Signal processing and damage detection in a frame structure excited by chaotic input force

2003 ◽  
Author(s):  
Liming W. Salvino ◽  
Darryll J. Pines ◽  
Michael D. Todd ◽  
Jonathan Nichols
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Frame Structure ◽  
Input Force

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.

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.

Health Monitoring of the Aircraft Structure during a Full Scale Fatigue Test with Use of an Active Piezoelectric Sensor Network

2015 ◽  
Vol 220-221 ◽  
pp. 328-332
Author(s):  
Michal Dziendzikowski ◽  
Krzysztof Dragan ◽  
Artur Kurnyta ◽  
Sylwester Klysz ◽  
Andrzej Leski
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Crack Growth ◽  
Fatigue Test ◽  
Piezoelectric Sensor ◽  
Full Scale ◽  
Growth Monitoring ◽  
Aircraft Structure ◽  
System Functioning ◽  
Signal Processing Methods

The paper presents an approach to develop a system for fatigue crack growth monitoring and early damage detection in the PZL – 130 ORLIK TC II turbo-prop military trainer aircraft structure. The system functioning is based on elastic waves propagation excited in the structure by piezoelectric PZT transducers. In the paper, a built block approach for the system design, signal processing as well as damage detection is presented. Description of damage detection capabilities are delivered in the paper and some issues concerning the proposed signal processing methods and their application to crack growth estimation models are discussed. Selected preliminary results obtained during the Full Scale Fatigue Test thus far are also presented.

A Vibration-Based Structural Damage Detection Method and its Applications to Engineering Structures

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Iterative Algorithm ◽  
Structural Damage ◽  
Detection Method ◽  
New Physics ◽  
Logistic Function ◽  
Frame Structure ◽  
Engineering Structures ◽  
System Equations ◽  
Extent Of Damage

Two major challenges associated with a vibration-based damage detection method using changes in natural frequencies are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistic function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using the Levenberg-Marquardt method is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. It is applied to various engineering structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation, and the locations and extent of damage can be successfully detected in experimental damage detection.

Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

2014 ◽  
Vol 578-579 ◽  
pp. 1020-1023
Author(s):  
Jing Zhou Lu ◽  
Jia Chen Wang ◽  
Xu Zhu
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Damage Detection ◽  
Structural Damage ◽  
Computing Time ◽  
Principal Component ◽  
Component Analysis ◽  
Identification Accuracy ◽  
Frame Structure ◽  
Ar Model

In this paper, we introduce a set of techniques for time series analysis based on principal component analysis (PCA). Firstly, the autoregressive (AR) model is established using acceleration response data, and the root mean squared error (RMSE) of AR model is calculated based on PCA. Then a new damage sensitive feature (DSF) based on the AR coefficients is presented. To test the efficacy of the damage detection and localization methodologies, the algorithm has been tested on the analytical and experimental results of a three-story frame structure model of the Los Alamos National Laboratory. The result of the damage detection indicates that the algorithm is able to identify and localize minor to severe damage as defined for the structure. It shows that the suggested method can lead to less amount of computing time, high suitability and identification accuracy.

Advanced signal processing technique for damage detection in steel tubes

2016 ◽  
Author(s):  
Umar Amjad ◽  
Susheel Kumar Yadav ◽  
Cac Minh Dao ◽  
Kiet Dao ◽  
Tribikram Kundu
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Steel Tubes

scholarly journals Structural Damage Identification Based on the Minimum System Realization and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
W. R. Li ◽  
Y. F. Du ◽  
S. Y. Tang ◽  
L. J. Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Information ◽  
Structural Response ◽  
Frame Structure ◽  
Structural Damage Detection ◽  
System Realization ◽  
Minimum System

On the basis of the thought that the minimum system realization plays the role as a coagulator of structural information and contains abundant information on the structure, this paper proposes a new method, which combines minimum system realization and sensitivity analysis, for structural damage detection. The structural damage detection procedure consists of three steps: (1) identifying the minimum system realization matrixes A, B, and R using the structural response data; (2) defining the mode vector, which is based on minimum system realization matrix, by introducing the concept of the measurement; (3) identifying the location and severity of the damage step by step by continuously rotating the mode vector. The proposed method was verified through a five-floor frame model. As demonstrated by numerical simulation, the proposed method based on the combination of the minimum realization system and sensitivity analysis is effective for the damage detection of frame structure. This method not only can detect the damage and quantify the damage severity, but also is not sensitive to the noise.

Sign in / Sign up

Export Citation Format

Share Document