Search Results (16)

To describe the fouling characteristics of compressor blades, fouling is categorized into dense and loose layers to characterize thickness and rough structures. An uncertainty model for dense fouling layer thickness distribution is constructed using the numerical integration and the Karhunen–Loève (KL) expansion method, while the Fouling Longuet-Higgins (FLH) model is proposed to address the uncertainty of loose fouling layer roughness. The FLH model effectively simulates the morphology characteristics of actual blade fouling and elucidates how parameters influence fouling roughness, morphology, and randomness. Based on the uncertainty modeling method, models for dense fouling layer thickness and loose fouling layer morphology are constructed, followed by numerical calculations and aerodynamic performance uncertainty quantification. Results indicate a 75.8% probability of aerodynamic performance degradation due to a dense fouling layer and a 97.2% probability related to the morphology uncertainty of a loose fouling layer when the roughness is 50 μm. This underscores that a mere focus on roughness is inadequate for characterizing blade fouling, and a comprehensive evaluation must also incorporate the implications of rough structures on aerodynamic performance. Full article

A diagnostic method for gas-path faults of turbofan engines, relying on a Probabilistic Neural Network (PNN) coupled with a thermodynamic model of the engine, is presented. The novel aspect of the method is that its training information is generated dynamically by an accompanying Engine Performance Model. In the proposed approach, the PNN efficiently addresses the first step of a diagnostic process (i.e., detection of the faulty component at the current operating point), while with the aid of an adaptive engine model, the fault is then further isolated and identified. A description of the proposed method and training aspects of the PNN are presented. The method is applied to the case of a mixed-flow turbofan engine to diagnose common gas-path faults in compressors and turbines (i.e., fouling, FOD, erosion, and tip clearance). Its performance is evaluated using realistic fault data that may be acquired at various operating conditions within a flight envelope. Full article

A review of existing research on signatures of gas turbine faults is presented. Faults that influence the aerothermodynamic performance of compressors and turbines, such as fouling, tip clearance increase, erosion, variable geometry system malfunction, and object impact damage, are covered. The signatures of such faults, which are necessary for establishing efficient gas path diagnostic methods, are studied. They are expressed through mass flow capacity and efficiency deviations. The key characteristics of the ratio of such deviations are investigated in terms of knowledge existing in published research. Research based on experimental studies, field data, and results of detailed fluid dynamic computations that exist today is found to provide such information. It is shown that although such signatures may be believed to have a unique correspondence to the type of component fault, this is only true when a particular engine and fault type are considered. The choice of diagnostic methods by developers should, thus, be guided by such considerations instead of using values taken from the literature without considering the features of the problem at hand. Full article

As the depth of mines continues to increase, the problems of high temperature and potential heat damage become more prominent. In this study, the characteristics of natural and industrial heat sources in mines were reviewed, and then mainstream heat hazard governance technologies and corresponding utilization methods were discussed and compared. The first category of technologies comprises the optimization of ventilation systems, the insulation of roc heat, and artificial refrigeration. These cooling approaches are limited because the heat resources cannot be recovered. The second category is the utilization of waste industrial heat in mines, including the use of waste heat from the air compressors, drainage water, and foul airflow, but the current applications of these approaches have limited effectiveness in cooling the underground space. The third category is the application of geo-structures to recover natural heat in mines. Based on the principles of the chiller/heat pump cycle and the characteristics of heat sources and sinks in mines, the potential and constraints of each technology were discussed and summarized. This study provides a scientific reference for the selection of suitable heat governance and utilization technologies. Full article

