A Hardware for Processing Magnetic Pressure Sensor Signals from Leak Detection in Waterworks

A Hardware for Processing Magnetic Pressure Sensor Signals from Leak Detection in Waterworks

A. Lay-Ekuakille (Department of Innovation Engineering, University of Salento, Lecce, Italy), G. Griffo (Department of Innovation Engineering, University of Salento, Lecce, Italy), D. Pellicanò (Department of Innovation Engineering, University of Salento, Lecce, Italy), P. Maris (Department of Civil Engineering, Energy, Environment and. Materials (DICEAM), University “Mediterranea” of Reggio Calabria, Reggio Calabria, Italy) and M. Cacciola (Department of Civil Engineering, Energy, Environment and. Materials (DICEAM), University “Mediterranea” of Reggio Calabria, Reggio Calabria, Italy)
Copyright: © 2013 |Pages: 11
DOI: 10.4018/ijmtie.2013070103

Abstract

Leaks in pipelines and waterworks are detected using different methods and among them spectral analysis is one of the most interesting ones. Sources of signals to be processed are different, for example: reflected signals from ground penetrating radar and acoustic sources, signals from dedicated sensors mounted on pipelines, etc… In the latter case, magnetic pressure sensors located on the pipeline acquire vibrations and oscillations of liquids (e.g. water) in the pipeline, following a leak in the pipeline. These vibrations and oscillations are transformed in electrical signal and processed using different methods and techniques like FFT (Fast Fourier Transform), ANN (Artificial Neural Network), STFT (Short-Term Fourier Transform), and Impedance Method (IM). But there are other advanced methodical approaches that can improve the quality of the signal related to the leak; one of them is FDM (Filter Diagonalization Method). Even in presence of an advanced method, recovered signal displays undesired attenuation and noisy behavior due to different reasons, namely, hardware, background noise, materials used for pipeline construction, sensors, etc.. This paper presents a complementary hardware for processing the above signals. The hardware is based on innovating approach that minimizes additional noisy components.
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2. Signal Features And Experimental Architecture

As recalled in the abstract, spectral analysis of signals, from magnetic sensors for the purposes of this experimental research, can be performed using FFT, STFT, and FDM. Since STFT can consider as a direct consequence of FFT, the application of this method is included in (Lay-Ekuakille, et al., 2009) while the impedance method is based on the search of characteristic impedance of the pipe in any instant for locating the leak (Lay-Ekuakille, et al., 2010; Lay-Ekuakille, et al., 2010). Hence the main comparison about magnetic sensor signal featuring is between FFT and FDM. An effective spectral representation allows to obtain information from a spectral function of operator for which eigenvalues and eigenvectors are known:

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