摘要
This paper presents an embedded sensing system for precisely measuring acceleration and temperature of interest points on a ball screw structure and diagnosis of different ball-screw preloads based on processing acquired signals with further classification using the support vector machine (SVM) method. The sensing system consists of a sensing unit and a hardware signal-processing unit. The core sensors utilize a MEMS-type accelerometer and glass-type SMD PT-100, integrated into a 1 cm×1 cm circuit board and packaged with a metal housing sensing unit with a dimension less than 1.5 cm 3 . The sensing unit is embedded into the screw nut of a designed preload-adjustable ball screw, installed on a computer-controlled single-axis stage for testing. Acquired signals with good noise immunity in an industrial environment are achieved through the developed hardware signal-processing unit. Measured acceleration and temperature data for different ball-screw preload levels based on time and frequency domain analysis are performed. The results demonstrate achieving diagnosis of a ball-screw preload within 20 s, with a preload level classification reaching nearly 100%. The developed sensing system and analysis method can apply to monitor ball-screw health and would be very useful in industrial applications. © 2011 Elsevier Ltd. All rights reserved.