scholarly journals Use of damping identification technique for damage detection

2018 ◽  
Vol 148 ◽  
pp. 14004
Author(s):  
Vikas Arora
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Natural Frequencies ◽  
Monitoring Methods ◽  
Structural Health ◽  
Damping Matrix ◽  
Step Procedure ◽  
Damage Structure ◽  
Identification Technique

Stiffness-based structural health monitoring methods are widely used for detecting the damage in a structure. These stiffness-based structural health monitoring methods uses change in natural frequencies and modeshapes for damage detection. These methods are based on identifying the change in stiffness of the healthy and damage structure to predict the damage in the structure. These stiffness-based methods are not efficient for detecting a small damage in a structure as there is a negligible change in natural frequencies and modeshapes due to a small damage in a structure, however the damping characteristics of the structure are highly sensitive to the damage in a structure. In this paper, new damping-based damage detection procedure has been proposed. In the proposed procedure, the changes in damping matrix of the structure has been used to detect the damage in the structure. The proposed procedure is able (or can) to detect both the location of the damage and the extend of the damage in the structure. The proposed procedure of damping-based damage detection is a 2-step procedure. In the first step, damping matrices of both the healthy and damage structure are identified and in the second step, the identified damping matrices are used for damage detection. Numerical and experimental case studies are presented to demonstrate the effectiveness of the proposed procedure. The results have shown that the proposed damping-based damage detection procedure can be used for detecting damage in a structure with confidence.

A Structural Health Monitoring System for Composite Beams With Coupled Bending-Torsion

2012 ◽  
Author(s):  
Zeaid Hasan ◽  
Ghassan Atmeh
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Natural Frequency ◽  
Health Monitoring ◽  
Composite Beam ◽  
Natural Frequencies ◽  
Mode Shapes ◽  
Current Time ◽  
Structural Health ◽  
Area Of Interest

Structural health monitoring (SHM) is the process of damage identification in structural systems which have been an area of interest and a well-recognized field of technology in the past decade. Such systems involve the integration of smart materials, sensors and decision-making algorithms into the structure to detect damage, evaluate the structural integrity and predict the remaining life time. These systems have the potential to replace traditional non-destructive evaluation (NDE) of structures. This study focuses on presenting an automated structural health monitoring (SHM) system based on detecting shifts in natural frequencies of the structure. The damage detection technique is implemented on a cracked composite beam vibrating in coupled bending-torsion where the crack is assumed open. Modal analysis is conducted on the composite beam in order to predict the natural frequency and the associated mode shapes. Based on this analysis, a database of information related to the specific composite beam being analyzed such as layups and natural frequencies are stored. The natural frequency will be measured and compared to that database for damage detection. A finite element model is also presented and compared with the analytical results. It is observed that the variation of natural frequencies in the presence of a crack is affected by the crack ratio, crack location and fiber orientation. In particular, the variation pattern is different as the magnitude of bending-torsion coupling changes due to different fiber angles. A simple circuit containing a microcontroller is implemented to simulate the automated SHM concept. The microcontroller serves as the data storage device as well as the decision maker based on the instantaneous comparison between the healthy and the damaged structure. The proposed system may be implemented in many structural components such as aircraft frames and bridges. This SHM technology may help replace the current time-based maintenance scheme with a condition-based one. The condition-based maintenance scheme relies on the ability to monitor the condition of the system and supply information of damage detection to allow a corrective action to be taken.

scholarly journals Magnetostrictive Sensors for Composite Damage Detection and Wireless Structural Health Monitoring

2019 ◽  
Vol 55 (7) ◽  
pp. 1-6
Author(s):  
Zhaoyuan Leong ◽  
William Holmes ◽  
James Clarke ◽  
Akshay Padki ◽  
Simon Hayes ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Health ◽  
Composite Damage

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Review of piezoelectric impedance based structural health monitoring: Physics-based and data-driven methods

2021 ◽  
pp. 136943322110384
Author(s):  
Xingyu Fan ◽  
Jun Li ◽  
Hong Hao
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Low Frequency ◽  
Data Driven ◽  
Mode Shapes ◽  
Monitoring Methods ◽  
Destructive Testing ◽  
Electromechanical Impedance ◽  
Structural Health

