The Application of Image Recognition Algorithm in Intelligent Monitoring of Herringbone Gate Closure Of Ship Lock

During the operation of the lock, there is a relative displacement between the herringbone gate shaft and the door leaf, and the traditional manual measurement method has a large workload and low accuracy, and the problem cannot be found in time. In the process of using the traditional way of measurement, due to the influence of environment, human and other factors, it is difficult to ensure the accuracy of the measurement results, and the efficiency of manual re-inspection in the later stage is low, and a lot of manpower and material resources are required. The intelligent monitoring system for the final alignment of the herringbone gate gate gate based on computer vision realizes the rapid measurement of key parameters such as the position and angle of the door leaf through real-time image recognition and analysis of the door leaf, and compares the image recognition result with the door leaf displacement curve, so as to provide accurate and timely data support for the operation and management of the lock. Ship crossing is a complex physical process, with multiple complex factors such as ships, locks, and waterways. The alignment of the lock under the herringbone door is mainly achieved by measuring the relative position between the lock door leaf and the door leaf when the ship passes through the gate. Due to the great influence of external factors, such as the violent shaking or collision of the ship during navigation, the measurement results are prone to deviation. Therefore, it is of great significance to study the intelligent monitoring system of herringbone gate closing and final alignment of ship locks. In this paper, based on the image recognition technology, the alignment of the lock door leaves under the herringbone door is studied, and the real-time monitoring of the alignment of the lock door leaves under the herringbone door is realized by using the image recognition algorithm, and an image recognition algorithm based on multi-feature fusion is proposed.