Unit Health Assessment- Oil & Gas Equipment Probabilistic Case Study

2021 ◽  
Author(s):  
Noor Azman Mohamat Nor ◽  
Andrew Findlay
Keyword(s):  
Pattern Recognition ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Success Factors ◽  
Health Assessment ◽  
Life Cycle Management ◽  
Statistical Correlation ◽  
Repair Work ◽  
Root Cause

Abstract The focus of this case study is the analysis of offshore Oil & Gas facilities recorded downtime data which are classified into gas turbine downtime categories and causes. Each event is then correlated with the maintenance repair records to determine the respective root cause. The key objective of this study is to establish the Critical Success Factors (CSF) for unit health after a gas turbine has been in operation for more than 10 years. The outcome is used to enhance the unit performance, efficiency, maintainability, and operability. As a first step, Content Analysis technique was employed to systematically decipher and organize the downtime causes from collected data. Over 500 data samples collected over a period of 3 years were sorted into relevant categories and causes: comprising a total downtime of 11,410 hours. The downtime data, which is interval scale in nature that is in ‘hours’, is meticulously tabulated against respective downtime categories and causes location by location for the 11 gas turbines sites and correlating this to the repair work. Within scope is downtime related to: Forced Outage Automatic Trip; Failure to Start; Forced Outage Manual Shutdown; and Maintenance Unscheduled while those out of scope are Non-Curtailing and Reserve Shutdown as these are external to gas turbine operational influence. In the second step, descriptive statistics analysis was carried out to understand the key downtime drivers by categories. Pattern recognition is used to identify whether the cause is a “One Time Event”, “Random Event” or “Recurring Event” to confirm data integrity and establish the problem statement. This approach assists in the discovery of erroneous data that could mislead the outcome of statistical analysis. Pattern recognition through data stratification and clustering classifies issue impact as reliability or availability. Simplistic analyses can miss major customer impact issues such as: frequent small shutdowns that do not accumulate a lot of hours per event but cause operational disruption; or infrequent time consuming events resulting from a lack of trained personnel, spares shortages, and difficulty in troubleshooting. In the third step, statistical correlation analysis was applied to establish the relationship between gas turbine downtime and repair works in determining the root causes. Benchmarking these analyses outcome with the actual equipment landscape provides for high probability root cause, thus facilitating solutions for improved site reliability and availability. The study identified CSF in the following areas: personnel training and competency; correct maintenance philosophy and its execution in practice; and life cycle management including obsolescence and spares management. Near term recommendations on changes to site operations or equipment based on OEM guidelines and current available best practices are summarized for each site analyzed.

Applications of an Interactive Balancing Procedure for Gas Turbines and Other Turbomachinery

2009 ◽  
Author(s):  
Timothy C. Allison ◽  
Harold R. Simmons
Keyword(s):  
Cost Function ◽  
Least Squares ◽  
Gas Turbine ◽  
Case Studies ◽  
Gas Turbines ◽  
Interactive Approach ◽  
Interactive Method ◽  
Balance Weight ◽  
The Cost

Least squares balancing methods have been applied for many years to reduce vibration levels of turbomachinery. This approach yields an optimal configuration of balancing weights to reduce a given cost function. However, in many situations, the cost function is not well-defined by the problem, and a more interactive method of determining the effects of balance weight placement is desirable. An interactive balancing procedure is outlined and implemented in an Excel spreadsheet. The usefulness of this interactive approach is highlighted in balancing case studies of a GE LM5000 gas turbine and an industrial fan. In each case study, attention is given to practical aspects of balancing such as sensor placement and balancing limitations.

Case Study of a Gas Turbine Chronic Failure at Saudi Arabia

2019 ◽  
Author(s):  
Abdullah N. AlKhudhayr ◽  
Abdulrahman M. AlAdel
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Oil And Gas ◽  
Electrical Power ◽  
Oil And Gas Industry ◽  
Machine Design ◽  
Severe Damage ◽  
Major Overhaul ◽  
Gas Industry

Abstract A gas turbine is a reliable type of rotating equipment, utilized in various applications. It is well known in power generation and aviation. In the oil and gas industry, gas turbines are utilized in locations with limited electrical power or a high power driven load requirement, such as offshore or a high-rated power 20MW compressor. Five gas turbines are used as mechanical drive equipment. After a few years of operation, the gas turbines were experiencing high operating temperatures in bearings, turbine compartments, high spread temperature, and the presence of smoke in the exhaust. During a major overhaul of the turbines, oil was found to have accumulated internally in the wrapper casing, along with damage to several internal combustion components. In one case, the exhaust casing experienced severe damage with deformation. This paper presents a case study of a gas turbine failure and its contributors. The paper explains the mitigated solution to overcome the challenges related to the gas turbine operation, maintenance, and machine design.

