A framework for hydro-power vibration dynamic measurement and decision-making based on natural language processing

The safety management construction of the hydro-power units is necessary to improve the level of engineering quality and economic benefits. However, the traditional hydro-power units lack a unified safety management decision-making platform, making knowledge retrieval and recommendation difficult. To improve the safety management level of the hydro-power units, the present article provides a framework of intelligent query and auxiliary decision-making in the traditional hydro-power operations. Based on the natural language processing technologies, the auxiliary decision-making platform is composed of three parts, namely, deep semantic similarity model, bidirectional long short-term memory network model and neural collaborative filtering algorithm. Lastly, a case study is conducted, and the auxiliary decision-making platform can provide the user the relevant knowledge guidance to the problem, including defect causes, handling methods, dangerous point analysis and operation preparation, which is helpful to improve the safety management level of the hydro-power units.