Engine On-line Detection Data Fusion Technology Based on Fractional Differential

Abstract

Aiming at the technical problem that the engine on-line monitoring system under the Internet of Things is difficult to obtain accurate detection data, this paper proposes a new idea of using fractional integral operator fusion to process engine online detection data under the Internet of things. After discussing the application characteristics of fractional order differential operator in signal fusion, then establish a fusion algorithm model of engine detection data based on fractional order differential operator, through the application of 0.5-order differential operator in the data fusion experiment of engine oil temperature on-line detection, realized the remote and high precision measurement of engine detection information, verifed the superiority of fractional order differential operator in the application of multisensor detection data fusion processing. The research results have important application value for improving the reliability of on-line monitoring system under multi-sensor and enhance the scientific policy making.