Objective Line structured light profile measurement is an important technique for rail profile detection. Currently, simulation analysis is instrumental in the research of rail grinding mechanism and track structure dynamics. Optical simulation design software has also been subjected to considerable research in optical system design, simulation modeling, and error analysis. However, few reports have focused on the simulation modeling of the line laser rail profile measurement system. In view of this situation, a simulation model of the rail profile measurement system based on Zemax software is proposed. The proposed simulation model is of guiding significance for designing optical systems, selecting optical elements, and improving measurement accuracy. It can provide theoretical support for the accuracy improvement and reliability evaluation of the rail profile measurement system.
Methods The rail profile measurement system is divided into image acquisition, system calibration, and profile measurement modules. The image acquisition module obtains the rail laser cross section image and mainly includes the line laser, lens, and camera. The system calibration module obtains the calibration parameters, i.e., the transformation relationship between the image plane in the pixel coordinate system and the measurement plane in the world coordinate system. The profile measurement module extracts the center pixel coordinates of the light stripe from the rail laser cross section image obtained using the image acquisition module. Then, it transforms the central pixel coordinates of the light stripe into the world coordinate system using the calibration data to determine the real rail profile. Based on the division of the system function modules, the system modeling process is divided into three steps (Fig. 3). In the first step, the image acquisition module is modeled (Fig. 8). First, the optical model of the main components is established in the Zemax non-sequential mode. Then, the system simulation model is established by combining the optical model of the components and optical structure parameters to ensure that the system simulation model has the image acquisition function. In the second step, the system calibration module is modeled based on the plane target calibration method (Fig. 10). The image acquisition module collects the calibration board images under different poses, and the system calibration parameters are calculated. In the third step, the profile measurement module simulates the rail profile measurement process (Fig. 12). The image acquisition module scans the rail at a certain sampling interval along the rail direction (extension direction) and obtains the rail laser cross-section image at equal intervals. The real rail profile is calculated using the rail laser cross section image; hence, the system simulation model has the profile measurement function (Fig. 9).
Results and Discussions To comprehensively evaluate the measurement accuracy of the system simulation model, component accuracy verification, rail simulation measurement, and actual rail measurement experiments are performed (Figs. 15--17). Experimental results show that the root mean square error (0.049 mm) obtained using the system simulation model is close to the root mean square error (0.066 mm) obtained using the actual measurement device based on the 20 repeated measurement data of rail vertical wear (Table 5). The system simulation model achieves high accuracy, and the simulation measurement results are consistent with the actual situation, thus demonstrating that the simulation model can better simulate the rail profile measurement system.
Conclusions A simulation model of the rail profile measurement system based on Zemax is proposed. The simulation model has image acquisition, system calibration, and profile measurement functions. The results show that the simulation model is consistent with the measurement results of the actual measurement system, and the simulation model can be used to simulate the rail profile measurement process using line structured light. The differences between the simulation model and the actual system are highlighted from different aspects, thus providing a reference for further improving the simulation model. The system simulation model can be used for analyzing related problems in the field of rail profile measurement, e.g., evaluating the impact of lasers on both sides of the rail that are not coplanar and generating rail surface defect samples using the system simulation model to solve the problem of a lack of negative samples in deep learning. Moreover, the system simulation model can be used for experimental verification and laboratory or field experiments can be performed simultaneously with system simulation experiments. The simulation data can not only verify the experimental results but also provide guidance for the experimental design. Finally, the system simulation model can be used to predict the results. Some tests unsuitable for field tests or parameters and cannot be well controlled can be performed using the simulation model, such as the vehicle body pose compensation test. The simulation model provides a new analysis method for studying rail profile measurements using line structured light and offers guiding significance for optical system design, optical element selection, and measurement accuracy improvement.
