Large engineering structure safety risk assessment method and system
A security risk and large-scale engineering technology, applied in the field of large-scale engineering structure safety risk assessment methods and systems, can solve problems such as large scale, difficulty in obtaining high-quality data samples, and complex composition of large-scale engineering structures
Pending Publication Date: 2020-12-11
ROCKET FORCE UNIV OF ENG
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Problems solved by technology
[0003] There are still several problems in the existing research: First, the large-scale engineering structure is complex in composition and large in scale, and there are many key parts that need to be monitored; Strong uncertainty, it is difficult for experts to judge its state based on experience alone; third, the abnormal data of large-scale engineering structures is limited, and it is difficult to obtain high-quality data samples
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Embodiment 1
[0136] In this example, a safety risk assessment is performed on a large LNG storage tank located in Hainan Province, China. 12 monitoring points were set up on the support column to monitor its settlement. However, disturbance factors such as ground pressure changes caused by tides may bring more uncertainties to the safety risk assessment of storage tanks. Methods such as artificial neural networks and support vector machines cannot describe these uncertainties. A single layer of BRB can handle uncertainty well, but data from 12 monitoring points can lead to rule explosion. Therefore, DLBRB can be used as a good choice to accurately estimate the safety status of LNG storage tanks. In this experiment, the monitoring data obtained were manually measured from 2012 to 2019, according to the "Building Deformation Measurement Specification" (JGJ8-2007) and "Petrochemical Steel Storage Tank Foundation Construction Specification" (SH3528-2005), The corresponding security status i...
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The invention relates to a large engineering structure safety risk assessment method and system. The method comprises the steps that an extraction block is constructed according to the correlation between historical monitoring indexes and historical risk indexes; constructing a processing block in combination with expert knowledge; optimizing the parameters of the extraction block by adopting a layer-by-layer learning strategy to obtain an optimized extraction block; optimizing the structure and parameters of the processing block by adopting a layer adaptive growth strategy to obtain an optimized processing block, and jointly forming an optimized depth confidence rule base by the optimized extraction block and the optimized processing block; and taking the monitoring indexes and the risk indexes as input, and inputting the monitoring indexes and the risk indexes into the optimized deep confidence rule base to obtain a security risk assessment result. According to the invention, rule information can be deeply mined, and accurate assessment of safety risks is realized.
Description
technical field [0001] The invention relates to the technical field of risk assessment of large-scale engineering structures, in particular to a method and system for assessing safety risks of large-scale engineering structures. Background technique [0002] In recent years, my country's economy has developed rapidly, which has effectively promoted the construction and development of large-scale engineering structures represented by large bridges, UHV power towers, and large storage tanks. Large-scale engineering structures occupy an important position in my country's infrastructure construction. In order to prevent the occurrence of potential safety hazards and ensure its safe and healthy operation, more and more studies regard safety risk assessment as the core content of maintenance and management of large-scale engineering structures. Safety risk assessment is conducive to early detection of safety hazards and timely maintenance measures. At present, domestic and forei...
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IPC IPC(8): G06Q10/06G06F30/27
CPCG06Q10/0635G06F30/27
Inventor 曹友周志杰胡昌华唐帅文胡冠宇张春潮
Owner ROCKET FORCE UNIV OF ENG