Verification and validation of a theoretical model of a direct drive valve-controlled electrohydrostatic actuator for primary flight control

In this work, a theoretical parametric nonlinear model for a hybrid variable pressure actuator was verified through dynamic system modeling techniques and validated using experimental data. The hybrid configuration under investigation combines design features of a valve-controlled hydraulic actuator and an electrohydrostatic actuator resulting in a variable pressure hydraulic actuator. A comparison analysis is conducted to determine the performance and, more specifically, power characteristics of the hybrid configuration relative to the two types of conventional flight control actuation - valve-controlled actuators and electrohydrostatic actuators. The hybrid configuration is unique in the sense that it allows for independent localized hydraulic system pressure control. In this analysis, bang-bang control is implemented by defining low-pressure and high-pressure thresholds resulting in active-passive electrical power consumption. The hybrid configuration was shown to exhibit power input superiority due to duty-cycle behavior of the electrical power element during high-load low-rate scenarios when compared to traditional actuation configurations

Electromechanical actuator bearing fault detection using empirically extracted features

Model parameter estimation when coupled with Principal Component Analysis (PCA) and Bayesian classification techniques form a potentially effective fault detection scheme for Electromechanical Actuators (EMAs). This work uses parameter estimation algorithms based on linear system identification methods, derives a novel feature extraction algorithm based on PCA and analyzes its performance through simulations and experiments. A Bayesian classifier is used to create well defined EMA health classes from the extracted features. Research contributions on fault detection in EMAs are significant because EMA faults and their detection are not yet well understood. Potential future applications - such as in primary flight control actuation in aircraft - require that quality fault detection systems be in place. Therefore, fault detection of EMAs is a vast area of ongoing research where highly capable solutions are gradually becoming available. Prior work in parameter estimation methods for feature extraction in DC motor drives - which includes EMAs - are amongst those available. While PCA is a popular feature extraction solution in a number of frequency-based fault detection approaches, the use of PCA for feature extraction from model parameters for detecting bearing faults in EMAs has not been previously reported. In this work, a linear difference model is applied to the EMA system data such that fault information is distributed amongst the estimated model parameters. A direct comparison of the parameter estimates from healthy and degraded systems offers little insight into health conditions because of the weak effects of faults on the signal data. However, the application of PCA to uncorrelate the linearly correlated model parameters while minimizing the loss of variance information from the data effectively brings out fault information. The present algorithm is successfully applied to data collected from a Moog MaxForce EMA. The results are consistent and display effective fault detection characteristics, making the developed approach a suitable starting point for future work

Bridging the gap between theory and practice in LPV fault detection for flight control actuators

Two different approaches for fault detection,the geometric and the detection filter based methods,are compared in the paper from practical aspects,using the linear parameter-varying (LPV) framework. Presenting two designs allows a comparison of global, system level, and local component level fault detection methods with special emphasis on their relevance to aircraft industry.Practical engineering design decisions are highlighted via applying them to a high-fidelity commercial aircraft problem. The successive steps of the design, including fault modelling, LPV model generation, and LPV FDI filter synthesis, including implementation aspects, are discussed. Results are presented according to the industrial assessment perspectives phrased within the EU ADDSAFE project

Innovative actuator fault identification based on back electromotive force reconstruction

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

Volume 2 – Conference

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 1 | 2: Digital systems Group 3: Novel displacement machines Group 4: Industrial applications Group 5: Components Group 6: Predictive maintenance Group 7: Electro-hydraulic actuatorsDer Download des Gesamtbandes wird erst nach der Konferenz ab 15. Oktober 2020 möglich sein.:Group 1 | 2: Digital systems Group 3: Novel displacement machines Group 4: Industrial applications Group 5: Components Group 6: Predictive maintenance Group 7: Electro-hydraulic actuator

Design and development of prognostic and health management system for fly-by-wire primary flight control

