Aircraft electrical power system diagnostics, prognostics and health management

In recent years, the loads needing electrical power in military aircraft and civil jet keep increasing, this put huge pressure on the electrical power system (EPS). As EPS becomes more powerful and complex, its reliability and maintenance becomes difficult problems to designers, manufacturers and customers. To improve the mission reliability and reduce life cycle cost, the EPS needs health management. This thesis developed a set of generic health management methods for the EPS, which can monitor system status; diagnose faults/failures in component level correctly and predict impending faults/failures exactly and predict remaining useful life of critical components precisely. The writer compared a few diagnostic and prognostic approaches in detail, and then found suitable ones for EPS. Then the major components and key parameters needed to be monitored are obtained, after function hazard analysis and failure modes effects analysis of EPS. A diagnostic process is applied to EPS using Dynamic Case-based Reasoning approach, whilst hybrid prognostic methods are suggested to the system. After that, Diagnostic, Prognostic and Health Management architecture of EPS is built up in system level based on diagnostic and prognostic process. Finally, qualitative evaluations of DPHM explain given. This research is an extension of group design project (GDP) work, the GDP report is arranged in the Appendix A

A New Prognostic Method Based on Simulated Annealing Algorithm to Deal with the Effects of Dry Friction on Electromechanical Actuators

In prognostics it is possible to apply several approaches with the aim to detect incipient failures, caused by progressive wear, of electromechanical actuators (EMA) in primary flight commands. The anticipation of a failure has to be performed through a correct interpretation of the degradation pattern, so to trig an early alert for maintenance and to properly schedule the servomechanism replacement. This paper proposes a prognostic approach based on the simulated annealing optimization method, able to identify symptoms of degradation before the behavior of the actuator becomes anomalous; friction failures are considered as the case study. The approach is validated through an experimental test bench, resulting in an adequate robustness and a high degree of confidence in the ability to early identify faults, with a low amount of false alarms or not annunciated failures

Dynamic power distribution management for all electric aircraft

In recent years, with the rapid development of electric and electronic technology, the All-Electric Aircraft (AEA) concept has attracted more and more attention, which only utilizes the electric power instead of conventional hydraulic and pneumatic power to supply all the airframe systems. To meet the power requirements under various flight stages and operating conditions, the AEA approach has resulted in the current aircraft electrical power generation capacity up to 1.6 MW. To satisfy the power quality and stability requirements, the advanced power electronic interfaces and more efficient power distribution systems must be investigated. Moreover, with the purpose of taking the full advantages of available electrical power, novel dynamic power distribution management research and design for an AEA must be carried out. The main objective of this thesis is to investigate and develop a methodology of more efficient power distribution management with the purpose of minimizing the rated power generating capacity and the mass of the electrical power system (EPS) including the power generation system and the power distribution system in an AEA. It is important to analyse and compare the subsistent electrical power distribution management approaches in current aircraft. Therefore the electrical power systems of A320 and B777, especially the power management system, will be discussed in this thesis. Most importantly the baseline aircraft, the Flying Crane is the outcome of the group design project. The whole project began in March 2008, and ended in September 2010, including three stages: conceptual design, preliminary design and detailed design. The dynamic power distribution management research is based on the power distribution system of the Flying Crane. The main task of the investigation is to analyse and manage the power usage among and inside typical airframe systems by using dynamic power distribution management method. The characteristics and operation process of these systems will be investigated in detail and thoroughly. By using the method of dynamic power distribution management, all the electrical consumers and sub-systems powered by electricity are managed effectively. The performance of an aircraft can be improved by reducing the peak load requirement on board. Furthermore, the electrical system architecture, distributed power distribution system and the dynamic power distribution management system for AEA are presented. Finally, the mass of the whole electrical power system is estimated and analysed carefully

Performance Evaluation of a Prognostic Framework for Electro-Hydraulic Actuators for Stability Control Augmentation Systems with Different Sensors Suites

