Broadband Excitation of Machine Tools by Cutting Forces for Performing Operational Modal Analysis

Abstract

The article is aimed at verifying the state of a real workplace using virtual reality. In analyzing the readiness of virtual reality applications, augmented reality was selected for the following work. The most significant advantage of augmented reality is the implementation of a virtual model and the ability to deal with the analysis in a real environment, which is particularly beneficial in the case of production plants. In the first phase of the work, an analysis of the current state of the workplace was carried out, where the requirements for the design of the new workplace were specified. This was followed by the phase of design preparation in 3D modeller. At this very stage it appeared to be advantageous to use virtual reality applications; in the design process, regular approval procedures are required as for an expert team (management, design, quality, ...), which puts high qualification requirements on the readiness of this team. In this phase, the 3D design of the new workplace was inserted into the application supported by augmented reality and some options were indicated to deal with the ergonomic and risk analysis. The result of this work is, in particular, an extension of options in designing and analyzing production workplaces and machinery in multidisciplinary teams.

Position Dependent FRF Identification without Force Measurement in Milling Process

“…Merging Eq. ( 16), (18) for machine-tool dynamics and Eq. ( 8) for force calculation including dynamic chip thickness.…”

“…al. [18] applied the same principle without a specially designed workpiece and has shown that same white noise requirements can be satisfied without a special workpiece. The author also presents methods to select process parameters to achieve excitation with various frequency content.…”

“…al. [18] also utilize motor current along with encoder readings and apply modelling of feed drive system to obtain force estimation. Load side disturbance observer (LSDO) relies on multiple encoder measurements and tool tip models.…”

Concept for Predicting Vibrations in Machine Tools Using Machine Learning

“…[7] EMA is a costly process requiring specialised equipment and machine downtime, therefore it is not usually performed on every machine. Recent research has focused on identifying machine properties during operation [8][9][10]. These approaches aim to use cutting forces to replace the external excitation, however they still require targeted experimentation and thus a loss of production time.…”