Gas turbines operate under harsh conditions of high temperature and pressure for extended periods, inevitably experiencing performance degradation. Predicting the performance degradation trend of gas turbines and optimizing planned maintenance cycles are crucial for the economic and safety aspects of gas turbine operation. In this study, a novel data-driven approach for predicting gas turbine performance degradation is proposed. Initially, gas turbine operating data are augmented using a mechanism model. Subsequently, a data-driven performance model is constructed based on support vector regression (SVR) and gas turbine operational characteristics, enabling real-time calculation of performance degradation indicators. Building on this, an Autoregressive Neural Network (AR-Net) is employed to construct a model for predicting the trend of performance degradation. The proposed method is applied to predict performance degradation caused by fouling in the compressor of a gas turbine. Comparative analysis with three other performance degradation prediction methods indicates that the proposed approach accurately identifies the performance degradation trend of gas turbines, determining the optimal maintenance timing. This holds significant importance for the condition-based maintenance of gas turbines. Full article

In the present work, the design and the implementation of a Fault Detection and Isolation (FDI) system for an industrial machinery is proposed. The case study is represented by a multishaft centrifugal compressor used for the syngas manufacturing. The system has been conceived for the monitoring of the faults which may damage the multishaft centrifugal compressor: instrument single and multiple faults have been considered as well as process faults like fouling of the compressor stages and break of the thrust bearing. A new approach that combines Principal Component Analysis (PCA), Cluster Analysis and Pattern Recognition is developed. A novel procedure based on the statistical test ANOVA (ANalysis Of VAriance) is applied to determine the most suitable number of Principal Components (PCs). A key design issue of the proposed fault isolation scheme is the data Cluster Analysis performed to solve the practical issue of the complexity growth experienced when analyzing process faults, which typically involve many variables. In addition, an automatic online Pattern Recognition procedure for finding the most probable faults is proposed. Clustering procedure and Pattern Recognition are implemented within a Fuzzy Faults Classifier module. Experimental results on real plant data illustrate the validity of the approach. The main benefits produced by the FDI system concern the improvement of the maintenance operations, the enhancement of the reliability and availability of the compressor, the increase in the plant safety while achieving reduction in plant functioning costs. Full article

Fouling, caused by the adhesion of fine materials to the blades of the compressor’s last stages, changes the airfoil’s shape and function and the inlet flow angle on the blades. As the fouling increases, the range of influence increases, and the mass flow rate and overall engine efficiency reduce. Therefore, the compressor is choked at lower speeds. This study aims to simulate compressor performance during off-design conditions due to fouling and to present an approach for modeling faults in diagnostic and health monitoring systems. A computational fluid dynamics analysis is carried out to evaluate the proposed method on General Electric’s T700-GE turboshaft engine, and the performance is evaluated at different flight conditions. The results show promising outcomes with an average accuracy of 88% that would help future turboshaft health monitoring systems. Full article

A gas path analysis approach of dynamic modelling was used to examine the gas turbine performance. This study presents an investigation of the effect of physical faults on the performance of a three-shaft gas turbine at full-load and part-load operation. A nonlinear steady state performance model was developed and validated. The datasheet from the engine manufacturer was used to gather the input and validation data. Some engineering judgement and optimization were used. Following validation of the engine performance model with the engine manufacturer data using physical fault and component health parameter relationships, physical faults were implanted into the performance model to evaluate the performance characteristics of the gas turbine at degradation state at full- and part-load operation. The impact of erosion and fouling on the gas turbine output parameters, component measurement parameters, and the impact of degraded components on another primary component of the engine have been investigated. The simulation results show that the deviation in the output parameters and component isentropic efficiency due to compressor fouling and erosion is linear with the load variation, but it is almost nonlinear for the downstream components. The results are discussed following the plots. Full article

