State-based and self-adapting algorithm for condition monitoring

Condition Monitoring and Maintenance prediction are permanent demands of state-of-the-art machine tools. Their IT-infrastructure including drive control systems and specific sensors deliver extensive amounts of data for monitoring. However to combine and link this data to define critical characteristic values remains challenging. The paper presents a novel approach to deal with these tasks. Firstly equal machine states are detected at different times by checking and comparing several parameters. If an equal state is detected an algorithm is executed which leads to a characteristic value. The value as well as its limits is self-adapting and time-depending by constant redefining based on the machine history. (C) 2017 The Authors. Published by Elsevier B.V.