Rotor Failure Research Articles

Nonlinear characteristics and radial-bending-torsional vibration of a blade with breathing crack

Rotor failures due to cracked blades are frequently observed in rotating machinery. The identification of cracking state of rotating blade based on vibration characteristics has garnered a lot of attention. However, nonlinear characteristics and vibration combining in radial, bending and torsional directions of a rotating blade induced by the crack breathing is yet not clear. This paper proposes a radial-bending-torsional dynamic model of rotating blade with breathing crack. A time-varying integration method is proposed for determining the crack state based on the strain energy release rate. The crack breathing behavior is described by Boolean operation and the numerical integration are applied to open or close the crack. The model is validated through modal analysis, vibration responses and contact state of crack surface. Frequency veering is changed between the 2nd flap and 1st edgewise frequency due to the existence of crack. Strong nonlinear behaviors are found in the radial and torsional vibrations because of the crack breathing. Nonlinearities are also found in the combined vibrations between the radial-bending and the bending-torsional directions. Radial and torsional vibration amplitude levels can be used as an indication of blade crack failure, but the applicability depends on the absolute response decided by the aerodynamic excitation and resonant vibration. These findings can serve as guidance in crack identification and cracking state monitoring of rotating blades.

Fault tolerant motion planning for a quadrotor subject to complete rotor failure

Assuring safety of a quadrotor subject to rotor failure has been heavily investigated at the control level in view of fault tolerant control (FTC) approach. Yet, the existing FTCs are often concerned with tracking the reference motion even when that reference may not be safely trackable due to the physical constraints of the quadrotor. This paper tackles the faulty quadrotor safety at the planner level, proposing a fault tolerant motion planner. Starting from the formal backward reachability problem formulation, the proposed motion planner generates the time trajectory of the coupled rotational and translational motions that safely guide the faulty quadrotor. The generated trajectory is theoretically guaranteed to be tracked by the embedded FTC without violating the physical constraints. Further, the trajectory is prescribed as an analytical closed-form expression and thus suitable for real-time emergency maneuvers. The effectiveness of the proposed motion planner is numerically validated in conjunction with the different FTC techniques and compared to the existing planning method. The simulation results clearly signify that the proposed planner can successfully complement the fault tolerance of quadrotor. The supplements including code implementations are available on GitHub repository: https://github.com/HMCL-UNIST/Fault-tolerant-motion-planner.

Failure Diagnosis for Dental Air Turbine Handpiece with Payload Using Feature Engineering and Temporal Convolution Network.

The internal mechanisms of dental air turbine handpieces (DATHs) have become increasingly intricate over time. To enhance the operational reliability of dental procedures and guarantee patient safety, this study formulated temporal convolution network (TCN) prediction models with the functions of causality in time sequence, transmitting memory, learning, storing, and fast convergence for monitoring the health and diagnosing the rotor and collet failure of DATHs. A handpiece mimicking a dentist's hand load of 100 g was employed to repeatedly mill a glass porcelain block back and forth for cutting. An accelerometer was employed to capture vibration signals during free-running of unrestrained operation of the handpiece, aiming to discern the characteristic features of these vibrations. These data were then utilized to create a diagnostic health classification (DHC) for further developing a TCN, a 1D convolutional neural network (CNN), and long short-term memory (LSTM) prediction models. The three frameworks were used and compared for machine learning to establish DHC prediction models for the DATH. The experimental results indicate that, in terms of DHC predicted for the experimental dataset, the square categorical cross-entropy loss function error of the TCN framework was generally lower than that of the 1D CNN, which did not have a memory framework or the drawback of the vanishing gradient problem. In addition, the TCN framework outperformed the LSTM model, which required a longer history to provide sufficient diagnostic ability. Still, high accuracies were achieved both in the direction of feed-drive milling and in the gravity of the handpiece through vibration signals. In general, the failure classification prediction model could accurately predict the health and failure mode of the dental handpiece before the use of the DATH when an embedded sensor was available. Therefore, this model could prove to be a beneficial tool for predicting the deterioration patterns of real dental handpieces in their remaining useful life.

