, the apparatus 20 includes: an acquisition unit 201, configured to acquire standard working data of a working component when the system has no fault; a first detecting unit 202, configured to detect and record, in real time, working data of a working component of the system in a process from an initial working time to a system failure of the system; a data selecting unit 203, configured to select failure data of the working component from the working data of the working component by using standard working data of the working component as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts; a drawing unit 204 for drawing a failure graph of the working member based on the failure data of the working member; a first calculation unit 205, configured to calculate a failure rate of the working component according to a failure graph of the working component; the model building unit 206 is configured to build a reliability model of the system according to the failure rate of the working component.
For the system reliability modeling apparatus 20, further comprising: a second detecting unit 207, configured to detect immediate working data when the working component of the system to be tested works after the model building unit 206 builds a reliability model of the system according to the failure rate of the working component; the first obtaining unit 208 is configured to input the real-time working data of the working component of the system to be tested in the reliability model, so as to obtain a reliability coefficient of the system to be tested.
For the system reliability modeling apparatus 20, further comprising: a second calculating unit 209, configured to calculate a load-carrying capacity of the working component according to a failure graph of the working component after the second detecting unit 207 detects immediate working data when the working component of the system to be tested is working; a second obtaining unit 210, configured to obtain a total load of the system to be tested; the first obtaining unit 208 is specifically configured to analyze a relationship between a bearing capacity of a working component and a total load of the system to be tested, and input real-time working data of the working component of the system to be tested when working into a reliability model, so as to obtain a reliability coefficient of the system to be tested.
For the system reliability modeling apparatus 20, the first calculation unit 205 includes: a first statistics module 2051, configured to count a total number of working components and a total working duration according to a failure graph of the working components; the second statistics module 2052 is configured to count, according to a failure graph of the working components, the number of failed working components and failure time of each failed working component; a calculation module 2053, configured to calculate a formula according to the failure rate
Calculation ofFailure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δt represents total working time of the working components, N represents total number of working components, ni represents failed working components, and ti represents failure time of failed working components ni.
It should be noted that, the system reliability modeling apparatus described in the apparatus embodiment corresponds to the method embodiment described above, and a specific implementation process of the system reliability modeling apparatus has been described in detail in the method embodiment, which is not described herein again.
In order to make the technical scheme and implementation method of the present invention more clear, the following describes its implementation process in detail in connection with a preferred embodiment.
Example 1
The present embodiment provides another system reliability modeling method, as shown in fig. 3, and fig. 3 is a flowchart of another system reliability modeling method according to the first embodiment of the present invention, including the following steps:
step S301: collecting standard working data of a working part when the system has no fault;
in the embodiment of the invention, a large number of product systems are required to be taken as samples, working data of working components contained in each sample in the absence of faults are collected, and the working data are taken as standard working data, wherein the absence of faults refers to the working data of normal working of the working components of the system detected in a period from an initial working state to the occurrence of faults of the system;
step S302: detecting and recording working data of working parts of the system in real time in the process from the initial working moment to the failure of the system;
step S303: selecting failure data of the working part from the working data of the working part by taking standard working data of the working part as a comparison standard;
in the embodiment of the invention, the failure data comprise the failure time, the failure reason and the failure number of the working parts;
optionally, comparing the working data of the working components with the standard working data one by one, when the difference between the working data of a certain working component and the standard working data exceeds the preset adjustable normal working range, indicating that the working data of the working component is invalid working data, namely that the working component is invalid, recording the invalid time of the working component at the moment, and recording the number of invalid working components of the system in real time after comparing the working data of all the working components contained in the whole system with the standard working data.
Step S304: drawing a failure curve graph of the working part according to the failure data of the working part;
step S305: according to the failure curve graph of the working parts, the total number of the working parts and the total working time length are counted;
step S306: according to the failure graph of the working parts, counting the number of failed working parts and the failure time of each failed working part;
step S307: according to the calculation formula of failure rate
Calculating the failure rate of the working part;
in the embodiment of the invention, lambda (t) represents failure rate, delta N (t) represents the number of failed working components, delta (t) represents total working time of the working components, N represents the total number of the working components, ni represents the failed working components, and ti represents the failure time of the failed working components ni.
Step S308: according to the failure rate of the working parts, a reliability model of the system is built;
step S309: detecting instant working data of a working part of a system to be tested when working;
step S310: calculating the bearing capacity of the working part according to the failure curve graph of the working part;
step S311: acquiring the total load of a system to be tested;
step S312: and analyzing the relation between the bearing capacity of the working part and the total load of the system to be tested, and inputting the instant working data of the working part of the system to be tested in a reliability model to obtain the reliability coefficient of the system to be tested.
In summary, through the above embodiment, working data of a plurality of product systems are collected first, and then working data of a failure working component is selected, so that failure rate of the product system is calculated, and thus, a reliability model of the product system can be built according to the failure rate, and when reliability detection needs to be performed on a product to be detected, reliability coefficients of the product can be obtained only by inputting instant working data of the product system into the reliability model. Therefore, not only the reliability of the product which is not delivered from the factory can be detected so as to detect whether the product is qualified or not, but also the reliability of the product in work can be detected, and further the service life of the product and the time point when the product possibly breaks down can be predicted more conveniently and accurately by a user.
