Detection of leakages in pipelines is a matter of continuous research because of the basic importance for a waterworks system is finding the point of the pipeline where a leak is located and − in some cases − a nature of the leak. There are specific difficulties in finding leaks by using spectral analysis techniques like FFT (Fast Fourier Transform), STFT (Short Term Fourier Transform), etc. These difficulties arise especially in complicated pipeline configurations, e.g. a zigzag one. This research focuses on the results of a new algorithm based on FFT and comparing them with a developed STFT technique. Even if other techniques are used, they are costly and difficult to be managed. Moreover, a constraint in the leak detection is the pipeline diameter because it influences accuracy of the adopted algorithm. FFT and STFT are not fully adequate for complex configurations dealt with in this paper, since they produce ill-posed problems with an increasing uncertainty. Therefore, an improved Tikhonov technique has been implemented to reinforce FFT and STFT for complex configurations of pipelines. Hence, the proposed algorithm overcomes the aforementioned difficulties due to applying a linear algebraic approach.
Beamforming is an advanced signal processing technique used in sensor arrays for directional signal transmission or reception. The paper deals with a system based on an ultrasound transmitter and an array of receivers, to determine the distance to an obstacle by measuring the time of flight and – using the phase beamforming technique to process the output signals of receivers for finding the direction from which the reflected signal is received – locates the obstacle. The embedded beam-former interacts with a PID-based line follower robot to improve performance of the line follower navigation algorithm by detecting and avoiding obstacles. The PID (proportional-integral-derivative) algorithm is also typically used to control industrial processes. It calculates the difference between a measured value and a desired set of points, then attempts to minimize the error by adjusting the output. The overall navigation system combines a PID-based trajectory follower with a spatial-temporal filter (beamformer) that uses the output of an array of sensors to extract signals received from an obstacle in a particular direction in order to guide an autonomous vehicle or a robot along a safe path.