Controllability Evaluation for VTOL Aircraft in Velocity Envelope: A Distance-Based Metric

This paper introduces an approach for evaluating and quantifying the controllability of vertical takeoff and landing (VTOL) aircraft across various flight states. By employing the controllability theory for linear systems subject to bounded control, this study derives sufficient conditions for the local controllability of the nonlinear VTOL system. These conditions are cohesively integrated with the trimmability condition directly derived from nonlinear dynamics, establishing a comprehensive criterion that facilitates the assessment of both trimmability and controllability of VTOL aircraft. This unified criterion elucidates the relation between desired and achievable specific forces and moments with clear implications for flight mechanics. Building upon this criterion, a distance-based metric is proposed to quantify the controllability, with an optimization-based algorithm developed for its calculation. Focusing on an exemplary lift plus cruise VTOL aircraft, this study investigates controllability variations within the aircraft’s velocity envelope and assesses the impact of rotor failures on controllability. These applications demonstrate the proposed method’s effectiveness in quantifying the controllability of VTOL aircraft in various flight conditions.

Fault tolerant control of an octorotor UAV using sliding mode for applications in challenging environments

This paper presents the development of fault-tolerant controller and their application for multirotor unmanned aerial vehicles – specifically an octorotor – in challenging environments e.g. nuclear power plant inspection or other dull, dirty and dangerous applications. This paper considers a combination of sliding mode control robustness properties (to deal with actuator faults) and control allocation (to automatically redistribute the control signals to healthy actuators, especially in the event of actuator failures). The resultant controller has the ability to operate in both fault-free and fault/failure conditions without reconfiguring the main baseline controller. The proposed controller also has the ability to operate for up to six rotor failures which represent an under-actuation condition i.e., a case when only two rotors are available. The under-actuation scenarios are conditions when most FTC schemes are not able to operate due to the lack of redundancy. The simulation results conducted on the nonlinear model with wind/gusts and sensor noise, show a good tracking performance under various fault-free and fault/failure scenarios (over-actuation, sufficient actuation and under-actuation conditions).

Landing trajectory and control optimization for helicopter encountering different tail rotor pitch lockups

In recent years, tail rotor failure has been a significant factor in helicopter accidents, contributing to around 30 % of all incidents. Among these failures, tail rotor pitch lockup accounts for nearly 2/3. However, there is currently a lack of research on the landing trajectory and control optimization for piloted helicopters facing tail rotor pitch lockup. Therefore, this paper aims to study the landing trajectory and pilot control strategy optimization during helicopter tail rotor pitch lockup. The findings of this research are expected to provide valuable insights and serve as a reference for subsequent real-time pilot-in-the-loop simulations and final flight tests. In this paper, we utilize the UH-60A helicopter as a prototype to establish a flight dynamics model and a pilot model. The aerodynamic forces and induced velocity of the main rotor are calculated using the blade element method and Pitt-Peters model. The rotor flap motion is simplified to a first-order harmonic quantity. We then formulate the problem of safe landing and control optimization as a nonlinear optimal control problem, with the cost function designed to reflect safety and feasibility during the flight and touchdown process. To solve the optimal control problem numerically, we use direct multiple shooting and sequential quadratic programming algorithms. Flight test data for the UH-60A, encompassing steady-state flight, dynamic response, and autorotation landing, are utilized to validate the accuracy of the flight dynamics model and the effectiveness of the optimal control algorithm. Finally, the paper investigates the safe landing trajectories and control strategies for the sample helicopter when encountering high tail rotor pitch lockup and low tail rotor pitch lockup, respectively. Simulation results demonstrate that when the tail rotor is stuck at a high pitch, it is advisable for pilots to execute a high-power state landing by maintaining the engine at high power while reducing forward speed and descent rate. Conversely, when the tail rotor is stuck at a low pitch, flying at an economical speed (in a low-power state) is advantageous, but it does not facilitate a safe landing thereafter. If the pilot attempts a conventional landing, the yaw rate at touchdown would be very high and potentially dangerous. In contrast, if an autorotation landing is executed, the landing will be safer with a much lower yaw rate at touchdown. The optimal landing trajectory and control process align with the recommendations from actual helicopter flight tests. The proposed method provides feasible pilot control strategies for safe landing when helicopters encounter various tail rotor pitch lockup situations. This research can serve as a reference for pilots before conducting actual flight tests.

Safety Design of Uncontained Engine Rotor Failure for Civil Aircraft Primary Flight Control System

The safety design of uncontained engine rotor failure for civil aircraft primary flight control systems is more difficult than other airborne systems. This paper presents a safety design method that establishes a two-stage collision model inspection mechanism and introduces an automatic analysis algorithm in the process of comprehensive impact analysis of the cascade system. The method applies to the detailed design stage of civil aircraft systems. It can reduce the difficulty of the safety analysis process and improve the accuracy of the analysis results. The verification of a civil aircraft primary flight control system design shows that after using the safety design method, the time cost of the analysis process is significantly reduced, and the analysis results are more accurate, thereby reducing the difficulty of design changes.

