Local damage identification method using finite element model updating based on a new wavelet damage function

Zhang, Wei; Sun, Lijun; Zhang, Liye

doi:10.1177/1369433217746837

Cited by 12 publications

(5 citation statements)

References 21 publications

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“…The three sensors of the sparse sensor array form a equilateral triangle. According to the sum and delay algorithm [22][23][24], three damage probability ellipses can be depicted based on the three sensors and the damage position can be pinpointed based on these ellipses. Compared with conventional sensor networks for large-scale structures, a much simpler sensing network can be arranged in each monitoring region by using the proposed triangle-shaped sensor array, as shown in figure 4.…”

Section: Layout Of the Triangle-shape Sensor Arraymentioning

confidence: 99%

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Qiu

Liao

et al. 2023

Smart Mater. Struct.

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Since numerous sensors are needed to create a sensor array for the structural health monitoring of large-scale structures, the equipment quantity and cost considerably increase. This study proposes a sparse, triangle-shaped sensor array to identify, orient, and assess the degree of structural damage in composite constructions in order to overcome this shortcoming. The damage-scattered Lamb waves are recorded by the sparse sensor array with a variety of features that are then extracted and fed into the Support Vector Machine (SVM) classification method. The location and severity of the damage in composite constructions can be determined by training the SVM model. The principle component analysis (PCA) technique is used to compress the wave feature vectors while maintaining the majority of the damage information because the high dimension of the wave feature vectors required a significant amount of calculation during the training phase. Proof-of-concept tests show that the trained model, by utilizing the many properties of Lamb wave signals, can orient and define the degree of damage with excellent accuracy. Multiple lamb wave properties can be used to make up for the triangle sensor array's loss of damage information. In conjunction with the SVM, the triangle-shaped sensor array that was proposed in this study can efficiently make it easier to identify and characterize damage to large-scale structures while using fewer sensors.

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Section: Layout Of the Triangle-shape Sensor Arraymentioning

confidence: 99%

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Qiu

Liao

et al. 2023

Smart Mater. Struct.

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“…On the other hand, the Haar function is discontinuous and not differentiable because it is similar to a square shape of the digital signal. This property of Haar wavelet can be an advantage to analyze signals with sudden changes such as defect monitoring [73]. The wavelet function to be selected is moved along the input signal with a particular shifting period.…”

Section: A Preprocessing Techniquesmentioning

confidence: 99%

Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

2019

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The development in materials technology has produced stronger, lighter, stiffer, and more durable electrically insulating composites which are replacing metals in many applications. These composites require alternative inspection techniques because the conventional nondestructive testing (NDT) techniques such as thermography, eddy currents, ultrasonic, X-ray and magnetic particles have limitations of inspecting them. Microwave NDT technique employing open-ended rectangular waveguides (OERW) has emerged as a promising approach to detect the defects in both metal and composite materials. Despite its promising results over conventional NDT techniques, OERW microwave NDT technique has shown numerous limitations in terms of poor spatial resolution due to the stand-off distance variations, inspection area irregularities and quantitative estimation in imaging the size of defects. Microwave NDT employing OERW in conjunction with robust artificial intelligence approaches have tremendous potential and viability for evaluating composite structures for the purpose mentioned here. Artificial intelligence techniques with signal processing techniques are highly possible to enhance the efficiency and resolution of microwave NDT technique because the impact of artificial intelligence approaches is proven in various conventional NDT techniques. This paper provides a comprehensive review of NDT techniques as well as the prospect of using artificial intelligence approaches in microwave NDT technique with regards to other conventional NDT techniques. INDEX TERMS Microwave nondestructive testing, open-ended rectangular waveguides, artificial intelligence.

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“…The variable ε is the noise level and C is a standard random vector subjected to the uniformly distributed random numbers within the interval [−1, 1]. The noise level 3% was adopted based on similar studies in the damage detection literature (Huang et al, 2018; Stutz et al, 2018; Zhang et al, 2018). In this case, both modeling and measurement errors have been considered.…”

Section: Damage Detection Approachmentioning

confidence: 99%

A study on the crack detection in beams using linear and nonlinear normal modes

Erdoğan

2019

Advances in Structural Engineering

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Linear and nonlinear normal mode motions may provide promising information about the condition of mechanical structures under small and large amplitude vibrations, respectively. In this view, this study investigates the nonlinear dynamics of cracked beams through use of the nonlinear mode motion and extends the crack identification methods that utilize the linear characteristics to nonlinear vibrating structures. At first, the nonlinear normal modes of the intact and cracked beams are calculated by a continuation algorithm. A finite element model of a geometrically nonlinear prismatic beam was created based on crack stress intensity. Subsequently, a method based on normal mode motion and minimization of strain energy, which is valid for linear and nonlinear vibrating beams, was developed as an optimization problem. To this end, hybrid optimization was also used due to its capability in finding global minimum along with its computational efficiency. It was shown that the proposed crack detection technique is applicable to beams vibrating in linear and/or nonlinear regimes and well capable of detecting both crack location and severity.

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Local damage identification method using finite element model updating based on a new wavelet damage function

Cited by 12 publications

References 21 publications

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

A sparse, triangle-shaped sensor array for damage orientation and characterization of composite structures

Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

A study on the crack detection in beams using linear and nonlinear normal modes

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