Industrial gas turbines serve in a variety of markets involving wide ranging duty cycles, fuel types and quality and emission requirements. For the Oil & Gas markets, applications range from mechanical drive, compressor sets and electrical generation that may be located in developed, remote or off-shore areas requiring a backup fuel (usually a liquid fuel). Upstream applications often require the gas turbine to burn a wide Wobbe range of fuels with varying gas compositions. For Power Generation applications, flexibility in operating range and low emissions are usually required. This paper describes Solar’s latest SoLoNOx™ (DLE) combustion system developments for the Titan 250 for both gaseous and liquid fuels with a focus on fuel type and quality, operability and emissions from both rig and engine tests. Several combustion systems will be discussed including gas only, dual fuel and a dual fuel Lean Direct Injection (LDI) system for burning lower quality liquid fuels. Engine tests were performed with blends of reactive gases (propane and butane), inert gas (carbon dioxide) and natural gas covering a wide Wobbe range from 30 to 60 WI (MJ/Nm 3 ). Full engine qualification testing was performed which included operability, emissions and combustion stability for both the gas only and LDI combustion systems. The LDI system is based on the dry low emissions combustion system used for gas operation and thus offers low NO x emissions on gaseous fuels with the ability to burn lower quality liquid fuels for backup operation. A dual fuel lean premixed combustion system was also fully engine qualified for natural gas and liquid fuel. High pressure single injector rig tests using hydrogen blends with pipeline quality natural gas were also performed to qualify these fuels for engine operation in the dry low emission combustion systems with up to 30% hydrogen. The primary focus of testing was to determine overall operability, turndown, flashback risk and emissions.

Understanding the heat transfer characteristics of impingement cooling of high-speed high-power gears is essential to design a reliable gearbox for a new generation of jet engines. However, experimental data on the impingement cooling of gears is limited in the literature. The experimental setup at the Institute of Thermal Turbomachinery aims at closing this gap. It includes a rotating gear instrumented with thermocouples. The measured temperatures are used to determine a spatially resolved heat transfer coefficient distribution on the gear tooth. The iterative evaluation approach applied in the post-processing of the experimental data is validated with two reference cases. First, it is shown that the interpolation of temperature data between thermocouple locations leads to inaccurate results and would not be valid for the evaluation of the experiments, even if the number of thermocouples were increased. The iterative evaluation approach can reproduce the reference heat transfer coefficient distributions very accurately even with a low spatial resolution of temperature data. A new iterative method based on the Levenberg-Marquardt algorithm is implemented within this study. The new method generally converges faster than the existing method. The difference in required computational time is negligible in the easy to evaluate high heat transfer case, whereas a speed-up of up to three times is observed in the relatively cumbersome evaluation of the low heat transfer case.

This paper provides a high-level review of the potential failure modes and hazards to which electrified aircraft propulsion (EAP) systems are susceptible, along with potential gas turbine control-based strategies to assist in the mitigation of those failures. To introduce the types of failures that an EAP system may experience, a generic EAP system is considered, consisting of gas turbine engines, mechanical drives, electric machines, power electronics and distribution systems, energy storage devices, and motor driven propulsors. The functionality provided by each of these EAP subsystems is discussed, along with their potential failure modes, and possible strategies for mitigating those failures. To further illustrate the role of gas turbine controls in mitigating EAP failure modes, an example based on a simulated EAP concept aircraft proposed by NASA is given. The effects of failures are discussed, along with turbomachinery control strategies, including reversionary control modes, and control limit logic.

The aerospace industry is driven more than ever to reduce time and cost of developing aircrafts while reducing weight without compromising performance. This challenge cascades down to design of aircraft engines, where manufacturers are striving to deliver engines with higher fuel efficiency and power per unit weight. The challenge cascades down further to aerospace systems such as gearboxes. The focus of this paper is to addresses this challenge through application of model-based systems engineering and a design workflow based on simulation and optimization. A typical gearbox design starts with system level performance requirements such as power requirements, speed, torques and operating conditions. The goal is to design a minimum weight, manufacturable gearbox in the shortest possible time that meets the performance requirements. In this paper, authors present a design workflow developed for meeting this goal. The efficiency of the workflow presented here comes from the use of advanced simulation technologies, seamless integration of the workflow tasks, and modern and intuitive user experience. The proposed workflow focuses on design of housing and lubrication. This workflow is demonstrated on an aircraft engine accessories gearbox. Gear and bearing design are currently out of the scope of this paper and can be addressed in future work. Demonstrating a fully detailed workflow on a real-life gearbox housing with all the physics covered here would require many man-months of work and is outside the scope of authors’ IRAD funding. Instead, authors have presented a proof of concept of the workflow while providing key statistics to support the value and feasibility of the workflow.

