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Electro-mechanical actuators (EMAs) are a primary actuation technology for unmanned aerial vehicles (UAVs). Intensive research has been conducted for designing and evaluating fault-tolerant EMAs for flight controls of UAVs to ensure their compliance with new airworthiness requirements for safe operation over civilian zones. The state-of-the-art research involves several fault-tolerant architectures for EMAs based on parallel electric motors or a single motor with internal fault-tolerant features. In this study, a fault-tolerant architecture is introduced, comprised of two serial electric motors driven by two isolated controllers and a health monitoring system. The procedures of developing various fault-tolerant features are discussed with a deep focus on designing health monitoring functions and evaluating their influence on the overall actuator stability and availability. This work has been conducted and evaluated based on operational data for ALAADy: a heavy gyrocopter-type UAV at DLR (German Aerospace Center).
Mohamed Ismail; Simon Wiedemann; Colin Bosch; Christoph Stuckmann. Design and Evaluation of Fault-Tolerant Electro-Mechanical Actuators for Flight Controls of Unmanned Aerial Vehicles. Actuators 2021, 10, 175 .
AMA StyleMohamed Ismail, Simon Wiedemann, Colin Bosch, Christoph Stuckmann. Design and Evaluation of Fault-Tolerant Electro-Mechanical Actuators for Flight Controls of Unmanned Aerial Vehicles. Actuators. 2021; 10 (8):175.
Chicago/Turabian StyleMohamed Ismail; Simon Wiedemann; Colin Bosch; Christoph Stuckmann. 2021. "Design and Evaluation of Fault-Tolerant Electro-Mechanical Actuators for Flight Controls of Unmanned Aerial Vehicles." Actuators 10, no. 8: 175.
Rising civilian applications that make use of unmanned aerial vehicles (UAVs) demand crucial precautions to minimize safety hazards. Future UAVs are expected to incorporate fault-tolerant architectures for critical on-board systems to ensure compliance with airworthiness certification. Reliability reports of in-service UAVs showed that flight control actuators are among the highest root-causes of UAVs mishaps. In this paper, the current state-of-the-art actuation architectures for UAVs are reviewed to identify technical requirements for certification. This work is part of a TEMA-UAV research project aimed at developing certifiable fault-Tolerant Electro-Mechanical Actuators for future UAVs.
M. A. A. Ismail; C. Bosch; S. Wiedemann; A. Bierig. Fault-Tolerant Actuation Architectures for Unmanned Aerial Vehicles. Recent Advances in Computational Mechanics and Simulations 2021, 345 -354.
AMA StyleM. A. A. Ismail, C. Bosch, S. Wiedemann, A. Bierig. Fault-Tolerant Actuation Architectures for Unmanned Aerial Vehicles. Recent Advances in Computational Mechanics and Simulations. 2021; ():345-354.
Chicago/Turabian StyleM. A. A. Ismail; C. Bosch; S. Wiedemann; A. Bierig. 2021. "Fault-Tolerant Actuation Architectures for Unmanned Aerial Vehicles." Recent Advances in Computational Mechanics and Simulations , no. : 345-354.
Torque measurements can significantly enhance control and monitoring loops for many mechatronic and aerospace applications. A typical challenge is to justify incorporating a torque sensor in terms of cost, system complexity, and reliability. Recently, sensorless torque estimation methods have been developed for robotic joints that include harmonic drive transmissions (HDTs). The principle is based on their relatively low torsional stiffness, which allows for estimating the transmitted torque by measuring the torsional angles (via existing joint encoders) and a compliance model. However, these methods are based on nonlinear models that are difficult to identify and tune. In this study, a simplified torque estimation method is introduced based on the structural damping friction of the HDTs. The structural damping can be correlated to the HDT torque using a simplified linear dynamic model and torsional rate measurements. Experimental results have validated the proposed method, using a robotic joint setup with an external torque sensor that has been previously utilized for testing several torque estimation methods.
