Behravan et al., 2021 - Google Patents
Fault diagnosis of DCV and heating systems based on causal relation in fuzzy bayesian belief networks using relation direction probabilitiesBehravan et al., 2021
View HTML- Document ID
- 14967061490258706610
- Author
- Behravan A
- Kiamanesh B
- Obermaisser R
- Publication year
- Publication venue
- Energies
External Links
Snippet
The state-of-the-art provides data-driven and knowledge-driven diagnostic methods. Each category has its strengths and shortcomings. The knowledge-driven methods rely mainly on expert knowledge and resemble the diagnostic thinking of domain experts with a high …
- 238000003745 diagnosis 0 title abstract description 118
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- 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
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Kang et al. | Remaining useful life (RUL) prediction of equipment in production lines using artificial neural networks | |
Mattera et al. | A method for fault detection and diagnostics in ventilation units using virtual sensors | |
Dey et al. | A case study based approach for remote fault detection using multi-level machine learning in a smart building | |
Tun et al. | Hybrid random forest and support vector machine modeling for HVAC fault detection and diagnosis | |
Calabrese et al. | Unsupervised fault detection and prediction of remaining useful life for online prognostic health management of mechanical systems | |
Melgaard et al. | Fault detection and diagnosis encyclopedia for building systems: a systematic review | |
Hodavand et al. | Digital twin for fault detection and diagnosis of building operations: a systematic review | |
Gálvez et al. | Fault detection and RUL estimation for railway HVAC systems using a hybrid model-based approach | |
Andrade et al. | Development of a methodology using artificial neural network in the detection and diagnosis of faults for pneumatic control valves | |
Chen et al. | Development of a unified taxonomy for hvac system faults | |
Zaitseva et al. | Application of the Structure Function in the Evaluation of the Human Factor in Healthcare | |
Meas et al. | Explainability and transparency of classifiers for air-handling unit faults using explainable artificial intelligence (XAI) | |
Matetić et al. | A review of data-driven approaches and techniques for fault detection and diagnosis in HVAC systems | |
Wang et al. | Remaining useful life prediction of aircraft turbofan engine based on random forest feature selection and multi-layer perceptron | |
Nelson et al. | Machine learning methods for automated fault detection and diagnostics in building systems—A review | |
Hosseini Gourabpasi et al. | Knowledge Discovery by Analyzing the State of the Art of Data-Driven Fault Detection and Diagnostics of Building HVAC | |
Aguilar et al. | An autonomic cycle of data analysis tasks for the supervision of HVAC systems of smart building | |
Zhu et al. | An Effective Fault Detection Method for HVAC Systems Using the LSTM-SVDD Algorithm | |
Martinez-Viol et al. | Semi-supervised transfer learning methodology for fault detection and diagnosis in air-handling units | |
Bezyan et al. | Detection and diagnosis of dependent faults that trigger false symptoms of heating and mechanical ventilation systems using combined machine learning and rule-based techniques | |
Youness et al. | An explainable artificial intelligence approach for remaining useful life prediction | |
Haruehansapong et al. | Deep learning-driven automated fault detection and diagnostics based on a contextual environment: a case study of HVAC system | |
Aliyu et al. | Prognostic health management of pumps using artificial intelligence in the oil and gas sector: a review | |
Behravan et al. | Fault diagnosis of DCV and heating systems based on causal relation in fuzzy bayesian belief networks using relation direction probabilities | |
Dou et al. | Detection and diagnosis of multiple-dependent faults (MDFDD) of water-cooled centrifugal chillers using grey-box model-based method |