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This paper presents the development and evaluation of an algorithm for the prediction of NOx emissions from a biomass fired combustion process based on flame radical imaging, image processing and soft computing techniques. The investigation was performed on a biomass-gas fired test rig. An algorithm which combines texture analysis and non-negative matrix factorization (NMF) is studied for the image...
The shape of a burner flame is an important characteristic closely linked to the burner configuration, fuel type, and other operational parameters of a combustion process. This paper presents an algorithm to extract the 3-D medial axis of a burner flame and use it as a descriptor for the flame shape characterization. The algorithm is based on the 2-D medial axes of two flame images captured from two...
The quantitative characterization of combustion flames has long been an important but challenging issue both in combustion research and industrial applications. The shape of a flame is recognized as one of most useful characteristics in the adjustment of combustion parameters. Although medial axis is a useful shape representation of a flame, limited work has been reported on how to extract the medial...
It is important to study the interface fluctuations between the two phases in a gas/liquid flow to achieve an in-depth understanding of the mixture flow and subsequent optimization of industrial processes. This paper presents a study of the interface fluctuations between the gas and liquid phases in a pipeline. Experimental data are obtained from a gas/liquid two-phase flow rig through electrical...
In electrical power generation there are many problems that may be solved through the application of image analysis. The presence of non ore gangue materials mixed with coal can have an impact on the combustion efficiency and emissions of power plants. Also known as tailings, often these materials are a hazardous byproduct of mining. Differentiation between coal and gangue is desirable for fuel quality...
This paper presents an approach to the automated inspection of laser spot welding processes using optical sensing and neural network techniques. An optical sensor is used to derive signals covering a spectrum ranging from visible to infrared bands. A set of features extracted from the signals is fed into a neural network to classify the quality of welds. A series of experiments was carried out using...
Time series feature extraction is a way to reveal the most important characteristics of a (or a set of) time series. It is an effective pre-processing step for many time series mining tasks such as clustering and indexing. In this paper, we propose a new qualitative feature extraction method. The method differs from most available methods in that it mainly focuses on the shape, instead of the actual...
This paper presents an approach to the automated inspection of laser spot welding processes using optical sensing and neural network techniques. An optical sensor is used to derive signals covering a spectrum ranging from visible to infrared bands. A set of features extracted from the signals is fed into a neural network to classify the quality of welds. A series of experiments was carried out using...
The emergence of the MPEG-4 standard has facilitated the development of new approaches to very-low bitrate coding, including model-based coding for human faces. As a tool in the synthetic/natural hybrid coding part of the standard, a face object is defined in terms of its shape-consisting of a set of facial feature points and texture. In addition, this face object can be animated by controlling these...
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