Critical Subassemblies Research Articles

Failure Mode and Effect Analysis (FMEA) of a Taurus 60 Gas Turbine Power Plant System (GTPPS), in Mowe, Nigeria

Failure Mode and Effect Analysis (FMEA) is an approach used for maintenance system reliability analysis. FMEA is applied to the Taurus 60 Gas Turbine Power Plant System (GTPPS). The unexpected failures with the associated maintenance costs are major problems in most power plants. In this study, critical components of the Taurus 60 gas turbine power plant were identified. Twenty-five sub-assemblies were identified and the probable failure modes of the main sub-assemblies. Failure analysis and the Risk Priority Numbers (RPN) of the critical sub-assemblies were determined using failure modes and effect analysis method. Failure analysis and the Risk Priority Numbers (RPN) of the critical sub-assemblies were determined using failure modes and effect analysis method. Based on criticality analysis, six (6) critical sub-assemblies were identified. These are fuel gas supply, air filter package, air trap package, gearbox, compressor rotor assembly and fuel injector with criticality numbers 12.5, 20.83, 20.83, 20.83, 16.67 and 20.83 respectively. The failure analysis for these critical sub-assemblies specified the failure modes, failure effects, maintenance tasks, frequency of inspection and strategies. The ranges of the Risk Priority Number (RPN) for the components of fuel gas supply, air filter package, air trap package, gearbox, compressor rotor assembly and fuel injector were 54-126, 60-90, 75-90, 72-84, 36-112 and 90-120 respectively. The critical sub-assemblies should be given close attention in terms of monitoring, routine checks which can be monitored using prepared checklists. The semi- critical and non- critical assemblies should not be neglected either.

Fault diagnosis of offshore wind turbine gearboxes using a dynamic Bayesian network

ABSTRACT The gearbox system is one of the most critical subassemblies in offshore wind turbine (OWT) drivetrains whose failures could lead to long downtimes and high repair costs. Therefore, it is crucial to accurately diagnose and predict the gearbox faults at an early stage of development. This study develops a new dynamic Bayesian network (DBN) framework for fault diagnosis and reliability analysis of OWT gearbox systems by incorporating components’ degradation information and condition-based maintenance (CBM) strategy. The reliability, availability, and mean-time between failures (MTBF) as well as the failure criticality index (FCI) for each subassembly are estimated. The results identified the loss of function in the bearing subassembly as the most likely underlying cause of a failure in the gearbox system.

Wind turbine reliability data review and impacts on levelised cost of energy

AbstractReliability is critical to the design, operation, maintenance, and performance assessment and improvement of wind turbines (WTs). This paper systematically reviews publicly available reliability data for both onshore and offshore WTs and investigates the impacts of reliability on the cost of energy. WT failure rates and downtimes, broken down by subassembly, are collated from 18 publicly available databases including over 18 000 WTs, corresponding to over 90 000 turbine‐years. The data are classified based on the types of data collected (failure rate and stop rate) and by onshore and offshore populations. A comprehensive analysis is performed to investigate WT subassembly reliability data variations, identify critical subassemblies, compare onshore and offshore WT reliability, and understand possible sources of uncertainty. Large variations in both failure rates and downtimes are observed, and the skew in failure rate distribution implies that large databases with low failure rates, despite their diverse populations, are less uncertain than more targeted surveys, which are easily skewed by WT type failures. A model is presented to evaluate the levelised cost of energy as a function of WT failure rates and downtimes. A numerical study proves a strong and nonlinear relationship between WT reliability and operation and maintenance expenditure as well as annual energy production. Together with the cost analysis model, the findings can help WT operators identify the optimal degree of reliability improvement to minimise the levelised cost of energy.

