CAJ | 학술논문

结构复杂性、运行环境独特性和诱发故障多源性大大增加了现代设备系统的不确定性,从而导致能够反映设备系统主要特征的数据较少。针对不确定性设备系统贫信息的特点,将新息灰预测方法应用于设备系统运行状态的预测。仿真研究给出了基于新息灰理论的工业实例建模过程和故障预测结果,并与BP神经网络方法的计算结果进行比较,验证了新息灰预测方法的有效性与实用性。
결구복잡성、운행배경독특성화유발고장다원성대대증가료현대설비계통적불학정성,종이도치능구반영설비계통주요특정적수거교소。침대불학정성설비계통빈신식적특점,장신식회예측방법응용우설비계통운행상태적예측。방진연구급출료기우신식회이론적공업실례건모과정화고장예측결과,병여BP신경망락방법적계산결과진행비교,험증료신식회예측방법적유효성여실용성。
Structural complexity,uniqueness of operating environments and multi-source of the failure greatly increase the uncertainties of modern equipment system.These uncertainties further result in the less data,which reflect main dynamic characteristic of system.Innovation Grey Prediction Model(IGPM) can get better model by updating data in time.For poor information of uncertainty equipment systems,IGPM is applied to prediction of equipment operation.The modeling procedure of emulation based on FIGPM is presented...