This paper describes a method for assessing the structural integrity of International America's Cup Class (IACC) yachts using a fiber optic distributed strain sensor. IACC yachts are made of advanced composite materials designed for high stiffness and lightness, however, a number of critical accidents have occurred during sailing. So we developed a health monitoring system and applied it to two Japanese IACC yachts to measure the distributed strain by using an optical fiber sensor installed in their hulls. We then estimated the three-dimensional distributed strain and compared the results with simulated data obtained by finite element analysis (FEA) to confirm the designed strength of these yachts.

We applied a Brillouin-OTDR, which is a distributed optical fiber strain sensor, to two actual concrete piles. The piles were made for use as highway foundations by on-site-pouring at construction sites and underwent load testing to ensure that their characteristics satisfied the required levels. Compressive strain caused by the load exerted on the piles was measured to an accuracy of 0.01% and a spatial resolution of 1 m. This measurement was obtained by embedding a strain-sensing optical fiber in the piles during construction. The results showed that there was good agreement between the measured strain and both the theoretical values and the values obtained with a conventional strain gauge based on electric resistance. Furthermore, the obtained strain distribution reflected the effects of friction between the pile surface and the ground. These results demonstrate the effectiveness of the Brillouin-OTDR for this kind of testing and also as a means of obtaining detailed data on the strain in concrete piles.

This paper presents a novel statistic computation technique for energy detection-based spectrum sensing with multiple antennas. The presented technique computes the statistic for signal detection after combining all the signals. Because the computation of the statistic for all the received signals is not required, the presented technique reduces the computational complexity. Furthermore, the absolute value of all the received signals are combined to prevent the attenuation of the combined signals. Because the statistic computations are not required for all the received signals, the reduction of the computational complexity for signal detection can be expected. Furthermore, the presented technique does not need to choose anything, such as the binary phase rotator in the conventional technique, and therefore, the performance degradation due to wrong choices can be avoided. Numerical examples indicate that the spectrum sensing performances of the presented technique are almost the same as those of conventional techniques despite the complexity of the presented technique being less than that of the conventional techniques.

This paper presents a novel spectrum sensing technique based on selection diversity combining in cognitive radio networks. In general, a selection diversity combining scheme requires a period to select an optimal element, and spectrum sensing requires a period to detect a target signal. We consider that both these periods are required for the spectrum sensing based on selection diversity combining. However, conventional techniques do not consider both the periods. Furthermore, spending a large amount of time in selection and signal detection increases their accuracy. Because the required period for spectrum sensing based on selection diversity combining is the summation of both the periods, their lengths should be considered while developing selection diversity combining based spectrum sensing for a constant period. In reference to this, we discuss the spectrum sensing technique based on selection diversity combining. Numerical examples are shown to validate the effectiveness of the presented design techniques.

This paper provides theoretical analyses for maximum cyclic autocorrelation selection (MCAS)-based spectrum sensing techniques in cognitive radio networks. The MCAS-based spectrum sensing techniques are low computational complexity spectrum sensing in comparison with some cyclostationary detection. However, MCAS-based spectrum sensing characteristics have never been theoretically derived. In this study, we derive closed form solutions for signal detection probability and false alarm probability for MCAS-based spectrum sensing. The theoretical values are compared with numerical examples, and the values match well with each other.

This paper describes a load carrying test for a concrete pipe designed to study the effectiveness of distributed strain measurement using an optical fiber sensor. We performed a load carrying test on a concrete pipe and attempted to detect the distributed strain inside it using an optical fiber sensor mounted inside the pipe. We confirmed that it was possible to detect the strain in a concrete structure by using an optical fiber sensor after a crack had occurred on the concrete surface. This paper shows that measurement using the optical fiber sensor was effective despite great changes in the strain conditions of the measured object over a short distance.

This letter presents a computational complexity reduction technique for space diversity based spectrum sensing when the number of receive antennas is greater than three (NR≥3 where NR is the number of receive antenna). The received signals are combined with phase inversion so as to not attenuate the combined signal, and a statistic for signal detection is computed from the combined signal. Because the computation of only one statistic is required regardless of the number of receive antenna, the complexity can be reduced. Numerical examples and simple analysis verify the effectiveness of the presented technique.

Since river levee collapse causes great damage, it is socially very important to prevent such disasters by using a monitoring system which can detect changes in the state of a river levee. To investigate the possibility of detecting the collapse of a levee slope at an early stage, we performed an experiment in which we used artificial rainfall and penetration to collapse a full-scale levee model, and measured the change in the levee state using a detection system during collapse. The system consists of sensor plates, a distributed fiber optic strain sensor, and a personal computer. With this system, the stretching produced in the sensor plates by the force resulting from the movement of the soil on the levee slope face is detected as strain by a sensing optical fiber fixed to the plates. Since the distributed fiber optic strain sensor can measure strain continuously and for a long distance along a fiber, it is suitable for monitoring civil structures such as river levees. The experiment confirmed that a change in a levee can be clearly detected when the slope face collapse progresses near the place where the sensor plates are buried. The results suggest the feasibility of being able to foresee the collapse of a levee slope.

In an optical time domain reflectometer type strain measurement system, we theoretically derive the shape of the Brillouin gain spectrum produced in an optical fiber under a parabolic strain distribution which is formed in a uniformly loaded beam. Based on the derived result, we investigate the effects of the parabolic strain distribution parameters and the measurement conditions such as the launched pulse width and the measurement position on the beam on the deformation of the Brillouin backscattered-light power spectrum shape. In addition, we investigate the strain measurement error resulting from the deformation of the power spectrum shape by analyzing the peak-power frequency at which the power spectrum is maximized.