Big impacts from pressure transients are known to be major contributors to pipeline failures, and even small impacts have the potential to result in pipeline deterioration. The effects of these impacts on a pipeline are not disclosed in detail and are hard to evaluate completely by theoretical modeling or numerical simulation. The impacts excite cylindrical structures containing liquid, which results in the development of wave propagation along pipelines. In particular, quasi-longitudinal waves are known to be developed by fluid-structure interaction during propagation. However, impact signal detection needs great care because extreme noise may corrupt the signal. An enhanced wavelet-based approach is proposed to detect and localize the impact source. The method makes use of continuous wavelet transform and band summation within a band of interest along scales to enhance time-difference detectability. In addition, a noise reduction algorithm intended to remove burst noises, in practice, frequently contaminates the impact signals of interest. Experimental results from a water supply network under operation demonstrate that the proposed approach is able to suppress noise and successfully reveal the impact location. The proposed approach provides a more precise and robust way to localize impacts missed by the conventional cross-correlation algorithm.

Buried pipelines, such as waterworks pipelines, are critical for transmitting essential resources and energy in modern cities, but the risk of pipeline failure, especially due to third-party interference, is a major concern. While various studies have focused on leak detection in waterworks pipelines, research on preventing impact damage is limited. To address this issue, this study proposes a novel algorithm that utilizes energy and similarity measurements for impact detection and compares it theoretically to existing leak-detection methods. The proposed algorithm utilizes frequency-domain kurtosis to determine the frequency band on which the energy of the impact signals is concentrated, along with a time-shift coherence function to measure the similarity of the signals. The application of the source location using the filtered signals enables accurate detection of the location of third-party interference. The proposed algorithm aims to ensure the safety and to prevent failures of buried pipelines. To verify the feasibility of the proposed algorithm, an excavation experiment using a backhoe was conducted on an in-service waterworks pipeline with a diameter of 2200 mm and a burial depth of 3 m. This experiment confirmed the effectiveness of the proposed algorithm in preventing failures of buried pipelines and demonstrated its practical applicability in the field. The experiment also validated the algorithm’s ability to detect third-party interference damage at various points.

Ultrasonic phased array imaging has been a promising method to visualize internal defects of structures. In addition, it has been developed in order to improve the spatial resolution of images to show the defects in detail. A cross-spectral method is known to be an imaging platform that successfully provides various opportunities of image enhancement. Moreover, the method is a post-processing algorithm; therefore, it can be perfectly available to a conventional phased array imaging system. De-convolution, in particular, was introduced to improve resolution by employing spatial impulse response, called point spread function or array pattern. The mathematical formulation of de-convolution is delineated to effectively apply it to phased array images, and some algorithms are compared to find the most proper algorithm for non-destructive phased array imaging among them. In addition, computer simulations show how the proposed method is effective to enhance the spatial resolution.

Crack growth is regarded as an important monitoring parameter for structural degradation. To precisely estimate crack size, therefore, has been highly demanded to monitor structural healthiness and to assess residual life of various structures from small components to huge plants. Conventional non-destructive inspections have been successfully detected cracks, but some deficiencies for accuracy still remain. Nonlinear sub-harmonic generation was well proved to detect closed cracks that could cause underestimation of crack size. Moreover, sub-harmonic phased array (PA) imaging was proposed to visualize where the closed cracks are. The sub-harmonic PA images, however, has lower spatial resolution than the fundamental frequency PA images due to its longer wavelength, which often prevents from clearly observing closed cracks. Many of signal processing techniques have been developed to improve spatial resolution of images for more than half a century, and some resolution enhancing techniques such as deconvolutions and an eigen-analysis based technique are employed to make the resolution of sub-harmonic imaging better. Point spread function issues for deconvolution have been also investigated theoretically and experimentally. In addition, some experiments with CT specimens have been done to prove closed-crack localization by improving spatial resolution of sub-harmonic imaging.