Publications

Analysis of the material and operational costs shows that the use of self-adhering elastomeric trailing edge wedges on the Apache (AH-64D) helicopter in main rotor (MR) blade tracking operations will significantly reduce the number of blades damaged by tab bending that must be repaired at the depot level. Wedge implementation will also allow for a decrease in the number of test flights and maintenance man hours associated with those flights. Additionally, the wedges will lower aircraft vibration levels. This paper describes the benefits of the implementation of MR wedges on the AH-64D. A 10-year return on investment (ROI) is calculated for projected peacetime flying hours and for the current flying rate. Dollar values and flight hour optempo have been removed to comply with the operations security process. These values have been replaced with percentages.

This paper discusses modifications made to the Natural Language Toolkit, a well-known natural language processing software package, to achieve improved information extraction results when applied to helicopter maintenance records. In doing so, it will also attempt to elaborate the components of a tool under development to allow for machine analysis of the free text fields of V-22 Osprey maintenance records. The authors have found that by adapting existing natural language processing software to suit peculiarities of the language found in maintenance records, substantive improvements can be made in the accuracy of information extraction. In particular, by modifying an existing text pre-processor to 1) take in multiple sentence inputs, 2) treat all code tokens as the same, and 3) ignore distinctions in punctuation, part-of-speech tagging accuracy has improved from 92.49% to 96.59%; subsequently, entity chunking precision has improved from 91.5% to 92.3%.

This paper discusses the research activities and capabilities at the University of South Carolina going through the theory behind the design of a test stand, laying out the specifications of the two test stands currently in operation, the tail rotor drive train (TRDT) and the main rotor swashplate (MRSP), and then ending with the an example of new sensor development. The Condition-Based Maintenance (CBM) program at the University of South Carolina has investigated many components in the AH-64. Different sensors, including thermal couples and accelerometers are used to gather data from the components being tested.

Nano-Particle additives are thoroughly investigated due to their promising attributes for lubrication improvement in the Intermediate Gearbox of the AH-64. This paper discusses the evaluation of the effective thermal conductivity and effective dynamic viscosity for nano-composite enhanced transmission Mobile AGL Oil. Experimental results using a unique transient method and viscometer showed significant thermal and rheological improvements of the Oil respectively due to the nano-particle additives. To capture the transport phenomena effectively, two new models based on the effective approach method [14] have been developed to describe non-spherical particles. These continuum models take into account the effects of particle size, particle shape, temperature, layering at the liquidsolid interface and thermo- hydrodynamic effects. The theoretical predictions from the effective thermal conductivity model and effective viscosity model agreed with the experimental data. In order to validate the versatility and goodness of the proposed models, different experimental data and models taken from literature are compared against model results from the current work and confirm that the presented model closely agrees.

Traditional linear spectral analysis techniques of the vibration signals, based on auto-power spectrum, are used as common tools of rotating components diagnoses. Unfortunately, linear spectral analysis techniques are of limited value when various spectral components interact with one another due to nonlinear or parametric process. In such a case, higher order spectral (HOS) techniques are recommended to accurately and completely characterize the vibration signals. In this paper, we use the bicoherence analysis as a tool to investigate nonlinear wave-wave interaction in vibration signals. Accelerometer data has been collected from an AH-64 helicopter drive-train research test bed simulating drive-train conditions under multiple faulted components namely faulted inner race in one hanger bearing, contaminated grease in another hanger bearing, misaligned and unbalanced drive shafts. The proposed bicoherence analysis provides more details about the spectral content of the vibration signal and how different fault frequencies nonlinearly interact with one another.

This paper introduces a stand-off vibration sensor based on the Doppler radar principle and its application to helicopter drive train monitoring. The noncontact advanced vibration sensing radar (ADVISER) provides a wide field of view for comprehensive monitoring of systems and non-moving support structures within a common framework. The baseline performance of ADVISER is compared with a high-quality accelerometer in a well-controlled laboratory environment. In this paper we present the preliminary comparison of ADVISER with the accelerometers on the drive train setup at University of South Carolina. The evaluation includes a study on location sensitivity for ADVISER. The results show the ADVISER viability for drive train CBM.