航天发射场供气系统健康管理技术

针对新一代航天发射场采用全新的在线供气模式,难以有效评估单样本设备健康状态的问题,提出一种基于隐马尔可夫的设备健康状态管理与预测方法。首先,利用设备监测数据构建隐马尔可夫健康状态评估模型,通过对不同观测序列与不同观测次数下的预测准确率进行仿真,确定出最优的模型参数;其次,把实时数据代入模型,根据模型的计算结果取最小值,从而判断出设备的健康状态;最后,将当前数据与历史数据进行拟合,预测出系统的安全可靠寿命。经实际检验,该方法有效解决了单样本多状态设备的健康评估。

Study on Prognosis and Health Management of the Space Launch Site Gas System

In order to solve the problem of the health status of single sample equipment, a new method of health management and forecasting based on hidden Markov is proposed. The method uses the equipment monitoring data to construct the hidden data. The Markovian health assessment model is used to simulate the prediction accuracy of different observation sequences and different observation times to determine the optimal model parameters. Then, the real-time data is substituted into the model, and the results are calculated from the model to determine the health of the equipment. Finally, the current data and historical data are fitted to predict the safe and reliable life of the system. The method can effectively solve the health assessment of single-sample multi-state equipment.