Stability Control Augmentation Systems (SCAS) are widely adopted to enhance the flight stability of rotary-wing aircraft operating in difficult aerodynamic conditions, such as low altitude missions, stationary flight nearby vertical walls or in presence of heavy gusts. Such systems are based upon small electro-hydraulic servosystems controlled in position through a dedicated servovalve. The SCAS operates with limited authority over the main control linkage translating the pilot input in the movement of the main flight control actuator. Being critical for the operability of the helicopter, the definition of a Prognostics and Health Management (PHM) framework for the SCAS systems would provide significant advantages, such as better risk mitigation, improved availability, and a reduction in the occurrences of unpredicted failures which still represent one of the most known downsides of helicopters due to their very severe operational environment. Since SCAS actuators are usually equipped with a low number of sensors, it is at the present time unclear whether a fully realized PHM system can be prepared without resorting to the introduction of additional sensors. This paper deals with this subject evaluating the performances of a fault diagnosis tool operating considering different sensors suite (traditional and with additional sensors), and different PHM strategies, using in-flight data or their combination with dedicated pre-flight checks to cover the most common failure modes. The analysis is then completed with an evaluation of the prognostic capabilities of the proposed strategies, highlighting benefits and limitations of the proposed solutions

Selection and Validation of Health Indicators in Prognostics and Health Management System Design

Health Monitoring is the science of system health status evaluation. In the modern industrial world, it is getting more and more importance because it is a powerful tool to increase systems dependability. It is based on the observation of some variables extracted in operation reflecting the condition of a system. The quality of health monitoring strongly depends on the selection of these variables named health indicators. However, the issue in their selection is often underestimated and their validation is, of what is known, an untreated subject. In this paper, the authors introduce a complete methodology for the selection and validation of health indicators in health monitoring systems design. Although it can be applied either downstream on real measured data or upstream on simulated data, the true interest of the method is in the latter application. Indeed, a model-based validation can be integrated in the design phases of the system development process, thereby reducing potential controller retrofit costs and useless data storage. In order to simulate the distribution of health indicators, a well known surrogate model called Kriging is utilized. Eventually, the method is tested on a benchmark system: the high pressure pump of aircraft engines fuel systems. Thanks to the method, the set of health indicators was validated in system design phases and the monitoring is now ready to be implemented for in-service operation

Predictive model for the degradation state of a hydraulic system with dimensionality reduction

In recent years, the optimization in the use of resources has a key role in achieving a bigger marginality, reducing the operative costs. Due to the advances in the data science field, even the maintenance context is living important changes. The predictive maintenance and the condition-based maintenance can overcome the classic traditional maintenance methods, like the time-based maintenance or the corrective maintenance, with respect to the first intervention, reducing the costs for unscheduled maintenance, manpower, or loss of production and extending the useful life of the components. Based on these presuppositions, the paper proposes the development of a predictive model for the degradation state of the components of a complex hydraulic system, with some tests and some suggestions about the dimensionality reduction. The system has four known types of breakdown, with different degrees of severity; moreover, a fifth parameter represents whether the cycle has reached stable conditions or not

Electromechanical actuators affected by multiple failures: a simulated-annealing-based fault identification algorithm

The identification of early evidences on monitored parameters allows preventing incoming faults. Early alerts can avoid rate of the failures and trigger proper out-of-schedule maintenance activities. For this purpose, there are many prognostic approaches. This paper takes into account a primary flight command electromechanical actuator (EMA) with multiple failures originating from progressive wear and proposes a fault detection approach that identifies symptoms of EMA degradation through a simulated annealing (SA) optimization algorithm; in particular, the present work analyses the functioning of this prognostic tool in three different fault configurations and it focuses on the consequences of multiple failures. For this purpose, we developed a test bench and obtained experimental data necessary to validate the results originated from the model. Such comparison demonstrates that this method is affordable and able to detect failures before they occur, thus reducing the occurrence of false alarms or unexpected failures. © 2016, North Atlantic University Union. All rights reserved

Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADe™ (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis

PHM Based Adaptive Power Management System for a More Electric Aircraft

This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study was carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been developed