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改进的军用飞机涡轮叶片预测性维修方法
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作者 杜晶 杨玫 张燕红 《舰船电子工程》 2020年第5期125-129,共5页
为了对军用飞机发动机涡轮叶片进行维修性预测,论文首次提出多变量分析与随机森林算法结合的预测方法。首先,利用多变量的方法进行归一化及变量选取,将待预测时刻最近一段时间的预测值与实际值构成融合矩阵,并与增量学习结合进行二次学... 为了对军用飞机发动机涡轮叶片进行维修性预测,论文首次提出多变量分析与随机森林算法结合的预测方法。首先,利用多变量的方法进行归一化及变量选取,将待预测时刻最近一段时间的预测值与实际值构成融合矩阵,并与增量学习结合进行二次学习。然后,通过多变量与维修频率相关性分析,对结果进行排序筛选出特征值;接下来,构建融合矩阵,将训练数据集和测试数据集输入到融合矩阵决策模型中进行预测,得到预测结果。最后,实验结果显示:几种不同方案的平均绝对百分误差(MPEG)均大幅下降。结果表明,论文方法能够有效提高预测精度,对于保障飞行安全、降低叶片损伤和报废率,从而降低维护成本有着重大意义。 展开更多
关键词 维修性预测 多变量分析 随机森林算法 融合矩阵
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Model of the Reliability Prediction of Masonry Walls in Buildings 被引量:1
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作者 Beata Nowogonska 《Journal of Mechanics Engineering and Automation》 2014年第12期975-980,共6页
The suitable repair forecasting is needed for proper maintenance of the buildings. The appropriate maintenance planning should be based on the prognostic analysis of the repair needs. However, in Poland, maintenance p... The suitable repair forecasting is needed for proper maintenance of the buildings. The appropriate maintenance planning should be based on the prognostic analysis of the repair needs. However, in Poland, maintenance planning is currently not seen as a long-term system. Repairs are understood as extemporary work and are carried out exclusively on the basis of intermittent inspections and controls. One of the numerous factors determining maintenance planning is exploitation reliability conditioned by durability. This article presents a proposal to determine the prediction of operational reliability of the building constructed using traditional technology. The method of behaving and changing the reliability of the building throughout its use will be useful in planning renovations. The presented analysis includes apartment buildings erected in a traditional technology and regards them as technical objects. For such approached buildings, it is proposed to apply rules applied for mechanical and electrical objects. The probability of the exploitation of a building without any breakdowns in a given period of time is defined as exploitation reliability. 展开更多
关键词 Exploitation reliability PREDICTION degree of technical wear.
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