Innovative sensor networks for massive distributed thermal measurements in space applications under different environmental testing conditions

Optical fiber has seen significant development in the technical fields where it has been used in the last years. In the first place, obviously, for the Internet and, more broadly, to improve communication efficiency; but, more recently, for medicinal, structural, or lighting engineering applications. Furthermore, many optical solutions are beginning to be researched in the aerospace sector. The use of optical fiber, in particular, is strongly related to the employment of FBG type optical sensors, which may be particularly suitable for specific measurements of relevant physical parameters to be performed on specimens with typical aeronautical and/ or space employment. More specifically, the performance of several FBG sensors for temperature measurement in vacuum for validation tests of space products has been examined during this work. Unlike typical thermocouples, the adoption of this new type of sensor can provide substantial benefits, beginning with a significant gain in terms of the size of the fiber, which ensures a minimum disturbance on thermal data. Furthermore, if supplied with a suitable coating (in polyimide), the optical fiber may guarantee a very high operating temperature range, which is extensively compatible with the high-temperature range existent in space. The measurements were divided into two independent phases. First, a preliminary test was performed in the laboratory using a climatic chamber to evaluate several sensor network integration methodologies on the specimens and select the most effective one for the vacuum test. The test demonstrated that a simple adhesive bonding of the fiber to the specimens ensures a precise temperature measurement under vacuum and stable conditions. The following vacuum test program confirmed that FBGs could be used as temperature sensors even at very high temperatures. The good results of this test encourage us to consider FBG strategic for space applications and, particularly, for thermal characterizations, thanks to the high number of available sensors, combined with the minimal cable's size. However, further studies are required in cryogenic cases to validate the entire range of extreme temperatures that characterize the space environment

A new CFD-Simulink based systems engineering approach applied to the modelling of a hydraulic safety relief valve

A safety relief valve is a simple hydro-mechanic device, needed to avoid overpressure transients inside hydraulic circuits. Such valves are a critical part of the hydraulic system of aircraft; hence their performances must be adapted to a specific nominal pressure level and design requirements. In the following paragraphs the authors will address the issue of designing and validating a safety valve through a hybrid CFD/MATLAB-Simulink® approach. The main constraints are the geometrical dimensions and the need to limit the weight of the device. A significant part of the work consists of gathering all the possible information available in the literature, dealing with the best design practices to achieve the performance objective. Thanks to a robust computational procedure, it should be possible to reduce the amount of “physical” prototypes required to validate the functionality of a safety relief valve. The process presented uses a numerical computational fluid dynamic (CFD) approach, to define the pressure field inside the valve and the forces acting on it; identifying the force distribution inside the valve is paramount to address the performance evaluation of the valve itself. The first step deals with the definition of a computer aided design (CAD) model of the valve. Then the CFD software uses the above-mentioned CAD model to define the domain of the problem. Once obtained the pressure field, it is possible to integrate it through the surface of the valve, thus obtaining the forces acting on the moving part (poppet). After the numerical scheme has been calibrated, some investigations are done to reduce the computational cost: the main aim is to run a complete simulation (meshing and solving) on a standard computer. Some of the positions (i.e. strokes) of the valve have been simulated as static, hence a steady-state calculation has been applied to solve the motion field. Another important result consists of creating a MATLAB-Simulink® model, capable to reach results comparable to the CFD simulation, but in shorter times. While the CFD model can provide high quality results, the MATLAB-Simulink® calculation should be used to create a “first guess” instrument, useful to address the very first valve geometry. The implementation of the Look-Up Tables (LUTs) links the MATLAB-Simulink® model to the CFD simulation, but increases the time required to obtain a solution: on the other hand, this reduces the amount of equation-modeled quantities, delivering a greater precision to the calculations

A review of simplified servovalve models for digital twins of electrohydraulic actuators

The development and detail design of complex electrohydraulic actuators for aircraft flight controls require the use of accurate, high fidelity fluid-dynamic simulations in order to predict the behaviour of the system within its whole operating envelope. However, those simulations are usually computationally expensive, and simplified models are useful for the preliminary design phases and real-time health monitoring. Within this context, this work presents a review of low fidelity models for the fluid-dynamic behaviour of an electrohydraulic servovalve. Those are intended to run in real time as digital twins of the physical system, in order to enable the execution of diagnostic and prognostic algorithms. The accuracy of the simulations is assessed by comparing their results against a detailed, physics-based high fidelity model, which computes the response of the equipment accounting for the pressure-flow characteristics across all the internal passageways of the valve

Proposal of a model based fault identification neural technique for more-electric aircraft flight control EM actuators

There are many different ways to detect incipient failures of electromechanical actuators (EMA) of primary flight command provoked by progressive wear. With the development of a prognostic algorithm it’s possible to identify the precursors of an electromechanical actuator failure, to gain an early alert and so get a proper maintenance and a servomechanism replacement. The present work aims to go beyond prognostic algorithms strictly technology-oriented and based on accurate analysis of the cause and effect relationships because if on one hand they show great effectiveness for some specific applications, instead they mostly fail for different applications and technologies. Through the development of a simulation test bench the authors have demonstrated a robust method to early identify incoming failures and reduce the possibility of false alarms or non-predicted problems. Authors took into account friction, backlash, coil short circuit and rotor static eccentricity failures and defined a model-based fault detection neural technique to assess data gained through Fast Fourier Transform (FFT) analysis of the components under normal stress conditions

