Motor Noise Research Articles

Influence of the magnetic pole shape on the cogging torque of permanent magnet synchronous motor

ABSTRACTAiming at the problem of the permanent magnet synchronous motor (PMSM) vibration, noise and poor control precision caused by the cogging torque, the influence of different pole shapes on the motor electromagnetic field was studied. Based on the FEM, the effects of two types of the magnetic poles with different eccentricity on the magnetic field and induced electromotive force (EMF) are studied. The relationship between the magnetic poles shapes, the magnetic field and the induced EMF is obtained. Secondly, based on the Fourier decomposition theory, the air gap flux density harmonic content and the induced EMF are studied. The influence mechanism of the magnetic pole shape on the air gap flux density and the induced EMF is revealed. Finally, the cogging torque of the PMSM with different magnetic poles is studied, and the influence of different magnetic pole shape on the cogging torque is obtained. By optimising the shape of the magnetic pole, the maximum fluctuation amplitude of the cogging torque is reduced by 80.4%. The motor cogging torque can be effectively weakened by the PM eccentric design. This work lays a theoretical foundation for the study of cogging torque.

Current-Detection-Independent Dead-Time Compensation Method Based on Terminal Voltage A/D Conversion for PWM VSI

Dead-time insertion increases noise and torque pulsation in motors under open-loop constant V/f control, and it results in instability in motors under sensorless field-orientated control or direct torque control at low speed, degrading performance of motor drive systems. In order to overcome the drawback of dead-time insertion, a novel current-detection-independent dead-time compensation technique based on terminal voltage A/D conversion is proposed in this paper. Both current polarity and compensation time can be extracted from the sampled terminal voltage. Experiments on an induction motor rated at 210 V, 2.2 kW demonstrated the proposed technique can significantly improve the performance of the fixed compensation, online compensation, and even the feedback compensation method. The proposed scheme does not rely on current sensors, and thus can be applied to both open-loop and closed-loop motor drive systems. When combined with the fixed compensation method, the performance of the proposed technique is even comparable with the feedback compensation method within a large frequency range, making it very attractive for open-loop constant V/f drives where current sensors are not available.

Obstacle Avoidance Strategy using Onboard Stereo Vision on a Flapping Wing MAV

The development of autonomous lightweight MAVs, capable of navigating in unknown indoor environments, is one of the major challenges in robotics. The complexity of this challenge comes from constraints on weight and power consumption of onboard sensing and processing devices. In this paper we propose the "Droplet" strategy, an avoidance strategy based on stereo vision inputs that outperforms reactive avoidance strategies by allowing constant speed maneuvers while being computationally extremely efficient, and which does not need to store previous images or maps. The strategy deals with nonholonomic motion constraints of most fixed and flapping wing platforms, and with the limited field-of-view of stereo camera systems. It guarantees obstacle-free flight in the absence of sensor and motor noise. We first analyze the strategy in simulation, and then show its robustness in real-world conditions by implementing it on a 20-gram flapping wing MAV.

A Stochastic Feedback Model to Simulate Saccadic Eye Movement Variability

Variability is an important behavioral signature of biological movements that can be used as a tool to understand motor control. This study has modeled the inter-trial variability of very rapid eye movements called saccades by using a stochastic feedback model. The proposed model represents the brainstem saccade generation system with noise in the loop. Three types of noise signal namely visual noise, premotor noise and motor noise are considered in this model. The model can predict the inter-trial variability in the angular displacement of saccade trajectories. The accuracy of the predictions of the model has been verified using experimental data of horizontal saccades. It is observed that the presence of all the three noise components is important for the prediction of the dynamic evolution of the inter-trial variability during eye movement. This work provides a way to better understand the control of the saccadic system.

Loss and Air-gap Force Analysis of Cage Induction Motors With Non-skewed Asymmetrical Rotor Bars Based on FEM

Non-skewed asymmetrical rotors bars can be used to eliminate the slot harmonic fields and the resulting noise and vibration in cage induction motors. However, it is difficult to determine the spatial distribution of the asymmetrical rotor bars and the slot combinations, which can affect the loss and the air gap force significantly. With a 5.5 kW, 4-pole induction motor as an example, this paper studies the influence of the above factors on the loss and the air gap force by time-stepping finite element method, and the experiments are performed to validate the calculations.

