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NASA NTRS1990

Dynamics of Multistage Gear Transmission with Effects of Gearbox Vibrations

A comprehensive approach is presented in analyzing the dynamic behavior of multistage gear transmission systems with the effects of gearbox induced vibrations and mass imbalances of the rotor. The modal method, with undamped frequencies and planar mode shapes, is used to reduce the degrees of freedom of the gear system for time-transient dynamic analysis. Both the lateral and torsional vibration modes of each rotor-bearing-gear stage as well as the interstage vibrational characteristics are coupled together through localized gear mesh tooth interactions. In addition, gearbox vibrations are also coupled to the rotor-bearing-gear system dynamics through bearing support forces between the rotor and the gearbox. Transient and steady state dynamics of lateral and torsional vibrations of the geared system are examined in both time and frequency domains to develop interpretations of the overall modal dynamic characteristics under various operating conditions. A typical three-stage geared system is used as an example. Effects of mass imbalance and gearbox vibrations on the system dynamic behavior are presented in terms of modal excitation functions for both lateral and torsional vibrations. Operational characteristics and conclusions are drawn from the results presented.

Choy, F. K.↗

NASA NTRS1994

Studies Of Vibrations In Gearboxes

Three NASA technical memorandums summarize studies of vibrations in gearboxes. Directed toward understanding and reducing gearbox noise caused by coupling of vibrations from meshing gears, through gear shafts and their bearings, to surfaces of gearbox housings. Practical systems in which understanding and reduction of gearbox noise beneficial include helicopter, car, and truck transmissions; stationary geared systems; and gear-driven actuator systems.

Choy, Fred K.↗

NASA NTRS1995

Diagnosis of helicopter gearboxes using structure-based networks

A connectionist network is introduced for fault diagnosis of helicopter gearboxes that incorporates knowledge of the gearbox structure and characteristics of the vibration features as its fuzzy weights. Diagnosis is performed by propagating the abnormal features of vibration measurements through this Structure-Based Connectionist Network (SBCN), the outputs of which represent the fault possibility values for individual components of the gearbox. The performance of this network is evaluated by applying it to experimental vibration data from an OH-58A helicopter gearbox. The diagnostic results indicate that the network performance is comparable to those obtained from supervised pattern classification.

Jammu, Vinay B.↗

NASA NTRS1995

Vibration Analysis of a Split Path Gearbox

Split path gearboxes can be attractive alternatives to the common planetary designs for rotorcraft, but because they have seen little use, they are relatively high risk designs. To help reduce the risk of fielding a rotorcraft with a split path gearbox, the vibration and dynamic characteristics of such a gearbox were studied. A mathematical model was developed by using the Lagrangian method, and it was applied to study the effect of three design variables on the natural frequencies and vibration energy of the gearbox. The first design variable, shaft angle, had little influence on the natural frequencies. The second variable, mesh phasing, had a strong effect on the levels of vibration energy, with phase angles of 0 deg and 180 deg producing low vibration levels. The third design variable, the stiffness of the shafts connecting the spur gears to the helical pinions, strongly influenced the natural frequencies of some of the vibration modes, including two of the dominant modes. We found that, to achieve the lowest level of vibration energy, the natural frequencies of these two dominant modes should be less than those of the main excitation sources.

Krantz, Timothy L.↗

NASA NTRS1996

Improving the Performance of the Structure-Based Connectionist Network for Diagnosis of Helicopter Gearboxes

A diagnostic method is introduced for helicopter gearboxes that uses knowledge of the gear-box structure and characteristics of the 'features' of vibration to define the influences of faults on features. The 'structural influences' in this method are defined based on the root mean square value of vibration obtained from a simplified lumped-mass model of the gearbox. The structural influences are then converted to fuzzy variables, to account for the approximate nature of the lumped-mass model, and used as the weights of a connectionist network. Diagnosis in this Structure-Based Connectionist Network (SBCN) is performed by propagating the abnormal vibration features through the weights of SBCN to obtain fault possibility values for each component in the gearbox. Upon occurrence of misdiagnoses, the SBCN also has the ability to improve its diagnostic performance. For this, a supervised training method is presented which adapts the weights of SBCN to minimize the number of misdiagnoses. For experimental evaluation of the SBCN, vibration data from a OH-58A helicopter gearbox collected at NASA Lewis Research Center is used. Diagnostic results indicate that the SBCN is able to diagnose about 80% of the faults without training, and is able to improve its performance to nearly 100% after training.

