System and method for estimating remaining useful life

摘要

Mechanisms for predicting a remaining useful life of a cutter head of a milling machine that includes a plurality of flutes are disclosed. Features are extracted from reference data associated with a plurality of reference cutter heads. The reference data includes reference vibration data and reference wear data. At least two Neural Network predictive models are trained in parallel for predicting the remaining life of a new cutter head based upon the extracted features. Operational data associated with the new cutter head is obtained. The operational data includes operational vibration data and operational wear data. Features extracted from the operational data are input into an optimal predictive model of the at least two Neural Network predictive models. A remaining useful life of the new cutter head is estimated by the optimal predictive model.

主权项

1. A method to predict a remaining useful life of a milling machine cutter head comprising a plurality of flutes, the method comprising the steps of:
extracting features from reference data from a plurality of reference cutter heads, the reference data including reference vibration data that quantifies vibrations of the plurality of reference cutter heads in three dimensions in operation and reference wear data that quantifies a wearing of the flutes of the plurality of reference cutter heads after each of a plurality of respective cuts by the plurality of reference cutter heads; training at least two Neural Network predictive models in parallel for predicting the remaining useful life of a target cutter head based upon the extracted features from the reference data; evaluating the at least two Neural Network predictive models and selecting an optimal predictive model; obtaining operational data associated with the target cutter head comprising a plurality of flutes, the operational data including operational vibration data that quantifies vibrations of the target cutter head in three dimensions in operation and operational wear data that quantifies a wearing of the plurality of flutes after each of a plurality of cuts by the target cutter head; inputting features extracted from the operational data into the optimal predictive model; and estimating, by the optimal predictive model, the remaining useful life of the target cutter head.