Mohamed A. A. Ismail; Jens Windelberg; Guangjun Liu. Simplified Sensorless Torque Estimation Method for Harmonic Drive Based Electro-Mechanical Actuator. IEEE Robotics and Automation Letters 2021, 6, 835 -840.
AMA StyleMohamed A. A. Ismail, Jens Windelberg, Guangjun Liu. Simplified Sensorless Torque Estimation Method for Harmonic Drive Based Electro-Mechanical Actuator. IEEE Robotics and Automation Letters. 2021; 6 (2):835-840.
Chicago/Turabian StyleMohamed A. A. Ismail; Jens Windelberg; Guangjun Liu. 2021. "Simplified Sensorless Torque Estimation Method for Harmonic Drive Based Electro-Mechanical Actuator." IEEE Robotics and Automation Letters 6, no. 2: 835-840.
Various drone detection systems (DDS) have been recently developed for civil and military applications. Such DDS are generally based on radio frequency (RF) radars, detecting control signals between drones and their pilots, drone's acoustic noise, optical surveillance, or a combination of these. However, existing DDS have safety critical gaps. For example, none of the current state-of-the-art technologies provide remote payload monitoring or verification. The registered payload of some commercial drones can be greatly increased by simple re-configuration procedures that may not be detected by current DDS. This study introduces patent-pending methods for remote identification and payload monitoring of standard and modified drones. Structural frequencies, measured by a long-range laser vibrometer, of commercial drones are proposed as a unique signature for remotely verifying registered specifications of a drone, e.g., payload capacity. In addition, a method is proposed to measure payload capacity of unknown drones based on their motion performance monitored via a motion dynamic model and a laser Doppler vibrometer. Preliminary flight tests have been successfully conducted for a group of standard and modified drones by the Institute of Flight Systems, DLR (German Aerospace Center).
Mohamed A.A. Ismail; Andreas Bierig. Identifying drone-related security risks by a laser vibrometer-based payload identification system. Laser Radar Technology and Applications XXIII 2018, 10636, 1063603 .
AMA StyleMohamed A.A. Ismail, Andreas Bierig. Identifying drone-related security risks by a laser vibrometer-based payload identification system. Laser Radar Technology and Applications XXIII. 2018; 10636 ():1063603.
Chicago/Turabian StyleMohamed A.A. Ismail; Andreas Bierig. 2018. "Identifying drone-related security risks by a laser vibrometer-based payload identification system." Laser Radar Technology and Applications XXIII 10636, no. : 1063603.
Electromechanical actuators (EMAs) are considered a promising energy-efficient technology for actuating the flight controls of future aircraft. When it comes to aerospace systems, the degradation of EMAs should be checked during regular maintenance events or through condition-based maintenance. Ball bearings have a significant failure rate for flight control EMAs and are usually monitored by vibration noise. A challenge for detecting bearing faults, using state-of-the-art industrial methods, is the presence of a ball-screw mechanism that produces nominal vibration noise similar to that of faulty bearings. No prior research has investigated this problem. This paper explores vibration noise generated from a set of healthy and faulty bearings included in a typical ball-screw EMA. In addition, a method is introduced for evaluating fault diagnosis performance for different time and frequency vibration features. The technique has been validated on an EMA actuator at the German Aerospace Center (DLR).
Mohamed A. A. Ismail; J Windelberg. Fault detection of ball screw-based electromechanical actuators using electrical, ultrasound and accelerometer sensors. International Journal of Condition Monitoring 2018, 8, 52 -57.
AMA StyleMohamed A. A. Ismail, J Windelberg. Fault detection of ball screw-based electromechanical actuators using electrical, ultrasound and accelerometer sensors. International Journal of Condition Monitoring. 2018; 8 (2):52-57.
Chicago/Turabian StyleMohamed A. A. Ismail; J Windelberg. 2018. "Fault detection of ball screw-based electromechanical actuators using electrical, ultrasound and accelerometer sensors." International Journal of Condition Monitoring 8, no. 2: 52-57.