The reliability and cost-effectiveness of energy conversion in gas turbine systems are strongly dependent on an accurate diagnosis of possible process and sensor anomalies. Because data collected from a gas turbine system for diagnosis are inherently uncertain due to measurement noise and errors, probabilistic methods offer a promising tool for this problem. In particular, dynamic Bayesian networks present numerous advantages. In this work, two Bayesian networks were developed for compressor fouling and turbine erosion diagnostics. Different prior probability distributions were compared to determine the benefits of a dynamic, first-order hierarchical Markov model over a static prior probability and one dependent only on time. The influence of data uncertainty and scatter was analyzed by testing the diagnostics models on simulated fleet data. It was shown that the condition-based hierarchical model resulted in the best accuracy, and the benefit was more significant for data with higher overlap between states (i.e., for compressor fouling). The improvement with the proposed dynamic Bayesian network was 8 percentage points (in classification accuracy) for compressor fouling and 5 points for turbine erosion compared with the static network. Full article

Degradation of compressors is a common concern for operators of gas turbine engines (GTEs). Surface roughness, due to erosion or fouling, is considered one of the major factors of the degradation phenomenon in compressors that can negatively affect the designed pressure rise, efficiency, and, therefore, the engine aero/thermodynamic performance. The understanding of the aerodynamic implications of varying the blade surface roughness plays a significant role in establishing the magnitude of performance degradation. The present work investigates the implications due to the degradation of the compressor caused by the operation in eroding environments on the gas turbine cycle performance linking, thereby, the compressor aerodynamics with a thermodynamic cycle. At the core of the present study is the numerical assessment of the effect of surface roughness on compressor performance employing the Computational Fluid Dynamics (CFD) tools. The research engine test case employed in the study comprised a fan, bypass, and two stages of the low pressure compressor (booster). Three operating conditions on the 100% speed-line, including the design point, were investigated. Five roughness cases, in addition to the smooth case, with equivalent sand-grain roughness ($k_s$) of 15, 30, 45, 60, and 150 µm were simulated. Turbomatch the Cranfield in-house gas turbine performance simulation software, was employed to model the degraded engine performance. The study showed that the increase in the uniform roughness is associated with sizable drops in efficiency, booster pressure ratio (PR), non-dimensional mass flow (NDMF), and overall engine pressure ratio (EPR) together with rises in turbine entry temperature (TET) and specific fuel consumption (SFC). The performance degradation evaluation employed variables such as isentropic efficiency (${\eta }_{is}$), low pressure compressor (LPC) PR, NDMF, TET, SFC, andEPR. The variation in these quantities showed, for the maximum blade surface degradation case, drops of 7.68%, 2.62% and 3.53%, rises of 1.14% and 0.69%, and a drop of 0.86%, respectively. Full article

Helicopters often operate in dusty sites, ingesting huge amounts of contaminants during landing, take-off, hover-taxi, and ground operations. In specific locations, the downwash of the rotor may spread soil particles from the ground into the environment and, once ingested by the engine, may stick to the compressor airfoils. In the present work, the Allison 250 C18 engine’s multistage axial-flow compressor is employed to study the fouling rate on rotor blades and stator vanes from both numerical and experimental standpoints. The compressor is operated in a typical ground-idle operation, in terms of the rotational regime and contaminant concentration, in laboratory-controlled conditions. The mass of deposits is collected from the airfoil surfaces at the end of the test and compared to that estimated through the numerical model. The experimental test shows that the airfoils collect almost 1.6% of the engine’s total mass ingested during a ground-idle operation. The capability of numerical methods to predict the fouling rate on the rotating and stationary airfoils of a multistage compressor is tested through the implementation of literature based deposition models. Sticking models show a good agreement in terms of the relative results; nevertheless, an overestimation of the deposited mass predicted is observed. Full article

The reliability of marine propulsion systems depends on the reliability of several sub-systems of a diesel engine. The scavenge air system is one of the crucial sub-systems of the marine engine with a turbocharger as an essential component. In this paper, the failures of a turbocharger are analyzed through the fault tree analysis (FTA) method to estimate the reliability of the system and to predict the cause of failures. The quantitative method is used for assessing the probability of faults occurring in the turbocharger system. The main failures of a scavenge air sub-system, such as air filter blockage, compressor fouling, turbine fouling (exhaust side), cooler tube blockage and cooler air side blockage, are simulated on a Wärtsilä-Transas engine simulator for a marine two-stroke diesel engine. The results obtained through the simulation can provide improvement in the maintenance plan, reliability of the propulsion system and optimization of turbocharger operation during exploitation time. Full article

