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

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.