Affiliation:
1. Institute of Science and Engineering, Kanazawa University, Kakuma-machi, Kanazawa-shi, Ishikawa 920-1192, Japan
2. Takamatsu Machinery Co., Ltd., Hakusan, Japan
Abstract
As a result of the development of network technologies, diagnosis techniques that can collect machine states continuously and prognostic health management (PHM) are available in the factory. PHM technology is also beginning to be implemented in the machine tool field. However, few studies have described causality between feature values, including vibration and acoustic emission data, collected by machine and physical phenomena of failures under the actual use of machine tools. In the present paper, a PHM system of lubrication failure of bearings in CNC lathe spindles is developed. An acceleration sensor is used to collect machine states, and statistical feature parameters that characterize the lubrication failure are extracted from the obtained vibration data. Moreover, in order to clarify the cause-effect relation between the extracted feature parameters and physical phenomena of lubrication failure, several analyses using surface roughness measurement, residual stress measurement, and grease consistency measurement are conducted.
Publisher
Fuji Technology Press Ltd.
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering
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