Gas Turbine Common Issues, Failure Investigations, Root Cause Analyses, and Preventative Actions

2016 ◽  
Author(s):  
Stephen Garner ◽  
Zuhair Ibrahim
Keyword(s):  
Control System ◽  
Internal Combustion Engine ◽  
Control Systems ◽  
Gas Turbine ◽  
Failure Mode ◽  
Gas Turbines ◽  
Combustion Engine ◽  
Internal Combustion ◽  
System Availability ◽  
Root Cause

Gas turbines are a type of internal combustion engine and are used in a wide range of services powering aircraft of all types, as well as driving mechanical equipment such as pumps, compressors in the petrochemical industry, and generators in the electric utility industry. Similar to the reciprocating internal combustion engine in an automobile, energy (mechanical or electrical) is generated by the burning of a hydrocarbon fuel (i.e., jet fuel, diesel or natural gas). The core of a gas turbine engine is comprised of three main sections: the compressor section, the combustor section, and the turbine section. To ensure that a gas turbine operates safely, reliably, and with optimum performance, all gas turbines are provided with a control system designed either by the OEM or according to the OEM’s specification. The OEM-provided control systems will typically include complex and integrated subsystems such as (but not limited to): a graphic user interface, an engine management system (EMS or ECS), a safety related system (SRS), and a package control system (PCS) that may interface with a facilities’ existing computerized control systems. Any failure of the mechanical systems, electro-mechanical systems, or logic based control systems of a gas turbine can result in forced outage. A forced outage of a gas turbine, whether in a mechanical service, such as pipelines, or in either a simple cycle or combined cycle power generation installation results in a reduction of system availability and therefore a loss in revenue. The significant capital investment in a gas turbine system necessitates a high degree of reliability and system availability while reducing forced outages. A power plant can minimize occurrences of forced outages and optimize recovery of capacity by effectively combining proactive and reactive solutions. This paper will discuss both proactive and reactive programs as well as their implementation in order to answer the key questions that often surround an outage: How is outage time minimized while increasing reliability and system availability? What went wrong and who or what is responsible? How soon can the unit or the plant get back online? And what operational or maintenance considerations are needed to prevent a similar recurrence. Proactive approaches to be discussed include process hazard analyses (PHA) such as hazard and operability studies (HAZOP), hazard identification (HAZID), layer-of-protection analyses (LOPA), what-if analyses, and quantitative risk assessments (QRA) in addition to failure mode and effects analysis (FMEA); and failure mode, effects and criticality analysis (FMECA). Reactive approaches to be discussed include various root cause analysis (RCA) and failure analysis (FA) techniques and methodologies such as fault-tree analysis. Case studies and some lessons learned will also be presented to illustrate the methods.

АКУСТИЧНА ПОМІТНІСТЬ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ З СИЛОВИМИ УСТАНОВКАМИ НА БАЗІ ПОРШНЕВИХ ДВИГУНІВ

2020 ◽  
pp. 62-80
Author(s):  
В. В. Руденко ◽  
И. В. Калужинов ◽  
Н. А. Андрущенко
Keyword(s):  
Control System ◽  
Internal Combustion Engine ◽  
Power Plants ◽  
Combustion Engine ◽  
Spectral Characteristics ◽  
Experimental Studies ◽  
Internal Combustion ◽  
Detection Range ◽  
Acoustic Signature ◽  
Static Conditions

The presence in operation of many prototypes of UAVs with propeller propellers, the use of such devices at relatively low altitudes and flight speeds makes the problem of noise reduction from UAVs urgent both from the point of view of acoustic imperceptibility and ecology.The aim of the work is to determine a set of methods that help to reduce the visibility of UAVs in the acoustic range. It is shown that the main source of noise from the UAV on the ground is the power plant, which includes the engine and the propeller. The parameters of the power plants influencing the processes that determine the acoustic signature of the UAV were investigated. A comprehensive analysis of the factors affecting visibility was carried out. The power plants include two-stroke and four-stroke engines, internal combustion and two-blade propellers. The use of silencers on the exhaust of the internal combustion engine was considered. The spectral characteristics of the acoustic fields of the propeller-driven power plants for the operating sample of the UAV "Eco" were obtained. The measurements were carried out in one-third octave and 1/48 octave frequency bands under static conditions. The venue is the KhAI airfield. Note that the propellers that were part of the power plants operated at Reynolds numbers (Re0,75<2*105), which can significantly affect its aerodynamic and acoustic characteristics. It is shown that when choosing a UAV control system, one should take into account the fact that two-stroke piston engines are the dominant source in the noise of propeller-driven control systems in the absence of a hood and mufflers in the intake and exhaust tracts. The use of a four-stroke internal combustion engine significantly reduces the noise of the control system. In the general case, the position of the boundaries of the zone of acoustic visibility of a UAV at the location of the observer is determined by the ratio between the intensity of acoustic radiation perceived by the observer from the UAV and the intensity of sound corresponding to the natural acoustic background and depends on the degree of manifestation of acoustic effects accompanying the propagation of sound in a turbulent atmosphere - the refraction of sound waves. Absorption and dissipation of acoustic energy. The calculation and comparison of the UAV detection range was carried out taking into account the existing natural maskers.The results of experimental studies are presented that allow assessing the degree of acoustic signature of the UAV. A set of measures aimed at reducing the intensity of the acoustic signature of the UAV in various regions of the radiation spectrum has been determined.

