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首页> 外文会议>Symposium on Novel Optoelectronic Detection Technology and Application;Society of Photo-Optical Instrumentation Engineers;Chinese Society of Optical Engineering;Science and Technology on Low-Light-Level Night Vision Laboratory >Reliability analysis method of aerospace equipment system based on big data
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Reliability analysis method of aerospace equipment system based on big data

机译：基于大数据的航空航天装备系统可靠性分析方法

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摘要

Aerospace equipment is developing in the direction of high speed, accuracy, stability and long life. However, thereliability and life expectancy of some equipment systems are still far from the world advanced level. The main reason isthat the data volume is not complete enough, and the data format is single. In order to ensure the healthy operation ofthese equipment systems, it is necessary to use a large amount of data to diagnose and predict faults. Therefore, theresearch from simple data collection to the whole process analysis of big data is of great significance for equipment lifeassessment and reliability analysis. Based on the analysis of big data, this paper proposes a processing method forequipment fault diagnosis and prediction, which is carried out from the aspects of aerospace big data characteristics, dataacquisition, data storage, algorithm model and prediction, from complex equipment operation. The fault information isdiscovered and analyzed to ensure the stable and safe operation of the entire system. Finally, we use the cloud serviceplatform method to simulate the life of the equipment. Compared with the traditional method, the long-term memorynetwork model has been added to predict the full life cycle of the equipment by more than 10%.
机译：航空航天设备正在朝着高速，准确，稳定和长寿命的方向发展。但是，那 一些设备系统的可靠性和预期寿命仍远未达到世界先进水平。主要原因是 数据量不够完整，并且数据格式单一。为了保证健康运行 这些设备系统中，有必要使用大量数据来诊断和预测故障。因此， 从简单数据收集到大数据全过程分析的研究对设备寿命具有重要意义 评估和可靠性分析。在对大数据进行分析的基础上，提出了一种处理数据的方法。 设备故障诊断与预测，从航空大数据特征，数据 复杂设备操作中的数据采集，数据存储，算法模型和预测。故障信息为 发现和分析，以确保整个系统的稳定和安全运行。最后，我们使用云服务 平台方法来模拟设备的使用寿命。与传统方法相比，长期记忆 已添加网络模型以预测设备的整个生命周期超过10％。

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