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A methodology based on Principal Component Analysis (PCA) and clustering is evaluated for process monitoring and process analysis of a pilot-scale SBR removing nitrogen and phosphorus. The first step of this method is to build a multi-way PCA (MPCA) model using the historical process data. In the second step, the principal scores and the Q-statistics(More)
A Sequencing Batch Reactor (SBR) is a wastewater process that occurs in a unique basin working with a predefined cycle. The reactor is monitored by the pH, Oxidation Reduction Potential, Dissolved Oxygen and Temperature sensors. This work proposes a qualitative representation of process variables based on episodes for ORP and pH signals to determine the(More)
The data set of batch biological and biotechnological processes can be organized in a three-way data matrix. In this paper the usefulness of different PCA approaches for monitoring is analyzed. Different ways of unfolding and scaling of data have been applied to a pilot-scale SBR data. PCA is used to reduce the dimensionality and to remove the non-linearity(More)
The paper focuses on the development of a classification strategy to identify critic situation in batch process control. Data acquired from a batch execution is reduced by means of multiway principal component analysis in order to be assessed according to the statistical model of the process. Multiple situations have been categorized by a classification(More)
The main idea of this paper is to develop a methodology for process monitoring, fault detection and predictive diagnosis of a WasteWater Treatment Plant (WWTP). To achieve this goal, a combination of Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) is proposed. First, MPCA is used to reduce the multi-dimensional nature of online(More)
—This paper describes the combination of Multi-variate Statistical Process Control (MSPC) and Case-Based Reasoning to situation assessment of a Waste Water Treatment Plant (WWTP). The goal of this work is to evaluate the capabilities of these techniques for assessing the actual state of a WWTP. The research was performed in a pilot WWTP operating with a(More)
Experiences in heterogeneous application domains treated with different data mining approaches are presented in this paper: Case based reasoning and self organising maps have used to diagnose beams and pipes after analysing their responses using wavelet decomposition. Also case based reasoning methodology has been used to improve electronic circuits(More)
This work deals with a previously proposed piezo-diagnostic methodology based on principal component analysis for structural damage detection. Previous works have demonstrated the effectiveness of baseline models to distinguish between structural damage and undamaged conditions, however, its robustness and reproducibility depends on a proper estimation of(More)
OBJECTIVES The objective was the development of a method for the automatic recognition of different types of atypical lymphoid cells. METHODS In the method development, a training set (TS) of 1,500 lymphoid cell images from peripheral blood was used. To segment the images, we used clustering of color components and watershed transformation. In total, 113(More)
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