CN113252218A - Insulator surface stress prediction method and prediction device - Google Patents
Insulator surface stress prediction method and prediction device Download PDFInfo
- Publication number
- CN113252218A CN113252218A CN202110518748.0A CN202110518748A CN113252218A CN 113252218 A CN113252218 A CN 113252218A CN 202110518748 A CN202110518748 A CN 202110518748A CN 113252218 A CN113252218 A CN 113252218A
- Authority
- CN
- China
- Prior art keywords
- neural network
- stress
- insulator
- value
- working conditions
- 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.)
- Granted
Links
- 239000012212 insulator Substances 0.000 title claims abstract description 80
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000013528 artificial neural network Methods 0.000 claims abstract description 63
- 238000001514 detection method Methods 0.000 claims description 21
- 230000005540 biological transmission Effects 0.000 claims description 15
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 claims 2
- 238000012549 training Methods 0.000 description 15
- 230000006870 function Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000007789 sealing Methods 0.000 description 3
- 239000004020 conductor Substances 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 210000002569 neuron Anatomy 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 239000000853 adhesive Substances 0.000 description 1
- 238000004026 adhesive bonding Methods 0.000 description 1
- 230000001070 adhesive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000003822 epoxy resin Substances 0.000 description 1
- 238000009422 external insulation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 229920000647 polyepoxide Polymers 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/25—Measuring force or stress, in general using wave or particle radiation, e.g. X-rays, microwaves, neutrons
- G01L1/255—Measuring force or stress, in general using wave or particle radiation, e.g. X-rays, microwaves, neutrons using acoustic waves, or acoustic emission
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Toxicology (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
本发明公开了一种绝缘子表面应力预测方法及预测装置,其中方法包括:确定绝缘子的工况,将工况分为正常工况以及螺栓松动时的工况;采集绝缘子在正常工况下的超声波信号值,以及在螺栓不同松动工况下的超声波信号值和应力值;将正常工况下和螺栓松动工况下的超声波信号能量差值以及应力值作为BP神经网络的输入值及输出值,对BP神经网络进行训练,得到训练好的BP神经网络;对所述BP神经网络的精度进行验证;本发明实现对在线盆式绝缘子的表面应力预测。
The invention discloses a method for predicting surface stress of an insulator and a prediction device, wherein the method comprises: determining the working conditions of the insulator, dividing the working conditions into normal working conditions and working conditions when bolts are loose; collecting ultrasonic waves of the insulator under the normal working conditions Signal value, as well as ultrasonic signal value and stress value under different bolt loosening conditions; the ultrasonic signal energy difference and stress value under normal working condition and bolt loosening condition are used as the input value and output value of the BP neural network, The BP neural network is trained to obtain a trained BP neural network; the accuracy of the BP neural network is verified; the invention realizes the prediction of the surface stress of the online basin insulator.
Description
Claims (7)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110518748.0A CN113252218B (en) | 2021-05-12 | 2021-05-12 | Insulator surface stress prediction method and prediction device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110518748.0A CN113252218B (en) | 2021-05-12 | 2021-05-12 | Insulator surface stress prediction method and prediction device |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113252218A true CN113252218A (en) | 2021-08-13 |
CN113252218B CN113252218B (en) | 2023-11-17 |
Family
ID=77223204
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110518748.0A Active CN113252218B (en) | 2021-05-12 | 2021-05-12 | Insulator surface stress prediction method and prediction device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113252218B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN119043543A (en) * | 2024-08-21 | 2024-11-29 | 南京林业大学 | Ultrasonic detection method and system for shaft force of cable clamp screw with consideration of uneven temperature and stress distribution |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2005119233A1 (en) * | 2004-06-01 | 2005-12-15 | Cantion A/S | Stress sensor with capture coating for detecting a target substance |
CN105005822A (en) * | 2015-06-26 | 2015-10-28 | 华能澜沧江水电股份有限公司 | Optimal step length and dynamic model selection based ultrahigh arch dam response prediction method |
CN105913122A (en) * | 2015-09-09 | 2016-08-31 | 广东技术师范学院 | Finishing axle sleeve surface residual stress prediction method based on hybrid Taguchi genetic algorithm |
CN106405352A (en) * | 2016-11-16 | 2017-02-15 | 国网河南省电力公司电力科学研究院 | Equivalent salt deposit density (ESDD) prediction and early warning system for power insulator surface contaminant |
CN108181562A (en) * | 2018-01-18 | 2018-06-19 | 福州大学 | Insulator breakdown diagnostic device and method based on Study On Reliability Estimation Method For Cold Standby Systems |
CN110207871A (en) * | 2018-02-28 | 2019-09-06 | 新疆金风科技股份有限公司 | Method, apparatus, storage medium and the system of the stress prediction of Wind turbines |
CN110672312A (en) * | 2019-10-12 | 2020-01-10 | 北京工业大学 | Method for predicting bolt residual clamping force based on BP neural network |
CN111948286A (en) * | 2020-08-10 | 2020-11-17 | 湖南大学 | A stress detection method, device and equipment based on ultrasonic and deep learning |
WO2021076575A1 (en) * | 2019-10-15 | 2021-04-22 | University Of Pittsburgh - Of The Commonwealth System Of Higher Education | Stress prediction based on neural network |
-
2021
