Method and device for predicting the condition of a component or system, computer program product

Abstract

The present invention relates to a device and a method for trend prediction of the course of a time-dependent series of data points of a component or system, in particular of a component or system for an aircraft or spacecraft, comprising the steps: providing an optimised decision tree, the input node of which is provided for inputting an input vector, the nodes of which contain the data points of a respective input vector and the leaves of which each contain an extrapolation function; iteratively calculating future data points by a respective time-dependent series of data points being inputted into the decision tree as an input vector and the decision tree calculating therefrom a data point subsequent to the last data point of the input vector in an automated manner, the calculated subsequent data point being added to the time-dependent series of data points in order to be used as a new input vector for the next iteration step. The present invention further relates to a computer program product.

Description

technical field [0001] The present invention relates to a computer-implemented method and apparatus for trending the process of measuring a time-correlated series of data points determined at a component or system to predict the condition of a component or system, in particular for an aircraft or aircraft. The invention also relates to a computer program product. Background technique [0002] Analysis of data pools determined by measurements has wide-ranging applications. This analysis includes a statistical analysis of the interrelationships of the data with respect to the data, and an analysis of the future development of these data, that is to say, known as trend forecasting. For trend forecasting, a trend model is usually established based on traditional time series analysis methods. Trend analysis and trend forecasting are statistical tools that allow better interpretation of measured or otherwise determined data. Trend analysis can be used for trend prediction to en...

AI Technical Summary

Problems solved by technology

However, after a certain period of time, the filters used can become clogged, the corresponding supply lines can become dirty and, for example, the fan can fail, for example due to a motor failure or due to a broken fan blade

Here, it is problematic that the clogging of the filters is especially unpredictable as it always depends on the surrounding environment and the application of the respective filter

This causes these filters to be checked frequently in the field, and these also include additional check time in the fixed time period of the aircraft

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