[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Wachla et al., 2015 - Google Patents

A method of leakage location in water distribution networks using artificial neuro-fuzzy system

Wachla et al., 2015

Document ID
4556411981731602636
Author
Wachla D
Przystalka P
Moczulski W
Publication year
Publication venue
IFAC-PapersOnLine

External Links

Snippet

The paper deals with a method to locate uncontrolled leaks in water distribution networks. The idea of the method is based on discretization of the water supply system to the predefined areas and then identifying an approximate location where a leakage can occur …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • G05B23/0243Electric 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024Quantitative 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00Systems involving the use of models or simulators of said systems
    • G05B17/02Systems involving the use of models or simulators of said systems electric
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks

Similar Documents

Publication Publication Date Title
Wachla et al. A method of leakage location in water distribution networks using artificial neuro-fuzzy system
Zhao et al. Remaining useful life prediction of aircraft engine based on degradation pattern learning
Chen et al. Prediction interval estimation of aeroengine remaining useful life based on bidirectional long short-term memory network
Ayodeji et al. Knowledge base operator support system for nuclear power plant fault diagnosis
He et al. A fuzzy TOPSIS and rough set based approach for mechanism analysis of product infant failure
Quiñones-Grueiro et al. Robust leak localization in water distribution networks using computational intelligence
da Silva et al. A new methodology for multiple incipient fault diagnosis in transmission lines using QTA and Naïve Bayes classifier
Orchard et al. A particle filtering-based framework for real-time fault diagnosis and failure prognosis in a turbine engine
Hanachi et al. Hybrid sequential fault estimation for multi-mode diagnosis of gas turbine engines
Montazeri-Gh et al. Gas path component fault diagnosis of an industrial gas turbine under different load condition using online sequential extreme learning machine
Garcia Improving heat exchanger supervision using neural networks and rule based techniques
Fritz et al. Fault diagnosis in structural health monitoring systems using signal processing and machine learning techniques
Jiang et al. Remaining useful life prediction of rolling bearings based on Bayesian neural network and uncertainty quantification
Moczulski et al. A methodology of leakage detection and location in water distribution networks—The case study
Calderano et al. An enhanced aircraft engine gas path diagnostic method based on upper and lower singleton type-2 fuzzy logic system
Sharma et al. A review of modeling and data mining techniques applied for analyzing steel bridges
Mazzuto et al. Health Indicator for Predictive Maintenance Based on Fuzzy Cognitive Maps, Grey Wolf, and K‐Nearest Neighbors Algorithms
Dang et al. seq2graph: Discovering dynamic non-linear dependencies from multivariate time series
Osigwe et al. Integrated gas turbine system diagnostics: components and sensor faults quantification using artificial neural networks
Kim et al. Improved reliability-based decision support methodology applicable in system-level failure diagnosis and prognosis
Alozie et al. An adaptive model-based framework for prognostics of gas path faults in aircraft gas turbine engines
Moczulski et al. SysDetLok-a leakage detection and localization system for water distribution networks
Fernandes et al. A new model to prevent failures in gas turbine engines based on TSFRESH, self-organized direction aware data partitioning algorithm and machine learning techniques
Shahzad Artificial neural network for transient stability assessment: A review
Sayar et al. Real-time prediction of electricity distribution network status using artificial neural network model: A case study in Salihli (Manisa, Turkey)