[go: up one dir, main page]

SG10201610116PA - Method and system for machine failure prediction - Google Patents

Method and system for machine failure prediction

Info

Publication number
SG10201610116PA
SG10201610116PA SG10201610116PA SG10201610116PA SG10201610116PA SG 10201610116P A SG10201610116P A SG 10201610116PA SG 10201610116P A SG10201610116P A SG 10201610116PA SG 10201610116P A SG10201610116P A SG 10201610116PA SG 10201610116P A SG10201610116P A SG 10201610116PA
Authority
SG
Singapore
Prior art keywords
weight range
basic
memory depth
machine failure
basic memory
Prior art date
Application number
SG10201610116PA
Inventor
Bhandary Chiranjib
Original Assignee
Avanseus Holdings Pte Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Avanseus Holdings Pte Ltd filed Critical Avanseus Holdings Pte Ltd
Publication of SG10201610116PA publication Critical patent/SG10201610116PA/en

Links

Classifications

    • 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
    • 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
    • G05B23/0243—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 model based detection method, e.g. first-principles knowledge model
    • G05B23/0254—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 model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • 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
    • G06N3/09—Supervised learning

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Physics (AREA)
  • General Physics & Mathematics (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Automation & Control Theory (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Debugging And Monitoring (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Abstract

METHOD AND SYSTEM FOR MACHINE FAILURE PREDICTION Embodiments of the invention provide a method and system for machine failure prediction. The method comprises: identifying a plurality of basic memory depth values based on a machine failure history; ascertaining a basic weight range for each of the plurality of basic memory depth values according to a pre-stored table including a plurality of mappings each mapping between a basic memory depth value and a basic weight range, or a predetermined formula for calculating the basic weight range based on the corresponding basic memory depth value; 10 ascertaining a composite initial weight range by calculating an average weight range of the ascertained basic weight range for each identified basic memory depth value; generating initial weights based on the composite initial weight range; and predicting a future failure using a Back Propagation Through Time (BPTT) trained Recurrent Neural Network (RNN) based on the generated initial 15 weights. (Figure 3) 20 32
SG10201610116PA 2016-11-03 2016-12-02 Method and system for machine failure prediction SG10201610116PA (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IN201611037626 2016-11-03

Publications (1)

Publication Number Publication Date
SG10201610116PA true SG10201610116PA (en) 2018-06-28

Family

ID=62021594

Family Applications (1)

Application Number Title Priority Date Filing Date
SG10201610116PA SG10201610116PA (en) 2016-11-03 2016-12-02 Method and system for machine failure prediction

Country Status (2)

Country Link
US (1) US10909458B2 (en)
SG (1) SG10201610116PA (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240385917A1 (en) * 2023-05-17 2024-11-21 Bank Of America Corporation System and Method for Multi Image Matching for Outage Prediction, Prevention, and Mitigation for Technology Infrastructure Using Hybrid Deep Learning
US12373271B2 (en) 2023-05-25 2025-07-29 Bank Of America Corporation System and method for matching multiple featureless images across a time series for outage prediction and prevention

Families Citing this family (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11494654B2 (en) * 2016-11-03 2022-11-08 Avanseus Holdings Pte. Ltd. Method for machine failure prediction using memory depth values
JP7221644B2 (en) * 2018-10-18 2023-02-14 株式会社日立製作所 Equipment failure diagnosis support system and equipment failure diagnosis support method
CN109583124B (en) * 2018-12-13 2023-02-03 北京计算机技术及应用研究所 HMM fault prediction system based on ADRC
CN111538914B (en) * 2019-02-01 2023-05-30 阿里巴巴集团控股有限公司 Address information processing method and device
EP3948708A1 (en) 2019-03-23 2022-02-09 British Telecommunications public limited company Automated device maintenance
CN109978275B (en) * 2019-04-03 2021-03-12 中南大学 Extreme strong wind speed prediction method and system based on mixed CFD and deep learning
CN110186570B (en) * 2019-05-16 2021-01-15 西安理工大学 Additive manufacturing laser 3D printing temperature gradient detection method
WO2020249429A1 (en) 2019-06-10 2020-12-17 Koninklijke Philips N.V. System and method to predict parts dependencies for replacement based on the heterogenous subsystem analysis
CN110555273B (en) * 2019-09-05 2023-03-24 苏州大学 Bearing life prediction method based on hidden Markov model and transfer learning
CN110817694B (en) * 2019-10-25 2020-08-28 湖南中联重科智能技术有限公司 Load hoisting weight calculation method and device and storage medium
KR102806266B1 (en) * 2019-11-18 2025-05-12 삼성전자주식회사 Storage device with artificial intelligence and storage system including the same
US11763160B2 (en) * 2020-01-16 2023-09-19 Avanseus Holdings Pte. Ltd. Machine learning method and system for solving a prediction problem
CN111476347B (en) * 2020-03-04 2023-03-24 国网安徽省电力有限公司检修分公司 Maintenance method, system and storage medium of phase modulator based on multiple factors
US20210356361A1 (en) * 2020-05-15 2021-11-18 Deere & Company Fault detection technique for a bearing