Industrial machinery is developing in the direction of large-scale, automation, and high precision, which brings novel troubles to mechanical equipment management and maintenance. Intelligent diagnosis of mechanical running state based on vibration signals is becoming increasingly important, and it is still a great challenge at pattern recognition. As one of the indispensable components in mechanical equipment, planetary gearboxes are widely used in wind power, aerospace, and heavy industry. However, the problem of automatically maximizing the accuracy of planetary gearbox under different working conditions has not been solved. Therefore, an intelligent diagnosis method for planetary wheel bearing based on constrained independent component analysis (CICA) and stacked sparse autoencoder (SSAE) is presented in this research. Firstly, the fault signal with obvious time-domain characteristics is extracted by constrained independent component analysis (CICA), and the fault signals and noise is separated. Then, calculating the correlation kurtosis value of the time domain signals at different iteration periods as the eigenvalue to obtain the training samples and the test samples. The parameters of the network layer, the number of hidden nodes and learning rate are determined to build the model of SSAE. In the end, the training samples are input into the model for training and the whole network is fine-tuned. The advantages and disadvantages of the model are verified by the test samples. The intelligent classification and diagnosis of the mechanical running state are completed. Experiments analysis with real datasets of planetary wheel bearing show that the proposed method can achieve higher accuracy and robustness for fault classification compared with other data-driven methods. The application of this method in other major machinery industry also has bright prospects.

Under the pressure of climate change, renewable energy gradually replaces fossil fuels and plays nowadays a significant role in energy production. Among different types of energy sources, wind power covered 14% of the EU’s electricity demand in 2018. The Operations and Maintenance (O&M) costs of wind turbines may easily reach up to 20–25% of the total leverised cost per kWh produced over the lifetime of the turbine for a new unit. According to Wood Mackenzie Power & Renewables (WMPR) onshore wind farm operators are expected to spend nearly $15 billion on O&M services in 2019. Manufacturers and operators try to reduce O&M on one hand by developing new turbine designs and on the other hand by adopting condition monitoring approaches. One of the most critical and rather complex assembly of wind turbines is the gearbox. Gearboxes are designed to last till the end of asset’s lifetime, according to the IEC 61400-4 standards. On the other hand, a recent study over approximately 350 offshore wind turbines indicated that gearboxes might have to be replaced as early as 6.5 years. Therefore a plethora of sensor types and signal processing methodologies have been proposed in order to accurately detect and diagnose the presence of a fault. Among others, Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated, usually after filtering around a selected frequency band excited by impacts due to the fault. Sometimes the gearbox is equipped with many acceleration sensors and its kinematics is clearly known. In these cases Cyclostationary Analysis and the corresponding methodologies, i.e. the Cyclic Spectral Correlation and the Cyclic Spectral Coherence, have been proposed as powerful tools. On the other hand often the gearbox is equipped with a limited number of sensors and a simple global diagnostic indicator is demanded, being capable to detect globally various faults of different components. The scope of this paper is the application and comparison of a number of blind global diagnostic indicators which are based on Entropy (Permutation entropy, Approximate entropy, Samples entropy, Fuzzy entropy, Conditional entropy and Wiener entropy), on Negentropy (Infogram), on Sparsity (Sparse-L2/L1, Sparse-L1/L0, Sparse-Gini index) and on Statistics (Mean, Standard deviation, Kurtosis, etc.). The performance of the indicators is evaluated and compared on a wind turbine data set, consisted of vibration data captured by one accelerometer mounted on six 2.5 MW wind turbines, located in a wind park in northern Sweden, where two different bearing faults have been filed, for one wind turbine, during a period of 46 months. Among the different diagnostic indicators Permutation entropy, Approximate entropy, Samples entropy, Fuzzy entropy, Conditional entropy and Wiener entropy achieve the best results detecting blindly the two failure events.

