The NO_x degradation performance of nano-TiO₂ as a coating material for the road environment was evaluated in this research. The nano-TiO₂ coating materials for both road surface and roadside were prepared by using anatase nano-TiO₂, activated carbon powder, silane coupling agent and deionized water. The impact of varying amounts of coating material and silane coupling agent were evaluated. The road environment of NO_x degradation was simulated by the photocatalytic test system designed by the research team. For the road surface coating, the photocatalytic degradation experiments of NO under different radiation intensities were carried out. The results show that the material has good photocatalytic degradation performance, and the proper amount of silane coupling agent can enhance the bonding performance of the material and asphalt mixture. For the roadside coating, sodium dodecylbenzene sulfonate was selected as the surfactant to carry out the photocatalytic degradation experiment of NO₂ with different dosages of surfactant. The results showed that when the mass ratio of nano-TiO₂ and surfactant was about 1:2, the catalytic degradation effect of the material was the best.

This paper presents a fiber Bragg grating (FBG)-based six-dimensional (6-D) force/torque (F/T) sensor that can be mounted on robot joints for the detection of comprehensive force/torque information. The sensor is designed based on a new concept of multilayer measurement in which the elastic structure is divided into four layers. A single optical fiber inscribed with 12 FBGs is symmetrically attached to the elastic structure to sense force/torque-induced strains by means of differential measurements. Because of the mechanical decoupling function of the structure and the reasonable arrangement of the FBG sensing elements, the designed sensor possesses a great advantage of low cross coupling compared with existing 6-D force/torque sensors, which simplifies the calibration and maintenance of the sensor. Calibration experiments demonstrate high resolutions of 7.8 N mm, 7.2 N mm, 15.8 N mm, 0.0067 N, 0.0066 N and 0.0825 N within the range of ±1.56 Nm, ±1.56 Nm, ±1.56 Nm, ±10 N, ±10 N and ±25 N for the detection of Mx, My, Mz, Fx, Fy and Fz, respectively. Dynamic performances of the designed sensor have been evaluated in comparison with a commercial force/torque sensor.

Automatic crack detection is always a challenging task due to the inherent complex backgrounds, uneven illumination, irregular patterns, and various types of noise interference. In this paper, we proposed a U-shaped encoder–decoder semantic segmentation network combining Unet and Resnet for pixel-level pavement crack image segmentation, which is called RUC-Net. We introduced the spatial-channel squeeze and excitation (scSE) attention module to improve the detection effect and used the focal loss function to deal with the class imbalance problem in the pavement crack segmentation task. We evaluated our methods using three public datasets, CFD, Crack500, and DeepCrack, and all achieved superior results to those of FCN, Unet, and SegNet. In addition, taking the CFD dataset as an example, we performed ablation studies and compared the differences of various scSE modules and their combinations in improving the performance of crack detection.

Efficient detection of pavement cracks can effectively prevent traffic accidents and reduce road maintenance costs. In this paper, an improved YOLOv5 network combined with a Bottleneck Transformer is proposed for crack detection, called YOLOv5-CBoT. By combining the CNN and Transformer, YOLOv5-CBoT can better capture long-range dependencies to obtain more global information, so as to adapt to the long-span detection task of cracks. Moreover, the C2f module, which is proposed in the state-of-the-art object detection network YOLOv8, is introduced to further optimize the network by paralleling more gradient flow branches to obtain richer gradient information. The experimental results show that the improved YOLOv5 network has achieved competitive results on RDD2020 dataset, with fewer parameters and lower computational complexity but with higher accuracy and faster inference speed.

This work presents a fiber Bragg grating (FBG) wide-range tilt sensor based on a cam structure. Two FBGs are fixed on a specially-designed sensor shell. When one FBG is stretched by the rotating cam driven by tilt, the other FBG moves along a standard semicircle with a constant radius, and compensates for temperature variations of the stretched FBG. By detecting the difference of the central wavelength shifts of two FBGs, variations of the tilt angle can be measured. The detailed mechanical structure design and measurement theory of the sensor is presented, and the sensor prototype is discussed. Testing results of comprehensive performance show that there is a good linear relationship between the tilt angle and the central wavelength of the FBG over three intervals from -90° to 90°. The repeatability and creep resistance of the FBG tilt sensor are good, the measuring accuracy is 1.516°, and the measuring resolution is 0.003°. The measurement range is much larger than comparable existing sensors, and it avoids cross-sensitivity between temperature and strain for FBG. The sensitivity of the sensor can be easily adjusted by changing the outline of the cam, or the length of the optical fiber between two fixed points.

This paper proposed a fiber Bragg grating (FBG)-based three-axis vibration sensor by using only five sensing elements. A composite structure of the cross-beam-type elastomer with multiplexed FBGs has been designed for three-axis vibration sensing. Because of the mechanical decoupling function of the structure and the reasonable arrangement of FBG sensing elements, the designed sensor possesses great advantages of low cross coupling and self temperature compensation capability. Theoretical model of the composite structure has been established, strain distribution and dynamic characteristics of the composite structure have been studied by the finite element analysis method. Amplitude-frequency test result shows that resonant frequencies of the sensor in X, Y, and Z directions were 980Hz, 960Hz, and 640Hz, respectively. Vibration sensitivities in X, Y, and Z directions were 9.7pm/g, 10.13pm/g, and 7.45pm/g, respectively. Vibration calibration test have validated that the designed sensor possess the capability to measure three-axis vibration.