This paper defines a methodology for the evaluation of the technical and economic performance of aeronautical engines through the upgrades introduced during its life. The CFM56 is a high-bypass turbofan engine. The variants share a common design, but the details are different. The fan and booster evolved over the different iterations of the engine, as did the compressor, combustor, and turbine sections. Maintenance consists of the activities carried out during the life cycle of an engine to ensure safe, reliable, and economic operation. Maintenance costs represent 20–25% of an airline’s operating costs, of which 35–40% refer to the engine. The changes in the performance parameters indicate the state of the engine in the medium to long term: for example, it is possible to detect blade fouling or data on vibrations, and highlight changes in the characteristic behavior of an engine. This work investigates the behavior of the performance parameters in the period prior to an engine development event: a comparison is made with the monitoring of engine vibrations. In the conclusions, a final expressive graph makes us aware of the significant progress, over the years, achieved with the methodology here presented. Full article

The objective of this paper is to describe an energy-based approach to visualize, identify, and monitor faults that may occur in a water-to-water transcritical CO ${}_2$ heat pump system. A representation using energy attributes allows the abstraction of all physical phenomena present during operation into a compact and easily interpretable form. The use of a linear graph representation, with heat pump components represented as nodes and energy interactions as links, is investigated. Node signature matrices are used to present the energy information in a compact mathematical form. The resulting node signature matrix is referred to as an attributed graph and is populated in such a way as to retain the structural information, i.e., where the attribute points to in the physical system. To generate the energy and exergy information for the compilation of the attributed graphs, a descriptive thermal–fluid model of the heat pump system is developed. The thermal–fluid model is based on the specifications of and validated to the actual behavioral characteristics of a physical transcritical CO ${}_2$ heat pump test facility. As a first step to graph-matching, cost matrices are generated to represent a characteristic residual between a normal system node signature matrix and a faulty system node signature matrix. The variation in the eigenvalues and eigenvectors of the characteristic cost matrices from normal conditions to a fault condition was used for fault characterization. Three faults, namely refrigerant leakage, compressor failure and gas cooler fouling, were considered. The paper only aims to introduce an approach, with the scope limited to illustration at one operating point and considers only three relatively large faults. The results of the proposed method show promise and warrant further work to evaluate its sensitivity and robustness for small faults. Full article

Variable geometry gas turbines are susceptible to various malfunctions and performance deterioration phenomena, such as variable inlet guide vane (VIGV) drift, compressor fouling, and high inlet air temperatures. The present study investigates the combined effect of these performance deterioration phenomena on the health and overall performance of a three-shaft gas turbine engine (GE LM1600). For this purpose, a steady-state simulation model of the turbine was developed using a commercial software named GasTurb 12. In addition, the effect of an inlet air cooling (IAC) technique on the gas turbine performance was examined. The design point results were validated using literature results and data from the manufacturer’s catalog. The gas turbine exhibited significant deterioration in power output and thermal efficiency by 21.09% and 7.92%, respectively, due to the augmented high inlet air temperature and fouling. However, the integration of the inlet air cooling technique helped in improving the power output, thermal efficiency, and surge margin by 29.67%, 7.38%, 32.84%, respectively. Additionally, the specific fuel consumption (SFC) was reduced by 6.88%. The VIGV down-drift schedule has also resulted in improved power output, thermal efficiency, and the surge margin by 14.53%, 5.55%, and 32.08%, respectively, while the SFC decreased by 5.23%. The current model can assist in troubleshooting the root cause of performance degradation and surging in an engine faced with VIGV drift and fouling simultaneously. Moreover, the combined study also indicated the optimum schedule during VIGV drift and fouling for performance improvement via the IAC technique. Full article