Health and Usage Monitoring

Health and Usage Monitoring Systems (HUMS) have been developed in order to monitor the health condition of helicopter drivetrains, focusing towards early, accurate and on time fault detection with limited false alarms and missed detections. Among other systems, the Main GearBox (MGB) is the heart of the drivetrain, reducing the high input speed generated by the engines, in order to provide the appropriate torque to the main rotors and to other auxiliary systems. HUMS are mounted on helicopters aiming to enhance the operational reliability and to support maintenance decision making, in order to increase the flight safety keeping in the meanwhile the overall maintenance cost low. Currently used HUMS seems to have reached their limits and the need for improvement has been recently highlighted by the post-accident analysis of the helicopter LN-OJF, which crashed in Norway in 2016. The aim of this paper is the application and further extension of recently proposed advanced cyclostationary based signal processing tools for the accurate detection of faults in helicopter gearboxes. The methodologies are tested, evaluated and compared with state of the art methods on datasets captured during experimental tests under various operating conditions on helicopter gearboxes, including a Category A Super Puma SA330 main planetary gearbox.

The large number of flight critical and maintenance intensive dynamic components in a helicopter has led to the development of diagnostic systems to improve flight safety and reduce operations and support costs. These systems, commonly called health and usage monitoring systems (HUMS), have been used on large commercial helicopters and are now being developed for military helicopters. US Navy embarked on an innovative approach to fielding an integrated mechanical diagnostic system for Navy helicopters. An accelerated program was started to field a militarized version of a commercial health and usage monitoring system for the CH-53E and SH-60B helicopters. An open systems architecture is critical to the military implementation of HUMS technology on multiple platforms. An open system architecture is essential for system upgrades and for the introduction of the broad range of new technologies as they become available from a number of different sources. Through significant team effort and participation, the IMD-KUMS program is successfully navigating the often-turbulent waters of open system architecture implementation. This paper will provide details on some of the lessons learned from both an industry and government perspective and provide a program status update.

Vibration monitoring of dynamic components is an important part of ensuring aircraft safety and has been used to determine the health of rotating components since the inception of the modern day helicopter. Some vibration checks have not changed from the time that a specific helicopter was placed into service and others have been modified with the addition of Health and Usage Monitoring Systems (HUMS) with the goal to improve them. A seeded fault test on an MH-47 aircraft was conducted to directly compare modified vibration checks to the legacy checks, identify a method to decrease vibrations, and minimize maintenance. Data was collected using Modernized Signal Processing Unit (MSPU) which replaced the Aviation Vibration Analyzer (AVA) for rotor smoothing and all drivetrain vibration checks. While this paper will present lessons learned, it will also provide successful HUMS benefits. This paper will demonstrate that HUMS can not only maintain legacy vibration checks but improve them as well with changes that enhance airworthiness and reduce maintenance burden. This is an example of how HUMS continues to evolve as we press forward in the pursuit of providing aircraft users with the best tools possible.

Structural usage and loads monitoring can enhance safety, by identifying unusual usage patterns by individual aircraft or sub-fleets (e.g. operators, missions, or locations), and provide benefit to operators by enabling extended retirement times of life-limited components. While flight regime recognition (RR) algorithms have been demonstrated and partially validated, the use of existing onboard generic RR software provided in legacy Health and Usage Monitoring Systems (HUMS) remains a challenge for achieving airworthiness approval of retirement time extensions using archived fleet data in compliance with existing guidance, such as the U.S. Army ADS-79E Handbook for Condition-Based Maintenance. The U.S. Army and Sikorsky Aircraft, a Lockheed Martin Company, conducted a joint Fatigue Life Management (FLM) project to configure, validate, and apply processes and methods for extending the retirement times of six high-value components for the Army's Black Hawk helicopter fleet, which is equipped with a state-of-the-art HUMS, known as the Integrated Vehicle Health Management System (IVHMS). A RR post-processing process for addressing key technical challenges associated with the use of legacy onboard RR software was configured and verified against existing UH-60 flight test data. These post-processing methods were then applied to a two year population of UH-60 fleet data to calculate usage statistics for individual aircraft within several sub-fleet populations associated with either different global deployment locations and/or missions. The fleet statistics were then used by the Army Aviation Engineering Directorate (AED) to establish a conservative update to the existing usage spectrum, which was applied by Sikorsky to calculate updated retirement times. The focus of this paper is on the successful configuration and verification of RR software used in compliance with ADS-79E to establish UH-60 A/L/M IVHMS fleet usage statistics. A companion paper, also published within proceedings of the AHS 74th Annual Forum, provides details on using the fleet statistics to define an updated UH-60 usage spectrum.