Electro-Hydraulic Servo Actuators (EHSA) is the principal technology used for primary flight control in new aircrafts and legacy platforms. The development of Prognostic and Health Management technologies and their application to EHSA systems is of great interest in both the aerospace industry and the air fleet operators. This Ph.D. thesis is the results of research activity focused on the development of a PHM system for servovalve of fly-by-wire primary flight EHSA. One of the key features of the research is the implementation of a PHM system without the addition of new sensors, taking advantage of sensing and information already available. This choice allows extending the PHM capability to the EHSAs of legacy platforms and not only to new aircrafts. The enabling technologies borrow from the area of Bayesian estimation theory and specifically particle filtering and the information acquired from EHSA during pre-flight check is processed by appropriate algorithms in order to obtain relevant features, detect the degradation and estimate the Remaining Useful Life (RUL). The results are evaluated through appropriate metrics in order to assess the performance and effectiveness of the implemented PHM system. The major objective of this contribution is to develop an innovative fault diagnosis and failure prognosis framework for critical aircraft components that integrates effectively mathematically rigorous and validated signal processing, feature extraction, diagnostic and prognostic algorithms with novel uncertainty representation and management tools in a platform that is computationally efficient and ready to be transitioned on-board an aircraft

On the use of context information for an improved application of data-based algorithms in condition monitoring

xi, 124 p.En el campo de la monitorización de la condición, los algoritmos basados en datos cuentan con un amplio recorrido. Desde el uso de los gráficos de control de calidad que se llevan empleando durante casi un siglo a técnicas de mayor complejidad como las redes neuronales o máquinas de soporte vectorial que se emplean para detección, diagnóstico y estimación de vida remanente de los equipos. Sin embargo, la puesta en producción de los algoritmos de monitorización requiere de un estudio exhaustivo de un factor que es a menudo obviado por otros trabajos de la literatura: el contexto. El contexto, que en este trabajo es considerado como el conjunto de factores que influencian la monitorización de un bien, tiene un gran impacto en la algoritmia de monitorización y su aplicación final. Por este motivo, es el objeto de estudio de esta tesis en la que se han analizado tres casos de uso. Se ha profundizado en sus respectivos contextos, tratando de generalizar a la problemática habitual en la monitorización de maquinaria industrial, y se ha abordado dicha problemática de monitorización de forma que solucionen el contexto en lugar de cada caso de uso. Así, el conocimiento adquirido durante el desarrollo de las soluciones puede ser transferido a otros casos de uso que cuenten con contextos similares

On the use of context information for an improved application of data-based algorithms in condition monitoring

xi, 124 p.En el campo de la monitorización de la condición, los algoritmos basados en datos cuentan con un amplio recorrido. Desde el uso de los gráficos de control de calidad que se llevan empleando durante casi un siglo a técnicas de mayor complejidad como las redes neuronales o máquinas de soporte vectorial que se emplean para detección, diagnóstico y estimación de vida remanente de los equipos. Sin embargo, la puesta en producción de los algoritmos de monitorización requiere de un estudio exhaustivo de un factor que es a menudo obviado por otros trabajos de la literatura: el contexto. El contexto, que en este trabajo es considerado como el conjunto de factores que influencian la monitorización de un bien, tiene un gran impacto en la algoritmia de monitorización y su aplicación final. Por este motivo, es el objeto de estudio de esta tesis en la que se han analizado tres casos de uso. Se ha profundizado en sus respectivos contextos, tratando de generalizar a la problemática habitual en la monitorización de maquinaria industrial, y se ha abordado dicha problemática de monitorización de forma que solucionen el contexto en lugar de cada caso de uso. Así, el conocimiento adquirido durante el desarrollo de las soluciones puede ser transferido a otros casos de uso que cuenten con contextos similares

Improving Energy Efficiency and Motion Control in Load-Carrying Applications using Self-Contained Cylinders