Jammu, Vinay B.↗

NASA NTRS2017

Cryo-Gearbox Using Bulk Metallic Glasses

Harmonic drives are a highly efficient and compact gearing technology that are widely used in robotics and aerospace applications (e.g. Mars Science Lab) due to their excellent torque-to-mass ratio, low backlash, and high positional accuracy. One major problem using any gearing on other planetary bodies is the need for heaters to keep the gearbox from freezing. Currently the Mars Science Lab uses 40% of its daily power output to operate heaters to keep the grease in the gearboxes from freezing. Also wear can limit the lifetime and performance of these systems. One possible solution to this problem could be to use a relatively new material known as Bulk Metallic Glasses (BMGs, also known as Amorphous Metals). BMGs are non-crystalline metallic alloys that exhibit superior mechanical properties. Compared to modern aerospace steels BMGs have a higher strength, higher elastic limit, and lower density. BMGs used in harmonic drives (especially the flex spline) could lead to longer system lifetimes, lower mass, and increased performance. Jet Propulsion Laboratory (JPL) is researching a new method of manufacturing the flex spline by injection molding and is hoping to have reduced costs as well as the benefits listed above. In conjunction with Kennedy Space Center (KSC), JPL is providing gearboxes that KSC will test greaseless in an extreme environment. KSC has completed the assembly and checkout of a test stand that is capable of testing a gearbox in a vacuum of less than 2 milli torr, 100 Kelvin temperature, 250 Nm of load, input and output torque measurements and 120 RPM input speed.

Drew Smith↗

DOE OSTI2022

Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators: Preprint

Studies in condition monitoring literature often aim to detect rolling element bearing faults because they have one of the biggest shares among defects in turbo machinery. Accordingly, several prognosis and diagnosis methods have been devised to identify fault signatures from vibration signals. The underlying idea behind traditional indicators often revolves around tracking both cyclostationarity and abnormal impulses in the vibration signals without distinguishing the two. A recently proposed method to capture the rolling element bearing degradation lays out the groundwork for new indicator families utilizing generalized likelihood ratio test. This novel approach exploits the cyclostationarity and the impulsiveness of vibration signals independently in order to estimate the most suitable indicators for a given fault. However, the method has yet to be tested on complex experimental vibration signals such as those of a wind turbine gearbox. In this study, the approach is applied to the NREL Wind Turbine Gearbox Condition Monitoring Round Robin Study data set for bearing fault detection purposes. The data set is measured on an experimental test rig of a wind turbine gearbox, hence the complexity of the vibration signals is similar to a real case. Furthermore, the new indicators are also tested with signals that carry multiple fault signatures. The outcome demonstrates that the proposed method is capable of distinguishing between healthy and damaged vibration signals measured on a complex wind turbine gearbox.

condition monitoring↗

DOE OSTI2016

Gearbox Reliability Collaborative Investigation of High-Speed-Shaft Bearing Loads

The loads and contact stresses in the bearings of the high speed shaft section of the Gearbox Reliability Collaborative gearbox are examined in this paper. The loads were measured though strain gauges installed on the bearing outer races during dynamometer testing of the gearbox. Loads and stresses were also predicted with a simple analytical model and higher-fidelity commercial models. The experimental data compared favorably to each model, and bearing stresses were below thresholds for contact fatigue and axial cracking.

17 WIND ENERGY↗

DOE OSTI2019

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

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.

17 WIND ENERGY↗

DOE OSTI2020

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2019

Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

Failures in gearbox bearings have been a primary source of reliability issues for wind turbine drivetrains, leading to costly downtime and unplanned maintenance. The most common failure mode is attributed to so-called white-etching cracks (WECs). This mode of failure can occur at 5%-20% of the predicted design life and has been observed in many other industries, bearing locations, bearing types, bearing parts, and steel types. The main drivers for the creation of WECs in steel specimens have been identified and verified by material testing. In a full-scale wind turbine gearbox, however, the conditions leading to WECs, the process by which this failure culminates, and the reasons for their apparent prevalence are all still highly debated. In a collaborative project, Flender Corporation, SKF and the National Renewable Energy Laboratory have instrumented a commercial drivetrain, installed it in a wind turbine, and operated the turbine for over a year. In this report, these measurements are used to validate two different modelling approaches for bearing sliding, one analytical dynamic model and one multi-body model. Once validated, these models can then be used to evaluate the roller slip losses or cumulative frictional energy that are each considered as potential driving factors for wind turbine gearbox bearing failures by WEC.

17 WIND ENERGY↗

DOE OSTI2021

Machine Learning for Gearbox Fault Prediction by Using Both Scada and Modeled Data

This presentation outlines the work in the paper titled "Prognostics of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data" published by the PHM Society and presented at its 2020 annual conference. It is accessible at https://papers.phmsociety.org/index.php/phmconf/article/download/1292/862. The technical work is on machine learning approaches for prognostics for gearbox faults. The methodology combines SCADA time series data and physics domain modeling data, derived from the models developed by the NREL team, as inputs to machine learning models to predict gearbox bearing failures with one month lead time. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score, and AUC (area under receiver operating characteristic curve). Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision, and F1 score, and AUC is about 33%, and 12%, and 6% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2018

Gearbox high-speed-stage bearing slip induced by electric excitation in a test facility