Co-design of a multirotor UAV with robust control considering handling qualities and motor failure

Over the last few decades, multirotor UAVs have become significantly popular because of their various applications. However, multirotors suffer from poor endurance performance as compared to other aircraft configurations with lifting surfaces. This limitation can be addressed by improving the technology of components or by developing design optimization approaches at the vehicle level. This paper presents a co-design approach for the multirotor structure and propulsive system to improve the vehicle's energetic efficiency while respecting dynamic performance requirements. For this purpose, the approach uses a bi-level formulation to optimize the design and control concurrently. The methodology offers the possibility to activate or not a passive fault tolerant strategy in the controller synthesis to be tolerant to single rotor failure. In contrast to conventional design approaches that sequentially design each part, the co-design approach leads to a better optimal solution by considering the interactions and couplings between design and control. With the proposed co-design approach, the results show the soundness of the proposed design methodology and a significant reduction in the consumed energy compared to a reference non-optimal design while maintaining the same requirements in terms of dynamic performance.

Fault Tolerance Conceptual Strategy for a Quadcopter Drone with Rotor Failure

The ability of a quadcopter drone to maintain its attitude relies solely on its four rotors. If even one motor fails, the drone loses its ability to hold attitude and altitude. This paper explores a new fault tolerance solution to enhance attitude control for quadcopter drones following the complete loss of a single rotor. By following the fundamental principle of balancing forces and moments on a quadrotor drone, the paper demonstrates that it is feasible to land the drone safely by minimizing roll, pitch, and yaw when a rotor fails. The concept centers around thrust vectoring, which allows an opposite motor to tilt independently. The results indicate that tilting the opposite rotor by 45o provides better management of the drone’s roll, pitch, and yaw, enabling the incapacitated drone to land in a more controlled and manageable manner. The paper includes simulation results and a summary table of the novel idea’s performance enhancements.

Study on the Optimal Design Method of the Containment Ring for an Air Turbine Starter

The airworthiness standards of transport category airplanes clearly stipulate that the equipment containing high-energy rotors must be shown by test that it can contain any failure of a high-energy rotor that occurs at the highest speed. The air turbine starter (ATS) is typical equipment containing high-energy rotors, and the manufacturers of ATS attach great importance to research on structural containment and weight reduction. In this paper, an optimal design method for a U-type containment ring is proposed. The method adopts the optimal Latin hypercube design, numerical simulation, response surface modeling, and genetic algorithm to achieve the multi-parameter optimal design of the containment ring section. By combining simulation and experiment, the influence weights of different structural parameters of the containment ring on the residual kinetic energy of debris and the containment ring volume were analyzed. The influence of different structural parameters of a U-type containment ring on containment results was studied, and a containment test was carried out to verify the containment capability of an optimized containment ring. The results show that the thickness of the containment ring has the greatest influence on the residual kinetic energy of the debris, and the weight ratio is 38%. The maximum radial deformation of the optimized containment ring can reach 22.3%, which means that the energy absorption effect of the containment ring on the disk fragments is significantly improved. With the same containment capability, the weight reduction effect of an optimized containment ring can reach 26.5%. The research results can provide weight reduction optimization methods and design theoretical guidance for U-type containment structures.

Development of an Abnormal Sound Detection System for Rotating Bodies Using Deep Learning

Conveyor systems have a rotating body component that generates various sound signals when malfunction occurs. This work studies the development of a system that collects sound signal data generated during operation of a rotating body, applies an artificial intelligence (AI) algorithm over the data, and diagnoses if the motion of the rotating body is abnormal. The conveyor belt system is installed in various working environments such as mines and factories and consists of a number of rotors. Multiple connected data collection devices developed in this work are placed around the conveyor belt rotors to detect abnormalities in the rotors. Each collection device is equipped with the AI algorithm, which performs the data preprocessing on the sound data collected by each device. For the diagnosis of the rotor failure, sound data collected from the devices are converted to 2D spectrogram images, and a convolutional neural network model is applied to the converted images for determining the status of the rotating body which is transmitted as normal or failure to the manager via Ethernet TCP/IP protocol.

