Redundant hydraulic secondary flight control systems behavior in failure conditions

The flight control systems, designed in order to assure the necessary safety level even in failure conditions, are generally characterized by a proper redundant layout. The redundancies must be designed in order to assure an adequate system behavior when some failures are present; in fact an incorrect layout may cause serious shortcomings concerning the response when some component is not operational. Therefore the usual correct design activities request the complete analysis of the system behavior in failure condition. The work analyses the response of a redundant secondary flight control hydraulic servo-mechanism equipped with some proper equalization devices, when some of the most probable and representative failures are present. It must be noted that the redundancy layout, designed in order to assure the necessary safety level even in failure conditions, may behave improperly during normal operations, if the system architecture is unsuitable, when manufacturing defects are present. The improper behavior, generally consisting of force fighting or speed fighting caused by different offsets or asymmetries between the two sections of the system, may be usually overcome by means of a suitable equalization device. Therefore, the system behavior during and following the failure transient greatly depends on both its redundancy architecture and related equalization device. The above mentioned problems have been studied by means of an appropriate physical-mathematical model of a typical electro-hydraulic servo-mechanism prepared to the purpose, performing a certain number of simulations of representative actuations in which different types of failures are accurately modeled. In the opinion of the authors, this paper concerns a topic quite neglected but important in the technical literature. At the best of the authors’ knowledge, no specific scientific work in this field is available, excepting some industrial technical reports

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

Optimization methodologies study for the development of prognostic artificial neural network

In this work, we discuss the implementation and optimization of an artificial neural network (ANN) based on the analysis of the back-EMF coefficient capable of making electromechanical actuator (EMA) prognostics. Starting from the pseudorandom generation of failure values related to static rotor eccentricity and partial short circuit of the stator coils, we simulated through a MATLAB-Simulink model the values of currents, voltages, position and angular velocity of the rotor and thanks to these we obtained the back-electromotive force which represents the input layer of the ANN. In this paper, we will turn our attention to optimizing the hyperparameters which influence supervised learning and make it more performing in terms of computational cost and complexity. The results are satisfactory dealing with the number of examples present in the available dataset

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

Lumped parameters multi-fidelity digital twins for prognostics of electromechanical actuators

The growing affirmation of on-board systems based on all-electric secondary power sources is causing a progressive diffusion of electromechanical actuators (EMA) in aerospace applications. As a result, novel prognostic and diagnostic approaches are becoming a critical tool for detecting fault propagation early, preventing EMA performance deterioration, and ensuring acceptable levels of safety and reliability of the system. These approaches often require the development of various types of multiple numerical models capable of simulating the performance of the EMA with different levels of fidelity. In previous publications, the authors already proposed a high-fidelity multi-domain numerical model (HF), capable of accounting for a wide range of physical phenomena and progressive failures in the EMA, and a low-fidelity digital twin (LF). The LF is directly derived from the HF one by reducing the system degrees of freedom, simplifying the EMA control logic, eliminating the static inverter model and the three-phase commutation logic. In this work, the authors propose a new EMA digital twin, called Enhanced Low Fidelity (ELF), that, while still belonging to the simplified types, has particular characteristics that place it at an intermediate level of detail and accuracy between the HF and LF models. While maintaining a low computational cost, the ELF model keeps the original architecture of the three-phase motor and the multidomain approach typical of HF. The comparison of the preliminary results shows a satisfactory consistency between the experimental equipment and the numerical models

Study of FBG-based optical sensors for thermal measurements in aerospace applications

Optical fibers have revolutionized several technological sectors in recent decades, above all that of communication, and have also found many applications in the medical, lighting engineering, and infrastructural fields. In the aerospace field, many studies investigated the adoption of fiber optics considering the planned transition from fly-by-wire to fly-by-light flight controls. A significant feature of optical fiber is its ability to be used not only as a transmission medium but also as a basis for fiber-embedded sensors; one of the most prominent types is based on Bragg gratings (FBGs). FBGs can replace several traditional sensors, providing measures of temperature, vibrations, and mechanical deformation. Optical sensors provide many advantages over traditional, electrical-based sensors, including EMI insensitivity, ease of multiplexing on a single line, resilience to harsh environments, very compact sizes and global weight saving. Furthermore, punctual knowledge of the temperature field is essential to perform the thermal compensation of the optical sensors used for strain measurements. In this work, the authors analyzed the performance of thermal sensors based on FBGs to verify their stability, accuracy, and sensitivity to operating conditions. Two different methods of FBGs surface application have been considered (gluing with pre-tensioning vs. non-tensioned bonding). The results were then compared to those acquired using typical temperature sensors to determine the relationship between the observed temperature and the Bragg wavelength variation (i.e. the proportionality coefficient Kt). The effects on the proportionality coefficient Kt, arising from fiber pre-tensioning and thermal expansion of the structural support, were then evaluated by comparing the results obtained with the two bonding approaches

