惯性器件长期贮存性能可靠性灰色马氏链预测

为了及时掌握武器系统惯性器件的性能，并为延长其使用寿命及维修提供依据，对其进行贮存可靠性评估和预测非常必要．讨论了一种灰色马氏链预测模型的建模方法，此方法兼具灰色模型和马氏链模型的优点，它不仅充分利用了灰色模型动态建模思想，来预报可靠性数据总体趋势，并且根据此总体趋势，进行状态的划分，从而大大克服了马氏链状态矩阵运算量大的缺点，而且拓宽了灰色模型的应用范围，使其适合于波动性较大的随机数据列的预测．最后，对某型导弹速率陀螺仪贮存性能可靠性进行估计，并进行灰色马氏链预测．

Grey Markov Chain Based Reliability Forecasting Approach for Inertial Device in Long-Term Storage

Inertial devices in weapon system are generally in no-working states of storage, maintenance and measurement. The storage reliability is as important as the working reliability. In order to know the characteristics of weapon's inertial device and to provide the information for prolonging its using period and maintenance, it is necessary to estimate and predict the storage performance reliability. A modeling approach for grey Markov chain prediction was discussed. The proposed method possesses the advantages of grey model and Markov chain model. It makes good use of dynamic modeling idea of grey model to predict the general trend of original reliability data. Then according to the trend, the states are divided so that it can overcome the disadvantage of large volume calculation of state transition probability matrix in Markov chain. Moreover, the presented approach expands the applied scope of grey model and makes it fit for forecasting of random data with bigger fluctuation. Finally, the storage performance reliability of the rate gyroscope for some missile was estimated and forecasted using the hybrid grey Markov chain.