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The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and low weight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer sev eral advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aimed to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems. [ABSTRACT FROM AUTHOR]

In the upcoming space revolutions aiming at the implementation of automated, smart, and self-aware crewless vehicles and reusable spacecraft, sensors play a significant role in the control systems. In particular, fiber optic sensors, with their small footprint and electromagnetic immunity, represent a great opportunity in aerospace. The radiation environment and the harsh conditions in which these sensors will operate represent a challenge for the potential user in the aerospace vehicle design and the fiber optic sensor specialist. We present a review that aims to be a primer in the field of fiber optic sensors in radiation environments for aerospace. We review the main aerospace requirements and their relationship with fiber optics. We also present a brief overview of fiber optics and sensors based on them. Finally, we present different examples of applications in radiation environments for aerospace applications. [ABSTRACT FROM AUTHOR]

Adoption of electromechanical actuation systems in aerospace is increasing, and so reliable diagnostic and prognostics schemes are required to ensure safe operations, especially in key, safety-critical systems such as primary flight controls. Furthermore, the use of prognostics methods can increase the system availability during the life cycle and thus reduce costs if implemented in a predictive maintenance framework. In this work, an improvement of an already presented algorithm will be introduced, whose scope is to predict the actual degradation state of a motor in an electromechanical actuator, also providing a temperature estimation. This objective is achieved by using a properly processed back-electromotive force signal and a simple feed-forward neural network. Good prediction of the motor health status is achieved with a small degree of inaccuracy. [ABSTRACT FROM AUTHOR]

This article describes a mitigation strategy against the risks potentially caused by RPAS capable of performing Specific Category of operations within not segregated airspace. A selection of hazards has been associated to these RPAS and it has been assessed thus obtaining a risk matrix. Considering the basic principles of risk analysis management based on Safety Management System theory, after having implemented the matrix (risks identification and ranking), a new mitigation strategy has been defined in order to maintain constantly the hazards consequences at or below an acceptable level. A strategy based on 'Expert Systems' has been chosen. 'Expert Systems' are computer systems capable of suggesting solutions to problems emulating human expertise in a given field of knowledge. There are many typologies of 'Expert Systems'; the ones considered in this article are the rule-based 'Expert Systems'. They are characterized by a basis of knowledge built from set of rules expressed as 'IF'-'THEN' statements. In this case, each statement has been directly implemented from the operational risks contained in the matrix with a one-to-one correspondence between mitigating rules and hazards for a given RPAS capable of performing Specific Category of operations. The novelty of this process is deemed to be the idea of laying down the basis for the implementation of a software based on artificial intelligence (the 'Expert System') to be integrated with the Flight Control System/Autopilot Subsystem of the RPASs object of the original risk assessment in order to recognize risks and promptly mitigate them during the execution of operational sorties within not segregated airspace. Two levels of integration (basic and advanced) are described and discussed in the article. [ABSTRACT FROM AUTHOR]

A general evolution of airspace and air traffic management is ongoing in Europe including significant novelties for manned aviation. The most important one is the full integration of Remotely Piloted Aircraft Systems (RPAS) in the next future and the full integration of automated air vehicles and Driverless Personal Air Vehicles (DPAV) afterwards with manned aircraft. The economic impact of integration of RPAS with manned aircraft into not segregated airspace to perform aerial work is very important. European and worldwide Aviation Authorities and other organizations (EUROCONTROL, JARUS, RTCA, etc.) are working to elaborate new regulations and standards to maintain the current level of safety of aerial operations facing the incoming new entry in the airspace. The implementation of a comprehensive preliminary risk model is deemed to be propaedeutic to any former safety analysis of the new operational scenario: RPAS and manned aircraft flying together into a not segregated airspace. Such risk model is defined in accordance to the Safety Risk Management Pillar of Safety Management System model. The safety analysis for the implementation of the above mentioned preliminary risk model is presented and discussed in this article. [ABSTRACT FROM AUTHOR]

In relatively recent years, electromechanical actuators have gradually replaced systems based on hydraulic power for flight control applications. Electromechanical servosystems are typically operated by electrical machines that transfer rotational power to the controlled elements (e.g. the aerodynamic control surfaces) by means of gearings and mechanical transmission. Compared to electrohydraulic systems, electromechanical actuators offer several advantages, such as reduced weight, simplified maintenance and complete elimination of contaminant, flammable or polluting hydraulic fluids. On-board actuators are often safety critical; then, the practice of monitoring and analyzing the system response through electrical acquisitions, with the aim of estimating fault evolution, has gradually become an essential task of the system engineering. For this purpose, a new discipline, called Prognostics, has been developed in recent years. Its aim is to study methodologies and algorithms capable of identifying such failures and foresee the moment when a particular component loses functionality and is no longer able to meet the desired performance. In this paper, authors have introduced the use of optimization techniques in prognostic methods (e.g. model-based parametric estimation algorithms) and have proposed a new model-based fault detection and identification method, based on Genetic Algorithms optimization approach, able to perform an early identification of the aforesaid progressive failures, investigating its ability to identify timely symptoms alerting that a component is degrading. [ABSTRACT FROM AUTHOR]

