2021IOP Conference Series Earth and Environmental ScienceOpen access

Research on Speed Control of Permanent Magnet Synchronous Motor for Air Compressor Based on UDE

Xiuxi Huang, Hanming Guo, Jialin Zhang, Rujiang Li, Yao Lu, Peihao Yang

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Abstract

Abstract This paper firstly establishes a four-dimensional index system for distribution network operation reliability. Using principal component analysis method, it extracts the main evaluation indicators from a large amount of data, and analyzes the influencing factors of the indicators according to the main evaluation indicators. According to the parallel association rules. The method establishes the relevant model, and extracts the main indicators of operational reliability and the strong correlation rules between each influencing factors, so as to obtain the main influencing factors. The artificial neural network is proposed to predict, based on historical data and real-time data. The main influencing factors are used as the input and output of the forecast, and the output is expressed by the main evaluation index, and the operational reliability index for a period of time is judged. The calculation of the proposed strategy can quickly and effectively predict the operational reliability of the distribution network.

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What this paper is about

Abstract This paper firstly establishes a four-dimensional index system for distribution network operation reliability. Using principal component analysis method, it extracts the main evaluation indicators from a large amount of data, and analyzes the influencing factors of the indicators according to the main evaluation indicators. According to the parallel association rules. The method establishes the relevant model, and extracts the main indicators of operational reliability and the strong correlation rules between each influencing factors, so as to obtain the main influencing factors. The artificial neural network is proposed to predict, based on historical data and real-time data. The main influencing factors are used as the input and output of the forecast, and the output is expressed by the main evaluation index, and the operational reliability index for a period of time is judged. The calculation of the proposed strategy can quickly and effectively predict the operational reliability of the distribution network.

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Available abstract

Abstract This paper firstly establishes a four-dimensional index system for distribution network operation reliability. Using principal component analysis method, it extracts the main evaluation indicators from a large amount of data, and analyzes the influencing factors of the indicators according to the main evaluation indicators. According to the parallel association rules. The method establishes the relevant model, and extracts the main indicators of operational reliability and the strong correlation rules between each influencing factors, so as to obtain the main influencing factors. The artificial neural network is proposed to predict, based on historical data and real-time data. The main influencing factors are used as the input and output of the forecast, and the output is expressed by the main evaluation index, and the operational reliability index for a period of time is judged. The calculation of the proposed strategy can quickly and effectively predict the operational reliability of the distribution network.

Key concepts: Reliability (semiconductor), Computer science, Principal component analysis, Index (typography), Control (management), Reliability engineering, Artificial neural network, Engineering

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