This paper describes the design of the Free Power Turbine (FPT) of the LM9000, in particularly the design of its Passive Clearance Control (PCC) system. The LM9000 is the aero-derivative version of the GE90-115B jet engine. Its core engine has many common parts with the GE90; what differs is the booster (low pressure compressor) and the lower pressure turbine (LPT). The booster of the LM9000 is without fan because the engine is not used to provide thrust but torque only, subsequently it has a new flow path [5]. The LPT has instead been replaced by an intermediate pressure turbine (IPT) and by the FPT. The IPT drives the booster, while the FPT is a free low-pressure turbine designed for both power generation and mechanical drive industrial applications, including LNG production plants. Due to its different application, the LM9000 FPT flow path differs sensibly from the GE90 LPT, however as the GE90 it is provided of a clearance control system that cools the casing in order to reduce its radial deflection. It is not the first time that a clearance control system has been used in industrial applications; in GE aero-derivative power turbines is already present in the LM6000 and LMS100. Design constraints, system complexity, high environment variability because the PCC is located outside the GT, harsh environments and long periods of usage still make the design of this component challenging. The design of the PCC has been supported by extensive heat transfer and mechanical simulations. Each PCC component has been addressed with a dedicated life calculation and all the blade and seal clearances have been estimated for all the operating conditions of the engine. Simulations have been validated by an extensive test campaign performed on the first engine.

Large mechanical drive steam turbines used in the oil & gas industry are operating at increasingly higher inlet pressure, generating higher shaft power. Those higher power requirements result in larger disk diameters and surface areas. High thrust forces can be a result, due to both the high inlet pressure and large disk surface area. Industry standards require oversizing of thrust bearings to handle uncertainty in thrust predictions. These factors make improvement in thrust prediction accuracy and mitigation strategies important. A full-size, axial flow steam turbine test rig capable of measuring turbine thrust, and static pressure in the upstream rotor-stator cavity was built and commissioned. The test rig was operated in single stage configuration for the tests reported here. The rotor disk had balance holes and stationary axial face seals near the disk rim. The face seals divide the upstream rotor-stator cavity into inner and outer circumferential cavities. The rotor-stator cavity upstream of the rotor disk was instrumented, on the stationary wall, to measure the radial and circumferential pressure distribution. Bearing thrust was measured with load cells. Tests varied nominal pressure ratios (1.2, 1.5, 2.0 and 3.0), velocity ratios (0.35–0.6), admission fractions (0.25–1.0) and shaft leakage flow rates. Circumferential pressure asymmetry, due to partial admission operation, was confined to the outer cavity. The inner cavity pressure coefficient was circumferentially uniform at all operating points. The average pressure coefficient in the upstream rotor-stator cavity generally decreased as the shaft leakage flow rate coefficient increased. Increased leakage flow rate coefficient also increased the magnitude of the upstream directed or negative thrust.

Ultra-High Bypass Ratio Geared (UHBRG) turbofan technology allows a significant reduction in fuel burn, noise and emissions — key metrics for aircraft engine performance. However, one of the main challenges in this technology is the large amount of waste heat generated by the Power Gearbox (PGB). Therefore, having a practical tool for precise prediction of the PGB-generated thermal loads in UHBRGs is becoming a necessity. Such a tool would assist in analyzing engine performance, as well as ensuring that engine physical limitations/restrictions are not breached (e.g. over-temperature in fuel and oil, cocking, etc.). This paper presents a methodological approach to mathematically model the waste heat generated by a PGB on a UHBRG for different points on a typical flight profile. To do this, the total power loss in a PGB system is firstly defined as the summation of load-dependent and load-independent losses. Physics-based equations for each heat loss mechanism are introduced and, through a combination of the associated equations, a simulation model for the thermal loads calculation in PGBs is developed. In addition, the heat losses and efficiency of the PGB has been analyzed across a simulated flight. The developed PGB model calculates the main power losses generated in a gear reduction system of a turbofan engine. It is found that in a typical flight, the heat loss generated by the PGB can reach about 80% of the total waste heat generated by the engine. The values of the mechanical efficiency calculated by the tool at different flight points are above 97% which is in good agreement with publicly available data for planetary gearboxes. This tool is intended to be utilized by engine thermal management system designers to predict and analyze the heat loads generated by the PGB at different flight conditions.

