Abstract—This paper presents a comprehensive ANN based multisensor fusion approach designed to support the implementation of an adaptive error compensation of geometric, thermal and dynamic errors for enhancing the accuracy of CNC machine tools. Accurate and efficient model to perform on-line error prediction is an essential part of the compensation process. The proposed approach consists of the following major steps: (i) design of an integrated spatial-variant model describing the machine topology, (ii) measurement of path-dependent rigid-body errors according to the model, (iii) design of time-variant models for error components through sensors fusion, (iv) continuous monitoring of the machine conditions using position, force, speed and temperature sensors for one-line error components prediction and integration to produce a correction vector, (v) total positioning error synthesis and software compensation. Implemented on a turning center, the proposed approach led to a consistent model able to accurately and reliably provide an appropriate error identification and compensation under variable machine tool conditions. 

Index Terms—machining, machine tools, machine tool accuracy, error compensation, sensor fusion, neural network

Cite: Abderrazak El Ouafi and Noureddine Barka, "A Multisensor Approach for Error Compensation in CNC Machine Tools," Journal of Automation and Control Engineering, Vol.1, No.3, pp. 232-239, Sep. 2013. doi: 10.12720/joace.1.3.232-239