CAJ | 학술논문

如今的工业过程系统结构复杂设备精密度高，随之而来的就是系统的高故障性，所以如何准确地检测到故障的发生已经成为一大难题。该文基于提高故障诊断性能的目的，提出一种DPCA-ICA的故障诊断方法。这种方法先采用DPCA对数据进行降维和去噪处理，得到能最大反映系统信息的低维数据，然后再通过ICA方法提取独立元，进行故障诊断。仿真结果表明，改进后的ICA故障诊断方法不仅具有比传统PCA方法更低的故障误报率，并且对一些PCA难以检测的故障也有很好的诊断效果。
여금적공업과정계통결구복잡설비정밀도고，수지이래적취시계통적고고장성，소이여하준학지검측도고장적발생이경성위일대난제。해문기우제고고장진단성능적목적，제출일충DPCA-ICA적고장진단방법。저충방법선채용DPCA대수거진행강유화거조처리，득도능최대반영계통신식적저유수거，연후재통과ICA방법제취독립원，진행고장진단。방진결과표명，개진후적ICA고장진단방법불부구유비전통PCA방법경저적고장오보솔，병차대일사PCA난이검측적고장야유흔호적진단효과。
Nowadays , The structure of industrial process system is complex and the equipment is pre-cise .So the possibility of fault is high .How to detect the fault exactly has become a major problem . Based on the purpose of improving the performance of fault diagnosis , we propose a DPCA-ICA method. The method first use DPCA for data dimensionality reduction and de-noising processing to obtain the infor-mation which is largest low-dimensional and can reflect the system's feature to a large extent , then we ex-tract independent element through ICA , and use it for diagnosis .Simulation results show that the im-proved ICA method has a lower failure rate of false positives than the traditional PCA method , and have a good effect on detecting the complex fault .