86 research outputs found
Haptics: Science, Technology, Applications
This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications
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Contour error compensation based on feed rate adjustment
To improve the performance of computer numerical control (CNC) machining, especially for large-curvature trajectories, this paper presents a contour error compensation algorithm based on reference trajectory modification. In order to estimate the contour error accurately and efficiently, a contour error estimation model is established. The reference trajectory is modified on the basis of the estimated contour error and partitioned into different segments, which adopt different feed rates according to a corner detection algorithm. The effectiveness of this contour error compensation algorithm is verified by experiments on a CNC machine tool
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Prediction and compensation of contour error of CNC systems based on LSTM neural-network
This paper proposes a contour error estimation and compensation method for computer numerical control (CNC) systems based on the long short-term memory neural network (LSTM-NN). This is achieved by performing modeling of each axis to predict the tracking error, calculating the actual trajectory, estimating the contour error, and modifying the reference trajectory. First, linear feature selection based on a simplified single-axis model and nonlinear feature selection based on a circular test are performed to achieve tracking error prediction. Then, a spline-approximation-based contour error estimation method is proposed to estimate the contour error between the reference trajectory and the predicted trajectory. Finally, contour error compensation is performed on the reference trajectory before it is run on CNC systems. The proposed method is validated through experiments on a three-axis CNC system
Adaptive Sliding Mode Contouring Control Design Based on Reference Adjustment and Uncertainty Compensation for Feed Drive Systems
Industrial feed drive systems, particularly, ball-screw and lead-screw feed drives are among the dominating motion components in production and manufacturing industries. They operate around the clock at high speeds for coping with the rising production demands. Adversely, high-speed motions cause mechanical vibrations, high-energy consumption, and insufficient accuracy. Although there are many control strategies in the literature, such as sliding mode and model predictive controls, further research is necessary for precision enhancement and energy saving. This study focused on design of an adaptive sliding mode contouring control based on reference adjustment and uncertainty compensation for feed drive systems. A combined reference adjustment and uncertainty compensator for precision motion of industrial feed drive systems were designed. For feasibility of the approach, simulation using matlab was conducted, and results are compared with those of an adaptive nonlinear sliding model contouring controller. The addition of uncertainty compensator showed a substantial improvement in performance by reducing the average contour error by 85.71% and the maximum contouring error by 78.64% under low speed compared to the adaptive sliding mode contouring controller with reference adjustment. Under high speed, the addition of uncertainty compensator reduced the average and absolute maximum contour errors by 4.48% and 10.13%, respectively. The experimental verification will be done in future.
Keywords: Machine tools, Feed drive systems, contouring control, Uncertainty dynamics, Sliding mode control
Undergraduate Student Catalog 2020-2021
The central pillars of Qatar University’s mission are highlighted through this document, namely the provision of high-quality education and the pursuit of an active role in the development of Qatari society. The courses described here have been designed, reviewed and assessed to meet the highest educational standards, with a strong focus on the knowledge and skill-based learning that is needed for a graduate to be competitive in today’s labor market and in graduate education pursuits. The many of the academic programs have attained independent external accreditation from internationally recognized associations, to cater to the needs of the country’s ambitious development course
Edge milled carbon fibre reinforced polymers: surface metrics and mechanical performance
Carbon fibre reinforced thermoset polymer (CFRP) components are becoming increasingly prevalent in aerospace and automotive industries where reduced weight and increased fuel efficiency is required. The manufacturing process typically requires the net shape to be edge trimmed, using a milling process, to achieve final part shape. The cutting process can cause defects on the trimmed edge which, due to the anisotropic nature of the CFRP material, may not be adequately captured by traditional, metallic material based surface quality metrics. More fundamentally, the effect on mechanical performance, in particular flexural strength, is not well understood.
The aim of this project is to investigate links between machined edge surfaces and static flexural properties. The effects of machine stiffness and cutting tool design, the effects of tool coating and tool wear, and finally, the effect of machining temperature on the surface quality and subsequent flexural strength are assessed. This is completed through the use of a robust framework to assess materials, machines and tools used in experimentation. Dynamometer data is captured and assessed through an original metric and current state-of-the-art 3D areal metrics are used to assess the machined surface topography. Additionally, scanning electron microscopy (SEM) is used to provide further qualitative data. Chips are collected and analysed, in a first for composite materials, to determine average geometry and changes due to machining variables. Finally, to address the shortcomings of current available metrics, a novel metric to observe sub-surface defects is proposed, validated and used to assess effects of machining variables on edge quality.
It has been found that edge quality does alter the mechanical strength of edge trimmed CFRP through static four-point bend analysis. Flexural strength of coupons machined by the 6-axis robotic system is 25.9% greater than the 5-axis gantry. Tool wear and machining at elevated temperatures can reduce flexural strength by 7.1 and 8.7%, respectively. Design of experiment (DoE) and analysis of variance (ANOVA) methods employed to show statistical correlations with machining variables and surface metrics. The edge quality of CFRP, machined using prescribed variables, has been successfully linked to amplitude and volumetric 3D areal metrics (p < 0.05). Cutting mechanisms of different fibre orientations have been successfully characterised through SEM and areal analysis. Analysis of machining chips has confirmed cutting mechanism changes when the CFRP material is pre-heated up to glass transition onset. A novel, validated strategy for measuring sub-surface defects, was able to observe defects in edge trimmed samples, particularly in the 90° fibre region where matrix smearing previously prevented observation of damage
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Reference trajectory modification based on spatial iterative learning for contour control of 2-axis NC systems
Contour error is a main factor that affects the quality of products in numerical control (NC) machining. This paper presents a contour control strategy based on digital curves for high-precision control of computer numerical control (CNC) machines. A contour error estimation algorithm is presented for digital curves based on a geometrical method. The dynamic model of the motion control system is transformed from time domain to space domain because the contour error is dependent on space instead of time. Spatial iterative learning control (sILC) is developed to reduce the contour error, by modifying the reference trajectory in the form of G code. This allows system improvement without interference of low-level controllers so it is applicable to many commercial controllers where interpolators and feed-drive controllers cannot be altered. The effectiveness of this method is verified by experiments on a NC machine, which have shown good performance not only for smooth trajectories but also for large curvature trajectories
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