Angular Acceleration Signal Research Articles

Torsional and lateral vibration analysis of wind turbine generator bearing outer ring fault considering unbalanced magnetic pull

Rolling bearings play a critical role in wind turbine generators, operating continuously in an electromagnetic excitation environment. Their fault vibration characteristics are affected by unbalanced magnetic pull (UMP), which has received little attention in previous studies. Moreover, torsional vibration can provide advantages in bearing fault diagnosis, since it has a good signal-to-noise ratio (SNR) and it can be easily measured by the encoder. However, torsional vibration is rarely considered in the existing model of wind turbine generator. Accordingly, this paper proposes a dynamic model with 8 degrees of freedom to analyze the bearing outer ring fault characteristics of wind turbine generator under the influence of UMP, while also taking into account the torsional vibration in the model. The validity of the model is verified through experiments conducted on a test rig. The results displays modulation of the ball pass frequency outer (BPFO) harmonics with both UMP frequency and rotation frequency in lateral vibration, and this phenomenon can also be observed in instantaneous angular speed (IAS) and instantaneous angular acceleration (IAA) signals that represent torsional vibration. Besides, the lateral vibration spectrum reveals two distinct resonance bands, and simulation analysis suggested that the rotor and bearings give rise to low-frequency and high-frequency resonance, respectively. This study provides a reference for bearing faults diagnosis in wind turbine generator.

Frame Angular Velocity Control Design of SGCMG for Unmanned Two-Wheeled Motorcycle

In contrast to driverless cars and other three-wheeled and four-wheeled motorcycle vehicles, driverless two-wheeled motorcycles have the problem of maintaining balance. In this paper, we propose the design of an SGCMG frame angular velocity controller to realize the balance control of the motorcycle under static and dynamic working conditions. Meanwhile, since the roll angular acceleration of the actual body movement of the cross roll cannot be obtained directly, this paper proposes a Kalman filtering method based on the nonlinear dynamics model of the motorcycle to obtain a reliable angular acceleration signal. First, we modeled the dynamics of the motorcycle by analyzing the various types of moments generated by the motorcycle equipped with the SGCMG under static and dynamic conditions; Then, the design of the angular velocity control of the SGCMG frame was carried out with the feedback and through MATLAB/Simulink simulation to restore various types of actual working conditions to verify the controller has good robustness; Finally, we have completed the test of the controller using the above filtering method on the real vehicle with an embedded system and compared the effect with other controllers, obtained the results that the body is stable and balanced under static conditions and the applied load can automatically find a new balance point, so as to prove the effectiveness of the designed control.

Dynamic response of a coal rock caving impact tail beam for hydraulic support

Based on the two-way coupling technology of Discrete Element Method-Multi Flexible Body Dynamics (EDM-FMBD), a virtual caving coal wall is established by using the discrete element software, EDEM. The rigid flexible coupling model of the tail beam of caving supports is established by using multibody dynamics software, RecurDyn. The stiffness of the oil cylinder is calculated by using the solid–liquid spring coupling theory and is replaced by a spring. By simulating the process of a coal rock collapse impacting the tail beam, the dynamic signal from the coal rock collapse impacting the tail beam to crushing in the coal caving stage of the comprehensive caving working face is studied, and the test is carried out underground. The angular acceleration at the hinge point of the tail beam is the largest and shows a variation pattern of "large at both ends and small in the middle". The definition of a "low amplitude band" on the surface of the tail beam is proposed. The force signal at the hinge point of the front link is the strongest and is the best measurement point for the force sensor; the angular acceleration signal at the hinge point of the tail beam is the strongest and it is the best measurement point for the angular acceleration sensor. The results have practical implications for the identification of the coal gangue and the adaptive control of support for integrated top coal mining.

로봇팔의 시간지연 제어기에서 각 가속도 추정에 대한 추종 성능 비교연구

This paper presents a comparative study of tracking performances between several methods of estimating acceleration signals for a time-delayed controller(TDC) of a robot manipulator. To implement the time-delayed controller completely, there are three requirements: 1) Fast sampling time, 2) constant inertia value, and 3) angular acceleration signals. This paper focuses on the acceleration estimation for TDC. Several methods for angular acceleration estimation are tested: 1) Finite difference method with low pass filtering, 2) Kalman filtering, 3) desired angular acceleration, 4) control input, 5) Jacobian relationship. We experimented five methods on one arm of a dual arm robot to follow a circular trajectory and their tracking performances are compared.

