Optimal design and implementation for online rail surface defects detection system

Under the premise for guaranteeing the accuracy of detection, combining with the characteristics of the rail surface image and the software engineering concepts, 3 optimization methods were presented for the issue of slower speed in rail surface defects detection, including the aspects of algorithm, programming technology and storage medium. According to redesign of the algorithm flow, the efficiency of the algorithm mapping to CPU was improved; the multithread programming was used to make full use of the multicore strengths of the CPU; the efficiency of the hardware was improved by using solid state drive (SSD) to read and write images, the SSD has the characteristics of fast reading and writing, light weight, low energy consumption and small size. The experiment results demonstrate that the average time consuming decreases from 17.94 ms to 8.33 ms per picture after optimization,the speed improves by 53.57%. That means the speed of train is about 207 km/h in 1 mm accuracy resolution and the system can satisfy the requirements of online detection of rail surface defects.