scholarly journals The Working Principle of a Turbine “Case Study: GE Frame 9E Gas Turbine”

2019 ◽  
pp. 1-20
Author(s):  
Obolo Olupitan Emmanuel
Keyword(s):  
Internal Combustion Engine ◽  
Gas Turbine ◽  
Combustion Engine ◽  
Mechanical Energy ◽  
Internal Combustion ◽  
Reciprocating Motion ◽  
Fuel Gas ◽  
Spark Plug ◽  
Working Principle

Gas Turbine is one of the machines that use the thermodynamic principle converting fuel energy to mechanical energy. It is an internal combustion engine. Also, designed to accelerate a stream of gas, which is used to produce a reactive thrust to propel an object or to produce mechanical power that turns a load. It functions in the same way as the internal combustion engine. It sucks in air from the atmosphere, and compress it. The fuel (gas) is injected and ignited (spark plug). The gases expand doing work and finally exhausts outside. Instead of reciprocating motion, the gas turbine uses a rotary motion throughout, and that is the only difference.

Modeling of the motion control system of an unmanned tracked vehicle with onboard gear units

2021 ◽  
pp. 15-19
Author(s):  
Keyword(s):  
Control System ◽  
Internal Combustion Engine ◽  
Motion Control ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Control Device ◽  
External Control ◽  
Programmable Logic ◽  
Cruise Control ◽  
Tracked Vehicle

The results of a study of the control processes of an automated transmission and internal combustion engine of a transport unmanned tracked vehicle when the speed of movement is set by an external control device are presented. Keywords: unmanned tracked vehicle, algorithm, motion control, onboard gear unit, programmable logic controller, cruise control. [email protected]

Model Based Performance Correction Methodology — A Case Study

2014 ◽  
Author(s):  
Koldo Zuniga ◽  
Thomas P. Schmitt ◽  
Herve Clement ◽  
Joao Balaco
Keyword(s):  
Control System ◽  
Control Systems ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Performance Test ◽  
Test Results ◽  
Model Based ◽  
Test Conditions ◽  
Partial Load

Correction curves are of great importance in the performance evaluation of heavy duty gas turbines (HDGT). They provide the means by which to translate performance test results from test conditions to the rated conditions. The correction factors are usually calculated using the original equipment manufacturer (OEM) gas turbine thermal model (a.k.a. cycle deck), varying one parameter at a time throughout a given range of interest. For some parameters bi-variate effects are considered when the associated secondary performance effect of another variable is significant. Although this traditional approach has been widely accepted by the industry, has offered a simple and transparent means of correcting test results, and has provided a reasonably accurate correction methodology for gas turbines with conventional control systems, it neglects the associated interdependence of each correction parameter from the remaining parameters. Also, its inherently static nature is not well suited for today’s modern gas turbine control systems employing integral gas turbine aero-thermal models in the control system that continuously adapt the turbine’s operating parameters to the “as running” aero-thermal component performance characteristics. Accordingly, the most accurate means by which to correct the measured performance from test conditions to the guarantee conditions is by use of Model-Based Performance Corrections, in agreement with the current PTC-22 and ISO 2314, although not commonly used or accepted within the industry. The implementation of Model-based Corrections is presented for the Case Study of a GE 9FA gas turbine upgrade project, with an advanced model-based control system that accommodated a multitude of operating boundaries. Unique plant operating restrictions, coupled with its focus on partial load heat rate, presented a perfect scenario to employ Model-Based Performance Corrections.

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