【摘要】：研究了結合貝葉斯網絡的動態(tài)因果推理鏈故障診斷模型。已有基于推理鏈的電網故障診斷方法存在推理子鏈個數較多、構造較復雜、未考慮保護和斷路器缺失、錯誤等不足,針對每個疑似故障元件根據保護邏輯建立原始的動態(tài)推理鏈,對誤報、漏報的報警信息進行糾正,形成改進后的動態(tài)推理鏈。對推理鏈中各保護和斷路器動作的可信度進行評估,將各保護和斷路器動作信息從二值邏輯的0或1模糊化為0,1之間的可信度值。針對每個疑似故障元件的推理鏈,建立相應的貝葉斯網絡模型,通過貝葉斯反向推理得到元件的故障概率。典型電網的多個故障案例驗證了所提方法的有效性。
[Abstract]:The fault diagnosis model of dynamic causal reasoning chain combined with Bayesian network is studied. The existing fault diagnosis methods based on inference chain have many disadvantages, such as the number of subchains of reasoning is more, the structure is more complicated, the protection and circuit breaker are missing, the fault is wrong and so on. For each suspected fault element, the original dynamic inference chain is established according to the protection logic, and the false positive and false alarm information is corrected to form the improved dynamic inference chain. The reliability of each protection and circuit breaker operation in the chain of reasoning is evaluated, and the operation information of each protection and circuit breaker is blurred from 0 or 1 of binary logic to the reliability value between 0 and 1. According to the inference chain of each suspected fault element, the corresponding Bayesian network model is established, and the fault probability of the component is obtained by Bayesian reverse inference. The effectiveness of the proposed method is verified by a number of fault cases in a typical power grid.
【作者單位】： 西南交通大學電氣工程學院;
【基金】：國家自然科學基金項目(51377137)~~
【分類號】：TM732

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相關碩士學位論文 前2條

1 張楠;基于推理鏈的電力系統(tǒng)故障診斷方法研究[D];上海交通大學;2015年

2 韓迎春;基于灰色關聯(lián)度分析和改進推理鏈的電網故障診斷[D];西南交通大學;2016年

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本文編號：2207067