Because of an increasing focus on environmental impact, including CO2 emissions and fluid spill pollution, inefficient hydraulic systems are being replaced by more environmentally friendly alternatives in several industries. For instance, in some offshore applications that have multiple diesel generators continuously running to produce electricity, all hydraulic rotating actuators supplied from a central hydraulic power unit have been replaced with AC induction motors containing a variable frequency drive and gearbox. However, hydraulic linear actuators are still needed in most load-carrying applications mainly because of their high reliability associated with external impact shocks. Moreover, their force capacity is higher than that of their linear electromechanical counterparts. Valve-controlled linear actuators (cylinders) supplied from a centralized hydraulic power unit are standard in offshore load-carrying applications. In addition to the advantages mentioned above of hydraulic linear actuators, they have, nevertheless, a number of important drawbacks, which include: 1) a high level of energy consumption due to significant power losses caused by flow throttling in both the pipelines and valves, 2) reduced motion performance due to the influence of load-holding valves, 3) high CO2 emissions and fuel costs related to the diesel generator that supplies electricity to the hydraulic power unit, 4) significant potential for hydraulic fluid leakage because of many leakage points, 5) demanding efforts with respect to installation and maintenance, as well as 6) costly piping due to the centralized hydraulic power supply. The work presented in this dissertation and the appended papers are devoted to replacing inefficient hydraulic linear actuation systems traditionally used in offshore load-carrying applications with more environmentally friendly solutions. Two alternative technologies are identified, namely electro-mechanical and electro-hydraulic self-contained cylinders. The feasibility of replacing conventional valve-controlled cylinders with self-contained cylinder concepts is investigated in two relevant case studies.publishedVersio

Fault detection in the electrohydraulic actuator using Extended Kalman Filter

In this thesis a fault detection technique for a high performance hydrostatic actuation system was developed and evaluated. The Extended Kalman Filter (EKF) was used for parameter identification and was applied to an Electrohydraulic Actuator (ERA) and the performance of the technique is discussed. The ERA is a high performance, closed loop actuation system consisting of an AC variable speed electric motor, a bi-directional gear pump, an accumulator, check valves, a cross-over relief valve, connecting tubes and a custom made symmetrical actuator. The ERA has potential applications in the aerospace industry for flight surface actuation and in robotics. Failures in the ERA can pose a safety hazard and unscheduled maintenance can result in costly downtime. Fault detection in the ERA will increase its safety and efficiency. The proposed preventive maintenance approach involves monitoring the ERA by estimating two parameters of interest, namely the effective bulk modulus and the viscous damping coefficient. Lowering of the effective bulk modulus, as a result of air entrapment, will affect the response of the ERA and may cause stability issues, by lowering the bandwidth of the system. Changes in the damping coefficient for the actuator can indicate deterioration of the oil, wear in the seals or changes in external friction characteristics. The two parameters were estimated using the EKF and changes in the estimated values were related to faults in the system. Prior to applying the EKF to the ERA prototype, an extensive simulation study was carried out to investigate the feasibility of the approach as well as the level of accuracy to be expected with the experimental system. The simulation study was used to verify that changes in the two parameters were detected and accurately estimated. In this study, an attempt was also made to visit some of the problems reported with the use of the EKF for fault detection purposes, namely the difficulty in setting the correct values in the matrices to initialize the EKF algorithm and the presence of biases in the estimates. The problem was believed to be linked to system observability which was investigated in this research. It was found that using observable state space models for the EKF improved the ability of the EKF to estimate parameters, both in terms of accuracy of the estimations and repeatability of experimental results. System observability was investigated in this work by first using simple mechanical systems and then using the more complex ERA system. An iterative approach was presented whereby parameters were not estimated at the same time but iteratively and using different models. System observability was maintained by reducing the number of states and by using the correct type and number of system measurements. Also, the use of observable systems eliminated the need to choose parameter values, in the initial state vector of the EKF, close to the desired parameter values, as was very often done in previous research. No a-priori knowledge about the parameters was assumed in this research. Biases in the estimates (this has been reported in previous studies) are believed to be due to the filter facing a local minima problem. This problem is linked to the error covariance matrix not converging to a global minimum. In the Kalman Filter, the main objective of the error covariance matrix is to compute the Kalman gain, which is in turn used to correct an estimate with the latest sensor measurement. Errors in the Kalman gain may lead to biases in the estimates. In this study, it was also found that although the system is not observable, it can be detectable, although the converse is not true, and as such, changes in parameters can be detected but not necessarily accurately estimated. Observability ensures uniqueness of the estimate. The effective bulk modulus and viscous damping coefficient were estimated successfully, both in simulations and using experimental data. Faults were introduced in the ERA prototype and changes in the parameters were detected and estimated. The friction characteristic of the actuator for the ERA was also investigated. A novel empirical friction model was proposed. The EKF was used to estimate iteratively (to maintain system observability), the coefficients of that friction function which was believed to be a realistic representation of friction effect in the prototype. Simulation and experimental results were presented. In summary, the application of the EKF technique to the ERA has produced very promising results