KEYWORDS: Signal processing, Interference (communication), Signal to noise ratio, Dynamical systems, Signal analyzers, Control systems, Complex systems, Sensors, Quantitative analysis, Electrical engineering
NC (numerical control) table is a complex dynamic system. The dynamic characteristics caused by backlash, friction and
elastic deformation among each component are so complex that they have become the bottleneck of enhancing the
positioning accuracy, tracking accuracy and dynamic behavior of NC table. This paper collects vibration acceleration
signals from NC table, analyzes the signals with SVD (singular value decomposition) method, acquires the singular
spectrum and calculates the singular entropy of the signals. The signal characteristics and their regulations of NC table
are revealed via the characteristic quantities such as singular spectrum, singular entropy etc. The steep degrees of singular
spectrums can be used to discriminate complex degrees of signals. The results show that the signals in direction of
driving axes are the simplest and the signals in perpendicular direction are the most complex. The singular entropy values
can be used to study the indetermination of signals. The results show that the signals of NC table are not simple signal
nor white noise, the entropy values in direction of driving axe are lower, the entropy values increase along with the
increment of driving speed and the entropy values at the abnormal working conditions such as resonance or creeping etc
decrease obviously.
This article employs SVD (singular value decomposition) method to study dynamic characteristics of NC (numerical control) table. Acceleration signals of the NC table at three directions were tested; the singular spectrum of the signals was acquired with SVD; principal components of the signals were found out; the dynamic characteristics of the signals and its contributing factors were studied through extracting dynamic characteristics of principal components; and quantitative analysis was made on signals and principal components through calculating signal energy. The results indicated that signal characteristics of the previous two principal components are apparent, based on which dynamic characteristics of chaotic signal can be extracted; signal at perpendicular direction of table is greatly correlated with that at the horizontal moving direction, indicating that they are excited from the same vibration source. But signals perpendicular to each other in terms of moving direction at the horizontal level is rarely correlated; total signal energy is maximum at moving direction, minimum at horizontal non-moving direction and in the middle at perpendicular non-moving direction; bending vibration of lead screw at perpendicular direction is far more violent than that at horizontal direction.
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