There is an on-going drive to expand the benefits achievable from Health and Usage Monitoring Systems (HUMS). In order to facilitate this expansion, the function of a HUMS needs to evolve from one of monitoring into that of management. This paper explains the differences between the two types of system and the benefits achievable from these. A number of examples are presented to illustrate the considerable amount of development activity being undertaken which has the common aim of producing a new generation of Health and Usage Management systems.

Accurate usage information collected by Health and Usage Monitoring Systems (HUMS) coupled with improved structural fatigue life calculation methodologies promise to reduce helicopter operational and support costs while maintaining current flight safety levels. Current fatigue life calculations assume worst-case flight profiles in determining component life. This approach may be outdated or not reflective of actual aircraft usage. On a small business innovative research (SBIR) contract the Intelligent Automation Corporation (IAC) has developed processing to include a low cost regime recognition and aircraft gross weight estimation capability as an extension to the US Army’s Vibration Management Enhancement Program (VMEP). IAC’s approach relies on multi-sensor data fusion technology and flight parameters collected by VMEP to provide an accurate flight regime calculation. Recording time in particular flight regimes has the potential of extending aircraft component life without changing proven lifing models. The regime recognition system has been implemented with the current release of IAC’s VMEP systems. Presented here are the methodology, development and visualization tools developed on the SBIR as well as results for using the system on AH-64 aircraft in follow-on work.

Health and Usage Monitoring Systems (HUMS) for helicopter rotor blades arise the demand for non invasive surveillance methods for slender composite structures. Integrating optical sensor systems within the manufacturing process of rotor blades holds challenges in fiber bonding, handling, the layup process and curing. Examining the steps of fiber integration using a co-bonding approach, the present work enlightens the challenges faced while manufacturing instrumented rotor blades. Apart from sensor integration it is crucial to show feasibility of integrated optical sensing networks. Measuring strain from Fiber Bragg Gratings (FBG), a deformation algorithm is applied to determine blade deflection along the airfoil section of a rotor blade using a NACA 0012 profile. Results from static deformation tests are used to validate the algorithm. In conclusion an experimental modal analysis is conducted and results obtained by accelerometers are compared to the ones from finite element simulation and to the eigenfrequencies measured by the FBG system.

Health and Usage Monitoring Systems (HUMS) for helicopter rotor blades arise the demand for non invasive surveillance methods for slender composite structures. Integrating optical sensor systems within the manufacturing process of rotor blades holds challenges in fiber bonding, handling, the layup process and curing. Examining the steps of fiber integration using a co-bonding approach, the present work enlightens the challenges faced while manufacturing instrumented rotor blades. Apart from sensor integration it is crucial to show feasibility of integrated optical sensing networks. Measuring strain from Fiber Bragg Gratings (FBG), a deformation algorithm is applied to determine blade deflection along the airfoil section of a rotor blade using a NACA 0012 profile. Results from static deformation tests are used to validate the algorithm. In conclusion an experimental modal analysis is conducted and results obtained by accelerometers are compared to the ones from finite element simulation and to the eigenfrequencies measured by the FBG system.

The introduction to autonomous vehicles and intelligent transportation systems, as well as related work on autonomous vehicles and intelligent transportation systems, are described in this chapter. Aside from that, it has a chapter on autonomous intelligent vehicles and autonomous vehicles. Issues and challenges in autonomous intelligent vehicles, as well as the framework of an intelligent transportation system. In addition, the chapter discusses research opportunities in autonomous intelligent vehicles, IPv4 and IPv6 issues, and the future of IPv9 for vehicles, as well as a survey on autonomous vehicles in highway scenarios. During the last century, the automobile industry has excelled at producing cars that are both safe and affordable. Because of significant advancements in the Internet of things (IoT), the programmable logic controller (PLC), and other aspects of computing, autonomous vehicles (AVs) are becoming a reality. Cars, trucks, and other vehicles that don’t need to be plugged in to get power are referred to as self-sufficient vehicles. The multi-agent-based transportation system, which demonstrates how vehicles, drivers, roads, infrastructure, and vehicles all work together, is one of the most important intelligent transportation systems because it demonstrates how all of these things work together. To solve and manage traffic problems, an intelligent transportation systems (ITS) system employs a variety of technologies. Communication and control, vehicle sensing, and electronics are among these technologies. ITS has been used in the developed world for the past two decades. It is still a novel concept in the developing world. Sensors and computers work together in the Internet of things to store and process data, and data analytics is used to make the traffic system run more smoothly.KeywordsAutonomous vehicle (AV)Intelligent transportation system (ITS)Autonomous intelligent vehicle (AIV)Advanced driver assistance system (ADAS)Advanced driving system (ADS)

