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This paper aims to explore the transformation process and transformation mechanism of carbon steel under the marine environment.

In this paper, the transformation and rust layers corrosion products on 0Cu2Cr carbon steel with different cycles coupon test was investigated and deeply explored by scanning electron microscope, energy dispersive spectrometer, X-ray diffraction.

The results showed that the thickness of rust layers grew from 71.83 µm to 533.7 µm with increasing duration of corrosion. The initial corrosion product was γ-FeOOH, then part of the γ-FeOOH continued growing, and under the capillary action, the other part of the γ-FeOOH transformed to α-FeOOH.

To the best of the authors’ knowledge, this paper puts forward for the first time a new viewpoint of the development of corrosion products of low-carbon steel in two ways. This discovery provides a new idea for the future development of steel for marine engineering.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.

Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.

The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10⁻¹ mm and the maximum value of posture error is reduced from 1.07 × 10⁻³ rad to 6.02 × 10⁻⁴ rad, which is superior to the accuracy without considering the gravity factor.

This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.