scholarly journals Monitoring of the Operational Conditions in Steel Pipes Using Fiber Optic Sensors

2021 ◽  
Keyword(s):  
Measured Signal ◽  
Leakage Detection ◽  
Operational Conditions ◽  
Steel Pipes ◽  
Inverse Effect ◽  
Temporal Aspects ◽  
Reliable Monitoring ◽  
Measured Strain ◽  
Maintenance And Inspection ◽  
Detection And Localization

Abstract. Oil and water transport pipeline systems are susceptible to damage due to harsh environmental conditions and operational factors, hence ongoing maintenance and inspection are required. The development of a continuous and reliable monitoring technique will ensure the safety usage of these structures and assist in the extension of their life span. In this study, the monitoring and assessment of pipelines are performed using a network of Fiber Bragg Grating (FBG) sensors mounted along the longitudinal and circumferential directions. The sensitivity of the measurements to assess pressure and flow variation in the pipe, in addition to leakage detection and localization were evaluated. Water at a controlled pressure and flowrate was pumped into the designed six-meter pipe testbed designed for this purpose. Leakage was simulated by opening one of the four designated valves installed on the pipe. The variation in the pressure inside the pipe highly impacted the amplitude of the measured strain increasing it significantly reaching 20%. An increase in flowrate had an inverse effect, it resulted in a 5% decrease in the amplitude of the measured strain drop. The change of hole leakage size greatly influenced the measured signal, resulting in a 55% change in amplitude between a 2 cm2 and a 5 cm2 hole leakage. For the location of leakage, only the temporal aspects of the signal were affected resulting in a slight shift in the response time of sensors relative to each other. The results were promising to monitor the structural conditions related to leakage detection and localization, based on the patterns observed.

scholarly journals Leakage detection and localization in water distribution systems: A model invalidation approach

2021 ◽  
Vol 110 ◽  
pp. 104755
Author(s):  
Stelios G. Vrachimis ◽  
Stelios Timotheou ◽  
Demetrios G. Eliades ◽  
Marios M. Polycarpou
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Leakage Detection ◽  
Detection And Localization ◽  
Model Invalidation

Multiple Leakage Detection and Localization Method Based on Bayesian Theory and Genetic Algorithm

2014 ◽  
Vol 635-637 ◽  
pp. 924-927
Author(s):  
Tao Jin ◽  
Ze Yuan Zhou
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Bayesian Theory ◽  
Leakage Detection ◽  
Localization Method ◽  
Simulation Results ◽  
Detection And Localization ◽  
Leakage Location

To detect and locate the leakage of the pipe correctly, genetic algorithm is combined with Bayesian theory to determine the leaked pipes. Leakage detection and leakage location are carried out separately. Leakage detection is conducted based on the assumption that there is only one leaked pipe, and the simulation result demonstrates its feasibility. When the leakage detection demonstrates there is leaked pipe in the water distribution system, leakage location starts. Based on the information gathered by the manometers, leakage probability in different combinations of the virtual nodal demand can be fixed according to calculating the pressure of the monitored node, then GA is applied to search the maximum Bayesian value, the pipes with maximum Bayesian leakage possibility are believed to be leaked pipes. Optimization programme was made with combination of Matlab and Epanet, numerical simulation results demonstrate the feasibility and effectiveness of the proposed method.

scholarly journals Detection and Localization of Terrestrial L Band RFI with GNSS Receivers

2021 ◽  
Author(s):  
Max Roberts ◽  
Thomas K. Meehan ◽  
Paul R. Straus ◽  
Jeffery Y. Tien ◽  
Bonnie L. Valant-Weiss ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Precise Orbit Determination ◽  
Detection Algorithm ◽  
Measured Signal ◽  
Regional Conflicts ◽  
Wide Range ◽  
Initial Work ◽  
Gnss Receivers ◽  
Highly Sensitive Detection ◽  
Detection And Localization

