22 research outputs found

    Gas Turbine Diagnostics

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    Neural Networks for Gas Turbine Diagnosis

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    The present chapter addresses the problems of gas turbine gas path diagnostics solved using artificial neural networks. As a very complex and expensive mechanical system, a gas turbine should be effectively monitored and diagnosed. Being universal and powerful approximation and classification techniques, neural networks have become widespread in gas turbine health monitoring over the past few years. Applications of such networks as a multilayer perceptron, radial basis network, probabilistic neural network, and support vector network were reported. However, there is a lack of manuals that summarize neural network applications for gas turbine diagnosis

    Gas Turbine Condition Monitoring and Diagnostics

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    Introductory Chapter: Gas and Wind Turbines and Their Models

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    Advanced Nonlinear Modeling of Gas Turbine Dynamics

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    The process of gas turbine development requires different mathematical models. In particular, physics-based nonlinear dynamic models are widely used in the development of control and diagnostic systems. The present chapter firstly reviews known works on nonlinear dynamic engine modeling centering on model applications and developments. As an important development, modeling of heating up engine components is considered. This phenomenon consists in a radial clearance change during transients that influences engine static and dynamic performances. This clearance change is usually computed by a finite element method that is critical to computer resources. The chapter secondly presents a new and more rapid simulation methodology to integrate two dynamic processes, a general engine transient and a clearance change. This allows creating a more accurate and relatively fast engine dynamic model that is easy to use in the design of control and diagnostic systems. Finally, the chapter introduces further methodology enhancement consisting in the consideration of the influence of varying metal temperature on the strains induced by mechanical loads. To validate methodology, it is applied to a particular turbofan engine, and the simulated and real engine dynamic performances are compared

    Systemic therapy of inflammatory breast cancer with type 2 diabetes mellitus – Prevention of high risk of radiation-induced progression of tumor tissue cancer

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    Introduction. Cancer mortality in diabetic patients has been reported to increase moderately compared to non-diabetic patients. The aim of the study aimed to assess the findings and identify radiotherapy's role in the comprehensive care of diabetic IBC patients with various hyperglycemia correction strategies. Methods. Patients with diabetes have shown a higher risk of radiation-induced cancer progression for tumor tissue, especially for inflammatory form. For 7 patients, to continue systematic chemotherapy with a scheme change (consecutive anthracyclines-taxanes, 2-week interval) and insulin with individual scheme for hyperglycemia correction on the basis of glycemic control – 1st group, the other (7 patients) – 2nd group, was given radiotherapy to the breast gland and lymphatic drainage ways. 45–50 Grey was prescribed for 25-28 fractions (per 1.8-2.0 Grey), 46–50 Grey in 23-25 fractions were used for zones of regional metastasis and for hyperglycemia correction metformin 2000 mg/day PO divided q8-12hr with meal on the basis of glycemic control. Results. Assessed were the number of patients who qualified for surgery and overall survival for 24 months. 2nd group showed a superior response following resistance to prior systemic treatment. Thus, 5 (71.41%) of the 7 patients exhibited a consistent response – complete or partial regression. There were only 2 individuals (28.61%) who responded to treatment among the patients who maintained chemotherapy. Conclusions. Breast cancer of the aggressive IBC variety requires multidisciplinary treatment from breast surgery, medical, and radiation oncology. Patients with diabetes appear to experience more side effects from radiation therapy than patients without the disease. Hyperglycemia, higher total RT doses, and radiosensitizers are a few techniques that can improve the impact of RT on local-regional management. Local-regional control rates for IBC are increasing with an individual patient strategy. Metformin also improves insulin resistance and has anticancer benefits

    A MORE REALISTIC SCHEME OF DEVIATION ERROR REPRESENTATION FOR GAS TURBINE DIAGNOSTICS

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    ABSTRACT Gas turbine diagnostic algorithms widely use fault simulation schemes, in which measurement errors are usually given by theoretical random number distributions, like the Gaussian probability density function. The scatter of simulated noise is determined on the basis of known information on maximum errors for every sensor type. Such simulation differs from real diagnosis because instead of measurements themselves the diagnostic algorithms work with their deviations from an engine baseline. In addition to simulated measurement inaccuracy, the deviations computed for real data have other error components. In this way, simulated and real deviation errors differ by amplitude and distribution. As a result, simulation-based investigations might result in too optimistic conclusions on gas turbine diagnosis reliability. To understand error features, deviations of real measurements are analyzed in the present paper. To make error presentation more realistic, it is proposed to extract an error component from real deviations and to integrate it in fault description. Finally, the effect of the new noise representation mode on diagnostic reliability is estimated. It is shown that the reliability change due to inexact error simulation can be significant
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