Vibration based structural health monitoring methods are usually dependent on the first several orders of modal information, such as natural frequencies, mode shapes and the related derived features. These information are usually in a low frequency range. These global vibration characteristics may not be sufficiently sensitive to minor structural damage. The alternative non-destructive testing method using piezoelectric transducers, called as electromechanical impedance (EMI) technique, has been developed for more than two decades. Numerous studies on the EMI based structural health monitoring have been carried out based on representing impedance signatures in frequency domain by statistical indicators, which can be used for damage detection. On the other hand, damage quantification and localization remain a great challenge for EMI based methods. Physics-based EMI methods have been developed for quantifying the structural damage, by using the impedance responses and an accurate numerical model. This article provides a comprehensive review of the exciting researches and sorts out these approaches into two categories: data-driven based and physics-based EMI techniques. The merits and limitations of these methods are discussed. In addition, practical issues and research gaps for EMI based structural health monitoring methods are summarized.

Radar-based structural health monitoring of wind turbine blades: The case of damage detection

2017 ◽  
Vol 17 (4) ◽  
pp. 815-822 ◽  
Author(s):  
Jochen Moll ◽  
Philip Arnold ◽  
Moritz Mälzer ◽  
Viktor Krozer ◽  
Dimitry Pozdniakov ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Wind Turbine ◽  
Health Monitoring ◽  
Turbine Blades ◽  
Heterogeneous Material ◽  
Material System ◽  
Wind Turbine Blades ◽  
Millimetre Wave ◽  
Structural Health

Structural health monitoring of wind turbine blades is challenging due to its large dimensions, as well as the complex and heterogeneous material system. In this article, we will introduce a radically new structural health monitoring approach that uses permanently installed radar sensors in the microwave and millimetre-wave frequency range for remote and in-service inspection of wind turbine blades. The radar sensor is placed at the tower of the wind turbine and irradiates the electromagnetic waves in the direction of the rotating blades. Experimental results for damage detection of complex structures will be presented in a laboratory environment for the case of a 10-mm-thick glass-fibre-reinforced plastic plate, as well as a real blade-tip sample.

scholarly journals Application of Machine Learning with Impedance Based Techniques for Structural Health Monitoring of Civil Infrastructure

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1139-1148
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Soft Computing ◽  
Health Monitoring ◽  
Multiple Cracks ◽  
Civil Infrastructure ◽  
Structural Health ◽  
Soft Computing Techniques

Increased attentiveness on the environmental and effects of aging, deterioration and extreme events on civil infrastructure has created the need for more advanced damage detection tools and structural health monitoring (SHM). Today, these tasks are performed by signal processing, visual inspection techniques along with traditional well known impedance based health monitoring EMI technique. New research areas have been explored that improves damage detection at incipient stage and when the damage is substantial. Addressing these issues at early age prevents catastrophe situation for the safety of human lives. To improve the existing damage detection newly developed techniques in conjugation with EMI innovative new sensors, signal processing and soft computing techniques are discussed in details this paper. The advanced techniques (soft computing, signal processing, visual based, embedded IOT) are employed as a global method in prediction, to identify, locate, optimize, the damage area and deterioration. The amount and severity, multiple cracks on civil infrastructure like concrete and RC structures (beams and bridges) using above techniques along with EMI technique and use of PZT transducer. In addition to survey advanced innovative signal processing, machine learning techniques civil infrastructure connected to IOT that can make infrastructure smart and increases its efficiency that is aimed at socioeconomic, environmental and sustainable development.

High-performance fiber optic systems for damage detection and structural health monitoring

2004 ◽  
Author(s):  
Mark E. Seaver ◽  
Stephen T. Trickey ◽  
Jonathan M. Nichols ◽  
Linda Moniz ◽  
Lou Pecora ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
High Performance ◽  
Fiber Optic ◽  
Structural Health ◽  
High Performance Fiber ◽  
Optic Systems
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