High accuracy detection technique for information data under the influence of multiple factors based on fractional partial differential equations

Abstract

In engineering practice, several factors affect the various types of information during the collection process. For example, information data measurement errors are caused by equipment performance and the working environment. During the transmission of detection information, signal distortion caused by energy loss and signal interference causes unpredictable detection errors in collected data. Through the study of fractional calculus theory, it was found that it is suitable for studying nonlinear, noncausal, and nonstationary signals, and has the dual functions of improving detection information and enhancing signal strength. Therefore, under the influence of many factors, we applied the fractional difference algorithm to the field of information-data processing. A multisensor detection data fusion algorithm based on the fractional partial differential equation was adopted to establish online detection data. A multi-sensor detection data fusion algorithm based on a fractional partial differential equation was established, which effectively fuses the information data detection errors caused by various influencing factors and significantly improves the detection accuracy of information data. The effectiveness of this method was experimentally demonstrated by its application.