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基于模糊控制和大數據算法模型的電力運維故障診斷設備方法
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上海樂(lè )研電氣有限公司

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TP391

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Design of power operation and maintenance fault diagnosis scheme based on improved big data algorithm model
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    摘要:

    針對現有技術(shù)中對電力運維故障檢測靈敏度低、診斷誤差大等問(wèn)題,設計了一種新型故障診斷方案。該方案將PID模糊控制計算器與大數據算法模型相結合,并采用實(shí)時(shí)布線(xiàn)的方法減少診斷面積,基于改進(jìn)型大數據算法模型提取電力運維設備故障數據特征,對電力運維設備運行工況構建診斷網(wǎng)絡(luò ),通過(guò)分析電力運維設備工況的功能系統完成數據診斷。為了減少診斷誤差,該研究設計了一種故障診斷設備,采用集成芯片化設計和算法程序,減小體積的同時(shí)保證檢測結果的準確性。實(shí)驗結果表明,該研究方法故障診斷誤差小,準確率最高達到98.6%。

    Abstract:

    Aiming at the problems of low sensitivity and large diagnosis error in power operation and maintenance fault detection in the existing technology, a new fault diagnosis scheme is designed. In this scheme, the PID fuzzy control calculator is combined with the big data algorithm model, and the real-time wiring method is used to reduce the diagnosis area. Based on the improved big data algorithm model, the fault data characteristics of power operation and maintenance equipment are extracted, the diagnosis network is constructed for the operating conditions of power operation and maintenance equipment, and the data diagnosis is completed by analyzing the functional system of the operating conditions of power operation and maintenance equipment. In order to reduce the diagnosis error, a fault diagnosis equipment is designed in this study. The integrated chip design and algorithm program are adopted to reduce the volume and ensure the accuracy of the detection results at the same time. The experimental results show that the fault diagnosis error of this research method is small, and the highest accuracy is 98.6%.

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金海勇,吳其樂(lè ),劉騰澤,張莉.基于模糊控制和大數據算法模型的電力運維故障診斷設備方法計算機測量與控制[J].,2022,30(11):71-76.

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  • 收稿日期:2022-05-20
  • 最后修改日期:2022-07-21
  • 錄用日期:2022-07-21
  • 在線(xiàn)發(fā)布日期: 2022-11-17
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