The application of ANFIS prediction models for thermal error compensation on CNC machine tools

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon the accuracy and robustness of the thermal error model and its input measurements. This paper first reviews different methods of designing thermal error models, before concentrating on employing an adaptive neuro fuzzy inference system (ANFIS) to design two thermal prediction models: ANFIS by dividing the data space into rectangular sub-spaces (ANFIS-Grid model) and ANFIS by using the fuzzy c-means clustering method (ANFIS-FCM model). Grey system theory is used to obtain the influence ranking of all possible temperature sensors on the thermal response of the machine structure. All the influence weightings of the thermal sensors are clustered into groups using the fuzzy c-means (FCM) clustering method, the groups then being further reduced by correlation analysis. A study of a small CNC milling machine is used to provide training data for the proposed models and then to provide independent testing data sets. The results of the study show that the ANFIS-FCM model is superior in terms of the accuracy of its predictive ability with the benefit of fewer rules. The residual value of the proposed model is smaller than ±4 μm. This combined methodology can provide improved accuracy and robustness of a thermal error compensation system

A novel approach for ANFIS modelling based on Grey system theory for thermal error compensation

The fast and accurate modelling of thermal errors in machining is an important aspect for the implementation of thermal error compensation. This paper presents a novel modelling approach for thermal error compensation on CNC machine tools. The method combines the Adaptive Neuro Fuzzy Inference System (ANFIS) and Grey system theory to predict thermal errors in machining. Instead of following a traditional approach, which utilises original data patterns to construct the ANFIS model, this paper proposes to exploit Accumulation Generation Operation (AGO) to simplify the modelling procedures. AGO, a basis of the Grey system theory, is used to uncover a development tendency so that the features and laws of integration hidden in the chaotic raw data can be sufficiently revealed. AGO properties make it easier for the proposed model to design and predict. According to the simulation results, the proposed model demonstrates stronger prediction power than standard ANFIS model only with minimum number of training samples

Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera

Thermal errors are often quoted as being the largest contributor to CNC machine tool errors, but they can be effectively reduced using error compensation. The performance of a thermal error compensation system depends on the accuracy and robustness of the thermal error model and the quality of the inputs to the model. The location of temperature measurement must provide a representative measurement of the change in temperature that will affect the machine structure. The number of sensors and their locations are not always intuitive and the time required to identify the optimal locations is often prohibitive, resulting in compromise and poor results. In this paper, a new intelligent compensation system for reducing thermal errors of machine tools using data obtained from a thermal imaging camera is introduced. Different groups of key temperature points were identified from thermal images using a novel schema based on a Grey model GM (0, N) and Fuzzy c-means (FCM) clustering method. An Adaptive Neuro-Fuzzy Inference System with Fuzzy c-means clustering (FCM-ANFIS) was employed to design the thermal prediction model. In order to optimise the approach, a parametric study was carried out by changing the number of inputs and number of membership functions to the FCM-ANFIS model, and comparing the relative robustness of the designs. According to the results, the FCM-ANFIS model with four inputs and six membership functions achieves the best performance in terms of the accuracy of its predictive ability. The residual value of the model is smaller than ± 2 μm, which represents a 95% reduction in the thermally-induced error on the machine. Finally, the proposed method is shown to compare favourably against an Artificial Neural Network (ANN) model

Platonic crystal with low-frequency locally resonant snail structures. Wave trapping, transmission amplification and shielding

We propose a new type of platonic crystal. The proposed microstructured plate includes snail resonators with low-frequency resonant vibrations. The particular dynamic effect of the resonators are highlighted by a comparative analysis of dispersion properties of homo- geneous and perforated plates. Analytical and numerical estimates of classes of standing waves are given and the analysis on a macrocell shows the possibility to obtain localization, wave trapping and edge waves. Applications include transmission amplification within two plates separated by a small ligament. Finally we proposed a design procedure to suppress low frequency flexural vibration in an elongated plate implementing a by-pass system re- routing waves within the mechanical system.Comment: 11 figures (20 files

