Thermal Error Modelling of a CNC Machine Tool Feed Drive System using FEA Method

Recirculating ball screw systems are commonly used in machine tools and are one of the major heat sources which cause considerable thermal drift in CNC machine tools. Finite Element Analysis (FEA) method has been used successfully in the past to model the thermal characteristics of machine tools with promising results. Since FEA predictions are highly dependent on the efficacy of numerical parameters including the surrounding Boundary Conditions (BC), this study emphasises on an efficient modelling method to obtain optimised numerical parameters for acquiring a qualitative response from the feed drive system model. This study was performed on a medium size Vertical Machining Centre (VMC) feed drive system in which two parameter dentification methods have been employed; the general prediction method based on formulae provided by OEMs, and the energy balance method. The parameters obtained from both methods were applied to the FEA model of the machine feed drive system and validated against experimental results. Correlation with which was increased from 70 % to 80 % using the energy balance method

Application of multi sensor data fusion based on Principal Component Analysis and Artificial Neural Network for machine tool thermal monitoring

Due to the various heat sources on a machine tool, there exists a complex temperature distribution across its structure. This causes an inherent thermal hysteresis which is undesirable as it affects the systematic tool –to-workpiece positioning capability. To monitor this, two physical quantities (temperature and strain) are measured at multiple locations. This article is concerned with the use of Principal Component Analysis (PCA) and Artificial Neural Networks (ANN) to fuse this potentially large amount of data from multiple sources. PCA reduces the dimensionality of the data and thus reduces training time for the ANN which is being used for thermal modelling. This paper shows the effect of different levels of data compression and the application of rate of change of sensor values to reduce the effect of system hysteresis. This methodology has been successfully applied to the ram of a 5-axis gantry machine with 90 % correlation to the measured displacement

Semi-leptonic Ds+D_s^+(1968) decays as a scalar meson probe

The unusual multiplet structures associated with the light spin zero mesons have recently attracted a good deal of theoretical attention. Here we discuss some aspects associated with the possibility of getting new experimental information on this topic from semi-leptonic decays of heavy charged mesons into an isosinglet scalar or pseudoscalar plus leptons.Comment: 11 pages, 4 figure

Electrical transport and optical studies of ferromagnetic Cobalt doped ZnO nanoparticles exhibiting a metal-insulator transition

The observed correlation of oxygen vacancies and room temperature ferromagnetic ordering in Co doped ZnO1-o nanoparticles reported earlier (Naeem et al Nanotechnology 17, 2675-2680) has been further explored by transport and optical measurements. In these particles room temperature ferromagnetic ordering had been observed to occur only after annealing in forming gas. In the current work the optical properties have been studied by diffuse reflection spectroscopy in the UV-Vis region and the band gap of the Co doped compositions has been found to decrease with Co addition. Reflections minima are observed at the energies characteristic of Co+2 d-d (tethrahedral symmetry) crystal field transitions, further establishing the presence of Co in substitutional sites. Electrical transport measurements on palletized samples of the nanoparticles show that the effect of a forming gas is to strongly decrease the resistivity with increasing Co concentration. For the air annealed and non-ferromagnetic samples the variation in the resistivity as a function of Co content are opposite to those observed in the particles prepared in forming gas. The ferromagnetic samples exhibit an apparent change from insulator to metal with increasing temperatures for T>380K and this change becomes more pronounced with increasing Co content. The magnetic and resistive behaviors are correlated by considering the model by Calderon et al [M. J. Calderon and S. D. Sarma, Annals of Physics 2007 (Accepted doi: 10.1016/j.aop.2007.01.010] where the ferromagnetism changes from being mediated by polarons in the low temperature insulating region to being mediated by the carriers released from the weakly bound states in the higher temperature metallic region.Comment: 7 pages, 6 figure

Towards obtaining robust boundary condition parameters to aid accuracy in FEA thermal error predictions

Finite Element Analysis (FEA) is used as a design tool within engineering industries due to the capability for rapid summative analysis accompanied by the visual aid. However, to represent realistic behaviour, FEA relies heavily on input parameters which must ideally be based on true figures such as data from experimental testing which sometimes requires time-consuming testing regimes. In the case of machine tool assemblies where complex structural joints and linkages are present, access to those areas can be a primary constraint to obtaining related boundary parameters such as heat flow across joints, for which, assumptions are incorporated to the FEA model which in effect increase the uncertainty in the FEA predictions. Similarly, in the case of thermal error modelling, simplifications are made when representing thermal boundary conditions such as the application of a uniform convection parameter to an assembly with parts assembled in both horizontal and vertical orientations. This research work aims to reduce the number of assumptions by providing experimentally obtained thermal boundary condition parameters. This work acknowledges experimental regimes that focus on obtaining thermal parameters related to the conduction across assembly joints (Thermal Contact Conductance-TCC) and measures the convection around areas such as belt drives and rotating parts to obtain convection parameters as inputs to the FEA. It provides TCC parameters for variable interfacial behaviour based on the varying contact pressure and the heat flow through dry and oiled contacts such as the conduction from spindle bearings to the surrounding housing and conduction from guideways into the associated assembly through carriages and contact bearings. It provides convection parameters across the test mandrel rotating at different speeds and around stationary structures such as convection parameters observed during TCC tests. It also provide details on the methods used to obtain all these parameters such as the use of thermal imaging, sensors placements and methods to obtain these boundary condition parameters. The significance of this work is to improve dramatically FEA thermal predictions, which are a critical part of engineering design. Although the focus is on machine tool design, the process and parameters can equally be applied to other areas of thermodynamic behaviour