The geared turbofan is a promising concept for civil aircraft jet engines. With the introduction of a gearbox between the low-pressure turbine and the fan, both components can rotate at their respective optimum speed. The geared turbofan enables a lower specific fuel consumption as well as jet engine noise reductions. A planetary gear train is usually chosen for the transmission with the sun gear connected to the low-pressure turbine. This high-speed reduction gear train needs to transmit high loads with a high efficiency in limited installation space. To ensure a safe operation of the gear train, the thermal behavior of the gears needs to be understood. The heat generated by the meshing processes is dissipated by oil impingement cooling. While the field of Elastohydrodynamic lubrication yields good results for the heat generation, no validated model for the impingement cooling process is available in literature. In this study, an analytical model is developed and validated against experimental data. First, the surface area of the oil film on the gear tooth flank formed by the impinging oil jet is calculated. Second, the heat transfer from the gear tooth flank to the oil film is determined. The fluid motion is modeled as an oil film that is flung off the gear tooth flank by centrifugal forces. In addition to the film flow, the presented model takes into account the temperature dependence of the viscosity of the oil and the initial oil film height. The effect of a lubrication oil film on the gear tooth flank before the oil jet impinges is included and its effect on the heat transfer is assessed. The analytical model agrees well with experimental results over the entire range of investigated operating conditions. Finally, a discussion on the effect of several assumptions in the derivation of the analytical model is presented. The validated analytical model can be used as an efficient tool for the design of gear trains with impingement cooled spur gears.

Nowadays a preliminary evaluation of environmental impact of a new product becomes more and more important, especially when the case study refers to an industrial gas turbine both for power generation and mechanical drive applications. The environmental impact evaluation, as well as the preliminary lifecycle cost analysis, will represent a critical driver to develop a competitive product during the conceptual design phase where the engine architecture is an outcome of different alternatives trade-offs. Scope of the following paper is the presentation of a set of Design-for-Environment considerations obtained through gas turbine functional decomposition in modules, identification of the most critical, assessment of their contribution compared to the whole engine in terms of environmental impact as well as the effect on the engine use depending on ambient and operating conditions. The outcome of this study is an approach to preliminarily evaluate the engine life-cycle impact as well as a set of indications to drive machine architecture, material selection and production processes towards the sustainability during manufacturing and operational phases.

Maintenance, repair, and overhaul activities are necessary and critical, often repeated, operations which occur during the lifecycle of turbomachinery components and assemblies. The ability to extend the life and performance of parts via sustainment type activities currently in service offers a significant and beneficial financial impact for both the manufacturers of these components as well as their end-users. Additive manufacturing not only enables manufacturers the ability to “print” complex geometries in a wide array of materials including metals but, in some instances, also offers a novel opportunity for the repair and overhaul of existing components. The MELD process is quickly becoming an established AM technology which has repeated demonstrated success in additive manufacturing, repair, coating, and joining operations. The MELD process creates fully-dense products with near wrought properties, and reduced distortion, at very high deposition rates. MELD is a solid-state process, which yields parts with superior mechanical properties as compared to those produced by liquid-state metal deposition or spray forming processes. It is an open atmosphere process, allowing for extreme scalability. By the nature of the process all depositions, repairs, and coatings are fully dense and do not require any additional processing for densification such as sintering or HIP. Potential disadvantages include the inability to construct complex, finely featured products. The MELD process is well suited for the fabrication, repair, and overhauling of large-scale components as it is not restricted to space restrictive powder beds or vacuum chambers. In addition, the MELD process carries a lower operating cost (comparable to a CNC mill) and requires less infrastructure than traditional melt-based AM technologies. In this presentation, the MELD process will be explored as a viable method for additive manufacturing, coating, repair, and joining operations. Unique attributes will be considered along with resulting advantages and disadvantages. Specific high-level real-world examples presented will include MELD applications which highlight the repair of a cast non-fusion weldable Mg helicopter gearbox housing, the joining and repair operations of simulated damage (holes and cracks) using 2XXX and 7XXX series aluminum alloys, the application of nickel-based super-alloy coatings on high-strength low alloy steels, and the additive manufacture and repair of titanium alloys.

The paper investigates the optimum size and potential economic, energetic and environmental benefits of ORC applications, as bottomer section in natural gas compressor stations. Since typical installations consist of multiple gas turbine units in mechanical drive arrangement, operated most of the time under part-load conditions, the economic feasibility of the ORC can become questionable even though the energetic advantage is indisputable. Depending on mechanical drivers profile during the year the optium size of the bottomer section must be carefully selected in order not to overestimate its design power output. To achieve this goal a numerical optimization procedure has been implemented in the Matlab environment, based on the integration of a in house-developed calculation code with a commercial software for the thermodynamic design and off-design analysis of complex energy systems (Thermoflex). Thus the optimal ORC design power size is identified in the most generic scenario, in terms of compressors load profile, installation site conditions (i.e. ambient conditions and carbon tax value) and gas turbine models used as drivers. Two different objective functions are defined aiming at maximize the CO 2 savings or the net present value. Different case studies are shown and discussed to prove the potential of the developed code. The comparison among the case studies highlights, chiefly, the influence of yearly mechanical drivers profile, part-load control strategy applied and carbon tax value on the ORC techno-economic feasibility.

