Yozo Fujino

Bio: Yozo Fujino is an academic researcher from Yokohama National University. The author has contributed to research in topics: Vibration & Bridge (interpersonal). The author has an hindex of 51, co-authored 465 publications receiving 9752 citations. Previous affiliations of Yozo Fujino include University of Yamanashi & Nagoya University.

Estimation curve for modal damping in stay cables with viscous damper

Abstract: To simplify the procedure of designing viscous dampers for stay cables in bridges, a universal estimation curve is proposed that relates the modal damping ratio of the cable with attached damper, the mode number, the damper size, the damper location, and three parameters of the cable: span, mass per unit length, and fundamental frequency. The curve is obtained from numerical complex‐eigenvalue analysis of a taut cable with a single damper near the anchorage, with judicious grouping of these parameters into nondimensional factors. Several numerical examples illustrate the convenient use of this design aid, as well as show realistic values of the required damper size and location and the expected additional damping in the first few modes. The damping to be attained is usually high enough to suppress most vibrations induced by wind. However it is noted that a small sag of the cable and slight nonviscous properties of the damper may reduce the damper effectiveness. A modified design curve may have to incorpor...

Concrete Crack Detection by Multiple Sequential Image Filtering

Abstract: This article presents a new robust automated image processing method for detecting cracks in surface images of concrete structures This method involves two steps: (1) development of an image filter for detecting major cracks using genetic programming (GP), and (2) elimination of residual noise after filtering and detection of indistinct cracks by iterative applications of the image filter to the local regions surrounding the cracks The proposed method can be used for the accurate detection of cracks in surface images recorded under various conditions Moreover, the widths of the detected cracks can be quantified on the basis of the spatial derivatives of the brightness patterns The estimated crack widths are in good agreement with those measured manually The paper shows how research on structural health monitoring of bridges and structures has received significant attention in recent years

Dynamic characterization of multiple tuned mass dampers and some design formulas

Abstract: Multiple Tuned Mass Dampers (MTMD) consist of a large number of small oscillators with natural frequencies distributed around the natural frequency of a controlled mode of the structure. In the present paper, the modal characteristics and efficiency of the MTMD are studied analytically. Perturbation solutions for the modal properties of the MTMD–structure system are obtained and the modal characteristics are discussed. An explicit formula to estimate the effectiveness of the MTMD subjected to harmonic forces is also derived. It is shown that the MTMD is efficient when at least one of the oscillators is strongly coupled with the structure in any mode. Based on this observation, a critical bandwidth of the natural frequencies of the MTMD to make the system multiply tuned is derived in a simple form, and furthermore a robustness criterion for the frequency tuning under a given bandwidth is proposed. It is shown that, when properly designed, the MTMD can be much more stable (robust) than a conventional single TMD while maintaining more or less the same efficiency. Numerical studies verify the accuracy of the perturbation solutions and the proposed formulas.

Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

Abstract: A number of image processing techniques IPTs have been implemented for detecting civil infrastructure defects to partially replace human-conducted onsite inspections. These IPTs are primarily used to manipulate images to extract defect features, such as cracks in concrete and steel surfaces. However, the extensively varying real-world situations e.g., lighting and shadow changes can lead to challenges to the wide adoption of IPTs. To overcome these challenges, this article proposes a vision-based method using a deep architecture of convolutional neural networks CNNs for detecting concrete cracks without calculating the defect features. As CNNs are capable of learning image features automatically, the proposed method works without the conjugation of IPTs for extracting features. The designed CNN is trained on 40 K images of 256 × 256 pixel resolutions and, consequently, records with about 98% accuracy. The trained CNN is combined with a sliding window technique to scan any image size larger than 256 × 256 pixel resolutions. The robustness and adaptability of the proposed approach are tested on 55 images of 5,888 × 3,584 pixel resolutions taken from a different structure which is not used for training and validation processes under various conditions e.g., strong light spot, shadows, and very thin cracks. Comparative studies are conducted to examine the performance of the proposed CNN using traditional Canny and Sobel edge detection methods. The results show that the proposed method shows quite better performances and can indeed find concrete cracks in realistic situations.

Structural control: past, present, and future

Abstract: This tutorial/survey paper: (1) provides a concise point of departure for researchers and practitioners alike wishing to assess the current state of the art in the control and monitoring of civil engineering structures; and (2) provides a link between structural control and other fields of control theory, pointing out both differences and similarities, and points out where future research and application efforts are likely to prove fruitful. The paper consists of the following sections: section 1 is an introduction; section 2 deals with passive energy dissipation; section 3 deals with active control; section 4 deals with hybrid and semiactive control systems; section 5 discusses sensors for structural control; section 6 deals with smart material systems; section 7 deals with health monitoring and damage detection; and section 8 deals with research needs. An extensive list of references is provided in the references section.

A summary review of wireless sensors and sensor networks for structural health monitoring

Abstract: In recent years, there has been an increasing interest in the adoption of emerging sensing technologies for instrumentation within a variety of structural systems. Wireless sensors and sensor networks are emerging as sensing paradigms that the structural engineering field has begun to consider as substitutes for traditional tethered monitoring systems. A benefit of wireless structural monitoring systems is that they are inexpensive to install because extensive wiring is no longer required between sensors and the data acquisition system. Researchers are discovering that wireless sensors are an exciting technology that should not be viewed as simply a substitute for traditional tethered monitoring systems. Rather, wireless sensors can play greater roles in the processing of structural response data; this feature can be utilized to screen data for signs of structural damage. Also, wireless sensors have limitations that require novel system architectures and modes of operation. This paper is intended to serve as a summary review of the collective experience the structural engineering community has gained from the use of wireless sensors and sensor networks for monitoring structural performance and health.

Modeling and Control of Magnetorheological Dampers for Seismic Response Reduction

Abstract: Control of civil engineering structures for earthquake hazard mitigation represents a relatively new area of research that is growing rapidly. Control systems for these structures have unique requirements and constraints. For example, during a severe seismic event, the external power to a structure may be severed, rendering control schemes relying on large external power supplies ineffective. Magnetorheological (MR) dampers are a new class of devices that mesh well with the requirements and constraints of seismic applications, including having very low power requirements. This paper proposes a clipped-optimal control strategy based on acceleration feedback for controlling MR dampers to reduce structural responses due to seismic loads. A numerical example, employing a newly developed model that accurately portrays the salient characteristics of the MR dampers, is presented to illustrate the effectiveness of the approach.

Health monitoring of civil infrastructures using wireless sensor networks

Abstract: A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.