Claims (4)
1. A system reliability modeling method, comprising the steps of:
collecting standard working data of a working part when the system has no fault;
detecting and recording working data of working parts of the system in real time in the process from the initial working moment to the failure of the system;
selecting failure data of the working part from the working data of the working part by taking the standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts;
drawing a failure curve graph of the working part according to the failure data of the working part;
according to the failure curve graph of the working part, calculating the failure rate of the working part;
establishing a reliability model of the system according to the failure rate of the working part;
after the reliability model of the system is established according to the failure rate of the working part, the method further comprises the following steps:
detecting instant working data of a working part of a system to be tested when working;
inputting instant working data of the working parts of the system to be tested when working into the reliability model to obtain the reliability coefficient of the system to be tested;
after detecting the instant working data of the working component of the system to be tested in working, the method further comprises the following steps:
calculating the bearing capacity of the working part according to the failure curve graph of the working part;
acquiring the total load of the system to be tested;
inputting instant working data of the working parts of the system to be tested in the reliability model to obtain the reliability coefficient of the system to be tested, wherein the method specifically comprises the following steps:
and analyzing the relation between the bearing capacity of the working component and the total load of the system to be tested, and inputting instant working data of the working component of the system to be tested when working into the reliability model to obtain the reliability coefficient of the system to be tested.
2. The method of claim 1, wherein calculating the failure rate of the working component from the failure graph of the working component comprises the steps of:
according to the failure curve graph of the working parts, the total number of the working parts and the total working time length are counted;
according to the failure curve graph of the working parts, counting the number of failed working parts and the failure time of each failed working part;
according to the calculation formula of failure rate
Calculating the failure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δ (t) represents total working time of the working components, N represents the total number of the working components, ni represents failed working components, and ti represents failure time of failed working components ni.
3. A system reliability modeling apparatus, comprising:
the collecting unit is used for collecting standard working data of the working parts when the system has no faults;
the first detection unit is used for detecting and recording working data of a working part of the system in real time in the process from the initial working moment to the system failure of the system;
the data selecting unit is used for selecting failure data of the working part from the working data of the working part by taking the standard working data of the working part as a comparison standard; the failure data comprise failure time, failure reasons and failure number of the working parts;
a drawing unit, configured to draw a failure graph of the working component according to failure data of the working component;
a first calculation unit, configured to calculate a failure rate of the working component according to a failure graph of the working component;
the model building unit is used for building a reliability model of the system according to the failure rate of the working part;
further comprises:
the second detection unit is used for detecting instant working data of the working component of the system to be tested when working after the model building unit builds a reliability model of the system according to the failure rate of the working component;
the first acquisition unit is used for inputting instant working data of the working parts of the system to be tested when working into the reliability model to obtain the reliability coefficient of the system to be tested;
further comprises:
the second calculation unit is used for calculating the bearing capacity of the working component according to the failure curve graph of the working component after the second detection unit detects the instant working data of the working component of the system to be detected when the working component works;
the second acquisition unit is used for acquiring the total load of the system to be tested;
the first obtaining unit is specifically configured to analyze a relationship between a bearing capacity of the working component and a total load of the system to be tested, and input instant working data of the working component of the system to be tested when working into the reliability model to obtain a reliability coefficient of the system to be tested.
4. The apparatus of claim 3, wherein the first computing unit comprises:
the first statistics module is used for counting the total number of the working parts and the total working time according to the failure curve graph of the working parts;
the second statistics module is used for counting the number of the invalid working parts and the invalid time of each invalid working part according to the invalid graph of the working parts;
the calculation module is used for calculating a formula according to the failure rate
Calculating the failure rate of the working part; wherein λ (t) represents failure rate, Δn (t) represents the number of failed working components, Δ (t) represents total working time of the working components, N represents the total number of the working components, ni represents failed working components, and ti represents failure time of failed working components ni. />
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108388202A (en) * | 2018-04-13 | 2018-08-10 | 上海理工大学 | Cnc ReliabilityintelligeNetwork Network predictor method based on history run fault data |
| CN109492254A (en) * | 2018-10-11 | 2019-03-19 | 西北工业大学 | Systems reliability analysis method based on interval model |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060212343A1 (en) * | 2005-03-18 | 2006-09-21 | Research In Motion Limited | Methods relating to reliability in product design and process engineering |
| US20070226546A1 (en) * | 2005-12-22 | 2007-09-27 | Lucent Technologies Inc. | Method for determining field software reliability metrics |
| ATE504871T1 (en) * | 2007-02-08 | 2011-04-15 | Siemens Ag | METHOD AND SYSTEM FOR DETERMINING RELIABILITY PARAMETERS OF A TECHNICAL SYSTEM |
| KR101543303B1 (en) * | 2013-07-22 | 2015-08-11 | 한양대학교 산학협력단 | Reliability Evaluation of Power System Considering Reliability Model of Demand Response |
| CN106502678A (en) * | 2016-10-30 | 2017-03-15 | 合肥微匠信息科技有限公司 | A kind of software development process reliability pre-detection method |
| CN108629082A (en) * | 2018-03-30 | 2018-10-09 | 北京半导体专用设备研究所（中国电子科技集团公司第四十五研究所） | system reliability modeling method and device |
| CN109598047A (en) * | 2018-11-26 | 2019-04-09 | 国家电网公司 | A kind of phase in transformer equipment longevity prediction technique and system |
| CN109635001B (en) * | 2018-11-26 | 2021-07-09 | 苏州热工研究院有限公司 | Product reliability improving method and system based on equipment failure data analysis |
-
2019
- 2019-07-17 CN CN201910646349.5A patent/CN110532116B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108388202A (en) * | 2018-04-13 | 2018-08-10 | 上海理工大学 | Cnc ReliabilityintelligeNetwork Network predictor method based on history run fault data |
| CN109492254A (en) * | 2018-10-11 | 2019-03-19 | 西北工业大学 | Systems reliability analysis method based on interval model |
Non-Patent Citations (1)
| Title |
|---|
| 具有"浴盆"型失效率变化规律的产品寿命概率分布模型;王正;王增全;谢里阳;;机械工程学报;第51卷(第24期);第193-200页 * |
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