The goal of this paper is to investigate the behaviour of the high-speed stage of a wind turbine gearbox during transient grid-loss events triggered at different power levels in a full-scale nacelle dynamometer test. The gear mesh behaviour and the bearing roller slip during these events are characterized by strain measurements placed in the gear teeth roots and embedded in the outer rings of the tapered roller bearing locating pair. From our experiments, we conclude that the high-speed stage experiences a multidimensional loading consisting of bending and torsional deformation during the transient event. This loading propagates throughout the gearbox and results in unfavourable loading conditions at the bearing that have the potential to go beyond the preload during the torque reversals that occur during the grid-loss event. During the torque reversal, roller slip can occur in the bearings. It is observed that the slip behaviour is directly linked to the initial power level of the generator. Electrically induced excitation that typically leads to dynamic torque events can therefore cause mechanical gearbox degradation.

17 WIND ENERGY↗

DOE OSTI2019

Electromagnetic analysis of a wind turbine magnetic gearbox

The design of the second stage of a 59:1 multi‐stage magnetic gearbox for a wind turbine demonstrator is presented. The multi‐stage series‐connected magnetic gearbox is composed of a 6.45 first stage and 9.14 second stage. A flux‐focusing spoke‐type rotor typology is used with a unique segmented fully laminated design. The impact of structural design changes is considered with respect to torque density. A new rotor typology is presented that enables the magnetic gearbox to be mechanically assembled first without magnets.

Li, Kang↗

DOE OSTI2019

Electromagnetic analysis and experimental testing of a flux focusing wind turbine magnetic gearbox

The electromagnetic design of the second stage of a 59:1 multistage magnetic gearbox for a wind turbine demonstrator is presented here. The multistage series connected magnetic gearbox is composed of a 6.45:1 first stage and 9.14:1 second stage magnetic gear. The magnetic gears utilize a flux focusing spoke type rotor typology with a unique segmented fully laminated design. The electromagnetic impact of structural design changes on the second stage gearbox is considered with respect to torque density. Severe 3-D edge effects were encountered that greatly reduced the expect torque density of the stage 2 magnetic gear. Experimental testing of the multistage magnetic gear highlight unexpected problems associated with eddy current loss and torque ripple.

17 WIND ENERGY↗

DOE OSTI2019

Designing and Experimentally Testing a Magnetic Gearbox for a Wind Turbine Demonstrator

Here, the design of the first stage of a 59:1 multistage magnetic gearbox for a wind turbine demonstrator is presented here. The multistage magnetic gearbox (MSMG) is composed of a two stage magnetic gearbox (MG). The first stage of the MSMG has a gear ratio of 6.45. A spoke type MG rotor typology is used with a unique segmented fully laminated rotor structure. Axial-ly segmented magnets and a unique set of radial deflection rotor support rings are utilized. Design issues with respect to losses and torque ripple are highlighted.

17 WIND ENERGY↗

DOE OSTI2018

Prototyping and Manufacturing of Magnetic Gearbox Components using Innovations in Castings

This project combines additive manufacturing with the broadly deployed practice of metal casting. Combining these methods will unlock new design possibilities while reducing the economic burden of early stage prototyping while leveraging well established high throughput sand casting. Two main approaches are evaluated: direct printing of single use sand molds and printing of reusable impression patterns used to create sand molds. Reusable impression molds typically can be used to produce hundreds to several thousands of casting thereby amplifying the function of the 3D printed replica mold. Emrgy’s newly developed and tested proprietary magnetic gearbox system for low head hydroelectricity generation was the subject part of this study. Leveraging ORNL’s additive manufacturing capability and expertise, a pattern impression was produced and used to create multiple sand molds of the gearbox during phase 1. Even before considering the cost savings possible once rigging and pattern mounting is optimized through repetition and improved design, final part costs using this combined method resulted in an 80% cost reduction over EMRGY’s previous method of subtractive manufacturing for gearbox production.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Report of the Condition of a General Electric Transportation Systems Gearbox

Wind power plant operations and maintenance (O&M) costs remain an appreciable contributor to the overall cost of wind energy. Premature of wind turbine gearboxes failures are often a result of abrasive wear, micropitting, scuffing, white-etch cracks, and macropitting issues. Micropitting is a fatigue phenomenon that occurs in Hertzian contacts in both gears and rolling-element bearings that operate in mixed or micro elastohydrodynamic lubrication regimes. Micropitting is influenced by and manifests itself in many different ways depending on operating conditions such as load, speed and operating temperature, and on factors such as gear geometry and accuracy, tooth flank roughness, percentage of tooth sliding, and lubricant composition. Despite much research by many investigators, micropitting remains complex, unpredictable, and difficult to control and remains a problem in wind turbine gearboxes. The purpose of this report is to document and describe the micropitting damage observed in a wind turbine gearbox, thereby facilitating further analysis and examination in future reports.

17 WIND ENERGY↗