- 2021-05-12 CN CN202110518748.0A patent/CN113252218B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2005119233A1 (en) * | 2004-06-01 | 2005-12-15 | Cantion A/S | Stress sensor with capture coating for detecting a target substance |
CN105005822A (en) * | 2015-06-26 | 2015-10-28 | 华能澜沧江水电股份有限公司 | Optimal step length and dynamic model selection based ultrahigh arch dam response prediction method |
CN105913122A (en) * | 2015-09-09 | 2016-08-31 | 广东技术师范学院 | Finishing axle sleeve surface residual stress prediction method based on hybrid Taguchi genetic algorithm |
CN106405352A (en) * | 2016-11-16 | 2017-02-15 | 国网河南省电力公司电力科学研究院 | Equivalent salt deposit density (ESDD) prediction and early warning system for power insulator surface contaminant |
CN108181562A (en) * | 2018-01-18 | 2018-06-19 | 福州大学 | Insulator breakdown diagnostic device and method based on Study On Reliability Estimation Method For Cold Standby Systems |
CN110207871A (en) * | 2018-02-28 | 2019-09-06 | 新疆金风科技股份有限公司 | Method, apparatus, storage medium and the system of the stress prediction of Wind turbines |
CN110672312A (en) * | 2019-10-12 | 2020-01-10 | 北京工业大学 | Method for predicting bolt residual clamping force based on BP neural network |
WO2021076575A1 (en) * | 2019-10-15 | 2021-04-22 | University Of Pittsburgh - Of The Commonwealth System Of Higher Education | Stress prediction based on neural network |
CN111948286A (en) * | 2020-08-10 | 2020-11-17 | 湖南大学 | A stress detection method, device and equipment based on ultrasonic and deep learning |
Non-Patent Citations (2)
Title |
---|
唐成顺等: "基于LSTM循环神经网络的汽轮机转子表面应力预测模型", 《中国电机工程学报》 * |
薛磊等: "基于SCADA数据和改进BP神经网络的塔筒应力预测", 《噪声与振动控制》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN119043543A (en) * | 2024-08-21 | 2024-11-29 | 南京林业大学 | Ultrasonic detection method and system for shaft force of cable clamp screw with consideration of uneven temperature and stress distribution |
Also Published As
Publication number | Publication date |
---|---|
CN113252218B (en) | 2023-11-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108413921A (en) | A kind of iron tower in power transmission line material deformation on-line monitoring system and monitoring method | |
CN107976307B (en) | An on-line monitoring device and monitoring method for the loosening of transmission line iron tower bolts | |
CN110285909B (en) | Method for calculating instantaneous cable force of cable-supported bridge based on synchronous compression transformation | |
CN104198929A (en) | Detection device and detection method for outdoor high voltage isolator | |
CN114323375B (en) | GIS basin-type insulator flange stress detection method and system | |
CN102422154A (en) | A structure damage detection system, equipment and structure damage detection method | |
CN113702778B (en) | A GIL arc discharge fault location method and system | |
CN110296802A (en) | Shaft tower bolt looseness method of discrimination based on vibrating speed sensors waveform acquisition | |
CN111474241A (en) | Method for evaluating latent fault factors existing in GIS structural state | |
CN115542099B (en) | Online GIS partial discharge detection method and device | |
CN112461358B (en) | Bridge modal parameter identification method based on instantaneous frequency of vehicle-bridge system | |
CN107976251A (en) | A kind of transmission pressure structure destroys on-line monitoring system and monitoring method | |
CN112556828A (en) | Transformer winding loosening fault detection method | |
CN107782478A (en) | Online pipe joint element erection stress detecting system and detection recognition method | |
CN110646119B (en) | A method for ultrasonic measurement of surface stress tensor of rolled metal materials | |
CN110596247A (en) | Ultrasonic structure health monitoring method in temperature change environment | |
CN113252218A (en) | Insulator surface stress prediction method and prediction device | |
CN118483508B (en) | Automobile wire harness performance detection system based on product production quality inspection | |
CN107340049A (en) | A kind of method and test device that the loosening of GIS sealing rings is judged based on vibratory drilling method | |
CN112285508B (en) | A localization method for partial discharge of high-voltage power cables | |
CN112444705B (en) | Regression correction method for wavelet transformation fault location | |
CN107036751B (en) | A flexible rope force calculation method for identifying vibration frequencies by weighted broadband peak search | |
CN115014603A (en) | An online stress detection system using ultrasonic longitudinal and transverse waves for fastening bolts of hydraulic turbine units | |
Daniel et al. | A Novel Hybrid Acquisition System for Industrial Condition Monitoring and Predictive Maintenance | |
CN119269936B (en) | Lissajous image feature-based silicon rubber composite insulator degradation state monitoring method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
TA01 | Transfer of patent application right | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20230902 Address after: No.6 Qingnian Road, Yingze Street, Yingze District, Taiyuan City, Shanxi Province, 030000 Applicant after: STATE GRID ELECTRIC POWER Research Institute OF SEPC Applicant after: Taiyuan University of Technology Address before: 030024 No. 79 West Main Street, Taiyuan, Shanxi, Yingze Applicant before: Taiyuan University of Technology |
|
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CB03 | Change of inventor or designer information | ||
CB03 | Change of inventor or designer information |
Inventor after: Song Jiancheng Inventor after: Jiao Guoxun Inventor after: Wang Wei Inventor after: Xu Yudong Inventor after: Zhang Jie Inventor after: Liu Hong Inventor after: Ge Jian Inventor after: Li Pengjiang Inventor after: Gao Jinwu Inventor before: Song Jiancheng Inventor before: Jiao Guoxun Inventor before: Ge Jian Inventor before: Li Pengjiang Inventor before: Gao Jinwu Inventor before: Zhang Jie |