عنوان المقالة:Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera 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
الملخص الانجليزي
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
تاريخ النشر
01/04/2015
الناشر
Elsevier
رقم المجلد
رقم العدد
رابط DOI
https://doi.org/10.1016/j.apm.2014.10.016
الكلمات المفتاحية
ANFISThermal error modellingFuzzy c-means clusteringGrey system theory
علي محمد عبد الشاهد | Ali M Abdulshahed | 10368