Blade Faults Diagnosis in Power Generation Gas Turbines

2017 ◽  
Author(s):  
Meng Hee Lim ◽  
Salman Leong ◽  
Kar Hoou Hui
Keyword(s):  
Power Generation ◽  
Statistical Analysis ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Vibration Signal ◽  
Health Condition ◽  
Baseline Data ◽  
Compressor Blades ◽  
Industrial Gas Turbines

This paper presents a case study in managing the dilemma of whether to resume or stop the operation of a power generation gas turbine with suspected blade faults. Vibration analysis is undertaken on the vibration signal of the gas turbine, to obtain an insight into the health condition of the blades before any decision is made on the operation of the machine. Statistical analysis is applied to study the characteristics of the highly unstable blade pass frequency (BPF) of the gas turbine and to establish the baseline data used for blade fault assessment and diagnosis. Based on the excessive increase observed on specific BPF amplitudes in comparison to the statistical baseline data, rubbing at the compressor blade is suspected. An immediate overhaul is therefore warranted, and the results from the inspection of the machine confirm the occurrence of severe rubbing at the compressor blades and labyrinth glands of the gas turbine. In conclusion, statistical analysis of BPF amplitude is found to be a viable tool for blade fault diagnosis in industrial gas turbines.

Predictive Compressor Wash Optimization for Economic Operation of Gas Turbine

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Houman Hanachi ◽  
Jie Liu ◽  
Ping Ding ◽  
Il Yong Kim ◽  
Chris K. Mechefske
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Power Plants ◽  
Economic Losses ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Considerable Saving ◽  
Service Period ◽  
Power Deficit

Gas turbine engines (GTEs) are widely used for power generation, ranging from stationary power plants to airplane propulsion systems. Compressor fouling is the dominant degradation mode in gas turbines that leads to economic losses due to power deficit and extra fuel consumption. Washing of the compressor removes the fouling matter and retrieves the performance, while causing a variety of costs including loss of production during service time. In this paper, the effect of fouling and washing on the revenue of the power plant is studied, and a general solution for the optimum time between washes of the compressor under variable fouling rates and demand power is presented and analyzed. The framework calculates the savings achievable with optimization of time between washes during a service period. The methodology is utilized to optimize total costs of fouling and washing and analyze the effects and sensitivities to different technical and economic factors. As a case study, it is applied to a sample set of cumulative gas turbine operating data for a time-between-overhauls and the potential saving has been estimated. The results show considerable saving potential through optimization of time between washes.

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.

Identification and Correction of Rotor Instability in an Oil-Free Gas Turbine

2008 ◽  
Author(s):  
Daniel R. Lubell ◽  
Jonathan L. Wade ◽  
Navjot S. Chauhan ◽  
John G. Nourse
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Early Stage ◽  
Turbine Wheel ◽  
Free Gas ◽  
Foil Bearings ◽  
Root Cause ◽  
Final Design ◽  
Acceptance Tests ◽  
Conventional Oil

The direction of advanced gas turbines and other turbomachinery has been towards oil-free designs, enabled by the significant improvements of high temperature foil bearings. The advantages of oil-free gas turbines have been studied and shown to be realistic. However, the oil-free technology is still at an early stage in its development relative to conventional oil lubricated turbomachinery systems which have been studied and manufactured for about 100 years, and the bearings even longer. Oil-free gas turbines are most successful as a system design initiated with oil-free bearings. Making these successful designs requires knowledge of the strengths and weaknesses of integrating oil-free bearings. A common example is foil bearings, the type typically considered for oil-free gas turbines. These bearings are lower in damping than their oil lubricated counterparts. Therefore special considerations are made by the experienced oil-free gas turbine designer early in the design process. Knowledge of the opportunities for instability that are not as common in conventional turbomachinery provides value to the final design. This paper presents the identification and correction of rotor instability in an oil-free microturbine of a 65 kW system. The manufacturer put significant effort into identifying the root cause of the seemingly random occurrences of rotor instability, in order to improve yield for acceptance tests. Through the application of conventional rotordynamics theory and techniques, combined with 3-D imaging of complex cast parts, the root cause was identified as an Alford’s-type force at the turbine driven by critical machined and cast features of the turbine wheel that would not have been important in a conventional oil lubricated turbomachine. A successful corrective process has been put in place, providing final confirmation of the root cause.

