Thick-Film Ceramic Strain Sensors for Structural Health Monitoring

Jabir, Saad A.A.; Gupta, Naren

doi:10.1109/tim.2011.2138310

Cited by 41 publications

(13 citation statements)

References 11 publications

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“…Thus, the bolt loosening damage not only affects the safety of the building, but it also causes severe accidents. The conventional structural health monitoring methods mainly collects acceleration, displacement, and strain . Then these characteristics are analyzed through wavelet transform and Bayesian transformation to obtain the location and size of the damage.…”

Section: Introductionmentioning

confidence: 99%

Bolt loosening angle detection technology using deep learning

Zhao

Zhang

Wang

2018

Struct Control Health Monit

102

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As an important part of the steel structure, the bolt damage will affect the safety of the structure and even cause severe accidents. However, it is difficult to detect the bolt loosening from the perspective of the conventional dynamics, due to the complex vibration characteristics of the bolt joints. In order to detect structural damage intuitively, machine vision has been introduced into the field of structural health monitoring. Therefore, this paper combines deep learning and machine vision to propose a bolt loosening angle detection technology. First, the data sets with bolts were collected and divided into training sets, validation sets, and test sets. Second, the data sets were trained using Single Shot MultiBox Detector. And the recognition accuracy of the model was evaluated, which can reach 0.914. Thereafter, the images obtained from different angles and lighting conditions were detected by the training model;the results showed that this method still has high recognition accuracy and meets the requirements of engineering. Finally, the training model was migrated to the smartphone to achieve quick and simple bolt loosening monitoring.KEYWORDS bolt loosening angle, deep learning, machine vision, smartphone, SSD | INTRODUCTIONWith the advancement of steel structures, it has developed rapidly in high-rise and supertall buildings. Compared with the concrete structure, the steel structure adopts steel plate instead of reinforced concrete, which has higher strength and better seismic performance. And its components can be prefabricated at the factory, which greatly reduces the construction period. As an important joint, bolts are widely used in steel structures. Thus, the bolt loosening damage not only affects the safety of the building, but it also causes severe accidents. The conventional structural health monitoring methods mainly collects acceleration, 1 displacement, 2 and strain. 3 Then these characteristics are analyzed through wavelet transform 4,5 and Bayesian transformation 6-8 to obtain the location and size of the damage. However, these methods rely on a large number of distributed sensors, and the feature extraction process need to intervention. The damage feature parameters directly determine the results of the damage detection. However, machine vision can complete damage monitoring from another perspective. Many damages on the structure can be detected more intuitively by vision. The bolt damage is mainly divided into rusty, shedding, and loosening, of which the most difficult to detect is loosening. To date, many researchers also used machine vision methods to monitor bolt loosening damage. For instance, Park et al. 9 proposed a bolt loosening angle detection method using Hough transformation, which detects bolt

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Section: Introductionmentioning

confidence: 99%

Bolt loosening angle detection technology using deep learning

Zhao

Zhang

Wang

2018

Struct Control Health Monit

102

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“…The moderate capital investment and low running costs make thick film a very popular technology for hybrid circuit fabrication [1][2][3]. The evolution in multichip module technology has led to the development of co-firing technologies -first High Temperature Co-fired Ceramic (HTCC) [4][5][6] and later Low Temperature Co-fired Ceramic (LTCC) fabrication have dominated the development of thick film technology [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Two-Stage Process for Laser Prototyping of Microwave Circuits in LTCC Technology

Shafique

Robertson

2015

IEEE Trans. Compon., Packag. Manufact. Technol.

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Abstract-An improved technique for laser prototyping of microwave circuits in LTCC technology is presented. This builds on previous work which demonstrated that laser machining of conductor layers on unfired LTCC tape could be used to fabricate multilayer microwave circuits without any patterned screens, stencils or masks. The improved process employs post-fire patterning of the top and bottom layer. In this way, sensitive microwave structures like couplers and filters can be fabricated on the outer layers because shrinkage uncertainty is no longer a problem. Track widths and gaps of 30 µm are demonstrated with edge definition of ±2 µm. A stripline coupler is successfully fabricated using this technique. The improved process can produce high precision microwave and millimeterwave components on the outer layers and provides rapid systemin-package prototyping for research and development.

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“…Therefore, the development of the soft electronic element has become a research focus [9]- [17]. As the pressure measurement is very important in the modern industry [18]- [26], the study on the flexible pressure sensitive material has attracted many research interests. Conductive polymer composite with flexibility and piezoresistivity [27]- [35] can be used to develop a soft pressure sensor [36]- [43], which is needed urgently in many modern industry fields, such as the interlayer stress monitoring between the curve surfaces and the robotic fingertip tactile sensor development, and so on.…”

Section: Introductionmentioning

confidence: 99%

A Prototype of Piezoresistive Fringe-Electrodes-Element Based on Conductive Polymer Composite

Wang

Han

2014

IEEE Trans. Electron Devices

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To improve the softness of the piezoresistive element based on conductive polymer composite, a prototype of fringe-electrodes-element is designed and investigated. The fringe-electrodes-element encompasses the pressure sensitive part, the connection part, and the interface part. Different from the traditional sandwich element, the pressure sensitive part of the fringe-electrodes-element has no electrodes, contributing to increasing the flexibility of the element. The connection part is used to connect the other two parts, and the function of it is similar to a conducting wire. The electrodes are located in the interface part for outputting the resistance signal. The experimental data show that the electrical resistance of the fringe-electrodes-element changes regularly with the external pressure. The sensitivity of the fringe-electrodes-element is lower than that of the traditional sandwich element, and decreases with the increase of the distance between the edge of the pressure sensitive part and that of the electrode. With the tunneling effect theory, the piezoresistive mechanism of the fringe-electrodeselement is explained. The results verify the feasibility to use the fringe-electrodes-element to realize the pressure measurement at the cost of some sensitivity.Index Terms-Carbon nanotube, conductive polymer composite, flexible pressure sensor, piezoresistive effect.

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Thick-Film Ceramic Strain Sensors for Structural Health Monitoring

Cited by 41 publications

References 11 publications

Bolt loosening angle detection technology using deep learning

Bolt loosening angle detection technology using deep learning

A Two-Stage Process for Laser Prototyping of Microwave Circuits in LTCC Technology

A Prototype of Piezoresistive Fringe-Electrodes-Element Based on Conductive Polymer Composite

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