In leak noise correlation surveys, time delay estimation (TDE) is of great importance in pinpointing a suspected leak. Conventional TDE methods involve pre-filtering processes prior to performing cross-correlation, based on a priori knowledge of the leak and background noise spectra, to achieve the desired performance. Despite advances in recent decades, they have not proven to be capable of tracking changes in sensor signals as yet. This paper presents an adaptive phase transform method based on least mean square (LMS) algorithms for the determination of the leak location to overcome this limitation. Simulation results on plastic water pipes show that, compared to the conventional LMS method, the proposed adaptive method is more robust to a low signal-to-noise ratio. To further verify the effectiveness of the proposed adaptive method, an analysis is carried out on field tests of real networks. Moreover, it has been shown that by using the actual measured data, improved performance of the proposed method for pipeline leakage detection is achieved. Hence, this paper presents a promising method, which has the advantages of simple implementation and ability to track changes in practice, as an alternative technique to the existing correlation-based leak detection methods.

Acoustic waves induced by leakage attenuate as they propagate in the piping system. Difficulties are generally encountered in leak localization in plastic pipes since these waves are heavily attenuated than in metallic pipes. This study presents a leak localization method based on the variable step normalized least mean square (VS-LMS) adaptive filter. In the method, the optimal weight vector of the filter is determined for time delay estimation (TDE) without requirement of the prior knowledge of statistical characteristics of leak and noise signals. It has a desirable feature of sharpening the main peak of TDE curve through adaptive iterative learning process, thus improving the accuracy of TDE for leak localization. By adjusting the update mode of iteration step, the convergence speed of the VS-LMS algorithm can be greatly improved. A simulation model of leak wave propagation is established and is subsequently analyzed for leak localization with respects to the TDE accuracy. Experimental work is further carried out on a plastic pipe to verify the effectiveness of the proposed method. The simulation sand experimental results demonstrate that the proposed method outperforms the original LMS and basic cross-correlation methods for the leak localization in a water-filled plastic pipe.

When ${\mathrm{CO}}_2$ leakage occurs from a high pressure enclosure, the ${\mathrm{CO}}_2$ jet formed can produce fierce turbulent flow generating acoustic emission with possible phase change, depending on the pressure of the enclosure, and a significant temperature drop in the region close to the releasing point. Acoustic Emission (AE) and infrared imaging technologiesare promising methods for on-line monitoring of such accidental leakage. In this paper, leakage experiments were carried out with a ${\mathrm{CO}}_2$ container under well controlled conditions in a laboratory. Acoustic signals and temperature distribution at the leakage area were acquired using an acoustic sensor and an infraredthermalimaging camera. The acoustic signal was analyzed in both time and frequency domains. The characteristics of the signal frequencies areidentified, and their suitability for leakage detectionis investigated. The location of the leakage can be identified by seeking the lowest temperature area or point in the infrared image.