Mr. Yushin Hara Profile

Yushin Hara

at Tohoku Univ.

SPIE Involvement:

Author

Publications (3)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 9 May 2024 Presentation + Paper

Wireless sensor node powered by piezoelectric vibration energy harvester for vibrational mode identification and structural health monitoring

T. Yamada, H. Asanuma, Y. Hara

Proceedings Volume 12946, 129460V (2024) https://doi.org/10.1117/12.3010821

KEYWORDS: Sensor networks, Vibration, Data transmission, Structural health monitoring, Continuous wavelet transforms, Image classification, Wireless sensors, Signal intensity, Capacitors, Sensors

Read Abstract +

We applied our previously developed wireless sensor node (WSN), which is powered by a piezoelectric vibration energy harvester (VEH), to structural health monitoring and verified its classification performance. The self-powered WSN can measure structural vibrations and transmit the three-axis acceleration waveform data wirelessly. A normal intact beam and four beams that had a single notch cut at four different locations were prepared for classification testing. The WSN, which was connected to the piezoelectric VEH, was mounted on the tip of an aluminum alloy beam, and a random vibration was then applied to the clamped end of the beam. First, the power of the piezoelectric VEH under the random vibration condition was investigated by introducing the probability of harvesting. The beam’s vibrational modes were identified within the 0–1,600 Hz frequency range using the transmitted waveform data. Second, based on an analogy to 2D image classification, we created an input image by arranging the x, y, z-axis acceleration spectrum data vertically and then classifying the arranged data using 2D convolutional neural network (2D-CNN) layers. The Bayesian optimization technique was used to maximize classification accuracy by optimizing the hyperparameters. We confirmed that the self-powered WSN can provide high classification accuracy of 99.9%. We also revealed the basis of this high classification accuracy using gradient-weighted class activation mapping (Grad-CAM) and the continuous wavelet transform (CWT). Our self-powered WSN, which can provide additional features by transmitting the three-axis acceleration waveforms, represents a useful tool for structural health monitoring or predictive maintenance applications.

Proceedings Article | 28 April 2023 Presentation + Paper

Structural modal parameter identification incorporating with semi-active piezoelectric control

Yushin Hara, Haruhiko Asanuma, Keisuke Otsuka, Kanjuro Makihara

Proceedings Volume 12483, 124830H (2023) https://doi.org/10.1117/12.2656930

KEYWORDS: Circuit switching, Transducers, Switching, Vibration, Switches, Deformation, Mathematical modeling, System identification

Read Abstract +

In this paper, we present a novel structural identification method using semi-active inputs generated by piezoelectric transducers. Structural identification using input and output information provides an accurate structural model. Conventional identification uses a maximum-length sequence, whose signal shape is similar to a square wave, as input. To generate inputs suitable for identification, several devices are required. These devices consume a lot of energy. If inputs are generated by a small number and simple design devices with low consumption, structural identification will be more practical. Piezoelectric semi-active control has been used in the research field of vibration control. This control generates a semi-active input whose signal shape is similar to a square wave. The semi-active input is generated by a simple circuit. The generation of the semi-active input consumes little energy. Therefore, the semi-active input has the potential to be used as an identification input instead of the maximum-length sequence. The property of the semi-active input is related to the generation strategy. This paper proposes a novel strategy to generate a semi-active input suitable for identification. Due to the unique mechanism of semi-active input generation, the novel strategy sometimes has the problem of generating semi-active inputs that are not suitable for identification. This paper discusses the reason and the solution to this problem. The feasibility of semi-active identification is presented through the numerical simulation and validation experiment. The identification result of the proposed method was close to the exact model. The proposed method achieved a 99% reduction in energy consumption.

Proceedings Article | 28 April 2023 Presentation + Paper

Acceleration-waveform-sending wireless sensor node powered by piezoelectric vibration energy harvester

T. Yamada, H. Asanuma, Y. Hara, A. Erturk

Proceedings Volume 12483, 124830R (2023) https://doi.org/10.1117/12.2657742

KEYWORDS: Sensor networks, Vibration, Capacitors, Data transmission, Power consumption, Wireless sensors, Sensors, Structural health monitoring, Frequency response, Transceivers

Read Abstract +

We have developed a wireless sensor node (WSN) powered by a piezoelectric vibration energy harvester that enables transmission of three-axis acceleration waveform data. Unlike a conventional WSN, which sends a single point representing the root mean square acceleration value, the proposed WSN allows the frequency, vibrational modes, and displacement of the target structure to be obtained. Therefore, this waveform-sending scenario is highly suitable for structural health monitoring applications. We used a power gating technique to reduce the standby energy consumption significantly and thus realize the waveform-sending concept. The overall dimensions and mass of the WSN are 3×3×3 cm³ and 26 g, respectively. The overall dimensions of the harvester are 5.6×2×2.1 cm3. The WSN measures the threeaxis acceleration of the structure’s vibration for 1.2 s at a sampling rate of 3,200 samples every 5 min, transmits the data, and then goes into standby mode. Because of the power gating technique, the energy consumption per cycle is as low as 108 mJ. We evaluated the WSN under both harmonic and random vibration conditions. For harmonic vibrations, the acceleration magnitude applied using a shaker was 1 m/s² at the harvester’s resonance. For random vibrations, a power spectral density (PSD) of 0.1 (m/s²)²/Hz and a frequency range of 10–100 Hz were set. The WSN operated successfully using only energy generated by the harvester and the transmitted waveforms matched the waveforms measured by a high-precision acceleration pick-up. Here, we report the WSN design methodology and the detailed charging characteristics of the energy storage capacitor.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years