The Application of ANN and ANFIS Prediction Models for Thermal Error Compensation on CNC Machine Tools -أريد

نوع النشر: مجلة علمية
المؤلفون بالعربي: Ali M Abdulshahed, Andrew P Longstaff, Simon Fletcher
المؤلفون بالإنجليزي: Ali M Abdulshahed, Andrew P Longstaff, Simon Fletcher
الملخص العربي: 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
تاريخ النشر: 01/02/2015
الناشر: Elsevier
رقم المجلد
رقم العدد
رابط DOI: https://doi.org/10.1016/j.asoc.2014.11.012
الكلمات المفتاحية: CNC machine toolThermal error modellingANFISGrey system theory