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A stringent requirement of government policy on Carbon Monoxide (CO) and Nitrogen Oxide (NOx) emissions leads to the introduction of dry-low emission (DLE) gas turbines. Although Rowen's model is well established for a gas turbine dynamic study, its utilization for a DLE representation has not been extensively studied. Thus, the objective of this research is to study the suitability of using the Rowen's...
The objective of this paper is to estimate the compressor discharge temperature measurements on an industrial gas turbine that is undergoing commissioning at site, using a data-driven model which is built using the test bed measurements of the engine. This paper proposes a Bayesian neuro-fuzzy modelling (BNFM) approach, which combines the adaptive neuro-fuzzy inference system (ANFIS) and variational...
Based on the rolling process data from practical engineering, a thermal damage mitigating model of domestic 300MW steam turbine unit is established, which includes power model of steam turbine and thermal damage model. In order to get the theoretical minimum variance, the coefficient matrix of this mitigating model is decomposed. Furthermore, an assessment for the PI control practice of steam turbine...
In the database community Polystores is an emerging and promising approach for data federation that aims at designing a unified querying layer over multiple data models. In the Semantic Web community a similar in spirit approach of Ontology-Based Data Access (OBDA) has been recently proposed, attracted a lot of attention, and proved its success in several industrial scenarios. In this paper we discuss...
This study present an application of Laguerre network-based hierarchical fuzzy modeling approach in fault diagnosis of the temperature sensors in industrial heavy duty gas turbines. The recorded experimental data from the performances of a V94.2 gas turbine unit were employed in modeling stage. A comparison between the responses of the models and real data indicate the capability of the model for...
In this work, different model-based procedures exploiting the analytical redundancy principle for the detection and isolation of the input-output sensor faults on a gas turbine simulated process are presented and compared. The contribution of the paper consists of exploiting several identification schemes in connection with linear and nonlinear residual generator design procedures for diagnostic purposes...
Automatic processing of data for the purpose of determining operating states and identifying faults has become essential for many modern industrial systems. Typical sources of this data include hundreds of sensors mounted at the industrial machinery measuring qualities such as temperature, vibration, pressure, and many more. However, sensors are complex technical devices, which means that they can...
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