Continuous Fixed-Time Sliding Mode Attitude Controller Design for Rigid-Body Spacecraft

Fast and high-precision attitude control for the rigid spacecraft is important for its broad applications in astronautics. In this paper, we address this problem via continuous nonsingular fixed-time sliding mode control approach. At first, by improving the adding power integral technique, a nonsingular nominal attitude controller is presented to achieve fixed-time convergence of the unperturbed attitude system, which underpins the basics for design of the sliding mode motion and surfaces for the subsequent proposed main results. Then, a fixed-time full-order sliding mode controller with an explicit bound of settling time is proposed to track the desire attitude even in the presence of external disturbances. However, this controller requires the angular acceleration signals which is usually unmeasurable. To this end, an integral sliding mode controller is further presented to achieve fixed-time attitude tracking without using any acceleration information. This proposed integral sliding mode controller can realize second-order sliding mode with rigorous proof of fixed-time convergence. Both the proposed fixed time full-order and integral sliding mode controller are inherent nonsingular and chattering-free. Numerical examples are illustrated to demonstrate the effectiveness of the results given herein in practical scenarios.

Validation of an anti-slip control method based on the angular acceleration of a wheel on a roller rig

This study deals with the validation of an anti-slip control method that is based on the acceleration of a wheel. The method uses the angular acceleration signal and a threshold value to prevent the wheel from a severe slip. Initially, the implemented method was tested with an experimental roller rig under several wheel–roller surface conditions (half-dry, wet and greasy). Then, the validity of the control algorithm was verified using the numerical model of a full-scale roller rig that is built via the MATLAB editor, with the simulation scenarios following the experiments. The results from both experiments and simulations confirm that the acceleration-based slip regulation controller prevents the excessive wheel slip and improves the traction performance of a rail vehicle. Moreover, it is observed that the performance of the controller could be further improved by properly setting the control parameters of the acceleration-based slip regulation controller.

Correction of cosine oscillation to the improved correlation method of estimating the amplitude of gravitational background signal**Project supported by the National Natural Science Foundation of China (Grant Nos. 11575160, 11175160, 11275075, and 11511130011).

In the measurement of G with the angular acceleration method, the improved correlation method developed by Wu et al. (Wu W H, Tian Y, Luo J, Shao C G, Xu J H and Wang D H 2016 Rev. Sci. Instrum. 87 094501) is used to accurately estimate the amplitudes of the prominent harmonic components of the gravitational background signal with time-varying frequency. Except the quadratic slow drift, the angular frequency of the gravitational background signal also includes a cosine oscillation coming from the useful angular acceleration signal, which leads to a deviation from the estimated amplitude. We calculate the correction of the cosine oscillation to the amplitude estimation. The result shows that the corrections of the cosine oscillation to the amplitudes of the fundamental frequency and second harmonic components obtained by the improved correlation method are within respective errors.

Design and performance analysis of control algorithm for a floating wind turbine on a large semi-submersible platform

A control algorithm for a floating wind turbine installed on a large semi-submersible platform is investigated in this study. The floating wind turbine is different from other typical semi-submersible floating wind turbines in that the platform is so large that the platform motion is not affected by the blade pitch control. For simulation, the hydrodynamic forces data were obtained from ANSYS/AQWA, and implemented to Bladed. For the basic pitch controller, the well-known technique to increase damping by reducing the bandwidth of the controller lower than the platform pitch mode was implemented. Also, to reduce the tower load in the pitch control region, a tower damper based on the nacelle angular acceleration signal was designed. Compared with the results obtained from an onshore wind turbine controller applied to the floating wind turbine, the floating wind turbine controller could reduce the tower moments effectively, however, the standard deviation in power increased significantly.

Influence of tungsten fiber's slow drift on the measurement of G with angular acceleration method.

In the measurement of the gravitational constant G with angular acceleration method, the equilibrium position of torsion pendulum with tungsten fiber undergoes a linear slow drift, which results in a quadratic slow drift on the angular velocity of the torsion balance turntable under feedback control unit. The accurate amplitude determination of the useful angular acceleration signal with known frequency is biased by the linear slow drift and the coupling effect of the drifting equilibrium position and the room fixed gravitational background signal. We calculate the influences of the linear slow drift and the complex coupling effect on the value of G, respectively. The result shows that the bias of the linear slow drift on G is 7 ppm, and the influence of the coupling effect is less than 1 ppm.

High-Precision Calibration for MEMS Gyroscopes Based on Persistent Excitation Signal Criterion

The micro inertial gyroscopes based on the electro-mechanical system (MEMS gyros) are widely used in many applications. The calibration parameters include zero drifts, scale factors and installation errors, which are determined by calibration. Measurements often show large errors because of being not precisely calibrated and effectively compensated. This paper selects the constant angular acceleration signal as the excitation signal based on Persistent Excitation Signal Criterion (PE Criterion) in the modern control theory. The calibration scheme and data acquisition program are proposed. Calibration parameters are obtained using superposition, cross-correlation data processing methods. The effectiveness and reliability of the proposed calibration procedures are proven by simulations. Experimental results show that the proposed method is an efficient and simple high-precision calibration method.