Frequency response function of motors for switching noise energy with a new experimental approach

Switching energy in electrical vehicles can create serious noise from the motors. However, the characteristics of switching noise in vehicle motors are not clear due to the complexity of measuring them. This study proposes a new experimental method to investigate the switching noise energy of a vehicle motor based on frequency response functions. A function generator-amplifier system is used to generate the switching energy instead of the complex battery-inverter system that has previously been used to examine the noise energy characteristics. Even though newly adapted experimental method is simple, the switching noise energy was explicitly investigated under various input signals. Thus, this simple new method can be used to investigate the dynamic characteristics of noise energy in a vehicle motor.

Potential implications of acoustic stimuli as a non‐physical barrier to silver carp and bighead carp

AbstractThe effectiveness of an acoustic barrier to deter the movement of silver carp, Hypophthalmichthys molitrix (Valenciennes) and bighead carp, H. nobilis (Richardson) was evaluated. A pond (10 m × 5 m × 1.2 m) was divided in half by a concrete‐block barrier with a channel (1 m across) allowing fish access to each side. Underwater speakers were placed on each side of the barrier opening, and an outboard motor noise (broadband sound; 0.06–10 kHz) was broadcast to repel carp that approached within 1 m of the channel. Broadband sound was effective at reducing the number of successful crossings in schools of silver carp, bighead carp and a combined school. Repulsion rates were 82.5% (silver carp), 93.7% (bighead carp) and 90.5% (combined). This study demonstrates that broadband sound is effective in deterring carp and could be used as a deterrent in an integrated pest management system.

A Novel Sound Quality Evaluation Method of the Diagnosis of Abnormal Noise in Interior Permanent-Magnet Synchronous Motors for Electric Vehicles

A novel sound quality (SQ) evaluation method is developed to diagnose abnormal noise of interior permanent-magnet synchronous motors (IPMSM) for electric vehicle (EV). A-weighted sound pressure level (A-W SPL) of noise in IPMSM and six psychoacoustic characteristics, which include sharpness, roughness, loudness, articulation index, tonality, and fluctuation strength, are described through the objective evaluation of SQ. The paired comparison method (PCM) and the grade evaluation method (GEM) are respectively applied in subjective evaluation on relative annoyance and absolute annoyance of IPMSM for EV, and the combined application of these two methods is proposed originally. Finally, the BP neural network model for SQ evaluation of abnormal noise in IPMSM is established, the characteristics, conditions, and influencing factors of abnormal noise are effectively diagnosed. This novel evaluation method effectively solves the problem that the annoyance level is unable to be evaluated through the PCM, and the GEM relies on rich audition experience of evaluation subject. It also improves the accuracy of diagnosis of abnormal noise in IPMSM for EV.

Predicting explorative motor learning using decision-making and motor noise.

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant’s level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.

Influence of pole and slot combinations on vibration and noise in external rotor axial flux in‐wheel motors

This study provides a detailed finding of the influence of pole and slot combinations on vibration and noise in external rotor axial flux in-wheel motors (AFWMs). Firstly, electromagnetic force exerted on the surface of permanent magnet is discussed and a two-dimensional fast Fourier transformation is implemented to analyse its spatial distribution and frequency characteristics. Then, a multiphysics model is developed to predict the vibration and noise and figure out the main origin from the perspective of electromagnetism. The influence of pole and slot combinations on vibration and noise is also analysed via the proposed model. Finally, the effect of load on vibration and noise in AFWMs is further investigated. It turns out that zeroth spatial order of axial electromagnetic force is the main origin of vibration and noise in axial flux motors, which is quite different from radial flux motors. Moreover, AFWMs with larger lowest common multiple (LCM) of pole number (2 p ) and slot number ( Q s ) show lower noise level and for the motors that satisfy LCM(2 p,Q s ) ≠ 6 p , vibration and noise are greatly influenced by load. This study provides guidance for the design of low noise AFWMs.

Sensorimotor simulation and emotion processing: Impairing facial action increases semantic retrieval demands.

Sensorimotor models suggest that understanding the emotional content of a face recruits a simulation process in which a viewer partially reproduces the facial expression in their own sensorimotor system. An important prediction of these models is that disrupting simulation should make emotion recognition more difficult. Here we used electroencephalogram (EEG) and facial electromyogram (EMG) to investigate how interfering with sensorimotor signals from the face influences the real-time processing of emotional faces. EEG and EMG were recorded as healthy adults viewed emotional faces and rated their valence. During control blocks, participants held a conjoined pair of chopsticks loosely between their lips. During interference blocks, participants held the chopsticks horizontally between their teeth and lips to generate motor noise on the lower part of the face. This noise was confirmed by EMG at the zygomaticus. Analysis of EEG indicated that faces expressing happiness or disgust-lower face expressions-elicited larger amplitude N400 when they were presented during the interference than the control blocks, suggesting interference led to greater semantic retrieval demands. The selective impact of facial motor interference on the brain response to lower face expressions supports sensorimotor models of emotion understanding.