Induction Motor Fault Diagnosis Using Support Vector Machine, Neural Networks, and Boosting Methods

Induction motors are robust and cost effective; thus, they are commonly used as power sources in various industrial applications. However, due to the characteristics of induction motors, industrial processes can stop when motor failures occur. Thus, research is required to realize the quick and accurate diagnosis of faults in induction motors. In this study, we constructed an induction motor simulator with normal, rotor failure, and bearing failure states. Using this simulator, 1240 vibration datasets comprising 1024 data samples were obtained for each state. Then, failure diagnosis was performed on the acquired data using support vector machine, multilayer neural network, convolutional neural network, gradient boosting machine, and XGBoost machine learning models. The diagnostic accuracies and calculation speeds of these models were verified via stratified K-fold cross validation. In addition, a graphical user interface was designed and implemented for the proposed fault diagnosis technique. The experimental results demonstrate that the proposed fault diagnosis technique is suitable for diagnosing faults in induction motors.

Dimensionality reduction method based on multiple feature-space collaborative discriminative projection for rotor fault diagnosis

At present, the trend for complex and intelligent rotating machinery and equipment, which generate a large amount of high-dimensional and nonlinear fault monitoring data that is difficult to handle, is becoming more and more apparent. This makes the traditional dimensionality reduction algorithms based on point-to-point metrics or a small number of graph-embedding structures lose their utility. To solve this problem, a multiple feature-space collaborative discriminative projection (MFSCDP) algorithm for rotor fault data set dimensionality reduction is proposed. The algorithm first improves the projection metric from sample point to feature space into the median metric in order to achieve the effect of weakening the extrapolation error of the algorithm, and based on this, we propose a sample point-to-point guided nearest-neighbor feature space selection method to improve the construction efficiency of the feature space embedding graph. Then, we use Relief F to indirectly construct the reduced dimensional projection matrix with multiple feature space of collaboration. Finally, the proposed MFSCDP algorithm is used for the dimensionality reduction process of a rotor fault data set. The algorithm’s performance was verified using experimental information from rotor failure simulations of two different structural types. The results show that the algorithm can reduce the difficulty of fault classification and improve the accuracy of identification.

Neural Classification of Rotor Faults in Three-Phase Induction Motors using Electric Current Signals in the Frequency Domain

Three-phase induction motors are widely used in different applications in the industry due to their robustness, low cost, and reliability. Untimely identification and correct diagnosis of incipient faults reduce cost and improve the maintenance management of these machines. This paper explores a new method for robust classification of rotor failures in three-phase induction motors (MITs) connected directly to the electrical network, operating in a steady-state, under unbalanced voltages and load conditions. Through an innovative methodology, an analysis of the electrical current signals from 1 hp and 2 hp motors in the frequency domain was performed. Such analysis was applied in constructing input matrices for a Multilayer Perceptron Neural Network (MLPNN) to detect faults. Furthermore, this methodology proved to be robust because the samples of the failing and healthy motors include voltage unbalance conditions in the electrical supply and a significant variation in the load applied to the motor shaft. Such load variation was used for the detection of failures of 1, 2, and 4 broken bars consecutively on the rotor and in the condition of 2 broken bars and 2 other broken bars diametrically opposite. The results were promising and were obtained using 847 real samples from an experimental bench used to construct the neural model and its respective validation.

Simultaneous Planning and Execution for Safe Flight of Quadrotors suffering One Rotor Loss and Disturbance

Safety is crucial for quadrotor flight, especially when the system suffers one rotor loss and disturbance. To enable quadrotors to survive in these worst cases, this paper proposes a Simultaneous Planning And Execution (SPAE) system strategy. First, the Euler angles under different equilibrium states are solved to ensure the feasibility of the control input when the quadrotors encounters rotor loss and disturbance. Based on the admissible Euler angle solutions, an emergency control strategy is proposed to realize desired angles by recalculating the desired trajectory and the disturbance observer. Meanwhile, this control strategy sacrifices the yaw angle control to handle further underactuation of the system caused by complete rotor failure. In addition to rotor losses, unsafe flight caused by actuator saturation is considered in the SPAE strategy where the planning and execution are simultaneous. As a decision maker, the planning considers the current disturbances and constraints of actuators, then generates a feasible trajectory for controller execution. As an executor of the decision, the controller feedback estimated disturbance information to the trajectory planning, which can help trajectory planning make admissible decisions consistent with the current situation. As a result, the actuator saturation caused by the underestimation of disturbance can be avoided under a feasible regenerated trajectory. Extensive simulations and experiments prove the validity of the proposed SPAE strategy.

