No abstract

Distributed optical fiber sensors can sensitively sense local temperature changes caused by leakage at any position of the pipeline, but massive monitoring data has significant spatio-temporal non-stationary characteristics, and it is difficult to directly diagnose leakage based on the monitoring data. Under the framework of statistical pattern recognition, a spatio-temporal big data analysis method based on sliding window outlier analysis is proposed. Only the internal characteristics of distributed temperature monitoring data can be used to realize the intelligent identification of pipeline leakage, and the sliding is determined. The value method of window length and abnormal state diagnosis window length, and the physical simulation of prototype insulation steel pipe leakage monitoring was carried out. The results show that when the pipeline is intact, this method will not cause false alarms. Once the pipeline leaks, the method can quickly identify the pipeline leakage event and accurately locate the leak location.

In some building construction, due to the influence of many factors such as site environment, geological conditions, construction design plan. the construction site environment is complicated and the construction process is staggered. For deformation monitoring under such conditions, a single, conventional monitoring method (baseline method, direction intersection method, corner measurement, etc.) may be difficult to carry out. If according to the characteristics of the project, several monitoring methods are used for comprehensive monitoring. It can better solve the difficult problem of on-site monitoring, and can significantly improve operation efficiency. This paper takes construction monitoring as an example to discuss the research of building displacement observation method under special environment.

Based on UAV low-altitude remote sensing technology and tilt photography technology, combined with highway projects, the UAV operating process, quality inspection and accuracy, and positioning accuracy in the mountainous complex terrain conditions are analyzed, and operating experience is summarized for subsequent navigation. The production provides guidance. At the same time, it also provides a reference for the exploration of digital mapping methods, and lays a theoretical foundation for the research of mapping methods. The combination of mapping methods in complex terrain with high technology is highly innovative.