Linear Electromechanical Actuators Affected by Mechanical Backlash: a Fault Identification Method Based on Simulated Annealing Algorithm

Several approaches can be employed in prognostics, to detect incipient failures of primary flight command electromechanical actuators (EMA), caused by progressive wear. The development of a prognostic algorithm capable of identifying the precursors of an electromechanical actuator failure is beneficial for the anticipation of the incoming faults: a correct interpretation of the fault degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. The research presented in this paper proposes a fault detection / identification technique, based on approaches derived from optimization methods, able to identify symptoms of EMA degradation before the actual exhibition of the anomalous behavior; in particular, the authors’ work analyses the effects due to progressive backlashes acting on the mechanical transmission and evaluates the effectiveness of the proposed approach to correctly identify these faults. An experimental test bench was developed: results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual fault, minimizing the risk of false alarms or not annunciated failures

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

Thermomechanical calibration of FBG sensors for aerospace applications

Optical fibers have found widespread use in engineering, from communication to sensors. Among them, Fiber Bragg Gratings are allowed to detect several parameters. Scope of this work is to assess their performances as temperature and mechanical strain sensors for aerospace: in this regard, an experimental calibration is discussed. Then, alternative approaches are tested in order to distinguish thermal from mechanical contributes. This is first addressed by using a hybrid system of digital and optical sensors, and then then with a fully optical system. Both the presented solutions reached the scope. A concept of a third, innovative approach, is also described

A genetic-based prognostic method for aerospace electromechanical actuators

Prior awareness of impending failures of primary flight command electromechanical actuators (EMAs) utilizing prognostic algorithms can be extremely useful. Indeed, early detection of the degradation pattern might signal the need to replace the servomechanism before the failure manifests itself. Furthermore, such algorithms frequently use a model-based approach based on a direct comparison of the real (High Fidelity) and monitor (Low Fidelity) systems to discover fault characteristics via optimization methods. The monitor model enables the gathering of accurate and exact data while requiring a minimal amount of processing. This work describes a novel simplified monitor model that accurately reproduces the dynamic response of a typical aerospace EMA. The task of fault detection and identification is carried out by comparing the output signal of the reference system (the high fidelity model) with that acquired from the monitor model. The Genetic Algorithm is then used to optimize the matching between the two signals by iteratively modifying the fault parameters, getting the global minimum of a quadratic error function. Once this is found, the optimization parameters are connected with the assumed progressive failures to assess the system's health. The high-fidelity reference model examined in this study is previously conceptualized, developed, implemented in MATLAB-Simulink and finally experimentally confirmed

Electrohydraulic Servomechanisms Affected by Multiple Failures: A Model-Based Prognostic Method Using Genetic Algorithms

In order to detect incipient failures due to a progressive wear of a primary flight command electro hydraulic actuator (EHA), prognostics could employ several approaches; the choice of the best ones is driven by the efficacy shown in failure detection, since not all the algorithms might be useful for the proposed purpose. In other words, some of them could be suitable only for certain applications while they could not give useful results for others. Developing a fault detection algorithm able to identify the precursors of the above mentioned EHA failure and its degradation pattern is thus beneficial for anticipating the incoming failure and alerting the maintenance crew so as to properly schedule the servomechanism replacement. The research presented in the paper was focused to develop a new prognostic procedure centered on the characterization of the state of health of a common electro-hydraulic actuator for primary command usage. It is based on an innovative model based fault detection and identification method (FDI) that makes use of deterministic and heuristic solvers in order to converge to the actual state of wear of the tested actuator. In particular, the proposed model takes in account three different types of progressive failures: the clogging of the first stage of the flapper-nozzle valve, the rising of friction between spool and sleeve and finally the rising of friction between jack and cylinder. To assess the robustness of the proposed technique, an appropriate simulation test environment was developed. The results showed an adequate robustness and confidence was gained in the ability to early identify an eventual EHA malfunctioning with low risk of false alarms or missed failures

A new genetic algorithm model-based prognostic approach applied to onboard electrohydraulic servomechanisms

The ever green solution of the electro hydraulic actuator (EHA) applications for the control of modern primary flight commands, justified by the superiority of hydraulic systems in furnishing more efficient solutions for power supplying in a controlled manner, brings us to focus on the need to make the EHA as efficient and reliable as possible. To this purpose, it must be noted that reliability of modern systems is increasingly more based on the valid support of diagnostics and prognostics; in fact, these two are the most robust instruments which mitigate life cycle costs without losing reliability and guarantee, in compliance with regulations, the bases for health management of integrated components, subsystems and systems. Developing a fault detection algorithm able to identify the precursors of EHA faults and their degradation patterns is thus beneficial for anticipating the incoming failure and alerting the maintenance crew so as to properly schedule the servomechanism replacement. About that, this paper proposes a new EHA model-based fault detection and identification method (FDI) that makes use of deterministic and heuristic solvers in order to converge to the actual state of wear of the tested actuator. The proposed FDI algorithm has been tested on three different types of progressive failures (the clogging of the first stage of the flapper-nozzle valve, the rising of friction between spool and sleeve and finally the rising of friction between jack and cylinder): to this purpose, a dedicated simulation test environment was developed. Results showed an adequate robustness and a suitable confidence was gained about its ability to early identify EHA malfunctions with low risk of false alarms or missed failures