Service life prediction method of high-speed numerical control milling machine cutter on basis of state space model

Abstract

The invention provides a service life prediction method of a vertical machining center milling cutter updated by Bayesian information on the basis of a state space model. According to the structural features of the vertical machining center milling cutter, a degeneration signal of the vertical machining center milling cutter is collected, and the obtained signal is processed to obtain a degeneration information characteristic quantity; and according to the obtained degeneration information characteristic quantity of the vertical machining center milling cutter, the state space model used for predicting the service life of the vertical machining center milling cutter is established. On the basis of a Bayesian theory under probability statistics, an established service life prediction model of the milling cutter is subjected to information alternation by sequential Monte-Carlo simulation, above parameters are estimated in real time, and the service life predication method is established. A residual life probability density distribution function of the vertical machining center milling cutter is output according to a failure threshold of the milling cutter to obtain a residual life prediction value. The service life prediction method has the beneficial effects that the work reliability of the cutter is improved through the on-line prediction of the residual life of the cutter, sudden accidents are reduced, and heavy losses and casualties are avoided.

Description

technical field [0001] The invention belongs to the field of operation reliability and life prediction of mechanical products, and specifically relates to a method based on real-time monitoring state-oriented high-speed CNC milling machine tool using a state space model to realize remaining life prediction, guiding state maintenance, prediction and health management, etc. Background technique [0002] The prediction in engineering is to reduce the risk caused by the sudden failure of equipment. Traditionally, predictions are usually judged based on people's experience. However, due to the increasing development of science and technology, the manufacturing process is developing towards high parameters and larger device scales, and the production process is trending towards large-scale, automated, high-parameter operation, and high energy storage. The reliability requirements of mechanical products are getting higher and higher, and there is an urgent need for advanced life pr...

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Problems solved by technology

In fact, its degradation process cannot be directly observed, and can only be expressed indirectly by using the characteristic indicators shown in the degradation process

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