Operator's manual for Army AH-64A helicopter.

"28 June 1984."

Aviation unit and intermediate maintenance repair parts and special tools list (including depot maintenance repair parts and special tools) for helicopter, utility - tactical transport, UH-1B, UH-1C, UH-1H, UH-1M, EH-1H (Bell), UH-1V, NSN 1520-00-713-9912 (UH-1B), 1520-00-997-8862 (UH-1C), 1520-00-087-7637 (UH-1H), 1520-00-809-2631 (UH-1M), 1520-00-368-8442 (EH-1H), 1520-01-043-4949 (UH-1V) [microform].

"15 March 1988"--[Vol.] 3.

Aviation unit and aviation intermediate mainenance manual (including repair parts and special tools list) : test set, armament subsystem, M16 (4933-00-056-0202).

"January 1972."

Maintenance and repair parts consumption planning guide for contingency operations : helicopter, cargo transport: CH-54B /

Jan. 18, 1979.

Impact of prediction accuracy on costs-noise technology applications in helicopter /

Mode of access: Internet.

Computed induced velocity, induced drag, and angle of attack distributions for a two-bladed rotor

Cover title.

Helicopter vibration sensor selection using data visualisation

The main objective of the project is to enhance the already effective health-monitoring system (HUMS) for helicopters by analysing structural vibrations to recognise different flight conditions directly from sensor information. The goal of this paper is to develop a new method to select those sensors and frequency bands that are best for detecting changes in flight conditions. We projected frequency information to a 2-dimensional space in order to visualise flight-condition transitions using the Generative Topographic Mapping (GTM) and a variant which supports simultaneous feature selection. We created an objective measure of the separation between different flight conditions in the visualisation space by calculating the Kullback-Leibler (KL) divergence between Gaussian mixture models (GMMs) fitted to each class: the higher the KL-divergence, the better the interclass separation. To find the optimal combination of sensors, they were considered in pairs, triples and groups of four sensors. The sensor triples provided the best result in terms of KL-divergence. We also found that the use of a variational training algorithm for the GMMs gave more reliable results.

Inference of helicopter airframe condition

The goal of this paper is to model normal airframe conditions for helicopters in order to detect changes. This is done by inferring the flying state using a selection of sensors and frequency bands that are best for discriminating between different states. We used non-linear state-space models (NLSSM) for modelling flight conditions based on short-time frequency analysis of the vibration data and embedded the models in a switching framework to detect transitions between states. We then created a density model (using a Gaussian mixture model) for the NLSSM innovations: this provides a model for normal operation. To validate our approach, we used data with added synthetic abnormalities which was detected as low-probability periods. The model of normality gave good indications of faults during the flight, in the form of low probabilities under the model, with high accuracy (>92 %). © 2013 IEEE.

Helicopter mechanic at LaGuardia Airport

General note: Title and date provided by Bettye Lane.

Aircraft mechanic working on a propeller

General note: Title and date provided by Bettye Lane.

Conversion of a Micro, Glow-Ignition, Two-Stroke Engine from Nitromethane-Methanol Blend Fuel to Military Jet Propellant (JP-8)

The goal of the thesis "Conversion of a Micro, Glow-Ignition, Two-Stroke Engine from Nitromethane-Methanol Blend Fuel to Military Jet Propellant (JP-8)" was to demonstrate the ability to operate a small engine on JP-8 and was completed in two phases. The first phase included choosing, developing a test stand for, and baseline testing a nitromethane-methanol-fueled engine. The chosen engine was an 11.5 cc, glow-ignition, two-stroke engine designed for remote-controlled helicopters. A micro engine test stand was developed to load and motor the engine. Instrumentation specific to the low flow rates and high speeds of the micro engine was developed and used to document engine behavior. The second phase included converting the engine to operate on JP-8, completing JP-8-fueled steady-state testing, and comparing the performance of the JP-8-fueled engine to the nitromethane-methanol-fueled engine. The conversion was accomplished through a novel crankcase heating method; by heating the crankcase for an extended period of time, a flammable fuel-air mixture was generated in the crankcase scavenged engine, which greatly improved starting times. To aid in starting and steady-state operation, yttrium-zirconia impregnated resin (i.e. ceramic coating) was applied to the combustion surfaces. This also improved the starting times of the JP-8-fueled engine and ultimately allowed for a 34-second starting time. Finally, the steady-state data from both the nitromethane-methanol and JP-8-fueled micro engine were compared. The JP-8-fueled engine showed signs of increased engine friction while having higher indicated fuel conversion efficiency and a higher overall system efficiency. The minimal ability of JP-8 to cool the engine via evaporative effects, however, created the necessity of increased cooling air flow. The conclusion reached was that JP-8-fueled micro engines could be viable in application, but not without additional research being conducted on combustion phenomenon and cooling requirements.