Parallel Specification of Visuomotor Feedback Gains during Bimanual Reaching to Independent Goals.

During goal-directed reaching, rapid visuomotor feedback processes enable the human motor system to quickly correct for errors in the trajectory of the hand that arise from motor noise and, in some cases, external perturbations. To date, these visuomotor responses, the gain of which is sensitive to features of the task and environment, have primarily been examined in the context of unimanual reaching movements toward a single target. However, many natural tasks involve moving both hands together, often to separate targets, such that errors can occur in parallel and at different spatial locations. Here, we examined the resource capacity of automatic visuomotor corrective mechanisms by comparing feedback gains during bimanual reaches, toward two targets, to feedback gains during unimanual reaches toward single targets. To investigate the sensitivity of the feedback gains and their relation to visual-spatial processing, we manipulated the widths of the targets and participants’ gaze location. We found that the gain of corrective responses to cursor displacements, while strongly modulated by target width and gaze position, were only slightly reduced during bimanual control. Our results show that automatic visuomotor corrective mechanisms can efficiently operate in parallel across multiple spatial locations.

Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

Objective. We studied the fundamentals of muscle afferentation by building a Neuro–mechano–morphic system actuating a cadaveric finger. This system is a faithful implementation of the stretch reflex circuitry. It allowed the systematic exploration of the effects of different fusimotor drives to the muscle spindle on the closed-loop stretch reflex response. Approach. As in Part I of this work, sensory neurons conveyed proprioceptive information from muscle spindles (with static and dynamic fusimotor drive) to populations of α-motor neurons (with recruitment and rate coding properties). The motor commands were transformed into tendon forces by a Hill-type muscle model (with activation-contraction dynamics) via brushless DC motors. Two independent afferented muscles emulated the forces of flexor digitorum profundus and the extensor indicis proprius muscles, forming an antagonist pair at the metacarpophalangeal joint of a cadaveric index finger. We measured the physical response to repetitions of bi-directional ramp-and-hold rotational perturbations for 81 combinations of static and dynamic fusimotor drives, across four ramp velocities, and three levels of constant cortical drive to the α-motor neuron pool. Main results. We found that this system produced responses compatible with the physiological literature. Fusimotor and cortical drives had nonlinear effects on the reflex forces. In particular, only cortical drive affected the sensitivity of reflex forces to static fusimotor drive. In contrast, both static fusimotor and cortical drives reduced the sensitivity to dynamic fusimotor drive. Interestingly, realistic signal-dependent motor noise emerged naturally in our system without having been explicitly modeled. Significance. We demonstrate that these fundamental features of spinal afferentation sufficed to produce muscle function. As such, our Neuro–mechano–morphic system is a viable platform to study the spinal mechanisms for healthy muscle function—and its pathologies such as dystonia and spasticity. In addition, it is a working prototype of a robust biomorphic controller for compliant robotic limbs and exoskeletons.

Inter-Joint Coordination Deficits Revealed in the Decomposition of Endpoint Jerk During Goal-Directed Arm Movement After Stroke.

It is well documented that neurological deficits after stroke can disrupt motor control processes that affect the smoothness of reaching movements. The smoothness of hand trajectories during multi-joint reaching depends on shoulder and elbow joint angular velocities and their successive derivatives as well as on the instantaneous arm configuration and its rate of change. Right-handed survivors of unilateral hemiparetic stroke and neurologically-intact control participants held the handle of a two-joint robot and made horizontal planar reaching movements. We decomposed endpoint jerk into components related to shoulder and elbow joint angular velocity, acceleration, and jerk. We observed an abnormal decomposition pattern in the most severely impaired stroke survivors consistent with deficits of inter-joint coordination. We then used numerical simulations of reaching movements to test whether the specific pattern of inter-joint coordination deficits observed experimentally could be explained by either a general increase in motor noise related to weakness or by an impaired ability to compensate for multi-joint interaction torque. Simulation results suggest that observed deficits in movement smoothness after stroke more likely reflect an impaired ability to compensate for multi-joint interaction torques rather than the mere presence of elevated motor noise.

