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在航空发动机的测试中通常使用多传感器组进行测量,刻画它们之间的关系并利用其发现和修正错误是本研究的目的。以协整和向量误差修正理论为基础,提出了一种用于描述同质传感器测试序列相互关系的模型,对该模型用测试数据序列进行了检验,并进一步设计出了传感器之间相互仿真和故障纠正的算法。通过某新型发动机的实际测试数据,表明上述模型能够用多个传感器的数据拟合仿真出某一传感器的输出,再由仿真值和实际值的比较可以判断出此传感器可能的故障。本方法能够以较少的输入数据,拟合出较好的模型参数,并进而达到较好的预测和发现异常的效果。本模型方法可以用于在发动机模拟试验平台中,实时监测并纠正错误。
In the testing of aeroengine, it is usually the purpose of this study to use multisensor groups to measure, characterize the relationships between them and use them to detect and correct errors. Based on the theory of cointegration and vector error correction, a model for describing the mutual relationship between homogeneous sensor test sequences is proposed. The model is tested with the test data sequence and further designed to simulate the interaction between sensors Fault correction algorithm. The actual test data of a new type of engine shows that the above model can simulate the output of a sensor with the data fitting of multiple sensors, and then the possible fault of the sensor can be judged by comparing the simulated value with the actual value. The method can fit better model parameters with less input data, and then achieve better prediction and find abnormal results. The model approach can be used to monitor and correct errors in real time in an engine simulation test platform.