Enhancing Structural Damage Identification Robustness to Noise and Damping With Integrated Bistable and Adaptive Piezoelectric Circuitry

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Jinki Kim ◽  
R. L. Harne ◽  
K. W. Wang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Piezoelectric Transducers ◽  
Practical Implementation ◽  
Frequency Shifts ◽  
Damage Prediction ◽  
Strongly Nonlinear ◽  
Bifurcation Phenomena ◽  
Engineered Structures ◽  
Robustness To Noise

The accurate and reliable identification of damage in modern engineered structures is essential for timely corrective measures. Vibration-based damage prediction has been studied extensively by virtue of its global damage detection ability and simplicity in practical implementation. However, due to noise and damping influences, the accuracy of this method is inhibited when direct peak detection (DPD) is utilized to determine resonant frequency shifts. This research investigates an alternative method to detect frequency shifts caused by structural damage based on the utilization of strongly nonlinear bifurcation phenomena in bistable electrical circuits coupled with piezoelectric transducers integrated with the structure. It is shown that frequency shift predictions by the proposed approach are significantly less susceptible to error than DPD when realistic noise and damping levels distort the shifting resonance peaks. As implemented alongside adaptive piezoelectric circuitry with tunable inductance, the new method yields damage location and severity identification that is significantly more robust and accurate than results obtained following the DPD approach.

Enhancing Damage Identification Robustness to Noise and Damping Using Integrated Bistable and Adaptive Piezoelectric Circuitry

2014 ◽  
Author(s):  
Jinki Kim ◽  
R. L. Harne ◽  
K. W. Wang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Piezoelectric Transducers ◽  
Practical Implementation ◽  
Frequency Shifts ◽  
Damage Prediction ◽  
Strongly Nonlinear ◽  
Bifurcation Phenomena ◽  
Engineered Structures ◽  
Robustness To Noise

The accurate and reliable identification of damage in modern engineered structures is essential for timely corrective measures. Vibration-based damage prediction has been studied extensively by virtue of its global damage detection ability and simplicity in practical implementation. However, due to noise and damping effects, the accuracy of this method is inhibited when direct peak detection (DPD) is utilized to determine resonant frequency shifts. This research investigates an alternative method to detect frequency shifts caused by structural damage based on the utilization of strongly nonlinear bifurcation phenomena in bistable electrical circuits coupled with piezoelectric transducers integrated with the structure. It is shown that frequency shift predictions by the proposed approach are significantly less susceptible to error than DPD when realistic noise and damping levels distort the shifting resonance peaks. As implemented alongside adaptive piezoelectric circuitry with tunable inductance, the new method yields damage location and severity identification that is significantly more robust and accurate than results obtained following the DPD approach.

scholarly journals Damage Identification in Plate Structures Using Sparse Regularization Based Electromechanical Impedance Technique

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7069
Author(s):  
Xingyu Fan ◽  
Jun Li
Keyword(s):  
Resonance Frequency ◽  
Structural Damage ◽  
Damage Identification ◽  
Physical Parameters ◽  
Inverse Identification ◽  
Plate Structures ◽  
Frequency Shifts ◽  
Sparse Regularization ◽  
Electromechanical Impedance ◽  
Damage Quantification

This paper proposes a novel structural damage quantification approach using a sparse regularization based electromechanical impedance (EMI) technique. Minor structural damage in plate structures by using the measurement of only a single surface bonded lead zirconate titanate piezoelectric (PZT) transducer was quantified. To overcome the limitations of using model-based EMI based methods in damage detection of complex or relatively large-scale structures, a three-dimensional finite element model for simulating the PZT–structure interaction is developed and calibrated with experimental results. Based on the sensitivities of the resonance frequency shifts of the impedance responses with respect to the physical parameters of plate structures, sparse regularization was applied to conduct the undetermined inverse identification of structural damage. The difference between the measured and analytically obtained impedance responses was calculated and used for identification. In this study, only a limited number of the resonance frequency shifts were obtained from the selected frequency range for damage identification of plate structures with numerous elements. The results demonstrate a better performance than those from the conventional Tikhonov regularization based methods in conducting inverse identification for damage quantification. Experimental studies on an aluminum plate were conducted to investigate the effectiveness and accuracy of the proposed approach. To test the robustness of the proposed approach, the identification results of a plate structure under varying temperature conditions are also presented.

Optimal Sensor Placement Algorithm for Structural Damage Identification

2020 ◽  
Vol 14 (1) ◽  
pp. 69-81
Author(s):  
C.H. Li ◽  
Q.W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Sensor Placement ◽  
Optimization Procedure ◽  
Frame Structure ◽  
Truss Structures ◽  
Optimal Sensor Placement ◽  
Structural Damage Identification ◽  
Placement Algorithm ◽  
Sensor Locations

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.

Sparse damage detection via the elastic net method using modal data

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Elastic Net ◽  
Sensitivity Matrix ◽  
Regularization Technique ◽  
Modal Data ◽  
Regularization Techniques ◽  
Net Method

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.

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