| 引用本文: | 付旭云,钟诗胜,张慕楠.一种改进的航空发动机剩余寿命预测方法[J].哈尔滨工业大学学报,2013,45(5):51.DOI:10.11918/j.issn.0367-6234.2013.05.010 |
| FU Xuyun,ZHONG Shisheng,ZHANG Munan.An improved method for aeroengine residual life prediction[J].Journal of Harbin Institute of Technology,2013,45(5):51.DOI:10.11918/j.issn.0367-6234.2013.05.010 |
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| 摘要: |
| 针对传统的发动机剩余寿命预测方法因为假定机队中所有发动机有相同的性能衰退模式,导致预测精度不高的问题,在分析发动机排气温度裕度数据的基础上,提出基于性能衰退模式的发动机剩余寿命预测方法．对发动机排气温度裕度粗大误差的处理进行了研究,定义了排气温度裕度时序数据的距离,给出了性能衰退模式挖掘步骤,采用CFM56-5B发动机的排气温度裕度时序数据对提出的方法进行了验证．结果表明,提出的方法与基于机队EGTM平均衰退率的预测方法相比,平均相对误差减少了2.5%。基于性能衰退模式的发动机剩余寿命预测方法可以为发动机拆发期限预测和维修计划制定提供可靠的支持． |
| 关键词: 航空发动机 剩余寿命 排气温度裕度；性能衰退 聚类 |
| DOI：10.11918/j.issn.0367-6234.2013.05.010 |
| 分类号: |
| 基金项目:国家高技术研究发展计划资助项目(2012AA040911)； 民航局科技计划项目(MHRD201122)； 哈尔滨工业大学(威海)校科学研究基金资助项目(HIT(WH)X201107). |
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| An improved method for aeroengine residual life prediction |
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FU Xuyun1, ZHONG Shisheng1, ZHANG Munan2
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(1.Department of Mechanical Engineering, Harbin Institute of Technology at Weihai, 264209 Shandong, Weihai, China;2.Air China Technics, Air China, Beijing 101312, China)
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| Abstract: |
| The traditional aeroengine residual life prediction method assumes that all aeroengines have the same performance deterioration pattern in a fleet, which leads to a low prediction accuracy. On the basis that the aeroengine exhaust gas temperature margin (EGTM) is analyzed, the aeroengine residual life prediction method based on performance deterioration pattern is proposed. The gross error removal of aeroengine EGTM time series data is studied. The distance measure of aeroengine EGTM time series data is defined, and performance deterioration pattern mining steps are given. Finally, the CFM56-5B aeroengine EGTM time series data is adopted to verify the proposed method. The results show that the average absolute relative error of the proposed method is reduced by 2.5％ compared to the method of average EGTM deterioration pattern in a fleet. Thus, the aeroengine residual life prediction method based on performance deterioration pattern can supply reliable support for predicting aeroengine removal deadline and making maintenance plan. |
| Key words: aeroengine residual life exhaust gas temperature margin performance deterioration clustering
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