CN105631199A - Data drive based fault diagnosis algorithm - Google Patents
Data drive based fault diagnosis algorithm Download PDFInfo
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- CN105631199A CN105631199A CN201510977065.6A CN201510977065A CN105631199A CN 105631199 A CN105631199 A CN 105631199A CN 201510977065 A CN201510977065 A CN 201510977065A CN 105631199 A CN105631199 A CN 105631199A
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- data
- fault diagnosis
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- diagnosis algorithm
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Abstract
The present invention discloses a data drive based fault diagnosis algorithm. The data drive based fault diagnosis algorithm comprises the following steps: 1) importing a to-be-diagnosed object into a computer, and performing a Fourier transformation on the to-be-diagnosed object by means of a Fourier algorithm, so as to acquire fault data of the to-be-diagnosed object; 2) performing region division on the fault data, so as to obtain a plurality of sub-regions; 3) performing data scanning on each sub-region separately, so as to acquire abnormal data information that is contained by each sub-region; and 4) performing secondary scanning on the abnormal data information, so as to acquire a fault diagnosis result. By adopting a novel algorithm structure design, the algorithm provided by the present invention improves accuracy and applicability of fault diagnosis algorithms.
Description
Technical field
The present invention relates to algorithm field, specifically, be related specifically to a kind of fault diagnosis algorithm based on data-driven.
Background technology
Along with the progress of industrial technology, the scale of modern industry production process is increasing, and complexity is also more and more higher. Complex process device, once break down, not only can cause huge economic loss, and it would furthermore be possible to cause casualties and the destruction to ecological environment. Fault diagnosis technology can by the running status of monitor production process, to the reason or the character that cause that systemic-function is abnormal, position and degree that fault occurs judge, and predict the development trend of malfunction, the countermeasure of Failure elimination is proposed, thus ensureing the safety of production and improving product quality.
Summary of the invention
Present invention aims to deficiency of the prior art, it is provided that a kind of fault diagnosis algorithm based on data-driven, to solve the problems referred to above.
Technical problem solved by the invention can realize by the following technical solutions:
A kind of fault diagnosis algorithm based on data-driven, comprises the steps:
1) will treat that diagnosis target imports computer, and treat diagnosis target by fourier algorithm and carry out Fourier transform, to obtain the fault data treating diagnosis target;
2) described fault data is carried out region division, obtain some subregions;
3) respectively described subregion is carried out data scanning, with the abnormal data information that acquisition wherein comprises;
4) described abnormal data information is carried out rescan, to obtain fault diagnosis result.
Further, described fault diagnosis algorithm is based on JAVA, C Plus Plus.
Further, described fault data is divided into 5 sub regions.
Compared with prior art, beneficial effects of the present invention is as follows:
By adopting brand-new algorithm structure to design, improve accuracy and the wide usage of fault diagnosis algorithm.
Detailed description of the invention
For the technological means making the present invention realize, creation characteristic, reach purpose and effect and be easy to understand, below in conjunction with detailed description of the invention, the present invention is expanded on further.
A kind of fault diagnosis algorithm based on data-driven, comprises the steps:
1) will treat that diagnosis target imports computer, and treat diagnosis target by fourier algorithm and carry out Fourier transform, to obtain the fault data treating diagnosis target;
2) described fault data is carried out region division, obtain some subregions;
3) respectively described subregion is carried out data scanning, with the abnormal data information that acquisition wherein comprises;
4) described abnormal data information is carried out rescan, to obtain fault diagnosis result.
Described fault diagnosis algorithm is based on JAVA, C Plus Plus.
Described fault data is divided into 5 sub regions. By adopting above-mentioned technology, further increase accuracy and the wide usage of fault diagnosis algorithm of the present invention.
The ultimate principle of the present invention and principal character and advantages of the present invention have more than been shown and described. Skilled person will appreciate that of the industry; the present invention is not restricted to the described embodiments; described in above-described embodiment and description is that principles of the invention is described; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements both fall within the claimed scope of the invention. Claimed scope is defined by appending claims and equivalent thereof.
Claims (3)
1. the fault diagnosis algorithm based on data-driven, it is characterised in that comprise the steps:
1) will treat that diagnosis target imports computer, and treat diagnosis target by fourier algorithm and carry out Fourier transform, to obtain the fault data treating diagnosis target;
2) described fault data is carried out region division, obtain some subregions;
3) respectively described subregion is carried out data scanning, with the abnormal data information that acquisition wherein comprises;
4) described abnormal data information is carried out rescan, to obtain fault diagnosis result.
2. a kind of fault diagnosis algorithm based on data-driven according to claim 1, it is characterised in that described fault diagnosis algorithm is based on JAVA, C Plus Plus.
3. a kind of fault diagnosis algorithm based on data-driven according to claim 1, it is characterised in that described fault data is divided into 5 sub regions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510977065.6A CN105631199A (en) | 2015-12-23 | 2015-12-23 | Data drive based fault diagnosis algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510977065.6A CN105631199A (en) | 2015-12-23 | 2015-12-23 | Data drive based fault diagnosis algorithm |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105631199A true CN105631199A (en) | 2016-06-01 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
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| CN201510977065.6A Pending CN105631199A (en) | 2015-12-23 | 2015-12-23 | Data drive based fault diagnosis algorithm |
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| CN (1) | CN105631199A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107689059A (en) * | 2017-06-30 | 2018-02-13 | 北京金风科创风电设备有限公司 | The abnormal recognition methods of wind generating set pitch control and device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050160324A1 (en) * | 2003-12-24 | 2005-07-21 | The Boeing Company, A Delaware Corporation | Automatic generation of baysian diagnostics from fault trees |
| CN104991547A (en) * | 2015-05-19 | 2015-10-21 | 重庆大学 | Multi-fault diagnosis method driven by practical fault symptom data |
-
2015
- 2015-12-23 CN CN201510977065.6A patent/CN105631199A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050160324A1 (en) * | 2003-12-24 | 2005-07-21 | The Boeing Company, A Delaware Corporation | Automatic generation of baysian diagnostics from fault trees |
| CN104991547A (en) * | 2015-05-19 | 2015-10-21 | 重庆大学 | Multi-fault diagnosis method driven by practical fault symptom data |
Non-Patent Citations (2)
| Title |
|---|
| 刘明等: "风力发电机组故障振动信号特征向量的提取", 《电力学报》 * |
| 周文斌等: "基于灰色理论的修复性维修器材需求的确定", 《四川兵工学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107689059A (en) * | 2017-06-30 | 2018-02-13 | 北京金风科创风电设备有限公司 | The abnormal recognition methods of wind generating set pitch control and device |
| CN107689059B (en) * | 2017-06-30 | 2020-01-31 | 北京金风科创风电设备有限公司 | Method and device for identifying abnormal variable pitch of wind generating set |
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| WD01 | Invention patent application deemed withdrawn after publication | ||
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Application publication date: 20160601 |