Abstract
Continuous high-speed (>80 km/h) tunnel-image detection introduces new challenges to defect image acquisition, including machine recognition of entry and exit from a tunnel, storage of massive image data streams, image distortion due to surface photography, and encoder errors. In this study, an automatic image acquisition system is designed, and several critical technologies are proposed for high-speed rail tunnels. The system realizes quick tunnel identification and automatic camera control and uses the proposed line-scan software-matching method to obtain accurate images. Before storage, the real-time modification of the distorted images is implemented using an error-correction algorithm. An alternative mapping storage algorithm is proposed to improve the efficiency and stability of long-term storage. The test results show that the proposed method effectively reduces photographic errors. The lateral pixel-error rate of the corrected image is 1.60%, which is 10 times lower than that of the pre-correction, and the error rate of the longitudinal image is controlled within 10% when the system is moving at a variable speed and within 1% when it is moving at a constant speed. Furthermore, experiments have proven that the alternate mapping storage algorithm improves the storage efficiency of RAID by 50% and ensures data integrity; storage is accomplished by 8 HDDs at a camera throughput of 1.52 GB/s. This study will contribute to improvements in the speed and accuracy of tunnel defect-image detection.
Published Version
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