灰色理论是一种研究惯性器件退化规律，并对其进行寿命预测的有效方法。为增强新信息价值，用加权模型对非等时距GM(1,1)模型进行了改进；针对离乱数据序列无法给出确切预测值的问题，提出了灰色区间预测的新方法，该方法同时利用数据整体趋势与极值点的信息，克服了仅用极值点来提取边界函数的缺陷。建模前先检验参数序列的光滑比，对满足准光滑条件的参数序列直接采用加权灰色模型建模，否则进行灰色区间预测。实例证明，直接建模时，加权模型使预测精度由2级提升为1级，灰色区间预测时，实际值落在预测区间，其上下边界预测的平均相对误差为4.88%，预测效果得到了显著提高。

Grey theory is an effective method for studying the performance degradation law of inertia device and for predicting its lifetime.To enhannce the value of new information, the non-equal interval GM (1, 1) model is improved with a weighted model.Considering that it is impossible to obtain an exact predictive value to chaotic data sequence, a new method of grey interval prediction is proposed, making use of the whole data trend together with extreme point information, which can overcome the shortage of extracting boundary function by only using the extreme point.Smooth ratio of the parameter sequence is examined firstly before modeling.The parameter sequence meeting the quasi-smooth condition is to be modeled directly with weighted grey model, and otherwise, grey interval prediction is performed.The example shows that:in direct modeling, the weighted model improves the prediction accuracy to level 1 from level 2;in grey interval prediction, the real value lies within the prediction interval, with the average relative error of its upper and lower boundary prediction being 4.88%, and the prediction effect is significantly improved.