Study of a Method for Reducing Electromagnetic Vibration and Noise of Motors, Focusing on Axial Mode Shapes of a Stator Core

Study of a Method for Reducing Electromagnetic Vibration and Noise of Motors, Focusing on Axial Mode Shapes of a Stator Core

SRモータの低振動・低騒音化

SRモータの低振動・低騒音化

Modeling and Analysis of Electromagnetic Force, Vibration, and Noise in Permanent-Magnet Synchronous Motor Considering Current Harmonics

This paper first derives the characteristics of radial electromagnetic force considering different types of current harmonics. By using two-dimensional fast Fourier transform, the force calculated by the finite element method is decomposed to obtain the frequencies of the force components in specific spatial order. Then, a multiphysics model for electromagnetic vibration and noise calculation is proposed. A modal test is implemented to validate the equivalent stator model and the nonuniform distribution of electromagnetic force acting on the teeth surface is taken into account through the nodal force transfer method. The calculated vibration and noise agree well with those obtained from experimental test. Finally, vibration and noise under different supply currents are investigated, and the variation patterns of the noise and vibration peaks are explained by the amplitude changes of the lowest spatial order force due to current harmonics. It is found that the influence of current harmonics on vibration and noise depends on their effect on the lowest spatial order force, and in order to figure out this effect, the phase angle, phase sequence, and frequency of current harmonics should all be considered.

Using noise to shape motor learning.

Many theories argue that we choose to make the specific movements that minimize motor noise. Here, by changing the relationship between movements and noise, we show that people actively learn to make movements that minimize noise. This not only provides direct evidence for the theories of noise minimization but presents a way to use noise to teach specific movements to improve rehabilitative therapies and human-machine interface control.

Motor noise is rich signal in autism research and pharmacological treatments.

The human body is in constant motion, from every breath that we take, to every visibly purposeful action that we perform. Remaining completely still on command is a major achievement as involuntary fluctuations in our motions are difficult to keep under control. Here we examine the noise-to-signal ratio of micro-movements present in time-series of head motions extracted from resting-state functional magnetic resonance imaging scans in 1048 participants. These included individuals with autism spectrum disorders (ASD) and healthy-controls in shared data from the Autism Brain Imaging Data Exchange (ABIDE) and the Attention-Deficit Hyperactivity Disorder (ADHD-200) databases. We find excess noise and randomness in the ASD cases, suggesting an uncertain motor-feedback signal. A power-law emerged describing an orderly relation between the dispersion and shape of the probability distribution functions best describing the stochastic properties under consideration with respect to intelligence quotient (IQ-scores). In ASD, deleterious patterns of noise are consistently exacerbated with the presence of secondary (comorbid) neuropsychiatric diagnoses, lower verbal and performance intelligence, and autism severity. Importantly, such patterns in ASD are present whether or not the participant takes psychotropic medication. These data unambiguously establish specific noise-to-signal levels of head micro-movements as a biologically informed core feature of ASD.

Development of a low-cost, low micro-vibration CMG for small agile satellite applications

The agility of the spacecraft which refers to the spacecraft's ability to execute fast and accurate manoeuvers within a fixed period of time, is a key satellite parameter. The spacecraft' s agility is directly proportional to the spacecraft actuators' output torque. For high torque inertial actuators (>0.5Nm), Control Moment Gyroscope (CMG) exhibits better performances in terms of mass and electrical power consumption than reaction wheels. However, in addition to the complex steering law required to avoid CMG singularities, one of the reasons why CMGs are not widely used is also due to their high micro-vibration emission which may interfere and disrupt the spacecraft' s sensitive instruments such as optical payloads. In this paper, an innovative two-stage viscoelastic isolation system has been designed and implemented in a new low micro-vibration CMG prototype. The first stage of the damping system acts at bearing level to attenuate the possible shock vibrations while the second stage acts at mechanism level to attenuate the structural resonances and motor noise. The developed CMG enables to combine high actuator output torque with a low micro-vibration signature. The viscoelastic damping system is cost effective as it is a fully passive system which requires no thermal control and no electronics. Furthermore, the attenuation provided by this innovative two stage damping system can reach a slope up to −80dB/dec which leads to a Mini-CMG micro-vibration signature lower than similar output torque reaction wheels not equipped with a damping system.