ON-LINE PROCESS MONITORING USING A ROBUST STATISTICS BASED METHODOLOGY
نویسندگان
چکیده
منابع مشابه
On-line Process Monitoring based on Wavelet-ICA Methodology
In this paper, a new process monitoring methodology is presented to detect fault occurrence. The proposed methodology incorporates a wavelet de-noising approach based on the fast wavelet transform (FWT) to extract the embodied fault dynamics from the noisy measured data. A level dependent soft thresholding technique using Daubechies 3 with three levels of decomposition is utilized. An appropria...
متن کاملThe outlier process: unifying line processes and robust statistics
This paper unifies “line-process” approaches for regularization with discontinuities and robust estimation techniques. We generalize the notion of a “line process” to that of an analog “outlier process” and show that a problem formulated in terms of outlier processes can be viewed an terms of robust statistics. We also characterize a class of robust statistical problems for which an equivalent ...
متن کاملA robust wavelet based profile monitoring and change point detection using S-estimator and clustering
Some quality characteristics are well defined when treated as response variables and are related to some independent variables. This relationship is called a profile. Parametric models, such as linear models, may be used to model profiles. However, in practical applications due to the complexity of many processes it is not usually possible to model a process using parametric models.In these cas...
متن کاملA Comprehensive Evaluation of Statistics Pattern Analysis Based Process Monitoring
Statistics pattern analysis (SPA) is a new multivariate statistical monitoring framework proposed by the authors recently. It addresses some challenges that cannot be readily addressed by the commonly used multivariate statistical methods such as principal component analysis (PCA) in monitoring batch processes in the semiconductor industry. It was later extended to the monitoring of continuous ...
متن کاملBiological Nitrogen Removal Process Monitoring Based on Fuzzy Robust PCA
In this study the Fuzzy Robust Principal Component Analysis (FRPCA) method is used to monitor a biological nitrogen removal process, performances of this method are then compared with classical principal component analysis. The obtained results demonstrate the performances superiority of this robust extension compared with the conventional one. In this method fuzzy variant of PCA uses fuzzy mem...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Latin American Applied Research - An international journal
سال: 2019
ISSN: 1851-8796,0327-0793
DOI: 10.52292/j.laar.2019.47