GNSS signals are critically important for a wide range of commercial, military, and science applications. Recent studies have identified threats to the performance of GNSS from both intended and unintended sources of radio frequency interference (RFI). Understanding the distribution of the sources of RFI and the nature of the signals they are emitting is critical to determine and mitigate their effects on the measurements made by GNSS receivers. Terrestrial RFI can be substantially detrimental to the received GNSS signals, affecting the interpretation of related science measurements. NASA's Blackjack/TriG GNSS receivers are used for precise-orbit determination and radio occultation measurements, providing a data record spanning most of the Earth’s surface for nearly 20 years. We have developed a highly sensitive detection algorithm which uses variations in the measured signal to noise ratio (SNR), on the order of 10-50 seconds, common to all satellites to identify times and locations subject to RFI. Initial work has focused primarily on detection of the presence of RFI and using the receiver’s orbital solution to record the location of detection events. Our inter-mission analysis creates a unique record of global RFI with the potential for a) rigorous detection of the presence of interfering signals during science measurements, b) geolocation of RFI sources, and c) characterization of the nature of the transmitted signal to better identify intent. Preliminary analysis has shown the presence of RFI is well correlated with regional conflicts and other geopolitical activity.

scholarly journals Water leakage detection and localization using hydraulic modeling and classification

2021 ◽  
Author(s):  
Eliyas Girma Mohammed ◽  
Ethiopia Bisrat Zeleke ◽  
Surafel Lemma Abebe
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Hybrid Approach ◽  
Leak Detection ◽  
Hydraulic Modeling ◽  
Hydraulic Model ◽  
Leakage Detection ◽  
Minimum Night Flow ◽  
Two Phases ◽  
Detection And Localization

Abstract A significant percentage of treated water is lost due to leakage in water distribution systems. The state-of-the-art leak detection and localization schemes use a hybrid approach of hydraulic modeling and data-driven techniques. Most of these works, however, focus on single leakage detection and localization. In this research, we propose to use combined pressure and flow residual data to detect and localize multiple leaks. The proposed approach has two phases: detection and localization. The detection phase uses the combination of pressure and flow residuals to build a hydraulic model and classification algorithm to identify leaks. The localization phase analyzes the pattern of isolated leak residuals to localize multiple leaks. To evaluate the performance of the proposed approach, we conducted experiments using Hanoi Water Network benchmark and a dataset produced based on LeakDB benchmark's dataset preparation procedure. The result for a well-calibrated hydraulic model shows that leak detection is 100% accurate while localization is 90% accurate, thereby outperforming minimum night flow and raw- and residual-based methods in localizing leaks. The proposed approach performed relatively well with the introduction of demand and noise uncertainty. The proposed localization approach is also able to locate two to four leaks that existed simultaneously.

scholarly journals Influence and Compensation of Temperature Effects for Damage Detection and Localization in Aerospace Composites

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4153
Author(s):  
Guillermo Azuara ◽  
Eduardo Barrera
Keyword(s):  
Guided Waves ◽  
Lamb Waves ◽  
Impact Damage ◽  
Reconstruction Algorithm ◽  
Fiber Reinforced Polymers ◽  
Carbon Fiber Reinforced Polymers ◽  
Reinforced Polymers ◽  
Operational Conditions ◽  
Detection And Localization ◽  
Non Destructive

Structural Health Monitoring (SHM) of Carbon Fiber Reinforced Polymers (CFRP) has become, recently, in a promising methodology for the field of Non-Destructive Inspection (NDI), specially based on Ultrasonic Guided Waves (UGW), particularly Lamb waves using Piezoelectric Transducers (PZT). However, the Environmental and Operational Conditions (EOC) perform an important role on the physical characteristics of the waves, mainly the temperature. Some of these effects are phase shifting, amplitude changes and time of flight (ToF) variations. In this paper, a compensation method for evaluating and compensating the effects of the temperature is carried out, performing a data-driven methodology to calculate the features from a dataset of typical temperature values obtained from a thermoset matrix pristine plate, with a transducer network attached. In addition, the methodology is tested on the same sample after an impact damage is carried out on it, using RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) and its geometrical variant (RAPID-G) to calculate the location of the damage.

scholarly journals GP-ARX-Based Structural Damage Detection and Localization under Varying Environmental Conditions

