Multi-damage detection with embedded ultrasonic structural radar algorithm using piezoelectric wafer active sensors through advanced signal processing

2005 ◽  
Author(s):  
Lingyu Yu ◽  
Victor Giurgiutiu
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Active Sensors ◽  
Piezoelectric Wafer Active Sensors ◽  
Piezoelectric Wafer

Advanced Signal Processing Techniques for Multi-Damage Detection With an Improved Embedded Ultrasonic Structural Radar Algorithm and Piezoelectric Wafer Active Sensors

2004 ◽  
Author(s):  
Lingyu Yu ◽  
Victor Giurgiutiu
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Large Area ◽  
Active Sensors ◽  
Piezoelectric Wafer Active Sensors ◽  
Active Sensor ◽  
Piezoelectric Wafer ◽  
Processing Techniques ◽  
User Friendly ◽  
Signal Processing Techniques

The embedded ultrasonic structural radar (EUSR) algorithm was developed by using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. EUSR was verified to be effective for detecting a single crack either at a broadside or at an offside position. However, the damage location was not very precise. This algorithm is improved by using advanced signal processing techniques. The improvement includes: 1) EUSR is able to provide better image of the specimen under monitoring; 2) it is able to detect multiple defects such as several cracks; 3) it is also able to identify different damage types. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then the application of using Hilbert transform for extracting the envelopes of the wave packages is discussed. This can eliminate or reduce the effect of side robes so that EUSR produces better images. The improvement of EUSR detectability is concluded through the comparison to the previous results, followed by the experiments to verify the multi-damage detection of EUSR. Finally, we present the results of how EUSR can distinguish different types of damage. This system is implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for an even more powerful EUSR for structural health monitoring and embedded nondestructive evaluation.

scholarly journals In-Situ Multi-Mode Sensing With Embedded Piezoelectric Wafer Active Sensors for Critical Pipeline Health Monitoring

2007 ◽  
Author(s):  
Lingyu Yu ◽  
Victor Giurgiutiu ◽  
Yuh Chao ◽  
Patrick Pollock
Keyword(s):  
Damage Detection ◽  
Time Data ◽  
Active Sensors ◽  
Flowing Fluid ◽  
Electromechanical Impedance ◽  
Corrosion Detection ◽  
Piezoelectric Wafer Active Sensors ◽  
Pipeline Systems ◽  
Piezoelectric Wafer

Pipelines are important infrastructures in petroleum and gas industries which are vital to the national economy. They are typically subjected to corrosion inside of the pipe and there is an urgent need for the development of a cost-effective, non-excavating, in-service, permanent critical pipeline damage detection and prediction system. In this paper, we proposed an in-situ multiple mode pipeline monitoring system by utilizing permanently installed piezoelectric wafer active sensors (PWAS). As an active sensing device, PWAS can be bonded to the structure or inserted into a composite structure, operated in propagating wave mode or electromechanical impedance mode. The small size and low cost (about ∼$10 each) make it a potential and unique technology for in-situ application. Additionally, PWAS transducers can operate at a temperature as high as 260°C which is sufficient for most critical pipeline systems used in gas/petroleum industry. This system can be used during in-service period, recording and monitoring the changes, such as cracks, impedance, wall thickness, etc., of the pipelines over time. Having the real-time data available, maintenance strategies based on these data can then be developed to ensure a safe and less expensive operation of the pipeline systems. The paper will first give an intensive literature review of current pipeline corrosion detection. Then, the basic principles of applying PWAS to in-situ SHM using in-plane propagation waves and impedance measurement for damage detection are studied and developed. Next, experiments were conducted to verify the corrosion detection and thickness measurement ability of PWAS sensor network in a laboratory setting and in water pipe with flowing fluid inside as well. In addition, the potential of PWAS application for high temperature pipeline thickness monitoring was also investigated.

scholarly journals Influence of Sensor Statistics on Piezoelectric and Magneto-Elastic Damage Detection

2012 ◽  
Author(s):  
David Conrad ◽  
Andrei Zagrai ◽  
Daniel Meisner
Keyword(s):  
Damage Detection ◽  
Mechanical Impedance ◽  
Active Sensors ◽  
Structural Dynamic ◽  
Detection Scheme ◽  
Piezoelectric Wafer Active Sensors ◽  
Impedance Response ◽  
Piezoelectric Wafer ◽  
Pulse Echo ◽  
The Impact

Increasing complexity of aerospace structures facilitates a growing need for structural health monitoring (SHM) systems capable of real-time active damage detection. A variety of sensing approaches have been demonstrated using embedded ultrasonic sensors such as piezoelectric wafer active sensors (PWAS) and magneto-elastic active sensors (MEAS). Common methodologies consider wave propagation (pitch-catch or pulse-echo) and standing wave (vibration or impedance) techniques with damage detection capabilities dependent upon structural geometry, material characteristics, distance to damage and damage size/orientation. While recent studies have employed damage detection and classification approaches that are dependent on cumulative statistics, this study explores the contribution of sensor parameters and experimental setup variability on the damage detection scheme. The impact of variability in PWAS and MEAS are considered on sensor use in ultrasonic and magneto-mechanical impedance damage detection. In order to isolate sensor parameters, measurements were conducted with PWAS in free-free boundary conditions. Variability of PWAS parameters was evaluated by measuring the sensors impedance response. An analytical model of PWAS was used to estimate sensor parameters and to determine their variability. Additionally, experiments using MEAS were performed that demonstrate variation of magneto-mechanical impedance during structural dynamic tests. From these experiments the importance of sensor setup is discussed and its contribution into the overall detection scheme is explored.

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