A real-time intelligent multiple fault diagnostic system

Bae, Young-Soo; Lee, Seok-Hee; Kim, Ho-Chan; Lee, Byung-Ryong; Jang, Jin Seok; Lee, Jay

doi:10.1007/s00170-005-2614-0

Cited by 25 publications

(8 citation statements)

References 10 publications

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“…It can be used both as a predictive model for predicting failure (in the short term) or as a diagnostic model once the failure as been observed. A special-purpose web interface [36] for the Linear Axis localcomponent model was developed to support the Test-step of the development process 3 . This has served as an important tool in the Test and Analysis-steps as the component supplier have been able to interact with the model at her own convenience.…”

Section: E Analysis and Deploymentioning

confidence: 99%

“…On the other hand, data driven approaches with little modelling requirements have also been investigated. These include artificial neural networks [3], fuzzy logic [4] and Bayesian networks [5], [6] among others. The models here do not necessarily capture precise nominal system behaviour as in model-based approaches, but rather a general understanding of how the system works.…”

Section: Introductionmentioning

confidence: 99%

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A methodology for developing local smart diagnostic models using expert knowledge

Madsen

Søndberg-Jeppesen

Lohse

et al. 2015

2015 IEEE 13th International Conference on Industrial Informatics (INDIN)

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Abstract-This paper describes an innovative modular component-based modelling approach for diagnostics and condition-monitoring of manufacturing equipment. The approach is based on the use of object-oriented Bayesian networks, which supports a natural decomposition of a large and complex system into a set of less complex components. The methodology consists of six steps supporting the development process: Begin, Design, Implement, Test, Analyse, and Deploy. The process is iterative and the steps should be repeated until a satisfactory model has been achieved. The paper describes the details of the methodology as well as illustrates the use of the componentbased modelling approach on a linear axis used in manufacturing. This application demonstrates the power and flexibility of the approach for diagnostics and condition-monitoring and shows a significant potential of the approach for modular componentbased modelling in manufacturing and other domains.

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Section: E Analysis and Deploymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A methodology for developing local smart diagnostic models using expert knowledge

Madsen

Søndberg-Jeppesen

Lohse

et al. 2015

2015 IEEE 13th International Conference on Industrial Informatics (INDIN)

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“…In specific fault diagnosis process, manmach ine interactive diagnosis is adopted to be the preliminary way, meanwhile with automatic diagnosis combined. Therefore, it can guide operation personnel to rapidly processing problems during locomotive operation process, provide correct ideas for fau lt analysis and processing and then improve the practicability of diagnostic system [5] .…”

Section: B Interface Design For Data Acquisition Module and Powerlinmentioning

confidence: 99%

Design of Portable Fault Diagnosis Device for Electric Locomotive

Cong¹,

Zheng²,

Tian³

et al. 2012

2012 Second International Conference on Instrumentation, Measurement, Computer, Communication and Control

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A portable fault diagnosis device for electric locomotive, which is online operational, is introduced in this paper. It realizes fault analysis and diagnosis, fault information storage and fault treatment method prompting for locomotive. Both software and hardware structure of this device is elaborated in this paper, especially the realization of fault diagnosis methods, data acquisition and communication. The device can effectively improve the speed of fault judgment and process, meanwhile reduce the performance impact of different kinds of fault, therefore, meets the actual demand of locomotive operation and the development trend of automation.

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“…In contrast to traditional fault diagnostic systems based on sequential fault diagnosis, which tend to be rather slow and incapable in the case of fast fault propagation, agent technology is regarded as a promising approach to achieve fault diagnosis in a control system [5,6]. Various approaches based on agent technology have been presented for achieving intelligent systems with diagnosis capabilities.…”

Section: Introductionmentioning

confidence: 99%

“…Various approaches based on agent technology have been presented for achieving intelligent systems with diagnosis capabilities. Bae et al developed an intelligent real-time fault diagnostic system based on a hierarchical artificial neural network [5]. Davidson et al presented a multi-agent system for the analysis of data from a SCADA system [7] and Tichý et al introduced the Autonomous Cooperative System (ACS) architecture for distributed industrial control applications [8].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Layer Approach for Failure Detection in a Manufacturing System Based on Automation Agents

Lepuschitz

Jirkovský

Kadera

et al. 2012

2012 Ninth International Conference on Information Technology - New Generations

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Automatically detecting component failures and unexpected behaviors is an essential service for achieving fault-tolerant robust manufacturing systems. The application of a multiagent system is regarded as a promising approach for designing complex systems such as manufacturing systems due to its distributed nature. In this paper we present an agent-based control system with diagnostic capabilities on several layers for a pallet transport system. Local diagnostic tasks for detecting failures are performed by the automation agents each controlling one physical component such as a diverter. In order to observe the correct behavior of the components on a system-wide scale, an approach based on Hidden Markov Models linked to the agents is employed.

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A real-time intelligent multiple fault diagnostic system

Cited by 25 publications

References 10 publications

A methodology for developing local smart diagnostic models using expert knowledge

A methodology for developing local smart diagnostic models using expert knowledge

Design of Portable Fault Diagnosis Device for Electric Locomotive

A Multi-Layer Approach for Failure Detection in a Manufacturing System Based on Automation Agents

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