Interoperability Optimization and Service Enhancement in Vehicle Onboard Infortainment Systems

This paper presents an overview on optimizing interoperability between different applications for enhanced return-on-investment through utilization of business intelligence in conjunction with prognostics and health management methodology. Such implementation is particularly suitable for deployment in mass-produced vehicle onboard diagnostics system

Wireless Biosensing Network for Drivers' Health Monitoring

Biosensors integrated into the vehicle controller area network are used for detecting symptoms such as anxiety, pain, and fatigue that may affect driving safety. The proposed system provides a flexible option for implementation in a diverse range of mass-produced automotive accessories without affecting the driver's movement

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Health and Usage Monitoring: Autonomous Vehicles

This thesis presents a work in progress related to the use of Health and Usage Monitoring Systems (HUMS) data to actuate an adaptive control system on an autonomous vehicle operating in an Intelligent Transportation Systems (ITS). The autonomous passenger vehicle has rapidly matured from a speculative concept to a reality that is quickly appearing within our sightlines. Autonomous (also called self-driving, driverless, or robotic) vehicles have long been predicted in science fiction and discussed in popular science media. Recently, major corporations have announced plans to begin selling such vehicles in the near future, and some jurisdictions have passed legislation to allow such vehicles to operate legally on public roads. Autonomous vehicles will be performing intelligent functions (navigation, maneuver, behavior, or task) by perceiving the environment and implementing a responsive action based on HUMS input. Once these vehicles begin to operate on public roads as a norm, safety and reliability becomes a major factor. The implementation or expanded use of HUMS can perceivably render these systems reliable and safe to operate in any environment or mode. This thesis also depicts a notational framework for HUMS in autonomous vehicles operating on ITS networks and future research needed to make this a reality. Keywords: Health and Usage Monitoring System (HUMS), Reliability, Adaptive Systems, Prognostics, Autonomous Vehicle, Intelligent Transportation SystemM.S., Mechanical Engineering and Mechanics -- Drexel University, 201

A Survey of Health Management User Objectives Related to Diagnostic and Prognostic Metrics

One of the most prominent technical challenges to effective deployment of health management systems is the vast difference in user objectives with respect to engineering development. In this paper, a detailed survey on the objectives of different users of health management systems is presented. These user objectives are then mapped to the metrics typically encountered in the development and testing of two main systems health management functions: diagnosis and prognosis. Using this mapping, the gaps between user goals and the metrics associated with diagnostics and prognostics are identified and presented with a collection of lessons learned from previous studies that include both industrial and military aerospace applications

A Concept of Operations for an Integrated Vehicle Health Assurance System

This document describes a Concept of Operations (ConOps) for an Integrated Vehicle Health Assurance System (IVHAS). This ConOps is associated with the Maintain Vehicle Safety (MVS) between Major Inspections Technical Challenge in the Vehicle Systems Safety Technologies (VSST) Project within NASA s Aviation Safety Program. In particular, this document seeks to describe an integrated system concept for vehicle health assurance that integrates ground-based inspection and repair information with in-flight measurement data for airframe, propulsion, and avionics subsystems. The MVS Technical Challenge intends to maintain vehicle safety between major inspections by developing and demonstrating new integrated health management and failure prevention technologies to assure the integrity of vehicle systems between major inspection intervals and maintain vehicle state awareness during flight. The approach provided by this ConOps is intended to help optimize technology selection and development, as well as allow the initial integration and demonstration of these subsystem technologies over the 5 year span of the VSST program, and serve as a guideline for developing IVHAS technologies under the Aviation Safety Program within the next 5 to 15 years. A long-term vision of IVHAS is provided to describe a basic roadmap for more intelligent and autonomous vehicle systems

Improvement of the Vehicle's Onboard Diagnostic System by Using the Vibro-Diagnostics Method