Improved automated diagnosis of misfire in internal combustion engines based on simulation models

In this paper, a new advance in the application of Artificial Neural Networks (ANNs) to the automated diagnosis of misfires in Internal Combustion engines(IC engines) is detailed. The automated diagnostic system comprises three stages: fault detection, fault localization and fault severity identification. Particularly, in the severity identification stage, separate Multi-Layer Perceptron networks (MLPs) with saturating linear transfer functions were designed for individual speed conditions, so they could achieve finer classification. In order to obtain sufficient data for the network training, numerical simulation was used to simulate different ranges of misfires in the engine. The simulation models need to be updated and evaluated using experimental data, so a series of experiments were first carried out on the engine test rig to capture the vibration signals for both normal condition and with a range of misfires. Two methods were used for the misfire diagnosis: one is based on the torsional vibration signals of the crankshaft and the other on the angular acceleration signals (rotational motion) of the engine block. Following the signal processing of the experimental and simulation signals, the best features were selected as the inputs to ANN networks. The ANN systems were trained using only the simulated data and tested using real experimental cases, indicating that the simulation model can be used for a wider range of faults for which it can still be considered valid. The final results have shown that the diagnostic system based on simulation can efficiently diagnose misfire, including location and severity.

Research on Application of Wavelet Denoising Method Based on Signal to Noise Ratio in the Bench Test

During the tests of the vehicle automatic transmission bench, the acceleration signal is needed to be denoised. As a means of denoising, wavelet threshold denoising method has small amount of calculation and better filtering effect. However, adopting different wavelet basis functions as well as different threshold rules might have a direct effect on the signal denoising. In this paper, we firstly construct the simulated noisy signal approximated to the observed signal, and then do the signal denoising experiment of parameter matching. Secondly, seven Symlets wavelet basis functions and four classical wavelet threshold rules are selected and tested one by one. Signal to noise ratio (SNR) and root mean square error (RMSE) of the denoised signal, the evaluation indicators, are calculated and carried out in accordance with the merits of denoising effect. Thus the optimal combination of the fixed threshold rule and sym8 wavelet basis function is obtained. Finally, this combination is used in the bench test to denoise the angular acceleration signal, and good filtering effect is achieved.

Inertia Compensation of EPS Based on Kalman Filtering

The dynamic performance of an electric power steering system (EPS) is deteriorated by the inertia of assistant motor embodied in EPS. To compensate the effect of motor inertia and improve the dynamic performance of EPS, the angular acceleration of the motor rotor is needed. However, the angular acceleration cannot be derived by differentiating the rotor angle signal of the permanent magnet synchronous motor (PMSM) directly, for the noise will be amplified. This paper attempts to get motor angular acceleration signal through Kalman filtering method and the angular acceleration signal acquired by this method is calibrated with high precision encoder, furthermore, the signal is verified though simulation and experiment of inertia compensation control. All the calibration results and simulation and experiment results of inertia compensation control show that the angular acceleration acquired through Kalman filtering method is available for the realization of motor inertia compensation control and can achieve the purpose of improving the dynamic performance of the steering system.

A Comparative Approach to Hand Force Estimation using Artificial Neural Networks.

In many applications that include direct human involvement such as control of prosthetic arms, athletic training, and studying muscle physiology, hand force is needed for control, modeling and monitoring purposes. The use of inexpensive and easily portable active electromyography (EMG) electrodes and position sensors would be advantageous in these applications compared to the use of force sensors which are often very expensive and require bulky frames. Among non-model-based estimation methods, Multilayer Perceptron Artificial Neural Networks (MLPANN) has widely been used to estimate muscle force or joint torque from different anatomical features in humans or animals. This paper investigates the use of Radial Basis Function (RBF) ANN and MLPANN for force estimation and experimentally compares the performance of the two methodologies for the same human anatomy, ie, hand force estimation, under an ensemble of operational conditions. In this unified study, the EMG signal readings from upper-arm muscles involved in elbow joint movement and elbow angular position and velocity are utilized as inputs to the ANNs. In addition, the use of the elbow angular acceleration signal as an input for the ANNs is also investigated.

