Satellite-borne equipment health prediction method based on data self-adaption

Abstract

The invention provides a satellite-borne equipment health prediction method based on data self-adaption, which aims at solving the problems of realizing trend prediction of parameters and calculation of performance degradation conditions by utilizing long-term monitoring data of satellite-borne equipment, and comprises the following steps of: selecting historical parameter data of the satellite-borne equipment in a specified time period; carrying out outlier elimination, null value filling and data sampling on the historical parameter data; performing data point-to-point comparison on the sampled data to obtain a comparison value sequence corresponding to the sampling sequence; analyzing the period of the comparison value sequence, and after the comparison value sequence of the data is obtained, decomposing the comparison value sequence into a periodic component, a trend component and a random component according to a time sequence decomposition method; and performing long-term trend prediction on the periodic component, the trend component and the random component by using corresponding prediction methods, adjusting parameter values in various prediction methods according to the period of the data, and after the prediction results of the three types of data are added, comparing the prediction data with the original data to realize the attenuation performance of the equipment parameters.

Description

technical field [0001] The invention relates to the field of satellite comprehensive testing and on-orbit management, and relates to a data self-adaptive-based on-board equipment health prediction method. Background technique [0002] The health status of onboard electronic equipment plays a very important role in the normal operation of satellites. Combined with the long-term acquisition of equipment data, operation managers, equipment experts and designers can accurately find abnormal operation conditions, analyze abnormal causes, and improve equipment design, thereby improving the overall operation and management design level of the satellite. During the working period of on-board electronic equipment, its performance change is an important basis for reflecting whether the current operating state of the equipment is normal or not, and the length of the future life of the equipment. The health prediction method based on the historical data of the equipment mainly uses the...

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Problems solved by technology

In the current long-term data forecasting, there are forecasting methods based on data, physical models and combined models, such as parameter regression analysis methods, data forecasting methods based on power theory models, etc., these methods can achieve data in some aspects. Trend prediction, but it does not combine the characteristics of the long-term prediction process of the actual working environment of the satellite, so it cannot make full use of the characteristics of the data to improve the long-term prediction effect of the data, while the prediction method based on the physical model has relatively high requirements for the system model. This method is powerless when the physical model cannot be obtained

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