Denial of service attacks and challenges in broadband wireless networks

Broadband wireless networks are providing internet and related services to end users. The three most important broadband wireless technologies are IEEE 802.11, IEEE 802.16, and Wireless Mesh Network (WMN). Security attacks and vulnerabilities vary amongst these broadband wireless networks because of differences in topologies, network operations and physical setups. Amongst the various security risks, Denial of Service (DoS) attack is the most severe security threat, as DoS can compromise the availability and integrity of broadband wireless network. In this paper, we present DoS attack issues in broadband wireless networks, along with possible defenses and future directions

FEA-based design study for optimising non-rigid error detection on machine tools

Non-rigid-body behaviour can have a considerable effect on the overall accuracy performance of machine tools. These errors originate from bending of the machine structure due to change in distribution of its own weight or from movement of the workpiece and fixture. These effects should be reduced by good mechanical design, but residual errors can still be problematic due to realistic material and cost limitations. One method of compensation is to measure the deformation directly with sensors embedded in a metrology frame. This paper presents an FEA-based design study which assesses finite stiffness effects in both the machine structure and its foundation to optimise the sensitivity of the frame to the resulting errors. The study results show how a reference artefact, optimised by the FEA study, can be used to detect the distortion

Explanatory model of illness of the patients with schizophrenia and the role of educational intervention

This randomized controlled trial was conducted at Department of Psychiatry, Lady Reading Hospital, Peshawar from February to August 2015 to explore beliefs and concepts of patients with schizophrenia about their illness and to find out the effectiveness of structured educational intervention in changing the explanatory models of illness of the patients and in their symptoms reduction. One hundred and three patients were recruited in the trial who were randomly assigned to two groups i.e., Experimental (n = 53) and Control i.e., Treatment As Usual, TAU (n = 50). Intervention was applied to experimental group only, once a month for three months. Short Explanatory Model Interview (SEMI), Brief Psychiatric Rating Scale (BPRS), Positive And Negative Syndrome Scale (PANSS), Global Assessment of Functioning (GAF) and Compliance Rating Scale were applied on all patients at baseline and at 3 months follow up. Scores on PANSS (Total), BPRS and GAF showed improvement in the experimental group as compared to TAU group, at follow up, with the p values of 0.000, 0.002 and 0.000, respectively. On follow up, 44 (95.6%) patients of experimental group achieved complete compliance as compared to 17 (47.2%) patients of TAU group [p = 0.000]. On baseline analysis of SEMI, in the experimental group, only 3.8% (n = 2) knew about name of the illness, which increased to 54.3% (n = 25) on follow up, while in TAU group it improved to 5.6% (n = 2) as compared to 0% at baseline (p = 0.000). The result suggest that Structured educational intervention can be effective in modifying the beliefs of the patients regarding their illness

Mutations in phosphodiesterase 6 identified in familial cases of retinitis pigmentosa.

To delineate the genetic determinants associated with retinitis pigmentosa (RP), a hereditary retinal disorder, we recruited four large families manifesting cardinal symptoms of RP. We localized these families to regions on the human genome harboring the α and β subunits of phosphodiesterase 6 and identified mutations that were absent in control chromosomes. Our data suggest that mutations in PDE6A and PDE6B are responsible for the retinal phenotype in these families

The Effect of Fish Size and Condition on the Contents of Twelve Essential and Non Essential Elements in Aristichthys nobilis

The correlation coefficients between fish size (body weight and total length) and metal contents (Na, K, Ca, Mg, Mn, Fe, Cu, Zn, Cr, Co, Cd and Pb) in whole fish (Aristichthys nobilis) were determined. A total of 71 fish samples were collected from hatcheries and fish reservoirs located in Islamabad and Fatehjung. Highly significant (P<0.001) relationship between metal concentrations and fish size was found. Most of the metals (Na, K, Ca, Mg, Cu, Zn, Cr, Cd and Pb) showed an isometric increase, while Mn, Fe and Co showed an allometric increase in with increasing body weight. All metals showed isometric increase, while, Na, Mn, Fe, Cu, and Co showed positive allometric growth in relation to total length. The correlation coefficient (r) between different variables and wet body weight, condition factor was found highly significant (P<0.001) in examined fish except for Na, Ca, Cu, Zn, Cd and Pb while for total length the same results found except Ca, Cd, Zn and Pb. Variance inflation factor values of regression coefficients in multiple regression analysis for each variable were lesser than 10. The metal levels of the examined fish were lower than the recommended values in fish and fishery products set by FAO