Performance validation of printed strain sensors for active control of intelligent tires

Hariri, Hassan; Kim, J.; Kim, W.S.; Fréchette, Luc; Masson, Patrice

doi:10.1016/j.apacoust.2017.03.011

Cited by 15 publications

(7 citation statements)

References 19 publications

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“…With regard to applications, most current studies focus on the use of strain sensors for wearable devices and human motion detection [ 15 , 16 , 17 ]. Nonetheless, other original applications of printed sensors have been demonstrated for strain monitoring of hip prosthesis [ 18 ], handguns [ 19 ], and tires [ 20 ]. Moreover, printed sensors have been successfully used to monitor vital signs [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Printed Strain Sensors Based on an Intermittent Conductive Pattern Filled with Resistive Ink Droplets

Żymełka

Yamashita

Sun

et al. 2020

Sensors

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In this study, we demonstrate a strain sensor fabricated as a hybrid structure of a conductive intermittent pattern with embedded single droplets of a functional resistive ink. The main feature of our proposed sensor design is that although the intermittent pattern comprises the majority of the entire sensor area, the strain sensitivity depends almost selectively on the resistive droplets. This opens up the possibility for fast and inexpensive evaluation of sensors manufactured from various functional materials. As the use of resistive ink was limited to single droplets deposition, the required ink amount needed to build a sensor can be considerably reduced. This makes the sensors cost-effective and simple for fabrication. In this study, our proposed sensor design was evaluated when a carbon-based ink was used as the resistive material incorporated into an intermittent structure made of silver. The developed strain sensors were tested during bending deformations demonstrating good strain sensitivity (gauge factor: 7.71) and no hysteresis within the investigated strain range.

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Section: Introductionmentioning

confidence: 99%

Printed Strain Sensors Based on an Intermittent Conductive Pattern Filled with Resistive Ink Droplets

Żymełka

Yamashita

Sun

et al. 2020

Sensors

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“…The available printing methods and materials allow the fabrication of sensors as well as passive components with their entire wiring systems on various types of lightweight flexible substrates [ 21 ]. Owing to the benefits of printed electronics, printed strain sensors have been studied for various applications [ 22 , 23 , 24 , 25 , 26 ], including SHM [ 27 , 28 , 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

Practical Evaluation of Printed Strain Sensors Based on Long-Term Static Strain Measurements

Żymełka

Togashi²,

Takeshita

et al. 2021

Sensors

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Recent progress in printable electronics has enabled the fabrication of printed strain sensors for diverse applications. These include the monitoring of civil infrastructure, the gradual aging of which raises concerns about its effective maintenance and safety. Therefore, there is a need for automated sensing systems that provide information on the performance and behavior of engineering structures that are subjected to dynamic and static loads. The application of printed strain sensors in structural health monitoring is of growing interest owing to its large-area and cost-effective fabrication process. Previous studies have proven the suitability of printable strain sensors for dynamic strain measurements on bridges; however, the analysis of the long-term stability of printed sensors during static strain measurements is still lacking. Thus, this study aims to assess the long-term stability of printed strain sensor arrays and their suitability for the static strain analysis of large civil structures. The developed sensors and a dedicated wireless data acquisition system were deployed inside a gravity dam, which was selected as the field test environment. This test environment was chosen owing to the relatively stable temperature inside the dam and the very slow static strain changes associated with periodic water level changes. The results exhibited an average signal drift of 20 μϵ over 127 days. One of the sensor arrays was installed on a small crack in the dam structure; it showed that the sensors can track static strain changes owing to variations in the crack opening, which are related to the water level changes in the dam. Overall, the results of the developed sensors exhibit good strain sensitivity and low signal drift. This indicates the potential suitability of printed sensors for applications in the static strain analysis of engineering structures.

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“…However, it is also important that the driver is aware of road conditions, such as whether the surface is normal, unpaved, wet, snow-covered, or icy [12,13]. Given that tires are in direct contact with the road surface, information regarding not only tire-related, such as pressure, temperature, wear condition, and tread depth, but also information on the degree of road surface friction and pavement condition, can be obtained [14]. Tires that collect such information through an internal sensor and relay data on the road surface conditions to the driver are called intelligent tires (iTires).…”

Section: Introductionmentioning

confidence: 99%

A Road Condition Classification Algorithm for a Tire Acceleration Sensor using an Artificial Neural Network

et al. 2020

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The automotive industry is experiencing a period of innovation, represented by the term CASE (connected, autonomous, shared, and electric). Among the innovative new technologies for automobiles, intelligent tire (iTire) collects road surface information through sensors installed inside a tire and informs the driver of the road conditions. iTire can promote safe driving. Various kinds of research on iTire is ongoing, and this paper proposes an algorithm to determine the road surface conditions while driving. Specifically, we have proposed a method for extracting the feature points of a frequency band, by converting acceleration data collected by sensors through fast Fourier transform (FFT) and determining road surface conditions via an artificial neural network. Lastly, the applicability of the algorithm was verified.

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Performance validation of printed strain sensors for active control of intelligent tires

Cited by 15 publications

References 19 publications

Printed Strain Sensors Based on an Intermittent Conductive Pattern Filled with Resistive Ink Droplets

Printed Strain Sensors Based on an Intermittent Conductive Pattern Filled with Resistive Ink Droplets

Practical Evaluation of Printed Strain Sensors Based on Long-Term Static Strain Measurements

A Road Condition Classification Algorithm for a Tire Acceleration Sensor using an Artificial Neural Network

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