Reliability, Availability and Maintainability Analysis for Grid-Connected Solar Photovoltaic Systems

Recently, solar power generation is significantly contributed to growing renewable sources of electricity all over the world. The reliability and availability improvement of solar photovoltaic (PV) systems has become a critical area of interest for researchers. Reliability, availability, and maintainability (RAM) is an engineering tool used to address operational and safety issues of systems. It aims to identify the weakest areas of a system which will improve the overall system reliability. In this paper, RAM analysis of grid-connected solar-PV system is presented. Elaborate RAM analysis of these systems is presented starting from the sub-assembly level to the subsystem level, then the overall system. Further, an improved Reliability Block Diagram is presented to estimate the RAM performance of seven practical grid-connected solar-PV systems. The required input data are obtained from worldwide databases of failures, and repair of various subassemblies comprising various meteorological conditions. A novel approach is also presented in order to estimate the best probability density function for each sub-assembly. The monitoring of the critical subassemblies of a PV system will increase the possibility not only for improving the availability of the system, but also to optimize the maintenance costs. Additionally, it will inform the operators about the status of the various subsystems of the system.

Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox

Predicting the remaining useful life (RUL) of critical subassemblies can provide an advanced maintenance strategy for wind turbines installed in remote regions. This paper proposes a novel prognostic approach to predict the RUL of bearings in a wind turbine gearbox. An artificial neural network (NN) is used to train data-driven models and to predict short-term tendencies of feature series. By combining the predicted and training features, a polynomial curve reflecting the long-term degradation process of bearings is fitted. Through solving the intersection between the fitted curve and the pre-defined threshold, the RUL can be deduced. The presented approach is validated by an operating wind turbine with a faulty bearing in the gearbox.

Testing and qualification of Control & Safety Rod and its drive mechanism of Fast Breeder Reactor

Prototype Fast Breeder Reactor (PFBR) has two independent fast acting diverse shutdown systems. The absorber rod of the first system is called Control & Safety Rod (CSR). CSR and its Drive Mechanism (CSRDM) are used for reactor control and for safe shutdown of the reactor by scram action. In view of the safety role, the qualification of CSRDM is one of the important requirements. CSR & CSRDM were qualified in two stages by extensive testing. In the first stage, the critical subassemblies of the mechanism, such as scram release electromagnet, hydraulic dashpot & dynamic seals and CSR subassembly, were tested and qualified individually simulating the operating conditions of the reactor. Experiments were also carried out on sodium vapour deposition in the annular gaps between the stationary and mobile parts of the mechanism. In the second stage, full-scale CSRDM and CSR were subjected to all the integrated functional tests in air, hot argon and subsequently in sodium simulating the operating conditions of the reactor and finally subjected to endurance tests. Since the damage occurring in CSRDM & CSR is mainly due to fatigue cycles during scram actions, the number of test cycles was decided based on the guidelines given in ASME, Section III, Div. 1. The results show that the performance of CSRDM & CSR is satisfactory. Subsequent to the testing in sodium, the assemblies having contact with liquid sodium/sodium vapour were cleaned using CO2 process and the total cleaning process has been established, so that the mechanism can be reused in sodium. The various stages of qualification programmes have raised the confidence level on the performance of the system as a whole for the intended and reliable operation in the reactor.

Ultra-fast flash X-ray pulses produced by Blumlein devices

The flash X-ray systems developed at the University of Texas at Dallas (UTD) centers on two critical subassemblies: (1) a Blumlein pulsed power source and (2) an X-ray diode properly designed and matched to the pulse forming line. The pulse generator consists of either a single or several triaxial Blumleins. For multiple lines, Blumleins are stacked in series at one end and charged in parallel and synchronously commutated with a single switching element at the other end. In this way, relatively low charging voltages are multiplied to give a high discharge voltage across an X-ray diode. Extensive characterization of these Blumlein pulsers have been performed over the past several years. Results indicate that they are capable of producing high-power waveforms with risetimes and repetition rates in the range of 0.1–50ns and 1–1000Hz, respectively, using a conventional thyratron, spark gap, or photoconductive switch. Our recent efforts have for the first time resulted in implementation and demonstration of high-power stacked Blumlein pulsers commutated by a single photoconductive switch. Presently, these devices reliably produce 50–100MW output waveforms with pulse durations of 1–3ns and risetimes as fast as 150ps. Prospects for producing X-rays with such fast-switching devices are discussed.