Results 251 to 260 of about 36,327 (304)
Some of the next articles are maybe not open access.
Intelligent fault detection and diagnostics in solar plants
Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011This paper discusses fault detection and diagnostics in a solar power plant. After reviewing relevant work, description of a data acquisition system for solar plant monitoring is presented and the list of potential faults to be taken care of is given.
Andon Coleman, Janusz Zalewski
openaire +1 more source
Fault detection, diagnostics, and prognostics: software agent solutions
IEEE Electric Ship Technologies Symposium, 2005., 2005Fault diagnosis and prognosis are important tools for the reliability, availability and survivability of navy all-electric ships. Extending the fault detection and diagnosis into predictive maintenance increases the value of this technology. The traditional diagnosis can be viewed as a single diagnostic agent having a model of the whole system to be ...
null Li Liu, K.P. Logan, D.A. Cartes
openaire +1 more source
Fault Detection and Diagnostics Using Data Mining
2014The purpose of data mining is to find new knowledge from databases in which complexity or the amount of data has so far been prohibitively large for human observation alone. Self-Organizing Map (SOM) is a special type of Artificial Neural Networks (ANNs) used in clustering, visualization and abstraction.
Sun Chung, Dukki Chung
openaire +1 more source
Data Clustering and Prediction for Fault Detection and Diagnostics
1988 American Control Conference, 1988The characterization of a data cluster representing a certain process behavior is achieved by developing steady-state nonlinear modeling of one or more critical signals as a function of other process variables in the system. This prediction model is used to detect either sensor maloperation or process anomaly by comparing the prediction and measurement
B. R. Upadhyaya, G. Mathai, J. D. Green
openaire +1 more source
Creating an automated chiller fault detection and diagnostics tool using a data fault library
ISA Transactions, 2003Reliable, automated detection and diagnosis of abnormal behavior within vapor compression refrigeration cycle (VCRC) equipment is extremely desirable for equipment owners and operators. The specific type of VCRC equipment studied in this paper is a 70-ton helical rotary, air-cooled chiller.
Margaret B, Bailey, Jan F, Kreider
openaire +2 more sources
Robust fault detection and isolation via a diagnostic observer
International Journal of Robust and Nonlinear Control, 2000Considering fault isolation and observer design methodologies, the objective is to achieve multiple and simultaneous fault isolation capabilities along with robustness to structural uncertainties through the design of a single diagnostic observer. The present approach is based on a complete solution of the disturbance decoupled fault detection observer
Xiong, Yi, Saif, Mehrdad
openaire +2 more sources
Intelligent Fault Detection and Diagnostics
2017This chapter contains the last part of the research methodology. On the bases of the methods discussed in Chaps. 3 and 4, it develops the planned FDD system.
openaire +1 more source
Detection and modeling of acoustic emissions for fault diagnostics
Proceedings of 8th Workshop on Statistical Signal and Array Processing, 2002The formation of microcracks in a material creates propagating ultrasonic waves that are called acoustic emissions (AEs). These AEs provide an early warning to the onset of material failure. In practical cases, however, these AEs have to be detected at very low SNRs, amongst strong interference and random noise.
D. West +4 more
openaire +1 more source
Model Uncertainity, Fault Detection and Diagnostics
2017The previous chapter has explained the concepts behind NF based model identification and how it relates to other models and the design in the framework of OBFs. It was stated that a good nonlinear model can be developed from plant operation data or a simulated output without knowing the model structure.
openaire +1 more source
Diagnostic bond graphs for online fault detection and isolation
Simulation Modelling Practice and Theory, 2006Abstract Analytical redundancy relations (ARR) are symbolic equations representing constraints between different known process variables (parameters, measurements and sources). ARR are obtained from the behavioural model of the system through different procedures of elimination of unknown variables.
A.K. Samantaray +4 more
openaire +1 more source