Functional Organization of Vestibular Commissural Connections in Frog

Central vestibular neurons receive substantial inputs from the contralateral labyrinth through inhibitory and excitatory brainstem commissural pathways. The functional organization of these pathways was studied by a multi-methodological approach in isolated frog whole brains. Retrogradely labeled vestibular commissural neurons were primarily located in the superior vestibular nucleus in rhombomeres 2/3 and the medial and descending vestibular nucleus in rhombomeres 5-7. Restricted projections to contralateral vestibular areas, without collaterals to other classical vestibular targets, indicate that vestibular commissural neurons form a feedforward push-pull circuitry. Electrical stimulation of the contralateral coplanar semicircular canal nerve evoked in canal-related second-order vestibular neurons (2 degrees VN) commissural IPSPs (approximately 70%) and EPSPs (approximately 30%) with mainly (approximately 70%) disynaptic onset latencies. The dynamics of commissural responses to electrical pulse trains suggests mediation predominantly by tonic vestibular neurons that activate in all tonic 2 degrees VN large-amplitude IPSPs with a reversal potential of -74 mV. In contrast, phasic 2 degrees VN exhibited either nonreversible, small-amplitude IPSPs (approximately 40%) of likely dendritic origin or large-amplitude commissural EPSPs (approximately 60%). IPSPs with disynaptic onset latencies were exclusively GABAergic (mainly GABA(A) receptor-mediated) but not glycinergic, compatible with the presence of GABA-immunopositive (approximately 20%) and the absence of glycine-immunopositive vestibular commissural neurons. In contrast, IPSPs with longer, oligosynaptic onset latencies were GABAergic and glycinergic, indicating that both pharmacological types of local inhibitory neurons were activated by excitatory commissural fibers. Conservation of major morpho-physiological and pharmacological features of the vestibular commissural pathway suggests that this phylogenetically old circuitry plays an essential role for the processing of bilateral angular head acceleration signals in vertebrates.

Recognition of the physiological actions of the triphasic EMG pattern by a dynamic recurrent neural network

Triphasic electromyographic (EMG) patterns with a sequence of activity in agonist (AG1), antagonist (ANT) and again in agonist (AG2) muscles are characteristic of ballistic movements. They have been studied in terms of rectangular pulse-width or pulse-height modulation. In order to take into account the complexity of the EMG signal within the bursts, we used a dynamic recurrent neural network (DRNN) for the identification of this pattern in subjects performing fast elbow flexion movements. Biceps and triceps EMGs were fed to all 35 fully-connected hidden units of the DRNN for mapping onto elbow angular acceleration signals. DRNN training was supervised, involving learning rule adaptations of synaptic weights and time constants of each unit. We demonstrated that the DRNN is able to perfectly reproduce the acceleration profile of the ballistic movements. Then we tested the physiological plausibility of all the networks that reached an error level below 0.001 by selectively increasing the amplitude of each burst of the triphasic pattern and evaluating the effects on the simulated accelerating profile. Nineteen percent of these simulations reproduced the physiological action classically attributed to the 3 EMG bursts: AG1 increase showed an increase of the first accelerating pulse, ANT an increase of the braking pulse and AG2 an increase of the clamping pulse. These networks also recognized the physiological function of the time interval between AG1 and ANT, reproducing the linear relationship between time interval and movement amplitude. This task-dynamics recognition has implications for the development of DRNN as diagnostic tools and prosthetic controllers.

Dynamic properties of vestibular reflexes in the decerebrate cat.

Vestibulocollic (VCR) and vestibulo-ocular (VOR) reflexes were studied during angular rotation in the horizontal plane in precollicular decerebrate cats. Angular position was modulated by sinusoids or sums of sinusoids with frequencies ranging from 0.05 to 5 Hz. Reflex motor output was measured by recording electromyographic (EMG) activity of the lateral rectus and dorsal neck muscles and discharge of abducens motoneurons. Measured with respect to input angular acceleration VCR motor output displayed a second order lag at low frequencies, bringing mean EMG phase (-136 degrees) and gain slope (-35 dB/decade) close to those of an angular position signal at 0.2 Hz. At higher frequencies the lag was counteracted by a second order lead bringing mean phase (-52 degrees) and gain slope (-5.6 dB/decade) back close to those of an angular acceleration signal at 3 Hz. By contrast, mean phase (-113 degrees to -105 degrees) and gain slope (-21 to -28 dB/decade) of the VOR motor output remained close to those of an angular velocity signal across the entire frequency range. The data suggest that neural pathways producing the VCR receive selective input from "irregular type" horizontal semicircular canal afferents which provide one lag and one lead in the overall transfer function while the other lag and lead are produced by central pathways. Transection of the medial longitudinal fasciculus (MLF), which eliminates all of the most direct (three neuron) arcs of the horizontal VCR, did not cause any detectable change in the horizontal VCR at either low or high frequencies. Reductions in overall gain occurred in some cases but these could be attributed to damage to axons outside the MLF. Less direct pathways, probably including vestibuloreticulospinal pathways, are thus able to produce both the low-frequency, phase-lagging and high-frequency, phase-leading components of the horizontal VCR.