Chapter 19 - Multi-sensor fusion in autonomous heavy vehicles

Energy-efficient cooperative transmission for intelligent transportation systems

This paper presents a framework to model and analyze the survivability and vulnerability of intelligent transportation system (ITS) networks. The proposed framework includes qualitative and quantitative approaches and can be implemented during the planning and design phase of new ITS projects or assess the survivability and vulnerability of existing ITS networks. The qualitative approach is based on Survivable System Analysis (SSA). It identifies threat mitigation strategies for each threat identified and provides suggestions for improved security and survivability. The paper also presents a quantitative survivable system analysis approach that is aimed to compute the essentiality of ITS network components and rank-order these essentialities to determine the most essential components of the network. The proposed framework provides a significant addition to the current design practices by integration system security, vulnerability, and survivability into the design, operation, and management of ITS networks. While the case-study presented in the paper focused on ITS networks, the proposed framework can be applied to any other critical infrastructure distribution, control, and monitoring networks.

Technological development and the massive investment in 'intelligent' vehicle technologies are likely to turn autonomous vehicles into reality in a few years. The insertion intelligence in road vehicles aims to obtain a reduction in traffic accidents due to the mitigation of errors committed by human drivers, thanks to their replacement by machines. In addition, autonomous vehicles should be able to mitigate hazards in road transportation systems without creating new risks. Thus, It is important to study how to ensure safety in this new scenario. Some research in this area has already been developed, but they do not show how to design properly an autonomous vehicle system in which existing methods can be applied to analyze and guarantee adequate levels of safety in such vehicles. As a result, this master's work develops a proposal that aims to facilitate the development and analysis of this new class of vehicles, in addition to ensuring levels of critical safety appropriate to autonomous vehicles. The proposal is represented by a system called Autonomous Vehicle Control (CVA), which was developed under the concept of Intelligent Transport Systems (STI). The CVA system is formed by two layers, one of operation (Autonomous Vehicle Operation -OVA), responsible for the driving of the vehicle and another one of protection (Autonomous Vehicle Protection -PVA). The main idea is to use the PVA layer for the prevention of accidents. The PVA layer was developed and tested in a simulation environment, considering a Case Study. It was observed that, as predicted, the CVA system, because it has a layer aimed at vehicular protection, was able to avoid several collision situations between vehicles.

Typical intelligent transportation systems (ITS) are comprised of geographically distributed ITS devices including sensors, cameras and dynamic message signs (DMS). There are several options for providing data communication between these field devices and traffic management centers (TMC). Wireless networks are attractive due to their relatively lower cost and ease of deployment compared to fixed networks. However, these face unique security and signal interference problems, and deploying new wireless networks can require significant equipment investment. In this work, a new extremely low-cost wireless strategy for ITS network communication is presented. This approach applies control channels of the Network Trunking System (NTS), a licensed radio frequency to support the voice communication, to control DMS operation under the National Transportation Communications for ITS Protocol (NTCIP). Because the NTS network has already installed in the metropolitan, urban, and rural areas in Oklahoma, it provides a cheap deployment solution requiring only additional adapter devices. Long term operation and maintenance costs can further be amortized between voice and data services. The proposed technique is compared to the existing ITS wireless networking strategies and hybrid network strategies merging wired and wireless networks deployed in Oklahoma. Details of the strategy for using wireless networking in the Oklahoma ITS and experiences with wireless ITS device deployment are also provided.

Pedestrian behavior interacting with autonomous vehicles during unmarked midblock multilane crossings: Role of infrastructure design, AV operations and signaling