Leak detection using structure-borne noise

A method for detection and location of air leaks in a pressure vessel, such as a spacecraft, includes sensing structure-borne ultrasound waveforms associated with turbulence caused by a leak from a plurality of sensors and cross correlating the waveforms to determine existence and location of the leak. Different configurations of sensors and corresponding methods can be used. An apparatus for performing the methods is also provided

NASA Tech Briefs Index, 1977, volume 2, numbers 1-4

Announcements of new technology derived from the research and development activities of NASA are presented. Abstracts, and indexes for subject, personal author, originating center, and Tech Brief number are presented for 1977

Monitoring of long steel pipes using acoustic emission

This thesis relates to the condition monitoring of long steel pipes using acoustic emission (AE). A number of experiments were carried out on pipes with a range of internal and external environments using a linear axial array of sensors with the ultimate aim of locating and reconstituting the time-domain and frequency-domain signatures of AE sources. The AE waves were generated from simulated, discontinuous, continuous, and semi-continuous sources and from real sources generated by impacts and crack propagation. The simulated source work in different internal and external environments was carried out to develop a generic empirical approach to AE propagation in long steel pipes which acknowledges the distortion of a source disturbance in the time and frequency domains. Generally, the acquired signals have two identifiable components and methods are developed for separating these components automatically and determining their group velocities. A simple model for attenuation is also developed which includes effects brought about by burial of the pipe and /or the nature of the fluid transported (liquid or gas). In the impact and crack extension tests a variety of intensities were simulated and the effect of type and intensity on time- and frequency-domain characteristics of the source was determined. The overall outcome is the demonstration of the potential of AE for identifying the nature, intensity and location of damaging events, such as crack growth and denting, and for the location and intensity assessment of leaks

Risk analysis and reliability of the GERDA Experiment extraction and ventilation plant at Gran Sasso mountain underground laboratory of Italian National Institute for Nuclear Physics

The aim of this study is the risk analysis evaluation about argon release from the GERDA experiment in the Gran Sasso underground National Laboratories (LNGS) of the Italian National Institute for Nuclear Physics (INFN). The GERDA apparatus, located in Hall A of the LNGS, is a facility with germanium detectors located in a wide tank filled with about 70 m3 of cold liquefied argon. This cryo-tank sits in another water-filled tank (700 m3) at atmospheric pressure. In such cryogenic processes, the main cause of an accidental scenario is lacking insulation of the cryo-tank. A preliminary HazOp analysis has been carried out on the whole system. The risk assessment identified two possible top-events: explosion due to a Rapid Phase Transition - RPT and argon runaway evaporation. Risk analysis highlighted a higher probability of occurrence of the latter top event. To avoid emission in Hall A, the HazOp, Fault Tree and Event tree analyses of the cryogenic gas extraction and ventilation plant have been made. The failures related to the ventilation system are the main cause responsible for the occurrence. To improve the system reliability some corrective actions were proposed: the use of UPS and the upgrade of damper opening devices. Furthermore, the Human Reliability Analysis identified some operating and management improvements: action procedure optimization, alert warnings and staff training. The proposed model integrates the existing analysis techniques by applying the results to an atypical work environment and there are useful suggestions for improving the system reliability

Leak detection of shock absorber tubes with acoustic emission

This thesis is aimed to study the feasibility of using Acoustic Emission (AE) for leak detection after the welding of tubes for shock absorbers, in order to replace the current bubble technique employed in the production. These tubes were pressurized and subsequently analyzed using the Vallen Visual AE system AMSY4. The trials that were carried out with AE in air showed a low reliability due to the high background noise that hides the sound of the leak. Therefore a variable threshold level and some filtering techniques were used to avoid this situation. Thanks to the energy, amplitude, hits, RMS and frequency graphs' information, the trials carried out in water in a lab environment provided results that were a bit better than those done before in air. However for the trials carried out in water and in a production environment did not provide a great reliability. _______________________________________________________________________________________________________________________________El objetivo de este Proyecto Fin de Carrera es estudiar la fiabilidad del uso de las Emisiones Acústicas (EA) en la detección de fugas en los tubos de amortiguadores tras su soldadura, para reemplazar la actual técnica de burbujas utilizada en producción. Estos tubos fueron presurizados y posteriormente analizados con el sistema de EA Vallen Visual AMSY4. Los ensayos que fueron llevados a cabo en aire con EA mostraron una baja fiabilidad debido al elevado ruido ambiental, que ocultaba el sonido de la fuga tratada. Para evitar esta situación, fue utilizado un nivel umbral variable de frecuencias y diversas técnicas de filtrado. Gracias a la energía, la amplitud, los golpes, el RMS y la información de las gráficas de frecuencia, los ensayos realizados en agua en un ambiente de laboratorio, proporcionaron unos porcentajes de fiabilidad superiores a los obtenidos anteriormente en aire. Sin embargo, los ensayos llevados a cabo en agua en un ambiente de producción no fueron lo suficientemente fiables, debido a la imposibilidad de distinguir entre las fugas y el ruido ambiental.Ingeniería Industria

Leak Detection and Localization in Pressurized Space Structures Using Bayesian Inference: Theory and Practice

Impact from micrometeoroids and orbital debris (MMOD) can cause severe damage to space vehicles. The crew habitat can begin to leak precious oxygen, critical systems can be punctured causing fatal failures, and an accumulation of impacts by MMOD can decrease the lifetime of any and all devices in space. Due to these and other potential dangers, MMODs have been considered the third largest threat to spacecraft after launch and re-entry. Many satellites and other spacecraft face this very problem inherent in all space travel on a daily basis, but often times they can be repaired. A major hurdle is to first be able to identify the presence of a leak. Many times an impact and subsequent leak is not discovered until it has caused a problem. A complete system is needed to detect and localize the impact to improve longevity of the habitat or other pressurized space structures. In this work, a system for detection and localization of air leaks using air-borne acoustic waves is proposed. The system uses microelectromechanical systems (MEMS) microphone sensors to detect and record high frequency noise in an environment, angle of arrival (AOA) calculations to estimate possible leak locations, and a Bayesian tree-search filter to detect and more accurately localize a leak. This work includes proof of concept, simulations, and physical prototypes as steps to creation of a complete system. Data from deployed flight test using said prototypes are analyzed. Modeling the effects of environmental reflections on the accuracy of localization is also studied

Localization of CO2_2 gas leakages through acoustic emission multi-sensor fusion based on wavelet-RBFN modeling

CO$_2$ leakage from transmission pipelines in carbon capture and storage systems may seriously endanger the ecological environment and human health. Therefore, there is a pressing need of an accurate and reliable leak localization method for CO$_2$ pipelines. In this study, a novel method based on the combination of a wavelet packet algorithm and a radial basis function network (RBFN) is proposed to realize the leak location. Multiple acoustic emission (AE) sensors are first deployed to collect leakage signals of CO$_2$ pipelines. The characteristics of the leakage signals from the AE sensors under different pressures are then analyzed in both time and frequency domains. Further, leakage signals are decomposed into three layers using wavelet decomposition theory. Wavelet packet energy and maximum value, and time difference calculated by cross-correlation are selected as the input feature vectors of the RBFN. Experiments were carried out on a laboratory-scale test rig to verify the validity and correctness of the proposed method. Leakage signals at different positions under different pressures were obtained on the CO$_2$ pipeline leakage test bench. Compared with the time difference of arrival method, the relative error obtained using the proposed method is less than 2%, which has certain engineering application prospects