Korea Institute of Machinery & Materials (KIMM) investigated a supercritical carbon dioxide (sCO2) cycle for a heat recovery power generation system for several years. The objective of the study focuses on the development of the technologies and the establishment of the development procedure of turbomachinery, heat exchangers, and auxiliary equipment for the sCO2 power cycle. A motor-driven centrifugal starter pump with an inducer is developed for startup operation. The main pump-drive turbine module adopts magnetic bearings as axial and radial bearings to remove oil lubrication and exhibits a hermetic structure to eliminate leakage problems. The power turbine and a generator are linked via a gearbox in the power turbine-generator module. An oil bearing and floating ring seal with dry gas injection are applied to minimize sCO2 leakage. The recuperator is developed as a printed circuit heat exchanger (PCHE) owing to its high efficiency and compactness. The integrated test facility is designed as a 250-kWe class sCO2 recuperated Rankine cycle to evaluate the performance of the core modules as opposed to demonstrating the viability of a particular sCO2 cycle. The test facility is proven to successfully operate in startup mode and self-sustaining mode using the starter pump and the main pump-drive turbine module. An overview of the operation of the startup mode and self-sustaining mode is presented.

The dynamic behavior of a wind turbine comprises three major parts: the external torque produced by the wind, the mechanical elements and the grid. For the aerodynamic response, there is three type of models: constant aerodynamic torque for Type I and Type IV turbines, a pseudo aerodynamic model for Type I and II, and linearized aerodynamic model for Type III. The drivetrain has been model either as a single-mass shaft model or as a double-mass shaft model. Most of the dynamic models of wind turbines consider the wind torque only as a function of the wind velocity, and they neglect the vibrations of the blades as an excitation torque. Therefore, a dynamic model that includes the aerodynamic power, the torque produced by the deflection of the blades, the vortex-induced vibrations of the blades and the torque caused by the eccentricity of the center of mass represents the excitation torque. The dynamic model of the wind turbine is a multibody dynamic model with six degrees of freedom. The blades are represented as a two lumped-masses, the torsional response of the main rotor is described as a single torsional mass, which is connected to the electric generator by a gearbox. The gearbox is represented as a double-shaft model, and the gear mesh is simulated with a nonlinear torsional stiffness. The generator is described as another torsional mass. The torque produced by the wind is calculated using QBlade for different pitch angles. The dynamic parameters of the blade were determined experimentally, and it was found that the blade has only two dominant vibration modes. For this reason, the blades were modeled as two lumped-masses. It was found that the vortex-induced vibrations modify the torsional vibrations of the generator and they are an extra source of perturbations for the electric generation, and they depend on the wind velocity and the pitch angle.

Digitally enhanced services for wind power could reduce Operations and Maintenance (O&M) costs as well as the Levelised Cost Of Energy (LCOE). Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things (IoT) and Big Data Analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components which are often responsible for machinery stops are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result an extended number of signal processing techniques and tools have been proposed during the last decades, focusing towards accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic Spectral Correlation and Cyclic Spectral Coherence, based on Cyclostationary Analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called IESFOgram, which is based on Cyclic Spectral Coherence and can automatically select the filtering band. Furthermore, the Cyclic Spectral Coherence is integrated along the selected frequency band leading to an Improved Envelope Spectrum. In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

Planetary gearbox is widely used in large and complex mechanical equipment such as wind power generation, helicopters and petrochemical industry. Gear failures occur frequently in working conditions at low speeds, high service load and harsh operating environments. Incipient fault diagnosis can avoid the occurrence of major accidents and loss of personnel property. Aiming at the problems that the incipient fault of planetary gearbox is difficult to recognize and the number of intrinsic mode functions (IMFs) decomposed by variational mode decomposition (VMD) must be set in advance and can not be adaptively selected, a improved VMD algorithm based on energy difference as an evaluation parameter to automatically determine the decomposition level k is proposed. On this basis, a new method for early fault feature extraction of planetary gearbox based on the improved VMD and frequency-weighted energy operator is proposed. Firstly, the vibration signal is pre-decomposed by VMD, and the energy difference between the component signal and the original signal under different K-values is calculated respectively. The optimal decomposition level k is determined according to the energy difference curve. Then, according to kurtosis criterion, sensitive components are selected from the k modal components obtained by the decomposition to reconstruct. Finally, a new frequency-weighted energy operator is used to demodulate the reconstructed signal. The fault characteristic frequency information of the planetary gearbox can be accurately extracted from the energy spectrum. The method is applied to the simulation fault data and actual data of planetary gearbox, and the weak fault characteristics of planetary gearbox are extracted effectively, and the early fault characteristics are distinguished. The results show that the new method has certain application value and practical significance.

