JP6996794B2 - 回転機器の自動故障診断・予後診断システムおよび方法 - Google Patents
回転機器の自動故障診断・予後診断システムおよび方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
- G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
- G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- Artificial Intelligence (AREA)
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- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Software Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
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- Biomedical Technology (AREA)
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- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medical Informatics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201762562365P | 2017-09-23 | 2017-09-23 | |
| US62/562,365 | 2017-09-23 | ||
| US15/862,146 US11188065B2 (en) | 2017-09-23 | 2018-01-04 | System and method for automated fault diagnosis and prognosis for rotating equipment |
| US15/862,146 | 2018-01-04 | ||
| PCT/CA2018/000177 WO2019056087A1 (en) | 2017-09-23 | 2018-09-21 | SYSTEM AND METHOD FOR AUTOMATED MALFUNCTION DIAGNOSIS AND PROGNOSIS FOR ROTARY EQUIPMENT |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2020534550A JP2020534550A (ja) | 2020-11-26 |
| JP2020534550A5 JP2020534550A5 (cg-RX-API-DMAC7.html) | 2021-10-28 |
| JP6996794B2 true JP6996794B2 (ja) | 2022-01-17 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020537813A Active JP6996794B2 (ja) | 2017-09-23 | 2018-09-21 | 回転機器の自動故障診断・予後診断システムおよび方法 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US11188065B2 (cg-RX-API-DMAC7.html) |
| EP (1) | EP3685137B1 (cg-RX-API-DMAC7.html) |
| JP (1) | JP6996794B2 (cg-RX-API-DMAC7.html) |
| CN (1) | CN111356910B (cg-RX-API-DMAC7.html) |
| WO (1) | WO2019056087A1 (cg-RX-API-DMAC7.html) |
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| AU2019244842B2 (en) * | 2018-03-28 | 2024-03-07 | L&T Technology Services Limited | System and method for monitoring health and predicting failure of an electro-mechanical machine |
| US11257001B2 (en) * | 2018-10-09 | 2022-02-22 | International Business Machines Corporation | Prediction model enhancement |
| CN109977920B (zh) * | 2019-04-11 | 2022-06-07 | 福州大学 | 基于时频谱图及卷积神经网络的水轮机组故障诊断方法 |
| CN110031226A (zh) * | 2019-04-12 | 2019-07-19 | 佛山科学技术学院 | 一种轴承故障的诊断方法及装置 |
| US20200341444A1 (en) * | 2019-04-24 | 2020-10-29 | Rob Dusseault | Systems and methods for wireless monitoring and control of machinery |
| CN110188485B (zh) * | 2019-06-03 | 2020-08-25 | 安徽理工大学 | 一种滚动轴承动态性能劣化趋势自适应获取方法 |
| CN110160775A (zh) * | 2019-06-04 | 2019-08-23 | 昆明理工大学 | 一种基于振动信号分析的高压隔膜泵单向阀故障诊断方法 |
| CN110287853B (zh) * | 2019-06-20 | 2021-02-09 | 清华大学 | 一种基于小波分解的暂态信号去噪方法 |
| CN110160791B (zh) * | 2019-06-27 | 2021-03-23 | 郑州轻工业学院 | 基于小波-谱峭度的感应电机轴承故障诊断系统及诊断方法 |
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| CN110458071B (zh) * | 2019-08-01 | 2020-12-15 | 北京邮电大学 | 一种基于dwt-dfpa-gbdt的光纤振动信号特征提取与分类方法 |
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| EP3685137C0 (en) | 2023-12-20 |
| WO2019056087A1 (en) | 2019-03-28 |
| EP3685137A4 (en) | 2021-06-30 |
| CN111356910B (zh) | 2022-04-08 |
| EP3685137B1 (en) | 2023-12-20 |
| EP3685137A1 (en) | 2020-07-29 |
| JP2020534550A (ja) | 2020-11-26 |
| US11188065B2 (en) | 2021-11-30 |
| CN111356910A (zh) | 2020-06-30 |
| US20190095781A1 (en) | 2019-03-28 |
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