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5448681A (en) * 1992-03-27 1995-09-05 National Semiconductor Corporation Intelligent controller with neural network and reinforcement learning
US6708160B1 (en) * 1999-04-06 2004-03-16 Paul J. Werbos Object nets
US20030065525A1 (en) * 2001-10-01 2003-04-03 Daniella Giacchetti Systems and methods for providing beauty guidance
CN107408230B (en) * 2015-03-11 2021-06-01 西门子工业公司 System and method for automated building diagnostics in a building management system
US9336482B1 (en) * 2015-07-27 2016-05-10 Google Inc. Predicting likelihoods of conditions being satisfied using recurrent neural networks
US10387768B2 (en) * 2016-08-09 2019-08-20 Palo Alto Research Center Incorporated Enhanced restricted boltzmann machine with prognosibility regularization for prognostics and health assessment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240385917A1 (en) * 2023-05-17 2024-11-21 Bank Of America Corporation System and Method for Multi Image Matching for Outage Prediction, Prevention, and Mitigation for Technology Infrastructure Using Hybrid Deep Learning
US12373271B2 (en) 2023-05-25 2025-07-29 Bank Of America Corporation System and method for matching multiple featureless images across a time series for outage prediction and prevention

Also Published As

Publication number Publication date
US10909458B2 (en) 2021-02-02
US20180121793A1 (en) 2018-05-03

Similar Documents

Publication Publication Date Title
SG10201610116PA (en) Method and system for machine failure prediction
PH12019502106A1 (en) Measurement reporting enhancements in beam based systems
PH12017501080A1 (en) User maintenance system and method
CY1123641T1 (en) METHODS AND APPARATUS FOR A DISTRIBUTED DATABASE OVER A NETWORK
ZA202007714B (en) System and method for real time prediction of water level and hazard level of a dam
WO2016094182A3 (en) Network device predictive modeling
WO2018030422A3 (en) Diagnosis device, learning device, and diagnosis system
GB2561479A (en) Generating an earth model from spatial correlations of equivalent earth models
SG10201801831QA (en) Method And Apparatus For Predicting Occurrence Of An Event To Facilitate Asset Maintenance
HK1257881A1 (en) Activity capability monitoring
WO2015127110A3 (en) Event-based inference and learning for stochastic spiking bayesian networks
GB2572293A (en) Reactivity mapping
AR109632A1 (en) SYSTEMS FOR DETERMINING AGRONOMIC RESULTS FOR A CULTIVABLE REGION AND RELATED METHODS AND APPLIANCES
PH12019000467A1 (en) System and method for training neural networks
MX359360B (en) Resource production forecasting.
EP3462315A3 (en) Systems and methods for service mapping
GB2557054A (en) Determining sources of erroneous downhole predictions
GR20140100091A (en) Acceptance of effective crowdsourcing contributors - high-quality contributions
BR112017014437A2 (en) wellbore acoustic imaging devices and methods
GB2543183A (en) Improvements related to forecasting systems
EP3671575A3 (en) Neural network processing method and apparatus based on nested bit representation
PH12017502421A1 (en) Method and device for service processing
IN2015CH01656A (en)
SG10201705666YA (en) Method and system for machine failure prediction
SG10201902788TA (en) Method for evaluating the conformity of a tracking system to a set of requirements and associated devices