Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

Abstract

The operation status of manufacturing equipment is directly related to the reliability of the operation of manufacturing equipment and the continuity of operation of the production system. Based on the analysis of the operation status of manufacturing equipment and its characteristics, it is proposed that the concept of assessing the operation status of manufacturing equipment can be realized by applying real-time acquisition of accurate inspection data of important parts of weak motion units and comparing them with their motion status evaluation criteria. Through the study of the application characteristics of fractional-order calculus theory, a differential data fusion model based on the fractional-order differential operator is established. The advantages of Internet of Things (IoT）technology and fractional order differential fusion algorithm are integrated to obtain real-time high-precision data of the operating parameters of manufacturing equipment, and the research objective of operating condition assessment of manufacturing equipment is realized. The feasibility and effectiveness of the method are verified by the application of the method in machining center operation status assessment.

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

“…Therefore, an ideal high-precision detection method for information under the joint action of multiple influencing factors has not been developed. To solve these problems, our team has been using the method of fractional calculus theory in data processing for many years [20][21][22][23][24][25][26] and found that fractional differential operators are suitable for studying nonlinear, non-causal, and non-stationary signals and have dual functions of improving detection information and enhancing signal strength. Therefore, by fusing the differences between the information and data, the information and data detection errors caused by various influencing factors can be eliminated.…”