NASA helicopter transmission system technology program

The purpose of the NASA Helicopter Transmission System Technology Program is to improve specific mechanical components and the technology for combining these into advanced drive systems to make helicopters more viable and cost competitive for commerical applications. The history, goals, and elements of the program are discussed

Rolling-contact bearing reference summary

Design and performance of rolling contact bearing

Prediction of ball and roller bearing thermal and kinematic performance by computer analysis

Characteristics of good computerized analysis software are suggested. These general remarks and an overview of representative software precede a more detailed discussion of load support system analysis program structure. Particular attention is directed at a recent cylindrical roller bearing analysis as an example of the available design tools. Selected software modules are then examined to reveal the detail inherent in contemporary analysis. This leads to a brief section on current design computation which seeks to suggest when and why computerized analysis is warranted. An example concludes the argument offered for such design methodology. Finally, remarks are made concerning needs for model development to address effects which are now considered to be secondary but are anticipated to emerge to primary status in the near future

Advanced gearbox technology

An advanced 13,000 HP, counterrotating (CR) gearbox was designed and successfully tested to provide a technology base for future designs of geared propfan propulsion systems for both commercial and military aircraft. The advanced technology CR gearbox was designed for high efficiency, low weight, long life, and improved maintainability. The differential planetary CR gearbox features double helical gears, double row cylindrical roller bearings integral with planet gears, tapered roller prop support bearings, and a flexible ring gear and diaphragm to provide load sharing. A new Allison propfan back-to-back gearbox test facility was constructed. Extensive rotating and stationary instrumentation was used to measure temperature, strain, vibration, deflection and efficiency under representative flight operating conditions. The tests verified smooth, efficient gearbox operation. The highly-instrumented advanced CR gearbox was successfully tested to design speed and power (13,000 HP), and to a 115 percent overspeed condition. Measured CR gearbox efficiency was 99.3 percent at the design point based on heat loss to the oil. Tests demonstrated low vibration characteristics of double helical gearing, proper gear tooth load sharing, low stress levels, and the high load capacity of the prop tapered roller bearings. Applied external prop loads did not significantly affect gearbox temperature, vibration, or stress levels. Gearbox hardware was in excellent condition after the tests with no indication of distress

Prognosis of Bearing Acoustic Emission Signals Using Supervised Machine Learning

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acoustic emission (AE) technique can be successfully utilized for condition monitoring of various machining and industrial processes. To keep machines function at optimal levels, fault prognosis model to predict the remaining useful life (RUL) of machine components is required. This model is used to analyze the output signals of a machine whilst in operation and accordingly helps to set an early alarm tool that reduces the untimely replacement of components and the wasteful machine downtime. Recent improvements indicate the drive on the way towards incorporation of prognosis and diagnosis machine learning techniques in future machine health management systems. With this in mind, this work employs three supervised machine learning techniques; support vector machine regression, multilayer artificial neural network model and gaussian process regression, to correlate AE features with corresponding natural wear of slow speed bearings throughout series of laboratory experiments. Analysis of signal parameters such as signal intensity estimator and root mean square was undertaken to discriminate individual types of early damage. It was concluded that neural networks model with back propagation learning algorithm has an advantage over the other models in estimating the RUL for slow speed bearings if the proper network structure is chosen and sufficient data is provided.Peer reviewe

Observer-biased bearing condition monitoring: from fault detection to multi-fault classification

Bearings are simultaneously a fundamental component and one of the principal causes of failure in rotary machinery. The work focuses on the employment of fuzzy clustering for bearing condition monitoring, i.e., fault detection and classification. The output of a clustering algorithm is a data partition (a set of clusters) which is merely a hypothesis on the structure of the data. This hypothesis requires validation by domain experts. In general, clustering algorithms allow a limited usage of domain knowledge on the cluster formation process. In this study, a novel method allowing for interactive clustering in bearing fault diagnosis is proposed. The method resorts to shrinkage to generalize an otherwise unbiased clustering algorithm into a biased one. In this way, the method provides a natural and intuitive way to control the cluster formation process, allowing for the employment of domain knowledge to guiding it. The domain expert can select a desirable level of granularity ranging from fault detection to classification of a variable number of faults and can select a specific region of the feature space for detailed analysis. Moreover, experimental results under realistic conditions show that the adopted algorithm outperforms the corresponding unbiased algorithm (fuzzy c-means) which is being widely used in this type of problems. (C) 2016 Elsevier Ltd. All rights reserved.Grant number: 145602

Magnetic Levitation for Long-Life Space Mechanisms: Technology Assessment and Remaining Challenges

Spacecraft mechanisms and mechanical systems must operate reliably and without failure to enable successful, long-term space missions. Such requirements place demands upon the tribological elements, especially bearings, which are frequently difficult or impossible to satisfy. Several recent, high-profile bearing failures in coolant fluid pumps and attitude control system (ACS) momentum wheels provided the impetus to assess the state-of-the-art non-contacting magnetic levitation-based, rotor support technologies.Magnetic levitation technology continues to gain acceptance for terrestrial applications and has been spaceflight demonstrated in mechanical systems such as reaction wheels (RWs) but is not in widespread use. The specific reasons inhibiting this new technology are not readily clear but include cost, weight, performance, and perceived risk. These reasons arise from a variety of real and perceived technical limitations in areas like materials, controls, sensors, thermal management and others. This white paper seeks to determine, define, and quantify the technical hurdles and gaps that must be overcome to enable the broad adoption of non-contacting bearings for long-life space mechanisms. It is anticipated that a better understanding of this complex topic may guide resource investments and clear the path to improved performance mechanical systems for spacecraft

Small Engine Component Technology (SECT) studies

A study was conducted to identify component technology requirements for small, expendable gas turbine engines that would result in substantial improvements in performance and cost by the year 2000. A subsonic, 2600 nautical mile (4815 km) strategic cruise missile mission was selected for study. A baseline (state-of-the-art) engine and missile configuration were defined to evaluate the advanced technology engines. Two advanced technology engines were configured and evaluated using advanced component efficiencies and ceramic composite materials; a 22:1 overall pressure ratio, 3.85 bypass ratio twin-spool turbofan; and an 8:1 overall pressure, 3.66 bypass ratio, single-spool recuperated turbofan with 0.85 recuperator effectiveness. Results of mission analysis indicated a reduction in fuel burn of 38 and 47 percent compared to the baseline engine when using the advanced turbofan and recuperated turbofan, respectively. While use of either advanced engine resulted in approximately a 25 percent reduction in missile size, the unit life cycle (LCC) cost reduction of 56 percent for the advanced turbofan relative to the baseline engine gave it a decisive advantage over the recuperated turbofan with 47 percent LCC reduction. An additional range improvement of 10 percent results when using a 56 percent loaded carbon slurry fuel with either engine. These results can be realized only if significant progress is attained in the fields of solid lubricated bearings, small aerodynamic component performance, composite ceramic materials and integration of slurry fuels. A technology plan outlining prospective programs in these fields is presented

An update on the life analysis of spur gears

An analytical method for predicting surface fatigue life of gears was presented. General statistical methods were outlined, showing the application of the general methods to a simple gear mesh. Experimentally determined values for constants in the life equation were given. Comparison of the life theory with test results and AGMA standards was made. Gear geometry pertinent to life calculations was reviewed