Bridge distress caused by approach embankment settlement

Surtees Bridge, which carries the A66(T) over the River Tees near Thornaby-on-Tees in the UK, has been showing signs of distress that predate its opening in 1981. Subsequent investigations have shown that the bridge distress is related to unexpectedly large settlement of the eastern approach embankment. Recent ground investigations prompted by a proposed widening of the river crossing have produced many new data on the alluvial deposits underlying the site, and explain why embankment settlement was so much larger than originally anticipated. Comparison of the geotechnical parameters obtained from the original and more recent ground investigations suggests that the original investigation significantly underestimated the thickness of an alluvial clay layer underlying the site, and that its coefficient of consolidation was overestimated. Settlement analyses using geotechnical data from the original ground investigations predict moderate embankment settlements occurring principally during construction. Settlement analyses based on all the available data predict far larger embankment settlements occurring over extended time periods. The latter analyses predict an embankment settlement similar to that observed and of sufficient magnitude to cause the observed lateral displacement of the bridge due to lateral loading of its piled foundation

Experimental study of thin part vibration modes in machining

The machining of thin walls generally generates milling chatter, that damage surface roughness and manufacturing tools. Stability lobes which include natural frequencies are successful in case of tool chatter. When milling thin webs models are less adequate, because the interaction with the tool disrupts the behaviour of the work piece. The modal approach generally used for stability charts may be not adequate enough because of neglecting the tool and the work piece contact. This paper presents the experimental phase of a work aiming at analyse vibration modes of a thin web during machining. A finite element calculation shows the influence of a contact on natural frequencies of the part. For a better investigation, field displacements of the work piece are analysed. This work eventually aims at better knowledge of the contact between the tool and the part to improve the hardiness of models

The effect of boundary constraints on finite element modelling of the human pelvis

The use of finite element analysis (FEA) to investigate the biomechanics of anatomical systems critically relies on the specification of physiologically representative boundary conditions. The biomechanics of the pelvis has been the specific focus of a number of FEA studies previously, but it is also a key aspect in other investigations of, for example, the hip joint or new design of hip prostheses. In those studies, the pelvis has been modelled in a number of ways with a variety of boundary conditions, ranging from a model of the whole pelvic girdle including soft tissue attachments to a model of an isolated hemi-pelvis. The current study constructed a series of FEA models of the same human pelvis to investigate the sensitivity of the predicted stress distributions to the type of boundary conditions applied, in particular to represent the sacro-iliac joint and pubic symphysis. Varying the method of modelling the sacro-iliac joint did not produce significant variations in the stress distribution, however changes to the modelling of the pubic symphysis were observed to have a greater effect on the results. Over-constraint of the symphysis prevented the bending of the pelvis about the greater sciatic notch, and underestimated high stresses within the ilium. However, permitting medio-lateral translation to mimic widening of the pelvis addressed this problem. These findings underline the importance of applying the appropriate boundary conditions to FEA models, and provide guidance on suitable methods of constraining the pelvis when, for example, scan data has not captured the full pelvic girdle. The results also suggest a valid method for performing hemi-pelvic modelling of cadaveric or archaeological remains which are either damaged or incomplete

Phylogenetic and phenotypic divergence of an insular radiation of birds

Evolutionary divergence of lineages is one of the key mechanisms underpinning large scale patterns in biogeography and biodiversity. Island systems have been highly influential in shaping theories of evolutionary diversification and here I use the insular Zosteropidae of the south west Pacific to investigate the roles of ecology and biogeography in promoting evolutionary divergence. Initially I build a phylogenetic tree of the study group and use it to reveal the pattern of colonisation and diversification. My results suggest a complex history of dispersal with the observed pattern most likely a result of repeated bouts of colonisation and extinction. I then use the new phylogeny to quantify the diversification rates of the Zosteropidae. I find a very high rate of lineage divergence and suggest the most likely explanation relates to extensive niche availability in the south west Pacific. I also find evidence for an overall slowdown in diversification combined with repeated bursts of accelerated speciation, consistent with a model of taxon cycles. I do not find evidence for sympatric speciation, however. Finally I combine morphological and phylogenetic data to investigate the mode of evolution, evidence for character displacement and influence of biogeography on trait evolution. I find little support for the traditional theory of character displacement in sympatric species. I do, however, find some support for biogeographic theories. Taken together my results do not support traditional theories on the ecological and biogeographical basis of divergence, even in those cases where Zosterops have been used as exemplars. This appears to be because those theories assume rather simple patterns of colonisation and a static ecological system. Instead, my results suggest that evolutionary diversification is dominated by recurrent waves of colonisation and extinction, which, viewed at any particular moment, tend to obscure any underlying ecological rules