2020 ◽  
Vol 9 (3) ◽  
pp. 41 ◽  
Author(s):  
Konstantinos Tatsis ◽  
Vasilis Dertimanis ◽  
Yaowen Ou ◽  
Eleni Chatzi
Keyword(s):  
Damage Detection ◽  
Time Scale ◽  
Structural Damage ◽  
Gaussian Process Regression ◽  
Parametric Models ◽  
Arx Model ◽  
Single Input Single Output ◽  
Operational Conditions ◽  
Long Time ◽  
Detection And Localization

The representation of structural dynamics in the absence of physics-based models, is often accomplished through the identification of parametric models, such as the autoregressive with exogenous inputs, e.g. ARX models. When the structure is amenable to environmental variations, parameter-varying extensions of the original ARX model can be implemented, allowing for tracking of the operational variability. Yet, the latter occurs in sufficiently longer time-scales (days, weeks, months), as compared to system dynamics. For inferring a “global”, long time-scale varying ARX model, data from a full operational cycle has to typically become available. In addition, when the sensor network comprises multiple nodes, the identification of long time-scale varying, vector ARX models grow in complexity. We address these issues by proposing a distributed framework for structural identification, damage detection and localization. Its main features are: (i) the individual estimation of local, single-input-single-output ARX models at every operational point; (ii) the long time-scale representation of each individual ARX coefficient via a Gaussian process regression, which captures dependency on varying Environmental and Operational Conditions (EOCs); (iii) the establishment of a distributed residual generation algorithm for damage detection, which produces time-series of well-defined stationary statistics, with detected discrepancies used for damage diagnosis; and, (iv) exploitation of ARX-inferred mode shape curvatures, obtained via ARX-inferred global state-space models, of the healthy and damaged states, for damage localization. The method is assessed via application on two numerical case studies of different complexity, with the results confirming its efficacy for diagnostics under varying EOCs.

Flight Tests Performed by EMBRAER with SHM Systems

2013 ◽  
Vol 558 ◽  
pp. 305-313 ◽  
Author(s):  
Ricardo Pinheiro Rulli ◽  
Fernando Dotta ◽  
Paulo Anchieta da Silva
Keyword(s):  
Continuous Monitoring ◽  
Structural Integrity ◽  
Lamb Waves ◽  
Flight Tests ◽  
Operational Conditions ◽  
Periodic Monitoring ◽  
Structural Parts ◽  
Inspection Tasks ◽  
Maintenance And Inspection ◽  
Periodic Inspections

This paper presents an overview of a set of tests performed by Embraer with two different SHM technologies in an E-Jets flight tests aircraft. Considered as promising technologies for monitoring structural parts, sensors networks including cables and connectors of CVM (Comparative Vacuum Monitoring) and LW (Lamb Waves) were installed in an Embraer-190 aircraft. The two technologies have been investigated by Embraer within the companys effort on Structural Health Monitoring. Scheduled maintenance and inspection activities can take advantage of the SHM technologies by evaluating the structural integrity of an aircraft with on-board sensors and performing less time-consuming procedures compared to current NDT technologies which can not only reduce the amount of time and burden of those activities, but also minimize the effects of human-factors when compared to current inspection tasks. The tests performed with CVM and LW components (sensors, connectors and cables) installed in a flight tests aircraft focus on the investigation of the technologies capabilities of withstanding the real aircraft operational conditions. Periodic monitoring of these on-board sensors has been performed using CVM and LW ground equipments. A further phase of this project is currently under development and focus on the demonstration of an on-board in-flight version of the CVM instrumentation system for continuous monitoring of aircraft structures during flight, aiming to demonstrate the ability of the CVM on-board equipment to withstand the aircraft in-flight environmental and operational conditions. Preliminary results on both partially and totally on-board equipments indicate that they can withstand the environmental and operational conditions; however, further tests need to be performed. Performing periodic inspections on ground with SHM systems lead to different qualification requirements when compared to those required for a complete on-board system that performs continuous monitoring. An overview of those two aspects of qualification requirements will also be presented.

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