Diagnostics of electro-mechanical actuators based upon the back-EMF reconstruction

Electrical systems are gradually replacing the more traditional hydraulic and pneumatic solutions for the transmission of secondary energy for onboard aircraft equipment. Therefore fault detection and health management strategies properly conceived for electrical devices are becoming a highly relevant topic for research and development in the aerospace disciplines. One possible practical implementation of these methodologies would be the identification of parameters for diagnostic and prognostic monitoring, which are highly sensitive to incipient faults but, at the same time, are less influenced by operating conditions (external loads, command input, temperatures, etc.). In this paper, the authors evaluated the effectiveness of counter-electromotive force (back-EMF) coefficient as a prognostic parameter, emphasizing a novel sampling approach that significantly lower the computational effort required while maintaining a good back-EMF coefficient curve reconstruction. The approach is virtual sensor-like, using only already available data for the correct operation of the BLDC motor. The proposed method was tested by evaluating the back-EMF coefficient reconstruction as a function of some progressive failures typical of EMA motors, such as inter-turn partial shorts and rotor static eccentricity. Its robustness to external disturbances has been tested by evaluating different actuation commands and operating conditions. As expected, the back-EMF signal shows a marked dependence on the considered failure modes and, at the same time, a suitable insensitivity to the other external factors

Design and development of innovative FBG-based fiber optic sensors for aerospace applications

In recent years aeronautical systems are becoming increasingly complex, as they are often required to perform various functions. New intelligent systems are required capable of self-monitoring their operation parameters, able to estimate their health status, and possibly perform diagnostic or prognostic functions. For these purposes, these systems frequently need to acquire several different signal types; although it is sometimes possible to implement virtual sensor techniques, it is usually necessary to implement dedicated sensing hardware. On the other hand, the installation of the required sensors can, however, significantly increase the complexity, the weight, the costs and the failure rate of the entire system. To overcome these drawbacks, new types of optical sensors, minimally invasive for measuring the system parameters and having a high spatial resolution and a minimum added complexity are now available. Fiber Bragg Gratings (FBGs) sensors are suitable for measuring various technical parameters in static and dynamic mode and meet all these requirements. In aerospace, they can replace several traditional sensors, both in structural monitoring and in other system applications, including mechatronic systems diagnostics and prognostics. This work reports the results of our experimental research aimed at evaluating and validating different FBG installation solutions such as deformation, bending, vibration, and temperature sensors. These were compared with numerical simulations results and measurements performed with traditional strain gauges and accelerometers

Fault Detection and Identification Method Based on Genetic Algorithms to Monitor Degradation of Electrohydraulic Servomechanisms

Electro Hydraulic Actuators (EHAs) keep their role as the leading solution for the control of current generation primary flight control systems: the main reason can be found in their high power to weight ratio, much better than other comparable technologies. To enhance efficiency and reliability of modern EHAs, it is possible to leverage the diagnostics and prognostics disciplines; these two tools allow reducing life cycle costs without losing reliability, and provide the bases for health management of integrated systems, in compliance with regulations. This paper is focused on the development of a fault detection algorithm able to identify the early signs of EHA faults, through the recognition of their precursors and related degradation patterns. Our methodology provides the advantage of anticipating incoming failures, triggering proper alerts for the maintenance team to schedule adequate corrective actions, such as the replacement of the degraded component. A new EHA model-based fault detection and identification (FDI) method is proposed; it is based on deterministic and heuristic solvers able to converge to the actual state of wear of the tested actuator. Three different progressive failure modes were chosen as test cases for the proposed FDI strategy: clogging of the first stage of the flapper-nozzle valve, spool-sleeve friction increase, and jack-cylinder friction increase. A dedicated simulation model was created for the purpose. The results highlighted that the method is adequate in robustness, since EHA malfunctions were identified with a low occurrence of false alarms or missed failures