Variable Speed Profiles Research Articles

Neural Network Based Control of Four-Bar Mechanism with Variable Input Velocity

For control applications, the angular velocity of the drive crank of a four-bar mechanism is traditionally assumed to be constant. In this paper, we propose control of variable velocity of the drive crank to obtain the desired output motions for the coupler point. To estimate the reference trajectory for the crank velocity, a neural network is trained with data from the kinematic model. The control law is designed from feedback linearization of the tracking error dynamics and a Proportional–Integral–Derivative (PID) controller. The applicability of the proposed scheme is validated through simulations for three variable speed profiles, obtaining excellent results from the system.

A tool for validating and benchmarking signal processing techniques applied to machine diagnosis

This paper proposes a tool for the generation of synthetic mechanical signatures of faulted gears and bearings in non-stationary conditions. Synthetic signals are commonly used to provide early validation of vibration-based diagnostics techniques. In the absence of a standard tool, each researcher builds his/her own model keeping into account the characteristic features expected in a faulted condition. This approach implies two main consequences. The first one is that the complexity of simulated signals strictly depends on the researcher skills that could lead to excessively simple models that compromises the validation process. The second one is that there is not a widely accepted algorithm, or tool, for the generation of synthetic signals. This lack hinders simpler and consistent comparisons among signal processing techniques. Hence, the main goal of this paper is to supply to the scientific community a standard tool for the generation of synthetic mechanical signatures. The tool is provided under Creative Commons license and it allows to simulate different possible situations: from the basic case of a single bearing fault to the case of a multi-stage gearbox having either a localized fault and a distributed bearing fault. Among several features, the proposed tool could take also into account variable speed profiles of the input shaft, cyclostationary contributions and effects of linear time-invariant systems.

Assessing Postural Instability and Cybersickness Through Linear and Angular Displacement.

To examine the hypothesis that constant speed is more comfortable than variable speed profiles and may minimize cybersickness. Current best practices for virtual reality (VR) content creation suggest keeping any form of acceleration as short and infrequent as possible to mitigate cybersickness. In Experiment 1, participants experienced repetitions of simulated linear motion, and in Experiment 2, they experienced repetitions of a circular motion. Three speed profiles were tested in each experiment. Each trial lasted 2 min while standing. Cybersickness was measured using the Simulator Sickness Questionnaire (SSQ) and operationally defined in terms of total severity scores. Postural stability was measured using a Wii Balance Board and operationally defined in terms of center of pressure (COP) path length. Postural measures were decomposed into anterior-posterior and medial-lateral axes and subjected to detrended fluctuation analysis. For both experiments, no significant differences were observed between the three speed profiles in terms of cybersickness or postural stability, and none of the baseline postural measures could predict SSQ scores for the speed profile conditions. An axis effect was observed in both experiments such that normalized COP movement was significantly greater along the anterior-posterior axis than the medial-lateral axis. Results showed no convincing evidence to support the common belief that constant speed is more comfortable than variable speed profiles for scenarios typical of VR applications. The present findings offer guidelines for the design of locomotion techniques involving traversal in VR environments.

A bearing fault model for Independent Cart Conveyor System and its validation

Independent Cart Conveyor System is one of the most promising technology in automation industries. It combines the benefits of servo motors with the advantages of linear motors. It consists of a close path made up of modular linear motors having a curved or a straight shape that control a fleet of carts independently. Each cart is placed along the motors and it is connected, through rolling bearings, to a rail set on the motors themselves. The bearings are subject to wear and the condition monitoring of these elements is challenging for the non-stationary working conditions of variable load and variable speed profiles. This paper provides a bearing fault vibration model that takes into account the mechanical design of the cart, its motion profile, the shape of the conveyor path, the load variation and the type of fault on the rolling bearing.

Experimental Evidence of the Speed Variation Effect on SVM Accuracy for Diagnostics of Ball Bearings

In recent years, we have witnessed a considerable increase in scientific papers concerning the condition monitoring of mechanical components by means of machine learning. These techniques are oriented towards the diagnostics of mechanical components. In the same years, the interest of the scientific community in machine diagnostics has moved to the condition monitoring of machinery in non-stationary conditions (i.e., machines working with variable speed profiles or variable loads). Non-stationarity implies more complex signal processing techniques, and a natural consequence is the use of machine learning techniques for data analysis in non-stationary applications. Several papers have studied the machine learning system, but they focus on specific machine learning systems and the selection of the best input array. No paper has considered the dynamics of the system, that is, the influence of how much the speed profile changes during the training and testing steps of a machine learning technique. The aim of this paper is to show the importance of considering the dynamic conditions, taking the condition monitoring of ball bearings in variable speed applications as an example. A commercial support vector machine tool is used, tuning it in constant speed applications and testing it in variable speed conditions. The results show critical issues of machine learning techniques in non-stationary conditions.

Not FLEXible enough: Exploring the temporal dynamics of attentional reallocations with the multiple object tracking paradigm.

The dynamic environment of human observers requires continuous reallocations of visual attention to compensate for location changes of the attended objects. Particularly, situations with reduced spatial distance between targets and other objects in the display are crucial for keeping track of the target objects. In the present experiments, we explored how the temporal dynamics of such moments of reduced spacing affects the reallocation of visual attention. We asked participants to track 4 targets among indistinguishable distractors. Hereby, we manipulated whether target and distractor objects moved at a constant speed or whether their actual speed followed a sine wave profile. The variable speed oscillated around the constant speed thus maintaining average speed as well as traveled distance and average spatial proximity. We observed inferior tracking performance with variable speed profiles relative to constant speed profiles (Experiments 1a and 1b). When we increased the number of pairs of targets and distractors moving with a variable speed profile (Experiment 2), performance declined continuously. Remarkably, tracking performance also declined when only distractors moved at variable speeds, suggesting that the dynamic changes in interobject spacing rather than the variable speed impairs tracking (Experiment 3). In sum, our results provide evidence for a flexible allocation of the attentional resource toward targets suffering spatial interference by demonstrating the temporal constraints of the reallocation process. (PsycINFO Database Record

Speed estimation in wireless systems using wavelets

A new technique is described for estimating the speed of a mobile station in a wireless system. The mobile speed maps the characteristic spatial scale of the received signal into a characteristic temporal scale. The continuous wavelet transform tracks changes in the temporal scale to estimate the mobile speed as a function of time. This technique requires neither knowledge of the average received power of the nonstationary signal nor adaptation of a temporal observation window, in contrast to other speed estimators given in the literature. Simulations show the tracking of a variable speed profile.

A new approach to stability analysis of variable speed machining systems

This paper presents a new method for the stability analysis of variable speed machining systems. By using spindle angular position as the independent variable, the system dynamics are modeled as a linear periodic time-varying system with fixed delay. This representation is proven much easier to analyze and to numerically simulate than the time-varying delay representation, which traditionally uses the real-time as the independent variable. With a finite difference scheme, the infinite dimensional periodic time-varying system is approximated by a finite dimensional periodic time-varying discrete system, which in turn is converted to a time-invariant system by multiplying the time-varying state transition matrix over one period of speed variation. System-relative stability becomes tractable by spectral radius analysis. This approach makes possible the quantitative characterization of system stability as a function of variable speed profiles as well as other system parameters such as stiffness and damping of the cutting process and the tool/workpiece structure. Verifications for the face milling process by numerical simulation and experiment for both constant and variable speed are given.