| 基于支持向量回归机的可靠度预测模型 |
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| 引用本文： | 冯添乐,江永丰. 基于支持向量回归机的可靠度预测模型[J]. 计算机与数字工程, 2011, 39(2): 29-32 |
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| 作者姓名： | 冯添乐 江永丰 |
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| 作者单位： | 1. 军械工程学院,石家庄,050003
2. 75233部队,韶关,512100 |
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| 摘 要： | 设备可靠度预测在设备的维修管理中扮演着重要的角色,有效的设备故障预测对降低设备维修费用、停机时间或运行风险都起到至关重要的作用。文章在分析设备状态数据的基础上,通过引入支持向量回归机,建立了基于退化数据的预测模型,并将该模型用于发动机可靠度的预测。
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| 关 键 词： | 可靠度 预测 健康状态退化 支持向量回归机 |
Prognostics Model of Machinery Reliability Based on SVR |
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| Feng Tianle,Jiang Yongfeng. Prognostics Model of Machinery Reliability Based on SVR[J]. Computer and Digital Engineering, 2011, 39(2): 29-32 |
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| Authors: | Feng Tianle Jiang Yongfeng |
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| Affiliation: | Feng Tianle1) Jiang Yongfeng2)(Ordnance Engineering College1),Shijiazhuang 050003)(No.75233 Troops of PLA2),Shaoguan 512100) |
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| Abstract: | Reliability prognostics plays a serious role in maintenance management of machine,the ability to forecast machinery failure is vital to reducing maintenance cost,operation downtime or operation risk.This paper presents a novel approach for machinery reliability prognostics via incorporating health degradation data of units and Support Vector Regression(SVR).The proposed model was used to forecast the reliability and failure time of the diesel motor. |
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| Keywords: | reliability prognostics health degradation support vector regression |
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