Online reconstruction of surface topography along the entire cutting path in peripheral milling

Abstract This paper presents a novel method for online reconstruction of 3D surface topography in peripheral milling. Compared with the traditional surface topography modeling only focusing on local features as well as losing the time and location information, the presented method can accurately depict not only the variation of dynamic characteristics and the topography features within the local scope, but also along the entire cutting path. Meanwhile, the actual machining time and workpiece location information are introduced in surface topography modeling by using sensor information. The multi-sensor information, including cutting force signals and the eddy current sensor information in multiple directions, is employed to model dynamic factors, namely the vibration relating to deflection of cutting tool and the machining system characteristics, respectively. Two parts of work are carried out on modeling the vibration relating to deflection along the entire cutting path. First, a method based on the Kolmogorov-Smirnov test is applied to the real-time force signals, where the force signals between the entrance and exit points of the cutting teeth along the entire cutting path can be automatically extracted. Second, combining with an axial weight distribution model of the instantaneous cutting thickness, the extracted force signals can be transformed into the required force factors and correspondingly nonlinearly distributed along the instantaneous cutting depth. A piecewise cubic Hermite algorithm is then introduced to create the discrete values of the dynamic factors as continuous models without losing original precision. The continuous models are successfully coupled into ideal cutting edge trajectory equation to form a surface topography model. Further, a numerical algorithm with the characteristics of self-searching function is performed to solve the surface topography model, any point on the workpiece surface can be precisely reconstructed and thus formed the reconstructed surface topography. Eventually, cutting experiments were conducted to validate the effectiveness of the proposed method by comparing the measured and reconstructed results. A good agreement on all the quantitative and qualitative indicators is found. The results demonstrate that the proposed method can accurately realize an online reconstruction of the surface topography along the entire cutting path, and is also an appropriate monitoring approach for a number of features on surface topography (e.g., surface roughness, form deviation).