Operation and maintenance costs are a major driver for levelized cost of energy of wind power plants and can be reduced through optimized operation and maintenance practices accomplishable by various prognostics and health management (PHM) technologies. In recent years, the wind industry has become more open to adopting PHM solutions, especially those focusing on diagnostics. However, prognostics activities are, in general, still at the research and development stage. On the other hand, the industry has a request to estimate a component’s remaining useful life (RUL) when it has faulted, and this is a key output of prognostics. Systematically presenting PHM technologies to the wind industry by highlighting the RUL prediction need potentially helps speed up its acceptance and provides more benefits from PHM to the industry. In this paper, we introduce a PHM for wind framework. It highlights specifics unique to wind turbines and features integration of data and physics domain information and models. The output of the framework focuses on RUL prediction. To demonstrate its application, a data domain method for wind turbine gearbox fault diagnostics is presented. It uses supervisory control and data acquisition system time series data, normalizes gearbox temperature measurements with reference to environmental temperature and turbine power, and leverages big data analytics and machine-learning techniques to make the model scalable and the diagnostics process automatic. Another physics-domain modeling method for RUL prediction of wind turbine gearbox high-speed-stage bearings failed by axial cracks is also discussed. Bearing axial cracking has been shown to be the prevalent wind turbine gearbox failure mode experienced in the field and is different from rolling contact fatigue, which is targeted during the bearing design stage. The method uses probability of failure as a component reliability assessment and RUL prediction metric, which can be expanded to other drivetrain components or failure modes. The presented PHM for wind framework is generic and applicable to both land-based and offshore wind turbines.

This paper presents the dynamic characterization of a two degree of freedom planetary gearbox prototype during the variation of the load condition. Tests with varying load are developed at three different operating speeds of the input shaft: 190, 380 and 590 rpm. The dynamic torques and vibrations on the input and output shafts are acquired during the experiments, such as the angular velocity of the output shaft. The experimental data are analyzed to evaluate the dynamics of the system during the exchange of operation between the first and second DOF operation. Then, the radial vibrations are analyzed during the operation of the second DOF by means of a methodology using different signal processing tools: first, the continuous wavelet transform is used to identify the nonlinear behavior and the main frequency content of the system; then, the vibrations are filtered by means of passband filters in order to keep the main frequencies of the system and delete any other; finally, the filtered signals are analyzed with both, the Kuramoto’s order parameter to quantify the dynamic synchronization of the gearbox and the phase diagram to characterize its stability. The results demonstrates the utility of the second DOF in the design of the planetary gearbox in order to avoid excessive torques in the components of the system. Furthermore, it is found that the synchronization of the system increases at higher operating speed, however, the system becomes unstable as the operating speed is increased.

Test facilities capable of simulating relevant operational environments for validating novel concepts are indispensable for advancing the state-of-the-art in turbomachinery sealing technology. A test rig suitable for demonstrating full-scale rotor-stator sealing concepts under operational environments relevant for a variety of turbomachinery gas paths was designed and commissioned at GE’s Seals Test Facility. The test rig, called the Advanced Seals Test Rig (or ASTR), can simulate conditions that include a range of rotor speeds, fluid pressures and temperatures, from steady state operating conditions of high pressure turbines of aircraft engines to sections of steam turbines. The present paper provides a system level description of the test rig. The main test section of the rig is housed within the centerpiece of a stamped pressure vessel. A drive train penetrates the pressure vessel and consists of an integral saddle mounted rotor. A motor connected to a high-speed gearbox through couplings on each end permits rotation of the test rotor. The test rotor is supported by two bearing pedestals. The paper describes these rig subsystems with focus on novel features for ease of operation. Key instrumentation and operating procedures that enable the rig to operate safely are also described. Key drivers of the rig design, such as test requirements, rotordynamics, mechanical design, ergonomics, safety and test productivity are outlined. Mechanical design considerations include strict requirements for thermal and pressure deformation under demanding conditions of pressure and temperature. Commissioning of the rig included phases of fabrication, installation, shakeout, calibration and benchmarking. Key learnings from the rig design and commissioning process, as well as operations, are summarized.