Vibration-based fault diagnosis has been utilized as a reliable method for identifying ball bearings health since the 1970s. Recently, there has been an increased research effort to develop methods for fault quantification with the aim of estimating the fault size to allow the service life of a ball bearing to be extended beyond the detection stage. These studies have shown that the vibration signal from a localized spall (e.g. fatigue defect) in a ball bearing exhibits features corresponding to two main events, namely, the entry into and the exit from the spall. The time span between these two events is correlated with the spall size. Studies have shown that the entry into the spall is the more challenging event to identify, which often requires extensive signal processing techniques. This paper introduces an automated vibration-based technique for estimating the size of a spall in a ball bearing under axial loading conditions similar to those of linear electro-mechanical actuators. This technique is based on the extraction of the entry/exit events from the vibrational jerk, which are numerically determined from accelerometer data. The differentiation of the acceleration data to estimate jerk signal is performed using a variant of Savitzky–Golay (SG) differentiators, which provide enhancement for the detection of the entry and exit points. Sensible spall size estimations have been achieved for 24 different scenarios of fault sizes, rotor speeds and loads measured on a test rig provided by DLR (German Aerospace Center).
Mohamed A. A. Ismail; Andreas Bierig; Nader Sawalhi. Automated vibration-based fault size estimation for ball bearings using Savitzky–Golay differentiators. Journal of Vibration and Control 2017, 24, 4297 -4315.
AMA StyleMohamed A. A. Ismail, Andreas Bierig, Nader Sawalhi. Automated vibration-based fault size estimation for ball bearings using Savitzky–Golay differentiators. Journal of Vibration and Control. 2017; 24 (18):4297-4315.
Chicago/Turabian StyleMohamed A. A. Ismail; Andreas Bierig; Nader Sawalhi. 2017. "Automated vibration-based fault size estimation for ball bearings using Savitzky–Golay differentiators." Journal of Vibration and Control 24, no. 18: 4297-4315.
Future aircraft architectures will incorporate more energy-efficient electromechanical actuators (EMA) for flight controls actuation. Development of reliable health monitoring techniques for EMAs promises to maintain or even increase the overall availability and safety of these new aircraft designs. When it comes to EMAs and similar mechanisms, certain fault types clearly manifest themselves through loss of functionality. Other faults, referred to as latent, do not immediately result in a significantly compromised actuator performance, thus making them challenging to detect. This paper presents a new vibration-based hybrid technique for detecting latent EMA faults without needing an initial stage of fault feature learning. The two faults considered in the study are a high-criticality jam and a low-criticality spall (metal flaking) in the actuator ballscrew mechanism. The actuator position is used to resample variable-speed vibration measurements of a single accelerometer into constant-rate measurements. A set of health characterization signatures is derived theoretically based on the EMA ballscrew kinematics. These theoretical signatures are compared with the signatures extracted from vibration signals measured experimentally on the EMA test articles. The vibration signatures approach is also compared to the diagnostic approach based on EMA motor current measurements. The ability to detect and classify latent faults early as high-or low-critical can improve maintenance planning and increase aircraft dispatch reliability. The technique has been validated on fault-injected data sets collected on the NASA Ames Research Center Flyable Electro-Mechanical Actuator (FLEA) test stand.
Mohamed A. A. Ismail; Edward Balaban; Holger Spangenberg. Fault detection and classification for flight control electromechanical actuators. 2016 IEEE Aerospace Conference 2016, 1 -10.
AMA StyleMohamed A. A. Ismail, Edward Balaban, Holger Spangenberg. Fault detection and classification for flight control electromechanical actuators. 2016 IEEE Aerospace Conference. 2016; ():1-10.
Chicago/Turabian StyleMohamed A. A. Ismail; Edward Balaban; Holger Spangenberg. 2016. "Fault detection and classification for flight control electromechanical actuators." 2016 IEEE Aerospace Conference , no. : 1-10.