Observer based rotor failure compensation for biplane quadrotor with slung load

In this study, mathematical modeling of biplane quadrotor with slung load is proposed. Performance of the biplane quadrotor is degrade while swinging of the slung load so to compensate it nonlinear observer based backstepping controller is designed that can not only handle the disturbance generated by the slung load but can also capable to tackle partial rotor failure and wind gust. Simulation study carried out by considering slung load swinging (only for quadrotor mode), wind gust, and rotor failure (for all three modes) as the external disturbance and nonlinear observer is design to estimate it. Backstepping control technique is used to design controller for all three modes of biplane quadrotor. Simulation study shows that proposed control scheme is cable to handle the disturbance generated by the different sources in quadrotor biplane.

Optimized Thermal Modeling and Broken Rotor Bar Fault Detection of BDFIG with Discrete Wavelet Transform

Nowadays, energy demand is increasing with the developing technology and industry. Due to the harmful effects of fossil fuels, which have a significant share in energy production and the fact that these fossil fuels will soon be consumed, alternative energy sources are needed to meet the unlimited request and demands of people on energy. Considering the sustainability of the fuel used in the production of energy and environmental damage, the importance of renewable energy sources increases. With the help of developing technology and research studies, the existing generator types have been tried to be improved and new types have been proposed. One of the proposed and still developing generator types is the brushless dual-supply asynchronous generator. The rotor structure can be coiled or squirrel cage type. In this study, the designs of the mentioned generator which are made so far have been investigated. As well as the electromagnetic field solution of the generator was made and further developed. The optimized thermal modeling of the machine has been proposed. In addition, rotor failure effect on magnetic field and flux was done by using analytical and finite element methods. Finally, detection of failure was carried out by using a discrete wavelet transform.

A sliding‐mode‐based active fault‐tolerant control for robust trajectory tracking in quad‐rotors under a rotor failure

AbstractIn this article an active fault‐tolerant control (FTC) is developed for the tracking problem in a quad‐rotor under the effects of a rotor failure and external disturbances. Such a strategy is composed of a finite‐time sliding‐mode observer, which estimates the full state from the measurable output and identifies uniformly bounded and Lipschitz disturbances. The failure scenario is analyzed in order to identify how it affects the dynamics. It is assumed that the failure has been isolated. The FTC design is composed of PID and continuous high‐order sliding‐modes controllers that allow the yaw angular velocity to remain bounded and the position tracking to be achieved even in the presence of some external disturbances. The closed‐loop stability is formally proven. Numerical simulations show the performance of the proposed control strategy.

Rotor Failure Compensation in a Biplane Quadrotor Based on Virtual Deflection

A biplane quadrotor is a hybrid type of UAV that has wide applications such as payload pickup and delivery, surveillance, etc. This simulation study mainly focuses on handling the total rotor failure, and for that, we propose a control architecture that does not only handle rotor failure but is also able to navigate the biplane quadrotor to a safe place for landing. In this structure, after the detection of total rotor failure, the biplane quadrotor will imitate reallocating control signals and then perform the transition maneuver and switch to the fixed-wing mode; control signals are also reallocated. A synthetic jet actuator (SJA) is used as the redundancy that generates the desired virtual deflection to control the pitch angle, while other states are taken care of by the three rotors. The SJA has parametric nonlinearity, and to handle it, an inverse adaptive compensation scheme is applied and a closed-loop stability analysis is performed based on the Lyapunov method for the pitch subsystem. The effectiveness of the proposed control structure is validated using numerical simulation carried out in the MATLAB Simulink.

Monocular Visual SLAM with 256-Bit Encryption on UAV

Abstract: Monocular Visual Slam with 256-Bit Encryption on UAV is based on the concept of Fault Tolerance Control System which is very crucial for the safety of critical systems such as quadrotors. Although, this method relies on external sensors, such as GPS or motion capture systems for state estimation. In this project, we propose the algorithm that combines fault tolerance control and onboard vision-based state estimation to achieve position control of a quadrotor subjected to complete failure of one rotor. It will use the video feed as input to create 2D pose estimation graph which will help it to pinpoint its location. In order to perform the VIO i.e., Visual Inertial Odometry, we need to combine the IMU sensor reading with the data coming from the monocular camera. To use VIO, PX4 Enabled flight controller needs to communicate with the companion computer via UART pin using MAVROS. Due to this, it will be an effective device in GPS denied environment. Its design will also allow the system to follow its set trajectory even after the rotor failure. And at last, the digital data transmission will take place in an encrypted format with AES-256 encryption to back up the data securely. We believe that our approach will render autonomous quadrotors safer in both GPS denied or degraded environment. Keywords: AES-256, Encryption, Visual SLAM, Visual Inertial Odometry, IMU