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针对飞机服役历程中复杂多变的使用环境和飞行任务,为了准确快速地获得其实际使用情况,提出了合成关联滤波算法。对于各实测数据任务段,建立对应的关联滤波器;并基于滤波结果和贝叶斯网络设计实现了一种飞机任务段推理决策方法。经实测数据验证表明,建立的任务段关联滤波器能够较好地识别出各飞行参数响应,采用任务段推理决策方法对测试样本的类别属性进行推断,结果的准确率达97.2%;可为飞机等大型机械结构的复杂使用情况监控提供新的技术途径,也可为其损伤/寿命监控提供必要的数据支持。
Aiming at the complicated and changeable operating environment and flight mission in the course of aircraft service, in order to obtain its actual usage accurately and quickly, a synthetic correlation filtering algorithm is proposed. For each measured data task segment, a corresponding correlation filter is established. Based on the filtering results and Bayesian network design, a decision method of aircraft task segment reasoning is implemented. The experimental data show that the established task segment correlation filter can better identify the flight parameters of the response, the use of task segment reasoning decision method to infer the category attributes of the test sample, the accuracy of the results of 97.2%; for the aircraft Such as large-scale mechanical structure of the complex monitoring of the use of new ways to provide technology, but also for its damage / life monitoring to provide the necessary data support.