Jeffrey Banks

Platform degrader analysis for the design and development of Vehicle Health Management Systems

The US Armypsilas Heavy Brigade Combat Team (HBCT) is investigating the implementation of Vehicle Health Management Systems across its fleet of platforms. A vehicle degrader analysis was conducted to determine where the application of vehicle health management systems (VHMS) could potentially have the greatest impact on increasing maintainer effectiveness and operational availability. The analysis was conducted for M1 Abrams tanks and M2/M3 Bradley Fighting Vehicles using data from three sources: (1) multi-year statistical data on repairs, operating and support costs, and logistics data, (2) interviews with maintainers, service representatives and operators, and (3) questionnaires completed by the platform OEMpsilas. The paper will describe how these alternative data and information sources were used when ideal data and information sources were not available. The statistical data provided an indication of vehicle consumable and repairable cost drivers, part replacement quantity and some indication of component failure isolation for vehicle systems. The interviews with vehicle maintainers, field service representatives and operators provided insight into platform reliability, maintainability and human factors issues. The maintainability, reliability and diagnostic coverage information from the OEMpsilas, provided information about mission criticality and general diagnostic capability for specific vehicle sub-systems and components. The results of the degrader analysis include a list of components and sub-systems that contribute most to maintainability, reliability and vehicle operational availability issues. The degrader results, were used to develop the conceptual design of the optimum application of embedded vehicle diagnostics and prognostics for more effective and efficient HCBT platform maintenance, logistic support and platform life cycle management.

System reliability and condition based maintenance

The need for high system reliability and platform availability in DoD assets is an increasing necessity with the continuing combat deployment of service personnel coupled with the high usage rates for the equipment that they rely upon to complete their mission. In general, reliability is obtained through a variety of measures including precision design, reduction in the number of parts required for functionality and component/system redundancy. The availability of an asset is affected by both reliability and maintainability. There is a significant amount of anecdotal evidence that condition based maintenance enabled by embedded diagnostics and prognostics can directly improve maintainability but not reliability. The focus of this paper is to discuss the impact of reliability on key platform performance parameters and to compare the impact of embedded system health monitoring on those same key performance parameters. If the reliability of a component is defined by its capability to function to a required standard when requested, then health management technology should be able to provide the same benefit as increasing inherent reliability. If a functional but faulted component is replaced before it fails, when the platform is not required to be operational, then the availability of the component and the asset will be maintained or increased with the same inherent reliability. The paper discusses the requirements imposed on the embedded health monitoring system in terms of replacing investments in increased inherent reliability with investments in system health monitoring. This is a well known scenario, but difficult to implement effectively in a real world environment. The effort will require reliability engineers and health management technologists to work together to accomplish this common objective. The context for the application of this concept is the U.S. Army Heavy Brigade Combat Team - Condition Based Reliability Analysis (HBCT- COBRA) program. The objective of this program is to increase the reliability and availability of the HBCT platforms through implementation of embedded diagnostics, prognostics and CBM methodology.

Embedded diagnostics enable military ground vehicle

The DoD has initiated programs to modernize logistics practices and processes. Among them is the requirement to build and deploy autonomic logistics (AL). AL is necessary to provide a focused and tailored logistics response to area of operations (AO). It is based upon knowing status, condition and health of all combat equipment in the AO. Embedded sensors monitor levels of consumables (fuel, ammo, water) and condition (health of components, subsystems and systems) and report those through the logistics operational architecture to Global Combat Support Systems (GCSS) and Global Command Control Systems (GCCS). Autonomic logistics fills the critical gap of interpreting, assimilating and synchronizing data from individual platforms into aggregated and actionable calls for supply, support and maintenance. Embedded diagnostics plays a critical role as an enabler for autonomic logistics and is the subject of this article.

Lubrication level diagnostics using vibration analysis

The purpose of this paper is to show how vibration analysis can be used to detect lubrication loss in an automotive type drive train differential. This preliminary test consisted of gathering broadband vibration data on two differentials on a U.S. Marine Corps light armored vehicle (LAV). One differential was used as a control, where the lubrication level remained full throughout testing and the other was the test differential where the lubrication levels were varied from a full to half full to completely empty. The results of the data analysis indicate that lubrication loss can be detected using vibration analysis when using a frequency band between 15 kHz and 24 kHz. This result shows that an accelerometer can be used not only for detecting faults in mechanical components including gears, bearings and shafts but can also be used to detect lubrication loss for the same system with unique processing. Future research can evaluate the effects of vehicle speed and load on the processing and analysis results and the effect of lubrication loss on the performance of algorithms for bearing and gear fault detection.