In the last years, the layout of servomechanisms used in the aeronautical field to actuate the flight controls has changed radically and, nowadays electromechanical actuators (EMAs) are increasingly replacing the older hydraulic powered actuator types. The definition of special monitoring procedures, based on the analysis of the system response and aiming to evaluate the evolution of faults, represents an important task of the modern system engineering taking into account that onboard actuators are typically safety critical items. The present paper proposes a new prognostic procedure centered on the characterization of the state of health of an EMA used in aircraft primary flight controls. This approach, based on the innovative use of a model-based fault detection and identification method (FDI), identifies the actuator actual state of wear of the actuator analyzing proper system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. The proposed FDI algorithm has been tested in case of EMA affected by two progressive failures (rotor static eccentricity and stator phase turn-to-turn short-circuit), showing an adequate robustness and a suitable ability to early identify EMA malfunctions with low risk of false alarms or missed failures. [ABSTRACT FROM AUTHOR]

The design of the whole airplane hydraulic system should be seen in an integrated form: in fact different configuration choices regarding each subsystem can appreciably affect the pumps sizing. The work highlights the interactions between the design choices concerning both the generation and power regulation (pumps and regulating devices) and the users in all the aspects important for the operation of the complete system outlining the design of a defined hydraulic system of an airplane. To this end the dynamic simulation models (with associated calculation programs) capable of analyzing the behavior of the complete system have been made; employing it a series of investigations was carried out, aiming to analyze the dynamic behavior of different configurations of the system in similar operating conditions. Examination of the results shows how seemingly minor design choices concerning the architecture of the subsystems can play a significant role in the functioning of the entire system, affecting its own sizing. [ABSTRACT FROM AUTHOR]

The increasing interest for adopting electromechanical actuators (EMAs) on aircraft demands improved diagnostic and prognostic methodologies to be applied to such systems in order to guarantee acceptable levels of reliability and safety. While diagnostics methods and techniques can help prevent fault propagation and performance degradation, prognostic methods can be applied in tandem to reduce maintenance costs and increase overall safety by enabling predictive and condition-based maintenance schedules. In this work, a predictive approach for EMAs friction torque estimation is proposed. The algorithm is based on the reconstruction of the residual torque in mechanical transmissions. The quantity is then sampled and an artificial neural network (ANN) is used to obtain an estimation of the current health status of the transmission. Early results demonstrate that such an approach can predict the transmission health status with good accuracy. [ABSTRACT FROM AUTHOR]

The ever increasing adoption of electrical power as secondary form of on-board power is leading to an increase in the usage of electromechanical actuators (EMAs). Thus, in order to maintain an acceptable level of safety and reliability, innovative prognostics and diagnostics methodologies are needed to prevent performance degradation and/or faults propagation. Furthermore, the use of effective prognostics methodologies carries several benefits, including improved maintenance schedule capability and relative cost decrease, better knowledge of systems health status and performance estimation. In this work, a novel, real-time approach to EMAs prognostics is proposed. The reconstructed back electromotive force (back-EMF), determined using a virtual sensor approach, is sampled and then used to train an artificial neural network (ANN) in order to evaluate the current system status and to detect possible coils partial shorts and rotor imbalances. [ABSTRACT FROM AUTHOR]

Traditional hydraulic servomechanisms for aircraft control surfaces are being gradually replaced by newer technologies, such as Electro-Mechanical Actuators (EMAs). Since field data about reliability of EMAs are not available due to their recent adoption, their failure modes are not fully understood yet; therefore, an effective prognostic tool could help detect incipient failures of the flight control system, in order to properly schedule maintenance interventions and replacement of the actuators. A twofold benefit would be achieved: Safety would be improved by avoiding the aircraft to fly with damaged components, and replacement of still functional components would be prevented, reducing maintenance costs. However, EMA prognostic presents a challenge due to the complexity and to the multi-disciplinary nature of the monitored systems. We propose a model-based fault detection and isolation (FDI) method, employing a Genetic Algorithm (GA) to identify failure precursors before the performance of the system starts being compromised. Four different failure modes are considered: dry friction, backlash, partial coil short circuit, and controller gain drift. The method presented in this work is able to deal with the challenge leveraging the system design knowledge in a more effective way than data-driven strategies, and requires less experimental data. To test the proposed tool, a simulated test rig was developed. Two numerical models of the EMA were implemented with different level of detail: A high fidelity model provided the data of the faulty actuator to be analyzed, while a simpler one, computationally lighter but accurate enough to simulate the considered fault modes, was executed iteratively by the GA. The results showed good robustness and precision, allowing the early identification of a system malfunctioning with few false positives or missed failures. [ABSTRACT FROM AUTHOR]