From Provider to Decider: The Changing Face of Royal Navy Gas Turbine Support

2007 ◽  
Author(s):  
Ian Timbrell ◽  
Howard Startin
Keyword(s):  
Life Cycle ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Strategic Plan ◽  
Life Cycle Management ◽  
Royal Navy ◽  
Service Support ◽  
Marine Propulsion ◽  
Care Package ◽  
Total Care

Marine Propulsion Systems Integrated Project Team (MPSIPT), part of the UK’s Defence Logistics Organisation (DLO), has traditionally provided gas turbine life cycle management to a collaboration of four European navies operating the Rolls Royce Olympus, Tyne and Spey marine gas turbines. With the drive towards the need to deliver greater efficiencies, a shrinking supplier base and in keeping with DLO’s Strategic Plan to transform in-service support arrangements, MPSIPT explored ways by which they could move from a provider to intelligent decider role. This transformation was realised in the form of a Total Care Package (TCP), introduced in April 2005, whereby Rolls Royce has taken responsibility for the support of Olympus and Tyne marine gas turbines. The issues raised should be of interest to Navies and other organisations facing similar challenges in gas turbine support. This paper gives a brief history behind how gas turbine life cycle management has been provided to the Royal Navy in the past, before concentrating on the reasons behind and the practical issues raised by our move to the TCP arrangement. The paper sets out the philosophy behind the DLO’s Strategic Plan, what that means in practical terms, how it has been applied for gas turbine support and the implications for the future. It explains how TCP has been approached in partnership with Rolls Royce, describes the issues that were faced, what the benefits are, what it means for the front line and our partners and how the contract is being managed. It concludes by identifying the lessons from the first year of operation of the TCP contract.

Advanced Gas Turbine Diagnostics Using Pattern Recognition

2011 ◽  
Author(s):  
Shintaro Kumano ◽  
Naotaka Mikami ◽  
Kuniaki Aoyama
Keyword(s):  
Artificial Intelligence ◽  
Power Generation ◽  
Pattern Recognition ◽  
Data Analysis ◽  
Gas Turbine ◽  
Remote Monitoring ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Threshold Levels ◽  
Monitoring Service

Power plant owners require their plants’ high reliability, availability and also reduction of the cost in today’s power generation industry. In addition, the power generation industry is faced with a reduction of experienced operators and sophistication of power generation equipment. Remote monitoring service provided by original equipment manufacturers (OEMs) has become increasingly popular due to growing demand for both improvement of plant reliability and solution of experienced operator shortage. Through remote monitoring service, customers can benefit from swift and appropriate operational support based on OEM’s know-how. Before implementation of remote monitoring, the customer and OEM often required repeated interchanges of information about operation and instrumentation data. These interchanges took a lot of time. Data analysis and estimation of deterioration were time-consuming. Remote monitoring has enabled us, OEMs, not only to access to a plant’s real-time information but also to trace the historical operation data, and therefore the required time of data analysis and improvement has been reduced. Mitsubishi Heavy Industries, Ltd. also embarked on around-the-clock remote monitoring service for gas turbine plant over a decade ago and has increased its ability over time. At present, the application of remote monitoring systems have been extended not only into proactive maintenance by making use of diagnostic techniques carried out by expert engineers but also into building a pattern recognition system and an artificial intelligence system using expert’ knowledge. Conventional diagnostics is only determining whether the plant is being operated within the prescribed threshold levels. Pattern recognition is a state-of-the-art technique for diagnosing plant operating conditions. By comparing past and present conditions, small deterioration can be detected before it needs inspection or repair, while all the operating parameter is within their threshold levels. Mahalanobis-Taguchi method (MT method) is a technique for pattern recognition and has the advantage of diagnosing overall GT condition by combining many variables into one indicator called Mahalanobis distance. MHI has applied MT method to the monitoring of gas turbines and verified it to be efficient method of diagnostics. Now, in addition to the MT method, automatic abnormal data discrimination system has been developed based on an artificial intelligence technique. Among a lot of artificial intelligence techniques, Bayesian network mathematical model is used.

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.

Heavy Duty Marine Gas Turbines: A Case Study

1972 ◽  
Author(s):  
R. A. Jones ◽  
W. J. Hefner
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Heavy Duty ◽  
General Electric ◽  
Electric Model

The Broken Hills Proprietary Company, Ltd. of Australia is building two gas turbine powered roll-on, roll-off ships. The main propulsion plants of these unique vessels are General Electric Model Series–5002 heavy duty marine gas turbines. This paper describes some of the features of these ships and their gas turbines as well as reviewing the controls and supporting systems.

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