Platform degrader analysis for the complex systems for the design and application of condition based maintenance

The US Armys Heavy Brigade Combat Team (HBCT) is investigating the implementation of Vehicle Health Management Systems across its fleet of platforms. A vehicle degrader analysis was conducted to determine where the application of vehicle health management systems (VHMS) could potentially have the greatest impact on increasing maintainer effectiveness and operational availability. The analysis was conducted for M1 Abrams tanks and M2/M3 Bradley Fighting Vehicles using data from three sources: 1) multi-year statistical data on repairs, operating and support costs, and logistics data, 2) interviews with maintainers, service representatives and operators, and 3) questionnaires completed by the platform OEMs. The paper will describe how these alternative data and information sources were used when ideal data and information sources were not available. The statistical data provided an indication of vehicle consumable and repairable cost drivers, part replacement quantity and some indication of component failure isolation for vehicle systems. The interviews with vehicle maintainers, field service representatives and operators provided insight into platform reliability, maintainability and human factors issues. The maintainability, reliability and diagnostic coverage information from the OEMs, provided information about mission criticality and general diagnostic capability for specific vehicle sub-systems and components. The results of the degrader analysis include a list of components and sub-systems that contribute most to maintainability, reliability and vehicle operational availability issues. The degrader results, were used to develop the conceptual design of the optimum application of embedded vehicle diagnostics and prognostics for more effective and efficient HCBT platform maintenance, logistic support and platform life cycle management.

Air Force C-130 Rainbow Fitting Diagnostic Technology Development

The C-130 Hercules has been a workhorse for the U.S. Air Force for decades and is projected to continue to accrue flight hours for years to come as a highly capable platform utilized for numerous mission profiles. In the past few years, many C-130 aircraft have developed fatigue cracks in the center wing box rainbow fittings. These cracks can be a significant flight safety risk, when the damage is extensive. In order to detect the existence of cracks in the rainbow fittings so that they can be repaired, implementation of labor intensive eddy current nondestructive inspection technology has been used to assess the condition of each aircraft on a scheduled basis. The Air Force is interested in the development and application of alternative fault detection techniques that are less time demanding to implement by the maintainers, while providing a high damage detection probability. Additionally, the future capability to embed effective rainbow fitting fault detection capability into the aircraft as an integrated systems health management (ISHM) solution is also desired.

Power system prognostics for the U.S. Army OH-58D helicopter

The OH-58D Kiowa Warrior helicopter has been a workhorse for the U.S. Army for decades and is projected to continue to accrue flight hours for years to come as a highly capable platform applied against various mission profiles. The U.S. Army is interested in the implementation of condition based maintenance (CBM) for this platform to increase operational availability of the aircraft, reduce the required number of maintenance activities and increase the inspection interval period. The CBM methodology and these objectives are directly dependent upon the capability of the health and usage monitoring system and its ability to detect diagnose and provide an estimate of remaining useful life (RUL). The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) has developed prognostic technologies for helicopter electrical power systems that can be integrated into an existing on-board Health and Usage Monitoring System (HUMS). The goal of the program was to develop a capability to monitor, detect and provide an estimated remaining useful life RUL for the starter/generator, battery and power inverter. The focus of this effort was to develop technologies that provide actionable prognostic information for forecasting part replacement and to extend existing time and usage-based maintenance intervals.

Embedded wireless corrosion detection technology

The Department of Defense spends a substantial portion of their maintenance and sustainment budget on fault detection and repair for aircraft. The sustainment cost of corrosion repair for critical structures, mechanical systems, avionic components and wiring harnesses is in the hundreds of millions of dollars per year. The ability to detect corrosion early in the material deterioration process is a key factor in reducing the financial burden associated with corrosion damage repair. The greatest potential for addressing this problem is through implementation of wireless corrosion detection sensors that can be embedded between the substrate and protective coating, and placed in a number of different critical areas. The intent is to provide the capability to detect the on-set of corrosion/material degradation at the earliest possible time in the fault evolution with minimally intrusive sensor technology. A multidisciplinary Applied Research Laboratory and Pennsylvania State University team is developing a unique embedded wireless corrosion detection sensor that combines spray-on ultrasonic transducers and advanced passive RF wireless interrogation and/or signal transmission. This paper will discuss the development and performance of this sensors for early corrosion detection.