© 2018 IEEE. The article analyzes ways to increase the operational reliability of trucks by monitoring and diagnosing their technical condition. Preventing sudden vehicles failures is possible with the help of built-in diagnostic systems. The article analyzes existing on-board and stationary diagnostic systems. The types of sensors and their signals used to diagnose the condition of vehicles systems are given. Methods of transformation and processing of signals are determined. The connections of structural and diagnostic parameters of the vehicles are established. The possibility of application of vibration diagnostics methods for assessing the technical condition and predicting the remaining life of the vehicle's clutch under operating conditions is explored. The authors proposed a way to improve the on-board diagnostics system with the help of a set of methods, rules and means necessary for measuring the parameters of the system's operation, converting them into diagnostic parameters to assess the technical state of the system under study. The article gives an example of an integrated system for diagnosing vehicle's clutch with vibration sensors

A framework for aerospace vehicle reasoning (FAVER)

Airliners spend over 9% of their total revenue in Maintenance, Repair, and Overhaul (MRO) and working to bring down the cost and time involved. The prime focus is on unexpected downtime and extended maintenance leading to delays in the flights, which also reduces the trustworthiness of the airliners among the customers. One of the effective solutions to address this issue is Condition based Maintenance (CBM), in which the aircraft systems are monitored frequently, and maintenance plans are customized to suit the health of these systems. Integrated Vehicle Health Management (IVHM) is a capability enabling CBM by assessing the current condition of the aircraft at component/ Line Replaceable Unit/ system levels and providing diagnosis and remaining useful life calculations required for CBM. However, there is a lack of focus on vehicle level health monitoring in IVHM, which is vital to identify fault propagation between the systems, owing to their part in the complicated troubleshooting process resulting in prolonged maintenance. This research addresses this issue by proposing a Framework for Aerospace Vehicle Reasoning, shortly called FAVER. FAVER is developed to enable isolation and root cause identification of faults propagating between multiple systems at the aircraft level. This is done by involving Digital Twins (DTs) of aircraft systems in order to emulate interactions between these systems and Reasoning to assess health information to isolate cascading faults. FAVER currently uses four aircraft systems: i) the Electrical Power System, ii) the Fuel System, iii) the Engine, and iv) the Environmental Control System, to demonstrate its ability to provide high level reasoning, which can be used for troubleshooting in practice. FAVER is also demonstrated for its ability to expand, update, and scale for accommodating new aircraft systems into the framework along with its flexibility. FAVER’s reasoning ability is also evaluated by testing various use cases.Transport System

A Proposed Scheme for Fault Discovery and Extraction Using ANFIS: Application to Train Braking System

This paper showcases the use of model oriented techniques for real time fault discovery and extraction on train track unit. An analytical system model is constructed and simulated in Mathlab to showcase the fair and unfair status of the system. The discovery and extraction phases are centered on a hybrid adaptive neuro-fuzzy inference feature extraction and segregated module. Output module interprites zero (0) as a good status of the traintrack unit and one (1) as an unpleasant status. Final results showcase the robustness and ability to discover and extract multitude of unpleasant scenarios that hinder the smooth operations of train track units due to its high selectivity and sensitivity quality

Load allocation for optimal risk management in systems with incipient failure modes

The development and implementation challenges associated with a proposed load allocation paradigm for fault risk assessment and system health management based on uncertain fault diagnostic and failure prognostic information are investigated. Health management actions are formulated in terms of a value associated with improving system reliability, and a cost associated with inducing deviations from a system's nominal performance. Three simulated case study systems are considered to highlight some of the fundamental challenges of formulating and solving an optimization on the space of available supervisory control actions in the described health management architecture. Repeated simulation studies on the three case-study systems are used to illustrate an empirical approach for tuning the conservatism of health management policies by way of adjusting risk assessment metrics in the proposed health management paradigm. The implementation and testing of a real-world prognostic system is presented to illustrate model development challenges not directly addressed in the analysis of the simulated case study systems. Real-time battery charge depletion prediction for a small unmanned aerial vehicle is considered in the real-world case study. An architecture for offline testing of prognostics and decision making algorithms is explained to facilitate empirical tuning of risk assessment metrics and health management policies, as was demonstrated for the three simulated case study systems.Ph.D